A Minister for Artificial Intelligence

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The United Arab Emirates (UAE) is the first nation with a government minister dedicated to AI. As tech companies begin to center their business models around AI, the UAE want to be at the forefront of this development. Dubai, for example, plans to put robot cops on the streets by 2030 and they’ve been pushing to get autonomous vehicles on the city’s roads and in its skies. https://futurism.com/dubai-just-appointed-a-state-minister-for-artificial-intelligence/

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The Intelligence Revolution has started!

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The world in undergoing a new revolution and it’s not just the 4th Industrial Revolution. It’s impacting on virtually every aspect of our business and personal lives. We can call it the Intelligence Revolution because it’s based on AI (artificial intelligence). The Industrial Revolution enabled us to build powerful machines that could do things for us. The Intelligence Revolution is enabling us to create machines that are making decisions for us with AI- a whole new step forward in technology. Try this link to see how your job will be affected. http://mobile.abc.net.au/news/2017-08-08/could-a-robot-do-your-job-artificial-intelligence/8782174?pfmredir=sm

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Music designed to help you focus, relax or sleep

Brain.fm is one of several companies using artificial intelligence to help you hone into a productive state of work, a. state of relaxation or a deep sleep,. While most music is designed to sound good, Brain.fm works with teams of scientists and engineers generating music that helps you achieve your desired state of mind. Human composers write and record the core sound tracks, and an AI engine mixes, matches, and remasters them into longer tracks. www.Brain.fm

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Finding koalas with heat seeking drones

Heat from animals can be identified using high tech sensors in cameras flown in drones. Artificial intelligence algorithms are used to analyse the thermal imagery to determine what’s seen and can identify koalas. Field tests after the heat-sensing camera work showed it was 100 per cent accurate. https://www.smh.com.au/environment/conservation/heat-seeking-drones-find-brisbane-s-hiding-koalas-20181003-p507km.html

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The world’s first digital super model

Shudu has been called the “world’s first digital supermodel.” Experts think she may be the beginning of a new wave of digital models. She arrives at a time in which Instagram, Snapchat filters and photo-editing apps that rely on artificial intelligence have blurred the lines between reality and fantasy, Some believe we might see a hybrid system in future in which models and celebrities license out their digital avatar, allowing them to book multiple appearances simultaneously. A model might appear at a New York fashion shoot in person, but their digital avatar would be in China promoting a movie using the local dialect. https://www.washingtonpost.com/technology/2018/08/08/soon-most-beautiful-people-world-may-no-longer-be-human/?

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A breakthrough in detecting early stage stomach cancer

Two Japanese national research institutes have succeeded in using artificial intelligence to identify early stage stomach cancer with a high accuracy rate. The breakthrough should help extend the lives of patients in Japan in particular, where stomach cancer is one of the leading causes of death. Stomach cancer causes few symptoms and is often found only after it reaches an advanced stage. At an early stage, even specialists have a difficult time distinguishing the cancer from inflammation. https://www.japantimes.co.jp/news/2018/07/22/national/science-health/japanese-researchers-use-ai-identify-early-stage-stomach-cancer-high-accuracy/#.W1Vk-aR_XDs

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Identifying the embryo with the best chance of life

“Ivy” is the artificial intelligence being developed by Sydney-based healthcare start-up Harrison-AI, and IVFAustralia (part of listed player Virtus Health), and allows embryologists to identify the embryo with the best chance of achieving a successful pregnancy as quickly as possible. https://www.afr.com/business/health/virtus-health-says-artificial-intelligence-has-potential-to-make-ivf-babies-20180627-h11xpl

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An AI system at the board table

The first live, public debate between an artificial intelligence system and two human debaters has happened. Using language and reasoning to debate is far more complicated than playing a game and the AI system matched the humans. Once AI is capable of persuasive arguments, it can be applied as a tool to aid human decision-making. One example of this might be boardroom decisions, where there are conflicting points of view. The AI system could, without emotion, listen to the conversation, take all of the evidence and arguments into account and challenge the reasoning of humans where necessary. The machine wouldn’t make the decision but would contribute to the discussion and act as another voice at the table. www.theguardian.com/technology/2018/jun/18/artificial-intelligence-ibm-debate-project-debater

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A robot fish that could revolutionise how we view the ocean

A team from MIT’s Computer Science and Artificial Intelligence Laboratory has developed a soft robotic fish that can independently swim alongside real fish in the ocean and take high-resolution photos and videos. It’s the first robotic fish that can swim untethered in three dimensions for extended periods of time. A robot like this can help explore a reef more closely than current robots. It has the potential to be a new type of tool for ocean exploration and to open up new avenues for uncovering the mysteries of marine life.” http://news.mit.edu/2018/soft-robotic-fish-swims-alongside-real-ones-coral-reefs-0321

