AI agents debate more effectively when given personalities and the ability to interrupt

In a typical online meeting, humans don’t always wait politely for their turn to speak. They interrupt to express strong agreement, stay silent when they are unsure, and let their personalities shape the flow of the discussion. Yet, when artificial intelligence (AI) agents are programmed to debate or collaborate, they are usually forced into a …

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Accelerating your marketing ideation with generative AI – Part 2: Generate custom marketing images from historical references

Marketing teams face major challenges creating campaigns in today’s digital environment. They must navigate through complex data analytics and rapidly changing consumer preferences to produce engaging, personalized content across multiple channels while maintaining brand consistency and working within tight deadlines. Using generative AI can streamline and accelerate the creative process while maintaining alignment with business …

‘Discovery learning’ AI tool predicts battery cycle life with just a few days’ data

An agentic AI tool for battery researchers harnesses data from previous battery designs to predict the cycle life of new battery concepts. With information from just 50 cycles, the tool—developed at University of Michigan Engineering—can predict how many charge-discharge cycles the battery can undergo before its capacity drops below 90% of its design capacity.

A Reinforcement Learning Based Universal Sequence Design for Polar Codes

To advance Polar code design for 6G applications, we develop a reinforcement learning-based universal sequence design framework that is extensible and adaptable to diverse channel conditions and decoding strategies. Crucially, our method scales to code lengths up to 2048, making it suitable for use in standardization. Across all (N,K)(N, K)(N,K) configurations supported in 5G, our …