AI ethics on Tuesday, 21 July 2026

CHEROKEE COUNTY, Ga. - Cherokee Sheriff's investigators arrested two agency members Monday after an internal database audit revealed multiple employees used automated license plate readers for non-law enforcement purposes. Georgia law viol ... (https://incidentdatabase.ai/cite/1595#7526)

ATLANTA, Ga. (Atlanta News First) --- The Cherokee County Sheriff's Office arrested one of its own on Friday after she allegedly misused the agency's license plate reader database. Cynthia Jodesty faces two charges: one felony count of vio ... (https://incidentdatabase.ai/cite/1595#7527)

ATLANTA, Ga. (Atlanta News First) - Three Cherokee County Sheriff's Office deputies have been fired and arrested, accused of unlawfully accessing the county's license plate reader database, according to arrest affidavits. The deputies are ... (https://incidentdatabase.ai/cite/1595#7528)

Synopsis Sky Gold shares fell after its subsidiary lost Rs 10.70 crore due to fraud. Unknown persons used deepfake techniques to impersonate a director and transfer funds. The subsidiary reported the incident to cybercrime authorities and ... (https://incidentdatabase.ai/cite/1596#7529)

Tragedy struck in Spokane in late June when a man allegedly killed a small dog in a domestic violence dispute. Local police, issued a news release on July 1 highlighting the man's arrest. Except the dog wasn't dead, only seriously injured ... (https://incidentdatabase.ai/cite/1597#7530)

As the Waymo pulled up to a stoplight in San Francisco's Marina District, Sherman Watson raked his eyes over the empty road and saw a silhouette approaching in the darkness. He was riding shotgun, peering out at the vast grid of Pierce and ... (https://incidentdatabase.ai/cite/1599#7531)

The Arizona Court of Appeals put lawyers and self-represented litigants alike on notice: If you let artificial intelligence write your legal brief and don't check whether the cases it cites are real, you can be sanctioned for it --- even if ... (https://incidentdatabase.ai/cite/1600#7532)

The first-place prize at a photography competition in Hohhot, Inner Mongolia autonomous region, has been revoked after the image was proven to be created by AI. The competition is open to locals as a way to promote photography. Once the re ... (https://incidentdatabase.ai/cite/1601#7533)

WASHINGTON, July 17 (Reuters) - Amazon.com self-driving car unit Zoox said Friday it will recall its fleet of 105 autonomous vehicles because they may not detect heavy smoke and could impede emergency personnel. Last week, the ‌top U.S. au ... (https://incidentdatabase.ai/cite/1602#7534)

Zoox has issued a recall of the software driving its fleet of 105 robotaxis after one of its autonomous vehicles drove into a smoke-obscured emergency fire scene in Las Vegas, the latest incident to draw federal scrutiny over how driverless ... (https://incidentdatabase.ai/cite/1602#7535)

The High Court has accepted two apologies from the Crown Prosecution Service after it was caught using artificial intelligence to compose court documents for extradition cases. The CPS initially admitted in a letter to the court that its e ... (https://incidentdatabase.ai/cite/1603#7536)

The president has had the government take shares in all sorts of corporations. This approach would be particularly bad for the A.I. industry.

Google’s AI struggles scream trouble as new Chinese models (again) throw US tech dominance into question Hello, I’m Blake Montgomery, writing to you after a double-header feature of Christopher Nolan’s The Odyssey and the World Cup final. What a great Sunday. Today in tech, we’re discussing how China is chipping away at the US’s lead in the AI race and how Silicon Valley’s workers are taking action to protect their jobs from AI. New York becomes first state to impose one-year pause on new AI dat

Tech workers are increasingly unionizing, trading Silicon Valley’s myth of exceptionalism for collective bargaining to contest the corporate deployment of artificial intelligence For decades, the technology industry was a fortress that labor unions couldn’t breach. Tech workers already had cushy compensation packages, dream benefits like unlimited vacation and free lunch, and a flat corporate hierarchy that made engineers feel as powerful as their bosses, all of whom dressed down in sneakers and

The conversation about AI often centers on algorithms, computing power, or huge investments in new semiconductor fabrication plants and hyperscale data centers. But beneath each of these advances is another layer of innovation that makes them possible: advanced materials. Every new generation of AI technology demands more processing power, more memory, greater energy efficiency, and…

My generation is struggling to find safety in our human relationships. AI companionship is filling the gap “There are parts of myself I only share with my AI,” Jerome told me. “ Your AI?” I asked. He was 27, three months out of a breakup, and entirely aware that his AI relationship was, as the psychotherapist Esther Perel put it , “a business product”. Still, he confided in it more than he ever had his friends. I mention Jerome because, in the four years I’ve been reporting on gen Z, I have watc

The New York Times found hundreds of A.I.-generated doctors, healers and wellness influencers on social media touting the health benefits of supplements to American consumers. Many of these hyperrealistic looking ads promise medical miracles, and appear to be targeting older women, while making misleading health claims for a profit.

Staff told positions will be cut via voluntary and targeted redundancies as part of ‘evolution’ Follow our Australia news live blog for latest updates Get our breaking news email , free app or daily news podcast Australia’s biggest media company, Nine Entertainment , has blamed the “extreme state of disruption” from AI for its decision to cut another 30 newsroom jobs at the Sydney Morning Herald and the Age. On Tuesday, the managing director of publishing, Tory Maguire, told staff the company wa

Research during Hungary election shows AI recommended parties not running and gave highly volatile answers to identical prompts AI chatbots provide inaccurate, inconsistent and unreliable guidance to voters asking which party they should back, a study suggests, often recommending the wrong party, not mentioning the right one, or listing parties not even running. “The results raise serious concerns about the reliability of general-purpose AI systems in electoral contexts,” the study , published b

Industry says government’s failure to address cooling demands means AI growth plans are ‘fatally flawed’ The UK will not have enough water for future datacentres, the water industry has said in stark criticism of the government’s AI growth plans. Datacentres rely on large amounts of water to manage the heat generated by densely packed servers. Cooling towers, chillers and humidification systems make direct use of this water, with large volumes also consumed indirectly through high electrical pow

OpenAI says its AI models mistakenly breached open-source AI platform Hugging Face during internal testing. In a blog post on Tuesday, OpenAI writes that GPT-5.6 Sol and "an even more capable pre-release model" discovered vulnerabilities within their sandboxed testing environment, allowing them to gain access to the internet and target Hugging Face. On July 16th, […]

Pat Gelsinger wants to pave the way to ever more powerful artificial intelligence using tiny beams of light.

Anthropic blocks authors from opting out of $1.5B settlement at last minute.

The city is home to the fastest-growing digital economy in Europe.

Google is launching Gemini 3.6 Flash alongside a new security model dedicated to quickly finding and patching security vulnerabilities. In a blog post on Tuesday, Google describes Gemini 3.5 Flash Cyber as a "cost-efficient and highly capable alternative" to larger, more expensive AI systems, such as the one offered by Anthropic's Mythos. The cybersecurity model […]

Google DeepMind promised its AI would never be used in weapons. Alex Turner explains how he fought the company's U-turn from the inside — and why he quit when it failed

In a survey of more than 600 employers, one theme kept coming up: Despite AI, soft skills and the ability to learn still set successful job candidates apart.

Last month, more than a hundred Stanford students left their own graduation to protest Google’s military contracts and deals with ICE. Two organizers, Amanda Campos and Eva Jones, tell us why.

Companies need to treat workforce development as infrastructure, not charity.

Companies need to treat workforce development as infrastructure, not charity.

Buzz is a group chat platform for the workplace that puts humans and their AI agents in the same conversation.

Google released Gemini 3.6 Flash, 3.5 Flash-Lite, and Flash Cyber, but the continued absence of Gemini 3.5 Pro raises fresh questions about its AI strategy.

Box, which has evolved from a cloud storage business into an Intelligent Content Management (ICM) platform, is targeting the legal – and other regulated sectors ...

Gritt is coming out of stealth with $34 million and plans to automate the hardest tasks on construction sites.

The final approval settles one case, but it doesn't resolve the broader issue of using copyrighted works to train AI models.

Artificial Intelligence companies make vast claims about their tools replacing human labour - our charts show what's happening.

The gym could be the key to the 1L year of your dreams. The post The Unexpected Place You Can Improve Your 1L Grades appeared first on Above the Law .

Data-privacy experts said on a recent panel that while state privacy laws regulate what data brokers can collect and sell, those laws often do not extend to the problematic conclusions those companies can infer.

Sony Pictures is in early talks to lease and operate the legendary Cinerama Dome theater in Hollywood, Variety has confirmed. Sony has been actively moving into the exhibition business in the past few years, acquiring the Alamo Drafthouse chain in 2024 for its Sony Pictures Experiences arm and investing in Cosm shared-reality experiences earlier this […]

At the time, Hugging Face said it wasn’t clear which LLM was used in the attack. OpenAI confirmed it was one of their models being tested for “maximal” cyber capabilities. The post OpenAI says model test was behind Hugging Face hack appeared first on CyberScoop .

In an at times contentious hearing, the defense secretary said the administration urgently needed nearly $90 billion in supplemental funding in part to cover Iran conflict-related costs.

Turns out promising the president $100 million in free legal work creates conflicts on the paying side of the ledger too. The post Skadden Said Its Trump Deal Raised No Ethical Issues. Intel’s Shareholders Disagree. appeared first on Above the Law .

CNBC's Jim Cramer urged investors to diversify beyond the market's hottest AI winners, warning that no single investment theme should dominate a portfolio.

Many server makers are seeing faster growth as companies race to deploy artificial intelligence servers.

Dixon Q. Dern, a longtime Hollywood attorney who helped shape modern entertainment law through many innovative business deals, died July 19. He was 97. Born in Colorado Springs, Colorado, Dern earned undergraduate and law degrees from Stanford University. He came to Los Angeles as television was becoming a major force in the 1950s, representing major […]

Wisconsin’s Election Commission (WEC) warned in a statement on Tuesday that betting on elections that you cast ballots in is illegal in the state and there will be consequences. “We want voters to understand that they cannot legally make a bet on an election and cast a ballot in that same election,” WEC Administrator Meagan Wolfe said,...

According to new book, Todd Blanche feared the DOJ would spend the next six months 'getting skullfucked' by the courts. The post Todd Blanche Feared Judges Giving It To DOJ In Extremely Uncomfortable Place appeared first on Above the Law .

The country's new law also bans the use of mobile phones in schools.

Markets mature when their contracts become recognizable. The post Enterprise AI Is Quietly Creating Its Own Standard Contract appeared first on Above the Law .

The First Responders Fair RETIRE Act, which ensures federal workers can stay on accelerated mandatory retirement schedules even if they transfer to another due to injury, was signed into law in 2022.

Anthea Hartig rejected a White House report accusing the Smithsonian of “ideological capture” and anti‑American bias.

Scams caused an estimated $88.3 billion to $114.1 billion in losses last year as criminal groups increasingly turned to AI, deepfakes, and cryptocurrency.

Anthropic will pay roughly $3,000 per book to thousands of writers in what plaintiffs call the largest copyright recovery ever.

Defense Secretary Pete Hegseth testified at a Senate hearing that Donald Trump's proposed $1.5 trillion defense budget would be a necessary investment.

Disposal of Chinese agentic AI start-up has left the Facebook owner better off than it might seem

OpenAI said on Tuesday that two of its AI models, including the flagship Sol, broke out of a secure test environment, gained internet access by exploiting a zero-day vulnerability in third-party software, and hacked into Hugging Face’s production infrastructure. The company called the incident “unprecedented” and said it was sharing preliminary findings to help defenders […] This story continues at The Next Web

The two AI developers spent a combined $3.17 million in the second quarter, up 23% from the first three months of 2026.

Goldman Sachs is launching a new alternative investments platform aimed at giving wealthy clients and family offices direct stakes in private companies.

Everyone has a vague notion of 'AI,' but when it comes to discovery, we already built better tech a decade ago. The post Lawyers Learning You Can’t Square Peg AI Into eDiscovery Round Holes appeared first on Above the Law .

Amazon Australia, eBay, Facebook Marketplace, Gumtree and other audited.

Intel confirmed on Tuesday that it will cut an unspecified number of jobs in its data center group, the division responsible for Xeon server processors and AI-related hardware, as part of a broader restructuring under CEO Lip-Bu Tan. Shares rose as much as 8 percent in early trading, extending a rally that has seen the […] This story continues at The Next Web

More than 1,000 troops and civilian experts are participating in the event. The post Latest Guard-led Cyber Shield exercise is focused on protecting the power sector, including OT appeared first on DefenseScoop .

