Google’s artificial intelligence research lab DeepMind is exploring whether its technology could be used to identify early signs of eye diseases that ophthalmologists might not spot.
DeepMind, which was acquired by Google in 2014, has struck an agreement with Moorfields Eye Hospital in London that gives it access to about a million anonymous retinal scans, which it will feed into its artificial intelligence software.
The algorithm will target two of the most common eye diseases: age-related macular degeneration and diabetic retinopathy, which affect more than 100 million people around the world.
There is a computing revolution coming, although nobody knows exactly when. What are known as “quantum computers” will be substantially more powerful than the devices we use today, capable of performing many types of computation that are impossible on modern machines.
But while faster computers are usually welcome, there are some computing operations that we currently rely on being hard (or slow) to perform.
Specifically, we rely on the fact that there are some codes that computers can’t break – or at least it would take them too long to break to be practical. Encryption algorithms scramble data into a form that renders it unintelligible to anyone that does not possess the necessary decryption key (normally a long string of random numbers).
Researchers at Bar Ilan University and the Interdisciplinary Center in Herzliya, both in Israel, have developed new technology that allows tiny bots to release drugs into the body controlled by human thought alone. The test involved a man using his thoughts to activate nano robots inside a cockroach.
The bots have been built using a DNA origami structure with hollow shell-like components, and they come with a “gate” that can be opened and shut with the help of iron oxide nanoparticles that act as a “lock” – which can be prized open using electromagnetic energy.
The Israeli team believe the bots could help in controlled release of drugs over time. Led by Dr Ido Bachelet of Bar Ilan University, scientists demonstrated how to control this process with human brainwaves. Using a computer algorithm, they trained the system to detect when a person’s brain was under strain from doing mental arithmetic. The team then placed a fluorescent drug in the bots and injected them into various cockroaches that were placed inside an electromagnetic coil.
Driving a motor vehicle requires making tough choices in the heat of the moment. Whether slamming on the brakes in traffic or speeding up before a light turns red, split-second decisions are often a choice between the lesser of two evils. Sometimes, a choice could lead to bodily injury or even a loss of life.
As more self-driving cars reach the road, life-and-death decisions once made by humans alone will increasingly shift to machines. Yet the idea of giving that responsibility over to a computer may be unsettling to some.
Self-driving cars have the potential to significantly reduce the tens of thousands of auto fatalities occurring yearly—but a reduction isn’t the same as elimination. In fact, some deaths will inevitably happen at the hands of computer algorithms once they make those decisions for us.
CIA reveals Spacenet ‘AI in the sky’ that could constantly monitor activity on Earth via high resolution satellites…
It sounds like something out of a sci-fi film — an AI that constantly monitors the Earth, looks for unusual activity.
However, CosmiQ Works, a division of the CIA’s venture arm, has revealed SpaceNet, a project with Amazon, satellite mapping firm DigitalGlobe and chip firm Nvidia to train algorithms to work out what’s happening on our planet.
The project will create a giant online database of hi-res images that AIs will be able to use to teach themselves — and started with images of Rio during the Olympics.
I have been seeing this for the recent weeks; I find it interesting and another step in China’s own move to be a global leader of tech. Could be either good or bad in the longer term.
China is taking a more inclusive tack in instituting cybersecurity standards for foreign technology companies, allowing them to join a key government committee in an effort to ease foreign concerns over the controls.
The committee under the government’s powerful cyberspace administration is in charge of defining cybersecurity standards. For the first time, the body earlier this year allowed select foreign companies— Microsoft Corp. MSFT −0.39 %, Intel Corp. INTC 0.43 %, Cisco Systems Inc. CSCO 0.14 % and International Business Machines Corp.—to take an active part in drafting rules, rather than participating simply as observers, said people familiar with the discussions.
How much influence the foreign companies will have over committee deliberations remains to be seen, these people said. Over the past few months, the committee’s seven working groups—which focus on encryption, big data and other cybersecurity issues—have each met at least once.
Hope they’re working with QC researchers in Los Alamos and DARPA; it is the US Government which is known for its silos and multi-layer bureaucracies.
Quantum computing is a novel way to build computers — one that takes advantage of the quantum properties of particles to perform operations on data in a very different way than traditional computers. In some cases, the algorithm speedups are extraordinary.
Specifically, a quantum computer using something called Shor’s algorithm can efficiently factor numbers, breaking RSA. A variant can break Diffie-Hellman and other discrete log-based cryptosystems, including those that use elliptic curves. This could potentially render all modern public-key algorithms insecure. Before you panic, note that the largest number to date that has been factored by a quantum computer is 143. So while a practical quantum computer is still science fiction, it’s not stupid science fiction.
(Note that this is completely different from quantumcryptography, which is a way of passing bits between two parties that relies on physical quantum properties for security. The only thing quantum computation and quantum cryptography have to do with each other is their first words. It is also completely different from the NSA’s QUANTUM program, which is its code name for a packet-injection system that works directly in the Internet backbone.)
Another spin on AI in how it eradicates poverty; hmmm.
Eradicating extreme poverty, measured as people living on less than $1.25 US a day, by 2030 is among the sustainable development goals adopted by United Nations member states last year.
A team of computer scientists and satellite experts created a self-updating world map to locate poverty, said Marshall Burke, assistant professor in Stanford’s Department of Earth System Science.
It uses a computer algorithm that recognizes signs of poverty through a process called machine learning, a type of artificial intelligence, he said. Results of the two-year research effort have been published in the journal Science.
Is Market Capitalism simply an accident of certain factors that came together in the 19th and 20th centuries? Does the innovation of economics require a new economics of innovation? Is the study of economics deeply affected by the incentive structures faced by economists themselves, necessitating a study of the “economics of economics”? In this broad ranging interview INET Senior Economist Pia Malaney sits down with Eric Weinstein — mathematician, economist, Managing Director of Thiel Capital (as well as her co-author and husband) to discuss these and other issues.
Underlying the seismic shifts in the economy in the last ten years, Dr. Weinstein sees not just a temporary recession brought on by a housing crisis, but rather deep and fundamental shifts in the very factors that made market capitalism the driving force of economic growth for the past two centuries. The most profound of these shifts as Dr. Weinstein sees it, is an end to 20th century style capitalism brought about not by a competing ideology, as many had once feared, but instead by changing technology. As production is driven increasingly by bits rather than atoms, he sees the importance of private goods give way to public goods, undermining a basic requirement of market models. In a different line of thinking, as software becomes increasingly sophisticated it takes on the ability to replace humans not only in low level repetitive tasks but also, with the use of deep learning algorithms, in arbitrarily complex repetitive tasks such as medical diagnosis.
