keeda

https://en.wikipedia.org/wiki/Robert_Metcalfe#Predicted_Inte...

Copyright very explicitly does NOT cover functional aspects, only creative expression. But the value of software is not in the expressive aspects of the code that generates it, the value is in the functionality it provides. And this is the exact thing that copyright does NOT protect!

Like, literally, we're protecting the fact that we used a for-loop instead of a while-loop to do a useful thing, not the useful thing itself. This is why rewriting enough code is sufficient to bypass all copyright protection, as the recent AI rewrites have shown.

This was always a huge legislative hack, rightfully controversial at the time it happened, but legislators didn't want to bother figuring out a proper IP regime for software -- maybe something between copyright and patents -- so they shoehorned code into copyright.

Google v Oracle was trivial to decide, but it got decided the wrong way. Because it became a trial around laws based on an ill-founded legislative hack and the decades of flawed case-law it spawned. Stepping back, it is very clear that Sun spent billions making a very useful thing and Google co-opted it for its own uses without recompense because they bet (correctly) that they could legally get away with it.

It is somewhat analogous to what the AI companies are doing with all the code and data out there. Funny that people are unhappy about THAT but cheered when Google did it to Sun / Oracle. I wonder what changed ;-)

My simplistic narrative, based mostly on the timing of market I observed, agrees with yours: the tech selloff was sparked by Google's earnings report. Mostly the fact that Google's Search cash cow seems to be getting cannibalized by its less profitable AI overviews, compounded by their cash flow turning negative due to their insane CapEx bill, which is only going to keep going up. And then Amazon reported a similar plight.

Hilariously, this even affected MSFT, which actually had a good quarter while being the only hyperscaler with positive cash flow, initially sending the stock to record highs. And then Google's earnings report hits and drags everything down. Satya must have been pretty annoyed.

Another way to look at it is, bureaucracy is an aspect of the corporate culture, and lasting security comes down to having the right culture. At least in that respect Microsoft is doing something right. Doubtlessly a lot of that bureaucracy is ineffective, but it's a signal that the cultural intention exists.

As a relevant counterexample, we've never heard of these kind of processes at Meta and so you get Cambridge Analytica.

My perspective is skewed by my experience being on a security-adjacent platform team for years. Our biggest challenge was not external threats, it was internal teams seeing us as friction on their productivity, to the extent that it regularly led to escalations.

So when Cambridge Analytica happened, I played it up for all it's worth; Meta may move fast because they didn't have our "bureuacratic team", but look where it got them! Unfortunately the $25B penalty happened just last week... I'd have gotten infinite political mileage out of that.

Of course in the short term we have to deal with pesky things like rent and food, for which we need jobs that are little more than filing TPS reports, which keep us from making progress towards our destiny…

But in the long term, after the economy implodes because AI starts filing all the TPS reports, and we rebuild it for a future where humans are actually allowed to reach for their full potential, we’re gonna need all the intelligence we can get!

Either way Anthropic will IPO soon and we’ll be one step closer to finding out.

One thought I had is that, bubble or not, this technology is likely going to upend economies of entire nations and impact all people, so it would be better if controlled by the people which is (in theory) represented by the government.

Looking at this as a backdoor bailout is the wrong perspective; it should be more like giving the people control over their economic future.

As is what constitutes the standard of “adequate.” Which BTW is the standard in ALL engineering (not just security or software) because we live in a world where economic pressures apply and costs must be managed. Trivial example: bridges only use an “adequate” amount of steel and concrete because they are not free. The word “adequate” fundamentally involves the concept of tolerances. There’s a reason we consider over-engineering a bad thing.

So which development approach would you say is better correlated with good security outcomes?

But they are also very highly incentivized to be more secure. They have millions of customers (hence a correspondingly higher expectation of trust) and billions in revenue from the trillions in economic activity happening on those platforms (hence a correspondingly larger target on their backs.) This means exponentially higher liabilities. And that probably matters more than any other factor.

I’m not even blaming Zuck for that, he didn’t really invent it, though he certainly popularized it — he just made an astute observation of the dynamics in software and turned it into a company motto.

