> generative AI is a product with no mass-market utility.
> I am neither an engineer nor an economist.
clearly.
> I am neither an engineer nor an economist.
clearly.
It's more plausible for me that we will see a notable productivity increase in a lot of sectors of the economy over the next decade. Part of me wonders if this is an additional reason why the Russell 2000 has been spiking lately (investors concluding that there is more money to be made from the general productivity increases in the wider economy than the tech companies providing the LLMs that don't seem to possess any monopolies on the technology), but this is just my speculation.
So why should we listen to him? ChatGPT has saved me a lot of time. Luckily it’s well trained on AWS API’s, tge SDK, CDK, Terraform and Kubernetes. Anything it isn’t trained on, I just give it links to the documentation
"Mass market utility" here refers to its ability to sell at the scale it would need to substantiate its costs. As it stands, LLMs do not have mass-market utility at the scale that they need to substantiate their costs. It is really that simple. If they did, these companies would be profitable, and they would be having a meaningful effect on productivity, which they are not.
See page 4 of this report from Daron Acemoglu of MIT: https://www.goldmansachs.com/images/migrated/insights/pages/...
The "killer app", as far as I can tell, is essentially natural language search. However, the core function (in my opinion) has existed since DuckDuckGo added contextual infoboxes to the right of search results ("knowledge panels"), and the benefit of using natural language has existed since Siri and has never seemed to add much to the experience for me. AI image generators seems to be used mostly by youtube creators and spammers. The main users of AI language generation seem to be spammers and crappy content farms on TikTok.
Commercials for AI products ALWAYS lie by speeding up the time it takes for results to arrive, and the most impressive demos always seem to end up as some version of the same useless feature: "what am I looking at right now?" Who needs that? AI-assisted coding also seems to have a similar issue. Demos that supposedly show off the technology never actually use it to create the kind of code that is actually worth money.
I'd be happy to be proven wrong here, but I keep looking and I never find that killer app.
if humans still have to fix the robots that seems fine, as long as they run for long enough without needing rewiring.
It’s a complicated problem, and apparently very misunderstood.
People have built dedicated plastering robots, strawberry picking robots etc. Each robot only really needs to be good at one thing. Almost nobody is making the foolish mistake of building humanoid robots that then tackle the problem exactly the way humans do. The plastering robots spray the plaster, which is much faster.
That doesn't answer what's happening now. The AI companies can't keep saying "AGI is around the corner!" for much longer.
Agents are evolving though. The coding agents a few months ago were a joke (Devin) and now they're actually usable for basics.
If I can compare it to Google search back in the 90s. There weren’t all these evangelists saying in 5-10 years blah blah blah. We just used it, in our daily lives. I don’t use AI at all except at work. And I couldn’t even tell you what product it’s going toward because I don’t think 99% of employees know. Why we don’t know, who knows!
The VC money is betting on a similar sort of monopolistic dynamic occurring in the AI space. They're not saying that 100s of billions of dollars of value is going to accrue to openAI because of chatGPT they're saying 100s of billions of dollars of value is going to accrue in the space and the most likely outcome is that the vast majority of that is going to be siphoned up by a couple of behemoths. Other than the incumbents (Microsoft, Google) OpenAI seems best positioned at the moment and whoever else creates breakthroughts will probably be acquired anyway just like instagram got bought out by facebook as soon as they got large enough to matter.
It's not about growth, it's that nobody had to make future claims about web search or online ordering being useful to the average person, they already were useful when someone tried them.
Outbound sales is being automated.
Lots of very hum-drum stuff. Ordering room service at a hotel for example.
Tons of data entry jobs are now gone.
LLMs are already better at humans from a cost perspective for many tasks.
If OpenAI's new voice mode turns out to be as versatile and context-aware as promised, it should be equally valuable for interactive spoken interpretation.
Think Microsoft in the late 80s through the 90s.
If you are charging for the platform, you can let thousands of other businesses try the risky hard to scale stuff and you'll get a cut of everything no matter who wins.
Or could we have instead done some simple web service that would do most things... The sad reality is that companies don't want easy and efficient customer service... As that would allow customers to cancel their continued payments...
