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Artificial intelligence (AI) powers 5G, blockchain, the internet of things, quantum computing and self-driving cars.

Source: The Scientist Magazine

Artificial intelligencedeals with the area of developing computing systems which are capable of performing tasks that humans are very good at, for example recognising objects, recognising and making sense of speech, and decision making in a constrained environment.

Machine Learningis defined as the field of AI that applies statistical methods to enable computer systems to learn from the data towards an end goal. The term was introduced by Arthur Samuel in 1959.

Neural Networksare biologically inspired networks that extract abstract features from the data in a hierarchical fashion.

Deep Learningrefers to the field of Neural Networks with several hidden layers. Such a Neural Network is often referred to as a Deep Neural Network.

I will refer to AI in this article as covering the spectrum of Machine learning and Deep Learning as well as the classical AI techniques such as Logic and Search algorithms.

Source: Qualcomm

5G refers to "5th Generation", and relates to the newest standards in mobile communications. The performance levels for 5G will be focused on ultra low latency, lower energy consumption, large rates of data, and enormous connectivity of devices. The era of 5G, that will spread around much of the world from 2020 onwards (with some limited deployments in 2019), will be world where cloud servers will continue to be used, and also one whereby we witness the rise in prominence of AI on the edge (on device) where the data is generated enabling real-time (or very near real time) responses from intelligent devices. 5G and edge computing with machine to machine communication will be of great importance for autonomous systems with AI such as self-driving cars, drones, autonomous robots, and intelligent sensors within the context of IoT. 5G with AI will also enable the invisible bank and payments that leading Fintech influencers, such as Brett King and Jim Marous, dream about. The significantly faster speeds of 5G over 4G will enable technologies that are suboptimal today such as Virtual Reality (VR) to perform much better. Augmented Reality (AR) and Holographic technologies will emerge across different use cases in this period too. Those companies that are going to thrive (even survive) the resulting digital transformation will be the ones that are already planning and exploring the potential.

As a society we need to be aware of the impending changes across all sectors of the economy. We need to ensure that our political leaders and regulators actually understand the scale of change that will arise and ensure that the regulatory frameworks and infrastructure are optimised to enable the deployment of AI for improving healthcare with personalized medicine, finance with better services for the customer, marketing with enhanced personalization and better service to the customer, plus smarter and more efficient manufacturing.

The graphic above shows an example of computers on board autonomous cars engaging in Machine to Machine communication as the vehicle in red broadcasts to all other vehicles upon discovering the broken down car.

Every single sector of the economy will be transformed by AI and 5G in the next few years. Autonomous vehicles may result in reduced demand for cars and car parking spaces within towns and cities will be freed up for other usage. It maybe that people will not own a car and rather opt to pay a fee for a car pooling or ride share option whereby an autonomous vehicle will pick them up take them to work or shopping and then rather than have the vehicle remain stationary in a car park, the same vehicle will move onto its next customer journey. The interior of the car will use AR with Holographic technologies to provide an immersive and personalised experience using AI to provide targeted and location-based marketing to support local stores and restaurants. Machine to machine communication will be a reality with computers on board vehicles exchanging braking, speed, location and other relevant road data with each other and techniques such as multi-agent Deep Reinforcement Learning may be used to optimise the decision making by the autonomous vehicles.Deep Reinforcement Learning refers to Deep learning and Reinforcement Learning (RL) being combined together. This area of research has potential applications in finance, healthcare, IoT and autonomous systems such as robotics and has shown promise in solving complicated tasks that require decision making and in the past had been considered as too complex for a machine. Multi-agent reinforcement learning seeks to enable agents that interact with each other the ability to learn collaboratively as they adapt to the behaviour of other agents.Furthermore, object detection using Convolutional Neural Networks (CNNs) will also occur on the edge in cameras too (autonomous systems and also security cameras for intruder detection). ACNN is a type of Deep Neural Network that uses convolutions to extract patterns from the input data in a hierarchical manner. Its mainly used in data that has spatial relationships such as images.

