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> Self driving is probably the most sophisticated domain besides chat, and there too it's the exact same problem. They can drive a vehicle in some complex scena
by vijucat 3y ago
> Self driving is probably the most sophisticated domain besides chat, and there too it's the exact same problem. They can drive a vehicle in some complex scenario with super human performance, and then they randomly drive straight into a highway divider at full speed on a clear day with no traffic.
Yes, very good point. Self-driving maximalists who believe that self-driving will be solved with more data need to realize that ChatGPT was trained with ALL the data possible and is still deficient. This defect is probably inherent to existing neural net models and a leap forward of some sort is necessary to solve this.
Another scary thought: just as each ChatGPT session is different, and you never know whether the agent is going to get angry, overly apologetic, or something else, every self-driving drive may be different due to emergent properties in neural networks that even the best in the field do not yet understand.
- mcculley 3y ago> ChatGPT was trained with ALL the data possible My understanding is that ChatGPT was trained on text from the Internet and public domain texts. There is orders of magnitude more text available to humans behind paywalls and otherwise inaccessible (currently) to these models. Am I missing something?
- nannal 3y agoYes, obvious hyperbole.
- mlboss 3y agoAlso there are images and video that it didn’t used for training
- samrus 3y agoYou are right. It is trained on a lot of data, more than what a person van read in many lifetimes, but not all. In fact it will be interesting how much more it would be at copywriting for specific feilds once it can train on that data. I imagine an LLM trained on all that dusty text in courthouse basements would become a much better paralegal (won't be a lawyer I'm afraid) than vanilla chatGPT
- sigg3 3y ago> person van Makes sense to use Transformers' data to train autonomous vehicles.
- copperx 3y agoDidn't Google have a project to scan and OCR all the books? I wonder whether these data were fed to Bard.
- lobstersammich 3y agoYou can find GPT-2's training dataset list - at a high level - in the GPT-2 repository on Github: https://github.com/openai/gpt-2/blob/master/model_card.md#datasets https://github.com/openai/gpt-2/blob/master/model_card.md#da... However, OpenAI goes dark after that regarding the 'data soup' that was fed into their LLMs. In general, start around 2019 and definitely by 2020 you'll notice that research labs became much less forthcoming about the data that went into their models. As far as I'm aware, BookCorpus is one of the more commonly-used 'large books dataset' that's been utilized in recent years to train large language models (LLMs) like generative pretrained transformers: https://12ft.io/proxy?q=https%3A%2F%2Ftowardsdatascience.com%2Fdirty-secrets-of-bookcorpus-a-key-dataset-in-machine-learning-6ee2927e8650 https://12ft.io/proxy?q=https%3A%2F%2Ftowardsdatascience.com... At my alma mater I remember the large-scale Google book scanning devices and what a herculean effort that was to digitize the largest university library system's books - University of Michigan - although only 7M texts from the entire collection of ~16 million texts: https://en.wikipedia.org/wiki/University_of_Michigan_Library https://en.wikipedia.org/wiki/University_of_Michigan_Library) were digitized.I too was curious about the state of the Google Books project: https://www.edsurge.com/news/2017-08-10-what-happened-to-google-s-effort-to-scan-millions-of-university-library-books https://www.edsurge.com/news/2017-08-10-what-happened-to-goo... This is an interesting piece of ephemera from 2005, when Google started digitizing books at UMich: https://apps.lib.umich.edu/files/services/mdp/faq.pdf https://apps.lib.umich.edu/files/services/mdp/faq.pdf As far as I recall, the Books project allowed the early n-grams functionality to be built out: https://ai.googleblog.com/2006/08/all-our-n-gram-are-belong-to-you.html https://ai.googleblog.com/2006/08/all-our-n-gram-are-belong-... The Google Books Ngram Viewer tool is actually still in existence; you can play around with it here: https://books.google.com/ngrams/graph?corpus=0&content=Vorsprung%20durch%20Technik https://books.google.com/ngrams/graph?corpus=0&content=Vorsp...
- codr7 3y agoIf that was the case, it threw more than half of it up again, because it's not making much sense atm.
- wilg 3y agoNo, it would be a gross misunderstanding to think ChatGPT has anywhere close to all the data possible. Not even close to all the data on the internet. Not even close to all text. Let alone data available by directly interacting with the world.
- lelanthran 3y ago> Not even close to all the data on the internet I agree with your other points, but why would you think ChatGPT was not given all the data on the internet? If you aren't storing the text, the only thing that stops you retrieving all the pages that can possibly be found on the internet is a small amount of money. I'm pretty certain that OpenAI has a lot more than a small amount of money.
- wilg 3y agoIn addition to what others have said, there is a significant amount of data on the internet that is not in text form.
- revertmean 3y agoBecause if it was, it would mostly talk about porn? :)
- yardstick 3y agoThere’s lots of paywalled content, and other content hidden behind logins and group memberships (Eg Facebook posts, University ex-alumni portals, University course portals). Even the paywall issue alone, I can’t see how they could scale doing paywall signups automatically. Each paywall form is different, may require a local phone number in a different country to receive a text, etc.
- hosh 3y agoLLMs might be good enough to sign up for sites, though maybe not yet fool “I am a human” test.
- namaria 3y ago
- ChatGTP 3y agoI don’t think you needed to take it literally.
- mcculley 3y agoI am very interested in what LLMs will be able to do when trained on something other than the content on the Internet, which is primarily generated to sell advertising views.
- ChatGTP 3y agoI highly doubt it’s trained on that. I’m the sure it was curated and trained on the good stuff.
