Expert system

Expert Systems Lesson 1 - Using an expert system

In this lesson we talk about what an expert system is and we also use the expert system I have created to get a feel of what an expert system does. Subtitles: English Link to expert system used in video:http://magicmonktutorials.com/IT/expertsystem/index.html Link to lesson 2: https://w

From playlist Expert Systems / Robotics

Expert Systems lesson 2 - What makes up an Expert System

In this lesson we take a deeper look at what makes up an Expert System - The Knowledge Base, the Inference Engine, and the shell program. We explain each one in detail with examples. Subtitles: English Topic covered in: Year 11 IPT Course, Queensland, Australia

From playlist Expert Systems / Robotics

Expert System Components

From playlist Decision Support Systems

Expert Systems Lesson 3 - Building an expert system with ES Builder

In this lesson we take you through how to build your own expert system with ES-Builder. The download link for ES-Builder is: http://www.mcgoo.com.au/html/es3_download.php Note: All of my links are obtained at the time I made the video. I cannot make guarantees that the link will work forev

From playlist Expert Systems / Robotics

System Design Interview: A Step-By-Step Guide

Learn something new every week by subscribing to our newsletter: https://bit.ly/3tfAlYD Checkout our bestselling System Design Interview books: Volume 1: https://amzn.to/3Ou7gkd Volume 2: https://amzn.to/3HqGozy ABOUT US: Covering topics and trends in large-scale system design, from th

From playlist System Design Interview

Expert System Advantages (1 of 2)

From playlist Decision Support Systems

Stanford Seminar - Universal Intelligent Systems by 2030 - Carl Hewitt and John Perry

Carl Hewitt of MIT and John Perry of Stanford discuss Universal Intelligent Systems. This talk was given on January 5, 2022. Universal Intelligent Systems (UIS) will encompass everything manufactured and every sensed activity. Every device used at home and work will be included as well a

From playlist Stanford EE380-Colloquium on Computer Systems - Seminar Series

What Are Reactive Systems?

Reactive Systems use a high-performance software architecture. They are resilient under stress, and their reactive design allows them to scale elastically to meet demand. The reactive design approach allows the creation of more complex, more flexible systems and forms the basis for some of

From playlist Software Engineering

Security Licence Expert System (2 of 2)

From playlist IPT2013

The Computer Chronicles - Fifth Generation Computers (1984)

Special thanks to archive.org for hosting these episodes. Downloads of all these episodes and more can be found at: http://archive.org/details/computerchronicles

From playlist The Computer Chronicles 1984 Episodes

GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding (Paper Explained)

Google builds a 600 billion parameter transformer to do massively multilingual, massive machine translation. Interestingly, the larger model scale does not come from increasing depth of the transformer, but from increasing width in the feedforward layers, combined with a hard routing to pa

From playlist Papers Explained

Nickel City Ruby 2014- How To Not Be An Expert

By, Jen Myers Help us caption & translate this video! http://amara.org/v/F1kZ/

From playlist Nickel City Ruby 2014

Decision making model based on expert evaluations - Cristina Zuheros Montes

About the conference: The 1st International ‘Turing’ conference on decision support and recommender systems will bring together junior and experienced researchers, industry professionals and domain experts to discuss latest trends and ongoing challenges in: - Human and AI-driven complex

From playlist 1st International conference on decision support and recommender systems

OpenAI tackles Math - Formal Mathematics Statement Curriculum Learning (Paper Explained)

#openai #math #imo Formal mathematics is a challenging area for both humans and machines. For humans, formal proofs require very tedious and meticulous specifications of every last detail and results in very long, overly cumbersome and verbose outputs. For machines, the discreteness and s

From playlist Papers Explained

SETFIT Few-Shot Learning outperforms GPT-3 | SBERT Text Classification (SBERT 43)

NEW: SBERT Few-Shot Learning (SetFit) outperforms GPT-3 in text classification tasks. Few-shot learning without prompts: SetFit. Given a limited training sample set per class the new SetFit methodology based on SBERT Sentence Transformers perform exceptionally well in text classification.

From playlist SBERT: Python Code Sentence Transformers: a Bi-Encoder /Transformer model #sbert

Security Licence Expert System (1 of 2)

From playlist IPT2013