Meta’s AI research lab is ‘dying a slow death,’ some insiders say. Meta prefers to call it ‘a new beginning’
Meta’s AI research lab is ‘dying a slow death,’ some insiders say. Meta prefers to call it ‘a new beginning’
Call it what you will, but all signs seem to indicate that generative AI is simply not as profitable as the evangelists want it to be.
The problem is the only customers are other corporation heads that want this not the regular customers,
No, the problem is that even if people who consider themselves really important want this really, really hard that doesn't change the reality that the technology doesn't do what they want it to do.
Not even remotely. LLMs have failed to find any viable market fit.
The problem continues to be hallucinations and limited utility. This is compounded by the fact that LLMs are very expensive to run. The latter problem wouldn't really be a problem if LLMs were truly capable of replacing a human employee, but they're not. They're just too unreliable for any serious enterprise grade application, and they're too expensive for any low severity application.
For example, as a coding assistant, a lot of people quite like them. But as a replacement for a human coder, they're a disaster. That means you still have to employ the expensive human, and you also have to pay an exorbitant monthly fee for what amounts to a very cool search engine.
There are tonnes of frivolous applications where they work really well. The AI girlfriend stuff, for example. A chatbot that sexts you is a very sellable product, regardless of how icky it might seem to some people. But no one is going to pay over $200 / month for it (as an example, ChatGPT still doesn't make a profit at their $200/month tier).
LLMs are too unreliable to make anything better than toys, but too expensive to sell as toys.
That is not true, we use Vision/LL Models to extract data and structure said data from documents. It is amazing how easy it is compared to OCR and needing to know where which information is located.
They’re just too unreliable for any serious enterprise grade application
I wouldn't go that far. They are perfectly capable of fucking up as badly as organizations with the "enterprise" warning label have for decades.
For example, as a coding assistant, a lot of people quite like them. But as a replacement for a human coder, they're a disaster.
New technology is best when it can meaningfully improve the productivity of a group of people so that the group can shrink. The technology doesn't take any one identifiable job, but now an organization of 10 people, properly organized in a way conscious of that technology's capabilities and limitations, can do what used to require 12.
A forklift and a bunch of pallets can make a warehouse more efficient, when everyone who works in that warehouse knows how the forklift is best used, even when not everyone is a forklift operator themselves.
Same with a white collar office where there's less need for people physically scheduling things and taking messages, because everyone knows how to use an electronic calendar and email system for coordinating those things. There might still be need for pooled assistants and secretaries, but maybe not as many in any given office as before.
So when we need an LLM to chip in and reduce the amount of time a group of programmers need in order to put out a product, the manager of that team, and all the members of that team, need to have a good sense of what that LLM is good at and what it isn't. Obviously autocomplete has always been a productivity enhancer for long before LLMs have been around, and extensions of that general concept may be helpful for the more tedious or repetitive tasks, but any team that uses it will need to use it with full knowledge of its limitations and where it best supplements the human's own tasks.
I have no doubt that some things will improve and people will find workflows that leverage the strengths while avoiding the weaknesses. But it remains to be seen whether it'll be worth the sheer amount of cost spent so far.
The biggest problem is that it is trying to be everything at the same time instead of being focused on a limited amount of knowledge. They are shooting for the moon and failing spectacularly, but since their staged presentations impress rich people who don't understand the need for reliable results it keeps getting jammed down everyone's throats.
