Month: August 2018

30 Aug 2018
Manahel Thabet

Advanced Artificial Intelligence Could Run The World Better Than Humans Ever Could

There are fears that tend to come up when people talk about futuristic artificial intelligence — say, one that could teach itself to learn and become more advanced than anything we humans might be able to comprehend. In the wrong hands, perhaps even on its own, such an advanced algorithm might dominate the world’s governments and militaries, impart Orwellian levels of surveillance, manipulation, and social control over societies, and perhaps even control entire battlefields of autonomous lethal weapons such as military drones.

But some artificial intelligence experts don’t think those fears are well-founded. In fact, highly-advanced artificial intelligence could be better at managing the world than humans have been. These fears themselves are the real danger, because they may hold us back from making that potential a reality.

“Maybe not achieving AI is the danger for humanity,” Tomas Mikolov, a research scientist for Facebook AI, said at The Joint Multi-Conference on Human-Level Artificial Intelligence in Prague on Saturday.

“Maybe not achieving AI is the danger for humanity.”

As a species, Mikolov explained, humans are pretty terrible at making choices that are good for us in the long term. People have carved away rainforests and other ecosystems to harvest raw materials, unaware of (or uninterested in) how they were contributing to the slow, maybe-irreversible degradation of the planet overall.

But a sophisticated artificial intelligence system might be able to protect humanity from its own shortsightedness.

“We as humans are very bad at making predictions of what will happen in some distant timeline, maybe 20 to 30 years from now,” Mikolov added. “Maybe making AI that is much smarter than our own, in some sort of symbiotic relationship, can help us avoid some future disasters.”

Granted, Mikolov may be in the minority in thinking a superior AI entity would be benevolent. Throughout the conference, many other speakers expressed these common fears, mostly about AI used for dangerous purposes or misused by malicious human actors. And we shouldn’t laugh off or downplay those concerns.

We don’t know for sure whether it will ever be possible to create artificial general intelligence, often considered the holy grail of sophisticated AI that’s capable of doing pretty much any cognitive task humans can, maybe even doing it better.

The future of advanced artificial intelligence is promising, but it comes with a lot of ethical questions. We probably don’t know all the questions we’ll have to answer yet.

But most of the panelists at the HLAI conference agreed that we still need to decide on the rules before we need them. The time to create international agreements, ethics boards, and regulatory bodies across governments, private companies, and academia? It’s now. Putting these institutions and protocols in place would reduce the odds that a hostile government, unwitting researcher, or even a cackling mad scientist would unleash a malicious AI system or otherwise weaponize advanced algorithms. And if something nasty did get out there, then these systems would ensure we’d have ways to handle it.

With these rules and safeguards in place, we will be much more likely to usher in a future in advanced AI systems live harmoniously with us, or perhaps even save us from ourselves.


28 Aug 2018
Manahel Thabet

Brain cell discovery could help scientists understand consciousness

A team of scientists today unveiled the discovery of a new kind of brain neuron called the rosehip cell. What makes this find important? It may be unique to the human brain – and it’s found in the same area thought to be responsible for consciousness.

A team of international researchers consisting of dozens of scientists made the discovery after running complex RNA sequencing experiments on tissue samples from the cerebral cortices of two brain donors. The results were then confirmed with live tissue taken from patients who’d undergone brain surgery.

Upon discovering the rosehip cell, the researchers immediately tried to replicate the finding using samples gathered from laboratory mice – to no avail. It appears the cell is specific to humans, or potentially primates, but the researchers point out they’re only speculating these neurons are unique to humans at this time.

What matters is what the rosehip cell does. Unfortunately, the scientists aren’t sure. Neurons are tough nuts to crack, but what they do know is this one is belongs to the inhibitor class of brain neurons. It’s possible the rosehip cell is an integral inhibitor to our brain activity, and at least partially responsible consciousness.

Some scientists believe that human consciousness has something to do with wrangling reality from the chaos inside our brains. It’s been shown that an infant’s brain functions much like that of someone on LSD – babies are basically tripping all the time. Perhaps these neural inhibitors develop as our brains grow and help us to separate reality from whatever babies are dealing with.

But, of course, the real science isn’t quite as speculative. For the most part, the rosehip cell research is exciting because it’s filling in some missing pages in our atlas of human neural activity.

