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=== 'Intelligent' can conjure & ask questions ===
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|keywords=ChatGPT, artificial, intelligence, machine, learning, GPT-4, GPT-5, NLP, NLG, NLC, NLU, models, data, singularity, moonshot, Sentience, AGI, Emergence, Moonshot, Explainable, TensorFlow, Google, Nvidia, Microsoft, Azure, Amazon, AWS, Hugging Face, OpenAI, Tensorflow, OpenAI, Google, Nvidia, Microsoft, Azure, Amazon, AWS, Meta, LLM, metaverse, assistants, agents, digital twin, IoT, Transhumanism, Immersive Reality, Generative AI, Conversational AI, Perplexity, Bing, You, Bard, Ernie, prompt Engineering LangChain, Video/Image, Vision, End-to-End Speech, Synthesize Speech, Speech Recognition, Stanford, MIT |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools 
  
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=== 'Intelligent' able to 'learn' the wide world web ===
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[https://www.youtube.com/results?search_query=moonshot+moon+shot+ai YouTube search...]
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[https://www.quora.com/search?q=ai%20moonshot%20moon ... Quora search]
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[https://www.google.com/search?q=moonshot+moon+shot+ai ...Google search]
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[https://news.google.com/search?q=ai+moonshot+moon+shot+ai ...Google News]
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[https://www.bing.com/news/search?q=moonshot+moon+shot+ai&qft=interval%3d%228%22 ...Bing News]
  
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* [[Artificial General Intelligence (AGI) to Singularity]] ... [[Inside Out - Curious Optimistic Reasoning| Curious Reasoning]] ... [[Emergence]] ... [[Moonshots]] ... [[Explainable / Interpretable AI|Explainable AI]] ...  [[Algorithm Administration#Automated Learning|Automated Learning]]
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* [[Large Language Model (LLM)]] ... [[Large Language Model (LLM)#Multimodal|Multimodal]] ... [[Foundation Models (FM)]] ... [[Generative Pre-trained Transformer (GPT)|Generative Pre-trained]] ... [[Transformer]] ... [[GPT-4]] ... [[GPT-5]] ... [[Attention]] ... [[Generative Adversarial Network (GAN)|GAN]] ... [[Bidirectional Encoder Representations from Transformers (BERT)|BERT]]
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* [[In-Context Learning (ICL)]] ... [[Context]] ... [[Out-of-Distribution (OOD) Generalization]]
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* [[Immersive Reality]] ... [[Metaverse]] ... [[Omniverse]] ... [[Transhumanism]] ... [[Religion]]
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* [[Telecommunications]] ... [[Computer Networks]] ... [[Telecommunications#5G|5G]] ... [[Satellite#Satellite Communications|Satellite Communications]] ... [[Quantum Communications]] ... [[Agents#Communication | Communication Agents]] ... [[Smart Cities]] ...  [[Digital Twin]] ... [[Internet of Things (IoT)]]
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* [[Time]] ... [[Time#Positioning, Navigation and Timing (PNT)|PNT]] ... [[Time#Global Positioning System (GPS)|GPS]] ... [[Causation vs. Correlation#Retrocausality| Retrocausality]] ... [[Quantum#Delayed Choice Quantum Eraser|Delayed Choice Quantum Eraser]] ... [[Quantum]]
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* [[Creatives]] ... [[History of Artificial Intelligence (AI)]] ... [[Neural Network#Neural Network History|Neural Network History]] ... [[Rewriting Past, Shape our Future]] ... [[Archaeology]] ... [[Paleontology]]
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* [[Humor]]
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** [https://www.vice.com/en/article/z43nke/joke-telling-robots-are-the-final-frontier-of-artificial-intelligence Joke-Telling Robots Are the Final Frontier of Artificial Intelligence | Becky Ferreira - Vice] ... [[Humor]] requires self-awareness, spontaneity, linguistic sophistication, and empathy. Not easy for a [[Robotics | robot]].
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*[https://medium.com/applied-data-science/how-to-build-your-own-alphazero-ai-using-python-and-keras-7f664945c188 How to build your own AlphaZero AI using Python and Keras]
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* [[What is Artificial Intelligence (AI)? | Artificial Intelligence (AI)]] ... [[Generative AI]] ... [[Machine Learning (ML)]] ... [[Deep Learning]] ... [[Neural Network]] ... [[Reinforcement Learning (RL)|Reinforcement]] ... [[Learning Techniques]]
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* [[Conversational AI]] ... [[ChatGPT]] | [[OpenAI]] ... [[Bing/Copilot]] | [[Microsoft]] ... [[Gemini]] | [[Google]] ... [[Claude]] | [[Anthropic]] ... [[Perplexity]] ... [[You]] ... [[phind]] ... [[Ernie]] | [[Baidu]]
  
