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Best field Artificial Intelligence: Learn More About AI

Artificial Intelligence


What is AI? Learn More About Artificial Intelligence


Artificial Intelligience

Understanding Artificial Intelligence (AI)


Simply put, artificial intelligence (AI) is a system or machine that can mimic human behavior in order to perform tasks and gradually learn from the information it gathers. AI has many incarnations, for example:

chatbots use AI to quickly analyze customer requests and provide appropriate responses;


smart assistants” use AI to extract information from large datasets in free form and optimize planning;

recommendation systems automatically select similar programs for viewers based on previously watched ones.


AI is not a format or a function, it is a process and the ability to think and analyze data. At the word “artificial intelligence”, many imagine intelligent humanoid robots that seek to conquer the world. However, AI is not intended to replace humans. Its goal is to expand human skills and capabilities. Which makes it a valuable business resource.

Artificial Intelligence (AI)


Oracle AI is a family of artificial intelligence and machine learning services. Developers can add pre-built models to applications and work systems. Data scientists can build, train, and deploy models using their favorite open source platforms, or take advantage of the high-speed machine learning capabilities built into databases.

Oracle AI:

Artificial Intelligence Services



Oracle AI Services provides pre-trained models that can be improved in accuracy through further individual training on the company’s own data, making it easier for developers to implement and use AI technologies.

Machine Learning Services


Oracle Machine Learning Services helps data scientists collaboratively build, train, and deploy models using their favorite open source platforms, or take advantage of the high-speed machine learning capabilities built into databases.

AI Applications For SaaS Services



Oracle AI applications help you work more efficiently with pre-integrated, out-of-the-box AI functions that feed directly into the software that powers your core business functions.

Terms Used In The Field Of Artificial Intelligence


Today, the term “AI” is widely used to refer to applications for complex tasks that previously could only be performed by humans. For example, customer service or a game of chess. It is not uncommon to use it as a synonym for machine learning and deep learning , which are actually sub-fields of the science of artificial intelligence. and have their own characteristics. For example, machine learning focuses on building systems that learn and evolve by processing and analyzing data. The difference is that machine learning always involves the use of AI, but AI does not always involve machine learning.

To harness the power of AI to the best of your business, you need to hire data scientists. Data science is a field at the intersection of statistics and computer science that uses the methods of these two disciplines for the business analysis of data obtained from various sources.

AI And Developers


Developers are using artificial intelligence to more effectively perform tasks that would otherwise have to be done manually, interact with customers, identify patterns, and solve problems. To get started with AI, developers will need mathematical knowledge and the ability to use algorithms.

If this is your first time using AI to build apps, it’s a good idea to start small. By creating a relatively simple tic-tac-toe project, you will master the basics of artificial intelligence. Learning by doing is a great way to develop any skill, and artificial intelligence is no exception. Having successfully completed several small projects, you will understand that the possibilities of artificial intelligence are truly endless.

How AI Technology Can Help Companies


AI makes it possible to replicate and improve the way we perceive and respond to the world around us. This property of AI is at the heart of innovation. AI is based on various machine learning technologies that recognize patterns in data and generate predictions. It creates added value for the business through the following features helps to use the full potential of the data,makes reliable forecasts and automates complex tasks.

AI And Corporations


AI-powered technologies help improve work efficiency and productivity by automating processes and tasks that were previously performed by humans. AI is also able to interpret volumes of data that a human cannot interpret. This skill can bring significant business benefits. For example, Netflix uses machine learning for personalization , which helped increase its audience by 25% in 2017.

Most companies have made data exploration a priority and are investing heavily in it. According to a recent Gartner survey of more than 3,000 CEOs, respondents cited data analytics and business intelligence as the top technologies for success. According to the respondents, these technologies are of the greatest strategic importance, therefore, they account for the bulk of investments.

AI offers benefits to all aspects and industries of any size business, both general and specialized,the use of operational and demographic data makes it possible to predict the amount of profit from the customer throughout the entire period of interaction (the value of the customer service cycle);optimization of pricing based on the behavior and preferences of buyers;pattern recognition for x-ray analysis and cancer diagnosis.

