Lifeboat Foundation: Safeguarding Humanity
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Category: robotics/AI

Artificial intelligence (AI) has emerged as a powerful approach for integrated analysis of the rapidly growing volume of multi-omics data, including many research and clinical tasks such as prediction of disease risk and identification of potential therapeutic targets. However, the potential for AI to facilitate the identification of factors contributing to human exceptional health and life span and their translation into novel interventions for enhancing health and life span has not yet been realized. As researchers on aging acquire large scale data both in human cohorts and model organisms, emerging opportunities exist for the application of AI approaches to untangle the complex physiologic process(es) that modulate health and life span. It is expected that efficient and novel data mining tools that could unravel molecular mechanisms and causal pathways associated with exceptional health and life span could accelerate the discovery of novel therapeutics for healthy aging. Keeping this in mind, the National Institute on Aging (NIA) convened an interdisciplinary workshop titled “Contributions of Artificial Intelligence to Research on Determinants and Modulation of Health Span and Life Span” in August 2018. The workshop involved experts in the fields of aging, comparative biology, cardiology, cancer, and computational science/AI who brainstormed ideas on how AI can be leveraged for the analyses of large-scale data sets from human epidemiological studies and animal/model organisms to close the current knowledge gaps in processes that drive exceptional life and health span. This report summarizes the discussions and recommendations from the workshop on future application of AI approaches to advance our understanding of human health and life span.

Aging is often described as the outcome of interactions among genetic, environmental and lifestyle factors with wide variation in life and health span between and within species (Newman and Murabito, 2013; Partridge et al., 2018; Singh et al., 2019). Exceptional life and health span represents an extreme phenotype characterized by exceptional survival (well-beyond average life expectancy), delayed onset of age-related diseases (before 80 years of age) (Pignolo, 2019) and/or preservation of good health/function relative to their peers (Perls et al., 2000, 2002; Kaeberlein, 2018). The identification of SNP associations with exceptional life and health span is a starting point for identifying targets for interventions that could potentially promote healthy human aging.

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Artificial intelligence hit some key milestones in 2017. At Facebook, chatbots were able to negotiate as well as their human counterparts. A poker-playing system designed by Carnegie Mellon professors mopped the floor with live opponents. There were even some potentially life-saving breakthroughs, like the machine vision system that can determine whether a mole is cancerous with more than 90 percent accuracy—beating out a group of dermatologists.

From agriculture to medicine and beyond, plenty of startups are using AI in innovative ways. Here are five companies you should expect big things from in 2018.

SoundHound has been around for 13 years, and has spent that time trying to build the most powerful voice assistant ever. The startup began by creating a Shazam-like song recognition app called Midomi; now, the newly released Hound app is capable of answering complex voice prompts like, “Show me all below-average-priced restaurants within a five-mile radius that are open past 10 p.m. but don’t include Chinese or pizza places,” or “What’s the weather like in the capital of the biggest state in the U.S.?”

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Machine learning, introduced 70 years ago, is based on evidence of the dynamics of learning in the brain. Using the speed of modern computers and large datasets, deep learning algorithms have recently produced results comparable to those of human experts in various applicable fields, but with different characteristics that are distant from current knowledge of learning in neuroscience.

Using advanced experiments on neuronal cultures and large scale simulations, a group of scientists at Bar-Ilan University in Israel has demonstrated a new type of ultrafast artificial algorithms—based on the very slow dynamics—which outperform learning rates achieved to date by state-of-the-art learning algorithms.

In an article published today in the journal Scientific Reports, the researchers rebuild the bridge between neuroscience and advanced artificial intelligence algorithms that has been left virtually useless for almost 70 years.

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Just five months ago at the RSA conference, the NSA released Ghidra, a piece of open source software for reverse-engineering malware. It was an unusual move for the spy agency, and it’s sticking to its plan for regular updates — including some based on requests from the public.

In the coming months, Ghidra will get support for Android binaries, according to Brian Knighton, a senior researcher for the NSA, and Chris Delikat, a cyber team lead in its Research Directorate, who previewed details of the upcoming release with CyberScoop. Knighton and Delikat are discussing their plans at a session of the Black Hat security conference in Las Vegas Thursday.

Before the Android support arrives, a version 9.1 will include new features intended to save time for users and boost accuracy in reverse-engineering malware — enhancements that will come from features such as processor modules, new support for system calls and the ability to conduct additional editing, known as sleigh editing, in the Eclipse development environment.

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The Defense Advanced Research Projects Agency (DARPA) is experimenting with using a swarm of autonomous drones and ground robots to assist with military missions. In a video of a recent test, DARPA showed how its robots analyzed two city blocks to find, surround, and secure a mock city building.

DARPA conducted its test back in June in Georgia, featuring both drones and ground-based robots. The demonstration was part of DARPA’s OFFensive Swarm-Enabled Tactics (OFFSET) program, which is designed to eventually accompany small infantry units as they work in dense urban environments, and could eventually scale up to 250 drones and ground robots. The test back in June was the second of six planned tests, which DARPA says will increase in complexity as they happen over the next couple of years.

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This video is the ninth in a multi-part series discussing computing and the second discussing non-classical computing. In this video, we’ll be discussing what quantum computing is, how it works and the impact it will have on the field of computing.

[0:28–6:14] Starting off we’ll discuss, what quantum computing is, more specifically — the basics of quantum mechanics and how quantum algorithms will run on quantum computers.

[6:14–9:42] Following that we’ll look at, the impact quantum computing will bring over classical computers in terms of the P vs NP problem and optimization problems and how this is correlated with AI.

[9:42–14:00] To conclude we’ll discuss, current quantum computing initiatives to reach quantum supremacy and ways you can access the power of quantum computers now!

Thank you to the patron(s) who supported this video ➤

Wyldn Pearson
Collin R Terrell

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Driverless cars seem straight out of the future, but thanks to developments in autonomous vehicle technology, that future could be right around the corner. Similar to the incremental adoption of electric cars — with hybrid models hitting the road first—car manufacturers have been introducing driverless features to conventional vehicles for some time now. Already on the road today we have partially autonomous vehicles, cars and trucks with cruise control, braking assistance and self-parking technology. And industry specialists predict that fully autonomous vehicles could be on the market in a matter of a few years.

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Of the 1,500 active volcanoes worldwide, about 6 percent of them erupt each year, or 50 to 85. Less than half of all volcanoes have sensors, and even fewer are considered well-monitored, the result of high costs and difficulty in maintaining equipment in such unforgiving environments. Volcanoes that are considered dormant rarely have any monitoring, despite surprises like the 2008 eruption of the Chaitén volcano in Chile after 8,000 years of inactivity.

Now, volcanologists are turning to satellite imagery and artificial intelligence to keep a closer eye on more volcanoes and, eventually, forecast eruptions. MOUNTS (Monitoring Unrest from Space), currently tracks 18 volcanoes, including Mount Fuego in Guatemala and Mount Etna in Italy.

With 800 million people living within 62 miles of an active volcano, there are plenty of reasons to increase monitoring.

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