You sound like an idiot

So powerful that Claude requires a billion little hacks to be optimized so as not to use ridiculous amounts of tokens. The programmers are so good they can't build those optimizations into the model to begin with.

AI was supposed to resolve these issues, not add to them. Claude is the worst offender of them all.

I suspect most of the amplification of right wing noise has something to do with the left wingishness of the complainers.

My stance comes from seeing it from the other side. I'm comfortably right of center and my previous experience with Twitter (x is a stupid name) is that it absolutely was a left wing echo chamber. It indeed was rather calmer because of the aggressive pruning of any conservative voices.*

I believe the algo serves you aggressively oppositional views to spur contrary posting and raise engagement. It's a rather simplistic but effective tactic. If you're leftish, you get served the worst of the right, along with a strong current of fringe left views to affirm you are "reasonably left, not like those crazies". If you're conservative you get the worst of the left, and a current of toxic right wing enough to affirm that you're not that far right.

My "for you" feed is exclusively militant socialists, feminists, pro trans activists, leftist local politicians (not hard to find as I'm in MN) all just ceaselessly toxic people.
My "following" is like wise a cess pool of right wing commenters, the worst of the worst shouting all sorts of racist, anti women nonsense, interspersed with occasionally interesting comments about ttrpg games and science subjects that are actually interesting.

I joke that "for you" is comments entirely from people I completely disagree with and despise. "Following" is only *mostly* people I disagree with and despise.

(I actually "follow" only maybe a dozen people in science, tech, ttrpg gaming, and work-related subjects. No politics, no dogmatics of either side. Certainly no politicians.)

As a result, I spend almost no time on Twitter

*(Nota bene to this day I still have a banned account from just before musk's takeover for a post in a David Axelrod thread, observing that transsexual strippers & burlesque dancers seemed to militantly insist on the right to dance in front of children to "express themselves" but I'd failed to see any comparable insistence to dancing in front of the elderly.)

About the most succinct, blather free summary I've seen.

Unfortunately, and definitely not to credit the legions of ai snake-oil sales going on, Jevons paradox probably means that rather than ai ushering in some sort of low-work utopia, we'll more likely indeed just figure out how to use it properly and end up back at 40 hour work weeks with (likely) an explosion of increased productivity.
I don't know how we get there personally but that's the sort of blindness we have before paradigms genuinely change, like the coming of the Internet.

New here? Slashdot has been suffused with politics for two decades, as tech stories are largely replaced with a feed that's more and more like the usual social media cesspool of left and right wing dogmatics shutting at each other.

When a candidate is granted a professorship based on race, and then militantly (irrationally) defended again largely based on race, how is nobody supposed to bring that up?

"automatically create personalized highlight reels"

Basically its posting dumb shit for you in the background while you are at a dinner party. Peak Facebook garbage

The only decent song they wrote.

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.

University is just becoming another adult daycare. Sad

...is not found in avoiding the problem.

You are here to educate these kids. This is your role.
Granted, these issues should have been addressed long before COLLEGE but the idea of entering supposed 'adulthood' without the mental armor to deal with things like "being rated for your performance" is...asinine.

STOP WRAPPING PEOPLE IN BUBBLE WRAP. You are not doing them favors, you are just kicking their mental health issues down the road (while exacerbating them, most likely) for someone else to deal with.