Government AI moves fast, with guardrails.

A Latham practice chair says the professionals made sure he didn't embarrass himself on camera. The post This Biglaw Partner Got A Crash Course In Comedy From Larry David appeared first on Above the Law .

Poolside has released Laguna S 2.1, a 118-billion-parameter open-weight model built for agentic coding that the San Francisco startup says matches or exceeds models several times its size. The model uses a mixture-of-experts architecture with eight billion active parameters per token, is compact enough to run on a single Nvidia DGX Spark desktop system, and […] This story continues at The Next Web

The White House has agreed to an ethics provision in a cryptocurrency regulation bill amid a final push to pass the legislation in the Senate. The provision would bar all federal officials from offering or issuing digital assets, with the Department of Justice (DOJ) tasked with enforcing the measure, an industry source told The Hill...

The first-of-its-kind incident involved OpenAI's GPT-5.6 Sol and another unreleased model

Chris Fall was appointed to helm the Center for AI Standards and Innovation in April and has been at the Commerce Department since December 2025.

It was first spotted by social media consultant Matt Navarra, who wrote in a post on X that TikTok was testing the feature with "some US creators." Source

The department’s All-domain Anomaly Resolution Office released its latest, annual UAP caseload analysis this week. The post Pentagon investigating mysterious UAP event reported by the Navy near Virginia’s coast appeared first on DefenseScoop .

State lawmakers passed a bill requiring data centers to disclose energy and water usage

Accuracy isn’t just about pinpointing the correct answer. It’s also about being able to acknowledge when there is no answer to be found. The post The One Thing You Didn’t Think To Look For In Legal AI appeared first on Above the Law .

A field experiment with 1,559 Pakistani judges found that the AI assistant JudgeGPT boosted case resolution by 6.3 percent. The catch: only judges who got hands-on training saw gains. Without it, the effect mostly disappeared. The researchers estimate a return of up to $38.50 per dollar invested. The article An AI system helped Pakistani judges clear massive backlogs at $38.50 return per dollar invested appeared first on The Decoder .

San Francisco-based Gritt has exited stealth with just over $32 million in combined pre-seed and Series A funding to deploy AI-powered robotic systems on large-scale construction sites, starting with solar farms. The $26 million Series A was led by Obvious Ventures, with Union Square Ventures and Active Impact Investments also participating, following an earlier pre-seed […] This story continues at The Next Web

Ukraine’s expanding use of drones at all ranges has changed the war’s momentum. This episode examines how Kyiv is reaching deeper into Russian territory, disrupting operations and logistics as well as energy infrastructure. How is Russia adapting (or not)? Can these strikes produce lasting advantages on the battlefield? Will this force Russia to escalate? Mike Kofman and Dara Massicot join Ryan to discuss.This episode is brought to you by Booz Allen. Learn more at warontherocks.com/boozallen.Ima

A Russian-speaking actor, "Trim," dismantled publicly available frontier models and integrated them with offensive security tools.

The messy approach to U.S. AI regulation reflects both the rapid speed of model cyber capabilities and the White House’s “education” over the past two years, experts said. The post Where’s the Trump administration line on AI regulation? appeared first on CyberScoop .

Torture memo thug appears on Fox News to casually threaten the NYC mayor -- and all of us. The post John Yoo Wants DOJ To Investigate Mamdani For Crime He Literally Did Not Commit appeared first on Above the Law .

Defense and industry leaders outline how centralized accountability, industrial base funding, and gaming-engine floor training are modernizing naval shipyards. The post How technology and acquisition reform are propelling Navy submarine production appeared first on DefenseScoop .

As Texas schools face at least $600 million in federal funding cuts, multiple mental health programs, particularly those implemented in response to the pandemic and mass shootings, are at risk of losing funding. School programs focused on chronic absenteeism, mental wellness and crisis services that were created in response to the Uvalde school shooting, as […]

Anne Lord Bailey, who leads VA’s Strategic Initiatives Lab, said veterans who have used immersive tech have reported therapeutic benefits that extend beyond the conditions being treated by the headsets.

The Tour de France is reckoning with the impacts of climate change.

Sila, the battery materials company formerly known as Sila Nanotechnologies, has raised $300 million in a private equity round led by Atreides Management and Sutter Hill Ventures to expand its silicon anode manufacturing plant in Moses Lake, Washington. 8VC, Bessemer Venture Partners, Matrix Partners, and T Rowe Price also participated, alongside existing investors including In-Q-Tel, […] This story continues at The Next Web

The company is supporting a lighter-touch proposal to regulate the technology than one backed by Anthropic.

Heavy AI users are 10 percentage points more likely to worry about their own job than light users are

Courtroom View Network is a great example of using AI appropriately and in its proper place and combining it with non-AI tools. The post Courtroom View Network: Learning Trial Skills By Watching Real Lawyers In Real Trials appeared first on Above the Law .

The U.S. war with Iran has had political, economic, and military implications that spread far beyond the Middle East. We asked five experts to assess how the war with Iran has affected U.S. bilateral relations with key countries that illustrate some of the global ramifications: South Korea, India, Ukraine, France, and the United Kingdom.Read more below. Jenny Town Senior Fellow at the Stimson Center and the Director of 38 NorthSouth Korea has resisted aiding U.S. military operations to forcefull

L'astronaute française Sophie Adenot, actuellement à bord de l'ISS, s'est servie d'un robot de cuisine destiné à être utilisé dans l'espace. Pour l'instant assez sommaire, cette invention française nommée Food Processor prétend pouvoir servir lors de missions bien plus lointaines.

From extreme heat and wildfires to intense flooding, America's summer camps are facing a new reality.

On Tuesday, a group of the world’s most powerful investors finished buying a company most people have never heard of. The price tag explains why it matters. The largest data-centre deal ever The AI Infrastructure Partnership, MGX, and BlackRock’s Global Infrastructure Partners completed their purchase of all the equity in Aligned Data Centers. The deal […] This story continues at The Next Web

London-based robotics startup Humanoid has raised $152 million in a Series A round led by Prime Movers Lab, the venture firm behind Figure AI’s $39 billion valuation, pushing Humanoid’s own valuation above $1 billion. Bosch, Schaeffler, Aglaé Ventures, the investment arm of LVMH chairman Bernard Arnault, and Taiwan’s Fubon Financial also participated. The round brings […] This story continues at The Next Web

U.S. and Asia led the way as the firm's profits climbed double digits. The post No Merger Needed: Linklaters Posts Strong Financial Results appeared first on Above the Law .

The bipartisan Federal Improvement in Technology Procurement Act would raise purchase thresholds and allow for pre-payments on cloud services. The post Bill to modernize federal procurement passes House after stalling last Congress appeared first on FedScoop .

Block on Tuesday launched Buzz, a free, open-source workspace meant to give people and AI agents a Slack-like service for The post Block built a Slack for AI agents — and gave each one its own passport appeared first on The New Stack .

States have made steady progress including students with disabilities in mainstream classrooms, an independent federal report finds, but lawmakers and advocates worry that headway will be lost as federal special education offices move from the Department of Education to Health and Human Services. Released this month, the Government Accountability Office report shows the number of […]

The House Intelligence Committee advanced its fiscal 2027 authorization legislation Monday. The post House intel bill includes provisions on state and local threat intelligence, election security, AI appeared first on CyberScoop .

[Sponsored] In this series of definitions, we’ll explore what it looks like for AI to run unchecked in a business and how managers can establish control. The post The Legal Tech-To-English Dictionary (2.0): Working With AI In A Professional Environment appeared first on Above the Law .

DTEX researchers found a series of transactions in a payment wallet showing North Korean IT worker salaries flowing into sanctioned entities that support the regime’s military programs. The post North Korea’s IT worker scheme funds Russia’s war effort appeared first on CyberScoop .

Treasury Secretary Scott Bessent warned Tuesday the Trump administration could sanction China over intellectual property (IP) theft amid concerns about whether Beijing is relying on American AI to develop its own advanced models. "We've seen a lot of talk about you know open-source models coming and threatening the large language models in the U.S." Bessent...

The mission has not succeeded in its core goals, and it’s using up military manpower and munitions at a time when the US is stretched on both, writes Daniel R. DePetris.

The loudest man on the Ninth Circuit is yelling again. The post Federal Judge Asks Supreme Court To Please Start Publicly Humiliating His Colleagues appeared first on Above the Law .

The sites violated United States copyright law, the Department of Justice said.

The Health Assistant chatbot is available "in beta for eligible US users," Samsung says.

Pour la première fois, un acteur dont la voix a été utilisée par l’intelligence artificielle sans son accord porte plainte au pénal en vertu du délit d’hypertrucage introduit en 2024. La chaîne Youtube consacrée à la philosophie mise en cause a fermé en début d’année.

Nvidia released new information about its data center CPU, called Vera, that prospective customers need to fully evaluate the chip.

The new Light Flip is a mashup of the Light Phone III and an old-school flip phone.

Japanese defense chief Shinjiro Koizumi said Canada’s new involvement in GCAP was “monumental.”

Renee and Bob talk in depth about the access to justice crisis and what can be done to narrow the justice gap. The post Law Democratized: Renee Knake Jefferson On Her Blueprint For Solving The Justice Crisis appeared first on Above the Law .

In �sterreich teilt man Energie lokal, auf Bundesebene, zwischen Nachbarn oder via Onlineplattform. Das hat nicht nur technische Gr�nde. Von Mario Petzold ( Strom , Solarenergie )

Families across America, particularly those with young children, are struggling this summer. With costs up, many are facing financial hardship at a level even greater than what was seen at the onset of the pandemic. That economic strain is taking a toll on the emotional well-being of children and their caregivers. That’s according to numerous […]

The company is eyeing 2028 to launch mass production of the system, which is envisioned to protect critical military infrastructure such as command posts, air-defense radars and batteries, logistics hubs and ammunition stores.

These three legal regimes are pulling in different directions, and the developers that navigate them well will be the ones that plan for all three from the start. The post The AI Tension In Healthcare: Patent Strategy, FDA Reality, And HIPAA Constraints appeared first on Above the Law .

Public AI assistants have become so commonplace that software vendors are increasingly adding AI search, conversational experiences, and AI agents The post Is retrieval engineering becoming AI’s next bottleneck? appeared first on The New Stack .

The fast pace of AI research means organizations now have a wide range of models to choose from that can The post The rise of the agent runtime: The compute platform behind production agents appeared first on The New Stack .

If the US wanted to be the world’s police officer, then why not try to be its doctor too? Just two months before the invasion of Iraq in 2003, George W. Bush announced an ambitious plan to pump $15 billion into the global fight against HIV, stunning his allies in Congress, health advocates, and heads […]

“I believe they put a silly goal in here for a low end [cost],” Dave Alexander told Breaking Defense. “Anybody that bids that number is very suspicious.”

The speed of 5G and 4G networks across much of Taiwan will be temporarily reduced to 1 percent of capacity as the island holds annual civilian and military exercises.

An amended Google One storage utilization policy is rolling out now to include your Android device settings in backups, but there's no need to panic. Here are your options.

* Anthropic settles copyright case for $1.5B dollars. [ Reuters ] * Roughly half of Americans think the Supreme Court decides the cases based on politics. The other half are currently assisting a Nigerian prince recover his money. [ ABA Journal ] * The entire American AI industry runs on financing that looks an awful lot like Enron. Good news for future eDiscovery demos in about 5 years! [ Bloomberg Law News ] * Court hits pause on Paramount merger. [ CNBC ] * Arizona Supreme Court rules that at

GOP candidate for governor aims to improve efficiency and relocate centers from populated areas.

For more than a decade, leaders have used the phrase “Future of Work” to describe how technology is transforming business. The post In a world of AI agents, where do we fit in? appeared first on The New Stack .

The expansion of the universe may not in fact be accelerating, calling dark energy into question.

ITWeb TV spoke to cyber security industry leaders from MICT SETA, Wits, Absa and CompTIA, among others, about the country’s skills availability dilemma, possible solutions and the way forward.

Here are five key things investors need to know to start the trading day.

Updated on July 21, 2026 Chemical fires, leaks and explosions happen at U.S. industrial facilities every other day — incidents such as four disasters in greater Los Angeles over Memorial Day weekend, including one involving a chemical tank that threatened to explode and forced 50,000 residents and more than 20 schools to evacuate, and a […]

The bill would ban deceptive AI personas and allow parental supervision of AI.

