Companies are taking control of their own data to tailor AI for their needs. The challenge lies in balancing ownership with the safe, trusted flow of high‑quality data needed to power reliable insights. This conversation from MIT Technology Review’s EmTech AI conference examines how AI factories unlock new levels of scale, sustainability, and governance—positioning data…
Hyperscale cloud providers are doing what any aggressive buyer with deep pockets would do: purchasing enormous volumes of DRAM and high-bandwidth memory to feed AI factories, new cloud regions, and expanding platform services. By securing supply ahead of competitors, they lock in favorable terms and ensure their growth is not constrained by component scarcity. From their perspective, this is smart business. From the enterprise market’s perspective, it is something else entirely.
When the largest infrastructure providers absorb a disproportionate share of a finite supply of memory, prices rise for everyone downstream. Enterprises attempting to refresh on-premises servers, expand private clouds, or maintain hybrid architectures suddenly face a distorted market. Hardware lead times grow. Budget assumptions fail. Planned refreshes become much more expensive than expected. In some cases, the cloud begins to look attractive not because it is strategically superior, but because the economics
Every data leader has a version of this story. A regulatory audit surfaces a metric that doesn’t match across systems. A board member catches conflicting revenue numbers in two reports presented back-to-back. An AI tool generates a recommendation based on data that hasn’t been governed since the analyst who built it left the company two […]
Ahead of the AI & Big Data Expo at the San Jose McEnery Convention Center, May 18-19, we spoke to Jerome Gabryszewski, the company’s AI & Data Science Business Development Manager about AI, processing data for AI ingestion, and local versus cloud compute. The technology media is fond of quoting that data is ‘the new […]
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The race to build the world’s most powerful AI factories demands networking that keeps pace with the ambitions of AI itself. NVIDIA Spectrum-X Ethernet scale-out infrastructure stands at the forefront of that race as the most advanced AI networking technology available today, deployed by industry leaders who can’t afford to compromise on performance, resilience or […]
Residents say AI factories with unknown environmental impacts are being rushed into development as proponents argue Australia must ride the data boom or be left behind
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When West Footscray resident Sean Brown takes his 19-month-old boy to the park, their walk passes an imposing new building cheerily spruiked as “Australia’s largest hyperscale AI factory”, a datacentre called M3.
He hates it: the construction noise from its constant expansion, the looming towers and the insistent background hum, the exhaust from the growing array of diesel generators that power the ranks of servers inside.
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Cybersecurity was already under strain before AI entered the stack. Now, as AI expands the attack surface and adds new complexity, the limits of legacy approaches are becoming harder to ignore. This session from MIT Technology Review’s EmTech AI conference explores why security must be rethought with AI at its core, not layered on after…
