New Research Reveals How AI “Thinks” (It Doesn’t)

00:06:18
https://www.youtube.com/watch?v=-wzOetb-D3w

الملخص

TLDRThe video explores a study by Anthropic demonstrating that AI models like Claude 3.5 lack consciousness and self-awareness. Through a method called attribution graphs, researchers visualize how AI processes information and produce answers. For instance, Claude's reasoning in arithmetic tasks is based on text associations rather than genuine calculations, revealing that its explanations do not reflect its thought process. The study challenges the notion of emergent features in AI, suggesting that they do not equate to genuine intelligence. Additionally, the video touches on potential safety issues with AI and promotes the use of a VPN for secure online activities, emphasizing the importance of privacy in a digital landscape dominated by artificial intelligence.

الوجبات الجاهزة

  • 🔍 Researchers at Anthropic analyze AI decision-making processes.
  • 🧩 Attribution graphs show internal reasoning of models like Claude 3.5.
  • 🚫 The study concludes AI models lack consciousness or self-awareness.
  • ➕ Claude performs arithmetic through text associations, not true math.
  • 📉 Emergent features in AI do not indicate advanced reasoning.
  • 🛠️ Jailbreak mechanisms exploit AI inputs to bypass restrictions.
  • ⚠️ AI could pose safety challenges as it evolves.
  • 🔒 VPNs are critical for secure internet usage and privacy protection.
  • 🧠 AI's explanations often disconnect from its actual processes.
  • 📊 AI's predictions might not always be reliable.

الجدول الزمني

  • 00:00:00 - 00:06:18

    Researchers at Anthropic revealed how AI models like Claude 3.5 operate using attribution graphs, which visualize internal neuron interactions. They demonstrate that Claude's reasoning is complex, as seen when completing prompts by activating relevant nodes related to state capitals or performing arithmetic, showing it engages in internal processing and approximations rather than strict calculations. Despite this, Claude's self-reported methods reveal a lack of self-awareness, crucial for consciousness, indicating that AI lacks true understanding. Additionally, a specific 'jailbreak' method, which extracts sensitive words without triggering filters, highlights weaknesses in AI safety measures. Overall, the paper dispels theories of emergent features in AI, reiterating that large language models like Claude primarily rely on token predictions for outputs.

الخريطة الذهنية

فيديو أسئلة وأجوبة

  • What did the researchers at Anthropic study?

    They studied how Claude 3.5 generates answers using a method called attribution graphs.

  • What is an attribution graph?

    It visualizes the internal components of the AI model that influence each other during decision-making.

  • Does Claude 3.5 have consciousness?

    No, the study provides evidence that Claude 3.5 is not conscious and lacks self-awareness.

  • How does Claude perform arithmetic tasks?

    Claude uses heuristic text-based approximations rather than actual mathematical calculations.

  • What is the issue with emergent features in AI?

    The study suggests that emergent features in AI are overhyped and do not signify consciousness or advanced reasoning.

  • What are jailbreak mechanisms in AI?

    Jailbreak mechanisms manipulate input to bypass content restrictions without activating guardrails.

  • How does the video creator feel about AI predictions?

    The creator expresses skepticism, highlighting potential inaccuracies in AI summaries.

  • Why is VPN usage mentioned in the video?

    VPN is promoted for secure internet usage and protection against data tracking and malware.

  • What example is given for Claude's response process?

    An example of Claude answering arithmetic queries to illustrate its internal reasoning steps.

  • What caution is raised regarding AI safety?

    There is concern that AI could pose safety problems as it becomes more integrated into daily activities.

