Lifeboat Foundation

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+

Continue reading “DARPA wants to design an army of ultimate automated data scientists” »

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.

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.

Continue reading “New chip design makes parallel programs run many times faster and requires one-tenth the code” »

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.

These autonomous robots are high-tech security guards.

Just another one of Musk’s ambitious predictions, or inevitable truth?

Working like a CEO; hmmm. Do they realize how hard many CEOs work? I am not talking about the Jamie Diamons or the Bezos of the world; but the majority CEOs in the world.

Get ready for a team of automated assistants.

Will the good bots finish last in the war of bots? Dark bots are definitely not that easily stopped by AI in companies.

The bot era is here, and the world has already begun to see its transformative potential. But like any technology, there will be bad bots as predictably as good ones. With every advancement, there are people looking to exploit it. Anticipating what they might do is key so that builders, developers, and users can prevent, preempt, and prepare.

Here are the “dark bots” we’re likely to see:

Continue reading “Dark bots: The cat-and-mouse game begins” »

Nice.

DARPA intends to ease the talent gap of data scientists with more complex A.I.