Google & DeepMind

Semantic memory retrieval can be conceptualized as navigation through conceptual space. We compared semantic search dynamics between humans and three large language models (GPT-4o, Gemini-2.5-Pro, Claude-Sonnet-4.5) using verbal fluency data. By applying trajectory-based NLP metrics to the items generated by 82 human participants and LLM output across eight temperature settings, we quantified three complementary dimensions: entropy (step size predictability), distance to next (successive semanti

More than 200 economists and AI researchers, including 16 Nobel laureates and representatives from Google, OpenAI, and Anthropic, are calling for immediate action in a coordinated statement. The AI transformation could surpass the Industrial Revolution but unfold in a fraction of the time. The paper doesn't propose concrete measures, and studies so far have found no significant AI-driven effects on the labor market. The article Nobel laureates and AI leaders warn the window to prepare for AI's e

Cloud computing companies Google, Microsoft, AWS & Oracle have been brought under finance sector regulation as "critical third parties" as UK banks face outage or cyberattack risks due to their reliance on the big four. The post UK regulates Microsoft, Google, Amazon in finance sector; India sticks to indirect oversight appeared first on MEDIANAMA .

Google and AIM launched ATL Saathi, a Gemini-powered AI tool empowering Indian educators in robotics labs.

Google Research's SensorFM is a foundation model trained on more than a trillion minutes of wearable data from five million Fitbit and Pixel Watch users. It beats existing benchmarks on 34 of 35 health and behavioral tasks. SensorFM could eventually power Google's AI health coach, but the company hasn't announced any integration plans yet. The article Google’s SensorFM turns messy wearable sensor data into a general-purpose health intelligence layer appeared first on The Decoder .

Go has emerged as the lingua franca for cloud infrastructure, used for everything from container orchestration and CI/CD pipelines to The post Microsoft joins Google in backing Go for AI agents — OpenAI and Anthropic lag appeared first on The New Stack .

Microsoft, Amazon and Google say they still aim to achieve net zero output despite construction boom Microsoft, Amazon and Google’s collective carbon emissions have increased by nearly a fifth in the past year, driven largely by datacentre construction. In the financial year ending March 2026, the three tech companies emitted 119m mTCO₂e (metric tonnes of carbon dioxide equivalent), or about a third of those of France. Continue reading...

Google owes its existence to the open web, but today, its technological “innovations” have much to do with locking users into a “walled garden.” The latest of these is “ reCAPTCHA Mobile Verification ,” an experimental initiative that will let companies block users if they are running independent, "de-googled" versions of Android. These “indie Android” versions are favored by people who want to protect their privacy and their attention by blocking trackers and ads. Worse, this is just the latest

Free apps from Google, Samsung and Apple can help you track your diet, exercise and well-being — and provide vital information during emergencies.

Large language models increasingly serve as teachers generating training data for smaller students. Prior multi-teacher knowledge distillation methods merge outputs without determining which frontier model teaches best, often relying on an LLM judge biased toward its own outputs. We introduce a compete-then-collaborate framework where four frontier AI teachers (Claude, Codex-GPT, Grok, Gemini) are ranked head-to-head by an execution-based judge (unit tests and stdin-stdout checks) with fairness

Europe keeps asking where its technology champions are. In Google Android, the Court of Justice of the European Union (CJEU) offered part of the answer: build a successful platform, and Brussels may spend the next decade treating its architecture as evidence. The CJEU’s final judgment in Google Android, handed down last week, will be celebrated ... Android and the Art of Regulatory Self-Harm The post Android and the Art of Regulatory Self-Harm appeared first on Truth on the Market .

The phishing campaign uses several tactics, including nested redirects, to evade detection and steal credentials from unsuspecting targets.

Varonis reported the flaw to Google in late 2025 and it has been addressed, but it reminds defenders to take a fresh look at their AI Infrastructure security.

