Consumer AI "Consumer Artificial Intelligence (AI)" refers to products and systems that utilize artificially intelligent machines and software that is readily available for purchase by the public. This category of AI is implemented into a number of subgroups that each interact with the user/consumer to fulfill a consumer need. Background AI research was founded on the idea that human intelligence could be studied, fully comprehended, and thus, simulated by machines. Since the field gained traction, it has faced a number of ethical and philosophical questions. That said, it is an ever-growing industry that manifests itself in everyday life. One of the ways that AI is used by consumers is through their electronic devices. Such devices tend to interact with a user by a "call and response" method, that involves the user telling or asking an AI agent something and the system responding to the user. Chatbots Computer programs used to simulate a human dialogue partner. One can interact with them via text. Some usages include customer service, info gathering (Search for user keywords and make choice) chat rooms. Chatbots often use complex natural language processors to thoroughly and accurately listen for and respond to user input. Some simpler designs use a database to scan for user input (words) and automatically select the best response given the input received. Help Bots: In terms of customer services chatbots, there are chatboxes that may appear as you are browsing a web page. You may have realized that there would be a prompt asking if you would like any help or if you had any questions. If you typed into the chatbox, an automated system will reply to you depending on whether the keywords you typed in matches any of their pre-programmed responses. Cleverbot: An AI developed by Rollo Carpenter to chat with people on the internet about anything. As with any AI’s that require personal interaction, this chat AI learns from what others say to it. Sometimes conversations will make sense and it’ll feel like you’re speaking to an actual human, but then there are times when Cleverbot says something completely random. "Intelligent Personal Assistants" (IPA) Another use of voice-aided AI comes in the form of "intelligent personal assistants (IPA)". In other words, systems that work with other applications and programs to execute user requests. Nowadays, one can easily have access to a virtual personal assistant whether it is through their mobile devices, tablets, or laptops. These personal assistants can perform many tasks such as tell the weather, jokes, and news, per a user's request. Siri (Speech Interpretation and Recognition Interface) : Apple's iOS IPA that pulls from a natural language database to complete requests made by users. Utilized on Apple devices (i.e. Mac, iPhone, iPad). Offers one a more convenient way to have hands-free interaction with your Apple devices. Over time, it becomes quicker and more personalized based on patterns and habits of the user. It also learns to recognize the voice patterns of the user better through consistent use. Can be activated with "Hey Siri." Siri also has access to the built-in Apple apps on your device such as Maps and Mail. If requested, these apps can be opened by Siri and the features utilized. Google Now/Google Assistant: (Google Assistant is an upgrade and extension of Google Now). Google-developed IPA that can be used by Apple's iOS or any Android device and made available through the Google Search application. Like Siri, Google Now utilizes a natural language database and is also predictive given users habits. Can be activated with "OK Google" and "Hey Google." Microsoft Cortana: Similar to Siri and Google Assistant, Cortana is Microsoft's version of an intelligent personal assistant. Cortana can be found on Windows devices such as a Windows 10 PC. Can be activated with "Hey Cortana" or brought up through the search button in the taskbar. There is also an integration with Microsoft Edge, Microsoft's web browser, where Cortana goes with it. You can type in a question and Cortana will give you a response back. Concerns over Chatbots for Recreational Use Chatbots have a number of implementations that are often used to gather information from users, however, there has been a growing concern over chatbots that are found in recreational settings, such as toys. Concern over what data is being collected and where the data is going lingers around chatbot usage. In addition to that, with most IPA's, the devices are always actively listening in order to see if you'd say the command to open them up so that brings up a privacy concern because it's always listening to what you say. Home Automated systems are nothing new but recently there has been a lot product development of such systems. Each Home A.I. system is unique in its functionality and design but the most common characteristic that defines a Home Automated System is the function to link all your electronics and systems in your home through a single interface and control them remotely or automatically. Most of these systems are voice-controlled and come