Cognitive architectures are blueprints for building intelligent and autonomous systems, essentially designing the 'minds' of AI agents. They provide guardrails or frameworks to control agents, improving their memory and capabilities, and preventing them from becoming too general or unreliable.
Multi-agent systems involve several AI agents working together, each with a specific role, similar to a cross-functional project team. They are expected to grow because they can handle more complex tasks and deliver better results by combining specialized agents, making them more practical and scalable for enterprises.
Multimodal abilities allow AI agents to perceive and interact with their environment using multiple senses like video, audio, and images. This enhances their ability to perform tasks more like humans, opening up new use cases, especially for accessibility and enterprise assistance.
Agent-oriented LLMs will be purpose-built for autonomous activities, prioritizing multi-step reasoning, long-term memory, and context retention. Unlike traditional LLMs designed for broad tasks, these models will be tailored to enhance agent performance, potentially using a mix of models for different tasks within an agent.
Agents will accelerate AGI discussions as they demonstrate increasingly autonomous behavior, especially when using advanced models like OpenAI's O3, which has surpassed human benchmarks in certain tasks. However, 2025 is not expected to be the year of AGI, but agents will blur the lines and reignite debates about AI's human-like capabilities.
2026 is expected to be a pivotal year as enterprises will likely deploy agents at scale, integrating them into their workforce. The learnings and developments from 2025 will set the stage for broader adoption, leading to significant advancements in how work and life are transformed by AI agents.
PART 2: Agents are the most important trend in AI heading into the new year. NLW is joined by Nufar Gaspar to count down 25 predictions for AI agents in 2025.
Nufar Gaspar is a seasoned AI expert and leader with vast experience in incubating and growing AI products, verticals and communities. She is the Director of AI Everywhere and Gen AI for Intel Design, and consults and trains organizations and teams on the usage of AI and building AI products and companies.
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