6 ms·

AI startups raised $6.9B in Q1 2020

67 points by noelceta 6y ago

thereyougo 6y ago
I expected to see a list of the startup names and how much they raised.
say_it_as_it_is 6y ago
What percentage of these "AI" startups do you think are doing no more than traditional automation with technology? Applying deep learning to do no more than what can be done with more accessible technology is like using Haskell on steroids, ensuring that no more than a few people will ever be able to maintain it.
- parkaboy 6y ago
  Pretty sure it's mainly platforms. https://hbr.org/2020/03/navigating-the-new-landscape-of-ai-platforms https://hbr.org/2020/03/navigating-the-new-landscape-of-ai-p... I've personally been seeing several pop up for helping with training+deployment for edge-oriented applications like Edge Impulse and Latent AI.
  - boltzmannbrain 6y ago
    Latent Sciences?? https://latentsci.com/ https://latentsci.com/
    - parkaboy 6y ago
      Were you referring to when I brought up Latent AI? If so, this is them: https://latentai.com/ https://latentai.com/
boltzmannbrain 6y ago
1. Many startups claiming AI are simply doing things with data; research shows two-fifths have no AI programs in their products [1]. 2. Round-closing announcements trail the actual closing by several months. Not to mention the actual raising and diligence takes months (even more so for larger/later rounds). Thus the $ reported here does not factor in covid19 and the current economic crisis, as implied. [1] https://www.ft.com/content/21b19010-3e9f-11e9-b896-fe36ec32aece https://www.ft.com/content/21b19010-3e9f-11e9-b896-fe36ec32a...
- axegon_ 6y ago
  I've spent an unhealthy amount of time at presentations, conferences, seminars and meetups. With that, on your first point, I'm more inclined to believe somewhere around 90% have absolutely no "AI" or "ML" for that matter in their products. And a large fraction of those who do have re-used existing open source solutions without digging a lot into them. De omnibus dubitandum est, of course, but this is the impression I get.
  - rjdagost 6y ago
    Your suspicion is largely correct, in my experience. I've worked as a consultant on a number of different AI / ML projects for start-ups. Most aren't doing anything all that new or groundbreaking from an ML point of view. Their real innovation is usually more about applying ML to industries / areas where it hasn't been used much before. But that doesn't get the investor dollars flowing in, so the founders try to make it seem like they have some radical new ML breakthrough. And in recent times, it has worked.
    - axegon_ 6y ago
      > And in recent times, it has worked. This is what __REALLY__ bugs me. Personally I'd love to see money poured into actual R&D rather than people abusing the "ML" and "AI" acronyms. Investors don't care about your R&D at all and commonly see it as a huge risk factor. Which it is of course. A semi-working prototype has a much better chance of succeeding so they stick to that. But as a consequence many people(myself included) are not even bothering with pitching anything to anyone and invest their own money, time, resources and savings into it. Blocking? Yes. Painful? Absolutely. Slow? Incredibly. I'm sure the next AI winter is around the corner, if it isn't here already: The virus outbreak might be the catalyst that triggers(or has triggered) it, given the staggering amount of people going full "I have AI which will provide a cure, vaccine and time travel to go back in time and warn the world, just gimme cash". I doubt anyone would deliver on any of those promises(and that's me being optimistic). But the crisis will likely push a lot of investors to pour millions into the empty promises that have a few buzzwords thrown in. I hope I'm wrong.
xiaolingxiao 6y ago
Is there a break down of percentage allocated from seed, series A, B, ... all the way down to F rounds?
lorey 6y ago
What's the value of this link over the original one? Original: https://venturebeat.com/2020/04/14/ai-startups-raised-6-9-billion-in-q1-2020-a-record-setting-pace-before-coronavirus/ https://venturebeat.com/2020/04/14/ai-startups-raised-6-9-bi...
te_chris 6y ago
https://a16z.com/2020/02/16/the-new-business-of-ai-and-how-its-different-from-traditional-software/ https://a16z.com/2020/02/16/the-new-business-of-ai-and-how-i... a very good take. Most AI startups are struggling to scale because models are hard to scale and generalize compared to SaaS. There'll be some fortunes made for sure, but we're still very early in building out these businesses and mostly these seem to be VC's who are (were?) desperate for "deep-tech" portfolio items to make them sound "bleeding-edge" at CogX, Davos, that thing in Aspen, etc.
- motohagiography 6y ago
  Seconded on this article. I shout from the rooftops to anyone who will listen that for ML, "the confusion matrix is the product," which summarizes much of what they say. The only thing I add to that adage now is that a meaningful product is a weighted function of Relationships, Data, and Expertise. Most ML companies have one, funded ones have two, and profitable ones have the right balance of three. Funding an ML company that isn't 85th percentile on at least two is dumb.
yahyaheee 6y ago
This is an insane amount of funding when you look at the projected revenue for machine learning over the next couple years. Maybe those projections are wrong, and I certainly love all the energy in this space, but it feels like a lot of investors are going to get burned.
barrenko 6y ago
"Anonymous Indians"
- barrenko 6y ago
  Was not trying to be racist, it's just a Twitter term for fake AI startups (started by one Indian man).
- nindalf 6y ago
  Wrong thread?
tkyjonathan 6y ago
Almost none of the company leaders or even VCs fully understand what AI even is or does. They just like to hear thats its there. If you don't have some AI in your company, you won't get investors.
- kavalg 6y ago
  Is it really that bad? I thought investors care more about business model and growth potential.
  - developerdylan 6y ago
    It isn't THAT bad. Investors definitely care more about model and growth potential. But you will certainly run into those who ask "How are you integrating AI into your platform?" without any real idea about what that means.
brenden2 6y ago
I was hoping the bubble had burst by now, but it sounds like it might not be there yet.
xiaolingxiao 6y ago
The key bit of information from this (https://venturebeat.com/2020/04/14/ai-startups-raised-6-9-billion-in-q1-2020-a-record-setting-pace-before-coronavirus/ https://venturebeat.com/2020/04/14/ai-startups-raised-6-9-bi...) is that "capital flows disproportionally into large late-state deals." I would read this as a lagging indicator of how "hot" the field is. Most of the companies have found their "niche" and identified the actual problems that need to be solved; like other commentators have said, these problems may only be tangentially related to ML models themselves. These companies are currently scaling up and locking themselves into the market. Given how long the sales cycle is and how sticky it may be in enterprise, this means now is not a great time to start a company just doing "AI".
correlator 6y ago
Incentives are really messed up here. Tacking the letters "AI" on the end of your company name will increase it's multiple. It will force your engineers to call their rules engine "AI" when on calls with customers. It's really unfortunate.

