They should show some performance comparisions between PyTorch and Mojo, PyTorch+kernel compilation + Triton vs Mojo, ThunderKittens vs Mojo.
8,452 karma · joined September 7, 2018
They should show some performance comparisions between PyTorch and Mojo, PyTorch+kernel compilation + Triton vs Mojo, ThunderKittens vs Mojo.
It was always easier than making a system secure.
I still believe it was the good decision, but I also know that I wouldn't be the first person to run the release in prod.
I think Jarred should start making release candidates instead of releases to take some of the pressure off.
Not really as one of the main goals ofr ARC-AGI 3 was measuring task efficiency on unseen games.
I'm sure there are cheats everywhere but the most sensible thing is to just accept that the LLMs of today are much more intelligent in solving reasoning tasks than the ones from half year ago.
My own private benchmark shows the same thing.
Non of these laws stop you from opting out of surveillance, but altogether it gets so hard that at some point you get more suspicious and tracked if you do all this than if you don't do any of these.
Humanity is on aggregate optimizing for increasing collective intelligence and I don't see that stopping as the main goal when AI gets smarter than humanity, just hope that we all will have a nice human life.
I also found Bob Martin entertaining, but after trying to follow his suggestions I just got into the trap that Casey Muratori shows: even if I don't care about the performance of the code at the start, the amount of abstractions Uncle Bob advises makes it just too easy to make the code extremely hard to optimize later.
If it’s a yes, it needs datacenters and get a lot more energy.
If no, it needs to transfer data to US for training/inferencing on it.
How can they do price fixing and discontinuing a product at the same time? It just looks like some companies are angry that AI / VC industry is outpricing them.
Twitter and Facebook also did what they ,,had to''.
The thing that's new here is that Antropic's growth rate was so enormous that Dario didn't have time to learn to lobby.
It means that most people will never understand how fast the landscape is moving: non-coding and non-homework use cases didn't change that much since last year.
Anyways SwiTransformer paper looks interesting and doing a post training to optimize for it looks interesting as well.
And then US chamber of commerce protected itself from liability as well to take export control law seriously after Antropic's CEO categorized Mythos without the cyber query filter as potential cyber weapon.
The problem here is that there's no real technical way to protect against the queries, just making them more expensive to create, as the models are getting smarter.
Also as the main jailbreak ,,technique'' is splitting the task into subtasks, and the main moat of Mythos is that it can solve more complex tasks, I also wouldn't categorize this jailbreak as serious.
Trump looks smart enough to understand the difference in how much political power he would lose if he would pardon SBF.
He wants full control back.
Also I asked questions about whether it's safe for me for example to work on just compilers or just inference kernel optimizations and it refused to answer me.
If I can't even ask what I can do safely without my code being destroyed, I just can't trust it not to sabotage my work ever.
The new designs were their main asset besides the amazing talent that went to NVIDIA, not the remaining DCs.
Also rsync is handling copying binary data, it’s a project that’s super sensitive to hardware faults for example, which means it’s not just enough for the tests to pass.