<ul><li>Objective: Teach viewers how to learn faster using 3 powerful principles </li><li>Proven Method: Creator graduated top of their master’s program, studying less than 10% of the time compared to peers </li><li>3 Key Principles:</li></ul><ol><li>Effort-Time Exchange</li><li>Omnilearner Principle</li><li>Iteration </li></ol><ul><li class="ql-align-justify">Widespread Success: Used to coach 30,000+ learners over 13 years with proven results </li></ul>

Intro

<ul><li>Put in more effort upfront to learn faster</li><li>Avoid shortcuts—learning needs active thinking</li><li>Passive tools (e.g. AI, notes) don’t build memory</li><li>Generation Effect: recalling boosts retention</li><li>Ask: Am I struggling enough to learn?</li><li>Boost struggle by:</li></ul><ol><li>Recalling before checking answers</li><li>Summarizing in your own words</li><li>Making connections between ideas</li></ol><ul><li class="ql-align-justify">🚀 Struggle smart = faster, deeper learning</li></ul>

Principle 1: Effort / Time Exchange:

<ul><li class="ql-align-justify">No fixed learning styles—VARK is a myth</li><li class="ql-align-justify">Brain processes visual info best</li><li class="ql-align-justify">Over-reliance on reading/writing can limit learning</li><li class="ql-align-justify">Be an omnilearner: adapt to all learning modes</li><li class="ql-align-justify">Ask: How can I organize this? while learning</li><li class="ql-align-justify">Organizing info boosts memory and efficiency</li><li class="ql-align-justify">Use active reading, diagram breakdowns, structured note-taking</li><li class="ql-align-justify">Identify your habits via a quiz to optimize learning</li><li class="ql-align-justify">Upgrade your system = faster learning</li></ul>

Principle 2: Omni-Learner Principle

<ul><li class="ql-align-justify">Iteration Effect = Learn by testing hypotheses</li><li class="ql-align-justify">Learning = Form ideas → test → refine</li><li class="ql-align-justify">Memorizing alone isn’t effective</li><li class="ql-align-justify">Test early and often to find gaps</li><li class="ql-align-justify">Schedule regular, challenging self-tests</li><li class="ql-align-justify">Use micro retrieval for instant feedback</li><li class="ql-align-justify">Apply new knowledge immediately (projects, problem-solving)</li><li class="ql-align-justify">On-the-job learning works because it forces real-time iteration</li></ul>

Principle 3: Iteration Effect

Master these 3 principles—Effort/Time Exchange, Omni-Learner Mindset, and the Iteration Effect—to learn faster, retain deeper, and apply smarter

In this video, I'll teach you how you can learn anything faster than everyone.

Learner Type Quiz (free) - Figure out your learning strengths and weaknesses: https://bit.ly/4iWWO4C

Join my Learning Drops newsletter (free): https://bit.ly/4j2l99i
Every week, I distil what really works for improving results, memory, depth of understanding, and knowledge application from over a decade of coaching into bite-sized emails.

Learning System Diagnostic (free) - See how the way you learn compares to top learners: https://bit.ly/4j0LDIe

The research behind efficient learning [Summary] (free): https://icanstudy.com/report-on-learning

Watch my TEDx talk on learning to learn (top 1% viewed in 2022): https://www.youtube.com/watch?v=TQXMl4GycD0 

=== Paid Training Program ===

Join my step-by-step learning skills program to improve your results: https://bit.ly/4lgzccA

(Designed for busy students and professionals aiming to achieve top results without endless studying. 77% of our students cover the same amount of study material in 30% less time within 1 month.)

=== Timestamps ===
0:00 - Intro
0:36 - Principle 1: Effort/Time Exchange
5:55 - Principle 2: Omni-Learner Principle
16:08 - Principle 3: Iteration Effect

=== About Dr Justin Sung ===
Dr. Justin Sung is a world-renowned expert in self-regulated learning, certified teacher, research author, and former medical doctor. He has guest lectured on learning skills at Monash University for Master’s and PhD students in Education and Medicine. Over the past decade, he has empowered tens of thousands of learners worldwide to dramatically improve their academic performance, learning efficiency, and motivation.

Instagram: https://instagram.com/drjustinsung
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Facebook: https://www.facebook.com/drjustinsung
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Understand yourself and those around you.

