Monthly Archives: March 2020

Secret document says WikiLeaks cable leaks disrupted tracking of nation-state hackers – TechCrunch

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A previously secret document from 2010 warned that classified diplomatic cables published by WikiLeaks would likely result in observable changes in the tactics and techniques used by foreign spies, potentially making it easier to avoid detection by U.S. agencies.

The document, recently declassified through a Freedom of Information request by the nonprofit National Security Archive and shared with TechCrunch, reveals a rare glimpse inside U.S. Cyber Command, the militarys main cyber-warfare unit, which feared that the leaked diplomatic cables of communications between U.S. foreign embassies would uncover and hamper its ongoing cyber operations.

Michael Martelle, a research fellow for the National Security Archives Cyber Vault Project, said the subsequent publication of the cables by WikiLeaks gave the adversaries a period of heightened advantage.

The publication of the document comes almost exactly a decade after U.S. Army intelligence analyst Chelsea Manning downloaded and forwarded 750,000 classified cables to leak-publishing site WikiLeaks. Manning was subsequently sentenced to 35 years in prison for what was then the largest leak of U.S. classified material in its history. Her sentence was commuted by then-President Barack Obama in 2017.

Cyber Command wrote its findings in a so-called situational awareness report dated December 2010, just days after The New York Times and several other news outlets published the full cache of diplomatic cables, albeit with redactions to protect sources. The highly redacted assessment warned that the military cyber unit expected to see foreign intelligence services active in cyber-espionage against the U.S. use the information published by WikiLeaks to their own advantage.

(Image: National Security Archive)

According to the assessment, the leaked cables clearly state that the U.S. government entities at the time have knowledge of specific tactics and techniques used by foreign adversaries, including malware, toolsets, IP addresses, and domains used in intrusion activity.

It went on to warn that those same adversaries are expected to modify their current infrastructure and intrusion techniques to evade U.S. cyber-defenses.

(Image: National Security Archive)

Although the redactions in the declassified document make it unclear exactly which adversaries Cyber Command was referring to, Martelle said that only one specific adversary China was mentioned in the entire cache of unredacted documents, which WikiLeaks published a year later, much to the chagrin of the news outlets.

Just one month before the first cables were published, Google had publicly accused Beijing of launching targeted cyberattacks against its network. Several other companies, including antivirus maker Symantec and defense contractor Northrop Grumman, were also hit by the attacks, in an offensive cyber campaign that became known as Operation Aurora.

Google subsequently withdrew from China following the furor.

Cyber Commands assessment said that all Dept. of Defense divisions and U.S. intelligence agencies remain vigilant to anomalies amid fears that its adversaries will leverage this new information to further their cyber initiatives.

When reached, a spokesperson for Cyber Command did not comment. Google also did not comment. An email to WikiLeaks went unreturned. WikiLeaks founder Julian Assange is currently detained and awaiting extradition to the U.S. for publishing the classified cables.

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Jury fails to decide whether former CIA engineer leaked secrets in WikiLeaks case | TheHill – The Hill

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A Manhattan federal judge declared a mistrial Monday after a jury was unable to decide whether to convict computer engineer Joshua Schulte on charges of leaking CIA materials to WikiLeaks.

While the jury was hung on eight counts, including illegal gathering and transmission of national defense information, jurors convicted him on charges of contempt of court and making false statements to the FBI, The New York Times reported.

The jury reportedly deliberated for six days, with one juror replaced after researching the case against the judges orders. She was never replaced, leaving 11 people to determine the final verdict.

Jurors also raised concerns about a second jurors attitude in a note, saying she was not participating in discussions, the Times reported.

Prosecutors said Schulte, who resigned in November 2016, was motivated by resentment over his belief that the agency was disregarding his workplace complaints.

The government may retry Schulte, who also faces a separate federal trial over thousands of images and videos of child pornography allegedly discovered on electronic devices during a search of his home.

Schultes attorneys argued the vulnerabilities in the CIAs computer network were widely known, and that it could have been breached by other sources, pointing in particular to a CIA employee identified as Michael who was close friends with Schulte and left the office with him on the night of the alleged theft.

The government placed Michael on administrative leave for refusing to cooperate with the investigation, but it did not notify Schultes defense ofthe action until six months later beforeMichael served as a witness for the government, according to the Times.

It shows their doubt about the case against Mr. Schulte, Schultes lawyer, Sabrina Shroff, said in her closing argument.

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US, Assange and WikiLeaks – Daily Times

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The fragility of the US, the worlds most powerful nation and said to be a model democracy, couldnt bemore stark when one follows its hounding of Julian Assange, the founder of the WikiLeaks, who had the temerity to expose the ugly and brutal side of the workings of US power, for instance, the killings of civilians in Iraq from aerial bombing for no real purpose.

In other words, it was in public interest that such informationshould be made known, which the WikiLeaks agreed to publish on its platform, as well as sharing, most of it, with respected newspapers such asTheGuardian and The New York Times.

While Assange is being hounded for the material published on Wikileaks, the newspapers that published that materialare spared so far because, for some odd reason, they are regarded as practising responsible journalism because they redacted some of the material that might put lives of some Western agents in danger.There is nothing so far to suggest that WikiLeaks jeopardised the lives of any agent/s.

