Luyện nói tiếng Anh bằng Shadowing qua video: Give Me 18 Minutes and I’ll Make you Dangerously Smart (with AI)
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Most people are letting AI destroy their ability to think,
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Most people are letting AI destroy their ability to think,
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training AI to become their own replacement.
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Tragic, because AI can make you dangerously intelligent.
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I went from being homeless to an MIT grad and running and advising AI companies worth billions.
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And here's what I've learned.
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The top 1% use AI backwards.
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They don't prompt to get answers.
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They use it to train their brain and outsmart almost any situation.
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So in this video, I'll break down a counter-intuitive system the top 1% use to get smarter faster with AI.
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Here is the four-step framework.
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Step 1.
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Intelligent laziness.
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A study in Harvard Business Review found that CEOs waste 72% of their time in meetings that don't move the needle.
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We've all experienced those meetings, haven't we?
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The one-hour meeting that needed only 15 minutes to get to a decision.
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But is hard to stop.
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So why do some of the most accomplished folks feel trapped this way?
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Because we all suffer from this biological glitch called completion bias.
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Your brain is wired to seek an immediate dopamine hit that you get from finishing a task.
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So we end up treating all tasks as equal
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because we're going to get roughly the same amount of dopamine
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when you spend time on redrafting an internal email or a million dollar strategy document.
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Everything is priority one, so none of it is.
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So how do you avoid this priority blindness?
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A good way to think about tasks is to see two curves.
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First curve has capped payoffs.
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This curve goes up and then flattens out once it reaches the zone of diminishing returns.
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So tasks like formatting slides or internal emails, expense reports, FYI meetings.
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What happens if you spend additional effort to make the outcome of these tasks pitch perfect?
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Nothing.
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There's no upside here because the value flatlines after a point.
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Nobody cares if you spend hours choosing better fonts or breathtaking designs in internal slides that are seen for six minutes.
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This curve shows you your zone of intelligent laziness.
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There was a Nobel Prize winning economist and computer scientist,
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and his name was Herbert Simon,
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and he came up with a concept called satisficing,
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which pretty much means stop when it's good enough.
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Satisfy and suffice.
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Satisfice.
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Now our second curve is the exact opposite.
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It has uncapped payoff.
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This curve stays flat for a long time,
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but then goes to the moon in a hurry.
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These are tasks like customer interactions,
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product design, pricing model, finding a co-founder or a life partner.
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Being 1% better here does not yield 1% better result.
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It actually solves the rest of the 99% of your problems.
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Pour your soul into this.
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Johnny Ive would obsess for many months on even the internal component design of iPhone.
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But you know, Steve Jobs never said,
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hey, this is costing us a lot of money and who's gonna pry open the iPhone?
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But Steve knew this was the second curve.
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So if the first curve is your zone of laziness,
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your second curve is your zone of obsession.
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Let's talk about how AI can help.
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The top 1% use AI on zone 1 or the zone of laziness.
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The more they outsource Zone 1 to AI,
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the more they can focus on Zone 2, the Zone of Obsession.
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So how do I decide what to outsource to AI, and when?
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So for that, I use a very simple framework called DRAG framework.
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D-R-A-G.
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Four categories of work you immediately should delegate to AI so you can stay in your Zone of Obsession.
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First, D equals drafting.
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This is the blank page problem we all face.
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It's hardest to get from 0 to 1 sometimes.
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AI can help here, tremendously actually.
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Give it a prompt using the AIM protocol that I've shared before.
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Hey AI, act in this role,
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use this input, and this is your mission.
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AIM.
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And that way, you get started very quickly on that email or code or presentation.
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The first draft from AI will be crappy and atrocious, but that's fine.
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Now you have a starting point.
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You're not staring at a blank page anymore.
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Now it'll trigger something in your brain and you're off to the races.
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R equals research.
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This helps you solve the information overload problem.
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Today if something requires deep research it can be dramatically accelerated using AI.
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Summarization, extraction, competitive intel.
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You know don't spend time doing that kind of research.
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Let your friendly neighborhood AI do it for you.
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When you use the deep research feature on ChatGPT or Gemini or Claude,
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it fires off hundreds of secondary search queries.
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It goes out to the web like a spider and finds hundreds of sites,
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consolidates the results, even checks his own work by asking what's missing,
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and follows up on its own to finally deliver a rich document to you.
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It's like you just hired a consultant for a week-long research project,
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but instead you get there in 10 minutes.
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Third is A for analysis.
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Let AI take the first pass at analyzing,
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summarizing, reasoning, especially if it's all unstructured data
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because AI is going to find patterns that we humans aren't going to be able to.
