You could have limited-instruction llms where the model does one thing, for example summaries. It could accept a limited amount of instructions for example, first token for verbosity, second for style etc...
These models rely on knowledge that are embedded in their weights, if a new library is released, a new linux version comes out, some new protocol succeeds the previous one, you want your llm to know about it. Sure you can just add that into the context window, but that has its own problems.
Unless new research, there are a few which look promising, gives a new method, training is going to be a constant cost sink.
On top of this, if you stop training, it is 6 months until someone releases an open weights model and now you are competing to give the lowest price for the same product.
Also we can't forget that this is a business that *has to* be in the global labor industry, not just a tech tool, they have to have much better models to justify the trillion dollar evaluation
What I don't understand is that if a lawsuit happens, then must the plaintiff produce their source code for verification ? Even so a git tree is trivial to change into some other arbitrary code even if a license violation has occurred. I also heard if proven the consequences are that they would lose all revenue starting from when the violation has occured
Thats a big sometimes for me. I am unfamiliar with the app development process. For backend,I would rather design the whole thing from scratch rather than try to fix a broken architecture. For frontend, maybe that is true, but I haven't had the chance to build anything complex, just forms and tables.
I am a backend dev, and building a mobile app for the first time, It is a toy sized project right now and it works, would have indeed taken me 5x the time to get to that point on my own.
I know from experience that to make it a non-toy project I am probably going to need to spend some, if not most of that saved time cleaning up in the future due to technical debt.
For backend, it is mildly useful at best, helpful with boilerplate and when I know exactly what needs to be built. I have not yet firsthand experienced these 10x, 100x productivity gains.
Frontend, forms,tables and generic dashboards is pretty good, I am sure one could get it done faster and better over the long term with proper technique and methods, but I just hate css
I am not a lawyer, from what I understand that the precedent is that you can use copyrighted material in ML process. Even though meta has, allegedly, pirated the material, the cost of violation would be pennies compared to the ai spend, since that is the violation, not that they used those materials,
I would guess that they would want to at the very least 10x their prices. Remember they need to make up for training, marketing, etc.. and make a big chunk of profit on top of that to justify their trillion dollar evaluation
I have been playing nonograms for a year now, there was never insta death, controls are a little off, title is hidden until its solved to avoid spoilers This is obviously programmed by someone who doesn't play nonograms. Safe to assume it was vibe-coded
Article says,this is a software issue. Where GPU'S are unable to get to be fully utilized due to scaling issues. I dont know how hardware that scale works, but it could very well be that they still need all of their hardware to get their current compute
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