
Microsoft has spent all year telling communities that when it brings a new data center into their area, it is committed to being a “good neighbor." It will pay local property taxes that support local hospitals, schools, parks, and libraries, and it will invest in “vital services the community cares about,” the company promised. And it has sent liaisons into those communities to learn what those needs are. But ask those liaisons how much the company is willing to invest, and the answers can be ha
Microsoft has promised to be a "good neighbor" in communities where it builds data centers by investing in local services, but church and community groups say the company's actual financial commitments fall far short of what it should contribute. A local Indiana organization proposed that Microsoft commit to donating a small percentage of its annual data center costs through a binding agreement, suggesting that even 1 percent could add tens of millions annually to community programs. The proposal matters because data center developers receive hundreds of millions in state tax breaks across multiple states, while communities lose significant tax revenue that once supported schools, hospitals, and other services. Microsoft has not publicly responded to the community group's proposal, and similar binding commitments are not yet common practice among data center developers, though some states have introduced legislation requiring such community benefits agreements.

Under the One Big Beautiful Bill Act, data center projects in rural areas could be eligible for major tax benefits starting next year. Some hyperscalers do not seem eager to take the free cash.

The price of anything with memory is skyrocketing thanks to AI. Aging streaming devices are no exception.
NVIDIA announced a new 64GB configuration of DGX Spark — from Acer, ASUS, Dell, Gigabyte, HP and MSI — its GB10-powered desktop AI system. It gives developers a way to start with one system for local models and agents, then cluster two 64GB units for 128GB of memory across the cluster and more compute when workloads grow. The direct message is: Run open models and always-on agents on your own desk, then cluster DGX Spark system as the work grows – instead of on a metered API. The ti
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