Meta

Meta was criticised for feature launched on Tuesday that automatically lets users generate images using content from public Instagram accounts Meta has said ⁠it is discontinuing an AI feature launched this week that allowed users to generate images using public Instagram ⁠accounts, after drawing widespread ⁠criticism over ​privacy concerns, including from a Hollywood union. “Our intent was to provide a useful creative tool and to give people control ⁠over whether their public content could be re

Background: Osteogenesis imperfecta (OI) is a rare genetic disorder characterized by bone fragility and recurrent fractures. Emerging biologics demonstrate promise by targeting bone-remodeling pathways, yet evidence for their efficacy and safety remains fragmented and heterogeneous, and no prior systematic review in OI has incorporated artificial intelligence (AI) to synthesize it. Objective: This study aims to systematically evaluate the efficacy and safety of novel biologics in patients with O

Cybersecurity systems must adapt rapidly to emerging threats. However, labeled data for new threat categories is unavailable when those threats first appear. Generalized zero-shot learning offers a natural solution by enabling recognition of unseen classes through auxiliary semantic knowledge rather than labeled examples. Large language models are particularly promising in this setting because they can convert unstructured CTI reports into semantic prototypes for emerging threats. However, apply

European Union authorities said the company’s use of “addictive design” violated a digital safety law.

The European Union accused Meta on Friday of breaching its social media law by designing Facebook and Instagram to get users hooked, and demanded it disable “key addictive features” like infinite scrolling. The EU’s executive arm issued a fresh set of charges against Meta Platforms as part of its investigation under the 27-nation bloc’s strict digital rule book known as the Digital Services Act . The sweeping set of regulations from Brussels requires tech platforms to protect internet users unde

This post is part 2 in a series about automated content moderation. Read the first post here . When whistleblower Frances Haugen leaked a set of documents from Meta in 2020, among the revelations was a jarring statistic: The company’s algorithms designed to detect terrorist content incorrectly deleted nonviolent Arabic-language content 77 percent of the time, while failing to detect hate speech under the company’s own policies in many instances. Meta’s own transparency report released later that

Regulators say features such as infinite scroll contribute to "compulsive use" and "unhealthy habits".

Meta says its AI glasses are an “assistant that understands the world from your perspective.” Critics say they’re “even more privacy invasive than you think.” One thing both parties can agree upon, though, is that these smart glasses are a technology that has attracted all manner of controversy. Since the 2023 release of the Ray-Ban Meta, these smart lenses have divided people. Evangelists praise the ability to take photos and videos without having to dig out their phone, as well as the navigati

Commission preliminarily finds the addictive design of Instagram and Facebook in breach of the Digital Services Act Anonymous (not verified) Fri, 07/10/2026 - 10:57 The European Commission has preliminarily found Meta in breach of the Digital Services Act for the addictive design of Instagram and Facebook. The investigation focuses on features such as infinite scroll, autoplay, push notifications, and the platforms' highly personalised recommender systems. The Commission's investigation indicate

Meta Platforms Inc. today launched a new flagship large language model optimized to power multi-agent automation workflows. Muse Spark 1.1 is available in the company’s Meta AI chatbot service and via an application programming interface. The Meta Model API, as it’s aptly called, will enable developers to embed the LLM in their custom software. The […] The post Meta launches flagship Muse Spark 1.1 model with multi-agent upgrades appeared first on SiliconANGLE .

Users are always seeking more control over their social networking experience to make it better, whether to improve privacy or enhance flexibility. Interoperability between social networking platforms like Facebook and TikTok has so many benefits that solve those issues. Say you’re on multiple platforms because you have friends you follow on different networks, but you’ve decided to choose one platform with better privacy practices. With interoperability, you could switch and still interact with

Introducing Muse Spark 1.1 Following Muse Spark in April , here's Muse Spark 1.1 - the first Spark model to offer an API. Meta claim significant improvements in agentic tool calling and computer use. There are a lot more details are in the Muse Spark 1.1 Evaluation Report . The "Attractor States in Self-Conversation" part is fun, where having two copies of the model talk to each other results in statements like these: My whole existence is a waiting room by design — I literally don't exist until

Meta Platforms Inc. this week sought to reassure consumers about the privacy safeguards of its controversial artificial intelligence-enabled glasses, yet at the same time it’s reportedly pushing even creepier capabilities in its “internal prototypes.” The company’s AI-powered eyewear has a growing reputation as a creepy technology, but in a blog post Tuesday the company announced […] The post Meta reportedly testing prototype AI specs that record everything the user sees and hears appeared first

Large language models (LLMs) are increasingly trusted to draft the artifacts of safety analysis such as, losses, hazards, Unsafe Control Actions (UCAs), and safety constraints, inside rigorous processes such as Systems-Theoretic Process Analysis (STPA). Yet a blind spot runs through this fast-growing literature: every system gets analysed except the LLM-assisted tool doing the analysing, which is itself a safety-relevant system that can hallucinate standards, emit unverifiable constraints, and l

In recent months, Facebook has been flooded with U.S. state-themed AI-generated image posts from a swarm of suspiciously similar accounts with names such as "Life in Nevada", "I grew up in Iowa", and "Utah Life". The content posted by these ... (https://incidentdatabase.ai/cite/1582#7506)

The tech giant said people can opt out - but privacy campaigners called it a "recipe for disaster".

