If you look at total software spend in the US a year it’s 500B, total spend on payroll is 5T. If companies become 10% more efficient because of GenAI you’re effectively doubling the size of current software market.
Actual value capture would obviously be lower, but 10% efficiency gains is a low estimate based on the studies coming out.
There’s a ton of terrible startups right now, but some of them will become whales. You can’t predict which ones ahead of time, so you invest in everything.
I haven't seen LLMs do anything more useful than generating a wedding speech in the style of H.P. Lovecraft and there are people out there earnestly predicting this technology will increase efficiency 10% across entire economies. I genuinely feel like I'm living in a different world to you all.
I have yet to see an example of Copilot do something that doesn't seem like basic autocomplete/snippets that editors and IDEs have been doing for decades or code so basic that it betrays the lack of competence by the user.
To be fair, a lot of software spending in Enterprise is what I would like to call Bullshit SaaS, a la David Graeber's analogy. Stuff that was subscribed to by some PM once upon a time, but then later sat unused, even as the company gets billed on it annually or monthly. Not to mention a lot of SaaS simply buying and using each other's products, fully funded by VC capital (which is the YC model).
Take for instance any of the Talk to your PDF products out there. They were popular when ChatGPT came out, but nothing close to the billions of dollars claimed to be in that market. Chatbase made a few millions in revenue, before selling, but now that OpenAI has native functionality, I'm certain that product has been zombified.
Of course, this is different from the large enterprise-level products being built by, say, companies like Harvey AI, but the utility of those products within an org over steady state (after all the hype has died down) remains to be seen.
I think people will lose their jobs with all types of cost-cutting but the people left will be left doing more of the work. I think like Web 2.0 a lot of AI software will be created to manage other AI software.
Buster - Software that links databases and large language models
Vectorview - Custom LLM evaluation
Nuanced - Helps detect deep fakes and misinformation
I'd love to see the studies mentioning 10% efficiency gains if you have a chance. also, do these studies balance against cost of running the models? remember, that's why stability.ai has collapsed.
> There’s a ton of terrible startups right now, but some of them will become whales. You can’t predict which ones ahead of time, so you invest in everything.
I know a company that claims to do AI. Their models didn't work so they ended hiring humans to manually do the job AI was supposed to do. Obviously that won't scale, but they still call themselves an AI company.
No because AI is just a marketing term for unproven technology to generate hype. Once something is proven and use cases/limitations understood its no longer AI. Spellcheck was once considered AI
The amount of AI news/HN discussion is mostly a decaying function of time since last major GPT release. Right now people have gotten accustomed to GPT 4, so people quietly muse that AI has plateaued and will never match human ingenuity.
When GPT 5 comes out we’ll see another burst of people saying that strong AI is now just around the corner (and should either be stopped — or businesses should be started up to capitalize on it).
The HN frontpage is pretty heavily moderated. You may have noticed no news related to Elon Musk/Twitter, for example, because that is usually instantly removed or downranked. The article about Israel's bombing in Gaza on the front page right now was initially removed but came back after too many people complained, and now has 800+ comments and upvotes. So what you see here isn't necessarily indicative of general public interest or even interest of the community.
Readit News
Actual value capture would obviously be lower, but 10% efficiency gains is a low estimate based on the studies coming out.
There’s a ton of terrible startups right now, but some of them will become whales. You can’t predict which ones ahead of time, so you invest in everything.
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Markets are just so tricky to define. The labor pool includes Netflix, even if they’re not competing for B2B SaaS spending.
Take for instance any of the Talk to your PDF products out there. They were popular when ChatGPT came out, but nothing close to the billions of dollars claimed to be in that market. Chatbase made a few millions in revenue, before selling, but now that OpenAI has native functionality, I'm certain that product has been zombified.
Of course, this is different from the large enterprise-level products being built by, say, companies like Harvey AI, but the utility of those products within an org over steady state (after all the hype has died down) remains to be seen.
Buster - Software that links databases and large language models
Vectorview - Custom LLM evaluation
Nuanced - Helps detect deep fakes and misinformation
https://www.nber.org/papers/w31161
For what value of “you”?
..bUt ThEy fInE TuNEd iT...
When GPT 5 comes out we’ll see another burst of people saying that strong AI is now just around the corner (and should either be stopped — or businesses should be started up to capitalize on it).
Progress is continuous but hype is cyclical.
Anecdotally, Lots of my friends and family was using it heavily when it came out but they seem to rarely use it anymore.
I use it all the time while coding and cooking but it is not something I couldn't live without. I can easily do the same thing even without chatgpt .
In the same vein as crypto, the grift continues in AI.
Dead Comment