The image above shows an example of Machine to Machine communication between autonomous vehicles and devices that may develop in the world in 5G to enable reduced accidents on the road.

The physical retail sector may transition from one whereby costly inventory is held in bulk to an inventory light model using smart mirrors, AR and VR combined with AI to provide personalised recommendations for apparel. In the event that the customer selects an item then an autonomous vehicle may deliver to the store whilst the customer is enjoying a digital experience and refreshments or to their home at a pre-agreed delivery time. Over time healthcare may evolve into a more efficient sector whereby the next generation of drugs will be developed with personalised medicine in mind so that side effects of a given drug are minimised and the benefits of the medication are maximised and data from Electronic Health Records is mined effectively, and medical imaging with explainable AI deployed efficiently across clinics and hospitals so as to improve timely diagnosis of a condition, and thereby reduce misdiagnosis for patients.

Source: Statista

The chart above illustrates the rapid growth in the number of connected devices. Statista estimated that there will be approximately 31 billion IoT connected devices in 2020 and 75 Billion by 2025. As we move into the world of 5G the role of AI will be of fundamental importance to the economy overall and to your day to day life.

In summaryI believe that AI and the other industry 4.0 digital technologies should be developed and encouraged to drive economic growth in ways that are cleaner, more efficient and allow wider participation across society for education, healthcare and better living standards. The issue of warfare and AI is a highly debated and emotive subject, and automation in warfare has been on display since the first Gulf war in the 1990s with fire and forget and cruise missiles. At the very least it is important to consider the need for transparency with robust frameworks to understand what is being done in order to ensure that there is sufficient oversight as a society over those making the decisions. However, in spite of what some in the media would have us believe, the vast majority of the AI community are not working on developing killer robots nor other autonomous weapons. Whilst attending speaking at an event on AI hosted in Davos during the WEF, I happened to meet Viktoriya Tigipko of TA ventures and@JamesPeyerof@Apollo_Venturesand was impressed with the positive outlook and vision that they had for AI in relation to healthcare and the development of next generation treatments that will help humanity. I have also been inspired by the work of the brilliant Dr Anna Becker who started her degree at the age of 16 and her postgraduate studies at 19 before going on to build and run an AI company. AI and in particular Machine Learning and Deep Learning serve at this moment in time (and in the foreseeable future) to solve for the issue of making sense of the deluge of data that we generate from digital platforms rather than to create Skynet with Terminator machines to wipe us out (AGI itself does not exist today nor the medium term future). AI also provides an opportunity to improve living standards and promote cleaner and more efficient industry, agriculture, smarter cities and energy systems as we move into the world of industry 4.0 with the arrival of 5G.

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How Artificial Intelligence Will Impact Your Daily Life in the 2020s - BBN Times

As all agents, brokers, and home buyers know, searching for a home is a deeply personal process, and one of the most difficult challenges for buyers is narrowing down what they want. When a prospective buyer walks through a home or searches for one online, they are making hundreds of value judgments, often without ever consciously realizing them or expressing them to the real estate professional they are working with.

Thankfully, artificial intelligence (AI) can now help bridge that gap and deliver a customized and personalized experience for consumers, without additional work by the agent or broker.

Here are a few exciting ways AI technology is making this possible:

For years, it has been easy to search for homes based on basic criteria like square footage, but what if a client wants something a little more specific, such as hardwood floors in all of the bedrooms, or homes with granite counters and white kitchen cabinets?

Thats where AI comes in. Those kinds of variables, or combinations of them, are not often captured by a listing data feed, but they can be critical to personalizing the customer experience. AI makes it easy to get the right search results quickly for even the most particular clients.

If you watch Netflix or use Amazon, youre already familiar with AI technology that reacts to each individual consumers preferences. On those platforms, what you stop to review, or even the amount of time you spend reviewing, is used to define preferences without ever asking you a specific question. In real estate, AI-powered search platforms are starting to offer buyers similar interactions.

