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Advanced analytics in the here-and-now

Smart enterprises are leveraging AI and machine learning today to improve customer experiences, energy consumption, and processes. Here's how they're delivering value to IT organizations and businesses alike.

When you look at the popular, artificially intelligent "assistants" on the market today, they're really just voice-recognition engines, coupled with pattern- and image-recognition and search engines. But those capabilities, when allowed to 'learn' over time, start to form the basis of cognition, inference, and then reasoning.

Add attitude, subjective opinion, and feelings, and we get close to the human-brain benchmarks that all machine-learning scientists are pursuing.

25 years of machine learning and advanced analytics

Bill Gates created Microsoft Research in 1991 with the vision that computers would one day see, hear, and understand human beings. In October 2016, researchers and engineers at what is today known as Microsoft Artificial Intelligence and Research exceeded expectations with the announcement of a major breakthrough in speech recognition, creating a technology that recognizes the words in a conversation as well as a person does.

In a paper published recently, a team at Microsoft shared news of a speech recognition system that makes the same or fewer errors as professional transcriptionists do. The researchers reported a word error rate (WER) of 5.9 percent, down from 6.3 percent reported the previous month.

"We've reached human parity," said Xuedong Huang, the company's chief speech scientist. "This is an historic achievement."

Fear the future?

That phrase, "human parity," strikes fear into the hearts of some of the world's foremost scientists and futurists, who refer to the moment that the intelligence of machines exceeds that of humans as "the singularity."

Lest you consider this to be a science-fiction reference, the geniuses involved include the likes of:

  • Bill Gates, who said, during a Q&A session on Reddit in January 2015, "I am in the camp that is concerned about super intelligence. First the machines will do a lot of jobs for us and not be super intelligent. That should be positive if we manage it well. A few decades after that, though, the intelligence is strong enough to be a concern. I agree with Elon Musk and some others on this and don't understand why some people are not concerned."
  • Elon Musk, for his part, feared aloud that he "Hope[s] we're not just the biological boot loader for digital superintelligence. Unfortunately, that is increasingly probable."
  • Stephen Hawking, who warned that because people would be unable to compete with an advanced AI, it "could spell the end of the human race."

Advancing human endeavor

SkyNet references aside, Microsoft has focused its efforts on a variety of vectors that lead to advanced human/digital experiences, advanced analytics, and machine learning.

A key driver of all "natural language interface" development, including cognitive technologies, machine learning, and artificial intelligence, is the effort to make it easier for people to work together, and to work with their information-management tools. Improving collaboration through advancements in computing and communicating has become the mission behind most everything that technologists and IT professionals do for their clients. We have quickly moved from systems that analyzed data and provided decision-support to systems that provide thought-support. This will be the continuing challenge for IT Pros in years to come.

The collaborative value of Office 365 continues to expand with a variety of analytic and operational tools that help people better understand people, including themselves. Most IT, IS, and DevOps resources find their own "stack" of requests to be fulfilled to be their greatest challenge. As such, the value of these tools often begins at home, with the developer, engineer, or integrator using them to analyze and manage their own workload:

  • Delve is an Office 365 application that draws on data from SharePoint, OneDrive, Office Graph, and social networks like Yammer to give a broad overview of documents and what people in the organization are working on.
  • MyAnalytics, originally named Delve Analytics and still available from the Delve dashboard, gives users a detailed analysis of how they are using their time, allowing them to set and track personal goals, and to include their interactions with specific other people in their organization. IT professionals often use their own experience to prove case, demonstrating to clients how they have optimized their own time utilization to create successful projects faster while controlling costs.
  • The Microsoft Graph API allows users to connect to the data that drives productivity - mail, calendar, contacts, documents, directory, devices, and more.
  • With the Azure Sentiment Analysis engine, users can analyze any English-language text to score the overall sentiment toward the subject. Companies can now monitor the perception of their brand or topic over time, automatically extract key phrases to identify the main points, and identify 120 other languages.

Emerging signs of intelligence

According to The New York Times, cloud-based CRM firms and established business software providers alike are pursuing machine learning to process big data workloads and achieve better levels of customer service and personalization. The space is heating up rapidly, and the opportunities to accelerate and improve the ways in which we work with information are simply too exciting to pass up.

While the links provided in this article provide an excellent roadmap, IT Pros may want to begin by visiting the Microsoft Cognitive Services website for a bigger picture perspective.