an idea for paid plans: your $20 plus subscription converts to credits you can use across features like deep research, o1, gpt-4.5, sora, etc. no fixed limits per feature and you choose what you want; if you run out of credits you can buy more. what do you think? good/bad?
GENERATIVE AI
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OpenAI’s Reasoning Approach: Response Generation as Better Term
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It's an OpenAI thing (
https://
openai.com/index/learning
-to-reason-with-llms/
…). I think "Response generation" would probably be a better, more general term. -
LangGraph BigTool: Scalable Agent Tool Access Library
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LangGraph BigTool langgraph-bigtool is a Python library for creating LangGraph agents that can access large numbers of tools. – Scalable access to tools: Equip agents with hundreds or thousands of tools.
– Storage of tool metadata: Control storage of tool descriptions, -
Google Enhances Deep Research with Advanced Features
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BREAKING: Google is developing an upgraded version of Deep Research that includes 'Thinking' capabilities and an option to convert reports into Audio Overviews. However, there is no indication yet that this is set for release.
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Harrison Chase and Waseem Alshikh discuss evaluating scaling agents
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Fireside Chat in SF with Harrison Chase (Co-Founder & CEO at LangChain) and Waseem Alshikh (Co-Founder & CTO at Writer) on Evaluating and Scaling Agents Join us for an exciting evening meetup in San Francisco hosted at Susa Ventures! Waseem and Harrison will take you
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Developers Showcase Creative AI Projects with DeepSeek on SambaNova
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We love seeing devs flex their creative ideas with @deepseek_ai on SambaNova Cloud 🦾
— SambaNova (@SambaNovaAI) 4 mars 2025
Tag us in your projects! 👇#AI pic.twitter.com/AFiLgDJ7AnWe love seeing devs flex their creative ideas with @deepseek_ai on SambaNova Cloud Tag us in your projects! #AI
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Blended Labs Uses Llama Models for Personalized AI-Native Learning
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Blended Labs, an EdTech company in Germany, is using Llama 3.1 + 3.2 models to enable a wide range of AI-native flows for personalized learning pathways, real-time feedback, instant educational content generation and social gamification
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Heterogeneous Transformers Accelerate General-Purpose Robot Training
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5. Training general-purpose robots faster The "Heterogeneous Pretrained Transformers" technique merges vast, diverse data to help train robots on many tasks w/o starting from scratch. This faster, cost-effective method outperformed traditional training by >20% in real-world
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LucidSim: AI-Powered Virtual Robot Training Without Real-World Data
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3. Robots that learn from machine dreams 💤
— MIT CSAIL (@MIT_CSAIL) 4 mars 2025
"LucidSim" uses genAI & physics engines to create diverse & realistic virtual training grounds for robots. W/o any real-world data, their robot achieved expert-level performance on difficult tasks. pic.twitter.com/yaIrdQsRqq3. Robots that learn from machine dreams "LucidSim" uses genAI & physics engines to create diverse & realistic virtual training grounds for robots. W/o any real-world data, their robot achieved expert-level performance on difficult tasks.
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Diffusion Forcing Combines Next-Token Prediction Video Diffusion
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2. Next-token prediction meets video diffusion ▶️
— MIT CSAIL (@MIT_CSAIL) 4 mars 2025
"Diffusion Forcing" method combines the strengths of next-token prediction & video diffusion, training neural networks to handle corrupted data while predicting the next steps. This flexible, reliable sequence model helps produce… pic.twitter.com/QfsYAq7pCQ2. Next-token prediction meets video diffusion "Diffusion Forcing" method combines the strengths of next-token prediction & video diffusion, training neural networks to handle corrupted data while predicting the next steps. This flexible, reliable sequence model helps produce