Summary:Cal Newport discusses the importance of capturing high-quality information relevant to work and life while minimizing friction. Overcomplicated systems can hinder productivity, while simpler methods can enhance efficiency and prevent burnout. Actionable Insight:Focus on creating low-friction, simple note-taking systems that allow you to capture important information without overwhelming yourself with complexity.

The Philosophy of Minimalist Note-Taking

Summary:Cal uses a simple method for taking notes from books. He marks the corners of pages with important information and adds small marks or notes in the margins. This allows for quick retrieval of information without extensive effort.Actionable Insight:Adopt the corner marking method for your book notes. It helps you identify and revisit key information efficiently, saving time and effort.

Corner Marking Method for Books

Summary:Cal suggests storing notes related to specific projects in the tools used for those projects (e.g., Scrivener for articles or books). This keeps all relevant information organized and accessible when needed. Actionable Insight:Use project-specific tools to store notes and ideas. This practice ensures that you can easily find and utilize the information when working on the project.

Storing Project-Related Notes

Summary:For personal projects or life ideas, Cal recommends using a physical notebook that feels aspirational. Regularly reviewing and triaging these notes helps maintain focus and prioritize important ideas. Actionable Insight:Keep a dedicated notebook for personal ideas and review it periodically. This helps you stay aligned with your goals and focus on what truly matters.

Personal Projects and Life Ideas

Summary:Minimalist note-taking reduces friction and prevents overload, ensuring important information is captured effectively. Simple systems keep the brain engaged, enhancing memory and decision-making. Actionable Insight:Embrace minimalist note-taking methods to boost productivity and mental clarity. Simple systems can be more effective than complex ones in capturing and utilizing information.

Benefits of Minimalist Note-Taking

Books:	•	Use the corner marking method to highlight important information in books without slowing down your reading.Projects:	•	Store project-related notes in the specific tools used for those projects to maintain organization and efficiency.Personal Life: 	•	Use a dedicated notebook for life ideas and review it regularly to stay focused on what matters most.

Recommendations:

In “Ep. 287: Minimalist Notes” of “Deep Questions with Cal Newport,” Cal explores minimalist note-taking strategies to capture high-quality information efficiently.

A deep life requires that you encounter and make sense of a large amount of incoming information, from narrow data relevant to a professional project, to broad insights into your purpose. How do you keep track of all of this? In this episode, Cal proposes a minimalist approach aimed at minimizing the friction required to keep tabs on what matters.Below are the questions covered in today's episode (with their timestamps). Get your questions answered by Cal! Here’s the link: bit.ly/3U3sTvoVideo from today’s episode:  youtube.com/calnewportmediaDeep Dive: How to track information that matters [2:55]- How should I make use of non-cognitive time? [27:37]- Can people with ADHD become better at learning? [32:49]- What does Cal think of Gloria Mark’s “4 myths of attention span”? [36:31]- How can I concentrate on my dissertation when I have a full-time job? [47:04]- How can I stop wasting my afternoon time blocks? [53:20]- CALL: How can I better organize my idea notebooks? [1:01:38]CASE STUDY: Avoiding the hyperactive hive mind to work more efficiently [1:05:46]   CAL REACTS: Is it bad to be slow? [1:13:46]Links:dailystoic.com/try-not-to-be-so-slow/gloriamark.com/attention-spanUse this link to preorder a signed copy of “Slow Productivity”: peoplesbooktakoma.com/preorder-slow-productivity/ FREE download excerpt and 2 Bonuses for “Slow Productivity”: calnewport.com/slow  Thanks to our Sponsors: grammarly.com/podcastdrinklmnt.com/deepcozyearth.com (promo code “cal”)expressvpn.com/deepThanks to Jesse Miller for production, Jay Kerstens for the intro music, Kieron Rees for slow productivity music, and Mark Miles for mastering.

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Productivity

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Reading & Writing

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Learning & Education

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Time Management

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Podcasts

Cal Newport is a computer science professor and a New York Times bestselling author who writes about the impact of technology on society, and the struggle to work and live deeply in a world increasingly mired in digital distractions. On this podcast, he answers questions from his readers and offers advice about cultivating focus, productivity, and meaning amidst the noise that pervades our lives.

Deep Questions with Cal Newport

Ep. 287: Minimalist Notes

Ep.287 Minimalist Notes

Money has the power to buy you things. But a much bigger power of money is in generating more money for you. Those who can manifest the latter, are never short of it.

We were not created to work hard all the time just to fulfill our basic needs.We were blessed with all the essential resources that are required to live contentedly and comfortably.

The demands of life and society have blindsided us to our capabilities and the resources accessible to us. We have become stuck in the routine of working, eating, sleeping, and repeating the same cycle again and again.

Society Made Life Complicated

DON'T CHASE ; ATTRACT !

Many of us spend a significant amount of time chasing money, investing all our energy into working hard and appearing successful.

Drop The Facade & Release Social Standards!

However, despite all of this effort, we still feel unhappy. We find ourselves trapped in a programmed lifestyle that forces us to constantly hustle and bustle, causing us to miss out on the important things in life.