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So use it for your advantage.
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And finally G is for all the grunt work.
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Tasks like reformatting, translating, tabulating,
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cleaning data, and on and on.
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The boring manual work.
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Just give it to AI.
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So what's the key principle behind drag?
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Apply it only when you are in your zone one.
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That first curve.
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If it requires human interaction or judgment or intuition or decision making or tastes, that's curve two.
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That you've got to do it yourself.
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But you know, I've found that 70 or 80 percent of my repetitive tasks tend to be in zone one.
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And you might find that too.
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So be lazy when you can use drag.
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Be obsessed for everything else.
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Step two, the intelligent hill.
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For 300 years, Isaac Newton convinced us that universe was a clockwork machine.
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Predictable and certain.
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But in 1927, another scientist named Heisenberg shattered those classical beliefs.
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He showed that our universe exists only as a cloud of possibilities at quantum level.
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It was a profound shift.
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You and I have to make a similar shift when we use AI nowadays.
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The first trick is to stop treating AI like a calculator.
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We like to live in a world with clear rules.
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You type 2 plus 2 into a calculator and you get 4.
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Always.
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It's predictable.
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But AI is not a calculator.
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It's a probability engine.
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If you ask the same question to AI again,
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it'll give you a completely different answer.
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It'll happily make things up for you unless you ask it to verify.
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AI is brilliant on some days,
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confused on others but on any given day it refuses to admit that it doesn't know the answer.
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It loves to make things up.
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So you don't just ask AI the way you ask a normal human being.
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You have to architect your questions very carefully.
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Now most people use a tactic called zero shot prompting.
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So for example they would ask give me the best new business idea
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and of course AI will dish out a response and tell you why it's the greatest idea in the world,
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but you're literally rolling the dice and looking to win.
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To get elite results though,
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you must climb the intelligent hill.
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There are four camps on the way.
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Each camp will show you a different way to work with AI.
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Our first camp is called one-shot prompting.
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When you prompt, give one clear example so the model doesn't guess blindly.
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So the prompt would look like,
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write a LinkedIn post about remote work.
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Use this specific post as a style guide.
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And so give it a post,
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give it an example, and paste that post in the prompt as a reference.
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And that simple act is already an upgrade than rolling the dice blindly.
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Second camp, few shot prompting.
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Now here you give AI three or more examples so it can find patterns of style,
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and substance and tone that you desire.
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Attached documents, links, data, or your prior work,
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this is called grounding the model.
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So basically it stops fantasizing and hallucinating and gets grounded to reality.
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Here's an example of a prompt.
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Here are the five of my previous presentations.
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And now write a new presentation based on my tone of voice on topic XYZ.
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And here's the pro tip.
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Ask the AI to explain the pattern back to you first.
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That way, AI is forced to articulate what it's doing,
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and more importantly, you're forced to learn how your brain works.
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How did it come up with those patterns?
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Now, you're being smart about being smart.
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Now let's move to the third camp.
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This one is called chain of thought reasoning.
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Again, fancy name, but the idea is simple.
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Ask the model to think long and hard before it responds.
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Your job is to slow AI down and force explicit clarity by asking it to show its work.
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That's all there is.
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This is also a good way to reduce hallucinations, of course.
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So let's say you're working on some report,
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and so you attach it and write a prompt that could look like this.
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Do not refine my research report yet.
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List the top three most impactful areas of improvement after you analyze it.
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Tell me why you think so and suggest how we address each.
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Think step by step.
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Show me your thinking for each step.
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That last line is the most important one.
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And our fourth and final camp is agents.
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According to Salesforce, AI agents help drive $67 billion in global sales during Cyber Week alone.
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So agents are already here.
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The best way to think about agents is to think about who you would hire for a task.
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So let's say if you wanted to hire a researcher,
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an analyst, and a copywriter.
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You can do that with a single agentic prompt that looks like this.
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Do deep research on trends on topic XYZ,
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analyze and cross-reference all the trends to find the three most important ones,
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and draft a one-page memo summarizing the findings.
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Now, what is actionable?
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Try this framework tonight.
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Open your favorite AI app and take any prompt that you were about to use.
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Just try to get to the next camp.
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That's how you start climbing up the intelligent hill.
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Remember, when you were dealing with a drunk genius,
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make sure you were the one driving the car.
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So now, at this point,
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everything we have done has made you fast and efficient.
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You're delegating better, you're prompting smarter,
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you're moving up the hill,
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and there's less friction than before.
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And that's exactly where most people would stop.
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But here's the plot twist.
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The top 1% go one step further.
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They slow things down deliberately.
