People have been having children later since about the 1930s. The change has been gradual, so it's only really hitting hard now because they've not had any children during the years when it's relatively easy, and now some can't. That could still be due to technology but not social media exclusively.

Coincidently though, this aligns pretty much perfectly to people's stability also shifting to happen later in life. Specifically the economic stability to raise a family on a single income. That's not really possible any more, so it shouldn't be a surprise that people don't do it.

Just to add a little factual data to this point, the fertility rate in England and Wales has been below two children per woman since the 1970s.

I imagine Claude could zero-shot a Chrome plugin for that.

Obviously you need a mixture of high recall and low false positive rate. If 7/8 flagged items are fine its much more likely people will ignore the warnings, much like they would any security tool with a 90% false positive rate. That is not optimized for the customer.

Presenting it as either a system that misses real problems or a system that has a huge number of false positives is a false dilemma. You can have a system that's designed to find all the problems and then optimize it to reduce the false positives. If you can't reduce the number then you optimize to identify false positives as fast as possible. Just ignoring the identified problems on the assumption that they're false is giant red flag and a signal that the org has a very a broken engineering culture (but, as you say, that's quite common.)

If you change a benchmark whenever you think it'll be 'wrong', then it becomes a measure of the heuristics you use to predict what'll impact the benchmark rather than a benchmark in its own right.

The market decides what the large-cap U.S. equities are, not S&P. If S&P excludes some of the largest U.S. companies, which based on their current rules, will exclude all of Anthropic, SpaceX, and OpenAI; then they do a poor job reflecting the benchmark they claim to follow.

It's not S&P's fault that market conditions have changed.

Sure, but right now they don't know how the market will react, so changing the index rules before there's any data would be a measure of their heuristics (e.g. what they believe the market will do), not a measure of what the market is actually doing.

Given these large-cap companies currently represent ~5% of the U.S. stock market capitalization, it's difficult to justify why these companies are excluded from a large-cap index.

It's not outside the realms of possibility that the price of the shares post-launch could collapse if the market decides they're over-priced. Shares in companies have been known to settle on valuations far below the IPO price in the past. At that point they won't represent ~5% of the total. Changing the index rules immediately before finding out what's going to happen feels like putting the cart before the horse.

Your "wait and see" argument doesn't apply, because (SpaceX, Anthropic, OpenAI) are excluded from the index for profitability reasons, not valuation reasons. These companies are deliberately reinvesting free-cash-flow into growth rather than booking GAAP profits. That's not going to change 6 months after IPO, and likely not for 3-5 years.

At the current pace, three of the ten largest US companies will not be included in the S&P 500, for probably 5 years after IPO.

The question still remains: should a benchmark that claims to represent large-cap US equities exclude companies that are demonstrably large-cap, just because they allocate their capital towards growing the company instead of generating profits?

Alternatively we just run the software in a browser (again, the primary advantage being to the developers, not the user) and need hardware to run 'browser + suboptimal app' instead of 'optimized app'.

Essentially modern dev is doing what Visual Basic did in the 1990s, only more so. The impact of that is we buy faster computers to run slower software at a reasonable speed.

The thing is though, this is all a massive win. The supply of software is by far the most important part of tech. It doesn't matter how fast your computer is if the app you need doesn't exist. We shouldn't change it.

One of the second order effects of AI collapsing the cost of building things is that product management is much more important now. A Product Owner/Manager who lacks the taste and insight (or data) to know what they should put in front of users and what they should just put in the bin will cause a company real harm, especially if the company moves to a "there's zero effort in building something, so we'll try everything!" model.

The only part that's really collapsed in effort is the translation from requirements into code. If you're using AI to generate requirements you're effectively building things based on what a 'random' requirements generator says. If that's as good as the requirements a Product Owner was writing then that person needs to improve.

We were doing the same things back then but with some nasty hacks to get things to work across different browsers. There's a reason why jQuery (released 2006) blew up, and plugin ecosystem was huge.

The belief that something is more likely to be secure because it's code instead of a prompt is likely only avoiding one particular type of attack. That's a win, but you probably shouldn't think of it as meaning your code is actually secure.

Slate published this about it in 2012: https://slate.com/technology/2012/03/narrative-science-robot...

For as long as we've had computers people have tried to make them sound human. It's not a new thing that people are concerned about knowing if they're talking to (or reading) a robot imitating a person.

Back in the day, baseball commentators sometimes did this for live games they couldn't see based on very limited information they were being passed. One such commentator was .. Ronald Reagan.

I was surprised how well it worked, even then.