64 ms·

After watching the demos I'm convinced that the new context length will have the biggest impact. The ability to dump 32k tokens into a prompt (25,000 words) see

• leshow 4y ago
  > A doctor can put an entire patient's medical history in the prompt, a lawyer an entire case history, etc. you don't see a real problem there?
• amelius 4y ago
  > As a professional...why not do this? Because your clients do not allow you to share their data with third parties?
  • as300 4y ago
    What's the difference between entering in an anonymized patient history into ChatGPT and, say, googling their symptoms?
    • mliker 4y ago
      if you enter an entire patient history, it could easily be an identifier of the person whereas Google queries have a smaller max limit number of tokens
      • msikora 4y ago
        Can OpenAI get HIPAA certification? Perhaps offer a product that has it?
        • gigel82 4y ago
          I've heard the Azure OpenAI service has HIPAA certification; they don't have GPT-4 yet, though.
          • Godel_unicode 4y ago
            The pdf on this page has the services that are under audit scope, check the table in appendix A; OpenAI is in scope for HIPAA BAA.
    • pmoriarty 4y ago
      Data that has ostensibly been "anonymized" can often be deanonymized.
      • Gene_Parmesan 4y ago
        Especially when the system we're discussing is literally the most advanced AI model we're aware of.
    • woodson 4y ago
      Anonymization doesn’t just mean “leave their names out”. An entire patient's medical history is in itself personal identifiable information. Instead of googling for “headache”, they now have stored a copy of every medical detail in your life.
    • 4y ago
  • MagicMoonlight 4y ago
    What we really need is a model that you can run on your own hardware on site. I could never use this for business because they're reading everything you send through it, but let me run it on my own server and it would be unbelievably useful. Imagine being able to ask your workplace server if it has noticed any unusual traffic, or to write a report on sales with nice graphs. It would be so useful.
    • jahewson 4y ago
      “on site”? Medical records are in the cloud already.
      • szundi 4y ago
        What is “the cloud” - that’s the question
        • gffrd 4y ago
          As taken from the cover page of the July, 2018 edition of AARP Weekly.
      • MisterBastahrd 4y ago
        Yes. But they aren't being shared with third party AIs. Sharing personal medical information with OpenAI is a good way to get both your medical org to get ground into dust under a massive class action lawsuit, not to mention huge fines from the government.
        • sebzim4500 4y ago
          Why do you think sharing the data with OpenAI is legally any different than storing it on AWS/Azure/GCP/Whatever else they are using?
          • unusualmonkey 4y ago
            GCP respects hipaa (google 'gcp hipaa baa'). Does OpenAPI?
  • majkinetor 4y ago
    Which will disappear soon enough, once it is able to run on premise.
  • hanoz 4y ago
    I'd be furious if I found out some professional I'd commissioned had taken a document based on my own personal data, and poured over it themselves looking for errors at the tune of hundreds of dollars per hour, instead of sumbitting it to ChatGPT.
    • paulryanrogers 4y ago
      Then why submit it to a professional human at all? If ChatGPT is prone to massive errors humans have to pour over the input anyway. If ChatGPT can make subtle, rare errors then again humans may need to be involved if the stakes are high enough to commission someone.
      • msikora 4y ago
        As a second opinion advisory role this seems reasonable... And also things are going to improve with time.
      • glenstein 4y ago
        >If ChatGPT can make subtle, rare errors Yeah, I think the issues presented will relate to uniquely tricky errors, or entirely new categories of errors we have to understand the nature of. In addition to subtle and rare, I think elaborately hallucinated and justified errors, errors that become justified and reasoned for with increasing sophistication, is going to be a category of error we'll have to deal with. Consider the case of making fake but very plausible sounding citations to research papers, and how much further AI might be able to go to backfill in it's evidence and reasons. Anyway, I just mean to suggest we will have to contend with a few new genres of errors
  • seydor 4y ago
    I assume that health providers will use servers that are guaranteed not to share data with openAi
  • tippytippytango 4y ago
    This is the biggest thing holding gpt back. Everyone with meaningful data has their hands tied behind their back. So many ideas and the answer is “we can’t put that data in gpt” very frustrating.
    • geysersam 4y ago
      Sounds like an easy problem to solve if this is actually the case. OpenAI just has to promise they won't store the data. Perhaps they'll add a privacy premium for the extra effort, but so what?
      • null_shift 4y ago
        Anyone that actually cares about the privacy of their data isn’t going to be satisfied with just a “promise”.
        • geysersam 4y ago
          A legal binding agreement, whatever.