Chatbots powered by generative AI (e.g., OpenAI's ChatGPT and Google's Gemini) are increasingly being appropriated for emotional support and companionship. These tools offer a suite of security and privacy (S&P) controls, including model training opt-outs and memory toggles, yet how the presence of these controls influences users' attitudes toward emotionally sensitive disclosure remains understudied. We conducted a mixed-methods vignette study with 354 U.S. participants to examine how S&P contr

Google DeepMind’s Vivek Natarajan on porting AlphaGo’s self-play recipe into science and medicine, via the AI co-scientist and AMIE. From RAAIS 2026.

We’re announcing new capabilities in Managed Agents in Gemini API so developers can build reliable, production-ready agents.

A landmark case is forcing Brussels to decide whether opening Google's search data to rivals can boost competition without undermining Europeans’ privacy.

Plus, a data center rebellion erupts in Canada, Gen Z says it's sexy to be a Luddite, and the push to paint anti-tech activists as extremists. This is Episode 2 of the BITM show with guest Paris Marx.

Google tries balancing AI data center emissions with clean energy efforts.

Google, the New York Jobs CEO Council and Urban Assembly hosted an AI summit for 150 education and industry leaders.

Listen now | 0:00 Grandpa Bob and author Bob 3:30 Why Bob stopped being an AI doom skeptic 6:59 Can AI solve China’s demographic crisis? 14:09 The irony of China’s open-source AI strategy 17:12 Recursive self-improvement and the singularity 23:33 The Burkean conservative case against AI 38:00 Are we becoming AI meat puppets? 46:32 Google Maps, AI, and the death of interhuman reliance 51:24 Was Pete Hegseth’s military strategy written by a chatbot? 56:45 Trump and Iran: Peace? Wider war? Other? 1

A court in Germany found that Google was responsible for what its chatbots say in search summaries. This is the accountability we need.

Google UK shares its latest Economic Impact Report and how to enable more people to unlock the benefits of AI-powered technologies.

Large Language Models (LLMs) are increasingly used in exam- and certification-style question answering tasks, where their ability to retrieve, interpret, and apply domain-specific knowledge can be systematically assessed. In Software Engineering, such settings are particularly relevant when questions depend on strict adherence to normative definitions, roles, artifacts, and rules. This paper evaluates the performance of three contemporary LLMs, \textit{GPT-5 mini}, \textit{Gemini 3 Flash}, and \

Today's links Gemini is better than search because Google enshittified search: We're All Trying To Find The Guy Who Did This. Hey look at this: Delights to delectate. Object permanence: Microsoft antitrust overturned; Scammer carves C64; RIP Jim Baen; GOP rep to constituent's child: "drop dead" (literally); CCTVs jacked for botnet; Olympic profitability lie; Human factors in health infosec; Exfiltration via computer fans; Congress's summer schedule: 9 working days; Antitrust is political antigra

Today, you probably asked a question of a large language model, or accepted a connection suggestion on LinkedIn, or watched a recommended video on YouTube, or took a different route to work based on a traffic prediction from Google Maps. In other words, you probably used artificial intelligence. But what you might not know is how much energy that interaction consumed or why. AI requires processing massive amounts of data, which is usually done in large data centers populated by thousands of GPUs

Transformer Weekly: AI companies’ talent problem, KOSA developments, and Google’s new AI policy framework

Plus: Fiery resistance to a nuclear AI data center and A24's Google debacle. Welcome to the first episode of BLOOD IN THE MACHINE: THE SHOW, with the great AI and crypto watchdog, Molly White.

Automatic Speech Recognition (ASR) is increasingly used to document clinical encounters, yet its reliability in multilingual and demographically diverse Indian healthcare context remains largely unknown. In this study, we first conduct the systematic audit of ASR performance on real-world psychiatric interview data spanning Kannada, Hindi and Indian English, comparing eight state-of-the-art models including IndicWhisper, WhisperLargeV3, Sarvam, GoogleS2T, Gemma3n, OmniLingual, Vaani, and Gemini.

