The other main issue that I see, is that even if there is a formally verified specification, at the moment, LLMs will not respect it perfectly. As long as LLMs are not able to non-deterministically follow a spec, the technology is not good enough.

A part from that, imo, in this age we should focus more on the mathematical aspect of computations, and I think we need to develop novel theories that take into account the non deterministic nature of LLMs in the process. I'm not sure this will ever work by merely extending current practices, as software design practices are extremely poorly defined from an engineer point of view. Just extending them by including randomeness does not seem a good idea.

If someone else struggle on this step, I added in vLLM args: --served-model-name "Qwen2.5-Coder-14B-Instruct" --served-model-name "default"

So default becomes an alias.

I didn't yet test Forge, I was just happy that it worked at the moment ;)

Massively Parallel Processors: A Hands-on Approach is not really good in my opinion, many small mistakes and confusing sentences (even when you know cuda).

CUDA by Example: An Introduction to General-Purpose GPU Programming is too simple and abstract too much the architecture.

Next year I'm planning to start writing a cuda book that starts by engineering the hardware, and goes up to the optimization part on that harware (which is basically a nvidia card) including all the main algorithms (except for graphs).

I'm already teaching the course in this way at uni, and it is quite successful among students.

Comments URL: https://news.ycombinator.com/item?id=47711651

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It had great success, now when I propose to them to use some model to do something, they tends to avoid.

Maybe software tinkerer?

I only use it on a sentence or paragraph basis, otherwise it misses the point 90% of the time.

I would strongly advise against this use for the moment. The important part of reading a paper is not only to extract general rules, but to build your own internal model. Without it you cannot effectively do research. The main interesting points are often in the subtleties of the details deep in the paper.

Internal tought that come easily to mind when I read :

- 'oh they used that equation, but that could be also be interpreted totally differently, what happens if we change point of view, does it makes sense from this other perspective'

- 'I see they claim to achieve better results than sota, but actually, they compared with other methods that are not solving exactly the same problem, what shortcut or changes did they had to do to obtain a fair comparison, is it a fair comparison, can I trust those numbers? '

- 'oh, the authors didn't realize that they solved this other problem, or did they realize but there was a block somewhere preventing it?'

- 'I like this trick to achieve that result, but at the same time, it will prevent to solve a whole class of other problems, so their method will not work on those cases'

...

Also, notice that a paper IS a summary of multiple months/years of work, and researchers summarize it already to the maximum to stay within the page limit, by summarizing a summary you will always miss many things.

Also, a collaborator is usually not a stranger over the internet, it's often someone who you know and you already worked with, so it is not that ackward to expose a new idea and propose to work together.

It takes time and social skills to make long lasting collaborations, the two parties must trust each other in order to collaborate. In this context, exchanging ideas is not really an issue.

Having said that, it's probably a good course, CMU courses are often great.

I was just expecting way more sota models in many fields due to the title.

If someone has this kind of ressource I would be extremely interested!

However, I use Manim for maths, for me having computational libraries (python) is a requirement. Most of the transformations that I do are found by using linear algebra, calculus and sometimes full neural networks. All my geometry is computed, not placed by hand.

I'm wondering if it would not be possible to have a 'canvas' backend for the web in the python version instead.

Btw, Manim is kind of easy to install in its own docker ;)

I only argue that if they are equal in quality of treatment and the 'total cost' is the evaluation parameter, it is way more complex than the treatment itself, and it could be justified to use proton therapy, even if more expensive.

Nice talk anyways :)

From my visits, they mostly focus on children that have some very nasty cancers, the IBA hospitals are all designed with children in mind (to avoid stressing them), and from my memory, a unique hospital is often enough to treat a whole country for the kind of cancer they target.

Now, if it is on par with classical radiotherapy BUT it gives less subsequent problems, it might be worth the cost as subsequent problems can be as expensive or even more than the original treatment. It becomes an actuarial issue to know where is the tradeoff.