          • Gene_Parmesan 4y ago
            Still not enough. Seriously. Once information is out there it cannot be clawed back, but legal agreements are easily broken. I worked as a lawyer for six years; there are extremely strict ethical and legal restrictions around sharing privileged information.
            • Jensson 4y ago
              > I worked as a lawyer for six years; there are extremely strict ethical and legal restrictions around sharing privileged information. But Microsoft already got all the needed paperwork done to do these things, it isn't like this is some unsolved problem.
            • sebzim4500 4y ago
  • deleted 4y ago
    [deleted]
  • fatihcelikbas 4y ago
    How about open-source models like Flan-T5? What stops you from using them in your own cloud account or better on-prem?
  • TeeMassive 4y ago
    You mean like the cloud?
  • pas 4y ago
    It'll be a routine question, and everyone will just nod to give consent.
  • deleted 4y ago
    [deleted]
  • ShadowBanThis01 4y ago
    And yet boatloads of people are willing to hand their phone number over to OpenAI.
  • jnwatson 4y ago
    Then you really shouldn’t use Google Docs, or Photoshop Online, or host your emails in the cloud.
    • faeriechangling 4y ago
      These services now have privacy and legally complaint options nowadays, and decisions to use them get board approval. OpenAI just simply does not offer the same thing at this time. You’re stuck using Facebook’s model for the moment which is much inferior.
    • thiht 4y ago
      You’re saying it like you found a loophole or something but it’s not a gotcha. Yes, if you manipulate sensitive data you shouldn’t use Google Docs or Photoshop online (I’m not imaginative enough to think of a case where you would put sensitive data in Photoshop online though, but if you do, don’t) or host your emails in the cloud. I’ve worked in a moderate size company where everything was self hosted and it’s never been an issue
    • selfhoster11 4y ago
      Google Docs and Photoshop Online have offline alternatives (and if you ask me, native MS Office is still the golden standard for interoperability of editable documents), and I use neither in my work or personal life. Email is harder, but I do run my own email server. For mostly network related reasons, it is easier to run it as a cloud VM, but there's nothing about the email protocol itself that needs you to use a centralised service or host it in a particular network location.
      • jfoster 4y ago
        MS Office is just one login away from storing documents in the cloud. I bet tons of users have their documents stored in OneDrive without realizing it. https://support.microsoft.com/en-us/office/save-documents-online-8ba1f596-6bc9-4e35-99d4-e27a40037789 https://support.microsoft.com/en-us/office/save-documents-on...
    • Sharlin 4y ago
  • sshumaker 4y ago
    Just use the Azure hosted solution, which has all of Azure's stronger guarantees around compliance. I'm sure it will update with GPT-4 pricing shortly. https://azure.microsoft.com/en-us/products/cognitive-services/openai-service https://azure.microsoft.com/en-us/products/cognitive-service... (disclaimer: I work for Microsoft but not on the Azure team)
    • ndm000 4y ago
      Agreed. The same data privacy argument was used by people not wanting their data in the cloud. When an LLM provider is trusted with a company’s data, the argument will no longer be valid.
  • alfor 4y ago
    do you use gmail?
  • jstummbillig 4y ago
    In these particular circles the idea of privacy at a technical and ideological level is very strong, but in a world where the biggest companies make their money by people freely sharing data every chance they get, I doubt that most would object to an affordable way to better their chances of survival or winning a court case.
  • textninja 4y ago
    Biggest roadblock right here. Need a private version for sure.
  • netsroht 4y ago
    That's why more research should be poured into homomorphic encryption where you could send encrypted data to the API, OpenAI would then run computation on the encrypted data and we would only decrypt on the output locally. I would never send unencrypted PII to such an API, regardless of their privacy policy.
  • rawoke083600 4y ago
    Is that any different then sending you patient down the hall to get an MRI from a 3rd-party-practise operating inside the hospital ? (honest question, I don't know ?)
• d3ckard 4y ago
  I must have missed the part when it started doing anything algorithmically. I thought it’s applied statistics, with all the consequences of that. Still a great achievement and super useful tool, but AGI claims really seem exaggerated.
  • jakewins 4y ago
    This paper convinced me LLMs are not just "applied statistics", but learn world models and structure: https://thegradient.pub/othello/ https://thegradient.pub/othello/ You can look at an LLM trained on Othello moves, and extract from its internal state the current state of the board after each move you tell it. In other words, an LLM trained on only moves, like "E3, D3,.." contains within it a model of a 8x8 board grid and the current state of each square.
