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Open-source AI platform supplier H2O.ai believes a mix of generative and predictive AI fashions makes for extra constant responses which enterprises need from an AI agent.
H2O.ai launched its new multi-agent platform that blends generative and predictive AI and is now typically obtainable.
The platform, h2oGPTe, makes use of the firm’s AI fashions Mississippi and Danube, however can even entry different massive and small language fashions obtainable. The corporate stated h2oGPTe works in air-gapped, on-premise and cloud techniques.
Sri Ambati, founder and CEO of H2O, advised VentureBeat that having each generative and predictive AI provides enterprises extra confidence that the brokers will work precisely as they want with out compromising safety.
“The number one problem with agents is consistency. Can I get a consistent response from an [large language model] LLM for the same prompt? I think you get two different, like multiple responses right now,” Ambati stated. “But you can bring multiple models that negotiate, plan and deliver an outcome. Think of it as humans can have a bit of variability with each other, but you still expect a consistent response, and that’s the domain of predictive AI combined with generative AI.”
Ambati defined that generative AI fashions are “decent at content generation and very good at code generation,” however predictive fashions deliver extra situation simulation to the desk. He stated the predictive fashions deliver consistency to agentic responses as a result of these don’t simply generate responses however study from patterns in information.
The platform is constructed for finance, telecommunications, healthcare and authorities enterprises that have to handle multi-step duties. H2O.ai’s agent works greatest for organizations that need to get insights into their enterprise and never only a information that runs via their workflows. It is because brokers inside the h2oGPTe platform can learn multimodal information like charts and craft solutions to questions like “Should my company sell more dolls this year?” that contemplate the enterprise’s historic monetary information or market development info they retailer.
Multimodal brokers
Like different AI brokers, h2oGPTe automates workflow duties so human staff don’t need to do these actions themselves. Ambati stated the multimodal capabilities of H2O.ai’s brokers open up extra info that it may possibly study from to supply one of the best, most constant solutions to customers.
The corporate stated the brokers can even create PDF paperwork with charts and tables grounded in enterprise information to visualise info for the human person. H2O.ai ensured that the brokers cite their sources for information traceability and supply customizable guardrails.
H2O.ai’s agentic platform builds in mannequin testing, together with automated query era, the place an AI mannequin will create variations of a immediate and barrage the agent with inquiries to see if it constantly responds. It additionally has a dashboard the place folks can establish which sort of database, mannequin, or a part of the workflow the brokers tapped.
Consistency and accuracy in brokers
With the hype round AI brokers predicted to proceed to the next yr, there’s a want to make sure brokers present worth to enterprises, together with performing constantly, reliably and precisely.
Reliability is important as a result of AI brokers are supposed to automate a big portion of an enterprise’s workflow with out human intervention.
H2O.ai’s method of mixing generative and predictive fashions is a method, however different firms are additionally methods to make sure AI brokers don’t trigger bother for enterprises. The startup xpander.ai launched its Agent Graph System for multi-step brokers. Salesforce additionally launched to a restricted preview its Agentforce Testing Middle to check agent response consistency.
