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I agree and so far I think it's picks and shovels all the way down. Most of the "AI" companies I see sell tooling, often to "help your AI team work faster|bette

I agree and so far I think it's picks and shovels all the way down. Most of the "AI" companies I see sell tooling, often to "help your AI team work faster|better|spend less time doing x|whatever. It all presupposes there are end uses, which are few and far between, certainly almost none are being sold. AI is still in the hype mode of companies having internal budget to "invest in AI" and so that's who the AI companies are targeting, as opposed to actually making products that do something. See also blockchain wallet companies. PS - I'm optimistic about AI, but it's important to be realistic about the current state of the industry

nemo44x 3y ago
Indeed, lots of tooling out there. Which makes sense as it's very early days. I imagine that LLM AI will be integrated into so many things down the road though that it will be an expected feature of most any product.
calebkaiser 3y ago
It's important to note that despite the recent excitement about LLMs, which is still an emerging technology, "AI" is not a new market by any means, nor are major companies only now investing in it. For the better part of a decade, ML has been widely adopted across industries, and the average person uses an "AI" system many times in a given day. For example, if you open the home screen on the average smartphone right now, you'll see apps like: - Delivery apps like Uber, Lyft, etc., whose recommendations, ETA predictions, driver matching, and more are built on ML. - Media apps like YouTube, Netflix, etc., all of whom rely on models for recommendations. - Email apps like Gmail, whose filtering (both spam and categorization) and text completion are based on ML. - Photo apps like Instagram, Snapchat, and even your phone's basic Camera app, all of which use computer vision. If you Google anything, you're perusing the output of a model. If you're being recommended something on basically any platform, you're interacting with ML. If you ever use speech-to-text, you're using a neural network. Your bank uses ML for fraud detection, your posts on social media are moderated by ML-based content moderation, and if you have a car with any recent-ish sort of lane departure assistance, you're driving with help from a neural network. Most of these companies have large, mature ML teams, whose outputs represent massive amounts of revenue. Hence, they represent a legitimate market for selling picks and shovels.
- lsmeducation 3y ago
  [flagged]
- version_five 3y ago
  That's the framing we've been using for years, look at some big tech ML or data science that we reframed as AI, your manufacturer/transportation/retail/whatever company needs it too, but there are no products for end uses in your industry, just lots of tooling and consulting services you can buy for bespoke projects.

nemo44x 3y ago

Indeed, lots of tooling out there. Which makes sense as it's very early days. I imagine that LLM AI will be integrated into so many things down the road though that it will be an expected feature of most any product.

calebkaiser 3y ago

It's important to note that despite the recent excitement about LLMs, which is still an emerging technology, "AI" is not a new market by any means, nor are major companies only now investing in it. For the better part of a decade, ML has been widely adopted across industries, and the average person uses an "AI" system many times in a given day. For example, if you open the home screen on the average smartphone right now, you'll see apps like: - Delivery apps like Uber, Lyft, etc., whose recommendations, ETA predictions, driver matching, and more are built on ML. - Media apps like YouTube, Netflix, etc., all of whom rely on models for recommendations. - Email apps like Gmail, whose filtering (both spam and categorization) and text completion are based on ML. - Photo apps like Instagram, Snapchat, and even your phone's basic Camera app, all of which use computer vision. If you Google anything, you're perusing the output of a model. If you're being recommended something on basically any platform, you're interacting with ML. If you ever use speech-to-text, you're using a neural network. Your bank uses ML for fraud detection, your posts on social media are moderated by ML-based content moderation, and if you have a car with any recent-ish sort of lane departure assistance, you're driving with help from a neural network. Most of these companies have large, mature ML teams, whose outputs represent massive amounts of revenue. Hence, they represent a legitimate market for selling picks and shovels.

lsmeducation 3y ago
[flagged]
version_five 3y ago
That's the framing we've been using for years, look at some big tech ML or data science that we reframed as AI, your manufacturer/transportation/retail/whatever company needs it too, but there are no products for end uses in your industry, just lots of tooling and consulting services you can buy for bespoke projects.