chilang
2.7K posts
chilang
@chilang
Workshop your ideas into reality, in the Cloud and on your Desktop

We just released Gemma 4 — our most intelligent open models to date. Built from the same world-class research as Gemini 3, Gemma 4 brings breakthrough intelligence directly to your own hardware for advanced reasoning and agentic workflows. Released under a commercially permissive Apache 2.0 license so anyone can build powerful AI tools. 🧵↓
The World Cup 2026 field is officially set 🏆 All 48 teams are now locked in on wccal! Updated with the final qualifiers from this week. Also shipped a few new things: → Color-coded groups for quick scanning → Shareable filter permalinks (e.g., link straight to your team's matches) → AI assistant that knows the full schedule Add it to your calendar in one click, filter by team/group/venue, and you're set for the summer. wccal.com

The World Cup 2026 field is officially set 🏆 All 48 teams are now locked in on wccal! Updated with the final qualifiers from this week. Also shipped a few new things: → Color-coded groups for quick scanning → Shareable filter permalinks (e.g., link straight to your team's matches) → AI assistant that knows the full schedule Add it to your calendar in one click, filter by team/group/venue, and you're set for the summer. wccal.com

Something fun with one prompt Try it out 👇 Prompt + repo





I ran a 35-billion parameter AI agent on a $600 Mac mini. Specs: M4 Mac-Mini 16GB RAM The model doesn't fit in RAM. It pages from the SSD at 30 tokens/second. On NVIDIA, the same paging gives you 1.6 tok/s. Apple Silicon gives you 30. That's 18.6x faster. No cloud. No API keys. $0/month. Here's what it can do 🧵




It's Opening Day! The best day of the year. ⚾ Baseball has always been THE sport of numbers. But wOBA? FIP? WRC+? For years I'd nod along and quietly Google later. So I built StatDNA. An interactive encyclopedia of baseball analytics. Explore metrics with easy to understand explanations and examples, compare park factors across all 30 stadiums, and ask an AI to break down any stat line you paste in. Started as something I wanted for myself, but hopefully it’s helpful for anyone looking to understand these stats a bit better too (because honestly, they make the game even more fun). Dropping the link below.
It's Opening Day! The best day of the year. ⚾ Baseball has always been THE sport of numbers. But wOBA? FIP? WRC+? For years I'd nod along and quietly Google later. So I built StatDNA. An interactive encyclopedia of baseball analytics. Explore metrics with easy to understand explanations and examples, compare park factors across all 30 stadiums, and ask an AI to break down any stat line you paste in. Started as something I wanted for myself, but hopefully it’s helpful for anyone looking to understand these stats a bit better too (because honestly, they make the game even more fun). Dropping the link below.
To celebrate Workshop's launch, we just open sourced dbt-skillz. Your @getdbt project already contains the knowledge of your data stack. dbt-skillz compiles that context into a skill your agent can use. Built for Workshop, @claude_code, Codex, @cursor_ai, et al. Repo 🔗 below
