I skimmed the paper but I couldn't figure out what they're doing to make concepts fundamentally different from tokens.
I would think that the purpose of concepts is to capture information at a higher density than tokens, so you can remember a longer conversation or better produce long-form output.
Given that, I would have expected that during the training phase, the concept model is evaluated based on how few concepts it emits until it emits a stop.
I think that considering Amazon, a company with independent business units in completely different business (retail and cloud computing) as an entity with a single personality is about as accurate as thinking everyone from the same country has the same personality.
It's not as if the small group of people at the top determine everything else about the company: they only hire the people directly below them, and their influence decreases the further down you go. I think the larger determinant of a company is the business it is in, since that determines at large what people the company is attractive to and which it tries to hire.
I imagine there's a lot of value in having your employees share a timezone for the benefit of easy cooperation, so it might make sense to have at least timezone-dependent salaries.
There might also be value in having your employees be able to easily physically meet, and then location-dependent salaries make sense.
I'm wondering whether the point you're making can be made even stronger.
I would phrase your argument as simple as: you estimate the world is much more likely to become uninhabitable if we don't use nuclear.
What's the worst case of not using nuclear? It's the same as the best case of using it. Best case, nuclear would enable us to entirely phase out fossil fuel energy production, reducing the world's CO2 production by 25%, reducing green house emissions to the point that large parts of the planet no longer become uninhabitable.
I think much of the software might be the same as at any another company. These companies are so profitable that they're willing to offer more $$$ to get slightly better people to do regular work slightly better than it's done on average.
Shorting a stock and having that information be public seems like a big risk, since it opens you up to people trying to make money by short squeezing you.
I think any single-seat election, regardless of voting system, stabilises when there are only two popular parties from which candidates can get elected. I don't believe voting systems such as instant-runoff or approval voting can avoid this problem.
Isn't YouTube banning certain content exactly what free speech is about? YouTube, a corporate entity with its own goals and beliefs, exercises its right to say what it thinks is the truth. It's similar to most newspapers: they're not entirely objective.
If content publishers want to post Corona related information that YouTube thinks is false, they'll just have to find/create another platform for it.
While reading I wasn't convinced this was going to work due to the collusion problem, until I read the comments on collusion which add an extra condition: "we need votes to be so private that even the person who made the vote can't prove to anyone else what they voted for."
However, this condition is not enough, it doesn't cover the case where someone is being watched while they are voting. The condition should be something like:
"we need votes to be so private that only the voter can know what he voted on"
I don't see many solutions to this, except the '19th century' way of voting at a voting station, or a voting machine that can read minds. Obviously it would be pretty strange inputting your vote through thoughts, especially since this system might never allow you to confirm what you voted on.
However, I guess even ballot voting could suffer from collusion since it's not fundamentally private. You could take a hidden camera into the voting box and record your vote, and afterwards get a payout.
There's a lot of talk in this thread about what intelligence is. Personally I found the AIXI model from algorithmic information theory a very convincing definition: https://en.wikipedia.org/wiki/AIXI
I'm surprised it's not more generally accepted as _the_ definition. Note that Markus Hutter the main author is currently working at DeepMind.
I'd be very interested in understanding mainland Chinese sentiment better. My impression is that there is a lot of love for the current Chinese political system, and I'd like to understand why that is. Can anyone refer me to writing pieces that focus on this?
> After selecting a particular phrase using my cursor control commands, I say “clip [foo]“, and every time I want to enter the same phrase after, I say “paste [foo]“. I therefore only have to dictate a particularly obnoxious variable name once.
A simpler solution might be an editor with an auto-completion feature where completion items can be selected using abbreviations or full names with small errors.
So, what would be an effective way of making censorship impossible?
I imagine a system where you publish news using your device (a mobile phone), and encrypted in a way so that only a small group of other devices, which you have explicitly trusted in an earlier step, can decrypt it, allowing only them to trace that the news came from you.
Then those trusted devices will decrypt and re-encrypt the news in such that they can forward it with only their trusted devices. When a device receives news from another, then it won't know whether the sender published that news, or is merely forwarding it.
Because all communication between devices is encrypted, a device can not be confirmed to be using this system, except by a device who he trusts.
When a device is compromised, he will only be able to see if another device is part of the system, if that device has trusted him. Also the compromised device will be able to read news shared to him, but he won't be able to see what device that news originates from.
To make sure that readers can filter news based on what publishers they like, there is the concept of a publisher.
Apart from news, devices can also share publishers. An publisher is a name plus public key. The creator of the publisher has the private key with which he can encrypt news (even before it encrypted for sharing), allowing readers of that news, who have the publisher's public key, to verify that the news came from that publisher. If a publisher is shared with a device while the device already knows a publisher with the same public key, then the device must chose which publisher to keep and which to delete.
What's the use-case for many virtual threads? I thought the main case for using threads was performance, where you need to use them to fully utilize the machine, although rather you wouldn't be using threads.
Another use-case for threads that I see is when you have work-queues that have different priorities, so you put each queue into its own thread with a matching priority. For example, 1 thread for responding to UI events, and 1 lower priority thread for all background work.
Anyways, none of these use-cases require many threads. What use-case am I missing that makes go-routines useful?
I guess doing something in a thread is a fail-safe way to make sure that 'some time' is spent processing it, so for example for the UI tasks, it would be easy to just dump all handling of UI events in virtual threads.
Although I don't agree with their way of communicating, I think the protestors' concern is valid: they will be forced to move because Google's rich employees will price them out of their living area. This is because of two reasons:
1) Renting: the protestors rent instead of own the homes they're living in, so their costs go up with the housing prices. The government could have reduced this problem by promoting home ownership in the past.
2) Income inequality: the protestors are not techies, so they won't be employed by Google, and will earn far less than Google's employees. The government can reduce this problem by increasing income leveling.
Well, I think I can make a simpler argument. Google will change this neighbourhood. The culture will change, the cost of things, not just rent, will increase. Assuming that the author is very happy with how his neighbourhood currently is, I can see how he doesn't want Google's change.
I think that, if the majority of the people in the area side with the author, there is an argument to be made to, through political means, block bringers of gentrifications such as Google from entering this area.
I think the author is correct in thinking that Google will cause him discomfort by creating this campus. Everyone in this area not employed by Google will have to move because Google is basically buying the land, directly or through its employees.
Some of Google's money will flow to locals not directly employed by Google, but will this offset the increased cost of their living expenses?
I would think that the purpose of concepts is to capture information at a higher density than tokens, so you can remember a longer conversation or better produce long-form output.
Given that, I would have expected that during the training phase, the concept model is evaluated based on how few concepts it emits until it emits a stop.