Lifeboat Foundation

A tsunami of change is already arriving. Artificial intelligence is now capable of doing desk jobs that were previously safe from automation. The social and economic effects remain to be seen, but is AI what we think it is?

Workplaces that include artificial intelligence (AI) will soon be reality, say researchers who believe the rise of AI in all areas of life is not only inevitable, it’s set to reshape the way we think about consciousness and human identity.

From Metropolis to 2001: A Space Odyssey and The Terminator, robots and super-intelligent AIs in film have seduced and terrified our collective consciousness, having an impact on how we view artificial intelligence. But will they really crush the puny humans and take over the world?

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Microsoft is bringing its Cognitive Toolkit version 2.0 out of beta today and should be helping out a ton of companies who depend on tools to deploy deep learning at scale.

The Cognitive Toolkit or CNTK to some is a deep learning tool that helps companies speed up the process of image and speech recognition. Thanks to today’s update, CNTK can now be used by companies either on-premises or in the cloud combined with Azure GPUs.

Cognitive Toolkit is being used extensively by a wide variety of Microsoft products, by companies worldwide with a need to deploy deep learning at scale, and by students interested in the very latest algorithms and techniques. The latest version of the toolkit is available on GitHub via an open source license. Since releasing the beta in October 2016, more than 10 beta releases have been deployed with hundreds of new features, performance improvements and fixes.

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If you’re an accountant, lawyer or data analyst, a robot may soon take over your job.

Amazon is using a “simulated dog” to test its delivery drones, according to IBTimes.

The e-commerce giant wants to use drones to deliver parcels to customers in less than 30 minutes but it clearly has some concerns about how dogs might interfere.

At least one simulated dog is being used to “help Amazon see how UAVs [unmanned aerial vehicles] would respond to a canine trying to protect its territory,” according to IBTimes.

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WASHINGTON—Challenging commonly held misperceptions, the U.S. Department of Justice published a report this week revealing that the vast majority of UFO abductions are perpetrated by aliens a person knows rather than extraterrestrials unfamiliar to victims. “The popular notion of UFO abductions is of a person being beamed up into the sky by strange, hostile beings from Sirius or Andromeda, but the reality is that most of these abductions are committed by an extraterrestrial acquaintance the victim trusts and feels comfortable around,” DOJ spokesman Devin Shane said of the estimated 2,800 reported victims of UFO abduction last year, many of whom were taken against their will into an advanced spacecraft and subjected to psychological experiments and medical examinations by nonhuman entities they already knew through family or friends. “While it’s true that a significant number of abductions are still carried out by extrasolar reptilian beings with planetary invasion-related motives, data shows that known relationships with extraterrestrials are by far the greater danger to civilians, with many aliens committing abduction for personal reasons, such as indulging their own cravings for power, control, or revenge, or siphoning human energy from host bodies in order to replicate.” Officials noted, with a degree of optimism, that evidence now shows only 10 percent of all UFO abductions result in aliens impregnating the victim with thousands of eggs.

We’ve developed an unsupervised system which learns an excellent representation of sentiment, despite being trained only to predict the next character in the text of Amazon reviews.

A linear model using this representation achieves state-of-the-art sentiment analysis accuracy on a small but extensively-studied dataset, the Stanford Sentiment Treebank (we get 91.8% accuracy versus the previous best of 90.2%), and can match the performance of previous supervised systems using 30-100x fewer labeled examples. Our representation also contains a distinct “sentiment neuron” which contains almost all of the sentiment signal.

OpenAI vs. Deepmind in river raid ATARI.

AI research has a long history of repurposing old ideas that have gone out of style. Now researchers at Elon Musk’s open source AI project have revisited “neuroevolution,” a field that has been around since the 1980s, and achieved state-of-the-art results.

The group, led by OpenAI’s research director Ilya Sutskever, has been exploring the use of a subset of algorithms from this field, called “evolution strategies,” which are aimed at solving optimization problems.

Continue reading “OpenAI Just Beat Google DeepMind at Atari With an Algorithm From the 80s” »

Transhumanism stuff out in these stories: http://z-news.link/the-future-of-the-earth-through-the-eyes-of-futurists-photo/ & http://yemcentral.com/2017/03/29/would-robots-make-better-po…an-humans/ & https://player.fm/series/lions-of-liberty-podcast/287-zoltan…nd-liberty

Futurism, or more precisely, futurology, is the study of possible hypotheses, probable and preferred options for the future. To understand what futurists predict in the improvement of the human condition, consider the progress happening in the field of science, medicine and computing.

Continue reading “The future of the Earth through the eyes of futurists. Photo” »

OpenAI researchers were surprised to discover that a neural network trained to predict the next character in texts from Amazon reviews taught itself to analyze sentiment. This unsupervised learning is the dream of machine learning researchers.

Much of today’s artificial intelligence (AI) relies on machine learning: where machines respond or react autonomously after learning information from a particular data set. Machine learning algorithms, in a sense, predict outcomes using previously established values. Researchers from OpenAI discovered that a machine learning system they created to predict the next character in the text of reviews from Amazon developed into an unsupervised system that could learn representations of sentiment.

“We were very surprised that our model learned an interpretable feature, and that simply predicting the next character in Amazon reviews resulted in discovering the concept of sentiment,” OpenAI, a non-profit AI research company whose investors include Elon Musk, Peter Thiel, and Sam Altman, explained on their blog. OpenAI’s neural network was able to train itself to analyze sentiment by classifying reviews as either positive or negative, and was able to generate text with a desired sentiment.

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