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The Results Are In: Failure Is a Vital Part of Successful Innovation

Failure is the worst, until it isn't.

Failure has seldom been sexier, with advocates believing that if you're not failing regularly, you're not pushing the boundaries far enough. Such cheerleaders often evoke the spirit of Edison, who famously remarked that his thousands of failed experiments were a necessary precursor to the invention of the lightbulb.

Edison's notorious example merely serves to illustrate the importance of learning from each dead end so that you can be more successful next time. To take such constructive feedback from failure, it's vital that we understand the essence of what our failures represent.

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Using Deep Learning Image Analysis To Spot Inequality

Inequality may seem something that is all too evident, as run down streets and communities show visible signs of lacking due care and attention, But in many communities, poverty can lie out of plain sight. New research from Imperial College London suggests deep learning can be used to better detect social, economic, environmental, and health inequalities than existing methods.

The researchers believe their system can help policymakers gain a greater understanding of the inequalities that exist within their city, and therefore have more informed policies for tackling them. What's more, the real-time nature of the metrics allows more effective interventions to be crafted.

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Why the Car Industry Needs to Take Lessons From Aviation to Make Autonomous Tech Safe

Before autonomous vehicles become fully autonomous, they were developing a range of driver assistance tools to help us navigate the roads safely and effectively. These tools aren’t always as straightforward as they sound, however, and various studies have illustrated how long it takes a human to regain safe control of a vehicle if they haven’t been concentrating on the road.

While these sorts of challenges are still relatively unfamiliar in a motoring context, they are very familiar in aviation, where difficulties in navigating the human/machine interface have caused numerous incidents. It’s a lesson a recent paper suggests we are not heeding.

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Using AI and Social Media to Detect Noisy Areas

Noise disturbances are far and away the most common form of anti-social behavior reported to the police and local authorities, and I'm sure we've all experienced the blight of loud parties. For officials, however, it's likely that the number of reported incidents is a fraction of the total number.

Researchers from the Universidad Politécnica de Madrid have developed an AI-driven tool that they believe will provide officials with a more accurate representation of noise concerns.

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How Can AI Be Used in Schools?

It's perhaps fair to suggest that much of the discussion to date around artificial intelligence and education has revolved around the impact AI will have on jobs, and the changes in skills required to work effectively with and alongside the new technology. It's been much less common to explore how AI might impact the act of education itself, so a recently published report from the innovation group, NESTA, makes timely reading.

The report first looks at the way AI is being used in workplaces today, before then exploring possible changes in the future. NESTA identified three main uses of AI in education today:

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Working Next to Robots

Recent estimates suggest that expenditure on robotics is set to reach $115 billion this year before rising to over $210 billion by 2022. Whereas traditionally industrial robots would be complex and heavyweight bits of equipment that worked largely in isolation from their human "colleagues," it's increasingly common to see man and machine working together.

This is resulting in a growing interest in the psychology and practicality of these interactions. For instance, a few years ago,  researchers explored how people feel about having robots for colleagues.

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Smart Cities Are Global Cities

There remains a sense that smart cities are a term more beloved of technology vendors than citizens, with various reports showing that citizens have not really reaped the promised benefits yet. That’s not to say such lackluster performance is pervasive, with a new report from the University of Glasgow exploring the smart city landscape to see what set the most advanced cities apart from the rest.

The researchers examined over 5,500 cities around the world before settling on 27 who were leading the way. Perhaps unsurprisingly, many of these vanguard cities were capital cities of their respective countries, and as such could be regarded as global cities. The authors believe this global outreach and engagement was vital to the success of their smart city work.

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The New System That Automates Washing the Dishes

Dishwashers have been around for decades, but while they have transformed the domestic kitchen, a commercial environment is a tougher proposition, as the volume and throughput are so much higher, plus the process of clearing food trays and so on is much more complex.

British startup Cambridge Consultants aims to change that with a new AI-powered system called Turbo Clean, which aims to automate much of the work. The system is able to clear each customers' tray using a combination of deep learning, machine vision, and robotics. This allows it to understand the contents of each tray and remove those items before loading them in either the appropriate waste bin or compartment of the dishwasher.

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The Smart Fabric That Can Regulate Heat Automatically

While wearable technology has allowed us to monitor our activity in a variety of interesting new ways, perhaps the most interesting angle is in developments in actual fabric itself. The latest example comes via the University of Maryland, whose researchers have developed a fabric that can automatically regulate the amount of heat that passes through it.

The work, which was documented in a recently published paper, saw the construction of a smart fabric from specially engineered yarn that had been coated with a conductive metal. This changes how the fabric interacts with infrared radiation, which in turn transmits or blocks heat.

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The Sensor Technology That Can Assess Reproductive Health

A couple of years ago, researchers at the Prague Fertility Center used AI as part of the IVF process. They believed that their work was the first automated technology to use AI to recognize and sort embryos.

