They're still playing the "Try to get IBM to pay us to go away." game. It didn't work the first time around. This one's even more futile because this particular argument was dealt with during the original case and IBM proved that the code they contributed to Linux wasn't code belonging to Project Monterrey at all but completely different code IBM wrote themselves for a different product. But I suppose, given the people behind this, lack of pattern recognition skills is a given.

I don't really get your point. Maybe some American thing? As an outsider, it looked like Fauci was trying to do the right thing whilst being undermined by the political "leadership". We got many things wrong in the UK, but the Covid vaccine program wasn't one of them: in this we excelled with a fast, well-planned rollout and very high uptake and levels vaccination. That vaccination programme showed fantastic results in reducing Covid deaths and led us to be one of the Western countries with the fastest return of full freedoms. It would surprise me two years later going to work events in the US and finding people still talking about Covid and taking precautions when it was a distant memory for us. WTF?

Although the impact on children was big, the schools were only really closed for under a year. Lockdowns started Easter-ish 2020 and then the UK was going through its lockdown easing steps a year later after the vaccine program had been going full-steam since January 2021, with about 90% school attendance by March 2021. I remember American colleagues shocked at our levels of freedom so soon! London was buzzing again very quickly.

https://en.wikipedia.org/wiki/...

Except his. He has a range of houses that he can move to as the bad air moves around. All of them paid for through by sleaze and corruption.

Have you been to London? The traffic in the centre is as bad as it ever was. It's faster to cycle.

Work from home has increased traffic in the outer boroughs during the work day.

The ULEZ brought the biggest improvements in air quality in the outer boroughs. Inner boroughs benefitted too. Sounds like a win.

The rest of your post is inarticulate. Take a breathe next time and explain the points you're trying to make properly.

I love that the Tory outer boroughs who fought hardest against the ULEZ have ended up the biggest benefits improvements of the ULEZ.

Sadly, their voters don't understand. Sadly, they don't get that their chosen politicians hate them and care little for their health.

While I can see how you arrived at that, I don't think they're all the amoral actors you describe.

Zuck has shown some changes in the last couple years, though I agree he's largely amoral.

Musk has a very peculiar set of morals which might be described as pragmatism or amorality, but he's always been very focal in both action and word about both ethics and responsibility.

You could probably accurately describe them all as transhumanists with varying degree of consistency.

If there's a crisis of trust - which there is - it's almost certainly largely provoked by Amodei. The guy has been a regular prophet of doom regarding AI: it's going to take all the jobs, it's dangerous and going to cause all sorts of disasterous side effects socially, economically, and politically. No wonder people are untrusty.

Pair that with the obscene levels of what appears to be state-level anti-AI and anti-datacenter propaganda, and you've got the current situation. The amount of absurd claims I've seen about datacenters and AI, from people who should know better - everything from completely false narratives about water use, land grabs, power use, and so on. The truth is, an AI DC doesn't uses less water than a Cosco and about as much electricity as a comparable industrial facility, or a similarly sized restaurant.

Didn't Amazon remove the mandatory arbitration clause a while back because too many users were using it, making Amazon have to spend too much money and time on arbitration? Or was that another large Internet vendor?

For anyone who thinks it's ridiculous that the US can't reproduce the Apollo missions, consider this: we can't (due to environmental factors) produce wrought iron anymore (because there are no longer any facilities setup to do so), as a species, and therefore, could not build the Bay Bridge in San Francisco (and I'm sure, any number of others, like the Brooklyn bridge).

The same limitations apply here. They have to redesign the vehicle on first principles because the foundational engineering (not scientific understanding) being used no longer exists. Most people simply do not realize how precariously our technological world hangs in the balance. It's why highly advanced ancient cultures collapsed, in large degree: they couldn't just start at the lower level again before working their way back to 'advanced civilization', they had to start all the way at zero again.

Here's a fun one I like playing with my kids, kind of the nerdy science version of the polysci "go back in time to kill Baby Hitler: which one scientific understanding would you bring back in time to Ancient Rome/the American Revolution/the 1950s/etc. and why? Dollars to donuts they'll say something like "the lightbulb" and not consider that it's at least 3 distinct discoveries and inventions, nevermind the engineering.

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.

Investors are chasing a company that achieves some kind of AI singularity. Let's set aside the fact that there's no reason to believe there is anything but diminishing marginal returns by making marginal refinements to current frontier models. Let's imagine someone hits the jackpot and gets, not even AGI, but a system that's as far ahead of today's frontier model are ahead of 2020's GPT 2.0 in performance.

Globally AI revenues are 150 billion, against a cumulative burn rate of 450 billion. A model that is a generation ahead of others would almost certainly capture the lion's share of that revenue.

If AGI magically appears as a Sam Altman has promised investors it will, a hundred million is way too low. Add, maybe, another zero to the revenues.

Conservatively, a safer assumption is that frontier models will get marginally better based on refinements in training and reinforcement and the other bits and bobs that go into these systems. The nobody is winning the lion's share of anything, at least overnight. But you have to define "safe". By "safe" I mean unlikely to lose money. But some investors are clearly defining "safe" as "having the greatest chance of owning a piece of the biggest thing ever."

I'm not following this super-closely, but if Anthropic is pursuing adding multi-step model based reasoning to their system, that could be the basis of a generational leap in capability. But if that is an approach that looks like it has a chance of working, then their competitors are no doubt pursuing the same thing. In that case you'd expect the revenue pie to grow as the scope of model utilty increases, but that growth to be split among several competitors. This could credibly result in a revenue stream for some of them that is as big as the entire industry's revenue stream today. But there's going to be hell to pay on the data center impacts end of things.