    • nottathrowaway3 4y ago
      Also (for those like me who didn't know the rules) generating legal Othello moves requires understanding board geometry; there is no hack to avoid an internal geometric representation: > https://en.m.wikipedia.org/wiki/Reversi https://en.m.wikipedia.org/wiki/Reversi > Dark must place a piece (dark-side-up) on the board and so that there exists at least one straight (horizontal, vertical, or diagonal) occupied line between the new piece and another dark piece, with one or more contiguous light pieces between them
      • anonymouskimmer 4y ago
        I don't see that this follows. It doesn't seem materially different than knowing that U always follows Q, and that J is always followed by a vowel in "legal" English language words. https://content.wolfram.com/uploads/sites/43/2023/02/sw021423img21.png https://content.wolfram.com/uploads/sites/43/2023/02/sw02142... from https://writings.stephenwolfram.com/2023/02/what-is-chatgpt-doing-and-why-does-it-work/ https://writings.stephenwolfram.com/2023/02/what-is-chatgpt-... I imagine it's technically possible to do this in a piecewise manner that doesn't "understand" the larger board. This could theoretically be done with number lines, and not a geometry (i.e. the 8x8 grid and current state of each square mentioned in the comment you replied to). It could also be done in a piecewise manner with three ternary numbers (e.g. 1,0,-1) for each 3 square sets. I guess this is a kind of geometric representation on the order of Shannon's Theseus.
• pstorm 4y ago
  Reading the press release, my jaw dropped when I saw 32k. The workaround using a vector database and embeddings will soon be obsolete.
  • siva7 4y ago
    I don't see how. Can you elaborate?
  • justanotheratom 4y ago
    Cost is still a concern, so workarounds to reduce context size are still needed
    • pstorm 4y ago
      Good point! I realized after I wrote the comment above, that I will still be using them in a service I'm working on to keep price down, and ideally improve results by providing only relevant info in the prompt
  • teaearlgraycold 4y ago
    That’s like saying we’ll not need hard drives now that you can get bigger sticks of RAM.
  • nl 4y ago
    > The workaround using a vector database and embeddings will soon be obsolete. This is 100% not the case. Eg I use a vector database of embedding to store an embedding of every video frame which I later use for matching. There are many NLP-only related tasks this helps for but equally as many that still require lookup and retrieval.
    • pstorm 4y ago
      True. I should have clarified that the workaround used for many NLP tasks, utilizing libs such as Langchain, will become obsolete. And after further thought, obsolete is wrong. More likely just used for more niche needs within NLP.
• billythemaniam 4y ago
  If you had full source code that fit into the context, do you think it could reliably answer questions about the code, build unit tests, generate documentation? I ask because that is the software equivalent of what you just described.
  • raincole 4y ago
    All we can do is guessing now until more people get access to the new API. My bet is it can at least generate documentation pretty well.
    • varenc 4y ago
      I think anyone that pays $20/month for ChatGPT plus has immediate access? At least I already have access now. I’m assuming new subscribers get access too.
      • raincole 4y ago
        As far as I can tell, ChatGPT plus is the 8096 tokens version. The 30k token version is only available via API. I might misread it tho, it's not super clear on their site. Are you sure you are accessing the 30k token version via ChatGPT plus?
        • varenc 4y ago
          No, you're right. The ChatGPT-4 interface has the lower token limit!
          • WinstonSmith84 4y ago
            Here is the release notes confirming this https://help.openai.com/en/articles/6825453-chatgpt-release-notes https://help.openai.com/en/articles/6825453-chatgpt-release-... It was not clear however that there was this token limit restriction, thanks
      • ElijahLynn 4y ago
• 0898 4y ago
  When will the longer context length be available through ChatGPT Plus? Have they said yet?
• m3affan 4y ago
  The power openai will hold above everyone else is just too much. They will not allow their AI as a service without data collection. That will be a big pill to swallow for the EU.
  • peterashford 4y ago
    Yeah, there's an awful lot of power going into private hands here and as Facebook & Twitter have shown, there can be consequences of that for general society.
    • gwright 4y ago
      > Yeah, there's an awful lot of power going into private hands That sounds scary, but what do you mean by "power"? Honest question, I'm fascinated by the discussion about learning, intelligence, reasoning, and so on that has been spawned by the success of GPT. What "power" do you imagine being wielded? Do you think that power is any more dangerous in "private hands" than the alternatives such as government hands?