Agents can now encourage consumers to find and upload images of what theyre looking for types of home, the finishes, the features, the layout and have tech tools handle the hard work of searching for similar properties on the market.

Firms like Wayfair, Home Depot, and others are leveraging tools that allow consumers to visualize what a room or a home would look like with different paint colors, with their own furniture or even after a renovation. This allows buyers and sellers to maximize the interest in a transaction by seeing what their home will look like in the future.

Instead of typing something like, New York, three-bedroom apartment, prospects are now able to simply speak into their phone or computer microphone and say something like, I need a three-bedroom apartment with a Central Park view in New York, facing east. And before long, platforms will be able to reply to them verbally. With computer vision technology, that becomes a reality by utilizing plain-English descriptions of what is tagged in images and searching for them.

For sellers, search placement can be improved by using technology that automatically tags home features in listing photos. That means that agents can avoid writing all those tags and detailed image descriptions, but still have their sellers benefit from optimal search engine placement. At a time when the vast majority of home searches start online, thats a big deal.

Put simply, developments like these are increasingly transforming the home search process and making it easy for real estate professionals to deliver an even more highly personalized service for their customers without adding more to their plates.

Red Bell Real Estate, LLC, a homegenius company, is at the forefront of these and other exciting technology developments that will make agents and brokers jobs easier and more lucrative. If youre interested in learning more about how this tech could work for you or your agents, visit homegenius.com.

2021 Radian Group Inc. All Rights Reserved. Red Bell Real Estate, LLC, 7730 South Union Park Avenue, Suite 400, Midvale, UT 84047. Tel: 866-626-2381. Licensed in every State and the District of Columbia. This communication is provided for use by real estate professionals only and is not intended for distribution to consumers or other third parties. This does not constitute an advertisement as defined by Section 1026.2(a)(2) of Regulation Z.

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6 ways artificial intelligence is revolutionizing home search - Inman

Margie and I were shopping at Sams Wholesale Club yesterday when all of a sudden a floor cleaning machine drove right past us.

This doesnt sound at all eventful, however - at second glance - I could see that the floor cleaning vehicle was driverless. There was a seat, controls, and a steering wheel, but there was no human driver.

As I processed this moment, the first thing I thought about was how cool this is. A driverless, automated vehicle that has a cleaning route all mapped out.

It automatically beeps its horn to alert people of its presence. I watched it break timely for human traffic.

Its amazing, game-changing technology. The store confidently operates this equipment during normal operating hours with people walking right near it. We were there right at 10:00 a.m., yesterday during the opening minutes of operation.

A moment later, I thought, wow, this equipment has taken away a good job that used to exist.

Now, its true that businesses all over America are having a hard time filling numerous open job classifications.

I couldnt help but think about the many jobs that have been eliminated over the past recent years because of technology.

A few years ago,a McKinsey reporthighlighted the following statistics:

Regarding workforce displacement, they conclude that as many as 800 million global jobs and 475 million employees could be disrupted by automation before 2030.

Here are some of the most recent jobs lost due to technology:

Here are six jobs that may disappear by 2030:

Here are five jobs that wont be eliminated by 2030:

In summary, technology is amazing and wonderful. Yet, on the other hand, good jobs that have existed for generations are being eliminated. People will have to become more nimble and adaptable than ever before and be prepared to potentially have to make a career change as the marketplace continues to evolve.

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Artificial Intelligence Is Taking Over Jobs That Humans Did For Years - wpgtalkradio.com

Art history is important to reflect and help to create a cultures vision of itself. Studying the art of the past teaches everyone how people have seen themselves and their world, and how they want to show this to others. Artificial Intelligence in art was not initially applied as a creator but as an impersonator. The technique is called style transfer and it uses deep neural networks to replicate, recreate and blend styles of artwork, by teaching Artificial Intelligence or AI to understand existing pieces of art.

Art history provides a means by which people can get in-depth knowledge about the human past and its relationship to the present because the act of making art is one of humanitys most ubiquitous activities.

