The most important AI paper of 2025 might have just dropped.
NVIDIA lays out a framework for Small Language Model agents that could outcompete LLMs.
Here’s the full breakdown (and why it matters):
Just discovered an incredible open-source collection of hands-on Generative AI experiments!
Over 100+ practical Jupyter notebooks covering everything from LLM basics to advanced AI agents, RAG systems, and real-world applications like chat with PDFs, GitHub readme generators,…
Free course to learn full stack perspective on building ML-powered products.
Covering everything from neural networks and PyTorch to deployment, monitoring, data management, and ML team management across 18 detailed videos.
Link in comments 😎👇
Huge AI news
Apple and Oxford just made AI 6.5x better at problem solving.
A new framework boosts AI agent success from 14% to 91% by teaching them to ask the most informative questions.
Using an Expected Information Gain (EIG) loop, agents hypothesize solutions, score…
Huge AI news
Apple and Oxford just made AI 6.5x better at problem solving.
A new framework boosts AI agent success from 14% to 91% by teaching them to ask the most informative questions.
Using an Expected Information Gain (EIG) loop, agents hypothesize solutions, score… https://t.co/jkyMkXW9a7
If you’re still learning AI from YouTube clips, you’re already behind. HuggingFace just dropped 9 expert-level courses for free and they’re the exact roadmap to master LLMs and agents before everyone else:
FREE Natural Language Processing Course from Stanford. Link in comment.
> 63 lectures covering everything from word representations and sentiment analysis to transformers, BERT, and neural information retrieval. > Perfect for mastering modern NLP techniques and building robust…
Our honest analysis of MIT Nanda's State of AI in Business report
Read with your eyes open, and you'll see much more beyond that flashy 95% figure of organizations getting zero return from AI investments ⬇️
Find a full breakdown on YouTube:
youtube.com/watch?v=WBPkkj…
This is the best Linear Algebra Playlist to build intuition. Link in comment.
> This free course by 3Blue1Brown will teach you linear algebra through stunning visual explanations.
> 16 comprehensive videos covering everything from basic vectors to eigenvalues, with a…
Anthropic just released Free AI courses on:
- Prompt Engineering
- Building agents
- Best practices for Agentic Coding
- Collaborate with AI systems
.... and so much more
9 best guides you don’t want to miss:
Fine motor skills are key to using robots in areas such as modern medicine; robots that operate in all areas of the world, enabling us to remedy the shortage of surgeons. What a great future!
Gemini Pro doesn't get enough credit for being able to upload 1500+ pages of text to reference (several textbooks in PDF form) and cites every response with a link to the text.
By far the most useful LLM for specific learning.
Announcement Time 📢🚀
Starting today @sciraai gives users the freedom to choose their own search provider. From now on the default in Scira is Parallel (@p0).
Scira is one of the first and a big open source project to introduce Parallel. This is a major step forward because it…
AI Engineering Toolkit!
Curated list of 100+ LLM libraries and frameworks for training, fine-tuning, building, evaluating, deploying, RAG, and AI Agents.
100% Open Source
AI Engineering Toolkit!
Curated list of 100+ LLM libraries and frameworks for training, fine-tuning, building, evaluating, deploying, RAG, and AI Agents.
100% Open Source https://t.co/R53lGxjUW3
If you found it useful, reshare it with your network.
Follow me → @Sumanth_077 for more such content and tutorials on ML, LLMs and AI Agents!
x.com/Sumanth_077/st…
If you found it useful, reshare it with your network.
Follow me → @Sumanth_077 for more such content and tutorials on ML, LLMs and AI Agents!
x.com/Sumanth_077/st…
AI Engineering Toolkit!
I have curated list of 100+ LLM libraries and frameworks for training, fine-tuning, building, evaluating, deploying, RAG, and AI Agents!
100% Open Source
📁 Sam Altman, CEO of OpenAI, says:
“Look, the models are going to be much smarter than we are. But there are a lot of things that people care about that have nothing to do with intelligence… People really care about other humans. This is, like, very deep.”
Presenting the GLM-4.5 technical report!👇
arxiv.org/abs/2508.06471
This work demonstrates how we developed models that excel at reasoning, coding, and agentic tasks through a unique, multi-stage training paradigm.
Key innovations include expert model iteration with…
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