After high school, I ended up working odd jobs, e.g., as a night shift cleaner at a fast-food restaurant. One especially nasty night, I decided that I had to at least try to get more out of my life and began self-studying coding every free minute I had, up to 20 hrs/day. 1/5.

I don't think Twitter will go down soon, mostly because I believe the (ex) eng and infra teams did a good job building resilient systems. But it's unlikely I'll be posting from now on. To anyone stumbling on my profile seeking advice on AI, feel free to reach out via email.

Truly visionary business moves this week. I wonder if more people will finally realize the emperor has no clothes.

The unsatisfying reality is that the day-to-day issues researchers run into are usually either at the ML framework level or at the ML compiler level, and neither would be fully addressed by a language with a cleaner API for array computing.

However, those switches have led to access to new major features or a significant boost in productivity and I just don't see opportunities to gain either in alternatives today. Python isn't great but all it has to be is *good enough* at serving as a DSL for ML compilers.

Some of it transfers but there's no way around stalling progress while general experience (incl. dealing with language quirks) is reacquired, tooling is redone, use cases validated, etc. Switches like this have happened in the past, actually several times in the last decade.

To start, I think Prof. Ringer is certainly correct in that Python is ill-suited for the task and there are potentially better alternatives. However, I also believe that despite the shortcomings, Python is *good enough*, and the cumulative cost of switching is just not worth it.

A bit late to the party but this subject comes up fairly often and I have some thoughts as I spend most of my time at the boundary of Python (JAX) and C++ (XLA), and in the past have been a (very minor) contributor to DeepMind's effort to speed up Python:

I feel like that blinking white guy meme coming back from a period of minimal social media to a Twitter full of stable diffusion / midjourney generated artwork. Genuinely in awe of the pace of progress.

Hot? take: we might reach (some form of) AGI before we reach SAE J3016 L5 driving automation.

Prompt engineering might be a legitimate profession in the future.

Amazing news! TPUv4's were instrumental for some of the recent large-scale efforts at DeepMind such as Chinchilla and Flamingo.

RT @jalayrac: It is great to see the excitement about 🦩! As shown in different examples during the last few days, interacting with 🦩 has be….

- Find fields of interest, do literature review.- Replicate interesting papers, showcase on GitHub.- Think of ideas to follow up the papers.- Reach out to paper authors, discuss your ideas.- Implement your ideas, showcase on GitHub.- Iterate to success.

Incomplete path to research engineering:.- Study calculus, lin. algebra, prob. theory.- Intro courses e.g. - Advanced courses e.g. - Join communities e.g.

If you want to contribute to AI research, consider joining industry labs as SWE or RE. PhD / RS is not the only way!.

People underestimate how much AI research is bottlenecked by engineering.

To be clear, of course we're not quite there yet. I had to lead the dialogue, correct rug <> scale, and explicitly ask about the joke. Andrej's "challenge" greatly influenced my outlook on AI and it was really exciting for me to see Flamingo handle it at all. I'll take "cute" :).

10 yrs ago @karpathy wrote a blog post on the outlook of AI: in which he describes how difficult it would be for an AI to understand a given photo, concluding "we are very, very far and this depresses me.".Today, our Flamingo steps up to the challenge.

People underestimate how much AI research is still driven by the hardware + compiler stack.

A group of Flamingos is called “flamboyance” which could be an apt description for the family of vision-language models I’m thrilled to see out in the wild! I believe using large pre-trained models in creative ways will be key and hope our work is a step in the right direction.