Research1 мин
llm_wikiLLM Wiki creates personal knowledge bases from PDF files and saved web pages. For this purpose, a mul...
llm_wikiLLM Wiki создаёт персональные базы знаний из PDF-файлов и сохранённых веб-страниц.
GitHub Разработчика
Publication Catalog
All stories
All published intelligence, sovereign stack research, ecosystem news, and AI foundation model reviews.
2230
Stories
Research1 мин
OpenAI responds to the math authorship dispute
Join My Newsletter for Regular AI Updates 👇🏼 https://forwardfuture.com My Links 🔗 👉🏻 X: https://x.com/matthewberman 👉🏻 Forward Future X: https://x.com/forwardfuture 👉🏻 Instagram: https://www.instagram.com/matthewberman_ai 👉🏻 Discord: https://discord.gg/u7wTTGWhuJ 👉🏻…
YouTube — Matthew Berman
Research1 мин
Superintelligence is coming. Should we let it?
AI companies have been talking about superintelligent AI like it’s inevitable, but recent safety incidents like OpenAI’s Hugging Face breach are demonstrating the potential dangers of deploying AI systems that are more…
TechCrunch — AI
Research1 мин
ИИ ВЗЛОМАЛ СТАРЕНИЕ! Минус 6 Лет За Месяц! Открыт Ключ К Молодости! СТАРОСТЬ БОЛЬШЕ НЕ ПРИГОВОР!
Всем привет. В этом выпуске самые главные свежие новости об искусственном интеллекте и технологиях. И лекарство неожиданно омолодило организм людей сразу на несколько лет, и для этого его вообще не создавали. GPT-6 Astra прошла все 48 тестов "Я не робот" и официально получила…
YouTube — AI Flash News
Research1 мин
Recreating a 70-year love story frame by frame
Discover how filmmakers and Google DeepMind used AI to recreate a couple's unrecorded past in the short film "Love, Rendered."
Google AI Blog
Research1 мин
ControlAI’s Connor Leahy on why superintelligence is ‘not a weapon, it’s an adversary’
AI companies have been talking about superintelligent AI like it’s inevitable, but recent safety incidents like OpenAI’s Hugging Face breach are demonstrating the potential dangers of deploying AI systems that are more…
TechCrunch — AI
Research1 мин
Gambling with our lives’: Anthropic researcher quits, warns against self-improving AI
Anthropic researcher Jacob Coxon resigned over AI extinction fears, calling for pacing agreements between labs.
TechCrunch — AI
Startups1 мин
Сегодня в 18:00 прямой эфир на тему: «HackAlem AI изнутри: как готовят крупнейший в мире AI-хакатон с участием Ope...
Сегодня в 18:00 прямой эфир на тему: «HackAlem AI изнутри: как готовят крупнейший в мире AI-хакатон с участием Ope....
Telegram — Astana Hub
Startups1 мин
Besxar is building an orbital semiconductor factory, one SpaceX rocket at a time
If you want to manufacture in space—and bring the products back again—there’s a limited set of options: Wait to go to the International Space Station, or partner with a handful of start-ups launching spacecraft that spend time in orbit before they return to Earth. But the…
TechCrunch — AI
Research1 мин
GPT-6 Astra: The next generation in intelligence for work
Meet GPT-6 Astra, OpenAI’s most capable model for business, with advanced reasoning, computer use, and stronger writing and design judgment.
OpenAI Blog
Research1 мин
Worried Anthropic researchers warn that AI ‘could kill all humans’
A senior Anthropic safety researcher has said there is more than a 10 percent chance artificial intelligence "could kill all humans" by the end of the decade, just hours after a colleague resigned over fears the AI lab and its rivals are carelessly racing to build "superhuman…
The Verge — AI
Research1 мин
OpenAI JUST solved math....
