[Wheatman]

While There is money to be made in further integrations, hell thats where i see most of thr priductivity increase from these tools coming from, OpenAI has already spent billions developing these tools, money which they have to pay back in some way soon.

This is also ignoring the giant elephant that is open models, soon enough models like Llama, would be able to match or even surpass what ChatGPT, by which point why would any sufficently large company pay for API when they can run their own model, especially when all those GPU used for training flood the market.

But then again, plenty of large comapnies still use aws, even when it makes no sense to go serverless, so they might have a market to capitalise on.

We live in interesting times for tech, moores law is dead, intel is falling, layoffs are everywhere...

I sure picked the best time to go to university for Computer Science T-T

[anshumankmr]

Those GPUs also cost a bomb to run. LLMops isn't super easy, I am working with a large OEM manufacturer rn as a consultant and they are also experimenting internally with LLMs, but they have enough resources to run those models. I don't see smaller companies having enough resources to experiment with various models at scale like they are.

>I sure picked the best time to go to university for Computer Science T-T

Going to be a bit contrarian here – while it's true that jobs can be tough to find and layoffs are discouraging, I genuinely believe it's also one of the most exciting times to be in the CS field. The fact that we can actually talk with an "algorithm" is still quite bonkers to me cause I remember fiddling with RNNs and LSTMs just to predict the next word or two in a sentence. There are still ways that we can leverage it to make something really cool. Perplexity is one. Phind is another. Notions's AI integrations are great.

I graduated about four years ago and faced my own setbacks, including getting laid off from my first job. But despite those hurdles, I've managed to find my footing and am doing reasonably well now. Just hang in there champ.

[Wheatman]

>Those GPUs also cost a bomb to run. LLMops isn't super easy, I am working with a large OEM manufacturer rn as a consultant and they are also experimenting internally with LLMs, but they have enough resources to run those models. I don't see smaller companies having enough resources to experiment with various models at scale like they are.

True, I sorta conflated running llama on your pc with what large comapnies.

Not to mention how I was somewhat conflating chat-gpt the product with OpenAI the company, What i argues was that soon enough ChatGPT itself won't be that special when comparing it to open source models.

OpenAI the company is in the weird position of both having a moat, and yet drowning in it: They have a huge advantage in skilled experts, engineers, and know-how to get a first mover advantage, especially now that they are practically another subsidiary of microsoft.

But they also have the notable disadvantage of spending billions upon billions of dollars developing a model that in the end is little to no better than what one could get for free from the internet.

A small company with a few dozen specialist could present a comparable product at a fraction of the cost, simply by not having to pay back the cost of developing their own model.

I feel like OpenAI would end up in a weird place in soon, maybe something like a cloud provider for companies, usefull for smaller ones where brand recognition and reliability matter, but having to compete with more specialised companies offering a similar service using llama, And at some point large companies could just build their own servers with open-source LLM's with their own servers and their own teams, bypassing OpenAI entirely.

The biggest winner here is those new small AI consulting teams that didn't have to spend nearly as much on finetuning the models that are already made.

You probably know way more about these things than me, what do you think of this prediction?

It doesnt sound as terrible for developers as I first thought, though it pains me to see how many people quit/never went into software development due to the AI hype, we lost a third of our class from 2023, and I assune things are even worse in america/developed countries.