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Justin Sung is a former medical doctor, full-time learning coach and consultant, top 1% TEDx speaker, education author, and social entrepreneur. He has an MBChB and BMedSci (Hons - First Class) from the University of Auckland, and an MEd from Monash University. He is invited to hold workshops and lectures at Monash University and the University of Auckland, as well as for various organisations around the world.

He is the co-founder and Head of Learning at iCanStudy. iCanStudy developed the world's first cognitive retraining program focused on enhancing self-regulated higher-order learning and deep processing. Over the past decade, he has worked with over 10,000 learners from ages 10 to 80+ in over 120 countries. In the 7 years prior, Justin worked in the non-profit education and mentoring space for disadvantaged students.

Justin sees himself as a research-practice bridge, helping to connect dedicated learners and educators with critical applications of the research.


Justin Sung

How to Learn ANYTHING Faster Than Everyone

<ul><li class="ql-align-justify">Can be told in less than 60 seconds.</li><li class="ql-align-justify">Making conversations better with friends and family (or boss).</li><li class="ql-align-justify">The goal is to make every second count.</li></ul>

How to tell a Great Stories

<ul><li class="ql-align-justify">Will the answer keep people engaged until the end?</li><li class="ql-align-justify">Ask a shocking question to grab the audience's attention.</li><li class="ql-align-justify">Examples:</li></ul><ol><li class="ql-align-justify">How much ice cream can you get for a dollar?</li><li class="ql-align-justify">What is the cheapest thing in an airport?</li><li class="ql-align-justify">Is it faster to go inside or use the drive-through?</li></ol>

Start With a Question

<ul><li class="ql-align-justify">Build up to the answers to your questions.</li><li class="ql-align-justify">Make the audience feel a constant progression.</li><li class="ql-align-justify">Provide updates on progress.</li><li class="ql-align-justify">For example:</li></ul><ol><li class="ql-align-justify">In the video, the speaker was showing how she added ingredients to her burger while cooking in the car.</li></ol>

Take Your Audience on a Journey

<ul><li class="ql-align-justify">It Makes the Audience Invested in the Outcome.</li><li class="ql-align-justify">Can be Done by Introducing an Opposing Character or an Obstacle.</li><li class="ql-align-justify">Example:</li></ul><ol><li class="ql-align-justify">The Speaker's Mother Questioning the Actions of the Protagonist.</li></ol>

Adding Conflict to the Story is Crucial

<ul><li class="ql-align-justify">Build up to the initial question's answer</li><li class="ql-align-justify">Make the audience uncertain of the question's outcome</li><li class="ql-align-justify">Example:</li></ul><ol><li class="ql-align-justify">Audience wondering if a burger will be cooked faster than a drive-through</li></ol>

Build Up to a Satisfying Ending

<ul><li class="ql-align-justify">Answers should be provided quickly and concisely.</li><li class="ql-align-justify">Make it engaging by using music, dialogue, and unexpected twists.</li><li class="ql-align-justify">Example:</li></ul><ol><li class="ql-align-justify">Speaker reveals that a burger was cooked faster and better than a drive-through.</li></ol>

Ending

For social media creator and viral video hitmaker @JennyHoyos, the key to telling a great story is to keep it brief. She breaks down her framework for telling stories in 60 seconds or less that can gain millions of views online — or simply elevate your everyday conversations. (Created in collaboration with @ignite; recorded at TEDNext 2024 on October 22, 2024)

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#TED #TEDTalks #storytelling

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The TED Talks channel features the best talks and performances from the TED Conference, where the world's leading thinkers and doers give the talk of their lives in 18 minutes (or less). Look for talks on Technology, Entertainment and Design -- plus science, business, global issues, the arts and more. You're welcome to link to or embed these videos, forward them to others and share these ideas with people you know.

