There is a lot of important stuff in this new paper by Anthropic that shows how people are actually using Claude. 1) The tasks that people are asking AI to do are some of the highest-value (& often intellectually challenging) 2) Adoption is uneven, but many fields already high

The Anthropic Economic Index is a new initiative by Anthropic aimed at analyzing AI's economic impact by examining millions of anonymized conversations with their AI model, Claude.

How are GenAI, data regulations, Postgres, DuckDB, and open table formats shaping data engineering in 2025? Here are the key takeaways from Anna Geller’s piece: 🔹 GenAI drives efficiency, but revenue impact remains limited 🔹 AI agents are evolving, but reasoning challenges

So, Google's Gemini just dropped a cool update where it can now pull up past chats to make its responses more on point and connected. This feature's rolling out for English-speaking Gemini Advanced users on Google One AI Premium, showing how Google's stepping up the AI game to

It's 2025, and I’ve finally updated my Python setup guide to use uv + venv instead of conda + pip! Here's my go-to recommendation for uv + venv in Python projects for faster installs, better dependency management: github.com/rasbt/LLMs-fro… (Any additional suggestions?)

we are analyzing the top papers on Hugging Face (~4000 papers mostly related to LLMs) and here is a list of the top 20 authors with the most papers published in less than 2 years. all of them Asian! (not necessarily in Asia) this is no competition, these alphas OWN the game.

Today we’re launching SWE-Lancer—a new, more realistic benchmark to evaluate the coding performance of AI models. SWE-Lancer includes over 1,400 freelance software engineering tasks from Upwork, valued at $1 million USD total in real-world payouts. openai.com/index/swe-lanc…

DeepSeek's NSA is basically a brainy shortcut for AI, sparsing out attention to handle crazy-long contexts fast, like 11.6x faster on big sequences, while still crushing benchmarks. It’s tailor-made for GPUs, and with Grok 3 dropping, it’s sparking some serious AI smackdowns.

one of the coolest LLM visualizations: > interactive and 3D > see all matrix operations > step by step layer processes > includes GPT 3

We now have INSTANT access to all data across X thanks to Grok 3 which has INSANE implications… 💥 Worked with Jay ⛽️ to build out a Market Research System using Grok + OpenAI Deep Research. Here are the prompts + how it works 👇 1️⃣ Define a rough idea of your elevator

Super stoked about Ross Taylor ’s General Reasoning launch, an open-source hub for AI reasoning! It’s got 1.5M+ problems, tons of data traces, and invites community input to rival big closed-source models. Big props for pushing personal, transparent AI after the ‘R1 moment

DeepSeek's dropping 5 open-source repos next week for #OpenSourceWeek! No hype, just real progress on AG...small team, big moves. Expect daily unlocks, no gatekeeping, just garage-energy vibes.

How Transformer² Adapts LLMs in Real-Time: A Visual Breakdown Check out this diagram from the new Transformer-Squared (Transformer²) paper. It illustrates how this self-adaptive LLM framework dynamically adjusts to new tasks without full retraining. Here’s what’s happening:

Claude 3.7 Sonnet: Anthropic's most intelligent model yet, with hybrid reasoning for instant or step-by-step thinking, plus Claude Code for advanced coding—redefining AI assistance for developers! Anthropic

Setting up your code environment is often the 1st step when building LLMs for education, research, or production. Made a new video where share my personal setup: "Build an LLM from Scratch 1: Set up your code environment": youtube.com/watch?v=yAcWnf… (Are videos like this helpful?)

When it comes to explainable AI this is all one needs #xai

Everyone is talking about MCP. I summarized all the MCP announcements/launches from Composio, Firecrawl, Cursor, Jira, Langchain, Firebase, and more Send to your engineering team (save for later)

My favorite one was watching the 'Manus' operating video. The AI agent, which launched in China, was automating about 50 tasks and scenarios simultaneously

Sebastian Raschka put together a solid breakdown of 12 new research papers on LLM reasoning. He goes through different ways models can get better at reasoning without needing massive training runs. If you're curious about where things are headed, this is worth checking out Sebastian Raschka

Manus AI, a Chinese AI marvel stunned with a professional Tesla stock analysis in just one hour: proof it’s the DeepSeek-like game-changer in AI, sparking global buzz and rivalry in 2025