91–100 of 121 posts
Earlier quoted context omitted.
No developer job has yet been lost to AI. We are in a huge recession, and companies like to have an excuse to fire people that can be spun as a positive.
> No developer job has yet been lost to AI. https://content.techgig.com/technology/developer-fires-entir...
Most of us believed that crypto currencies were trash. Look how valuable its now . LLMs are a million times better than Crypto currencies.
Earlier quoted context omitted.
But I can actually use an LLM to do useful work for me and no one gets hurt. I think there’s too much hype and money, but LLMs are useful right now.
SAE Level 2 automated vehicles are useful now, just not so useful that it's safe to take one's eyes off the road and hands off the wheel. LLMs are in a similar place, and still a long way from doing the whole job reliably by themselves. The current state of AI is one or several unknown unknowns away from real AGI. We're missing something fundamental. Likewise with autonomous vehicles, the mythical SAE level 5 vehicle…
I ride in waymo all the time, they are SAE 4.
I know many people who take a waymo every day.
What percentage of driving represents the delta between 4 and 5?
SAE 4 level LLM/Ai (if we can really even make that comparison) would have far less difficulty in deployment and would be far more disruptive in a far shorter period of time than SAE 4 self driving cars.
If they do "figure it out" (both AGI and a viable business model), a lot of people here will likely be out of a job. If they don't, the whole thing will come crashing down, taking our invested savings with it.
The comparison to crypto keeps coming up. Not everyone's savings went into crypto, but a lot of people's savings and retirement funds are being invested in funds tied to the stock market. And right now its growth depending on pumping cash into the AI bubble.
Earlier quoted context omitted.
I think it's easy to forget how much low-hanging-fruit there still is, in terms of taking full advantage of this technology. People are still figuring out very basic integrations, and even now, at this early stage, the things I can do with LLMs are pretty incredible. For example, I was able to set Cursor up on finally dragging an old codebase out of the dark ages. It then built new features that I've long wanted. It…
"I think it's easy to forget how much low-hanging-fruit there still " Such as?
This technology demos incredibly well and you can just see how everyone gets giddy with excitement around using it. I watch my colleagues and executives proud to show what they could do or make endless jokes about it. It reminds me of when people first got their phones and couldn't stop showing everyone how cool they were. This leads to an over rotation in the perceived value.. the value is significant just as the mo…
There are no error bars, no confidence intervals. Just a one trick pony that pastes tokens together to give you something that may look good to many people. Sure there are many good use cases, but there are still enough non-patchable and indeterminable in size holes in the watering pail to limit its effectiveness.
What's the path to recouping that money? Even if every major company in the US spends $100,000 a year on subscriptions and every household spends $20/month, it still doesn't seem like enough return on investment when you factor in inference costs and all the other overhead. New medical discoveries, maybe? I saw OpenAI's announcement about gpt-bio and iPSCs which was pretty amazing, but there's a very long gap between…
Earlier quoted context omitted.
$100k/year is literally nothing. Think of it as maybe $10k/employee, figuring a conservative 10% boost in productivity against a lowball $100k/year fully burdened salary+benefits. For a company with 10,000 employees that’s $100m/year.
Even at $10k/yr/employee, you'd need 30 million people on the 10k/yr plan to hit 300B ARR. I think that's a hell of a big swing. 3 million, recoup over ten years? Maybe, but I still don't think so. And then competition between 4 or 5 vendors, larger customers figuring out it's cheaper to train their own models for one thing that gives them 90% of the productivity gains, etc. But rather than speculating, I'm generally…
Earlier quoted context omitted.
"I think it's easy to forget how much low-hanging-fruit there still " Such as?
So many things, once you start looking. However, most of the critics seem to focus on what it can't do currently, which seems to turn off their brains to the possibilities. Just look at what Cursor (and similar) have done in terms of the tooling for LLMs. There's still tons of progress to be made there, but similar tooling can happen across a variety of industries and categories. For example, I run a database of info…
Ok fella. Its so abundant right. So why not go ahead, start your own firm and profit from this opportunity, that according to you exists? lol.