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Category: robotics/AI

The Defense Advanced Research Projects Agency has launched its Data-Driven Discovery of Models program that aims to automate aspects of data science to help non-experts construct their own empirical models.

DARPA said Friday D3M looks to address a data science expertise gap the agency says is reflected by lack of results for predictive questions among popular search engines.

“The construction of empirical models today is largely a manual process, requiring data experts to translate stochastic elements, such as weather and traffic, into models that engineers and scientists can then ask questions of,” said Wade Shen, a DARPA program manager in the information innovation office.

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Whether referred to as AI, machine learning, or cognitive systems, such as IBM Watson, a growing cadre of business leaders is embracing this opportunity head on.

That’s because their consumers are using cognitive applications on a daily basis — through their phones, in their cars, with their doctors, banks, schools, and more. All of this consumer engagement is creating 2.5 quintillion bytes of data every day. And thanks to IT infrastructures designed for cognitive workloads — that can understand, reason, and learn from all this data — organizations and entire industries are transforming and reaping the benefits.

What’s important to remember is that this sci-fi-turned-reality-show of cognitive computing cannot happen without the underlying systems on which the APIs, software, and services run. For this very reason, today’s leading CIOs are thinking differently about their IT infrastructure.

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Your next sex-buddy may be made of silicone, designed to your specifications and willing to put up with even your most outrageous quirks – much to Noel Sharkey’s chagrin. The emeritus professor of robotics at Sheffield University in the UK is blowing up over the proliferation of realistic sex dolls.

According to the Daily Mail, Sharkey and other academics are voicing concern about the dolls and a new generation of sex-bots that may one day have full-blown speech recognition.

At that point, the profs warn, fabricated mates may become as prevalent as Internet porn and wreak havoc with our love lives. “What if it’s your first time? Your first relationship?” Sharkey asks. “What [will] you think a man or woman is? It will get in the way of real life, stopping people from forming relationships with normal people.”

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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.

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Hmmm; ok.

Artificial intelligence visionaries from academia, government and industry meet to discuss how to responsibly integrate ever-evolving AI technology into the real world in such a way that all can benefit.

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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- 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.

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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.

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