Yep, it always was.

Drones are massively key in a very unusual conflict between Russia and Ukraine. I wonder if other wars would find them useful.

For example, a recent article shared on HN highlighted that the cheap drones become useless once there is any signal jamming going on. Russia can't jam too aggressively as their own comms are not good enough to be useful in such an environment. But what about NATO? Would they just jam the EM spectrum to oblivion and render all these drones useless?

Not a great point of comparison, but Israel v Gaza seems to use next to no drones (certainly not the small cheap variety), and the little that is known of Israel v Iran also focused on big expensive manned and unmanned aircraft. Plus massive, enormous, eye-wateringly-expensive bombs. Not converted Mavic drones. To the extent that Iran used drones, reportedly they gave no tactical benefit, as they were all shot down long before they reached Israel.

This paper is solving (basically) high-school-level problems by training neural networks on the "obvious" cost function. All of those problems can be solved much cheaper by standard numerical solvers for ordinary differential equations. They don't even compare to standard methods.

So what's the point? Riding the neural network hype?

These days I keep wondering what a 4d or 3d chess board looks like.

The energy usage concern is also funny in that it doesn't try to compare the energy usage of a human doing the same task (if one were to not use LLM to do the task). If we assume it's true that asking ChatGPT a question costs 3 bottles of water, you should take into account how long that question takes to answer by a human doing the research. If it takes you a couple of hours, you need to include the food and drink intake it takes to power yourself for a couple of hours. If it's anything like beef or almonds it takes way more than 3 bottles of water.

It seems like your claiming that the perceived benefits of eating meat (by those who do) exactly equals the benefits of using ChatGPT. Is that right? If so, I disagree.

I think projects like that would have been a godsend 2-3 decades ago, when even a basic oscilloscope costed as much as a used car.

Nowadays, very good oscilloscopes with 200 MHz bandwidth, good user interfaces, and responsive displays are selling for $300 - I'm talking Siglent, Rigol, UNI-T. So the merits of DIYing something much worse just aren't quite there. It's that one piece of equipment you use to troubleshoot all your other designs, so you want it to be dependable, easy to use, and accurate.

This is not to say it's not a fun, geeky project to work on and publish... but you know, only once you have a real oscilloscope. If you're just setting up, do yourself a favor and spend a bit more money on this. The remaining equipment is not nearly as critical.

Makes no sense to use AI for everything. If you’re not dealing with a natural language processing problem, there’s better solutions. He’s a crank.

AI is an existential threat to tech companies not software engineers.

In many domains, the scope and complexity of software systems goes beyond the ability of a single software engineer to manage. A coordination layer becomes necessary when the number of engineers required goes beyond a threshold (say 5 or so). When the development effort must be coordinated over extended periods (say several months or years), mechanisms to raise capital and manage risk become necessary. These functions are why companies exist.

Consider that a massive increase in software engineer productivity will make coordination unnecessary for many kinds of software. In the market that opens up, companies with expensive executives, middle management and coordination inefficiencies will not be competitive. Smaller shops with a solo engineer or a team of less than 5 will outcompete larger players because their costs will be significantly lower. Massive one-size-fits-all products will be harder to justify when a small dev shop can quickly build or customise software for the unique requirements of a business or niche.

Before the CEOs stop needing engineers, engineers will stop needing CEOs and managers to coordinate their efforts and raise capital.