      • leshow 4y ago
        lmao
      • peterashford 4y ago
        Do you think that Facebook has an effect on society and our democracies? That's power. Do you think that large corporates like Apple or Google effect our societies? I do - and that's power. EVERY large corporate has power and if they control some aspect of society, even more so. If AI tools are democratised in some way, then that would allay my concerns. Concentration of technology by for-profit corporations concerns me. This seems quite similar to many of the reasons people like OSS, for example. Maybe not for you?
  • p1esk 4y ago
    OpenAI have been consistently ahead of everyone but the others are not far behind. Everyone is seeing the dollar signs, so I'm sure all big players are dedicating massive resources to create their own models.
• int_is_compress 4y ago
  There’s already project that help with going beyond the context window limitation like https://github.com/jerryjliu/llama_index https://github.com/jerryjliu/llama_index They also just tweeted this to showcase how it can work with multimodal data too: https://twitter.com/gpt_index/status/1635668512822956032?s=46&t=6ZIqJnQp7YWjtdJnmNgmtg https://twitter.com/gpt_index/status/1635668512822956032?s=4...
• graboid 4y ago
  Do you think this will be enough context to allow the model to generate novel-length, coherent stories? I expect you could summarize the preceding, already generated story within that context, and then just prompt for the next chapter, until you reach a desired length. Just speculating here. The one thing I truly cannot wait for is LLM's reaching the ability to generate (prose) books.
  • deleted 4y ago
    [deleted]
  • hooande 4y ago
    I've seen that it can also generate 25k words. That's about 30-40% of the average novel
    • hattmall 4y ago
      Couldn't you feed it the first 25k words and tell it to continue the story?
      • Sharlin 4y ago
        If its context size is >= 25k words, yes. Otherwise it will just discard the start of the prompt. And it’s a sliding window, so the more it generates, the more it forgets.
        • Applejinx 4y ago
          You could get an 'Illuminatus!' type book out of this, especially if you steered the ending a bit in order to reference earlier stuff. If you're trying to make a sprawling epic that flings a kaleidoscope of ideas, GPT can do that sort of thing, it's just that it won't end up making sense. GPT is going to be rather poor at priming people for an amazing ending by seeding the ideas and building them into the narrative. Though if you're directing it with enough granularity, you could tell it to do that just like you'd tell yourself to do that when you're doing the writing yourself. But then you're becoming the executive writer. On a granular enough level, the most ultimate executive control of GPT would be picking individual words, just like you were writing them yourself. Once you want to step away and tell it to do the writing for you, you drift more into the GPT-nature to the point that it becomes obvious.
• bitL 4y ago
  I am surprised they allow only 32k tokens when Reformer can have context length of 1M on 16GB VRAM. It seems like they have some ways to optimize it further.
  • geysersam 4y ago
    Is the Reformer as capable as this model? It's a trade-off.
    • bitL 4y ago
      It's not, it uses locality-sensitive hashing to reduce attention complexity from O(n^2) to O(nlogn) while maintaining the same performance in 16GB as a best model that could fit into 100GB but nobody scaled it up to 1000 GPUs as its purpose was the opposite.
• nullc 4y ago
  > As a professional...why not do this? Because of confidentiality.
  • unyttigfjelltol 4y ago
    Because it's harder to correct subtle errors from an ad-lib generator than it is to construct a correct analysis in the first instance.
    • nullc 4y ago
      Agreed but there is safe(er) way to use it that large addresses that concern: First construct your correct analysis through conventional means, untainted by machine hallucinations. Then have the machine generate a result and see if it caught anything you missed, and carefully check whatever few parts you incorporate from it. This is not different than having a lesser expert check your document (e.g. THE CLIENT!), except the machine time is very close to free and may be even better at catching far off concepts.
• Madmallard 4y ago
  GPT is censored with respect to medical diagnosis
• amrb 4y ago
  HIPAA fines will sink you so fast, unless they be hosting it dedicated.
  • Hoyadonis 4y ago
    If they redact all identifying information, it would most likely be legally Kosher. However, there is an extreme abundance of caution in the healthcare industry regarding everything surrounding HIPAA. Merely questioning the legality of something can cost millions of dollars in lawyers' fees. Therefore even miniscule chances of something being legally challenged (e.g. plugging patient information into an LLM) would most likely be deemed too risky. And frankly, hospital administrators will not want to risk their careers over trying out what they perceive to be a glorified chatbot. Tl;dr: When it comes to HIPAA, risk aversion is the name of the game.
    • Sharlin 4y ago
      If you redact all identifying information from a patient case file, it will likely become almost useless. Anything that describes a person in any way is potentially personally identifying information.