=== Autonomous vehicles ===
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The “Sputnik” moment for [[Government Services#China|China]] came a year ago when a Google computer program, AlphaGo, beat the world’s top master of the ancient board game of Go. Now, [[Government Services#China|China]] is racing to become the world leader in artificial-intelligence. In [[context]], what do you think would be a "Moonshot" response?
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<hr><center>
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<b><i>The 'moonshot' milestones along the road to Artificial General Intelligence (AGI)</i></b>
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</center><hr>
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In the [[context]] of AI, a "moonshot" refers to a project or goal that aims to achieve a major breakthrough in artificial intelligence that has the potential to transform society or address significant global challenges. The term "moonshot"  is derived from the Apollo program, which was a series of space missions undertaken by the United States in the 1960s and early 1970s with the goal of landing humans on the Moon. The Apollo program was considered a moonshot because it represented a major technological and engineering challenge that required significant innovation and investment.
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== Can Conjure & Ask Questions ==
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[https://www.youtube.com/results?search_query=ai+ask+question+cognitive+computing+general+artificial+intelligence Youtube search...]
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[https://www.google.com/search?q=ai+ask+question+cognitive+computing+general+artificial+intelligence ...Google search]
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* [[Inside Out - Curious Optimistic Reasoning]]
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* [https://www.youtube.com/results?search_query=smartest+animals Animals]
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* [https://www.youtube.com/results?search_query=general+artificial+intelligence General Intelligence]
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* [https://www.youtube.com/results?search_query=consciousness+artificial+intelligence Consciousness]
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<youtube>gtThWYWOyFQ</youtube>
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<youtube>L4QYUEz0mI8</youtube>
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<youtube>8zYp4yH4PoQ</youtube>
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<youtube>xBKEOVDBqoQ</youtube>
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== Able to Predict the Future ==
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[https://www.youtube.com/results?search_query=predict+future+artificial+intelligence Youtube search...]
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[https://www.google.com/search?q=predict+future+artificial+intelligence ...Google search]
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<youtube>Wf1UFz2jAJU</youtube>
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<youtube>VrIMLt__CJc</youtube>
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<youtube>5olCp-JEzrI</youtube>
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<youtube>8z0Mrbj34uY</youtube>
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== Able to 'Learn' the Wide World Web ==
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[https://www.youtube.com/results?search_query=learn+wide+world+web+artificial+intelligence Youtube search...]
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[https://www.google.com/search?q=learn+wide+world+web+artificial+intelligence ...Google search]
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<youtube>_V8MGzvJEXY</youtube>
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<youtube>XZmGGAbHqa0</youtube>
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== Autonomous Vehicles ==
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[https://www.youtube.com/results?search_query=Autonomous+vehicles+self+driving+autocomplete+artificial+intelligence Youtube search...]
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[https://www.google.com/search?q=Autonomous+vehicles+self+driving+autocomplete+artificial+intelligence ...Google search]
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* [[Transportation (Autonomous Vehicles)]]
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<youtube>yt015gM-ync</youtube>
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<youtube>1L0TKZQcUtA</youtube>
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<youtube>_Zd1ByhigPU</youtube>
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<youtube>Oy8gxRD_BUE</youtube>
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= <span id="Meeting the Winograd Schema Challenge (WSC)"></span>Meeting the Winograd Schema Challenge (WSC) =
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[https://www.youtube.com/results?search_query=Winograd+Schema+Challenge+WSC+turing+test+machine+artificial+intelligence+ai Youtube search...]
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[https://www.google.com/search?q=Winograd+Schema+Challenge+WSC+turing+test+machine+artificial+intelligence+ai ...Google search]
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The Winograd Schema Challenge (WSC) is a natural language understanding task proposed as an alternative to the Turing test in 2011. In this work we attempt to solve WSC problems by reasoning with additional knowledge. By using an approach built on top of graph-subgraph isomorphism encoded using Answer Set Programming (ASP) we were able to handle 240 out of 291 WSC problems. The ASP encoding allows us to add additional constraints in an elaboration tolerant manner. In the process we present a graph based representation of WSC problems as well as relevant commonsense knowledge. [https://www.cambridge.org/core/journals/theory-and-practice-of-logic-programming/article/using-answer-set-programming-for-commonsense-reasoning-in-the-winograd-schema-challenge/5CB1C6B33E940A98E086F2EBECA24A09 "Using Answer Set Programming for Commonsense Reasoning in the Winograd Schema Challenge" | Arpit Sharma]
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<youtube>m3vIEKWrP9Q</youtube>
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<b>The Sentences Computers Can't Understand, But Humans Can
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</b><br>The Winograd schema is a language test for intelligent computers. So far, they're not doing well.
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<youtube>nZxHF-ndvFo</youtube>
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<b>The Winograd Schema Challenge - Models of Reasoning
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</b><br>This video corresponds to the online presentation assingment of the subject Models of Reasoning. Authors: Carla Fernández González and Teresa Grau Mateo.  Taking the name from Terry Winograd, who first presented an example following the schema [13], Levesque, Davis and Morgenstern created Winograd Schemas as an alternative to the Turing Test and started a competition to encourage researchers to work in this area of commonsense reasoning.
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<youtube>GHyDAs2xOos</youtube>
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<b>Improving Winograd Schemas Using Ambiguous [[context]]s
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</b><br>I created this presentation for a graduate class at NYU. It also serves as a gentle introduction to Winograd Schemas.  There's one error: at 7:35 I say "she's the receiver of the thanks" when I mean "receiver of the help."  Also, I mean no ill will to Tom Scott.  He's a great computer enthusiast and content creator.
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<youtube>Ey_trzJPp_I</youtube>
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<b>ICLP19 paper "Using ASP for Commonsense Reasoning in the Winograd Schema Challenge"
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</b><br>This video is a presentation which provides an overview of the ICLP 2019 conference paper titled [https://www.cambridge.org/core/journals/theory-and-practice-of-logic-programming/article/using-answer-set-programming-for-commonsense-reasoning-in-the-winograd-schema-challenge/5CB1C6B33E940A98E086F2EBECA24A09 "Using Answer Set Programming for Commonsense Reasoning in the Winograd Schema Challenge"]
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Latest revision as of 19:44, 19 March 2024

