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

If there's a workaround, it's ok. Users usually post workarounds in the thread.

This is in the FAQ at https://news.ycombinator.com/newsfaq.html and there's more explanation here:

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

https://news.ycombinator.com/item?id=10178989

Some HN threads on "glass ceiling"

* "A Truth About the Glass Ceiling No One Wants to Talk About" https://news.ycombinator.com/item?id=5130335

* "Glass Walls: Partial Solution to The Glass Ceiling?" https://news.ycombinator.com/item?id=7423648

* more: https://hn.algolia.com/?q=glass+ceiling

It looks like the most commented-on posts are from 10+ years ago.

I first heard of Solarpunk from the Imaginary Worlds podcast:

https://www.imaginaryworldspodcast.org/episodes/solarpunk-th...

Which I prompted me to post the Wikipedia link 4 years ago, several others posted similar links prior to that, and others have posted interesting links hear too:

https://hn.algolia.com/?dateRange=all&page=3&prefix=false&qu...

I will deeply deeply having someone so well connected to such incredibly complex contemporary digital rights issues in a place of power. Patrick Breyer's work in advocating & sharing what's going on has been such an incredibly high form of service, has illuminated such a dark & scary part of governance, and it's hard to imagine who else in the world is going to step up & be the light in Patrick's absence.

Patrick, thank you for the many years of incredible service. Your writing online about what's happening is without peer. https://hn.algolia.com/?query=patrick%20breyer&sort=byDate

Anything this common becomes noise, since it doesn't add any new information.

Heres' another way to look at it: since the idea of HN is to be intellectually interesting (https://hn.algolia.com/?dateRange=all&page=0&prefix=true&sor...), repetition is the most important thing to avoid (https://hn.algolia.com/?dateRange=all&page=0&prefix=false&so...).

At least as far as Hacker News is concerned, I'd call htmx way more marketed. It has hundreds of HN submissions in the past year alone [0] including one that broke 1000 points, compared to Hotwire which is sitting at about 40 submissions in the past year [1], the most popular of which is this one.

[0] https://hn.algolia.com/?dateRange=pastYear&prefix=true&query...

[1] https://hn.algolia.com/?dateRange=pastYear&prefix=true&query...

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