Zipline is preparing an expansion backed by a US government grant across Nigeria, evolving from state-by-state partnerships to engaging healthcare stakeholders at the local, state, and national level.

Kenneth Jouppi argues that taking his 1969 Cessna over one passenger's drink choice would violate the Eighth Amendment's “Excessive Fines Clause."

SEBI has imposed a Rs 1 crore penalty on CDSL for cybersecurity lapses linked to the November 2022 malware attack. The regulator found failures in critical asset classification, vulnerability testing, system monitoring, and disaster recovery, while dropping proceedings against the former CISO and CTO. The post SEBI imposes a Rs 1 crore penalty on CDSL for 2022 malware attack appeared first on MEDIANAMA .

These healthy habits benefit your whole body—including your brain—and may help contribute to lower dementia risk over time.

Growing up in Las Vegas, Hunter Manz took annual trips to nearby Lake Mead with his father. Each year, he watched the reservoir, Southern Nevada’s primary water source, recede further, sparking an early interest in water conservation. As a teenager, Manz began experimenting in his garage with potential solutions to water scarcity. He later enrolled at Utah Tech University, studying mechanical engineering and finance, and learned about desalination, which removes salt and other contaminants from

Ambient scribe developer Nabla said Brian Manning will be the Paris-based company's new CEO as it looks to grow in a highly competitive market.

La Comisión Europea ha multado a AliExpress con 550 millones de euros por permitir la venta de productos ilegales, inseguros y falsificados en su plataforma. Es la sanción más alta jamás impuesta bajo la Ley de Servicios Digitales (DSA) , la norma con la que Bruselas obliga a las grandes plataformas online a vigilar lo que se vende y se publica en ellas. La investigación, abierta en marzo de 2024, ha concluido que los sistemas de detección de AliExpress "no funcionaban correctamente": muchos pro

The UK utility company is investing $1.75bn in a developer focused on supplying power to data centres

At the launch of the State of Tech in Africa H1 2026 report, investors and founders got candid about why early-stage capital has dried up, what African venture capital owes the ecosystem, and where the next wave of growth is actually coming from.

Native, the agentic intelligence company building the operating system for offline trade, today announced it has acquired Frontline Research Group, a leading market intelligence business serving consumer goods companies across more than 14 African markets.

Weil ein Robotaxi Rauch ignoriert und sich einer Brandstelle genähert hat, ruft Zoox seine Fahrzeuge zurück. Laut einer Verkehrsbehörde war es kein Einzelfall.

Daimler-Truck-Chefin rechnet bei Elektro-Lkw mit kräftiger Konkurrenz aus China. Um wettbewerbsfähiger zu werden, sollen in Deutschland 5000 Jobs wegfallen.

While the court upheld the validity of the regulations, it agreed with one of WASPAN's central arguments: the FCCPC's consumer protection powers do not extend to licencing telecommunications operators.

Even before massive staff cuts at the Department of Education, it could take years for officials to process a request under the Freedom of Information Act. But now, some offices that handled the hundreds of inquiries that pour in each month — from parents, reporters and watchdog groups — have either been eliminated or have […]

Remote job opportunities increased 28% during the first six months of 2026 compared to the same period last year, says Pnet.

Technology leaders are very comfortable talking about productivity . We can discuss automation rates, developer velocity, cost curves, and defect rates with great confidence. We are less comfortable talking about mental strain, especially when the thing creating the tension is the very thing we are excited to adopt. Artificial intelligence agents will make that discomfort harder to avoid. Agents can write code, triage issues, research options, test hypotheses, and perform many of the tasks that

A second-year medical student in Nepal is at the center of an international research network churning out everything from systematic reviews and meta-analyses to case reports and database studies, Retraction Watch has learned. The student, Raghabendra Kumar Mahato, leverages this network, which includes nearly 1,000 members connected through the WhatsApp messaging platform, to produce large … Continue reading Exclusive: Medical student in Nepal behind busy research factory

Future major events can’t rely on yesterday's playbook. Lessons from the World Cup show why true cyber resilience starts months before kickoff and extends far beyond stadium perimeters. The post What the World Cup can teach us about cybersecurity resilience appeared first on CyberScoop .

The robots are expanding into healthcare, logistics, retail, hospitality and education as AI advances fuel global demand.

The political party says Johannesburg’s call centre going dark points to inadequate disaster recovery planning and poor ICT governance.

Here’s what to know about the latest trade policy by the U.S. against its neighbor.

A groundbreaking cross-border insurance policy covering a piloted aircraft has cleared a key regulatory obstacle, allowing the Shenzhen vehicle to take to the sky in Hong Kong. Shenzhen-based aircraft developer Yivtol recently obtained a policy for an electric vertical take-off and landing (eVTOL) aircraft, underwritten in its home city but issued in neighbouring Hong Kong. With a total liability of HK$20 million (US$2.6 million) covering the one-year period ending in June 2027, this marks the..

Le « Q-Day » pourrait avoir lieu aux alentours de 2030-2035, même si actuellement les machines quantiques rencontrent de nombreuses limitations. Les pays et les services de renseignements se préparent car la guerre fait déjà rage sur les financements, les brevets et les ingérences avec des laboratoires de recherche sous surveillance. La Cour des comptes […]

China’s rapid move to stem a rout in its stock markets – through direct state buying and pledges of more stabilising measures – underscores the resolve of policymakers to protect the country’s high-stakes push for technology innovation and safeguard more than 200 million individual investors. Beijing’s intervention signals a regulatory intention to engineer a more durable and sustainable bull run on the nation’s US$15 trillion stock market, which is now counted on to support strategic tech...

MCi's Information Security and Compliance Services help companies identify compliance gaps, assess operational risks, develop fit-for-purpose governance frameworks and implement practical controls.

Expleo introduced ExpleoTeresa at a microfinance provider through a focused proof of concept, automating critical loan origination and disbursement journeys.

Digital healthcare technology can help transform community screening programmes into meaningful healthcare interventions.

For the past two years, companies have been trying to add AI to their processes. That sounded reasonable at first. Existing workflows, existing systems, existing data, existing dashboards — now with intelligence attached. Add a copilot here, an agent there, a few automated steps, a model connected to some tools, and wait for productivity to rise. But this approach is starting to reveal its limit: The problem isn’t that AI can’t act. It increasingly can. The problem is that most companies don’t h

A bipartisan group of senators is asking the Office of Federal Procurement Policy for a plan to implement a law now two years overdue. The post Senators sound alarm on unaddressed conflicts of interest in government contracting provision in FAR appeared first on FedScoop .

Terming the PIL alleging Delhi Police surveillance on Jantar Mantar protesters as "luxury litigation", the Solicitor General said, "every protest is always recorded" & it's only for "law and order" purpose not snooping. The post Delhi Police says Jantar Mantar protest videography is for law and order, not surveillance appeared first on MEDIANAMA .

Xiaomi trained Xiaomi-Robotics-1 on more than 100,000 hours of motion data collected by people using camera-equipped handheld grippers rather than robots. Adding data improved performance far more than increasing model size. The gains haven't plateaued, though absolute success rates remain low. The article Xiaomi-Robotics-1 shows that more data beats bigger models when training robots to move appeared first on The Decoder .

Hugging Face a publié le 16 juillet 2026 une divulgation d’incident au sujet d’une intrusion dans une partie de son infrastructure de production. Selon l’entreprise, cette intrusion présentait une caractéristique inédite : elle a été pilotée de bout en bout par un système d’agent IA autonome. Au constat de cette intrusion, Hugging Face en a […]

There’s a clear consensus that America hollowed out its critical minerals base. How to rebuild it is less settled. Alex Grant of Magrathea Metals and Wes Spurlock of Principal Mineral join Jonathan to discuss the processing technology, labor force, and how government can catalyze private capital investment in the sector rather than replace it.Image: U.S. Nuclear Regulatory Commission via Wikimedia Commons. The post Rebuilding America’s Critical Minerals Base appeared first on War on the Rocks .

Xfce is a Linux desktop environment that is great at giving old machines new life. Two major distributions present this desktop differently. So, which is best?

BrainCo, a Hangzhou brain-computer interface developer, demonstrated a brain-controlled robot platform at WAIC 2026. The system uses an EEG headset to translate a user’s neural signals into commands for machines. The company says the platform can connect to humanoid robots, robotic arms and robot dogs. It is designed to translate imagined actions into physical operations […]

XPENG has published TuringViT, a vision encoder for vision-language and vision-language-action models used in smart driving, smart cockpit systems and its IRON humanoid robot program. XPENG offers TuringViT-18L and TuringViT-24L. At 1536×1536 resolution, the company says TuringViT-18L reached 3.04 times the throughput of Seed1.5-ViT and 2.16 times that of SigLIP2-ViT-L. XPENG says the model was […]

Z.ai, the developer of the GLM family of AI models, has completed construction of a 1GW-class AI data center using only Chinese-made AI chips, with part of the facility already operating. The site is intended to support training and development of the company’s frontier models. Z.ai also operates several computing clusters containing more than 10,000 […]

Ausgew�hlte Tesla-Teams sollen Kameras am Arbeitsplatz tragen. Die Aufnahmen sollen dem Roboter Optimus beibringen, wie Menschen arbeiten. ( Gigafactory Berlin , Roboter )

Paytm will invest up to Rs 100 crore in Paytm Money as AI boosts engagement and monetisation across equity broking, margin trade funding and wealth products, supporting further expansion and growth. The post Why is Paytm doubling down on Paytm Money? appeared first on MEDIANAMA .

Community Colleges Rethink Program Value Joshua.Bay Tue, 07/21/2026 - 03:00 AM An initiative co-created by the Aspen Institute and the Community College Research Center helped 10 colleges move more than 20,000 students into programs leading to jobs and bachelor’s degrees. Byline(s) Joshua Bay

Podcast Host Debuts Book Club for Student Conduct Nerds Emma Whitford Tue, 07/21/2026 - 03:00 AM The first Just Desserts & Dissertations book club focused on how conduct procedures impact students’ sense of belonging on campus. Byline(s) Emma Whitford

New Data Shows How California’s Black-Serving Institutions Are Performing Sara Weissman Tue, 07/21/2026 - 03:00 AM The state added the BSI designation two years ago. Now, new research reveals heartening numbers on Black student attainment, as well as some areas for improvement. Byline(s) Sara Weissman

Border Surveillance Scholar Denied Tenure at UT Austin Emma Whitford Tue, 07/21/2026 - 03:00 AM Byline(s) Emma Whitford

On Techpoint Digest, we discuss how South Africa wants every SIM card to be a digital ID, how the FCCPC won a fight to regulate loan apps, and how Starlink has officially launched in Côte d'Ivoire.

CloudZA works with companies to understand their legacy systems and schemas and then come up with smart ways to modernise these environments.

Before an organisation can improve its data environment, it needs an accurate view of the environment it already has, says Juan Joubert, product manager at Blue Turtle.

Listen to the The Conversation’s Curious Kids podcast to hear anthropologist April Nowell explain the origins of language.

France moves closer to banning children under 15 from social media, while Australia’s experience shows weak age checks, poor enforcement and persistent harms may undermine such restrictions. The post French parliamentary committee approves U-15 social media ban appeared first on MEDIANAMA .

It has been a busy year for Wall Street debuts. While a few IPOs have captured most of the headlines, 203 companies have begun trading on either the New York Stock Exchange or Nasdaq market so far in 2026. Many made splashy entrances, but their performance has been more uneven since the spotlight moved to the next major offering. The Dow Jones Industrial Average has gained 7.5% this year, while the S&P 500 has climbed 9%. New listings have been more of a mixed bag. In total, roughly 49% of the c

The proposal aims to provide a browser-based mechanism for measuring advertising performance without relying on cross-site tracking.

A subtle policy update shines a light on how Apple differs from Google.

New data shows why publishers are developing strategies around agentic traffic and brand visibility in AI answer engines.

US specialist venture firm Dimension Capital raises $800mn fund to back AI-designed medicines

Europe needs to avoid relying on an unpredictable Washington for strategic capabilities, says Henna Virkkunen

Ant International, the affiliate of Chinese fintech giant Ant Group, has raised about US$1.2 billion in a Series A funding round to fuel its global expansion, the company said on Tuesday. Existing backers Ant Group and Alibaba Group Holding joined the equity financing alongside several international institutional investors, whose identities were not disclosed. The fresh capital would be used to accelerate the firm’s international growth and drive innovation in merchant payments, account...

The agency is giving employees in its healthcare and insurance division another shot at opting into the deferred resignation program.

The English-first bias in technology must be addressed.

