Lifeboat Foundation

What is the meaning of affective computing? Are machines able to feel? Find out more about this new concept in this analysis from Ahmed Banafa for OpenMind.

By the year 2030, artificial intelligence (A.I.) will have changed the way we travel to work and to parties, how we take care of our health and how our kids are educated.

That’s the consensus from a panel of academic and technology experts taking part in Stanford University’s One Hundred Year Study on Artificial Intelligence.

Focused on trying to foresee the advances coming to A.I., as well as the ethical challenges they’ll bring, the panel yesterday released its first study.

Continue reading “Scientists look at how A.I. will change our lives by 2030” »

Excellent marathon runner, A.I. pioneer or outstanding scientist: who was Alan Turing? Read more here 👉 http://bit.ly/1USRuOF

The Anthrobotics Cluster seeks to start conversations (and answer questions) regarding some of the biggest topics in AI research. Here, Luis de Miranda, one of the founders, discusses anthrobots and the relationship between humans and machines.

Technology is accelerating at an ever increasing rate. Each year, we develop smaller and smarter systems…systems that allow us to interact with information in ways that previous eras only dreamed about. In fact, given their ability to process, identify, and categorize information—and their uncanny ability to synthesize information and make judgments—many of our systems seem to be developing a true form of intelligence. In this respect, it seems that the dawning age of AI is truly upon us.

But what does this mean?

Continue reading “Anthrobotics: Where The Human Ends and the Robot Begins” »

Friday, Sep 2, 2016 4:35 PM UTC

Robot “employees” coming to select Lowe’s this fall.

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Traditional cancer research is well funded but ALT cancers are not. SENS Research is aiming to raise funds to address this vital gap in our scientific knowledge. Most scary thing of all is that some regular cancers that abuse telomerase can switch to this ALT method to keep growing when telomerase blocking therapies are used.

The paper I’ll point out today is a timely one, given that the SENS Research Foundation’s fundraiser for early stage work on a therapy for alternative lengthening of telomeres (ALT) cancers is nearing its close. There are still thousands of dollars left in the matching fund, so give it some thought if you haven’t yet donated. The search for ways to safely sabotage ALT is a useful, important line of research because blocking telomere lengthening is a path to a universal cancer therapy, those research groups presently working on it are all looking to achieve this goal by interfering in the activities of telomerase, cancers can switch from using telomerase to using ALT, and next to no-one is working on ways to suppress ALT mechanisms. It seems fairly clear based on the evidence to date that the universal cancer therapy that lies ahead, built by inhibiting telomere lengthening, must involve a blockade of both telomerase and ALT. The open access paper below reinforces this point, the authors investigating how exactly cancers switch from telomerase to ALT to maintain their dangerous growth.

Cancer research today has a grand strategy problem. There is only so much funding and only so many researchers, but hundreds of subtypes of cancer. Therapies tend to be highly specific to the peculiarities of one type of cancer or a small class of cancers, meaning that great expense and time leads to a treatment that is only applicable for a fraction of cancer patients, all too often a tiny fraction. Further, since tumors evolve at great speed, any one individual patient’s cancer may find its way out from under the hammer by changing its signature and mode of operation. All is not doom and gloom, however. Consider that the research community could build a therapy applicable to all cancers with little to no modification, where the cost of development would be no greater than any one of the highly specific therapies presently in use and under development. That therapy would be, of course, based on the blockade of telomere lengthening.

Continue reading “An Investigation of How Telomerase Cancers can Switch to Become ALT Cancers” »

Engineers showed laboratory research into the ‘hoverbike,’ a rectangular shaped quadcopter that has since been named the Joint Tactical Aerial Resupply Vehicle, or JTARV.

‘Anywhere on the battlefield, Soldiers can potentially get resupplied in less than 30 minutes,’ said Army researcher Tim Vong.

Continue reading “US soldiers could soon travel like stormtroopers on new ‘hoverbike’” »

[Figure about depicts a layout, showing two ‘somas’, or circuits that simulate the basic functions of a neuron. The green circles play the role of synapses. From presentation of K.K. Likharev, used with permission.]

One possible layout is shown above. Electronic devices called ‘somas’ play the role of the neuron’s cell body, which is to add up the inputs and fire an output. In neuromorphic hardware, somas may mimic neurons with several different levels of sophistication, depending on what is required for the task at hand. For instance, somas may generate spikes (sequences of pulses) just like neurons in the brain. There is growing evidence that sequences of spikes in the brain carry more information than just the average firing rate alone, which previously had been considered the most important quantity. Spikes are carried through the two types of neural wires, axons and dendrites, which are represented by the red and blue lines in figure 2. The green circles are connections between these wires that play the role of synapses. Each of these ‘latching switches’ must be able to hold a ‘weight’, which is encoded in either a variable capacitance or variable resistance. In principle, memristors would be an ideal component here, if one could be developed that could be mass produced. Crucially, all of the crossnet architecture can be implemented in traditional silicon-based (“CMOS”-like) technology. Each crossnet (as shown in the figure) is designed so they can be stacked, with additional wires connecting somas on different layers. In this way, neuromorphic crossnet technology can achieve component densities that rival the human brain.

Likarev’s design is still theoretical, but there are already several neuromorphic chips in production, such as IBM’s TrueNorth chip, which features spiking neurons, and Qualcomm’s “Zeroeth” project. NVIDIA is currently making major investments in deep learning hardware, and the next generation of NVIDIA devices dedicated for deep learning will likely look closer to neuromorphic chips than traditional GPUs. Another important player is the startup Nervana systems, which was recently acquired by Intel for $400 million. Many governments are are investing large amounts of money into academic research on neuromorphic chips as well. Prominent examples include the EU’s BrainScaleS project, the UK’s SpiNNaker project, and DARPA’s SyNAPSE program.

Continue reading “Neuromorphic Chips: a Path Towards Human-level AI” »

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