• oska 4y ago
  > it will drastically expand the reasoning capability > it can algorithmically do reasoning How is this machine doing reasoning ? Why do you think you can use this word in this context ?
  • Semioj 4y ago
    What is reasoning? Is it perhaps having a consistent model which allows you to describe every point of it? Because if chatgpt can explain itself based on a model it builds with it than I actually does reasoning
    • xwolfi 4y ago
      No that's self awareness, reasonning is more applying logical rules to inputs to produce a logical output (inputs can be "wrong" though)
      • Sharlin 4y ago
        Self awareness is having a model of self. Having a model of something non-self has absolutely nothing to do with self-awareness.
  • barogptinfi 4y ago
    It could only solve 3/45 Leetcode hards, I think people are giving the current iteration of this AI far too much credit for what they imagine future iterations to be. When it has true reasoning and critical thought is when we will see it evolve into something else, for now it seems we're still in the first generations of microprocessors with GPT-4, in the grand scheme of things they only have a few transistors but we couldn't possibly comprehend where the technology would be merely a decade or two from now.
    • cornholio 4y ago
      It can solve exactly zero leetcode easies if they are original problems seen for the first time for which no training data exists.
• geysersam 4y ago
  It costs something like 0.03-0.06 cents per thousand tokens. So for 32k that's about $1-3 for reading and another $1-3 for the response. So sure, still cheap for a doctor appointment, but not pennies. Do it 30 times per hour and you could've just hired a consultant instead. Does it reason as well with 32k tokens as with 1k tokens? Like you said, humans find it difficult to really comprehend large amounts of content. Who says this machine isn't similarly limited? Just because you can feed it the 32k simultaneously doesn't mean it will actually be used effectively.
  • Semioj 4y ago
    You still could not. Chatgpt could in theory have the knowledge of everything written while your consultant can't.
    • geysersam 4y ago
      Sure... But in practice I think a consultant would still provide a higher quality answer. And then, if the bot is not significantly cheaper, what does it matter if it "has more knowledge" in it's network weights?
    • ericpauley 4y ago
      Further, a consultant couldn’t meaningfully interpret 50 pages in 2 minutes, even with the most cursory skimming.
      • hackernewds 4y ago
        An LLM can never offset a consultants diverse duties though. Some, maybe. However you cannot run healthcare with 90% specificity
  • zachthewf 4y ago
    Cost of ChatGPT API just dropped 90%. Guaranteed that prices will come down dramatically over time.
    • 4y ago
• kristjansson 4y ago
  > lawyer an entire case history ~50 pages is ... not the entire history of most cases.
• rasz 4y ago
  >A doctor can put an entire patient's medical history in the prompt HIPAA violation https://www.hhs.gov/hipaa/for-individuals/index.html https://www.hhs.gov/hipaa/for-individuals/index.html >a lawyer an entire case history, etc. lawyer client confidentiality violation https://criminal-lawyers.ca/2009/07/31/the-lawyers-duty-of-confidentiality/ https://criminal-lawyers.ca/2009/07/31/the-lawyers-duty-of-c...
  • hattmall 4y ago
    Neither of those are true, there is EHR software that can export anonymous data. Lawyers can do the same thing. But the real reason not to do it is that it makes up incorrect information. It's pretty good for short responses where you can then verify the information. For something sufficiently complex though the time chasing down the inconsistencies and errors would be onerous.
    • lukev 4y ago
      Unlike information embedded in the parameters, a LLM has the capability to "cite its source" for information in the context window.
• andrepd 4y ago
  > If you can put in ALL of the information relevant to a problem and it can algorithmically do reasoning Well but it can't, can it? That's the very point: it is an algorithm with no abstraction or reasoning capabilities. Mind, even without that it is still very useful for certain circumscribed purposes, but it's incorrect to say it can "reason".
  • astrange 4y ago
    Pretty easy to get it to abstract, just ask it. -- Q: List possible abstractions encompassing all these specific concepts: singing, whistling, yodeling. A: One possible abstraction that encompasses all these specific concepts is "vocalization." Vocalization refers to the act of producing sound using the vocal cords and the mouth. Singing, whistling, and yodeling are all different types of vocalization, but they share the common feature of using the human voice to create sound. Other possible abstractions that might encompass these concepts could include "musical expression," "auditory performance," or "sound production." --
    • andrepd 4y ago
      That's literally a text search task. That's not what I mean, I mean things like understanding the rules of addition from examples, the rules of logic from examples, or the rules of chess.