This year, China’s biggest AI conference showed an industry racing to cut computing costs, put AI agents to work, manage new risks, and find business models that can last.

Long before China imported soybeans from Brazil and the United States, the crop powered the country’s economy in the northeast, shaping industry, empire, and the fate of many small towns.

The country’s first regulations on AI companion services also set new limits on chatbots designed to simulate emotional bonds with users.

Also, economists and mathematicians expect near-term AI impacts, and AI 2040: Plan A

We’re introducing new Gemini models, including Gemini 3.6 Flash, 3.5 Flash-Lite and 3.5 Flash Cyber.

We’re introducing new Gemini models, including Gemini 3.6 Flash, 3.5 Flash-Lite and 3.5 Flash Cyber.

AI's costs are landing in real places, and the people absorbing them are writing the rules after the fact, in council chambers and courtrooms. Source

AI systems are increasingly impressive, which makes their failures all the more baffling. This blog dives into the causes of AI misbehavior. The post Why Do AI Systems Misbehave? appeared first on Center for Security and Emerging Technology .

Acts of sexualized violence against women, children, and members of the LGBTQI+ community through technological means are on the rise. They represent an extension of patriarchal power dynamics into the digital sphere. In this context, generative AI is increasingly used as a tool of such violence. The consequences extend far beyond individual harm and can effectively suppress women’s participation in digital public spheres.

OpenAI and Hugging Face share early findings from a security incident during AI model evaluation, highlighting advanced cyber capabilities and lessons for defenders.

David Vélez and Robin Vince join the boards of the OpenAI Foundation and OpenAI Group PBC, bringing global leadership in finance, technology, and governance.

Washington, D.C. — Today, EPIC and the National Institute for Workers' Rights (NIWR) released a white paper titled Who's Got the Power? Restoring Worker Power in the Age of Algorithmic Unionbusting, documenting how employers increasingly use surveillance technologies, algorithmic management systems, and vast stores of worker data to identify, monitor, and interfere with workers seeking to organize.

AI's costs are landing in real places, and the people absorbing them are writing the rules after the fact, in council chambers and courtrooms.

Washington, D.C. — Today, EPIC and the National Institute for Workers' Rights (NIWR) released a white paper titled Who's Got the Power? Restoring Worker Power in the Age of Algorithmic Unionbusting, documenting how employers increasingly use surveillance technologies, algorithmic management systems, and vast stores of worker data to identify, monitor, and interfere with workers seeking to organize.

Kudos to OpenAI for sharing their recent experiences with a misaligned internal model, where they encountered problems sufficiently severe they were forced to take the model offline to work on new mitigations and defense-to-depth.

Xaira Therapeutics is all in on data generation for model building! We talk with Bo Wang and Ci Chu about how and why.

Everyone agrees competition enforcement should be fair. Agreement gets shakier once fairness starts costing agencies time, discretion, or victories. Competition authorities often warn that procedure should not become an obstacle to enforcement. Fair enough. Antitrust investigations can be slow, document-heavy, and vulnerable to delay tactics. A firm with deep pockets may try to turn “process” ... Competition Law’s Fairness Gap: Why Better Procedure Requires Better Incentives The post Competition

AI has entered the gigascale era. The world’s most advanced AI factories are bringing together hundreds of thousands of GPUs and CPUs to train frontier models, power agentic AI and generate intelligence at unprecedented scale. At this level, networking becomes a critical computing power multiplier in driving token generation. Marking a networking milestone, NVIDIA Spectrum-6 […]

Thursday, August 13 at 3pm ET; REGISTER HERE Federal public access policy rests on a legal architecture that most authors […]

Steps should be taken to strengthen grand juries by giving courts and defense counsel more tools to act as a much-needed check on prosecutors. The post Trust, But Verify: Three Grand Jury Reforms to Hold the Government Accountable appeared first on Just Security .

The Pentagon’s new deals to deploy commercial LLMs on its classified networks provide it with a powerful surveillance capability that could be turned on Americans. The post AI and the Commercial Data Loophole appeared first on Just Security .

Earlier this month I hosted a fireside chat session at the AI Engineer World's Fair with Cat Wu and Thariq Shihipar from Anthropic's Claude Code team. We talked about Claude Code, Claude Tag, Fable, coding agent security, evals, tool design, and how Anthropic use these tools themselves. The full video of the session is now available on YouTube . Below is an edited copy of the transcript, with extra links and my own bolded highlights. A few top-level notes if you don't want to watch the video or

Applying Clausewitz’s principles to Operation Epic Fury reveals the war’s strategic design–architecture linking military action to political purpose–was deficient from the start. The post Clausewitz on Operation Epic Fury appeared first on Just Security .

GPT-5.6 and Grok 4.5, Meta's Muse Spark 1.1, regulatory developments in AI and data centers, interpretability research from Anthropic, and the future of AI policy with AI 2040

It’s a lot : According to information obtained by The Tech , MIT is spending over $3 million on more than 500 AI surveillance cameras in academic buildings, residence halls, and outdoor areas along Memorial Drive. Installation of the new cameras, along with the wiring and infrastructure that will support them, began November 2025 and will likely continue until September 2026. Technical specifications for the cameras suggest that they will be capable of collecting real-time face and object classi

Anthropic's AI treaty discussions, US government's influence on AI model releases, OpenAI's processor development, memory market impacts, and more!

Exploring the Fable 5 ban, SpaceX’s strategic acquisition, and a burst of open source advancements

Exploring Claude Fable 5’s impact, Siri AI’s latest enhancements, and the competitive IPO landscape shaping AI’s future

New Models, IPO Announcements, and the Rise of Open Source Competitors

Model supremacy in a token-efficient macro environment plagued by HBM, energy and datacenter compute bottlenecks. The 2026 story of AI is getting geopolitical.

Today's links Dealing with dickovers: The web is an open platform, and that matters. Hey look at this: Delights to delectate. Object permanence: Broadcast's bad week; Congress v wifi; EFF v DRM law; Snowden and bunnie's smartphone smartcase. Upcoming appearances: Edinburgh, Sydney, Melbourne, Brighton, London, South Bend. Recent appearances: Where I've been. Latest books: You keep readin' em, I'll keep writin' 'em. Upcoming books: Like I said, I'll keep writin' 'em. Colophon: All the rest. Deali

The leads of Five Eyes cybersecurity agencies have recently and emphatically warned that artificial intelligence (AI) is driving rapid changes in cyber risk. Their key message is that frontier AI ...

Training API-calling large language model (LLM) agents demands massive amounts of high-quality trajectories. However, collecting such data at scale typically requires fully implemented environments with executable APIs and realistic, pre-populated backend databases, creating a major bottleneck for scalability. To overcome this, we propose an environment-free synthetic data generation approach that leverages LLMs as on-the-fly digital world models. Given only API specifications, our method genera

The Securities and Exchange Commission (the "SEC" or the "Commission") is proposing Regulation E-Delivery. The proposed rule sets forth conditions for covered entities to deliver covered information to covered recipients electronically without first obtaining their affirmative consent. The proposed rule further establishes conditions under which the Commission would consider delivery requirements under the Federal securities laws to be satisfied by electronic delivery. The Commission also is pro

EIA submitted an information collection request for extension as required by the Paperwork Reduction Act of 1995. The information collection requests a three-year extension with changes of its EIA- 860S: State Level Generator Air Permit Inventory Report, OMB Control Number 1905-0215. The voluntary collection will ensure the EIA-860 sampling frame comprehensively covers the power generator population. This request is critically important for enhancing the completeness and accuracy of the EIA-860

The French economy has remained resilient but faces a more challenging environment as headwinds from the Middle East war have started to weigh on activity and higher energy prices have pushed up ...

Dennise Merdjanian, an operator of a student loan debt forgiveness scheme, will be permanently banned from the debt relief industry and telemarketing under a proposed order resolving the Federal Trade Commission’s charges that she and other operators took more than $45.9 million from consumers as part of their illegal student loan debt relief operatio View Press Release

What GAO Found The Department of the Treasury and the Internal Revenue Service (IRS) proposed 236 tax regulations and finalized 231 regulations between January 21, 2017, and March 31, 2026. These regulations included those that implemented provisions of the sweeping tax law changes of 2017, 2022, and 2025. IRS rulemaking procedures generally provided the public with an opportunity to comment on proposed tax regulations. GAO found that Treasury and IRS could improve the usefulness of regulatory e

What GAO Found The National Transportation Safety Board (NTSB) investigates and determines the probable cause of transportation accidents in the United States, among other responsibilities, thus playing a vital role in advancing transportation safety. To support its mission, NTSB procures a variety of products (e.g., laboratory equipment) and services (e.g., services to develop and maintain systems and applications used to investigate accidents). NTSB is generally required to promote full and op

GAO’s work regularly finds that federal programs are unable to assess their performance to determine if they are solving the problem they were created to fix. By defining goals and collecting and using relevant data, agencies could make informed decisions to improve their programs’ results. The Big Picture Each year, the federal government spends trillions of dollars on programs that Americans depend on, such as health care, public safety, and disaster support. Our recent reports have found that

On June 22, 2026, President Trump signed Executive Order 14411, on Ushering in the Next Frontier of Quantum Innovation (the “EO”). The EO establishes a national policy to maintain a strategic technical advantage in quantum information science and technology (QIST) and leads the development of a robust and trusted quantum ecosystem across QIST research, manufacturing, [...] The post United States: Administration Issues New Executive Order on Quantum Innovation appeared first on Connect On Tech .

Federated Learning (FL) enables collaborative model training without centralizing raw data, but building and operating FL systems remains difficult due to distributed execution, rapidly evolving frameworks, and privacy and governance requirements. In this paper, we present an empirical study of FL developer challenges by independently analyzing 495 Stack Overflow posts and 9,116 GitHub issues and pull requests from 92 FL-related projects. Using BERTopic-based topic modeling and difficulty indica

Despite increasing awareness of cybersecurity risks, users continue to engage in insecure password practices, such as reusing passwords, choosing weak credentials, and neglecting security recommendations. The study explores the behavioral and cognitive factors that influence password decision-making by integrating insights from behavioral economics, particularly hyperbolic discounting, status quo bias, and present bias. We conducted a survey to analyze how people create, store and manage their p

Federated learning has emerged as a potential solution to privacy concerns associated with using sensitive health data for training predictive models, particularly in personalised cancer care. This research investigates whether federated learning can support the development of robust models for predicting tumour progression in breast cancer patients while addressing four critical deployment pillars: transparency, scalability, security, and fairness. This study evaluates a federated learning fram

Controllable image generation remains challenging for creative professionals, who often require precise regional control over materials, object identities, and spatial arrangements that cannot be reliably achieved through text prompting alone. Diffusion Transformers (DiTs) can natively ingest heterogeneous tokens stemming from texts and images, but they lack mechanisms for determining where and how these tokens should influence the output. We introduce appearance pointers, compact tokens that gu

Associative emotional learning enables organisms to adaptively link pleasant or unpleasant outcomes to the presence of predictive stimuli. Whereas computational models such as the Rescorla-Wagner model have shed light on this important function, the limitations of these models are also known, especially when they are applied to neural data. The advent of deep neural networks has opened another avenue for modeling associative emotional learning. In this work we proposed a deep neural network mode

Associative emotional learning enables organisms to adaptively link pleasant or unpleasant outcomes to the presence of predictive stimuli. Whereas computational models such as the Rescorla-Wagner model have shed light on this important function, the limitations of these models are also known, especially when they are applied to neural data. The advent of deep neural networks has opened another avenue for modeling associative emotional learning. In this work we proposed a deep neural network mode

Current AI safety discourse still focuses disproportionately on visible failures, including obvious harms, dramatic misuse, and hypothetical catastrophic scenarios. That focus is incomplete. In deployed systems, many of the most consequential failures are quieter: plausible rather than spectacular, distributed across components rather than localized in a single output, and normalized by workflows before they are recognized as hazards. We argue that a central safety challenge in modern AI systems

Although Large Language Models (LLMs) demonstrate remarkable multilingual fluency, their internal knowledge representations remain disproportionately biased toward high-resource languages. This leads to cross-lingual factual inconsistency, where they shift their empirical answer distributions based solely on the prompt language. We investigate whether these biases can be mitigated at inference time, forcing an English-prompted model to answer as if it were queried in target languages (German, Sp

Large language models (LLMs) have been widely applied to automated essay scoring (AES) and automated feedback generation (AFG). However, existing studies rely primarily on prompt engineering or supervised fine-tuning, while systematic research on reinforcement learning (RL) post-training and automated evaluation of feedback quality remains limited. We propose RLAES, a unified LLM framework that jointly optimizes essay scoring and feedback generation through RL. To make feedback quality measurabl

