Does this logic also apply to industry-specific "AI Infra?," where the APIs are wrapping a service that solves a domain-specific problem using AI, rather than general purpose infra technology? And provides those APIs to other businesses within that industry?
Why AI Infrastructure Startups Are Insanely Hard to Build
151–160 of 190 posts
Re: Why AI Infrastructure Startups Are Insanely Hard to Build
#152Earlier quoted context omitted.
AI is a long term trend, next is more products on top of AI. Just like the internet. Biotech and space will both be trends but slower and less bubbly because the cost to play is high, though the returns are possibly huge in both.
> AI is a long term trend, next is more products on top of AI. Just like the internet. This is legitimately just the same damn hype train the tech sector is constantly attempting to create. Now AI is the next internet. Before that it was the metaverse. Before that it was NFTs. Before that it was cryptocurrency. Before that it was quantum. Before that it was VR. Before that it was AR. None of those were the revolution…
Neither of those things you listed were mainstream trends. If you can not distinguish between fads and major trends that is your problem.
Internet, Mobile, Cloud and now AI are technology trends with mainstream buy in from the biggest companies in the world.
Re: Why AI Infrastructure Startups Are Insanely Hard to Build
#153Earlier quoted context omitted.
Put a number on it. How much value of this will they capture from you personally (we'll assume, very very charitably by the sound of it, that you represent an "average" user of AI products) when this market matures? Exactly how much will your employer pay for a meeting summarizer? $10/mo a seat, $20/mo a seat, $50/mo a seat? Could the product sustain a 5x, 10x, 50x price hike that is going to have to happen to recoup…
Agreed. Even if right now this seems like stuff companies want to throw money at for novelty/FOMO related reasons, I think eventually reality ought to catch up. Probably an unpopular opinion, but I think the most efficient companies of the future will tackle the ironies of automation effectively: Carefully designing semi automation that keeps humans in the loop in a way that maximises their value - as opposed to just…
Re: Why AI Infrastructure Startups Are Insanely Hard to Build
#154Earlier quoted context omitted.
The S&P 500 is a list of the largest and most profitable public companies. It's hard to do better than the most successful businesses. Most other indices and hedge funds don't outperform the S&P 500. Most private equity shops don't. Most real estate investors don't. So it shouldn't come as a surprise that venture capital doesn't. Most startups don't get big. How many startups founded in the past decade have become hu…
It's hard to do better than the most successful businesses is not a statement that makes sense from the investor's perspective. The price of an investment is based on the expected profitability of a company, an investment in a barely profitable company, if priced correctly, should yield returns at least equal to good companies like Apple, Google, and Microsoft, as the investment would be discounted to compensate for…
Re: Why AI Infrastructure Startups Are Insanely Hard to Build
#155Way too many founders don't understand the impact of competing with cloud vendors. Almost all enterprises have pre-committed budgets for cloud which means unless your product is FOSS it's going to be hard to convince someone to bet their business on it. Especially given that in this fundraising environment there is a 95% chance they won't be around in a year or two anyway. It's going to be a brutal few years especial…
> Almost all enterprises have pre-committed budgets for cloud which means unless your product is FOSS it's going to be hard to convince someone to bet their business on it. This isn't a death knell. 1. If you get into the marketplace, enterprises can spend their commit against you. 2. A few million in ARR is ~nothing to a hyperscale cloud, but meaningful to most startups. If you find the right positioning, you can ge…
Re: Why AI Infrastructure Startups Are Insanely Hard to Build
#156Infra has always been a tarpit idea. Google didn't start out as an "infra" company, and neither did Amazon or Facebook. In fact, the few "infra companies" that did start back then (companies like Godaddy) are minuscule compared to the aforementioned. VC pouring money in LLM infra is legitimately crazy to me. It's clear as day that there will be winners of this AI cycle, but, as always, they will be companies that pro…
> VC pouring money in LLM infra is legitimately crazy to me. VC business model is throwing money at the wall and seeing what sticks. They love congratulating themselves on how smart they are but at the end of the day their overall returns trail S&P 500. They are salespeople and their job is to sell themselves to private capital on how smart and connected they are.
Re: Why AI Infrastructure Startups Are Insanely Hard to Build
#157Earlier quoted context omitted.
> Even OpenAI doesn't really have a product. They are making a ton of money off subscriptions.
I'm skeptical that $20 / month is enough to run OpenAI and be profitable. I would bet the real number is an order of magnitude higher.
Re: Why AI Infrastructure Startups Are Insanely Hard to Build
#158Earlier quoted context omitted.
Sounds like you need a consultancy and not a startup to solve your problem.
maybe that's really where the business here is.. working through a whole bunch of custom data-sets and trying to generalise from there. It'll be hard to generalise all of it, but I'm sure there'll be pockets of functionality that can be shared across more than a single data-set. And maybe that's at the core of the issue here, namely that this service in its current form doesn't scale like b2c internet tech
I think we will go back to tools combined with humans to solve at least some of them. So it's services and software.
Re: Why AI Infrastructure Startups Are Insanely Hard to Build
#159Earlier quoted context omitted.
> VC pouring money in LLM infra is legitimately crazy to me. VC business model is throwing money at the wall and seeing what sticks. They love congratulating themselves on how smart they are but at the end of the day their overall returns trail S&P 500. They are salespeople and their job is to sell themselves to private capital on how smart and connected they are.
People allocating capital in VC funds are trying to diversify a very large portfolio, not just picking a high IRR asset. VC is very uncorrelated to S&P 500 performance as most of the best VC vintages were during public market downturns.
Re: Why AI Infrastructure Startups Are Insanely Hard to Build
#160Earlier quoted context omitted.
Author here. I think the tarpit extends to most chatgpt wrappers as well, which is why I called out pivoting prematurely to application layer is a futile exercise.
So AI infrastructure startups are tarpits and so are the wrappers? Is it just tarpits all the way down?