8 ms·

That example is wild. But I’m still pretty awed by the fact that we make similar verbal mistakes. The temporal reasoning in these models is getting better than

• tomxor 4y ago
  I'm still not convinced they are capable of temporal reasoning. I've asked it temporal questions before but without explicitly mentioning the temporal nature... the answers tend to contradict themselves if they haven't already seen the question before (even when querying general knowledge), until you point out the temporal component, even then it trips up and cannot build upon this reasoning in my tests. I suspect a large component of the interesting responses we see where it appears to be doing logical reasoning beyond language are due to statistical correlation in language because of the sheer, inhuman quantity of linguistic knowledge it's effectively encoded. The problem with this is: It can't reason about new things (because it can't actually reason - much), makes it appear smarter than it is, which IMO largest danger in applied ML today, especially to those less familiar with it's limitations, it looks like magic, and people start mandating it be used for sensitive things.
  • b33j0r 4y ago
    I can’t really argue with that, good line of thought. See, my reaction has been, “perhaps our reasoning and actions are pretty much just a biologically-encoded statistical model too, it just doesn’t _feel_ that way because of some other factor.”
    • mrtranscendence 4y ago
      When my wife tells me “you should call your mother”, I don’t think her brain assigned probabilities to “you should call your TV”, “you should call your xylophone”, “you should call your airplane”, etc, and then chose a suitable high-probability word (“mother”).
      • drdeca 4y ago
        Would the natural analogy of “tokens” be “words”, or something more like, “portion of mouth-movement”?
        • b33j0r 3y ago
          I more imagine someone speaking another language, when I break down written phonemes for tokenization purposes. As a native English speaker who grew up around code-switching Spanish speakers, I often heard speech that sounded really fast. But I was hearing “hay-un-a-al-pa-ca-per-si-gui-en-do-un tren-de-car-ga” I heard that as individual tokens, while my friends simply heard “¡There is an alpaca chasing that freight train!”
      • zamnos 4y ago
        Talk so someone with aphasia or other brain disorder, or talk to a neurologist about it, and you'll see that's not quite the case. There really does seem to be a probability of saying TV when you meant to say "your mother", it's just that the language centers of our brains don't consciously calculate your probabilities and present them to our conscious mind.
  • famouswaffles 4y ago
    >I've asked it temporal questions before but without explicitly mentioning the temporal nature... the answers tend to contradict themselves if they haven't already seen the question before GPT-3 or 4 ?
  • inciampati 4y ago
    Very insightful! I agree that the models on their own may truly be simulating awareness of certain concepts, and not "directly" modeling them. It's hard to know, but these kinds of experiments do make it clear that there are profound limits to the current systems. For instance, even if they are superhuman polyglot poets they may not have any model of "time" (ironically, the most commonly used word in many languages).
  • deleted 4y ago
    [deleted]
  • pulvinar 4y ago
    GPT-3.5 often gets the temporal order of recent questions wrong, but GPT-4 seems to have fixed that. I just tested that on both.
    • lanstin 4y ago
      gpt4 is so much better than any other released version there is no point to understanding capabilities on other models tfa's model editing tho seems like a generic capabilitity.
  • adoos 4y ago
    It's good at temporal reasoning and causality is baked in. I spent a lot of time asking gpt to tell me what is happening at the current moment of a story and it always responds with a causal representation. Where humans might tend to be more visual etc. Remember time is not real anyway we just have a bunch of codependent stuff happening so gpt gets it. What it lacks is just memory and experience and some other things to showcase the ability better. I think it's the training on code more than language that gave it logical reasoning. Humans are logical sometimes but our code really is the summit of our logic. Anyway regardless of how inherently good they are at temporal reasoning I think a secondary module explicitly for reasoning will come around soon. I believe in the brain some neurons organize into hexagons or other geometries to better capture logic, maths, etc. The LLM basically needs some rigidity in it if we don't want fuzzy outputs. And the largest danger is not people getting lazy and letting the LLM do it. That kind of danger is really long term globalization type danger. Short term we've got much more to worry.