When Artificial Intelligence in art gets attention for recovering lost works of art, it makes the AI technology sound less scary than when it garners headlines for creating deep fakes that falsify politicians speech or for using facial recognition for authoritarian surveillance.

According to reports, many scientists are conducting constant studies of art history with the help of artificial intelligence but rather than lionizing these studies as heroic achievements, those responsible for conveying their results to the public should see them as opportunities to question what the computational sciences are doing when they appropriate the study of art. And they should ask whether any of this is for the good of anyone or anything but AI, its most zealous proponents, and those who profit from it.

AI and art have great potential together and many new artists perspectives can be explored with the help of Artificial Intelligence like earlier this autumn, several media houses reported that a Swiss company using artificial intelligence (AI) to assess the authenticity of artworks had calculated a 91.78% probability that Samson and Delilah were not painted by Rubens. The same company also wrote a report on another painting in the National Gallery A View of Het Steen in the Early Morning (c. 1636) which stated a 98.76% probability that Rubens painted the work.

So, there are always two sides to coins, and the same goes with AI technology. It can be used to hijack art history or one can utilize artificial intelligence to assess the authenticity of artworks.

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Analytics Insight is an influential platform dedicated to insights, trends, and opinions from the world of data-driven technologies. It monitors developments, recognition, and achievements made by Artificial Intelligence, Big Data and Analytics companies across the globe.

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Can Artificial Intelligence Hijack Art History of The World? - Analytics Insight

Scientists develop a software that can be used in combination with MRI data for research and diagnosis

Viewing behavior provides a window into many central aspects of human cognition and health, and it is an important variable in many functional magnetic resonance imaging (fMRI) studies. Researchers from the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig and the Kavli Institute for Systems Neuroscience in Trondheim have now developed software that uses artificial intelligence to directly predict eye position and eye movements from MRI images. The method opens up rapid and cost-effective research and diagnostic possibilities, for example, in neurological diseases that often manifest as changes in eye-movement patterns, writes the Max Planck Institute in a press release.

To record eye movements, research institutions typically use a so-called eye tracker a sensor technology in which infrared light is projected onto the retina, reflected, and eventually measured. Because an MRI has a very strong magnetic field, you need special MRI-compatible equipment, which is often not feasible for clinics and small laboratories, says study author Matthias Nau, who developed the new alternative together with Markus Frey and Christian Doeller. The high cost of these cameras and the experimental effort involved in their use have so far prevented the widespread use of eye tracking in MRI examinations. That could now change. The scientists from Leipzig and Trondheim developed the easy-to-use software DeepMReye and provide it for free.

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With it, it is now possible to track participants viewing behavior even without a camera during an MRI scan. The neural network we use detects specific patterns in the MRI signal from the eyes. This allows us to predict where the person is looking. Artificial intelligence helps a lot here, because we often dont know exactly which patterns to look for as scientists, Markus Frey explains. He and his colleagues have trained the neural network with their own and publicly available data from study participants in such a way that it can now perform eye tracking in data the software has not been trained on. This opens up many possibilities. For example, it is now possible to study the gaze behaviour of participants and patients in existing MRI data, which were originally acquired without eye tracking. In this way, scientists could use older studies and data sets to answer entirely new questions.

The software can also predict when eyes are open or closed. Moreover, it can track eye movements even when the eyes remain closed. This may allow to perform eye tracking even when study participants are asleep. I can imagine that the software will also be used in the clinical field, for example, in the sleep lab to study eye movements in different sleep stages, says Matthias Nau. In addition, for blind patients, the traditional eye-tracking cameras have rarely been used because an accurate calibration was very cumbersome. Here too, studies can be carried out more easily with DeepMReye, as the artificial intelligence can be calibrated with the help of healthy subjects and then be applied in examinations of blind patients. The software could thus enable a variety of applications in research and clinical settings, perhaps even leading to eye tracking finally becoming a standard in MRI studies and everyday clinical practice.

Also interesting: Artificial intelligence in healthcare? Dont focus solely on technology

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Predicting eye movements with Artificial Intelligence - Innovation Origins