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Why is that important?
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The trick that top 1% know is this.
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They know when to shift the gear.
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Because long-term intelligence isn't built through convenience, it's built through resistance.
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and that's why we need to go to step three, the intelligent gym.
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Most people use AI as wheelchair for the mind and if you sit in a wheelchair when you can still walk,
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eventually your legs stop working,
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atrophy and today is happening faster than at any point in human history but the top 1% use a very different principle.
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For information tasks, use AI to remove friction.
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For transformation tasks, use AI to add friction.
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When you go to a physical gym,
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we all know how muscles are built, right?
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Through resistance.
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You lift increasingly heavier weights to introduce wear and tear to your muscle fibers,
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so they break and they grow back stronger.
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That is called progressive overload.
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But when it comes to our minds,
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we do the exact opposite somehow.
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We avoid resistance.
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We use AI to outsource our thinking.
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Write my LinkedIn post, fix my resume, summarize this book.
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That's like going to the gym and asking someone else to lift weights on your behalf.
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You know, when astronauts spend months in zero gravity,
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their muscles and bones atrophy dramatically, up to 20%.
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AI is like zero gravity for your thinking.
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No friction, no load, no growth.
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The intelligent gym is not about information.
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It's about transformation.
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For things where you need to be smart and capable,
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you can think of AI as your spotter.
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In any gym, a spotter doesn't lift the weight for you.
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They stand next to you and help you lift.
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They also make sure that you don't get crushed when you're lifting the weight.
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So do the same with AI.
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Here's a concrete example.
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If you want to learn a concept,
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study it first yourself and then go to your spotter, your AI.
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Paste the concept text and then prompt AI.
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I need to master this concept.
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Quiz me on it.
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And now comes the most important part of your intelligent gym.
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Ask AI to apply progressive overload.
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Four levels.
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Level one, quiz me like I am a high school student.
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Level two, ask me questions like I am a college student.
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Level three now grill me like you're interviewing me for an executive job
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and level four now challenge me like an irate boss Who thinks I'm unprepared
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so that truly strengthens and deepens your understanding on that concept
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So now we have covered three key steps to learn how the top 1% Become smarter by using AI
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but there is one internal adjustment that changes everything and that is our final step step number four The intelligent fool.
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You know, the biggest obstacle to intelligence isn't ignorance, it's ego.
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That's why the smartest people are obsessed with what they don't know.
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And this is what I call the fool's advantage.
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Let me give you an example.
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Microsoft went from $300 billion to $300 trillion in market cap with just one mental, cultural shift.
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When Satya Nadella became the CEO of Microsoft in 2014,
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they had missed two huge disruptions, search and mobile.
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The cloud race was ongoing,
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but it was slipping away from them with Amazon becoming the 800 pound gorilla.
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And the culture inside the company was toxic and political.
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And everyone was terrified to admit that there were gaps in their knowledge.
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Satya made one cultural move.
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He told the entire company,
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were switching from a culture of know-it-alls to learn-it-alls.
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A complete reboot of Microsoft culture.
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The smartest people in the room were finally given permission to say,
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I don't know, or I was wrong,
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and to embrace that beginner's mind.
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Now, Wall Street was skeptical at first,
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but the market cap eventually went from $300 billion to over $3 trillion.
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keeps growing.
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10x growth in a decade.
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And here's why this matters.
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Neuroscience tells us that our brain can rewire all the time.
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It's called neuroplasticity.
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This rewiring happens only at the edge of your ability.
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It happens when you are making errors.
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It happens when you're frustrated,
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when you're feeling that discomfort.
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And if you aren't feeling stupid, you aren't learning.
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And aren't you glad that AI has just handed you the ultimate training ground to be a student again?
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You can bring your beginner's mind to AI all day long.
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Ask questions you would never ask your colleagues out of fear of embarrassment.
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AI doesn't roll its eyes.
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Pick one thing that you don't understand in your field.
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Something that everyone else thinks you know,
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but you know you don't.
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And then ask AI the most basic questions about that topic that you can think of.
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And then ask.
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Can you explain it to me in a simpler way?
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Teach me like I am 10 years old.
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I ask these questions all the time.
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In fact, I ask three times in a row to simplify again and again.
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And sure, I guarantee you,
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you'll feel ridiculous at first.
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I do all the time.
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But that's the whole point.
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Have the courage to play the fool today so you can be the genius tomorrow.
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The trick to mastery is going back to simplicity itself.
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If you examine some of the greatest masters across human history,
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you'll see one consistent pattern.
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Every master is a student for life.
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And you can be a genuine student if you're hiding behind a mask of mastery.
