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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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How the world can tackle the power demands of artificial intelligence

CIO

The world must reshape its technology infrastructure to ensure artificial intelligence makes good on its potential as a transformative moment in digital innovation. New technologies, such as generative AI, need huge amounts of processing power that will put electricity grids under tremendous stress and raise sustainability questions.

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LLM benchmarking: How to find the right AI model

CIO

But how do companies decide which large language model (LLM) is right for them? LLM benchmarks could be the answer. They provide a yardstick that helps user companies better evaluate and classify the major language models. LLM benchmarks are the measuring instrument of the AI world.

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China banks on open source in AI cold war with US

CIO

After more than two years of domination by US companies in the arena of artificial intelligence,the time has come for a Chinese attackpreceded by many months of preparations coordinated by Beijing. Its approach couldchange the balance of power in the development of artificial intelligence.

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How Banks Are Winning with AI and Automated Machine Learning

By leveraging the power of automated machine learning, banks have the potential to make data-driven decisions for products, services, and operations. Read the whitepaper, How Banks Are Winning with AI and Automated Machine Learning, to find out more about how banks are tackling their biggest data science challenges.

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Multi-LLM routing strategies for generative AI applications on AWS

AWS Machine Learning - AI

Organizations are increasingly using multiple large language models (LLMs) when building generative AI applications. Although an individual LLM can be highly capable, it might not optimally address a wide range of use cases or meet diverse performance requirements.

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How AI orchestration has become more important than the models themselves

CIO

Large language models (LLMs) just keep getting better. In just about two years since OpenAI jolted the news cycle with the introduction of ChatGPT, weve already seen the launch and subsequent upgrades of dozens of competing models. From Llama3.1 to Gemini to Claude3.5 In fact, business spending on AI rose to $13.8

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How Banks Are Winning with AI and Automated Machine Learning

By leveraging the power of automated machine learning, banks have the potential to make data-driven decisions for products, services, and operations. Read the white paper, How Banks Are Winning with AI and Automated Machine Learning, to find out more about how banks are tackling their biggest data science challenges.

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Intelligent Process Automation: Boosting Bots with AI and Machine Learning

But in order to reap the rewards of Intelligent Process Automation, organizations must first educate themselves and prepare for the adoption of IPA. In Data Robot's new ebook, Intelligent Process Automation: Boosting Bots with AI and Machine Learning, we cover important issues related to IPA, including: What is RPA?

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Resilient Machine Learning with MLOps

Today’s economy is under pressure from inflation, rising interest rates, and disruptions in the global supply chain. As a result, many organizations are seeking new ways to overcome challenges — to be agile and rapidly respond to constant change. We do not know what the future holds.

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MLOps 101: The Foundation for Your AI Strategy

Many organizations are dipping their toes into machine learning and artificial intelligence (AI). Download this comprehensive guide to learn: What is MLOps? How can MLOps tools deliver trusted, scalable, and secure infrastructure for machine learning projects? Why do AI-driven organizations need it?

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Embedding BI: Architectural Considerations and Technical Requirements

While data platforms, artificial intelligence (AI), machine learning (ML), and programming platforms have evolved to leverage big data and streaming data, the front-end user experience has not kept up. Traditional Business Intelligence (BI) aren’t built for modern data platforms and don’t work on modern architectures.

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The Role of Artificial Intelligence in Pandemic Response: Lessons Learned From COVID-19

In March 2020, the world was hit with an unprecedented crisis when the COVID-19 pandemic struck. As the disease tragically took more and more lives, policymakers were confronted with widely divergent predictions of how many more lives might be lost and the best ways to protect people.

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5 Things a Data Scientist Can Do to Stay Current

With the number of available data science roles increasing by a staggering 650% since 2012, organizations are clearly looking for professionals who have the right combination of computer science, modeling, mathematics, and business skills. Fostering collaboration between DevOps and machine learning operations (MLOps) teams.

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How to Choose an AI Vendor

You know you want to invest in artificial intelligence (AI) and machine learning to take full advantage of the wealth of available data at your fingertips. But rapid change, vendor churn, hype and jargon make it increasingly difficult to choose an AI vendor.