Like, in the theorycrafting in my comment that I linked before, I didn't assume any change in userbase; just how lucrative (or not) each step in a chat-based journey could be versus a search-based one.

Personally I have doubts that AI search would ever be as lucrative as traditional search, which I expanded on in that comment I linked.

https://arstechnica.com/gadgets/2026/10/google-admits-ai-sea...

I’ve been saying for a while that AI is going to be a bigger problem for Google than many realize: https://news.ycombinator.com/item?id=47957708

What they’re doing now is just being a lot more overt about it, because they want to carve up their old cash cow to feed their AI ambitions before ChatGPT and Claude eat it up first.

Like I'd be really curious to see evidence of people saying, either directly or indirectly, that "we should be suspicious of competence and excellence."

On the other hand, you already mentioned concrete evidence of money-seeking causing disasters: Boeing.

To me Ayn Rand's writings always seemed like an Economics Horror story: effective at instilling dread in its readers, but of some highly unrealistic boogeyman.

Like, a normal person is not going to open up an arXiv preprint from Google search because for approximately the entire population, it's going to be way beyond the limits of their comprehension. They won't even glance at the link, if Google even serves it up as a result.

But, with a chatbot, they could actually ask questions and get answers in a format they can understand. They may get a very rough understanding of the topic, but I would bet it's 100 times better than the same reference explained by modern "science journalism," which insists on presenting the most clickbait-y interpretation they can find.

And this is not theoretical, I've seen my high-school level kids figure out undergrad (or higher) level concepts like locality sensitive hashing with the help of ChatGPT, and I know they understood it because they could sketch out working solutions using those concepts. They didn't get the Mathematical underpinnings, but they understood the high-level behavior and that was enough.

Everybody can now understand anything if they really want to. Nobody is doing it today because they don't know it's possible. But they can, and we should encourage them to do so.

Turns out there are ways to monetize commodities, to the tune of double-digit billions in revenue per quarter.

It may not seem like it in the moment, but writing code to specifications, or filling out reports in a given template, or formatting power points, was straightforward enough that it gave our brains some respite between cognitively intense bouts of synthesizing what we were about to write down: diagnosis, analysis, problem solving, "stakeholder alignment", design, architecture.

The act of generating the actual durable work product (code, reports, documents, spreadsheets, slides, etc) is largely just translating the results of this cognitively intense phase. It may not seem like drudge work, but it is a lot more mechanistic and hence cognitively lighter, even meditative in a sense. The separation of phases is never that clean, of course, but I think you see what I mean: writing a for-loop is muscle memory, figuring out that you need that for-loop is the hard part.

Now with all that drudge work being done by AI, all we're left with is the hard part. Which is why it feels more stressful: because it is.

Relevant article: https://hbr.org/2026/02/ai-doesnt-reduce-work-it-intensifies...

If it's not happening on a GPU, is it really a "token"? ;-)

It's like information theory for abstract concepts.

Secondly, this is not how Economics works. Relevant terms here would be "supply and demand" because that's what determines almost all wages. Knowledge workers (or any workers) are not paid based on how much it costs to sustain them, like some function of the COGS bill. Knowledge workers are paid so much higher because they supplied the one thing that was pretty rare but for which the demand was very high: intelligence.

AI is not "rectifying" that by consuming less energy, but by providing a supply of intelligence that scales with energy and compute, both of which are technically easier to scale than humans. Which is another piece he misses, the monopoly is not on AI, but on compute. (See: all the kerfuffle about export restrictions on Nvidia chips.)

He is right about some other things in that article though.

To be fair, I see where they're coming from: if they're providing you (what they consider) valuable AI services, they would want to monetize it somehow, because that inference ain't free. And people won't pay for it with their money, because they've trained this generation of Internet users to pay with their attention.

I also suspect they have little choice, because they foresee that the old search modality (and with it, their prized cash cow) withering away pretty soon. Personal Intelligence may well be their next big consumer cash cow, and competitors are already swooping in to try to capture that market (especially Apple with its privacy pitch.)

Dichotomy solved, let’s go get lunch! ;-)