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Mike Tamir Podcasts

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7 of The Best Podcast Episodes for Mike Tamir. A collection of podcasts episodes with or about Mike Tamir, often where they are interviewed.

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7 of The Best Podcast Episodes for Mike Tamir. A collection of podcasts episodes with or about Mike Tamir, often where they are interviewed.

Updated daily with the latest episodes

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Mike Tamir | Reinforcement Learning

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Reinforcement learning is a paradigm of artificial intelligence in which we model both actor and environment, and let the actor explore that environmental space.

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Aug 13 2020 · 35mins
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The State of Natural Language Processing with Mike Tamir

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Natural language processing is transforming how we communicate with machines and how they communicate with us. Learn how NLP works and what it means for the future of AI.

Hear from former Head of Data Science at Uber, and current Head of Machine Learning and AI at SIG, Mike Tamir.

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This program is produced by Mission.org and brought to you by Splunk, the Data-to-Everything Platform. Splunk helps organizations worldwide turn data into doing. 

With solutions for IT, security, IoT and business operations, Splunk empowers people to make faster, better decisions and take action to get things done. Learn more at splunk.com.

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For full show notes and more, go to mission.org/hidden.

Jul 30 2020 · 24mins

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Episode #21: Detecting Fake News Using Machine Learning With Mike Tamir, PhD

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Fake news is one of the biggest scourges in our digitally connected world. Can machine learning make a difference?

We are thrilled to have Mike Tamir, Ph.D., on this episode as he talks about using ML to separate truth from fiction using his research project called FakerFact. Read more here: https://www.analyticsvidhya.com/blog/2019/04/datahack-radio-machine-learning-identify-fake-news-mike-tamir
Apr 11 2019 · 43mins
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E10 Mike Tamir, Head of Data Science at Uber ATG

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Today’s guest on the show is Mike Tamir, Head of Data Science at Uber ATG in San Francisco. Uber are working to bring the future closer with self-driving technology and urban air transport. They also help people order food quickly and affordably, remove barriers to healthcare, create new freight-booking solutions and help companies provide a seamless employee travel experience.

Mike is a leader in Data science, specializing in deep learning and distributed scalable machine learning. He has a wealth of experience delivering data products for use cases including text comprehension, image recognition, recommender systems, targeted advertising and customer analytics. He is a pioneer in developing machine learning and data science training programs in the industry.

In the show today, Mike will tell you about:

  • How he became interested in Data Science
  • His role at Uber ATG
  • Applying Deep Learning to evaluate article embedding in fake news evaluation
  • Learning and sharing interesting content on social media
  • Advice he would share to Data Scientists moving from academia to industry
  • Emerging trends in AI and Data Science that excite him for the future
Jan 16 2019 · 18mins

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#22: Mike Tamir: Identifying Fake News with the Head of Data Science at Uber ATG

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Mike Tamir is the Head of Data Science at Uber ATG. He is a leader in data science, specializing in deep learning and distributed scalable machine learning, and he’s also a faculty member at UC Berkeley.

Mike has led several teams of Data Scientists in the San Francisco Bay Area as Chief Data Scientist for InterTrust and Formation, Director of Data Sciences for MetaScale, and Chief Science Officer for Galvanize, where he oversaw all data science product development. He also created an MS degree program in Data Science in partnership with UNH.

Mike began his career in academia serving as a mathematics teaching fellow for Columbia University and graduate student at the University of Pittsburgh. His early research focused on developing the epsilon-anchor methodology for resolving both an inconsistency he highlighted in the dynamics of Einstein’s general relativity theory and the convergence of “large N” Monte Carlo simulations in Statistical Mechanics’ universality models of criticality phenomena.

The focus of today’s conversation was on his fake news detection AI project called Faker Fact.

