H2O.ai recently announced the launch of its new multi-agent platform h2oGPTe, which combines generative and predictive AI models to provide businesses with more consistent responses. Sri Ambati, founder and CEO of H2O.ai, stated that a major demand from enterprises for AI agents is to maintain response consistency. The h2oGPTe platform utilizes H2O.ai's proprietary models Mississippi and Danube, while also allowing access to other models.
With the rapid development of artificial intelligence (AI) technologies in industrial sectors, experts indicate that high-quality data and data governance will be more important than generative technologies. By 2025, companies must focus more on scalable and flexible solutions when adopting AI, rather than solely relying on Generative AI (GenAI). Image note: The picture is generated by AI, authorized by the image service provider Midjourney, based on the analysis by Qlik, the key to fully harnessing AI's potential lies in companies' investments in high-quality, real-time data.
In today's wave of the digital economy, artificial intelligence is reshaping the business landscape at an unprecedented speed. Appier, a Software as a Service (SaaS) company dedicated to leveraging AI for business decision-making, has recently made significant strides in the field of generative AI, crafting a new blueprint for enterprise digital transformation. Artificial intelligence is dramatically altering the business ecosystem at an astonishing pace. A report from McKinsey predicts that generative AI will contribute between $2.6 trillion to $4.4 trillion annually to the global economy. Gartner's data further highlights the remarkable potential.
A recent study indicates that generative AI models, particularly large language models (LLMs), can be used to create a framework that accurately simulates human behavior across various scenarios. This finding provides a powerful new tool for social science research. The researchers initially recruited over 1,000 participants from diverse backgrounds in the United States and conducted in-depth interviews lasting up to two hours, collecting information about their life experiences, opinions, and values. Subsequently, they utilized these interview records along with a large language model to construct.