Lifeboat Foundation

The possibility of time travel through the geodesics of vacuum solutions in first order gravity is explored. We present explicit examples of such geometries, which contain degenerate as well as nondegenerate tetrad fields that are sewn together continuously over different regions of the spacetime.

These classical solutions to the field equations satisfy the energy conditions.

Over the last few years, Google and Coursera have regularly teamed up to launch a number of online courses for developers and IT pros. Among those was the Machine Learning Crash course, which provides developers with an introduction to machine learning. Now, building on that, the two companies are launching a machine learning specialization on Coursera. This new specialization, which consists of five courses, has an even more practical focus.

The new specialization, called “Machine Learning with TensorFlow on Google Cloud Platform,” has students build real-world machine learning models. It takes them from setting up their environment to learning how to create and sanitize datasets to writing distributed models in TensorFlow, improving the accuracy of those models and tuning them to find the right parameters.

As Google’s Big Data and Machine Learning Tech Lead Lak Lakshmanan told me, his team heard that students and companies really liked the original machine learning course but wanted an option to dig deeper into the material. Students wanted to know not just how to build a basic model but also how to then use it in production in the cloud, for example, or how to build the data pipeline for it and figure out how to tune the parameters to get better results.

Continue reading “Google and Coursera launch a new machine learning specialization” »

Why do artificial intelligent algorithms sound like a human? Why do AI robots look human? This article looks at why AI algorithms and robots are created to look and sound like a human.

Professor Daniel Kahneman was awarded a Nobel Prize for his work on the psychology of judgment and decision-making, as well as behavioral economics. In this age of human/machine collaboration and shared learning, IDE Director, Erik Brynjolfsson, asked Kahneman about the perils, as well as the potential, of machine-based decision-making. The conversation took place at a recent conference, The Future of Work: Capital Markets, Digital Assets, and the Disruption of Labor, in New York City. Some key highlights follow.

P rofessor Daniel Kahneman was awarded a Nobel Prize for his work on the psychology of judgment and decision-making, as well as behavioral economics. In this age of human/machine collaboration and shared learning, IDE Director, Erik Brynjolfsson, asked Kahneman about the perils, as well as the potential, of machine-based decision-making. The conversation took place at a recent conference, The Future of Work: Capital Markets, Digital Assets, and the Disruption of Labor, in New York City. Some key highlights follow.

Erik Brynjolfsson: We heard today about algorithmic bias and about human biases. You are one of the world’s experts on human biases, and you’re writing a new book on the topic. What are the bigger risks — human or the algorithmic biases?

Continue reading “Where Humans Meet Machines: Intuition, Expertise and Learning” »

The technical skills of programmer John Carmack helped create the 3D world of Doom, the first-person shooter that took over the world 25 years ago. But it was level designers like John Romero and American McGee that made the game fun to play. Level designers that, today, might find their jobs threatened by the ever-growing capabilities of artificial intelligence.

One of the many reasons Doom became so incredibly popular was that id Software made tools available that let anyone create their own levels for the game, resulting in thousands of free ways to add to its replay value. First-person 3D games and their level design have advanced by leaps and bounds since the original Doom’s release, but the sheer volume of user-created content made it the ideal game for training an AI to create its own levels.

Continue reading “An AI Created New Doom Levels That Are as Fun as the Game’s Original Ones” »

Time feels real to people. But it doesn’t even exist, according to quantum physics. “There is no time variable in the fundamental equations that describe the world,” theoretical physicist Carlo Rovelli tells Quartz.

If you met him socially, Rovelli wouldn’t assault you with abstractions and math to prove this point. He’d “rather not ruin a party with physics,” he says. We don’t have to understand the mechanics of the universe to go about our daily lives. But it’s good to take a step back every once in a while.

“Time is a fascinating topic because it touches our deepest emotions. Time opens up life and takes everything away. Wondering about time is wondering about the very sense of our life. This is [why] I have spent my life studying time,” Rovelli explains.

Continue reading “This physicist’s ideas of time will blow your mind” »

Check out the internal Google film, “The Selfish Ledger”. This probably wasn’t meant to slip onto a public web server, and so I have embedded a backup copy below. Ping me if it disappears. I will locate a permanent URL.

This 8½ minute video is a lot deeper—and possibly more insipid—than it appears. Nick Foster may be the Anti-Christ, or perhaps the most brilliant sociologist of modern times. It depends on your vantage point, and your belief in the potential of user controls and cat-in-bag containment.

He talks of a species propelling itself toward “desirable goals” by cataloging, data mining, and analyzing the past behavior of peers and ancestors—and then using that data to improve the experience of each user’s future and perhaps even their future generations. But, is he referring to shared goals across cultures, sexes and incomes? Who controls the algorithms and the goal filters?! Is Google the judge, arbiter and God?

Continue reading “Selfish Ledger: Google’s mass sociology experiment” »

Q) Why Algorithmic leaps can be better than Hardware leaps?

Ans) Hardware constraints create bottlenecks that are hard to tackle as uncertainty of physics at small scale (nano-meters and less) come into play (electrons start jumping around).

At this point, ideas (algorithms) can be used to unleash full potential of the feasible hardware.

Continue reading “Machine Learning of Human Brain” »

WASHINGTON — The U.S. military got is first big taste of artificial intelligence with Project Maven. An Air Force initiative, it began more than a year ago as an experiment using machine learning algorithms developed by Google to analyze full-motion video surveillance.

The project has received high praise within military circles for giving operators in the field instant access to the type of intelligence that typically would have taken a long time for geospatial data analysts to produce.

Project Maven has whetted the military’s appetite for artificial intelligence tools. And this is creating pressure on the National Geospatial-Intelligence Agency to jump on the AI bandwagon and start delivering Maven-like products and services.

Continue reading “Artificial intelligence is changing everything, ‘We need a different mentality’” »