As of v7:
- ~9M images
- 600 object classes
- bounding boxes
- visual relatoinships are really hard: storage.googleapis.com/openimages/web/factsfigures_v7.html#visual-relationships e.g. "person kicking ball": storage.googleapis.com/openimages/web/visualizer/index.html?type=relationships&set=train&c=kick
- google.github.io/localized-narratives/ localized narratives is ludicrous, you can actually hear the (Indian women mostly) annotators describing the image while hovering their mouses to point what they are talking about). They are clearly bored out of their minds the poor people!
This section is about companies that primarily specialize in machine learning.
The term "machine learning company" is perhaps not great as it could be argued that any of the Big tech are leaders and sometimes, especially in the case of Google, has a main product that is arguably a form of machine learning.
Interesting website, hosts mostly:
- datasets
- ANN models
- some live running demos called "apps": e.g. huggingface.co/spaces/ronvolutional/ai-pokemon-card
What's the point of this website vs GitHub? www.reddit.com/r/MLQuestions/comments/ylf4be/whats_the_deal_with_hugging_faces_popularity/
Many people believe that knowledge graphs are a key element of AGI: Knowledge graph as a component of AGI.
Bibligraphy:
Related:
- twitter.com/yoheinakajima/status/1759107727463518702 "smallest RAG test possible of an indirect relationship on a knowledge graph"
- www.quora.com/Do-knowledge-graphs-bases-have-a-place-in-the-pursuit-of-artificial-general-intelligence-AGI-or-can-their-features-be-better-represented-in-a-learning-based-system "Do knowledge graphs / bases have a place in the pursuit of artificial general intelligence (AGI), or can their features be better represented in a learning-based system?"
GraphRAG: The Marriage of Knowledge Graphs and RAG by Emil Eifrem
. Source. This is one of those idealistic W3C specifications with super messy implementations all over.
In this tutorial, we will use the Jena SPARQL hello world as a starting point. Tested on Apache Jena 4.10.0.
Basic query on rdf/vcard.ttl RDF Turtle data to find the person with full name "John Smith":Output:
sparql --data=rdf/vcard.ttl --query=<( printf '%s\n' 'SELECT ?x WHERE { ?x <http://www.w3.org/2001/vcard-rdf/3.0#FN> "John Smith" }')---------------------------------
| x |
=================================
| <http://somewhere/JohnSmith/> |
---------------------------------To avoid writing Output:
http://www.w3.org/2001/vcard-rdf/3.0# a billion times as queries grow larger, we can use the PREFIX syntax:sparql --data=rdf/vcard.ttl --query=<( printf '%s\n' '
PREFIX vc: <http://www.w3.org/2001/vcard-rdf/3.0#>
SELECT ?x
WHERE { ?x vc:FN "John Smith" }
')---------------------------------
| x |
=================================
| <http://somewhere/JohnSmith/> |
---------------------------------Bibliography:
- UniProt contains some amazing examples runnable on their servers: sparql.uniprot.org/.well-known/sparql-examples/
Pinned article: Introduction to the OurBigBook Project
Welcome to the OurBigBook Project! Our goal is to create the perfect publishing platform for STEM subjects, and get university-level students to write the best free STEM tutorials ever.
Everyone is welcome to create an account and play with the site: ourbigbook.com/go/register. We belive that students themselves can write amazing tutorials, but teachers are welcome too. You can write about anything you want, it doesn't have to be STEM or even educational. Silly test content is very welcome and you won't be penalized in any way. Just keep it legal!
Intro to OurBigBook
. Source. We have two killer features:
- topics: topics group articles by different users with the same title, e.g. here is the topic for the "Fundamental Theorem of Calculus" ourbigbook.com/go/topic/fundamental-theorem-of-calculusArticles of different users are sorted by upvote within each article page. This feature is a bit like:
- a Wikipedia where each user can have their own version of each article
- a Q&A website like Stack Overflow, where multiple people can give their views on a given topic, and the best ones are sorted by upvote. Except you don't need to wait for someone to ask first, and any topic goes, no matter how narrow or broad
This feature makes it possible for readers to find better explanations of any topic created by other writers. And it allows writers to create an explanation in a place that readers might actually find it.
Figure 1. Screenshot of the "Derivative" topic page. View it live at: ourbigbook.com/go/topic/derivativeVideo 2. OurBigBook Web topics demo. Source. - local editing: you can store all your personal knowledge base content locally in a plaintext markup format that can be edited locally and published either:This way you can be sure that even if OurBigBook.com were to go down one day (which we have no plans to do as it is quite cheap to host!), your content will still be perfectly readable as a static site.
- to OurBigBook.com to get awesome multi-user features like topics and likes
- as HTML files to a static website, which you can host yourself for free on many external providers like GitHub Pages, and remain in full control
Figure 3. Visual Studio Code extension installation.
Figure 4. Visual Studio Code extension tree navigation.
Figure 5. Web editor. You can also edit articles on the Web editor without installing anything locally.Video 3. Edit locally and publish demo. Source. This shows editing OurBigBook Markup and publishing it using the Visual Studio Code extension.Video 4. OurBigBook Visual Studio Code extension editing and navigation demo. Source. 
- Infinitely deep tables of contents:
All our software is open source and hosted at: github.com/ourbigbook/ourbigbook
Further documentation can be found at: docs.ourbigbook.com
Feel free to reach our to us for any help or suggestions: docs.ourbigbook.com/#contact