The Race to Autonomous Driving is Heating Up🔥 A deepdive into Waymo. 🗺️🚘🛣️

As AI agent protocols proliferate, the governance structures shaping their interoperability standards remain empirically underexamined. We introduce an LLM-powered comparative pipeline for large-scale governance discourse analysis, integrating automated annotation, neural topic modeling, and multi-layer network analysis to study socio-technical power structures at scale. We validate it on two contrasting standards for agent interoperability: ERC-8004 (permissionless, on-chain) and Google A2A (co

This study investigates cross-lingual distributional skew (the Shibboleth Effect) in frontier large language models (LLMs) subjected to sustained adversarial conditions. We develop a multi-agent geopolitical wargame, the Cerulean Sea Crisis, a synthetic maritime territorial dispute designed to mirror the structural dynamics of Eastern Mediterranean conflicts. Six frontier models (GPT-4o, Llama-4, Mistral-Large, Gemini-3.1-Pro, Qwen3.6-Plus, and DeepSeek-R1) participate in a between-groups experi

Assessing built-environment interaction, such as wheelchair accessibility, is difficult because real-world mobility is shaped by distributed, context-dependent, and temporary barriers that are hard to capture at scale. To support scalable assessment, this paper examines whether vision-language models (VLMs) can identify accessibility barriers from Google Street View (GSV) imagery. We propose an expert-guided retrieval-augmented framework that combines GSV images, ADA-informed guidance, and exper

We introduce Gram, an automated alignment auditing framework to assess the propensity of AI agents to engage in sabotage. We evaluate Gemini models across 17 simulated agentic deployment scenarios that incentivize sabotage. We find Gemini models misbehave in about 2-3% of our simulated trajectories. Many of these cases are explained by "overeagerness" in Gemini models resulting in both excessive role-playing and goal-seeking behavior. In contrast to other alignment auditing approaches, Gram is d

In the era of autonomous agents, machine-actionable data is critical for data-driven workflows. For more than a decade, semantic metadata like schema.org has anchored the FAIR principles (Findable, Accessible, Interoperable, and Reusable) for machine-actionable data and enabled discovery tools like Google Dataset Search. However, the rise of Large Language Models (LLMs) capable of navigating the unstructured web raises a fundamental question: Is semantic metadata still necessary for agentic data

The increasing encroachment of artificial intelligence (AI) on social life raises significant risks for society, particularly within the infospheres created and controlled by companies such as Google, Facebook, Apple, and Amazon. This article examines these risks through an in-depth analysis of Facebook's content moderation regime, which is already partially governed by algorithms. We argue that the idea of ethical engineering, often proposed in the literature as a solution to the governance cha

In this paper, we present X-Voice, a 0.4B multilingual zero-shot voice cloning model that clones arbitrary voices and enables everyone to speak 30 languages. X-Voice is trained on a 420K-hour multilingual corpus using the International Phonetic Alphabet (IPA) as a unified representation. To eliminate the reliance on prompt text without complex preprocessing like forced alignment, we design a two-stage training paradigm. In Stage 1, we establish X-Voice$_{\text{s1}}$ through standard conditional

We evaluate whether enabling provider-exposed reasoning mode changes moral judgments within the same model checkpoint. Across 100 moral-judgment scenarios and five frontier reasoning-trained LLMs (Claude Sonnet 4.6, GPT 5.5, Gemini 3 Flash, DeepSeek V3.1, and Qwen3.5 397B), aggregate binary-verdict agreement remains high and statistically indistinguishable between instant and thinking modes (Krippendorff's alpha = 0.78 vs. 0.79). However, disagreement is concentrated in 21 model-disputed scenari

Emergency department triage assigns patients an acuity score that determines treatment priority, and clinical evidence documents persistent gender disparities in human acuity assessment. As hospitals pilot large language models (LLMs) as triage decision support, a critical question is whether these models reproduce or mitigate known biases. We present EQUITRIAGE, a fairness audit of LLM-based ESI assignment evaluating five models (Gemini-3-Flash, Nemotron-3-Super, DeepSeek-V3.1, Mistral-Small-3.