LLM

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Specialized Small AI Models: Reshaping the Future of AI Technology

Carsten Krause 0 Comments 12 min read

Generative AI’s initial allure is giving way to a more practical, specialized approach, with smaller, focused models gaining ground. Organizations are also shifting towards on-device AI for privacy and efficiency. While Gen AI faces challenges, aligning AI initiatives with organizational goals and focusing on sustainability can lead to strategic success. Embracing specialized models, open-source solutions, and sustainability is crucial while avoiding the Gen AI trap. I lay out in detail how in this article.

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PepsiCo and JetBlue: Case Studies in Securing RAG LLM Deployments

Carsten Krause 0 Comments ,  12 min read

The rise of Retrieval-Augmented Generation (RAG) models in natural language processing has brought about significant changes in various industries. This article focuses on the secure deployment of RAG Language Learning Models (LLMs), including role-based access control, secure hosting environments, and continuous monitoring. Case studies from PepsiCo and JetBlue illustrate their approaches to securing generative AI in both internal and external contexts.

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Navigating the Green Dilemma: The Hidden Environmental Toll of Generative AI

Carsten Krause 0 Comments 14 min read

The escalating energy demands of generative AI technologies are at the heart of a looming crisis, prompting a critical reevaluation of the sustainability of AI. Efforts are underway to quantify and mitigate AI’s environmental impact, including strategies for energy-efficient model design and legislative measures. Digital leaders must proactively integrate sustainability into technology evaluation and selection, aligning innovation with ecological stewardship for a green future. In this article we explore what digital leaders can do to do their part to make sustainable decisions for their digital transformation programs.

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The Dawn of Digital Delegation: A Seismic Shift of Autonomous Agents Reshaping Work

Carsten Krause 0 Comments ,  ,  18 min read

In an era of rapid technological advancement, autonomous agents are reshaping work and industries. These digital entities, leveraging advanced AI capabilities, are redefining productivity, efficiency, and customer experiences. Their applications span finance, healthcare, transportation, and more, offering substantial gains in efficiency and cost reduction. As businesses integrate these agents, the potential for enhanced operational capabilities and new service offerings is significant. In this article we dive deep into this new trend that will shake up how we interact with and leverage technology as a team mate.

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Unlocking the Power of Generative AI: A Comprehensive AI Pilot Guide

Carsten Krause 0 Comments ,  ,  26 min read

Generative AI represents a new era in artificial intelligence. Unlike traditional AI systems that rely on predefined rules and patterns, Generative AI possesses the remarkable ability to generate content, whether it be text, images, or even music, autonomously. This capability is made possible by neural networks, particularly models like OpenAI’s GPT-4, which can understand and generate human-like text with astonishing accuracy. Many organizations are looking at ways to take advantage of this disruptive innovation. At CDO TIMES we take the guesswork away from you by providing implementation frameworks for a generative AI pilots.

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The Lawler Model for Designing AI Products: A BloombergGPT Case Study

Carsten Krause 0 Comments ,  ,  16 min read

The advent of BloombergGPT is more than just a technological marvel—it’s a shift in how we understand the application of AI in finance. It represents the culmination of years of research, collaboration, and fine-tuning to create a tool that doesn’t just understand finance but thrives in it. As CDOs and tech leaders evaluate tools to bring their operations into the future, BloombergGPT stands as a compelling benchmark of what is achievable. It’s not just about automating tasks; it’s about enhancing decision-making, improving security, and ultimately, driving profitability. In a nutshell, BloombergGPT is not the future of financial technology; it is the technology that will build that future.

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