> The sad reality is that companies don't want easy and efficient customer service... As that would allow customers to cancel their continued payments...
This is not true at all. The true reason is that a well trained call center employee can easily cost a company $20 per customer issue resolved (total cost inclusive of training, office space, equipment, etc).
For any low margin business (e.g. hardware under $500 USD!) that basically destroys the entire profit from that customer.
Customer service is expensive.
Uh... you realize they were already algorithms, right? Meaning, they have a flow chart they follow. They don't make any decisions, they take input and respond to output.
The only reason they're not computer programs is because they NEED to be human. So the human on the other end trusts them. Even though everyone understands they have no free will or reasoning abilities (or if they use them they get canned).
AI doesn't fit that use case. Number 1 is because AI IS NOT algorithmic. So it's a liability to use. Number 2 is it's not human. Again, if you're going the no human route there's infinite cheaper, more reliable, faster, and overall better in every way programs you can use.
Anyone who is sight impaired, or doesn’t have their glasses on while reading a menu, or looking at a sign in another language.
It’s clearly not in final form. In 1978, people couldn’t see the use of home computers. In 1988, most people were saying the same thing about email. In 1998, most people were saying the same thing about the internet.
It might not prove out, but evaluating something super early isn’t all that interesting. Let’s see where we are in 2030 at least.
Give it a few more years for more people to forget about how hard things like NFTs got pushed with the same sort of arguments- then this'll come off better.
Regarding email - it's probably one of the most used bits of technology in existence, and I bet it has a similar OOM economic impact to something like Excel. Calling it a dead technology is not accurate - so much business is done via email, especially internally at SMB.
But also...the reason they might have is that email kind of sucked back then. Of course you wouldn't see the promise in something that was clunky and slow and nobody used.
This isn't a comparable to LLMs, though, because even someone who found them clunky could see why you'd want to send an email versus sending a letter.
I think it’s not obvious yet that they go much further beyond that?
It’s a lot of money, sure, but it’s not world-transforming stuff.
But AI code generation is garbage, just like AI text generation is. AI generated books, and songs, and poetry etc is just appalling rubbish that nobody wants to read or hear. AI generated art is ugly and generic, and stands out immediately as zero-effort and near-zero cost. Except of course, it cost alot of money to make, but nobody is willing to pay for it and it's so far been bankrolled by VC capital.
"create an express server that uses CORS to only accept requests from <mydomain> that has 3 async endpoints defined, 2 GET endpoints titled <a, b> and 1 POST enndpoint titled <c>. The POST endpoint should accept JSON, and the GET endpoints will return JSON. Stub out the route handlers, they will be defined in another file. For the POST endpoint parse out the userId from <header field> and also pass it in along with the JSON"
"Here is a typescript definition of the JSON being posted to this endpoint, validate all string fields are less than 100 characters long, and that none of the values are null, then write the data to a redis DB at <location> using auth values already loaded up in the environment. Data should be written to <userid/location>"
"Now add exception and error handling around this code, cover the following case: Data is invalid - Return an error message to the user with HTTP error code 400, Redis is not accessible - HTTP 500. Also log errors using the <logging library> that has already been imported and initialized up above, and increment an appropriately named counter using the <analytics library> that is also already imported and initialized."
If you are getting garbage AI code, you are not using proper tools. If you just go to ChatGPT and ask it for stuff, you won't get very good code (and IMHO GPT4o is much worse at coding).
Use a proper editor that prompt engineers code generation (such as Cursor), and LLMs can write some really good code.
Can it end to end generate an entire service with just a vague description? No. But it can easily 2x-4x development speed. Heck I've thrown code at GPT4 and asked it to "please look for common concurrency bugs that may have been overlooked in this code" and watched as GPT4 saved me literal hours of debugging.
What OpenAI has is a problem monetizing the value their product brings, since the value to each customer is so different. When I'm at home, I'm happy to pay $15 a month in API usage fees to accelerate my coding, but a company should be happy to pay hundreds of dollars per month to accelerate the speed code is written. Figure $100 an hour average cost for a dev on the east or west coast of the USA, if GPT4 saves 10 hours a month (easy!) then OpenAI should be charging at least $200-$500 a seat licenses per month.