Maintaining large-scale AI capacity at Meta

Meta is going hard into AI (both hardware and software), which is great to see. Something that&#x27;s not super obvious is what specific features of existing apps require AI, that is, how will Meta get return on investment?<p>Two uses I can think of are i) text and image content moderation on fb and instagram (won&#x27;t need as many human reviewers if bots are as&#x2F;more effective), and ii) chatbots for businesses (businesses could provide their business documentation to a meta LLM which could handle customer inquiries via messenger and whatsapp).<p>Anything else?

Even if this scale is massive and second-to-none, it’s funny how some issues are the same for all of us. In particular “Bad hosts are very bad” aka “a chain is only as strong as its weakest link” can happen with as little as a few (4) machines, and then ruin your day.

I’m old enough to remember when companies were eager to claim that their data centers (or some aspect) were finally “carbon neutral”.<p>Now, with the enormous data center growth for AI purposes, companies don’t even bother pretending that any of this is sustainable.<p>At best, they might delude themselves into believing that a glorified text autocomplete program will magically solve the world’s problems, including the unsustainability of the machines running the program.

So I was pondering, NVidia quarterly datacenter revenue is around 18.4 billion. Meaning that the raw cost input to the AI industry is somewhere around 14-24 billion dollars per year post depreciation. This is against known revenues of ~3.8 Billion at OpenAI and ~800 Million at Anthropic. Based on reported revenue at cohere of 20 MM - I think it&#x27;s a fair assumption that the only other material revenue in the industry is in the applications side either at megacaps or smaller startups targeting various back office tasks.<p>One could make a bearish claim on NVidia, that their revenue&#x2F;valuation is unsustainable unless the AI industry grows 100x over the next few years.

Maintenance trains, interesting takeaway from this. There&#x27;s a trolley problem joke in there somewhere.

We have gone full circle back to building the HPC supercomputer after quarter century of clusters.

Sounds like this opsplanner software has a fair bit of autonomy

They make people into slaves. I’d be extremely happy when Facebook gets shutdown.