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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. This process, where both input and output of the model are automated, is known as AI deployment.

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Can Artificial Intelligence Replace Human Intelligence?

The Crazy Programmer

Artificial Intelligence is a science of making intelligent and smarter human-like machines that have sparked a debate on Human Intelligence Vs Artificial Intelligence. Will Human Intelligence face an existential crisis? Impacts of Artificial Intelligence on Future Jobs and Economy.

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Leveraging AMPs for machine learning

CIO

Data scientists and AI engineers have so many variables to consider across the machine learning (ML) lifecycle to prevent models from degrading over time. Fine-Tuning Studio Lastly, the Fine-tuning Studio AMP simplifies the process of developing specialized LLMs for certain use cases.

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Have we reached the end of ‘too expensive’ for enterprise software?

CIO

Generative artificial intelligence ( genAI ) and in particular large language models ( LLMs ) are changing the way companies develop and deliver software. Instead of manually entering specific parameters, users will increasingly be able to describe their requirements in natural language.

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How Banks Are Winning with AI and Automated Machine Learning

Estimating the risks or rewards of making a particular loan, for example, has traditionally fallen under the purview of bankers with deep knowledge of the industry and extensive expertise. By leveraging the power of automated machine learning, banks have the potential to make data-driven decisions for products, services, and operations.

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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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Stability AI backs effort to bring machine learning to biomed

TechCrunch

Called OpenBioML , the endeavor’s first projects will focus on machine learning-based approaches to DNA sequencing, protein folding and computational biochemistry. Stability AI’s ethically questionable decisions to date aside, machine learning in medicine is a minefield. Image Credits: OpenBioML.

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How Banks Are Winning with AI and Automated Machine Learning

Estimating the risks or rewards of making a particular loan, for example, has traditionally fallen under the purview of bankers with deep knowledge of the industry and extensive expertise. By leveraging the power of automated machine learning, banks have the potential to make data-driven decisions for products, services, and operations.

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Trusted AI 102: A Guide to Building Fair and Unbiased AI Systems

The risk of bias in artificial intelligence (AI) has been the source of much concern and debate. Numerous high-profile examples demonstrate the reality that AI is not a default “neutral” technology and can come to reflect or exacerbate bias encoded in human data.

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Realizing the Benefits of Automated Machine Learning

While everyone is talking about machine learning and artificial intelligence (AI), how are organizations actually using this technology to derive business value? This white paper covers: What’s new in machine learning and AI.