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| # AI Core Lecture list | ||
| ---------------------------------------------------------- | ||
| # AI Introduction and Future | ||
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| ## 1. [The incredible inventions of intuitive AI](https://www.youtube.com/watch?v=aR5N2Jl8k14) | ||
| - Speaker: Maurice Conti(Designer, futurist) | ||
| - 15:23 | ||
| - Intuitive AI 발전에 대한 전반적 내용입니다. | ||
| - What do you get when you give a design tool a digital nervous system? Computers that improve our ability to think and imagine, and robotic systems that come up with (and build) radical new designs for bridges, cars, drones and much more -- all by themselves. Take a tour of the Augmented Age | ||
| - 영문 + 한글 자막 지원 | ||
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| ## 2. [How AI can enhance our memory, work and social lives](https://www.ted.com/talks/tom_gruber_how_ai_can_enhance_our_memory_work_and_social_lives#t-248994) | ||
| - Speaker: Tom Gruber, Co-creater of Siri | ||
| - 9:46 | ||
| - 기억이라는 관점에서 인공지능이 우리에게 어떻게 도움을 주고 어떻게 발전되어 나갈 것인지에 대한 내용입니다. | ||
| - How smart can our machines make us? Tom Gruber, co-creator of Siri, wants to make "humanistic AI" that augments and collaborates with us instead of competing with (or replacing) us. He shares his vision for a future where AI helps us achieve superhuman performance in perception, creativity and cognitive function -- from turbocharging our design skills to helping us remember everything we've ever read and the name of everyone we've ever met. "We are in the middle of a renaissance in AI," Gruber says. "Every time a machine gets smarter, we get smarter." | ||
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| ## 3. [What AI is - and isn't](https://www.ted.com/talks/sebastian_thrun_and_chris_anderson_the_new_generation_of_computers_is_programming_itself) | ||
| - Speaker: Sebastian Thrun · Educator, entrepreneur | ||
| - 24:22 | ||
| - 인공지능에 대한 전반적인 설명과 예시를 들고 있습니다. | ||
| - Sebastian Thrun discusses the basic concepts of AI, the progress of deep learning, why we shouldn’t fear AI, and how society and businesses can benefit when machines do most of the everyday tedious work. | ||
| - 영문 + 한글 자막 지원 | ||
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| ## 4. [Artificial Intelligence: Mankind's Last Invention](https://www.youtube.com/watch?v=Pls_q2aQzHg) | ||
| - Aperture | ||
| - 20:21 | ||
| - Artificial Intelligence: Mankind's Last Invention - Technological Singularity Explained. As artificial intelligence becomes more and more advance how will it impact mankind’s future? AI could be a great thing or a very bad thing. It is interesting to hear what great minds have to say about artificial intelligence. | ||
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| ## 5. [Exploring trends that are changing the Future](https://www.youtube.com/watch?v=21EiKfQYZXc) | ||
| - Speaker: Andrew Ng | ||
| - 1:27:43 | ||
| - AI Artificial Intelligence is the New Electricity. He spoke to the Stanford Graduate School of Business community as part of a series presented by the Stanford MSx Program. | ||
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| -------------------------------- | ||
| # Oject Recognitions | ||
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| ## 1. [How we teach computers to understand pictures](https://www.ted.com/talks/fei_fei_li_how_we_re_teaching_computers_to_understand_pictures#t-1816) | ||
| - Speaker: Fei Fei Li (Computer scientist) | ||
| - 17:59 | ||
| - When a very young child looks at a picture, she can identify simple elements: "cat," "book," "chair." Now, computers are getting smart enough to do that too. What's next? In a thrilling talk, computer vision expert Fei-Fei Li describes the state of the art — including the database of 15 million photos her team built to "teach" a computer to understand pictures — and the key insights yet to come. | ||
| - 영문 + 한글 자막 지원 | ||
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| ## 2. [How computers learn to recognize objects instantly](https://www.youtube.com/watch?v=Cgxsv1riJhIh) | ||
| - Speaker: Joseph Redmon(Computer scientist) | ||
| - 7:37 | ||
| - 내용 : YOLO (You Only Look Once) system을 이용하여 실제 영상 처리하는 것을 보여주면서 강의 하는 점에서 영상 처리 + classifier + 신경망 사용을 볼 수 있습니다. | ||
| - Ten years ago, researchers thought that getting a computer to tell the difference between a cat and a dog would be almost impossible. Today, computer vision systems do it with greater than 99 percent accuracy. How? Joseph Redmon works on the YOLO (You Only Look Once) system, an open-source method of object detection that can identify objects in images and video -- from zebras to stop signs -- with lightning-quick speed. In a remarkable live demo, Redmon shows off this important step forward for applications like self-driving cars, robotics and even cancer detection. | ||
| - 영문 + 한글 자막 지원 | ||
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| ## 3. [How a Driverless Car sees the Road](https://www.ted.com/talks/chris_urmson_how_a_driverless_car_sees_the_road?language=ko) | ||
| - Speaker: Chris Urimson, Former head of Googl's driverless car program | ||
| - 15:30 | ||