The brain is one of the most complex constructs in the universe, and the cerebral cortex is its most complicated part. It’s going to take a long time to figure the whole thing out.

The team intends to look for the rosehip cell in the brains of people who suffer from neurological disorders next – work that could lead to a vastly increased understanding of how the brain functions, and what causes it to break down.


26 Aug 2018
Manahel Thabet

NASA is developing AI to give directions in space

There’s no GPS in outer space. If people get lost on the Moon, or on the way to Mars they’re pretty much screwed. NASA and Intel want to keep that from happening, so they’ve turned to AI for solutions.

NASA Frontier Development Lab (FDL) recently concluded its eight week summer program with a demonstration event hosted by Intel. The program included nine teams working on core problems for space travel and extraterrestrial colonization. Its goal was to address these specific knowledge gaps using artificial intelligence.

Hard Fork?

Hard Fork.


The event covered the search for exoplanets, sending a probe to observe the sun up close, and other topics of interest to present and future spacefarers. Two presentations in particular focused on the problem of extraterrestrial navigation for both humans and robots, and how we’re finally able to address them with today’s deep learning techniques.

The first dealt with the problem of localization on the Moon. It’s relatively easy to figure out where you are on Earth. We can use an old-fashioned map, an app, GPS, search for visual landmarks, walk in one direction until we hit water, or simply ask someone for directions. It’s different on the Moon where, at the surface level, everything looks like this:

Credit: NASA

So how can AI help? Researchers Andrew Chung, Philippe Ludivig, Ross Potter, and Benjamin Wu developed a system for simulating the Moon’s surface and comparing the simulation to a local enviroment. In essence, they teach an AI what the moon looks like by feeding it millions of images and then use a neural network to create a virtual moon.

Credit: NASA

In theory, a person standing on the Moon’s surface should be able to localize by taking pictures of their surroundings and having the AI compare the real images with the simulation.

This AI-powered solution should work for any surface we’re able to take images of – including Mars. It likely won’t have the same efficacy for open space localization, but flying through space presents a different challenge than navigating an alien surface.

The next team to present was another Intel-sponsored group working on a problem many of our readers are already familiar with: Base-building on another planet (or the Moon, in this case).

Credit: NASA

Yes, ‘StarCraft’ aficionados and old school ‘Command and Conquer’ lovers: NASA is working on autonomous base construction, mining, and resource management for Lunar and Martian colonies. And it couldn’t be done without machine learning.

The team, consisting of researchers Drew Bischel, Zahi Kakish, Francisco Lera, and Ana Mosquera, set out to approach the problem of getting driverless vehicles and autonomous robots to conduct operations in hostile environments – such as the dark, freezing side of the Moon.

Rather than forcing humans to build around areas too dangerous for us, or making solar powered vehicles avoid dark spots all-together, the team created a framework to solve the problem — which is similar to an old math puzzle called The Traveling Salesman Problem.

In the Traveling Salesman Problem a scientist is tasked with discerning the shortest possible route for a salesman to travel between cities — without visiting the same place twice — and return to their point of origin. It seems simple enough if you’re traveling from say, New York to Chicago, then San Francisco and back.

Credit: NASA

But when you apply it to an environment like the Moon where you have to factor in the location of resources, dark spots, temperature fluctuations that could cause instrument and mechanical failures, and a myriad of other environment-specific tasks, the difficulty of controlling hundreds or thousands of independent machines making millions of decisions becomes too great for simple computations. Such an endeavor requires advanced deep learning solutions.

Intel provided the two teams with access to the Intel DevCloud which runs on the Intel Xeon Gold processors and includes MKL optimizations for Python and Tensorflow. And Intel provided a dedicated Xeon server for the localization team.

Eventually both projects could be scaled to work on other planets and satellites. The research is currently in early-stage development, but the path forward is clear: AI is the future of space travel and extraterrestrial colonization.


25 Aug 2018
Manahel Thabet

We’ll Soon Have A Telescope That Will Show Us the Edge of the Universe

BIG DAY. We can now put a price tag on a view of the edge of the universe: $1 billion.

That’s what it’s going to cost to build the Giant Magellan Telescope, and we’re officially on our way to bringing the massive device to fruition.

