awesome-ai-safety VS hn-search

Giskard - Testing framework for ML models| Multiple roles | Full-time | France | https://giskard.ai/

We are building the first collaborative & open-source Quality Assurance platform for all ML models - including Large Language Models.

Founded in 2021 in Paris by ex-Dataiku engineers, we are an emerging player in the fast-growing market of AI Quality & Safety.

Giskard helps Data Scientists & ML Engineering teams collaborate to evaluate, test & monitor AI models. We help organizations increase the efficiency of their AI development workflow, eliminate risks of AI biases and ensure robust, reliable & ethical AI models. Our open-source platform is used by dozens of ML teams across industries, both at enterprise companies & startups.

In 2022, we raised our first round of 1.5 million euros, led by Elaia, with participation from Bessemer and notable angel investors including the CTO of Hugging Face. To read more about this fundraising and how it will accelerate our growth, you can read this announcement: https://www.giskard.ai/knowledge/news-fundraising-2022

In 2023, we received a strategic investment from the European Commission to build a SaaS platform to automate compliance with the upcoming EU AI regulation. You can read more here: https://www.giskard.ai/knowledge/1-000-github-stars-3meu-and...

We are assembling a team of champions: Software Engineers, Machine Learning researchers, and Data Scientists ; to build our AI Quality platform and expand it to new types of AI models and industries. We have a culture of continuous learning & quality, and we help each other achieve high standards & goals!

We aim to grow from 15 to 25 people in the next 12 months. We're hiring the following roles:

Giskard - Testing framework for ML models| Multiple roles | Full-time | France | https://giskard.ai/

We are building the first collaborative & open-source Quality Assurance platform for all ML models - including Large Language Models.

Founded in 2021 in Paris by ex-Dataiku engineers, we are an emerging player in the fast-growing market of AI Safety & Security.

Giskard helps Data Scientists & ML Engineering teams collaborate to evaluate, test & monitor AI models. We help organizations increase the efficiency of their AI development workflow, eliminate risks of AI biases and ensure robust, reliable & ethical AI models. Our open-source platform is used by dozens of ML teams across industries, both at enterprise companies & startups.

In 2022, we raised our first round of 1.5 million euros, led by Elaia, with participation from Bessemer and notable angel investors including the CTO of Hugging Face. To read more about this fundraising and how it will accelerate our growth, you can read this announcement: https://www.giskard.ai/knowledge/news-fundraising-2022

In 2023, we received a strategic investment from the European Commission to build a SaaS platform to automate compliance with the upcoming EU AI regulation. You can read more here: https://www.giskard.ai/knowledge/1-000-github-stars-3meu-and...

We are assembling a team of champions: Software Engineers, Machine Learning researchers, and Data Scientists ; to build our AI Quality platform and expand it to new types of AI models and industries. We have a culture of continuous learning & quality, and we help each other achieve high standards & goals!

We aim to grow from 15 to 25 people in the next 12 months. We're hiring the following roles:

* Software Engineer - https://apply.workable.com/giskard/j/AD2C90B581/ (Python, Java, Typescript, Vue.js, Cloud skills)

* Machine Learning Researcher - https://apply.workable.com/giskard/j/E89FE8E310/ (post-PhD)

* Data Science lead - https://apply.workable.com/giskard/j/E89FE8E310/ (ML + consulting experience required)

* Growth marketing intern - https://apply.workable.com/giskard/j/C8635E9B0C/

* Data Science intern - https://apply.workable.com/giskard/j/7F0B341852/

Hi! I’ve been working on this automatic scanner for ML models to detect issues like underperforming data slices, overconfidence in predictions, robustness problems, and others. It supports all main Python ML frameworks (sklearn, torch, xgboost, …) and integrates with the quality assurance solution we are building at Giskard AI (https://giskard.ai) to systematically test models before putting them in production.

It is still a beta and I would love to hear your feedback if you have the time to try it out.

We have quite a few tutorials in the docs with ready-made colab notebooks to make it easy to get started.

If you are interested in the code:

https://github.com/Giskard-AI/giskard/tree/main/python-clien...

Repository: https://github.com/Giskard-AI/awesome-ai-safety

- Ads with Psychological tricks

Truly good websites have around 2 facts per 10 word sentence, and get instantly to the chase. Also: good websites give you the names of all their competitors/alternative websites before showing their own stuff, and give you further reading.

Right now the world of technology is supposedly more innovative than ever, but somehow Wikipedia (https://www.wikipedia.org/) and Search Hackernews (https://hn.algolia.com/) beat billion dollar search engines.

Articles written decades ago are still unsurpassed in terms of quality and ease of understanding, but the best modern websites can do is textbook explanations. It is time society graduates from boilerplate buzzword textbook culture.

Now the gems of the internet are slowly being buried beneath mountains of trash.

If something sounds boilerplate it isn't good enough.

Don't bother saying something that has been said before, and better.

>for more detail: https://hn.algolia.com/?dateRange=all&page=0&prefix=false&qu...

Oh, I see. We actually discussed Pound about four years ago - just a little back and forth about the ABC of Reading: https://news.ycombinator.com/item?id=24196681

>What's your explanation of why Pound went Fascist?

I'm not sure I particularly have one; I haven't read any of his longer political or cultural (i.e. non-literary) works. I just think it's silly to correlate an approach to translation that you dislike with fascism. Especially as I'm not sure it even makes sense on its own terms: I can only read your comment as 'lazy translator? Figures that he would be a fascist', but if I imagine the type of translation a fascist would approve of, the approach I picture is fastidious, fussy, concerned with fidelity to the point of stickler-ishness. (Isn't that from where we get 'grammar nazi'?)

And oh, well, since you ask I'll take a shy at it: my vague sense is that he became fascist because saw a society in decline due to it becoming more and more a sham society: opulence without virtue, power without vigour, money no longer tied to actually existing goods. (Of course, all of this shades easily into antisemitism.) He saw fascism as the answer; It's easier to see in retrospect that it wasn't.

"multiplayer notepad" goes back 15 years at least - https://hn.algolia.com/?dateRange=all&page=0&prefix=false&qu... notepad&sort=byDate&type=comment

it was used back with a popular website which opened a text document and anyone viewing could type, but I can't remember the name. That became a thing in Google Docs, Microsoft Office, Floobits, and lots of self-hosted and cloned sites.

If you see a post that ought to have been moderated but hasn't been, the likeliest explanation is that we didn't see it. You can help by flagging it or emailing us at [email protected].

https://hn.algolia.com/?dateRange=all&page=0&prefix=false&qu...

Ok, but please don't post unsubstantive comments to Hacker News.

I understand the reason for repeating these sentiments—it's the same reason why they get upvoted to the top of threads*—but repetition of this kind is what we're most trying to avoid here.

https://hn.algolia.com/?dateRange=all&page=0&prefix=false&so...

https://news.ycombinator.com/newsguidelines.html

* I've marked this one off topic now.

I was looking for it in the guidelines. There are a couple of conventions for postings. Consider a bit of prior examples: [https://hn.algolia.com/?q=show+hn]

yeah there are only three stories coming up from the site search

https://hn.algolia.com/?q=postgres+clustering

only one is semanthically correct, the other pick up the wrong version of clustering (i.e. k-means instead of multi master writes)

but yeah if one doesn't test the hard cases, how does one know it preserves semantics :D

Like dismissing the work of Feyerabend or Wittgenstein without seemingly having read either:

https://hn.algolia.com/?dateRange=pastMonth&page=0&prefix=tr...

https://hn.algolia.com/?dateRange=all&page=0&prefix=true&que...