Pranjal Srivastava

28 posts

Pranjal Srivastava

Pranjal Srivastava

@pranjalks

Working on Efficient ML!

Katılım Haziran 2023
360 Takip Edilen7 Takipçiler
Pranjal Srivastava
Pranjal Srivastava@pranjalks·
Would be fun to see Kapil Dev's iconic 175 runs innings from the 1983 World Cup come to life! #Google #Cricket
Google@Google

For over 60 years, @Pele’s legendary "lost goal" at Rua Javari lived in the memories of those who were there. In close collaboration with historians, experts and Pelé’s family, we used @GoogleDeepMind technology to bring this iconic moment to life. ⚽️ See the film ↓

English
0
0
2
23
Peter Crouch
Peter Crouch@petercrouch·
If anyone gets hit by lightning it’s me isn’t it
Peter Crouch tweet media
English
1.5K
11.2K
267.8K
11.1M
Pranjal Srivastava
Pranjal Srivastava@pranjalks·
Happy to see my name in the Google I/O 2026 announcement! 🎉 The Google Tensor ML SDK has officially graduated to Beta — bringing a unified LiteRT workflow and 100+ models to the Pixel 10 TPU.
English
1
0
1
84
Pranjal Srivastava retweetledi
Swaroop Nath
Swaroop Nath@swaroopnath6·
Agree with this view. We stand at a cusp of discovering several (beyond code) use cases of AI. Such a motto necessitates foundational research. I have a nice anecdote from Google, along the lines of what George Dantzig did in his Berkeley stat class. Mental blocks are unnecessary
Manish Gupta@ManishGuptaMG1

Dear @NandanNilekani You initiated a huge technology based revolution in India by starting with a strong "foundation" (aadhar), why not with AI? Once again, I respectfully, but strongly, disagree. India should be aiming to do both. Otherwise, it won't be a true leader.

English
0
1
3
413
Pranjal Srivastava
Pranjal Srivastava@pranjalks·
@gabriberton Yeah, that was also surprising to see. It also leads to an added benefit of reduced training computation, as the heavy Encoder only has to process 25% of the input image. Overall, it is a win-win.
English
0
0
1
39
Pranjal Srivastava
Pranjal Srivastava@pranjalks·
@gabriberton I was just reading this paper the other day. Fascinating how MAE solves the information density gap between pixels and words. In vision, pixels are redundant, hence 75% mask ratio is applied to force the model to learn semantic objects and not just interpolate features.
English
2
0
5
930
Gabriele Berton
Gabriele Berton@gabriberton·
Thread on a staple of modern computer vision: Masked AutoEncoder (MAE) This 2021 FAIR paper proposes a new self-supervised technique to pretrain ViTs. It is one of the first ViT-specific SSL technique, which showed the world the flexibility of the transformer [1/6] 🧵
Gabriele Berton tweet media
English
6
34
338
25.1K
Pranjal Srivastava
Pranjal Srivastava@pranjalks·
@gabriberton To give more context, the only loss function they use is the normalized MSE loss over the Masked patches.
English
1
0
4
759
Seth Karten
Seth Karten@sethkarten·
@pranjalks I think there is sufficient interest, but pending sponsorship to make it a reality. Also the potential competition will be slightly different based on current challenges in the field.
English
1
0
1
53
Pranjal Srivastava
Pranjal Srivastava@pranjalks·
@polymagelabs Looks cool. Added to my reading list. Also, great to see a deeptech startup in the domain of ML Compilers from India!
English
0
0
1
114
PolyMage Labs
PolyMage Labs@polymagelabs·
Finally, here's the paper on PolyBlocks describing how fully code-generating compilers for AI chips can be built! This is the culmination of multiple years of R&D and engineering. There is now enough reusable infrastructure in our toolkit to quickly build high-performing PyTorch/JAX compilers for new chips, no matter how weird or unique their capabilities are, and without relying on any "kernel" libraries or manual model optimization or porting. The paper isn't exhaustive, but it provides details on the key parts, the design choices, and why they are powerful. arxiv.org/abs/2603.06731
English
2
20
88
5.7K
Vuk Rosić 武克
Vuk Rosić 武克@VukRosic99·
What should our LLM research goal be outside of working for OpenAI, DeepMind, DeepSeek etc? Should it be "Train GPT-5 level LLM for $100"? Does it make sense to research LLMs if we are not working at an LLM company, since we are not gonna make better LLMs than them? Should LLM research focus on helping big companies make better LLMs? Should we bail LLMs completely, work on JEPA or something else? How do we discover path forward, just doing research and seeing where it leads us?
English
11
0
41
6.4K
Sahil Chopra
Sahil Chopra@schopra909·
Turns out better VAE reconstruction quality can make your diffusion model worse. We learned this the hard way over 4 months. Writeup + open-source Image-Video VAE model. linum.ai/field-notes/va…
Sahil Chopra tweet media
English
3
1
16
3.1K
Abhishek Maiti
Abhishek Maiti@o_v_shake·
If ai summit is crowded (im not there), log on to workatafrontierlab.com so that the next time, you can get a key note speaker entry.
English
1
0
10
387
Pranjal Srivastava retweetledi
Deep-ML
Deep-ML@real_deep_ml·
What paper should we make a question on next?
English
3
0
3
719
Pranjal Srivastava
Pranjal Srivastava@pranjalks·
@willccbb Are the remote jobs only for US based folks or whether folks residing in the APAC region will also be considered?
English
1
0
0
404
Sayak Paul
Sayak Paul@RisingSayak·
I like to capture raw logs. One of the commands I overuse when running stuff from the console is: ``` <COMMAND_TO_RUN> 2>&1 | tee log.txt ``` Captures everything I need and stores it in `log.txt`. It's my default.
English
1
1
12
2.5K