Vinay

CTO @ - 2x Founder - AI enthusiast - Georgia Tech Engineer - Father of 4

[Vinay @vinaygode]

Amazing work in cv

[SkalskiP @skalskip92]

supervision just hit 40,000 GitHub stars!

it now powers over 6.5k open-source computer vision projects, including all my demos like basketball AI

link: https://t.co/xXMRaS4ejS

[Vinay @vinaygode]

https://t.co/NPDNd0AoqH

[How To AI @HowToAI_]

Yann LeCun was right the entire time. And generative AI might be a dead end.

For the last three years, the entire industry has been obsessed with building bigger LLMs. Trillions of parameters. Billions in compute.

The theory was simple: if you make the model big enough, it will eventually understand how the world works.

Yann LeCun said that was stupid.

He argued that generative AI is fundamentally inefficient.

When an AI predicts the next word, or generates the next pixel, it wastes massive amounts of compute on surface-level details.

It memorizes patterns instead of learning the actual physics of reality.

He proposed a different path: JEPA (Joint-Embedding Predictive Architecture).

Instead of forcing the AI to paint the world pixel by pixel, JEPA forces it to predict abstract concepts. It predicts what happens next in a compressed "thought space."

But for years, JEPA had a fatal flaw.

It suffered from "representation collapse."

Because the AI was allowed to simplify reality, it would cheat. It would simplify everything so much that a dog, a car, and a human all looked identical.

It learned nothing.

To fix it, engineers had to use insanely complex hacks, frozen encoders, and massive compute overheads.

Until today.

Researchers just dropped a paper called "LeWorldModel" (LeWM).

They completely solved the collapse problem.

They replaced the complex engineering hacks with a single, elegant mathematical regularizer.

It forces the AI's internal "thoughts" into a perfect Gaussian distribution.

The AI can no longer cheat. It is forced to understand the physical structure of reality to make its predictions.

The results completely rewrite the economics of AI.

LeWM didn't need a massive, centralized supercomputer.

It has just 15 million parameters.

It trains on a single, standard GPU in a few hours.

Yet it plans 48x faster than massive foundation world models. It intrinsically understands physics. It instantly detects impossible events.

We spent billions trying to force massive server farms to memorize the internet.

Now, a tiny model running locally on a single graphics card is actually learning how the real world works.

[Chroma @trychroma]

Introducing Chroma Context-1, a 20B parameter search agent.

> pushes the pareto frontier of agentic search

> order of magnitude faster

> order of magnitude cheaper

> Apache 2.0, open-source

[Vinay @vinaygode]

@NaveenSpark @clawzempic The song 🙂

[Vinay @vinaygode]

@zaraistastys Oh how true!

[Vinay @vinaygode]

@trashh_dev Crime don’t climb

[Vinay @vinaygode]

@dystopiabreaker Just keep in mind if you spin up too many polecats you’ll want an agent to manage them 🤣

[Vinay @vinaygode]

@rvivek Work hard now or never get the opportunity to work again

[Vinay @vinaygode]

Another Deepseek moment

[MiniMax (official) @MiniMax_AI]

Introducing M2.5, an open-source frontier model designed for real-world productivity.

- SOTA performance at coding (SWE-Bench Verified 80.2%), search (BrowseComp 76.3%), agentic tool-calling (BFCL 76.8%) & office work.

- Optimized for efficient execution, 37% faster at complex tasks.

- At $1 per hour with 100 tps, infinite scaling of long-horizon agents now economically possible

MiniMax Agent: https://t.co/aIzrFYcfUz
API: https://t.co/fHRdSV7BwZ
CodingPlan: https://t.co/FDhZBBjQrX

[Vinay @vinaygode]

@bindra_dhruv Open source and swap out the MIT license

[Vinay @vinaygode]

@shauseth Okay but is it small batch and ethically sourced

[Vinay @vinaygode]

Starting to dive into agent lightning. This could be a great unlock for making agents have better reasoning and improving tool use

https://t.co/M70581tF79

[Vinay @vinaygode]

@Marko_Jozef I hope all voice agents in the future can have an efficient no bs backdoor

[Vinay @vinaygode]

LayerZero is the chosen one

[a16z crypto @a16zcrypto]

https://t.co/aT37H26LMN

[tweet davidson @andyreed]

claude: want me to check on the subagents?

meanwhile the subagents:

[Vinay @vinaygode]

@_StanGirard Great find. What a gem

[Vinay @vinaygode]

@chddaniel @shipper_now time to go public

[Vinay @vinaygode]

@0xgaut feels like the early days of crypto

[Vinay @vinaygode]

@KingBootoshi that's going to be a spicy bill

[Vinay @vinaygode]

the entire clawhub ecosystem needs a rewrite. challenge accepted

[Daniel Lockyer @DanielLockyer]

malware found in the top downloaded skill on clawhub

and so it begins