equipped with an A.I. similar to iPhone’s personal assistant Siri, or Google’s Google Assistant. Devices & Benefits/Features There are many competing products in this market but one of the most talked about is Amazon’s Echo. Amazon Echo (Alexa): Echo is a cylindrical shaped device that has a voice-controlled interface, and has much of the same functionality as a smartphone virtual assistant. Can be activated with the word "Alexa." She is always actively listening for the wake word, however there is an option for you to mute the microphone for privacy. It can do many things that a personal assistant can do: like answer questions tell you the weather, or play music. But it can also be used to communicate with third party hardware, allowing you to control electronics like your light switches and thermostats. Some devices even come equipped with security features. Similar to the IPA's, Alexa can learn to recognize your voice patterns. There is a "Skills" store that Alexa can "learn." Afterwards, you are able to use the skill with whatever command that is programmed with it. There are many categories within the Skills like Music, Travel, and Food. Branto: A spherical home assistant can show you a 360 view of its surroundings, which you can view remotely. Its software will also alert you when it detects suspicious movements while you're away. EmoSPARK: More focused on the artificial intelligence aspect. EmoSPARK uses facial recognition to sense your emotions. So if it detects that you’re sad it will try to cheer you up by telling you jokes or playing cheerful music. When you don’t want EmoSPARK to respond to your voice, you can always put it in privacy mode which is a feature that is not available in the other Home A.I. systems Google Home: A Chromecast enabled-speaker. Can be used with Google Assistant. Pairs with third party apps and devices like Philips Hue light bulbs to turn on your lights if desired. Very similar features with Amazon Echo. Convenient with Android devices and gear. Advantages An advantage of a Home A.I. assistant is its ease of access. It is very convenient as it can control the lighting within your house or thermostat with just a simple command. Security cameras can also be activated with just one command. Because Home A.I. assistants are voice-controlled, they are simple to use for people of all ages and groups. Furthermore, it gives you the feeling of having an actual personal assistant where you can easily get access to information regarding either your personal life or what is happening around the world. Disadvantages One of the disadvantages with all of these Home A.I. assistants is its lack of portability. You can’t carry it around like a smartphone, it is only meant for the home and can only be accessed from one room. There are also some serious issues that comes with owning a Digital Home assistant. Some owners for example have expressed concerns that their privacy is being violated. One couple, for example, were baffled when Echo unexpectedly responded with “That’s not very nice to say” when Echo heard them arguing. This couple also were shown an advertisement for diapers a few days after they were discussing about babies. Additionally, Home AI consoles like Amazon Echo were reported to have security vulnerabilities. It would be unlikely but very possible that someone could hack into your system through man-in-the-middle or other means. Once they have access to your system they could potentially unlock your automated door or eavesdrop on your conversations. Ethical Implications Although a lot of these Home Automated Systems offer a lot of great services that can improve your quality of life, it seems you have to sacrifice privacy for ease of living. When purchasing one of these devices a consumer has to decide whether they are willing to allow possible violation of privacy for convenience. Modern Integration Though it may not seem like it, much of the Artificial Intelligence we know today have been integrated through video games. AI have been integrated into games to help players navigate through an alternate reality that have simulated real-life situations. Through this, many game developers have used specialized game monitoring software to track a player’s action, thoughts, and predictions through the game engine’s telemetry. This has caused a variety of moral and ethical concerns, as it is an invasion of ones' privacy. Interaction Analysis An example of this in research would be Crowdsourcing Human-Robot Interaction. The research on human-robot interaction was over whether it was possible to use online games as a means of generating large-scale information. By developing a small game of task-management without any strict assignment of social roles between a human user and a robot, the researchers were able to encapsulate the decisions of 82,479 actions and analyze how humans would react to different situations. Ethical Implications The other equally difficult ethical concerns that this raises are the moral obligations of society toward its robotic counterpart which include the right to life and liberty, freedom of