Live data from Hacker News

Why AI Infrastructure Startups Are Insanely Hard to Build

nextword.substack.com

11–20 of 190 posts

Re: Why AI Infrastructure Startups Are Insanely Hard to Build

#11

Way 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…

I’m also sort of curious as to how much of a market research they’ve done if they’re trying to compete with Azure and AWS.

Even before the recent LLM rush took off, AI was a thing. In the city of Copenhagen there was a project to digitalise a few million case files (which is 10-100 documents per case file), and how it was done was basically with an intermediary company who knew the training and a cooperation with Microsoft. Yes, I’m dumping down the complexity of it all, but once the training period of half a year was over, Azure made a lot (and I mean a lot) of infrastructure available for not a lot of money and the process completed in a week or so. Since it had to happen and because it was a PoC the same project was also done by real humans. This was the “actual” project and every time deadline and whatnot the AI project had came from how long it would take X humans to do it. I can’t recall how many X was, but it was enough to meet the legal deadline for when these case files had to be digitised and sorted correctly.

The human project was the result, and then the AI PoC was later used as a lesson on whether it could be done this way or not. It can, it was more accurate and not more expensive.

Anyway… I’m not sure who would’ve been capable of competing with Azure. (Outside the usual suspects). Maybe a company of Hetzner could? But you would need someone who can offer you a massive amount of computing on demand, and the only companies which are going to have that are big vendors.

Maybe it’s different with LLMs because the requirement is a continuous thing rather than something you need for a short period of time?

Re: Why AI Infrastructure Startups Are Insanely Hard to Build

#12
post #3

Good article, but what is the alternative? What can you build today as a software engineer that can have impact? Nothing seems to come close to AI / AI infra, even of its hard / risky / a moving landscape.

It's fine to be in AI.

My takeaway from the article is instead of being a Gen AI startup be a Gen AI startup for a specific use case.

Re: Why AI Infrastructure Startups Are Insanely Hard to Build

#13
post #3

Good article, but what is the alternative? What can you build today as a software engineer that can have impact? Nothing seems to come close to AI / AI infra, even of its hard / risky / a moving landscape.

Slightly different take than some of the siblings: you can still just build this stuff. If your goal is impact, maybe the best place to do it will be at a cloud vendor or other big corp. If your goal is actually just a big VC exit, then maybe not.

If your product is something that can be ripped off in 3 months, then it probably wasn’t going to have a long term impact anyway.

Re: Why AI Infrastructure Startups Are Insanely Hard to Build

#15
post #11

Way 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…

I’m also sort of curious as to how much of a market research they’ve done if they’re trying to compete with Azure and AWS. Even before the recent LLM rush took off, AI was a thing. In the city of Copenhagen there was a project to digitalise a few million case files (which is 10-100 documents per case file), and how it was done was basically with an intermediary company who knew the training and a cooperation with Mic…

[deleted]

Re: Why AI Infrastructure Startups Are Insanely Hard to Build

#17
post #9
post #4

Earlier quoted context omitted.

Everything we build has some kind of impact. At risk of getting philosophical, I’d ask yourself what your goals actually are if you feel only AI can have the impact you desire .

Not sure why this is down voted, that is the key question. Impact means different things to people. Could be: 1. Building a sustainable business and making decent money 2. Building a market leader and making ludicrous amounts of money 3. Advancing the state of the art in technology 4. Helping people with their little daily struggles 5. Solving pressing problems humanity is facing Or many other things I suppose. Now i…

The motive is to get acquired in most cases. It’s obvious and starts to make sense when you see startup that has no feasible monetisation strategy on the horizon, yet they exist and get funding. They’re betting on building infra to be hopefully used in large corp and this is their demo/PoC.

Re: Why AI Infrastructure Startups Are Insanely Hard to Build

#18
Infra 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 provide actual, real, tangible value. Making shovels works for huge companies like Nvidia or Intel, but it won't work for you. It's sad to see so much capital funneled in frameworks upon frameworks upon frameworks instead of fresh new ideas that could revolutionize the way we interact with our devices. I know it's a bit of a meme, but I'd rather see more Rabbit R1 and less LangChain.

Even OpenAI doesn't really have a product. Just throwing data at a bunch of video cards isn't value-generating in itself. We need a Dropbox or a Slack or an Instagram: something people love that makes their life easier or better.

Re: Why AI Infrastructure Startups Are Insanely Hard to Build

#19
post #3

Good article, but what is the alternative? What can you build today as a software engineer that can have impact? Nothing seems to come close to AI / AI infra, even of its hard / risky / a moving landscape.

All the same stuff, to be honest. If AI is set to replace human work, well we have had a cheap human labour market for decades and yet we still need software. An LLM can't replace a business itself, which is made up of niche processes, direction and purpose, which we sometimes codify into a SaaS. We'll still need to do all that even if AI replaces some of the human parts of the business.

Re: Why AI Infrastructure Startups Are Insanely Hard to Build

#20
The title is true. But, the arguments don't hold water for me. 12 years ago, I started a big data company. It looked similar for big data companies when Cloudera raised almost $1B in 2014. Too many people building data warehouses, especially in the cloud. I exited. Who knew that Snowflake and Databricks would emerge against the incumbents. Similarly, there will be winners in the AI infrastructure space. To win, you need to focus on your customers and delight them. Narrowing focus makes a lot of sense. Don't pay attention to the doom and gloom, or you'll never do a startup.
Post reply on HN