Artificial Intelligence (AI) is one of the major developments of our time. In particular, Machine Learning, and the implications that go with it, is shaking up many aspects of how we do things, allowing us to deploy AI software where we previously used a human or a more inefficient process. Sometimes this is to the consternation of people, particularly those who worry about AI systems and machine intelligence taking over human jobs, or perhaps the sci-fi scenario of AI being intelligent and organized enough to overrule humans.
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One thing we do know is that we’ve probably only scratched the surface in terms of what is possible. As Oracle EVP and head of applications, Steve Miranda said at a recent event, “Two years from now, we’ll probably be talking about a whole new set of things in this category that probably none of us is even thinking about today.”
In other words, AI and its methods like Machine Learning are moving pretty fast. What we discuss today may not be what we will discuss in just a few years.
AI Development Trends
Since it is important to stay informed about the state of AI, here are some recent AI trends that demonstrate how the technology is advancing:
AI Robots Learning Through Observation
The mechanism through which AI “learns” is generally through training by humans or Machine Learning, where the bot learns by processing data by itself. For example, a bot might observe that you seem to go to the same place at the same time every day, and it may start to automatically look for traffic and weather conditions to provide you with an estimated driving time.
A groundbreaking development in AI has been the development of robots’ abilities to learn through observing the actions of humans. Nvidia demonstrated a robot that performs tasks in a real-world setting by watching how the tasks are done, a different and more hands-off mechanism from how robots are usually trained.
If robots can learn through observing demonstrations, this has implications, particularly for the workplace and for carrying out physical tasks. Perhaps robots of the future will be in homes, observing how household tasks are performed and taking care of those?
In another development along similar lines, a bot program called AlphaGo taught itself advanced strategies for playing the game Go, with no training from humans. This is further highlighting a growing trend of AI that is able to be independent from human knowledge.
AI Robot Caregivers Are Filling a Shortfall
How would you feel about being cared for by a robot nurse, or your elderly relatives being cared for by robot caregivers? Many countries throughout the world are heading towards a crisis in terms of having enough carers for aging populations. Particularly, as the large baby boomer generation reaches their elderly years, the shortage is predicted to be more pronounced.
Artificial Intelligence is being developed to step in and make up for the shortfall. The Japanese government, in particular, is working on increasing acceptance of technology filling in for human nursing and caregiving roles. Japan is facing a predicted shortfall of 370,000 caregivers by 2025, and developers are focusing their attention on simple applications of AI technology. For example, a robot might help a person to get out of bed, or it might predict when a patient is going to need to use the restroom.
Potential resistance to help from a robot is one of the issues researchers are working on. The next research priorities include wearable mobility aid devices and technology that guides people to the restroom at what it predicts is the right time.
AI Beer Brewers
What if the perfect beer could be brewed using the help of AI? Okay, “perfect” is going to very much be in the eye of the beholder, but Artificial Intelligence is being used by IntelligentX to take customer feedback into account as much as possible. So technically, the beer is a product of customer experience, AI, and skilled brewers.
Basically, the process works by using an algorithm that is behind a Facebook Messenger bot. The bot takes the customer feedback and passes it on to the humans who are actually brewing the beer. The technology facilitates brewers receiving that feedback quicker than they ever did before.
The company places QR codes on bottles that direct customers to interact with the bot. They are then asked a series of questions, the answers to which are interpreted by the algorithm. Feedback is accumulated to spot trends and inform the brewing process.
Cybersecurity has been a hot topic ever since it became necessary. As technology evolves, so do potential threats to sensitive information and networks. There has been increased demand for AI solutions to boost cybersecurity. Professionals are hoping it will accelerate incident detection, improve incident response, identify and communicate risk, and generally help them to maintain optimum situational awareness.
Palo Alto Networks recently introduced Magnifier, a behavioral analytics AI solution. It models network behavior by using structured and unstructured Machine Learning to improve threat detection.
There’s also Google’s parent company, Alphabet, which introduced Chronicle, a cybersecurity intelligence platform. Chronicle is a powerhouse for cybersecurity data, allowing for rapid search and discovery. The idea is that security teams already have the information they need within their systems, but it is often hidden among the millions of data centers. Machine Learning advanced search capabilities are the driver for more rapid search.
AI Diagnostics for X-Rays
Medical technology is a field that’s ripe for innovation from AI. Areas such as diagnostics traditionally rely on human intelligence and capabilities being able to read and interpret tests or imaging results. This naturally creates some kind of lag in processing and leaves open the possibility for human error.
There are major challenges in the area of AI adoption for diagnostics. For example, the AI must be taught to correctly interpret results under human supervision, and it is difficult to teach the identification of rare pathologies, due to a shortage of images.
A recent development has essentially “used Machine Learning, to do Machine Learning,” by using computer-generated x-rays to augment AI training. As Shahrokh Valaee, a Google scholar stated, “we are creating simulated x-rays that reflect certain rare conditions so that we can combine them with real x-rays to have a sufficiently large database to train the neural networks to identify these conditions in other x-rays.” This development brings the idea of AI actually taking the diagnostics role even closer.
Artificial Intelligence Trends in App Development
App development is not exempt from the most recent developments in Artificial Intelligence. Developers are using new and powerful AI tools to enhance the app development process as well as the User Experience. These are some of the most important ways in which Artificial Intelligence is impacting app development:
AI in Smartphone Apps
AI is making an appearance in a broad range of smartphone apps that are designed for everyday consumers. Gartner predicts that by 2022, 80% of smartphones will be equipped with on-device AI capabilities (compared to the 10% that have these capabilities right now). This makes Artificial Intelligence a key opportunity for developers of all types of apps.
Here are just a few that are currently in use:
- Google Assistant – You can access your assistant by holding down the home button on your Android phone, or saying aloud, “Okay Google.” From there you can send messages, check appointments, play music, and a host of other things hands-free.
- Socratic – Math help is here! Socratic is a smart tutoring app that can explain how to solve problems by analyzing a picture of the math problem.
- Microsoft Pix – Everyone wants to be able to take and share the perfect photo. Microsoft Pix helps by capturing ten frames per shutter click, using AI to select the best three, then deleting the rest, saving you storage space.
Artificial Intelligence in FinTech
FinTech has seen a lot of disruptive technology in the last decade. Traditional financial institutions are facing the challenge to keep up with technology as new apps emerge. AI is another disruptor in the sector.
AI is able to reduce financial institution’s operation processing times. For example, your bank probably has an app that allows you to photograph a check for a deposit. The funds are often available immediately, in part due to AI being able to read the check. This eliminates the need for a human operator to accurately read and deposit the check.
Fraud detection is another effort that Machine Learning is helping with. For example, Pixmettle is developing enterprise-level Artificial Intelligence tools to help flag things like duplicate expenses and corporate policy violations.
Chatbots are also now widely in use. Many banking apps use them as part of their customer service suite, while there are apps that have specifically been developed to connect financial accounts with Facebook Messenger (such as Trim), allowing users to ask questions via the app, make cancellations, or get reports.
Of course, FinTech is also ripe for AI cybersecurity, as mentioned earlier. Artificial Intelligence is scalable and able to rapidly analyze large amounts of data, making digital systems more secure, helping customers protect their financial products.