thought and expression and equality before the law. The other ethical concern would be the overall transparency over creating these agents; AI developers are representatives of future humanity and thus have an ethical obligation to be transparent in their efforts. Games have been around since the beginning of mankind, but electronic games are relatively new, historically speaking. In the 20th century we saw the rise of Artificial Intelligence which has been used in many different facets of society from food production, to medicine, to entertainment. DeepBlue One such entertainment use is in playing against humans. IBM was working on a machine named Deep Thought (later renamed Deep Blue) that could calculate chess moves in advance, and could compete against human chess players. To show off its skill, IBM challenged a world champion chess player, Garry Kasparov, to a chess match. The first game it won was in 1996, where Deep Blue won the first match,but lost with a score of 2-4. IBM would make upgrades to their machine, and in 1997, hold a rematch against Kasparov. This time, Deep Blue won the match by making what Kasparov referred to as a deeply intelligent move. This left Kasparov angry at the end, accusing IBM of cheating. IBM denied this accusation. Kasparov then asked for a rematch. IBM denied him this request, and simultaneously shutdown and dismantled Deep Blue. It revealed 15 years later that, the completely unexpected move by Deep Blue back in 1997 was actually a bug in the programming. Deep Blue was unsure of what to do as a first move, so it randomly made a play – which happened to be a good one that threw Kasparov off his game. AlphaGo AlphaGo began as a research project around 2014 to test a form of machine learning called deep learning on the game called Go. While working on this project, programmers decided to test their AI against 2-dan Go player Fan Hui, and beat him in 2015. This marked the first time that a machine has beaten a professional player, unhandicapped at Go. The game of Go is considered a difficult game for machines to win at, because it involves a very large number of possible moves that a machine has trouble deciding what its next move should be. A year later in 2016, AlphaGo beat 9-dan professional player Lee Sedol. AlphaZero AlphaZero, a repurposed version of AlphaGo, can play games like shigo and chess. Because of machine learning, it doesn't require any human input or knowledge in order to play a game like chess. All it needs are the rules of the game and it is good to go. AlphaZero took just four hours to learn the entirety of chess and beat the world's best chess-playing program. The separating difference with AlphaZero and other competitive AI's is that it doesn't need any prior knowledge with its machine learning. It learns from its mistakes as it plays. Ethical Implications While the advancement of AI to a level where it can beat humanity’s greatest champions may be hailed as a great testament to our technological prowess, we need to consider what implications (if any) this means for the future. One of the biggest questions about AI, is what if they act outside their parameters? What if they make decisions that we didn’t intend? In the case of DeepBlue, the machine was created to win at chess by following an expansive algorithm. What ended up happening was DeepBlue winning at chess by not following the algorithm. This bug caused debate about the legitimacy of the win. What if this machine had a more dangerous task, such as target shooting with a gun, and a bug decided that the “closest” target is a stack of unused targets directly behind it, between the robot and a crowd of people. This calls into questions several issues, but one of which is whether or not t’s acceptable to make an AI capable of out-performing a human at the expense of safety or regulation. Cars are also in the field of AI Consumer technologies. One of the most prominent fields of development on autonomous technologies is the automobilistic. The idea of self-driving cars is one of the most common amongst human beings when talked about how the future should be. As the idea completely changes the concept of how transportation will be developed, new companies have emerged to compete with the classic players that have been in the industry since the beginning. In most of the cases, these new companies are not in possession of the car itself but rather have created the technology behind them to make them autonomous. Some of these companies pushing towards self-driven cars are Waymo, Tesla, Uber or Aptiv. It is important to notice that there are different levels depending on how important is the figure of the driver and how much he/she is required to control the car. Level 0: No self-driving features. Level 1: Cars may have one or more systems that can control speed or steering. Level 2: Cars that can control steering and speed simultaneously, without driver interaction for short periods of time. Level 3: Cars can control a car in all situations and the car is constantly monitoring the road but in case of a failure will require the driver to