Transformer models have proven to be especially powerful for Natural Language Processing applications and image generation, and have been popularized by models such as GPT-3, Stable diffusion, and BERT. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the term Transformer Networks, explain how these terms relate to AI and why it’s important to know about them. Continue reading AI Today Podcast – AI Glossary Series: Transformer Networks at Cognilytica....
Jun 02, 2023•12 min•Season 6Ep. 341
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the term Boltzmann Machine, explain how these terms relate to AI and why it’s important to know about them. Want to dive deeper into an understanding of artificial intelligence, machine learning, or big data concepts? Want to learn how to apply AI and data using hands-on approaches and the latest technologies? Continue reading AI Today Podcast: AI Glossary Series – Boltzmann Machine at Cognilytica....
May 31, 2023•10 min•Season 6Ep. 340
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Decoder, AutoEncoder, Generative Adversarial Network (GAN), explain how these terms relate to AI and why it’s important to know about them. Want to dive deeper into an understanding of artificial intelligence, machine learning, or big data concepts? Continue reading AI Today Podcast: AI Glossary Series – Encoder-Decoder, AutoEncoder, and Generative Adversarial Network (GAN) at Cognilytica....
May 26, 2023•12 min•Season 6Ep. 339
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the term Convolutional Neural Network (CNN), explain how these terms relate to AI and why it’s important to know about them. Want to dive deeper into an understanding of artificial intelligence, machine learning, or big data concepts? Want to learn how to apply AI and data using hands-on approaches and the latest technologies? Continue reading AI Today Podcast: AI Glossary Series – Convolutional Neural Network ...
May 24, 2023•14 min•Season 6Ep. 338
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Recurrent Neural Networks (RNN) and Long-Short Term Memory (LSTM), explain how these terms relate to AI and why it’s important to know about them. Want to dive deeper into an understanding of artificial intelligence, machine learning, or big data concepts? Continue reading AI Today Podcast: AI Glossary Series – Recurrent Neural Networks (RNN) and Long-Short Term Memory (LSTM) at Cognilytica....
May 19, 2023•11 min•Season 6Ep. 337
Usually used as a simple example for how deep learning neural networks work, a feed-forward neural network is the most basic, “vanilla” general kind of neural network. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the term Feed-Forward Neural Network, explain how these terms relate to AI and why it’s important to know about them. Continue reading AI Today Podcast: AI Glossary Series – Feed-Forward Neural Network at Cognilytica....
May 17, 2023•9 min•Season 6Ep. 336
In order for machine learning systems to work, they need to be trained on data. But there are different types of data and depending on the situation you may want to use one type of data over another, or a combination of different types. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms “Ground Truth” Data and Synthetic Data, explain how these terms relate to AI and why it’s important to know about them. Continue reading AI Today Podcast: AI Glossary ...
May 12, 2023•10 min•Season 6Ep. 335
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Pre-Trained Model and Transfer Learning, explain how these terms relate to AI and why it’s important to know about them. Want to dive deeper into an understanding of artificial intelligence, machine learning, or big data concepts? Continue reading AI Today Podcast: AI Glossary Series – Pre-Trained Model and Transfer Learning at Cognilytica....
May 10, 2023•9 min•Season 6Ep. 334
As AI applications become more complex and data-intensive, the need for scalable and efficient storage solutions becomes increasingly important. AI models require vast amounts of data to be processed, and as the size and complexity of these models continue to grow, so does the need for more storage. Storage considerations are critical for both the training and the deployment of AI models. Continue reading AI Today Podcast: Why Data Storage Matters When it Comes to AI: Interview with Justin Emers...
May 08, 2023•30 min•Season 6Ep. 333
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms CPU, GPU, TPU, and Federated Learning, explain how these terms relate to AI and why it’s important to know about them. Want to dive deeper into an understanding of artificial intelligence, machine learning, or big data concepts? Continue reading AI Today Podcast: AI Glossary Series – CPU, GPU, TPU, and Federated Learning at Cognilytica....
