Media


Humans vs Robots: The Difference Between AI and AGI

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We've all seen the film where robots take over the world, with their mechanical bodies causing Hollywood-style screams from unsuspecting (or maybe very suspecting) victims. And, while these kinds of films let us live an alternate reality for an hour and a half, there's always that niggling thought at the backs of our minds telling us that this could actually happen in the not-too-distant future. In fact, the "father of AI", Alan Turing, was beavering away on it in the 1950s. He developed the Turing Test, which had a judge ask questions to a machine and a human. The judge would then have to decide who was the human and, if the computer could fool the judge at least half of the time, it was considered intelligent.


Can Artificial Intelligence Replace Your Favorite Musicians?

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Truth be told, the answer to questions that start with "Can Artificial Intelligence..." will almost always be "yes" in the long term. However, is it really possible at some point in the future machines will be able to produce music indistinguishable from that of a human? Music is ultimately a set of patterns that humans find meaning in. Since it is closely related to our feelings and emotions, it is hard to imagine an "emotionless" robot composing the works of the great Chopin or Pink Floyd. Humans make music out of almost a need, a need to explain the "human experience."




r/MachineLearning - [D] Using (known) symbolic rules to improve classification/segmentation ?

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Using one of your examples, for me the symbolic constraints for OCR of printed source code seem conceptually similar to how standard OCR systems implement the split between the character OCR model (which provides the probabilities of individual characters) and the language model (which provides the probabilities of long combined sequences of possible alternative characters) - any symbolic rules and constraints could be integrated straight into the language model, by adding an extra penalty to the likelihood of sequences that don't match some rule. The algorithms to effectively explore the solution space in this manner (often some form of beam search) already exist and would be already implemented and tested in an OCR system, so the symbolic rules would just change how the cost function is calculated.


How Artificial Intelligence Is Transforming The Media World: An Interview with Vilynx CEO JC Riveiro

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Some tech CEOs run the show but don't really understand the nuts and bolts of the company's product. Riveiro is the CEO of Vilynx (pronounced "VEE-links"), a firm which uses artificial intelligence (AI) and machine learning to help media companies make video "smarter." To date, the Spanish company has received about $15 million in funding from European and North American venture capital and angel investors. Vilynx has offices in Barcelona, Palo Alto and New York City. This interview has been edited for brevity and clarity.


AWS AI & Machine Learning Podcast - Episode 6

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Sign in to report inappropriate content. In this episode, I have a chat with Cosmin Catalin Sanda, a Data Science Engineer for AudienceProject (https://www.audienceproject.com). We talk about real life ML, what it takes for ML projects to be successful (experimentation, agility, intuition, etc.), how SageMaker helps, and more. Don't forget to subscribe to be notified of future episodes Cosmin's Twitter: https://twitter.com/cosminsanda This podcast is also available in audio at https://julsimon.buzzsprout.com/


AI and Chill: How OTT Platforms Can Benefit from AI

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OTT platforms are becoming popular now than ever before. The competition between different OTT platforms has increased tremendously. Technologies like AI for OTT services can help businesses stay relevant in this cut-throat competition. According to a report, by the end of 2019, about 182.5 million people in the US will view content via OTT services. This represents more than 50% of the US population and provides huge business opportunities for OTT service providers.


iHeartMedia sacks over 50 radio hosts, invests in artificial intelligence

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As MBW reports, the latest staffing changes have made waves due to the statement that came with the news citing a renewed investment in artificial intelligence. "We are modernizing our company to take advantage of the significant investments we have made in new technology and aligning our operating structure to match the technology-powered businesses we are now in," said iHeartMedia. It's believed that the 57 are mostly radio jocks carry decades of experience working across genres of music including Rock, Urban, Country, Top 40, Hits and more. "During a transition like this it's reasonable to expect that there will be some shifts in jobs – some by location and some by function – but the number is relatively small given our overall employee base of 12,500." "That said, we recognize that the loss of any job is significant; we take that responsibility seriously and have been thoughtful in the process."


Artificial Intelligence Software Market to Reach $126.0 Billion in Annual Worldwide Revenue by 2025

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Artificial intelligence (AI) within the consumer, enterprise, government, and defense sectors is migrating from a conceptual "nice to have" to an essential technology driving improvements in quality, efficiency, and speed. According to a new report from Tractica, the top industry sectors where AI is likely to bring major transformation remain those in which there is a clear business case for incorporating AI, rather than pie-in-the-sky use cases that may not generate return on investment for many years. "The global AI market is entering a new phase in 2020 where the narrative is shifting from asking whether AI is viable to declaring that AI is now a requirement for most enterprises that are trying to compete on a global level," says principal analyst Keith Kirkpatrick. According to the market intelligence company, AI is likely to thrive in consumer (Internet services), automotive, financial services, telecommunications, and retail industries. Not surprisingly, the consumer sector has demonstrated its ability to capture AI, thanks to the combination of three key factors – large data sets, high-performance hardware and state of the art algorithms.