[SimianSci]

Anthropic is looking to IPO here soon. A key aspect of this is to prove profitability.

Shifting their focus from Training new models to instead serving inference, they would greatly reduce their spend. In fact this is something being reported on that they are already doing, which is the reason for their first ever profitable quarter.

Its awfully convenient that the company which has greatly reduced its spend on training is now asking for a slow down in this area.

[Theodores]

Honest question: Is anyone here looking to put their own money into the Anthropic, OpenAI or SpaceX IPOs?

Maybe it is my poverty mindset that is holding me back, however, I can't imagine becoming an investor in any of the AI 'startups'.

There are plenty of pundits able to advise others on where to put their money, and sometimes there is everyone and their dog advising you to get into Bitcoin, gold or some other scheme. With alt-coins there were lots of people saying that you should get in, and plenty of naysayers. Yet I am not hearing anyone that uses AI professionally try to convince others to get into the AI IPOs coming up. Maybe the overall economic situation precludes it.

Hence my question, is anyone here planning to put their own hard-earned money into Anthropic (or the other AI 'start ups')?

[isomorphic_duck]

I can’t imagining investing into these frontier labs for the simple reason that Open Source is very likely to catch up in a relatively short period of time. I don’t see how OpenAI/Anthropic could then continue to serve their models with such large inference margins.

[wnmurphy]

I'm considering Anthropic. I think they will be one of the survivors if/when the AI bubble bursts.

I was dubious about SpaceX (orbital data centers need to solve for extreme radiation and error-correction during training), but then I remembered that xAI is actively working on virtualizing white collar workers ("Macrohard").

In my opinion, this is the only TAM that justifies $1T in data center investment, because the consumer market for ChatGPT-style AI is saturated. There's a lot of enterprise TAM available for AI, but I think what these companies training frontier models are really after is selling a product that allows companies to eliminate the cost of white collar salaries.

[danny_codes]

I mean, my passive funds will be forced to buy a little bit I assume, given recent entry changes to indexes. So.. yes? I guess?

[sushisource]

I'll probably buy and sell on opening day. The hype train is worth making a quick trade on.

Long term? Way, way less interested.

[danny_codes]

Their model lead is tiny. If they cut training focus they'll be quickly overtaken, one imagines. Seems dicey, if any of the OSS players comes out with a better model.. well, there are a bunch of better harnesses than Claude code you can download.

This is a very undifferentiated, swappable product. Kind of like tissue paper in that respect

[malfist]

I mean, if they've consumed all of human knowledge. What's left for them to train on? This pivot isn't only because it's cheaper and a way to juice the numbers for an IPO, it's survival because they can't improve more.

[hasteg]

IIRC when they make a big enough architecture change to the model they will need to rerun pre training . So not like they’re feeding it more data (they will be but will be a drop in an s3 bucket compared to their dataset reserves) but rather training models with different architectures.

[applicative]

It did sound to me like they feel some sort of wall coming.