DeepMind also addresses something of a meta-concern about AI. The researchers say that a powerful AI in the wrong hands could be dangerous if it is used to accelerate machine learning research, resulting in the creation of more capable and unrestricted AI models. DeepMind says this could "have a significant effect on society's ability to adapt to and govern powerful AI models." DeepMind ranks this as a more severe threat than most other CCLs.
An AI-generated musician persona run by a human R&B artist has received a $3 million record deal -- amidst several lawsuits targeting AI companies encroaching on creative industries. Also: Will AI damage human creativity? Most Americans say yes Telisha "Nikki" Jones, who's behind the AI-generated artist Xania Monet, accepted the record deal, which is with . She combines elements of her real-life songwriting abilities with AI-generated vocals, images, and musical production.
By The Associated Press Chipmaker Nvidia will invest $100 billion in OpenAI as part of a partnership announced Monday that will add at least 10 gigawatts of Nvidia AI data centers to ramp up the computing power for the owner of the artificial intelligence chatbot ChatGPT. Per the letter of intent signed by the companies, the first gigawatt of Nvidia systems will be deployed in the second half of 2026. Nvidia and OpenAI said they would be finalizing the details of the arrangement in the coming weeks.
A new study from advisory firm KPMG found that 45% of workers surveyed reported feelings of loneliness in the workplace, and the majority would trade 20% in salary in exchange for working with close friends. And 99% of workers are interested in an AI chatbot that could become a close friend or trusted companion at work. There's a business case, too: Nearly 90% said friendship-enabling cultures are crucial for retention.
Artificial intelligence has changed my business entirely. The majority of my business is ecommerce-based, and AI has allowed me to automate many of the most time-consuming tasks. This shift hasn't just saved me time; it's made daily operations more efficient and enabled smarter, data-driven decisions that have elevated both productivity and customer satisfaction. In the early days, I spent nearly every waking hour creating products and listing them online.
It takes a lot of computing power to run an AI product - and as the tech industry races to tap the power of AI models, there's a parallel race underway to build the infrastructure that will power them. On a recent earnings call, Nvidia CEO Jensen Huang estimated that between $3 and $4 trillion will be spent on AI infrastructure by the end of the decade - with much of that money coming from AI companies themselves.
Oracle is shaking up its executive suite as it sets its sights set on AI infrastructure dominance. The company announced Monday that it is promoting Clay Magouyrk and Mike Sicilia to co-CEO roles. Magouyrk joined Oracle in 2014 from Amazon Web Services. He was a founding member of Oracle's cloud engineering team and has served as the president of Oracle's cloud infrastructure business unit for more than a decade.
Moody's said late last week that the OpenAI "contract size is staggering - highlighting the tremendous potential for Oracle's AI Infrastructure. However, the related risks of the build are significant." It pointed to the significant "counterparty risk" in Oracle's projected growth - the possibility that another party fails to meet its obligations. "Counterparty risk is always a key consideration in any type of project financing, particularly where there is a high reliance on revenue from a single counterparty," Moody's analysts wrote on Wednesday.
The OpenAI CEO said in a post on X on Monday that the company is launching "new compute-intensive offerings" over the next few weeks. Altman said because of the costs involved, some features will initially be limited to Pro subscribers, while certain new products will have extra fees. Altman framed the push as an experiment in stretching AI infrastructure to its limits: "We also want to learn what's possible when we throw a lot of compute, at today's model costs, at interesting new ideas," he wrote.
Google first introduced Gemini for its TV operating system at CES in January, pitching the voice assistant's ability to process natural language and offer highly contextual responses. The idea was that Gemini could not only surface shows, movies, and channel recommendations across the TV's catalog of streaming services and apps but also handle general inquiries like homework problems, vacation planning, and more. The end goal? An AI-driven experience that's burdenless and easy to navigate (whether through text or speech) and transforms your TV into the ultimate centerpiece. Beyond serving as a multimedia consumption device, a Gemini-enhanced TV should feel more like an interactive smart hub, an information resource that removes some of the friction from constantly picking up our smartphones.
AI replacing entry-level jobs isn't a distant headline, it's the elephant in the room. My students know it's possible, and they don't treat it as science fiction. What I've seen isn't fear or denial. It's movement. Instead of getting stuck in 'what if' debates, Gen Z is choosing clarity over panic, quietly steering their careers toward stability in a way that's easy to miss if you only listen for loud signals.