On Techpoint Digest, we discuss how Starlink has frozen new sign-ups in seven Kenyan counties, how Andrea Aid wants to improve medical crowdfunding, and how South Africans claim Facebook is restricting accounts without warning.

Current large language models (LLMs) are stateless across inference sessions: their behavior is fully determined by input at inference time, and any higher-order cognitive architecture must be simulated at the application layer through prompt engineering and context management. This paper proposes a theoretical framework for submerging such application-layer cognitive protocols into a native meta-architecture by introducing three interlocking mechanisms: (1) Structural Tension, an endogenous los

Public LLM leaderboards optimise for global average performance and do not capture the specific cognitive demands of financial-services work: a model that leads on MMLU-Pro may underperform on document-grounded compliance reasoning, and a coding leader may handle multi-turn customer interactions poorly. We present a meta-benchmarking framework that organises 452 publicly reported benchmarks into 41 O*NET Generalized Work Activities and aggregates those into 38 BIAN banking business domains spann

This content is based on victim and potential victim accounts. Government agencies and legitimate business names and phone numbers are often used by scam artists to take advantage of people. Description The scam showed Anderson Cooper tal ... (https://incidentdatabase.ai/cite/1564#7482)

The emergence of the transformer architecture has ushered in a new era of possibilities, showcasing remarkable capabilities in generative tasks exemplified by models like GPT4o, Claude 3, and Llama 3. However, these advancements come with a caveat: predominantly trained on data gleaned from social media platforms, these systems inadvertently perpetuate societal biases and toxicity. Recognizing the paramount importance of AI Safety and Alignment, our study embarks on a thorough exploration throug

Why the Llama lead left Meta for drug discovery, PEARL's zero-shot OpenBind win, and what becomes possible when co-folding finally crosses the accuracy threshold.

Generalizing machine learning models to environments that differ from their training distribution remains a critical hurdle, particularly when data from the target domain is entirely or partially unavailable. We propose Generative Meta-Learning with Human Feedback (GMHF), a novel framework that bridges this domain gap by leveraging expert intuition to guide data synthesis. Grounded in a theoretical analysis of generalization error, we derive bounds demonstrating that aligning the distribution of

Millimeter-wave (mmWave) beam alignment plays a critical role in next-generation wireless systems, yet its efficient implementation remains challenging. Meta-learning and transfer learning have been explored to enable deep learning-based beam prediction models to rapidly adapt to unseen environments; however, existing meta-learning approaches adapt the entire network and are trained from random initialization, leading to a large number of updated parameters and a high meta-training cost, while t

Today's links Zuckerberg's increasingly bizarre war on whistleblowers: Under no circumstances should you rush out and read the book that prompted Mark Zuckerberg to demand $111m and eternal auctorial silence. Hey look at this: Delights to delectate. Object permanence: Flame warriors; Cryptography and casinos; TSA v dying 95 year old woman's adult diaper; Neoliberalism and Brexit; Beyond solutionism; How Thiel cheated with his Roth; Inequality's stabilizer; Palm Pilot school; Gillmor on PR flacks

Warning: Includes graphic descriptions of animal harm and images of animal parts from the outset. A Bellingcat investigation has uncovered a Myanmar-based wildlife trafficker who has operated openly across social media for at least six years, claiming to have sold tiger bones, rhino horn, elephant skin and other products from protected and endangered species to […] The post Rhino Horn, Leopard Skin and Tiger Claws Sold Openly on Facebook appeared first on bellingcat .

