How digital assistants like Siri work #shorts

Jay Alammar · Beginner ·📐 ML Fundamentals ·3y ago

Key Takeaways

This video explains how digital assistants like Siri work using multiple machine learning systems

Full Transcript

ever wonder how siri works let's look digital assistants like siri are a good showcase for a machine learning system let's ask siri a question when was ai invented artificial intelligence was formed in 1956 this actually demonstrated multiple machine learning systems working together the first system took the audio and turned it into text this is a speech-to-text ml system then the text was handed to a language processing system to decide what to do with it that system determined that the text is a question and decided to search for an answer search is a third ml system which is able to find an answer to this question and a final text-to-speech system turns the text into an audio as if a human was speaking it

Original Description

Multiple machine learning systems work together to make something like Siri work. This is a look at how we may build a simple version of Siri or Alexa. The actual systems have a lot more parts and complexity though. It's useful to get a general sense of the main parts though #shorts
Watch on YouTube ↗ (saves to browser)
Sign in to unlock AI tutor explanation · ⚡30

Playlist

Uploads from Jay Alammar · Jay Alammar · 18 of 38

1 Jay's Visual Intro to AI
Jay's Visual Intro to AI
Jay Alammar
2 Making Money from AI by Predicting Sales - Jay's Intro to AI Part 2
Making Money from AI by Predicting Sales - Jay's Intro to AI Part 2
Jay Alammar
3 How GPT3 Works - Easily Explained with Animations
How GPT3 Works - Easily Explained with Animations
Jay Alammar
4 The Narrated Transformer Language Model
The Narrated Transformer Language Model
Jay Alammar
5 My Visualization Tools (my Apple Keynote setup for visualizations and animations)
My Visualization Tools (my Apple Keynote setup for visualizations and animations)
Jay Alammar
6 Explainable AI Cheat Sheet - Five Key Categories
Explainable AI Cheat Sheet - Five Key Categories
Jay Alammar
7 The Unreasonable Effectiveness of RNNs (Article and Visualization Commentary) [2015 article]
The Unreasonable Effectiveness of RNNs (Article and Visualization Commentary) [2015 article]
Jay Alammar
8 Neural Activations & Dataset Examples
Neural Activations & Dataset Examples
Jay Alammar
9 Up and Down the Ladder of Abstraction [interactive article by Bret Victor, 2011]
Up and Down the Ladder of Abstraction [interactive article by Bret Victor, 2011]
Jay Alammar
10 Probing Classifiers: A Gentle Intro (Explainable AI for Deep Learning)
Probing Classifiers: A Gentle Intro (Explainable AI for Deep Learning)
Jay Alammar
11 Inspecting Neural Networks with CCA - A Gentle Intro (Explainable AI for Deep Learning)
Inspecting Neural Networks with CCA - A Gentle Intro (Explainable AI for Deep Learning)
Jay Alammar
12 Language Processing with BERT: The 3 Minute Intro (Deep learning for NLP)
Language Processing with BERT: The 3 Minute Intro (Deep learning for NLP)
Jay Alammar
13 Behavioral Testing of ML Models (Unit tests for machine learning)
Behavioral Testing of ML Models (Unit tests for machine learning)
Jay Alammar
14 Favorite AI/ML Books: Intro to ML with Python (Book Review)
Favorite AI/ML Books: Intro to ML with Python (Book Review)
Jay Alammar
15 Favorite Python Books: Effective Python
Favorite Python Books: Effective Python
Jay Alammar
16 Favorite Stats Books: Seven Pillars of Statistical Wisdom
Favorite Stats Books: Seven Pillars of Statistical Wisdom
Jay Alammar
17 Understanding Animal Languages - Seeing Voices 2
Understanding Animal Languages - Seeing Voices 2
Jay Alammar
How digital assistants like Siri work #shorts
How digital assistants like Siri work #shorts
Jay Alammar
19 Writing Code in Jupyter Notebooks #shorts
Writing Code in Jupyter Notebooks #shorts
Jay Alammar
20 Experience Grounds Language: Improving language models beyond the world of text
