Introduction
Artificial intelligence (AI) is one trend that is seen and used everywhere. This includes large investments, numerous startups, established technology vendors, as well as enterprises both, big and small who are experimenting with what it can do for their business. The primary reason why AI is considered a revolution as it points towards a future where machines not only do all of the physical work, but also the thinking work. The means AI is capable of planning, strategizing as well as making decisions. The adoption of artificially intelligent products will continue to scale into different verticals from manufacturing to education, retail and more in 2019.
Amidst all the discussions one question that arises ultimately boils down to advances and implementations of AI. Now that AI is getting better and able to work more independently, what’s next? What are the most recent advances in artificial intelligence? What new technologies can we expect to see in 2019? Will there be new regulations on AI? These are the questions that tech industry professionals have in their mind. And all the signs where AI is heading to directs towards on how AI will help humans and be of assistance in many other forms.
Benefits of Artificial Intelligence
AI is one of the rapidly developing technology offers significant development opportunities that many industries have already been quick to seize upon. Along with a lot of advancements made, listed below are some of the major advantages that AI as technology has to offer.
Digital Assistance
Some of the highly advanced organizations use avatars which are replicas or better known as digital assistants. These are well equipped to interact with users, thus saving the need for human resources. For artificial thinkers, emotions come in the way of rational thinking and are not a distraction at all. The complete absence of the emotional side, makes the robots think logically and take the right program decisions. Emotions are associated with moods that can cloud judgment and affect human efficiency. This is completely ruled out for machine intelligence.
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Error Reduction
One major advantage of artificial intelligence is that it helps in reducing errors and the chance of reaching accuracy with a greater degree of precision is possible. This technology is applied in various studies. Intelligent robots are fed with information and are sent to explore different areas of industries. These machines are created and acclimatized in such a way that they cannot be modified or get disfigured or breakdown in any kind of hostile environment.
Data Mining
The technology of artificial intelligence is able enough to quickly discover important and relevant findings during the processing of big data. This thus provides businesses with previously undiscovered insights that can help give it an advantage in the marketplace.
Operational Automation
Artificial intelligence has the ability to operate other technologies that increase automation in business. In Japan, human-looking robots now serve as receptionists in some of the countries’ hotels automating check-ins, booking services and dealing with customer enquiries. In retail, AI is also being linked with RFID and cloud technology to track inventory. In China, police forces use AI to catch criminals. The country has a vast CCTV network and AI uses facial recognition to spot and track suspects so that they can be apprehended.
Outcome Prediction
Among all the advantages of AI, the one that stands out is that it is able to predict outcomes based on data analysis. The way it functions is where it recognizes patterns in customer data that can show whether the products currently on sale are likely to sell and in what volumes. This proves to be useful in helping a company purchase the correct stock and in the correct volumes. AI is also used in many other areas, for example, in banking where it can predict currency and stock price fluctuations or in healthcare where, remarkably, it can predict outbreaks of infections by analyzing social media posts.
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5 AI Developments Expected in 2019
AI technology has shown a lot of potentials to make our lives easier. The fact that the use of this technology advancements does not stop in our homes, as businesses constantly come up with new ways to use AI to engage with customers. Thus making processes easier and pull revenues to new highs. The effectiveness and popularity of AI-powered chatbots in recent years has grown to increase interest in how artificial intelligence is deployed to improve the results of a lot of campaigns.
As 2019 is already here, there have been a number of generative AI technologies that seem to gain popularity. More significantly, they’ll be embedded in a growing range of AI products and services. The advance of this technology will trigger more developments throughout the global culture, inflame more political discussions along with a number of advancements. Let’s look at some of the major AI developments to be seen in the coming year.
Generative Models
Generative models estimate an entire probability distribution so that new content can be generated such as images, text, or speech. These models learn some classifier to predict the probability of an output label given inputs. Generative artificial intelligence refers to programs that make it possible for machines to use things like text, audio files and images to create content. A generative model tends to learn the entire probability distribution over the inputs for some desired output, allowing entirely new images to be generated upon request. Recurrent neural networks have been generating text for some time but only recently have advances in deep learning improved enough for images to be generated.
Models that can generate photorealistic images have evolved very quickly in the last few years. They can now generate some truly impressive results. These models are a powerful way of learning any kind of data distribution using unsupervised learning and it has achieved tremendous success in just a few years. The primary functionality that these generative models have developed to function are Generating life-like images, Language translation, Image understanding, Sequence prediction.
