3,698 items tracked: 33 reported by two or more outlets, the rest by a single source. Most-corroborated first.
Large Language Models (LLMs) increasingly ship with explicit "thinking modes", yet their counterpart, "no-thinking", has received far less attention.
Most image generation models rely on uniform tokenization, allocating the exact same computational budget to equally-sized image patches.
Large foundation models have accelerated progress toward general-purpose agents that interact with humans and other agents through language and multimodal signals.
Flow matching has emerged as a scalable paradigm for training high-quality generative models, but sampling from the learned probability flow requires many network evaluations.
A latent recurrent language model applies a shared block of layers repeatedly, so one checkpoint can trade inference compute for accuracy by changing the loop count.
Speculative decoding accelerates large language model inference by using a lightweight drafter to propose multiple tokens that are subsequently verified in parallel by the target model.
Computer-use agents (CUAs) are rapidly improving, yet synthesizing diverse and reliable software environments at scale remains challenging.
Humans effortlessly react to the world; they adeptly return a tennis shot, catch a falling cup, step aside from a passing cart, or pass a box tossed during truck unloading.
A 4D audio-visual scene comprises a video, the dynamic geometry it depicts, and the sound sources that populate it, each with its own position and trajectory.
Static coding benchmarks are fixed at release.
Online reinforcement learning (RL) fine-tunes diffusion models with black-box rewards, but reverse-process methods such as Flow-GRPO are limited in efficiency by poor credit assignment, while forward-process methods such…
Reward modeling often requires jointly representing and reasoning over multiple evaluation criteria, yet verbalizing this process token by token can incur substantial inference cost.
Most robot policies keep a model in the control loop: a VLA maps observations to actions, and an Agent Harness, such as Agent-as-Policy or Harness VLA queries a VLM for decision making at run time.
Multimodal large language models (MLLMs) are rapidly evolving toward continuous audio--visual reasoning, creating an urgent need for evaluations that expose their capability limits.
Single-image, multi-image, and video deep research require different visual operations but share a workflow of visual grounding, external retrieval, and fact composition.
Large language model (LLM) coding agents have advanced test generation across diverse programming tasks.
Existing spatial reasoning benchmarks mainly test spatial perception: reading off relations already visible in the input.
Skill-augmented agents improve sample efficiency by distilling successful trajectories into reusable strategies.
Spatial coding agents significantly improve spatial reasoning in Multimodal Large Language Models (MLLMs) by using external tools to generate verified execution traces.
Large language model (LLM) routing distributes inference work across different models, advancing the cost-quality Pareto frontier of LLM serving.
Generating an egocentric video from a single exocentric recording is a challenging case of novel view synthesis, as the two cameras share little overlap and much of the target view is unobserved.
We present DreamTrue, a multi-view, cross-embodiment robot world model for action-faithful and physically plausible video prediction.
General-purpose service robots need navigation systems that can handle diverse human requests in unfamiliar environments, combining task generality with scene generality.
Large Multi-modality Models (LMMs) have made significant progress in visual understanding and generation, but still face challenges in visual editing, particularly in following complex instructions, preserving appearance…
Geometrically faithful and functional articulated 3D assets are essential for real-to-sim robot manipulation, where policies trained in simulation must transfer to physical objects.
Dense retrievers have made significant progress on text and image corpora, but whether these capabilities extend reliably to mixed corpora containing text, image, and fused text-image documents remains unclear.
The memory-bound nature of the decoding stage of large language model (LLM) inference incurs significant latency.
Interactive virtual worlds allow agents to learn through exploration and interaction.
Mecka AI series_b reported $60m
Anthropic PBC today released Claude Haiku 5.5, pricing its newest small model at roughly a quarter of what Haiku 4.5 costs to run.
Opus-built Creative Cloud alternatives are ambitious, free, and nowhere near finished.
But don't worry, it's totally safe because the agents and models will (probably) be running locally.
I’ve been putting off writing a blog post that seems very important to me, because it seems important, and so should be done on a later day when I am a better person, and able to do it justice.
Many people expect the AI paradigm to approximately AGI complete, and expect it to smoothly scale to AI that can do innovative science.
OpenAI is rolling out GPT-6 to ChatGPT, and it will come with the capability to build more visual responses.
The developer of Hermes Agent raised a $90 million Series B.
Epistemic status: a curiosity I chased for an afternoon.
Persistent agents appeal to AI companies, but demand isn't obvious
OpenAI Group PBC has published 722 math papers that it generated using an unreleased artificial intelligence model.
Cisco Systems Inc.
Back-end AI gives manufacturers opportunities to improve operations, but choosing where to apply it requires attention to business value.
Microsoft revealed the specs and price for its Surface Laptop Ultra, AI PCs that run on Nvidia chips that are designed to run AI models and agents.
The research found that important guardrails for teens using ChatGPT often failed.
Nvidia-backed open source startup makes splashy entrance.
Agentic AI governance helps midsized distributors decide which tasks software agents can handle and which require human oversight.
Women hold just a fraction of new AI jobs but are overrepresented in roles with high risk of AI disruption There’s a common fear among people who work in Silicon Valley: snag one of the fast-growing, high-paying jobs in…
OpenAI is launching a new Intelligent UI feature in ChatGPT that allows the chatbot to answer your questions with interactive visuals.