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Comment by joenot443 | Hacker News Reader

I'm glad this is getting more attention!

I posted the original reporting from The Australian yesterday - it's a good primer.

https://news.ycombinator.com/item?id=47379740 https://archive.is/pvRaG

I'm amazed no-one has used the term "Regulatory Drawbridge". It's a classic thing that happens in a number of industries - the big players push for more and more regulation. It costs them money and time, but it makes a massive barrier for new incumbents who don't have the cashflow and manpower to work through the regulatory process.

Medicine is the classic example, but it's happening in the tech industry too. The FAANGs of the world took advantage of an unregulated landscape, but now that they're in the castle they're pulling up the drawbridge behind them.

(sidenote - this is why regulation like the Digital Markets Act in the EU should be great. It's only a cost to larger businesses. In practice we're not yet seeing the changes that it should create).

99% sure it's BS though.

How can anyone believe that a guy could use a text-generating AI to design a novel cancer treatment, but not write some compliance document?

Come on!

The LLM didn't oneshot the mRNA treatment, it merely suggested the idea. Most of the steps in the process were done with specialized tools. And no novel treatments were invented wholesale, it's more applying a documented process with existing open-source tools that's just too personalized and expensive to be offered by any vet.

I find this story perfectly plausible.

Why do you find the idea of a man complaining about having painstakingly hand typed a 100 page document over three month when he claims he can use an LLM in a way pretty much no-one has before him?

It's several orders of magnitude easier to get an LLM fill some kind of red tape than it could be to use it in the way he claims to have used it.

He is not using an LLM in some new and exciting way. The process of making a personalized mRNA vaccine looks something like this:

1. Collect and sequence patient's normal and tumor genomes 2. Predict immunogenic neoantigens from genome 3. Generate optimized mRNA sequence from neoantigens 4. Create vaccine from sequence

modulo some variations, which I wrote off the top of my head because I understand this technology.

Steps 1 and 4 are done by contracted labs. Steps 2 and 3 are doable through open-source computational tools and a little engineering. What does ChatGPT do here? ChatGPT explains the process, finds labs that will do 1 and 4 for pay, finds published algorithms and data for steps 2 and 3. It's barely more complicated than what ChatGPT would do to help a student with their homework.

Legal documents, on the other hand? Have you ever tried to get an LLM to do your taxes? It's not easy.

> Legal documents, on the other hand? Have you ever tried to get an LLM to do your taxes? It's not easy.

Taxes are numerate, which is where LLMs fuck up.

Legal documents are structured texts, which is where LLMs shine. Should you blindly trust the outcome? fuck no, but a good first pass is trivially achievable if you set the right parameters. and make sure its relevant to the right jurisdiction.

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