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The Practical AI Digest

Mo Bhuiyan via NotebookLM
Machine Learning
Artificial Intelligence
Generative Adversarial Networks
Graph Neural Networks
AI and Machine Learning
Image Generation
Large Language Models
Agentic AI
Impact-E Framework
Data Preparation
Loss Functions
Data Structures
Marketing Mix Modeling
Hyperparameters
Reinforcement Learning
AI Applications
Tool Use
Chip Design
Navigation Systems
Gpt-3

Distilling AI/ML theory into practical insights. One concept at a time. No jargon.

PublishesTwice monthlyEpisodes20Foundeda year ago
Number of ListenersCategory
Technology

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Artwork for The Practical AI Digest

Latest Episodes

Building an AI model is one thing: keeping a large language model running reliably in the real world is another. In this episode, we discuss LLMOps, the emerging set of practices and tools for deploying, monitoring, and maintaining large language mod... more

In this episode, we explore how AI is moving from the cloud to tiny devices. TinyML is the field of optimizing models and algorithms to run on microcontrollers, smartphones, and other edge devices with very limited compute and power. We discuss techn... more

This episode is all about the specialized hardware that makes modern AI possible. We explain how GPUs became the workhorses of deep learning by offering massive parallelism for matrix math, and how companies like Google went further to build TPUs (Te... more

In this episode, we explore how synthetic data is created and used to improve AI models. Synthetic data refers to artificial datasets generated by models (like GANs or language models) that mimic real data. We discuss how this can help in situations ... more

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Recent Guests

Kula Rao
author associated with the successor paper to Laura
Episode: Efficient Fine-Tuning: Adapting Large Models on a Budget

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Apple Podcasts
#54
Indonesia/Technology

Talking Points

Recent interactions between the hosts and their guests.

How Embeddings and Vector Databases Power Generative AI
Q: How do we extract information from video content effectively?
The extraction process starts with automatic speech recognition to transcribe audio and then key visual frames are identified for further processing.
How Embeddings and Vector Databases Power Generative AI
Q: Let's talk about Retrieval Augmented Generation, or RAG.
RAG is crucial for allowing AI models to pull in current specific information rather than just relying on prior training.

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Frequently Asked Questions About The Practical AI Digest

What is The Practical AI Digest about and what kind of topics does it cover?

A technology-focused show that distills AI and machine learning concepts into practical, approachable insights. Across recent episodes, the hosts and guests tend to unpack how modern AI tools work in real settings—from interpreting complex models with practical explainability techniques to implementing efficient fine-tuning, multimodal systems, and code-assisted development. Listeners can expect clear explanations of hands-on techniques, concrete trade-offs, and pragmatic guidance for deploying AI responsibly in engineering, product, and data science roles. The program often highlights tooling, benchmarks, and real-world pitfalls, making it a useful resource for engineers and product leaders who want to stay current without getting lost in ... more

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Which podcasts are similar to The Practical AI Digest?

These podcasts share a similar audience with The Practical AI Digest:

1. Everyday AI Podcast – An AI and ChatGPT Podcast
2. The AI Daily Brief: Artificial Intelligence News and Analysis
3. AI Today Podcast
4. The Joe Rogan Experience
5. Up First from NPR

How many episodes of The Practical AI Digest are there?

The Practical AI Digest launched a year ago and published 20 episodes to date. You can find more information about this podcast including rankings, audience demographics and engagement in our podcast database.

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Recent guests on The Practical AI Digest include:

1. Kula Rao

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