lars

The comment section at the bottom of the article is pretty interesting. 20 years of people thinking about this.

Misinformation generation as a service. Is there any thinkable use case for this that isn't destructive for society?

I basically share your sentiment. However, Greg Yangs work seems to have produced something of direct practical benefit for training large neural nets, based on the NTK literature. µ-Parametrization is apparently very useful in real world practice.

Yes, it was. From their site: "It has been trained on a selection of English language and source code from publicly available sources, including code in public repositories on GitHub."

I think they would in any case. My impression is that data is siloed internally at Google, and that data sharing between departments would be way more complex than just setting up some (possibly redundant) logging.

Idea: We could stop using cryptocurrencies.

Any downsides to that?

Similar to how "god of the gaps" arguments work, there's a "god of complexity" phenomenon in tech, where people will project infinite possibilities onto technology they don't understand.

Blockchain is a brilliant solution to an extremely rare problem. It lets you do distributed consensus among untrusted nodes in a setting where contributing compute power is economically incentivized (e.g. where there's mining). That applies to cryptocurrencies, but basically nothing else.

It's amazing how much bullshit has been pitched under the flag of "blockchain". Millions of dollars have been poured into projects that are technically unsound or that had no use for a blockchain to begin with. This has been going on for years.

Did you respond to right comment? You seem to be arguing against something that I'm not arguing for.

Well, this is the discussion I'd like to see.

You have people born in the 90s hospitalized in Norway now. Many experience long term physical and cognitive effects. And as long as we're assuming everyone goes unvaccinated, the chance of contracting COVID goes towards 1 over time, while the R-number explodes as we open up society to avoid economic ruin. Not a good scenario IMO.

As I said, the relevant comparison in the real world is versus waiting for another vaccine, where it the choice is much less obvious, and dependent on the disease level in the population.

I'm happy this research has been done so quickly, but am somewhat annoyed that the public conversation is so focused on whether or not the vaccine can possibly cause any problems, and not at all focused on the risk management question of what the optimal choice here is.

The chance of getting a blood clot seems so low that it may for all I know be equivalent to the risk of dying in the streets while jaywalking to get to the vaccination center. Compared to the risk of going unvaccinated, it's an obvious choice.

That's not the choice we have though. The correct comparison seems to be the expected risk of taking the vaccine vs expected risk of waiting for a dose of another vaccine. Calculating this on an individual level should be straight forward given the risk of contracting COVID in a given area. Ideally the calculation would also take into account the effect that vaccination has on the virus reproduction number. That's harder to model, but approximate models like this exist.

If you actually put numbers to it and do this computation, you'll get an answer, or at least a distribution of outcomes, where it's straight forward to see what choice is optimal. Then public discussion can be around what the parameters of this model should be, and we'll stand a chance of making the right choice.

This is a potentially very consequential optimization problem, and the public discussion about it is as if no one understands that that is what it is.