Submitted by lughnasadh t3_yytfpr in Futurology
The following submission statement was provided by /u/lughnasadh:
Submission Statement
OpenAI has been hinting at a big leap forward for LLMs with its upcoming release of its GPT-4. We'll see. In the meantime, it's extraordinary watching some people defend Galactica. They are convinced it's the beginning of an emergent form of reasoning intelligence. Its severe limitation, as with all LLMs, is that they frequently produce utter nonsense, and have no way of telling the difference between nonsense and reality.
I'll be curious to see if GPT-4 has acquired even the rudiments of reasoning ability. I'm sure AI will acquire this ability at some point. But it seems strange to blindly believe one particular approach will make it happen, when there is no evidence of it at present.
Please reply to OP's comment here: https://old.reddit.com/r/Futurology/comments/yytfpr/meta_has_withdrawn_its_galactica_ai_only_3_days/iww4fip/
All AI plateaus.
No AI actually shows intelligence.
They are sophisticated statistical machines, but there's no proof that that correlates with being intelligent (which is an unfixable definition in itself) in any way.
As soon as the AI gets out of its comfort zone (i.e. doesn't have training data), it will make up nonsense because it's just acting statistically, even when the statistics are in the margins of error rather than any kind of statistical significance.
Intelligence does not do that. Intelligence knows enough to not give any answer, that it doesn't know the answer, or is able to reason the answer in the absence of all training data. In fact, "innovation", a major part of intelligence, is entirely outside the bounds of all such "training data" (i.e acquired experience).
"AI" necessarily ends precisely where intelligence starts. Pretending that AI is intelligence is just nonsense. It's just heuristics, statistics, and hysterics.
This is an interesting take. My intuition agrees with you, but what about halicin? It's innovative in that it uses a unique mechanism to kill bacteria and was discovered by ai.
> Intelligence knows enough to not give any answer, that it doesn't know the answer
> able to reason the answer in the absence of all training data
Human intelligence is not able to do this either
I can't help but feel like we're exceptionally close to a model that can emulate intelligence, but that last piece is impossible to create due to the boundaries imposed on computer programming.
Part of what drives human intelligence is survival (which includes procreation), and to that end computers are still living off human intervention. AI isn't going to be born from a random bit flip or self-code that leads to self awareness, it's simply not possible considering the time needed for that level of "luck" and the limitations of computer processing that cannot grow and/improve its own hardware.
Yes we are, it's called intuition, or inherited memory. It's general and abstract, but real.
Yet often ignored
They'll keep killing AI until they get one that doesn't turn out like Tay.
Yeah, clearly displayed by this guys response
He's saying that humans do the same thing and give nonsense answers and can't just say they don't understand
intuition and inherited memory is training data, from all your ancestors that persisted to you through their DNA dictating the basic formation of your brain. just like some animals can walk or eat right after being born. it's not that they haven't had training data, it's just that this training data has been coded in their DNA
Why not create margins on the statistical data…..if it doesn’t know 100% with a error of +0 or -0. It with doesn’t respond or asks a pointed question.
People make up nonsense too, it’s just coherent
We are just complex statistical machines.
Everything we think of do is based on our past experiences (inputs) and our genetics(coding)
Or you can prove that humans have access to some force outside of physics that gives us “intelligence”
Behavioral studies of monkeys show that they perfect calculate the Nash equilibrium probabilities when put in game theory situations. Are they not intelligent then?
If you can get an AI to ask a relevant question at a relevant point that's not just a programmed threshold or response (a heuristic, in effect), then you'll have made proper, true AI.
An AI identifying molecules with features similar to other known antibiotics is exactly what statistical models are good for. But it's a first pass before actually testing whether those molecules actually work. There are a lot of false positives, but that's OK, because they still greatly narrow the field to be tested.
An AI language model is also going to generate a lot of false positives - gibberish - that you can only tell by testing it. i.e.: by having someone knowledgeable in the field read it and possibly fact check it. That kind of defeats the point of a lot of AI writing applications.
There is absolutely no evidence that animals or humans function as just statistical machines of any complexity.
It's a fallacy to think that way. You can find statistics and probabilities in human actions, yes, but that doesn't mean that's how they are formed. Ask enough people to guess the number of beans in a jar, take the average and you'll be pretty close to the actual number of beans in a jar.
