When William Legrand finally decrypted the string, it did not seem to make much more sense than it did before. But at least it did sound more like natural language, and eventually guided the main character of Edgar Allan Poe's "The Gold-Bug"36 to discover the treasure he had been after. Legrand solved a substitution cipher using symbol frequencies. He first looked for the most frequent symbol and changed it into the most frequent letter of English, then similarly inferred the most frequent word, then punctuation marks, and so on. Both before and after 1843, the natural impulse when faced with some mysterious message has been to count frequencies of individual tokens or subassemblies in search of a clue. Perhaps one of the most intense and fascinating subjects for this kind of scrutiny have been biosequences. As soon as some such sequences became available, statistical analysts tried to link characters or blocks of characters to relevant biological functions.

Marvin Minsky, an American scientist working in the field of artificial intelligence (AI) who co-founded vthe Massachusetts Institute of Technology (MIT) AI laboratory, wrote several books on AI and philosophy, and was honored with the ACM A.M. Turing Award, passed away on Sunday, Jan. 24, 2016 at the age of 88. Born in New York City, Minsky attended the Ethical Culture Fieldston School, the Bronx High School of Science, and Phillips Academy, before entering the U.S. Navy in 1944. After leaving the service, he attended Harvard University, where he earned a bachelor's degree in mathematics in 1950. He then went to Princeton University, where he built the first randomly wired neural network learning machine, the Stochastic Neural Analog Reinforcement Calculator (SNARC), before earning his Ph.D in mathematics there in 1954. Doctorate in hand, Minsky was admitted to the group of Junior Fellows at Harvard, where he invented the confocal scanning microscope for thick, light-scattering specimens, decades in advance of the lasers and computer power needed to make it useful; today, it is in wide use in the biological sciences.

Zittrain, J. Engineering an election – digital gerrymandering poses a threat to democracy.

The four-color map theorem says no more than four colors are required to color the regions of a two-dimensional map so no two adjacent regions have the same color. Over the past two decades, mathematicians have succeeded in bringing computers to bear on the development of proofs for conjectures that have lingered for centuries without solution. Following a small number of highly publicized successes, the majority of mathematicians remain hesitant to use software to help develop, organize, and verify their proofs. Yet concerns linger over usability and the reliability of computerized proofs, although some see technological assistance as being vital to avoid problems caused by human error. Troubled by the discovery in 2013 of an error in a proof he co-authored almost 25 years earlier, Vladimir Voevodsky of the Institute for Advanced Study at Princeton University embarked on a program to not only employ automated proof checking for his work, but to convince other mathematicians of the need for the technology.

U.S. President Barack Obama discussing his Computer Science for All plan to give students across the country the chance to learn computer science in school. In late January, U.S. President Barack Obama asked Congress to approve 4.1 billion in spending in the coming fiscal year to support the Computer Science for All initiative, aimed at providing computer science education in U.S. public schools. Obama pointed out computer science is no longer "an optional skill" in the modern economy," yet "only about a quarter of our K–12 (kindergarten through 12th grade) schools offer computer science. Twenty-two states don't even allow it to count toward a diploma." While many organizations have contributed to the national effort to see real computer science exist and count toward graduation requirements in U.S. public schools, former ACM CEO John R. White said, "ACM has been there from the beginning." Indeed, White contends Obama's Computer Science for All initiative "in a way represents the ...

More than 20% of U.S. adults live with some form of disability, according to a September 2015 report released by the U.S. Centers for Disease Control and Prevention. The latest generation of smartphones, tablets, and personal computers are equipped with accessibility features that make using these devices easier, or at least, less onerous, for those who have sight, speech, or hearing impairments. These enhancements include functions such as screen-reading technology (which reads aloud text when the user passes a finger over it); screen-flashing notification when a call or message comes in for the hearing impaired; and voice controls of basic functions for those who are unable to physically manipulate the phone or computing device's controls. Other technologies that can help the disabled have or are coming to market, and not all of them are focused simply on providing access to computers or smartphones. Irrespective of the accessibility provided, most market participants agree more needs to be done to help those with disabilities to fully experience our increasingly digital world.

Secretary of Defense Ash Carter is just out of frame on the right side of the screen. As soon as it was airborne, the drone flying inside West Point crashed to the ground at the feet of Secretary of Defense Ash Carter. The soldier responsible for the drone's demise gently lowered the weapon, no smoke wafting from its barrel, not even a sound made with the shot. Built by the Army Cyber Institute at West Point, the rifle was demonstrated last fall at the Association of the United States Army exposition in Washington, DC. Unlike pretty much every other variety of gun, this rifle doesn't shoot any projectiles.

It is widely regarded as one of the greatest human achievements ever made, but putting a man on the moon was no cheap undertaking. The Apollo missions to send just 12 men onto the dusty lunar surface cost 25 billion ( 17 billion) – estimated to be worth around 170 billion ( 120 billion) in modern monetary value. But it appears we may be able to send humans back to our rocky satellite and set up a permanent base where they could live for just a fraction of the cost. The cost of building a base on the moon could be a fraction of what has been previously expected. Scientists say it may be possible to build a permanent base (illustrated) housing 10 people within the next five to seven years for around 10 billion.

Following in the wake of the recent trouncing of humans by artificial intelligence platform AlphaGo, Google has announced the launch of a cloud-based machine learning platform. The search giant's new large-scale platform will be able to learn and make predictions'across a whole variety of scenarios', and is reminiscent of the fictional Skynet service from Terminator. A limited preview of the service is now available for users to build their own machine-learning models'that work on any type of data, of any size'. Following in the wake of the recent trouncing of humans by artificial intelligence platform AlphaGo, Google has announced the launch of a cloud-based machine learning platform. The search giant's new large-scale platform will be able to learn and make predictions'across a whole variety of scenarios' A limited preview of the service is now available for users to build their own machine-learning models'that work on any type of data, of any size'.

Google had an announcement that means strictly business for its push to be known as a leader in cloud services. "Today [Wednesday], "we've taken a major stride forward with the announcement of a new product family: Cloud Machine Learning." The move is all about taking Cloud Machine Learning mainstream, "giving data scientists and developers a way to build a new class of intelligent applications," according to a post from Fausto Ibarra, director, product management, Google Cloud Platform. Blair Hanley Frank of IDG News Service said in so doing, that "Google is making it easier for businesses to take advantage of the machine learning revolution with a new product for building models that predict the future." Cade Metz in Wired said "the company unveiled a new family of cloud computing services that allow any developer or business to use the machine learning technologies that power some of Google's most powerful services." Basically, as Robert Hof in SiliconANGLE put it, "Now that Google has infused the brand of artificial intelligence known as machine learning into everything from search to speech recognition, it's tossing the technology it views as tech's next big wave into the public domain." The announcement was part of events at a two day conference in San Francisco, namely the Google Cloud Platform (GCP) Next 2016. The company said the Cloud Machine Learning provides machine learning services, with pre-trained models and platform so that a person can generate his or her own tailored models. Major Google applications use Cloud Machine Learning, including Photos (image search), the Google app (voice search), Translate, and Inbox (Smart Reply)--but now their platform is available as a cloud service for business applications. Google is not shy about blowing its own horn when it comes to machine learning technology: Compared to other large scale deep learning systems, said Google, "Our neural net-based ML platform has better training performance and increased accuracy." This announcement may be filed under strategy. Robert Hof made the observation: "Google made it clear that it intends to pitch the Cloud Machine Learning services announcement as a key differentiator.