"Today's agents are generalists. Every time you ask them to do a task, you take a leap of faith."
"Current agents, whether from Claude Code, OpenClaw or Perplexity's computer tools, successfully complete tasks as intended only about 50% of the time."
"For humans, our continued learning process is essentially the process of building a world model for any profession, any environment."
"We believe for agents to become experts, they need to learn autonomously to build a model of any given micro world."
Investors are actively seeking AI researchers to create startups focused on improving AI reliability and efficiency. Yu Su, an Ohio State professor, founded NeoCognition, a startup developing self-learning AI agents, after recognizing the potential of foundational model advancements. NeoCognition has secured $40 million in seed funding to address the inconsistency of current AI agents, which only complete tasks correctly about 50% of the time. The goal is to create agents that can autonomously learn and specialize in various domains, similar to human learning processes.
Read at TechCrunch
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