Xuanhua Shi

Professor of Computer Science, Huazhong University of Science and Technology

[Jeff Dean @JeffDean]

@moderncpp7 @clu_cheng @NeurIPSConf @drfeifei @jiahuiyu @edchi I didn't see the talk, but the images I've seen of the slide seem quite offensive. Such generalizations should have no place in NeurIPS or anywhere else.

[Association for Computing Machinery @TheOfficialACM]

🏆 We're thrilled to announce the recipient of the 2023 #ACMTuringAward: Avi Wigderson! Wigderson is recognized for his foundational contributions to the theory of computation. Join us in celebrating his incredible achievements! Learn more here: https://t.co/UfEpOFgBN2 @the_IAS

[Torsten Hoefler 🇨🇭 @thoefler]

Are you wondering how to make you #SC24 @Supercomputing submission even better?

Check out the scientific benchmarking paper for parallel systems.

Twelve rules to improve the scientific quality of your #HPC paper.

https://t.co/Cz4HLFSFsi

[Xuanhua Shi @Xuanhua2]

😂

[Xavier Bresson @xbresson]

ICML Reviewer2

"The paper is well-structured and easy to follow" ⇒ Presentation: 1 poor

".. is a significant contribution" ⇒ Contribution: 2 fair

"Due to my limited time to review, I did not catch up with the most novel point in the paper" ⇒ Rating: 1 Very Strong Reject

😞

[Shruti @heyshrutimishra]

NVIDIA just released FREE online courses in AI.

Here are 9 courses you can't afford to miss:

[lingjiao chen @ChenLingjiao]

A surprising finding: a larger number of LLM calls can incur worse performance of compound AI systems! Why and what is the desired number of LLM calls? We initialize the study of scaling properties of compound AI systems both theoretically and empirically: https://t.co/MWmmgosENz

[lingjiao chen @ChenLingjiao]

Focusing on one-layer Voting Inference Systems, we find (i) that item difficulty plays an important role, and (ii) that predicting the scaling trend and optimal number of LLM calls is possible.

[Torsten Hoefler 🇨🇭 @thoefler]

Satoshi Matsuoka @ProfMatsuoka tells us how Supercomputing saved Japan billions of dollars in economic downturn during covid. Fugaku's ROI is 68-90 times!

The opportunity for EVE is similar or even bigger! Let's unite and reap it together combining #HPC and #AI.

[Xuanhua Shi @Xuanhua2]

@dingwen_tao Congratulations!

[Xuanhua Shi @Xuanhua2]

#ASPLOS GZKP Lightning Talk: Session 7B - 6 https://t.co/bXmjKzDGiX 来自 @YouTube

[Association for Computing Machinery @TheOfficialACM]

Congratulations to Bob Metcalfe, who receives 2022 ACM A.M. Turing Award for "the invention, standardization, and commercialization of Ethernet," which has become the dominant way of connecting computers to other devices, to each other & to the Internet: https://t.co/HV3dgCdcTz

[Lior Alexander @LiorOnAI]

OpenAI truly built a world-class engineering team.

The last 8 months:

Aug '22 → DALL·E
Nov '22 → ChatGPT
Sep'22 → Whisper
Dec '22 → Point·E
Feb '23 → ChatGPT Plus
March '23 → ChatGPT API
March '23 → GPT-4

[Mira Murati @miramurati]

Unveiling GPT-4 -- our large multimodal model that exhibits human-level performance on various professional and academic benchmarks. With iterative alignment and adversarial testing, it's our best-ever model on factuality, steerability, and safety.
https://t.co/rjsIYWTN3Y

[Abhishek Ekaanth @abhiarys]

I just published What are Proofs? What are Zero-knowledge proofs and what are the types of ZKP? https://t.co/yuz9OIERIQ

#zeroknowledge #interactiveproofs #noninteractiveproofs #zkp

[Mira Murati @miramurati]

Just made ChatGPT available on our API! Our incredible team of builders has delivered 10x cheaper model than our existing GPT-3.5 models, through system-wide optimizations, making it easier to power as many applications as possible.

https://t.co/dUSp7rLs1I

[ACM SIGOPS @ACMSIGOPS]

Our premiere conference for computer systems technology will now be held every year. https://t.co/pRYcYHeEaa

[Jean de Nyandwi @Jeande_d]

A Comprehensive Survey on Pretrained Foundation Models: A History from BERT to ChatGPT

A nice review of recent advances, current and future researches in pretrained foundation models in NLP, computer vision, graph learning, and other modalities.

https://t.co/GySvfMRrul

[Dawn Song @dawnsongtweets]

Our ZKP MOOC (https://t.co/HBdayPfIik) has been really exciting with ~3500 enrolled globally!
Today we're thrilled to announce a new ZKP/web3 hackathon, open to the public, March 1-May 2, virtual & in-person @UCBerkeley, with prizes up to $200K+!
Sign up: https://t.co/9CT75yNiQg

[Xuanhua Shi @Xuanhua2]

We just evaluate the NTT on 4090, it looks good! 2^26 is around 33ms.

[Xuanhua Shi @Xuanhua2]

We built a GPU Accelerated Zero-Knowledge Proof System. The paper has been accepted in ASPLOS'23 @ASPLOSConf , which is now available in the ACM Digital Library. https://t.co/A5I7lz7zKq

[Guillaume Lample @ NeurIPS 2024 @GuillaumeLample]

Today we release LLaMA, 4 foundation models ranging from 7B to 65B parameters.
LLaMA-13B outperforms OPT and GPT-3 175B on most benchmarks. LLaMA-65B is competitive with Chinchilla 70B and PaLM 540B.
The weights for all models are open and available at https://t.co/q51f2oPZlE
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