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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. John Gallant, CIO.coms Enterprise Consulting Director and Vito Mabrucco, NTT Corp. John Gallant, CIO.coms Enterprise Consulting Director and Vito Mabrucco, NTT Corp.

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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. These autoregressive models can ultimately process anything that can be easily broken down into tokens: image, video, sound and even proteins.

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Extend large language models powered by Amazon SageMaker AI using Model Context Protocol

AWS Machine Learning - AI

These tools are integrated as an API call inside the agent itself, leading to challenges in scaling and tool reuse across an enterprise. Amazon SageMaker AI provides the ability to host LLMs without worrying about scaling or managing the undifferentiated heavy lifting. The following diagram illustrates this workflow.

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AI in action: How enterprises are scaling AI for real business impact

CIO

To capitalize on the enormous potential of artificial intelligence (AI) enterprises need systems purpose-built for industry-specific workflows. Enterprise technology leaders discussed these issues and more while sharing real-world examples during EXLs recent virtual event, AI in Action: Driving the Shift to Scalable AI.

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LLMOps for Your Data: Best Practices to Ensure Safety, Quality, and Cost

Speaker: Shreya Rajpal, Co-Founder and CEO at Guardrails AI & Travis Addair, Co-Founder and CTO at Predibase

Large Language Models (LLMs) such as ChatGPT offer unprecedented potential for complex enterprise applications. However, productionizing LLMs comes with a unique set of challenges such as model brittleness, total cost of ownership, data governance and privacy, and the need for consistent, accurate outputs.

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Are enterprises ready to adopt AI at scale?

CIO

Whether it’s a financial services firm looking to build a personalized virtual assistant or an insurance company in need of ML models capable of identifying potential fraud, artificial intelligence (AI) is primed to transform nearly every industry. Before we go further, let’s quickly define what we mean by each of these terms.

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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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The Business Value of MLOps

As machine learning models are put into production and used to make critical business decisions, the primary challenge becomes operation and management of multiple models. Download the report to find out: How enterprises in various industries are using MLOps capabilities.

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Democratizing AI for All: Transforming Your Operating Model to Support AI Adoption

Democratization puts AI into the hands of non-data scientists and makes artificial intelligence accessible to every area of an organization.

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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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ERP Migration: Why Data Quality Comes First

Automation and machine learning are augmenting human intelligence, tasks, jobs, and changing the systems that organizations need in order not just to compete, but to function effectively and securely in the modern world. ERP (Enterprise Resource Planning) system migration is a case in point.