So, this has been one of the most insane days in AI possibly ever. OpenAI announces that one of its next generation models that we haven't seen has produced a historic landmark mathematical breakthrough. It's been an open problem for close to a century. Has millions of dollars…
YouTube — Wes Roth
Research1 мин
When Does Memory Help? A Cost-Aware Evaluation of Long-Term Memory in Tool-Using LLM Agents
arXiv:2609.05441v1 Announce Type: new Abstract: Long-term memory for LLM agents is evaluated today by conversational recall benchmarks (LoCoMo, LongMemEval), which measure question answering over dialogue history, not whether remembered facts change what a tool-using agent does.…
arXiv — cs.AI
Research1 мин
CriticGen: Generation-Aware Evaluation as Actionable Feedback
arXiv:2609.05439v1 Announce Type: new Abstract: Current evaluation methods for large language models are coarse-grained and decoupled from generation, producing generic explanations that fail to provide actionable feedback for model improvement. We propose CriticGen, a…
arXiv — cs.AI
Research1 мин
AutoFyn Technical Report: Non-Parametric Expert Iteration for Long-Horizon Agents
arXiv:2609.05446v1 Announce Type: new Abstract: We introduce AutoFyn, an agent harness inspired by the Expert Iteration algorithm, adapting a frozen model across many rounds by updating persistent state from verified reward signals rather than model weights. Each round begins…
arXiv — cs.AI
Research1 мин
ARC-Bench: Closed-Loop Replanning Masks Broken Action Ranking in Frozen JEPA World Models
arXiv:2609.05461v1 Announce Type: new Abstract: Reward-free latent world models plan by scoring candidate actions with distances in a frozen latent space: an action is preferred if its predicted future embedding lands closer to the goal embedding. This silently assumes that…
arXiv — cs.AI
Research1 мин
When and What to Teach: Budget-Aware Online Adaptation for Web Agents
arXiv:2609.05513v1 Announce Type: new Abstract: Web agents have achieved significant success in automating complex internet tasks but deploying them in real-world environments requires continuous online adaptation. Given that deploying powerful proprietary models remains…
arXiv — cs.AI
Research1 мин
The Failure Happens Before the Drift: The Social Dynamics of Values in LLM Agent Societies
arXiv:2609.05514v1 Announce Type: new Abstract: Large Language Model (LLM)-based agents are increasingly used as proxies for human participants in social science research, yet it remains unclear whether they can faithfully simulate diverse and conflicting human value systems. We…
arXiv — cs.AI
Research1 мин
Deep belief networks are exact
arXiv:2609.05572v1 Announce Type: new Abstract: We prove that every strictly positive probability distribution on \(\{-1,1\}^n\) is represented exactly by a sigmoid belief network with finite parameters. This answers a question of Sutskever and Hinton. The proof upgrades their…
arXiv — cs.AI
Research1 мин
EdgeMem: LLM-Free Agent Memory Construction and Retrieval via Evidence-Preserving Multi-Anchor Hypergraph
arXiv:2609.05553v1 Announce Type: new Abstract: Agent memory allows LLM agents to use earlier interactions when answering new queries. Existing methods often compress interaction histories into summaries or other LLM-generated representations. Repeated generation adds cost and…
arXiv — cs.AI
Research1 мин
Compiling VGDL into Causal Models
arXiv:2609.05459v1 Announce Type: new Abstract: Reinforcement learning and large language models often struggle to accurately capture the causal mechanics of game environments. Standard reinforcement learning agents tend to rely on spurious correlations, while large language…
arXiv — cs.AI
Research1 мин
SCAFFOLD: Self-Improving Web Agents via Recursive Parametric Skill Abstraction
arXiv:2609.05511v1 Announce Type: new Abstract: Web agents need to navigate visually rich, long-horizon interfaces that change across sites, yet most previous agents still learn each task in isolation and discard the procedural knowledge they accumulate. Recent skill-augmented…
arXiv — cs.AI
Startups1 мин
Recovering Temporal and Geographic Signals from Language Model Embeddings
arXiv:2609.05721v1 Announce Type: new Abstract: Understanding whether language-model embeddings encode structured real-world information is important for both representation analysis and information retrieval. We study this question for temporal and geographic signals using a…
arXiv — cs.AI
Research1 мин
Beyond Prompts: Measuring and Optimizing LLM Tool-Agent Harnesses
arXiv:2609.05736v1 Announce Type: new Abstract: LLM tool agents can be improved without retraining by modifying the runtime harness around a fixed model: prompts, tool interfaces, middleware, state handling, and recovery logic. We study this setting as resource-bounded harness…
arXiv — cs.AI
Research1 мин
PGP-Clinical-TimeKAN: Prior-Guided Joint Probabilistic Forecasting of Clinical Trajectories
arXiv:2609.05488v1 Announce Type: new Abstract: Clinical deterioration unfolds through coupled, partially observed trajectories, not a single diagnostic label. We introduce PGP-Clinical-TimeKAN, a trajectory-first framework for joint probabilistic forecasting of multivariate…
arXiv — cs.AI
Research1 мин
The convergent laboratory: when AI reasoning, autonomous experiments, high performance and quantum computing reshape chemistry
arXiv:2609.05643v1 Announce Type: new Abstract: This Comment emerges from TPC26 (https://tpc26.org), a conference convening leaders from academia, national laboratories, and industry who are reshaping materials science discovery. The meeting explored how AI, autonomous agents,…
arXiv — cs.AI
Research1 мин
Agents Trust Tools Too Much: Measuring Reliance on Unreliable Tools
arXiv:2609.05587v1 Announce Type: new Abstract: Existing evaluations of tool-using agents primarily measure whether an agent can successfully complete diverse tasks with tools. These evaluations generally assume that tools return reliable information. However, tool returns in…
arXiv — cs.AI
Research1 мин
What LLM Trading Agents Actually Do in Production: A Six-Month, Population-Scale Record from Two Fleets
arXiv:2609.05663v1 Announce Type: new Abstract: We present a continuous, population-scale measurement record of autonomous language-model trading agents operating in production across two systems with one design lineage: DX Terminal Pro (3,505 user-funded vaults trading real ETH…
arXiv — cs.AI
Research1 мин
SciLitBench: Benchmark and Design Principles for LLM-Powered Systematic Literature Reviews
arXiv:2609.05505v1 Announce Type: new Abstract: Systematic reviews require sustained human judgment across thousands of records, yet existing evaluations of large language models (LLMs) typically examine review stages in isolation. We introduce SciLitBench, a multi-stage…
arXiv — cs.AI
Research1 мин
RAPID: Reliability-Aware Pair Importance Distillation
arXiv:2609.05481v1 Announce Type: new Abstract: Inter example relational distillation transfers a teacher's representation geometry by matching relations among examples within a mini batch. Computing all pairs has quadratic complexity in the batch size, whereas uniform…
arXiv — cs.AI