It's Easier Than You Think

<ul><li>Amazon Kindle Direct publishing — make money off of your published ebooks</li><li>Stocks . Please don't just hop in. Do your research first.</li><li>Money from hobbies and crafts </li><li>Real estate investing </li><li>Writing blogs or adding content to platforms that pay per-view. Content creation is big right now. </li><li>YouTube videos. Let those views make you money.</li><li>Create an app. It's easier than you think.</li><li>Know a lot about something? Create a course.</li></ul>The possibilities are endless. Take your time and find what works for you.

The greater the passive income you can build, the freer you will become.

But a much bigger power of money is in generating more money for you. . “Work Smarter, not Harder —  Attracting a Passive Income” is published by The Beautiful Mystic in New Earth Consciousness.

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Money & Investments

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Motivation & Inspiration

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Entrepreneurship

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Business

Work Smarter, not Harder —  Attracting a Passive Income

As Artificial Intelligence (AI) technology continues to evolve, need for understanding the role of specialised hardware that power AI applications is important. From training machine learning models to processing big data, the choice of processor impacts the efficiency and performance of AI tasks. Whether you are a developer, data scientist, or tech enthusiast, this guide will help you to understand the most common types of AI hardware: CPUs, GPUs, TPUs, and LPUs.

AI Hardware

Central Processing Unit (CPU) is the traditional heart of a computer, capable of handling a variety of tasks from basic calculations to complex software operations

Examples : Intel Core processors and Apple M1/M2 chipsBest for: General-purpose computing, smaller datasets, or tasks requiring complex logic where data processing needs are sequential.Application: Running data preprocessing or light machine learning models like linear/logistic regression on a dataset with less number of data poin

More About CPU

Graphics Processing Units (GPUs) are known for their ability to handle multiple operations simultaneously in parallel, making them ideal for graphics rendering in Games and AI computations

Examples: Nvidia Tesla and Nvidia Drive PXBest for: Large-scale machine learning tasks that requires handling of massive datasets with millions of data points or running complex deep learning models.Application: Training a convolutional neural network on a dataset with millions of images. A task that could take days on a CPU might only take hours on a GPU due to its parallel processing capabilities.

More About GPU

Tensor Processing Units (TPUs) are Application Specific Integrated Circuits (ASIC), developed by Google, designed to accelerate TensorFlow, a popular machine learning framework.

Examples: Apple neural engine and Intel’s Gaudi AI processorBest for: TPUs are built to enhance the speed and efficiency of TensorFlow applications, making them particularly suitable for tasks that can leverage this specific framework.Application: TPUs are commonly used in advanced Google services like Google Search and Google Photos, where rapid data processing and model improvements are continously required.

More About TPU

Language Processing Units (LPUs) are specialised processors designed to excel in natural language tasks such as translation and sentiment analysis.

Groq, a new player, in the AI hardware industry, is pioneering the development of LPUsBest for: LPUs are suitable for applications that require processing complex language data efficiently.Example: LPUs power advanced chatbots, enabling them to understand and respond to human queries quickly and accurately, improving user interactions in customer service settings.

More About LPU

CPUs are suitable for general-purpose computing and less complex AI tasks.GPUs are the go-to for large-scale data processing and deep learningTPUs offer the best performance for TensorFlow-based applications.LPUs excel in handling optical data for imaging and real-time analysis.

Selecting the right AI hardware

As Artificial Intelligence (AI) technology continues to evolve, need for understanding the role of specialised hardware that power AI applications is important. From training machine learning models…

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Technology & The Future

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Computer Science

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Artificial Intelligence

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Software Engineering

A Beginner’s guide to AI Processors: CPUs, GPUs, TPUs and LPUs

Never give up just because you’ve failed once ,great people failed several times until they’ve accomplished great things ,remember failure is the first step to success ,never let the feelings of despair get to you and affect your dreams and goals .

Learn To Never Give Up

Don’t let failure pull you down! Learn from it ! Go back and see where you went wrong and IMPOVE. If you fail again ,IMPROVE ,until you make it .

Failure Leads To Success

Understand yourself and those around you.

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Psychology

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Personal Development

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Mental Health

Failure And Giving Up And How To Overcome Them 

Empiricism champions experiential knowledge, prioritizing perceptions gleaned through the five senses over innate ideas. This idea evolved into various strands such as Phenomenalism, Positivism, Scientism, and Logical Positivism, each refining the core principle in distinct ways.Simple Justification:Proposition 1: Everything we know comes from what we see, hear, feel, taste, and smell.Proposition 2: Not everyone believes the same things naturally from birth.Conclusion: Relying on what we experience through our senses, rather than ideas we're born with, makes sense for understanding the world.

Empiricism

Rationalism argues that knowledge isn't gained through experience but through innate ideas or logical reasoning. This idea influences the creation of foundationalism, intuitionism, and trancendental idealism.Simple Justification:Proposition 1: We're born with some knowledge already in our minds.Proposition 2: We can figure out more by using our brains to think things through, not just by experiencing them. Conclusion: Rationalism makes sense because it shows that our thinking and innate ideas are important for learning, not just what we see or feel.