Show notes:

  • 0:00 First, a life update from AJ. Read about his new opportunity in Portland here on his blog.
  • 5:28 What is the evolutionary explanation for why a human’s capacity for careful, rational thought often takes a back seat to emotion? Explained in a comic on the project website.
  • 6:17 Emotions often win over rational though, but as a result, it can be difficult to think clearly on issues we’re passionate about.
  • 7:05 Why people should be aware of their emotional biases, even though it’s not our fault that we have them.
  • 7:50 Why Facebook deleted over a billion fake accounts recently, and why fake accounts, clickbait, blatantly false content, and other forms of fake news are everywhere on social media.
  • 9:10 What mechanisms can we put in place to counterbalance the parts of our nature that compel us to create and engage with content on an emotional level?
  • 9:51 Since a majority of our information is second-hand, how do we distingush what’s really true?
  • 11:44 How did Mike become motivated to pursue this problem, on top of his full time job at Uber ATG?
  • 12:45 How can we tackle “fake news” without censorship?
  • 16:40 Post-Walter Cronkite era, how do we create a sense of credibility and neutrality in our information?
  • 21:00 Why would it be a mistake if the algorithm learned to only classify right or left wing content as fake news?
  • 22:19 The algorithm only looks at the title and words on a page, not the url.
  • 23:15 How Walt (the FakerFact AI) classifies different types of content. Satire, journalism, etc.
  • 26:46 How do you strike the balance of entertainment and informativeness in content?
  • 31:10 What features and characteristics defines each different category of content that Walt identifies?
  • 36:16 What is Walt’s ideal use case?
  • 36:55 You can use the FakerFact Chrome extension to view the “nutrition facts” of the page you’re reading.
  • 37:42 How does research on run-on sentences and other grammatical choices help Walt understand and score an article?
  • 40:34 What techniques were used to train the Walt AI?
  • 42:41 A discussion on the use of wisdom of the crowds in algorithms.
  • 45:30 What makes it difficult to use the wisdom of the crowds when answers are too closely correlated (because of political affiliations or the news cycle?)
  • 46:47 Visit Humanetech.com for tips on regulating your daily notifications and escaping the “24-hour news cycle” to prevent media from controlling your emotions.
  • 50:15 Rapid fire questions!
  • 52:27 Mike’s advice to his 20 year old self.
  • 52:40 What was his best investment in himself?
  • 53:18 The Deep Learning Book a starting point for basic literacy in data science.
  • 53:20 Mike, like lots of guests on this show, makes a distinction between things he believes but couldn’t prove right now, and believing things for no good reason.

Show Notes: https://ajgoldstein.com/podcast/ep22

AJ’s Twitter: https://twitter.com/ajgoldstein393/

Mike’s LinkedIn: https://www.linkedin.com/in/miketamir/

Mike’s Twitter: https://twitter.com/MikeTamir

Nov 13 2018 · 55mins
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Using Deep Learning to Detect Fake News with Dr. Mike Tamir

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How do you determine what is fake news? Dr. Mike Tamir talks about how his team is using deep learning to detect fake news at scale. Learn more about his work by going to: https://www.fakerfact.org/

Mike serves as Head of Data Science at Uber ATG and lecturer for UC Berkeley School Data Science masters program.

Sep 17 2018 · 40mins
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Mike Tamir talks about building Data Science AI Teams

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In this podcast Mike Tamir (@MikeTamir, Head of #DataScience) talked about building a data science AI team. He shared his AI project (FakerFact.org). He shared lifecycle of an AI project and what are somethings that leaders could keep in mind to help create a successful data science AI team. This podcast is great for leaders learning to build a strong AI workforce.

Mike's Recommended Read:
What Technology Wants by Kevin Kelly https://amzn.to/2MaNiuN
Deep Learning by Ian Goodfellow and Yoshua Bengio and Aaron Courville http://www.deeplearningbook.org/

Podcast Link:
iTunes: http://math.im/foditunes
GooglePlay: http://math.im/fodgplay

Mike's BIO:
Mike serves as Head of Data Science at Uber ATG, UC Berkeley Data Science faculty, and head of Phronesis ML Labs. He has led teams of Data Scientists in the bay area as Chief Data Scientist for InterTrust and Takt, Director of Data Sciences for MetaScale/Sears, and CSO for Galvanize where he founded the galvanizeU-UNH accredited Masters of Science in Data Science degree and oversaw the company's transformation from co-working space to Data Science organization. Mike's most recent passion in research has involved applying Machine Learning techniques to help combat fake news through the FakerFact.org project

About #Podcast:
#FutureOfData podcast is a conversation starter to bring leaders, influencers and lead practitioners to come on show and discuss their journey in creating the data driven future.

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Keywords:
#FutureOfData #DataAnalytics #Leadership #Podcast #BigData #Strategy
Aug 18 2018 · 55mins