In this episode, we explore the Chinese AI ecosystem with 'L-squared,' an anonymous tech worker based in Beijing. We discuss major players, model quality, public engagement, regulation, and the US 'chip ban.'
Testing Chinese models: Yi-34B-Chat (made by Kai-Fu Lee's team 01.AI) can be tried out via Replicate or Hugging Face. You can also use the ChatGLM playground and Baidu's ERNIE without a Chinese SIM card.
Benchmarking models: SuperCLUE is one of the most prominent benchmarks - the latest results are on GitHub and the paper explaining the methodology is here.
Regulation: Explainer from Matt Sheehan; piece on how genAI regs are affecting Chinese companies.
US-China competition: Jeff Ding's work on the diffusion deficit in S&T; Bloomberg piece on Huawei's semiconductor development efforts.
Staying up to date: Sign up to alerts from CSET's Scout tool; subscribe to Concordia AI's AI safety in China newsletter.
A 2016 profile on Microsoft Research Asia by Wang Jingjing, covered in Jeff Ding's ChinAI newsletter.
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The Brave search API can be used to assemble a data set to train your AI models and help with retrieval augmentation at the time of inference. All while remaining affordable with developer first pricing, integrating the Brave search API into your workflow translates to more ethical data sourcing and more human representative data sets. Try the Brave search API for free for up to 2000 queries per month at https://bit.ly/BraveTCR
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(00:00) Introduction
(07:24) China's AI Ecosystem
(13:40) Public AI Engagement
(17:33) Sponsors : OCI / Omneky
(18:50) AI Tools Comparison
(35:37) Sponsors : Brave / Squad / Plumb
(39:14) AI Regulatory Maze
(51:02) AI Performance, Censorship
(55:28) Chinese AI Regulations
(01:04:37) Tech, Research Role
(01:12:11) Global AI Ecosystem
(01:23:22) Cultural AI Perspectives
(01:29:14) AI Safety, Cooperation
In this episode, Nathan sits down with Katja Grace, Cofounder and Lead Researcher at AI Impacts. They discuss the survey Katja and team conducted including over 2,700+ AI researchers, the methodology, and the results’ implications for the industry as a whole.
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Nathan sits down with Pablo Arredondo. They discuss the evolution of legal research, how GPT-4 has changed legal practices, security and privacy in AI driven legal services, and more.
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