I agree. The person had better get explicit permission from everyone present and be prepared to remove the wearable or prepare for the consequences.

and then the noise blows over and they'll allow the free-for-all to continue again. Nothing good is going to come from having pervasive surveillance of people just going about their daily lives in their car. They've taken an inch, then a foot....the mile isn't far off. Y'all metric using folks can convert to your favourite units.

Very likely has nothing to do with Machine Learning. My old mentor worked for a defense contractor where they had 6 SPARC processors in a missile for its advanced guidance system. Thousands of dollars worth of compute, used to guide a missile accurately to the point where it would explode. What a damn waste.

These are likely chips used for missile guidance and thrust/fin control.

Amazing win for people in France. We all know none of these laws have anything to do with protecting children. They're all about digitally fingerprinting every individual online to their citizenship, censorship and prevention of dissent. Age verification laws are the means to technocracy and they should be opposed at every level.

It's the parent's responsibility to instill values about things like social media and pornography, not the state.

You can get this kind of basic image recognition on $20 ARM boards from China. I've got a rock3a (older, barely capable compared to whats available now) board cluster that does this kind of image recognition for my cameras. rpi3 level stuff. That it was nvidia just speaks to what is available.

Sure, let's discuss that. You've got a handful of methods historically:

- GPS/GLONASS/Starlink - can be jammed.
- Wire - inaccurate, not suitable for OTH guided missiles
- Pigeon - inaccurate and expensive
- Radar - can be jammed
- IR/laser - line of sight/requires IR signatures
- inertia - inaccurate, expensive.

There's nothing which really compares to "AI" in capability or accuracy. It's the only option which can't be jammed directly short of active EMP and provides the required/desired accuracy.

That's kind of been the bread and butter for cloud providers - "data velocity". They say: keep all your stuff on our cloud, it'll be safe forever, you don't need to worry about it.

A single copy is zero copies and 2 is 1. This is overlooked on all clouds, on the basis that 3 copies on a cloud provider is still 1 copy.

This kind of oversight failure has ended many companies when they've had DR scenarios. I know of 2 that had to close shop because the egress cost of all their data from AWS was larger than insurance would pay out, and the cash difference was significant.

In most cases, it makes more sense to keep 2 local copies (different storage) than 2 cloud copies, for this reason alone.

Jetson Orin is roughly 4 year old tech that's EOL now. I'm not sure how newsworthy this is. It's a graphics chip for mobile applications, not really an AI chip.

Nothing to see here....

Even if frontier models only continue to get 'marginally better' in terms of evaluations, as they have been for the past year, it's quite apparent that the newer models tend to be significantly better in aggregate and practice.

We're also starting to see a stratification across frontier models:

- Anthropic seems focused on "one shot" capabilities (latest generations have suffered significantly in other departments)
- GLM seems to be increasing their focus on security and coding robustness
- Google seems to be leaning in on 'fast and cheap' and 'good enough'
- Agnes (while not quite frontier) seems to be going for "broad scope of capabilities"
- LiquidAI is focusing on specialized, small local models for agentic pipeline work
- OpenAI seems stratified on do-everything frontier models with functional stratification based on task complexity
- Qwen - local capability focus.
- Grok - code centric + fast.
- Deepseek - also local-capability focus while trying to optimize the full stack

Then you've got the mess of models like Laguna (last generation capabilities but local-focus) and Agnes (more like google's approach, with a wide and cheap portfolio).

As for Anthropic (and , it is quite apparent that they're architecturally behind in many ways to other models. The release of dflash papers and the subsequent speed increase on the competitor models made that plainly obvious.

Not enough competition. Macs are too expensive and Linux still doesn't come pre-installed on many systems and there are way too many desktops. That might be great for us geeks but Mr and Mrs Average just want a consistent and intuitive (hello Gnome devs, anyone listening?) desktop experience.

This is at least the 2nd time they've done a retreat in China.

There has never been a level playing field there for foreign companies.

At this time, Transcranial Magnetic Stimularion (TMS) has shown similar positive benefits as ECT without the brutal side effects of ECT. I believe that TMS is now favored over ECT for initial use despite slightly lower remission rates, mostly because TMS has much milder side effects and people are less likely to quit mistreatment. https://pmc.ncbi.nlm.nih.gov/a...

I guess I'm atypical then. I tend to get a "flagship" phone when I need one and then I keep it until support dries up. Rinse. Repeat.

The problem is that AI has made it very obvious that teachers have not been doing their jobs.

For instance: one history test, one report. Two different responses: "Contrast the political sentiments at the time of the American Revolution with modern day American sentiments and political events." 1 page report.

You could just paste that into chat and get a useable if not undetectable result. The result is obvious. Instead, a curious student could use the tool to pose a more complete question to chat: take into mind more emotional similarities between different political factions, as well as the contrast amongst social classes. It'll help them stand out a bit and it'll be different, and they might learn something.

But, I do note: this would require a curious student. Teachers have all but punished curiosity and a love for education for decades, catering to the dumb ones to keep them engaged instead of punishing them for wanting to be dumb.

That's the dumbest thing I've ever heard.

AI has only accelerated my desire for learning. I can learn so much more (though perhaps not as thoroughly or as deeply, because you don't have to go below the architectural surface as much anymore) now than I could before: much less switching between tabs, copy/pasta'ing, digging for documentation (and reading a lot of things that I don't remember 3 seconds later because I'm looking for something specific).

The same goes for reading about history, or anything else. Curiosity is rewarded rapidly with AI.

No, the biggest problem with education in the schools is the schools and how they teach. They've made it un-interesting and curiosity is generally punished. They have completely destroyed education long before AI was even a question - I'd argue shortly after the Internet became available and approachable for your typical 100-IQ public school teacher, in the late 90s.