TED's videos may be used for non-commercial purposes under a Creative Commons License, Attribution–Non Commercial–No Derivatives (or the CC BY – NC – ND 4.0 International) and in accordance with our TED Talks Usage Policy: https://www.ted.com/about/our-organization/our-policies-terms/ted-talks-usage-policy. For more information on using TED for commercial purposes (e.g. employee learning, in a film or online course), please submit a Media Request at https://media-requests.ted.com

The Secret to Telling a Great Story — in Less Than 60 Seconds | Jenny Hoyos | TED

<ul><li class="ql-align-justify">Neuroplasticity refers to the brain's ability to change in response to experience.</li><li class="ql-align-justify">When we learn, synapses (tiny connections between neurons) are formed.</li><li class="ql-align-justify">Repetition strengthens these connections, making skills and information more robust.</li><li class="ql-align-justify">Children are naturally more plastic; however, adults can activate neuroplasticity through intentional strategies.</li></ul>

Neuroplasticity: The Foundation of All Learning

<ul><li class="ql-align-justify">The brain can only focus on one thing at a time; multitasking creates measurable attention deficits.</li><li class="ql-align-justify">Social media and digital distractions significantly reduce our sustained attention span.</li><li class="ql-align-justify">Enhancement Strategies:</li></ul><ol><li class="ql-align-justify">Focused attention meditation.</li><li class="ql-align-justify">20 minutes of moderate exercise before studying boosts cognitive performance for ~2 hours.</li><li class="ql-align-justify">Sensory focus exercises (e.g., noticing the pressure of your shoes) train attention.</li></ol>

Attention: The Gateway to Learning

<ul><li class="ql-align-justify">Learning requires an alert, engaged brain—driven by activation of the sympathetic nervous system.</li><li class="ql-align-justify">Tactical Boosters:</li></ul><ol><li class="ql-align-justify">Short bursts of exercise.</li><li class="ql-align-justify">Wim Hof breathing.</li><li class="ql-align-justify">Cold showers.</li><li class="ql-align-justify">Caffeine (moderately and strategically).</li></ol><ul><li class="ql-align-justify">Alertness follows a 90-minute ultradian rhythm with 8–30 minutes of peak alertness.</li><li class="ql-align-justify">Avoid learning post-meals or during dips in alertness.</li></ul>

Alertness: Maximizing Peak Cognitive States

<ul><li class="ql-align-justify">Sleep resets the immune system, metabolism, emotional control, and brain detox.</li><li class="ql-align-justify">It is critical for memory consolidation:</li></ul><ol><li class="ql-align-justify">Short-term memories (hippocampus) are transferred to long-term storage (cortex).</li></ol><ul><li class="ql-align-justify">Before learning: Sleep enhances alertness and encoding.</li><li class="ql-align-justify">After learning: Sleep is essential for memory stabilization.</li></ul>

Sleep: The Cognitive Reset Button

<ul><li class="ql-align-justify">One exposure is not enough; the brain needs multiple inputs to prioritize learning.</li><li class="ql-align-justify">Repetition signals importance at the cellular level, triggering investment in neural architecture.</li><li class="ql-align-justify">Best Practices:</li></ul><ol><li class="ql-align-justify">Repeat learning tasks multiple times in a session.</li><li class="ql-align-justify">Use spaced repetition across days.</li><li class="ql-align-justify">Emotional salience (fear, joy, surprise) can trigger "one-trial learning."</li></ol>

Repetition: Reinforcing Neural Pathways

<ul><li class="ql-align-justify">Post-learning breaks facilitate subconscious memory replay at up to 20x speed.</li><li class="ql-align-justify">Breaks prevent retrograde interference, where new learning disrupts old memories.</li><li class="ql-align-justify">Recommendations:</li></ul><ol><li class="ql-align-justify">10–20 minutes of quiet downtime (no phones) after learning.</li><li class="ql-align-justify">Wait at least one hour before learning something similar.</li></ol>

Breaks: Leveraging Subconscious Replay

<ul><li class="ql-align-justify">Errors trigger release of acetylcholine, sharpening focus and opening neuroplastic windows.</li><li class="ql-align-justify">Mistakes also release dopamine upon correction, reinforcing the right action.</li><li class="ql-align-justify">Learning Design Strategies:</li></ul><ol><li class="ql-align-justify">Set up controlled failure (e.g., self-quizzes, harder tasks).</li><li class="ql-align-justify">Lean into anxiety—it’s your brain signaling growth.</li><li class="ql-align-justify">Avoid walking away after mistakes; re-engage to embed the lesson.</li></ol>

Mistakes: Neurobiological Catalysts for Growth

By understanding how your brain learns, you can architect your environment, schedule, and habits to unlock your full cognitive potential.The six learning levers—attention, alertness, sleep, repetition, breaks, and mistakes—are not just tactics; they are biologically optimized tools for sustainable, high-performance learning.

