A M Y T • Think AI Outside Box 🇮🇳 retweeted
How to get AI to make discoveries on open scientific problems?
Most methods just improve the prompt with more attempts. But the AI itself doesn't improve.
With test-time training, AI can continue to learn on the problem it’s trying to solve: test-time-training.github.io…
A M Y T • Think AI Outside Box 🇮🇳 retweeted
The LLM training eras:
202x Pre-training (foundation)
2022 RLHF + PPO
2023 LoRA SFT
2024 Mid-Training
2025 RLVR + GRPO
A M Y T • Think AI Outside Box 🇮🇳 retweeted
Founders can delegate everything except recruiting, fundraising, strategy, and product vision.
A M Y T • Think AI Outside Box 🇮🇳 retweeted
BREAKING:
we've partnered with @metaai and @paperswithcode to build a successor to Papers with Code (which was sunsetted yesterday)
PWC, founded by @rbstojnic and @rosstaylor90 has been an invaluable resource for AI scientists and engineers over the years (and an inspiration for us to build @huggingface)
We are happy to follow in their path and provide a new section of HF for the community to follow trending Papers, linked to their code implementations on GitHub 🔥
link in the next tweet ⤵️
And hat/tip @joespeez @ThomasScialom for helping with this 🥰
A M Y T • Think AI Outside Box 🇮🇳 retweeted
✅ Looking for job opportunities in India’s top funded startups?
I’ve curated a list of startups in India that have raised funding in 2025, where you can apply for jobs or inquire about opportunities through cold emailing.
How to Use This List?
1- Visit the LinkedIn Jobs section and apply directly.
2- On the company’s LinkedIn page, find employee data to request referrals.
3- Visit the career portal and apply directly.
4- Send them a cold email to inquire about job opportunities. You can find email addresses in the footer or on the "Contact Us" page.
🔗 Want access to this?
1️⃣ Like ❤️ & Follow
2️⃣ Repost 🔁 to help others
3️⃣ Reply “India” ✍️
👉 Make sure to follow so I can send you the link!
Once this post hits 100 likes & replies, I’ll drop the link in the thread for everyone. Don’t miss it!
🔁 Share this with friends who are job hunting in the startup space!
#startups #funded
A M Y T • Think AI Outside Box 🇮🇳 retweeted
Top AI Papers of The Week (July 14 - 20):
- Agentic-R1
- Context Rot
- Scaling up RL
- A Survey of AIOps
- Chain-of-Thought Monitorability
- One Token to Fool LLM-as-a-Judge
- A Survey of Context Engineering for LLMs
Read on for more:
A M Y T • Think AI Outside Box 🇮🇳 retweeted
Infinite Wiki
⁕
Every word is a hyperlink. Every description is generated in real-time (in ~1 second)
⁕
Runs on Gemini 2.5 Flash Lite. ASCII diagrams using 2.5 Flash
Honest take from a mathematician on OpenAI's IMO Gold wins
though Google DeepMind isn't far behind
#IMO2025 #OpenAI #deepmind #LLMs
A M Y T • Think AI Outside Box 🇮🇳 retweeted
Two cents on AI getting International Math Olympiad (IMO) Gold, from a mathematician.
Background:
Last year, Google DeepMind (GDM) got Silver in IMO 2024.
This year, OpenAI solved problems P1-P5 for IMO 2025 (but not P6), and this performance corresponds to Gold. (1/10)
A M Y T • Think AI Outside Box 🇮🇳 retweeted
Run this command in your terminal:
claude mcp add "Deep Graph MCP" npx -- -y mcp-code-graph@latest microsoft/markitdown
That’s all it takes to connect the codebase graph of any GitHub repo with Claude Code 🙌
This quoted post is unavailable.
A M Y T • Think AI Outside Box 🇮🇳 retweeted
A curriculum-ordered list of concepts to learn Reinforcement Learning:
FOUNDATION
- MDP
- Bellman Eqn
- Bellman Expectation Eqn
- Value iteration
- Policy Iteration
- Tabular Q learning, SARSA
DQNs
- DQN
- Double DQN
- Dueling DQN
- Replay buffers, Prioritized Experience Replay
- On policy vs Off policy
POLICY GRADIENTS
- REINFORCE
- Advantages
- A2C, A3C
- DDPG, TRPO
- PPO, GAE
- SAC
COOL ALGORITHMS/CONCEPTS
- GAIL, IRL, Imitation learning
- Hindsight Experience Replay
- Curiousity
- Random Network Distillation
- HRL
- Sim to real
MODEL BASED
- Dyna-Q
- MPC
- World Models
- Dreamer
MULTI AGENT
- POMDPs
- Independent variants (I-PPO)
- Decentralized vs Centralized
- Centralized critic decentralized execution (MA-DDPG)
- Self play
- parameter sharing
- value decomposition (VDIN, QMIX)
- Communication rabbit hole
A M Y T • Think AI Outside Box 🇮🇳 retweeted
From GPT to MoE: I reviewed & compared the main LLMs of 2025 in terms of their architectural design from DeepSeek-V3 to Kimi 2.
Multi-head Latent Attention, sliding window attention, new Post- & Pre-Norm placements, NoPE, shared-expert MoEs, and more...
magazine.sebastianraschka.co…


























