Resources

  Learn how cross-layer coordination—power, cooling, scheduling—unlocks stranded data center capacity for AI inference. By prioritizing latency-tolerant workloads, operators can gain boost throughput.

  Artificial intelligence is growing fast, and everyone talks about GPUs, models, and data. According to Hammerhead founder Rahul Kar, the real constraint is something more basic. It is power. He believes that how the industry manages power will shape the next decade of AI

  Hammerhead AI has emerged from stealth after raising a $10 million seed round to tackle power constraints in large-scale AI infrastructure. The company is targeting AI data centers, where GPUs are being deployed faster than operators can secure power, leaving some systems running at 30–50 percent of their potential. Hammerhead claims that this results […]

  The extensive energy demands of artificial intelligence are causing a bottleneck in data centers, and Hammerhead AI Inc. wants to do something about it after raising $10 million in seed funding today.

  AutoGrid Veterans Unveil Orchestrated Reinforcement Learning (RL) Control Agents to Maximize AI Tokens and Accelerate AI Deployment Without Waiting For The Grid.

  The conversation around data center load flexibility has reached a fever pitch, largely precipitated by the landmark Duke University paper earlier this year that argued a small amount of curtailment could free up massive amounts of capacity on the grid. Much of the conversation in the months since has centered on how data centers […]