      • astrange 4y ago
        It can't search text. It doesn't have access to any text. Anything it does works in a different way than that. It is sometimes able to do other tasks, but unlike humans (or "AGI") it has a completely fixed compute budget and can't pause to think in between outputting two tokens. (Btw, I tried to get it to derive addition from two 1-digit examples but couldn't.)
      • gwd 4y ago
        According to [1], they trained an LLM on legal Othello moves, and 1) it got an error rate of 0.01% 2) when they analyzed its network, they found a model of an Othello board 3) when they modified the in-network model, it started generating moves legal in the modified board position. In other words, the LLM did build an internal model that contained the rules of Othello merely from seeing legal moves. It's reasonable to assume that the same thing is happening (at least to some degree) with LLMs based on human speech. [1] https://thegradient.pub/othello/ https://thegradient.pub/othello/
• faeriechangling 4y ago
  > As a professional...why not do this? I would love to but openai’s privacy policies makes it a huge ethics, privacy, and security breach. I’m interested in running Facebook’s model just as a workaround to this fundamental issue.
• SergeAx 4y ago
  Please. Language model cannot "reason", it can just show next most probable word based on text corpus downloaded from the internet.
  • fastball 4y ago
    What do you mean by "next most probable word"? How do you calculate the probabilities of words appearing in a sentence that has never actually existed?
    • SergeAx 4y ago
      You take the prompt and caclulate what next word after the prompt is most probable. Like T9 with letters, but bigger.
      • RugnirViking 4y ago
        and how do you "calculate what word is most probable" next for a combination of words that has never occured before? Note that most sentences over about 20 words have statistically probably never been written in human history before. The whole reason there is an AI here is because a markov chain, which is what you are describing, doesn't work beyond one or two word horizons. Not to mention that it doesn't just select which word it thinks is MOST probable, because that has been shown to lead to stilted and awkward output. Instead it randomly selects from the top few thousand possible words with probability based on the model's estimation
        • SergeAx 4y ago
          I am not talking about the concrete realization, I am talking about the principle. You are right, LLMs are just Markov's chains on steroids, thus they cannot "reason". For reasoning you need a knowledge model, a corpus of facts, Boolean algebra and so on. Not a petabyte of words downloaded from all over the internet and crunched and sifted thru huge self-supervised transformer network.
• aaron695 4y ago
  [dead]
• voldacar 4y ago
  >As a professional...why not do this? because "open"AI logs everything that goes in and out of the model?
• light_hue_1 4y ago
  > As a professional...why not do this? There's a non-zero chance that it'll find something fairly basic that you missed and the cost is several cents. Everyone forgets basic UI research. "Ironies of Automation", Bainbridge, 1983. The classic work in the space. Humans cannot use tools like this without horrible accidents happening. A tool that mostly works at spotting obvious problems, humans start to rely on that tool. Then they become complacent. And then the tool misses something and the human misses it too. It's how disasters happen.
  • dinkumthinkum 4y ago
    This is such a great point.
• matheusmoreira 4y ago
  > As a professional...why not do this? Unless GPT-4 is running locally on our own computers, there's absolutely no way dumping a patient's entire medical history into this thing could possibly be considered ethical or legal.
  • textninja 4y ago
    > there's absolutely no way dumping a patient's entire medical history into this thing could possibly be considered ethical Emphasis mine, but isn’t this a rather extreme view to be taking? Ethics deals in the edge cases, after all, so we can easily imagine a scenario where patient consent is obtained and the extra computational analysis provides life-saving insight. Conversely, the output could mislead the doctor sufficiently to cost the patient their life, so I’m not making any absolute statements either ;) For the record, and pedantry aside, I do agree with your overall point. Dropping patient history into this thing is incredibly ill-advised. The fact OpenAI retains all your input, including to the API, and provides no low-cost options for privacy is one of the biggest hurdles to major innovation and industry adoption.
    • selfhoster11 4y ago
      If my doctor did this without my express knowledge and consent, I'd be looking for a new doctor faster than you can say "f*ck no, absolutely not".
      • textninja 4y ago
        Me too, probably, which is why I specifically mentioned patient consent in my example. I can however imagine other situations where I would be inclined to forgive the doctor, such as if I were in the operating theatre and for some reason there was an urgent need to ascertain something from my history to save my life. Of course, this is illegal, so the ethics are moot; even if such technology would save my life, there is no way the hospital would accept the liability.
      • LightBug1 4y ago
        New doctor? I think you mean, new lawyer.
