TECH NEWS

'The challenge is no longer only how much power is needed, but whether it can be delivered reliably': Report finds AI data centers are draining more power than the grid can provide

Electricity demand is now growing faster than energy suppliers can keep up with
Volatile AI workloads cause unpredictable peaks and troughs in demand
AI could actually help predict, despite also being the cause

With three in four (77%) electricity execs now believing that data center energy demand will grow faster than utilities can keep up with, two-thirds (68%) expect electricity shortages to become more commonplace as demand for AI soars.

New data from a Capgemini report reveals just how unpredictable AI energy demands can be, with 77% admitting they struggle to accurately forecast demand amid volatile AI workloads.

Not only is this leading to more constrained energy supply, but also more extreme and less predictable demand spikes.

Data center energy demand is a whole new ball game

All of this comes as local opposition continues to mount against data centers, with residents increasingly concerned about power outages and rising energy...

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If you use Google, you’re training its AI. Here’s how to opt out.

Consider this a belated PSA: A recent change to Google’s privacy settings is allowing the company to store more of your data, including media such as “images, files, and audio and video recordings,” to improve its AI models. In other words, if you upload any media to Google’s

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Level up your agentic AppSec powers

The first half of 2026 has been a blur for application security. Agentic AI has moved from experiment to expectation, reshaping how software is written, reviewed, attacked, and defended. Across security, engineering, and executive teams, many are still trying to grasp what this shift really means in practice. As we

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Enterprise hits and misses - harness engineering takes over enterprise AI, and tokenomics is in full swing

Lead story - In enterprise AI, the agent harness you choose matters more than the model Last week, I addressed reader pushback on my real-time organizational truth missive. I also unfurled something of a call to action: * Studies have shown that smaller models can reduce LLM operating costs by as

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Run MiniMax models on Amazon Bedrock | Amazon Web Services

Organizations are increasingly adopting open-weight foundation models (FMs) to power production AI workloads, from agentic coding assistants to long-context document analysis. As these workloads move from experimentation to enterprise deployment, two requirements shape every model selection decision: the model must deliver the capabilities the workload demands, and the inference environment

Data center energy demand is a whole new ball game

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If you use Google, you’re training its AI. Here’s how to opt out.

Level up your agentic AppSec powers

Enterprise hits and misses - harness engineering takes over enterprise AI, and tokenomics is in full swing

Run MiniMax models on Amazon Bedrock | Amazon Web Services