JBits

I'm really confused by this list: every link I click on either doesn't work or takes me to a project for Go written in Go. I haven't been able to navigate to a single Cobol project.

I agree. The idea that mathematical achievements by LLMs could involve plagiarism didn't seem common before but now the question can be asked of any new novel proof of construction generated by LLMs.

It's also notable that the Open AI proof may not even be interesting to mathematicians.

Even if people already had an idea that LLMs were training on user inputs, it's the first time it's actually caused an issue. Mathematicians, and plenty of researchers, working in ambitious or competitive field now have a very good reason to avoid LLMs.

I have to say, it's hilarious to me that solving a Millennium problem has given mathematicians a reason to doubt the mathematical abilities of LLMs.

Quite a few of the challenges revolve around asking for LLMs to complete tasks reliably and aren't about whether an instance of an LLM completing the task exists. Quite a few of the goalposts are consequently completely changed without the surrounding context, are not the same as what the HN commenter requested and hence seem disingenuous to me.

They look at each problem individually.

As the ARC AGI guidelines [1] state, 'a core design principle of ARC-AGI is that the test taker must not know what the test will be.'

[1] https://arcprize.org/policy#dataset-security

Being a superset of Python may not be necessary to be successful, but perhaps non-committally proposing it was necessary for Modular to win the funding they wanted. While lots of people indirectly run GPU kernels with PyTorch, I think the number of people wanting to write their own kernels is considerably smaller and that this niche already has established players (plenty of whom even already build on top of MLIR), making Mojo's most obvious use case difficult to sell.

I think it was there for marketing purposes and that there was little actual intention to work on it.

From the roadmap:

>Mojo may or may not evolve into a full superset of Python, and it's okay if it doesn't.

I don't think the goal of being a true Python superset ever existed.

Given that there are so many failed attempts to optimise arbitrary Python code, it was dubious from the start. Furthermore, the documentation completely ignored these challenges and made it clear that Mojo's goal was to compile to MLIR in order to write kernels for machine learning. The first example of Mojo code was a low level matrix multiplication kernel taking advantage of fancy compilation features and the documentation advertised pointers inspired by Rust's move semantics, neither of which are typically considered friendly or relevant to high level programmers.

An AI able to play Slay the Spire sounds pretty impressive!

What do you mean by agent in this context? Does it mean LLMs?

What search problem are you solving for deck building and is MCTS for combat the same as that in Go AIs?

At the time, Java ran on the web so he could easily share demos.

He used LWJGL, which probably covered a lot of his library needs.

Java has a JIT, so it's not comparable to Ruby and Perl.

Is it mainly the reactivity part of Vue that you benefit from, or are there other aspects which are important?

While perhaps this is on me for not stating my position while repeating Bill's comment, I think you are unfairly assuming bad faith.

You are wrong to state that I am motivated by fanatism or jealousy.

I have no involvement whatever with Odin and am in agreement with the parent article (though I think it's personal criticisms veer a bit too far). The creator of Odin using Odin at jangafx is not an appropriate source in my view.

It is disappointing to see that the v programming language has a Wikipedia article given it's history of being essentially fraudulent.

Perhaps it is because Malbolge is notable within the category of esolangs.

Is there any reason why they're not considering a single '?' like rust? Is it a parsing issue?

So you'd have: obj?:method(…)

But it demonstrates that LLMs struggle with basic reasoning. A criticism of LLMs is that they're imitating without a understanding of what they're doing and without a clear plan, so this inability to solve a simple logic puzzle is very relevant. If LLMs didn't struggle with reasoning problems then something like ARC-AGI wouldn't exist.

If you're happy with NumPy's API, then surely JAX is exactly what you're looking for.

You can't claim to have superior knowledge if you admit you're wrong.

> Once this happens, players will be able to switch between OpenGL rendering and Vulkan rendering

I think this means you'll be able to continue using Minecraft with OpenGL.

What would be the best way to use Vulkan 1.4 in Rust today? Using the C headers with bindgen or writing my own vk.xml generator?

Clip Studio Paint seems very popular for animation. You could also consider Aseprite for pixel art animation.

Really fun! Developing my intuition for a sphere as I played was a nice experience. As other commenters have mentioned, the game ramps up a bit too slowly. Perhaps it would worth adding more than one food item.

One of the reasons I'm really excited about JAX is that I hope it will allow me to write fast Python code without worrying about these details.

Has the talent moved to anywhere in particular?

People still appear to use Flash these days by downloading an old version and getting a license key from Reddit/YouTube/etc.

Can confirm as someone who was using pre-subscription Office to write/read files while everyone else at work was using the 365 version. Now that I'm using 365 too, I do however appreciate the ability to do shared live editing in the office programs.

If CLU only supported composition, was the Liskov substitution principle still applicable to CLU?

For me, it's the very basics of general relativity which made the distinction between the cotangent and tangents space click. Optimisation on Riemannian manifolds might give an opportunity to apply more interesting tensor calculus with a non-trivial metric.

A good use of linear algebra that I'm working with at the moment is the use of splines as a basis for real (vector) functions. After obtaining the matrix/vector representations you can solve for the spline coefficients (and then plot them).

Linear transforms (such as rotations and displacements) in GPU graphics.

Fourier series in signal processing.

JPEG compression.

Obtaining the best fit element in a vector space of curves given data or other constraints.

Understanding autodiff in JAX.

The mathematical definition of a tensor helps develop intuition for manipulating arrays/tensors in array libraries.

Transition matrices of a Markov chain.

PageRank.

At least you're working with Rust now.

As someone with zero knowledge of psychology, I'm biased against it. Partly because of my vague impression that psychology tries to fit people to models, rather than viewing models as limited approximations.

For a while I've thought it would be nice to know what results the field of psychology actually has that are trusted. Was there anything at all in the taught content which you liked? I didn't realise the DSM-V was that bad. If research on trans people can be cherry-picked, then does that mean that some reliable research exists?