Updated 2026-10-29 03:40 UTC
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But the AI responses get more forthright when asked outside the US.
AI-assisted context, not publisher reporting. It may contain errors.
Following improvements made to Chrome's enhanced autofill last year that included your name, passport number, email address, and physical addresses sourced from your Google Accounts and services like…
AI-assisted context, not publisher reporting. It may contain errors.
Tech leaders are flaunting how out of touch they are when they brag about using AI to connect with their families.
Artificial intelligence has thoroughly infiltrated business and politics, but it’s also starting to divide companies and investors. That was the takeaway from leaders at The Information’s WTF Summit…
When Pony Ma called Tencent Holdings Ltd.’s AI endeavor “a leaky ship” this summer, the billionaire founder sent ripples through a company that for years dominated the industry with WeChat. The…
Dowson Tong, CEO of Tencent Cloud and Smart Industries Group in an exclusive conversation with BTV's Stephen Engle talks about the company's investment shifts from being AI consumer agents to…
OpenAI’s GPT-6 Astra, the most powerful model the company has released, has met with strong demand since its release in early September. One growing customer base: Chinese AI labs that look to…
Samsung Electronics Co. hiked its spending plans after relentless demand for AI infrastructure drove memory prices higher, though its chip division’s profit missed lofty investor expectations.
There was a lot to digest from Wednesday’s earnings reports from Microsoft and Google, long the No. 2 and 3 players in cloud computing, respectively. But let’s start with the most interesting…
Sheryl Sandberg says the 32-year-old executive reminds her of Mark Zuckerberg. Josh Payne must now take his startup public at a tumultuous moment for the AI industry.
CNBC’s Jim Cramer said SK Hynix’s blockbuster earnings showed that AI stocks can still rally.
South Korean AI chip startup FuriosaAI quadrupled its valuation to $2.9 billion in a fresh funding round, bolstering its bid to challenge the likes of Nvidia Corp.
Firms are moving some manufacturing back to offset surging memory and storage chip prices fueled by AI demand.
Alphabet’s stock fell 7% in after-hours trading Wednesday after the company missed profit projections and increased its AI spending past $50 billion in the third quarter.
The announcement came alongside parent company Alphabet's third-quarter earnings report, which saw revenue grow 25% year over year to $127.6 billion.
Anthropic’s PBC structure could put its AI mission ahead of shareholder returns
Gemini 4 Carbon is our strongest model with state-of-the-art cybersecurity and long horizon capabilities.
In general, LLM performance is incredibly multidimensional. There's no guarantee of a fixed ordering where the model that is best at math is also the model that's best at jokes. Despite that complexity, much of the variation in…
Paul Copplestone and Ant Wilson on building the backend for AI agents
Today, we are rolling out immersive explorations in the new Gemini student hub.
We are excited to announce the release of PyTorch® 2.15 (release notes)! The PyTorch 2.15 release features the following changes: Rewritten NCCL backend becomes the default, with a flight recorder... The post PyTorch 2.15 Release Blog…
XREAL AURA, the first wired XR glasses powered by Android XR, lets you work, watch, and play anywhere with Gemini by your side.
We’re announcing new connected apps partners and a new platform for developers to build and track their apps in one place.
I'm at GitHub Universe today (GitHub gave me a free ticket through their "GitHub Stars" program). EVP Jay Parikh just announced this year's Octoverse report, and highlighted these numbers in particular: This is a pretty stark…
OpenAI and ServiceNow expand their partnership to bring OpenAI models and agents into ServiceNow and ServiceNow workflows into ChatGPT and Codex.
I've written before about how November 2025 was an inflection point for coding agents - the point where Opus 4.5 and GPT-5.1 crossed a tipping point that meant their respective coding agents became reliable daily drivers for software…
A sort of review of the benchmarking industry and what's missing.
Education Innovation
The full text is finally here, so we are giving it the full RTFB of model card treatment.
How AI might enter the org chart—beneath, beside, and between us.
See how Legora uses OpenAI models, ChatGPT, and Codex to accelerate legal workflows, expand contract analysis, and free lawyers to focus on higher-value work.
Vision--Language--Action (VLA) models generate robot actions from visual observations and language instructions, but their understanding of physical dynamics remains limited. Video world models can capture scene dynamics, yet…
Diffusion video models produce striking clips, but they cannot reliably render an exact formula, a correct chart, a rule-consistent game or narration synchronized to on-screen events. A different route is emerging: multimodal agents…
Discrete visual tokens represent vision in a discrete form analogous to language, offering a native interface for multimodal modeling under a shared next-token prediction objective. However, quantization error is widely assumed to…
Video captioning aims to preserve visual information through compact descriptions, predominantly using natural language. However, precisely expressing fine-grained spatial structures and temporal dynamics in natural language often…
Multimodal perception forms the foundation of multimodal intelligence. In particular, spatial perception and multimodal long-context understanding are two pivotal tasks that underpin embodied AI and multimodal agents. However…
Novel view synthesis and 3D reconstruction have advanced rapidly with radiance fields and splatting, yet their memory and computational demands limit their use in resource-constrained settings. We introduce Hexels: novel planar…
Vision-Language-Action (VLA) models have made substantial progress in robotic manipulation, but their generalization remains constrained by the diversity and coverage of action-labeled robot demonstrations. Human videos provide much…
Test-time adaptation helps a deployed model respond to changing inputs, but the same intervention can rescue one batch and damage the next. Updating normalization statistics, for example, can improve corrupted images yet fail when a…
We introduce Heads of Security (HoS), a prompt injection defense that enforces instruction-data separation via a small set of learned per-head attention gates. HoS learns how each head should redistribute attention between trusted and…
Relations compose through the entity they share - Alice is Bob's mother and Bob is Carol's father, so Alice is Carol's grandmother - and the order matters, since a father's mother is not a mother's father; verifying a composed…
Atmospheric chemical mechanisms are commonly distributed in the language of the Kinetic PreProcessor (KPP), which generates efficient Fortran or C code but does not fit into the differentiable programming frameworks in which…
Dexterous manipulation with multi-fingered hands is the next frontier of robotics, yet learned hand skills remain limited to simple grasps or basic repeated motions, such as rotating an object. As robots attempt more demanding in-hand…
Large Language Models (LLMs) are increasingly used in multi-turn agentic workloads that require sustained interaction with complex environments. Existing reflective prompt optimizers such as GEPA learn from failed rollouts, but…
Scientific discovery often begins with an unexpected observation that prompts a new research question. In a world with altered physical laws, can large language models (LLMs) notice unexpected behavior, such as heavier objects falling…
We explore how to build performant large language model (LLM) tool-use agents that complete complex, multi-step tasks. Specifically, we study how data composition in synthetically generated tool-use environments affects the training…
Weight decay and explicit weight-norm constraints improve optimizer performance in language model pretraining, yet a unified understanding of why such control helps and how much is needed remains incomplete. We analyze norm control in…
Self-attention plays a key role in long-sequence modeling, but its quadratic time complexity fundamentally limits the scaling of Large Language Models. Recently, Multi-State Linear Attention (MSLA) mechanisms have been proposed to…
Diffusion language models offer a promising path to efficient agents through parallel token generation. However, efficient interaction requires adapting both where computation is spent and how much text is generated. We introduce a…