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Philip - AI Explained

This is aimed at absolutely anyone interested in AI, from c-suite and software engineers to curious parents and engaged amateurs. No technical background is necessary, as no matter your background you will leave much better informed about key (and controversial) terms in AI.

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This is aimed at absolutely anyone interested in AI, from c-suite and software engineers to curious parents and engaged amateurs. No technical background is necessary, as no matter your background you will leave much better informed about key (and controversial) terms in AI.

You will learn about 8 of the key terms used in AI - which are bandied around as if everyone should know them. Each term comes with complex and storied histories and implications, relevant to both practitioners and interested onlookers.

What does 'stochastic parrot' actually mean, and are LLMs merely parrots? Do language models actually 'reason' and has the idea of 'emergent behaviors' been debunked already? Why is the term 'open source' being replaced with 'open weights' and what on earth is meant by 'artificial general intelligence'? I challenge anyone to leave this short 3-5 hour course without a much more nuanced understanding of the key debates in AI.

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What's inside

Syllabus

Stochastic Parrot
Learn about a controversial label for LLMs, whether it holds up, and what on earth parrots have to do with it.
Emergent Behaviors
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Deciding if you think models display emergent behaviors could shape your perspective on AI, so take the time to learn why this term is so controversial.
Open Source
In some quarters, the most controversial term of them all. Here, we mainly focus on the difference between open source and open weights - a key distinction!
The 'Bitter Lesson'
You won’t (I hope) be bitter after learning about the bitter lesson - a seminal insight onto what works best in AI, and why.
Deep Dive - Reasoning
Now we’re getting deep. Reflecting on whether models actually ‘reason’ - and what that word actually means - or just pattern-match, is crucial for anyone interested in using AI.
Deep Dive - Hallucinations (+ Model Biases)
It’s easy to ‘know’ that models hallucinate and are biased, but actually exploring demonstrations on how they are, and how to minimise that, is a whole other matter - a matter we discuss in this deep dive!
'Takeoff' Speeds
‘Takeoff' and 'takeoff speeds' are terms worth learning about, even if they are deeply theoretical, and even if you disagree with the entire notion of a takeoff. The fact that these terms have led to debate even at CEO-level is enough to make it worth grasping their meaning, whichever 'side' you are on.
Artificial General Intelligence
Perhaps the most controversial term of them all. Whatever your stance is, knowing the origins, nuances and key positions on this term will serve you well.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Provides overview without requiring technical background
Geared toward individuals who want a general understanding of key AI terms and concepts
Led by instructor(s) who have knowledge and experience in AI
Introduces advanced concepts like reasoning and hallucination, providing a deeper understanding of AI
May not be suitable for individuals seeking a comprehensive or in-depth study of AI

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in 8 Most Controversial Terms in AI, Explained with these activities:
Review Open AI's Blog
Become familiar with the latest research and advancements in AI from a leading organization.
Browse courses on Artificial Intelligence
Show steps
  • Visit Open AI's blog
  • Read recent articles
  • Summarize key concepts
Identify AI Terminology
Test understanding by applying AI terminology accurately.
Show steps
  • Create a list of AI terms
  • Practice identifying each term in real-world examples
  • Use flashcards or online quizzes to test knowledge
Experiment with GPT-3 Playground
Gain practical experience using a cutting-edge AI tool.
Show steps
  • Explore the GPT-3 Playground website
  • Follow tutorials to create text, code, and images
  • Experiment with different parameters
Four other activities
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Develop a Glossary of AI Terms
Reinforce understanding by creating a resource that defines key AI concepts.
Show steps
  • Brainstorm a list of AI terms
  • Research each term to gather definitions
  • Organize the terms into a glossary
  • Illustrate the glossary with real-world examples
Discuss AI Case Studies
Share insights and learn from peers by analyzing real-world AI applications.
Show steps
  • Join or start a study group
  • Select relevant AI case studies
  • Analyze the case studies and identify key concepts
  • Discuss the findings with the group
  • Reflect on the discussions and apply the learnings
Contribute to an Open-Source AI Project
Gain hands-on experience in the AI community by collaborating on open-source projects.
Browse courses on Open Source
Show steps
  • Identify relevant open-source AI projects
  • Choose a project to contribute to
  • Follow the project's contribution guidelines
  • Submit code or documentation improvements
  • Engage with project maintainers and other contributors
Develop an AI-Powered Solution to a Real-World Problem
Apply AI principles and techniques to solve a practical problem.
Show steps
  • Identify a real-world problem
  • Research and gather data
  • Develop and train an AI model
  • Test and evaluate the model
  • Package the solution and submit a report

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