With generative AI evolving rapidly, organizations need to cut through the noise and prioritize what matters. This article from Gartner outlines what to expect from the next generation of GenAI technologies, including the platforms, capabilities, and architectural choices that will shape enterprise adoption. Read the article to gain strategic insight into building sustainable GenAI initiatives, and contact Lotus Beta Analytics to start shaping your approach with expert support.
What is the role of synthetic data in Generative AI?
Synthetic data plays a crucial role in addressing challenges related to data quality and privacy regulations. By incorporating synthetic data into their strategies, organizations can simulate responses, accelerate time-to-market, and focus on customer signals, ultimately driving innovation and customer-centric approaches.
How do autonomous agents change human interactions with AI?
Autonomous agents represent a significant shift in human interactions with Generative AI. These agents can handle complex tasks with minimal human intervention, enhancing efficiency and aligning more closely with human intent. The evolution of these agents will depend on carefully engineered prompts and access to knowledge resources.
What sustainability practices should organizations adopt for AI?
Organizations should optimize their Generative AI implementations by using energy-efficient computational methods, diversifying suppliers, and prioritizing sustainability in vendor risk management. Regularly reviewing vendors' product roadmaps for energy efficiency improvements can also help mitigate costs and environmental impacts.
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