Max Smolaks

1 week ago | intelligence.uptimeinstitute.com | Max Smolaks

Intelligence Resource How can the grid become more sustainable and reliable? What steps can the data center industry take to maintain grid stability, better integrate renewables, and shorten interconnect queues and times? Join Uptime experts on as they discuss and answer questions on grid demands and sustainability strategies while debating how to meet decarbonization goals. The series is an exclusive benefit available only to Uptime Network Members and Uptime Intelligence subscribers.

3 weeks ago | intelligence.uptimeinstitute.com | Max Smolaks

Specialized IT hardware designed to perform generative AI training and inference is much more efficient at the job than generic IT systems. However, it is becoming clear that GPU-heavy servers are subject to many of the same problems that negatively impact the efficiency of traditional enterprise IT: low infrastructure utilization, high idle power and wasteful peak performance states. The data center industry is at the precipice of an escalating power problem.

1 month ago | silicon.co.uk | Todd R. Weiss |Peter Judge |Michelle Maisto |Max Smolaks

Low energy ARM processors are ready to take over the data centre. They need some software, and the Raspberr Pi can help, says Peter Judge

1 month ago | intelligence.uptimeinstitute.com | Max Smolaks

The specialized IT equipment required to perform AI training and inference is relatively new. These devices are expensive and need to be used effectively, especially GPUs for AI. Yet research literature, disclosures by AI cluster operators and model benchmarks suggest that — similarly to other types of IT infrastructure — GPU resources are often wasted. Many AI teams are unaware of their actual GPU utilization, often assuming higher levels than those achieved in practice.

2 months ago | intelligence.uptimeinstitute.com | Max Smolaks

UII UPDATE 354 | APRIL 2025 Intelligence Update “Reasoning” models — and their offshoots, such as “deep research” — have emerged as a major trend in generative AI, helping improve the accuracy and reliability of responses to complex problems. However, this approach significantly increases the computational costs of generating responses.