take control of the car. Level 4: No driver interaction is needed and the car will stop itself if the systems fail. From this level and above, things like steering wheel or brakes for a driver are not needed but can be included in the car. Level 5: These cars are not supposed to be driven by people in any circumstances. They can monitor every aspect of the road and condition such as roads with no clear lines for example. Autonomous vehicles can change the way we communicate through transport taking it to a whole new level. Now that the figure of the driver disappears, the number of possibilities on what to do in your driving routines multiply. One of these possibilities can be the ability to attend calls, work on your projects or simply admiring the views of a ten-hour journey with no necessity of being concentrated on the road. Another important aspect will be that everyone will be able to use a car since the figure of the diver disappears.It will also create a safer atmosphere for the driving community. People often cannot communicate properly or let their emotions get the best of them which can lead to issues on the road. Since cars are controlled by software, driving becomes safer and more efficient since randomness is removed. This is the basic idea to create networks of cars. All the cars in the road are interconnected between them, which makes everyone aware of what movements are going to be made which should make the cars on a road act like an accordion synchronize between them. As a consequence, traffic jams will disappear or at least be reduced to a higher amount which results also in a positive impact for the environment. The main problem with autonomous cars is the security of their passengers. Any small failure in the system could result in the death of people and that reason make the development of the algorithms critic since life is in danger. Security also becomes one of the key aspects of autonomous cars because if an attacker is able to get access to someone’s car could control the car the way he wants being able to kill the passenger if needed. There is also a technological barrier in the case of the car networks we talked about since they need practically no delay because of our initial problem. A small fraction of a second in taking the decision could result in tragedy. It is believed that with the introduction of 5G and its own specification, it would be possible to develop this kind of networks. IT is important to notice that autonomous cars bring a problem of transitioning due to having to change everyone in the world or even a country to fully adopt the autonomous car to have a perfect and unison network. When they are fully established, people will become more dependent of machines which will lead to many people to loss driving jobs like taxis, and truck drivers. Privacy concerns are also a problem with this evolution since now car manufacturers will be able to know where we are moving at all times. Autonomous cars also bring one big ethical and law-related problem. Imagine the situation in which someone crosses the street when it is not permitted and a car is approaching the position. What should the car do? Should it keep the same route and kill the person crossing, or should it crash itself killing the person inside the car? In both cases, who is responsible for the death of that individual or group of individuals? These are some of the questions that need to be addressed regarding autonomous vehicles and AI technology in general because it brings great possibilities for everyone to improve life quality, but also big questions that could not happen due to the non-existence of technology similar to this. Technology is spreading at a rapid pace and so is its outreach. With every day that passes, the more people that gain access to computers or computer-like devices. This spread and access to technology poses a risk and many threats to individuals and companies alike. These risks come in the form of malicious content such as viruses and malware. To combat these threats, anti-viruses have been produced to protect the users of the technology we hold today. Standard Antivirus Methods Many antiviruses today use several strategies in order to mitigate the risks of attacks and malware that can affect a computer system such as: Signature-based detection: Files, programs, and applications (especially .EXE files) are checked against a known list of malware. Heuristic-based detection: A commonly used method that utilizes signature-based detection as it can try to detect similar variants of known malware or new malware similar to known viruses. Behavioral-based detection: This method is used more to detect malware based on the characteristics and behavior of malware during its execution. It can detect if the program performs malicious actions but only during execution. Sandbox detection: This method works almost the same way as the behavioral-based detection but is different as it runs the suspected program in a separate virtual environment where it can be safely tracked. The Purpose of AI Antivirus The methods above have been