Murakkab: accelerating and making agentic AI workflows more energy-efficient

Colleagues, a brief AI update: researchers at MIT and Microsoft have unveiled Murakkab — a system for optimizing multi-step agentic workflows.

Key points:
- Automatically selects models and tools from natural-language descriptions.
- Dynamically configures hardware and scheduling to balance speed, accuracy and cost.
- In tests, reduced compute by ~35%, energy consumption by ~27%, and lowered expenses.

Why it matters: resource savings are critical for scalable cloud AI applications.

Do you think cloud providers are ready to adopt such solutions?

#AI #cloud #energyefficiency #machinelearning