Image Credit: GMTO

BIG TELESCOPE. On Tuesday, GMTO Corporation (GMTO), the company spearheading the project, announced it had begun construction on the telescope at Las Campanas Observatory in Chile.

Once completed, the massive device will consist of seven round mirrors arranged like a honeycomb that measure a total of 24 meters (80 feet) in diameter. An advanced computer program will help it correct the distortion caused by Earth’s atmosphere. This combination of sophisticated hardware and software will make the Giant Magellan Telescope will be 10 times as precise as the Hubble telescope.

Image Credit: GMTO

BIG QUESTIONS. The Giant Magellan Telescope should be online and ready for use in 2024, but researchers already have big plans for the device.

It will be able to collect more light than any telescope every built, including light from the earliest days of the universe (because of how long it takes light to travel such immense distances, looking at that light invariably means looking back in time). The device will allow us to determine the distance of far-off objects from the Earth and their composition.

According to the Giant Magellan Telescope website, this improved view of our universe could help answer many of the greatest questions of modern astronomy, including how galaxies form, the nature of dark matter and dark energy, and how stars formed after the Big Bang.

It might even be able to help answer the question pondered by nearly everyone who’s ever looked at the night sky: Are we alone in the universe?

Source: Futurism

25 Aug 2018
Manahel Thabet

Manahel Thabet Ph.D. is positioned among the 30 Smartest individuals alive by SuperScholar

Manahel Thabet is the Founder and President of SmartTips Consultants, President (Middle East and North Africa/MENA) of The Brain Trust Foundation, leader of the World IQ Foundation, Vice President of the World Intelligence Network (WIN), Deputy Director of the Institute for Brain Chemistry and Human Nutrition and Vice Chancellor of The Gifted Academy.

Manahel Thabet Ph.D. is positioned among the 30 Smartest individuals alive by SuperScholar, Genius of the Year 2013 by the World Genius Directory speaking to ASIA and Brain of the Year Award Winner 2015-2016.

In 2014 she was chosen the AVICENNA Award Laureate as a successor to Professor Tony Buzan given each year to the individuals who introduce best practice in science, associating East with West through science and information. In 2015 Dr. Thabet broke another Guinness World Record in 2015 of every a standout amongst the most muddled instructing techniques.

In 2012 Dr Manahel was the Chairperson of the Scientific Committee, Recommendation Committee and Senior Adviser to the International Asia Pacific Giftedness Conference held in Dubai – UAE facilitated by Hamdan Bin Rashid Awards for Distinguished Academic Performance. The gathering facilitated masters from 42 nations, 320 papers and in excess of 2000 members in the field of Talent and Gifted Education.

Dr Thabet Partoned the Women’s Leadership MBA at Synergy University Dubai, filled in as GoodWill Ambassador for Eco International of Prince Albert II De Monaco Foundation. Dr Thabet is the President of IQuestion, individual from Young Arab Leaders, judge for the Drones for Good Awards UAE (2015-2016), warning board for In-Sight: Independent Interview-Based Journal, individual from the International Association of Quantitative Finance (once in the past International Association of Financial Engineers), proofreader of IQ area in magazine Synapsia and manager of the Arabian Intelligence Network.

Manahel Thabet is additionally the victor of Middle East Achievement Awards in Science and was positioned among the 100 most great Women in the Middle East and most ground-breaking 500 Arabs in the World by Arabian Business. Dr. Manahel is a Royal Grand Cross Officer of the Companionate of the White Swan and a Fellow of the Royal Society of Medicine in London, UK. In 2016 she was gave with the renowned respect of Freedom of the City of London. Recently she was highlighted among the BBC most motivational 100 ladies around the globe.

23 Aug 2018
Manahel Thabet

Artificial Retinas Made Of This Ultra-Thin Super Material Could Help Millions See Again

TRULY SUPER. There’s a reason researchers call graphene a “super material.” Even though it’s just a single layer of carbon atoms thick, it’s super strong, super flexible, and super light. It also conducts electricity, and is biodegradable. Now an international team of researchers has found a way to use the super material: to create artificial retinas.

They presented their work Monday at a meeting of the American Chemical Society (ACS).

