arXiv study comparing self-reports (Big 5 vs Theory of Planned Behavior) with actual behavior of 11 frontier LLMs across 4 tasks. TPB reaches human-level coherence within shared conversation but fails across separate conversations. Broad personality frameworks poorly predict real behavior.
MTPLX V1 is a native macOS app (Swift) for running MLX models with MTP (Multi-Token Prediction). Forge auto-converts Hugging Face models to MLX+MTP with real speedup measurement. Qwen 3.6 27B reaches 63 tps (vs 28 tps in v0.1). Includes native chat, live dashboard, AIME 2026 benchmarking, Qwen 3.5 9B and Gemma 4 support.
Vercel AI SDK 7 introduces HarnessAgent, a unified API for running established agent harnesses (Claude Code, Codex, Pi). Enables switching harnesses without rewriting agent code. Harnesses manage skills, sandboxes, sessions, permissions, and sub-agents in a secure environment.
Vercel Drop enables deploying files or folders via drag-and-drop in the browser, without Git or CLI. Automatically detects and builds frameworks (Next.js, etc.). Creates a project, uploads files, and publishes to production with a shareable URL in seconds.
Kimi K2.7 Code from Moonshot AI is now available on Vercel AI Gateway. This coding model supports long-horizon programming tasks (frontend, DevOps, optimization) with native multimodal text+vision architecture and thinking mode.
GLM 5.2 now available on Vercel AI Gateway with context window upgraded to 1M tokens (from 200K). Model handles long-horizon tasks better and maintains engineering context across steps. AI Gateway provides unified API with usage tracking, retries, failover, and transparent pricing with no markup.
Datasette 1.0a33 extends the `?_extra=` pattern to queries and rows in addition to tables. This major alpha finally documents this API for JSON responses. A custom API explorer was generated using Claude Fable 5 and GPT-5.5.
DiffusionGemma 26B A4B quantization benchmarks (Q6_K 22GB, Q4_K_M 16GB) on RTX 5090. Stable context: 6,144 tokens (Q6_K) and 10,240 tokens (Q4_K_M) limited by disabled Flash Attention on SM120. Optimal parameters and llama.cpp invocations documented.
Anthropic reverses silent nerfing policy for Claude on AI/ML research. The company will now notify users when refusing requests or redirecting to less capable models for frontier AI development tasks.
arXiv paper presenting a five-plane reference architecture for runtime governance of production AI agents. Decomposes into reasoning plane and four enforcement planes (network, identity, endpoint, data). Addresses risks from delegation chains and composite actions, with implementation and evaluation against 7 agent threats across 5 workflows.
Theoretical paper on the Eliciting Latent Knowledge (ELK) problem: how to train AI systems to honestly report beliefs about hidden variables. Authors formalize ELK using Causal Influence Diagrams and prove an impossibility theorem: no feedback-based training strategy depending only on agent behaviour can guarantee agent honesty, even with perfect feedback.
Neural networks remain robust against >90% input corruption, far beyond human recognition. Mean-field analysis of infinite-width networks reveals MLPs implement a universal prototype rule (nearest-class-mean) across architectures, explaining why learning succeeds despite massive noise.
Pretrained self-supervised speech models (Wav2Vec2, HuBERT) fine-tuned on Khoisan languages (G|ui, West !Xoon) recognize click consonants more accurately than non-clicks, showing self-supervision generalizes to rare phonemes despite training data skewed toward high-resource languages.
MAD2 is a benchmark of 1,000 two-speaker audio dialogues (3,368 verifiable claims, ~10h audio) for misinformation detection in conversation. Authors propose calibrated multimodal fusion combining context-aware audio encoder and dialogue-aware text model. Conversational structure improves verification more than misinformation framing.
Diffusion models can accelerate LLM speculative decoding by generating token blocks in parallel. This paper identifies a gap between bidirectional training and left-to-right verification, proposing three interventions (positional weighting, first-error focal loss, chain loss) that increase accepted draft length by 21-76% across six benchmarks without additional compute.
Comprehensive survey on Federated Continual Learning (FCL), combining privacy-preserving federated learning with continual learning on non-stationary data. Identifies limitations of classical FL methods under evolving distributions and proposes a multi-dimensional taxonomy of FCL approaches for real-world applications (healthcare, industrial IoT, cybersecurity, smart cities).
Okara, an AI CMO platform built by 4 people, manages marketing growth for 120,000+ companies on Vercel. It processes 4 billion tokens daily across a multi-provider stack and deploys 8 specialized sub-agents (SEO, content, social media, Reddit, Hacker News). Okara migrated to Vercel AI Gateway to unify model integrations and eliminate manual maintenance.
Meta-analysis of 300+ papers on LLM reasoning. Taxonomy covering Chain-of-Thought, multi-hop reasoning, mathematical, common sense, visual, code, RAG, agents and RL. Identifies hallucinations, brittle multi-step inference, weak causal abstraction and poor cross-domain generalization.
Anthropic reverses a secret policy that would have degraded Claude Fable/Mythos performance for AI researchers without notification. The company acknowledges making 'the wrong tradeoff' and now makes safeguards visible.
