It has been decades since science fiction put humanity inside the Matrix and even longer since HAL refused to open the pod bay doors, but real-life technology has finally caught up enough to begin offering Artificial Intelligence, or AI.
What Is AI?
Artificial intelligence is a way of programming computers, not with static logic, but with the ability to imitate human perception and thought. To achieve this end, computers need to be able to both take in data (perception) and to analyze and do something with that data beyond following specific instructions (thought).
A standard computer function might be for a grocery store to generate a coupon for diapers whenever a shopper buys baby formula. This is the basic If/Then programming that has been around for a long time. If the shopper buys diapers, then print a formula coupon.
However, this approach can be made more successful. The machine can analyze more data than the current purchase, while also learning, or training, itself as to what types of coupons generate the most success for each type of customer. Do men buying diapers buy formula at the same rate as women? What about couples shopping together, or customers buying just a few items versus those with a full shopping cart?
Accomplishing such an analysis for more than a handful of shoppers would take a monumental amount of programming from scratch. That is where Microsoft AI comes in. The company’s platform provides tools and services that allow users to focus on building the specific model.
Microsoft’s AI Platform
Making AI work takes powerful algorithms, lots of data, and fast computing power. Not surprisingly, Microsoft brings many of these features together under its Azure computing platform.
Without machine learning, it’s just programming. Microsoft AI continues the company’s paradigm of offering a low-code, or no-code version, and a full-code developer option.
The low-code version is Machine Learning Studio. With Studio, users can use a drag and drop interface to start creating and training machine learning solutions using pre-built algorithms. Azure Machine Learning Service also offers pre-build algorithms but can be programmed using Microsoft’s own Python SDKs, or open-source solutions like ONNX, TensorFlow, and PyTorch.
Before you can perform human like thought, the machine needs data, and Microsoft offers several ways to get it. First, the company’s Cognitive Services offer several ways to bring in data using human like perception. While computers are pretty bad at touch, smell, and taste, the Azure Cognitive Services allow AI to acquire knowledge with the other human senses. Vision APIs, for example, provide the ability to analyze not only pictures and faces, but handwriting, forms, and even videos.
Nothing says human-like more than being able to talk, and Microsoft provides AI with the ability to speak via a set of Speech APIs, and the ability to understand what humans say back via Language APIs. These are the same services used to power Microsoft’s Cortana assistant.
The Search APIs, powered by Microsoft’s Bing search engine, offer the ability for machines to go find new data, analyze it, and use it for training and prediction. Finally, Decision APIs provide a way to monitor the incoming data.
Getting data from users or searches is just one option. Many enterprises are already drowning in data. For them AI is about being able to use enormous existing data sets.
Microsoft AI takes advantage of the Azure Databricks platform to store, retrieve, and process big data that already exists. Databricks is an Apache Spark-based platform designed to work with Azure Blob Storage, Azure Data Lake Storage, or Azure SQL Data Warehouse.
Finally, the Azure Bot Service provides the interactivity that makes an AI application seem human. The simplest form looks like a standard chat type session with a customer service representative. Instead of a human being, the Microsoft AI solution takes in data, parses it, and responds as it has been trained to do.
Integrated with Cognitive Services, however, the Bot Service can both listen to a human talking and reply with spoken language. Connected back to Search, the Bot Service can retrieve information when asked, or it can dig into existing data using Azure Databricks. Ultimately, this integration can create a human sounding, human understanding, artificial intelligence with access to enormous amounts of data.
Obviously, all of these features can require a lot of computing power, and that’s where Microsoft’s Azure offering comes in. Like all Microsoft Cloud computing, customers are only charged for what they use and can spin up more power or storage whenever necessary to handle increasing loads from machine learning enabled AI.
Ready to Learn More?
The Microsoft AI platform offers everything you need to get AI applications and services up and running. Look here for a list of real world case studies with companies using Microsoft AI today.
Interesting in leveraging Microsoft AI within your organization? Contact Imaginet to learn more about how Microsoft AI can benefit you.
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