praveen gupta

[praveen gupta @praveengupta95]

@KhusbooT14835 AI

[Khusboo Tayal @KhusbooT14835]

ChatGPT + laptop + internet connection + 60 minutes per day = $9500 every month.

I normally sell this guide for $81, but for the next 48 hours, it’s yours 100% FREE.

To get it FREE: -

1. Follow me (So I can DM you )
2. Retweet [Mandatory]
3. Like + Reply " Ai "

Must follow me to get DM. Free for 48 hours

[Srishti @srishticodes]

Stanford just dropped their full LLM course on YouTube.

9 lectures.
Completely Free.
Real curriculum-level depth.

CME 295: Transformers & Large Language Models

This isn’t:
• a hype tutorial
• a prompt-engineering hack
• a tech influencer hot take

It’s Stanford’s Autumn 2025 course.

They cover: Transformers from first principles
Tokenization, attention, positional embeddings
Decoding, MoE, scaling laws
LoRA, RLHF, fine-tuning
RAG, tool calling, evaluation
RoPE, quantization, optimization tricks

This is foundation-level AI knowledge.
The kind that actually gets you ahead.

If you’re serious about learning AI:
👉 bookmark this
👉 repost for later
👉 stop doomscrolling and build

Playlist link: https://t.co/6rEBdY9tIU

[AI at Meta @AIatMeta]

🆕 New video – Knowledge Distillation with Llama 3.1 405B. In this extended discussion, @nazeri2010 & @subramen delve into the importance of fine-tuning — and how Llama 405B can be used to generate synthetic data. Full video on YouTube ➡️ https://t.co/WAHxCk5Dga

[AI at Meta @AIatMeta]

As we continue to explore new post-training techniques, today we're releasing Llama 3.3 — a new open source model that delivers leading performance and quality across text-based use cases such as synthetic data generation at a fraction of the inference cost.

[AI at Meta @AIatMeta]

Through experimentation @LinkedIn found EON-8B, a domain-adapted version of Llama 3.1 8B, to be 75x and 6x cost effective in comparison to GPT-4 and GPT-4o respectively.

More on their domain-adapted foundation model work ➡️ https://t.co/mZGuiZaxCY

[AI at Meta @AIatMeta]

🎥 Today we’re premiering Meta Movie Gen: the most advanced media foundation models to-date.

Developed by AI research teams at Meta, Movie Gen delivers state-of-the-art results across a range of capabilities. We’re excited for the potential of this line of research to usher in entirely new possibilities for casual creators and creative professionals alike.

More details and examples of what Movie Gen can do ➡️ https://t.co/M19x2ndwnr

🛠️ Movie Gen models and capabilities
Movie Gen Video: 30B parameter transformer model that can generate high-quality and high-definition images and videos from a single text prompt.

Movie Gen Audio: A 13B parameter transformer model that can take a video input along with optional text prompts for controllability to generate high-fidelity audio synced to the video. It can generate ambient sound, instrumental background music and foley sound — delivering state-of-the-art results in audio quality, video-to-audio alignment and text-to-audio alignment.

Precise video editing: Using a generated or existing video and accompanying text instructions as an input it can perform localized edits such as adding, removing or replacing elements — or global changes like background or style changes.

Personalized videos: Using an image of a person and a text prompt, the model can generate a video with state-of-the-art results on character preservation and natural movement in video.

We’re continuing to work closely with creative professionals from across the field to integrate their feedback as we work towards a potential release. We look forward to sharing more on this work and the creative possibilities it will enable in the future.

[AI at Meta @AIatMeta]

📣 Llama 2 and Code Llama are now on #KaggleModels!

[Andrej Karpathy @karpathy]

Yay, llama2.c can now load and inference the Meta released models! :) E.g. here inferencing the smallest 7B model at ~3 tokens/s on 96 OMP threads on a cloud Linux box. Still just CPU, fp32, one single .c file of 500 lines: https://t.co/CUoF0l07oX
expecting ~300 tok/s tomorrow :)

[Yann LeCun @ylecun]

A history of LLMs derived from LLaMA.

https://t.co/pz0zcCOBLb

[Sebastian Raschka @rasbt]

LLaMA-Adapter: finetuning large language models (LLMs) like LLaMA and matching Alpaca's modeling performance with greater finetuning efficiency

Let's have a look at this new paper (https://t.co/uee1oyxMCm) that proposes an adapter method for LLaMA instruction finetuning

1/5

[Andrej Karpathy @karpathy]

Next frontier of prompt engineering imo: "AutoGPTs" . 1 GPT call is just like 1 instruction on a computer. They can be strung together into programs. Use prompt to define I/O device and tool specs, define the cognitive loop, page data in and out of context window, .run().

[Navalism @NavalismHQ]

"The ideal life would be one where you had a hobby that as a byproduct made you money, you had a hobby that as a byproduct kept you healthy, you had a hobby that as a byproduct made you smarter and more creative."

@naval

[Navalism @NavalismHQ]

"You are a story that you tell yourself."

@naval

[Navalism @NavalismHQ]

"If you want to make the wrong decision, ask everyone."

@naval

[Yann LeCun @ylecun]

Good article on LLMs at Forbes.

The media are starting to agree with my much-criticized statements about LLMs.

"LLMs as they exist today will never replace Google Search. Why not? In short, because today’s LLMs make stuff up."

https://t.co/Cngp2Zyisq

[Andrej Karpathy @karpathy]

Random quick note on Transformer block unification. People are usually a bit surprised that the MLP and Attention blocks that repeat in a Transformer can be re-formated to look very similar, likely unifiable. The MLP block just attends over data-independent {key: value} nodes:

[Chris Hladczuk @chrishlad]

Work-life balance in your 20s is an easy way to guarantee a mediocre career.

[Nithin Kamath @Nithin0dha]

I have spent the last couple of years thinking quite a bit about health. Experimenting with myself and our team, and supporting startups that are trying to help Indians make healthier choices.

A few thoughts on how and why you should focus on your health. 1/9

[anshul gupta @anshgupta64]

What will happen to a car with two drivers?

In the UK, the two drivers are the government and the central bank, and the car is the UK's economy.