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Should We Worry About Artificial Intelligence (AI)? - Coding Dojo Blog

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Humanity at a Crossroads--Artificial Intelligence is one of the most intriguing topics today, filled with various arguments and views on whether it's a blessing or a threat to humanity. We might be at the crossroads, but what if AI itself is already crossing the line? If we look at "I, Robot," a sci-fi film that takes place in Chicago circa 2035, highly intelligent robots powered by artificial intelligence fill public service positions and have taken over all the menial jobs, including garbage collection, cooking, and even dog walking throughout the world. The movie came out in 2004 starring Will Smith as Detective Del Spooner who eventually discovers a conspiracy in which AI-powered robots may enslave and hurt the human race. Stephen Hawking, famed physicist, also once said: "Success in creating effective AI could be the biggest event in the history of our civilization. So we can't know for sure if we'll be infinitely helped by AI, or ignored by it and side-lined, or conceivably destroyed by it."


Sentient? Google LaMDA feels like a typical chat bot

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LaMDA is a software program that runs on Google TPU chips. Like the classic brain in a jar, some would argue the code and the circuits don't form a sentient entity because none of it engages in life. Google engineer Blake Lemoine caused controversy last week by releasing a document that he had circulated to colleagues in which Lemoine urged Google to consider that one of its deep learning AI programs, LaMDA, might be "sentient." Google replied by officially denying the likelihood of sentience in the program, and Lemoine was put on paid administrative leave by Google, according to an interview with Lemoine by Nitasha Tiku of The Washington Post. There has been a flood of responses to Lemoine's claim by AI scholars. University of Washington linguistics professor Emily Bender, a frequent critic of AI hype, told Tiku that Lemoine is projecting anthropocentric views onto the technology. "We now have machines that can mindlessly generate words, but we haven't learned how to stop imagining a mind behind them," Bender told Tiku. In an interview with MSNBC's Zeeshan Aleem, AI scholar Melanie Mitchell, Davis Professor of Complexity at the Santa Fe Institute, observed that the concept of sentience has not been rigorously explored. Mitchell concludes the program is not sentient, however, "by any reasonable meaning of that term, and the reason is because I understand pretty well how the system works."


Sentient? Google LaMDA feels like a typical chat bot

ZDNet

LaMDA is a software program that runs on Google TPU chips. Like the classic brain in a jar, some would argue the code and the circuits don't form a sentient entity because none of it engages in life. Google engineer Blake Lemoine caused controversy last week by releasing a document that he had circulated to colleagues in which Lemoine urged Google to consider that one of its deep learning AI programs, LaMDA, might be "sentient." Google replied by officially denying the likelihood of sentience in the program, and Lemoine was put on paid administrative leave by Google, according to an interview with Lemoine by Nitasha Tiku of The Washington Post. There has been a flood of responses to Lemoine's claim by AI scholars. University of Washington linguistics professor Emily Bender, a frequent critic of AI hype, told Tiku that Lemoine is projecting anthropocentric views onto the technology. "We now have machines that can mindlessly generate words, but we haven't learned how to stop imagining a mind behind them," Bender told Tiku. In an interview with MSNBC's Zeeshan Aleem, AI scholar Melanie Mitchell, Davis Professor of Complexity at the Santa Fe Institute, observed that the concept of sentience has not been rigorously explored. Mitchell concludes the program is not sentient, however, "by any reasonable meaning of that term, and the reason is because I understand pretty well how the system works."


What is generative artificial intelligence (AI)?

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We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - 28. Join AI and data leaders for insightful talks and exciting networking opportunities. Many artificial intelligence (AI) algorithms are used to classify, organize or reason about data. Generative algorithms create data using models of the world to synthesize images, sounds and videos that often look increasingly realistic. The algorithms begin with models of what a world must be like and then they create a simulated world that fits the model. Generative AIs are frequently found in various content creation roles.


6 Best Programming Languages for AI

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Originally published on Towards AI the World's Leading AI and Technology News and Media Company. If you are building an AI-related product or service, we invite you to consider becoming an AI sponsor. At Towards AI, we help scale AI and technology startups. Let us help you unleash your technology to the masses. You've probably seen what artificial intelligence (AI) can do in science fiction movies like Terminator or Her.


How to Test a Recommender System - neptune.ai

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Recommender systems fundamentally address the question – What do people want? Although it is an extensive question, in the context of a consumer application like e-commerce, the answer could be to serve the best products in terms of price and quality for a consumer. For a news aggregator website, it could be to show reliable and relevant content. In a case where a user would have to look through thousands or millions of items to find what they are looking for, a recommendation engine is indispensable. The engine filters over 3,000 titles at a time using 1,300 recommendation clusters based on user preferences. It is so accurate that personalised recommendations from the engine drive 80% of Netflix viewer activity. However, building and evaluating a recommender system is very different compared to a single ML model regarding design decisions, engineering, and metrics. In this article, we will focus on testing a recommendation system. The second and third require a lot of user-item interaction data. If that is not available, one might start with the first type of recommender system.


The Voice Synthesis Business: 2022 Update

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Sounds like the perfect technology for anyone who wants to advance Steve Bannon's'flood the zone with shit' strategy.


The Robot Brains Podcast: Eric Horvitz of Microsoft on AI for the greater good on Apple Podcasts

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On Episode 15 of Season 2, we're joined by Eric Horvitz, Microsoft's first ever Chief Scientific Officer. His research spans theoretical and practical challenges with developing systems that perceive, learn, and reason. He's the company's top inventor since joining in 1993 with over 300 patents filed. He has been elected Fellow of the Association for the Advancement of Artificial Intelligence (AAAI), Fellow of the National Academy of Engineering (NAE), Fellow of the American Academy of Arts and Sciences, and Fellow of the American Association for the Advancement of Science (AAAS). He was a member of the National Security Commission on AI and he also co-founded important groups like the Partnership on AI, a non-profit organization bringing together Apple, Amazon, Facebook, Google, DeepMind, IBM, and Microsoft to document the quality and impact of AI systems on things like criminal justice, the economy, and media integrity.


What Is Artificial Intelligence? - ExtremeTech

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To many, AI is just a horrible Steven Spielberg movie. But what is artificial intelligence, exactly? The answer depends on who you ask. Broadly, artificial intelligence (AI) is the combination of computer science and robust datasets, deployed to solve some kind of problem. Many definitions of artificial intelligence include a comparison to the human mind or brain, whether in form or function. Alan Turing wrote in 1950 about "thinking machines" that could respond to a problem using human-like reasoning.


How to Become a Data Scientist in 2022?

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Data Science offers lucrative career opportunities in this day and age. Data scientists produce actionable business insights using data and implement mathematical algorithms to solve complex business problems. In fact, Amazon product recommendations, Netflix movie suggestions, Google Maps traffic predictions are some of the prime examples of data scientist work that we use every day in our lives! Data scientists' algorithms are helping many companies generate more revenue and enhance the customer experience of their products and services. Owing to these reasons, everybody aspires to be a data scientist these days.