How Kyle Mooney incorporated our fears of AI using the'Y2K' hysteria Mashable Gift Lab Tech Science Life Social Good Entertainment Deals Shopping Games Search Cancel * * Search Result Gift Lab Tech Apps & Software Artificial Intelligence Cybersecurity Cryptocurrency Mobile Smart Home Social Media Tech Industry Transportation All Tech Science Space Climate Change Environment All Science Life Digital Culture Family & Parenting Health & Wellness Sex, Dating & Relationships Sleep Careers Mental Health All Life Social Good Activism Gender LGBTQ Racial Justice Sustainability Politics All Social Good Entertainment Games Movies Podcasts TV Shows Watch Guides All Entertainment SHOP THE BEST Laptops Budget Laptops Dating Apps Sexting Apps Hookup Apps VPNs Robot Vaccuums Robot Vaccum & Mop Headphones Speakers Kindles Gift Guides Mashable Choice Mashable Selects All Sex, Dating & Relationships All Laptops All Headphones All Robot Vacuums All VPN All Shopping Games Product Reviews Adult Friend Finder Bumble Premium Tinder Platinum Kindle Paperwhite PS5 vs PS5 Slim All Reviews All Shopping Deals Newsletters VIDEOS Mashable Shows All Videos Home Entertainment How Kyle Mooney incorporated our fears of AI using the'Y2K' hysteria Was the Y2K hysteria that different than our fears of Artificial Intelligence? ByMark Stetson on December 6, 2024 Share on Facebook Share on Twitter Share on Flipboard Watch Next A24's'Y2K' trailer is the '90s internet remix of our nightmares The cast of'Hysteria!' on what makes a society go hysterical 5:51 James Acaster's'Hecklers Welcome' was created as a form of "immersion therapy" 9:45 Kristin Chenowith is Lindsay Lohan's'monster-in-law' in'Our Little Secret' 2:35 Rachel Zegler and Jaeden Martell join Kyle Mooney to discuss their new film Y2K and reveal which old-school movies they would tattoo on their bodies. Y2K is now in theaters. Topics Artificial Intelligence Film Latest Videos Billy Eichner's story about being mis-recognised by Travis Kelce at a party is hilarious So gloriously awkward. Loading... Subscribe This newsletter may contain advertising, deals, or affiliate links.

"This work represents a significant step forward in strengthening our information advantage as we combat sophisticated disinformation campaigns and synthetic-media threats," says Bustamante. Hive was chosen out of a pool of 36 companies to test its deepfake detection and attribution technology with the DOD. The contract could enable the department to detect and counter AI deception at scale. "This is the evolution of cyberwarfare." Hive's technology has been trained on a large amount of content, some AI-generated and some not.

Despite fears that artificial intelligence (AI) could influence the outcome of elections around the world, the United States technology giant Meta said it detected little impact across its platforms this year. That was in part due to defensive measures designed to prevent coordinated networks of accounts, or bots, from grabbing attention on Facebook, Instagram and Threads, Meta president of global affairs Nick Clegg told reporters on Tuesday. "I don't think the use of generative AI was a particularly effective tool for them to evade our trip wires," Clegg said of actors behind coordinated disinformation campaigns. In 2024, Meta says it ran several election operations centres around the world to monitor content issues, including during elections in the US, Bangladesh, Brazil, France, India, Indonesia, Mexico, Pakistan, South Africa, the United Kingdom and the European Union. Most of the covert influence operations it has disrupted in recent years were carried out by actors from Russia, Iran and China, Clegg said, adding that Meta took down about 20 "covert influence operations" on its platform this year.

Every time a new AI model is released, it's typically touted as acing its performance against a series of benchmarks. OpenAI's GPT-4o, for example, was launched in May with a compilation of results that showed its performance topping every other AI company's latest model in several tests. The problem is that these benchmarks are poorly designed, the results hard to replicate, and the metrics they use are frequently arbitrary, according to new research. That matters because AI models' scores against these benchmarks determine the level of scrutiny they receive. AI companies frequently cite benchmarks as testament to a new model's success, and those benchmarks already form part of some governments' plans for regulating AI.

