He's got a valid point. For example, if you use wolfram alpha after you do a math problem to check the result you came up with you can actually learn MORE than just doing the problem yourself, and may even add to the time the work takes, as if your result is wrong, you'll spend extra time working out where you went wrong and fixing it. And ultimately learning more in the process.

OTOH - If you use wolfram alpha to DO the question for you, you will learn nothing at all.

But further to that, you can even use tools to save time and learn more.

The other day, my daughter and I chatted about docker build scripts while she was doing her homework (which used docker containers), and that conversation clarified a lot of details and subtleties. (I learned a few things in the course of that conversation myself.) Nothing we talked about wasn't in the documentation, strictly speaking, but the conversation was a more natural way to learn and address the specific details we were talking about, with examples, and use cases that we came up with on the flay to make sense of and highlight those specific nuances. She probably could have read and reread the docs and easily spent more time on it, while learning less.

Now, in this case, she was learning 'from me', but you could swap "Dad" out for an "LLM", and get the same benefit.

All that said, I don't think the AI systems we have right now are likely a good idea for homework. The temptation to use it self-destructively is just going to be too high for a large number of students. Probably the majority of them. But it definitely can be used to learn more, and even learn more faster in the hands of someone who uses it for that.

There's a lot wrong with your question.
Firstly, China's gun laws are among the strictest in the world. Private ownership of firearms is generally prohibited. You'll get better returns on matching China's homicide rates by matching their firearms laws than you will by catching up with them on surveillance.

Are you wiling to do that? I somehow doubt it. And to be a safe as china, you could do both -- give up your guns AND submit to a police surveillance state. What could go wrong?

China has done other things too - absolutely massive government investments in infrastructure and construction, creating jobs and reducing poverty in the process, uplifting people who would otherwise be more desperate and more likely to turn to crime etc.

And speaking of Crime, China is pretty busy with state executions too. And is quite adept at artificially making those numbers look smaller, frequently recording the execution of multiple people as a single execution. That may play a part in the lower homicide rate too.

Secondly, you imply the tradeoff is simple prudishness - we give up peoples lives for the ability to "go to a strip club secretly".
That's not that half of it, and you should know that. It's also the ability to go, for example, to a political party meeting secretly.

Do you really trust your government so much that you'd give them that power over you? That some fuckwit won't get into power and leverage this against the people? The best protection the civilian population has from government abuse is to resist giving them the tools to abuse you in the first place. The government doesn't need to know where every person is at all times, this will inevitably be used against you. The supposed 'safety' gains are not worth living in a police surveillance state.

The real issue is that the packaging process used to create vaccines in quantity is a process where you mix a tank of mRNA with a tank of other stuff and get a tank of lipid nanoparticles. Getting different mRNA in each dose means you only get one patient's vaccine per time you start and stop the machine. There's also a step where one copy of mRNA is used to make a macroscopic quantity of copies in a bioreactor that needs to be flushed in between different sequences, but can just run when making enough of the same thing for a large population. It's likely that the cost for each different sequence will come down if it's worth designing and building equipment that switches every dose, but there's an intermediate time between proving that the treatment is useful and being able to provide it in a cost-effective way.

It's clearly all the superfans who hear that there's a new album and immediately drive into their local record store. (Rather than doing the sensible, calm thing and entering the store on foot.)

Investors are chasing a company that achieves some kind of AI singularity. Let's set aside the fact that there's no reason to believe there is anything but diminishing marginal returns by making marginal refinements to current frontier models. Let's imagine someone hits the jackpot and gets, not even AGI, but a system that's as far ahead of today's frontier model are ahead of 2020's GPT 2.0 in performance.

Globally AI revenues are 150 billion, against a cumulative burn rate of 450 billion. A model that is a generation ahead of others would almost certainly capture the lion's share of that revenue.

If AGI magically appears as a Sam Altman has promised investors it will, a hundred million is way too low. Add, maybe, another zero to the revenues.

Conservatively, a safer assumption is that frontier models will get marginally better based on refinements in training and reinforcement and the other bits and bobs that go into these systems. The nobody is winning the lion's share of anything, at least overnight. But you have to define "safe". By "safe" I mean unlikely to lose money. But some investors are clearly defining "safe" as "having the greatest chance of owning a piece of the biggest thing ever."

I'm not following this super-closely, but if Anthropic is pursuing adding multi-step model based reasoning to their system, that could be the basis of a generational leap in capability. But if that is an approach that looks like it has a chance of working, then their competitors are no doubt pursuing the same thing. In that case you'd expect the revenue pie to grow as the scope of model utilty increases, but that growth to be split among several competitors. This could credibly result in a revenue stream for some of them that is as big as the entire industry's revenue stream today. But there's going to be hell to pay on the data center impacts end of things.

