Baidu acaba de romper una de las limitaciones más grandes del OCR actual.
Unlimited-OCR procesa documentos enteros de una sola pasada, sin chunking.
Es el siguiente paso después de DeepSeek-OCR.
REPOOO👇
Google Brain founder, Andrew Ng:
"100% of my tasks are done by ai agents, self-improving loops are next.
Give it 3-6 months and prompting is gone."
31 minutes of clear explanation on building self-improving agents from scratch.
Worth more than any $500 agentic course.
Watch it, then read the full guide on loops below.
This day has come: Cafe Cursor is coming to Kyiv on June 30 ⚡️
Together with @bohdanpodvirnyi, @maksymatalks, and @cursor_ai, we’re turning CultMotiv on Podil into a one-day co-working cafe for people building with Cursor and AI.
Bring a laptop, grab coffee, work, meet others!
ANTHROPIC 🔥: Claude for mobile is getting Cowork support soon!
> Keep Cowork going when you are on the go
> Start and steer tasks directly from your phone
> Check in from your phone, browser, or Claude desktop app
> Work continues in the background, even when you close the app
h/t @M1Astra via DevMode
Google DeepMind 🤝 @A24
We’re launching a research partnership with A24 to ensure the tools of the future are shaped by the creators who use them. Find out more → https://t.co/KN3HdGVjGS
We’re expanding OpenAI Daybreak to help democratize patching vulnerable software at machine speed:
- Codex Security plugin: find, validate, and fix vulnerabilities right inside Codex
- The full version of GPT-5.5-Cyber model: a great model for trusted defenders
- Cyber Partner Program: powering products built on top of our best cyber capabilities for leading security companies to secure the world's software
- Patch the Planet: working with maintainers to secure critical open source projects
https://t.co/hyIi6gQmkm
Andrew Ng:
"100% of my tasks are now done by AI agents - hype has exceeded my expectations. Loops is next step.
in 3-6 months, everyone will be using self-improving loops. No more prompting."
In a 30-minute talk, Andrew Ng explains how to build self-improving agentic systems from scratch.
Worth more than a $500 agentic course.
Many people think any given ML project is 99% training.
In reality, it’s 50% evaluation, 40% data cleaning, 8% integration, and 2% training.
The first two set the noise floor for learning. No ML magic matters; the model cannot lower the noise floor, as that’s the optimal bound of Shannon encoding of your data.
Thus, not a single day goes by without me thinking about ontology. Even the old labels have to be constantly reviewed.
A bit of news: After nearly 9 years, I have decided to leave Google DeepMind and join Anthropic (after taking some time to recharge). I am incredibly grateful for my time at GDM. @demishassabis took a real chance letting me lead the AlphaFold team just six months after finishing my PhD, and the entire GDM team taught me so much about how to do great science. GDM is a special place, and I’ll still be excited to hear about what amazing things they discover next.
Introducing Goal Mode in Kimi Work
Goal lets your desktop agent run 24/7 until the task is done, built for long-horizon tasks and complex multi-step workflows.
Today we introduce a new vectorized dataset for mapping fine-scale ecological features, such as hedgerows, that often go undetected by standard satellites. This precision provides a new roadmap for addressing climate & biodiversity challenges without compromising food security. More: https://t.co/NRU3hrqvrd
Today on the blog, we discuss a pathway for the second life of phones through the exploration of “phone cluster computing”, which can directly reduce the environmental footprint of computing by avoiding the need for further raw material extraction. More →https://t.co/FFUNjfaEm5
🚨 @Karpathy predicted the power of the "LLM Wiki." Google just formalized it.
Meet Open Knowledge Format (OKF): a vendor-neutral standard for giving foundation models the curated context they need.
I can genuinely see this replacing Notion, Obsidian, or traditional wikis for developer teams, and the reason comes down to bookkeeping.
Traditional wikis fail because humans inevitably abandon the tedious work of updating them.
As Andrej Karpathy pointed out recently, LLMs don't get bored.
They don't forget to update a cross-reference, and they can touch 15 files in a single pass.
OKF standardizes the interoperability layer so agents can actually do that heavy lifting autonomously.
Because the format is minimally opinionated, it doesn't dictate what you write, it just dictates how it's structured. You get:
→ Human-readable documents that live right alongside your code in version control
→ Cross-links that map out complex entity relationships without needing a graph database
→ A system that survives moving between different tools and organizations
There is no complex compression scheme.
No central registry.
If you can cat a file, you can read it.
If you can git clone a repo, you can deploy it.
This is how we stop rebuilding context pipelines from scratch every time a new model drops.
Announcement + spec file in 🧵↓
Claude Code creator:
"100% of our pull requests at Anrtopic are run by Claude Code. 80–90% of code review too.
The feature I’m using the most today is /loops. I’m not prompting Claude anymore - I’m building loops"
in 1-hour interview, Boris reveals his setup, which helps him build the #1 coding tool of this year.
Worth more than a $500 vibe-coding course.
🚨Anthropic just showed a 24-minute workshop on how to actually do prompts for Claude.
Taught by the people who built it.
Free. No registration. No paywall.
I've seen $300 courses that don't cover what they teach in the first 8 minutes.
Watch it and bookmark it now.