Our 206th episode with a summary and discussion of last week's big AI news!
Recorded on 04/07/2025
Editorial note: my startup just launched a public demo of what we’ve been working on!
Would appreciate if you go check it out over at Astrocade.com :)
Hosted by Andrey Kurenkov and Jeremie Harris.
Feel free to email us your questions and feedback at [email protected] and/or [email protected]
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In this episode:
Meta releases LlAMA-4, a series of advanced large language models, sparking debate on performance and release timing, with models featuring up to 2 trillion parameters for different configurations and applications.
Amazon's AGI Lab debuts NOVA Act, an AI agent for web browser control, boasting competitive benchmarking against OpenAI's and Anthropic's best agents.
OpenAI's image generation capabilities and ongoing financing developments, notably a $40 billion funding round led by SoftBank, highlight significant advancements and strategic shifts in the tech giant’s operations.
Timestamps + Links:
(00:00:00) Intro / Banter
Tools & Apps
(00:01:46) Meta releases Llama 4, a new crop of flagship AI models
(00:13:55) Amazon unveils Nova Act, an AI agent that can control a web browser
(00:17:06) Alibaba Preparing for Flagship AI Model Release as Soon as April
(00:17:59) Runway releases an impressive new video-generating AI model
(00:19:10) Adobe launches Premiere Pro’s generative AI video extender
(00:20:54) OpenAI prepares reasoning slider and memory update for ChatGPT users
Applications & Business
(00:21:28) Nvidia H20 Chips: $16 Billion Orders from ByteDance, Alibaba, and Tencent
(00:24:45) Elon Musk sells X for $33 billion to his own AI startup company xAI
(00:30:48) DeepMind is holding back release of AI research to give Google an edge
(00:36:04) Google-backed Isomorphic Labs raises $600m to advance AI drug discovery
Research & Advancements
(00:38:03) PaperBench: Evaluating AI's Ability to Replicate AI Research
(00:43:50) Crossing the Reward Bridge: Expanding RL with Verifiable Rewards Across Diverse Domains
(00:48:39) Inference-Time Scaling for Complex Tasks: Where We Stand and What Lies Ahead
(00:54:34) Overtrained Language Models Are Harder to Fine-Tune
Policy & Safety