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technologyreview.com·3h ago
AI Research
BAIR Blog·29d ago·5 min read
Intelligence is Free, Now What? <br> Data Systems for, of, and by Agents
TL;DR
As AI inference costs plummet, data systems must adapt to support agent-based workloads. New challenges arise in designing systems for agents rather than humans.
✦ Why It Matters
Engineers should start redesigning data architectures to optimize for agent-based interactions and workflows.
Key Takeaways
- Redesign data systems to accommodate agent interactions.
- Explore structured memory for efficient data retrieval.
- Implement agentic speculation in data processing.
- Monitor AI cost trends to inform system upgrades.
Full Summary
AI capabilities are becoming increasingly affordable, with costs for models like GPT-4 dropping from $30 to under $1 per million tokens in just a year. This trend indicates a shift towards an era of nearly free intelligence, suitable for everyday knowledge work.
As a result, data systems will need to evolve to accommodate agents—automated entities that perform tasks on behalf of users. Key challenges include redesigning data architectures to handle the unique characteristics of agents, which differ significantly from human users.
The authors propose exploring new methodologies such as agentic speculation and structured memory to create custom data systems. These innovations could lead to more efficient data processing and management, ultimately transforming how knowledge work is conducted.