Now, a team from Imperial College London and the University of Hong Kong have developed sensor technology that they believe can measure hormones in real time and provide a reliable assessment of fertility.

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Is 2019 The Year When Organizations Will Benefit From Data?

As with so many new technologies, the era of big data has been more hype than reality, with many organizations struggling to get high quality data out of internal silos in order to derive timely and actionable insights from it. According to a recent survey from PwC, however, now is the time that will all change. Their latest pulse survey reveals that 86% of companies believe that 2019 will be the year they finally extract value from data.

This priority was emphasized by the 94% of executives who thought customer data was critical, although the size of the challenge was underlined by the fact that just 15% thought they had sufficient data in this area. When asked to explain some of the barriers they faced, the responses were those we've heard many times before, including the quality and standardization of data, the security of it, and the regulatory uncertainties surrounding the collection, storage, and use of data.

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A Collaborative Approach to Cybersecurity

Recent data from security firm LogRhythm highlights the long way most companies still have to go before their cybersecurity is up to scratch. In their survey of 1,500 IT professionals, they found that just 15 percent were confident in their organization’s cybersecurity capabilities.

“These results are worrying as whilst firms have expressed concerns about the regular occurrence of data breaches hitting today’s headlines, it seems like there’s still a long way to go when it comes to addressing their own cybersecurity capabilities,”LogRhythm say. “Today’s hackers are smart, creative, and persistent enough for even the most well-equipped business to be compromised. Having the most up-to-date, sophisticated tools in place is key in combatting modern-day threats.”

While the study cites things like the need for automation to tackle the ever growing speed and complexity of threats, something they neglect to mention is the need for cooperation across the industry. That is exactly the rationale behind the creation of the Charter of Trust by German industrial giant Siemens. The charter, which was originally formed with nine members, has recently grown to 16, including AES, Airbus, Allianz, Atos, Cisco, Daimler, Dell Technologies, Deutsche Telekom, Enel, IBM, NXP, SGS, Total, and TÜV Süd.

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Is a Human Life Worth as Much as a Robotic Life?

You might think that it would be impossible for people to value a piece of hardware over human life, yet new research from Radboud University suggests that such circumstances may exist. Bizarrely, one of these circumstances might involve a perception that robots feel pain.Image title

"It is known that military personnel may mourn a robot that is used to clear mines in the army. Funerals are organized for them. We wanted to investigate how far this empathy for robots extends, and what moral principles influence this behavior towards robots. Little research has been done in this area as of yet, " the authors explain.

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Can AI Help Identify Alcohol Abuse?

I've written before about some interesting applications of big data and AI to predict which patients might progress to substance abuse, with a team from the University of Colorado developing technology to predict potential opioid abuse among patients.

A second project, from Loyola Medicine and Loyola University Chicago, now aims to do a similar thing for alcohol abuse. The work, which was documented in a recently published paper, uses natural language processing to assess each patient's electronic medical records to identify potential alcohol misusers.

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Why Open Data Is Key to Solving Global Challenges

The launch of the Global Risks Report from the World Economic Forum outlined the importance of cooperation when trying to solve problems that are inherently global in nature. The report warned however that the willingness for such cooperation was dwindling as states entered a dog-eat-dog mindset.

A new report from UK academia suggests the key to global problems is not just global cooperation per se, but specifically open data. The report, which was penned by the Open Research Data Task Force, which itself is a group of senior professors from higher education, highlights how open research data significantly increases the likelihood that science will be able to infer patterns and identify solutions in complex problems.

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Should Driverless Car Data Be Open to All?

Driverless cars both generate and rely upon huge quantities of data, and there have been understandable concerns raised about the security of that data, the availability of it for insurance and regulatory concerns, and even ownership of it for the greater societal good. It’s on this latter topic that a recent paper from Dartmouth was published.

Autonomous vehicles are generating huge quantities of data as they attempt to make sense of the world around them. Data on traffic, pedestrian movements, other vehicles, and all manner of environmental features are all consumed and absorbed. There is a temptation for companies to keep a tight grip on this data, but governments, citizens, and other groups have a vested interest, too.

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Using AI to Improve Diagnoses and Prognoses of Diseases

Smarter diagnosis and prognosis of a disease has obvious benefits to patients and healthcare providers alike. A team from Cardiff University believes that artificial intelligence can play a big role in doing just that. In a recently published study, the team describes how AI can help improve risk assessments for patients with cardiovascular disease in an efficient manner that requires neither expertise or human interaction.

"If we can refine these methods, they will allow us to determine much earlier those people who require preventative measures. This will extend people's lives and conserve NHS resources," the researchers explain.

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Making AI Facial Recognition Less Racist

AI has famously been rather poor at recognizing faces in a non-racist way. The size of the challenge was highlighted by recent work from MIT and Stanford University, which found that three commercially available facial-analysis programs displayed considerable biases against both gender and skin-types.

For instance, the programs were nearly always accurate in determining the gender of light-skinned men but had an error rate of over 34 percent when it came to darker-skinned women.