somewhat effective for the past several decades but as the technology age grows and grows, it may not be enough to mitigate new threats that we see everyday. This marks the beginning of a new generation of anti-virus methods which integrates AI and machine learning in order to try to effectively reduce the damage of zero-day attacks and new viruses as well as variants of other types of malware. AI’s role in this market is to identify new threats and patterns on its own and be able to add that information to existing databases. This would decrease the time it would take to identify risks massively. Companies like Microsoft are getting into AI in antiviruses because as they said “Microsoft sees artificial intelligence as the next solution for security as attacks get more sophisticated. ‘If we're going to stay on top of anything that is changing that fast, you have to automate,’ Lefferts said. About 96 percent of detected cyberattacks are brand new, he noted.” AI is here to decrease the human intervention in antiviruses and automate as antiviruses would then be able to identify threats by themselves. Lots of time will be saved and mostly like a lot of damage could be reduced. This all stems to the fact that the AI themselves are faster and more efficient that humans are in this area of expertise and many humans cannot keep up against them. AI Antivirus Methods There are several methods of AI antivirus detection that are being utilized right now or are being considered. Many of these methods go beyond the nature and complexity of current antiviruses. They are: Heuristic Technology: This technology is very similar to the heuristic methods of standard antiviruses as it detects unknown viruses using previous learned instruction sequences or sets of previously known malware to new variants or new viruses altogether. Data mining techniques: This technique tries to utilize the act of data mining, or the examination of big data to generate new information to learn if a program is malicious or not. Data mining is supposedly be able to detect double the amount of new malicious executables. Agent Technology: This methodology is hoping to have computers automatically and efficiently respond to new viruses before they are able to spread rapidly and do major damage without any holdback. Effectively, the agent technology is a collection of “agents”, which can be anything from small forms of artificial life to simple computer programs. The whole system is similar to an immune system as the agents function like antibodies. The agents perform simple tasks individually and together can perform intelligent and complex tasks. Such tasks include copying/moving files, opening files, and executing files. Once a irregulrity is detected on a system by an agent, because they do simple tasks to find them, different agents come to capture samples, then more agents approach to remove the virus, and more agents come to report the incident and compile those reports. Artificial Immune Technology: This technology is very similar to agent technology and uses many of the same concepts such as the immune system of a human and agents. It is mainly based on biological strategies made by our immune system. The major difference is that this system is more complex and acts more like the biological immune system. It is able to evolutionary improve itself. Artificial Neural Networks: This methodology uses the concept of neural networks of humans and animals and how we think. It is a popular concept as it allows for associate memory and real-time calculations to detect malicious code in real-time. It uses a large-scale parallel and distributed processing and storage that is self-organized by the system, adapts, and has self-learning technology. These methods of antivirus AI are implemented or considered in order combat the rising increase of new viruses everyday. AI Antivirus Ethical Issues The ethical issues involved in this are similar to ethical issues of AI in other markets and areas. As human interaction and intervention decreases, how do we decide how the AI should proceed according to our standards? AIs will make the decisions in terms of the security of our technology and devices and this is an issue as they have a lot of power because of those decisions. A decrease of human intervention and interaction and increased automation in our technology will result in increased AI authority. There is a great many people in our world today with access to phones or computers that have access to the Internet. Every person who holds any piece of technology is subject to malicious code and malware. Every piece of tech is vulnerable in some way and that means that it can be attacked with malicious intent. This is what many people hope AI will help with. But this also puts a lot of responsibility on the shoulders of the AI as well. Artificial Intelligence (AI), where computers perform undertakings that are typically expected to require human intelligence, is as of now being discussed in almost every area of science and engineering. AI has been around us for decades, and the increasing adoption of