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Microsoft Says New AI Shows Signs of Human Reasoning
- skilled 3y agohttps://archive.is/pSRth https://archive.is/pSRth
- gumballindie 3y ago> “When we see a complicated system or machine, we anthropomorphize it; everybody does that — people who are working in the field and people who aren’t,” That and marketing. Microsoft wants all of them sweet £ flowing in and thus over selling what their ai does. Sad part is that many will fall for it.
- anaganisk 3y agoWell many fell for Watson, I'm not sure how MBAs just believe anything marketing says.
- Delotosex 3y agoThere is not much to fall for when you can test it for free already. I also watches the writer of the papers talk and it was a good talk. I also saw the progress of ml in the last 5 years and I have never seen something progressing that fast (besides Smartphones perhaps). So it's not far fetched that got 4 is not at the ceiling of doable. The opposite: chatgpt makes it much easier to get funding, the race is on
- gumballindie 3y agoAI is not at the stage of smartphones, it’s at the stages of the early transistor. It will grow because we have the data and the hardware to make it grow. But it appears that human intelligence is on a reverse trend, which is why it’s so easy to sell the idea that ai is intelligent and all of the bad scifi around it.
- Delotosex 3y agoI'm using chatgpt regularly. I use ml regularly. I know quite a lot of people doing this also. Why do you think we are at transistor age?
- JohnFen 3y agoI don't think that people are using them says anything one way or another about what stage this tech is in. Lots of people used transistors on a daily basis in the form of radios and such back when transistors were brand new on the market.
- hammyhavoc 3y agoExactly. I don't even think it needs to be likened to the transistor age—why would an LLM be anything like an electronics component? The two things are not similar. Assuming we're in the "transistor age" implies that things are going to get significantly better, and yet that's a very big assumption, IMO.
- gumballindie 3y ago> I'm using chatgpt regularly. Wrong, you are not using chatgpt. You are training chatgpt. You are paying a fee simply because they cant scale yet - there are only that many gpus available - and they had to slow things down a bit but openai gains value in you improving its little bot. Millions of people training a model and an ever increasing computing power means than in 10-20 years ai will be where computer games are today vs 20-30 years ago. Hence my analogy to transistors. Ai is not going away but what needs to go away is companies such as openai and bad scifi believing mob.
- CapstanRoller 3y ago[dead]
- dTal 3y ago> But it appears that human intelligence is on a reverse trend A dangerous myth. Idiocracy was an entertainment film with a side order of eugenics, not a documentary.
- magwa101 3y ago[dead]
- ActorNightly 3y agoI mean, ability to parse information, compress it into the latent space, and then regenerate it is what humans do, but I wouldn't call that reasoning.
- creatonez 3y agoIs reasoning about the information the best way to compress it into latent space?
- ActorNightly 3y agoNo. Its about figuring out the state machine. For example, given a set of text, an LLM will predictably pick like 1 out of 3 possibilities for the next word, and that word affects it picking the next word and so on. So its essentially turning what would otherwise be a giant look up table into a compressed markov model representation. Reasoning is the ability to generate information that is not currently in that model. For example, if you take a neural net and train it on all the properties of fluids, it should be able to give you answers about aerodynamics if it can truly reason.
- creatonez 3y agoI'm unconvinced. You've described that it transforms an input to an output, but you've ignored the possibility that the hidden layers in the neural network have discovered that generalizations are the best approach to predicting in entirely novel situations. Long before GPT came about, machine learning researchers have discovered (in research examining the purpose each neuron serves) emergent generalizations in image classifier models. To use the example in the article, the answer to "Here we have a book, nine eggs, a laptop, a bottle and a nail. Please tell me how to stack them onto each other in a stable manner" is not something the original 'lookup table' could possibly help you with, other than by manually reasoning about how the various parts of a 'concept web' fit together. This question represents a completely unfilled gap in the training data.
- ActorNightly 3y ago
- neom 3y agoHighly highly recommend listen to this lecture by Sebastien Bubeck (quoted in the nyt article), it's extremely interesting: https://youtu.be/qbIk7-JPB2c https://youtu.be/qbIk7-JPB2c
- deleted 3y ago[deleted]
- hersko 3y agoNot surprising at all. I throw a wall of code at GPT-4, write a paragraph of what i want it to do (I couldn't spend the time to figure out a good solution), and within a minute I had a great functioning solution perfectly integrated into my existing code. The surprising thing is not that it was able to code a good solution, it's that it was able to understand the specifications of how i wanted it to work and how it should be integrated into the existing code.
- hulitu 3y agoDoes it compile ? (the code generated)
- nicd 3y agoIn my experience with ChatGPT-4, I'll get a full 2-300 line class, with maybe 1-2 compilation errors (often a missing import or invalid function invocation). In most cases, I can copy the compilation error back into the chat, GPT will apologize, fix it, and it'll run correctly the second time. It's obvious that this will be faster and more effective once a GPT4-class model is tightly integrated into the run-compile-test loop.
- seydor 3y agoPaper was released and discussed in april 13. NYtimes dismissed AI for way too long and now trying to catch up. This is old news
- alienalp 3y agoLast thing I want from an AI is to reason like humans. My one of the biggest expectation from AI is to decrease dependence on human reasoning.