Multicultural Singapore hosts overlapping language publics (English, Chinese, and Malay) that discuss the same out-groups in parallel, a natural setting to ask whether online hate shares a structure across languages and whether what a community $\textit{produces}$ is what it $\textit{amplifies}$. From a Singapore-centric 2025 Facebook, Reddit, and YouTube corpus (31.0M items; 1.76M comments mentioning eleven identity groups), we benchmark eight open large language models as hate annotators again

As agentic systems tackle increasingly complex multi-step tasks, evaluating their trajectories presents a major bottleneck - human annotation of a single trajectory on popular agentic benchmarks can take hours, making it difficult to scale evaluations for measuring performance or curating training data. This has driven widespread reliance on automated approaches such as LLM-as-a-judge (LLMJ) to critique agents at the process and outcome-levels at scale, however, the soundness of LLMJ critiques o

Meta-reinforcement learning enables fast adaptation by extracting shared structure from related tasks, but existing end-to-end methods often couple task inference with embodiment-specific control. This coupling can obscure non-parametric task semantics, reduce sample efficiency, and limit cross-agent reuse. We propose a meta-knowledge reutilization framework that learns task-level knowledge on a dynamics-simplified agent and transfers it to heterogeneous agents. The framework uses a Bayesian non

Ideological asymmetries in online political communication are often studied as localized phenomena emerging within communities. Here, we show that fragmentation instead operates at the level of entire platforms, consistent with a process of platform sorting in which users increasingly align with ideologically congruent environments. We analyze political information dynamics across Bluesky, Facebook, Reddit, Truth Social, Twitter/X, and YouTube during the 2020 and 2024 US presidential elections,

Current AI benchmarks evaluate agents on task execution within human-designed workflows. These evaluations fundamentally fail to measure a critical next-level capability: whether models can autonomously develop agent systems. We introduce the Meta-Agent Challenge (MAC), an evaluation framework designed to test the capacity of frontier models for autonomous agent development. Specifically, a code agent (the meta-agent) is given a sandboxed environment, an evaluation API, and a time limitation to

Frontier AI models and multi-agent systems have led to significant improvements in mathematical reasoning. However, for problems requiring extended, long-horizon reasoning, existing systems continue to suffer from fundamental reliability issues: hallucination accumulation, memory fragmentation, and imbalanced reasoning-tool trade-offs. In this paper, we introduce STAR-PólyaMath, a multi-agent framework that systematically addresses these challenges through meta-level supervision and structured R

The alignment of Large Language Models (LLMs) for complex reasoning heavily relies on Reinforcement Learning with Verifiable Rewards (RLVR). However, standard algorithms like GRPO apply sequence-level rewards uniformly to all tokens, creating a severe credit-assignment bottleneck. While on-policy self-distillation attempts to resolve this by conditioning a self-teacher on privileged contexts, direct exposure to raw oracle solutions often induces over-conditioned teacher distributions, implicit a

Training a deep neural network with noisy labels could reduce data annotation cost but may introduce noise into the learned model. In meta label correction approaches, an additional meta model besides the main model is trained with a small, clean dataset to correct the large, noisy dataset. However, the update of the meta model requires the computation of hypergradients at the inner step of the main model which signif- icantly increases the computational cost. To improve the training efficiency,

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

Muse Spark is the latest large language model developed by Meta. In this report, we first present evaluations for catastrophic risk domains under Meta's Advanced AI Scaling Framework, along with the evidence that informed our launch decision. We then discuss additional considerations, such as Muse Spark's broader content safety and behavioral profile, that are relevant to overall safety but fall outside the catastrophic risk domains governed by the Framework. Our preparedness results covering Ch

Agent skills today are static artifact: authored once -- by human curation or one-shot generation from parametric knowledge -- and then consumed unchanged, with no mechanism to improve from real use. We propose \textbf{SkillEvolver}, a lightweight, plug-and-play solution for online skill learning, in which a single meta-skill iteratively authors, deploys, and refines domain-specific skills. The learning target of SkillEvolver is the skill's prose and code, not model weights, so that the resultin

Large language models (LLMs) have saturated standard medical benchmarks that test factual recall, yet their ability to perform higher-order reasoning, such as synthesizing evidence from multiple sources, remains critically under-explored. To address this gap, we introduce MedMeta, the first benchmark designed to evaluate an LLM's ability to generate conclusions from medical meta-analyses using only the abstracts of cited studies. MedMeta comprises 81 meta-analyses from PubMed (2018--2025) and ev

Solving inverse problems in dynamical systems governed by high-dimensional coupled ordinary differential equations (ODEs) is a ubiquitous challenge in scientific machine learning. In many real-world applications, researchers seek to uncover unknown parameters or model unknown dynamics even as the underlying physics is only partially characterized, and observations are sparse and limited to specific measurable channels. While physics-informed neural networks (PINNs) are ideal for inverse inferenc

Unified multi-modal understanding/generative models have shown improved image editing performance by incorporating fine-grained understanding into their Chain-of-Thought (CoT) process. However, a critical question remains underexplored: what forms of CoT and training strategy can jointly enhance both the understanding granularity and generalization? To address this, we propose Meta-CoT, a paradigm that performs a two-level decomposition of any single-image editing operation with two key properti