Media
Foundation's new season has dramatic potential – but sadly falls flat
Mel Brooks and Carl Reiner used to spend every evening watching movies. Their favourites were cheesy – the type of film where someone says, "Secure the perimeter!" Why do I mention this in the context of Foundation? Because this adaptation of Isaac Asimov's novels started out as a thought-provoking series, but is now a "Secure the perimeter!" It has been two years since Foundation last aired, so if you have forgotten where we left off, that is understandable.
CEO Linda Yaccarino announced resignation from Musk's X
Elon Musk-owned X's CEO Linda Yaccarino announced her resignation in a surprise move, just months after the social media platform was acquired by the billionaire's AI startup, xAI. In a statement posted on the platform Wednesday, the former NBCUniversal advertising executive said she had "decided to step down as CEO of X" following what she described as "two incredible years" leading the company through a major transformation. After two incredible years, I've decided to step down as CEO of . When @elonmusk and I first spoke of his vision for X, I knew it would be the opportunity of a lifetime to carry out the extraordinary mission of this company. Yaccarino's departure from the social media company adds to the turbulence in Musk's sprawling business empire, including falling sales at his electric vehicle maker Tesla and artificial intelligence-related controversies.
The Download: a conversation with Karen Hao, and how did life begin?
In a wide-ranging Roundtables conversation for MIT Technology Review subscribers, journalist and author Karen Hao recently spoke about her new book, Empire of AI: Dreams and Nightmares in Sam Altman's OpenAI. She talked with executive editor Niall Firth about how she first covered the company in 2020 while on staff at MIT Technology Review. They discussed how the AI industry now functions like an empire and went on to examine what ethically-made AI looks like. Read the transcript of the conversation, which has been lightly edited and condensed. And, if you're already a subscriber, you can watch the on-demand recording of the event here.
The AI band that's fooled millions: Controversy over fake indie group Velvet Sundown goes into overdrive - so why IS Spotify peddling their 'music'?
AI tools are being fed artists' songs to'learn' their vocal styles and musical hallmarks before being able to generate brand new approximations, with new lyrics and melody (file photo) But it appears The Velvet Sundown is not the only fake artist on Spotify, which has more than 600 million users worldwide. According to a report last year from The Week, Spotify is becoming inundated with unlicensed covers of songs generated by AI.
Prime Day Picks From People Who Obsessively Test Gear & Track Prices
Amazon Prime Day began as one day and is now much more of an event, lasting four days this year. The Prime Day deals started dropping last month, and will go on through Friday. We'll be dangerously caffeinated and working in shifts, covering 20 hours a day through the end. The WIRED Reviews team only recommends deals on products we've actually tested and approved, and which are actually discounted. If you're looking for up-to-the-minute coverage of deals, check out our Amazon Prime Day liveblog, which will run from 5 am to midnight daily. Updated July 9, 2025: We've added over two dozen new deals on our favorite laptops, robot vacuums, TVs, security cameras, and more. If you want something hard-wearing and fast charging from the best USB-C cables, this is our pick. It tops out at 240 watts and has a tough, braided nylon exterior made from 100 percent recycled plastic. Anker promises this cable will last a century and it can operate in temperatures from -40 degrees to 176 degrees ...
Inside OpenAI's empire: A conversation with Karen Hao
These are our subscriber-only events where you get to listen in to conversations between editors and reporters. Now, I'm delighted to say we've got an absolute cracker of an event today. I'm very happy to have our prodigal daughter, Karen Hao, a fabulous AI journalist, here with us to talk about her new book. Hello, Karen, how are you doing? Thank you so much for having me back, Niall.
Futurist Adam Dorr on how robots will take our jobs: 'We don't have long to get ready – it's going to be tumultuous'
If Adam Dorr is correct, robots and artificial intelligence will dominate the global economy within a generation and put virtually the entire human race out of a job. The social scientist doubles up as a futurist and has a stark vision of the scale, speed and unstoppability of a technological transformation that he says will replace virtually all human labour within 20 years. The Guardian's journalism is independent. We will earn a commission if you buy something through an affiliate link. Dorr heads a team of researchers who have studied patterns of technological change over millennia and concluded that the current wave will not just convulse but obliterate the labour market by 2045.
Constella: Supporting Storywriters' Interconnected Character Creation through LLM-based Multi-Agents
Park, Syemin, Park, Soobin, Lim, Youn-kyung
Creating a cast of characters by attending to their relational dynamics is a critical aspect of most long-form storywriting. However, our formative study (N=14) reveals that writers struggle to envision new characters that could influence existing ones, to balance similarities and differences among characters, and to intricately flesh out their relationships. Based on these observations, we designed Constella, an LLM-based multi-agent tool that supports storywriters' interconnected character creation process. Constella suggests related characters (FRIENDS DISCOVERY feature), reveals the inner mindscapes of several characters simultaneously (JOURNALS feature), and manifests relationships through inter-character responses (COMMENTS feature). Our 7-8 day deployment study with storywriters (N=11) shows that Constella enabled the creation of expansive communities composed of related characters, facilitated the comparison of characters' thoughts and emotions, and deepened writers' understanding of character relationships. We conclude by discussing how multi-agent interactions can help distribute writers' attention and effort across the character cast.
News Source Citing Patterns in AI Search Systems
AI-powered search systems are emerging as new information gatekeepers, fundamentally transforming how users access news and information. Despite their growing influence, the citation patterns of these systems remain poorly understood. We address this gap by analyzing data from the AI Search Arena, a head-to-head evaluation platform for AI search systems. The dataset comprises over 24,000 conversations and 65,000 responses from models across three major providers: OpenAI, Perplexity, and Google. Among the over 366,000 citations embedded in these responses, 9% reference news sources. We find that while models from different providers cite distinct news sources, they exhibit shared patterns in citation behavior. News citations concentrate heavily among a small number of outlets and display a pronounced liberal bias, though low-credibility sources are rarely cited. User preference analysis reveals that neither the political leaning nor the quality of cited news sources significantly influences user satisfaction. These findings reveal significant challenges in current AI search systems and have important implications for their design and governance.
Self-supervised learning of speech representations with Dutch archival data
Vaessen, Nik, Ordelman, Roeland, van Leeuwen, David A.
This paper explores the use of Dutch archival television broadcast data for self-supervised learning of speech foundation models, specifically wav2vec 2.0. We first study data quality assumptions for pre-training, and show how music, noise and speaker overlap affect SSL convergence and downstream fine-tuning performance. Secondly, we explore effectively pre-processing strategies to convert the noisy broadcast dataset into a qualitative dataset for pre-training, by using Whisper and WhisperX. Thirdly, we compare mono-lingual and multilingual pre-training with equivalent amounts of data, and show that mono-lingual pre-training is more robust to out-of-domain data. Lastly, we achieve a state-of-the-art LARGE wav2vec 2.0 model for the Dutch language, by a continuation of pre-training a wav2vec 2.0 XLS-R model checkpoint with our 55 k hour archival dataset.