Those music libraries and personal photo and video collections that would force us to purchase one hard drive after another can instead be squeezed into portions of a single drive.
Compression allows us to pull up volumes of data from the Internet virtually instantaneously.
Researchers from the University of Jyväskylä were able to simplify the most popular technique of artificial intelligence, deep learning, using 18th-century mathematics. They also found that classical training algorithms that date back 50 years work better than the more recently popular techniques. Their simpler approach advances green IT and is easier to use and understand.
The recent success of artificial intelligence is significantly based on the use of one core technique: deep learning. Deep learning refers to artificial intelligence techniques where networks with a large number of data processing layers are trained using massive datasets and a substantial amount of computational resources.
Deep learning enables computers to perform complex tasks such as analyzing and generating images and music, playing digitized games and, most recently in connection with ChatGPT and other generative AI techniques, acting as a natural language conversational agent that provides high-quality summaries of existing knowledge.
Summary: A recent study hints at a harmonious synchronization of movement, heart rate, and even the excitement level among audience members during classical concerts.
This in-depth exploration into the physical responses of 132 individuals during a live performance of classical pieces unveiled a fascinating cohesion in their bodily rhythms, notably in heart and breathing rates. Interestingly, personality traits, such as agreeableness and openness, appeared to elevate the propensity for such synchronization among listeners.
This novel insight opens up a captivating dialogue about the intertwining of music, communal experience, and individual physical responses.
For me, one of the most exciting aspects of the recent wave of generative AI technology is the democratizing impact it has on creativity. We’ve seen how anyone can use tools like ChatGPT or Midjourney to express their ideas with words or pictures. And the way we create and listen to music is about to be turned on its head, too.
Loudly is a generative AI-driven music platform that aims to allow anybody to “create, customize and discover music.” Recently, I was joined by founder and CEO Rory Kenny for my podcast, covering a number of topics that I personally find fascinating.
Does AI threaten human creativity by ushering in a future where all of our art and entertainment is conjured up from… More.
The transition to Artificial General Intelligence (AGI) signifies more than a change in terminology; it represents a major leap in capabilities. It will take many years for AGI to be fully realized, but we are well underway in this evolution. In the meantime, most of the AI applications developed remain classified as NarrowAI.
Simply, AGI is any task that a human can do could be accomplished by general AI. It technically has all the potential of a human brain. It could tackle any problem or task in any area, whether it be music composition or logistics—all the potential actions humans can perform.
This article discusses General AI and highlights how the AI industry is unfolding advancing efforts to develop General AI.
The instrumental title track “I Robot”, together with the successful single “I Wouldn’t Want To Be Like You”, form the opening of “I Robot”, a progressive rock album recorded by The Alan Parsons Project and engineered by Alan Parsons and Eric Woolfson in 1977. It was released by Arista Records in 1977 and re-released on CD in 1984 and 2007. It was intended to be based on the “I, Robot” stories written by Isaac Asimov, and actually Woolfson spoke with Asimov, who was enthusiastic about the concept. However, as the rights had already been granted to a TV/movie company, the album’s title was altered slightly by removing the comma, and the theme and lyrics were made to be more generically about robots rather than specific to the Asimov universe. The cover inlay reads: “I ROBOT… HE STORY OF THE RISE OF THE MACHINE AND THE DECLINE OF MAN, WHICH PARADOXICALLY COINCIDED WITH HIS DISCOVERY OF THE WHEEL… ND A WARNING THAT HIS BRIEF DOMINANCE OF THIS PLANET WILL PROBABLY END, BECAUSE MAN TRIED TO CREATE ROBOT IN HIS OWN IMAGE.” The Alan Parsons Project were a British progressive rock band, active between 1975 and 1990, founded by Eric Woolfson and Alan Parsons. Englishman Alan Parsons (born 20 December 1948) met Scotsman Eric Norman Woolfson (18 March 1945 — 2 December 2009) in the canteen of Abbey Road Studios in the summer of 1974. Parsons had already acted as assistant engineer on The Beatles’ “Abbey Road” and “Let It Be”, had recently engineered Pink Floyd’s “The Dark Side Of The Moon”, and had produced several acts for EMI Records. Woolfson, a songwriter and composer, was working as a session pianist, and he had also composed material for a concept album idea based on the work of Edgar Allan Poe. Parsons asked Woolfson to become his manager and Woolfson managed Parsons’ career as a producer and engineer through a string of successes including Pilot, Steve Harley, Cockney Rebel, John Miles, Al Stewart, Ambrosia and The Hollies. Parsons commented at the time that he felt frustrated in having to accommodate the views of some of the musicians, which he felt interfered with his production. Woolfson came up with the idea of making an album based on developments in the film industry, where directors such as Alfred Hitchcock and Stanley Kubrick were the focal point of the film’s promotion, rather than individual film stars. If the film industry was becoming a director’s medium, Woolfson felt the music business might well become a producer’s medium. Recalling his earlier Edgar Allan Poe material, Woolfson saw a way to combine his and Parsons’ respective talents. Parsons would produce and engineer songs written by the two, and The Alan Parsons Project was born. This channel is dedicated to the classic rock hits that have become part of the history of our culture. The incredible AOR tracks that define music from the late 60s, the 70s and the early 80s… lassic Rock is here!
Is there an 8-dimensional “engine” behind our universe? Join Marion Kerr on a fun, visually exciting journey as she explores a mysterious, highly complex structure known simply as ‘E8’–a weird, 8-dimensional mathematical object that for some, strange reason, appears to encode all of the particles and forces of our 3-dimensional universe.
Meet surfer and renowned theoretical physicist Garrett Lisi as he rides the waves and paraglides over the beautiful Hawaiian island of Maui and talks about his groundbreaking discovery about E8 relates deeply to our reality; and learn why Los Angeles based Klee Irwin and his group of research scientists believe that the universe is essentially a 3-dimensional “shadow” of this enigmatic… thing… that may exist behind the curtain of our reality.
Google announced this morning it will be shutting down its Google Podcasts app later in 2024 as part of its broader transition to move its streaming listeners over to YouTube Music. The company earlier this year announced YouTube Music would begin supporting podcasts in the U.S., which will expand globally by year-end, and more recently said it was adding the ability for podcasters to upload their RSS feeds to YouTube also by year-end.
Today, Google says it plans on further increasing its investment in the podcast experience on YouTube Music and making it more of a destination for podcast fans with features focused on discovery, community and switching between audio podcasts and video. The latter is something rival Spotify has also been working on with its rollout of video podcast support to creators worldwide last year, along with community features like Q&As and polls.
However, to make YouTube Music the new home for podcasts, that means moving users away from the current offering, Google Podcasts. The company notes this plan reflects how people are already listening. According to Edison, about 23% of weekly podcast users in the U.S. say YouTube is their most frequently used service versus just 4% for Google Podcasts.
With video calls becoming more common in the age of remote and hybrid workplaces, “mute yourself” and “I think you’re muted” have become part of our everyday vocabularies. But it turns out muting yourself might not be as safe as you think.
Kevin Fu, a professor of electrical and computer engineering and computer science at Northeastern University, has figured out a way to get audio from pictures and even muted videos. Using Side Eye, a machine learning assisted tool that Fu and his research team created, Fu can determine the gender of someone speaking in the room where a photo was taken—and even the exact words they spoke.
“Imagine someone is doing a TikTok video and they mute it and dub music,” Fu says. “Have you ever been curious about what they’re really saying? Was it ‘Watermelon watermelon’ or ‘Here’s my password?’ Was somebody speaking behind them? You can actually pick up what is being spoken off camera.”