The only issue I have with those tools, and I have not seen a single one even acknowledge this, is that it becomes completely useless when holding meetings in a hybrid fashion where some people are remote and others are in the office with a shared mic.
Almost all of our meetings are hybrid in this way, and it's a real pain having almost half of the meeting be identified as a single individual talking because the mic is hooked up to their machine.
It's a total dealbreaker for us, and we won't use such tools until that problem is solved.
It can be solved with speaker segmentation/embedding models, although it is not perfect. One thing we do with Hyprnote is that we have a Descript-like transcript editor that allows you to easily edit/assign speakers. Once we integrate a speaker diarization model with that, I think we'll be in good shape.
Either everyone is in the same physical room, or everyone is remote.
The quality of communication plummets in the hybrid case:
* The physical participants have much higher bandwidth communication than those who are remote — they share private expressions and gestures to the detriment of remote.
* The physical participants have massively lower latency communications. In all-online meetings, everyone an adjust and accommodate the small delays; in hybrid meetings it often locks out remote participants who are always just a little behind or have less time to respond.
* The audio quality of remote is significantly worse, which I have seen result in their comments being treated as leas credible.
* Remote participants usually get horrible audio quality from those sharing a mic in the room. No one ever acknowledges this, but it dramatically impacts ability to communicate.
you might need an AI for in-person meeting first. Such tools are available to doctors who see patients. The note taking is great but I think it is skewed towards one-person summary where the name of the patient remains unknown. I wonder if the same tool can take notes if two patients are in the room and distinguish between each one.
The second tool is likely hardware limitation. A multi-cam-mic with beam forming capability to deconstruct overlapping sounds.
hyprnote can be used for in-person meetings as well! we have doctors like ophthalmologists or psychiatrists using it right now. and yes - definitely going to be working on speaker identification as it crucial.
I recently tried Vibe (https://github.com/thewh1teagle/vibe) from a recording of a meeting taken on one side. It was able to identify the speakers. As Speaker 1, 2, etc. But still useful to see.
You say that, next thing you know this guy installs bsnes on a Raspberry Pi going on a rampage on innocent Goombas from an illegal ROM of Super Mario World. What then?
He’s clearly a dangerous maniac and a threat to the society.
As a metric alone no agreed, but I do think there is some truth in it. Someone not using anything wouldn't use it much so likely not effectively on the other end of the spectrum though someone burning through a billion tokens might be super effective or not at all.
For coffee beans particularly I don’t think finding the mean of people’s ratings would be useful. For example, I don’t like light roasted beans and might rate them 0/5 while people who love lightly roasted beans might give it a 5. Average it out and you might get 2.5/5 which doesn’t convey much information.
This is a great thought. I'll have to do some planning around this. Though I'd assume if you don't like light roasts you'd not be buying them and then would have nothing to rate. But trusting the users to not "hate rate" may not be the bust idea.
That’s part of what C does, but it’s not the only thing.
Assembly adds mnemonics and a logical structure to machine code.
C largely does the same, but adds a cross-platform abstraction, mechanisms for organizing and sharing source code, a standard library, and various other things.
Syntactic sugar is such a broad and vague term that those features you mentioned could also technically be considered syntactic sugar. Instead of having to write harder longer code you can write easier and less code.
I think we can understand syntactic sugar as an alternative (hopefully more convenient, elegant, or pleasing) syntax for expressing something that can already be expressed.
That is, something that works the same but looks better (hopefully).
A cross-CPU abstraction, a preprocessor, a standard library all have certain elements of syntax in them, but go well beyond alternative syntax.
Someone suggested adding a comparison to the backtest results, showing the profit and loss from buying and holding the asset versus the profit and loss from the user-defined strategy. I think this is really interesting to see.
Unfortunately, I don't have data on the performance of professional traders, so I can't say whether most of them beat index funds. If you have any sources, I would love to see them.
Prices are made by humans, including the edge case of automation where instructions are still human.
On average not beating an average where there are transaction and membership fees is therefore expected, it could not be any other way. That doesn't however make the index the best predictor of itself.