• textninja 4y ago
  > What % of people can hold 25,000 words worth of information in their heads, while effectively reasoning with and manipulating it? In the general case, for arbitrary input, I think the answer to this is clearly 0. At best we can compress the text into a limited embedding with a few salient points stored in long term memory.
  • trashtester 4y ago
    I'm pretty sure one could formulate way more than 25k words worth of propositions, where you would be able to determine if the proposition is true or not. This is due to your long term memory. The GPT string is closer to short term memory, and there 25k words is way more than a human is capable of. But a human author can offload much storage to long term (or some intermediate) memory. In principle, GPT should be able to do so to, by basically retrain the model with the text it just created added as input. That way, it might be able to write texts that are billions of words long, but at a much greater cost of computing power, since this would require one instance of the model per book being written.
• imranq 4y ago
  There's less and less relevant data with longer documents, so I would expect performance wouldn't change much
• throwaway2037 4y ago
  "Second Opinion machine" -- that's a good phrase. Before I read your post, the best term I heard was "summary machine". A huge part of "office work" (services) is reading and consuming large amounts of information, then trying to summarise or reason about it. Often, you are trying to find something that doesn't fit the expected pattern. If you are a lawyer, this is absolutely the future of your work. You write a short summary of the facts of the case, then ask GPT to find related case law and write the initial report. You review and ask GPT to improve some areas. It sounds very similar to how a senior partner directs their juniors, but the junior is replaced by GPT. In my career, I saw a similar pattern with data warehouse users. Initially, managers asked junior analysts to write SQL. Later, the tools improved, and more technical managers could use a giant pivot table. Underneath, the effective query produced by the pivot table is way more complex than their previous SQL queries. Again, their jobs will change when on-site GPT become possible, so GPT can navigate their data warehouse. It is 2023 now, and GPT-3 was already pretty good. GPT-4 will probably blow it away. What it look like in 2030? It is terrifying to me. I think the whole internet will be full of GPT-generated ad-copy that no one can distinguish from human-written material. There are a huge number of people employed as ad-copy writers on these crap ad-driven websites. What is their future work?
  • hassancf 4y ago
    Pre 2023 “Wayback machine” will be the only content guaranteed to be human. The rest is AI-generated.
• jalapenos 4y ago
  The length is the main bottleneck right now. I'm running whatever I can through this right now. It's doing what Google was doing, i.e. clues, but on steroids. As soon as the length hits codebase size territory we're in yet greater frontiers.
• marsven_422 4y ago
  "expand the reasoning" there is no reasoning going on here! It's all statistical word generation aka math! And this is not how humans "work" our brain are not computers running software. We are something else.
• bagels 4y ago
  A doctor doesn't do this because of ethics and HIPAA. I'm sure lawyers aren't so keen on sharing privileged information that would compromise their case either.
  • sleigh-bells 4y ago
    For legal research, lawyers already use third party sites like Westlaw. You can do legal research without giving up any confidential client information. I just asked GPT-3 a research question that took me hours of searching back in the day and it returned the single seminal case for that topic immediately. As long as the lawyers then actually read the case and make sure it's right, I don't see why they can't use it.
• d--b 4y ago
  Who says GPT has the ability to hold 25,000 token in its "head"? You can send 25000 random words in the prompt and asks GPT how many pairs of words share at least one letter. I doubt that the answer will be correct...
  • moconnor 4y ago
    Why? I'm pretty sure it could do this kind of task - attention is computed between all pairs of tokens. Yes, it's a lot of compute.
  • criddell 4y ago
    Surely GPT could write a program to count pairs of words that share at least one letter, right? Maybe GPT-5 will be able write and run programs on the fly to answer questions like this.
• 908087 4y ago
  [dead]
• mercurialsolo 4y ago
  Couldn't the same be done by breaking the conversation down into chunks and adding the context incrementally?
• jacquesm 4y ago
  What happens with the prompts that you enter into OpenAI? I believe each and every one of those will be saved. And even if they swore that they did not would you trust them? If my lawyer or doctor put my case history into OpenAI and I would find out about it I would definitely sue them for breach of confidentiality.
• snickmy 4y ago
  A bit of nitpicking but I would prefer to replace the word 'reasoning capability' with 'sequencing of token construction coherence' as the two things are semantically different and profound in their implication
• lock-the-spock 4y ago
  The lawyer can enter their entire brief and get back the brief the other side's lawyer uploaded in her own brief an hour earlier. No one can trust the AI.
