WEDNESDAY, APR01
1. Imagine IF meets The Bitcoin Standard, 2. Mined in America Act, 3. Hashrate relocates, 4. Princeton challenges monolithic AI
From Proto and Bitkey - part of the Bitcoin ecosystem at Block, Inc.
1. imagine
Gabrielle J. Frei, writing on Medium, recounts how attending Bitcoin Park’s Imagine IF conference catalyzed a deeper study of Saifedean Ammous’s The Bitcoin Standard and reshaped her understanding of money itself. Frei, who broke into the digital assets space over the past year while researching a startup at the intersection of digital assets and law, argues that the book’s opening chapters on monetary history are its most potent contribution. She highlights Ammous’s framing of proof-of-work security, noting his observation that “the security of Bitcoin lies in the asymmetry between the cost of solving the proof-of-work necessary to commit a transaction to the ledger and the cost of verifying its validity.” The piece walks readers through Bitcoin’s technical architecture from hashing to the 51% attack threshold, landing on a personal conclusion that Bitcoin’s lasting role is as a decentralized store of value and a political symbol of individual sovereignty in the digital age.
-EDITOR·OP_DAILY2. reshoring
Republican Senators Bill Cassidy and Cynthia Lummis introduced the Mined in America Act, a bill that would establish a federal certification program for domestic bitcoin mining operations, phase out reliance on foreign-manufactured hardware, and codify Donald Trump’s Strategic Bitcoin Reserve executive order into statute. According to Micah Zimmerman, the legislation directs the Department of Commerce to develop reshoring initiatives for mining hardware manufacturing to reduce dependence on Chinese-built ASICs. “Digital asset mining is a big part of our economy. We should be doing it here in America,” Cassidy said in a statement. Lummis framed the bill as part of a broader effort to position the United States as a global hub for digital assets. The move to codify the Strategic Bitcoin Reserve into law is the more structurally significant element, transforming what is currently an executive order into durable legislative policy that would require congressional action to reverse.
-EDITOR·OP_DAILY3. hashrate
According to Billy Boone in The Bitcoin Mining Investor, public bitcoin miners have signed $70 billion in AI data center contracts and may draw 70% of their revenue from AI hosting by the end of 2026, up from roughly 30% today. The pivot is driven by brutal post-halving economics: miner debt surged 500% to $12.7 billion in a single year, hashprice fell 44%, and the weighted average cost to produce one bitcoin among public miners now sits near $80,000. Boone frames the exodus not as a death spiral but as a sorting mechanism, arguing that “the network does not care who leaves. It reprices the reward for those who remain.” Cheap ASIC hardware liquidated by departing public miners is flowing to stranded gas operators in the Permian Basin, where spot gas prices went negative on 38 of 51 trading days in 2026, and to international hydro sites running at one to three cents per kilowatt-hour. The infrastructure leaves, but the hashrate simply relocates.
-EDITOR·OP_DAILY4. scaling
A Princeton research team led by Niraj K. Jha has published a paper on arXiv arguing that the generative AI industry’s pursuit of artificial general intelligence through ever-larger monolithic models is colliding with hard physical constraints including grid failures, water consumption, and diminishing returns on data quality. The paper proposes an alternative: “domain-specific superintelligence,” or DSS, built from societies of small specialist models coordinated by orchestration agents rather than a single massive generalist. The authors note that the dominant energy burden has shifted from one-time training runs to “recurring, unbounded inference,” a cost that reasoning models inflate by orders of magnitude per query. Their framework pairs knowledge graphs and formal logic with compact language models, enabling what they describe as intelligence that can “migrate from energy-intensive data centers to secure, on-device experts.” The proposal reframes the AI scaling debate around composability and efficiency rather than raw parameter count, with direct implications for how energy infrastructure is allocated to AI workloads.
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