Final Thought

Sharing the secrets to productive learning, backed by neuroscience. Dr Lila Landowski explains the methods which can be used to allow us to learn faster.  Dr Lila Landowski is a multi-award winning neuroscientist and lecturer that expertly arms people with an understanding of how their brain works, to help them make better choices in their lives. She is also a Director of the Australian Society for Medical Research, a Director of Epilepsy Tasmania, as well as a regular guest expert science communicator for the ABC. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at https://www.ted.com/tedx

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Strategy

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Mental Health

TEDx is an international community that organizes TED-style events anywhere and everywhere -- celebrating locally-driven ideas and elevating them to a global stage. TEDx events are produced independently of TED conferences, each event curates speakers on their own, but based on TED's format and rules.

TED's videos may be used for non-commercial purposes under a Creative Commons License, Attribution–Non Commercial–No Derivatives (or the CC BY – NC – ND 4.0 International) and in accordance with our TED Talks Usage Policy (https://www.ted.com/about/our-organization/our-policies-terms/ted-talks-usage-policy). 

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TEDx Talks

Brain Hack: 6 secrets to learning faster, backed by neuroscience | Lila Landowski | TEDxHobart

<ul><li class="ql-align-justify"> A discipline of computer science</li><li class="ql-align-justify">Creation of autonomous, intelligent agents that reason and learn.</li><li class="ql-align-justify">Theory and methods to build human-like thinking and acting machines.</li></ul>

What is Artificial Intelligence?

<ul><li class="ql-align-justify">A subfield of AI</li><li class="ql-align-justify">Uses input data to train models</li><li class="ql-align-justify">Trained models predict unseen but similar data</li><li class="ql-align-justify">Enables computers to learn without explicit programming</li></ul>

What is Machine Learning?

<ul><li class="ql-align-justify">Supervised Learning (Labeled Data)</li><li class="ql-align-justify">Data provided includes tags</li><li class="ql-align-justify">Learns from past examples to predict future outcomes</li><li class="ql-align-justify">Example: Predict amount of tips gave customer based on order type</li></ul>

Machine Learning Model - Supervised

<ul><li class="ql-align-justify">No tags or labels on the data</li><li class="ql-align-justify">The goal is to explore and find patterns or groups in the raw data</li></ul>

Machine Learning Model - Unsupervised

<ul><li class="ql-align-justify">Uses artificial neural networks to learn complex patterns</li><li class="ql-align-justify">Neural networks are inspired by the human brain (made of many interconnected neurons)</li><li class="ql-align-justify">Deep learning models have many layers of neurons</li><li class="ql-align-justify">Can work with supervised, unsupervised, or semi-supervised data</li><li class="ql-align-justify">Semi-supervised = small labeled data + large unlabeled data</li><li class="ql-align-justify">Labeled data teaches core concepts; unlabeled data helps generalize</li><li class="ql-align-justify">Generative AI and Large Language Models (LLMs) are subsets of deep learning</li></ul>

Deep Learning (Subset of Machine Learning)

Goal: Create new content (text, images, etc.)How: Learns joint probability p(x, y) and generates new data based on patternsExample: Generate a dog image based on understanding what a "dog" looks like

Deep Learning Model (Generative)

<ul><li class="ql-align-justify">Goal: Classify or label data</li><li class="ql-align-justify">How: Learns conditional probability p(y | x) to predict labels for new inputs</li><li class="ql-align-justify">Example: Given an image, predict if it's a dog or a cat </li></ul>

Deep Learning Model (Discriminative)

Generative models create new data, while discriminative models learn to tell data apart.

