Too Many Secrets, the Greatest Math Discovery, and More
The Wikileaks publication of tens of thousands of classified U.S. military records last week is inevitably prompting a review of information security practices to identify remedial steps. I have been arguing that one of those steps ought to be a rethinking of classification policy. “The reform that may be needed more urgently than any other is a careful reduction in the size of the secrecy system.” See “Afghan Leaks: Is the U.S. Keeping Too Many Secrets?” by Alex Altman, Time, July 30.
The Department of Defense has updated its doctrine on “foreign internal defense,” which refers to actions taken to support a foreign government’s efforts to combat domestic subversion, insurgency or terrorism. See Joint Publication 3-22, “Foreign Internal Defense,” July 12, 2010.
“The Army in Multinational Operations” is the subject of a newly updated U.S. Army Field Manual, FM 3-16, May 2010.
Michel de Montaigne (1533-1592), whose essays transformed Western consciousness and literature, was not capable of solving basic arithmetic problems. And most other people would not be able to do so either, if not for the invention of decimal notation by an unknown mathematician in India 1500 years ago. That is the contention of a neat little essay recently published by the Department of Energy (based in part on a book by Georges Ifrah). See “The Greatest Mathematical Discovery?” by David H. Bailey and Jonathan M. Borwein, May 12, 2010.
The NCARS Act would amend the National Security Act of 1947 to establish a durable, coordinated federal approach to national resilience.
Federal data is a diverse ecosystem with well over 500,000 datasets – including those tackling Alzheimer’s disease and related dementias (ADRD).
To build an affordable, modern grid powered by clean energy, we need more than the right policies; we must also upgrade—and, in some cases, redesign—PUCs to regulate in the public interest and effectively implement new policies.
X-Labs seek to expand on what FROs have shown is possible: the generation of foundational infrastructure for entire new fields of research science.