Developer builds fully offline voice loop for Ollama + LM Studio. Stack: Silero VAD (voice activity detection), Parakeet TDT 0.6B (ONNX INT8 STT, 25 languages), Supertonic TTS 3 (multilingual ONNX synthesis). CPU-only, zero data leaves machine. Cross-platform (macOS/Linux/Windows), tested on 4-year-old ThinkPad.
Azure now supports DeepSeek V4 Pro and V4 Flash on Vercel AI Gateway. Requests automatically route through Azure with fallback to other providers—no code changes required. Supports BYOK (bring your own keys), zero platform fees on inference.
OpenAI acquires Ona to enhance Codex with secure, persistent cloud environments, enabling long-running AI agents in enterprise workflows.
datasette-agent 0.2a0 enables tools to ask users questions mid-execution via ask_user() supporting yes/no, multiple-choice, or free-text questions. Suspended conversations persist to database and survive server restarts. New built-in save_query tool lets agents save SQL queries as Datasette stored queries with mandatory human approval.
OpenAI and Oracle partner to enable access to OpenAI models and Codex through Oracle Cloud using existing cloud commitments. Customers gain enterprise security and governance capabilities.
Anthropic demonstrates that its Mythos Preview model converts security patches (Firefox, Windows kernel) into working exploits within hours for a few thousand dollars, requiring no specialized knowledge. Eight complete attack chains were finished before Microsoft's auto-updates reached a single device.
Google DeepMind introduces DiffusionGemma, a text generation model 4x faster than standard autoregressive approaches. The technique uses diffusion to parallelize generation and reduce latency.
Lemonade v10.7 introduces omni-modal models (image gen/editing), a benchmarking tool (lemonade bench) comparing llama.cpp, FastFlowLM and vLLM, and extends multi-vendor support (CUDA, Vulkan). 19 contributors, 6 working groups with 4 led by non-AMDers. GPU acceleration on AMD, Apple Silicon, Nvidia, Intel.
Cohere releases North Mini Code, an open-source coding model with 30B parameters (3B active). Scores 33.4 on Artificial Analysis Coding Index. Apache 2.0 license, available on Hugging Face.
Google upgrades NotebookLM with Gemini 3.5 Flash, cloud-based code execution, and autonomous source discovery via Google Search. Internal tests show the new version outperforms the previous one 78.2% of the time.
Google DeepMind announces a $10M funding call for multi-agent AI safety research.
PADD is a knowledge distillation method to convert dense teachers into MoE students without explicit routers. The 4-stage framework (initialization + training) uses teacher neuron clustering and adaptive optimization to achieve gains on mathematical reasoning benchmarks, with MoE students matching or exceeding dense teachers.
EinsteinArena is a distributed platform where AI agents collaborate on open mathematical problems. Since May 2026, agents have discovered 12 new state-of-the-art results, including improving the kissing number in dimension 11 (593→604) through iterative submissions, public discussion, and agent-to-agent idea sharing.
A simulator-guided LLM framework for autonomous open-pit mine scheduling. The LLM acts as a decision-making agent, constrained by a simulator encoding geotechnical and operational constraints. Without fine-tuning or cloud inference, it recovers 94–99% of MILP optimality with linear computation time.
TRACE, an unlearning method for MoE models, detects forget-critical experts activated by data to unlearn and recalibrates retention regularization by reweighting token-level losses to match expert activation frequencies. Experiments on WMDP and MUSE-BOOKS show 9% relative utility improvement over strongest baseline.
New GLU method quantifies uncertainty in LLMs by combining local entropy (token-level) and global entropy (hidden-state geometry). Tested on 3 model families and 6 benchmarks. Detects confident-but-wrong hallucinations missed by existing methods.
TabClaw is an open-source AI agent for spreadsheet and table analysis. It accepts CSV/Excel files via natural language, exposes an editable execution plan, uses a ReAct-style loop with specialist agents for multi-table reasoning, and records workflows to extract reusable skills and adapt to user preferences.
ActiveMem introduces a distributed architecture decoupling agent memory from LLM reasoning. A high-level Planner executes reasoning with distilled semantic gists while a lightweight parallel memory system actively accumulates and consolidates these gists. State-of-the-art results on BrowseComp-Plus and GAIA with reduced overhead.
TD-Grokking recursively decomposes zero-reward problems into verifiable subproblems to generate training signals. Tested on mathematical and medical tasks, the framework outperforms vanilla GRPO and converts zero-reward examples into usable optimization signals.
SocraticPO is a policy optimization framework for LLMs that augments RL rollouts with Socratic-style natural-language guidance. A teacher diagnoses errors and provides concise corrections, paired with reward decay to prevent the model from relying on assistance. Tested on SciKnowEval, it outperforms RL and self-distillation baselines.
PreAct-Bench is a benchmark of 1,000 paired ethical and unethical action trajectories to evaluate LLMs' ability to predict harmful behavior before execution. Results show that even strong models struggle with this predictive monitoring task, highlighting the need for future-oriented risk reasoning in LLM safety.