Artificial Intelligence vs. Intelligent Assistance

“Artificial intelligence” and “intelligent assistance” are two sides of the same coin, separated only by the way humans engage with either technology. In this blog post, I explain the key differences between the two concepts, and how tools like IBM Watson and the Amazon Echo benefit users in the business world.

Smartbridge is constantly searching for ways to innovate and produce positive business transformation. Cognitive computing is one of the latest topics we have begun to investigate, given its tremendous potential to provide companies with a competitive advantage via automation, forecasting, and prescriptive analysis. As I explored cognitive computing capabilities, I found extensive similarities between artificial intelligence and intelligent assistance that prompted me to ask: what’s the difference?

Artificial Intelligence

When the topic relates to Artificial Intelligence (AI), one of the first thoughts that come to my mind is the Terminator. Imagine a machine that can learn, process, plan, and execute faster than humans; it’s scary, right? To put things in perspective, the scope of the tasks expected of an AI machine is immense because the machine would have to consider:

  • Problems
  • Approaches
  • Tools
  • Identifying the relationships between the three above while administering them towards a goal
The definition of AI seems to be a moving target. Machines like IBM’s Deep Blue & Chess or Google’s AlphaGo are intelligent contextually, but cannot apply the same cognitive ability in other areas. Therefore, the study into Artificial Intelligence continues.

The Current State of Machine Intelligence

The Current State of Machine Intelligence (Source)

Intelligent Assistance

Intelligent Assistance (IA) refers to the use of intelligent agents that help individuals perform tasks or services. While intelligent agents may seem like any other software application that completes a group of coordinated functions, tasks, or activities, they can actually do one or many of the following:

  • Work autonomously
  • Meet goals
  • Maintain historical data
  • Perceive and assist

Artificial Intelligence vs. Intelligent Assistance

In simpler terms: AI machines mimic humans while IA machines assist humans. Due to the breadth of the research involving both technologies, it can be easy to confuse the two. Artificial intelligence is the practice of studying of intelligent agents and identifying the limits of their intelligence. Intelligent assistance is the use of intelligent agents to serve humans, meaning that such agents exist within predefined parameters. Their intelligence is measured by many factors, including but not limited to:

  • Problem Solving
  • Learning
  • Language processing
IBM’s Watson understands unstructured data by relying on Natural Language Processing (NLP). Watson breaks down the data it receives, determines context, and identifies the intent of the user. To achieve the results, some underlying components are necessary, along with some level of human interaction:

  • Corpus – Watson’s reference material, consisting of all kinds of unstructured text. Similar to the sources one might use to write a course paper.
  • Ingestion – Refers to the knowledge consumption process for Watson
  • Curate – In the ingestion phase, Watson separates the necessary material and leaves bad, incorrect, or dated sources in the Corpus
  • Reasoning Algorithms – Watson cycles through different algorithms to imagine different scenarios, then weighs them to arrive at the best possible solution
With the use of the above components, IBM Watson incorporates “much more context into [its] evaluation” of language. This type of language processing is called “Deep NLP,” due to the amount of data that is evaluated to reach the solution. To forecast some of the business implications of IBM Watson, consider the wealth of information that businesses accumulate across all industries. With cheaper means to store data, we are storing more than ever before, making tools like IBM Watson indispensable in industries like finance, wealth management, and education. IBM Watson can even be used in sensitive matters like oncology diagnosis, where it assists doctors by matching patients’ symptoms with necessary treatments for the best possible care.

Utilization management seeks to maximize the results of healthcare services provided to patients to avoid waste and reduce cost. IBM Watson assists that goal by using clinical and patient data to assist in the decision-making process, thereby:

  • reducing the amount of time needed for approvals
  • reducing waste
  • prescribing specific treatments
As #IA becomes more popular, Smartbridge excitedly integrates @AmazonEcho and @OracleJDEdwards. Click To Tweet

Integrating Amazon Echo & JDE EnterpriseOne

The quality of services provided by companies that can cater to their clients’ needs will increase significantly, and allow industry leaders to separate themselves from the rest. As the practical use cases for intelligent assistants in the workplace continue to grow, Smartbridge is excited to introduce the integration of Amazon Echo and JDE EnterpriseOne.

We are extending the services of the Echo and using Alexa’s NLP to build conversational applications with JDE EnterpriseOne. As we continue to build out our use cases, some of the most common scenarios involve one or many of the following:

  • Inquiry
  • Suggest & Approve (Execute)
  • Notifications

Currently, our workflows do follow a defined process and flow to meet certain needs and extend enterprise services with JDE EnterpriseOne. JDE EnterpriseOne supports a variety of industries, from finance to real estate to warehousing and inventory. If you are interested in discussing more or would like a demo, please reach out so we can identify what’s possible.

If you’d like to know more about how we’re accomplishing the integration between Alexa and JDE, please refer to our previous blog posts on adapting voice assistance for business and developing for Amazon’s Alexa.

By |2017-05-11T09:10:26+00:00May 3, 2017|Categories: Strategy, ERP / JD Edwards|

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