May 05, 2023•11 min•Season 6Ep. 332
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Tokenization and Vectorization, explain how these terms relates to AI and why it’s important to know about them. Want to dive deeper into an understanding of artificial intelligence, machine learning, or big data concepts? Want to learn how to apply AI and data using hands-on approaches and the latest technologies? Continue reading AI Today Podcast: AI Glossary Series – Tokenization and Vectorization ...
May 03, 2023•11 min•Season 6Ep. 332
In order for machine learning systems to work they need to be trained on data. But as the old saying goes “garbage in is garbage out” so you need to make sure you have a dataset of prepared data that is cleaned so you can incrementally train a machine learning model to perform a particular task. Continue reading AI Today Podcast: AI Glossary Series – Training Data, Epoch, Batch, Learning Curve at Cognilytica....
Apr 28, 2023•12 min•Season 6Ep. 331
Backpropagation was one of the innovations by Geoff Hinton that made deep learning networks a practical reality. But have you ever heard of that term before and know what it is at a high level? In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Backpropagation, Learning Rate, and Optimizer, explain how these terms relates to AI and why it’s important to know about them. Continue reading AI Today Podcast: AI Glossary Series – Backpropagation, Learning ...
Apr 26, 2023•11 min•Season 6Ep. 330
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Loss Function, Cost Function and Gradient Descent, explain how these terms relates 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 Intelligence Glossary Series: Artificial General Intelligence (AGI), Strong AI, Weak AI, Narrow AI Glossary Series: Heuristic & Brute-force Search AI Gloss...
Apr 21, 2023•13 min•Season 6Ep. 329
Deep Learning is powering this current wave of AI interest. But do you really know what Deep Learning is? In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms hidden layer and deep learning, explain how these terms relates to AI and why it’s important to know about them. Continue reading AI Today Podcast: AI Glossary Series- Hidden Layer and Deep Learning at Cognilytica....
Apr 19, 2023•12 min•Season 6Ep. 328
The Perceptron was the first artificial neuron. The theory of the perceptron was first published in 1943 by McCulloch & Pitts, and then developed in 1958 by Rosenblatt. So yes, this was developed in the early days of AI. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the term Perceptron and explain how the term relates to AI and why it’s important to know about it. Continue reading AI Today Podcast: AI Glossary Series – Perceptron at Cognilytica....
Apr 14, 2023•13 min•Season 6Ep. 327
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Bias, Weight, Activation Function, Convergence, and ReLU and explain how they 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 AI Glossary Series – Machine Learning, Algorithm, Model Glossary Series: Machine Learning Approaches: Supervised Learning, Unsupervised Learning, Reinforcement Learning Glossary Ser...
Apr 12, 2023•13 min•Season 6Ep. 326
If we can replicate neurons and how they are connected, can we replicate the behavior of our brains? In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms (Artificial) Neural Networks, Node, and layer, and explain how they relate to AI and why it’s important to know about them. Continue reading AI Today Podcast: AI Glossary Series – (Artificial) Neural Networks, Node (Neuron), Layer at Cognilytica....
Apr 07, 2023•14 min•Season 6Ep. 325
For a number of reasons, it can be important to reduce the number of variables or identified features in input training data so as to make training machine learning models faster and more accurate. But what are the techniques for doing this? In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Feature Reduction, Principal Component Analysis (PCA), and t-SNE, explain how they relate to AI and why it’s important to know about them. Continue reading AI Tod...
Apr 05, 2023•11 min•Season 6Ep. 324
For time-consuming parts of the machine learning workflow people often look for tricks and techniques to help speed up the process. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms feature and feature engineering, explain how they relate to AI and why it’s important to know about them. Continue reading AI Today Podcast: AI Glossary Series – Feature and Feature Engineering at Cognilytica....