Experience Grounds Language: Improving language models beyond the world of text
Jay Alammar
21 pandas for data science in python #shorts
pandas for data science in python #shorts
Jay Alammar
22 The Illustrated Retrieval Transformer
The Illustrated Retrieval Transformer
Jay Alammar
23 AI Image Generation is MIND BLOWING! #shorts
AI Image Generation is MIND BLOWING! #shorts
Jay Alammar
24 A Generalist Agent (Gato) - DeepMind's single model learns 600 tasks
A Generalist Agent (Gato) - DeepMind's single model learns 600 tasks
Jay Alammar
25 The Illustrated Word2vec - A Gentle Intro to Word Embeddings in Machine Learning
The Illustrated Word2vec - A Gentle Intro to Word Embeddings in Machine Learning
Jay Alammar
26 AI Art Explained: How AI Generates Images (Stable Diffusion, Midjourney, and DALLE)
AI Art Explained: How AI Generates Images (Stable Diffusion, Midjourney, and DALLE)
Jay Alammar
27 What is Generative AI? 4 Important Things to Know (about ChatGPT, MidJourney, Cohere & future AIs)
What is Generative AI? 4 Important Things to Know (about ChatGPT, MidJourney, Cohere & future AIs)
Jay Alammar
28 AI is Eating The World - This is Where YOU Can Use it to Compete (AI Product Moats)
AI is Eating The World - This is Where YOU Can Use it to Compete (AI Product Moats)
Jay Alammar
29 What is LangChain? Where does it fit with LLMs like ChatGPT and Cohere? #shorts
What is LangChain? Where does it fit with LLMs like ChatGPT and Cohere? #shorts
Jay Alammar
30 Are language models with more parameters better? #shorts #chatgpt
Are language models with more parameters better? #shorts #chatgpt
Jay Alammar
31 How to manage LLM prompts with tools like LangChain #languagemodels #chatgpt
How to manage LLM prompts with tools like LangChain #languagemodels #chatgpt
Jay Alammar
32 What is Llama Index? how does it help in building LLM applications? #languagemodels #chatgpt
What is Llama Index? how does it help in building LLM applications? #languagemodels #chatgpt
Jay Alammar
33 prompt chains are important for building large language model applications
prompt chains are important for building large language model applications
Jay Alammar
34 ChatGPT has Never Seen a SINGLE Word (Despite Reading Most of The Internet). Meet LLM Tokenizers.
ChatGPT has Never Seen a SINGLE Word (Despite Reading Most of The Internet). Meet LLM Tokenizers.
Jay Alammar
35 What makes LLM tokenizers different from each other? GPT4 vs. FlanT5 Vs. Starcoder Vs. BERT and more
What makes LLM tokenizers different from each other? GPT4 vs. FlanT5 Vs. Starcoder Vs. BERT and more
Jay Alammar
36 Building LLM Agents with Tool Use
Building LLM Agents with Tool Use
Jay Alammar
37 SWE-Bench authors reflect on the state of LLM agents at Neurips 2024
SWE-Bench authors reflect on the state of LLM agents at Neurips 2024
Jay Alammar
38 Learn how ChatGPT and DeepSeek models work: How Transformer LLMs Work [Free Course]
Learn how ChatGPT and DeepSeek models work: How Transformer LLMs Work [Free Course]
Jay Alammar

Related Reads

📰
Reproducing OpenAI’s “persistently beneficial models” - GRPO trait install barely moves. Ideas? [P] [R]
Reproduce OpenAI's persistently beneficial models by troubleshooting GRPO trait installation with small-scale RL
Reddit r/MachineLearning
📰
Mixture Density Networks
Learn how Mixture Density Networks can improve prediction models for complex tasks like self-driving cars
Medium · Machine Learning
📰
How to Crack Technical Interviews as a Fresher
Learn strategies to crack technical interviews as a fresher and increase your chances of landing your first job in the tech industry
Dev.to · Subhalaxmi Paikaray
📰
Programming Assignments: A Complete Guide to Solving Coding Problems Faster and Smarter
Learn to solve coding problems faster and smarter with a complete guide to programming assignments
Medium · Programming
Up next
SQLite3 Tutorial - Learn SQL for Python in 17 Minutes
Thomas Janssen
Watch →