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You know, the biggest benefit of intelligence is not the end of ignorance,
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it's the end of pretending.
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You know, we're surrounded by endless images of flawless people in their flawless poses, flawlessly photoshopped.
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But in the end, all art is about asymmetry.
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We're beautiful because we're broken.
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Because the real purpose of intelligence,
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of this thing called life,
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is to travel far and wide only to return to yourself and fully accept who you are.
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That is your truest intelligence.
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If you like this video, don't forget to subscribe.
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If you want to use AI to start a business,
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here's another video where I walk you through exactly what I would do.
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Thank you and I love you.
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Phổ biến
Tại sao nên luyện nói với video này?
Luyện nói qua video không chỉ giúp bạn cải thiện khả năng phát âm mà còn nâng cao kỹ năng giao tiếp trong môi trường thực tế. Video này cung cấp một cái nhìn sâu sắc về cách mà trí tuệ nhân tạo (AI) có thể được sử dụng để tối ưu hóa tư duy của bạn. Với tầm nhìn của một người đã trải qua quá trình từ vô gia cư đến tốt nghiệp MIT và thành công trong lĩnh vực AI, diễn giả chia sẻ những bài học quý giá mà bạn có thể áp dụng. Khi thực hành shadow speak, bạn không chỉ đơn thuần nghe và lặp lại mà còn nắm bắt được ngữ điệu, cách sử dụng ngôn từ và các biểu cảm tự nhiên.
Ngữ pháp & Biểu thức trong ngữ cảnh
Trong video, diễn giả sử dụng một số cấu trúc câu và biểu thức điển hình mà bạn có thể áp dụng vào cuộc sống hàng ngày:
- “Most people are letting AI destroy their ability to think”: Câu này sử dụng cấu trúc hiện tại tiếp diễn để chỉ ra sự xảy ra liên tục và có tính chất tạm thời của việc AI ảnh hưởng đến khả năng tư duy.
- “I went from being homeless to an MIT grad”: Đây là một ví dụ điển hình của cấu trúc quá khứ đơn giản, tạo ra sự chuyển biến rõ rệt trong câu chuyện cá nhân.
- “When you spend time on redrafting”: Cấu trúc này giúp diễn tả hành động tiếp diễn và mạnh mẽ, nhấn mạnh tầm quan trọng của việc chọn lựa cách sử dụng thời gian hợp lý.
Khi luyện nghe nói qua video, hãy chú ý đến cách diễn giả sử dụng các cấu trúc này trong ngữ cảnh cụ thể để làm phong phú thêm ngôn ngữ của bạn.
Các bẫy phát âm thường gặp
Trong video, có một số từ và cụm từ mà người học tiếng Anh thường gặp khó khăn khi phát âm:
- “AI”: Nhiều người có thể phát âm sai với cách nhấn âm không chính xác.
- “cap” và “payoff”: Đây là hai từ trong một cụm từ quan trọng mà có thể dễ dàng bị nhầm lẫn trong phát âm.
- “satisficing”: Một từ mới mà bạn có thể cần luyện tập thêm để phát âm rõ ràng và chuẩn xác.
Để cải thiện khả năng phát âm, hãy thực hành shadow speech với các cụm từ này, nghe đi nghe lại và mô phỏng lại ngữ điệu cũng như âm điệu của diễn giả. Kỹ thuật shadowing tiếng anh sẽ giúp bạn có sự kết nối tốt hơn với ngôn ngữ.
Phương Pháp Shadowing Là Gì?
Shadowing là kỹ thuật học ngôn ngữ có cơ sở khoa học, ban đầu được phát triển cho chương trình đào tạo phiên dịch viên chuyên nghiệp và được phổ biến rộng rãi bởi nhà đa ngôn ngữ học Dr. Alexander Arguelles. Nguyên lý cốt lõi đơn giản nhưng cực kỳ hiệu quả: bạn nghe tiếng Anh của người bản xứ và lặp lại to ngay lập tức — như một "cái bóng" (shadow) đuổi theo người nói với độ trễ chỉ 1–2 giây. Khác với luyện ngữ pháp hay học từ vựng bị động, Shadowing buộc não bộ và cơ miệng phải đồng thời xử lý và tái tạo ngôn ngữ thực tế. Các nghiên cứu khoa học xác nhận phương pháp này cải thiện đáng kể phát âm, ngữ điệu, nhịp điệu, nối âm, kỹ năng nghe và độ lưu loát khi nói — đặc biệt hiệu quả cho người luyện IELTS Speaking và muốn giao tiếp tiếng Anh tự nhiên như người bản ngữ.