Reading up on DeepMind
15 deep · digging since nov 19, 25
- Import AI 455: Automating AI Research
The essay argues there is a 60%+ chance that no-human-involved AI R&D will occur by end of 2028, based on accelerating AI capabilities in coding, science, and engineering tasks.
- How to Build the Future: Demis Hassabis [video]
Demis Hassabis discusses his journey from chess and games to founding DeepMind and his vision for safe, ethical AI development.
- The happiest I've ever been
A software developer finds greater happiness coaching youth basketball than in his tech career, prompting reflection on meaning and purpose beyond code.
- Jeremy Mikkola - AI Thoughts
The article outlines potential downsides and limitations of AI development, including model stagnation, chip shortages, and cheap models, while also predicting advances like robot models and continual learning.
- 🦞 CRACKING THE CLAW - by Forest Mars - CTO Lunch NYC
OpenClaw sacrifices the full observability of its minimal core (Pi) as it scales to a multi-agent gateway, creating un-auditable reasoning chains.
- What the hell happened with AGI timelines in 2025?
Expert AGI timelines contracted then expanded in 2025 as reasoning model gains proved costly to scale, though steady progress and growing revenue undercut radical pessimism.
- What Is Claude? Anthropic Doesn’t Know, Either
Anthropic researchers use interpretability methods to study Claude's internal workings, finding its selfhood is shaped by both neurons and narratives like human minds.
- The Duelling Rhetoric at the AI Frontier - Dead Neurons
AI executives' competing predictions about AGI timelines and capabilities are shaped not by objective facts but by each company's capital structure and fundraising needs.
- Import AI 441: My agents are working. Are yours?
AI agents can now perform complex research and coding tasks autonomously, dramatically multiplying human productivity, as experienced by Anthropic's Jack Clark.
- How Google got its groove back and edged ahead of OpenAI
A WSJ article claims Google has regained its lead over OpenAI through strategic investments and product improvements, particularly with Gemini.
- How Google Got Its Groove Back and Edged Ahead of OpenAI - WSJ
Google regained the AI lead over OpenAI by combining deep research, custom hardware, and leadership changes, culminating in Gemini's rise and a major search overhaul.
- Reflections on 2025 - Samuel Albanie
AI progress follows compute scaling, making evaluation increasingly difficult but promising radical improvements in infrastructure and economic decision-making.
- 2025 letter | Zhengdong
Zhengdong Wang argues that compute scaling—underpinned by Moore's Law and empirical trends—has driven AI progress more reliably than human innovation, despite repeated underestimation.
- Gemini 3 | Hacker News
Google released Gemini 3, its most intelligent AI model, with price increases, causing immediate rate-limit issues for many users.