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We focus on Ai business related topics that you need to know, can use and get started with now.
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September 12 · Issue #3 · View online
➥ Artificial Intelligence & Blockchain insights to fast-track your business growth today.
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We focus on Ai business related topics that you need to know, can use and get started with now. Einstein’s KISS explained simply:
“If you can’t explain it simply, you don’t understand it well enough.”
- Albert Einstein
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Out-of-the-box A.I. enabled marketing solutions is a saturated market. I currently track and profile 128 best-in-class such companies. “The hype machine is in full swing” per the first article below. Yet, same says “AI will undeniably be the intelligence backbone of likely all technology systems at some future time”. Examples of A.I. ready marketing & sales solutions: ➧ Churn prediction & smart customer engagement ➧ AI-powered content creation ➧ AI-enhanced PPC advertising & Ad targeting ➧ AI-powered customer insights ➧ Predictive customer service Below are 5 low-tech articles worth scanning. Sales & marketing A.I. automation is a favorite topic of mine and will explore more in upcoming issues. Ask Me a Question: CLICK HERE
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➥ Artificial Intelligence is Here: 5 Brands Using AI
- Is A.I. for Marketing All Hype? Click Here- When A.I. Becomes the New Face of Your Brand Click Here- A.I. Will Disrupt Brand Building As We Know It Click Here- How A.I. & Technology Drive Brand Storytelling Click Here- Five Laws of Branding A.I. Click Here
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➥ What is an algorithm and why should you care?
A great 5 min. Khan Academy video explaining what an algorithm is. Note, not all algorithms are Machine Learning algorithms and we will explore what makes the difference. This discussion is a follow-up to my “Food for thought” quote in issue #2 copied below:
“If company A has algorithms (software) that are manually improved by software engineers, and company B has Ai algorithms (software that can self-improve, ie, learns from data) at an increasing rate, company B wins.”
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Algorithm Definition: A step-by-step procedure for solving a problem or accomplishing some end especially by a computer.
An Algorithm But Not Machine Learning: Given a list of positive numbers, return the largest number on the list. Pretty straightforward procedure for solving for maximum. Is the 1st # larger than the 2nd, if yes, discard #2 and, repeat.
Simplest Machine Learning (ML) Algorithm: Given the 4 data points in the below chart, find the best-fitting straight line through the points so that the line minimized the distance all the points are from the line. The algorithm to solve this is called “linear regression” and the technical term that qualifies this as a machine learning algorithm is “optimizing a loss function”. Once the computer has learned the best fitting line based on a training data set, you can then predict Y given a new X value. For example, X is square feet of a house, Y is the price. ML algorithms get much more complex and there is a debate whether linear regression is really a ML algorithm or just statistics. The answer is, yes, according to this article Click Here. At any rate, all machine learning algorithms, simple or complex, need good data, lots of it, to be trained. Read next section “Show me the data!”.
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➥ Why “Big Data” Is a Big Deal
Big Data, Data Lakes, Data Warehouses, Data Science, Data Engineering… all these technologies came about to help an organization to better and more economically retain, store, organize and prepare ALL the data a company generates from social, mobile, web, logs, emails, documents, devices… so that Machine Learning systems can extract insight from this ocean of data. UBER, for the first time, this month published a detailed article how it is building its insight engine from the massive data it gathers: NOT SO LOW-TECH
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About Author | everymans.ai
I manage a group of machine learning and data scientist professionals at Everymans.ai, a boutique marketing, and Ai enabling consultancy. We help companies quickly exploit marketing opportunities by building AI-enabled Minimum Viable Products (MVP) that will differentiate their products and services to gain a competitive edge with Ai. Have an early stage Ai startup looking for advice, investment or want to explore your MVP ideas, I’d love to hear from you.
Email me at info (at) everymans.ai
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http://Linkedin.com/in/Georgepolzer
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