AI agents promise to change that. Think of them as AI models with a script and a purpose. They tend to come in one of two flavors. The first, called tool-based agents, can be coached using natural human language (rather than coding) to complete digital tasks for us. Anthropic released one such agent in October--the first from a major AI model-maker--that can translate instructions ("Fill in this form for me") into actions on someone's computer, moving the cursor to open a web browser, navigating to find data on relevant pages, and filling in a form using that data.

Ria Cheruvu has been ahead of the curve for most of her life. After graduating from her Arizona high school at just 11, the student deemed prodigy became one of the youngest people to ever graduate from Harvard. Her collegiate record is a marvel to many. Following a period studying neurobiology and during the completion of her first computer science degree, Cheruvu was hired for Intel's ethics team -- preceding the AI boom that would soon hit mass markets, and years before the phrase became a household utterance. At the time of her hiring, Cheruvu was just 14 years old.

Artificial intelligence (AI) systems are increasingly supplementing or taking over tasks previously performed by humans. On the one hand, this relates to low-risk tasks, such as recommending books or movies, or recommending purchases based on previous buying behavior. But it also includes crucial decision making by highly autonomous systems. Many current systems are opaque in the sense that their internal principles of operation are unknown, leading to severe safety and regulation problems. Once trained, deep-learning systems perform well, but they are subject to surprising vulnerabilities when confronted with adversarial images.9 The decisions may be explicated after the fact, but these systems carry the risk of wrong decisions affecting the well being of people.

The Hawk-Eye computer vision system made its tennis debut in 2003 for broadcasting purposes, but was approved in 2005 after a notorious U.S. Open Tennis match between Serena Williams and Jennifer Capriati in 2004, during which Williams was the victim of multiple bad calls in the third set and went on to lose the match. Use of Hawk-Eye was expanded during the COVID-19 pandemic, and the 2020 U.S. Open was played without line judges on all but two of the main courts. Since Hawk-Eye has been in use, between 190 and 200 judges have been replaced, depending on the stage of the tournament, says Sean Carey, managing director of competition operations, at the U.S. Tennis Association (USTA). "The reason we bring technology in for this level of tournament--and we want to do it across every level if we could afford it--is to ensure integrity and the fairest and most even calls,'' Carey said. Hawk-Eye, which uses cameras to track the trajectory of a ball and create a three-dimensional (3D) representation of it, is now being used by 23 of the top 25 global sports leagues and federations, according to the company. Yet, the sentiment appears to be that AI will never fully replace human judges. This has been the subject of much debate in Major League Baseball (MLB), a sport grounded in tradition, noted Daniel Martin, an associate professor of economics at the University of California at Santa Barbara. MLB is using Hawk-Eye to automatically monitor strike zones, and is questioning whether to get rid of umpires, given that the system is "incredibly accurate,'' he said.

When Donald Trump was last President, ChatGPT had not yet been launched. Now, as he prepares to return to the White House after defeating Vice President Kamala Harris in the 2024 election, the artificial intelligence landscape looks quite different. AI systems are advancing so rapidly that some leading executives of AI companies, such as Anthropic CEO Dario Amodei and Elon Musk, the Tesla CEO and a prominent Trump backer, believe AI may become smarter than humans by 2026. Others offer a more general timeframe. In an essay published in September, OpenAI CEO Sam Altman said, "It is possible that we will have superintelligence in a few thousand days," but also noted that "it may take longer."

Eight years ago, the November US election results profoundly shocked the small staff at Backchannel, the boutique tech publication I headed. The morning after, an editor posted on our Slack that working on a technology story seemed tone-deaf, if not futile. On a plane from New York to San Francisco, I wrote a column to answer that impulse, directed as much to myself and my colleagues as it was to readers. I argued that regardless of the enormity of this event, one thing hadn't changed; the biggest story of our time was still the technological revolution we were living through. Disruptive politicians, even destructive ones, may come and go--or refuse to go.