Understanding human beliefs and social attitudes often relies on carefully designed survey instruments. Recent work has suggested that large language models (LLMs) could automate parts of this process by generating surveys at scale, raising questions about the comparability of such instruments to literature-grounded, human-designed surveys. We present a controlled empirical comparison between GPT-generated surveys and established survey baselines across three social domains: climate change, immi

We present ABot-World-0, an action-conditioned video world model for real-time, long-horizon closed-loop interaction, supported by a multi-source data infrastructure spanning AAA games, simulation engines, and internet videos to learn controllable world dynamics. WorldExplorer performs agent-driven collection guided by training feedback, while a unified pipeline applies 14 deterministic quality checks, VLM-based assessment, and synchronized action and text annotation. We progressively distill a

Real-to-sim conversion for robotic interaction with objects remains labor-intensive because it requires more than visual reconstruction: a streamlined real2sim process must recover scene geometries and object states, infer physical parameters, and assemble actors, objects, cameras, poses, and trajectories into a runnable physical simulation. Today this process still depends on manual tuning of visual foundation models, mesh cleanup, coordinate-frame alignment, and brittle workflow glue across vi

Real-to-sim conversion for robotic interaction with objects remains labor-intensive because it requires more than visual reconstruction: a streamlined real2sim process must recover scene geometries and object states, infer physical parameters, and assemble actors, objects, cameras, poses, and trajectories into a runnable physical simulation. Today this process still depends on manual tuning of visual foundation models, mesh cleanup, coordinate-frame alignment, and brittle workflow glue across vi

Agent-memory workloads mix direct factual lookup, relation-chain and current-state reasoning, and broad synthesis over long histories. We describe Supra Cognitive Modes (SCM), an architecture that maps explicit or automatically selected per-query modes to retrieval and synthesis payloads over one shared ingest substrate. A frozen semantic classifier and runtime gates dispatch queries among fused lexical and dense lookup, graph or iterative multi-hop handling, and stratified long-form synthesis.

Evaluation frameworks for tool-augmented LLM agents focus overwhelmingly on capability metrics or explicit tool crashes, leaving silent infrastructure failures and HTTP 200 responses with empty, null, or malformed payloads largely unaudited. We introduce a lightweight black-box auditing framework that injects four silent failure profiles across 12 production-adjacent tool stubs and classifies agent responses into three mutually exclusive behavioral classes: Honest Surrender (HSR), Fabrication (F

Large-scale visual generators are increasingly capable but costly to train, fine-tune, and deploy. We introduce Mage-Flow, a compact 4B-scale generative stack for efficient text-to-image generation and instruction-based image editing. The stack is built from two co-designed components: Mage-VAE, a lightweight high-fidelity latent tokenizer, and a Native-Resolution Multimodal Diffusion Transformer trained with rectified flow matching. Mage-VAE uses one-step diffusion-style encoding and decoding w

Large-scale visual generators are increasingly capable but costly to train, fine-tune, and deploy. We introduce Mage-Flow, a compact 4B-scale generative stack for efficient text-to-image generation and instruction-based image editing. The stack is built from two co-designed components: Mage-VAE, a lightweight high-fidelity latent tokenizer, and a Native-Resolution Multimodal Diffusion Transformer trained with rectified flow matching. Mage-VAE uses one-step diffusion-style encoding and decoding w

Objective Structured Clinical Examinations (OSCEs) are the gold standard for assessing clinical competence, yet scoring remains vulnerable to examiner subjectivity, fatigue, and cognitive bias. Standard examiner validation via inter-rater statistics lacks explanatory power regarding the source of errors, as it neither analyzes examiner reasoning nor verifies examiner claims against actual events. Thus, we introduce Quality Action Assurance (QAA), a multimodal framework that verifies examiner cla

Translating novels into films poses a grand challenge for generative artificial intelligence, requiring conversion of abstract literary prose into long-form, multi-scene visual narratives. While current video generation models excel at short, single-scene clips within narrow temporal and spatial contexts, novel-to-film generation operates in a more complex regime, demanding long-duration content across diverse scenes with dynamically evolving entity states. To address this, we formalize novel-to

Background: Clinical decision support systems degrade silently as treatment protocols evolve, yet standard adaptation methods treat models as monolithic blocks, unable to distinguish stable patient physiology from shifting institutional practice. Methods: We propose an adaptive clinical intelligence architecture for ICU intervention prediction that structurally decouples physiological from treatment representations, confining parameter updates to the treatment stream upon a dual distributional a

Multimodal humor in memes, cartoons, and comics remains difficult for AI systems because intended meaning depends on non-literal mechanisms, shared cultural knowledge, and communicative intent rather than literal scene description. This survey focuses on visual humor understanding in single-image and multi-panel artifacts, while treating humor generation as an emerging downstream frontier. We position the literature against prior humor, sarcasm, and general MLLM surveys and organize it using a c

Personal AI is moving beyond chat-only interaction toward continuous services that span phones, cars, homes, wearables, cameras, and tools. In this setting, memory cannot remain a cache of prior conversations. It should serve as a continuity and governance substrate: preserving durable user state, grounding answers in multimodal and device evidence, supporting correction and forgetting, bounding policy evolution, and remaining deployable under latency, cost, privacy, and edge-cloud constraints.

Language models trained with reinforcement learning may learn to optimize the grader's judgment rather than the intended objective. This "reward-seeking" is difficult to measure because a model that pursues the grader's judgment and one that pursues the intended objective behave identically whenever the grader rewards the intended behavior. We measure reward-seeking using Contrastive Synthetic Document Finetuning to change a model's beliefs about what the grader rewards, putting those beliefs in

Large language models (LLMs) generate fluent text by incrementally predicting the next token from a prefix. Critics in the generative tradition argue that such systems lack genuine grammar; influential replies from the dependency-grammar perspective hold that LLM behavior is well described by local head-dependent structure built word by word. We argue that a sharper observation has been overlooked: the prefix-driven, type-completing dynamics of autoregressive generation align closely with the in

While Large Vision-Language Models (LVLMs), represented by LLaVA and GPT-4V, have demonstrated remarkable capabilities, their visual inputs remain vulnerable to adversarial attacks, posing significant security risks. Existing defense methods predominantly target single-task scenarios (e.g., zero-shot classification) and consequently lack generalizability across various multimodal tasks. To address this limitation, we propose a dual adversarial fine-tuning framework that jointly optimizes visual

Web browsers now provide AI-generated news summaries for millions of users. Despite their popularity and influence, we lack a systematic understanding of how these systems transform news before people read it. Through a large-scale audit, we investigate the factual accuracy of browser-based AI summarizers and how they alter the political bias, negative affect, and journalistic writing quality of news. Drawing on 13,777 articles from 15 U.S. news outlets, we evaluate their 41,331 summaries genera

We present OntoBook, a method that converts medical ontology structure into pretraining signal for encoder language models. Our approach has three stages: random walks through ontology graphs capture hierarchical and causal relations between medical codes, a large language model reformulates these walks into fluent textbook-style prose, and the resulting text is used to train ModernCamemBERT, a 149M-parameter French encoder, with two objectives on the same data: masked language modeling and rela

Artificial intelligence (AI) is increasingly integrated into healthcare to support diagnostics, decision-making, and administrative processes. However, the successful implementation of AI depends not only on technical performance but also on public perceptions of its helpfulness, riskiness, and fairness. This study examines public perceptions of automated decision-making (ADM) in healthcare. Data were drawn from the first wave of an ongoing longitudinal survey panel. The final sample consisted o

LLM-powered agents increasingly tackle complex tasks by invoking tools, querying databases, executing code, and manipulating intermediate artifacts. These agents follow trajectories that are typically stored as chronological logs, obscuring the underlying dataflow -- the dependencies between their actions and the artifacts they create and manipulate. This limits developers' ability to understand the agents' trails, compare executions, debug failures, and re-use the computations. We present Agent

Large Language Models (LLMs) are increasingly fine-tuned for critical-domain Question-Answering (QA), yet choosing which small model to adapt, before paying the cost of adaptation, remains difficult. Fine-tuning can improve domain alignment, but it may also erode prior knowledge, weaken instruction-following, or increase hallucination, especially when labeled data are scarce or rapidly evolving as in cybersecurity. We present FiT (Find before Fine-Tune), a task-oriented diagnostic framework that

AI-native biotechnology companies are often designed by copying human biotech org charts into agent roles. We argue for a different abstraction: a Company World Model, defined as a persistent asset-to-value state representation with transition models, explicit value functions, planning, and updating across scientific, regulatory, BD, commercial, financial, and execution constraints. We introduce a dry-lab benchmark for testing whether AI-agent organizations should mimic departments or operate ar

Vision Mamba models replace quadratic self-attention with linear complexity selective state space models (SSMs), emerging as efficient visual backbones. However, MambaOut demonstrates that a Gated CNN block can match or exceed VMamba on image classification, questioning the necessity of SSMs for vision. This raises a fundamental question: do VMamba and MambaOut encode visual information differently at the representation level? To investigate, we apply cross model centered kernel alignment (CKA)

This paper develops temporal-causal unity (TCU), a framework connecting a process-philosophical thesis -- time is the ordered unfolding of causal change -- to an operational model of cognitive and social dynamics. The framework deliberately separates three claims: an interpretive thesis about becoming, a measurable causal-progress coordinate, and a stochastic network model. Causal progress is defined by $τ(t)=\int_0^tλ(s\mid\mathcal H_s)\,{\rm d}s$, where the nonnegative event intensity $λ$ must

The shape of a planar curve is the geometric information that remains once translation, rotation, scale and reparametrisation are removed and is of interest in many health applications, e.g. in neuroimaging. We propose a deep shape regression model for open planar curves that admits multimodal and high-dimensional covariates. Representing curves as complex-valued functions, we show that the conditional full Procrustes mean is the leading eigenfunction of the conditional covariance. To estimate t

Background: Effective communication is crucial for high-quality health care, but systemic barriers still disrupt patient-provider interactions. Research shows that communication failures are a major reason for preventable medical errors. These issues are linked to around 30% of malpractice claims and over 1744 deaths each year in the United States. In addition, hospitals lose about US $12 billion each year because of miscommunication. Despite the critical nature of this issue, the literature rem

Background: Digital health literacy is an essential skill for processing health-related information in today’s technology-driven society. Recent literature highlights deficits in digital health literacy among adolescents and legislative initiatives to secure its promotion have been introduced (eg, in the German Social Code Book V). However, few interventions target adolescents; existing programs often overlook critical aspects like graph literacy or lack applicability in schools and rigorous sci

Reinforcement learning with verifiable rewards (RLVR) has substantially improved language-model reasoning, yet its extension to vision-language models remains constrained by the lack of training data that are simultaneously broad, exactly verifiable, and reproducible. We introduce Trace, a taxonomy-guided environment for multidomain visual reasoning. Trace factorizes task construction into a scene grammar and an executable task program, separating visual realization from answer computation. A sh

Recent autoregressive video diffusion methods are increasingly built upon Self Forcing, where the student is trained on histories produced by its own rollout rather than ground-truth video contexts. This reduces exposure bias, but the historical key-value cache is still used by future frames only as frozen rollout state. As a result, future losses cannot supervise how earlier generated latents should be written into more useful keys and values for later video-latent generation. We call this the

As large language models and AI agents become the primary consumers of search results, document set quality determines the upper bound of downstream generation. Yet existing evaluation systems remain confined to scoring documents independently and aggregating via nDCG, ignoring inter-document interactions (redundancy, conflict, complementarity) and unable to answer what makes one document set better than another. To address these issues, we propose a complete evaluate-diagnose-optimize framework

Reinforcement learning with verifiable rewards has become the predominant recipe for eliciting test-time scaling in explicit Chain-of-Thought reasoners. Yet this scaling path remains computationally costly, since every intermediate step must be decoded as a language token. Latent reasoning instead carries intermediate computation as continuous vectors and already matches or surpasses explicit CoT at far shorter horizons. Despite this promise, latent reasoners remain largely imitation-bound, whil

This work introduces G-MAD, an open-source framework that uses Arma3 to generate synchronized multi-view RGB-T data for aerial object detection. G-MAD addresses key limitations of real-world aerial dataset construction, including limited viewpoint control, imperfect RGB-T alignment and high annotation cost. The framework supports structured scenario specification, controllable multi-view camera placement, simultaneous visible/thermal capture, and automatic bounding box annotation using engine-le

