Listen "AI Companies Market Drop 💸 // Meta's Custom Chip Artemis 🚀 // Amazon's Shopping AI Rufus 🛍️"
Episode Synopsis
Major AI players like Microsoft, Google, AMD, and Nvidia took a hit after their latest earnings reports failed to impress investors.
Meta is rolling out a new custom AI chip called Artemis in their data centers this year, which will complement the Nvidia H100 chips they've acquired.
Amazon has announced an AI-based shopping assistant called Rufus, which uses generative artificial intelligence to help users search for products.
The papers discussed in this episode cover topics such as open language models, enhancing the Winograd Schema Challenge, and mitigating reward overfitting and overoptimization in RLHF.
Contact: [email protected]
Timestamps:
00:34 Introduction
01:37 AI companies lose $190 billion in market cap after Alphabet and Microsoft report
03:17 Exclusive: Meta to deploy in-house custom chips this year to power AI drive - memo
04:49 Amazon announces AI shopping assistant called Rufus
06:05 Fake sponsor
08:01 OLMo: Accelerating the Science of Language Models
09:22 WSC+: Enhancing The Winograd Schema Challenge Using Tree-of-Experts
11:15 Iterative Data Smoothing: Mitigating Reward Overfitting and Overoptimization in RLHF
12:58 Outro
Meta is rolling out a new custom AI chip called Artemis in their data centers this year, which will complement the Nvidia H100 chips they've acquired.
Amazon has announced an AI-based shopping assistant called Rufus, which uses generative artificial intelligence to help users search for products.
The papers discussed in this episode cover topics such as open language models, enhancing the Winograd Schema Challenge, and mitigating reward overfitting and overoptimization in RLHF.
Contact: [email protected]
Timestamps:
00:34 Introduction
01:37 AI companies lose $190 billion in market cap after Alphabet and Microsoft report
03:17 Exclusive: Meta to deploy in-house custom chips this year to power AI drive - memo
04:49 Amazon announces AI shopping assistant called Rufus
06:05 Fake sponsor
08:01 OLMo: Accelerating the Science of Language Models
09:22 WSC+: Enhancing The Winograd Schema Challenge Using Tree-of-Experts
11:15 Iterative Data Smoothing: Mitigating Reward Overfitting and Overoptimization in RLHF
12:58 Outro
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