Aklesh Mishra

AI Researcher | NLP Research & CSE from IIIT-H

[Anthropic @AnthropicAI]

New Anthropic research: Natural Language Autoencoders.

Models like Claude talk in words but think in numbers. The numbers—called activations—encode Claude’s thoughts, but not in a language we can read.

Here, we train Claude to translate its activations into human-readable text.

[Shunyu Yao @ShunyuYao12]

Still use ⛓️Chain-of-Thought (CoT) for all your prompting? May be underutilizing LLM capabilities🤠

Introducing 🌲Tree-of-Thought (ToT), a framework to unleash complex & general problem solving with LLMs, through a deliberate ‘System 2’ tree search.

https://t.co/V6hjbUNjbt

[Aklesh Mishra @iminevitable10]

@Kohli_Beliver18 That's the big reason why none can match what Dhoni has done in his life; that is actually a pro for him, NOT a point of troll, these trollers indirectly do PR of him 🤣

[Claude @claudeai]

New from Code with Claude Tokyo: scheduled deployments and environment variables in vaults are in public beta in Claude Managed Agents, and dynamic workflows in Claude Code are generally available.

Agents now run on a schedule, use your tools securely, and take on bigger jobs.

[Viktor Oddy @viktoroddy]

Claude Mythos is Insane!

❤️‍🔥Just recorded a 12-min tutorial on how to build animated, award-Winning websites with Claude Fable 5!

[Andrej Karpathy @karpathy]

This is a super exciting release - Claude Fable 5 is the same underlying model as Mythos but with added safeguards. The benchmarks are great and it's SOTA on everything by a margin but I'll add that *qualitatively* also, this is a major-version-bump-deserving step change forward (imo of the same order as Claude 4.5 was in November), peaking especially for long problem-solving sessions on very difficult problems. You can give it a lot more ambitious tasks than what you're used to, the model "gets it" and it will just go, and it's never felt this tempting to stop looking at the code at all (but don't do this in prod!). The model still has quirks that people will run into and the safeguards are configured to be a little too trigger happy for launch, which can hopefully be tuned over time.

I feel a lot of things changing as working software increasingly comes out on a tap. The Jevon's paradox kicks in and I feel my own demand for software growing substantially. You can ask for anything - explainers, visualizers, dashboards, bespoke single-use apps (e.g. a full wandb that is hyper-specific just for your project), you can 10X your test suite, auto-optimize code, run giant research projects with custom HTML for the results, anything! "Free your mind" (Matrix ref). Really looking forward to all the things people build!

[Aklesh Mishra @iminevitable10]

@KunalVkf18 Dhoni deserves the credit! He never asks for it, unlike Others. Why does Virat get the credit for the RCB win? ain't he deserve blame for RCB's 17 years of failure? if runs r only imp then RCB wud hv so many trophies. ppl r smart, they know who deserves it. And none can be dhoni.

[Aklesh Mishra @iminevitable10]

@Bihar_se_hai I don't like to defend, but w/o evidence, using Dhoni's name is unfair for any purpose. @Bihar_se_hai

[Claude @claudeai]

Introducing Claude Fable 5: a Mythos-class model that we’ve made safe for general use.

Its capabilities exceed those of any model we’ve ever made generally available.

[Aklesh Mishra @iminevitable10]

@imNoorAbrahim Dhoni in first 4y, which ur talking about, won 2 ICC + 1 Asia + 2 CT + 2 IPL + 2 Test mace + 1 Tri-series = 10 titles. 3 formats + 2 different leagues + different squads, NEVER compare anyone w DHONI, he is a god-like cricketer, not w virat as well and I mean it.

[OpenAI @OpenAI]

AI can give researchers the freedom to pursue “crazier” ideas.

For Terence Tao, AI creates more room to experiment, test unexpected paths, and discover what might otherwise stay out of reach.

[Anthropic @AnthropicAI]

Introducing Project Glasswing: an urgent initiative to help secure the world’s most critical software.

It’s powered by our newest frontier model, Claude Mythos Preview, which can find software vulnerabilities better than all but the most skilled humans.
https://t.co/NQ7IfEtYk7

[Anatoli Kopadze @AnatoliKopadze]

instead of watching 2 hours of Netflix tonight, watch this Stanford lecture

it's the clearest explanation I've seen of how ChatGPT and Claude actually work

useful whether you've never touched AI in your life or have been using it every day for the past year

I took the key ideas and turned them into a practical guide on how to actually get 100% out of Claude

find it below

[Tabassum Parveen @Tabbu_ai]

Instead of watching Netflix tonight, watch this 2-hour Stanford lecture.

It will teach you more about how LLMs like ChatGPT and Claude are actually built than most people learn in years working in AI.

Stanford released it for free.

Save this.

[R𝛼m 🦅 @rambuilds_]

15 AI related accounts you should follow on Twitter:

1. @karpathy
His tweets already create LLMs narratives that you later see on linkedin in 2 months.