In other words, newspapers like The Guardian and The New York Times were practising journalism, while Assange and his WikiLeaks were not in that business and hence not worthy of public interest journalism. Assange, therefore, was engaged in espionage when publishing the secret information, and hence accountable for the said offence of espionage.

Of course, the trial in the US on espionage charges will happen as and when the judicial process of extradition in the UK is completed, and Assange is found to be liable for proceedings in the US. It is important to note that the extradition between the US and UK excludes political offences.

But the whole process seems to assume that Assanges leaking of the US documents was a criminal offence for which he is liable to face consequences in the US. In other words, it is essentially a political process rolled out as a criminal case, in which Assange is already viewed as having committed alleged act/s of espionage against the US. To put it more bluntly, the UK judicial process seems tailored to hand over Assange to the US over a period, where he is said to be facing multiple life imprisonment of 175 years. It is simply vendetta dressed as justice, with the US proclaiming loudly that no matter what your citizenship status and/or the place of alleged crime, the US would hunt you down. Even though President Barack Obama pardoned Manning for supplying the documents to WikiLeaks, Assange must face the music for daring to reveal the USs ugly and brutal side.

Assange, according to reports, has been strip-searched and repeatedly handcuffed like some violent criminal, prevented from any communication with his legal team, and was thrown into solitary confinement

Even before Assange faces justice in the US after the extradition process in the UK, as and when it is completed, proceedings in the magistrates court pre-judge him as a criminal. Assange, according to reports, has been strip-searched and repeatedly handcuffed like some violent criminal, prevented from any communication with his legal team, and was thrown into solitary confinement and the like. His treatment has been so abysmal that more than 60 British doctors protested at his torture.

Assange is an Australian citizen but his own government being part of the US-led Five Eyes intelligence-sharing compact-whichincludes the US, Britain, Australia, Canada and New Zealand-islargely letting Assange face his destiny with the US justice system when he is delivered from his British nightmare into a US dungeon.

It was reported that a Trump associate/confidant had let it be known that if Assange would declare that his leaking of a trove of Hillary Clinton related emails, towards the close of the presidential election, was not a part of Russian interference to favour Trump, he might be pardoned. The Trump camp has denied any such deal.

One, however, wonders why Assange is such a criminal when at the height of the election campaign, Trump, as a presidential candidate, openly encouraged WikiLeaks to come out with Hillary leaks, saying that he loved WikiLeaks. However sordid the whole WikiLeaks saga is from the beginning the sad thing is the USs model democracy is hounding an individual for exposing the truth behind an image that was illusory.

The writer is a senior journalist and academic based in Sydney, Australia

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Top 10 Unexpected Future Applications Of Quantum Computers …

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Quantum computing is a major trend in computer science. Its jaw-dropping to think that it all started from observing the weird properties of light! There have been several pioneers in quantum computing, the main one being Richard Feynmanhe explained that quantum computers are feasible and that they are the future of computing.

Quantum computers have existed since way before you think. The first quantum computation was carried out in 1997, using NMR on chloroform molecules.[1] Nowadays, weve been trying to slap the quantum buzzword on just about anything. Even then, there are still a few applicationsin the endless list of quantum technologiesthat are really mind-boggling.

Cancer is one of the leading causes of death around the world. In fact, according to a recent survey from the World Health Organization (WHO), respiratory cancers alone claimed 1.7 million lives in 2016. However, if cancer is recognized at an early stage, the chances of recovery through treatment are much higher. There are many ways cancer can be treated. One is to remove it by surgery; another is through radiotherapy.

Beam optimization is critical in radiotherapy, as it is important to make sure that the radiation damages as little healthy cells and tissues near the cancer region as possible. There have been many optimization methods for radiotherapy in the past that use classical computers. In 2015, researchers at the Roswell Park Cancer Institute came up with a new technique that uses quantum annealing computers, like the ones manufactured by D-Wave, to optimize radiotherapy in a manner that is three to four times faster than that of a regular computer [2]

Many of us are familiar with waking up early and setting off for work, only to find a traffic jam waiting on the way. And then comes the terrifying feeling that youre going to be late for work. Google has been working on fixing this problem by monitoring traffic and suggesting alternative routes to its users. However, Volkswagen is taking it to another level with their research.

In a 2017 experiment, Volkswagen tried to tackle the issue of traffic, not through monitoring but rather by optimizing traffic flow itself. They used the Quadratic Unconstraint Binary Optimization (QUBO) technique with quantum annealing computers to find the optimal route for a select number of cars and possible routes in consideration.[3]

So far, they have tested this with 10,000 taxis in Beijing to show how their method can optimize traffic flow significantly faster than a classical computer. However, many people are skeptical of Volkswagens claims, since they used a D-Wave quantum annealing computer to do the processing. Many scientists state that the quantum annealers D-Wave manufactures do not offer a speedup as significant as Volkswagen claims.

We have all been in a spot where the mobile data reception is excessively bad, and wed rather just use that slow WiFi hotspot in that nearby coffee shop. Well, it seems that a company called Booz Allen Hamilton might just have found the solution to the horrible network coverage problem, with the help of quantum computers, of course!

