Andrew Humphreys’ Post

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Senior Director Analyst | Software Engineering - Integration and API Strategies

AI, and GenAI in particular, have been the hot topic for a couple of years now, but what is getting traction in turns of delivering real value and what is turning out to be less important? Take a look at Gartner's latest Hype Cycle on AI to find out. Research led by Haritha Khandabattu and Afraz Jaffri

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Empowering Technology Executives & Leaders | TEDx Speaker

Gartner's Hype Cycle for Artificial Intelligence, 2024 is out! The two biggest movers on this year’s Hype Cycle, AI engineering and knowledge graphs, highlight the need for means of handling AI models at scale in a robust manner. AI engineering is a fundamental requirement for delivery, at scale, of enterprise AI solutions that demand new team topologies. Knowledge graphs provide dependable logic and explainable reasoning, in contrast to the fallible, yet powerful, predictive capabilities of the deep-learning techniques used by GenAI. More about this in the comments. Gartner subscription is required! #BuildwithGartner #ArtificialIntelligence

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Helping Accelerate Integrations and Automation to Drive Agility and Growth

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