Altogether, Lumen said construction was underway coast-to-coast, and that it has delivered "significant" progress in its mission to build the backbone for the artificial intelligence (AI) economy. It added that it was moving forward with a multibillion-dollar build, with plans to add 34 million intercity fibre miles by the end of 2028, as part of the 47 million intercity fibre mile target.
When OpenAI launched its new GPT-5 model in August, the company bragged loud and hard about how GPT-5 is its "smartest, fastest, most useful model yet" and how interacting with it was like "chatting with a helpful friend with PhD‑level intelligence." When it comes to creative tasks like writing, GPT-5 immediately felt like a major step backward. But as I've tested the model more extensively, I've seen that it does excel at many pragmatic tasks like writing code and analyzing data.
In the span of less than two years, Core Scientific went from a bankrupt crypto mining company to a $9 billion acquisition target. How? By reinventing itself as an upstart player in the artificial intelligence-driven data center craze. Only now, one of the company's largest shareholders is urging other investors to vote down the deal - arguing that $9 billion isn't nearly enough. While a takeover battle between little-known data center firms might seem like
The future of banking is not in a single, clean leap. It's showing up in fragments: APIs on top of legacy systems, automation paired with human judgment, digital tools balanced by hand-holding for companies new to the digitization journey. Emerging from these fragments aren't just new tools or products, but a slow rebuild of banking's operating system. My recent stories on Amex, Citizens, and BNY highlight different layers of this rebuild.
DJ Seo, Neuralink's president, told an audience at the Korea Foundation for Advanced Studies in Seoul that the company hopes to demonstrate communication with large language model AI platforms "at the speed of thought," potentially faster than spoken speech. "We think that it's actually possible to demonstrate abilities to speak to the latest AI model, or LLM models, at the speed of thought, even faster than how you're speaking, and being able to potentially get that information back through your AirPods, effectively closing the loop," Seo stated.
The tech layoff wave is still kicking in 2025. Last year saw more than 150,000 job cuts across 549 companies, according to independent layoffs tracker Layoffs.fyi. So far this year, more than 22,000 workers have been the victim of reductions across the tech industry, with a staggering 16,084 cuts taking place in February alone. As businesses continue to embrace AI and automation, this tracker serves as a reminder of the human impact of layoffs - and what could be at stake with increased innovation.
"I'm not a big buzzword person," she tells me in our sit-down interview. "You sometimes lose credibility when you use it [AI] too much. What I like about what we're doing is that we're actually doing things, products that are already shipping, that you can use, right now." Diana points to tools like Flow Studio and MotionMaker, both live and used in production on TV shows and films, designed to solve real-world bottlenecks.
The last decade has seen the emergence of APAC as the world's proving ground for new technology, driven by a culturally diverse, mobile-first population whose behavior is paving the road for the future of its digital economy. This year, APAC's Data & AI market is expected to reach $90 billion, with nearly 80% of enterprises implementing AI solutions into digital strategies. The momentum of its fast-growing digital market attracted numerous firms seeking to play their role in driving innovation in the region.
For years, Big Tech CEOs have touted visions of AI agents that can autonomously use software applications to complete tasks for people. But take today's consumer AI agents out for a spin, whether it's OpenAI's ChatGPT Agent or Perplexity's Comet, and you'll quickly realize how limited the technology still is. Making AI agents more robust may take a new set of techniques that the industry is still discovering.
The challenge? Finding the best ones for the job. In this blog post, we've compiled a list of the best GPTs for research to help you save time, boost efficiency, and focus on your ideas. 🎯 Best GPTs for Research at a Glance The Best GPTs for Research Not all GPTs are worth your time for research. Some miss the mark, while others actually help you find useful insights. These are the ones that get it right.
At the IAA Mobility 2025 show in Munich, Candice Yuan, senior director and head of product at Xpeng's Autonomous Driving Center, told CarNewsChina that the company has grown increasingly confident in its vision-based approach since pulling lidar from its vehicles. "The lidar data can't contribute to the AI system," Yuan told the outlet, adding that the company's large language model is fed mainly 10 to 30-second short videos, taken from its customer vehicles, and then used to train the AI system.
What we've learned is that this is not a race so much as a long, curved, and fragmented road - one that looks more like the fan of an alluvial plain than a racetrack - to develop and prove the technology works a nd make it a profitable business. It's not a race against others as much as an internal contest with existential stakes.
