One concern many users have about AI is that often their data leaves their PC and their network, with inferencing happening in the cloud. They have big questions about data protection. That's one of the main drivers for Microsoft's Copilot+ PCs; the neural processing units that are built-in to the latest CPU systems on a chip run inferencing locally using small language models (SLMs) and other optimized machine-learning tools.
Elon Musk said in late November that he's "tried to warn" legacy automakers and "even offered to license Tesla Full Self-Driving, but they don't want it," expressing frustration with companies that refuse to adopt the company's suite, which will eventually be autonomous. Tesla has long established itself as the leader in self-driving technology, especially in the United States. Although there are formidable competitors, Tesla's FSD suite is the most robust and is not limited to certain areas or roadways. It operates anywhere and everywhere.
Agentic AI is all the buzz in the business world as people envision creating and using special AI agents to carry out both routine and complex tasks on their behalf. Now, Google is launching a new product for Workspace users who want to see if they can benefit from such agents.
This week, a U.K. coalition comprised of the Independent Publishers Alliance, non-profit tech-justice company Foxglove, and non-profit advocacy group Movement for the Open Web revealed that they have kicked off a lobbying effort with the Department of Justice, in the hope that the U.S. regulator will hear their evidence for why and how Google's AI Overviews has caused "substantial and irreparable harm" to independent publishers' traffic and revenue.
"By the time these changes appear in official statistics, policymakers may already be reacting to yesterday's disruptions, committing billions to programs that target skills already displaced," the researchers said.
Marketing through the ages has always depended on human effort, but now AI's greatest strength is its ability to analyze large amounts of data in a very short time. Marketers no longer have to spend long hours reviewing daily reports, as machines now spot trends, forecast customer behavior, and identify new marketing opportunities. The AI-driven platforms are capable of: Figuring out the audience groups that are going to convert
As technology continues to advance and companies look to remain competitive in meeting market demand, the skills that employees will need are also evolving. A growing number of companies are exploring how to address these skills and workforce gaps with artificial intelligence. HR can use AI to reveal "patterns and gaps" and benchmark "current workforce skills against evolving business needs or industry trends," said Lauren Winans, CEO and principal human resources consultant at Next Level Benefits.
Some of the world's most powerful and well-connected leaders converged in Manhattan on Wednesday, and one subject dominated the room: artificial intelligence. Three years after ChatGPT launched, revolutionizing the way the world thinks about and uses AI, the arms race is bigger than ever - perhaps too big. At the annual New York Times DealBook Summit, leaders from BlackRock's Larry Fink to Lai Ching-te, the President of Taiwan, were asked about the state of the AI industry and the potential for an AI bubble, a hot topic in Silicon Valley and on Wall Street over the past few months.
Artificial intelligence has fueled a multi-trillion-dollar stock market surge over the past few years, propelling companies like Microsoft ( NASDAQ:MSFT ) and Nvidia ( NASDAQ:NVDA ) to record valuations. Investors poured funds into AI on promises of transformative efficiency and new revenue streams, driving the S&P 500 's tech-heavy gains. Yet doubts about AI's staying power are mounting as evidence shows limited returns on investment. Meta Platforms ( NASDAQ:META ), for instance, implemented an AI hiring freeze in August after aggressive poaching, signaling a pause amid restructuring and bubble fears.
Look at the large tech companies in the world today. Most of them have a business in advertising or social media or, you know, content distribution...Nvidia is the only company in the world that's large whose only business is technology, Huang said. We only build, we don't advertise. The only way that we make money is to create amazing technology and sell it. Between the lines: Companies like Meta and Google are referred to as tech companies, but much of their revenue comes from advertising. Technology fuels their advertising businesses, however, with AI features creating a windfall of ad-revenue at Meta, for example. As Wall Street has worried about the return on investment in AI, some investors tell Axios that the revenue for tech will still come from advertising in an AI-world.
According to a recent report from digital transformation and industrial automation provider Rockwell Automation, the UK already leads Europe in smart manufacturing, with 53% of its manufacturers using AI on the factory floor and 98% overall planning to implement it. This compares to a global average of 41% introducing AI and machine learning (ML), as well as 95% planning to implement.
