The Turing Lectures series features influential figures from the world of data science and artificial intelligence. The latest lecture, which took place in October, was given by Dr Abeba Birhane, Senior Fellow in Trustworthy AI at Mozilla Foundation, and Adjunct Lecturer/Assistant Professor at the School of Computer Science and Statistics at Trinity College Dublin, Ireland. […]
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Why do we still learn to code? Come and join on Monday 18th for another session of Data Science Speakers Club that will be hosted in QuantumBlack, AI by McKinsey offices in Central London. In this session I will be one of the speakers on the topic "Why do we still learn to code?". This topic is inspired from a recent interview of Jensen Huang, CEO of Nvidia and his views of education in computer science. To join this session please follow this https://lnkd.in/e_H_Awgi Toastmasters International #publicspeaking #datascience #ai
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Do you have plans for May 29th? Don't miss the start of this #shortcourse! 📅 Graphs are universal data structures that can represent complex relational data. This course covers key modern graph neural networks and computational modules. 🎓 Enjoy 👉 https://bit.ly/3yvq14l
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Top 10 Princeton Tech Courses: Don't Miss Them! To those who would like to delve deeper into the programs offered by Princeton University in Computer Science, more information can be found on the university website or by contacting the Computer Science Department directly. https://shorturl.at/CF356 #Top10PrincetonTechCourses #PrincetonTechCourses #TechCoursesInPrinceton #TechCourses #PrincetonUniversity #AI #AINews #AnalyticsInsight #AnalyticsInsightMagazine
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AI and Software Engineering specialist since 1992. Did you know that AI was officially born in 1956?
A very interesting article about the birth of AI. The term “machine learning” was first used in 1959
The “birth of AI”. 1956. John McCarthy (Dartmouth), Marvin Minsky (Harvard), Nathaniel Rochester (IBM) and Claude Shannon (Bell Labs). Of course, this might not have been possible without Ada Lovelace writing the world’s first computer program. https://lnkd.in/exHwkEND
Dartmouth Summer Research Project: The Birth of Artificial Intelligence - History of Data Science
historyofdatascience.com
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From MIT Technology Review. How AI is helping historians better understand our past.
The application of modern computer science to the distant past helps draw connections across a broader swath of the historical record than would otherwise be possible, correcting distortions that come from analyzing history one document at a time. But it introduces distortions of its own, including the risk that machine learning will slip bias or outright falsifications into the historical record. All this adds up to a question for historians and others who, it’s often argued, understand the present by examining history: With machines set to play a greater role in the future, how much should we cede to them of the past? https://trib.al/Ahlpq9M
How AI is helping historians better understand our past
technologyreview.com
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Senior Director @ Verizon | MBA, M.Sc. Finance, Applied Economics, Process Improvement
“In other words, there’s a risk that artificial intelligence, from historical chatbots to models that make predictions based on historical records, will get things very wrong. Some of these mistakes are benign anachronisms: a query to Aristotle on the chatbot Character.ai about his views on women (whom he saw as inferior) returned an answer that they should “have no social media.” But others could be more consequential—especially when they’re mixed into a collection of documents too large for a historian to be checking individually, or if they’re circulated by someone with an interest in a particular interpretation of history.” Fascinating… as it becomes easier and easier to generate new and convincing content, entirely new means of guaranteeing context and governance seem more and more important…
The application of modern computer science to the distant past helps draw connections across a broader swath of the historical record than would otherwise be possible, correcting distortions that come from analyzing history one document at a time. But it introduces distortions of its own, including the risk that machine learning will slip bias or outright falsifications into the historical record. All this adds up to a question for historians and others who, it’s often argued, understand the present by examining history: With machines set to play a greater role in the future, how much should we cede to them of the past? https://trib.al/Ahlpq9M
How AI is helping historians better understand our past
technologyreview.com
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Futurist Keynote Speaker on Tech, Story, and Ethics. I distill complex trends into compelling stories that leverage change and reinvent uncertainty into opportunity.
In retrospect, this interview with Geordie Rose I recorded in 2013, has turned out to be prophetic: Geordie Rose: Machine Learning is Progressing Faster Than You Think https://lnkd.in/dkTVTwB
D-Wave CTO Geordie Rose: Machine Learning is Progressing Faster Than You Think
https://www.singularityweblog.com
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The application of modern computer science to the distant past helps draw connections across a broader swath of the historical record than would otherwise be possible, correcting distortions that come from analyzing history one document at a time. But it introduces distortions of its own, including the risk that machine learning will slip bias or outright falsifications into the historical record. All this adds up to a question for historians and others who, it’s often argued, understand the present by examining history: With machines set to play a greater role in the future, how much should we cede to them of the past? https://trib.al/Ahlpq9M
How AI is helping historians better understand our past
technologyreview.com
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Mark your calendars for “Guidance on the Future of Computer Science Education in an Age of AI!” This August 14 webinar addresses common misconceptions about AI in computer science education and offers a balanced perspective on critical issues. Learn more: https://buff.ly/4djMO2g
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