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 ai hype cycle


This Is the Worst Part of the AI Hype Cycle

WIRED

Earlier this week, Paul McCartney sent the music-nerd internet ablaze with some news: Artificial intelligence had helped resurrect a bit of John Lennon's voice for a new Beatles song, more than four decades after his death. The song is set for release later this year and comes from vocals Lennon recorded on an old demo. "We were able to take John's voice and get it pure through this AI," McCartney told BBC Radio 4, "so then we could mix the record, as you would normally do." The reaction this elicited on WIRED Slack channels was somewhere between "cool" and "gross." Using AI to resurrect Lennon for a new song has its appeal, but given the recent ethical questions around using the technology to make fake songs from artists like Drake and The Weeknd, it also feels icky.

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The AI Hype Cycle: What Blockchain Can Teach Us About Managing Expectations - Grit Daily News

#artificialintelligence

Technology can be a topic difficult to understand and make predictions on, even for those with a strong technical background and perceived expertise. From Ethernet's creator Robert Metcalfe's 1995 prediction that the internet would "catastrophically collapse" by the next year to Intel's prediction that 3D TV was the future, it is clear that predicting tech trends is a difficult endeavor. No matter how hard predicting the future of technology is, every new technology that creates disruption will go through this cycle. Most recently, we have gone through multiple hype cycles with innovations like blockchain, cryptocurrency, the metaverse, VR, and now, AI. Every single of these technologies has captivated not only the public but also developers and investors, blurring the line between facts and fiction.


How ChatGPT Broke the AI Hype Cycle

#artificialintelligence

According to the Gartner hype cycle, the least amount of time a product takes to hit the'plateau' of expectations is two years. The hot chatbot has shattered all records of a product lifecycle, going through all stages of the cycle within 3 months. Launched in November-end last year, ChatGPT has already been through the innovation trigger, inflated expectations, disillusionment, enlightenment, and is now reaching a mature period of measured expectations, leading to industry adoption. A contributing factor to this might be the bot's meteoric growth, which scaled to 10 million users within 40 days. For contrast, Instagram took almost a year to reach the same milestone.


Gartner's AI Hype Cycle; AI used medical notes to teach itself; 10 years later, DL 'revolution' rages on; AI Isn't Ready to Make Unsupervised Decision

#artificialintelligence

I hope that you enjoy the latest AI news, insights, and the Web3 section at the end! See the outlook and impact. It isn't ready to assume human qualities that emphasize empathy, ethics, and morality. Even experts don't know what it will mean: Behind the headlines and memes a fundamental revolution is underway – with profound social, artistic, economic, and technological implications. Engage directly with top 20 thought leaders in AI/ML from Google, IBM, AWS, Samsung, Oxford Brookes University, Volkswagen, SAP, Mercedes Benz, and more!


Reality check: Analysts check in on the AI hype cycle

#artificialintelligence

When analysts evaluate the maturity of AI, the first step is to parse out the many technologies that fall under the AI umbrella. Natural language processing, RPA, machine learning and deep learning have all found individual use cases across industries within the past few years. "2020 is the year that AI is going to enter the mainstream of enterprise adoption," said Jack Fritz, a principal in Deloitte Consulting LLP's Technology, Media, and Telecommunications practice. "It's already integrated into a lot of enterprise applications like ERP, CRM." In a survey of 1,100 AI adopters, Deloitte found that about 70% are using machine learning and around half of them were deploying deep learning.


AI Hype Cycle Is Over: 3 Ways AI Will Transform Customer Experience

#artificialintelligence

Retailers are expected to spend 7.3 billion dollars on AI annually by 2022, according to a CapGemini Research Institute report. This investment is largely motivated by companies' interest in improving customer experience across all engagement points, including marketing, buying, and after-sales service. Eugenio Cassiano is the chief innovation officer for the SAP Customer Experience organization. He talked about three ways AI can deliver great customer experiences for retailers and other types of organizations. According to Cassiano, conversational AI is moving into the mainstream.