artificial in healthcare solves a variety of problems for the patients, hospital and the industry overall. Major scientific competitions like ImageNet Large Scale Visual Recognition Challenges are giving proof that computers can accomplish human-like competence in image recognition. AI has likewise empowered huge advance in speech recognition and natural language processing. These advances open questions regarding how such abilities can support, or even improve, human decision making in health and healthcare. We are entering a new era of health – Modern health where systems can treat and cure more diseases than ever before. New technology is bringing innovation to old treatments. Yet significant quality, access and cost issues remain, and our health systems are becoming increasingly unsustainable. The emergence and increasing use of artificial intelligence (AI) and robotics will have a significant impact on healthcare systems around the world. The potential for both AI and robotics in healthcare is huge. Much the same as in our consistently lives, AI and robotics, both are progressively a part of our healthcare ecosystem. AI is getting progressively advanced at doing what people do, however more effectively, more rapidly and at a lower cost. Also, the AI health market is seeing explosive growth. Development opportunities in healthcare are difficult to find substantial investment, yet artificial intelligence (AI) is a self-running engine for the development in healthcare. As per Accenture analysis, whenever combined, key clinical well-being AI applications can possibly make $150 billion in yearly investment funds for the United States medicinal services economy by 2026. AI is exploding in popularity with the immense power to release upgrades in cost, quality, and access. Development in the AI health market is anticipated that would reach $6.6 billion by 2021—that is a compound annual development rate of 40 percent. In only the following five years, the health AI market will develop more than 10x. Development is as of now quickening, as the number of healthcare-focused AI deals went up from less than 20 in 2012, to nearly 70 by mid-2016. Artificial intelligence and robotic technologies have long been seen as promising areas for healthcare. The explosion of healthcare data combined with the rise in demand from aging populations around the world, rising costs, and a shortage of supply – both in the number of healthcare professionals needed to treat and care for an increasing number of sick people and the availability and access to a broader range of necessary services than ever before – has left a monumental gap that only technology can fill. Mining medical records within minutes in the age of Big Data, it is no doubt how important patient information is. At the point when such tech giants as Google or IBM show up in the field of patient information mining, everybody knows, it is something worth doing. 1.) Google Deepmind Health: Recently, the AI explore the branch of the organization launched its Google Deepmind Health project, which is utilized to mine medicinal records keeping in mind the end goal to serve better and speedier health services. Google Deepmind can process a huge number of restorative data inside minutes. In spite of the fact that exploration into such information reaping and machine learning is in its initial stage, right now Google is participating in the Moorfields Eye Hospital NHS Foundation Trust to enhance eye treatment. Additionally, Verily, the life sciences arm of Google's umbrella organization, Alphabet is chipping away at its hereditary information gathering activity, the Baseline Study. It plans to utilize a portion of similar calculations that power Google's popular pursuit catch keeping in mind the end goal to investigate what makes individuals sound. This likewise incorporates exploring different avenues regarding malady checking advances, including a computerized contact focal point that could identify glucose levels. 2.) IBM WatsonPaths: IBM Watson propelled a venture called WatsonPaths in a joint effort with the Cleveland Clinic Lerner College of Medicine of Case Western Reserve University. WatsonPaths comprises of two subjective processing advancements that can be utilized by the AI calculation, Watson, which are relied upon to enable doctors to settle on more educated and exact choices quicker and to separate new bits of knowledge from electronic therapeutic records (EMR). In the course of recent years, the rapid development of technology has begun to satisfy this guarantee and it's just the beginning. As these technologies grow, quicker and better diagnoses; and the sky is the limit from there powerful medications will spare more lives and cure more diseases, what's more, we will have more open doors empowered by this technology to live more beneficial and healthier lives. In any case, whether we like, or dislike AI and robotics are the future of human care. “Access to quality, affordable healthcare, and better healthcare for everybody is the ultimate goal.” The financial and social preferences to be picked up