In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Machine Learning Development Languages: Python, R, Julia, Scala, explain how these terms relate to AI and why it's important to know about them.



Show Notes:




FREE Intro to CPMAI mini course



CPMAI Training and Certification



AI Glossary



Glossary Series: (Artificial) Neural Networks, Node (Neuron), Layer



Glossary Series: Hidden Layer, Deep Learning



Glossary Series: Loss Function, Cost Function & Gradient Descent



Glossary Series: Backpropagation, Learning Rate, Optimizer



Glossary Series: Feed-Forward Neural Network



AI Glossary Series - Machine Learning, Algorithm, Model



AI Glossary Series - Model Tuning and Hyperparameter



AI Glossary Series: Overfitting, Underfitting, Bias, Variance, Bias/Variance Tradeoff


AI Today Podcast: AI Glossary Series – Machine Learning Development Languages: Python, R, Julia, Scala

Technology

Tech News

Podcasting

Gadgets

Software How-To

The Four-Part AI-Enabled Vision of the Future



In 2018, when at the time we thought AI hype couldn’t get any more hype-y, we at Cognilytica spent time thinking about what the broad implications of AI would be on our individual lives, our business and work lives, and on society in general. This thinking led us to put together our four-part vision we called the “AI-Enabled Vision of the Future”. In this episode of AI Today hosts Kathleen Walch and Ron Schmelzer review our AI Enabled Vision of the Future and dive deep on what the world looks like when everything is AI enabled. What does it look like to have augmented and autonomous AI everything?



Autonomous or AI Enhanced?



In this episode we discuss that in the AI-enabled future, because AI is truly everywhere, even in things that it shouldn’t be in, that means AI will be in everything. Back in 2018, we discussed how autonomous everything will change the landscape around us. This was primarily because autonomous vehicles captured everyone’s attention. In this podcast we discuss the impact of autonomous vehicles on society and the urban landscape. But, autonomous isn't just about vehicles. We discuss what homes and interactions and experiences look like in an autonomous and AI-enhanced future. And we discuss what the future looks like with fully realized augmented intelligence.



Show Notes:




Free Intro to CPMAI course



CPMAI Certification



Subscribe to Cognilytica newsletter on LinkedIn



Cognilytica’s AI-Enabled Vision of the Future – UPDATED [AI Today Podcast]



Cognilytica’s AI-Enabled Vision of the Future: The AI-Enhanced Organization [AI Today Podcast]


Cognilytica’s AI-Enabled Vision of the Future: AI-Augmented Everything [AI Today Podcast]

The Four-Part AI-Enabled Vision of the Future



In 2018, when at the time we thought AI hype couldn’t get any more hype-y, we at Cognilytica spent time thinking about what the broad implications of AI would be on our individual lives, our business and work lives, and on society in general. This thinking led us to put together our four-part vision we called the “AI-Enabled Vision of the Future”. In this episode of AI Today hosts Kathleen Walch and Ron Schmelzer review our AI Enabled Vision of the Future and dive deep on what the AI-enhanced organization looks like.



The AI-Enhanced Organization of the Future



Already, AI is proving to be a massive enhancement and augmentation to the everyday work and tasks of businesses, enterprises, and organizations of all types. However, in the AI-enabled future, this will be accelerated on steroids. In this podcast we discuss what the acceleration of productivity using AI will look like. We discuss what organizations will look like with actual, intelligent, adaptive systems that can handle whatever is thrown at them to deal with the ever changing needs of moving data and information between systems. Forget dumb automation of today!



Also, we discuss what mass customization and personalization looks like. Hyperpersonalization will finally be achieved! And, we also discuss impacts to the workforce. The workforce of the AI-enabled future will not look like today’s workforce. Further, the organization of the future will not look like today’s organization. 



Overall, in the AI-enabled future, AI capabilities are available to the average person, and the self-employed become absolute powerhouses. The AI-enabled future workforce won’t be mass unemployed, but rather mass self-employed. Each individual will be armed with capabilities to multiply their skills and talents, and they will provide those skills to the organizations who can leverage them best. 



Subscribe and tune in to hear Cognilytica's thought leadership ideas around the organization of the future!



Show Notes:




Free Intro to CPMAI course



CPMAI Certification



Subscribe to Cognilytica newsletter on LinkedIn



Cognilytica’s AI-Enabled Vision of the Future – UPDATED [AI Today Podcast]



Who Is On The AI Team?






