AI is likely simple and won't require much processing power after all, so it will be impossible to ban it because it would imply more regulation and surveillance than what would be sustainable. Also global warming will likely kill us anyhow. The rational conclusion is to enjoy our supermarkets and warm showers as long as they last. They will probably last longer if we deny these threats so as to avoid causing mass panic and nihilism.
We can survive global warming. We can fix it. We can come back from it. We will never come back from ai. It’s not impossible to ban ai. And we would be stupid to assume it’s impossible instead of trying to find out through an effort to save ourselves.
As far as I know, there are no "AI" companies listed on the NASDAQ.
Of course, there are listed companies with significant AI investments. But I'd argue their valuations are driven by their existing/conventional/ad-driven scale, not their AI arms.
Whether or not they're overvalued remains to be seen. The era of cheap money seems (?) to be coming to an end, so it will be an interesting few years.
The poster children of the dotcom boom certainly were - pets.com, webvan, etoys.com (though I can't say with 100% certainty they were all specifically listed on NASDAQ).
It was the IPOs that drove the boom (and subsequent bust). Public investors falling over themselves wanting to get in on the "next big thing". Older generation companies were never going to deliver the kind of quick return multiples that characterized the boom (though as we saw, the enthusiasm certainly jacked up their share prices too, but by and large they managed to ride out the storm).
Not agreeing with OP, but citing single studies is often pretty misleading. It is better to look for meta studies because the outcomes typically vary considerably, so you cannot be sure a single study is reliable.
Here are two meta studies based on 20 and 140 other studies, respectively, and they only find a weak to no link between gender diversity and productivity, so neither does the science prove that gender diversity is particular beneficial, nor that it is harmful:
Anonymity will always be greater than privacy. What I'm saying is that there should be a focus on being anonymous without a care (almost) of what you're doing.
I just think it's a futile kind of paranoia. Your anomalous behavior puts you on some list. Writing about it here puts you on some list. As every admin knows so well, spying on user data is much too easy for that not being done all over. We'd need to tear down large scale digital infrastructure to make even a dent into the problem of massive abuse potential. Deleting cookies is cope.
Depending on the context, platform, and data, de-anonymization is almost trivial to perform. Worse, someone can replicate your patterns and masquerade as you (thinking about that "lodestar" opinion where people were debating whether it was Pence or not).
How does multi microphone filtering work? I guess they localize different sound sources by cross-correlation (to get the timings) and triangulation (based on the timings and the speed of sound)?
I think the (or perhaps only one) key phrase is "beamforming". A single microphone element has a certain sensitivity pattern (e.g. it may be a very directional microphone, or be equally sensitive in all directions). With multiple pick-ups, you can emulate some different sensitivity patterns.
A related idea in radar is synthetic-aperture radar (SAR).
A lot of the interesting things in audio were inspired by radar. Dan Wiggins at Sonos used to work on radar, and Don Keele created a loudspeaker technology called "CBT" that's based on radar technology.
Because microphones are basically the inverse of loudspeakers, what works in loudspeaker arrays can also work in microphone arrays.
When you record with a single microphone, you are going to pick up a great deal of background noise. This is because the mic will pic up the person speaking AND the background noise; there's no way to differentiate the two.
With two microphones, we know the following:
1) we know where the microphones are
2) we have a general idea where the persons mouth is, because we know how they hold the phone
Based on that, we have a good idea of how long it should take for the sound to arrive, because the speed of sound is a fixed number.
The first time I ever heard a dual mic phone was when one of my coworkers made a call from the inside of our data center. Typically, he'd have to shout into the phone, because the data center was so noisy, and worst of all, the noise was completely random and broadband. But with dual mics, poof, background noise is gone. It was almost like he was speaking in a quiet room.
Amazon Alexa takes this quite a bit further, and uses something called "beamforming." What beamforming allows you to do is to determine WHERE the person is in the room, based on the arrival times of the sound. It's sort of the inverse of a dual mic setup; in a dual mic setup we can 'clean up' the signal because we know where the person speaking is. In a beamforming arrangement, we can use the arrival times to FIGURE OUT where the person is in the room.
If some security company was clever, they could probably use a beamforming microphone array to train a camera on people in the room.
And keep in mind, Alexa beamforming is two dimensional, but you could go crazy and do a 3D beamforming array if you wanted to! (Alex only knows where you are on a horizontal plane.)
That does sound neat. Sounds like it could be combined with 3D localization to allow eavesdropping particular sounds sources even e.g. in large rooms with lots of people talking. Multipath/ghosting might make precise localization difficult though.
You can do this with ICA (Independent component analysis, a somewhat lesser known, non-Gaussian cousin of principal component analysis). Basically you take the data with multiple components and break it down into its consistent component parts.
Have you actually tried to implement outlier detection in production on any serious level? Most who do realize pretty quickly that deep learning is way overkill and finicky, and pretty soon head for resources like this.
I think Photoshop also operates on a reduced image for previewing the outputs of filters and other tools. Compared to Photoshop, Photopea is a bit laggy with large images on my 8 year old machine, just like GIMP.
The processes are also designed such that people do not feel overstepped and ignored. After all, most things in life are about social status, or more immediately about salary status and job position.
If someone secretly implements an awesome feature, others might be envious as it does not seem deserved if their idea did not receive the same level of scrutiny by the usual processes as other decisions did.
Theoretically, it probably won't cause much chaos at all if programmers are allowed to add small GUI tweaks and the product likely benefits from it.
The degree to which this would work probably depends a lot on the extent to which the programmers have reached Kegan level 5, so practically it probably won't work all that well.
It's pretty rare for someone to secretly implement an awesome feature. Usually the way that works is as you hint at: someone who already has high social status in the organization gets a lot of leeway to do his own thing while everyone else is constrained to the usual process.
The envy isn't about the awesome feature: it's about the fact that this developer gets even more attention and positive notice from leadership by means that aren't available to other workers due to social status (rather than merit).
