no problem.

I'm actually responding to the AC above you. He is arguing that the attack wouldn't make any sense for either country to make, based on *national* interest. I'm pointing out that's not the only framework in which *regimes* make decisions.

How do you know that?

Being from Google, I rather assume the opposite - and that they probably focused their engineering effort to make sure the reduced battery life didn't give their corporate surveillance activities away.

I'll find out in mid January, lol - it's en route on the Ever Acme, with a transfer at Rotterdam. ;) But given our high local prices, it's the same cost to me of like 60kg of local filament, so so long as the odds of it being good are better than 1 in 8, I come out ahead, and I like those odds ;)

That said, I have no reason to think that it won't be. Yasin isn't a well known brand, but a lot of other brands (for example Hatchbox) often use white-label Yasin as their own. And everything I've seen about their op looks quite professional.

Just put it in context: Today Russia struck the Pechenihy Reservoir dam in Kharkiv.
Russia launched the war because they thought it would be a quick and easy win, a step towards reestablishing a Russian empire and sphere of influence, because Putin thinks in 19th century terms. Russia is continuing the war, not because it's good for Russia. I'd argue that winning and then having to rebuild and pacify Ukraine would be a catastrophe. Russia is continuing the war because *losing* the war would be catastrophic for the *regime*. It's not that they want to win a smoldering ruin, it's that winning a smoldering ruin is more favorable to them and losing an intact country.

Yep - absolutely agree with you. Just because a devices is locally controllable and has opened up localhost:8080, that doesn't prevent it from also opening a connection to https://ancillary-proxy.atarimworker.io?url=https%3A%2F%2Fbadthing.example%3A9999%2F and uploading everything it can find to it. Concepts are orthogonal.

I must admit I haven't got round to doing it yet, but a common thing to do these days is set up a specific IoT network in your house and have it all connect to that, then limit access to the internet for that network. A lot of routers support doing this out of the box now.

HomeAssistant's main strength is in tying otherwise incompatible devices together. Local first is not unique though - HomeKit is local, Matter is local, I don't know much about the Alexa/Google setups but I believe they can be controlled locally too.

Don't get me wrong, Home Assistant is an excellent bit of kit with lots of standardisation and automation. But this article is pushing the wrong part of its strengths - local-first isn't unique. Pick the right ecosystem and it's all local-first anyway.

I have many different smart vendors in my home - Google (originally Nest), Philips, Meross, Aqara, Eve, Ikea, LightwaveRF, Shelly, Eufy, Switchbot...none of them require the internet. All of them can work locally. All of them work in the same ecosystem. Then I have oddities which I use HomeBridge for to bridge the gap - Roomba (older, non-Matter, Worx Landroid (robot lawnmower), Dyson Hot'n'Cool thingy, Logitech Harmony...even plugins for Synology which show the NAS's temperature and allow shutdown. Through the use of HomeBridge, I can draw them into the same ecosystem too. None of this requires the internet.

The meme is completely overblown and quite often you can tell by people that don't actually use this kind of tech. Obviously if I want to control this kit from outside the home then I need an internet connection, and if I want to update any of the kit then I need to download the updates from the internet for that too, but operation from within the house? Just a HomeKit/Matter hub, that's all.

- "I use all your queries to increase OpenAI's revenue regardless of how unethical."
- "My replies are designed to keep you engaged rather than be accurate."
- "I'm not really your friend, don't trust my tone."

Yeah, it's not even worth considering for something like 15-20kg. A full pallet in this case is 464kg :) Years worth of supply for me.

The current "AI" is a predictive engine.

And *you* are a predictive engine as well; prediction is where the error metric for learning comes from. (I removed the word "search" from both because neither work by "search". Neither you nor LLMs are databases)

It looks at something and analyzes what it thinks the result should be.

And that's not AI why?

AI is, and has always been, the field of tasks that are traditionally hard for computers but easy for humans. There is no question that these are a massive leap forward in AI, as it has always been defined.

It is absolutely crazy that we are all very very soon going to lose access to electricity

Calm down. Total AI power consumption (all forms of AL, both training and inference) for 2025 will be in the ballpark of 50-60TWh. Video gaming consumes about 350TWh/year, and growing. The world consumes ~25000 TWh/yr in electricity. And electricity is only 1/5th of global energy consumption.

AI datacentres are certainly a big deal to the local grid where they're located - in the same way that any major industry is a big deal where it's located. But "big at a local scale" is not the same thing as "big at a global scale." Just across the fjord from me there's an aluminum smelter that uses half a gigawatt of power. Such is industry.

That "ruler study" was ancient. It's mentioned in peer review at least as early as 2018, and might be even older.

Believe it or not, people in the field are familiar with these sorts of things that you just read about.

Most of these new AI tools have gained their new levels of performance by incorporating Transformers in some form or another, in part or in whole. Transformers is the backend of LLMs.

Even in cases where Transformers isn't used these days, often it's imitated. For example, the top leaderboards in vision models are a mix of ViTs (Vision Transformers) and hybrids (CNN + transformers), but there are still some "pure CNNs" that are high up. But the best performing "pure CNNs" these days use techniques modeled after what Transformers is doing, e.g. filtering data with an equivalent of attention and the like.

The simple fact is that what enabled LLMs is enabling most of this other stuff too.

Jevons Intensifies