You're actually right. I'm a software engineer but taught myself electrics, plumbing and carpentry over the years to carry out repairs to my home. I've fitted a whole bathroom on my own and did all the wiring on an extension I had built in my house. I'm sure I'm capable of getting work as a plumber or electrician if things go to pot (carpentry is probably a bit too dangerous as you're breathing in dust all day) but I really don't relish the idea of that. It's hard physical labor, I like getting paid to sit in my nice warm house to mess around with computers.

No, in an ideal world this is sensible. things are probably moving a bit too quickly at the moment. We've waited decades for this so pausing for 6 months to ensure were moving forward safely is sensible.

But it's not an ideal world, not everyone will agree to this so it's pointless.

It's too slow at inference for something like that. It's probably far easier to do it the other way around. If you want your software to interface with GPT 4 build in some sort of scripting interface to your app

With enough investment it wouldn't take long to catch up with OpenAI. I think by this time next year there will be multiple models better than GPT-4, maybe even hundreds. Almost anyone can do it. It's possibly the case that GPT 4 isn't even trained optimally. Its very slow so presumably didn't build on the optimal data/parameters balance shown in the chinchilla paper.

I think it can work, I'm trying to get it working in a game I'm developing at the moment. You have to have a mix of randomness and structured story telling. I literally have to say to ChatGPT, the user is saying xyz, reply to the user but try to work this plot point into your reply.

I'm actually adding ChatGPT NPCs to the Unreal Engine 5 game I'm developing at the moment, it's a rogue like set in a post singularity world, gameplay is similar to Hades so there's plenty of dialogue in the game. at the minute it's difficult to get a model to run on the local PC so I'm using OpenAI's API. There are challenges like latency while you're waiting for the API to return, it's also quite expensive so releasing a free demo of the game is out of the question. It could potentially cost several dollars per user in API fees over the life of the game so that will of course limit your pricing flexibility, you can only reduce the price so much in steam sales etc. I'm hoping though that inference costs will come down by the time the game is finished.

I haven't posted any footage with the GPT dialogue added to the game but I might post it here in a couple of weeks.

Paradoxically technology will become easier to navigate not harder thanks to LLMs. You can now just tell Excel what you want from your spreadsheet rather than having to learn complicated formulas and pivot tables etc

We actually don't need AI to develop much beyond where it is at the moment for crazy advances in medicine and technology over the next decade. Just applying ML where it is now to thousands of different applications will lead to crazy breakthroughs. Imagine thousands and thousands of Models like Alpha Fold and what they will bring to scientific advancement. There was a defusion model that can literally read people's minds using brain MRIs posted here yesterday. That's crazy sci-fi stuff already happening. Things are already happening that a year ago I wouldn't have thought would be possible in my lifetime.

Just hit the stop loading page button in Your browser after you click on the link and it works fine. Most paywalls can be defeated like that, they wait for the page to finish loading to blur everything

This is a good point. It's pointless arguing that the AI that completely replaced you at work despite you having a masters degree isn't actually an AGI because it can't make a cup of coffee.

How long though before LLMs perform at the same level as experts in a most fields? A year, two, three? When you get to that point you can generate synthetic data that's the same quality as human produced data. The Reflexion paper mentioned in another thread claims that giving GPT 4 the ability to test the output of its code produces expert level coding performance. This output could be used to train an open source model.

We don't understand how it works. We understand how it's trained but we don't really understand the result of the training and exactly how it arrives at a particular output. The trained model is an incredibly complex system.

I've been testing this approach today and it works well. My aim is to try and reduce the numbers of tokens used and therefore the cost when calling the API. Punctuation counts as a token which is annoying so all the : and , characters cost

This is definitely within that capacity of humans and could happen. Imagine if Robot armies existed in the 1930s. The Nazis literally set about killing millions of people who they thought weren't beneficial to society. They killed gypsies, Jews, gays, the disabled etc.

Jews were biologically the same as Nazi Germans but it didn't stop them killing them. Poor people become a problem if they're consuming too many resources. The wealth of the rich has to feed and clothe the poor if the poor aren't able to work.

This happened less than a hundred years ago, we haven't evolved since then and as a species are more than capable of doing the same again. Also what happened in the 30's and 40's isn't an anomaly in human history, humans have continually treated one another like this. Look at slavery in the US, apartheid in South Africa, the British empire ruling one 1/5 of the globe. The fact that we have a special word for genocide give a clue about how ubiquitous it's been in our history

You don't have to develop quantum computers to crack encryption. You need quantum computers to brute force it but it's entirely possible that an algorithm could be developed that runs on regular computers that's able to solve encryption.