The problem with being a safety focused AI lab, is you're also a danger focused AI lab. I don't think being danger focused leads you to build inspiring things.

We really need some open source project to manage all the shims across the world. Like in Seattle the WSDOT API has live ferry locations but they never made a GTFS feed for, so i made my own shim for it. I feel like there needs to be some way to make the data access easier for developers.

As far as I can tell is these standards (MCP/MHS/etc) are just semi obvious tool inferfaces that Anthropic uses as training scenarios.

Surprised Amazon managed to fumble mechanical turk at the same time Mercor/Scale and all these other companies started hiring humans to do data labeling tasks.

I spent multiple hours every week in various risk management meetings one semester for our drone building student team. There was no risk management done, they just made it clear they would try and expell and sue us if we tested our drone.

Thanks! It was really cool to work a layer deeper in the stack

Direct link to the repo on github: https://github.com/jonready/vllm-ios

I wouldn’t include YouTube given how only Google is allowed to index it

I hope it will force institutions to simplify entitlements. Right now the institutions can pretend like their kafkaesque system is fine because nobody manages to navigate the maze.

A single 3090 will train qwen 0.8B just fine. While it’s not a very capable model any training technique you would want to master can be used to make real progress. And all the skills you need to learn how to do this can be learned watching Andrej Karpathy’s zero to hero series (shame he quit educational content and went to anthropic)