Manpreet Singh

Always Learning, Always Improving!

#PQC #PQCEnthusiast

[Manpreet Singh @creatorManpreet]

Remember....

[Ricardo Sánchez @desde_el_sur]

¿Qué sucede cuando el campo magnético del Sol se retuerce hasta su límite absoluto?
Aquí vemos un filamento solar retorcido o cuerda de flujo magnético flotando sobre la fotosfera, una estructura colosal formada por plasma denso y relativamente frío atrapado en líneas 👇

[Manpreet Singh @creatorManpreet]

@sourceryy @ScottWu46 Raising seed money from the likes of Peter Thiel is the biggest advantage one can get in the market. Of course, execution matters a lot but having solid ecosystem behind you is equally important and necessary.

[Manpreet Singh @creatorManpreet]

September 5th Progress - Longer distance but maintained pace.

[Manpreet Singh @creatorManpreet]

August 29th Progress - Pace baby pace! I can definitely do little better than this. I need to squeeze it.

[Manpreet Singh @creatorManpreet]

@a16z I would like to deploy this in space and specifically in our solar system to study and see beautiful realities of space.

[a16z @a16z]

World Labs co-founders Fei-Fei Li, Justin Johnson, Ben Mildenhall, and a16z's Martin Casado on Atlas, a world model for spatial intelligence:

LLMs are built on next token prediction. Video models are built on next frame prediction. Atlas is built on new view prediction, and it's the first model to unify pixel generation and pixel reconstruction, two problems computer vision has kept in separate tracks for half a century.

The practical result is a 50 to 100x reduction in what it takes to digitally capture a 3D representation of a space. Previously, you needed 100 to 300 photos of a single room. Atlas can work from just three.

In this conversation, they get into the slow motion shot from The Matrix that took hundreds of cameras and now takes three iPhones, the overnight Slack message that made them bet the company in five seconds, why robotics is bottlenecked on data rather than chips, and the case that new view prediction is AI-complete.

00:00 Intro
01:50 The Matrix slow motion scene now takes three iPhones
02:48 Why new view prediction is the primitive
07:10 Unifying generation and reconstruction
11:15 Gaussian splats became the bottleneck
14:17 Dense capture used to mean 300 photos
17:30 Why reconstruction needs generation to fill the gaps
18:44 The LLM lesson image models missed
23:39 The video that made them go all in
28:04 3D design is 95% revisions
30:50 The problem in robotics is data, not chips
32:48 Why a robot policy can't be trained like an image model
34:44 When the simulator becomes the planner
36:45 Frozen time required footage full of movement
40:57 Why new view prediction is AI-complete
42:43 Nature gave animals eyes but not trees

YouTube: https://t.co/AvR59efen0

@drfeifei @jcjohnss @BenMildenhall @theworldlabs @martin_casado

[Manpreet Singh @creatorManpreet]

@ishanr07 @ycombinator Ishan - I could be the only one telling you that you will never regret decision to go back to college and study. Wish you all the best and do tons of research if you get an opportunity.

[Manpreet Singh @creatorManpreet]

@rdominguezibar Most apt video. I have been scared of this happening to me but finally started reaching out to VCs and people in my network. Thank you.

[Manpreet Singh @creatorManpreet]

@apartovi Canoo was trying to do this but they went bankrupt. Building couple of prototypes is easy but building an actual scalable production plant is extremely difficult. Tesla almost went bankrupt as well. Rivian and Lucid are facing operational expenses challenges as well.

[Anthropic @AnthropicAI]

Checking that a major mathematical proof is correct can take years. Formalization—converting the mathematical reasoning into a form computer proof assistants like Lean can verify—can help.

Last month, Claude completed the first formalized proof of Fermat’s Last Theorem, one of the most famous theorems of all time. This was a project experts thought would take many years. It is the largest Lean proof ever written.

Fermat’s Last Theorem was first proven in 1995 by Sir Andrew Wiles, more than 350 years after it was conjectured. Our proof, which totals over 13 million lines of code, provides machine verification. More importantly, it proves over 29,000 other theorems that the proof requires, across many areas of math which had never before been formalized.

We see this as a major step in the long process of firming up the core of mathematical knowledge, building on work from three centuries of mathematicians and hundreds of contributors to Lean and Mathlib. We are optimistic that AI-assisted verification of mathematical proofs will help reduce the burden of refereeing mathematics in an era where more proofs are being produced than ever before.

You can read about the process on our Science Blog: https://t.co/ryYnDEAU6J

And see the complete proof on GitHub: https://t.co/wlYMXYnofz

[Manpreet Singh @creatorManpreet]

Here we go!

[penlu @penlume]

4397328654844826923795068102505872571721883526553349659561256924505973939597593482272505698004801207988043088656411102133523080581 divides RSA-260

[Manpreet Singh @creatorManpreet]

@coryalthoff Talk about bad leadership, Cory.

[Manpreet Singh @creatorManpreet]

Not forking existing open source projects and building complex engineering tools from scratch is a massive undertaking. It can even amaze an AI and you can get deep appreciation from the AI.

[Manpreet Singh @creatorManpreet]

@Paulfruitful_ @StephNass Great question! I know lot of founders from other countries apply for YC and a16zspeedrun. Once, they are selected, then these accelerators help with immigration as well. I like a16Zspeedrun program(personal opinion). Check out @andrewchen as well.

https://t.co/Drqsk2Acw4

[OpenAI @OpenAI]

This is GPT-6 Astra.

Anything you can do on a computer, Astra can do for you. Fast.

[Manpreet Singh @creatorManpreet]

@Paulfruitful_ @StephNass Yes. Just look at the number of immigrant founders who have found success in raising the money with US VCs.

[Manpreet Singh @creatorManpreet]

Flat organization is what we need!

[David Senra @davidsenra]

“IBM was 80% of the market cap of the entire tech industry. It was a level of scale and importance nobody else had. The founder was convicted of antitrust crimes *before* he started IBM. Then he monopolized the mainframe business and they convicted him again. He’s a double dipper.”

@pmarca tells the unparalleled history of IBM:

[Manpreet Singh @creatorManpreet]

@Molson_Hart Congratulations, Molson!

[Manpreet Singh @creatorManpreet]

@Molson_Hart @jacob_posel I was about to ask this question.

[Manpreet Singh @creatorManpreet]

Keep Improving!

[Manpreet Singh @creatorManpreet]

@rdominguezibar Got 14 slides in my pitch deck. Very close to the sweet spot!