miket

4 ms·

1.
Diffbot GraphRAG LLM(github.com)
2 points by miket 2y ago|1 comments
2.
by miket 2y ago
Open source LLM that outperforms ChatGPT search mode, Gemini, and Perplexity
3.
OpenAI Jukebox(jukebox.openai.com)
2 points by miket 3y ago|1 comments
4.
by miket 3y ago
Here's a good way to identify how entity-dense your text is: https://demo.nl.diffbot.com/
5.
by miket 4y ago
Much easier to exit than standard vim!
6.
by miket 4y ago
Any question asking about the letters of words is bound to underwhelm because GPT3 is trained on sub-word tokens, so it does not have random access to individual letters. The word "prime" is tokenized as a single token, instead of
7.
How to Upload Your Consciousness to Physical Infrastructure Using Docker Compose(digitalocean.com)
13 points by miket 4y ago|1 comments
8.
by miket 4y ago
https://www.diffbot.com/products/extract/ works pretty well.
9.
by miket 5y ago
https://en.wikipedia.org/wiki/Wu_Dao
10.
by miket 5y ago
https://twitter.com/andrewyng/status/930938692310482944
11.
From Knowledge Graphs to Knowledge Workflows(blog.diffbot.com)
2 points by miket 6y ago|0 comments
12.
by miket 6y ago
MediaWiki, the software that Wikipedia uses is open source and Wikibase, the software that WikiData uses is also open source
13.
The Hottest Chat App for Teens Is Google Docs (2019)(theatlantic.com)
1 points by miket 6y ago|0 comments
14.
Know-it-all AI learns by reading the entire web nonstop(technologyreview.com)
4 points by miket 6y ago|0 comments
15.
Photonic tensor cores for machine learning(aip.scitation.org)
4 points by miket 6y ago|0 comments
16.
by miket 6y ago
> To put it plainly, if you don't have enough data to train a machine learning model, what, exactly, are your options? There is only one option: to do the work by hand. Wikipedia, with its army of volunteers, has a much better shot
17.
by miket 6y ago
Hi, founder of Diffbot here, we are an AI research company spinout from Stanford that generate the world's largest knowledge graph from crawling the whole web. I didn't want to comment, but I see a lot of misunderstandings here ab
18.
Flatten the Curve – How to Control an Artificial Life Pandemic(youtube.com)
3 points by miket 7y ago|0 comments
19.
by miket 7y ago
The article hardly supports its conclusion with these cherry-picked examples; however, the core reason these results don't meet the author's expectations is that Google's AI does not understand the content of webpages well en
20.
by miket 7y ago
When people think about using computers for Natural Language Processing, they often think about end-tasks like classification, translation, question answering, and models like BERT that model the statistical regularities in text. However,
21.
KnowledgeNet: A Benchmark for Knowledge Base Population(blog.diffbot.com)
33 points by miket 7y ago|7 comments
22.
by miket 7y ago
Seconded on Insomnia - I switched to it when encountering a bug in the encoding of the curl command generation in Postman, and haven't looked back.
23.
by miket 7y ago
I think there can very much be two segments. Both a high-volume self-service segment (I know this is what I prefer when evaluating developer tools) as well as a high-touch enterprise segment for training and implementation (think Bloomberg
24.
The Diffbot Master Plan(blog.diffbot.com)
1 points by miket 7y ago|0 comments
25.
The Economics of Building Knowledge Bases(blog.diffbot.com)
104 points by miket 7y ago|9 comments
26.
Neural Network(nxxcxx.github.io)
154 points by miket 7y ago|14 comments
27.
The Economics of Building Knowledge Bases(blog.diffbot.com)
1 points by miket 7y ago|0 comments
28.
Diffbot's Approach to Knowledge Graph(blog.diffbot.com)
2 points by miket 7y ago|0 comments
29.
The Diffbot Master Plan(blog.diffbot.com)
2 points by miket 7y ago|0 comments
30.
by miket 7y ago
Much of the knowledge that humans derive from reading text is implicit rather than explicit. The derived knowledge is also context-dependent and probabilistic, i.e. they are not binary facts but we assign a degree of confidence to them. In

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