Perhaps it depends on which tech director he was chatting with. Google's internal coding models are better than Claude, because they are trained on Google's own codebase, and they are being used extensively. But there may be large pockets of lameness within Google?
GENERATIVE AI
-
80s Expert Knowledge Input vs 2020s Data Labeling Efficiency
By
–
In the 80s they paid experts to input their knowledge into AI. In the 2020s we do the same, except it’s much less efficient because the input is in the form of labeling data.
-
PipSqueak 2 AI Agent Update Enhances Memory and Expression
By
–
PipSqueak 2 just entered the chat ･:*｡･:*三ᘛ⁐̤ᕐᐷ better memory, more expressive, and less repetitive.
PSQ2 lets your Character stay in character more reliably c.ai+ members will have early access starting today, with all free users getting access in early May!
go -
Multiple AI Realities: Access Shapes Business Workflows
By
–
There are multiple realities of AI right now. And what you have access to drastically changes your workflows, trust in AI, and ability to adapt to the future. Here’s the briefest state of the AI world for business professionals (not engineers) Free AI – you use free
-
Anthropic Criticized for Irresponsible AI Development Practices
By
–
Funny how the most irresponsible AI company is Anthropic.
-
HSImul3R: Physics-Realistic Virtual Human-Scene Interactions
By
–
What if virtual humans could interact with their environments with perfect physical realism?
— 机器之心 JIQIZHIXIN (@jiqizhixin) 14 avril 2026
Enter HSImul3R!
This novel reconstruction technique embeds real-world physics directly into the process, generating human-scene interactions that are seamlessly "simulation-ready."… pic.twitter.com/PNCZLDOfLhWhat if virtual humans could interact with their environments with perfect physical realism? Enter HSImul3R! This novel reconstruction technique embeds real-world physics directly into the process, generating human-scene interactions that are seamlessly "simulation-ready."
-
TinyFish AI: 87% Token Reduction, 2x Task Completion
By
–
4/ The workflow also feels way cleaner. The output goes to the filesystem instead of just filling up your context window, and TinyFish says it uses 87% fewer tokens than MCP per operation, with 2x higher task completion on more complex multi-step tasks.
-
Qwen 3.5’s overthinking helps infer intent, boosting Gemma 4’s performance
By
–
Qwen 3.5 tends to overthink, which ironically helps it better infer intent Gemma 4 is the opposite, you have to spell everything out (probably guardrails) Had Qwen rewrite my prompts, then used those on both models Gemma’s performance jumped noticeably