>It's having a general understanding/view of the "baseline", aka healthy anatomy. This is something LLMs will never have
You're making the mistake of conflating AI with LLMs.
I don't think LLMs will reliably be better than a board of doctors. But an Expert System probably will (if it isn't already). That's literally what they were created for.
The biggest downside of LLMs IMO isn't the millions of Jules wasted on training models that are ultimately used to create funny images of cats with lasers. It's that all that money isn't being invested into truly helpful AI systems that will actually improve and save our lives, such as medical expert systems.
The nature of expert systems is to become experts on a system.
The reason you need a doctor, or more often, let's be honest, a good nurse, is because systems can fail in any one of 10000 as yet undiscovered ways. New nurses. New residents. New techs. And on and on and on. All the measurements you're feeding to the system are an amalgamation of the potential errors of a potentially different set of professionals each time you move a patient through the enterprise.
Full disclosure, my first startup was building PACS and RTP software back before AI reading was a thing. Current startup working across dental and medical. Rethinking the link between oral and systemic health. Partner has been in the C-suite of several hospitals over the past few decades and now runs large healthcare delivery networks.
The reason you can't hand things over to AI, is precisely because there are so many humans in the system. Each of whom are fallible. Human experts are quicker to catch it. Expert systems are not. At least not any ES or AI I've seen. And I've been going to, for instance, RSNA, for well over 25 years.
If you have an ES or AI in the system, you would naturally put the same professionals responsible for catching human screwups, in charge of catching AI and ES screw ups. Even if these AI's turn 100% accurate based on the inputs they are given, that professional would still be responsible for catching those bad inputs.
Example, it's never happened to one of my companies knock on wood, but I have seen cases of radiation therapy patients being incorrectly dosed. The doctor almost never was the one who miffed in the situation, but ultimately, s/he's responsible.
Why? Bad input should have been caught.
Another example, situations where you operate on the wrong side of the body because someone prepped the wrong leg. Surgeon didn't do the prep. Whoever did do the prep may have simply relied on the software. But the software was wrong. May have been anything. Point is, the team is good, but everyone just fell into too complacent of a pattern with each other and their tools.
Trust is good. Complacency is not.
The same will hold true for AI team members that integrate into these environments. It's just another "team member", and it better have a "monitor". If not, you're asking for trouble.
The "monitor" ultimately responsible for everything will continue to be the provider. Any change in that reality will take decades. (And in the end, they probably will not change the current system in that regard.)
If something has several clear positive effects, and a possible small, arguably irrelevant, negative effect, most people will agree that yes, it's good for you.
It's like trying to argue that running may have a negative effect on some people's meniscus under some specific circumstances. That doesn't negate the generalization "running is good for you".
One of my pet peeves with git (and systems both similar, and based on it) is that automated tests run after you've made the commit and push.
In my mind the commit (let alone the push to a publicly accesible server) should be done after, and only if, the automated tests are successfully executed. And there's no easy way to implement this, other than having a dirty branch that you discard after rebasing onto a more long lived one.
There are lots of reasons to commit when things are yet working. How else would you share code that you need help with?
The solution is gated merges. No merging to main unless ci passes.
Every org I have worked at bemoaned a flaky release process and refused e2e black box acceptance tests because "they are too slow." And every org I have worked at has realized they were wrong. We got appropriate gates that run in 5 minutes and an ops person is the only person who can force past any gate in case of emergency.
Guardrails like this only become more important with the accelerant that is ai.
You can use a pre-receive hook on a git server to reject pushes that fail compilation. Downside is that it requires admin access on git forges, so you're only able to do this if you self-host.
You get the starter by leaving flour and water at room temperature for several days. Once the starter is ready, it's just more flour and water, plus additional ingredients (salt, seeds, olive oil, etc) sitting for several hours until it's ready to go in the oven.
I've followed sourdough recipes that were extremely complicated, which required me doing task every few hours for 3 days (so no way to do it if you have a regular job). But at the most basic level sourdough is just a fermented mixture of flour and water that is then cooked.
> and left all their code available, as required by OSS.
IANAL, and I don't have a horse in this race, but I don't think that's required by OSS, not by the spirit of "the law", and (at least) not by GPL, MIT, and other similar mainstream licenses.
The spirit of open source is: you buy (or just download for free) a binary, you get the 4 rights. Whatever happens when the developer/company stops distributing (whether at a cost or free as in beer) that binary is completely outside the scope of the license.
You only have the right to modify if you can access the source.
If you got (a snapshot of) the source along with the binary, that's fine, there's no need to keep hosting the source anywhere.
But if the company said "for source, see: our github", then that github has to stay up/public, for all the people who downloaded the binary a long time ago and are only getting around to exercising their right to modify today.
They don't need to post new versions of their software to it, of course. But they need to continue to make the source available somehow to people who were granted a right that can only be exercised if the source is made available to them.
(IIRC, some very early versions of this required you to send a physical letter to the company to get a copy of the source back on CD. That would be fine too. But they'd also have to advertise this somewhere, e.g. by stubbing the github repo and replacing it with a note that you can do that.)
I used to love HN. Lots of interesting stuff, great articles, novel projects. Now it feels like the frontpage is always around 70% LLM-related stuff. And not breakthrough research or projects, just "new Claude version X" and shit like that. Eternal September I guess?
>They banned the_donald (which, yes, was spammy, but it seemed to be organic
I used to frequent /r/t_d when it was created, before the Republican primaries for the 2016 election. I visited every day because I was absolutely astonished at the gigantic marketing effort behind it. I had never seen anything like that before, and haven't since. It probably had a team of dozens or hundreds of Russians behind it, creating memes and shitposting on a payroll. And it obviously was 100% inorganic.
You're making the mistake of conflating AI with LLMs.
I don't think LLMs will reliably be better than a board of doctors. But an Expert System probably will (if it isn't already). That's literally what they were created for.
The biggest downside of LLMs IMO isn't the millions of Jules wasted on training models that are ultimately used to create funny images of cats with lasers. It's that all that money isn't being invested into truly helpful AI systems that will actually improve and save our lives, such as medical expert systems.