2. @fchollet
posts thoughtful research on intelligence, benchmarks, and AI limitations. Keras creator + ARC-AGI

3. @ylecun
Yann LeCun is Deep learning pioneer & Meta Chief AI Scientist; big-picture research takes and critiques (and drama).

4. @AndrewYNg
Andrew Ng is AI education legend; practical ML advice, courses, and real-world implementation. creator of deeplearning ai

5 @rasbt
Sebastian Raschka posts on Practical ML/LLM implementations, "build from scratch" tutorials, and books.

6. @dair_ai
Weekly ML/AI paper threads and accessible research explainers (high-signal for staying current).

7. @lilianweng
Lilian Weng is ex-OpenAI and her Lil'Log-style threads are good. has In-depth LLM research breakdowns

8. @jeremyphoward
posts interesting takes on AI/crypto news, and works on democratizing practical deep learning and accessible education.

9. @simonw
Simon post Practical LLM tools, takes, experiments, prompting, and engineering breakdowns. django co-founder

10. @_akhaliq
Curates the latest arXiv papers, model releases, and open-source AI drops.

11. @ID_AA_Carmack
AGI/low-level optimization takes that makes you think about the problem.

12. @gwern
Really high-quality long-form AI research notes and essays.

13. @goodside
LLM evaluation, prompting research, and real capabilities testing

14 @drfeifei
Computer vision pioneer; human-centered AI and spatial intelligence research

15 @demishassabis
Been following his work for 9 years. Demmis is my hope against google usurpating their power with AI. Demmis is google DeepMind's CEO

Let me know who I missed guys and save it for future

[OpenAI @OpenAI]

Introducing GPT-Realtime-2 in the API: our most intelligent voice model yet, bringing GPT-5-class reasoning to voice agents.

Voice agents are now real-time collaborators that can listen, reason, and solve complex problems as conversations unfold.

Now available in the API alongside streaming models GPT-Realtime-Translate and GPT-Realtime-Whisper — a new set of audio capabilities for the next generation of voice interfaces.

[Charly Wargnier @DataChaz]

🚨 Karpathy was right. He warned that 90% of AI advice dies in 6 months.

spoiler: most tools will not even survive 90 days.

this guy is literally giving away the exact 2026 playbook for AI Agents.

he covers what to learn, what to build, and what to skip 👀

↓ read this today

[Atal @ZabihullahAtal]

MIT published 12 AI textbooks written by the top researchers who built the field.
These are not just books these are primary source material behind the world top AI ChatGPT, Claude, Gemini... (save this!)

1. Foundations of Machine Learning https://t.co/cyIHr6qm2z
2. Understanding Deep Learning https://t.co/5XUo4bPHRu
3. Machine Learning Systems https://t.co/l5bCCyXSV0
4. Algorithms for Decision Making https://t.co/1ZNU1XvSYK
5. Deep Learning https://t.co/JAo52d4JTI
6. Reinforcement Learning: An Introduction https://t.co/0XqopIY5CR
7. Distributional Reinforcement Learning https://t.co/z7bqEUK2ky
8. Multi-Agent Reinforcement Learning https://t.co/KgOtpxXAUc
9. Algorithms for Decision Making (Long Game) https://t.co/F6J9Za0igV
10. Fairness and Machine Learning https://t.co/r9egFAY6tL
11. Probabilistic Machine Learning: An Introduction https://t.co/xmmj7Ev7Of
12. Probabilistic Machine Learning: Advanced Topics https://t.co/6lUCb9blt8

I hope you found this helpful,
For more such useful resources you can follow me @ZabihullahAtal

[Python Space @python_spaces]

Think Python Book for FREE!

To get your copy, do the following.
- Like and Repost
- Comment "Python"
- Follow me so that I can DM you.

[Ruben Hassid @rubenhassid]

Instead of watching Netflix tonight.

Spend a day mastering Claude here: https://t.co/Vn60ElPZ2i

→ Level 1 - 24 min: The basics.

Claude For Dummies: https://t.co/HNa5MrCLVU
Claude Setup: https://t.co/jw2qdIcjnh

→ Level 2 - 1 hour: Real workflows.

Claude Cowork: https://t.co/uWTpOI3Woc
Claude for teams: https://t.co/qxlcqhf8bM
Claude Design: https://t.co/ZY8Fg5D2ea
Cowork + Projects: https://t.co/Q7AN9CZAbO
Claude for slides: https://t.co/L0bPMgXci6
Claude Skills: https://t.co/6cHYYfjXEA

→ Level 3 - 3.5 hours: The pro moves.

Avoid sycophancy: https://t.co/5i8xSJBGUl
Claude Code: https://t.co/UgE9xBXVbE
Claude 101: https://t.co/OvBmlvnVqL
Stop hitting Claude limits: https://t.co/j5fEzSH5br
Stop Prompting: https://t.co/j1LATSJiat

→ Level 4 - 8 hours: Expert mode.

Claude Computer: https://t.co/TxYuHPjgbV
Build with Claude API: https://t.co/RcCbfNjlzz

Pro tip: Don't binge it. Do one level per sitting.

Actually apply each guide before moving to the next