Application Of AI In Corporations


According to the latest Harvard Business Review report , companies are predominantly using AI for the following purposes:

detecting and preventing security breaches (44%);

elimination of technical problems of users (41%);

reduction of product management tasks (34%);

evaluation of internal compliance with approved suppliers (34%).

Why has AI become so popular?

Three factors are driving the widespread adoption of AI:

Availability of high-performance computing resources at a low price. The presence of numerous computing resources in the cloud has made them available to a wide audience. Previously, AI computing systems were local and prohibitively expensive.

Availability of large amounts of data for training. To teach AI to make accurate predictions, it must process large amounts of data. The emergence of various tools for data labeling, as well as simple and affordable means of storing and processing structured and unstructured data, enable an increasing number of companies to create and train AI algorithms.

Competitive advantages of AI. More and more companies are becoming aware of the competitive advantages of AI for business and are making adoption of this technology a priority. For example, specialized AI recommendations help you make better decisions faster. AI also offers many tools and opportunities to reduce costs and risks, speed time to market, and more.

5 Common Myths About Enterprise AI


Many companies have successfully implemented artificial intelligence technology into their processes, however, there are still many misconceptions about its functions. Therefore, enterprises do not always understand in which areas this technology can be useful, and in which it cannot. In this article, we will look at five common myths about artificial intelligence.

Myth #1: Enterprise AI requires in-house solutions.


Reality: Most enterprises are adopting AI, using both in-house developments and off-the-shelf solutions from third-party vendors. In-house AI technologies enable the enterprise to solve its unique challenges, while off-the-shelf AI solutions are easy to implement and simplify the solution of more common business problems.

Myth #2: AI magically delivers desired results right away.


Reality: It takes time, careful planning, and a clear vision of what you want to achieve for AI technology to deliver tangible value. It is necessary to take an iterative approach and have a certain strategy so that the AI ​​environment does not end up as a set of useless, disparate solutions.

Myth #3: Employees won’t have to control how enterprise AI systems work.


Reality: Enterprise AI is not robots out of control. The value of AI lies in the fact that it complements human capabilities and helps employees to solve more strategically important tasks. In addition, it depends on the employees on the basis of what data the technology will work and how it will use this data.

Myth #4: The more data, the better.


Reality: Enterprise AI systems must operate on the basis of good data. Only up-to-date, relevant, enriched high-quality data will help you find truly useful business information.

Myth #5: All you need to run enterprise AI systems effectively is data and models.


Reality: data, algorithms, and models are just the beginning. An AI solution must be scalable so that it remains relevant in an ever-changing business environment. Today, most enterprise AI solutions are developed by data scientists. These solutions have to be configured and maintained manually, which is quite laborious. Also, they don’t scale. For AI to deliver value, solutions need to scale as business needs change and the company’s AI strategy is implemented.

Benefits and Challenges of Implementing AI


The value of AI for business is confirmed by many success stories. Adding machine learning and cognitive operations to traditional business processes and applications provides improved convenience and productivity.

However, the implementation of AI is associated with certain difficulties. Few companies are tapping into the full potential of AI, and for several reasons. For example, if a company does not use the cloud, the cost of AI computing will be too expensive. In addition, AI is difficult to develop and requires the involvement of scarce specialists. Understanding where and why AI is needed, as well as addressing the challenge of engaging third-party service providers, will help minimize these problems.

AI success stories


AI has played an important role in these success stories.

According to a report by the Harvard Business Review , the Associated Press has produced 12 times as many articles by training AI to write short news stories. This gave journalists the opportunity to focus on working on larger stories.

Deep Patient, an AI-based diagnostic tool developed by Mount Sinai Hospital’s Icahn School of Medicine, helps identify high-risk patients before a diagnosis is made. According to insideBIGDATA , the tool can proactively diagnose nearly 80 diseases by analyzing patient medical data.

