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Capitalism, at work. Wherever there is a cost, there will be attempts made at cost efficiency. Google understands that hiring designers or artists is expensive, and they want to offer a cheaper, more effective alternative so that they can capture the market.

In a coffee shop this morning I saw a lady drawing tulips with a paper and pencil. It was beautiful, and I let her know... But as I walked away I felt sad that I don't feel that when browsing online anymore- because I remember how impressive it used to feel to see an epic render, or an oil painting, etc... I've been turned cynical.


I guarantee if there's even a 0.1% chance of this architecture eventually outperforming traditional ones, then Zuckerberg et al are already eating the cost and have teams spinning up experiments doing just that.


That's not true. The AI industry appears to play a game of follow the leader copying other companies and major researchers. There's all kinds of good ideas we never see applied by big companies. So, it's not safe to assume they tried them all and they didn't work.

In fact, we've sometimes seen new companies show up with models based on research big companies didn't use, the new models are useful or better in some way, and people use them or big companies acquire them. I'd say that's proof big companies miss a lot of good ideas internally.


Not every company is investigating every direction. Like, it's clear that Google is investing a lot in embodiment and multimodal understanding, but Anthropic barely cares about either. Across the field though?

I think it's fairly safe to say that every remotely promising thing that showed up in the papers was tried at some big lab at least once. If it showed good results, they'd pick it up.


Absolutely agreed, but we may not even hear about it as Meta has made it clear they're not necessarily committed to the open source first policy at this point.


Replacing faulty nodes or equipment in space seems totally reasonable... It's not like getting faulty drives replaced in my datacenter racks don't already take weeks/months...


It's a hoop to jump through, but I'd recommend checking out Apple's container/containerization services which help accomplish just that.

https://github.com/apple/containerization/


You're likely still targeting Nvidia's stack for LLMs and Linux's containers on MacOS won't help you there.


Anecdotally, I would have thrown "127,271 BTC to USD" into Google. I didn't mind it.


This is also somewhat highlighted in Google's paper "Borg, Omega, and Kubernetes" which they published in 2016.

https://static.googleusercontent.com/media/research.google.c...


HRW would cover the simple case, but they needed way more-- e.g. per-request balancing, zone affinity, live health checks, spillover, ramp-ups, etc. Once you need all that dynamic behavior, plain hashing just doesn’t cut it IMO. A custom client-side + discovery setup makes more sense.


Interesting. In a thought process while editing a PDF, Claude disclosed the folder hierarchy for it's "skills". I didn't know this was available to us:

> Reading the PDF skill documentation to create the resume PDF

> Here are the files and directories up to 2 levels deep in /mnt/skills/public/pdf, excluding hidden items and node_modules:


The world is full of useful shapes! No reason that math shouldn't :)


Somewhere between 85% and 90% of all countries have some sort of mandated severance pay in the event of a layoff.

A small percentage of countries also mandate severance even if the employee is fired (with cause).


US doesn't seem to be such a country though?


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