The LLM boom of the last year (Open AI, llama, et al) has me giddy as a software person. It's a reach, but I truly feel like I'm watching the pyramids of our time get made.
Just as the GUI made computer software available to billions LLMs will be the next revolution.
I'm just as excited as you! The only downside is that it now make me feel bad that I'm not doing anything with it yet.
If that's the only downside that you see... I guess enhanced phishing/impersonation and all the blackhat stuff that come with it don't count.
I for one already miss the time where companies had support teams made of actual people.
And yes, in 20 years you can tell your kids that 'back in my day' support consisted of real people. But truthfully, as someone who worked on a ISP helpdesk it's much better for society if these people move on to more productive areas.
People like to just suppose that these will help discover drugs and design buildings and what not, but what we actually know they’re capable of doing is littering our information environment at massive scale.
But is it, though? I started my career in customer support for a server hosting company, and eventually worked my way up to sysadmin-type work. I would not have been qualified for the position I eventually moved to at the start, I learned on the job. Is it really better for society if all these entry level jobs get automated, leaving only those with higher barriers to entry?
The answer then was extending schooling, so that people (children at the time) could learn those skills without having their labour exploited. I would argue we should consider that today, extend mandatory free schooling. The economic purpose of education is that at the end of it the person should be able to have a job, removing entry level jobs doesn't change the economic purpose of education, so extend education until the person is able to have a job at the end of it again.
The social purpose of schooling is to make good members of society, and I don't think that cause would be significantly harmed by extending schooling in order for students to have learned enough to be more capable than an LLM in the job market.
Considering that the democratic backsliding across the globe is coincidentally happening at the same time as the rise of social media and echo chambers, are we sure about that? LLM have the opportunity to create a handcrafted echo chamber for every person on this planet, which is quite risky in an environment where almost every democracy of the planet is fighting against radical forces trying to abolish it.
But you don't see the positive, you just have faith. That's beautiful in a way, but dangerous too. Just like the common idea that "I have faith that somebody will find a technological solution to climate change". When the risk is that high, I think we should take a step back and don't bet our survival on faith.
The last four chats with ChatGPT (not GPT4) where a constant flow of non existent API functions with new hallucinations after each correction until we reached full circle.
Years ago I had a business DSL customer with a router and static IP. From everything in my testing it appeared that traffic broke somewhere at the local telco, not with my modem. It took 8 straight hours of arguing with L1 that no, it is not my windows. No, we have a router and it's not a computer issue. No, it's not the router (we could put the router in DHCP mode and it would work), it was an issue with static IP.
The next day we finally broke out of the stupid loop and got to IP services, who where just as confused. Eventually they were on the phone with people on the floor of the local office. A card of some type had been pulled and put in the wrong slot. Ooof.
I can read the website, I don't need a fake person to give me the information available on the website. When I contact support, it's because I need to talk to a human.
However, medical secrecy, processes and laws prevent such things, even if they would save lives.
I don't see ChatGPT being any different.
Medical secrecy, processes and laws have indeed prevented SOME things, but a lot of things have gotten significantly better due to enhanced statistical models that have been implemented and widely used in real life scenarios.
Example: my favourite team is X. So if I want to keep it a secret, when I ask for the history of championships of X, I will ask for X. My local agent should ask for 100 teams, get all the data, and then report back for only X. Eventually the mothership will figure out what we like (a large wenn diagram). But this is not in anyone's interest, and thus will not happen.
Also, like this the local agent will be able to learn and remember us, at a cost.
In my view, while statistical models would probably be an improvement ( assuming all confounding factors are measured ), the ultimate solution is not to get better at educated guessing, but to remove the guessing completely, with diagnostic tests that measure the relevant bio-medical markers.
This becomes even more true when you consider there is risk to every test. Some tests have obvious risks (radiation risk from CT scans, chance of damage from spinal fluid tap). Other tests the risk is less obvious (sending you for a blood test and awaiting the results might not be a good idea if that delays treatment for some ailment already pretty certain). In the bigger picture, any test that costs money harms the patient slightly, since someone must pay for the test, and for many the money they spend on extra tests comes out of money they might otherwise spend on gym memberships, better food, or working fewer hours - it is well known that the poor have worse health than the rich.
But if we are talking about being truly transformative - then a Star-trek tricorder is the ultimate goal, rather than a better version of twenty questions in my view.
So I'm not saying it's not useful, just that it's not the ultimate solution.
> Similar possibilities existed in medicine for 50 years
It would've been like building the tower of babel with a bunch of raspbery pi zeros. While theoretically possible, practically impossible and not (just) because of laws, but rather because of structural limitations (vector dbs of the internet solves that)
> Patents and byzantine regulations will stunt its potential
Thats the magic of this technology, its like AWS for highly levered niche intelligence. This arms an entire generation of rebels (entrepreneurs & scientists) to wage a war against big pharma and the FDA.
As an aside, this is why I'm convinced AI & automation will unleash more jobs and productivity like nothing we've seen before. We are at the precipice of a Cambrian explosion! Also why the luddites needs to be shunned.
can you, though? it's not scalably confirmable. what you can say in a British accent to another human person in the physical world is not necessarily what you can say in unaccented text on the internet.
Funnily enough, it is scalably confirmable. You can feed all my HN comments before chatGPT into well.. chatGPT and ask it whether I'm british based on the writing.
I bet we are just a version or two away from being able fine tune it down to region based on writing. There are so many little things based on whether your from Scotland, Wales or London. Especially London!
Imagine for example that 'disease books' are published each month with tables of disease probabilities per city, per industry, per workplace, etc. It would also have aggregated stats grouped by by age, gender, religion, wealth, etc.
Your GP would grab the page for the right city, industry, workplace, age, gender etc. That would then be combined with the pages for each of the symptoms you have presented with, and maybe further pages for things from your medical history, and test results.
All the pages would then be added up (perhaps with the use of overlayed cellophane sheets with transparency), and the most likely diseases and treatments read off.
When any disease is then diagnosed and treatment commenced (and found effective or ineffective), your GP would fill in a form to send to a central book-printer to allow next months book edition to be updated with what has just been learned from your case.
The medical possibilities that will be unlocked by large generative deep multimodal models are on an entirely different scale from "statistical diagnoses." Imagine feeding in an MRI image, asking if this person has cancer, and then asking the model to point out why it thinks the person has cancer. That will be possible within a few years at most. The regulatory challenges will be surmounted eventually once it becomes exceedingly obvious in other countries how impactful this technology is.
Your deep multimodal models or the MRI imaging?
What you are essentially saying is the signal is so subtle that only a large NN can reliably extract it.
While that may well be the case, it would be better to have a scan/diagnostic that doesn't need that level of signal processing to interpret.
For example - you don't need a large generative deep multimodal model to read a Covid antigen or PCR test.
We've picked a lot of the low-hanging simple to extract signals, we need large models to go to the next phase for things like parkinsons, etc.
From convenience perspective, it saves me LOADS of time texting myself on Signal on my specs/design-rabbit-hole, then copying & pasting to Firefox, and getting into the discussion. So yeah, happy for this.
I think this could bring back Google Glass, actually. Imagine wearing them while cooking, and having ChatGPT give you active recipe instructions as well as real-time feedback. I could see that within the next 1-3 years.
I think they're using Siri for dictation, though. Using Whisper, especially if they use speaker identification, is going to be great. But, a shortcut will still be required to get it going.