patapong

Yep - I like to phrase it as "AI is better at most tasks than most people". AI will still be beat at experts at specific tasks, but in general I find it to be better than me at the areas where I have no expertise. It's the ultimate generalist.

It might be cheaper when internalizing the externalities of CO2 emissions. Once/If we start properly taxing the impact of these emissions, this plane could offer much cheaper flights then fossil fuel driven competition.

Very napkin math shows that annual energy consumption from fossil fuels is 500 exajoules. Every day the earth receives 15,000 exajoules in solar energy.

So to cover double the energy consumption of fossil fuels with solar we need to cover 0.2% of the surface in solar. Compare to around 10% covered in farmland.

Again, very back of the envelope math, but in my opinion this does not seem impossible.

I agree that it's not easy, but we could in theory use solar energy, which is abundant and cheap. I.e. We can use different energy than the one we got out of the fossil fuels we burned.

It depends - if you are looking to raise potentially billions of dollars, showing that you are contributing at SOTA level in GenAI through papers could be a good strategy.

GPT-5.6 Terra just showed up in Codex for me.

But haven't you heard, software is solved?

"Make this OS and ecosystem more efficient. Make no mistakes."

So? Computers are the dream machine, we should strive to do better than physical reality, not mimic it.

At the same time, there's some commonality for what words mean in different contexts. For example, even though we all have our own experiences with the concept of "dog", there's a common core where we have enough of an understanding what other people refer to as "dog" to allow discussing the concept. Likewise, for most people, dog is more similar to cat than to house.

Imagine if we could build a machine that reads a bunch of texts and tries to extract this meaning by looking at which words commonly co-occyr with other words in different contexts. Perhaps something interesting would happen...

But mining costs are (cost of equipment+cost of electricity)/total coins mined, so can miners not end up in a situation where they need to keep mining to pay off equipment despite the individual coins being unprofitable?

Synthesizers! I like it because it's tactile and immediate, and you're not glued to a screen, but can create fun-sounding beats.

Nowadays there are nice, cheapish groove boxes that are perfect for noodling on the couch. I started with the Novation Circuit Tracks, and also really enjoy the Teenage Engineering EP-133. Not to say that I am any good at this, but it's an enjoyable hobby! Bonus if you are friends who are also into it and you can jam together :)

One of the biggest recent indie hits, Balatro, was made in Löve!

I really like it, the developer experience is so smooth for beginners, just drag a zip onto the exe and it starts. And the APIs are simple enough to memorize while allowing pretty cool rendering stuff.

I think this is a very important debate, and I think the author here adds a lot to this discussion! I mostly agree with it, but wanted to point out a few areas where I do not fully agree.

> Take away the agent, and Bob is still a first-year student who hasn't started yet.

This may be true, but I can see almost no conceivable word where the agent will be taken away. I think we should evaluate Bob's ability based on what he can do with an agent, not without, and here he seems to be doing quite well.

> I've been hearing "just wait" since 2023.

On almost any timeline, this is very short. Given the fact that we have already arrived at models able to almost build complete computer programs based on a single prompt, and solve frontier level math problems, I think any framework that relies on humans continuing to have an edge over LLMs in the medium term may be built on shaky grounds.

Two very interesting questions today in this vein for me are:

- Is the best way to teach complex topics to students today to have them carry out simple tasks?

The author acknowledges that the difference between Bob and Alice only materializes at a very high level, basically when Alice becomes a PI of her own. If we were solely focused on teaching thinking at this level (with access to LLMs), how would we frame the educational path? It may look exactly like it does now, but it could also look very differently.

- Is there inherent value in humans learning specific skills?

If we get to a stage where LLMs can carry out most/all intellectual tasks better than humans, do we still want humans to learn these skills? My belief is yes, but I am frankly not sure how to motivate this answer.