toxicity VS datapane

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...

If you're looking for an easy way to build an HTML report using Python, you might find Datapane (https://github.com/datapane/datapane) helpful. I'm one of the people building it! We don't support polars (yet, on the roadmap) but we do support pandas so you can convert to a pandas DataFrame and include your data and any plots, etc.

If you're interested in an easier way to create reports using Python and Plotly/Pandas, you should check out our open-source library, Datapane: https://github.com/datapane/datapane - you can create a standalone, redistributable HTML file in a few lines of Python.

You might be interested in what we're hacking on at Datapane (I'm one of the founders): https://github.com/datapane/datapane.

You can create standalone HTML data reports from Python/Jupyter in ~3 lines of code: https://docs.datapane.com/reports/overview/

You can build web apps from Jupyter using Datapane [0]. I'm one of the founders, so let me know if I can help at all.

You can either export a static site [1] (and host on GH pages or S3), or, if you need backend logic, you can add Python functions [2] and serve on your favourite host (we use Fly).

We have specific Jupyter integration to automatically convert your notebook into an app [3].

[0] https://github.com/datapane/datapane

[1] https://docs.datapane.com/reference/reports/#datapane.proces...

[2] https://docs.datapane.com/apps/overview/

[3] https://docs.datapane.com/reports/jupyter-integration/#conve...

Our GitHub is https://github.com/datapane/datapane and you can get started here: https://docs.datapane.com/quickstart/

Thanks a lot! Yes, absolutely, a few people have brought this up and working working on removing the header right now. If I can help at all, feel free to reach us on GH Discussions: https://github.com/datapane/datapane/discussions