In a 2017 publication, they suggested that optimal satellite coverage is pretty tough to figure out. This is because there are a lot of possible alignment combinations, and it is really hard to check all these combinations with classical computers.

The solution? They suggest that using the QUBO technique, as previously mentioned, with the help of D-Waves quantum annealing computers, can help find the optimal satellite coverage position required.[4] This would not mean that the satellites would be able to cover all the bad reception spots, but the likelihood of being able to find a spot with better reception can be increased significantly.

Molecule simulation has been a crucial field in biology and chemistry, as it helps us understand the structure of molecules and how they interact with each other. But it also helps us discover new molecules.

Although classical computers nowadays may be able to simulate these molecular dynamics, there is a limitation on the complexity of molecules in a given simulation. Quantum computers are able to effectively break this barrier. So far, theyve only been used to simulate small molecules, like beryllium hydride (BeH2), for example. It might not seem like much, but that fact that it was simulated by a seven-qubit chip shows that if we had more qubits at our disposal, we might be able to run extremely complex molecular simulations.[5] This is because the processing power of quantum computers increases exponentially as the number of qubits increase.

Other hardwarelike D-Waves quantum annealing computershas also been used by researchers to come up with simulation methods that might be just as good, if not faster, than current methods.

Some of us might have heard of the scare about quantum computers being able to break cryptosystems such as RSA or DSA. This seems to be true for some cryptosystems, as they rely on prime numbers to generate a key based on prime factors. An algorithm, called Shors algorithm, can be used by quantum computers to find the prime factors used to generate the key, and they can do it much more efficiently.

But what about the other cryptosystems which do not rely on prime numbers to generate keys? There is another algorithm called Grovers algorithm which might be used to brute force a key faster than a classical computer. However, this is not as big of a speedup as Shors algorithm would offer, compared to a classical computer (quadratic vs. exponential speedup). This would mean that we would need significantly faster quantum computers than the ones that currently exist to even attempt to break these cryptosystems.

Even with that, there are some cryptosystems that would be impossible for quantum computers to break. These cryptosystems are categorized within the field of post-quantum cryptography. Overall, though, it would seem that at least RSAwhich is often used in digital signatureswould be obsolete.[6]

Artificial intelligence is an extremely trending field in computer science. Scientists have been trying to make AI more humanlike through the means of machine learning and neural networks. Seems terrifying, but now add quantum computers to the concoction, and it is taken to a whole new level.

Neural networks run on matrix-based data sets, and the processing done in neural networks is computed through the means of matrix algebra. However, quantum computing itself fundamentally works in such a nature that matrices are often used to define and determine the quantum states of qubits.[7] So with that, any computational process done on the neural network would be similar to using transformational quantum gates on qubits. Hence, quantum computers seem like the perfect fit for neural networks incorporated in AI.

Not only that, but quantum computers can also help to significantly speed up machine learning compared to a classical computer. This is why Google has been investing in quantum computer research to improve Google AI by means of quantum hardware.

This is very different from post-quantum cryptography, as it is not meant to prevent quantum computers from breaking cryptosystems, though it does that, anyway. This type of cryptography uses the means of quantum mechanics itself. But how is it more versatile than other forms of cryptography?

Quantum cryptography mainly focuses on the key distribution part of a cryptosystem, here two pairs of entangled qubits are used. One is sent to the receiver, while the sender keeps the other. Entangled particles in a superposition, when measured, affect the other qubit. Send a stream of these qubits, and you have a key usable for encryption.[8]

The best part about it is that eavesdropping is impossible, as the qubits cannot be copied. They cant be measured, either, as there are methods to determine whether the qubit has been tampered with before being received by the intended recipient. This makes it a robust method for cryptography, which is why scientists are still researching this field.

Weve all had that time where weve checked the weather forecast, and it said that it was going to be a wonderful, sunny day. Then, only moments later, it starts to pour, and you didnt bring your umbrella. Well, it seems quantum computers might have a solution for that.

In 2017, a Russian researcher published a paper about the possibility of using quantum computers to predict the weather more accurately than classical computers. There are a few limitations with current computers in predicting all the intricate changes in weather.[9] This is because large amounts of data are involved, but quantum computers seem to offer a big speedup compared to classical means because of Dynamic Quantum Clustering (DQC) methodology, which is claimed to generate useful datasets that classical techniques cannot.

Even so, it must be noted that not even quantum computers can predict the weather with absolute accuracy, but at least it will be less likely that we will regret not bringing an umbrella on suspicious sunny days!

We all hate it when we search for an article, only to find it to be littered with advertisements. Most of it doesnt even seem relevant! Luckily, Recruit Communications has found a solution for one of those two problemsthe relevancy of ads.

In their research, they explained how quantum annealing can be used to help companies wanting to advertise to reach a wider range of people without spending too much. The quantum annealing can be used to match relevant advertisements to customers so that theyre more likely to click them.[10]

With all the speedup quantum computers offer in the computing field, one thing gamers might be curious about is whether they can be used to make a sweet gaming rig which can run games at blazing high framerates. The answer would be, Sort of.

