Because of a plethora of data from sensor networks, Internet of Things devices and big data resources combined with a dearth of data scientists to effectively mold that data, we are leaving many important applications – from intelligence to science and workforce management – on the table.
It is a situation the researchers at DARPA want to remedy with a new program called Data-Driven Discovery of Models (D3M). The goal of D3M is to develop algorithms and software to help overcome the data-science expertise gap by facilitating non-experts to construct complex empirical models through automation of large parts of the model-creation process. If successful, researchers using D3M tools will effectively have access to an army of “virtual data scientists,” DARPA stated.
+More on Network World: Feeling jammed? Not like this I bet+
This army of virtual data scientists is needed because some experts project deficits of 140,000 to 190,000 data scientists worldwide in 2016 alone, and increasing shortfalls in coming years. Also, because the process to build empirical models is so manual, their relative sophistication and value is often limited, DARPA stated.
Computer chips have stopped getting faster. For the past 10 years, chips’ performance improvements have come from the addition of processing units known as cores.
In theory, a program on a 64-core machine would be 64 times as fast as it would be on a single-core machine. But it rarely works out that way. Most computer programs are sequential, and splitting them up so that chunks of them can run in parallel causes all kinds of complications.
In the May/June issue of the Institute of Electrical and Electronics Engineers’ journal Micro, researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) will present a new chip design they call Swarm, which should make parallel programs not only much more efficient but easier to write, too.
This 1-min video centered on transhumanism aired across the country today on many Fox channels. It’s part of a new news show for millennials:
Presidential candidate Zoltan Istvan is putting science at the forefront of his politics.
On social? Let’s be friends! @top30tv
Good news alien hunters! A Kickstarter to fund a year-long investigation into KIC 8462852—the star voted most likely to harbor an advanced alien civilization—just got funded. Alien megastructure or not, we may finally get to the bottom of this bewildering, flickering star.
This crowdfunding campaign was set up in May by Yale astronomer Tabby Boyajian, and it managed to meet its $100,000 goal in just 30 days. A $10,000 surge in the last 100 minutes of the campaign managed to put the project over the top. The next step is to figure out the logistics, but Boyajian, who’s been leading the research into KIC 8462852, says observations could start as early as later this summer.
The ultimate goal of the project will be to determine why this star’s light dims at such irregular intervals, and at times by as much as 20 percent. These huge dips in luminosity are way too large to be a passing planet, hence the suspicion the anomaly is being caused by swarms of comets, a distorted star, some unknown astronomical phenomenon—or an advanced alien civilization in the process of building a gigantic solar array around the star.
Posted in governance, neuroscience, robotics/AI
OpenAI’s mission is to build safe AI, and ensure AI’s benefits are as widely and evenly distributed as possible. We’re trying to build AI as part of a larger community, and we want to share our plans and capabilities along the way. We’re also working to solidify our organization’s governance structure and will share our thoughts on that later this year.
Our metric
Defining a metric for intelligence is tricky, but we need one to measure our progress and focus our research. We’re thus building a living metric which measures how well an agent can achieve its user’s intended goal in a wide range of environments.
