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Why AI Infrastructure Startups Are Insanely Hard to Build

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Re: Why AI Infrastructure Startups Are Insanely Hard to Build

#161

Post by marcosdumay »

dvt wrote: post #33
siquick wrote: post #27

Earlier quoted context omitted.

> We need a Dropbox or a Slack or an Instagram: something people love that makes their life easier or better. People seem to not mind ChatGPT or Claude and safe to say that a very large majority of AI products are using one of the APIs of those companies.

In my humble opinion, a chat interface (API or not) does not a product make. Not to mention that Llama is free and competitive with both (same with Mistral, heck the 7B model works great on my RTX 3080). If you started a company that blew up because you made a badass product (and let's say you used ChatGPT under the hood), you would just eventually train and deploy your own model because an LLM is not a product .

> an LLM is not a product

I imagine you meant to say that LLMs are comoditized.

Getting the correct words here is important, as you can see by all the people disagreeing on the literal interpretation of your post.

And yeah. LLMs have got the fastest transition from highly innovative singular product to plain commodity I've ever seen or read about. BSD licensed software libraries do not move that quickly. They were mostly not even adopted yet, and have a huge barrier to entry, what makes it much more of a feat.

Re: Why AI Infrastructure Startups Are Insanely Hard to Build

#162

Post by ToucanLoucan »

rapsey wrote: post #152
ToucanLoucan wrote: post #146

Earlier quoted context omitted.

> 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…

> 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. Neither of those things you listed were mainstream trends. If you can not distinguish between fads and major trends th…

> If you can not distinguish between fads and major trends that is your problem.

You're distinguishing based on hindsight. It's mainstream if it succeeds and if it doesn't, it was a fad. How much did Zuckerburg put into Facebook's metaverse projects? I believe it was $46 billion. Then there was Decentraland too, those were as mainstream as it got. You had tons of internet-famous people cashing in for hundreds of thousands of dollars just for selling their original copies of reddit memes. How is that not at least somewhat mainstream?

I have zero doubt whatsoever that after the AI bubble lets go, I'll be having this same damn conversation with someone else and they'll be saying AI was a fad. That's my entire point.

Re: Why AI Infrastructure Startups Are Insanely Hard to Build

#163

Post by devoutsalsa »

eropple wrote: post #154
staticman2 wrote: post #132

Earlier quoted context omitted.

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…

That's getting into perfectly-spherical-cow territory, though. Investors aren't logical and neither are founders, and there's a real chance that an investor-fair deal isn't going to get any bites. The BATNA for most founders who don't secure funding is "go get a job that pays a lot of money"; while most VC investment is lopsided in the investor's favor through other means (equity preferences etc.), not landing deals…

One could argue that illogical investing is called speculation or gambling.

Re: Why AI Infrastructure Startups Are Insanely Hard to Build

#164

Post by gopher2000 »

belter wrote: post #82
dvt wrote: post #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 pro…

> We need a Dropbox or a Slack or an Instagram: something people love that makes their life easier or better. None of those three make my life better or easier: Dropbox -> We drop your data directly on S3 but give you worst security... Slack -> Being able to navigate our messy interface is an IQ test in itself... Instagram -> Only makes your life better if you have bikini posts to share....

Many people clearly love them and have found great utility using them. Not sure what point you're trying to make - that you're different?

Re: Why AI Infrastructure Startups Are Insanely Hard to Build

#165

Post by marcosdumay »

mlsu wrote: post #29
jdross wrote: post #21

Earlier quoted context omitted.

personally? - writing and refactoring code. probably 50 times a day now - improving documentation across the company - summarizing meetings automatically with follow ups - drafting most legal work before a lawyer edits (saved 70% on legal bills) - entity extraction and data cleanup for my users

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…

I'd say that if your team needs a meeting summarizer, your team has a meeting problem.

It's a clutch that will help you cope with the problem. But the real value is on fixing the actual issue.

Re: Why AI Infrastructure Startups Are Insanely Hard to Build

#166

Post by rapsey »

ToucanLoucan wrote: post #162
rapsey wrote: post #152

Earlier quoted context omitted.