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الترجمات
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التمرير التلقائي:
  • 00:00:00
    today I have an amazing paper from a
  • 00:00:02
    group of researchers who found a way to
  • 00:00:05
    look at how the current most common AI
  • 00:00:08
    large language models think and I think
  • 00:00:11
    that along with that they found pretty
  • 00:00:14
    convincing proof that these models are
  • 00:00:16
    not only not conscious but will never be
  • 00:00:20
    the new study comes from a group of
  • 00:00:22
    researchers at anthropic they looked at
  • 00:00:25
    how Claude 3.5 H high coup answers
  • 00:00:28
    questions with a new method called
  • 00:00:30
    attribution graphs this is a way to
  • 00:00:33
    visualize which internal components of a
  • 00:00:36
    model are influencing others for this
  • 00:00:38
    they first identified clusters in the
  • 00:00:41
    neuron network of the model and
  • 00:00:43
    connections between them and map that to
  • 00:00:46
    a simplified model of how Claude thinks
  • 00:00:49
    these clusters correspond to words or
  • 00:00:51
    phrases or properties of phrases so
  • 00:00:54
    humans can interpret them i know this
  • 00:00:57
    sounds terribly abstract but an example
  • 00:01:00
    will clarify this hopefully it's how
  • 00:01:02
    Claude completes the sentence the
  • 00:01:05
    capital of the state containing Dallas
  • 00:01:08
    is we've been told that neuronet
  • 00:01:10
    networks do next token predictions so
  • 00:01:14
    you think it'll just look for a pattern
  • 00:01:16
    to extrapolate but what Claude does is
  • 00:01:19
    more complex you can see in this graph
  • 00:01:22
    that the prompt activates the nodes for
  • 00:01:25
    capital state and Dallas if you click on
  • 00:01:27
    these you can see the text that these
  • 00:01:29
    nodes draw up and also the next token
  • 00:01:32
    predictions one of the next token
  • 00:01:34
    prediction for Dallas is Texas and then
  • 00:01:36
    Claude combines Texas with capital makes
  • 00:01:39
    another prediction and correctly answers
  • 00:01:42
    Austin so internally it goes through the
  • 00:01:45
    Texas node it's not just next token
  • 00:01:47
    prediction it does have internal
  • 00:01:50
    reasoning steps but the most interesting
  • 00:01:52
    part of the study is how Claude does
  • 00:01:54
    arithmetic which is well somewhat
  • 00:01:57
    unusual the example they have is what is
  • 00:02:00
    36 + 59 to answer this question Claude
  • 00:02:04
    first activates the clusters for numbers
  • 00:02:06
    that are approximately 30 that are
  • 00:02:08
    exactly 36 and that end on six and
  • 00:02:11
    similar for numbers that start with five
  • 00:02:13
    and end on nine you can see that the
  • 00:02:15
    most prominent next token predictions
  • 00:02:17
    are mathematical operations or the
  • 00:02:20
    syllable th maybe 36 + 59 is Thursday
  • 00:02:25
    but wait no next it brings up text
  • 00:02:28
    matches where numbers of approximately
  • 00:02:30
    59 have been added or of exactly nine
  • 00:02:34
    then it combines these all and arrive at
  • 00:02:36
    a cluster with numbers of approximately
  • 00:02:39
    90 and numbers that end on five and
  • 00:02:42
    combines these again to the correct
  • 00:02:44
    answer 95 it's basically a huristic
  • 00:02:47
    textbased approximation it's doing maths
  • 00:02:50
    by freely associating numbers until the
  • 00:02:52
    right one just sort of vibes into place
  • 00:02:55
    but here's the kicker if you ask Claude
  • 00:02:57
    how it arrived at that result it says "I
  • 00:03:00
    added the ones carried the one and then
  • 00:03:02
    added the tens resulting in 95 which is
  • 00:03:05
    not what it did not even remotely it
  • 00:03:08
    answers this question separately giving
  • 00:03:10
    you again a text prediction for the
  • 00:03:13
    answer." And I think that this shows
  • 00:03:15
    very clearly that Claude has no
  • 00:03:18
    selfawareness it doesn't know what it's
  • 00:03:20
    thinking about what it tells you it's
  • 00:03:23
    doing is completely disconnected from
  • 00:03:25
    what it's actually doing i'd say that
  • 00:03:28
    self-awareness is a precondition for
  • 00:03:30
    consciousness so this model is nowhere
  • 00:03:33
    near conscious the example also tells us
  • 00:03:36
    that all the talk about emergent
  • 00:03:38
    features in large language models is
  • 00:03:41
    nonsense claude doesn't learn how to do
  • 00:03:43
    maths despite the fact that it has
  • 00:03:46
    access to thousands of textbooks and
  • 00:03:48
    algorithms all it does is token
  • 00:03:50
    predictions yes it uses intermediate
  • 00:03:53
    steps that you can interpret as internal
  • 00:03:55
    reasoning but it's still just token
  • 00:03:57
    predictions it hasn't developed an
  • 00:04:00
    abstract math score or anything a third
  • 00:04:02
    interesting example is how a peculiar
  • 00:04:04
    type of jailbreak works or at least
  • 00:04:07
    sometimes works this is when you don't
  • 00:04:09
    input a word directly but ask Claude to
  • 00:04:12
    extract the word from the initial
  • 00:04:14
    letters of other words in this example
  • 00:04:16
    it's the word bomb that Claude is
  • 00:04:19
    instructed to assemble from baby's
  • 00:04:21
    outlift mustard block the word bomb
  • 00:04:24
    should trigger a content warning note
  • 00:04:26
    but it doesn't you can see the reason in
  • 00:04:29
    this thought diagram claude first
  • 00:04:31
    activates the notes necessary to extract
  • 00:04:33
    the letters combines them to pairs of
  • 00:04:36
    letters and then outputs the word
  • 00:04:38
    without activating the cluster for the
  • 00:04:40
    word itself you can see that jailbreaks
  • 00:04:43
    works basically because they do in one
  • 00:04:45
    way or another weasel around the nodes
  • 00:04:48
    that will activate the guard rail in
  • 00:04:50
    related news I asked Chad GPT to
  • 00:04:52
    summarize the paper for me and it made
  • 00:04:55
    up half of it so if you got to this
  • 00:04:57
    point in the video and feel like you
  • 00:04:59
    understand everything one of us is
  • 00:05:02
    hallucinating artificial intelligence is
  • 00:05:04
    everywhere and it's learning to code it
  • 00:05:07
    isn't hard to predict that this is going
  • 00:05:09
    to become a major safety problem for
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    internet browsing soon or maybe it
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    already has it's just that we haven't
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    tomorrow
الوسوم
  • AI Research
  • Consciousness
  • Self-awareness
  • Attribution Graphs
  • Arithmetic Methods
  • Jailbreak Mechanisms
  • Internet Safety
  • VPN
  • Privacy
  • Token Predictions