It's hard to unpack without knowing more about the use case, but adding discriminant properties (e.g. "user_type") to all the types in the union can make it easier to handle the general and specific case.
E.g.
if (user.user_type === 'authenticated') {
// do something with user.name because the type system knows we have that now
}
The dot com boom is an apt analogy: the internet took off, we understood it had potential, but the innovation didn't all come in the first wave. It took time for the internet to bake, and then we saw another boom with the advent of mobile phones, higher bandwidth, and more compute per user.
It is still simply too early to tell exactly what the new steady state is, but I can tell you that where we're at _today_ is already a massive paradigm shift from what my day-to-day looked like 3 years ago, at least as a SWE.
There will be lots of things thrown at the wall and the things that stick will have a big impact.
other than constantly feeling gaslit about the quality of these tools, I can tell you where we are _today_ is basically the same in my day to day as it was three years ago.
oh except, sometimes someone tells me I could use the bot to generate a thing, and it doesn't work, and I waste some time, and then do it manually.
Having used the latest models regularly, it does feel like we're at diminishing returns in terms of raw performance from GenAI / LLMs.
...but now it'll be exciting to let them bake. We need some time to really explore what we can do with them. We're still mostly operating in back-and-forth chats, I think there's going to be lots of experimentation with different modalities of interaction here.
It's like we've just gotten past the `Pets.com` era of GenAI and are getting ready to transition to the app era.
I would really like to see the current generation of this tech make it into video games. Not the Sora type where the entire game is an interactive video (though that would be interesting to explore as well), but in more subtle and imaginative ways.
Perhaps as an extension of procedural generation, in interesting mechanics such as [1], or eventually even fully interactive NPCs.
PCs are starting to become more capable of running models locally, which can only make this tech more accessible. Like you say, we've barely begun exploring the possible use cases.
For sure. Thanks for explaining, I think you're right.
Whenever I hear him interviewed (or read his books) I come away with the impression Silverman is a bit up his own rear but I don't see what's objectionable about writing recommendations for people you've worked with. That's pretty normal.
I’ve never been able to put it into words, but when we think about engineering in almost any discipline, a significant amount of effort goes into making things buildable by different groups of people. We modularize components or code so that different groups can specialize in isolated segments.
I always imagined if you could have some super mind build an entire complex system, it would find better solutions that got around limitations introduced by the need to make engineering accessible to humans.
An "optimal" solution may do away with "wasteful" abstraction of interfaces and come up with something more efficient. But there is wisdom in narrow interfaces and abstractions. Structure helps to evolve over time which at least for now most computer optimization focuses on getting the best solution now.
I think it’s half-guess and half-hope but I imagine we’ll spend centuries building really dumb mechanism, then suddenly be completely left in the dust intellectual. I guess that’s what you’d call the singularity. I don’t know if that hypermind will bother designing circuits for us.
The "iPhone moment" gets used a lot, but maybe it's more analogous to the early internet: we have the basics, but we're still learning what we can do with this new protocol and building the infrastructure around it to be truly useful. And as you've pointed out, our "bandwidth" is increasing exponentially at the same time.
If nothing else, my workflows as a software developer have changed significantly in these past two years with just what's available today, and there is so much work going into making that workflow far more productive.
But if this is like the internet, it’s not refuting the idea that this is a huge bubble. The internet did have a massive investment bubble.
And I’d argue it took decades to actually achieve some of the things we were promised in the early days of the internet. Some have still not come to fruition (the tech behind end to end encrypted emails was developed decades ago, yet email as most people use it is still ridiculously primitive and janky)
Yes. But this article argues two things at once - that the technology is itself not useful and not used, and that this won't change in the future. And it also argues that this is a bad investment, at least in the form of OpenAI.
I have very little idea of the second - it's totally possible OpenAI is a bad investment. I think this article is massively wrong about the first part though - this is an incredible technology, and this should be evident to everyone (I'm a little shocked we're still having an argument of the form "I'm a world-class developer and this increases my productivity" vs. "no, you're wrong!" on the other).
While there was certainly a software bubble during the early internet, it still took obscene amounts of investments in brand new technologies in the late 90's. Entire datacenters full of hardware modems. In fact, 'datacenters' had to become a thing.
Then came DSL, then came cable, then came fiber. Countless billions of dollars invested into all these different systems.
This AI stuff is something else. Lots of hardware investment, sure, but also lots of software investment. It is becoming so good and so cheap its showing up on every single search engine result.
Anyway, my point is, while there may have been aspects of the early internet being a bubble, there were real dollars chasing real utility, and I think AI is quite similar in that regard.
Can it be an investment bubble but also a hugely promising technology? The FOMO-frothing herd will over-invest in whatever is new and shiny, regardless of its merits?
> If nothing else, my workflows as a software developer have changed significantly in these past two years with just what's available today, and there is so much work going into making that workflow far more productive.
this is exactly the problem
The more productivity AI brings to workers, the fewer employees employers need to hire, the less salary employers need to pay, and the less money workers have for consumption.
I think the answer is that open source made developers more valuable because they could build you a whole lot more functionality for the same amount of effort thanks to not having to constantly reinvent every wheel that they needed.
More effective developers results in more demand for custom software, resulting in more jobs for developers.
My hope is that AI-assisted programming will have similar results.
I don't really know myself, but I think there's a decent change that most developer jobs will actually disappear. Your argument isn't wrong, but when we're nearing (though still far from) the state where all productive tech work can be handled by LLMs. Once it can effectively and correctly fix bugs and add new well-defined features to a real codebase, things start to look very different for most developers.
https://www.anthropic.com/jobs?team=4050633008
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