My small, no name company has lost its mind with AI

I've settled on using a plain and simple and unadorned UI as possible, regardless of what the product is, as long as it is easy to use.

My reasoning is that if people need it to be pretty before they'll pay for it then it's not really a pain-point that the product is solving.

OTOH, if people are willing to hand out cash for the functionality then I'm onto something.

[1]Want to do B2B, but will depend on what I can come up with.

LLMs are absolutely worthless for medical information.

Please, please tell me you at least read these academic papers to make sure they claim what ChatGPT said they're claiming?

But it does know a lot of things and can be super useful. Personally i think search engine is a terrible use case, unless you use the Bing enabled version, or bing chat.

I've used it to write pretty complicated scripts where I had no idea what I was doing, rebuild crusty httpd configs from first principles, explain disassembled code, explain regular code, explain configs, read dmidecode and lspci for me and make a pcie slot report... It's bloody brilliant.

Other: read and translated my blood tests. Accurately!

It both picked out the interesting places of note, and then I asked it to plan them in such a way that made sense walking-wise (so I wasn't backtracking) and it did so without a hiccup.

What Bing does is to use your query to search the web and use the top N search results in the context window for the chat.

However I’ll push back on your pushback. ChatGPT doesn’t need to be perfect to be a killer app. It is highly flawed. Maybe it was a bit to strident to say ChatGPT will kill Google search, but it’s strictly better for a lot of squishy queries that don’t have a factual basis.

How can I convince my boss to give me a raise? gets you a listicle on Google and a highly specific response on ChatGPT. And if some of the advice doesn’t apply, you can continue directing the conversation. It’s an idea generator, even if some of them are bad or don’t make sense.

For Google, they’re at the mercy of whatever the internet has.

The only "if" to all this is if we will destroy the LLMs by feeding them their own diarrhea. I expect a sort of natural selection here to play out, especially in the open source space. Ones that are trained on LLM generated blogspam will probably, I expect, get outperformed by ones that are trained on genuine information, or at the very least ones made using new techniques that adequately filter noise.

If you are looking for a location on the internet, use a search engine. LLMs do not memorise the data sources verbatim.

If you want to know how to do something, it will normally give you a better answer than you would find by googling around multiple blogs. No location on the internet needed.

> There’s no way this is remotely legal, right? Unless it’s some sort of on-prem product?

It's definitely legal, not sure why one would think it wouldn't be. There are dedicated, HIPAA-compliant medical transcription services that use voice-to-text tech that have been around for decades. I would say in the past 10 years or so the tech has gotten to the point where it's very good, and I know companies that have laid off transcriptionists because the tech is considerably cheaper.

You can read some of the history of buggy whip makers. They were specialized manufacturers with established brands built around quality, special materials and style. Some were able to convert to new products but not all. They did survive a couple decades past the invention of the car, to your point, but once cars proliferated their sales cratered.

Whip manufacturers shouldn’t be shamed for hubris (what happened did not seem as guaranteed then as it now seems with hindsight) but they all would’ve done well to have converted into automobile manufacturing supply by the teens and many did not.

A link to get you started: https://civilwartalk.com/threads/what-company-made-the-last-...

To understand why that is, you need to understand why they are doing all this generating random numbers nonsense in the first place. They are doing this to establish distributed consensus. You have some chain of blocks b_1... b_2 ... b_3. To make the next block you want to put a bunch of transactions together, calculate their hash and mint it, but there's a problem: In a distributed system, who gets to decide what goes into the block? We all need to agree what b_4 is otherwise the system loses consensus. We can't have me publishing something and calling it b_4 and you publishing something and calling it b_4. The way the "proof of work" mechanism does this is by everyone guessing random numbers until someone chooses the right number at which point that person has the right to mint b_4.[1]. If you wanted that computation (instead of being just choosing random numbers) to do something useful, you'd have to figure out a way to decide what the correct number is without knowing it beforehand. Otherwise you might train your ML model just fine but your computation couldn't be used to establish who gets to mint the next block so wouldn't work in a proof of work consensus algorithm.

People have done this with distributed computations where doing the computation is hard but checking the computation is easy. For example finding large Mersenne primes, is extremely expensive but once you have a big number, checking whether or not it is a Mersenne prime is very cheap. But training an ML model isn't that kind of computation.

[1] Proof of stake just picks who gets to do it randomly from a pool of people who have staked, which is why it is so much more efficient.