> 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. Neither of those things you listed were mainstream trends. If you can not distinguish between fads and major trends th…

> If you can not distinguish between fads and major trends that is your problem. You're distinguishing based on hindsight. It's mainstream if it succeeds and if it doesn't, it was a fad. How much did Zuckerburg put into Facebook's metaverse projects? I believe it was $46 billion. Then there was Decentraland too, those were as mainstream as it got. You had tons of internet-famous people cashing in for hundreds of thou…

Only zuck was metaverse obsessed. Decentraland I've never heard of it, so it was not mainstream at all. NFTs were never mainstream. All of your examples are bad.

AI has buy in from the entire tech sector. Just like the cloud, mobile and internet did.

Re: Why AI Infrastructure Startups Are Insanely Hard to Build

#167

Post by fragmede »

marcosdumay wrote: post #165
mlsu wrote: post #29

Earlier 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…

I'd say that if your team needs a meeting summarizer, your team has a meeting problem. It's a clutch that will help you cope with the problem. But the real value is on fixing the actual issue.

I'd say if you're not using a meeting summarizer, you're wasting someone's time by having them write up notes. if you're not writing up notes, you're wasting someone else's time recapping the meeting for them. meeting notes are a 1 (meeting):many relationship for conveying information as to what was discussed. how else do you go back and see what the one person on the storage team talked to your the person on your team who left last week about so you can go into the next meeting with them prepared?

Re: Why AI Infrastructure Startups Are Insanely Hard to Build

#168

Post by morgante »

golly_ned wrote: post #155
morgante wrote: post #43

Earlier quoted context omitted.

> 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…

Hyperscale cloud has stringent security and compliance requirements, and within hyperscale cloud, it's institutionally difficult to lobby for spending on a startup. I spent about six years in hyperscale cloud and never saw a case where we spent a few million on a startup.

You seem to have misunderstood, I'm not referring to the hyperscaler spending money themselves.

If you don't think any ISVs are making millions through the marketplace you're simply mistaken. I worked at Google Cloud and personally know at least one startup that made the majority of their revenue through cloud partnerships.

Re: Why AI Infrastructure Startups Are Insanely Hard to Build

#169

Post by mlsu »

Art9681 wrote: post #149
mlsu wrote: post #10

Earlier quoted context omitted.

I would almost invert that statement. Sorry if this comes off ranty, but what exactly are people doing in the "AI space" currently that isn't "undifferentiated spam/chatbot" being sold to non-techies who heard about AI on NPR? What are real people using "AI" for that is so insanely valuable today? How much "company Y: same product with a chat window, sparks emoji" do we all need before this thing levels out and we al…

What do you consider "AI"? Because machine learning models have been deployed in enterprise systems for years. Video processing, security, data labeling, sentiment analysis. The sexiest one I can think of in recent memory is nVidia DLSS.

Broadly, what marketing is saying is “AI.” There is huge value being created with deep learning today on internal systems. Recommenders, machine translation, computational photography… it is huge, improves people's lives, drives revenue.

None of that is marketed as "AI." It's just a thing the computer does. The single most valuable application of deep learning so far (content recommenders) is a cultural phenomenon, but it’s not referred to as “AI” but rather “the algorithm.”

Re: Why AI Infrastructure Startups Are Insanely Hard to Build

#170

Post by marcosdumay »

fragmede wrote: post #167
marcosdumay wrote: post #165

Earlier quoted context omitted.

I'd say that if your team needs a meeting summarizer, your team has a meeting problem. It's a clutch that will help you cope with the problem. But the real value is on fixing the actual issue.

I'd say if you're not using a meeting summarizer, you're wasting someone's time by having them write up notes. if you're not writing up notes, you're wasting someone else's time recapping the meeting for them. meeting notes are a 1 (meeting):many relationship for conveying information as to what was discussed. how else do you go back and see what the one person on the storage team talked to your the person on your te…

If your meeting produces "notes", and those are relevant for people that were not in it, you are doing it wrong.

If your meeting is aimed at producing "general understanding", it's already a dangerous one, and the understanding should go to the correct documentation (what is best done during the meeting). Otherwise, it should produce "focused understanding" between a few people and with immediate application.

If all you take from it is notes, well, I'm really sure that your team won't go digging through meetings notes every time they need to learn about some new context. Meeting notes are useful for CYA only, and if people feel safe they'll be filled directly at /dev/null.

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