sabas123
sabas123 on Hacker News
I don't understand the backlash against this interview.
When listening to the interview it sounded clear that it was just in context of local inference.
To me it came across as stating that setting up local inference, when dram is limited, is indeed limiting from a global perspective.
I think it's a bit disingenuous to state that his opinion is that we shouldn't have any ram being used for any local purposes.
Puzzle pirates used to have AI bots help you too if you couldn't find any crew. God I miss that game :(
> except in some special circumstances (e.g. childrens' toys)
Don't nearly all electronics fall under it too, this is the second item after children toys in the link you posted.
> Here is a non-exhaustive list of products that are included in EU laws about CE marking:
> Toys, drones, electrical and electronic equipment, pyrotechnic products, recreational crafts and watercraft
I actually do a phd in a closely related area.
Creating better tools to do research with is definitely part of the research process.
While there is a lot of work in general operating systems, those aimed to specifically do a lot of microarchitectural experiments is still undiscovered ground.
> It wouldn't stop people from feeding them into the Show HN stream, which is the problem. If we had a good enough way to tell them apart, we could factor them into two streams, but we don't yet.
But it would allow for a culture to grow where the posters would self-contain their submissions into those threads.
> Do you really believe that year after year game developers and game engines get worse and worse at performance? Of course not.
If you strictly want to blame Denuvo then that assumes game developers cannot think of a way to spend their extra performance either. Which is obviously not the case.
It is the average of sub sets of humans, which can be vastly better than just entire population.
Example it can easily do moderately advanced calculus, that is way better than the average human.
This is even the official OpenAI guideline too.
We also have had a significant rise inglobal population. Making for an unfair comparison.
What is the point of having this if code generation is not functional yet? That is the entire point of this app.
Without providing any proof that either this or SELinux is backdoored.
> No, we get applications so hideously inefficient that your $3000 developer machine feels like it it's running a Pentium II with 256 MB of RAM.
> We get software that's as slow as it was 30 years ago, for no reason other than our own arrogance and apathy.
I feel like I read this exact same take on this site for the past 15 years.
The problem is that we already can provide an alternative, but we don't switch to them. Which might be even worse.
Is it really such a pivot when they invested a lot in AI already?
They bought DeepMind in 2014 and always showed of a ton of AI research.
If I list you 10x many cases which failed, would you switch your opinion then?
You make it sound like security is a binary thing, which is not true.
> We don't want a world where only three old bearded guys can write a compiler or a physic engine.
Don't write your own OS does not mean do not contribute to something like the linux kernel.
I asked ChatGPT, gemini and both answered 3, with various levels of explainations. Was this a long time ago by any chance?
Which is not necessarily a good thing.
> Today we have a huge oversupply of scientists, however there's too many of them to allow judging for potential, and many are not actually capable of dramatic impact.
Realistically speaking it's also much harder to achieve the same level of impact back then as most, not just low-hanging, fruits have been plucked.
As somebody that occasionally studies pure math books those can be very, very light on regular English.
If you make an LLM which design goal is to state "I do not know" any answer that is not directly in its training set, then all of the above statements don't hold.
Being a "University Professor" means jack shit unless precisely in their (sub)-field. The authors are experts in biology, and evolution of information representation/communication, and about misinformation.
I'll gladly defer to their expert opinion on those topics, but IMO to use such an authoritative voice when they are not experts in actual AI systems. Judging the massive progress in the field of AI, how can anyone even remotely state what these systems inherently are, when they are still so new and ever-evolving?
> currently designing a course to hopefully arm medical students with the required basic knowledge they need to navigate the changing world of medicine in light of the ML and LLM advances
Could you share what you think would be some key basic points what they should learn? Personally I see this landscape changing so insanely much that I don't even know what to prepare for.
IIRC there base kit like garbage collector and runtime are all the same between community and enterprise. The biggest feature that comes to mind that is behind the enterprise-only wall (or at least used to be) is Profile Guided optimization.
Keep in mind that getting meltdown to work might be very difficult depending on your setup. I wouldn't have been able to at least when starting out my teacher didn't provide us with targetable hardware.
A spectre (particularly RSB-based ones) are nice to start out with imo.
> Today's most advanced projects are able to compile pretty much arbitrary rust code into provable RISC-V programs
Provable does not imply secure.
From a security perspective a lot of changes to this world would be an upgrade. However implementing security features is always a trade off, and sometimes good security is just not worth the loss of other things.