    • wizzwizz4 4y ago
      > and it always responds with a causal representation. It responds with a language representation. It uses "causal" words because that's how the English language works: we have tenses. > I think a secondary module explicitly for reasoning will come around soon. This has been an unsolved, actively-researched problem for ages – certainly since before you were born. I doubt very much that a solution will "come around soon"; and even if it does, integrating the solution into a GPT-based system would be a second unsolved problem – though probably a much easier (and more pointless) one. If you have any ideas, I invite you to pursue them, after a quick literature search.
      • adoos 4y ago
        It describes the present moment as a series of causal events. Like event x led to y which led to z. Doesn't matter if you ask it for English or code or to not use any tenses, those conditions don't affect its baseline understanding. I might be missing your point though. For the second thing. I think from any point in history saying "coming soon" , well the current moment is the most accurate time to say it. And especially with events x and y and chat gpt right behind us. Chat gpt has basically been a problem since before I was born too, but stating as much a few months ago would just be as pessimistic as the statement you made. Only because i think the LLM hallucination problem may be simple. But it's only a hunch, based on our wetware.
  • AlecSchueler 4y ago
    Do you have examples? Not that I'm doubting you, I just want to play with this myself.
  • pmoriarty 4y ago
    Here are some simple tests I ran on ChatGPT (not GPT4): Q: "Who was elected first, President Trump or President Lincoln? Describe your reasoning." A: "President Lincoln was elected first, not President Trump. Abraham Lincoln was elected as the 16th President of the United States in 1860. He served as President from March 1861 until his assassination in April 1865. Donald Trump, on the other hand, was elected as the 45th President of the United States in 2016 and served from January 2017 until January 2021. So, based on the historical record and the order of their respective presidencies, it is clear that President Lincoln was elected first." Q: "Which happened first, Pearl Harbor or the Battle of Waterloo?" A: "The Battle of Waterloo happened first, not Pearl Harbor. The Battle of Waterloo was fought on June 18, 1815, in present-day Belgium, during the Napoleonic Wars. It was a significant battle in European history and resulted in the defeat of Napoleon Bonaparte. Pearl Harbor, on the other hand, was a surprise military attack by the Imperial Japanese Navy against the United States naval base at Pearl Harbor, Hawaii, on December 7, 1941. It led to the United States' entry into World War II. Therefore, based on the historical record, the Battle of Waterloo took place many years before the attack on Pearl Harbor." Q: "Would someone who died in the Civil War die before someone who died in World War Two? Explain your reasoning." A: "Yes, someone who died in the Civil War would have died before someone who died in World War II. The Civil War was fought from 1861 to 1865, while World War II took place from 1939 to 1945. Therefore, the Civil War occurred many years before World War II. As a result, anyone who died in the Civil War would have passed away before anyone who died in World War II. This is simply because the Civil War took place earlier in history than World War II. It's worth noting that the exact dates of death for individuals who died in either war could vary widely, depending on when and where they were serving. However, in general, the Civil War took place before World War II, so anyone who died in the former would have passed away before anyone who died in the latter." It looks like it's perfectly capable of at least simple temporal reasoning to me.
    • aix1 4y ago
      It's interesting how, having given a good answer to the last question in the penultimate paragraph, it then goes off the rails with It's worth noting that the exact dates of death for individuals who died in either war could vary widely, depending on when and where they were serving. However, in general, the Civil War took place before World War II... Here, "could vary widely" is IMO nonsense given how we're talking a 5-6 year window for either war. Also, the "in general" bit is just weird. I wonder if this is an artefact of how ChatGPT has been trained for being inoffensive and not opinionated.
  • refulgentis 4y ago
    When you explicitly instruct it that its knowledge about current affairs is dated to 2021 and inject documents and provide clear instruction about the documents are correct about current affairs, etc. etc. it works like a charm. Adds ~3-5 seconds of latency so I have a switch to turn it on and off, for now