Every GPU cluster has dead time. Training jobs finish, workloads shift and hardware sits dark while power and cooling costs keep running. For neocloud operators, those empty cycles are lost margin.The [...]
AI engineers often chase performance by scaling up LLM parameters and data, but the trend toward smaller, more efficient, and better-focused models has accelerated. The Phi-4 fine-tuning methodology [...]
For more than a decade, Nvidia’s GPUs have underpinned nearly every major advance in modern AI. That position is now being challenged. Frontier models such as Google’s Gemini 3 and Anthropic’s [...]
Google Cloud is introducing what it calls its most powerful artificial intelligence infrastructure to date, unveiling a seventh-generation Tensor Processing Unit and expanded Arm-based computing optio [...]
The prevailing assumption in AI development has been straightforward: larger models trained on more data produce better results. Nvidia's latest release directly challenges that size assumption â [...]
The tools are available to everyone. The subscription is company-wide. The training sessions have been held. And yet, in offices from Wall Street to Silicon Valley, a stark divide is opening between w [...]
ScaleOps has expanded its cloud resource management platform with a new product aimed at enterprises operating self-hosted large language models (LLMs) and GPU-based AI applications. The AI Infra Prod [...]