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Sam Altman defends AI’s energy toll by saying it also takes a lot to ‘train a human’

OpenAI CEO also downplayed concerns about how much water datacenters require at AI summit in IndiaThe OpenAI boss, Sam Altman, has tried to ease concerns about how much power is used by artificial intelligence models by comparing it to the amount of energy required by human development.“People talk about how much energy it takes to […]

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How to make a cash flow forecasting app work for other systems

Your cash flow forecasting app is working beautifully. Your teams add their own data to keep forecasts running smoothly. Its predictions, tracking variances, and insights seem great.  …Until you take a closer look at the details, and determine that none of these systems actually talk to one another. And that’s a problem. Consolidating all of

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New datacentres risk doubling UK electricity use, regulator says

Ofgem says about 140 proposed projects, driven by AI use, could require more power than current peak demandThe amount of power being sought by new datacentre projects in the UK would exceed the country’s current peak electricity consumption, according to an industry watchdog.Ofgem said about 140 proposed datacentre schemes, driven by use of artificial intelligence,

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How to build resilient agentic AI pipelines in a world of change

Change is the only constant in enterprise AI. If your data workflows aren’t built to handle it, you’re setting your entire operation up for failure. Most data pipelines are brittle, breaking when data or infrastructures slightly change. That downtime can cost millions (upwards of $540,000 per hour), lead to compliance gaps that invite lawsuits, and

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AIs can generate near-verbatim copies of novels from training data

The world’s top AI models can be prompted to generate near-verbatim copies of bestselling novels, raising fresh questions about the industry’s claim that its systems do not store copyrighted works. A series of recent studies has shown that large language models from OpenAI, Google, Meta, Anthropic, and xAI memorize far more of their training data

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AIs can generate near-verbatim copies of novels from training data

The world’s top AI models can be prompted to generate near-verbatim copies of bestselling novels, raising fresh questions about the industry’s claim that its systems do not store copyrighted works. A series of recent studies has shown that large language models from OpenAI, Google, Meta, Anthropic, and xAI memorize far more of their training data

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