Ready-made solutions simplify the implementation of AI in the enterprise

The advent of AI-based solutions and tools means that more companies can take advantage of this technology to save money and time. AI-enabled solutions, tools, and software include built-in AI tools or help automate algorithm-based decision making.

These range from stand-alone databases that use machine learning to self-repair, as well as off-the-shelf models that can be used for tasks such as pattern recognition and text analysis. All of this helps companies accelerate time to value, increase productivity, reduce costs and improve customer relationships.

Getting started with AI


Using chatbots to communicate with customers. Chatbots use linguistic processing to analyze customer questions and provide answers and information. Chatbots can learn and over time begin to bring more and more advantages.

data center monitoring. Centralizing network, application, database performance, QoS and more with a single cloud platform that automatically monitors thresholds and detects outliers helps IT save time and effort.

Perform business analysis without the help of an expert. Analytic tools with a visual user interface make it easy to query the system and provide visual results.

Obstacles to unlock the full potential of AI

Despite the many opportunities for AI and machine learning, few companies manage to realize their full potential. Why? Oddly enough, the main obstacle is… people. Inefficient processes can prevent a company from realizing the full potential of AI.

For example, data scientists may find it difficult to obtain the resources and data they need to build machine learning models. Or problems may arise when interacting with colleagues. In addition, data scientists have to deal with numerous open source tools, and application developers are sometimes forced to completely recode learning models to fit them into applications.

The list of AI-based tools is constantly growing, forcing IT professionals to devote more time to supporting the data science department by updating the working environment. In addition, existing standards limit what data scientists can do.

In addition, executives may not always be able to fully appreciate the return on investment in AI. As a result, they do not provide sufficient support and funding to create an effective integrated ecosystem, which is the key to the successful use of AI.

How to create the right culture


To maximize the power of AI and overcome barriers to successful adoption of new technologies, you need to create a team culture that supports the AI ​​ecosystem. In such an environment:

business analysts and data scientists jointly define tasks and goals;

data engineers provide data management and a platform to perform analysis;

data scientists prepare, study, visualize and model data using a specialized platform;

IT system architects provide infrastructure management for data exploration both locally and in the cloud;

Application developers deploy models in applications to create data-driven products.

From artificial intelligence to adaptive intelligence

AI is increasingly used in manufacturing operations, which has led to the emergence of a new term – adaptive intelligence. Responsive, intelligent applications help you make better business decisions by leveraging real-time internal and external data and highly scalable infrastructure.

Applications like this enable you to “work smart” in every sense of the word and offer customers better products, recommendations, and services—and, ultimately, higher profits.

Strategic Necessity And Competitive Advantages of AI


AI is a strategic necessity for any company that wants to increase productivity, unlock new profit opportunities, and build customer loyalty. This technology has already helped many companies achieve a competitive advantage. With AI, you can do more in less time, provide effective personalized service, and predict results, which means more profit.

However, AI remains a fairly new and complex technology. To unlock its full potential to create and apply AI-based solutions, a high level of skill is required. It’s not enough to simply hire data scientists to be successful. The right tools, processes and management strategies must be used.

Best Practices To Get The Most Out Of AI


The Harvard Business Review makes the following recommendations for getting started with AI:

apply AI to areas that have the most immediate and most significant impact on profits and costs;

use AI to increase productivity instead of reducing or increasing staff;

start the implementation with the support departments (it is best with IT and accounting).

Getting help on your AI journey

AI is becoming an integral part of business. Sooner or later, all companies will be forced to use AI technologies to create their own ecosystem and remain competitive. Those who neglect progress risk being left behind in the next 10 years.

Your company may be the exception to the rule, but most businesses don’t have the in-house data scientists and resources to build an ecosystem and develop applications to help put the power of AI to their service.

If you need help developing the best strategy and accessing the tools to successfully implement AI, seek the help of a trusted partner who has extensive experience and a wide range of suitable solutions.

Build, test, and deploy applications on Oracle Cloud for free.

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