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Artificial Intelligence in practice

CIO

The world has known the term artificial intelligence for decades. Developing AI When most people think about artificial intelligence, they likely imagine a coder hunched over their workstation developing AI models. Today, integrating AI into your workflow isn’t hypothetical, it’s MANDATORY.

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Build a strong data foundation for AI-driven business growth

CIO

In the quest to reach the full potential of artificial intelligence (AI) and machine learning (ML), there’s no substitute for readily accessible, high-quality data. If the data volume is insufficient, it’s impossible to build robust ML algorithms. If the data quality is poor, the generated outcomes will be useless.

Business 419
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AI Tools Make Short-Selling Possible with Algorithmic Trading

Smart Data Collective

Artificial intelligence is driving a number of changes in the financial sector. AI technology has helped investors make automated trades with algorithmic trading. Algorithmic trading for short-selling with AI Technology. But, there’s another way to do it, which is algorithmic trading which relies on AI algorithms.

Algorithm 351
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AI market evolution: Data and infrastructure transformation through AI

CIO

Artificial Intelligence (AI), a term once relegated to science fiction, is now driving an unprecedented revolution in business technology. Many believe that responsible AI use will help achieve these goals, though they also recognize that the systems powering AI algorithms are resource-intensive themselves. Nutanix commissioned U.K.

Marketing 483
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The key to operational AI: Modern data architecture

CIO

Recent research shows that 67% of enterprises are using generative AI to create new content and data based on learned patterns; 50% are using predictive AI, which employs machine learning (ML) algorithms to forecast future events; and 45% are using deep learning, a subset of ML that powers both generative and predictive models.

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AI data readiness: C-suite fantasy, big IT problem

CIO

Confidence from business leaders is often focused on the AI models or algorithms, Erolin adds, not the messy groundwork like data quality, integration, or even legacy systems. Successful pilot projects or well-performing algorithms may give business leaders false hope, he says. Thats where the friction arises.

IT 504
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Dulling the impact of AI-fueled cyber threats with AI

CIO

Artificial Intelligence: A turning point in cybersecurity The cyber risks introduced by AI, however, are more than just GenAI-based. Then there’s reinforcement learning, a type of machine learning model that trains algorithms to make effective cybersecurity decisions.

Security 482