Expertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. As the world becomes increasingly digital, the demand for computing power has skyrocketed.

AI's energy consumption is projected to surge in the coming years, straining power grids and potentially hindering decarbonization efforts. Quantum computing offers a potential solution by ...

The AI boom is driving an explosive surge in computational demands and reshaping the landscape of technology, infrastructure, and innovation. One of the biggest barriers to widespread AI deployment ...

Sustainable computing practices have the power to both infuse operational efficiencies and greatly reduce energy consumption, says Jen Huffstetler, chief product sustainability officer at Intel. In ...

The future of computing needs to be more sustainable with artificial intelligence (AI) playing a role in achieving this, even as the growing adoption of the technology fuels energy consumption.

The escalating global demand for computation, juxtaposed with the imperative to reduce environmental impact and operating costs, has rendered energy‐efficient computing a central focus within modern ...

Energy-efficient neural network computing represents a transformative approach to mitigating the increasing energy demands of modern artificial intelligence systems. By harnessing cutting-edge ...

With the rise of AI, energy and heat efficiency have once again become pressing concerns for companies that use and build chips. The skyrocketing demand for hardware to run AI models is dragging up ...

The world is abuzz with the new opportunities being created by artificial intelligence (AI), enabled by the availability of unprecedented amounts of data. AI runs on the semiconductor engine, and in ...

Bitcoin mining converts excess, stranded energy into portable economic value, reframing miners as energy buyers rather than ...

Machine learning (ML), a subset of artificial intelligence (AI), has become integral to our lives. It allows us to learn and reason from data using techniques such as deep neural network algorithms.

As artificial intelligence (AI) proliferates rapidly, AI models and datasets are also growing rapidly in size. This growth far outpaces performance improvement in hardware systems, and is increasing ...