One of the biggest recent challenges we hear from many of you is around virtualization costs - licenses, fees are skyrocketing. You're faced with rigid architecture and upcoming deadlines and single vendor runtime models are becoming harder to adapt and afford. It is not enough to lift and shift to the public cloud. You need a cloud model and experience everywhere.
AI design tools are everywhere right now. But here's the question every designer is asking: Do they actually solve real UI problems - or just generate pretty mockups? To find out, I ran a simple experiment with one rule: no cherry-picking, no reruns - just raw, first-attempt results. I fed 10 common UI design prompts - from accessibility and error handling to minimalist layouts - into 5 different AI tools. The goal? To see which AI came closest to solving real design challenges, unfiltered.
Rather than thinking about it solely as a job replacement tool, how do you think about reducing someone's workload by 50%? Can we now free a merchant up who's spending 50% of their time building spreadsheets, responding to emails, communicating with suppliers? If AI can take that task away, can you now take 50% of that merchant's time, and they can focus on sales-driving initiatives? That's what we're trying to understand.
Chinese AI firm DeepSeek has made yet another splash with the release of V3.2, the latest iteration in its V3 model series. Launched Monday, the model, which builds on an experimental V3.2 version announced in October, comes in two versions: "Thinking," and a more powerful "Speciale." DeepSeek said V3.2 pushes the capabilities of open-source AI even further. Like other DeepSeek models, it's a fraction of the cost of proprietary models, and the underlying weights can be accessed via Hugging Face.
Governments are budgeting for increased AI spending to address mission-critical national security needs and other operations. BigBear.ai (NYSE: BBAI) is a leader in providing generative AI tools for national security and defense. It's positioning itself to capitalize on this surging demand with its recent acquisition of AskSage. AskSage could be a game changer in accelerating the company's growth. It offers a platform that combines AI models and AI agents to perform tasks autonomously and is purposefully built for handling sensitive data.
C3.ai ( NYSE: AI) reports after the close, last quarter's results were sharply disappointing, with revenue falling 19 percent year over year and management openly characterizing execution as "completely unacceptable." The stock has since become a referendum on whether C3.ai can convert its vast pilot activity into predictable subscription revenue while restoring confidence in its sales organization. With a new CEO installed, a fully restructured commercial org and a refreshed partner-led strategy, this quarter is positioned as an inflection point where the company must demonstrate that stabilization is underway.
Discord has detailed how it rebuilt its machine learning platform after hitting the limits of single-GPU training. By standardising on Ray and Kubernetes, introducing a one-command cluster CLI, and automating workflows through Dagster and KubeRay, the company turned distributed training into a routine operation. The changes enabled daily retrains for large models and contributed to a 200% uplift in a key ads ranking metric. Similar engineering reports are emerging from companies such as Uber, Pinterest, and Spotify as bespoke models grow in size and frequency.
Of the accounts that posted content most frequently, half focused on content related to the female body. These AI women are always stereotypically attractive, with sexualised attire or cleavage, the report said. AI Forensics found the accounts did not label half of the content they posted and less than 2% carried the TikTok label for AI content which the nonprofit warned could increase the material's deceptive potential.
After ChatGPT blindsided the company in 2022 and turned OpenAI into the face of generative AI, Google spent three years working to regain its footing. The company launched Gemini 3, calling it its most advanced model yet. The positive reviews the AI bot has received since its debut could be the clearest sign yet that Google's turnaround is real. Now, it's OpenAI that appears to be on its heels.
Zuckerberg, Chen said, has personally "hand-cooked" and "hand-delivered" soup to researchers he wanted to recruit away from OpenAI. And it wasn't a joke, the executive insisted. "It was shocking to me at the time," Chen admitted. But in Silicon Valley, if the enemy brings broth, you must respond in kind. Chen confessed he has now adopted the tactic, delivering soup to his own recruits as he hopes to poach talent from Meta.
