Knowledge catalogue
Uber reportedly now caps coding agents at $1,500/month per employee per tool - seems sensible to me, but it's also an interesting hint at the value Uber thinks these tools are providing https://simonw
The U.K.’s antitrust regulator has ordered Google LLC to give publishers more control over how their content appears in search results. The Competition and Markets Authority, or CMA, announced the mov
arXiv:2606.03748v1 Announce Type: cross Abstract: Real-time vision demands models that are accurate, efficient, and simple to deploy across diverse hardware. The YOLO family has become widely deployed
arXiv:2606.03135v1 Announce Type: new Abstract: Large Language Model (LLM) agents often operate under underspecified user instructions, where latent uncertainty over user intent leads to erroneous too
arXiv:2606.03868v1 Announce Type: new Abstract: Recent world action models leverage video foundation models by aligning broad visual-dynamics priors with executable robot actions. We revisit this alig
arXiv:2606.03581v1 Announce Type: new Abstract: Unstructured scenes present unique challenges for autonomous driving, as irregular obstacles and sparse scene layouts undermine the effectiveness of tra
Unsupervised Robotaxi now available in the greater Austin area. Nevermind. As of 10am today unsupervised @robotaxi is working in the whole geofence. In one currently heading to the north part of the m
Tesla's Waymo robotaxi service has expanded to cover the entire Austin metropolitan area without human safety drivers. This expansion represents a significant milestone in autonomous vehicle deploymen
arXiv:2606.03719v1 Announce Type: new Abstract: The do-calculus defines a general system of inference for interventional queries, allowing causal quantities to be transformed through successive applic
Using open models and inference clouds (which serve open models) is a leading indicator of what is to come. The advantage of open weights is that you can train, serve, and continually improve your own
arXiv:2606.03962v1 Announce Type: cross Abstract: Classical reinforcement learning (RL) typically seeks a deterministic policy that maximizes the expected sum of a scalar reward. Yet, modern applicati
Ollama v0.30.2 is a patch release from the 0.30 series, which features improved compatibility and performance using llama.cpp, augmented MLX engine support on Apple Silicon, and broader model support
Ollama v0.30.3 adds support for the Gemma 4-12B model . This is a minor patch release that builds on the v0.30 series, which provides improved compatibility and performance improvements. The release w
Ollama v0.30.4 is a patch release within the v0.30 series, which offers improved compatibility and performance using llama.cpp, augments the MLX engine on Apple Silicon with wider hardware support, an
Ollama v0.30.4 is a patch release addressing a bug in the llama-server component related to incorrect parameter wiring in the Gemma 4 model implementation. This fix ensures Gemma 4 models operate corr
This release candidate fixes a Windows-specific issue where the llama-server process wasn't being properly terminated during cleanup operations. The fix addresses GitHub issue #16458 and improves the
arXiv:2606.03321v1 Announce Type: new Abstract: Artificial-intelligence surrogates can support second-by-second thermal-hydraulic forecasting, but models selected and frozen offline may become conditi
arXiv:2606.03928v1 Announce Type: cross Abstract: Reasoning models improve accuracy through extended chains of thought, but their long outputs create a memory and compute bottleneck. KV cache eviction
Quarq's team has developed an AI agent built on LangGraph that currently leads the LongMemEval-S benchmark, demonstrating advances in long-context memory evaluation. The work represents a notable achi
arXiv:2606.03971v1 Announce Type: new Abstract: Causal video generators must predict from the past, but they need not learn only from it. In streaming autoregressive video diffusion, each emitted segm
arXiv:2606.03635v1 Announce Type: cross Abstract: Understanding short online videos involves more than identifying visible objects and actions; video makers often include an underlying message or purp
arXiv:2606.03273v1 Announce Type: cross Abstract: Visual DeepSearch requires multimodal large reasoning model (MLRM) agents to answer complex visual queries by repeatedly inspecting image regions, gro
arXiv:2606.02673v1 Announce Type: new Abstract: Graphs have been used to enhance large language models (LLMs) for structured reasoning, mostly as external knowledge sources are provided to models at t
arXiv:2606.03871v1 Announce Type: cross Abstract: Visual instruction tuning effectively adapts a pre-trained Large Language Model (LLM) to process image information alongside text. Yet, it remains unc
arXiv:2512.22539v2 Announce Type: replace-cross Abstract: While Vision-Language-Action models (VLAs) are rapidly advancing towards generalist robot policies, it remains difficult to quantitatively und
arXiv:2606.03954v1 Announce Type: new Abstract: As AI systems increasingly assist humans in physical tasks, ensuring safety becomes paramount -- physical actions carry immediate and irreversible conse
arXiv:2603.04444v3 Announce Type: replace-cross Abstract: As large language models (LLMs) diversify across modalities, capabilities, and cost profiles, the problem of intelligent request routing -- se
arXiv:2603.13384v2 Announce Type: replace-cross Abstract: Software vulnerabilities often depend on cross-file data flow, build options, framework conventions, and runtime guards, so isolated function
arXiv:2603.04956v2 Announce Type: replace Abstract: This paper considers the problem of converting a given dense linear layer to low precision. The tradeoff between compressed length and output discre
arXiv:2606.02631v1 Announce Type: cross Abstract: This paper studies whether audio, images, and video can share a common wavelet token schema rather than relying on separate modality-specific latent g