At this point, the field of quantum computers is still at its infancy, and current hardware still hasnt reached quantum supremacywhich is when quantum hardware can compute faster than the current best computers, though the definition is still vague. This is because quantum computer algorithms work very differently from classical ones. Even with that, quantum gaming still seems to be possible.

There have been a few games which have been developed to utilize quantum computers. One of them is called Quantum Battleships, which is based on the Battleships board game.[11] Furthermore, Microsoft has been working on a programming language called Q#, which uses both classical and quantum hardware to compute. It is also very similar to C#, which would mean that it is very possible to develop games using Q# that take advantage of quantum hardware. Maybe well have Call of Duty Q one day!

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Harnessing the power of light: A European history of photonics – EURACTIV

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Europe has a long and rich history of harnessing the power of light to extend the technical and practical capacities of the human species. The modern-day utilisation of light for such means takes its form in the technology of photonics, and today, Europes clout in the arena is formidable.

Currently, the continent ranks second only to China in the global photonics market, and projections estimate that the sector could attain a compound annual growth rate of 8.6% leading up to 2022.

While today photonics technologies are used in high-tech applications such as quantum computing applications, Internet of Things devices, wearable devices, self-driving cars, and healthcare technologies, the origin of Europes relationship with light technologies stretches back millennia.

In order to unlock the technological possibilities of tomorrow, our ancestors first had to wrestle with the mystifying theoretical foundation of the material property known as light, and it befell one of Europes most dominant civilisations, the ancient Greeks, to first pursue this tract.

One of the earliest influential documentations on materials theories of light appeared in mathematician Euclids treatise on vision, whose earliest surviving manuscript dates from the 10th century.

Euclids postulated over the geometrical properties of light leading him to conceptualise the law of reflection. Euclid, along with Greek mathematician Ptolemy, subscribed to what is known as emission theory the notion that the visible perception of things occurred as a result of the eyes themselves emitting rays of light.

Inspired by Euclid and Ptolemys work, the Arab mathematician Ibn al-Haytham hypothesised that the objects themselves radiate light.

The next most relevant development on photonics back in Europe came by way of Issac Newtons work in the 17th century. Based on his renowned prism experiment, he concluded that light is a mixture of various colours having different refractivity, which eventually formed the basis for his Light Particle Theory as outlined in the 1704 title Opticks.

One of the main opponents to Newtons theory was the Dutch mathematician Christiaan Huygens, who, being inspired by Rene Descartes 1637 treatise, Dioptrics, believed that light took the form of waves.

Planck and Einstein make the leap

But it finally fell upon Max Planck and then Albert Einstein to make the greatest scientific leaps in photonics research, and reveal the true nature of light.

Plancks contribution to the world of quantum physics was a momentous leap in the pursuance of photonics technologies. In 1900 Planck managed to find an association between the amount of energy that a photon is able to carry and the frequency of the wave by which it travels giving rise to the now famous Plancks Constant theory.

In 1905, Einstein published a paper refuting the commonly accepted proposition that a light-beam is a wave travelling through space, contending instead that it is an amalgam of discrete wave packets, later dubbed photons, that each contain a quantity of energy. Einstein discovered that as part of the photoelectric effect, the phenomena of photons striking elections, light was never made up of merely waves nor particles, but in fact both.

Einstein has settled the age-old theory on the material properties of light, and in so doing, was awarded the 1921 Nobel Prize for Physics.

Einstein is the father of modern photonics technologies, and without his findings, many of the applications used across Europes optical industries would probably never have come into being.

In terms of European innovation, Einsteins work became fundamental in many later technological developments, including Hungarian-British scientist Dennis Gabors 1948 invention of holograms, and more modern applications, such as the University of Regensburg in Germanys research into how laser-light pulses can be used in quantum computing.

Revolutionary potential

More broadly, from computer screens to lasers in healthcare devices and solar panels, from cameras in smartphones to optical fibre technologies, the revolutionary potential of photonics has been recognised by the European Commission as a Key Enabling Technology of the 21st century.

In this vein, a 2018 report by the European Investment Bank recognised the potential of photonics technologies to enrich and extend the capabilities of other next-generation applications, which, without Europes history in scientific research, would never have been possible.

Deep tech applications such as artificial intelligence, big data, additive manufacturing, robotics, the Internet of Things (IoT), and autonomous driving will require faster, more reliable, more energy efficient and more powerful photonics and semiconductor components, the report states.

The success of Europe in this next wave of innovation will ultimately depend on photonics and semiconductor components.

With Europes valiant scientific excursions into the theory of light and photoelectric research being well-established, there are also those who have touted photonics as an area in which the wider political goals of the European Union can be pursued.

While the Von der Leyen Commission has been quick to employ the term sovereignty across the digital and data fields, there are those who believe that amid the current global economic climate, Europe must place an emphasis on an industry that bears the development of so many other technologies.

A recent paper entitled Exploration of Photonics Markets,published by the industry lobby Photonics21, found that Chinas annual spending in photonics will hit 1 billion in 2020.

There are concerns that Europes well-established research in light technologies could fall by the wayside while larger global players commit to substantial investments.

A December 2018 letter penned by leading scientists in the field brought these concerns to the fore, highlighting the importance of photonics technologies playing a central role in the Digital and Industry section of the next Horizon budget 2021-2027.

