Title should be more about stats rather than lessons.
Lessons from YC AI Startups
41–50 of 98 posts
Re: Lessons from YC AI Startups
#42Most of my dev work is in logistics for a very staid industry which doesn't even make this list, that would have a difficult time finding a use for LLMs, because most of the day-to-day jobs involve manual labor. That said, I've been asked "how can AI help us" quite a bit (the unsaid ending to that sentence being, "...help us lay off workers"). Just as a thought experiment, I've considered the pros and cons of automat…
It really sounds like AI is a bubble if people ask how they can cram AI into their workflow rather than coming up with real problems they want to automate.
I suspect that a very large number of applications that could've been "normal" programs are going to be AI'd with no clear pros but many cons.
Re: Lessons from YC AI Startups
#43Anyone know what the Energy, Materials Science, and Security ones were? All other categories I can generally intuit how AI is being used, especially LLMs, but not so those three categories. Edit: here they are: Energy: - https://www.ycombinator.com/companies/elyos-energy - https://www.ycombinator.com/companies/line-build - https://www.ycombinator.com/companies/helios-climate-industr... - https://www.ycombinator.com/c…
Previously worked on the intersection of ML and Material Science (specifically batteries). I think the link to osium-ai[0] tells the story pretty well. Material science is plagued by long, expensive, exploration phases - even in places you wouldn't expect them. ML ends up being really good at cutting the expense of these phases by >50% by making you just a little smarter in your exploration. [0] https://www.ycombinat…
But this isn't new, isn't it?
I remember, e.g, Italy and Brazil had projects more than ten years ago where they used some sort of machine learning to find hidden historical buildings under terrain or jungle by looking at patterns in satellite/aerial image and it was successful in finding archeological sites in both countries.
Re: Lessons from YC AI Startups
#44Anyone have the full list of startups?
at the yc website. their twitter page also posts the latest ones
Re: Lessons from YC AI Startups
#45Are there any examples if successful exits or AI companies making it into the black yet? In general, not just YC
I feel that really there are no more place for "AI startup" as there is for "database startup" - there are some exceptions, but it's hard to compete with open source and large corporations treating AI tech as loss leader. Of course there are exceptions.
I work on AI startup that with squinted eyes could be described "AI for pricing the insurance policy". As the company grows, we really add a lot of more non-AI pieces. A lot more goes into the frontend that keeps getting non-AI features. In a closed industry you can't get clean dataset for everything, so lots of heuristics and domain knowledge goes into some pieces of equation. Custom APIs and integrations for customers, etc.
My point is, any "AI startup" by the time of exit won't be AI startup, but "problem X startup", where AI was initially used to address X. It will have a lot more non-AI pieces than AI. Rare exceptions of AI base technology will get commoditized pretty soon anyway.
Re: Lessons from YC AI Startups
#46Something I've noticed going through founder's LinkedIn pages is that it seems that entrepreneurs seem to be significantly more attractive than the average person. I assume a partial causative factor could be that the number of positive impressions you make on people with influence correlates with success of your startup, and one's capacity to make positive interpersonal impressions correlates with physical attractiv…
I don't believe that there's a well defined thing called "physical attractiveness". It's quite possible that "looks like an entrepreneur" is part of your definition of "attractive" in this instance, in which case your observation rather boils down to "people look like what they are", which is still an interesting observation, of course, and one might want to ask how/why people look like what they are. I think I once…
My definition of attractive generally means harmonious facial features (nothing too big or too small, positioned visibly weirdly), clear skin, symmetry, sexual dimorphism, class 1 bite with good teeth well aligned with the face and forward-grown jaw structure. Id say there is a specific "looks like an entrepreneur" element to it where these people tend to have a somewhat friendly, vaguely supercilious, clean cut, non-distinctive look. However a preponderance of the former objectively attractive features is hard to ignore compared to the people you see on the street, at Starbucks, at the Post Office, etc. I do also agree grooming and the effects of a good diet/exercise routine which correlates with the strata of educated middle upper class people who apply to YC is a factor too.
Re: Lessons from YC AI Startups
#47Odd that the first two categories of AI startups were AI infrastructure. Reminds me of blockchain to some degree. Would have expected to see more vertically focused solution on the top 4 list. Eg, transportation, oil & gas, agriculture, etc… all huge markets.
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Re: Lessons from YC AI Startups
#48Something I've noticed going through founder's LinkedIn pages is that it seems that entrepreneurs seem to be significantly more attractive than the average person. I assume a partial causative factor could be that the number of positive impressions you make on people with influence correlates with success of your startup, and one's capacity to make positive interpersonal impressions correlates with physical attractiv…
A) professional headshots make a big difference
B) the people promoting themselves the most on LinkedIn also tend to care the most about their image (including looks)
C) there’s a large component of sales for any startup. There’s plenty of ugly yet successful entrepreneurs, but looks do seem to matter.
Re: Lessons from YC AI Startups
#49Odd that the first two categories of AI startups were AI infrastructure. Reminds me of blockchain to some degree. Would have expected to see more vertically focused solution on the top 4 list. Eg, transportation, oil & gas, agriculture, etc… all huge markets.
Wait a couple of years and they will appear
Re: Lessons from YC AI Startups
#50Most of my dev work is in logistics for a very staid industry which doesn't even make this list, that would have a difficult time finding a use for LLMs, because most of the day-to-day jobs involve manual labor. That said, I've been asked "how can AI help us" quite a bit (the unsaid ending to that sentence being, "...help us lay off workers"). Just as a thought experiment, I've considered the pros and cons of automat…
It really sounds like AI is a bubble if people ask how they can cram AI into their workflow rather than coming up with real problems they want to automate. I suspect that a very large number of applications that could've been "normal" programs are going to be AI'd with no clear pros but many cons.
Yup. Well said.
As for the cons, a nice way to put it would be that adding a black box into the workflow makes everything after it undefined behavior. And there's no shortage of C-Suite guys with itchy trigger feet.