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Deep learning techniques

If you have been wondering how there is always so much to do yet so little time, time has come when you can finally put a halt to that thought as artificial intelligence has just the things you need. In fact, with artificial intelligence and cognitive computing you can get things done with greater efficiency and much lesser effort than you thought was possible. Deep learning, which is one of the technologically superior methods behind the formulation of Artificial Intelligence, traces the evolution path of human intelligence design to develop machines that can perform tasks on their own and without human supervision helping in automation. It is very interesting to note how deep learning has altered the way we operate in various aspects of daily activities and necessity areas. Let us take into consideration 10 practical use cases of Deep Learning Techniques that have been witnessed in the last few years. ONE: Facial Recognition using visual intelligence of machines It is astounding how security cameras have grown over the years. Today, machine learned security cameras used at airports or secured parking lots use their analytical ‘mind’ to not only record a particular intrusion but also review and analyze the scene. Objective: To identify, detect and track persons of interest, parked vehicles, missing luggage and many more using CCTVs or other high-end cameras. Deep Learning Technique:  A VPU or a Vision Processing Unit, is a much advanced deep learning product that takes over the conventional CPU or GPU. A lot of processing and machine learning is conducted on the device which helps it to analyze a particular scene. It uses Convolutional Deep Learning Models to detect and track objects and individuals. Inference: Most of the airports are now able to use the deep learning techniques to identify and track persons of interest (e.g. terror suspects, etc.), track your luggage and detect any suspicious item very quickly. These VPU-enabled security cameras installed at airports, generate alerts the moment they find someone leaving their luggage, thus making it possible to detect airport security threats within minutes. Installed in traffic scenarios, they can also recognize driver-less cars and help them find the right parking spots.  TWO: Understanding customer behaviour in ecommerce Deep learning is being used to develop techniques to get clearer ideas about customer wants and expectations in the ecommerce industry. Let us see how. Objective : To understand customer behaviour and their propensity to purchase a particular product. Deep Learning technique: Recurrent Neural Networks (RNN) has a potential for higher accuracy than any other machine learning technique. An RNN network is generally made up of computational cells which are fed with consumer histories. These cells are provided with a given-time step, which helps the program to understand the consumer’s step-wise behaviour when he/she is viewing a particular product on a site. For example, an RNN cell will note when the consumer clicks on an ad, is directed to a site, views a product and adds it to the shopping cart. These RNNs are often long-time memory cells and they remember and relate customer behaviour across a line of products. Inference: E-commerce sites, such as ebay and Amazon, are greatly benefited through Deep Learning.  The entire session journey of consumers are noted. The longer and dynamic an event is, the greater is the propensity of people to click on the ‘buy now’ button. Once a particular consumer behaviour is noted in case of a range of products, the site is optimized to ensure that the next time a similar consumer visits, they get a more engaging experience so as to convert into a purchase within the shortest time.  THREE: Having a private tech self-support With the introduction of computers, there were recurring talks about how machines would replace humans one day. It is now possible to minimise human-labour and improve efficiency with machine learning. Objective: To improve work efficiency of an organization by installing machine-learned support staff unit, instead of hiring manual labour. Deep Learning technique : Algorithmic Scheduling Agents are built using a blend of deep learning algorithms that ensure distribution of labour so that a number of tasks are performed within the shortest possible time and at minimum costs. Agents like cyborg systems are developing using the technique. Inference: For calendar coordination and scheduling, we have Clara and to gather staff report and consolidate meeting information we have Howdy. Google Now is the preferred program for keeping on schedule through proactive alerts, and for follow-ups after meetings, GridSpace Sift is a brilliant manager. FOUR: Transforming industrial sector through Internet of Things Data Industrial Internet of Things (IIoT) refers to the interlinking of physical devices, buildings, vehicles and other items through electronic, sensors and software so that the data is collected and exchanged. Objective : To initiate preventive maintenance of machine units through machine learned sensors, in order to improve longevity and improve performance. Deep Learning technique: Sensor data analysis. By using machine-learned sensors and IIoT, accurate maintenance time predictions are made. Timely maintenance of machines is very important to ensure that work for a long period of time. Initially manufacturers would mostly rely on guesswork to time the maintenance interval of machines. IIoT is combined with predictive analysis gives the perfect maintenance times. Machine learning of prior downtime incidents also play a great role. Inference: In several countries, chemical manufacturing units and aircrafts units are installing machine learned sensors to get complete idea of new challenges and insights. This has helped in reducing pitfalls and machine breakdown, thus considerably reducing costs and maintaining a healthy and hygienic environment in manufacturing units. FIVE: Convolutional neural networks finding minerals Multi-special satellite images have helped found mineral resources in several countries like Australia. Geologists have been able to use the mineral indexes integrated with the algorithms to find traces of minerals (even gold) deep inside the earth’s crust. Objective: Detecting mineral deposits using multi-special satellite images have helped found mineral resources. Deep Learning technique: Transfer learning is a great way for convolutional neural networks to carry out this function. These networks are pre-trained and fed with data over minerals and geographical location accuracy, before they are operated. Converting information into geospatial data is the challenge that has to be undertaken. Inference: Geologists in Austria, are currently using the procedure to locate minerals in relatively unexplored areas of the land. SIX: Deep learning facilitating automatic grading of eye diseases GPU-based medical research machines are now using deep learning methods for medical break-throughs. […]