Mar 31, 2023•11 min•Season 6Ep. 323
Regression is a statistical and mathematical technique to find the relationship between two or more variables. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Regression and Linear Regression and explain how they 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 AI Glossary Series – Machine Learning, Algorithm, Model Glossary Series: Machine Learning Appr...
Mar 29, 2023•8 min•Season 6Ep. 322
The idea of grouping similar types of data together is the main idea behind clustering. Clustering supports the goals of Unsupervised Learning which is finding patterns in data without requiring labeled datasets. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Clustering, Cluster Analysis, K-Means, and Gaussian Mixture Model, and explain how they relate to AI and why it’s important to know about them. Continue reading AI Today Podcast: AI Glossary ...
Mar 24, 2023•12 min•Season 6Ep. 321
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define DeepBlue, including what it is and why it’s notable for AI. Show Notes: FREE Intro to CPMAI mini course CPMAI Training and Certification AI Glossary AI Glossary Series – Symbolic Systems & Expert Systems AI Glossary Series: Cognitive Technology Continue reading AI Today Podcast: AI Glossary Series – Deep Blue at Cognilytica....
Mar 22, 2023•9 min•Season 6Ep. 320
Before this latest wave of AI where neural nets became the hottest algorithm of choice, an approach to machine learning that uses logic and constructs similar to the way that humans reason through problems called Symbolic Systems were actually the system of choice. Popularized in the late 1980s and early 1990s expert systems became the AI system of choice for organizations investing in cognitive technology. Continue reading AI Today Podcast: AI Glossary Series: Symbolic Systems & Expert Systems ...
Mar 17, 2023•Season 6Ep. 319
Sometimes for reasons such as improving performance or robustness it makes sense to create multiple decision trees and average the results to solve problems related to overfitting. Or, it makes sense to boost certain decision trees. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Random Forest and Boosted Trees, and explain how they relate to AI and why it’s important to know about them. Continue reading AI Today Podcast: AI Glossary Series – Rando...
Mar 15, 2023•9 min•Season 6Ep. 318
Sometimes for reasons such as improving performance or robustness it makes sense to combine the results of multiple different models trained on the same data. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the term Ensemble Models, and explain how it relates to AI and why it’s important to know about them. Continue reading AI Today Podcast: AI Glossary Series – Ensemble Models at Cognilytica....
Mar 10, 2023•8 min•Season 6Ep. 317
There are many algorithms that can be used for classification and it’s important to at least know them at a high level. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Support Vector Machine & Kernel Method, and explain how they relate to AI and why it’s important to know about them. Continue reading AI Today Podcast: AI Glossary Series – Decision Trees at Cognilytica....
Mar 08, 2023•11 min•Season 6Ep. 316
There are many algorithms that can be used for classification and it’s important to at least know them at a high level. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Support Vector Machine & Kernel Method, and explain how they relate to AI and why it’s important to know about them. Continue reading AI Today Podcast: AI Glossary Series – Support Vector Machine & Kernel Method at Cognilytica....
Mar 03, 2023•9 min•Season 6Ep. 315
There are many algorithms that can be used for classification and it’s important to at least know them at a high level. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms K-Nearest Neighbor and Lazy Learning, and explain how they relate to AI and why it’s important to know about them. Continue reading AI Today Podcast: AI Glossary Series: K-Nearest Neighbor and Lazy Learning at Cognilytica....
Mar 01, 2023•8 min•Season 6Ep. 314
Probabilities play a big part in AI and machine learning. After all, AI systems are Probabilistic systems that must learn what to do. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Bayes’ Theorem, Bayesian Classifier, Naive Bayes, and explain how they relate to AI and why it’s important to know about them. Continue reading AI Today Podcast: AI Glossary Series – Bayes’ Theorem, Bayesian Classifier, Naive Bayes at Cognilytica....
Feb 24, 2023•17 min•Season 6Ep. 313
