Rhode Island Data Center News

Apr 6, 2026

Two New England states say no to new data centers

The Maine legislature has proposed a moratorium pausing new data center projects of 20 megawatts or more until November 2027 while the state studies environmental and electric grid impacts.

Main action: The proposed law would pause new projects of 20 megawatts or more until November 2027; the bill passed the Maine House with bipartisan support, is expected to clear the Senate, and Gov. Janet Mills reportedly backs the moratorium while supporting an exception for one planned project in Jay, Maine.
Background and related actions:Smithfield, Rhode Island (Town Council/Planning Board) is preparing a local ban with a two-year review requiring developers to request a use variance; at least 11 states have introduced temporary data center moratorium bills this session, and data centers are cited as consuming 183 TWh in 2024 (projected to 426 TWh by 2030) with examples such as data centers using ~26% of Virginia’s 2023 electricity supply.

Mar 26, 2026

Arm shifts course, moves into silicon business

Arm has announced it will expand into production silicon and launched the Arm AGI CPU with Meta as lead partner and first customer.

Main announcement: Arm is entering production silicon with the new Arm AGI CPU, positioned as a CPU purpose-built for agentic AI data centers, co-developed with Meta; the chip is designed by Ampere and will be manufactured by TSMC on a 3-nanometer process node. Key product specs announced include up to 136 Arm Neoverse V3 cores per CPU, 6GB/s memory bandwidth per core at sub-100ns latency, 300W TDP, claims of >2x performance per rack versus x86, support for 1U air-cooled deployments up to 8,160 cores per rack and liquid-cooled systems delivering 45,000+ cores per rack. Early systems are available now, with broader availability expected in the second half of the year.
Background and partners: The chip was designed and manufactured by Ampere (acquired by SoftBank for $6.5 billion last year). Arm confirmed additional commercial momentum with partners/customers including Cerebras, Cloudflare, F5, OpenAI, Positron, Rebellions, SAP, and SK Telecom, and is working with OEM/ODM partners ASRock Rack, Lenovo, Quanta Computer, and Supermicro for system deliveries. Independent analyst commentary (Jim McGregor, Tirias Research) raised questions about benchmark comparators and emphasized the AGI CPU is targeted at AI/accelerator orchestration rather than general-purpose enterprise CPU use.

Mar 16, 2026

Palantir partners with Nvidia to streamline AI data center deployment

Palantir Technologies and Nvidia have announced the Palantir AI OS Reference Architecture (AIOS-RA).

Main announcement: The AIOS-RA is an end-to-end reference architecture and operating system designed to support processes from hardware acquisition to application deployment, running both training and inference on Nvidia Blackwell Ultra systems (each system incorporates eight Blackwell Ultra GPUs and Spectrum-X Ethernet networking). It is built on a hardened Kubernetes substrate and integrates Palantir’s software suite (AIP, Foundry, Apollo, Rubix, AIP Hub) to serve as a blueprint for designing, deploying, and scaling high-performance on-premises, edge, and sovereign cloud AI factories.
Additional details / background: Management and security are handled via Palantir Rubix (zero-trust Kubernetes security) and Apollo (autonomous deployment and lifecycle oversight). The collaboration also includes Nvidia’s stack (Nvidia AI Enterprise, CUDA-X Libraries, Nemotron open models, Magnum IO) and targets customers with existing GPU infrastructure, latency-sensitive workflows, data sovereignty requirements, and high geographic distribution.

Mar 11, 2026

Datalec targets rapid infrastructure deployment with new modular data centers

Datalec Precision Installations has launched a next-generation Data Centre Modularization Solution to enable faster, more flexible deployment of data centre capacity for colocation providers, hyperscale and AI infrastructure teams.

Main announcement: Datalec launched a next-generation Data Centre Modularization Solution that shortens typical deployment timelines (company states a full build can fall from about 16 months to 10 months, and the design phase from 6 months to 2 months). Modules are engineered and manufactured through Datatec’s integrated production process, with a larger share of work done offsite to reduce onsite construction time and disruption.
Background and details: The solution targets standard server to AI/high-density compute use cases and offers bolt-on services including a digital wrapper (digital twinning, lifecycle and global support). Datalec manufactures specialized elements (cabinets, ceilings), provides design development and consulting, and competes with vendors such as Schneider Electric, Vertiv, and Flex.

Mar 11, 2026

Study finds significant savings from direct current power for AI workloads

Enteligent published a study promoting 800V DC for AI data centers and said it is conducting NDA-level tests and pilots of an 800V-to-50V converter with a formal product announcement planned within the next few weeks.

Study findings and claimed savings:50%–80% reduction in copper usage, 8%–12% reduction in annual energy-related OpEx, and $4 million–$8 million CapEx savings per 10 MW build for AI-first facilities; Enteligent positions 800VDC as enabling fewer conductors, lower current/heat, and simpler distribution.
Product and deployment details / timeline: CEO Sean Burke says Enteligent’s unreleased converter will partition 800V DC to 50V for servers; the company is at NDA testing and pilot programs now and plans a formal announcement within the next few weeks; Burke recommends greenfield all-DC builds and selective all-DC retrofits for high-power GPU deployments. Competitors noted include Vertiv, Rutherford, Siemens, and Eaton.

Feb 11, 2026

Climate Change Solutions - February 10, 2026

The Environmental and Energy Study Institute (EESI) published a newsletter highlighting climate risks to winter sports, related policy updates, and upcoming briefings and events.

