Now THAT would be an undertaking, looking at the topographic map of Iran....

I believe you completely misinterpret that curve. The peak shown in the right hand graph is not for value, it is for the rate of growth (i.e. change). As the left hand graph shows, the value will stay there, just the rate of change will slow down.

And we are nowhere near the inflection point, is is still early days, i.e. good entry point.

Actually the speed of development IS that fast. Just 5 months ago Agentic AI coding wasn't there yet. Then came Claude Code, Sonnet and Opus, Skilling and Agents and things have changed. And remember, this is not the peak, we only have scratched the surface. It will become more skilled, cheaper, faster, easier to use. Just try now Opencode and Big Pickle model, there's a free tier (mind security implications though with those free models). You'll be surprised.

Yes, this is extortion, and I think Pentagon has shot themselves in the foot with this. Other companies will now think twice before doing any business with Pentagon. Sure, they might get a few extra bucks from a DoD deal, but they also risk losing many times that, if/when Pentagon uses this extortion tactic again.

It is not about standing up to the US. It is about protecting corporations that want to retain at least some ethics. And punishing those, that don't.

Dark matter is not the problem. It is easy to imagine stuff which is not luminous, but still affecting galaxies. Dark Energy is the problem, invented to explain Supernova redshifts. I hope they get rid of it with this new evidence, forcing to rethink.

Not unlike many people. https://blog.thelinguist.com/p...

AI has learned the language from those code examples and repositories. What it does with the language is often (not always, mind you) original.

LLMs have learned English (and other languages) from vast amounts of written text. It is easy to use LLMs to create work that is original (say, prompt it to create a poem in Shakespearean style about AI utilizing tennis racket to paint a house - or whatever). Similarly with software development, AI has learned the syntax and coding styles for different programming languages, and utilizes that information to create original code.

Stop right there, this basic premise is false. AI has learned the language from those code examples and repositories. What it does with the language is often (not always, mind you) original.

LLMs have learned english (and other languages) syntax from examples, it is easy to use them to create work that is original (say, prompt it to create a poem in Shakespearean style about AI utilizing tennis racket to paint a house - or whatever). Similarly, AI has learned the syntax and coding styles for different PROGRAMMING languages, and can utilize that information to create original code. The syntax of the programming language is not copyrighted.

I don't think it will affect the QUALITY of the ads themselves. It just makes the ad space easier to sell for Facebook and cheaper for marketing people to target the group that they want to part with their money.

There are a lot of scientific papers written about the research done by these companies. See e.g. here: https://openai.com/research/in...

In many markets (not just neighborhoods), there is nowadays so much wind power on a windy day, electricity IS free. That's why they are coming up with ideas, how to use that cheap energy.

The solution presented in TFA converts Hydrogen to Methanol and that is converted to gasoline. It is wiser to build the infrastructure to use that hydrogen directly. In fact, they already are doing exactly that, here in Finland at least: https://gasgrid.fi/en/developm... And not just in Finland, but extending to Baltics and other Nordic countries as well.

Exactly. And in the case presented in TFS, the system created python programs to solve problems. And it would run those programs to see, which ones worked. And used this information to improve itself.

If you set aside your hate for anything LLM-related, could you please explain, why this amplifies GIGO? I understood there is a clear reward-function, which should steer it towards the working solution.

In a not so dissimilar way, AlphaGo played against itself millions of games, learning along the way the winning strategies, eventually beating humans. It it worked for those kind of neural networks, why wouldn't it work with LLMs?

There have been stories in the Finnish media that even exchange students have been forced to participate in that act. Weird.