Artificial Intelligence, Machine Intelligence, and Machine Learning are hot buzzwords today and they are, sometimes used interchangeably.
The perception that they are the same often leads to some confusion. But, under the covers, they are different. ML and MI do not get as much attention as AI, yet they are the underlying enablers of it. As they evolve, the differences will become more obvious and this webinar will unpack not only AI but MI and ML as well.
This presentation takes a look at these platforms, what they are, and how they differ. Their infusion into platforms such as ChapGPT, social media, industry, and societal segments change the landscape as significantly as the splitting of the atom.
WHY SHOULD YOU ATTEND?
To give the attendee an unbiased understanding of the AI/MI/ML and the deep learning landscape. This is a semi-deep dive into the elements of AI, what they are, how they differ, and what components make it up. The key takeaway is to understand what it is, and what it is not.
AREA COVERED
- AI
- MI
- ML
- Deep learning
- Underlying principles of the components and elements
- Structuring of data
- Use cases
- Methodologies (how things flow and how the various elements come together)
- Limitations
- How big data plays into it
LEARNING OBJECTIVES
- Defining AI and its tangential elements (ML and MI)
- Use cases for each
- How are functions (algorithms, models)
- Deep learning
- Methodologies and techniques
- Neural networks
- The AI case for big data
- AI Chat
WHO WILL BENEFIT?
- Technical - engineers
- Semi-technical – product managers, technicians
- Non–technical – C-level, Sales, and marketing (to gain a fundamental knowledge of the technology)
- Students
- IT individuals
- Teachers
- Social media
To give the attendee an unbiased understanding of the AI/MI/ML and the deep learning landscape. This is a semi-deep dive into the elements of AI, what they are, how they differ, and what components make it up. The key takeaway is to understand what it is, and what it is not.
- AI
- MI
- ML
- Deep learning
- Underlying principles of the components and elements
- Structuring of data
- Use cases
- Methodologies (how things flow and how the various elements come together)
- Limitations
- How big data plays into it
- Defining AI and its tangential elements (ML and MI)
- Use cases for each
- How are functions (algorithms, models)
- Deep learning
- Methodologies and techniques
- Neural networks
- The AI case for big data
- AI Chat
- Technical - engineers
- Semi-technical – product managers, technicians
- Non–technical – C-level, Sales, and marketing (to gain a fundamental knowledge of the technology)
- Students
- IT individuals
- Teachers
- Social media
Speaker Profile
Ernest Worthman
Ernest Worthman is an analyst and SME in several segments of high technology and the VP of content and Technology for AGL Information and Technology, LLC.He is also a nationally and internationally published technical editor/writer for wireless, semiconductor, cybersecurity, and other industries and regularly speaks at industry events.As well, he is a guest lecturer at Colorado State University’s College of Electrical Engineering.Ernest has over 25 years of experience in high-tech print and online publishing. He has held several editorial positions across several high-tech publications including Semiconductor Engineering’s cybersecurity and Internet of Everything/Everyone (IoX) channels, Editor of RF Design, Editorial Director …
Upcoming Webinars
HIPAA Compliance in 2026 — Practical Strategies for Breach …
Launch Your Career: The Ultimate Guide for Emerging Profess…
Moving From an Operational Manager to a Strategic Leader
Discover how Emotional Intelligence turns AI from a technic…
Dealing With Difficult People: At Work & In Life
I-9 Audits: Strengthening Your Immigration Compliance Strat…
Empowering Conflict Resolution: Letting Go to Gain Control
The 60 Minutes Introduction to DAX
The 6 Most Common Problems in FDA Software Validation and V…
High-Impact Performance Management: Tools, Tactics & Coachi…
AI Across the Business: Practical Use Cases for Founders an…
Faster, Better Talent Acquisition: Leveraging AI & ChatGPT …
The Anti-Kickback Statute: Enforcement and Recent Updates
Do's and Don'ts of Giving Effective Feedback for Performanc…
Emotional Intelligence: Mastering the Emotions of Great Lea…
Copilot and HR: An Introduction for HR Professionals
Goal Mastery: From Resolutions to Results in 2026
Your AI Advantage: How HR Professionals Can Use Claude to S…
Human Error Reduction Techniques for Floor Supervisors
Validation of FDA-Regulated Medical Device and SaMD Product…
Human Factors Usability Studies Following ISO 62366 and FDA…
Managing Toxic & Other Employees Who Have Attitude Issues
I-9 Enforcement & Compliance: A 5-Step Plan for Employers t…
Major cGMP Issues: FDA Concerns in 2026
4-Hour Virtual Seminar on Transformational Leadership - The…
Understanding EBITDA – Definition, Formula & Calculation
DOL Reverses Course on Independent Contractor Rule for 2026…
Managing Toxic Employees: Strategies For Leaders To Effecti…
ChatGPT and Project Management: Leveraging AI for Project M…
Navigating HR Like A Pro: What Every Small Business & New H…
HPLC Analytical Method Development and Validation
Negotiating Skills For Professional Results - Winning Strat…
Managing Projects When AI Joins the Team: Human Judgment, A…
Excel Spreadsheets; Develop and Validate for 21 CFR Part 11…
Paying and Receiving Payments for Referrals: You Can Go to …
Ten Red Flags that Signal Financial Distress in Business Cu…
The Age-Inclusive Workplace: How to Lead and Work Across Ge…
Tattoos, hijabs, piercings, and pink hair: The challenges …
Fatal Errors Employers Make When Updating Employee Handbook…
AI Fundamentals for All Leaders and Managers: How to Work S…