67 points by noelceta 6y ago

I expected to see a list of the startup names and how much they raised.

What percentage of these "AI" startups do you think are doing no more than traditional automation with technology? Applying deep learning to do no more than what can be done with more accessible technology is like using Haskell on steroids, ensuring that no more than a few people will ever be able to maintain it.

parkaboy 6y ago
Pretty sure it's mainly platforms. https://hbr.org/2020/03/navigating-the-new-landscape-of-ai-platforms https://hbr.org/2020/03/navigating-the-new-landscape-of-ai-p... I've personally been seeing several pop up for helping with training+deployment for edge-oriented applications like Edge Impulse and Latent AI.
- boltzmannbrain 6y ago
  Latent Sciences?? https://latentsci.com/ https://latentsci.com/
  - parkaboy 6y ago
    Were you referring to when I brought up Latent AI? If so, this is them: https://latentai.com/ https://latentai.com/

boltzmannbrain 6y ago

1. Many startups claiming AI are simply doing things with data; research shows two-fifths have no AI programs in their products [1]. 2. Round-closing announcements trail the actual closing by several months. Not to mention the actual raising and diligence takes months (even more so for larger/later rounds). Thus the $ reported here does not factor in covid19 and the current economic crisis, as implied. [1] https://www.ft.com/content/21b19010-3e9f-11e9-b896-fe36ec32aece https://www.ft.com/content/21b19010-3e9f-11e9-b896-fe36ec32a...

