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что происходит в безопасности ML и LLM прямо сейчас

Most people still use AI like a 2015 search box. You type, you read, you type again. A newer pattern replaces that manual back-and-forth with a loop. This guide explains loop engineering using two verified artifacts. The sources are Andrej Karpathy’s autoresearch repository and t

Превращение генеративных моделей в самостоятельные сущности в информационных сетях ознаменовало начало совершенно новой эпохи внутри сферы информационной безопасности. Недавний аналитический доклад, опубликованный специалистами Фонда Карнеги, фиксирует крайне тревожную тенденцию:

I run a small site tracking what the big 4 recommend for "best X" tooling questions and yesterday got curious if the tier dropdown actually matters, like does Haiku recommend the same stack as Opus. Ran the identical prompt through every tier I could reach as a normal subscriber:

Overview Every piece you need to run AI in a company already exists as open source. A gateway to the models. Guardrails. PII masking. Policies. Evals. Audit. Lineage. Vector search. The problem was never the parts. It was wiring them into one thing that works — and keeping every

Anthropic has just extended access to Claude Fable 5 for paid subscribers until July 19, giving you another week to keep using the most powerful model. [...]

Hi everyone, I just wrote a deep-dive article on where the AI agent space is heading regarding identity and authorization boundaries. Most organizations today treat AI agents like classic microservices, running them with static service accounts or long-lived API keys. But agentic

I originally created this project about 2 years ago. Recently, I decided to update it and make it completely uncensored using a custom jailbreak prompt for my own personal use. But honestly, I thought, why keep it to myself? I figured I'd open it up as a free hobby project so you

Anthropic’s research on Claude found a silent internal workspace they call J-space — hidden reasoning that never shows up as visible text. Classic example: the model answers 49, but inside J-space they caught 21 → 42 → 49. Important distinction: Chain-of-thought = text you can re

Sharing something I built for my own projects: toolnexus, a small vendor-neutral tool-calling library + client loop, ported byte-identically across five languages. What it gives you: One Tool interface over six sources: MCP servers, agent skills (SKILL.md folders), your own funct

TL:DR: I’m a grad student in AI, I saw that Google released TabFM and TimesFM last week, I built an MCP wrapper to serve both transformer models in a single Docker container so you can connect their new ML transformer models to a local LLM via Open WebUI, Claude Code, or Codex an

Toolnexus is a small, vendor-neutral library that gives any LLM the dynamic tool-calling an agent framework has, but ported byte-identically across five languages (JavaScript, Python, Go, Java, C#). The idea: MCP servers, agent skills, your own functions, HTTP endpoints, the buil

TL:DR: I’m a grad student in AI. I saw that Google released TabFM and TimesFM last week. I built an MCP wrapper to serve both transformer models in a single Docker container so you can connect their new ML transformer models to a local LLM via Open WebUI, Claude Code, or Codex an

sharing the design since this sub goes deep on agent infra. the problem: agents working the same codebase from different machines can't see each other's uncommitted changes, so they build against stale interface shapes and it all surfaces at merge. the server puts agents in a sha

I think we need a new breakthrough in AI architecture. Just scaling LLMs will not help solve their foundational problems, such as hallucination, slop, lack of taste, strong opinions, character consistency, jailbreaking, prompt injection, deep customization, and determinism. What

Anthropic analyzed 1.2 million Claude Cowork sessions from more than 600,000 organizations. About half of all usage goes toward business processes and text creation, what Anthropic calls "the work around the work." That means tasks like compiling status reports, building onboardi

OpenAI CEO Sam Altman now says he's "pretty sure" AI has created more jobs than it's eliminated. That's a sharp turn from his earlier warnings about entire professions disappearing. Anthropic CEO Dario Amodei is walking back similar claims, too. But studies so far back neither th

The AgenticSTS project replaces the ever-growing chat log of AI agents with five separate memory layers. Tested on the card game Slay the Spire 2, the prompt stays at around 5,000 tokens instead of ballooning past 500,000. The agent wins 6 out of 10 games, while competing agents

Hey I am running a few models on a strix halo box. Especially for the larger models (like Qwen 3.5 122B) they work okayish performance wise if the cache is utilised properly but a full cache miss at 100k context causes roughly 10-20 minute of PP time - which is extremely annoying

«Внедрить ИИ» — формулировка, за которой на практике скрываются совершенно разные по масштабу работы. Одной компании нужен агент, который годами живёт на сервере и разбирает входящие заявки. Другой — разовый прогон одного документа через связку нейросетей перед подписанием акта.

Anthropic recently published their paper on "Global Workspaces" (J-Space) inside language models, showing that looking at internal "workspace noise" (entropy) can catch hallucinations better than just looking at output logprobs. `solarkyle` followed up with a great open-source im

The more I think about autonomous agents paying for tools, the less I like the phrase “agent wallet.” A wallet sounds like ownership. For most practical agent workflows, I think the safer abstraction is delegated permission. For example, I would rather give an agent something lik

Hey guys, I've been running Qwen 3.6-27b locally on an RTX 3090 for a while now, and it's been genuinely great at solving software issues. However, life happened and I recently had to use Opus 4.8 alongside the Zed editor and the Claude Code agent. While I can definitely see a no

Thinking Machines Lab published "The Future Worth Building Is Human." The essay frames human participation, model ownership, and decentralized alignment as technical challenges. It ties them to interaction models and Tinker's LoRA fine-tuning, where teams train and keep their own

OpenCode has the following FREE models to use now: Free Model on OpenCode AI Lab DeepSeek V4 Flash Free DeepSeek MiMo V2.5 Free Xiaomi Hy3 Free Tencent Nemotron 3 Ultra Free NVIDIA North Mini Code Free Cohere Big Pickle Stealth Some of these models are Frontier Model quality acco

I connected 4 MCP servers to one agent and noticed tool-selection accuracy dropping as I added more, and It wasn't random either, the decline was surprisingly consistent and almost tracked linearly with server count, so i started counting tokens. Every tool an MCP server exposes

10 июля, на следующий день после публичного запуска GPT-5.6 Sol Ultra, OpenAI заявила, что ее флагманская модель нашла доказательство гипотезы о двойном покрытии циклами — одной из самых известных открытых задач теории графов, стоявшей около полувека. По словам сотрудника OpenAI

10 июля, на следующий день после публичного запуска GPT-5.6 Sol Ultra, OpenAI заявила, что ее флагманская модель нашла доказательство гипотезы о двойном покрытии циклами — одной из самых известных открытых задач теории графов, стоявшей около полувека. По словам сотрудника OpenAI

I built this thing called ContextOps over the past few days and finally decided to open source it. The idea came from working on RAG pipelines and AI agents, where it felt like we spend a lot of time evaluating model outputs but almost no time looking at what actually goes into t

So I think I'm turning crazy. Everyone has a crazy agent setup on twitter. But I personally keep running into the same wall building agents. I don't really know when I change a prompt or a MCP, it looks fine when I test by hand, and then it will quietly break later. Somewhere I d