Carlos Lee, director-general of the European Photonics Industry (EPIC), recently told EURACTIV that photonics technologies should be heralded as a European success story.

And, looking at the figures, its hard to disagree. Estimates published by EPIC show that the photonics sector, built up predominantly of SMEs, features around 5,000 companies that have created more than 300,000 skilled jobs, with an annual turnover of 60 billion.

These fast-growing figures are a testament to Europes intellectual, scientific and philosophical history in theorising the properties of light, and how such a source can be harnessed to transform our technological landscape.

Only time will tell whether the continent will be able to distinguish itself further in this domain by ensuring that photonics remains at the forefront of the technological developments of tomorrow.

[Edited by Zoran Radosavljevic]

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Artificial Intelligence (AI) Definition

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What Is Artificial Intelligence (AI)?

Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving.

The ideal characteristic of artificial intelligence is its ability to rationalize and take actions that have the best chance of achieving a specific goal.

When most people hear the term artificial intelligence, the first thing they usually think of is robots. That's because big-budget films and novels weave stories about human-like machines that wreak havoc on Earth. But nothing could be further from the truth.

Artificial intelligence is based on the principle that human intelligence can be defined in a way that a machine can easily mimic it and execute tasks, from the most simple to those that are even more complex. The goals of artificial intelligence include learning, reasoning, and perception.

As technology advances, previous benchmarks that defined artificial intelligence become outdated. For example, machines that calculate basic functions or recognize text through optimal character recognition are no longer considered to embody artificial intelligence, since this function is now taken for granted as an inherent computer function.

AI is continuously evolving to benefit many different industries. Machines are wired using a cross-disciplinary approach based in mathematics, computer science, linguistics, psychology,and more.

Algorithms often play a very important part in the structure of artificial intelligence, where simple algorithms are used in simple applications, while more complex ones help frame strong artificial intelligence.

The applications for artificial intelligence are endless. The technology can be applied to many different sectors and industries. AI is being tested and used in the healthcare industry for dosing drugs and different treatment in patients, and for surgical procedures in the operating room.

Other examples of machines with artificial intelligence include computers that play chess and self-driving cars. Each of these machines must weigh the consequences of any action they take, as each action will impact the end result. In chess, the end result is winning the game. For self-driving cars, the computer system must account for all external data and compute it to act in a way that prevents a collision.

Artificial intelligence also has applications in the financial industry, where it is used to detect and flag activity in banking and finance such as unusual debit card usage and large account depositsall of which help a bank's fraud department. Applications for AI are also being used to help streamline and make trading easier. This is done by making supply, demand, and pricing of securities easier to estimate.

Artificial intelligence can be divided into two different categories: weak and strong. Weak artificial intelligence embodies a system designed to carry out one particular job. Weak AI systems include video games such as the chess example from above and personal assistants such as Amazon's Alexa and Apple's Siri. You ask the assistant a question, it answers it for you.

Strong artificial intelligence systems are systems that carry on the tasks considered to be human-like. These tend to be more complex and complicated systems. They are programmed to handle situations in which they may be required to problem solve without having a person intervene. These kinds of systems can be found in applications like self-driving cars or in hospital operating rooms.

Since its beginning, artificial intelligence has come under scrutiny from scientists and the public alike. One common theme is the idea that machines will become so highly developed that humans will not be able to keep up and they will take off on their own, redesigning themselves at an exponential rate.

Another is that machines can hack into people's privacy and even be weaponized.Other arguments debate the ethics of artificial intelligence and whether intelligent systems such as robots should be treated with the same rights as humans.

Self-driving cars have been fairly controversial as their machines tend to be designed for the lowest possible risk and the least casualties. If presented with a scenario of colliding with one person or another at the same time, these cars would calculate the option that would cause the least amount of damage.

Another contentious issue many people have with artificial intelligence is how it may affect human employment. With many industries looking to automate certain jobs through the use of intelligent machinery, there is a concern that people would be pushed out of the workforce. Self-driving cars may remove the need for taxis and car-share programs, while manufacturers may easily replace human labor with machines, making people's skills more obsolete.

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Whats The Impact Of Artificial Intelligence And Technology On Society – Forbes

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What do we need to consider about a future where artificial intelligence (AI) and tech have transformed the way we live? That was exactly what we pondered when I recently spoke with Jamie Susskind, barrister, speaker and award-winning author of Future Politics: Living Together in a World Transformed by Tech.

Whats The Impact Of Artificial Intelligence And Technology On Society

Trends That Are Changing Civilization

Technology is changing society. Digitization is challenging the way we live. These changes create conveniences and ways of problem-solving that were never possible before. Along with the positives, there are also challenges that need to be overcome.

Here are three trends that are taking us to a phase of civilization thats quite different than anything thats come before.

1.Increasingly capable systems

We already live in a world where non-human systems can do things that previously only humans could do. In some cases, these non-human systems can do tasks even better than we can. Artificial intelligence can now mimic human speech, translate languages, diagnose cancers, draft legal documents and play games (and even beat human competitors). Were already in a society where systems can accomplish tasks we didnt believe would be possible in our time. The capabilities of non-human systems will continue to expand.