YouTube search... ... Quora search ...Google search ...Google News ...Bing News


The “Sputnik” moment for China came a year ago when a Google computer program, AlphaGo, beat the world’s top master of the ancient board game of Go. Now, China is racing to become the world leader in artificial-intelligence. In context, what do you think would be a "Moonshot" response?



The 'moonshot' milestones along the road to Artificial General Intelligence (AGI)



In the context of AI, a "moonshot" refers to a project or goal that aims to achieve a major breakthrough in artificial intelligence that has the potential to transform society or address significant global challenges. The term "moonshot" is derived from the Apollo program, which was a series of space missions undertaken by the United States in the 1960s and early 1970s with the goal of landing humans on the Moon. The Apollo program was considered a moonshot because it represented a major technological and engineering challenge that required significant innovation and investment.


Can Conjure & Ask Questions

Youtube search... ...Google search

Able to Predict the Future

Youtube search... ...Google search

Able to 'Learn' the Wide World Web

Youtube search... ...Google search

Autonomous Vehicles

Youtube search... ...Google search


Meeting the Winograd Schema Challenge (WSC)

Youtube search... ...Google search

The Winograd Schema Challenge (WSC) is a natural language understanding task proposed as an alternative to the Turing test in 2011. In this work we attempt to solve WSC problems by reasoning with additional knowledge. By using an approach built on top of graph-subgraph isomorphism encoded using Answer Set Programming (ASP) we were able to handle 240 out of 291 WSC problems. The ASP encoding allows us to add additional constraints in an elaboration tolerant manner. In the process we present a graph based representation of WSC problems as well as relevant commonsense knowledge. "Using Answer Set Programming for Commonsense Reasoning in the Winograd Schema Challenge" | Arpit Sharma

The Sentences Computers Can't Understand, But Humans Can
The Winograd schema is a language test for intelligent computers. So far, they're not doing well.

The Winograd Schema Challenge - Models of Reasoning
This video corresponds to the online presentation assingment of the subject Models of Reasoning. Authors: Carla Fernández González and Teresa Grau Mateo. Taking the name from Terry Winograd, who first presented an example following the schema [13], Levesque, Davis and Morgenstern created Winograd Schemas as an alternative to the Turing Test and started a competition to encourage researchers to work in this area of commonsense reasoning.

Improving Winograd Schemas Using Ambiguous contexts
I created this presentation for a graduate class at NYU. It also serves as a gentle introduction to Winograd Schemas. There's one error: at 7:35 I say "she's the receiver of the thanks" when I mean "receiver of the help." Also, I mean no ill will to Tom Scott. He's a great computer enthusiast and content creator.

ICLP19 paper "Using ASP for Commonsense Reasoning in the Winograd Schema Challenge"
This video is a presentation which provides an overview of the ICLP 2019 conference paper titled "Using Answer Set Programming for Commonsense Reasoning in the Winograd Schema Challenge"