axegon_ 6y ago
I've spent an unhealthy amount of time at presentations, conferences, seminars and meetups. With that, on your first point, I'm more inclined to believe somewhere around 90% have absolutely no "AI" or "ML" for that matter in their products. And a large fraction of those who do have re-used existing open source solutions without digging a lot into them. De omnibus dubitandum est, of course, but this is the impression I get.
- rjdagost 6y ago
  Your suspicion is largely correct, in my experience. I've worked as a consultant on a number of different AI / ML projects for start-ups. Most aren't doing anything all that new or groundbreaking from an ML point of view. Their real innovation is usually more about applying ML to industries / areas where it hasn't been used much before. But that doesn't get the investor dollars flowing in, so the founders try to make it seem like they have some radical new ML breakthrough. And in recent times, it has worked.
  - axegon_ 6y ago
    > And in recent times, it has worked. This is what __REALLY__ bugs me. Personally I'd love to see money poured into actual R&D rather than people abusing the "ML" and "AI" acronyms. Investors don't care about your R&D at all and commonly see it as a huge risk factor. Which it is of course. A semi-working prototype has a much better chance of succeeding so they stick to that. But as a consequence many people(myself included) are not even bothering with pitching anything to anyone and invest their own money, time, resources and savings into it. Blocking? Yes. Painful? Absolutely. Slow? Incredibly. I'm sure the next AI winter is around the corner, if it isn't here already: The virus outbreak might be the catalyst that triggers(or has triggered) it, given the staggering amount of people going full "I have AI which will provide a cure, vaccine and time travel to go back in time and warn the world, just gimme cash". I doubt anyone would deliver on any of those promises(and that's me being optimistic). But the crisis will likely push a lot of investors to pour millions into the empty promises that have a few buzzwords thrown in. I hope I'm wrong.

xiaolingxiao 6y ago

Is there a break down of percentage allocated from seed, series A, B, ... all the way down to F rounds?

lorey 6y ago

What's the value of this link over the original one? Original: https://venturebeat.com/2020/04/14/ai-startups-raised-6-9-billion-in-q1-2020-a-record-setting-pace-before-coronavirus/ https://venturebeat.com/2020/04/14/ai-startups-raised-6-9-bi...

te_chris 6y ago

https://a16z.com/2020/02/16/the-new-business-of-ai-and-how-its-different-from-traditional-software/ https://a16z.com/2020/02/16/the-new-business-of-ai-and-how-i... a very good take. Most AI startups are struggling to scale because models are hard to scale and generalize compared to SaaS. There'll be some fortunes made for sure, but we're still very early in building out these businesses and mostly these seem to be VC's who are (were?) desperate for "deep-tech" portfolio items to make them sound "bleeding-edge" at CogX, Davos, that thing in Aspen, etc.

motohagiography 6y ago
Seconded on this article. I shout from the rooftops to anyone who will listen that for ML, "the confusion matrix is the product," which summarizes much of what they say. The only thing I add to that adage now is that a meaningful product is a weighted function of Relationships, Data, and Expertise. Most ML companies have one, funded ones have two, and profitable ones have the right balance of three. Funding an ML company that isn't 85th percentile on at least two is dumb.

yahyaheee 6y ago

This is an insane amount of funding when you look at the projected revenue for machine learning over the next couple years. Maybe those projections are wrong, and I certainly love all the energy in this space, but it feels like a lot of investors are going to get burned.

barrenko 6y ago

"Anonymous Indians"

barrenko 6y ago
Was not trying to be racist, it's just a Twitter term for fake AI startups (started by one Indian man).
nindalf 6y ago
Wrong thread?

tkyjonathan 6y ago

Almost none of the company leaders or even VCs fully understand what AI even is or does. They just like to hear thats its there. If you don't have some AI in your company, you won't get investors.

kavalg 6y ago
Is it really that bad? I thought investors care more about business model and growth potential.
- developerdylan 6y ago
  It isn't THAT bad. Investors definitely care more about model and growth potential. But you will certainly run into those who ask "How are you integrating AI into your platform?" without any real idea about what that means.

brenden2 6y ago

I was hoping the bubble had burst by now, but it sounds like it might not be there yet.

xiaolingxiao 6y ago

The key bit of information from this (https://venturebeat.com/2020/04/14/ai-startups-raised-6-9-billion-in-q1-2020-a-record-setting-pace-before-coronavirus/ https://venturebeat.com/2020/04/14/ai-startups-raised-6-9-bi...) is that "capital flows disproportionally into large late-state deals." I would read this as a lagging indicator of how "hot" the field is. Most of the companies have found their "niche" and identified the actual problems that need to be solved; like other commentators have said, these problems may only be tangentially related to ML models themselves. These companies are currently scaling up and locking themselves into the market. Given how long the sales cycle is and how sticky it may be in enterprise, this means now is not a great time to start a company just doing "AI".

correlator 6y ago

Incentives are really messed up here. Tacking the letters "AI" on the end of your company name will increase it's multiple. It will force your engineers to call their rules engine "AI" when on calls with customers. It's really unfortunate.