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No, the difficulty is not the lack of ideas. The difficulty is to develop a taste for which strategy is suitable for your personal circumstances and goals, and which ones look viable even before you devote the time to diligently backtest them. This taste for prospective strategies is what I will try to convey in this chapter.
Ernest P. Chan • Quantitative Trading
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First, we have a fire hydrant (hydrogen) with helium-filled balloons (helium) tied to the top of the hydrant. The helium balloons are touching the light bulb (lithium). The light bulb is burning the different berries (beryllium). The berries are being eaten by a smelly wild boar (boron). A car with a bun attached to it (carbon)
Kevin Horsley • Unlimited Memory: How to Use Advanced Learning Strategies to Learn Faster, Remember More and be More Productive
I passionately want you to believe in a specific counterfactual world—the one with systematic behavior change at the center of the creation process—and adopt it as your own.
Matt Wallaert • Start at the End: How to Build Products That Create Change
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we mean that Mark Manson doesn’t care about adversity in the face of his goals, he doesn’t care about pissing some people off to do what he feels is right or important or noble. We
Mark Manson • The Subtle Art of Not Giving a F*ck: A Counterintuitive Approach to Living a Good Life (Mark Manson Collection Book 1)
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Instead, we're moving into Software 2.0 (a shift that Michael Taylor recently wrote about), where we describe a goal that we want to achieve and train a model to accomplish it. Rather than having a human write instructions for the computer to follow, training works by searching through a space of possible programs until we find one that works. In
... See moreDan Shipper • Five New Thinking Styles for Working With Thinking Machines
The Shift from Formal Theories to Engineering Outcomes in AI Development: In recent years, the development of artificial intelligence (AI) has transitioned from focusing primarily on formal theories and mathematical models to emphasizing practical engineering outcomes. This shift reflects a growing recognition of the importance of real-world applications, such as improving user experience and enhancing automation, over purely theoretical advancements. As a result, researchers and developers are increasingly prioritizing iterative design and testing processes to create more effective and user-friendly AI systems.
This is because you and I have different values than Mustaine does, and we measure ourselves by different metrics. Our metrics are probably more like “I don’t want to work a job for a boss I hate,” or “I’d like to earn enough money to send my kid to a good school,” or “I’d be happy to not wake up in a drainage ditch.” And by these metrics, Mustaine
... See moreMark Manson • The Subtle Art of Not Giving a F*ck: A Counterintuitive Approach to Living a Good Life (Mark Manson Collection Book 1)
.implementation very good example of what are values and how do we measure them
The issue is that personality is extremely individual. Traits that play a critical role in peak performance—such as your risk tolerance or where you land on the introversion-to-extroversion scale—are genetically coded, neurobiologically hardwired, and difficult to change. Add in all the possible environmental influences that come from variations in
... See moreSteven Kotler • The Art of Impossible
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Sherlock Holmes has illustrated the four elements most likely to allow us to do just that: selectivity, objectivity, inclusivity, and engagement.
Maria Konnikova • Mastermind
Pilots are tightly scoped interventions that we expect not to work (remember, we have to explicitly prove efficacy as a defense against confirmation bias), so we use small populations, focus on speed to market, and do them in an operationally dirty way. Besides being fun to say, “operationally dirty” just means that we’re shooting for minimal
... See moreMatt Wallaert • Start at the End: How to Build Products That Create Change
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