rosstaylor90

Many math questions are easy to verify, and it's a classic benchmark for reasoning -> so it's a good hill to climb.

I agree with your meta-point that better benchmarks testing more types of task would be good!

RL has more than two steps...

I disagree, 10 years ago AIs nailing these types of competition would have been seen as very impressive. The fact goal posts can move on this now shows how much AI has progressed.

(Also the term “approximate retrieval” is a bad one - reasoning is inherently a process of chaining together associations. What matters is whether the reasoning reaches the right conclusions. Still some way to go, but already very impressive in tasks traditionally considered harbours of human reasoning!)

Thanks for feedback! Yes, we’re looking to improve quality in the coming months. Couple of notes:

- The initial use of data is distillation so we’re less bound by question quality (anything that evinces output diversity is good).

- But moving onto RL, we’ll need stronger quality. We have much better things planned both on data filtering and verification!

- Surprisingly, a lot of ML datasets actually look like this when you look under hood. We’re hoping having more eyeballs on it will help improve quality in long run over less transparent status quo!

Happier now, upgraded the backend :) (co-creator here)

What's your AIME 2025 score? https://gr.inc/RJT1990/AIME2025/

No, the primary reason is that the UK is a heavily service-based economy. Quarantine impacts the service-based subset of the economy the most. Therefore it makes sense that the UK would be hard hit. A “nation of shopkeepers” suffers when the shops are closed...

Ed Thorp’s Princeton/Newport Partners was the first great quant hedge fund.

I'm from Suffolk - my school used to go here on school trips. The funny thing about the site is that it's basically just a hill in a field now, so needless to say it was a massive letdown for eight-year-old me who was expecting to see a massive Viking longboat. The tourist centre is nice though.

ATLAS ML | London, UK | Full Stack Developer | Remote | FULL-TIME

Our mission is to systemise the world's deep learning knowledge.

We are building a discovery platform and tooling for deep learning that links ideas with implementations, and allows everyone to access and apply the state of the art in AI. We are a team of researchers and engineers from the University of Cambridge, and our founders include an early core developer at Wikipedia and an open source machine learning developer.

We are looking for a full stack developer to help us develop our popular and growing platform. Our tech is built on Python (Django) and React. Additionally we have a number of other roles - including product and advocacy roles.

Learn more here www.atlasml.io or apply at https://angel.co/atlas-ml/jobs

I think your conclusion is too strong. Yes, we know bigger models and data generally lead to better performance (e.g. BigGAN results last year) but progress in architecture can still speed up progress in ML tasks. If we were still stuck using RNNs and LSTMs for language modeling we wouldn't be talking about this news today.

Philosophical Investigations - Wittgenstein. Just stunningly thoughtful and changed the way I interpret most things around me.

Cool example for a music video here: https://www.youtube.com/watch?v=-k9qDxyxS3s.

Hey all,

One problem we face is how unmodular deep learning code can be, meaning that adapting someone else's code for your own dataset, your own workflow, your own way of training, and so on, can be a real pain.

We made an open source resource and framework to make it easy to combine and train deep learning models and datasets, with a heavy focus on modularity. Right now we have a few example models and datasets - mainly GANs! - that you can play with on the site.

We invite you to contribute to this new open source resource. We will be also adding a lot of content in the coming weeks. Of course, if you have any feedback that would be great too.

I'm going to get one printed in real-life - once I do some superresolution and probably a bit of manual Photoshop editing. Which design do you guys like best?

Hi all, just sharing a project I've been working on.

Mantra is a deep learning development kit that manages the various components in an deep learning project, and makes it much easier to do routine tasks like training in the cloud, model monitoring, model benchmarking and more. It works with your favourite deep learning libraries like TensorFlow, PyTorch and Keras.

This is an very early alpha release, so your comments on the general concept and what you like or don't like about it would be awesome!

Sorry to ask that annoying question that people tend to ask, but how does this differ from https://github.com/trending?