break ambitious goals into verifiable steps

We now appear to be entering the era of token rationing.

A key through line of all these tasks is that they are time consuming

By handling the specific invalid behavior instead of rejecting the entire trajectory, this approach helps prevent the training instability and model collapse that can happen when rollouts are abruptly stopped.

As a limited-time promotion through the end of September, off-peak usage is billed at 1×. (Peak hours are 14:00–18:00 UTC+8 (Beijing Time) daily).

Uber capped employee AI spending after blowing through its budget in four months.

This dynamic UI management is the future of software value : the harness to control the interface/ensure it's correct & the knowledge management to rationalize all the AI products over time

The enterprise version of that is I don't want a CRM unless at least two other giant enterprises have successfully used that CRM for six months. [...] You want solutions that are proven to work before you take a risk on them.

Putting a leaderboard in place was always going to incentivize much more AI usage.

Responsible AI is not keeping pace with AI capability, with safety benchmarks lagging and incidents rising sharply.

Mercor, which provides data to AI labs for training, became one of the fastest-growing companies in history before losing four terabytes of data to hackers last week.

And botched the schedule the day after grand opening, scrambling to email employees asking someone to come in.

The first thing you need to do is identify which people are going to be your leaders that help you pull this off. This is going to be a 12 month death march and you need to find out who is willing to go through the pain with you. There's good news, though: somewhere in your org, there are ~five people who are going to deliver you 100x the amount of value you ever thought possible.

select known-vulnerable dependency versions 50% more often than humans.