@tinystride@shortdiv You both probably know this but @pidotdev has a great html export feature I use pretty regularly for this exact use case. I’ve also played around with backing up and *restoring* the raw session jsonl files. Works a treat.
🎙️ New Episode of State of Agentic Coding with @bentlegen and me is out. This time with @GeoffreyHuntley as guest.
- Code mode and self modifying harnesses
- @dhh's rails keynote
and a lot of other things
@izerop143 Agreed except the rust part. Languages matter less now than before imo. You can now pick the language for the problem at hand which is incredible.
@burkelibbey Allow unfree is in every configuration.nix I have. Also flakes can kick rocks imo.
But yeah this is why I tell people “I use nixos, you shouldn’t” 😆
@wesbos Not exactly what you’re after but maybe it sparks an idea: https://t.co/reW3uQGGAm
It lets me visually select a portion of my screen that I can share in google meet / zoom whatever.
recommended reading, with the caveat that i think the article goes too hard on bend 2.
the kernel: you often only understand a problem by experiencing the journey, i.e. building a solution for it.
if you hand that journey off to an agent, you will get something. but not necessarily something good, or even correct.
https://t.co/ss3aIYHbHV
It’s unreal how poorly the “AI labs” communicate and how high on their own supply they are. Never forget Anthropic employs a psychiatrist…for LLMs 🙈
This on the other is clear, sensible, and contains no hysterics about human extinction.
Last month I wrote about how we can build a positive and safe future for everyone: https://t.co/eoLGVY8yad
Every lab has the responsibility and incentive to move at the pace required to train its models safely, and the ability to take its own actions to ensure that happens.
The reality is:
- People won't want to use agents that are misaligned with them and that don't do what they ask, so labs have a strong natural incentive to make their models more aligned.
There is a lot of debate about slowing progress on capabilities until alignment catches up. My view is that trust and alignment are quickly becoming the most important capabilities that will differentiate agents and models. Any lab that doesn't focus on alignment will fall behind.
- Labs face significant liability if their models cause harm, so they have a strong incentive to prevent this as well.
Meta delayed shipping Muse for several months to focus on safety and security. We didn't call for everyone else to do this before we would. We just did it as part of our day-to-day work because it was clearly the right thing for people and for us. I'm proud of the security foundations we've built.
- Engaging independent evaluators and advisors is industry best practice. MSL already does this today in several areas because it helps produce better work. Other labs can just do this too. In general, it would be helpful for there to be a larger and more diverse ecosystem of evaluators.
- Committing the significant majority of compute towards serving people rather than racing towards recursive self-improvement is one of the best ways to ensure we develop this technology safely. Meta has made this commitment and other labs can do this as well.
I believe the key to building a positive future for everyone is maintaining the right balance of power. This is within our power to do.