Our 215th episode with a summary and discussion of last week's big AI news!
Recorded on 07/04/2025
Hosted by Andrey Kurenkov and Jeremie Harris.
Feel free to email us your questions and feedback at contact@lastweekinai.com and/or hello@gladstone.ai
In this episode:
Cloudflare's new AI data scraper blocking feature, its potential implications, and technical challenges
Meta's aggressive recruitment for its Super Intelligence Labs division is covered, highlighting key hires from OpenAI and other leaders in the field
Anthropic loses significant talent to Cursor, with details on their new economic futures program focusing on AI's impact on the labor market
Notable open-source AI model releases from Baidu and Tencent are also discussed, including their performance metrics and potential applications.
Timestamps + Links:
(00:00:11) Intro / Banter
(00:01:43) News Preview
Tools & Apps
(00:02:55) Cloudflare Introduces Default Blocking of A.I. Data Scrapers
(00:05:44) Runway is going to let people generate video games with AI
(00:16:23) No one likes meetings. They’re sending their AI note takers instead.
(00:18:08) Google launches Doppl, a new app that lets you visualize how an outfit might look on you
(00:19:14) Google's Imagen 4 text-to-image model promises 'significantly improved' boring images
Applications & Business
(00:22:18) Mark Zuckerberg announces his AI ‘superintelligence’ super-group
(00:29:35) Anthropic Revenue Hits $4 Billion Annual Pace as Competition With Cursor Intensifies
(00:35:10) As job losses loom, Anthropic launches program to track AI’s economic fallout
(00:38:04) OpenAI says it has no plan to use Google's in-house chip
(00:41:08) Nvidia stakes new startup that flips script on data center power
Projects & Open Source
(00:46:57) Baidu releases open source model family ERNIE 4.5
(01:00:11) GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning
(01:04:10) DiffuCoder: Understanding and Improving Masked Diffusion Models for Code Generation
Research & Advancements
(01:06:21) Wider or Deeper? Scaling LLM Inference-Time Compute with Adaptive Branching Tree Search
(01:13:07) The Automated LLM Speedrunning Benchmark: Reproducing NanoGPT Improvements
(01:21:37) Performance Prediction for Large Systems via Text-to-Text Regression
(01:25:38) Does Math Reasoning Improve General LLM Capabilities? Understanding Transferability of LLM Reasoning
(01:26:33) Correlated Errors in Large Language Models
Policy & Safety
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