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LangSmith integrates with OpenTelemetry: https://blog.langchain.dev/opentelemetry-langsmith/

Almost none of those things are part of the LangGraph framework? LangGraph does the scheduling, checkpointing, state management, etc.

All of those things are LangChain abstractions that you can use when building a graph.

Yes but loading weights into memory takes time

Making maple syrup from sap is an illuminating experience. You have to reduce something like 40x the volume of sap to create the desired quantity of syrup.

Promethease [1] is a great resource

[1] https://www.promethease.com/

10% of income is the standard

My prior intuition was that rank-choice voting would be preferable to approval voting, but this [1] was pretty helpful. Thanks!

[1] https://electionscience.org/library/approval-voting-versus-i...

Don't forget the Colossal Clean Crawled Corpus [1] too!

Came here thinking it was another neural network + data visualization tool.

[1] https://ai.googleblog.com/2020/02/exploring-transfer-learnin...

Seems to be based on features generated using a model similar to that proposed in [1].

[1] https://research.google/pubs/pub45611/

I think the parent's point is that since price increases are capped, landlords cannot increase beyond a certain point in a single bumper year. To compensate, they may increase rents beyond what they would otherwise to be able to maintain a similar average increase. Citation is needed, of course.

The "bookcorpus" is from this paper by Zhu, Kiro, et. al. [0]. You can see the project web page here [1] which indicates you can crawl books from this site [2] to create your own. This repo seeks to replicate the original dataset [3]

[0] https://www.cv-foundation.org/openaccess/content_iccv_2015/p...

[1] https://yknzhu.wixsite.com/mbweb

[2] https://www.smashwords.com/

[3] https://github.com/sgraaf/Replicate-Toronto-BookCorpus

There's also a huge variance in microphone quality for Android devices. The engineering focus to ensure uniform sound quality could take away from the team's focus in its early stages.

Zipline is having real impact in places with insufficient infrastructure to quickly transport medical supplies.

https://flyzipline.com/

F# was one of the first languages I learned. Great resource!

Hugged until KO: https://web.archive.org/web/20210204154139/http://www.theora...

Then they can enact a moritorium on leverage buys to protect themselves. They have no liability for clients who are buying without leverage.

Does this not discourage lending? Who would issue a loan the year before a debt jubilee?

Has there been any good work applying causal inference explicitly to common NLP tasks like question-answering? Or to game-play? The lack of common-sense in models like GPT-3 would seem to indicate a huge opportunity, perhaps in tandem with COMET[0] or some other graph-based approach. [0] https://arxiv.org/abs/1906.05317