I predict a distinct change in the tone and content of ATC radio instructions. Use of the gamer word will skyrocket.

When I think about it, I can see a clear difference.

There were all manner of places where human eyes were accepted, but still/video cameras were not, long predating "smart glasses". From changing rooms, saunas, locker rooms, and bath houses to performances like plays and concerts, and movie theatres to executive board room meetings, and even court rooms in many cases.

There are lots of scenarios where everybody accepts and consents that other people will see/hear them, but do not accept or consent to be recorded.

  Are you really incapable of seeing the multiple clear and obvious differences between "seeing/hearing something" and "recording something" ?

Step 1: Make a lot of crimes, such that everyone is at least technically a criminal

Step 2: Stop enforcing the laws against traditional property crimes (theft, vandalism, burglary, etc)

Step 3: Propose cameras, claiming to use them to solve crime problem. People rejoice

Step 4: Use cameras to catch all those crimes you made in step 1. Continue to fail to enforce laws against traditional property crimes.

Step 5: Put on trollface, ask citizens who are being fined and jailed and having guns stuck in their face "We're catching criminals, isn't that what you wanted?"

With their COVID vaccine, the first time was the highest dose they knew would have only acceptable side effects, and they reduced it for the next iteration when they saw how effective it was. (If you remember the myocarditis rare side effect, that was only seen with the first version.) I would guess that the next step is backing off on the dosage to reduce the side effects now that they have results on effectiveness, which will also let them make a better case for younger people at less risk from the flu.

Some important background for this is that, around 1900, mathematics got formalized to the point that there is a standard for whether a proof is valid or not that doesn't depend on humans thinking about it, just doing a bit calculation following an algorithm. However, it is such a large calculation that nobody wrote complete formal proofs or verified all of the steps (since they'd be spending huge amounts of time on obvious parts, and not the novel aspects). Then, in the past 20 years, people have made computer systems that work on complete formal proofs while showing you the interesting parts, with the rest in macros, and check these proofs automatically. This means that finding proofs has the form of things like what AlphaZero is good at: something to check if moves are legal and a win condition. However, only a relatively small portion of mathematical research has been put into Lean so far, and that doesn't include the sorts of obscure results that often turn out to be useful in other problems. So the current wave is using LLMs to find results in the literature that might be relevant and producing formal versions of them, game AI to put them together, and deterministic validation to check each of these as it goes along and then people can see at the end that the calculation shows the proof is valid. The only part requiring mathematicians is checking that what the proof proves is what they understood the open question to be.

Protein intake increases thermogenesis. This FGF21 is probably being released when protein is low because more body heat is needed when digestion and absorption aren't producing it, but we know protein-rich diets result in more total thermogenesis.

But the individual didn't destroy it. The agent did the physical act of destroying it.

Suppose you were at the border with your phone, and the agent confiscated it.
Then the agent had said, how do i get into this phone?
You said, "put it in a blender".
If the agent puts it in the blender, the agent destroyed it, not you.

Now clearly, one would expect the agent to know that putting it in a blender would destroy it.

And equally clearly the inference here is that the agent did not know that the password he was given would wipe the phone as part of opening it. But isn't the onus still on the officer?

If it had been a physical safe, and you gave him the code, but the safe contained something that would self-destruct in exposure to air, and must be opened inside an enclosure with inert gas to get at the contents... who would be responsible for destroying the evidence inside the safe?

As a second scenario, what if you had printed a PIN password on a piece of paper and included that in your wallet. If the agent had confiscated your wallet and discovered the paper; and then used that password on your phone? If that was your duress password, who is responsible for destroying evidence in that case?

Legally, Isn't the onus ultimately still on the agent to apply caution before pushing buttons on a device they confiscated?

To blame you the suspect for destroying evidence on something the agent had custody and full physical control over seems a bit far fetched to me.

On a 13" screen most people would have scaling enabled to see it anyway. Not really sure its worth the extra horsepower to push quadruple the pixels, and average them out.

Don't get me wrong, I love 4k screens. My desktop has a pair of 32" 120hz 4k screens.

But on a laptop, especially a 13" model, my priority is going to be battery life, not performance; so 4k is not a hard requirement. Plus this unit features a more old school 3:2 aspect ratio which is arguably more practical and useful than a 1.78:1 widescreen at 13".

Higher than a 13" dell xps. Higher than the 13" Macbook Neo. Higher than a 13" Macbook air... hell it just edges out the display on the Macbook air 15".

Its 120Hz. It's matte. It's touchscreen (if you care).
It seems to be a very solid 13" laptop screen overall.