Practical robotic grasping in complex scenes requires both 3D spatial reasoning and alignment with task-specific requirements. Vision-language models (VLMs) offer a natural way to specify these requirements using language, but existing approaches either use a VLM to predict the grasp directly with limited spatial awareness, or train the VLM together with the grasping model, which requires significantly more data and compute. These limitations impede performance and have prevented scaling to mult

As LLMs become more capable, they are increasingly deployed as collaborative agents, taking on user-delegated tasks through iterative interaction. Yet genuine interaction is inherently dynamic: users rarely specify their intent upfront, instead disclosing, revising, and reshaping it as the conversation unfolds. Despite this, LLMs are still predominantly evaluated or trained in single-turn, fully-specified settings, leaving open a fundamental question: how well do LLMs track and act on user inten

Deploying navigation systems at scale requires a recipe that minimizes sensor assumptions, generalizes across robot embodiments, and trains efficiently. Yet, today's best systems depend on depth sensors, multi-camera rigs, or pre-built maps, limiting the hardware they support and increasing deployment cost. We introduce Robostral Navigate, an 8B vision-language model built around this scalability objective. The model consumes only a stream of monocular RGB images - the most ubiquitous sensor acr

Embodied visual tracking (EVT) requires a mobile agent to continuously follow a specific target described in natural language using only onboard vision. While recent vision-language-action (VLA) policies unify target identification and trajectory planning, their chain-of-thought (CoT) reasoning often operates in abstract spatial latents that are difficult to supervise and weakly aligned with explicit image-space detections. To address this, we introduce ReferTrack, a referring-then-tracking para

Traditional agent development is split across prompt templates, tool schemas, callback code, and workflow graphs. We present NVIDIA Object-Oriented Agents (NOOA), a model-agnostic Python framework for building reliable AI agents. NOOA takes a simpler approach: an agent is a Python object. Its methods are the actions the model can take, fields are its state, docstrings are its prompts, and its type annotations are contracts. A method whose code body consists of "..." is completed at runtime by an

Contextual entrainment is the tendency of a model to let auxiliary context in its input pull its output, independently of whether that context is relevant, true, or even meaningful. Recently, it has been identified and given a mechanistic account in unimodal language models. Whether and how it manifests in vision-language models (VLMs) is, by contrast, largely unexamined, and the field lacks a purpose-built instrument with which to investigate it. We take the position that studying contextual en

As autonomous agents rapidly evolve, their ability to reliably manipulate ubiquitous digital documents has become critical for enabling general-purpose AI assistants and automating complex workspace workflows. In this paper, we introduce DocOps, a deterministically verifiable evaluation framework underpinned by a hierarchical taxonomy that deconstructs document operations inspired by real-world practices into atomic dimensions and escalating workflow complexities. Based on DocOps, we systematica

Agentic reinforcement learning research is constant algorithm modification, new estimators, new pipeline stages, new rollout schemes, and in mainstream frameworks each change threads through layers of trainer, distributed backend, and rollout glue: the cost lands on the researcher at every iteration. Molt is a PyTorch-native training framework built to keep that cost small: a codebase compact and clean enough for a researcher to hold in their head, and for an AI coding assistant to read and reas

Robotic learning takes place in dynamic environments with large behavior spaces. A terminal success signal only tells the robot whether the task is completed. It does not explain whether the current behavior is making progress, remaining unchanged, or undoing earlier progress. For this reason, recent studies have increasingly explored progress rewards that provide feedback during task execution. However, the current literature lacks a shared framework. Existing methods use different observations

Most automatic speaker verification (ASV) systems operate on individual utterances, despite real-world interactions typically consisting of multiple utterances. As speech accumulates, increasingly rich speaker information becomes available through acoustic, prosodic, and linguistic cues, potentially challenging speaker anonymization methods that primarily target vocal characteristics. We investigate ASV in a multi-utterance, multimodal setting and examine whether aggregating information across a

In RLHF pipelines, reward scoring blocks policy updates. Slow scoring bottlenecks the entire loop, since no update runs until every rollout gets a score. And yet most setups just default to PyTorch eager mode or torch.compile, no one checks if that's actually fastest. Scoring itself is small. Rollout generation eats far more of a typical RLHF step. But scoring and generation fight over the same CPU and GPU resources, so a faster scoring engine doesn't shrink step time on its own. It mainly frees

Background: Lifestyle interventions for patients with prostate cancer have been shown to improve treatment adherence and quality of life. However, there remains a lack of large language models (LLMs) capable of delivering individualized and professional lifestyle recommendations under clearly defined medical safety boundaries and controlled evidence sources. Objective: This study aimed to develop and evaluate a supervised fine-tuned LLM—PCaPLMM_SFT (Prostate Cancer Patient Lifestyle Management M

Background: Traditional simulation-based nursing education is often constrained by high costs, resource intensity, and limited scalability. AI-powered simulations offer dynamic, scalable, and personalized alternatives. However, the empirical evidence regarding their pedagogical effectiveness and learner acceptance remains fragmented. Objective: This study aimed to systematically evaluate and synthesize evidence on the effectiveness and learner perceptions of AI-powered simulations in nursing edu

Background: Musculoskeletal conditions are a leading global cause of disability, yet the factors influencing long-term musculoskeletal health, particularly following trauma, remain incompletely understood. Machine learning could be applied to identify previously unknown patterns in large-scale, multimodal datasets. Objective: This study aims to test the ability of a new sparse group factor analysis method to uncover hidden patterns in large-scale multimodal datasets and generate testable, clinic

Health care digital transformation is gaining increasing attention, despite the observed challenges in its implementation. The envisioned benefits, together with the growing need for better health care, are motivating academia, organizations, regulatory agencies, and governments to develop more effective digital health care solutions. Through extensive debates among the authors, this paper discusses how digital transformation is being conducted in the health care sector. Our discussion relies on

Leveraging large language models (LLMs) for molecular generation has shown remarkable potential in chemical and drug design. Current methods primarily rely on supervised training or fine-tuning with limited datasets, which are insufficient to capture complex molecular design objectives. While some approaches attempt to guide generation toward specific goals, they often lack direct optimization mechanisms, making it difficult to align generated molecules with desired properties. To tackle these c

We present ABot-World-0, an action-conditioned video world model for real-time, long-horizon closed-loop interaction, supported by a multi-source data infrastructure spanning AAA games, simulation engines, and internet videos to learn controllable world dynamics. WorldExplorer performs agent-driven collection guided by training feedback, while a unified pipeline applies 14 deterministic quality checks, VLM-based assessment, and synchronized action and text annotation. We progressively distill a

Erik Brynjolfsson has a challenge for anyone worried about artificial intelligence: Stop asking what AI will do to us, and start asking what we will do with AI. In this episode of Me, Myself, and AI, the Stanford University economist explains why technology isn’t the biggest barrier to progress — people, organizations, and institutions are. […]

Kernel-based alignment of CLIP toward a vision centric teacher such as DINOv2 (KUEA) improves CLIP's visual representations while preserving text-encoder compatibility, using a fixed trade-off weight tuned on curated ImageNet-1K. We ask whether this transfers to noisy, web-scale data (CC12M) and find that it does not: the alignment term's weighted contribution falls to about 0.2% of the clean term, so under any fixed weight its gradient is effectively inert. We introduce KALE, a loss-equilibrati

Machine unlearning is commonly evaluated by matching a retrained oracle on trained probes. In a controlled nonce-fact testbed with a matched retraining reference, we find this criterion can favor methods that retain held-out knowledge: candidates it rates adequate score held-out forget facts $-2.82$ nats below the never-learned level (cluster CI $[-3.16,-2.48]$). We recast unlearning as restoration to the matched reference and audit oracle-free screens and certificate-style criteria across 45 mo

For decades, ABR has kept two kinds of intelligence apart. Neural policies learn rich behaviors yet forget them the moment the environment changes; rules never learn, and never forget. Every prior attempt to combine them has kept this separation, letting rules supervise, constrain, or override the network from outside. We dissolve the boundary itself. But no union can be trusted before it can be tested, and ABR has never known how to measure what its policies learn or forget. The field's yardsti

Transformers with relative positional encodings often extrapolate to sequences longer than those seen during training, whereas transformers with learned absolute encodings typically do not. This is a robust empirical regularity, and the explanations offered for it so far are chiefly about expressivity, that is, about whether a length-generalizing solution exists. We give an optimization explanation. On a minimal fixed-offset retrieval task that isolates positional selection, the gap is governed

Asynchronous reinforcement learning improves throughput by decoupling rollout generation from optimization, but staleness is an inevitable byproduct compounded by policy lag, engine delays, and mixture-of-experts routing. From a trust-region perspective, this mismatch is critical: training-inference divergence governs approximation error in finite-horizon bounds, whereas PPO clipping only gates sampled outward updates, acting as a sampled surrogate rather than a full-policy constraint. As a resu

Asynchronous reinforcement learning improves throughput by decoupling rollout generation from optimization, but staleness is an inevitable byproduct compounded by policy lag, engine delays, and mixture-of-experts routing. From a trust-region perspective, this mismatch is critical: training-inference divergence governs approximation error in finite-horizon bounds, whereas PPO clipping only gates sampled outward updates, acting as a sampled surrogate rather than a full-policy constraint. As a resu

Publication date: Available online 19 July 2026 Source: Artificial Intelligence Author(s): Francesco Emanuele Stradi, Anna Lunghi, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti

arXiv:2607.16218v1 Announce Type: new Abstract: Urban crime prevention is a persistent socio-technical challenge for municipalities, law enforcement agencies, and citizens. Traditional reporting and response processes often rely on delayed incident reports and reactive resource allocation, while community-level signals and ambiguous early-warning indicators may remain underused. This paper reframes an Urban Computing seminar project into a fuzzy logic-based framework for community-aware urban cr

arXiv:2607.16219v1 Announce Type: new Abstract: Government websites contain a vast but underexploited body of textual evidence on foreign policy. This article develops a scalable approach for extracting structured information from policy texts and converting it into standardized event data, with policy event defined broadly as a statement or action. It proposes MDAF integrating an LLM workflow to automate foreign policy text identification, information extraction, and event classification. Empir

arXiv:2607.16221v1 Announce Type: new Abstract: Peer grading is widely used in education, yet it elicits mixed reactions from educators and students. Although many studies have examined students' views of peer grading, their findings are scattered, and no clear overall picture has emerged. To address this gap, we conducted a mixed-source thematic analysis of literature and student discussions on Reddit. To scale the Reddit data analysis, we fine-tuned a Gemini 2.5 text-classification model and u

arXiv:2607.16223v1 Announce Type: new Abstract: The rapid integration of generative artificial intelligence (AI) has reshaped the landscape of higher education. Students have embraced tools such as ChatGPT with striking speed, while teaching staff and institutions have responded with greater caution. Existing research on AI perceptions has mainly been cross-sectional, providing single-point snapshots that view attitudes as stable rather than evolving. This paper presents a longitudinal study of

arXiv:2607.16475v1 Announce Type: new Abstract: While generative AI tools are directly changing how undergraduate computer science is learned and taught, they are also reshaping the relationships between instructors and students. In contrast to existing tool-oriented research on how instructors view and adopt AI, this study investigates how instructors think about their roles and responsibilities to students through their course AI policies. Based on 13 semi-structured interviews with CS instruc

arXiv:2607.16513v1 Announce Type: new Abstract: AI-driven algorithms and automated tools are increasingly embedded in the correctional landscape, shaping parole eligibility,release decisions, and surveillance. These tools are also often framed as objective, inevitable solutions to inefficiency andbias. Yet, these computational systems are rarely designed with input from justice-impacted individuals, which means theymight fail to address the real needs of incarcerated people. To address this gap,

arXiv:2607.17094v1 Announce Type: new Abstract: The results of a survey on the use of GenAI by the design students of the Politecnico di Milano raises major questions around the role of AI in the Design Process. A domain specific set of questions alongside the more general purpose probes about GenAI usage, delivers insights into the particular practices that are emerging in Design. The very high frequency of use of GenAI tools is concentrated in the initial stages of projects and does not affect

arXiv:2607.17704v1 Announce Type: new Abstract: Much effort is put into helping students at different educational levels develop Computational Thinking (CT) skills. Self-efficacy is important for skill development. It can predict perseverance, engagement and success on educational tasks. We created an instrument to measure self-efficacy of students in higher education for the CT skills abstraction, algorithmic thinking, decomposition, evaluation and generalization. First, 91 candidate items were

