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Comment · 1 year ago
[flagged]
Comment · 1 year ago
I recall doing a rather large technical case for using raft and a replicated log for water industry back in 2017 it must have been.

That's from knowing nothing about the shape of consensus algorithms to almost getting one adopted.

To me Raft's brilliance is how easy, clear and comprehensible they made thinking about it.

Comment · 1 year ago
> I was surprised how well the bird was getting around.

SurvivorBias.png except it's a silhouette of a goose with numerous red arrows drawn over it.

Comment · 1 year ago
You'd be surprised what's in there, a few forms of NNs are already supported for denoising, speech detection.

I think having this flow out to all of the deps of libav is a greater good than notions of lib purity.

Comment · 1 year ago
More precisely libavfilter, so it's also soon in mpv and other dependent players.

This is going to be great for real-time audio translation.

Comment · 1 year ago
The fact that you think it was suggested _by_ them is I think where your mental model is misleading you.

LLMs can be thought of metaphorically as a process of decompression, if you can give it a compressed form for your scenario 1 it'll go great - you're actually doing a lot of mental work to arrive at that 'compressed' request, checking technical feasibility, thinking about interactions, hinting at solutions.

If you feed it back it's own suggestion it's no so guaranteed to work.

Comment · 1 year ago
What technologies we have in 2025!
Comment · 2 years ago
It seems to be the "conversation" part, not necessarily "communication", one of the early stages in children's language acquisition is teaching the flow of back and forth responses and pausing for the other to speak: which seems to be what they're indicating in this article.
Comment · 3 years ago
No, it doesn't, Turk is what we call Turkish people too.
Comment · 3 years ago
The "chemical burns" in the title are https://en.wikipedia.org/wiki/Nitrogen_mustard burns, a blistering agent and schedule 1 substance under the chemical weapons convention.
Comment · 4 years ago
Completely not the focus of the article, and you've turned the result of an error rate of 0.8 percent for gender classification of light-skinned men and a 34.7 percent error rate for the same classifier on dark-skinned women - into some kind of google image search language game?

I can only quote Joy Buolamwini on this:

“To fail on one in three, in a commercial system, on something that’s been reduced to a binary classification task, you have to ask, would that have been permitted if those failure rates were in a different subgroup?”

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