Tag: simulation
-
The Register: Cadence invites you to play with Nvidia’s biggest iron in its datacenter tycoon sim
Source URL: https://www.theregister.com/2025/09/10/cadence_systems_adds_nvidias_biggest/ Source: The Register Title: Cadence invites you to play with Nvidia’s biggest iron in its datacenter tycoon sim Feedly Summary: Using GPUs to design better bit barns for GPUs? It’s the circle of AI With the rush to capitalize on the gen AI boom, datacenters have never been hotter. But before signing…
-
Slashdot: Microsoft’s Analog Optical Computer Shows AI Promise
Source URL: https://hardware.slashdot.org/story/25/09/08/0125250/microsofts-analog-optical-computer-shows-ai-promise?utm_source=rss1.0mainlinkanon&utm_medium=feed Source: Slashdot Title: Microsoft’s Analog Optical Computer Shows AI Promise Feedly Summary: AI Summary and Description: Yes Summary: The text discusses a project by Microsoft Research involving an analog optical computer (AOC) designed for AI workloads, significantly enhancing computation speed and energy efficiency compared to traditional GPUs. The initiative offers opportunities for…
-
Slashdot: Google’s New Genie 3 AI Model Creates Video Game Worlds In Real Time
Source URL: https://tech.slashdot.org/story/25/08/05/211240/googles-new-genie-3-ai-model-creates-video-game-worlds-in-real-time?utm_source=rss1.0mainlinkanon&utm_medium=feed Source: Slashdot Title: Google’s New Genie 3 AI Model Creates Video Game Worlds In Real Time Feedly Summary: AI Summary and Description: Yes Summary: Google DeepMind’s release of Genie 3 marks a significant advancement in AI capabilities, specifically in the realm of interactive 3D environment generation. The ability for users and AI…
-
Cloud Blog: Understanding Calendar mode for Dynamic Workload Scheduler: Reserve ML GPUs and TPUs
Source URL: https://cloud.google.com/blog/products/compute/dynamic-workload-scheduler-calendar-mode-reserves-gpus-and-tpus/ Source: Cloud Blog Title: Understanding Calendar mode for Dynamic Workload Scheduler: Reserve ML GPUs and TPUs Feedly Summary: Organizations need ML compute resources that can accommodate bursty peaks and periodic troughs. That means the consumption models for AI infrastructure need to evolve to be more cost-efficient, provide term flexibility, and support rapid…