Curved screens are often significantly harder (and more expensive, even at independent shops) to replace than standard flat screens.

It’s not just random jitter, it also likely adds context, including the device you’re using, other recent queries, and your relative location (like what state you’re in).

I don’t work for Google, but I am somewhat close to a major AI product, and it’s pretty much the industry standard to give some contextual info to the model in addition to your query. It’s also generally not “one model”, but a set of models run in sequence— with the LLM (think chatGPT) only employed at the end to generate a paragraph from a conclusion and evidence found by a previous model.

Relaying a key signal 20 ft when you know the key is there isn’t too tricky, like when you’re home. But I would propose that trying to relay a signal across hundreds of feet, like a busy mall or store, when you’re not even sure the owner is there is quite another thing. You can also require that the IR blaster is in the car before starting. There’s also a technology Google has been using for a while now where the device (car) would emit a constant ultrasonic signal for the other device (key) to pick up on to determine if they are close to each other. Something that could be done through clothing, but not easily relayed.

Potentially better idea, add a gyroscope to the key fob, and stop broadcasting after the fob is perfectly still for some threshold. That way when you set it down inside it can’t be relayed, but if it’s in your pocket, it won’t remain perfectly still, and will start transmitting. Could also add an IR blaster to detect if you set it down in the car. Battery life would start to become a bigger issue, but I think solutions to these problems could be engineered.

Indexing and lookups on datasets as big as companies like Google and Amazon are running also take trillions of operations to complete, especially when you take into account the constant reindexing that needs to be done. In some cases, encoding data into a neural network is actually cheaper than storing the data itself. You can see this in practice with gaussian splatting point cloud capture, where they are training networks to guide points in the cloud at runtime, rather than storing the position of trillions of points over time.

I firmly believe it will slow down significantly. My prediction for the future is that there will be a much bigger focus on a few “base” models that will be tweaked slightly for different roles, rather than “from the ground up” retraining like we see now. The industry is already starting to move in that direction.

While I agree in principle, one thing I’d like to clarify is that TRAINING is super energy intensive, once the network is trained, it’s more or less static. Actually using the network isn’t dramatically more energy than any other indexed database lookup.

Actually, Windows does allow you to use an alternate “compositor”— a feature which is used quite frequently in the industrial/embedded space. Windows calls them “custom shells”. The default is Explorer, but it can be set to any executable.

https://learn.microsoft.com/en-us/windows/iot/iot-enterprise/customize/shell-launcher

Autopilot maintains altitude and bearing between waypoints in the sky, and in some (ideal) situations can automatically land the aircraft. In terms of piloting an aircraft, it can handle the middle of the journey entirely autonomously, and even sometimes the end (landing).

Autopilot (the Telsa feature) is not rated to drive the car autonomously, requires constant human supervision, and can automatically disengage at any time. Despite being sold as an “autonomous driver”, it cannot function as one, like autopilot on a plane can. It is clearly using the autopilot feature of an aircraft to imply that the car can pilot itself through at least the middle of the journey without direct supervision (which it can’t). That is misrepresentation.

Investigate it? The dude literally named it “autopilot”, what is there to investigate, they market this explicitly in their advertising.

I could 100% see them offering user replaceable memory, but with a slower max speed than factory installed. Gotta have something to point to when the regulators come a-knockin.

Apple TV seems to be doing just fine. Considering investing in one. I don’t think it’s likely they’ll start putting ads in the hone screen and such.

Nope, it’s either inspecting the TTL of packets coming from your phone (unless you have a VERY custom setup, the TTL from devices other than your phone will be very different), or it’s deep packet inspection. I tried to trick t-mobile last year into giving me home internet on a phone sim, so I did a whack ton of research.

You don’t need to exercise your stock options to access their value. It’s common practice to take loans out against their value, which allows you to access your money effectively tax free by instead paying interest against the loan. This is (again) a fairly commonplace practice used to make collecting tax difficult, and allow them to make the argument to regulators that they aren’t actually being paid that much, it’s totally just options they would never sell off. That’s why C suite has such a “burn everything to the ground, as long as our stock price goes up” mentality, because if it doesn’t, they have to start worrying about interest on their loans— because they have fairly low liquidity (percentage wise).

Base pay is a meaningless figure in tech. Total comp is all that matters. The true high rollers intentionally keep their base pay low to dodge taxes. This doesn’t mean they aren’t still getting and using this money, it’s just an intentional straw man to allow them to make this exact argument.

You can attach a fake one in software via XVFB (X Virtual Frame Buffer). It’s a little involved if you aren’t familiar with X, but it only took me an hour or so to get setup. Then you don’t need any hardware at all, and can set whatever resolution you’d like.

