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A powerful earthquake, possibly the strongest in years, has devastated the island nation of Vanuatu, killing at least 14 people. More than 200 are reported injured according to a post on X by Katie Greenwood, Fiji-based head of the Red Cross in the Pacific.

The 7.3-magnitude jolt rocked the region on Tuesday sending tremors through homes, businesses and critical infrastructure. Witnesses described buildings collapsing, roads blocked by landslides and hospitals stretched thin as reports of injuries — and unconfirmed casualties — surfaced.

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Chris McHenry is Vice President of Product Management at Aviatrix.

Enterprise reliance on cloud computing is no longer a question of “if” but “how much” and “how secure.” The cloud has become the backbone of modern business, enabling rapid scaling, seamless integration and global reach.

However, as cloud adoption matures, so do its associated costs—driven significantly by the rise of artificial intelligence (AI) and the escalating energy demands of data centers. For instance, OpenAI recently revealed plans to increase its prices by 120% over the next five years, even after securing an industry-record $6.6 billion in funding.

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Originally published on Towards AI.

One of the major challenges in using LLMs in business is that LLMs hallucinate. How can you entrust your clients to a chatbot that can go mad and tell them something inappropriate at any moment? Or how can you trust your corporate AI assistant if it makes things up randomly?

That’s a problem, especially given that an LLM can’t be fired or held accountable.

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A small team of AI researchers at Adobe Inc., working with a colleague from Auburn University and another from Georgia Tech, has developed a small language model (SLM) that they claim can be run locally on a smart phone with no access to the cloud. The group has written a paper describing their new app, which they call SlimLM, and have posted it to the arXiv preprint server.

As LLM technology continues to mature, researchers across the globe continue to find new ways to improve it. In this new effort, the research team has found a way to cut the cord for a specific type of AI application—processing documents locally.

As LLMs such as ChatGPT become more popular, users have become more worried about privacy. And it is not just individuals—companies large and small have adopted AI applications that assist with a variety of business processes, some of which require a high degree of privacy.

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Interim Intel co-CEO Michelle Johnston Holthaus announced that the first engineering samples of hardware manufactured with the company’s 18A semiconductor node have been delivered to customers. Her comments aim to reassure industry observers that Intel’s foundry business remains on track to compete with TSMC’s and Samsung’s 3nm and 2nm nodes starting next year.

At the Barclays Annual Global Technology Conference, Holthaus and co-CEO David Zinsner discussed Intel’s upcoming Panther Lake processors, which will debut the 18A process node upon their expected launch in the second half of 2025. Holthaus revealed that eight foundry customers have powered on ES0 (likely “Engineering Sample 0”) chips built on the 18A node, signaling significant progress compared to six months ago.

Intel released version 1.0 of the 18A process design kit in July, enabling customers to begin developing chips based on the node. In August, the company confirmed that internal samples of Panther Lake and Clearwater Forest processors, built on the 18A node, successfully powered on and booted Windows with satisfactory performance. The statements made at the Barclays event mark the first confirmation of 18A usage outside of Intel.

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What is time? Is it just a ticking clock, or is it something more profound?

In this thought-provoking episode of Into the Impossible, Stephen Wolfram challenges everything we know about time, offering a revolutionary computational perspective that could forever change how we understand the universe.

Stephen Wolfram is a computer scientist, physicist, and businessman. He is the founder and CEO of Wolfram Research and the creator of Mathematica, Wolfram Alpha, and Wolfram Language. Over the course of 4 decades, he has pioneered the development & application of computational thinking. He has been responsible for many discoveries, inventions & innovations in science, technology, and business.

Continue reading “What is Time? Stephen Wolfram’s Groundbreaking New Theory [Ep. 468]” | >

Quantum sensors, a cutting-edge technology capable of detecting subtle signals from the human body, could soon transform how diseases are diagnosed and monitored, according to a report from the Quantum Economic Development Consortium (QED-C).

The report outlines how quantum sensing tools — ranging from diamond-based detectors to optically pumped magnetometers — offer unprecedented sensitivity compared to traditional medical devices. These sensors could enable earlier diagnoses for diseases like Alzheimer’s, provide better imaging of fetal development, and even analyze the microbiome in real time.

“Improved sensors could impact diverse aspects of biomedicine,” the report states. “For example, quantum sensors offer the possibility of significantly more efficient and accurate medical diagnoses for patients, thanks to their increased sensitivity and novel options for form factor. These attributes could enable quantum sensors to collect vast amounts of data about patients and medical conditions, and thus facilitate drug and treatment development and earlier diagnosis of disease. The advantages of quantum sensors encourage new ideas about solutions, quantum use cases, and business models across the biomedical industry — from prenatal care to cancer detection and treatment.”

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From the early days of mechanical automatons to more recent conversational bots, scientists and engineers have dreamed of a future where AI systems can work and act intelligently and independently. Recent advances in agentic AI bring that autonomous future a step closer to reality. With their supercharged reasoning and execution capabilities, agentic AI systems promise to transform many aspects of human-machine collaboration. The agentic AI prize could be great, with the promise of greater productivity, innovation and insights for the human workforce. But so, too, are the risks: the potential for bias, mistakes, and inappropriate use. Early action by business and government leaders now will help set the right course for agentic AI development, so that its benefits can be achieved safely and fairly.

Page-utils class= article-utils—vertical hide-for-print data-js-target= page-utils data-id= tag: blogs.harvardbusiness.org, 2007/03/31:999.397606 data-title= What Is Agentic AI, and How Will It Change Work? data-url=/2024/12/what-is-agentic-ai-and-how-will-it-change-work data-topic= Generative AI data-authors= Mark Purdy data-content-type= Digital Article data-content-image=/resources/images/article_assets/2024/12/Dec24_12_1450615814-383x215.jpg data-summary=

The next era of human-machine collaboration will present new opportunities and challenges.

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In this episode of the Eye on AI podcast, we dive into the world of Artificial General Intelligence (AGI) with Ben Goertzel, CEO of SingularityNET and a leading pioneer in AGI development.

Ben shares his vision for building machines that go beyond task-specific capabilities to achieve true, human-like intelligence. He explores how AGI could reshape society, from revolutionizing industries to redefining creativity, learning, and autonomous decision-making.

Continue reading “Ben Goertzel: AGI, SingularityNET and Decentralized AI” | >