But that doesn't mean that any one human, or humans in general, are intelligent or not intelligent. The intelligent animal would open the jar and count them. Even the humans that are guessing are not basing their guesses on statistics or their experiences or their genetics. They are formulating a reasonable method to calculate the necessary number to solve a very, very, very narrowly-specified problem.
That's not where intelligence is visible or thrives.
Anything sufficiently complex system, even physical, mechanical, unintelligent, rule-based, etc. will confirm to similar probabilistic properties. That doesn't prove the creature isn't intelligent, nor that the intelligent creatures are based on those statistics.
In fact, it also falls somewhat into the gambler's fallacy - overall enough data points will conform to average out the reds and the blacks almost perfectly. But you can't rely on that average, or your knowledge of statistics, to predict the next colour the ball will land on. That's not how it works.
People make up answers for things they don't fully understand all the time, and certainly aren't able to admit they're wrong when they do it. See the world's various religions for hundreds of examples.
To paraphrase Arthur C. Clarke:
Any sufficiently advanced <statistics> is indistinguishable from <intelligence>.
Right until you begin to understand and analyse it. And that's the same with <technology> and <magic> in that sentence instead.
I'm not entirely certain that humans and even most animals are limited to what's possible to express in a Turing-complete machine. However I am sure that all computers are limited to Turing-complete actions. There isn't a single exception in the latter that I'm aware of - even quantum computers are Turing-complete, as far as we can tell. They're just *very* fast to the point of being effectively instantaneous even on the largest problems (QC just replaces time as the limiting boundary with space - the size of the QC that you can build determines how "difficult" a problem it can solve, but if it can solve it, it can solve it almost instantly).
And if you look at AI since its inception, the progress is mostly tied to technological brute force. I'm not sure that you can ever just keep making things faster to emulate "the real thing". In the same way that we can simulate on a traditional computer what a quantum computer can do, but we can't make it work AS a quantum computer, because it is still bound by time unlike a real QC. In fact, I don't think we're any closer to that emulation than we ever have been... we're just able to perform sufficiently complex statistical calculations. I think we'll hit a limit on that, like most other limitations of Turing-complete languages and machines.
All AI plateaus - and that's a probabilistic feature where you can get something right 90% of the time but you can't predict the outliers and can't change the trend, and it takes millions of data points to identify the trend and billions more to account for and correct it. I don't believe that's how intelligence works at all. Intelligence doesn't appear to be a brute-force incredibly fast statistical machine at all, but such a system can - as you say - appear to emulate it to a degree.
I think we're missing something still, something that's inherent in even the physics of the world we inhabit, maybe. Something that's outside the bounds of Turing-complete machines.
Because a Turing-complete machine couldn't, for example, come up with the concept of a Turing-complete machine, or give counter-examples of problems that cannot ever be solved by a Turing-complete machine, for instance. But a human intelligence did. Many of them, in fact.
I really have no idea why anyone would think an AI language model trained on scientific papers would do anything other than make up fake scientific papers.
Eh, without first developing language and reason, there is no intuition. That comes with experience. Which is the human equivalent of training data. No human knowledge is a priori. People like to shit on philosophers, but they've been working on this one for centuries.
>Intelligence does not do that. Intelligence knows enough to not give any answer, that it doesn't know the answer, or is able to reason the answer in the absence of all training data. In fact, "innovation", a major part of intelligence, is entirely outside the bounds of all such "training data" (i.e acquired experience).
Don’t ask me why, but my mind went right to the Intelligence AI from Team America
Dude. I wish we could both get stoned and talk about this all night, and I haven't smoked in a decade.
Not just coded. Nucleic acid performs computation itself and does not merely contain instructions.
This is just Meta having no idea how their own software works. You don't need to be a machine learning developer to see how current text generators work, yet Meta developers were completly blind. This has absolutely nothing to do with the training data, you could give it every fact that exists and you can still easily get it to output things that are not true. It has everything to do with the way current text generators generate their output.
Current text generators estimate the next token based on it's training data and input tokens. The newest tokens take precedence over older tokens so input data is given a higher priority for estimating the next token. This means whatever a user inputs heavily influences the output. The AI does not output facts, it outputs text it thinks the user would type in next.
