keithwhor

The economics of production cost, investment and distribution have created a lopsided industry where only guaranteed hits get funded. Less soul = pandering to more people.

With new tools we can reduce the production costs of great movies considerably. More budget, if it exists, can go to marketing and distribution. I expect this will lead to more experimental films and a lot more "soul." There will be a TON of slop, too, but that's fine! It's all part of experimentation with a new medium.

My guess is that intelligence gets commodified to the point where LLMs and diffusion models are sold on chips and we seamlessly integrate them into the HW + SW stack. Then they’re just another abstraction; we talk to our computers to get things built. At essentially zero cost, truly too cheap to meter.

In parallel there’s an explosion of creative output; Marvel movies turn around in 1 year instead of 4, solely blocked on availability of actors. Some actors license their likeness to unblock their calendar from reshoots so they can earn more. We don’t replace them wholesale because people idolize celebrity.

And demand for movies? Skyrockets. With new mediums to pursue. Classics like Goodfellas resurrected in high-fidelity 3D on the Vision Pro. A combination of diffusion models and Gaussian splatting means every movie can be upscaled to immersive 3d.

Video games enter a second renaissance, with indie developers having the advantage. For large studios, nostalgia is the moneymaker. The remake of Final Fantasy VII across three games that costs $100Ms and decades? Final Fantasy VIII gets rebuilt from scratch with a team of 30. But the rest of the money and team that would’ve been on that project now expand to other, more ambitious projects.

This is just the tip of the iceberg. Mars? Why stop at Mars? Let’s start megaprojects to explore the galaxy. Mine asteroids for resources. What’s stopping us? Humans yearn for the unknown. When we exhaust resources or a modality of existence, we dream bigger, not smaller.

I personally see consumer and entertainment spending, and people employed lucratively in these sectors, growing dramatically. Maybe SaaS and a lot of businesses that have traditionally employed white collar employees fade. And a bunch of boring “financistas” don’t know how to make a buck betting in the casino anymore because boring old businesses and things nobody really wanted to do anyway aren’t lucrative anymore.

But, personally, the whole reason I got into software was to build cool stuff. Starting with video games! The type and scale of cool stuff I can build is only getting better, at an insanely fast rate. My bet is we thrive.

One that goes boom.

You’ve just described what Roblox is already doing.

It’s also possible for LLMs to be inevitable, generate massive amounts of wealth and still be mostly fluff in terms of objective human progress.

The major change from my perspective is new consumer behavior: people simply enjoy talking to and building with LLMs. This fact alone is generating a lot (1) new spend and (2) content to consume.

The most disappointing outcome of the LLM era would be increasing the amount of fake, meaningless busywork humans have to do just to sift through LLM generated noise just to find signal. And indeed there are probably great products to be built that help you do just that; and there is probably a lot of great signal to be found! But the motion to progress ratio concerns me.

For example, I love Cursor. Especially for boilerplating. But SOTA models with tons of guidance can still not reliably implement features in my larger codebases within the timeframe it would take me to do it myself. Test-time compute and reasoning makes things even slower.

I think it's likely we learn to develop healthier relationships with these technologies. The timeframe? I'm not sure. May take generations. May happen quicker than we think.

It's clear to me that language models are a net accelerant. But if they make the average person more "loquacious" (first word that came to mind, but also lol) then the signal for raw intellect will change over time.

Nobody wants to be in a relationship with a language model. But language models may be able to help people who aren't otherwise equipped to handle major life changes and setbacks! So it's a tool - if you know how to use it.

Let's use a real-life example: relationship advice. Over time I would imagine that "ChatGPT-guided relationships" will fall into two categories: "copy-and-pasters", who are just adding a layer of complexity to communication that was subpar to begin with ("I just copied what ChatGPT said"), and "accelerators" who use ChatGPT to analyze their own and their partners motivations to find better solutions to common problems.

It still requires a brain and empathy to make the correct decisions about the latter. The former will always end in heartbreak. I have faith that people will figure this out.

I think this is a cop out. OpenAI literally published a better integration spec two years ago, stored on `/.well-known/ai-plugin.json`. It just gave a summary of an OpenAPI spec, which ChatGPT could consume and then run your functions.

It was simple and elegant, the timing was just off. So the first shot at this problem actually looked quite good, and we're currently in a regression.

In the grand scheme of things I think we are still very early. MCP might be the thing which is why I'd rather try and contribute if I can; it does have a grassroots movement I haven't seen in a while. But the wonderful thing about the market is that incentives, e.g. good customer experiences that people pay for, will probably win. This means that MCP, if it remains the focal point for this sort of work, will become a lot better regardless of whether or not early pokes and prods by folks like us are successful or not. :)

Quick follow up:

I anticipate alignment issues as well. Anthropic is building MCP to make the Anthropic experience great. But Anthropic's traffic is fractional compared to ChatGPT - 20M monthly vs 400M weekly. Gemini claims 350M monthly. The incentive structure is all out of whack; how long are OpenAI and Google going to let an Anthropic team (or even a committee?) drive an integration spec?

Consumers have barely interacted with these things yet. They did once, with ChatGPT Plugins, and it failed. It doesn't entirely make sense to me that OpenAI is okay to do this again but let another company lead the charge and define the limitations of the end user experience (because that what the spec ultimately does, dictates how prompts and function responses are transported), when the issue wasn't the engineering effort (ChatGPT's integration model was objectively more elegant) but a consumer experience issue.

The optimistic take on this is the community is strong and motivated enough to solve these problems as an independent group, and the traction is certainly there. I am interested to see how it all plays out!

I mean you don’t need gRPC. You can just treat all tool calls as SSEs themselves and you have streaming. HTTP is pretty robust.