toxicity VS Fleet

I'm a PM at a human data company (https://www.surgehq.ai) that helps the large language model companies ensure their models are safe (we're the “clever prompt engineers” who helped Redwood assess their model performance).

We actually just published a blog today that includes our perspective on building “AI red teams” and best practices for AI alignment/safety: https://www.surgehq.ai/blog/ai-red-teams-for-adversarial-tra...

I'd love to chat. Want to reach out to the email in my profile? I'm the founder of a much higher-quality data startup (https://www.surgehq.ai), and previously built the human computation platforms at a couple FAANGs.

We work with a lot of the top AI/NLP companies and research labs, and do both the "typical" data labeling work (sentiment analysis, text categorization, etc), but also a lot more advanced stuff (e.g., training coding assistants, evaluating the new wave of large language models, adversarial labeling, etc -- so not just distinguishing cats and dogs, but rather making full use of the power of the human mind!).

> Rather than operating under a strict definition of toxicity, we asked our team to identify comments that they personally found toxic.

[0]: https://github.com/surge-ai/toxicity

Love language? So do we, and our mission is to infuse AI with that same love. At Surge, we're building the human infrastructure to power NLP — from detecting hate speech, to parsing complex documents, to injecting human values into the next wave of language models. Our first product is a platform that helps ML teams create amazing, human-powered datasets to train AI in the richness of language. We're a team of former Google, Facebook, and Airbnb engineering leads, and we work with top companies at the forefront of machine learning. Our tech stack is Ruby on Rails, React, and Python. We’re rapidly growing, and we're looking for full-stack engineers to join the team and develop our product. To apply, please email [email protected] with a resume and 2-3 sentences describing your interest in Surge. We love personal projects and writings too!

More information: https://www.surgehq.ai/about#careers

A blog post explaining the problems we are working to solve: https://www.surgehq.ai/blog/the-ai-bottleneck-high-quality-h...

Yo! We're working on the fix. You can track progress here: https://github.com/fleetdm/fleet/issues/17165

Disclosure #2: I'm the CEO

One of my fav things about this is that we're solving the "Linux MDM problem". As a person who likes to use Linux, it's exciting that, no matter how big the company gets, I can still use whatever OS I want at work (and still be "offboard-able", with everyone passing their audits.)

Source code for Fleet is available at https://github.com/fleetdm/fleet.

It is indeed early stage. The oldest company is Fleet https://fleetdm.com/ who do open source device management and raised at $100m post in 2022 https://techcrunch.com/2022/04/28/fleet-nabs-20m-to-enable-e...

Thanks for clarifying. You may want to look into Fleet at the link below. The intent of the question wasn't to voice an opinion but to determine if any opensource solutions that cost more to support via self-hosting would incur more costs than Intune licenses if it's only for one customer.

Looking at Fleet for managing primarily Mac-based environments.

* https://github.com/fleetdm/fleet

Supposedly, One can search github using `language:typescript filename:docker-compose.yml stars:>1000` but it's not working for me somehow.

Osquery + Fleet. https://osquery.io/ https://fleetdm.com/, using the two allows you to build a query to answer what ever questions you (or an auditor) might have about your environment.

Also see Fleet (https://fleetdm.com/) for an open source self-hosted solution. I'm currently using this at a small company to query / enforce policies across a bunch of Windows laptops.