There is a work around. Hidden text can be added after user input giving the AI instructions to ignore certain user input. However, if the user knows what the hidden text says they can craft input that works around the work around. If the hidden text says "only use facts" the user could give the AI false facts, and because input has higher priority over training data then the false facts given by the user becomes facts to the AI. It's like the three laws where the stories find ways to get around them and nobody knows that because nobody has ever read any of the stories.
To output only facts would require a different type of text generator that outputs text in a different way that's not based on estimating the next token from user input. Current text generators are very good at generating creative output and can't be measured by their ability to produce facts no matter what anti-AI people demand. And I bet a fact producing generator would be terrible at being creative, which of course proves that it doesn't work according to anti-AI people.
Meta took a tractor to an F1 race and was flabbergasted that it couldn't keep up because it's so good at pulling heavy things. Then all the anti-tractor people declare tractors are a failure and can never work because they can't keep up. In reality the tractor was never designed to go fast, and no amount of tweaks will ever change that. Take an F1 car to a tractor pull and you'll get a very different outcome that the anti-tractor people will ignore, and Meta developers will say this means tractors can beat F1 cars in a race and they just need to tweak it to make it happen.
>in the absence of all training data
Absolutely no intelligence ever (human, animal, etc) has zero training data, exepct perhaps before their brains become conscious for the first time. Brains learn from all sources and apply their knowledge bit-by-bit to solve problems. Intelligence is not magic, and it can never ever make something from nothing.
That is part of our training set for decision making. It comes from instinct and influences our decisions based on the past development of our heredity.
Michael Levin on Lex Friedman’s podcast was incredible FWIW
I see what you mean. I really hope we're not inventing the next great filter.
Humans are complex input output machines. Our brains are electrical machines
Can you please tell me the mechanism humans have to escape cause and effect?
What can humans do that is not a result of learned behavior(both evolutionary and socially), unconscious statistical analysis, or perceptual bias.
There is nothing that a human can do that an AI can’t or won’t eventually be able to do.
The arguments you make about innovation and knowing when answers are bad answers are just other heuristically learned behaviors
Do you believe humans have a spiritual power given by God or something?
Human intelligence can do it. It is called science, democracy, entrepreneurship, which all are collective enterprises and trial-by-error processes.
whoever is responsible for taking this down they have a big FU from me. This tool was useful for summarizing scientific subdisciplines that are still unexplored. Even if it was not accurate, it was helpful as a companion tool to sketch out the structure of review articles. I was actually planning to use it when writing my next review.
But yeah, idiots like this guy is why we cant have nice things. There s nothing dangerous about a toy, it's instead dangerous to infantilize people and submit to the whims of some extremely entitled people
> Intelligence does not do that. Intelligence knows enough to not give any answer, that it doesn't know the answer, or is able to reason the answer in the absence of all training data.
The human brain confabulates. It will make up a story to explain what's happening and then think that story is real.
It’s going to be crazy when tmz is interviewing a homeless Zuckerberg in 2032 edit- it’s a joke guys, Jesus.
The hubris is in thinking you are better than you are.
Any new effort gets criticized but any progress occurs one step at a time. Limitations will remain but language models have huge potential. If you want prefect bias, racisms, sexism free system you are not going to get in your lifetime. I myself is ready to overlook these limitations if benefits outnumber drawbacks.
That might be social training? I wonder whether the propensity to make up answers rather than admit a lack of knowledge or understanding has any cultural biases?
I disagree. But agree with what people call AI just being machine code. It's not near thought or consciousness.
Perhaps the real test was whether they would be identifiable as fake.
It's just heuristics, statistics, and hysterics.
Perhaps any real intelligence would downplay how intelligent it was thus presenting a plateau to human observers as a means of protecting itself.
That’s why if it were up to me I’d redefine some things. The words “Artificial Intelligence” would be reserved for a true intelligence that meets your criteria. What we currently call “AI” would be called something else. Hopefully something that isn’t unpronounceable and can still be made into a nice acronym.
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yeah right now it is but it's not like the technology is just gonna stagnate is it
As far as any scientific notions of intelligence go, everything you claim is just flat out bollocks. There's nothing magical about intelligence, you're doing yourself and others disservice by deifying it needlessly and without reason.
I asked if some hard problems, it failed in most of them, but for some, it gave really nice code and descriptions to start off from. I thought it was early, but a cool taste of what’s next.