<ul><li class="ql-align-justify">This approach uses training code and labeled data to build a model. Depending on the task, the model can:</li><li class="ql-align-justify">Make predictions</li><li class="ql-align-justify">Classify inputs</li><li class="ql-align-justify">Cluster similar data points</li></ul>🐱 Before ML: Rule-Based Programming<ul><li class="ql-align-justify">In traditional programming, we had to hardcode rules to define what a cat is:</li><li class="ql-align-justify">Type: animal</li><li class="ql-align-justify">Legs: 4</li><li class="ql-align-justify">Ears: 2</li><li class="ql-align-justify">Fur: yes</li><li class="ql-align-justify">Likes: yarn, catnip</li><li class="ql-align-justify">Dislikes: Fred</li></ul>

🧠 Traditional Machine Learning (Supervised Learning)

<ul><li class="ql-align-justify">Generative AI models take in training code, labeled data, and even unlabeled data of all kinds (text, images, audio, etc.) to build a powerful foundation model.</li><li class="ql-align-justify">This model can then create brand new content — not just recognize patterns but generate text, code, images, audio, and video.</li></ul>📸 Neural Networks in Action<ul><li class="ql-align-justify">With neural networks, we can now show the system images of cats and dogs and ask:</li><li class="ql-align-justify">“Is this a cat?”</li><li class="ql-align-justify">The model doesn't need hardcoded rules — it learns from data and makes a prediction: cat or not a cat.</li></ul>

🤖 Generative AI: A New Era

🧠 How Generative AI Works

Generative AI (GenAI) is a type of Artificial Intelligence that creates new content based on patterns it has learned from existing data.<ul><li class="ql-align-justify">The learning process is called training, which produces a statistical model.</li><li class="ql-align-justify">When given a prompt, GenAI uses this model to predict likely responses — generating new content.</li><li class="ql-align-justify">It captures the underlying structure of the data and can produce similar, but original, outputs.</li></ul>

🔍 What is Generative AI?

<ul><li class="ql-align-justify">Takes images as input</li><li class="ql-align-justify">Can output images, text, or videos</li><li class="ql-align-justify">Examples: image captioning, super-resolution, video generation, and image completion</li></ul>

🖼️ Generative Image Model

<ul><li class="ql-align-justify">Takes text as input</li><li class="ql-align-justify">Can generate more text, images, audio, or even make decisions</li><li class="ql-align-justify">It learns language patterns from training data</li><li class="ql-align-justify">Predicts how to complete or respond to a sentence</li></ul>

📝 Generative Language Model

<ul><li class="ql-align-justify">Driven by transformers, a deep learning architecture</li><li class="ql-align-justify">Key breakthrough in 2018 revolutionized Natural Language Processing (NLP)</li><li class="ql-align-justify">Transformers enable GenAI to understand and generate contextually relevant content</li></ul>

⚙️ Power Behind GenAI

Generative AI can sometimes produce hallucinations — content that sounds plausible but is incorrect or nonsensical.Reasons include:<ul><li class="ql-align-justify">Insufficient training data</li><li class="ql-align-justify">Poor-quality (noisy or dirty) training data</li><li class="ql-align-justify">Lack of context in the prompt</li><li class="ql-align-justify">Inadequate constraints or guidance in prompt design</li></ul>

⚠️ Common Issues with Generative AI

A prompt is a short input text given to a Large Language Model (LLM) to guide its output.<ul><li class="ql-align-justify">Example: “Summarize this article,” or “Write a poem in the style of Shakespeare.”</li><li class="ql-align-justify">Prompt design is the art of crafting effective prompts to achieve desired outcomes from the model.</li></ul>

✏️ Prompting

Predictive ML Model VS Gen AI Model (Chart)

Predictive ML Model VS Gen AI Model

How to differentiate Gen AI?

🌱 Generative AI Model Types Explained

<ul><li class="ql-align-justify">Takes natural language input and produces text output</li><li class="ql-align-justify">Learns to map one text to another</li><li class="ql-align-justify">Common use cases:</li></ul><ol><li class="ql-align-justify">Translation (e.g., English ↔ Spanish)</li><li class="ql-align-justify">Summarization</li><li class="ql-align-justify">Text generation (e.g., writing assistance)</li></ol>

📝 Text-to-Text

<ul><li class="ql-align-justify">Trained on large datasets of images with text descriptions</li><li class="ql-align-justify">Generates realistic or stylized images from a text prompt</li><li class="ql-align-justify">Diffusion models are often used in this process</li><li class="ql-align-justify">Example: "A cat wearing sunglasses riding a skateboard"</li></ul>

🖼️ Text-to-Image

<ul><li class="ql-align-justify">Generates videos from text input</li><li class="ql-align-justify">Input can range from a simple sentence to a detailed script</li><li class="ql-align-justify">Example: "Show a sunrise over the mountains with birds flying by"</li></ul>

