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Is Your Company’s Data Ready for Generative AI?

Harvard Business Review

While CDOs and data leaders are excited about generative AI, they have much work to do to get ready for it. Despite excitement, companies have yet to see clear value from generative AI and need to do significant work to prepare their data.

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Using Generative AI to Drive Corporate Impact

TechEmpower Innovation

Generative AI is revolutionizing how corporations operate by enhancing efficiency and innovation across various functions. Focusing on generative AI applications in a select few corporate functions can contribute to a significant portion of the technology's overall impact.

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Innovation thinking in Ecosystem and Generative AI design.

Paul Hobcraft

Innovation is undergoing a radical change, in opening up to technology, collaborative thinking and the value of generative AI thinking. For me, ecosystem innovation and generative AI have arrived at that pivotal point to significantly influence future innovation design. Innovation needs reinventing.

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Embracing the Future: Fractional Executives and Generative AI

Tullio Siragusa

Embracing the Future: Fractional Executives and Generative AI The concept of fractional executives has emerged as a game-changer for companies of all sizes. The rise of Generative Artificial Intelligence (AI) has further empowered fractional executives, enabling them to produce full-time results in significantly less time.

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Navigating the Future: Generative AI, Application Analytics, and Data

Generative AI is upending the way product developers & end-users alike are interacting with data. Despite the potential of AI, many are left with questions about the future of product development: How will AI impact my business and contribute to its success?

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Innovation on Steroids: Next Generation AI-Powered Phases and Gates

Leapfrogging

AI technologies bring a new dimension of analytical capabilities and insights that were previously unattainable. By harnessing the power of AI, organizations are able to process vast amounts of data, identify patterns, and make more informed decisions at every phase of the innovation process.

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Has Generative AI Peaked?

Harvard Business Review

This calls for a rethink of the incentives and economics surrounding human-generated content. The real bottleneck in generative AI might not be computation capacity or model parameters, but our unique human touch. Yet, we are on the brink of a digital world that is increasingly filled with AI-generated clutter.

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Embedded Analytics Insights for 2024

Organizations look to embedded analytics to provide greater self-service for users, introduce AI capabilities, offer better insight into data, and provide customizable dashboards that present data in a visually pleasing, easy-to-access format.

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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

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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LLMs in Production: Tooling, Process, and Team Structure

Speaker: Dr. Greg Loughnane and Chris Alexiuk

Technology professionals developing generative AI applications are finding that there are big leaps from POCs and MVPs to production-ready applications. However, during development – and even more so once deployed to production – best practices for operating and improving generative AI applications are less understood.