paubric

11 ms·

1.
Local-first CLI tool inspired by Claude's Artifacts UX(noemaresearch.com)
4 points by paubric 2y ago|1 comments
2.
by paubric 2y ago
If you've experimented with Claude's Artifacts, you know how much of an impact good UX can have on dev workflows. We built an internal tool for managing a model's read-write access to external resources, and we're now op
3.
Show HN: Pinboard, pin files for contextual, codebase-level AI assistance(github.com)
1 points by paubric 2y ago|0 comments
4.
The Autoregressive Operating System(paulbricman.com)
6 points by paubric 4y ago|1 comments
5.
Translation Is Pervasive(paulbricman.com)
1 points by paubric 4y ago|0 comments
6.
Diffusion magnetizes manifolds (DALL-E 2 intuition building)(paulbricman.com)
1 points by paubric 4y ago|0 comments
7.
by paubric 5y ago
context: interned at UiPath on a team doing ML A lot of unnecessary hype indeed, though you can actually throw in occasional OCR/NER blocks in the workflow you design. Most often it's common NLP tasks on documents being moved arou
8.
by paubric 5y ago
Thanks for the interest! What I've been playing with in the project is not really a summarizer, though I think it could work well with a summarization model. This one is simply about highlighting relevant bits of a certain text (be it
9.
by paubric 5y ago
What it says on the tin: BERT attention per token gets converted to CSS styling to grab the user's attention. The idea came from thinking about content consumption as perceiving large bodies of information, rather than searching for a
10.
Show HN: Cybersalience – Guiding user attention using transformer attention(paulbricman.com)
3 points by paubric 5y ago|3 comments
11.
by paubric 5y ago
Hi there! The first few paragraphs say it all: I was curious about how we might train a virtual assistant to actually help the user reach conclusions, rather than simply throw in the right answer. While the outcome is far from perfect, it w
12.
Show HN: Oneironomicon – Training collaborative AI on dreamed-up users(paulbricman.com)
2 points by paubric 5y ago|1 comments
13.
by paubric 5y ago
I had similar doubts initially. I went for the name they used in the paper: https://arxiv.org/pdf/2102.05169.pdf . It takes the sentence out of its original context. A "contextualizer" might instead turn a t
14.
by paubric 5y ago
Thanks for the thoughtful reply! If I understood correctly, you argue that the lexiscore might still lead you down a rabbit hole, even if through ever more challenging ideas, rather than helping you find nutritious content outside that echo
15.
by paubric 5y ago
I'm really glad you like it! It should soon get its biggest update yet, related to sharing features / learning in public. More details at the end of this last article: https://paulbricman.com/reflections/think
16.
by paubric 5y ago
tldr: You add content in a self-hosted web app (e.g. as RSS, PDF, EPUB...), and it measures how interesting it is by trying to reconstruct it with a GPT-3-like model and seeing how predictable it is. Indeed, the page is more of a write-up t
17.
by paubric 5y ago
It could work if the extension called on a server to do the heavy lifting of reconstructing the text with the language model. I have a feeling that trying to do it all in the browser today would essentially mean implementing non-trivial par
18.
by paubric 5y ago
Thanks for the kind words! I totally agree, I feel we'll look back at how we currently find online content in a few years from now and wonder how could we possibly be okay with it.
19.
by paubric 5y ago
Hi all, I started experimenting with this new approach to finding valuable content online after I got frustrated with traditional recommendation systems leading to echo chambers and all sorts of other nasty failure modes listed in the write
20.
Show HN: Lexiscore – a nutritional label for food for thought(paulbricman.com)
66 points by paubric 5y ago|12 comments
21.
by paubric 5y ago
That would be a neat little study for one of those people with a casual Obsidian vault of 80K notes: 1. Randomly pick 2 notes 2. Compute semantic distance and minimum traversal distance through the graph (Linkedin 3rd degree connection styl
22.
by paubric 5y ago
The conceptarium (currently) uses OpenAI's CLIP model which encodes both texts and images into a semantic space so that related items are close to each other. This means that if you have a picture of a bike pump and a written note abou
23.
by paubric 5y ago
Thanks for the thoughtful bit of commentary! It's true, my disproportionate focus on embeddings and no explicit links might have been just an extreme reaction to the current state of tools for thought which are 99% graph-based. Was cur
24.
Unconference on Building Tools for Thought(opencollective.com)
3 points by paubric 5y ago|0 comments
25.
Awesome-Doesnotexist – An Existing List of Thispersondoesnotexist-Style Projects(github.com)
3 points by paubric 8y ago|0 comments
26.
Synthetic Bots – The Ultimate Guide to Being Human(medium.com)
1 points by paubric 8y ago|0 comments
27.
DeepFake Ransomware – What happens when harassment gets automated at scale?(medium.com)
2 points by paubric 8y ago|0 comments