Google DeepMind just dropped new open-source embedding model:
> Based on Gemma 3 270M
> highest ranking open model under 500M
> runs on less than 200MB of RAM
> input context length of 2048 tokens
> trained on over 100 languages
AI that actually fits in your pocket.
Google DeepMind just dropped new open-source embedding model:
> Based on Gemma 3 270M
> highest ranking open model under 500M
> runs on less than 200MB of RAM
> input context length of 2048 tokens
> trained on over 100 languages
AI that actually fits in your pocket. https://t.co/oZcUkJHiGk
He shares some of the best ways of using Claude Code you might’ve missed like using “ultra think” for better planning, for research, background tasks, and more. Highly recommended.
GPT-5 has become the cheapest frontier model
on the Aider leaderboard, GPT-5 is the lowest-priced among the top models while still leading in accuracy
> gpt-5-high: cheaper than o3-pro, Grok-4, and Gemini 2.5 pro
> gpt-5-md: higher accuracy than Gemini 2.5 Pro at a much lower…
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🚨BREAKING: A new open-source voice model just dropped and it’s better than ElevenLabs.
This open-source voice AI is ultra-expressive, high quality, and fully free with no paywalls, no limits.
Here’s how it works (with real examples):👇
Recent research papers that you should definitely take a look at:
▪️ Mobile-Agent-v3
▪️ Prompt Orchestration Markup Language
▪️ SSRL: Self-Search Reinforcement Learning
▪️ Atom-Searcher
▪️ MindJourney
▪️ Deep Think with Confidence
▪️ Controlling Multimodal LLMs via Reward-guided…
I work for a university and I want to help our faculty and staff learn how AI is affecting their specific fields of expertise.
What is the best resource for this?
I'd love to see current AI news for each department you might find in a university.
If you’re a CS student,
you're not competing over hard skills anymore.
The real fight is how well you can tune out all the crap telling you to stop programming or AI will replace you in 3 years.
Do not fall for the scam.
If you found it insightful, reshare with your network.
Find me → @akshay_pachaar ✔️
For more insights and tutorials on LLMs, AI Agents, and Machine Learning!
If you found it insightful, reshare with your network.
Find me → @akshay_pachaar ✔️
For more insights and tutorials on LLMs, AI Agents, and Machine Learning!
“A fresh college grad on top of AI can outperform a full-stack engineer with 10 yrs of experience that is still doing things as they were back in 2022.”
@AndrewYNg explains perfectly why we need more programmers, not less.
Next #BillionDollarStartups listee Basis makes AI accounting software that can do clerical work in minutes, streamlining data entry tasks like transferring information from receipts. trib.al/3v6Qp3qtrib.al/3v6Qp3q
New memory architecures will be important for model development and deployment...Huawei pushing the envelope here...lots of innovation in China beyond just scaling....
New memory architecures will be important for model development and deployment...Huawei pushing the envelope here...lots of innovation in China beyond just scaling....
AI buildout is massive, ~$6.7T by 2030 across data centers, with AI driving most new capacity.
AI alone needs ~$5.2T and ~156 GW of capacity, so the money clusters around chips, power, and sites.
McKinsey Report.
📈 Where the demand line points
Global data center capacity…
🏆NVIDIA AI-Q, an NVIDIA Blueprint for building AI agents with advanced reasoning skills, is now the leading open and portable #AIagent for high-fidelity research on the Deep Research Bench leaderboard. ➡️ nvda.ws/47fYiUl
✅ Built with NVIDIA Llama Nemotron for reasoning…
- Google Maps uses graph ML to predict ETA
- Netflix uses graph ML (GNN) in recommendation
- Spotify uses graph ML (HGNNs) in recommendation
- Pinterest uses graph ML (PingSage) in recommendation
Here are 6 must-know ways for graph feature engineering (with code):
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