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Posts Tagged ‘machine learning’

Successful Machine Learning: Part 1 (Questions and Baselining)

Monday, May 17th, 2021

Machine Learning Chip

In this series of posts, I’m delving into the limitations of machine learning and AI, hamstrung by current techniques, while considering technologies and practices to transform business intelligence efforts beyond the status quo.

Question of Intelligence

What is intelligence? What underlies intelligence? What aspects of intelligence do we want machine learning to demonstrate? What is artificial intelligence as opposed to intelligence? What capabilities does a computer need to achieve intelligence? Can programs be written to derive intelligence within a modern computer?

Questions delving into intelligent systems go on and on. I’m going to spend a few blog entries exploring machine learning and our quest to create and benefit from intelligent computer systems. Through this discussion, I’ll explore these questions.

Framing the Discussion

Note that my focus is business automation, what are organizations seeking to gain from machine learning and intelligent systems. I am purposefully avoiding a philosophical discussion of intelligence. To that end, a primary assumption is that we are interested in applying human-style intelligence to advance business or operational success. Put another way, animals and plants demonstrate intelligence of differing types; however, mimicking these is not an organization’s goal when employing machine learning.

Key Terms

To begin, I need working definitions for learning and intelligence. These will serve as touchstones for exploring computer-based learning and intelligence. Merriam-Webster’s dictionary provides helpful initial entries for each. The definition for “learn” is “to gain knowledge or understanding of or skill in by study, instruction, or experience.” While “Intelligence” is defined in two parts, “the ability to learn or understand or to deal with new or trying situations” and “the ability to apply knowledge to manipulate one’s environment or to think abstractly as measured by objective criteria (such as tests).”

The terms knowledge and understanding appear in both definitions and are vital to successful machine learning applications. Knowledge and understanding are based on information.



The Cognitive Corporation™ – Effective BPM Requires Data Analytics

Tuesday, October 25th, 2011

The Cognitive Corporation is a framework introduced in an earlier posting.  The framework is meant to outline a set of general capabilities that work together in order to support a growing and thinking organization.  For this post I will drill into one of the least mature of those capabilities in terms of enterprise solution adoption – Learn.

Business rules, decision engines, BPM, complex event processing (CEP), these all invoke images of computers making speedy decisions to the benefit of our businesses.  The infrastructure, technologies and software that provide these solutions (SOA, XML schemas, rule engines, workflow engines, etc.) support the decision automation process.  However, they don’t know what decisions to make.

The BPM-related components we acquire provide the how of decision making (send an email, route a claim, suggest an offer).  Learning, supported by data analytics, provides a powerful path to the what and why of automated decisions (send this email to that person because they are at risk of defecting, route this claim to that underwriter because it looks suspicious, suggest this product to that customer because they appear to be buying these types of items).

I’ll start by outlining the high level journey from data to rules and the cyclic nature of that journey.  Data leads to rules, rules beget responses, responses manifest as more data, new data leads to new rules, and so on.  Therefore, the journey does not end with the definition of a set of processes and rules.  This link between updated data and the determination of new processes and rules is the essence of any learning process, providing a key function for the cognitive corporation.