| - 내용 : 통계적으로, 가장 믿을 수 없는 자동차의 일부는 운전자입니다. 크리스 엄슨은 구글의 무인자동차 프로젝트를 이끌며 운전자 좌석을 빈 공간으로 만드는데 공헌하고 있습니다. 그는 무인자동차의 현재와 작동방식에 대해서 보여줍니다. 그의 강연은 우리에게 무인자동차의 미래에 대한 결정을 생각하게 합니다. | ||
| - Chris Urmson, former head of Google’s driverless car program, gives us the lowdown on how autonomous vehicles take decisions in real-time about what to do next. | ||
| - 영문 + 한글 자막 지원 | ||
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| ------------------------ | ||
| # AI applications | ||
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| ## 1. [How ai is making it easier to diagnose disease](https://www.youtube.com/watch?v=mhEYvrFOP88) | ||
| - Speaker: Pratik Shah · Medical technologist | ||
| - 11:19 | ||
| - 인공지능을 활용해서 질병을 발견하는 방법. | ||
| - Today's AI algorithms require tens of thousands of expensive medical images to detect a patient's disease. What if we could drastically reduce the amount of data needed to train an AI, making diagnoses low-cost and more effective? TED Fellow Pratik Shah is working on a clever system to do just that. Using an unorthodox AI approach, Shah has developed a technology that requires as few as 50 images to develop a working algorithm -- and can even use photos taken on doctors' cell phones to provide a diagnosis. Learn more about how this new way to analyze medical information could lead to earlier detection of life-threatening illnesses and bring AI-assisted diagnosis to more health care settings worldwide. | ||
| - 영문 + 한글 자막 지원 | ||
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| ## 2. [How we can teach computers to make sense of our emotions](https://www.youtube.com/watch?v=hs-YuHv0vUk) | ||
| - Speaker: Raphael Arar · Designer, researcher | ||
| - 11:19 | ||
| - How can we make AI that people actually want to interact with? Raphael Arar suggests we start by making art. He shares interactive projects that help AI explore complex ideas like nostalgia, intuition and conversation -- all working towards the goal of making our future technology just as much human as it is artificial. | ||
| - 영문 + 한글 자막 지원 | ||
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| ## 3. [Can a robot pass a university entrance exam?](https://www.ted.com/talks/noriko_arai_can_a_robot_pass_a_university_entrance_exam/transcript) | ||
| - Speaker: Noriko Arai (AI expert) | ||
| - 13:37 | ||
| - AI가 어떻게 문제를 해결하는지 예시로 AI에 대해서 설명합니다. | ||
| - AI expert Noriko Arai and her team created Todai Robot, whose sole purpose is to pass the entrance exam for the University of Tokyo, the most prestigious university in Japan. So far it hasn’t succeeded in getting in, even though it scores better than 80 percent of its human competitors. | ||
| - 영문 + 한글 자막 지원 | ||
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| ## 4. [The basics of AI for Business](https://www.ted.com/talks/philipp_gerbert_your_business_needs_ai_and_here_s_why) | ||
| - Speaker: Philipp Gerbert | ||
| - 12:29 | ||
| - Philipp Gerbert dispels the myth of AI as a complex and mysterious tool for business. In reality, he says, even those of us outside Silicon Valley can have an intimate understanding of AI and put it to work today. Gerbert walks us through the ABC's of AI and what it can mean for your organization. | ||
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| ------------------------------------------------------------ | ||
| # Highly Technical Lectures | ||
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| # Algorithms | ||
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| 인공지능(기계학습)을 핵심을 이루고 있는 인공신경망의 기본 알고리즘들을 가장 쉽게 설명하는 강의입니다. | ||
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| ## 1장 [신경망이란 무엇인가?](https://www.youtube.com/watch?v=aircAruvnKk) | ||
| - 3Blue1Brown | ||
| - 19:13 | ||
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| ## 2장 [경사하강, 신경 네트워크가 학습하는 방법](https://www.youtube.com/watch?v=IHZwWFHWa-w&list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi&index=2) | ||
| - 3Blue1Brown | ||
| - 21:01 | ||
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| ## 3장 [What is backpropagation really doing?](https://www.youtube.com/watch?v=Ilg3gGewQ5U&index=3&list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi) | ||
| - 3Blue1Brown | ||
| - 13:54 | ||
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| ## 4장 [backpropagation calculus](https://www.youtube.com/watch?v=tIeHLnjs5U8&list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi&index=4) | ||
| - This one is a bit more symbol heavy, and that's actually the point. The goal here is to represent in somewhat more formal terms the intuition for how backpropagation works in part 3 of the series, hopefully providing some connection between that video and other texts/code that you come across later. | ||
| - 3Blue1Brown | ||
| - 10:18 | ||
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| ---------------------------------------------------- | ||
| # Deep learning | ||
| 본 과목에서는 다루지 않는 심층학습에 관련된 강의들입니다. | ||
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| ## [Tensorflow and deep learning](https://www.youtube.com/watch?v=vq2nnJ4g6N0) | ||
| - 3Blue1Brown | ||
| - 10:17 | ||
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| ---------------------------- | ||
| _One thing I know, I was blind but now I see. John 9:25_ |