Things are also getting better now that Intel is dying. I mean, the new Apple silicon chips are astoundingly fast and energy efficient, an M1 from 5 years ago is still going strong and probably won't truly need replacing for another 2. Similar for Ryzen chips from 5 years ago!

Things have changed a lot in 20 years. In 2005 we didn't consume all of our video / audio media online. We didn't have social media, just blogs and RSS readers. YouTube had just been released. TikTok, Facebook and Twitter didn't exist. Hypermedia today is very rich and necessitates a lot of resources. But at the same time, most work the past 10 years has been on native apps (on mobile particularly but also PCs), not web sites. Most people don't use the web browser as much.

Certainly the emergent behaviour is exciting but we tend to jump to conclusions as to what it implies.

This means we are far more trusting with software that lacks formal guarantees than we should be. We are used to software being sound by default but otherwise a moron that requires very precise inputs and parameters and testing to act correctly. System 2 thinking.

Now with NN it's inverted: it's a brilliant know-it-all but it bullshits a lot, and falls apart in ways we may gloss over, even with enormous resources spent on training. It's effectively incredible progress on System 1 thinking with questionable but evolving System 2 skills where we don't know the limits.

If you're not familiar with System 1 / System 2, it's googlable .

Not trying to be a smarty pants here, but what do we mean by "reason"?

Just to make the point, I'm using Claude to help me code right now. In between prompts, I read HN.

It does things for me such as coding up new features, looking at the compile and runtime responses, and then correcting the code. All while I sit here and write with you on HN.

It gives me feedback like "lock free message passing is going to work better here" and then replaces the locks with the exact kind of thing I actually want. If it runs into a problem, it does what I did a few weeks ago, it will see that some flag is set wrong, or that some architectural decision needs to be changed, and then implements the changes.

What is not reasoning about this? Last year at this time, if I looked at my code with a two hour delta, and someone had pushed edits that were able to compile, with real improvements, I would not have any doubt that there was a reasoning, intelligent person who had spent years learning how this worked.

It is pattern matching? Of course. But why is that not reasoning? Is there some sort of emergent behavior? Also yes. But what is not reasoning about that?

I'm having actual coding conversations that I used to only have with senior devs, right now, while browsing HN, and code that does what I asked is being produced.

Reasoning appears to actually be more accurately described as “awareness,” or some process that exists along side thought where agency and subconscious processes occur. It’s by construction unobservable by our conscious mind, which is why we have so much trouble explaining it. It’s not intuition - it’s awareness.

I’m using Opus 4 for coding and there is no way that model demonstrates any reasoning or demonstrates any “intelligence” in my opinion. I’ve been through the having conversations phase etc but doesn’t get you very far, better to read a book.

I use these models to help me type less now, that’s it. My prompts basically tell it to not do anything fancy and that works well.

it me

Is that very unlike humans?

You seem to be comparing LLMs to much less sophisticated deterministic programs. And claiming LLMs are garbage because they are stochastic.

Which entirely misses the point because I don't want an LLM to render a spreadsheet for me in a fully reproducible fashion.

No, I expect an LLM to understand my intent, reason about it, wield those smaller deterministic tools on my behalf and sometimes even be creative when coming up with a solution, and if that doesn't work, dream up some other method and try again.

If _that_ is the goal, then some amount of randomness in the output is not a bug it's a necessary feature!

We deal with non determinism any time our code interacts with the natural world. We build guard rails, detection, classification of false/true positive and negatives, and all that all the time. This isn’t a flaw, it’s just the way things are for certain classes of problems and solutions.

It’s not bad software - it’s software that does things we’ve been trying to do for nearly a hundred years beyond any reasonable expectation. The fact I can tell a machine in human language to do some relative abstract and complex task and it pretty reliably “understands” me and my intent, “understands” it’s tools and capabilities, and “reasons” how to bridge my words to a real world action is not bad software. It’s science fiction.