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First human-free bank branch

The China Construction Bank, China’s second-largest bank, has opened a branch in Shanghai run entirely by technology. A humanoid robot answers customers’ questions and directs traffic, and human client relationship managers remotely interact with customers via videoconference. Customers can pay to engage in small interactive augmented reality games to make the experience more of an occasion rather than just a branch visit. A virtual reality machine is also available to showcase CCB’s latest home rental offerings. This virtual reality, artificial intelligence and facial recognition technology is expected to support 90 percent of customer demand. https://m-scmp-com.cdn.ampproject.org/v/m.scmp.com/business/companies/article/2141203/meet-new-face-branch-banking?

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Fighting Tech Innovation’s Dark Side

Since we live in a machine age, the growing concern is that new technologies like artificial intelligence, cryptocurrencies, autonomous cars, and precision medicine are so powerful, pervasive and evolving that they can become uncontrollable. So how do we overcome it? New technologies can be potentially scary and bad. It’s a step into the unknown with uncertainty whether it may fail and it takes to integrate into society. Since we live in a machine age, the growing concern is that new technologies like artificial intelligence, cryptocurrencies, autonomous cars, and genetically customised ‘precision medicine’ are so powerful, pervasive, and fast-changing that they become uncontrollable. All this can put society and quite possibly the entire human race in grave danger. For instance, July 2017 saw Facebook abandon an experiment after two artificially intelligent programs appeared to be chatting to each other in a strange language that only they understood. The two chatbots communicated with one another having created their own changes to English which seemed to make it easier for them to work, but it was mysterious to the supervising human engineers. The chatbots’ bizarre discussions happened as Facebook challenged them to try and negotiate a trade with one another in attempt to swap items like hats and balls that were all given a certain value. But negotiations quickly broke down as the robots appeared to oddly chant to each other in a pattern of incomprehensible English that didn’t seem to be a glitch. Were the robots becoming uncontrollably too intelligent for their own good? Even more recently, Amazon’s voice assistant device, Alexa, let out unprompted creepy cackles. The device is designed to respond or act only when prompted by with a wake word that’s “Alexa” or “Amazon”, but this apparent glitch is happening without any prior interaction, spooking Alexa owners. Alexa is intended to be a domestic device in the home, so the use of voice assistants is often met with caution — voice commands are recorded and sent to the cloud for processing, a system that stokes a fear of eavesdropping, unintended or otherwise. Incidents like this and at Facebook, where an AI assistant seems to rebel against its owner, naturally furthers such concern. Upon that note, tech pioneer Elon Musk, CEO of Tesla, has  said, “AI is a fundamental risk to the existence of human civilisation.” He has also said, in relation to a self driving car ,“You’d test the living daylights out of it before you let it on the streets.” To counteract that and to control the different levels of future technological uncertainty before going to market, would be to apply regulations to the technology sector. After all, within any industry, regulation is necessary to keep things in check — it should not be too restrictive, but obviously progressive. However, there is a lack of government involvement within technological innovation because government ministers don’t understand it and they don’t know what to do about it. This is starting to change on an international scale with the World Economic Forum which is tackling the dangers of big tech. Within the UK, there are such organisations like Nesta, an innovation charity which works globally and always in partnership, as they do with Manchester University on the Manchester Institute of Innovation Research (MIoIR). They address the strategic intelligence, governance, and responsible research and innovation aspects of new and emerging technologies. Organisations supporting innovative entrepreneurs are London Innovators who help radical London-based entrepreneurs and GSMA supporting initiatives that shape the future of mobile communications and expand opportunities for the whole industry. There’s also N77 Society, whose recruited field experts as members assess advancing technological projects’  benefits or dangers to society. They all add a strong filter to adjust and cancel out technology’s bad with good. All organisations and societies in the the technology field can help develop an ‘innovation culture’ for larger regulatory bodies i.e. government to certainly promote the positive impact of innovations. It can inform and teach public officials who regulate technologies, business people who build them, and citizens who use or are affected by them — to craft inclusive policies that governments or companies can try out. Overall, technological innovation is necessary. We as humans constantly progress together as a society, country and a world. Throughout time, technology has enhanced our daily lives and we all take it for granted in all areas. Whether it be communication with the Internet and smartphones; travel with planes and motor vehicles or entertainment with televisions and music formats, it’s all there right before us. The attraction towards more advanced technological innovation is a belief in progress towards an improved or more advanced condition — a brighter future as we all move forward. Francesco Segramora 16 March 2018

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