ARTIFICIAL RETINAS. The retina is the layer of light-sensitive cells at the back of the eye responsible for converting images into impulses that the brain can interpret. And without a functional one, a person simply can’t see.

Currently, millions of people suffer from retinal diseases that strip them of their vision. To help them see again, researchers have developed artificial retinas. What we’ve got now, though, isn’t exactly ideal — because the implants are rigid and flat, the images they produce are often blurry or distorted. And even though the implants are fragile, they can also somehow damage nearby eye tissue.

Graphene, with all its unique attributes, might be the key to creating a better artificial retina.

GRAPHENE TO THE RESCUE. Using a combination of graphene, molybdenum disulfide (another 2D material), gold, alumina, and silicon nitrate, researchers from the University of Texas and Seoul National University constructed an artificial retina that  of a natural retina better than existing models.

Based on studies in the lab and in animal subjects, the researchers determined that their artificial retina is both biocompatible and capable of mimicking human eye features. And it better matches the dimensions of a natural retina to boot.

“This is the first demonstration that you can use few-layer graphene and molybdenum disulfide to successfully fabricate an artificial retina,” said researcher Nanshu Lu in a press release. “Although this research is still in its infancy, it is a very exciting starting point for the use of these materials to restore vision.”

If further studies on the graphene-containing artificial retina goes as the researchers hope, we could eventually add another super power to the super material’s resume: restoring sight to the visually impaired.

Source: Futurism

20 Aug 2018
Manahel Thabet

An AI that ‘hears’ machine failure might soon be used for roller coasters

How do we know when the things we own or the items we use everyday need maintenance?

In most cases, people only take corrective measures when things stop working. For some organizations, periodic maintenance checks are the order of the day; however, these can be costly as planned downtime is needed to carry these out.

And what about items that are used on a much larger scale? Like theme park rides?

One such theme park, Netherlands-based Efteling, is working at providing a solution to preventing downtime. Initially originating as a sports park in 1952, Efteling has since grown into an international award-winning theme park, enchanting visitors for 66 years. In 2017, it welcomed 5.18 million visitors.

Yet, just like any other theme park it also suffers from ride downtime. In order to find a solution, Efteling is taking part in a specifically designed challenge organized by The Next Web and Vodafone, which connects 10 established companies to startups to solve a problem through IoT solutions.

The theme park already has an extensive maintenance scheme and on-the-ground engineering crews to fix issues. Yet, the growth of Efteling is showing that this is no longer cost-effective. Additionally, predicting or preventing unexpected issues is not always possible.

Speaking to me in an interview, Jonas Rietbergen, a strategist who is responsible for the innovation program at Efteling, said the main issue with ride downtime is guest satisfaction. If there is unexpected downtime of a ride, he says that customers are disappointed, especially when no announcements are made either. When a ride does go out of operation, a team of mechanics and engineers is sent to it to fix it straight away.

“For Efteling, this means a 10-14 hour standby time of these teams,” Rietbergen adds.

The goal of Efteling is to ensure that it has a 95 percent to 100 percent uptime of rides; however, to do so requires extensive maintenance and checks. In order to minimize the impact to the guests’ experience, the theme park undertakes checks before the park opens, when the park is closed, and during specific blocks of days when rides are under construction.

“To give you an idea, Droomvlucht (a top three ride) is scheduled to be closed for only five days in 2018,” says Rietbergen.

Building Efteling’s “Haunted Castle” in 1978

Using AI to detect rides malfunctioning

Speaking on the issue in an interview with me were Paolo Samontanez, CTO of OneWatt, an Amsterdam-based company, and Kai Sakesla, CEO of Noiseless Acoustics, a Helsinki-based organization. Both of them are using artificial intelligence (AI) to better understand the sound patterns of machines to detect failures.

For Noiseless Acoustics technology to work, Sakesla explains that “the problem has to be acoustically detectable.” He adds that it doesn’t necessarily have to be heard by the human ear, but it should be measurable.

Noiseless Acoustics use a mixture of hardware, software, and analytics to listen to sound. They use several tools, such as their NL Camera, which locates heat images that signal noise on a screen, and their NL Sense, which is a compact wireless hub and sensors that locates where exactly a problem is.

