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Meta’s AI strategy: Building for tomorrow, not immediate profits

AI News

Meta has signalled a long-term AI strategy that prioritises substantial investments over immediate revenue generation. During the company’s Q2 earnings call, CEO and founder Mark Zuckerberg outlined Meta’s vision for the future and emphasised the need for extensive computational resources to support their AI initiatives.

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Nicholas Brackney, Dell: How we leverage a four-pillar AI strategy

AI News

Nicholas Brackney, Senior Consultant in Product Marketing at Dell, discussed the company’s AI initiatives ahead of AI & Big Data Expo North America. This ensures that AI is a fundamental component of Dell’s offerings. “We’ve Looking to the future, Dell is particularly excited about the potential of AI PCs.

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Singapore-based Firmus wins recognition for AI data centre design

AI News

The project highlights a potential pathway for sustainable AI development by achieving a pPUE of 1.02 The achievement aligns with Singapore’s National AI Strategy 2.0, which emphasises sustainable growth in AI and data centre innovation. and a reduction in energy consumption of 45%.

Big Data 286
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How the EU AI Act and Privacy Laws Impact Your AI Strategies (and Why You Should Be Concerned)

Unite.AI

Navigating this new, complex landscape is a legal obligation and a strategic necessity, and businesses using AI will have to reconcile their innovation ambitions with rigorous compliance requirements. GDPR's stringent data protection standards present several challenges for businesses using personal data in AI.

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Tech executives confident in AI skills, but adoption barriers persist

AI News

Budget restrictions (41%), shortage of AI talent (38%), and technical complexity (35%) were cited as primary obstacles. Michal Szymczak, Head of AI Strategy at Zartis, commented on this apparent contradiction: “AI adoption isn’t some ‘on or off’ switch.

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How to Build AI That Customers Can Trust

Unite.AI

Transparency = Good Business AI systems operate using vast datasets, intricate models, and algorithms that often lack visibility into their inner workings. This opacity can lead to outcomes that are difficult to explain, defend, or challengeraising concerns around bias, fairness, and accountability. It needs regular checkups.

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AI Paves a Bright Future for Banking, but Responsible Development Is King

Unite.AI

For example, an AI model trained on biased or flawed data could disproportionately reject loan applications from certain demographic groups, potentially exposing banks to reputational risks, lawsuits, regulatory action, or a mix of the three. The average cost of a data breach in financial services is $4.45