living in uncertainty

each of us is wrong sometimes. when a prediction you made turns out to be false, it's a good exercise to back-propagate it to your world model (what did i miss?) and then do a forward pass to understand what other implications this discovery has (what else must be true that i thought is false). usually it's not a big deal. often it is some wrong assumption/bias which impacts few things. you update your world model and move on

the ai of today was in the realm of fantasy a few years ago. i tried to find what we missed, but all plausible theories explaining llms suggest that we missed something very fundamental, and which has a lot of profound implications. among all world model updates i consider, the delta is large (the rabbit hole is deep), but also i'm not certain which one is the most accurate. just as an example, i am not aware of a theory that would explain why llms are getting good at coding but wont explain why they will eventually become good at everything else.

moreover it is dynamic. last year the talk was about prompt engineering. this year it's agents. i expect it to be different next year, and in general i expect things to continue to evolve. more capabilities will be developed, more work automated and more population waking up

it can be challenging to live like that: we like certainty. you might be used to have some life plan that you follow (say you are a prospective student who chooses your major). any plan has to assume that things that were true during planning will stay true. ok, maybe instead of a static plan you have a more dynamic strategy, essentially a function that accepts the current state and returns suggested actions. well, that function is still compressed knowledge of what works and what doesn't, but that knowledge might also get stale as the world changes

certainty is a luxury. i expect it to continue decreasing. i'm not even sure it will be coming back in our lifetimes, so I'd suggest to start getting used to a world where you can't be very confident in the increasing number of things (this is particularly hard for very smart people who are right most of the time and got used to that)

the only advice i have is gain some humility, be open minded and get ready to constantly adapt to the world changing under our feet

I appreciate being mentioned in top-30 AI people in Uzbekistan. Thanks.
https://yuksalish.org/uz/news_detail/835

Anthropic's first postmortem about the model being dumber, with a level of detail that we usually don't share
https://www.anthropic.com/engineering/a-postmortem-of-three-recent-issues

what an idiot. i mean, the fact that he is an idiot is not new, but this is the new level
https://x.com/whitehouse/status/1969147079478989220?s=46

OpenAI released a new eval that measures performance on economically valuable, real-world tasks across 44 occupations.

https://openai.com/index/gdpval/

great example of why i didn't even consider applying for openai. think of implications in a country with a racist president

https://x.com/gabrielpeterss4/status/1973120058907041902?s=46

You can now connect Slack to Claude. It can search your workspace channels, DMs, and files/gdocs to provide context for deep work.

You can also connect Claude app to slack, e.g. ask something in the app and claude can read your slack, search info there, etc.

Video below

https://x.com/claudeai/status/1973445694305468597?s=46

🦀 i recommend spending a year with Rust

i don't think i can explain all the reasons why do that in a way that's both short and clear. most likely i'll lose the reader in the middle of the post before i'd get to the point. it is only after some first-hand prolonged experience of learning the Rust way you start getting it.

just trust me on this 😎 go ahead and do yourself a favor

fair warning: first 6mo can be painful, but we have LLMs now that help a lot

haiku 4.5 (just released) is as smart as sonnet 4.0, but it's 2x faster and 3x cheaper. i've been using it in claude code for a while (primarily because of speed) and i can recommend it. i use it more often than sonnet 4.5 and definitely more than opus

https://www.anthropic.com/news/claude-haiku-4-5

Addressing seemingly common misunderstanding.

- Sonnet 4.5 is smarter than Opus 4.1.
- Haiku 4.5 nearly as smart than Sonnet 4.0

how come? Scaling laws suggest that the intelligence of models grows with scale (aka the bitter lesson). We increase training scale all the time, so it is not surprising that a newer model is more intelligent than an older model.

Besides, smaller models are:
- much faster, so you are getting more done
- cheaper, so your quota lasts longer

per aspera ad astra!

Anthropic + NVIDIA + Microsoft

video: https://x.com/anthropicai/status/1990797993281536420?s=46

i started feeling the agi with this model

if you are building frontend, enable the frontend plugin
https://x.com/trq212/status/1993786552233939042?s=46

RIP coding

I started coding approx 26-28 years ago. There were many months that i wrote code every day. It was my main hobby. I no longer write code and I don't think I will.

I still produce a lot of code, but i don't type it myself. I mostly direct agent(s) and review their code

It was fun 🫗🫡