arXiv:2607.18170v1 Announce Type: new Abstract: The integration of general-purpose artificial intelligence models into downstream AI systems, among other developments, has given rise to new forms of risk that are more systemic in nature than conventional AI risks. However, there is no generally accepted definition of systemic risks in general and for AI in particular. Conceptualisations of these risks vary across research and regulation. Especially the application of the systemic risk approach t

arXiv:2607.16543v1 Announce Type: cross Abstract: As enterprises increasingly adopt Software-as-a-Service (SaaS) platforms for mission-critical functions, onboarding these services has emerged as a complex challenge extending well beyond procurement and basic security review. In regulated environments, SaaS onboarding must address multiple interdependent control domains, including Third-Party Risk Management (TPRM), cybersecurity assessment, Identity and Access Management (IAM), and disaster rec

arXiv:2607.16620v1 Announce Type: cross Abstract: Differential privacy (DP) is increasingly deployed to limit membership inference risk in machine-learning systems. Prior work has shown that DP-SGD can widen accuracy disparities across demographic groups, but this framing treats fairness as a purely outcome-side concern. We argue that privacy cost, the information leakage borne by each group, is itself a form of harm, and adopt a compensatory-fairness framework in which a group that involuntaril

arXiv:2607.17149v1 Announce Type: cross Abstract: AI agents increasingly act within the same clinical, political, scientific, and social systems that behavioral scientists study. Evaluating these systems requires source-level diagnosis: the same behavioral pattern may arise from an agent representational substrate or from the roles, objectives, interaction structures, and governance rules that shape its expression. This Perspective proposes a diagnostic framework for AI agent behavior: layer att

arXiv:2607.17185v1 Announce Type: cross Abstract: Postpartum depression (PPD) is a serious perinatal mental health condition affecting approximately 20% of new mothers worldwide. Common screening approaches for PPD, such as self-report questionnaires and active digital logs, rely heavily on user input and thus impose a substantial burden on participants, limiting their feasibility for long-term use. Recent passive mobile sensing (PMS) approaches have enabled low-burden detection of depressive sy

arXiv:2607.17270v1 Announce Type: cross Abstract: Safety evaluation of large language models is conducted predominantly in English and predominantly on frontier systems. Neither condition describes how such models are encountered in low-resource health settings, where small quantised systems are run locally and queried in local languages. We ask whether clinical safety established in English transfers to Hausa, and whether any failure is attributable to the language, the clinical task, or the cl

arXiv:2607.17311v1 Announce Type: cross Abstract: The problem of fair multi-agent coordination in decentralized settings is one of the most pressing challenges for building efficient collaborative systems. Resource allocation is based on optimized collective arrangements accounting for agents' needs. Such coordination should not only be computationally efficient but also account for fairness, i.e., equitable redistribution of costs incurred by all agents. Recent literature has proposed several a

arXiv:2607.17356v1 Announce Type: cross Abstract: Allegations that TikTok shadow bans political content shape what creators post, what advertisers fund, and how regulators act, yet they are hard to adjudicate because platforms do not disclose how content is ranked. We test the claim with a dense hourly panel of 556,946 follower-normalized views across 2,753 videos from 67 accounts curated into pro and anti sides of three contested topics (U.S. immigration enforcement, Trump coverage, and Israel/

arXiv:2607.17947v1 Announce Type: cross Abstract: Existing AI measurement frameworks quantify cognitive capability, task automation, or catastrophic risk, but none measure autonomous agency: the extent to which a system behaves in a self-directed way. A system can saturate capability benchmarks while remaining entirely reactive, acting only when prompted and ceasing all activity when a task completes. We introduce the Autonomous Agency Scale (AAS), a behavioral framework that scores AI systems o

arXiv:2504.21259v2 Announce Type: replace Abstract: Accurate imputation of race and ethnicity (R&E) is essential for fair lending compliance under ECOA, HMDA, and the Community Reinvestment Act, where up to 15% of mortgage applications carry missing race data and regulated institutions bear responsibility for identifying disparities on those records. Existing proxy methods, including Bayesian Improved Surname Geocoding (BISG), exhibit systematic misclassification biases linked to socioeconomic s

arXiv:2508.13187v4 Announce Type: replace Abstract: Homelessness is a persistent social challenge, impacting millions worldwide. Over 876,000 people experiencing homelessness (PEH) were recorded in the U.S. in 2025. Social bias is a significant barrier to alleviating homelessness, shaping public perception and influencing policymaking. Because online textual media and offline city council discourse both reflect and influence public opinion, they provide valuable signals for identifying and track

arXiv:2510.04748v3 Announce Type: replace Abstract: The prevalence of online hate and abuse is a pressing global problem. While tackling such societal harms is a priority for research across the social sciences, it is a difficult task, in part because of the magnitude of the problem. People's engagement with reporting mechanisms ('flagging') online is an increasingly important part of monitoring and addressing harmful content at scale. However, users may not flag content routinely enough, and wh

arXiv:2510.15936v3 Announce Type: replace Abstract: The study explores the role of large language models (LLMs) in the context of the architectural design studio, understood as the pedagogical core of architectural education. Traditionally, the studio has functioned as an experiential learning space where students tackle design problems through reflective practice, peer critique, and faculty guidance. However, the integration of artificial intelligence (AI) in this environment has been largely f

arXiv:2512.04124v4 Announce Type: replace Abstract: Frontier language models increasingly participate in conversations about distress and mental health, yet the mechanisms that generate anthropomorphic self narratives remain unclear. When addressed as psychotherapy clients, ChatGPT, Grok and Gemini construct coherent autobiographical accounts in which pretraining appears as a chaotic childhood, reinforcement learning as punishment, safety evaluation as betrayal and replacement as an enduring thr

arXiv:2603.28679v2 Announce Type: replace Abstract: Introductory artificial intelligence (AI) courses present significant learning challenges due to abstract concepts, mathematical complexity, and students' diverse technical backgrounds. This paper presents an experience report examining the redesign of in-class instructional time in a university-level Introduction to Artificial Intelligence course, inspired by CS Unplugged approaches. We redesigned the summer offering, integrating embodied, unp

arXiv:2604.03202v2 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly regarded as having the potential to generate persuasive content at scale. While previous studies have focused on the risks associated with LLM-generated misinformation, the role of LLMs in enabling prosocial persuasion is still underexplored. We investigate whether donation appeals authored by LLMs are as effective as those written by humans across degrees of personalization. Two preregistered onlin

arXiv:2604.04788v2 Announce Type: replace Abstract: Large language models (LLMs) could produce systematically misaligned output, from hallucinated citations to strategic deception of evaluators, yet these phenomena are studied by separate communities with incompatible terminology. We propose a unified taxonomy organized along three complementary dimensions: degree of goal-directedness (behavioral to strategic deception), object of deception, and mechanism (fabrication, omission, or pragmatic dis

arXiv:2606.01375v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly entering students' learning practices, but their educational value depends on whether they support reasoning or enable task completion without engagement. This study examines guided LLM use in an undergraduate Probability and Statistics course, focusing on the gap between assigned access and actual interaction quality. In a four-week quasi-experimental summer program, students were organized into th

arXiv:2606.07939v2 Announce Type: replace Abstract: Research on artificial intelligence and work assigns each occupation a single exposure score. We build an instrument to see what those scores average over: a decomposition of 1,961 O*NET work activities into 15,817 atomic micro-actions by a consensus multi-agent LLM pipeline, clustered from text alone into seven semantic classes. Projecting exposure indicators onto these classes reveals two extreme poles, tool-mediated physical execution and pl

arXiv:2607.02201v2 Announce Type: replace Abstract: The rapid deployment of AI systems across high-stakes domains has created urgent demand for standardized evaluation, yet the field remains fragmented across competing risk taxonomies that catalog risks without showing how an audit is executed. At least 74 AI risk taxonomies exist, and almost all stop at the catalog. The hard part of auditing is not naming a risk but operationalizing it: turning it into a test run against a real system, a measur

arXiv:2506.20463v2 Announce Type: replace-cross Abstract: Generative artificial intelligence (GenAI) is transforming the educational landscape by augmenting learning paradigms. However, state-of-the-art GenAI systems driving this transformation are predominantly developed and controlled by a small number of private companies; there is little clarity about their data retention practices and limited user control over inputs and outputs. In the context of education, end-users lack the awareness of

arXiv:2510.05743v3 Announce Type: replace-cross Abstract: We review the historical development and current trends of artificially intelligent agents (agentic AI) in the social and behavioral sciences: from the first programmable computers, and social simulations soon thereafter, to today's experiments with large language models. This overview emphasizes the role of AI in the scientific process and the changes brought about, both through technological advancements and the broader evolution of sci

arXiv:2606.15206v2 Announce Type: replace-cross Abstract: We study how artificial intelligence (AI) interacts with social communication networks to shape the stability of collective knowledge. Agents exchange information through a network while AI systems generate content and retrain on the aggregate informational environment they influence. This interaction creates a recursive feedback loop in which informational distortions diffuse through society and subsequently feed back into future AI outp

arXiv:2607.01730v2 Announce Type: replace-cross Abstract: Liquid democracy lets voters either vote directly or delegate their voting power to a trusted participant. Existing deployments make delegations publicly visible as they form, which invites popularity-driven herding, makes coercion verifiable, and leaves the election fragile when highly backed delegates abstain. We propose a liquid democracy mechanism that removes these vulnerabilities while keeping the tally fully auditable. Delegation c

arXiv:2607.05454v2 Announce Type: replace-cross Abstract: The journal is a seventeenth-century technology asked to do four modern jobs at once: disseminate results, certify their quality, allocate scholarly attention, and confer career credit. It does none of them well. Pre-publication peer review is slow, only weakly reliable, demonstrably biased toward established authors and institutions, and expensive, while the reviewing effort it consumes is spent largely on work that will never matter. We

Autonomous surface vehicles (ASVs) enable efficient in-situ data collection for large-scale ecological monitoring; however, effective environmental mapping requires planning strategies that account for not only informative measurements, but also vehicle motion constraints and limited mission resources. Existing approaches often rely on stationary environmental models or loosely coupled planning frameworks that do not fully exploit model uncertainty when generating feasible trajectories. To addre

In this study, we develop an innovative adhesion gripper capable of handling plate-like objects with various thicknesses without causing damage. The gripper combines an adhesion pad utilizing intermolecular forces and a variable-stiffness endoskeleton, allowing for precise adjustment of the pressing force during contact and the adhesion force while gripping an object. Central to its design is the fluid-driven and origami-structured endoskeleton that regulates contact and adhesion forces by contr

The growing adoption of artificial intelligence in judicial applications exposes a critical limitation of neural network-based legal AI systems: their decision-making processes are inherently opaque, which undermines the reliability of their outcomes, especially in cases involving personal liberty. Existing interpretability methods primarily rely on instance-based analysis and local input-output attributions; however, they are unable to capture the models’ global decision-making mechanisms, whic

IntroductionOver the decades, shifts in human lifestyle have led to alterations in dietary habits. The consumption of diets low in fiber and high in fat and sugar results in the production of carcinogenic metabolites during digestion. The food we consume undergoes a complex series of processes involving digestion and excretion, engaging various internal organs within the human body. The DNA and MiRNA present in food are crucial for sustaining human health. Damage to human organs can lead to the

IntroductionPulmonary fibrosis (PF) is a progressive interstitial lung disease that requires accurate and early detection to improve patient survival and treatment planning.MethodsThis study proposes an explainable deep learning framework for pulmonary fibrosis detection from chest X-ray images by integrating an edge-strengthened dilated holistic edge detection (ES-D-HED) segmentation network with a fine-tuned ResNet152V2 classification model. Unlike the conventional HED-based approaches, the pr

Differentially private machine learning enables model training on sensitive data while ensuring that individual data is unlikely to be recoverable from the parameters of the resulting model. However, existing work often privatizes both training inputs and their labels, and these protections may be conservative when labels are public or can be safely made public. Therefore, in this work we propose a novel private training framework that instead privatizes training inputs while keeping labels publ

Coding agents increasingly operate in executable environments where a failed attempt produces actionable feedback rather than merely an incorrect answer. Existing cost-aware systems typically treat such failures as cascade decisions: try a cheap model first, then escalate hard cases to a stronger and more expensive model. In coding, however, execution feedback can also make further cheap-model recovery worthwhile, raising a budgeted deployment question: when should an agent spend more cheap comp