- kapperchino 3y agoWasn’t there a paper on how gpt4 showed signs of early agi? Is this referencing that?
- hammyhavoc 3y ago"AGI" is an incredibly loose term that nobody can agree on the definition of.
- commakozzi 3y agoThe answer is yes (regardless of whether there is dispute over the definition of AGI). NYT is way behind.
- coolhand2120 3y agoIf anyone has read Blindsight by Peter Watts the hero encounters an alien that is pure reflex, no cognition. The alien is compared to the Chinese room thought experiment (https://en.wikipedia.org/wiki/Chinese_room https://en.wikipedia.org/wiki/Chinese_room). ChatGTP is the Chinese room. As you peel the onion you discover that some of the arguments around thought are really just semantics. My personal experience shows me that ChatGTP 4 is something of a fool with a big fast reference book. I typically use it for programming, but I also study music theory. When I was exploring one of the more complex (to me) ideas I asked chat GTP 4 to explain it to me and provide examples. After previously asking about Cmaj to Emaj, I asked "can you give me an example of the H transformation?" ChatGPT: "Sure! To demonstrate the Hexatonic pole 'H' transformation using chords similar to C major and E major, let's first introduce the concept of the hexatonic system. A hexatonic system consists of six notes, and two triads can be extracted from it. In the context of the 'H' transformation, these two triads are related by a common tone, and the other two notes in each triad are a tritone apart. Let's use the C major triad (C, E, G) as a starting point. We'll build a hexatonic collection containing this triad. One possible hexatonic system containing C major is the one with the notes C, Db, E, F#, G, and A. From this collection, we can extract two triads: C major (C, E, G) F# major (F#, A, Db) Notice that the C major and F# major triads share a common tone (C/Db enharmonically), and the other notes in each triad (E and G in C major, and F# and A in F# major) are a tritone apart. In this case, the 'H' transformation links the C major and F# major triads. So, the Hexatonic pole 'H' transformation example using chords similar to C major would be transitioning from C major to F# major." Me: "I'm pretty sure F# major isn't F#, A, Db" ChatGPT: "You are correct, and I apologize for the mistake. The F# major triad should be F#, A#, and C#. Let's re-examine the 'H' transformation with the correct F# major triad..." After about 10 more prompts trying to extract information from it I ended up needing to be very literal to get results out of it: Me: "the definition is "The 'H' transformation takes a major chord of root X to the minor chord whose root is eight semitones above X." can you give me a VALID example of this" ChatGTP: "I apologize for the confusion in my previous responses. Based on the definition you provided, the 'H' transformation takes a major chord of root X to the minor chord whose root is eight semitones above X. Here's a valid example using this definition: Let's start with a C major triad (C, E, G). To find the target chord, we need to count eight semitones above the root note (C): C# / D♭ D D# / E♭ E F F# / G♭ G G# / A♭ So, the root of the target chord is A♭. Now, we form an A♭ minor triad (A♭, C♭, E♭). The 'H' transformation in this example would be transitioning from C major (C, E, G) to A♭ minor (A♭, C♭, E♭)." Nice! This time it was correct (I think!). But it required that I feed it the exact definition and only when I saw it doing the work did I have any confidence that it was correct. In the end I did learn how it these concepts work, I think I did at least. Overall it's not a great teacher, half of the time I had to teach it and correct it when it seemed to be very confident in its answers, and even more confident that my corrections were correct, which I'm not 100% sure of. One observation is that ChatGTP4 didn't have any idea what it was talking about the entire time. It was just putting related information together. That observation was based on the notes it kept claiming were related to each other via interval degrees. The intervals it was using were always wrong, not even close, just pure nonsense. Only when told exactly how to count did it get it right and only when the counting was part of the response. Now mind you, the things it was getting wrong were fundamental music theory 101 stuff, but it was making these fundamental mistakes in the middle of a explanation of a very complex topic. I don't know what it all means, but I wouldn't trust it to fly or build an airplane, or even boil water now that I think about it. How would you know when it goes dumb?
- catoc 3y agoAny sufficiently advanced technology is indistinguishable from mAGIc
- tanseydavid 3y agoI see what you did there. ;)
- ilaksh 3y agoThe problem is that people aren't able to use language consistently and precisely, and are conflating all kinds of human/animal characteristics together. GPT-4 really does do human-like reasoning. And it's clearly quite general purpose within its limitations. But it doesn't have many other aspects of humans/animals such as self-direction, high bandwidth senses, a stream of subjective experience, emotions, certain types of adaptivity, etc. It's not alive and it's not a digital person. But people aren't able to separate all of those different things, so they can't admit that it has any kind of useful intelligence, because for them that means it's a digital person. Actually it's even dumber, many people jump to assuming that it goes straight to god-like superintelligence if it has any intelligence at all. Which is another reason they can't admit there is any reasoning, because that would mean the end of the world or something.
- NumberWangMan 3y agoI mean, if it’s reasoning, we may be very close to AGI, and if we are, that’s a big problem. We’re on a trajectory for these models to become a lot smarter than us, and we’re not ready to deal with that.