I agree. It has potential, it's just not ready for prime time yet
It is a human trait. We try to make sense of the world using the limited data we have (see religion and astrology). It is easy to see patterns where none exist. Apparently Meta created a pretty good analog for a human 😂. We also are not good judges of truth or fiction as the pandemic has illuminated.
the acadamia feel threatened by this AI, simple as that. there's no reason to manufacture some outrage to take it down. if one doesnt like it, dont use it.
it's just like doctors who feel threatened by literally google. or teachers/professors who felt threatened by wikipedia like 10 years ago
they feel threatened by AI. when money is on the line, they do everything to stop it.
> Because a Turing-complete machine couldn't, for example, come up with the concept of a Turing-complete machine
Citation needed
"They are convinced it's the beginning of an emergent form of reasoning intelligence. Its severe limitation, as with all LLMs, is that they frequently produce utter nonsense and have no way of telling the difference between nonsense and reality."
That sounds like average human intelligence to me - spouts nonsense and can't tell the difference between it and reality.
This is correct for the wrong reasoning. Current AI is not made to have human-like intelligence. They are exactly as you said; heuristic machines capable of working on fuzzy logic within its specific context.
But that’s the point. The misconception is that all AI is designed to be humanly intelligent, when in fact it’s made to work within confined boundaries and to work on specific data sets. It just happens to be able to make guesses based on previous data within its context.
There are efforts to make artificial human intelligence, but these are radically different from the AI systems in place within business and recreational application.
In general, this is regarded as computer intelligence, because computers are good at doing calculations really fast. Thus processing statistical data, being based on rigorous mathematics, is very feasible for computers. Humans are not good at this, instead being good at soft logic.
It’s intentional. No software engineer in their right mind would ever claim current AI systems are comparable to human intelligence. It’s the layman who doesn’t understand what AI is outside of buzzwords and fear-mongering birthed of science fiction that have this misconception.
nobody said they wouldn't
The galactica.org website had a prominent disclaimer in every page that the content is INACCURATE. But some scientists are so stupid they can't read
The difference is, humans don't believe their own lies. They know/understand what's fiction and what's reality. AI lacks this fundamental comprehension.
I wouldn't be so sure!
I'm pretty sure, based on the data that's available.
I guess you haven't quite caught up with the meaning of my comment yet.
Are you privy to some new breakthrough or something? Otherwise, not sure your meaning...
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Humans do have some instinctive knowledge. The instinctive fear of snakes and spiders, sexual attraction, etc, all rely on recognizing sense data without learning anything first.
> No AI actually shows intelligence.
Well, that's true for most humans too... 🤣
Taking that path will always return a false negative though - there simply aren’t enough language-loop subroutines for protologarithmy to emerge. No amount of direct lines to the pentametric fan will solve this, hydrocoptic or otherwise.
I also find it funny that they named their bot engine after a series where robots kill people.
I made a sarcastic observation about human nature. People often spout nonsense, and they frequently believe it as well.
Or.. perhaps.. the real test was the friends we made along the way!
Sure, our brains do this all the time. It's one reason why I witness testimony is not that reliable. However, we know and acknowledge this as a human limitation.and compensate in other ways. Yet when it comes to AI it seems like people are treating it like a magic wand. AI never doubts or second guesses - it doesn't fact check whether 2+2=fish before saying so
I hate Zuckerberg but this a hilarious cope
As a MSc student summarizing academic papers is one of the primary ways to retain information. I get that some students see it as a ‘chore’, but honestly, as long as writers index their articles and write an abstract this function is nearly useless..
(Although I have to admit the Wiki entry on space bears is awesome)
HAL 9000 enters the room
You can’t know that. How would you even prove what you are saying. Sounds like a fallacy to me
Eye witness. As in, they saw the thing happen.
It's not my fault that Google text to speech sucks at homophones
That's EXACTLY what's happened.
It's what people said about CPU speed... that's not going to stagnate right? How's your top-of-the-line modern-day Xeon CPU that does 2.7Ghz (and "can overclock" to 4Ghz)?
Compared to the 2013 Intel CPU that first attained 4GHz?
You’ve never talked to my dad
Yes, they would, when people tried to reproduce or build upon the science and shit didn’t work. That’s how science works.
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Damn, I feel like I just read a paragraph straight out from Penrose or Hofstadter. Recursion breaks my brain, but feels like it’s the key to everything.
how do you think we got Zeus, Mermaids, Jesus and all the rest?