- mcculley 3y agoDid you arrive at this certainty through reading something other than what OpenAI has published? The document [0] that describes the training data for GPT-2 makes this assertion hilarious to me. [0]: https://github.com/openai/gpt-2/blob/master/model_card.md#datasets https://github.com/openai/gpt-2/blob/master/model_card.md#da...
- lhuser123 3y agoMaybe they’ll end up using a bunch of if statements :)
- worrycue 3y ago> Yes, very good point. Self-driving maximalists who believe that self-driving will be solved with more data need to realize that ChatGPT was trained with ALL the data possible and is still deficient. This defect is probably inherent to existing neural net models and a leap forward of some sort is necessary to solve this. This is the thing that bugs me about ChatGPT4 which everyone says is a lot better. Did they fix the underlying issues or does it just have more data? If it's the latter, that means if it's force to operate outside of its "domain" it's going to produce rubbish again - and heaven knows where the limits of its current domain are. These AIs need to not catastrophically fail if they are missing information. IMHO in order for AI to be truly useful, we need to be able to trust it. I can't trust something that produces rubbish wherever it's out of its depth instead of just saying "I don't know."
- weaksauce 3y ago> IMHO in order for AI to be truly useful, we need to be able to trust it. I can't trust something that produces rubbish wherever it's out of its depth instead of just saying "I don't know." I wholeheartedly agree. what we have now is a very capable and convincing liar.
- deleted 3y ago[deleted]
- ants_everywhere 3y ago> what we have now is a very capable and convincing liar. I think things might get even wilder once companies start allowing advertisers to influence chat results like they do with search. Imagine a capable and convincing liar who has an ulterior motive when it talks to you.
- zdragnar 3y agoIt cannot tell the truth, because it does not have the context or understanding of what is true or incorrect. It is less a liar (who intends to mislead) and instead a fantastic bullshitter who just talks and sounds convincing.
- 3y ago
- Spooky23 3y agoI think this is one of the greatest features of LLMs. They are incredibly powerful tools, but have obvious limitations that require a certain amount of finesse to manage. During the peak Uber hype cycle, insufferable self-driving people were always yabbering on about how superior the AI is, robot taxis will take over, etc. it was difficult to assess or discuss those statements then when the AI models cost millions and weren’t available outside of major companies, who tend to downplay their failures. Now, thousands or even millions of people can set LLMs onto a variety of critical and mundane tasks that they can actually objectively evaluate. As end users, we can now build fluency in how different approaches to AI work and don’t work.
- dragonwriter 3y ago> ChatGPT was trained with ALL the data possible No, it wasn’t, except under a very limited conception of “possible”.
- vijucat 3y agoTrue. I shouldn't have used a universal qualifier. I should have, "all the data possible (that one corporation can get it's hands on)" or something qualified.
- throwuwu 3y agoProbably not even that. Remember that the constraints also include cost and time so it’s unlikely they just threw everything at it willy nilly.
- MacsHeadroom 3y agoThe CEO and CTO of OpenAI have both said that they currently have more than 10x data than they used to train GPT-4, agreements to collect 30x more, and that collecting 100x more would not be a problem.
- hooande 3y agoDo you have a source link for this?
- simonh 3y agoAnother avenue is training on generated text. This is likely to be important in teaching these things reasoning skills. You identify a set of reasoning tasks you want the system to learn, auto-generate hundreds of millions of texts that conform to that reasoning structure but with varying ‘objects’ of reasoning, then train the LLM on it and hope it generalises the reasoning principles. This is already proving fruitful.
- robryan 3y agoIt would be fair to say though that there wouldn't be an order of magnitude more data to train a future version with.
- enono 3y ago[flagged]
- circuit10 3y agoI think it’s a limitation with the amount of parameters in the model and the way the RLHF training was done, not anything about neural networks. GPT-4 is better at this sort of thing
- throwawayadvsec 3y ago"need to realize that ChatGPT was trained with ALL the data possible" That's just 100% not true
- woeirua 3y agoWe don’t know for sure. OpenAI isn’t being transparent.
- whimsicalism 3y agoHave they been reading my diary?
- throwawayadvsec 3y agoThink about it for half a second dude, seriously. GPT has not been trained on this message for example, or yours.
- Rexxar 3y agoImho, for self-driving it could be much more simple if we don't try to be too clever but we just add more signage to help the car on road where we want to allow self-driving.
- j5155 3y agoI mean, there is no requirement that we use neural networks for driving (or for all of driving); standard logic and sensor analysis is also an option if less general. There are also things like automatic emergency braking that kick in with direct logic even when a human is driving; presumably we may be able to make more advanced similar systems for self driving. But in general I would definitely agree that putting chatgpt into a car would end poorly.
- runeks 3y ago> I mean, there is no requirement that we use neural networks for driving (or for all of driving); standard logic and sensor analysis is also an option if less general. I really think this is the way forward for self-driving cars. I wonder how expensive it would be have a highly precise, synchronized clock in all cars, and have them send out digitally signed, time-stamped messages every ~millisecond in order to enable locating them via triangulation. They could also report information from their own sensors, such that e.g. a traffic jam further up the road can be transmitted to cars further back. This would require that each car contain a private key in a TPM, where the entity that issues license plates would act as the certificate authority.
- nuancebydefault 3y agoThe thing is, in the real world, you cannot rule out that there are cars that don't have the required hw or sw on the road. Maybe in some future there will be no such exceptions, but the driverless cars technology is not going to wait for that. For the foreseeable future, the solution must be a hybrid (human/old tech/new tech) , unfortunately.