from integrating AI and robotics flawlessly into our current healthcare systems, and afterward making new models of healthcare based on these technology, are gigantic. However, healthcare stays individual, and we must not lose sight of the human component. This will mean rethinking the different parts of healthcare professionals and guaranteeing that the new fundamental abilities are understood and taught in medical schools. "Chatterbot." Wikipedia. Web. 27 Apr. 2016. Coldewey, Devin. "What Are Chatbots? And Why Does Big Tech Love Them So Much?" NBC News. NBC Universal, 11 May 2016. Web. 24 Apr. 2018. Saenz, Aaron. "Cleverbot Chat Engine Is Learning From The Internet to Talk Like A Human." SingularityHub. Singularity Education Group, 13 Jan. 2010. Web. 24 Apr. 2018. Beal, Vangie. "IPA - Intelligent Personal Assistant." Webopedia. QuinStreet Inc., (n.d.). Web. 24 Apr. 2018. "Siri." Wikipedia. Web. 27 Apr. 2016. O'Boyle, Britta & Grabham, Dan. "What Is Siri? Apple's Personal Voice Assistant Explained." Pocket-lint. Pocket-lint Limited, 9 Feb. 2018. Web. 24 Apr. 2018. "Google Now." Wikipedia. Web. 27 Apr. 2016. Betters, Elyse. "What Is Google Assistant, How Does It Work, and Which Devices Offer It?" Pocket-lint. Pocket-lint Limited, 26 Jan. 2018. Web. 24 Apr. 2018. Fee, Tyler & Grabham, Dan. "Cortana in Windows 10: How It Works on the Taskbar and in Microsoft Edge." Pocket-lint. Pocket-lint Limited, 8 Mar. 2018. Web. 24 Apr. 2018. Carroll, Rory. "Goodbye Privacy, Hello Alexa: Here's to Amazon Echo, the Home Robot Who Hears It All." The Guardian. Guardian News and Media, 21 Nov. 2015. Web. 27 Apr. 2016. O'Boyle, Britta & Grabham, Dan. "Amazon Alexa Review: What Is Alexa and What Can Amazon Echo Do?" Pocket-lint. Pocket-lint Limited, 2 Mar. 2018. Web. 24 Apr. 2018. [1] [The American Heritage Dictionary of the English Language, Fourth Edition [Open Source AI. Bill Hibbard. 2008 proceedings of the First Conference on Artificial General Intelligence, eds. Pei Wang, Ben Goertzel and Stan Franklin.] Gibbs, Samuel. "AlphaZero AI Beats Champion Chess Program After Teaching Itself in Four Hours." The Guardian. Guardian News and Media, 7 Dec. 2017. Web. 24 Apr. 2018. Greenblatt, Nathan A. 2016. “Self-driving cars and the law.” IEEE Spectrum 53, no. 2: 46-51. Academic Search Complete EBSCOhost (accessed April 27, 2016). "Self-Driving Technology" CES. CES, n.d. Web. 9 Apr. 2018. https://www.ces.tech/Show-Floor/Marketplaces/Self-Driving-Technology.aspx Aaron Cole. “What are the different levels of self-driving cars?” Washington Post. 21.February.2017. Web. 9 April 2018 https://www.washingtonpost.com/cars/what-are-the-different-levels-of-self-driving-cars/2017/02/21/444a2a80-f877-11e6-aa1e-5f735ee31334_story.html Filipe Mutz, Lucas P. Veronese, Thiago Oliveira-Santos, Edilson de Aguiar, Fernando A. ➞Auat Cheein, Alberto Ferreira De Souza, Large-scale mapping in complex field scenarios ➞using an autonomous car, Expert Systems with Applications, Volume 46, 15 March 2016, Pages 439-462, ISSN 0957-4174, http://dx.doi.org/10.1016/j.eswa.2015.10.045 Ludovic Lassauce.”The future of mobile and the autonomous vehicle network” Tata Communications blog. Tata Communications, 11 Jan. 2018. Web 8.Apr.2018 Le Vine, S., Zolfaghari, A., & Polak, J. (2015). Autonomous cars: The tension between occupant experience and intersection capacity. Transportation Research: Part C, 521-14. How Antivirus Works? | How Antivirus Software Detect Virus. (2017, October 05). Retrieved April 22, 2018, from https://antivirus.comodo.com/how-antivirus-software-works.php Rahman, H. (2017, June 30). Artificial Intelligence Techniques To Power Antivirus Detection: Identify A Threat By Just Seeing It. Retrieved April 22, 2018, from https://www.eyerys.com/articles/artificial-intelligence-techniques-power-antivirus-detection-identify-threat-just-seeing-it Ng, A. (2017, June 27). Microsoft is using 400 million PCs to build antivirus protection. Retrieved April 22, 2018, from https://www.cnet.com/news/microsoft-build-smart-antivirus-using-400-million-computers-artificial-intelligence/ Wang, X., Yang, G., Li, Y., & Liu, D. (2008). Review on the application of artificial intelligence in antivirus detection systemi. 2008 IEEE Conference on Cybernetics and Intelligent Systems. doi:10.1109/iccis.2008.4670733 Trently, C. M. (n.d.). Computer Virus Response Using Autonomous Agent Technology. Mitretek Systems,1-10. Retrieved April 22, 2018. ARTIFICIAL INTELLIGENCE (AI): Healthcare’s New Nervous System. (2017). Accenture.com. Retrieved 24 April 2018, from https://www.accenture.com/us-en/insight-artificial-intelligence-healthcare Why AI and robotics will define New Health. (2017, June). Pwc.com. Retrieved 23 April 2018, from https://www.pwc.com/gx/en/industries/healthcare/publications/ai-robotics-new-health/ai-robotics-new-health.pdf Top Artificial Intelligence Companies in Healthcare to Keep an Eye On - The Medical Futurist. (2018). The Medical Futurist. Retrieved 23 April 2018, from https://medicalfuturist.com/top-artificial-intelligence-companies-in-healthcare/
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