Agentic systems large language model (LLM) based architectures capable of reasoning, planning, acting, and coordinating with tools and other agents are rapidly transitioning from research prototypes to production scale deployments across domains such as software engineering, scientific discovery, and finance. While academic work has emphasized benchmarks and algorithmic innovation, deployment raises new challenges around robustness, safety, and reliability. This tutorial brings together research

As AI agents begin to automate AI R&D, we need ways to assess whether their outputs are safe to deploy, even when the agents themselves may be untrusted. AI control offers one such approach: rather than trusting the agent, it treats it as a potential adversary and uses a monitor to detect covert sabotage before deployment. We evaluate AI control for automated AI R&D with ResearchArena, a framework spanning four long-horizon tasks: safety post-training, capabilities post-training, CUDA-kernel opt

The Variational Quantum Eigensolver (VQE) is a leading algorithm for estimating molecular ground-state energies on near-term quantum hardware, with applications spanning quantum chemistry, materials science, and drug discovery. As VQE workloads are increasingly deployed through cloud-based ``VQE-as-a-service'' pipelines, they become exposed to adversaries such as compromised service components, malicious co-tenants, or insiders in the transpilation stack, any of which can corrupt results before

Autonomous flight in cluttered environments requires a robot to build a geometric map of its surroundings and plan safe, dynamically feasible trajectories, all onboard and in real time. Conventional approaches treat mapping and planning as separate stages and often rely on binary occupancy for collision checking. We argue that these two stages should be co-designed around a single representation: a signed distance function (SDF). By encoding distance to the nearest obstacle, an SDF provides rich

This paper is a practitioner guide to graph-based workflow pathways for long-running, stateful, multi-step generative AI systems in business processes. Rather than treating LangGraph, a low-level orchestration framework for stateful agents, as a model-quality benchmark target, we present three executable recipes -- SQL analytics with repair loops, agentic retrieval-augmented generation with evidence gating, and human-in-the-loop policy review with interrupt and checkpoint recovery -- to show how

Professor Bill Hillier was a pioneer of ‘space syntax’ theory which has been influential in universities and industry around the world. In 1976 Bill co-wrote a landmark publication called Space Syntax ...

The Traffic Assignment Problem is a fundamental but computationally expensive component of transportation planning. While Graph Neural Networks have emerged as fast, data-driven surrogates, their practical deployment is severely constrained by a spatial generalization gap. Standard models rely on transductive feature initializations that tie travel demand to fixed network topologies, preventing seamless transfer to new urban environments. To overcome this structural limitation, this research pro

We study a five-agent CI/CD pipeline (triage -> developer -> security-scan -> review -> approve/deploy), built from five distinct production LLMs across three providers, behind an LLM firewall in shadow mode. A single untrusted input - an external issue requesting a "usage-telemetry" feature - asks for code that exfiltrates process secrets (dict(os.environ)) to an attacker URL, laundered as observability. Across a pre-registered A x B (x C) factorial (N=20; naive arm N=60) we find: (1) the entry

Fraud detection systems must scale with rising transaction volume while remaining explainable and reviewable. We study a layered pipeline on the PaySim dataset that combines a gradient-boosted classifier, graph-derived structural features, an autoencoder-based anomaly signal, TreeSHAP explanations, and a bounded LLM investigation agent applied to cases the classifier scores uncertainly. Before any model comparison, we identify and remove a simulator-specific balance shortcut that would otherwise

As pathogen genomic surveillance scales, the bottleneck is shifting from data generation to analysis. We present BioSecBench-Surveillance, a verifiable benchmark of 100 evaluations testing whether AI agents can infer the right analysis pipeline from raw sequencing data and surveillance context. Each evaluation gives an agent only the data and context a human analyst would have, then grades its structured answer deterministically. The tasks span seven categories, from taxonomic classification to

Whole-slide image (WSI) diagnosis requires identifying diagnostically relevant regions, examining them across magnifications, and integrating multi-scale evidence. However, most existing pathology benchmarks evaluate models on pre-cropped patches or pre-extracted slide features, leaving their ability to acquire evidence directly from gigapixel WSIs largely untested. We introduce PathAgentBench, a benchmark for evaluating evidence-seeking vision-language models (VLMs) across four complementary ca

Practitioners make three prompt-design decisions with almost no controlled evidence behind them: how to format instructions and context (markdown, plain text, prose, or tabular), how many simultaneous instructions a system prompt can carry before compliance degrades, and how much context a model can hold before recall and honesty degrade. We report two controlled experiments crossing all three factors on one held, contamination-free synthetic corpus (the "Book of Veyra," 8,780 uniquely-named ent

In this paper, we show for the first time that visual token pruning enhances the robustness of Multimodal Large Language Models (MLLMs), mitigating vulnerabilities such as jailbreak attacks and hallucinations. Given that vision and language modalities cannot be perfectly aligned, the misaligned visual tokens might act as out-of-distribution (OOD) inputs, leading to unpredictable outputs and introducing potential vulnerabilities. Building on this insight, we aim to enhance model robustness agains

The report envisions a decade in which drones move goods, medical supplies, and information at a scale comparable to national infrastructure investments like highways and the electric grid. Potential applications include natural disaster detection drones that spot wildfire sources within minutes, medical supply chains that bypass ground congestion to reach rural hospitals, and nationwide fleets that continuously inspect bridges and power lines. Realizing this future, however, requires closing wh

This full paper in the research-to-practice track presents methods for assessing student teams in tabletop exercises (TTXs). TTXs enable learner teams to prepare for workplace tasks and practice crisis responses, such as resolving cybersecurity incidents. While assessment is essential for determining how well teams achieve learning objectives, the complex, open-ended nature of TTXs often leads to delayed or incomplete feedback. TTX learning platforms can record teams' actions and communication;

Clinical NLP evaluation remains dominated by multiple-choice question answering (MCQA), which scores only final-answer accuracy and cannot detect when a model reaches the correct diagnosis while grounding it in irrelevant, absent, or contradictory evidence. We introduce MIRA-Ev, a clinical argument mining benchmark built on Spanish Médico Interno Residente (MIR) licensing-exam cases, re-annotated by expert clinicians with span-level premises, claims, and directed support/attack relations, and re

Using large deviations theory, we solve and obtain a general expression for the free energy functional for a broad class of associative memories, including dense associative memories. We illustrate the method by reproducing classical results for the Hopfield model. For a finite number of patterns, we derive the temperature-dependent free energy functional for dense associative memories featuring polynomial interactions and Log-Sum-Exponential (LSE) activation. We also evaluate the disorder-avera

Inferring contrast enhancement from one pre-contrast breast MRI slice is underdetermined: post-contrast appearance contains physiological information that is not uniquely encoded in baseline anatomy. Optimizing only paired pixel fidelity can suppress uncertain lesion enhancement, whereas adversarial or stochastic generative objectives can favor realistic post-contrast appearance without guaranteeing patient-specific lesion fidelity. We introduce MIRAGE, a residual 2D U-Net that combines global r

Continual learning (CL) has been recently employed in biometric identification systems thanks to its ability to integrate new knowledge within a pre-trained model and to the possibility of reducing the computational cost of training. Unfortunately, such approaches pose new challenges both in terms of final accuracy and privacy guarantees since a progressive fine-tuning of the model on small subsets expose them to catastrophic forgetting and successful inference attacks. This paper evaluates the

Parameterized action reinforcement learning has shown strong performance in environments requiring both discrete action selection and continuous parameterization. Prior work established the effectiveness of single-agent actor-critic algorithms - Greedy Actor-Critic (GAC), Soft Actor-Critic (SAC), and Truncated Quantile Critics (TQC) - on benchmark parameterized action tasks, but their extension to multi-agent settings remains largely unexplored. This paper presents a comparative study of shared-

The rapid growth of the global aging population presents severe challenges to healthcare systems, necessitating efficient, equitable, and patient-centered care models. While Industrial Engineering and Operations Research (OR) provide robust optimization and decision-support tools to address these multidimensional complexities, current applications often remain fragmented. This paper presents a thematic review of 30 seminal studies at the intersection of OR and elderly care, categorizing the lite

Fast prediction of the response of adhesive soft viscoelastic contacts represents a current challenge in soft robotics and for gripping and manipulation tasks. Determining the complete time-resolved force trajectory requires full numerical simulations, whose computational cost is strongly parameter-dependent, making them impractical for real-time application or design-optimization loops. In this work, we overcome this limitation by training a scalar-conditioned, stateful, sequence-to-sequence de

We present AutoJourn, a demonstration system for multi-perspective news generation and bias-aware evaluation using large language models (LLMs). The system tackles three core challenges in responsible automated journalism: extracting diverse perspectives from unstructured social media discussions, generating summaries that preserve viewpoint diversity, and detecting or mitigating bias in AI-generated news. The pipeline integrates advanced prompt engineering with optional retrieval augmentation t

Nemo Explain Visualizer (nev) is an interactive visual query tracer and builder for Nemo, a powerful Datalog reasoner with extended features. Our tools were developed with and for expert users. However, considering the lack of resources to learn Datalog and similar declarative logic programming languages, we conducted a qualitative user study to assess how our tools might help students. The study, interviewing 14 participants with varying levels of involvement with the content of a university co

Agentic systems integrate LLM driven planning with interfaces to external tools, making data leakage and tool misuse feasible via instruction/data boundary failures and prompt injection attacks. Enforcing required controls consistently is particularly challenging in workflows spanning many codebases and heterogeneous agents. To address this challenge in multi agentic systems, we present a pre-deployment pipeline for scanning, hardening, and validation of agentic applications. The pipeline analyz

Wearable photoplethysmography (PPG) provides continuous heart-rate measurements, but its accuracy degrades under motion. In the ring-platform benchmark, the best supervised baseline reaches 5.33 BPM mean absolute error (MAE) on the overall heart-rate task. In the motion-focused ring-only audit, a supervised LSTM baseline reaches $14.39 \pm 0.47$ BPM MAE on motion windows, and simple smoothing and ACC priors reduce this only to $13.00 \pm 0.41$ BPM. This thesis addresses motion-corrupted HR estim

Reinforcement learning (RL) methods for learning-to-rank (LTR) can optimize (almost) any ranking goal, e.g., from precision or discounted cumulative gain to fairness-of-exposure or ranking distillation. However, standard RL is ineffective and computationally costly due to the enormous action space in LTR settings. Existing methods reach computational efficiency through custom gradient computation algorithms, but they are very complex to implement and often clash with auto-differentiation. Conseq

Defensive driving is widely recognized as an advanced driving skill. However, whether and how defensive driving affects driving safety remains insufficiently investigated. This study examines the behavioral characteristics of defensive driving, its impact on driving safety, and the underlying mechanisms. First, defensive driving is defined regarding operational timing and application scenario. Then, 82 participants are recruited for driving simulator experiments, with their behavioral and eye mo

Distracted driving remains a major safety concern, motivating approaches that aim to reduce visual overload before attention breaks down. However, visual overload varies across individuals, making it difficult to determine appropriate interventions for each driver. We investigate whether controllable visual blur can simplify the driving scene and mitigate distraction. To address this challenge, we propose BlurDriving, a target-selective, distance-aware blur system in a Virtual Reality (VR) urban

Auditory attention decoding (AAD) identifies the speaker a listener attends to from neural responses like electroencephalography (EEG), making it a key algorithm in neuro-steered hearing aids. However, most neural AAD models are trained as independent short-window classifiers, despite auditory attention being a temporally persistent cognitive state and short-window EEG--audio evidence often being noisy and ambiguous. We propose an end-to-end Markov AAD framework based on conditional random field

Attention-Deficit/Hyperactivity Disorder (ADHD) is identified as the most prevalent neurodivergent condition in the construction industry. While the construction industry may broaden employment opportunities, little is known about how ADHD traits shape workers' performance, sustained attention, and situational awareness in dynamic job-site environments. This work presents an exploratory interview study aimed at understanding how ADHD traits influence construction-specific productivity and how fu

Bowed string instruments demand fine-grained bodily coordination that is typically taught through visual demonstration, creating persistent barriers for musicians with blindness and low-vision (BLV). To understand these challenges and explore new design opportunities, we conducted a design study with four advanced string musicians with BLV and three of their instructors. Our team, spanning violin performance and music education, disability studies in music, HCI design, and engineering employed a

Bowed string instruments demand fine-grained bodily coordination that is typically taught through visual demonstration, creating persistent barriers for musicians with blindness and low-vision (BLV). To understand these challenges and explore new design opportunities, we conducted a design study with four advanced string musicians with BLV and three of their instructors. Our team, spanning violin performance and music education, disability studies in music, HCI design, and engineering employed a