If that were solely true, there would be a lot more competition in the field right now. Amazon, (and to a much lesser extent the other 2 big names, GCP and Azure) are so massive not because they have a lot of power (plenty of other companies like digital ocean or OVM have plenty of scaling power too)— but because the integrations between their products are so seamless. Most of that functionality has a foundation in FOSS software that they’ve built on top of.

That would be a dream come true for Youtube. Think about how that would affect them financially, they would be serving significantly less load, but they would still rake in all those Youtube premium subscriptions. It would effectively be campaigning to remove the users who aren’t monetized from the platform.

I’m out and about today, so apologies if my responses don’t contain the level of detail I’d like; As for the law being collective morality, all sorts of religious prohibitions and moral scares HAVE ended up in the law. The idea is that the “collective” is large enough to dispel any niche restrictive beliefs. Whether or not you agree with that strategy aside, that is how I believe the current system works in an ideal sense (even if it works differently in practice), that’s what it is designed to protect from my perspective.

As for anti-AI artists, let me pose a situation for you to illustrate my perspective. As a prerequisite for this situation, a large part of a lawsuit, and the ability to advocate for a law is based on standing, the idea that you personally, or a group you represent has been directly, tangibly harmed by the thing you are trying to restrict. Here is the situation:

I am a furry, and a LARGE part of the fandom is based on art and artists. A core furry experience is getting art commissioned of your character from other artists. It’s commonplace for all these artists to have a very specific, identifiable signature style, so much so that it is trivial for me and other furs to be able to identify artists by their work alone at just a glance. Many of these artists have shifted to making their living full time off of creating art. With the advent of some new generational models, it is now possible to train a model exclusively off of one singular artists style, and generate art indistinguishable from the real thing without ever contacting them. This puts their livelihood directly at risk, and also muddies the waters in terms of subject matter, and what they support. Without laws regulating training, this could take away their livelihood, or even give a (very convincing, and hard to disprove) impression that they support things they don’t, like making art involving political parties, or illegal activities, which I have seen happen already. This almost approaches defamation in my opinion.

One argument you could make is that this is similar to the invention of photography, which may have directly threatened the work of painters. And while there are some comparisons you could draw from that situation, photography didn’t fundamentally replace their work verbatim, it merely provided an alternative that filled a similar role. This situation is distinct because in many cases, it’s not possible, or at least immediately apparent which pieces are authentic, or not. That is a VERY large problem the law needs to solve as soon as possible.

Further, I believe the same, or similar problems exist in LLMs, like they do in the situation involving generative image models above. Sure with enough training, those issues are lessened in impact, but where is the line of what is ok and what isn’t? Ultimately the models themselves don’t contain any copyrighted content, but they (by design) combine related ideas and patterns found in the training data, in a way that will always approximate it, depending on the depth of training data. While “overfitting” might be considered a negative in the industry, it’s still a possibility, and until there is some sort of regulations establishing the fitness of commercially available LLMs, I can envision situations in which management would cut training short once it’s “good enough”, leaving overfitting issues in place.

Lastly, with respect, I’d like to push back on both the notion that I’d like to ban AI or LLMs, as well as the notion that I’m not educated enough on the subject to adequately debate regulations on it. Both are untrue. I’m very much in favor of developing the technology, and exploring all it’s applications. It’s revolutionary, and worthy of the research attention it’s getting. I work on a variety of models across the AI and LLM space professionally, and I’ve seen how versatile it is; That said, I have also seen how over publicized it is. We’re clearly (from my perspective) in a bubble that will eventually pop. We’re claiming products use AI to do this and that across nearly every industry, and while LLMs in particular are amazing, and can be used in a ton of applications, it’s certainly not all of them— and I’m particularly cautious of putting new models in charge of dangerous or risky processes where they shouldn’t be before we develop adequate metrics, regulation, and guardrails. To summarize my position, I’m very excited to work towards developing them further, but I want to publicly express the notion that it’s not a silver bullet, and we need to develop legal frameworks for protecting people now, rather than later.

The law is (in an ideal world), the reflection of our collective morality. It is supposed to dictate what is “right” and “wrong”. That said— I see too many folks believing that it works the other way too, that what is illegal must be wrong, and what is legal must be ok. This is (decisively) not the case.

In AI terms, I do believe some of the things that LLMs and the companies behind them are doing now may turn out to be illegal under certain interpretations of the law. But further, I think a lot of the things companies are doing to train these models are seen as “immoral” (me included), and that the law should be changed to reflect that.

Sure that may mean that “stuff these companies are doing now is legal”, but that doesn’t mean we don’t have the right to be upset about it. Tons of stuff large corporations have done was fully legal until public outcry forced the government to legislate against it. The first step in many laws being passed is the public demonstrating a vested interest in it. I believe the same is happening here.