2.Systems become more ubiquitous

This line between online and offline, real space and cyberspace is one that will become less important and less meaningful as time goes on. Systems are becoming more capable and more integrated into the world around us, Susskind explained. It used to be very easy to distinguish between technology and non-technology. Today and increasingly in the future, technology will be dispersed in the world around us in objects and artifacts that we never previously thought of as technology such as smart homes with smart appliances and in public spaces in smart cities dense with sensors.

3.Increasingly quantified society

We generate more data now every couple of hours than we did from the dawn of time to 2003. What that means is that when that data is caught, captured and sorted those who own it and control it have an insight into our lived experience beyond anything that anyone in the past could ever have dreamed of into what we think, what we care about, how we feel, where we go, what we buy, who we speak to, what we say, what we do on any given day, who we associate with. We leave a trail of these things which offers a window into our soul both individually and collectively that dwarfs anything that the philosophers or the kings or the priests of the past could have dreamed of, Susskind explained.

These three trends are accelerating, and it seems highly unlikely that we as humans are going to be unchanged in the way we live together as a result of them. Weve never had to live alongside such powerful non-human systems. Weve never known what its like to be surrounded by technology thats never switched off. Weve never been in a world where our lives are datified to such as extent. In his book, Future Politics, Susskind examines these changes and proposes what we might need to do, theorize and think about regarding these changes as a society.

The Digital is Political

The digital is political. Instead of looking at these technologies as consumers or capitalists we need to look at them as citizens. Those who control and own the most powerful digital systems in the future will increasingly have a great deal of control over the rest of us, Susskind predicts.

Technologies exert power. They contain rules that the rest of us must follow and those who write the rules increasingly have a degree of power.In our society there are two major benefactors of technology and who wield this power: governing bodies that can use technologies and surveillance for enforcement of rules and large corporations, specifically tech companies or companies who use a lot of tech and are increasingly writing the rules we must abide by (think the 280-character limit on Twitter).

By gathering data about our preferences, browsing history and more other people have power over us. They know what makes us tick and they know our carrots and sticks. In the example of Cambridge Analytica and the 2016 U.S. presidential campaign, the company had a couple of thousand data points about 200 million Americans. This enabled them to project an image of a candidate that was tailored to the preferences and prejudices and biases at an individual level.

Bottom line: The more data that is gathered about us, the easier it is for others to persuade, influence and manipulate us. In addition, just knowing that data is being gathered about us is likely to change our behavior. Many people dont understand the level of surveillance thats already going on. As more people become more cognizant of the fact that were always being watched, Susskind believes that people will start changing their behavior. This is a kind of power itself, albeit subtle but important.

Technology Enables Perception Control and Power

We currently rely on third parties to tell us what is going on in the world and those third parties are more often than not mediated by digital technology. When we get our news from a newsfeed were at the mercy of those technologies who decide which very small slice of reality were going to be presented. We must acknowledge that those who own and control the technologies that filter our perception of the world are very, very powerful because they shape our innermost feelings and our soul as well as our collective understanding of what matters.

Power cascades onto other simple political concepts like democracy. How we deliberate online changes the democratic process. There are also questions of freedom. What does it mean to live in a world when rules are set often not by states but private companies and often in ways that arent liberty maximizing?

Thinks about justice. Whats it going to be like living in a world where your access to important things like jobs, insurance or credit might well be mediated by algorithms which are themselves not necessarily as fair as morality or the law would like them to be? As an example, there have been face recognition systems that dont see people of color because they were trained on datasets of white people. Similarly, voice recognition systems can struggle to understand voices with accents. Previously these kinds of problems were seen as engineering problems or corporate problems, but Susskind sees them as political problems.

Call for Clarity

While individuals have the power to improve digital hygiene, one person by their individual actions doesnt have the power to sway these issues. These are problems that can only be solved through collective means and mechanisms. Susskind believes if you want the rules of the game to be changed for everyone, then law, legislation and regulation are the only way to do it.

Its a call to action at a level which will make some people uncomfortable particularly in the United States because some are skeptical about the state trying to correct issues that are thrown up by private ordering but I think is necessary, Susskind shared.

Although some are reticent to trust governments to establish regulations and boundaries for technology, Susskind believes we must have some faith in politics if were going to make sure we dont live in a world where were not fundamentally buffeted around by forces that are effectively invisible and out of our control because they are concentrated in private hands.

Tech companies are led by humans who have the pursuit of profits as a goal in a capitalist society. While there is nothing wrong with that, we designed political systems to hold them to account for when they slip up. Thats precisely why the political steps we take are critical in a world transformed by technology.

For more on AI and technology trends, see Bernard Marrs book Artificial Intelligence in Practice: How 50 Companies Used AI and Machine Learning To Solve Problems and his forthcoming bookTech Trends in Practice: The 25 Technologies That Are Driving The 4ThIndustrial Revolution, which is available to pre-order now.

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Whats The Impact Of Artificial Intelligence And Technology On Society - Forbes

Artificial Intelligence: The DNA Of Data That Fills The Gap – Forbes

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Artificial intelligence, or AI, often brings to mind hospitality robots and self-driving cars -- the shiny, flashy machines effortlessly performing everyday tasks with superhuman speed and efficiency. Yet, peek under the hood, and youll find the real magic. Its here that AI has a different meaning as the DNA of data that fills in the gaps.