OneWatt focuses on detecting problems in motors. According to Samontanez, the company’s technology could be a solution to Efteling’s challenge of better predicting rides malfunctioning which is why the company has submitted their application to join the Vodafone TNW IoT Challenge.

“Preventing anomalies in motors is one of OneWatt’s key activities and De Efteling’s motors are similar in a sense to industrial motors,” he adds.

Even though the theme park is at an early stage with predictive maintenance, Rietbergen explains that it would deliver two important benefits.

“For our guests, it will mean less unannounced downtime of rides and therefore an even better experience,” he explains. “For the Efteling it means that we can have a cost-effective and extensive maintenance scheme for our 66-year-old park. This will keep the heritage of the Efteling future proof.”

Embracing IoT technologies

Implementing the technology, though, in Samontanez’s opinion, would require some tweaking. This includes removing background noises to adjust it to the acoustic profile of a theme park, in order to test and verify what the problem is.

“The environment is a bit different compared to a normal industrial facility,” he explains. “It is in an open place and might have a lot of external factors such as the visitors from the park.”

Sakesla adds that their NL Sense, for example, could be installed on the theme park rides to detect ride failure as long as the locations it is installed in has electricity.

“We provide our customers with a few devices to do the acoustic profiling — they build up the acoustic fingerprint, which is then used for problem detection,” he notes. “The fingerprint gets better the longer we have the solution installed.”

For Efteling, the theme park’s purpose is to help people get a break from everyday life. And while the park has been updated to modern times and bigger audiences, rides should still run just as smoothly as they did 40 years ago.

Will Efteling turn to the Internet of Things to prevent downtime, if the right solution presents itself? “We should and will embrace IoT technologies that will enable us to do so,” Rietbergen says. “So the short answer is: yes, definitely.”


Source: TNW

19 Aug 2018
Manahel Thabet

TECH Ripple’s CTO invented a distributed computer system 20 years before blockchain

he mysterious Satoshi Nakamoto is often credited with inventing blockchain – the tech behind the recent cryptocurrency and decentralization boom. But long before Nakamoto published his seminal paper that shaped Bitcoin as we know it, Ripple $XRP▼3.08% chief technology officer David Schwartz had already come up a similar concept.

Almost 30 years ago on August 25, 1988, Schwartz filed a patent for a “multilevel distributed computer system” that would “preferably” run on “personal computers.” The technology was designed to leverage the combined processing power of numerous devices to accomplish singular tasks.

Three years later, Schwartz was eventually granted the patent. While the undertaking ultimately didn’t pan out, we spoke with the Ripple CTO about what his vision for the distributed system entailed – and how it overlaps with today’s blockchain tech.

The origin story

One of the main problems Schwartz, whose background is in cryptography, was trying to solve was how to distribute computing-intensive tasks (that would’ve been otherwise impossible to process by a single machine) to a network of devices.

“A distributed computer system is a network of computers each of which function independently of but in a cooperative manner with each other. Versatility of a computer system can be increased by using a plurality of small computers, such as personal computers, to perform simple tasks and a central computer for longer more complex tasks,” the patent documentation reads. “Such an arrangement lessens the load on the control computer and reduces both the volume and cost of data transmission.”

“I was working on graphics rendering problems that require significant amounts of CPU power,” Schwartz told Hard Fork. This is how the idea for his invention was born – and ironically, how it came to a halt.

“CPUs improved in performance much more quickly than expected and there didn’t seem to be much need for distributing tasks dynamically to CPUs with available processing power,” Schwartz explained.

But before this so-called distributed computer system got shelved, the cryptographer and his team were able to run some experiments on the technology.

“We had a working implementation that generated images of fractals,” Schwartz revealed to Hard Fork. “You could add more CPUs to the cluster and workloads would dynamically distribute to them.”

Distributed computing and blockchain tech

That said, Schwartz’s system was far from perfect. For one, establishing a connection between various computers was much more complicated back then than it is now. Another challenge had to do with breaking the intended tasks down into smaller portions that can be processed and transferred from one computer to the next.

While the invention of the internet has mostly solved the interconnection issue, some of the issues Schwartz encountered back in the 1990s continue to persist today. Indeed, breaking down large network components into smaller portions is a challenge Ethereum is still trying to solve.

