TLDR: It's MIT licensed

Edit: don't bet or gamble, we build this for curiosity, not to push unethical businesses!

Comments URL: https://news.ycombinator.com/item?id=44983829

Points: 1

# Comments: 1

Sure, astral's products are remarkable and widely loved, but I would like to understand if there's a USP beyond that?

- There is already a mlflow builtin tool to log shap plots. This is quite helpful but becomes tedious if you want to dive deep into explainability, e.g. if you want to understand the influence factors for 100s of observations. Furthermore they lack interactivity. Here's the link to the builtin tool: https://mlflow.org/docs/latest/ml/evaluation/shap

- There are tools like shapash or what-if tool, but those require a running python environment. This plugin let's you log shap values in any productive run and explore them in pure html, with some of the features that the other tools provide (more might be coming if we see interest in this).

Here are the links: what-if tool (though it's not actively maintained): https://github.com/PAIR-code/what-if-tool

shapash: https://github.com/MAIF/shapash

Comments URL: https://news.ycombinator.com/item?id=44656682

Points: 4

# Comments: 2

What it does: - generates standardized interactive XAI visualizations with just a few lines of code - support for open-source ML libraries (supports scikit-learn, XGBoost, TensorFlow, PyTorch, etc.) - model explanations, feature importance - scales to millions of predictions via cloud infrastructre scaling (only on hosted plan) - let's you run XAI procedures in parallel to inference runs - collaboration-ready insights for both devs and non-tech stakeholders - easy integration via Python SDK or REST API - helps fulfill GDPR or CCPA requirements

Check it out, have a look at the sample use case and let us know what you think.

Comments URL: https://news.ycombinator.com/item?id=44365693

Points: 2

# Comments: 0

- Project manager mathematicians: Tao draws a future where mathematical insights are "produced" like anything else in our society. He attributes the lack of this productionalization of mathematics to a lack of tools in this area but AI and proof assistants might be revolutionary in this regard (proof assistants already are). Human interaction and guidance still needed

- Implicit Knowledge: he points out that so much knowledge is not in papers, e.g. intuition and knowledge of failures. This is crucial and makes it necessary even for top mathematicians to talk to one another to not make mistakes again.

- Formalization of mathematics: one would think that mathematics is pretty formalized already (and it is) but in the papers a lot of common knowledge is taken for granted so having proofs formalized in such a way that proof assistants can understand will help more people actually understanding what is going on.

I think this just shows how Tao always searches for new ways to do mathematical research, which I first came across in his talk about one of the polymath projects.

These ideas are repeated often and I lean more to the specificity side of things: you only get good at what you learn/train. You won't become better at decision maker by learning chess/poker, you won't (or just become a slightly better) endurance swimmer by becoming a good runner, you won't understand human psychology by getting good at coding.

I remember a talk of top-notch mathematics where they were asked about related mathematical topics and most of them would just answer something like: "I just try to understand my field of mathematics well, I can't say much about something else". This was the discussion from the Breakthrough Prize in Mathematics 2015: https://www.youtube.com/watch?v=eNgUQlpc1m0&list=PLyF3OMOiy3...

Comments URL: https://news.ycombinator.com/item?id=39641488

Points: 1

# Comments: 1

Thanks

Comments URL: https://news.ycombinator.com/item?id=37723667

Points: 1

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Comments URL: https://news.ycombinator.com/item?id=37483155

Points: 3

# Comments: 4

Comments URL: https://news.ycombinator.com/item?id=32737479

Points: 7

# Comments: 17

That said, I always choose optimism over so called realism and pessimism. This optimism doesn't mean that anything changes for the better by itself but that personal decisions can have an impact for the better.

For me that means that reducing the barrier to start is the most important aspect to get things done, gamification (as suggested in the article) can help of course.