They've come a long way compared to other countries to be fair. But literaly just google women's rights in Saudi Arabia if you have a burning desire to know more.

No, it's not at all designed to be logically correct, it's designed to appear correct based on replications of the training dataset.

One the one hand, it's pretty impressive that it can do what it does using nothing but a statistical model of language. On the other hand, it's a quite unimpressive example of artificial intelligence because it is just a statistical language model. That's why it's abysmal at even simple math and logic questions, things that computers have historically been quite good at.

Human intelligence is nothing like a statistical language model. THAT is the real point, the one that both you and the OC, and frankly much of this sub at large, aren't getting.

Part of model building is that it compresses well and doesn't need to store the original data. It consumed 45TB of internet, and stores it in its 700GB working memory (the inference engine can be stored in less space, but I cant pin down a specific minimal number).

It has to figure out what's worth remembering (and how to remember it) without access to the test. It studied the general knowledge, but it didn't study for this particular exam.

26% of the people in the United States can't go to the grocery store because of their disability? Is that your assertion?

its alright at explaining math. I was asking it earlier to explain Riemann and Hilbert Space as well as relationships between Eigenvalues and Eigenvectors and it was spot on at making the explanation simple.

Truth.

ChatGPT cannot write an application. But it CAN write blocks of code that I, with my knowledge, can assemble into an application, and it can do that much faster than I can. And those code blocks are often better thought out than what I would have written.

Working with it has made my coding speed go up by about 30% AND made my code cleaner. I still have to fact check and debug everything it does (it gets things hilariously wrong sometimes). As I get more used to using it, I imagine my output will go up even more.

This thing is very early. I could imagine a model that uses ChatGPT, in it's current state, as a sort of sub processor... Like a human being defines an application, the model (trained on a bunch of open source software) looks for applications similar to what was defined, then starts asking ChatGPT (as a separate layer) for blocks of code it can assemble into the final app. When it runs into emergent bugs when these blocks conflict, it asks ChatGPT to solve the underlaying problem. Then it runs the final output through a bunch of benchmarks and optimization layers. It could even ask something like Stable Diffusion for graphical components.

I actually don't think that kind of capability is that far off. I can imagine it and I think it could be assembled from parts we have right now, given time and effort. And yeah, the final result might need some human input to clean it up (and pentest it!), but the effort saved would be phenomenal.

The long term effects of this tech on the economy are going to be... Weird. Probably painful at first. The capitalist mindset is not well equipped to deal with the disruption these kinds of tools can cause. But it's also going to cause an explosion of human expression and creativity, and give people the ability to do things they couldn't before (thanks to Stable Diffusion, I can make art in a way I never could before, I haven't even begun to scratch the surface of what I might want to do with that). What an exciting, fun and scary time to be alive.

humans aside, saying it doesn't need to acquire additional information from the internet or elsewhere isn't saying much if it already acquired the information from the internet and elsewhere. It already studied for the exam

Available for everyone any time? Fat chance. Computation time on a super computer isn’t free. The dataset isn’t free. Liability isn’t resolved. The team of phds who built it didn’t work for free. And only the whole of human knowledge that it has license to access or it’s dataset was trained on. Most of the data it would need is not public domain and would likely be heavily guarded and monetized.

That’s just the dataset The ai doctor still needs data about you to make conclusions. That means lab tests, scheduling, cost considerations, etc.

No, I have seen and driven the first gen Leaf-s with 300k+ on the odometer and 70% SOH, this is real life. With the original battery.

For clarification, there is a taxi company here that exclusively uses electric cars. They managed to rack up those 300k km quite quickly, using rapid charging as well. Really brutal usage pattern. And still the batteries had ~70% SOH at 250k - 350k km, there was quite a bit of variance which may be due to driver usage patterns or the chemistry change in 2013/2014.

Ya, that's magical lab only numbers and you know it. Find me a single company boasting those numbers right now, not in the future and I'll ceed the point.

No, you are missing the understanding of how language models work. They are designed to guess the next word, and they can’t do any more than that. This works because language is a subjective interface - far from logical correctness

I wrote a long response but reddit made it disappear. Things of note were only 1.3 mil were EV, the rest were hybrid. The last three ish years are the results of a long leadup in production capacity with insane production numbers 50%+ higher every year. And a few other things. It was mostly saying that I went too high but your is too low. I did screw up using total EV's and not looking at the last few years production.

We were discussing at work today how something like ChatGPT would be great to look through software documentation and give us an easy to follow instructions to how to access a feature.

It’s literally designed to get the answer right. How is that ever “by accident”?

I mean, humans can't either give you information that they don't have exposure to. We just acquire more data during our normal day to day lives. People also do their best to infer from what they know. They are more willing to code their certainty in their language, sure, but humans also can only work off of the knowledge they have and the connections they can find within.

Do some maths. 1kWh of battery capacity lasts for about 10k km before falling below the "magical" 70% SOH level. That means that an average EV like the Model 3 which has a 60kWh battery, will last for about 600k km. The average European drives around 15k km a year. It would take 40 years for them to drive the battery to that level. Other chemical degradation issues will probably apply before the 40 year mark which is why I brought out 20-30 years.

Oh, and the 1kWh per 10k km is based on first gen Leaf without battery thermal management. Newer chemistries and better cooling/warming solutions might have already pushed that number up so I would not be too surprised when Model 3-s end up lasting a million kilometers.

same difference.

sounds about the same thing. given the data before vs looking for it now. Fact is it cannot produce useful responses when it comes to facts without exposure to the data. Would be like someone talking about something they know absolutely nothing about. Which might be why sometimes it's accused of making things up confidently.

Look at the trends, in EU already ~10% of new cars are electric. Even without the ban over 90% would be EV-s by 2035. This ban only makes things more predictable for larger players, allowing them to have some certainty as to where to direct investments.

Your missing a key point here, when you say mining your talking about active mines. There aren’t enough active mines to begin with. Do you know how long it takes to get a new mine approved, get the exploration done to see if it’s even a feasible site, and then begin the actual mining? 15 years.

No one is saying 30 years. Most are talking from 8 to 20 at the high end.

Think back to the source of what’s required, active and producing mines. There literally aren’t enough mines in the world to handle the output needed to see this kind of growth.

New mines from exploration to resource extraction takes 15 years. This is just delusional and if you think inflation is bad now, boy oh boy just wait until we’re heavily reliant on minerals that will be immensely scarce because of the demand this is going to create. I’m not saying there’s a scarcity of minerals, but a scarcity of actual mines.

Copper is a huge input into EVs, guess what else relies on copper? Almost every other industry in existence related to technology, industrial processes, and construction.

because its basic functionality for computers. And it's the easiest thing because the solution is not ambiguous. But sounds like it just isn't able to put it in a math form as given.

>That's also about how long between battery pack changes on EV's.

That is way off. I agree that first gen Leaf and maybe first gen Teslas had batteries that might require replacement after 10 years, more likely a batterypack lasts 20-30 years in an EV.

Also, many EV-s are already migrating away from cobalt based chemistries and some are already looking towards lithium free chemistries. There lies the "solution": there are many options of battery chemistries that are viable for EV-s and there is no requirement to only use one. The ones that have more supply will be used at the time and in the end they will stabilize.

Ok. And the people who live in the country, you know those rural areas where we grow the food. How do they travel and bring the food to market? How do they plant and harvest? The ships that transport the food to places that can't grow it. The fishing boats that provide fish. The trucks that move the food from the port to the train or market. The mining equipment used to mine resources that we use to make things.