The sentient pieces of metal might dominate popular imagination, but in todays world, AI is more likely to be an obscured yet essential building block of any business. Most organizations understand the importance of using data to reduce costs and serve clients and customers effectively, but what happens when the data is too voluminous to understand? AI steps in to help turn what would otherwise be an unconnected rabble of data into meaningful insights into every facet of the business.

From computer code to big data to AI to business results

Ideas for computer code existed in the human mind for hundreds of years. But it wasnt until the 20th century that hardware caught up, allowing a spate of programming languages to manipulate the new machines and create the big data condition that is the modern world.

Weve recently reached a point where our devices generate mind-blowing amounts of data. According to a recent Forbes article, the amount of newly created data in 2020 was predicted to reach 35 zettabytes (or 35 trillion gigabytes). Two years ago, we were at 33 zettabytes, leading IDC to predict that in 2025, 175 zettabytes (or 175 trillion gigabytes) of new data will be created worldwide. Its far too much for any human worker or team of workers to process. Instead, organizations rely on artificial intelligence to aggregate, analyze and assess data -- something that happens across industries.

Banking, for example, benefits from AI tremendously. At HDFC Bank in India, machine learning, a subset of AI, analyzes demographic, geographic and other data for thin loan applications. This enables the banks human analysts to quickly identify the best applicants and manage the companys risk.

In content management, AI has dozens of use cases, assisting departments seemingly as different as marketing, editorial and enterprise search. Finding, reading and recommending articles is an age-old process of getting the news that today owes itself to the collaboration of custom-built AI algorithms and teams of up to 20 employees.

Data is the foundation, and AI is the DNA

For all its power, AI is nothing without data. An algorithms ability to locate patterns and offer suggestions is contingent on whatever it can draw from raw data. Yet, as data proliferates, it runs the risk of becoming chaotic and unruly. Data today isnt just strings of numbers, letters and symbols. It could be thousands of characters representing human-based speech. So, how does one make sense of it all?

Natural language processing (NLP), a subfield of computer science that relies heavily on machine learning, works at the nexus of computers and natural language. Its one example of a cognitive technology that can quickly analyze large, unstructured data sets -- such as medical data, contracts and legal literature -- to elicit trends and discover solutions to complex problems. Its a time-consuming task that a human would struggle to complete, but it can now be done in seconds.

Another example is translation. A person starting from scratch might spend years (if not a lifetime) learning to translate a piece of work from English to Japanese. A machine learning-based algorithm can now do it instantaneously as you type.

Its in these ways that AI proves itself as the DNA of data. Data alone cant automatically solve a problem. A database containing every word in every language in the world would be useless without an interpreter to fill in the gaps.

One study showed that object transplanting trips up deep facial recognition AI, concluding that the double-take, an instinctive human gesture that helps us identify when things might not be what they seem, continues to elude smart algorithms. AIs evolution as the DNA of data cannot be dismissed, and sometimes the merger of human and machine is uncanny.

Conclusion

To solve a classic machine learning problem -- correctly identifying handwritten numbers -- Caltech researchers developed an artificial neural network made out of DNA. If we have the capacity to program AI into synthetic biomolecular circuits, companies should be able to use AI to better serve their customers.

By integrating technological back ends with middleware and filling the gaps with AI, applications become flexible, ground-up platforms where this happens. Built with speed and agility, they can cut the number of steps in a process from 20 to four, while evolving with customer demand.

An enterprise corollary concept is an intelligent data hub, a centralized architecture for managing data about various parties, places and things. As the data grows and becomes increasingly complex, the hub keeps them easily relatable with its layer of artificial intelligence, governing them while serving them up to real-time business users.

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Artificial Intelligence: The DNA Of Data That Fills The Gap - Forbes

Leveraging artificial intelligence to automate data extraction from geotagged images – Geospatial World

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CSS Corp is enabling leading mapping companies to accelerate POI extraction from geotagged images through AI-ML led automation

While navigating using a mobiledevice, we often select a source and a destination that are well-known andfrequently visited places, such as hotels, apartment complexes, touristattractions, corporate offices, etc. In mapping parlance, these places are calledpoints of interest (POI). Most location-based applications and services needaccurate POI data to serve their users effectively. Among several ways tocapture POI data, extracting it from geotagged images is one of the mostpopular. Geotagged images contain geographical metadata like latitude,longitude, and place names, etc.

However,mapping companies often find it challenging to get detailed POI data generated from geotaggedimages accurately. Fierce competition in this field has created a demand forhigh quality and freshness of POI data. It necessitates using efficientprocesses that bring reality to the maps in real-time or as soon as possible.

A leading mapping and location dataplatform provider was under immense pressure to scale their services andcapture the market share rapidly. A critical component of their services was seamlessPOI extraction from field-collected geotagged images while maintaining qualityand accuracy benchmarks. Done manually, this process can be tedious andtime-consuming. CSS Corp was able to support them through rapid deployment oftrained resources at scale, empowered with an assisted automation approach,that accelerated the time-to-market for their services. It leveraged itsproprietary Geo.Intelli system which uses artificial intelligence for automatedextraction of POI data from geotagged images, resulting in faster and efficientprocessing.

