Steps to Grow From Machine Learning to Artificial Intelligence

The technological advances in machine learning and development of Artificial Intelligence (AI) open many possibilities for the future. AI is nothing more than a continuation of machine learning which has been around for a long time.

Machine learning was meant to give computers the ability to deduct patterns and make them faster and better at gathering knowledge. The idea was to enable machines to become better at performing a specific task.

Machines “learn” by optimizing algorithms that perform tasks, such as minimizing errors or maximizing predictions, making the program faster and more accurate.

Machine Learning is only one part of the equations. It optimizes data, making it easier for humans to analyze it and make decisions. What truly separates and makes AI unique from machine learning is that in an AI system, the machine is able to make decisions on its own. 

What Is AI and What Are the Possibilities?

At its core, AI is nothing more than a branch of computer science that deals with improving intelligent behavior in computers. What this means is giving computers the ability to think and behave like a rational human and make decisions similar to what we would expect from a normal human being.

In order to make decision similar to humans, the computer would need sensory organs similar to humans. This involves giving computers vision to see, perception to recognize, recognize differences in tone and facial expressions, etc.

Based on the sensory input, a good AI program would be able to behave, or speak in an intelligent manner, almost like a human being. The more difficult it becomes to distinguish between human behavior and computer response to external stimuli, the more perfect the AI is considered to have become.

By now, almost everyone must have heard of or interacted with a virtual assistant. Siri, popularized by iPhone, is a good example of an AI virtual assistant. It learns and improves its knowledge and recommendations based on the lifestyle and interactions from its users.

Similar but advanced virtual assistants are now available that can do everything from set appointments or provide driving instructions to controlling smart appliances in your home.

Perhaps the biggest possibility for future AI comes with the development of the Internet of Things (IOT). This newly developing technology allows integration of computing devices, digital machines, people, and even animals with the ability to transfer data and instructions without a need for human input. 

Applications of AI based IOT can be found in a number of industries such as agriculture, healthcare, energy, transportation, and building management.

Benefits of AI

A lot of people are excited about the benefits that AI has to offer, and for good reason too. It can make life easier for individuals while also making businesses more efficient and productive by cutting down on the time doing repetitive and boring jobs.

AI Systems in Healthcare

AI can be utilized in healthcare as a virtual health assistant, reminding people about medication and providing health counseling. 

AI based systems can also be used for precise diagnosis of medical conditions. These systems can read CT scans, X-rays, and digital imaging. 

AI systems have the potential to decrease medical costs by up to 50% while improving outcomes by 30 to 40 percent.

AI Systems in Financial Industry

A report from the Financial Stability Board shows that AI systems are more efficient at the processing of information regarding credit decisions, financial markets, and contracts. Instances where AI and machine learning are implemented by the regulators results in improved supervision and compliance.

The report also concludes that AI and machine learning could result in new forms of interconnections between financial markets and institutions which will increase speed and efficiency

AI Systems in Logistics

AI is the best platform for businesses that want to gain a competitive advantage. Supply chain management systems have the most to gain from AI. 

A single supply chain serves manufacturers, producers, brokers, retailers, transport companies, and customers. While big retailers such as Wal-Mart could impose trade requirements on some partners, they cannot do it for all.

With a centralized automated logistics network, all the stakeholders can be connected together to streamline the process. 

How to Move to an AI System

Given that the benefits of strong AI system are assured, the main question is how to implement it in your organization. Businesses will need to create a foundation. 

Using Cloud Storage

Cloud backup stores your data on an online repository. This gives you access to the data from anywhere, which is the first step towards making businesses become truly online.

The latest encryption methods ensure that the data remains secure from threats of hacking or getting stolen. According to IBM sources, companies have made heavy investments in the private and public cloud space.

Hybrid Data Management

Businesses have the option of taking a cloud-first or a hybrid approach when it comes to data management through multi-cloud environments.

A hybrid cloud-based database allows flexibility, as it reduces transaction and marketing times, letting businesses grow and connect across platforms as varied as the IOT, web steaming, or big data. Hybrid databases adapt to multiple personas and data types.

Unified Governance and Integration

A unified governance and integration platform provides components that make it easy and secure to share data between cloud platforms. The process enables robust data preparation, policy creation, authorization, auditing, and much more.

This allows businesses to analyze and monitor the data which ensures accuracy and helps build trust. It gives flexible access to the platform, allowing companies to stop or add a product or apply the same flex point to another offering in the platform.

Data Science & Machine Learning

Data science is the technique used to extract knowledge from data to solve complex equations. Machine learning algorithms are predictive models that learn to formulate rules based on historical trends.

These techniques collectively provide analysis of data types and empower people to interpret complex data sets meaningfully in a way that makes sense to humans. 

Business Analytics & Visualization

Business Analytics & Visualization are specialized tools that take data as input and transform it into meaningful presentations and charts that are easier to understand. 

Artificial Intelligence APIs

Rapid advancements in AI will have a significant impact on application programming interface (API) design. This is expected to be achieved through four processes:

• Automation of the process of discovering APIs
• Improved prediction of developer consumer habits
• Allowing innovative third party tooling
• Powering new API functionalities

Want To Learn More From The Experts?

Join me & Rob Thomas (IBM General Manager), Katie Linendoll (Tech Host), Gary Kasparov (World Chess Champion) & sign up for “Machine Learning Everywhere: Build Your Ladder to AI

Event Schedule: February 27, 2018, 1:00 p.m. EST.