arXiv:2509.19305v2 Announce Type: replace-cross Abstract: Diffusion probability models have shown significant promise in offline reinforcement learning by directly modeling trajectory sequences. Howev
we are seeing costs start to matter! uber just set limits of $1500 in tokens per developer per month i think we're going to start seeing more of this, and LangSmith Gateway is a great way to implement
We have a winner of the Lenny's Newsletter x @Replit buildathon 🏆 Congratulations @andrey_esipov on your mind-blowing project, Operators. Y'all need to check this out: https://operators--andreyyesipov
We have partnered with @Cognition to bring their AI coding platform, Devin, to the Public Sector. Together, we’re helping organizations modernize software development and accelerate secure AI adoption
We just announced the integration of our knowledge engine, Pinecone Nexus, with @Microsoft OneLake at #MSBuild. Want to build a reliable, production-grade knowledge layer directly over your structured
We partnered with @FireworksAI_HQ to train open-source models for legal. Here's what we found: 1) Hybrid legal agents can beat frontier models on quality and cost by routing selectively to a frontier
arXiv:2601.22443v2 Announce Type: replace-cross Abstract: Can a diffusion model trained on bedrooms recover human faces? Diffusion models are widely used as priors for inverse problems, but standard a
arXiv:2606.03220v1 Announce Type: cross Abstract: Existing benchmarks for MLLM-generated web artifacts assess interaction through local evidence and miss the requirement-induced states and transitions
Welp, that happened faster than I predicted. Thought it would be end of 2027, then early 2027, but agentic traffic growing so fast that bots have now passed human traffic online for the first time in
We’re bringing new capabilities to GPT-Rosalind, a model series purpose-built for life sciences research at enterprise scale. It brings GPT-5.5’s agentic coding and tool use together with stronger int
We're building a global movement to prohibit superintelligence internationally. Our new campaign in Canada is supported by over 30 MPs and Senators calling for a ban. After our success in the UK, it's
What are you investing in? Hopium: Former BlackRock fund manager Ed Dowd on the stock market: 'If 45% of your market cap is AI and there's no profits yet, what are you investing in?' 'You're investing
arXiv:2606.02965v1 Announce Type: new Abstract: Benchmarks for autonomous agents measure whether agents complete tasks, yet this framing is systematically blind to whether an agent should have proceed
arXiv:2606.03052v1 Announce Type: new Abstract: Knowledge Distillation (KD) is a powerful tool for model compression, yet the precise mechanisms by which student models acquire feature representations
arXiv:2606.03461v1 Announce Type: new Abstract: Stronger code agents are commonly assumed to be superior teachers for post-training, yet this assumption remains poorly disentangled from task difficult
Whether you use it for data preparation, real-time interactive queries, AI model training, or something entirely different, running Apache Spark at scale is demanding — you shouldn’t have to manage th
This Reddit discussion from r/ollama explores user experiences with uncensored Ollama language models, featuring anecdotal accounts of unusual or extreme use cases and recommendations for popular unce
arXiv:2606.03265v1 Announce Type: new Abstract: Accurate and robust localization remains a fundamental challenge for autonomous ground vehicles. In this work, we propose a hybrid neural inertial navig
arXiv:2606.03569v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have demonstrated remarkable capabilities but suffer from significant computational overhead during inference. While vis
arXiv:2606.03244v1 Announce Type: new Abstract: A common intuition is that sentence embeddings should adapt to the difficulty of the input. We test this intuition in a controlled, multi-seed setting:
arXiv:2606.03712v1 Announce Type: new Abstract: Graph Language Models (GLMs) have become a promising direction for adapting Large Language Models (LLMs) to graph learning tasks. By transforming graph
arXiv:2606.02866v1 Announce Type: new Abstract: When does multi-agent debate help data cleaning, and when does it hurt? Across three benchmarks, four model families, and over 6,000 task-condition pair
arXiv:2606.03391v1 Announce Type: cross Abstract: Model merging has emerged as a cost-effective approach for consolidating the capabilities of multiple LLMs without retraining. However, existing mergi
arXiv:2508.21448v3 Announce Type: replace Abstract: Large language models (LLMs) sometimes refuse to follow benign instructions, such as declining to argue a political position or adopt a stated perso
arXiv:2606.03238v1 Announce Type: cross Abstract: Reinforcement learning from human feedback (RLHF) makes large-scale post-training possible by replacing an underspecified human objective with learned
when sam quotes the bible, you know things aren’t going well for OpenAI one of the quotes i find most inspiring on a hard day: 'Whatever your hand finds to do, do it with all your might, for in the re
arXiv:2602.11908v3 Announce Type: replace Abstract: LLMs are widely used, yet they remain prone to factual errors that erode user trust and limit adoption in high-risk settings. One approach to mitiga
arXiv:2606.03532v1 Announce Type: cross Abstract: Self on-policy distillation trains a student policy against a teacher derived from its own parameter history, yet the teacher's update schedule -- whi
When the country needed a serious principled political party on the “right”, I launched @_AdvanceUK. The situation has since changed. And so we too must change. We are not in politics for the sake of
arXiv:2606.03741v1 Announce Type: new Abstract: Long-horizon reasoning requires a system to commit to medium-horizon intent without becoming rigid: re-plan too often and computation never coheres into