Geo.Intelli is a smart GIS system thatautomates the geotag extraction for POI location from images and leverages NLPto check the completeness of POI or address name. Its AI-ML based APIs automaticallyextract the relevant data from images, perform a quality check on images, andreject images that are blurred, non-geocoded, or in invalid format. To ensurehigh accuracy, the system automatically cross-validates the extracted data withreference source data like area, city, latitude, longitude, and ZIP Code. Italso allows for multiple POI addition from a single image.

Certain assisted automation processesin the system leverage agents expertise and oversight to deliver high-qualityresults, for example, automated image analyzer with configurable fieldattributes, automated text extraction for additional information, and automatedtranslation/ transliteration processes.

The system also enhances the teamsproductivity with integrated editingand review workflows and progress dashboards for instant reviews and analytics.Once the system extracts the POI, various users like agents, team lead, and QA canedit, review and perform quality checks within the system as per the workflowsset and see the project performance on customized dashboards. Geo.Intelli givesusers multiple export options to download final POI files in the desiredformat.

The system continuously learnsfrom its data and updates its algorithms to get better with every dataextraction. Today, it can extract English text from images with an accuracy ofover 94%. Speaking of benefits to the client, the ability to make faster decisions on key addressattributes accelerated the teams productivity by 25%. Automated quality checkson key fields safeguarded data quality and reduced editing scope by 60%.Overall, the combination of CSS Corps Geo.Intelli system and a highlyskilled team improved the efficiency of POI processing by 22%, enabling theclient to scale their services faster than the competition.

With location-based services andapplications becoming essential for every aspect of businesses, having completeand accurate real-time data in maps becomes crucial. Stiff competition to thetop is prompting location services providers to look for ways to optimize andaccelerate their processes by leveraging AI and automation. CSS CorpsGeo.Intelli is a GIS automation solution that is designed to enable leadingmapping and location players to uplift their user experience with betternavigation while also creating more business opportunities for them.

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KNAPP and Covariant Introduce the Pick-it-Easy Robot, Powered by Artificial Intelligence (AI) to North American Market – Business Wire

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KENNESAW, Ga.--(BUSINESS WIRE)--Today at MODEX 2020, KNAPP, a leading supplier of intralogistics systems, and Covariant, a leading AI Robotics company, announced a partnership to deploy and bring to market advanced AI Robotics solutions. KNAPP and Covariant have already developed several solutions together. The Pick-It-Easy Robot powered by Covariant AI, is designed for high performance single-piece picking applications and is currently operating in production at several customer sites in North America and Europe, including at Obeta, a German electrical supply wholesaler outside Berlin.

Artificial intelligence will be a defining feature of the warehouse of the future, impacting all aspects of operations and fundamentally changing how business is done, said Jusuf Buzimkic, SVP Engineering at KNAPP. We looked at every solution on the market, and Covariant was the clear winner. Our partnership with Covariant will enable us to deliver cutting-edge artificial intelligence technology to our customers, providing a major leg up in an increasingly competitive world.

Deploying AI Robotics solutions in customer environments is extremely challenging, said Pieter Abbeel, President, Chief Scientist and co-founder of Covariant. To be successful, you need to combine AI software with robotics hardware components, then make sure they integrate into a customers warehouse, which has dozens of other systems running. Its a complex process that requires that every piece of technology is seamlessly integrated. KNAPPs reputation, scale, and 50+ years of experience delivering innovative logistics technology makes them an ideal partner to deploy our AI Robotics technology to customer environments.

KNAPP implemented its first Pick-It-Easy Robot seven years ago in Europe and has been actively developing and refining robotic and vision system technology since that time. The new Pick-It-Easy Robot powered by Covariant is now deployed, field proven and ready to use. According to Jusuf Buzimkic, It can handle unlimited SKU types and works on challenging objects including polybags, banded-apparel, transparent objects and blister packs. It also learns to pick new objects its never seen before and improves over time. The system can easily integrate into warehouses and facilities in the e-commerce, retail, electronics, cosmetics, food, pharmaceuticals and healthcare industries; and a formidable advantage when leveraging the sequencing and versatility of KNAPPs OSR ShuttleTM EVO.

About Covariant

Covariant is building the Covariant Brain: universal AI that allows robots to see, reason and act on the world around them. Founded in 2017 by the worlds top AI researchers and roboticists from UC Berkeley and OpenAI, Covariant is bringing the latest artificial intelligence research breakthroughs to the biggest industry opportunities. The company is headquartered in Berkeley, CA. For more information, visit covariant.ai.

About KNAPP

KNAPP is an internationally operating company and is one of the world market leaders in warehouse logistics and automation with over 4,000 employees worldwide. As a solutions provider, KNAPP provides one-stop, custom-designed intralogistics solutions in health care, retail, apparel, food, manufacturing and ecommerce sectors. Our clients experience results that are flexible, resource efficient, ergonomic and self-learning. The companys North American headquarters are in Atlanta, GA. For more information, visit http://www.knapp.com.

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KNAPP and Covariant Introduce the Pick-it-Easy Robot, Powered by Artificial Intelligence (AI) to North American Market - Business Wire