Cognilytica’s AI-Enabled Vision of the Future: The AI-Enhanced Organization [AI Today Podcast]

Back in 2018, when at the time we thought AI hype couldn’t get any more hype-y, we at Cognilytica spent time thinking about what the broad implications of AI would be on our individual lives, our business and work lives, and on society in general. This thinking led us to put together our four-part vision we called the “AI-Enabled Vision of the Future”. In this episode of AI Today hosts Kathleen Walch and Ron Schmelzer revisit our AI Enabled Vision of the Future and dive deep on updating for the realities of where AI is now and where things are heading.



The Four-Part AI-Enabled Vision of the Future



We see four major transformational movements impacting all aspects of our lives with AI. These include the AI-Enhanced Organization, Augmented (Autonomous) Everything, Enhancing the Human Experience, and Pervasive Knowledge. From Cognilytica’s perspective, we see AI as being an important, transformational change agent not only to the way business is done, but also to the way people live their daily lives. But, what does that future look like when everything has been transformed? In this episode we review each of these four parts on this podcast at a high level. And in future episodes we'll be digging deeper into each one so stay subscribed to AI Today.



Show Notes:




Free Intro to CPMAI course



CPMAI Certification



Subscribe to Cognilytica newsletter on LinkedIn



Who Is On The AI Team?


Cognilytica’s AI-Enabled Vision of the Future – UPDATED [AI Today Podcast]

Generative AI is one of the most accessible forms of AI currently available. While in the past, you might have used AI without knowing it, you can use Generative AI purposefully in ways that have immediate and dramatic impact on your daily life. In this episode of AI Today hosts Kathleen Walch and Ron Schmelzer discuss what soft skills are necessary to get what we want out of Generative AI.



Why are soft skills important in the age of AI?



The great thing about Generative AI, is that it doesn’t require “hard skills”. Hard skills include programming, math, analytics skills, database and data engineering skills, or anything else that requires specific education and years of training. You don’t need to be an expert in math skills such as Statistics & Probability, Calculus or Linear Algebra to get value from using Generative AI. You also don’t need to be skilled in using different Data Visualization tools. Nor do you need to have knowledge of different algorithms & modeling skills.



Rather, we can use our existing “soft skills” of communication, planning, creativity, and critical thinking to get what we want out of Generative AI. No surprise, soft skills are incredibly important when it comes to effective prompting, since hard skills aren’t used at all when creating prompts that interact with Generative AI systems. In this episode we go into detail on why these soft skills are so important and how they help you get better at prompt engineering.



Show Notes:




Free Intro to CPMAI course



CPMAI Certification



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Properly Scoping AI Projects [AI Today Podcast]



Prompt Engineering Best Practices: What is Prompt Chaining? [AI Today Podcast]



Prompt Engineering Best Practices: Using Custom Instructions [AI Today Podcast]



Prompt Engineering Best Practices: Hack and Track [AI Today Podcast]


Prompt Engineering Best Practices: Soft Skills [AI Today Podcast]

AI, and in particular generative AI, is having a profound impact on just about every industry. In this episode of AI Today hosts Kathleen Walch and Ron Schmelzer interview Saby Waraich to discuss AI's impact on Project Management. Saby is CIO at Clackamas Community College and and speaking at the PMI Austin, TX Professional Development Day May 2, 2024.



What impact will artificial intelligence (AI) have on the field of project management?



Saby shares with us how he is seeing Generative AI tools changing the role of project management. He also discusses why soft skills are so important. And, what soft skills are going to become most important for PMs in a generative AI world. As project managers continue to use GenAI and become more comfortable creating and iterating on prompts, the benefits will continue to increase.



How can a project manager use GenAI to improve power skills?



PMs already have many soft skills they leverage on a basis. Saby shares how PMs can leverage their skills such as communication, critical thinking, adaptability, and attention to detail to build conversational skills with AI. Saby shares first hand experiences about prompts he has currently used. And, how he is getting creative with his prompts and asks to LLMs. He also discusses why trust is so important. After all, if you're not trusting your AI tool, you probably won't want to use it.



Show Notes:




PMI Austin, TX Chapter



Free Intro to CPMAI course



CPMAI Certification



Subscribe to Cognilytica newsletter on LinkedIn



Properly Scoping AI Projects [AI Today Podcast]



Prompt Engineering Best Practices: What is Prompt Chaining? [AI Today Podcast]



Prompt Engineering Best Practices: Using Custom Instructions [AI Today Podcast]


AI Today Podcast: AI Glossary Series – Machine Learning Development Languages: Python, R, Julia, Scala

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