Main announcement: EESI released coverage on climate impacts to winter sports at the 2026 Winter Olympics in Milan and Cortina D’Ampezzo, citing over $1 billion in losses in the United States and the closure of 265 ski resorts in Italy; the newsletter links to a feature article, a 30-minute podcast with sport ecologist Madeleine Orr, and an archival piece on ice rink refrigerant emissions (mitigation strategies and policy). It also promotes EESI articles on data center water use and a recorded briefing on grid optimization and energy efficiency.
Legislative and events details: The newsletter summarizes congressional activity and announces upcoming briefings and dates:
- Legislation: reintroduction/advancement of H.R.1355 (Weatherization Enhancement and Readiness Act), H.R.3474 (Federal Mechanical Insulation Act) reported to the House floor, S.688 (FISH Act of 2025) advanced in Senate, companion H.R.3756, and introduction of H.R.7257 (SECURE Grid Act).
- Events (dates/times/locations/subject):
  - Feb 20, 12:00 p.m. - 12:30 p.m. (online): “Frozen Infrastructure: Winter Storm Impacts on Communities and the Power Grid” — rapid readout on Winter Storm Fern impacts and recovery pathways.
  - Feb 26, 3:30 p.m. - 5:00 p.m., Rayburn House Office Building Gold Room (Room 2168) & online: “Understanding Load Growth and Energy Affordability” — factbook findings in partnership with BCSE (data center energy demand discussed).
  - Mar 3, 3:00 p.m. - 4:30 p.m., Russell Senate Office Building Room 385 & online (reception to follow): “Igniting Innovation: Progress and a Path Forward for Wildfire Policy” — solutions and federal policy strategies (costs cited: up to $424 billion annually to the U.S.).
  - Mar 12, 3:30 p.m. - 5:00 p.m., Rayburn House Office Building Gold Room (Room 2168) & online: “Strategies to Lower Utility Bills Now for Households and Small Businesses.”

Jan 26, 2026

Intel wrestling with CPU supply shortage

Intel said it expects CPU supply to improve after Q1 following its Q4 2025 earnings call and accompanying statement by CFO David Zinsner.

Main announcement/action:Intel stated its factory network will improve available supply beginning in Q2 and for each remaining quarter in 2026 (CFO David Zinsner). The company said the CPU shortage is peaking this quarter, is impacting the data center/server business, and that Intel is prioritizing mid-/high-end client chips and shifting excess capacity to data center customers. It announced a simplified server roadmap focusing on 16-channel Diamond Rapids, accelerating Coral Rapids (reintroducing multithreading) and a custom Xeon integrated with Nvidia NVLink.
Background/details: Q4 2025 revenue declined 4% year-over-year to $13.7 billion; the Data Center and AI segment revenue grew 9% YoY to $4.7 billion, and Intel said revenue would have been meaningfully higher if it had more supply. Intel cited yields on the 18A process node improving month-over-month with a target of 7%–8% improvement each month. This content is reporting from Intel’s earnings call and an accompanying statement (not an opinion piece).

Jan 23, 2026

Reports of SATA’s demise are overblown, but the technology is aging fast

Rumors reported that Samsung would phase out SATA SSD production in 2026, which Samsung denied; the article analyzes the industry momentum toward NVMe and the remaining use cases for SATA.

Main announcement/context: The article describes a report that Samsung would phase out SATA-based SSD production in 2026 (Samsung has denied the reports). Micron also shifted away from consumer (Crucial) toward enterprise products. IDC market share cited: Samsung 15%–18%. Performance figures:SATA III ~550 MB/s vs PCIe 5.0 NVMe up to 16 GB/s (benchmarks ~14 GB/s). Form factors: SATA uses 2.5-inch drives with cables; NVMe commonly uses M.2 (no cables).
Background and details:SATA history: debuted as SATA 1.0 in 2003, advanced to SATA III in 2009 (no SATA IV). Enterprise usage: vendors like Seagate and Western Digital still supply 20 TB and 30 TB SATA drives for cloud cold storage. Analysts quoted: Bob O’Donnell (TECHnalysis Research) and Rob Enderle (The Enderle Group), who note consumer SATA is declining but high-capacity SATA remains in legacy and cold-storage roles.

Jan 20, 2026

What’s causing the memory shortage?

TrendForce and industry analysts (Tom Mainelli of IDC and Jim Handy of Objective Analysis) warn that the DRAM memory shortage driven by AI-oriented data center buildouts will extend into 2027.

TrendForce projectsDRAM prices will rise 50%–55% this quarter versus Q4 2025; the market is concentrated among three major suppliers: Micron, SK Hynix, Samsung and analysts say the shortage will last at least into 2027 with capacity expansion taking 12–18 months or longer.
HBM adoption is diverting wafer capacity because an HBM byte uses ~3x silicon per DDR byte, forcing memory makers to build new fabs with long equipment lead times; OEMs are currently absorbing higher costs, tariffs are not a factor, and smaller Chinese vendors are considered too small to materially increase supply.

Jan 19, 2026

What's your AI footprint? Tech has an environmental cost

The Arizona Republic reports research and expert analysis quantifying AI’s environmental footprint and the resource demands of data centers.

Main finding and announcement: Reporting highlights research (Cornell; Jegham & Li) estimating that AI growth could emit 24 to 44 million metric tons CO2 annually by 2030 and use water comparable to 6 to 10 million American households; study-level details include per-query and scaled impacts (e.g., 700 million queries/day ≈ electricity of 35,000 U.S. homes and freshwater for 1.2 million people).
Background and study details: The piece summarizes multiple studies and expert comments: on-site cooling and off-site power-plant water use, a measurement showing GPT-3 training used water equal to two Olympic-size pools, location-specific metrics (Arizona: 17-ounce water bottle per 16 GPT-3 queries), and recommendations from researchers (Jegham, Pengfei Li) that developers measure and improve model resource efficiency.

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