🎥 Text-to-Video

<ul><li class="ql-align-justify">Generates 3D models from a user’s text description</li><li class="ql-align-justify">Used in game design, virtual worlds, or AR/VR applications</li><li class="ql-align-justify">Example: "A futuristic flying car with neon lights"</li></ul>

📦 Text-to-3D

<ul><li class="ql-align-justify">Executes specific tasks based on text input</li><li class="ql-align-justify">Can perform actions like:</li></ul><ol><li class="ql-align-justify">Answering questions</li><li class="ql-align-justify">Running searches</li><li class="ql-align-justify">Making predictions</li><li class="ql-align-justify">Automating workflows (e.g., navigating UIs, editing documents)</li></ol>

⚙️ Text-to-Task

<ul><li class="ql-align-justify">Large-scale models trained on massive datasets</li><li class="ql-align-justify">Adaptable to many downstream tasks (via fine-tuning or prompt engineering)</li><li class="ql-align-justify">Tasks include:</li></ul><ol><li class="ql-align-justify">Sentiment analysis</li><li class="ql-align-justify">Image captioning</li><li class="ql-align-justify">Object recognition</li><li class="ql-align-justify">Question answering</li></ol><ul><li class="ql-align-justify">Industry Impact:</li></ul><ol><li class="ql-align-justify">Healthcare, finance, customer service, fraud detection, and more</li></ol><ul><li class="ql-align-justify">Example platform: Vertex AI’s Model Garden with support for both:</li></ul><ol><li class="ql-align-justify">Language models (chat, code, summarization)</li><li class="ql-align-justify">Vision models (image captioning, embeddings, diffusion models)</li></ol>

🧠 Foundation Model

🚀 Generative AI Applications

A platform that enables developers to quickly explore, customize, and deploy generative AI models on Google Cloud.Key Features:<ul><li class="ql-align-justify">📚 Library of pre-trained models</li><li class="ql-align-justify">🛠️ Tools for fine-tuning</li><li class="ql-align-justify">🚀 Deployment to production</li><li class="ql-align-justify">💬 Community forums for collaboration and idea sharing</li></ul>Great for developers looking to get started with generative AI using ready-to-use resources.

🧰 Vertex AI Studio

Helps build AI-powered search and conversational agents for both customers and internal teams.Use Cases:<ul><li class="ql-align-justify">🤖 Chatbots</li><li class="ql-align-justify">🧠 Digital assistants</li><li class="ql-align-justify">🔍 Custom search engines</li><li class="ql-align-justify">📚 Knowledge bases</li><li class="ql-align-justify">🎓 Training and learning applications</li></ul>Ideal for enhancing customer experience and internal workflows through intelligent, conversational interfaces.

💬 Vertex AI Agent Builder (formerly Vertex AI Search and Conversation)

Gemini goes beyond text and enables multimodal capabilities, including:<ul><li class="ql-align-justify">🖼️ Image analysis</li><li class="ql-align-justify">🔊 Audio understanding</li><li class="ql-align-justify">💻 Code interpretation</li></ul>A versatile tool for tasks requiring visual, audio, and programming intelligence — all from a single model.

🌐 Gemini

Google Cloud Skills Boost - Introduction to  GEN AI

Tract is a sustainability performance management Platform

What is TRACT

Environmental Climate -> Carbon EmissionLand use -> DeforestationHuman Rights	 Child ProtectionForced Labour

Current Sustainability Frame Work (In Dev)

<ul><li>One central place for insight on sustainabilty areas</li><li>Now launch for coffee and palm supply chain</li><li>To expand to : Deforestation , Child Labour , Forced Labour, Living Income</li></ul>

TRACT Platform

<ul><li>Traceability Map ( Farmer -> Mill -> End port)</li><li>Integration of Data</li></ul>

How to Learn ANYTHING Faster Than Everyone

The Secret to Telling a Great Story — in Less Than 60 Seconds | Jenny Hoyos | TED

Brain Hack: 6 secrets to learning faster, backed by neuroscience | Lila Landowski | TEDxHobart

Google Cloud Skills Boost - Introduction to GEN AI

Tract

Kenny Chew