"We didn't need dialogue," Norma Desmond tells a young screenwriter in "Sunset Boulevard," recalling her silent-film-era glory days. Screenwriters famously suffer all sorts of indignities--dumb studio notes, credit squabbles--but now and then they get to win Oscars. Norma's heyday was just fading when the first Academy Awards were held, in 1929; the three writing categories that year were Best Original Story, Best Adapted Story, and (for the first and last time) Best Title Writing. It took several decades for the categories to settle into the modern dichotomy of Best Adapted Screenplay and Best Original Screenplay, though the distinction can be tricky: originality, of course, is relative. This year's nominees draw on a wide range of sources, including the untold history of NASA, Jacques Demy musicals, science fiction, several lost mothers, and two plays about black life half a century apart.

Recent breakthroughs in machine learning and artificial intelligence mean AI-enabled technologies are gaining traction. The billion-dollar cybersecurity industry is no exception, as vendors begin to scale and automate their processes intelligently – all while locked into the early stages of a security arms race with professional hackers. A recent report from analyst firm ABI Research estimates that machine learning in cybersecurity will enormously bolster spending in big data, intelligence and analytics, reaching as much as $96 billion (£71.9 billion) by 2021. Vendors are likely to find buyers in large enterprises, and more than likely, across industries that are especially prone to attack: think government and defence, banking, and across the technology sector. At the moment, ABI's report says, User and Entity Behavioural Analytics – using machine learning for threat detection by analysing data at scale – is the driving force. "Using static machine learning models to detect previously unknown malware is the only use case I'm aware of that offers clear evidence of effective results," says cybersecurity analyst at 451 Research, Adrian Sanabria.

Every year, we are confronted with new facts and scenarios emerging out of climate change and global warming, each more terrifying and apocalyptic than the last. In fact, several well-known scientists and tech moguls have made predictions regarding them. Prominent linguist and public intellectual Noam Chomsky said last year that the COP22 Marrakech climate summit in Morocco, which began on Nov. 7, "basically ceased" to function on Nov.9 after the delegates were confronted with the news that Donald Trump was elected as the next U.S. president. Speaking to over 2,000 people at Riverside Church on Dec. 5, Chomsky also made several related climate change predictions. "The question that was left was whether it would be possible to carry forward this global effort to deal with the highly critical problem of environmental catastrophe, if the leader of the free world, the richest and most powerful country in history, would pull out completely, as appeared to be the case," Chomsky said.

We are at the point where computers and machines are no longer going to be simply tools. Computers are becoming, literally, part of us. "There are a couple of very interesting things happening as we speak facilitating humans and machines working together in a very different way," said Justin Sanchez, director of the Biological Technologies Office at DARPA. Smart exoskeletons help people with paralysis walk again, give soldiers extra strength and endurance, and implanted computer chips help the blind see again or help others feel a sense of touch in a prosthetic foot. It might not be a sci-fi vision of cyborgs, but a near future where soldiers might have implanted chips that help them communicate in the battlefield or receive information from GPS systems or drones.

Mini drones sporting horsehair coated in a sticky gel could one day take the pressure off beleaguered bee populations by transporting pollen from plant to plant, researchers said. Roughly three-quarters of the world's flowering plants and about 35 percent of the world's food crops depend on animals to pollinate them, according to the U.S. Department of Agriculture. Some of nature's most prolific pollinators are bees, but bee populations are declining around the world, and last month, the U.S. Fish and Wildlife Service listed a native species as endangered for the first time. Now, researchers from Japan said they've taken the first steps toward creating robots that could help pick up the slack from insect pollinators. The scientists created a sticky gel that lets a $100 matchbox-size drone pick up pollen from one flower and deposit it onto another to help the plants reproduce.

Major source contributions and support come from SYSTRAN. Basically it is: "A Modularized Translation Program using Seq2Seq Attention Model" 3. Features of OpenNMT Simple general-purpose interface, requires only source/target files. Speed and memory optimizations for high-performance multi-GPU training. Includes a dependency-free C translator for model deployment. Latest research features to improve translation performance.

My thirties started off in countries ravaged by environmental destruction and dictatorships. Back then, I was a journalist for National Geographic, spending most of my time abroad, even though I still called Los Angeles--my birth city--home. In the 100 countries I visited, I reported on some harrowing stories: the Killing Fields in Cambodia, the near total deforestation of Paraguay, and the tense nuclear stand-off between India and Pakistan. I always hoped my words and on-camera television commentary brought some sanity and peace to the chaos. While on assignment in Vietnam near the demilitarized zone, a near-miss with a landmine that could have been catastrophic sent me back home to the safety of the United States.

"Microsoft Monday" takes a look back at the past week of news related to Microsoft. This week, "Microsoft Monday" includes details about the acquisition of "Wiki" by Agile Extensions, a leaked Project NEON screenshot hinting at Windows 10 design changes, a federal judge ruling in favor of Microsoft in regards to the Justice Department lawsuit, the new suggested reminders feature for Cortana, Visual Studio 2017 launching on March 7th, the Surface Hub "Try & Buy Program" and more! In the past, Microsoft has been notorious for making design changes that did not sit well with consumers like we have seen in Windows Vista and Windows 8. Tom Hounsell, the creator of a Windows build tracker website called BuildFeed, published this leaked screenshot of the Windows 10 Project NEON design: The most notable Project NEON change is the removal of the window borders. This new user interface change could cause confusion in terms of resizing and moving windows. For example, some users may be confused about where to place the mouse in order to perform those functions.

Manipulation, bribery, and control are well-studied ways of changing the outcome of an election. Many voting rules are, in the general case, computationally resistant to some of these manipulative actions. However when restricted to single-peaked electorates, these rules suddenly become easy to manipulate. Recently, Faliszewski, Hemaspaandra, and Hemaspaandra studied the computational complexity of strategic behavior in nearly single-peaked electorates. These are electorates that are not single-peaked but close to it according to some distance measure. In this paper we introduce several new distance measures regarding single-peakedness. We prove that determining whether a given profile is nearly single-peaked is NP-complete in many cases. For one case we present a polynomial-time algorithm. In case the single-peaked axis is given, we show that determining the distance is always possible in polynomial time. Furthermore, we explore the relations between the new notions introduced in this paper and existing notions from the literature.

Math word problems provide a natural abstraction to a range of natural language understanding problems that involve reasoning about quantities, such as interpreting election results, news about casualties, and the financial section of a newspaper. Units associated with the quantities often provide information that is essential to support this reasoning. This paper proposes a principled way to capture and reason about units and shows how it can benefit an arithmetic word problem solver. This paper presents the concept of Unit Dependency Graphs (UDGs), which provides a compact representation of the dependencies between units of numbers mentioned in a given problem. Inducing the UDG alleviates the brittleness of the unit extraction system and allows for a natural way to leverage domain knowledge about unit compatibility, for word problem solving. We introduce a decomposed model for inducing UDGs with minimal additional annotations, and use it to augment the expressions used in the arithmetic word problem solver of (Roy and Roth 2015) via a constrained inference framework. We show that introduction of UDGs reduces the error of the solver by over 10 %, surpassing all existing systems for solving arithmetic word problems. In addition, it also makes the system more robust to adaptation to new vocabulary and equation forms .