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.

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.

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.

"3 dimensional thinking and problem solving is something you can learn to be good at"

It really isn't, not to a meaningful degree. You can sharpen cast iron, too, but that doesn't mean you'll have a sharp knife.

Spatial thinking (which is heavily linked to problem solving) is fairly tightly coupled to inborn intellect and early education capability attainment.

"Normal" meaning what would be a normalized average of other countries. The typical US national park is bigger than all but the biggest parks throughout Europe. They're absent even fire trails throughout most of them, and they do not have nearby civilian residences for wanderers to happen upon.

Larger parks are closer to what would be considered "remote wilderness" in the furthest extents of Asia. You've got some of these places just hours from our biggest metropolitan cities.

Really, the only places in the world which compare would be China and Russia, and large parts of South America. But in most cases those are actually wilderness, all but inaccessible.

He isn't even an expert. He's a hype man, a salesman.

Frankly, he's engaging in a zero sum fallacy. Because it's not perfect, it can't be done. But it quite clearly has been done, successfully, with a drastic reduction in fatalities and injury. Is it perfect? No. But it's better than anything Waymo has been able to achieve with fancy intrusive useless sensors (there's nothing quite as infuriating as getting in a Waymo and having it just sit there confused about the homeless guy standing on the curb), but it's made by Waymo's biggest potential competitor - Tesla.

You forget that Tesla's now got a (small) working Tesla robotaxi fleet, and their capabilities are far superior to what Waymo offers.

That isn't half of it.

How many people in the audience own a Tesla?

He's talking to people who, if they are not personally intimate with fully self-driving capabilities in a Tesla, are at least aware of the capability.

It's like Steve Jobs going to Xerox to give a talk about why mice are superior input devices for navigation over just a keyboard.

a) and yet, nobody pays for anything in these situations, usually. Healthcare picks it up. The price is inflated specifically because of socialized services: what's about $10k in operational cost ends up with a bill for $50k because of collusion in the subsidized healthcare environment.
b) and? We need people to fail to be guidestones for the others.
c) then the fee would be significantly higher.
c1) "normal countries" do not have parks like in America.
c2) no, they are not.

These kids compounded stupid decisions. Instead of sitting and waiting and giving their water to someone else to go get help, they went ahead recklessly. It's also an exceptional situation. You don't design your entire system around the exception.

The sick thing is, this is probably the first time most of those kids have ever really been outdoors on their own. They did this, in all likelihood, without any parental involvement, oversight, or inform.

Anyone who's spent more than an a couple hours hiking outdoors would be able to tell you that an 18 mile, 6k elevation hike is a 2 day backpacking trip for people in good shape. lol

The artifact - the dashboard - is unimportant. He was just using an example that his intended audience would understand the value of: C-level executives who live by dashboards.

The process is what's important, and he wrapped it in Microsoft's proprietary ecosystem to bring value proposition of his platforms forward.

The process isn't new, it isn't specific or special to Microsoft, but it would resonate with his intended audience. It's a good process, and one which maps well onto other technologies.

I can trivially do these things today, and could not before:
* I can pull current market data into a local database and not only build new reports and analysis off of them but then feed them through complex workflows
* I can pull current job postings via API and holistically analyze them against my resume, with my intent and purpose in mind (and then I can circle back and trivially build a personalized reusable expert system based on those analysis artifacts).

All of this is of course, fully possible without AI. It's just not practicable: what would take me 6-12 months of concerted effort to make useful can be done in a couple weekend hours over the course of a month. Systems integration is hard, and time consuming, work, arguably more complicated in many ways than development of a singular platform because you've got multiple domains you've got to have expert understanding of to be successful.

No different than any other corporate spin about the inflexibility or uselessness of their platform. AWS does this quite well. "Undifferentiated heavy lifting" - while ignoring the absurd complexity and beta quality of their own services. Every issue I have with their shit, I experience a new and different bug or incorrectness in their documentation, and it takes years for it to get corrected. There are still bugs in Lambda that I discovered and reported 5+ years ago which haven't been resolved.

At every level. They must be using claude to make their business decisions, too.

It's not only being demonstrated, it's being reveled in. Astounding.

I don't know if this is just the symptom of the AI bubble, cronyism, or "late stage capitalism" (even though the resemblance to capitalism long since ceased). But it's a mess.

20 years ago, these guys would've been tried for criminality by now. Both Anthropic and OpenAI. They're making Enron look like amateurs.