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4 resources
Academic initiative edited by Seth Lazar, Jeffrey Howard and Rachel Sterken, with an annual conference and planned open-access Oxford University Press volume. The public site describes its scope, paper submission rules and AI usage policy; it is not a published research paper.
Company building thermodynamic computing hardware it claims is far more energy efficient than GPUs.
From the site: Building thermodynamic computing hardware that is radically more energy efficient than GPUs.
Why I recommend it: The energy cost of AI is becoming the constraint, and this is one bet on solving it in hardware. The efficiency claims are the company's own and unproven at scale.
Official news from CERN, the European particle physics laboratory: accelerator and experiment updates, computing and engineering write-ups, and knowledge-sharing pieces, filterable by topic and audience (general public, students, educators, policymakers). Free to read, no account.
Why I recommend it: Worth following if you want technology news written by the people doing the work rather than by a tech press cycle. The Computing and Knowledge sharing topics are the useful filters for a career audience — CERN publishes plainly about large-scale computing, data handling and open-source work, and the writing is aimed at non-specialists.
A body of writing and practice on computing that lasts — repairable hardware, small software, low energy use.
Why I recommend it: The counterweight to "more compute solves everything".