The fact “reliably” shows up is the non determinism. Not perfectly, although on a retry with a new seed it often succeeds. This feels like most software that interacts with natural processes in any way or form.

It’s remarkable that anyone who has ever implemented exponential back off and retry, has ever implemented edge cases, and sir and say “nothing else matters,” when they make their living dealing with non determinism. Because the algorithmic kernel of logic is 1% of programming and systems engineering, and 99% is coping with the non determinism in computing systems.

The technology is immature and the toolchains are almost farcically basic - money is dumping into model training because we have not yet hit a wall with brute force. And it takes longer to build a new way of programming and designing highly reliable systems in the face of non determinism, but it’s getting better faster than almost any technology change in my 35 years in the industry.

Your statement that it “very often produces wrong or nonsensical output” also tells me you’re holding onto a bias from prior experiences. The rate of improvement is astonishing. At this point in my professional use of frontier LLMs and techniques they are exceeding the precision and recall of humans and there’s a lot of rich ground untouched. At this point we largely can offload massive amounts of work that humans would do in decision making (classification) and use humans as a last line to exercise executive judgement often with the assistance of LLMs. I expect within two years humans will only be needed in the most exceptional of situations, and we will do a better job on more tasks than we ever could have dreamed of with humans. For the company I’m at this is a huge bottom line improvement far and beyond the cost of our AI infrastructure and development, and we do quite a lot of that too.

If you’re not seeing it yet, I wouldn’t use that to extrapolate to the world at large and especially not to the future.

What in the accelerationist hell?

Vision Pro was all about selling an enthusiast device that pushes the boundaries of XR technology into what they thought was appropriate baseline that would shift the market. They succeeded at that, the entire market is changing their strategy to respond to visionOS. visionOS has set the baseline for spatial computing so much that even horizon OS is copying it now. Apple takes the product line very seriously, they they’re just playing a different game than you want them to play.

I mean, I don't care what they do (other than as a shareholder, lol. But it's not a major part of my portfolio.)

I just do not think they have made an impact on the mass-market -- and at their market cap, anything short of mass-market should be considered a failure and a distraction from products that actually sell.

"Horizon OS copying them" is flattering I guess, but they're not copying all the stupid things about AVP: The heavy, expensive metal construction, the silly outer display, the stupid tethered proprietary battery, the $3500 price tag. I do have a Quest 3 though, which is vaguely fun, but was an impulse buy I only occasionally use.

I've never even tried the AVP, and while that seems like a disqualification of me as a judge of it, that's just the point: I'm a geek. If even I dismiss it as a useless and overpriced toy, it will never be mass market, because normal people need more of a justification than I do to adopt a gadget. It needs to do something amazing that people immediately see the value of. Which is why I cited courtside NBA games (not a 10-minute short btw) as an example.

If Apple's 'game' is to make a niche device with no important apps and about 5,000 MAUs then they're playing it great.

People who follow the XR industry know that most aspects of the AVP were very carefully considered engineering and design trade-offs, including the aluminum construction, which is arguably lighter than plastic for the nature of the headset design requiring a certain level of durability and recyclability. Tethered battery is also a very smart design decision, that I think we will see followed by other manufacturers. The outwardfacing display is necessary if the headset is to be integrated in the workplace or in a social environment, such as cafés or airplanes. In my experience, my family and coworkers appreciate it.

For me that part is just proof that they are determined, even after you spend $3.5k, to nickel and dime you: the only way to get increased battery life is either to buy additional hundred plus dollar (so, marked up 10x from their cost) batteries from Apple, or to daisy-chain the heavy battery to your own heavy battery (or to the darn wall.)

Goggles have not bombed, and are not going away for at least a decade. Apple will not be abandoning visionOS for spectacles, I know you keep repeating this, but it’s false.

VisionOS is clearly a triumph and the basis of UX for their entire product line. The scepticism is gonna age like those who were sceptical about the original Mac and Windows. Vision Pro isn’t even all that expensive by historical standards.