- Human Reading Speed (English): ~250 words per minute

- Human Speaking Speed (English): ~150 words per minute

Should be treated like the Doherty Threshold [1] for generative content.

[1] https://lawsofux.com/doherty-threshold/

I get around ~140 ms per token running a 13B parameter model on a thinkpad laptop with a 14 core Intel i7-9750 processor. Because it's CPU inference the initial prompt processing takes longer than on GPU so total latency is still higher than I'd like. I'm working on some caching solutions that should make this bareable for things like chat.

Comments URL: https://news.ycombinator.com/item?id=35192102

Points: 4

# Comments: 0

GPT-3.5 (what's being used here) is a little better at zero-shot in-context learning as it's been intstruction fine-tuned so it's only given the general format in the context.

Search is one application, and it might be crap right now, but for Microsoft it only needs to provide incremental value, for Google it's life or death. Microsoft is still better positioned in both the enterprise (Azure, Office365, Teams) and developer (Github, VSCode) markets.

(Best + Worst + 4 * Average) / 6

One nice property is that it imposes a distribution that adjusts for longer tailed risks.

https://en.wikipedia.org/wiki/Three-point_estimation

[1] https://tailscale.com/kb/1185/kubernetes/#subnet-router

Not fully-featured yet but what I'd like to eventually do is set it up in a similar way to the mermaidjs editor [3]. They encode the entire diagram in the url. That makes it really easy to link to from markdown documents and has the nice benefit that the diagram is immutable for a given url so you don't need a backend to store anything.

[1]: https://www.npmjs.com/package/pikchr-js

[2]: https://pikchr-editor.insert-mode.dev/

[3]: https://mermaid-js.github.io/mermaid-live-editor

[0]: https://zipcpu.com/tutorial/

I'm not sure if this is possible in SQLite, as far as I know the WITH clause is limited to SELECT statements.

> Are they actually efficient in sqlite even for trees?

Recursive common table expressions work by adding returned rows to a queue and then performing the recursive select statement independently on each row in the queue until it's empty.

You can use WITH RECURSIVE to traverse a tree by adding the root node to the queue and recursively visiting adjacent rows until the queue is empty. This works correctly and quickly because trees have only a single path between nodes. If you try the same query on a DAG though it will return every path to a given node, you then have to perform a GROUP BY to find the shortest path outside of the recursive query. In the worst case, if you have a graph with many paths between nodes, this method is exponentially slower than a standard BFS.

[0]: https://github.com/abetlen/sqlite3-bfsvtab-ext

If you're an i3 user here are a couple cool things to check out:

- scratchpad [1]: Little known i3 feature. Let's you put individual windows in a scratch workspace and then pull them up quickly over your regular workspaces. Really useful docs and things like that, I keep my time tracker in a scratch workspace.

- rofi [2]: This is a dmenu replacement with a nicer interface that lets you combine lists of commands in a single search window. I have it configured so I can search through my open windows by title or run any program from the same interface.

[1]: https://i3wm.org/docs/userguide.html#_scratchpad

[2]: https://github.com/davatorium/rofi

From having spent time volunteering at a nursing home, that 87% number is not far off from my experience. I'd add that they tended to put volunteers with people who had less severe forms of cognitive impairment.

That being said, you would occasionally meet people who seemed mentally impervious to aging, I had the pleasure to speak with an 87 year old computer programmer who was still actively using all kinds of technology. He talked to me about punch card programming accounting systems on IBM 1401's and dealing with technology skeptical secretaries who would double check every computer calculation by hand.

According to this survey of Canadian nursing homes, around 87% of residents suffer from some kind of cognitive impairment such as dementia, alzheimer's, or stroke related trauma [1].

Even assuming that you still have any friends around by the time your in a nursing home, the odds that neither of you suffer from cognitive impairment is about 1.7% (someone let me know if that math is wrong).

[1]: https://www.cihi.ca/en/dementia-in-canada/dementia-care-acro...

https://youtu.be/XvDZLjaCJuw?t=828

[1]: https://en.wikipedia.org/wiki/Villa_Las_Estrellas

[1]: https://www.antarctica.gov.au/about-antarctica/people-in-ant...