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Cyber Defense
Cyber defense is a computer network defense mechanism that focuses on preventing, detecting and providing timely responses to attacks or threats to infrastructure and information. Artificial intelligence is now being used to move cyber defense into a new evolutionary phase in response to an increasingly hostile environment. It was found that that the breach level index detected was a total of over 2 billion breached records during 2017. Seventy-six per cent of the records in the survey were lost accidentally, and 69% were an identity theft type of breach. Recurrent neural networks, which are capable of processing sequences of inputs, can be used in combination with AI techniques to create supervised learning technologies. These specifically uncover suspicious user activity and detect up to 85% of all cyber attacks.
Many companies in the industry that pair behavioural analytics with advanced mathematics to automatically detect abnormal behaviour within organizations also apply AI algorithms to stop malware and mitigate damage from zero-day attacks. There are firms in the market that are completely working in the area of AI-powered cyber defense. DeepInstinct is a cyber defense company which has a deep learning project named “Most Disruptive Startup” by Nvidia’s Silicon Valley ceremony, protects enterprises’ endpoints, servers, and mobile devices.
Meta Learning
Meta-learning is one of the most creative artificial intelligence developments. This concept is all about machines attempting to master how to learn and then transfer that learning ability to new domains that it hasn’t been exposed to. Meta-learning starts at a higher level and is concerned with accumulating experience over several applications of a learning system. It is a concept that monitors the automatic learning process itself, in the context of the learning problems it encounters and tries to adapt its behaviour to perform better. Meta-learning is relevant for the first objective of its existence which is primarily developing AI with gradual learning capabilities.
Although meta-learning is still a growing concept, automatic machine learning is being applied effectively to conduct hyperparameter search more efficiently than brute-force grid search. Also to automatically learn exotic connectionist architectures. The concept of meta-learning follows a process that typically includes wherein, the model is trained to learn tasks in the meta-training set. There are two optimizations at play – the learner, which learns new tasks, and the meta-learner, which trains the learner. Methods for meta-learning have typically fallen into one of three categories. These categories are referred to as recurrent models, metric learning, and learning optimizers.
Reinforcement Learning
One of the major advancements of AI that 2019 will notice is reinforcement learning. This is the method of solving sequential decision-making problems that are common in robotics, game playing and financial markets. The approach of reinforcement learning is meant for solving problems in which an agent interacts with an environment and receives a reward signal at the successful completion of every step. Reinforcement learning algorithms aim to find a policy, which means a mapping from state to action, which maximizes the expected cumulative reward (value function) under that policy.
A number of industry discussions conducted regarding reinforcement learning this year focused on one thing i.e data efficiency. There have been noticeable breakthroughs applying what is called policy networks to play a number of games introduced in the industry. However, these methods require vast resources to simulate millions of iterations of a game. Pertaining to Google’s DeepMind, a professional in reinforcement learning said, cannot be reproduced by general AI researchers because we don’t have access to the thousands and hundreds of cloud GPU’s that DeepMind does. This is why there has been a focus to create reinforcement learning algorithms that not only play games well but are also reusable, robust and reproducible.
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Marketing Automation
The marketing industry has benefited to a major extent from AI so far. So there is great faith placed in AI within this industry for a legit reason. According to market research, fifty-five per cent of marketers is sure AI will have a greater impact in their field that social media has. As marketing automation allows companies to improve engagement and increase efficiency to grow revenue faster, the role that AI has played in this is huge. This concept software to automate customer segmentation, customer data integration, and campaign management, and streamlines repetitive tasks, allowing strategic minds to get back to doing what they do best. One of the leaders in this field is Adext AI. This firm’s audience management platform can boost ad spend efficiency by up to +83% % in just 10 days. The software automates all the process of campaign management and optimization, making more than 480 daily adjustments per ad to super-optimize campaigns and managing budgets across multiple platforms and over 20 different demographic groups per ad.
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Conclusion
AI technology has grown to provide businesses with a wide range of benefits, including personalized marketing, customer service, operational automation, inventory management and recruitment. And these are just a few of the many ways AI can be used. What’s remarkable, however, is that many of the AI applications, which are designed specifically for cloud-based systems, are quickly and easily deployable. With so many benefits being recognized of AI, 2019 is surely going to be a year which will notice a takeover by artificial intelligence.