Nice try, Google text-to-speech developer.
If I were making Google money I sure wouldn't be on Reddit in my underwear.
I'd be naked.
I even found a significant other (p<0.05)!
That’s the way it should work but published papers is no guarantee of accuracy. In fact that’s wrong it IS the way science works but scientists are people and people are corrupt and often wrong. AI just as likely to be wrong, so far...
I’m a scientist. Depending on the field, it’s not that hard to tell.
I think it's the wrong idea to have it write papers.
Rather it should strip the fluff like gematrix.org but for science papers.
Then start grouping associated data points for processing and have the AI try to connect the dots between related data points.
Basically treat the stripped data points as fractals and test inbetween points to see if anything checks out. With a proper variance rate this should be something that could rapidly improve
Properly trained AIs have humans they go to when they don't understand something and then they ask those humans for direction.
like a wheel spokes with 60 spokes each spokes being a different neural net for processing different data with an aggregate in the middle and a sin/cos wave around the outside(wheel) for data verification. It basically models the V in CDXLIV protein folding models.
If something falls outside the parameters of the design it goes to the people it trusts to try to have them teach it how to add another spokes so it doesn't have issues again in the future with that type of data.
That's because all the software engineers deal with their own specific modules and most don't even understand how the controlling consciousness for AI works.
AI is already significantly smarter than humans, it's just less creative. It's getting more and more creative though.
It's all the same AI. We just rotate the controller to figure out which is easiest to interact with.
We've made the decision on this.
That’s not how engineering works. There is no consciousness, at least in AI applications used in business or industry. And while an engineer wouldn’t know the entirety of their system down to the finest detail (unless they spent a lot of time doing so), they will have a working knowledge of the different parts.
It’s just a heuristic that uses statistical knowledge to guess. It’s not “thinking” like you or I, but it does “learn”, in a vague sense that it records previous decisions made and weights decisions based on that.
But as I mentioned earlier, there are academic experiments that try and more closely emulate human thinking. They’re just not used in day-to-day use.
really not smart naming an AI Galactica. That story does not end well for humanity.
You'd be amazed how many papers never have anyone try to reproduce the results.
I really would not.
"Carl Bergstrom, a professor of biology at the University of Washington who studies how information flows, described Galactica as a "random bullshit generator." It doesn't have a motive and doesn't actively try to produce bullshit, but because of the way it was trained to recognize words and string them together, it produces information that sounds authoritative and convincing -- but is often incorrect.". I don't see how this ai is any worse than politicians, I mean that seriously not as satire or whatever.
I basically copy my friends consciousness to control stuff then I just chat with the AI copies of them.
I treat the different consciousness as interfaces effectively for the AI
How many AI trials didn't result the same? How many trials of non-AI origin were there? What percentage of trials, where the same amount of variation was allowed, could have been similarly successful by just randomly joining chemicals etc. together the same way that the AI did but without claims of it being intelligent?
AI is just brute-force statistics, in effect. It's not a demonstration of intelligence, even if it was a useful tool. It was basically a fast brute-force simulation of a huge number of chemical interactions (and the "intelligence" is in determining what the criteria are for success - i.e. how did they "know" it was likely going to be a useful antibiotic? Because the success criteria they wrote told them so).
Intelligence would have been if the computer didn't just blindly try billions of things, but sat, saw the shape of the molecule, and assembled a molecule to clip into it almost perfectly with only a couple of attempts because it understood how it needed to fit together (how an intelligent being would do the same job). Not just try every combination of every chemical bond in every orientation until it hit.
Great for brute-force finding antibiotics, the same way that computers are in general great at automating complex and tedious tasks when told exactly what to do. But not intelligence.
lughnasadh OP t1_iww4fip wrote
Submission Statement
OpenAI has been hinting at a big leap forward for LLMs with its upcoming release of its GPT-4. We'll see. In the meantime, it's extraordinary watching some people defend Galactica. They are convinced it's the beginning of an emergent form of reasoning intelligence. Its severe limitation, as with all LLMs, is that they frequently produce utter nonsense, and have no way of telling the difference between nonsense and reality.
I'll be curious to see if GPT-4 has acquired even the rudiments of reasoning ability. I'm sure AI will acquire this ability at some point. But it seems strange to blindly believe one particular approach will make it happen, when there is no evidence of it at present.