As far as Schwartz’s adventure into distributed computing from 30 years ago goes, he says the experience is still coming in handy in his work today.

“It does seem that the things I worked on in the past keep coming up in the things I’m working on now,” Schwartz added. “I think that’s more just due to most of my work being in the same general area of distributed computing and cryptography.”


18 Aug 2018
Manahel Thabet

Developing bionics: How IBM is adapting mind-control for accessibility

What if there was a way to give everyone suffering from conditions like paralysis or Locked-in syndrome the means to operate prosthetic devices and tech gadgets using mind-control? Well, there is – or at least, there will be.

IBM Research recently developed an end-to-end proof-of-concept for a method of controlling an off-the-shelf robotic arm with a brain-computer interface built using a take-home EEG monitor. To accomplish this, the researchers developed AI to interpret the data from the EEG monitor as commands for the robotic arm.

That may not sound like something that will change everything overnight – and IBM isn’t the only or first company to dabble in brain-computer interfaces. But they’re one of the only that appear interested in figuring out how to build a system that uses inexpensive hardware that’s already available.

We reached out to Stefan Harrer, a research scientist at IBM Research working on the project. :

Our primary design goals were (i) low-cost and (ii) suitable for use in an unrestricted real-life environment. (i) allows the system to transition from an expensive research grade exploratory setup (the status-quo of BMIs) to a setup that is affordable for the broad public (the first of our main objectives) – (ii) allows the system to be taken out of highly specialized research lab environments and moved into everyday environments for use by the broad public (the second of our main objectives).

This early work indicates people can control machines with their minds alone, using commonly available technology and cutting-edge AI. That’s huge for those who don’t have that same control over their own bodies.

Harrer told us that, with further development, the same machine learning techniques could potentially be applied to control a prosthetic limb or even a robot assistant.

IBM‘s system isn’t ready for prime-time just yet though. Harrer says the team is working on reducing latency and doesn’t have any current plans for human trials. But the proof-of-concept indicates it’s only a matter of time before devices built using this technology become a common accessibility solution.

Source: TNW

16 Aug 2018
Manahel Thabet

The World Economic Forum warns that AI may destabilize the financial system

Artificial intelligence will reshape the world of finance over the next decade or so by automating investing and other services—but it could also introduce troubling systematic weaknesses and risks, according to a new report from the World Economic Forum (WEF).

Compiled through interviews with dozens of leading financial experts and industry leaders, the report concludes that artificial intelligence will disrupt the industry by allowing early adopters to outmaneuver competitors. It also suggests that the technology will create more convenient products for consumers, such as sophisticated tools for managing personal finances and investments.

But most notably, the report points to the potential for big financial institutions to build machine-learning-based services that live in the cloud and are accessed by other institutions.

“The dynamics of machine learning create a strong incentive to network the back office,” says the report’s main author, Jesse McWaters, who leads the AI in Financial Services Project at the World Economic Forum. “A more networked world is more vulnerable to cybersecurity risks, and it also creates concentration risks.”

In other words, financial systems that incorporate machine learning and are accessed through the cloud by many different institutions could present a juicy target for hackers and a single point of systemic failure.

Wall Street is already rapidly adopting machine learning, the technology at the center of the artificial-intelligence boom. Finance firms generally have lots of data and plenty of incentive to innovate. Hedge funds and banks are hiring AI researchers as quickly as they can, and the financial industry is experimenting with back-office automation in a big way. The automation of high-frequency trading has already created systemic risks, as highlighted by several runaway trading events, or “flash crashes,” in recent years.

Andrew Lo, a professor at MIT’s Sloan School of Management, researches the issue of systemic risk in the financial system, and he has previously warned that the system as a whole may be vulnerable because of its sheer complexity.

The WEF report raises other issues as well. It says that big tech companies will have an opportunity to get into finance, often through tie-ins with financial firms, because of their expertise in AI as well as their access to consumer data.

And McWaters says that as AI becomes more widely used in finance, it will be important to consider issues like biased algorithms, which can discriminate against certain groups of people. Financial companies should not be too eager to simply replace staff either, he says. As the study suggests, human skills will remain important even as automation becomes more widespread.

Source: MIT