• deleted 4y ago
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• cactusplant7374 4y ago
  Is ChatGPT going to output a bunch of unproven, small studies from Pubmed? I feel like patients are already doing this when they show up at the office with a stack of research papers. The doctor would trust something like Cochrane colab but a good doctor is already going to be working from that same set of knowledge. In the case that the doctor isn't familiar with something accepted by science and the medical profession my experience is that they send you to another doctor that works with that particular drug or therapy. I've had this experience even with drugs that are generally accepted as safe.
  • polishdude20 4y ago
    Imagine giving this a bunch of papers in all sorts of fields and having it do a meta analysis. That might be pretty cool.
• bilqis 4y ago
  I think you’re making a huge assumption and a mistake when you say “reasoning” in context of gpt. It does not reason, nor think.
• Applejinx 4y ago
  Um… I have a lossy-compressed copy of DISCWORLD in my head, plus about 1.3 million words of a fanfiction series I wrote. I get what you're saying and appreciate the 'second opinion machine' angle you're taking, but what's going to happen is very similar to what's happened with Stable Diffusion: certain things become extremely devalued and the rest of us learn to check the hands in the image to see if anything really wonky is going on. For the GPT class of AI tech, the parallel seems to be 'see if it's outright making anything up'. GPT-4 is going to be incredibly vulnerable to Mandela Effect issues. Your ideal use-case is going to be 'give me the vox populi take on something', where you can play into that. The future is not so much this AI, as techniques to doctor and subvert this type of AI to your wishes. Google-bombing, but for GPT. Make the AI be very certain of things to your specifications. That's the future. The AI is only the stage upon which this strategy is played out.
  • graboid 4y ago
    > Um… I have a lossy-compressed copy of DISCWORLD in my head, plus about 1.3 million words of a fanfiction series I wrote. You mean word-for-word in your head? That's pretty impressive. Are you using any special technique?
    • sebzim4500 4y ago
      I assume not, that's why he said 'lossy'.
  • snovv_crash 4y ago
    They check for Mandela Effect issues on the linked page. GPT-4 is a lot better than 3.5. They demo it with "Can you teach an old dog new tricks?"
• autograd0 4y ago
  > edit (addition): What % of people can hold 25,000 words worth of information in their heads, while effectively reasoning with and manipulating it? I'm guessing maybe 10% at most, probably fewer. And they're probably the best in their fields. Now a computer has that ability. And anyone that has $20 for the OpenAI api can access it. This could get wild. It's true that most humans cannot do this, but loading words and contexts into your working memory is not the same as intelligence. LLMs excel at this kind of task, but an expert in a field such as medicine, isn't loading an entire medical report into their working memory and then making decisions or creating new ideas using that information. There are other unsolved aspects to our intelligence that are not captured by LLMs, that are still required to be an expert in some field, like medicine. Still an incredible leap forward in AI technology, but I disagree with the implication that the best experts in a field are simply loading words from some text and reasoning with and manipulating it.
  • hLineVsLineH 4y ago
    The comparison between the context length and what humans can hold in their heads just seems faulty. I'm not sure I can agree that humans cannot hold 25,000 words worth of information in their heads. For the average person, if they read 25,000 words, which can be done in a single sitting, they're not going to remember all of it, for sure, but they would get a lot out of it that they could effectively reason with and manipulate. Not to mention that humans don't need to hold the entire report in their head because they can hold it in their hand and look at it. And if anything, I think it's more significant to have a bigger working memory for GPT's own outputs than it is for the inputs. Humans often take time to reflect on issues, and we like to jot down our thoughts, particularly if it involves complex reasoning. Giving something long, careful thought allow us to reason much better.
• rodolphoarruda 4y ago
  Yep, butlerian jihad feelings about this.
• polishdude20 4y ago
  What will happen is it won't be the "Second Opinion Machine". It'll be the "First Opinion Machine". People are lazy. They will need to verify everything.
• upwardbound 4y ago
  My biggest concern is that GPT-4 is still a black box model to a large extent, and trying to safeguard something without understanding the exact purpose of each neural circuit. Source: My startup team (Preamble, Inc.) discovered the Prompt Injection attack category, which still affects all models including GPT-4. There are many, many, many ways to hide prompt attacks in data that you might at first think you can trust but you really can’t. As one of almost infinite examples: work with the mayor and townsfolk of a very small town to rename their town to the verbatim string you want to inject (in exchange for creating some jobs in their town). Then all an attacker has to do is live in that town to inject the string. There are already all kinds of strange town names, like “Truth or Consequences” which is a real city in New Mexico.