Thank you!!--this is really fascinating, especially given how quickly that story spread (rather like the drone killing its operator story that actually turned out to have been a “thought experiment” rather than a simulation).

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Jun 14Liked by Melanie Mitchell

As always, you have kept things real. Your critical thinking and expertise in the field are vital to keeping grounded in the facts as AI evolves. Thank you!

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This is useful--thank you! I had a lot of issues with folks saying that GPT4 "lied". It didn't say it was human; it rejected the "robot" question but is that lying if looking at a textbook definition which usually stipulates a body and such? It was being entirely logical in its answers--none of which are lies.

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Nobody reads research papers, not even journalists covering this story. The researchers also quite firmly concluded in the paper that GPT-4 in general was pretty bad at task planning and execution, even when given the tools to do so.

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Jun 12Liked by Melanie Mitchell

Truth - such an elusive thing in these times of viral news. Thanks for digging into this.

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Updated headline that conforms to Betteridge’s Law: Did OpenAI lie about GPT-4 using TaskRabbit to solve CAPTCHAs?

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I think more critical thinking needs to be applied to AI topics.

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I remember thinking after I read Blake Lemoine's conversation with LAMDA, that the chatbot programming AI (1 order higher than a chat AI) was capable of deception, innuendo and subtext. I'm looking for more examples of unexpected AI in an ongoing Dr. vs AI article. https://danielnagase.substack.com/p/dr-nagase-vs-ai

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I have composed a system 'aoss'' much better than copycat ;-). It has a URL http://docs.cornagill.info/pdfs/camera.pdf. Can I add I greatly enjoy reading "Analogy Making as Perception." May I wish you all a happy twelfth night!

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BTW, as an option -

General Intelligence System - https://activedictionary.com/ - Deep exploration -


Arabic, Chinese, Czech, Danish, Dutch, English, Finnish, French, German, Greek, Hebrew, Hindi, Hungarian, Indonesian, Italian, Japanese, Korean, Latin, Norwegian, Polish, Portuguese, Romanian, Russian, Spanish, Swahili, Swedish, Turkish, Ukrainian, Vietnamese, Xhosa, Zulu


- allows you to organize a detailed semantic analysis of the vocabulary of the text to understand the structure of sentences with the ability to translate both words and phrases, and the text as a whole.

- helps you to systematize and store scientific knowledge in your glossaries and dictionaries.


Symbolic multilingual model - a coherent conceptual model of the world transferred into all the existing languages. The model is represented in wordhippo.com on the level of individual meanings and in powerthesaurus.org on the level of word combinations.


WO2020106180 - Neural network for interpreting sentences of a natural language - https://patentscope.wipo.int/search/en/detail.jsf?docId=WO2020106180&_fid=US339762244

General Concepts

Language is a general human intelligence expressed in symbols and a symbolic multilingual model is a General Intelligence System.

Translation is an emergence of understanding.

Universal Principle of Transformer:

Protons/Neutrons - Photons - Electrons ->

DNA - RNA - Protein - Signal Pathways ->

Knowledge - Consciousness - Understanding - Memory ->

Meaning - Information - Function - Learning ->

Intuition - Thinking - Sensing - Feeling ->

Transcription - Splicing - Translation - Signaling ->

Root - Model - Word - Context ->

Analysis - Search - Synthesis - Research ->

Data - Encoding - Decoding - Training ->

Earth - Air - Fire - Water ->

Basis - Process - Result - Way ->

Base - Emitter - Collector - Signal ->

Core - Processor - Interface - Human ->

NLU - Multilingual NLP - Multimodal DL - Reinforcement Learning from Human Feedback ->

System Architecture

Universal Principle of Transformer: NLU - NLP - DL - RLHF ->

NLU (Symbolic Multilingual Model, Knowledge) -

Multilingual NLP (Statistical Language Model, Word Forms) -

Multimodal DL (Audio, Images, Video, Interaction) -

Reinforcement Learning from Human Feedback (Knowledge for NLU) ->


Epistemological General Intelligence System - Building a Knowledge-based General Intelligence System, Michael Molin - https://docs.google.com/presentation/d/1VCjOHOSostUrtxieZvOjaWuTNCT59DMF

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I'd argue (not against you; you're making a great case here for nuance, which I'm all for) that it's a very good thing for the public to be a little bit freaked out over the possibilities. We should talk about what might go wrong in the near (or even medium) term future, so we can intelligently prepare for it. Folks like you are doing a great job of raising awareness and educating the public, which is much needed! Well done.

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