We talked with Dermot Turing about his presentation: Alan Turing, Artificial Intelligence, and Stamp Collecting (More)

Jordan Etem: Driving Innovation (More)

Building reliable, robust software is hard. It is even harder when we move from deterministic domains (such as balancing a checkbook) to uncertain domains (such as recognizing speech or objects in an image). The field of machine learning allows us to use data to build systems in these uncertain domains, but the field mostly concentrates on accuracy of results. Peter Norvig looks at techniques for achieving reliability (and some of the other -ilities). (More)

Bringing together thought leaders in large-scale data analysis and technology to transform the way we diagnose, treat and prevent disease. Visit our website at http://bigdata.stanford.edu/. (More)

What do the classrooms of the future look like? Aditi Avasthi takes us on a brief tour of how AI is can help identify traits in a student that a traditional student-teacher pair cannot, and provide tailor-made education. (More)

The annual Biology Week debate, held at the The Royal Institution, London. (More)

Professor Björn Schuller charts the history of human-centred AI focusing on aspects of artificial, emotional and health intelligence. #ImperialInaugurals
Join the event on Microsoft Teams: https://bit.ly/IL-BjoernSchuller (More)

While it’s important to consider the diversity of your dataset and the performance of your model across different demographic group, this is just a narrow slice of the issues we need to consider related to bias and fairness. Using machine learning for medicine as a case study, I’ll illustrate some of the broader considerations related to bias, power, and participation that all data scientists need to take into account. (More)

This talk was presented at PyBay2018 – the Bay Area local Python conference. See pybay.com for more details about PyBay and click SHOW MORE for more information about this talk. (More)

Machinoia, Machine of Multiple Me: Integrating with Past,Future and Alternative Selves
Pat Pataranutaporn, Valdemar Danry, Pattie Maes (More)

My talk delivered at the conference ‘The Digital World: AI’ organised by BSI in London, 27th February 2020. The full video with all the talks posted by BSI can be seen here: https://youtu.be/bDJyLur5_eI (More)


Discuss this talk on the Effective Altruism Forum: https://forum.effectivealtruism.org/posts/6uiXHHJQEtMaYQrti/max-tegmark-effective-altruism-existential-risk-and (More)

Do we live in one of many universes? On this episode of StarTalk, Neil deGrasse Tyson and comic co-host Chuck Nice investigate the theory of the multiverse with physicist and author, Prof. Max Tegmark. (More)

Artificial Intelligence (AI) and robotics in Canada, Deep Learning, Machine Learning — Bloomberg Businessweek presents an exclusive premiere of the latest episode of Hello World, the tech-travel show hosted by journalist and best-selling author Ashlee Vance and watched by millions of people around the globe. (More)

How to solve a Rubik’s Cube? You will need the GAN I Smart Rubik’s Cube, your iPhone and robot.
Moreover, this robot can solve the Rubik’s Cube in record time, which is faster than the world record. (More)

#lgrobot #lg #cloi #hollywood #youngactress #aglayasemenova #lgcloi #newrobot #украинскаяактриса #голливуд #актриса (More)

Deep learning is a revolutionary technique for discovering patterns from data. We’ll see how this technology works and what it offers us for computer graphics. Attendees learn how to use these tools to power their own creative and practical investigations and applications. (More)

Help fund future projects: https://www.patreon.com/3blue1brown
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Special thanks to these supporters: http://3b1b.co/nn3-thanks (More)

What’s actually happening to a neural network as it learns?
Next chapter: https://youtu.be/tIeHLnjs5U8
Help fund future projects: https://www.patreon.com/3blue1brown
An equally valuable form of support is to simply share some of the videos.
Special thanks to these supporters: http://3b1b.co/nn3-thanks (More)

Enhancing Photorealism Enhancement
Stephan R. Richter, Hassan Abu AlHaija, and Vladlen Koltun (More)

This is a Q&A excerpt on the topic of AI from a lecture by Richard Feynman from September 26th, 1985. (More)

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Intelligent Technology Smart Farming Automatic Cow Feeding, Modern Cow Milking Automatic Machine
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– This video is purely fan-made, if you (owners) want to remove this video, please contact me through the YouTube private messaging system. We will respectfully remove it. (More)

Mini Intelligent ATM Machine Unboxing & Testing – Chatpat toy tv
Buy Link: https://amzn.to/2KBwt0X
KITI KITS Money Saving Bank with Electronic Lock with ATM Piggy Bank (More)

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Bad Intelligent Machine Dog Chases Panda | Panda’s Magic Tie | Magical Chinese Characters | BabyBus (More)

A word embedding is a learned representation for text where words that have the same meaning have a similar representation. It is this approach to representing words and documents that may be considered one of the key breakthroughs of deep learning on challenging natural language processing problems. (More)

Take an adapted version of this course as part of the Stanford Artificial Intelligence Professional Program. Learn more at: https://stanford.io/2rf9OO3 (More)

An overview of the gpt-3 machine learning model, why everyone should understand it, and why some (including its creator, open AI) think it’s dangerous. (More)

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Talk by Ekaterina Kochmar, University of Cambridge, at the Cambridge Coding Academy Data Science Bootcamp: https://cambridgecoding.com/datascience-bootcamp (More)

🔥 Python Certification Training: https://www.edureka.co/data-science-python-certification-course
This Edureka video on ‘If Else In Python’ will help you understand how you can use a conditional if and else statements in python for decision making with concepts like shorthand if and else, nested if else etc. Following are the topics discussed:
0:52 – What Are Python Conditions?
1:45 – What Is If And If Else In Python?
3:08 – Syntax For If Else In Python
9:58 – Shorthand If Else
12:13 – Use Case – Nested If Else (More)

Learn about the latest product and platform innovations at Google in a Keynote led by Sundar Pichai. (More)

In his talk, Professor Dhar answers the question “when do we trust machines?” by walking us through various situations in our everyday lives — investing, playing sports, riding in driverless cars, and using social media platforms — to encourage us to question the faith we put in technology. In answer to his question, Dhar utilizes a “trust matrix in order to illustrate how the answer depends on two key elements: how often machines make mistakes and the costs or consequences of these mistakes. Vasant Dhar is a professor at the Stern School of Business and the Center for Data Science at New York University. He is Editor-in-Chief of the journal Big Data, and the founder of SCT Capital Management, a machine-learning-based hedge fund in New York City. Dhar’s central research question asks when we should trust AI machines that learn from data. His research has addressed this question in a number of areas including financial markets, social media and healthcare. Dhar has authored over 100 research papers, as well as articles for publications such as the Financial Times, Wall Street Journal, Forbes, Wired, and the Harvard Business Review. He has appeared on CNBC, Bloomberg TV, and National Public Radio. He was recently named as one of the top 12 people to know in hedge funds and top 20 data scientists in Finance and Banking by efinancialcareers.com. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at https://www.ted.com/tedx (More)

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