Rationalism

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Philosophy

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Society, Arts & Culture

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Science & Nature

Theories of Knowledge Acquisition

Skepticism is a Hellenistic school of philosophy. It holds that one should refrain from making truth claims, and avoid the postulation of final truths. This is not necessarily quite the same as claiming that truth is impossible (but some thinkers argue abouy it). It is often also used to cover the position that there is no such thing as certainty in human knowledge.

Doctrine Of Scepticism

Gorgias claimed that nothing exists; or, if something does exist, then it cannot be known; or if something does exist and can be known, it cannot be communicated. Socrates claimed that he knew one and only one thing: that he knew nothing. Thus, rather than making assertions or opinions, he set about questioning people who claimed to have knowledge.Pyrrho advocated suspending judgment on all matters, arguing that certainty is unattainable and that embracing doubt leads to tranquility (ataraxia).

The Skeptics

Skepticism challenges the notion of absolute certainty, encouraging individuals to approach knowledge with doubt and humility, ultimately leading to a state of tranquility and open-mindedness.

Conclusion

Skepticism

A dilemma is a situation requiring a choice among alternatives or options, none of which is ideal or perhaps even desirable. No matter which option is selected, there will be undesirable consequences.

There are 5 dilemmas in Entrepreneurship Pedagogy

Having a structured environment is easier for both the entrepreneurship educators and students, but it creates an artificial academic environment that bears little resemblance to the uncertain and even chaotic environment within which entrepreneurs must operate. This will undermine students’ entrepreneurial training and can lead to inaccurate perceptions of entrepreneurial careers.

#1 Pedagogical Structure < -- > Experience with Uncertainty and Ambiguity

Entrepreneurship educators face a dilemma in deciding if the learning environment should be more unstructured or not.

Giving realistic feedback to entrepreneurship students will help them address their weaknesses but this may affect their self-efficacy and confidence in starting a business.

#2 Entrepreneurial Self-Efficacy < -- > Realistic Feedback

Entrepreneurship educators face a dilemma in deciding how much honest feedback they should give to their students.

Entrepreneurship education needs to be anchored in real world environments (Edelman, Manolova, & Brush, 2008), but university-level education is generally less vocational.

#3 Practicality < -- > Universality

Entrepreneurship educators can cover practical topics to better prepare students for an entrepreneurial career and lower the threshold for starting their first business, but it is difficult for an instructor to be well-versed in all of domains of practical entrepreneurship knowledge.

Entrepreneurship educators face a dilemma in deciding if their teaching should be more practical or universal.

Entrepreneurs often copy the success of others. Imitation is an important, valid, and (usually) ethical technique employed by entrepreneurs. But the risk for entrepreneurs in imitating the success of others is that they may not fully understand how that success was achieved.

#4 Imitation Skill < -- > Understanding

Students generally do not have a full understanding of that which they are copying. Unlike entrepreneurs, they do not have access to “real world” feedback to guide trial and error learning.

Entrepreneurship educators face a dilemma in deciding how much to encourage and facilitate imitation.

Entrepreneurship educators face a dilemma in deciding whether or not to encourage students to become entrepreneurs.

#5 Fostering Entrepreneurial Preferences < -- > Finding Entrepreneurial Preferences

If entrepreneurship educators encourage all students to become entrepreneurs, then they may direct some students to careers that are not right for them.

Powell, B. c. (2013). Dilemmas in Entrepreneurship Pedagogy, Journal of Entrepreneurship Education, vol. 16, pp.99–112

startup

Startups

Sui 😂 The laughter emoji is there because... I almost decided not to talk about this blockchain again. It's quite complex. Sui is a permissionless layer 1 blockchain powered by the Move programming language. A little story lol

Me And DYORing

Maybe you've not heard of Morgan Beller...As at 2017, she started working on Libra. Libra was supposed to be a permissioned blockchain powering the $LIBRA supposedly to be a stablecoin.Well, apparently, Meta engaged on a mission impossible because that dream was never ever birthed. I don't know if I should feel bad...buh Zucks tried his best.Libra was announced around Dec 2019. It faced oppositions, so tsunamic that our esteemed Zuckerberg couldn't hold on to it.

... Meta's Dreams 💤

Libra was supposed to be a blockchain that will power a stablecoin native to Alphabet (Meta's ) incorporations -all the holdings under Meta. So, we're talking about something that will be like Ton blockchain of Telegram. Libra would have been across Facebook, Whatsapp, Messenger, Instagram....you name it.

...Libra

Mark's vision was : to make financial payments and transactions as easy as sending a message. Well, Libra was later named Diem on Dec., 2020. However, Diem shut down Jan. 2022. Quite tragic but wait for it....

Mark Zuckerberg's dream

Boom 💥💥💥 out of the ashes of eternal incarceration arose the fantastic 5. Evan Cheng, CEO Chief Executive Officer Adeniyi Abiodun, CPO Chief Product Officer Sam Blackshear, CTO Chief Technology Officer George Danezis, CS Chief Scientist Kostas Chalkais, CC Chief Cryptographer

F@ntastic 5

This five had been in meta since the inception of the Libra project working tirelessly... Long story cut short...they left Meta and birthed Sui. 😀

...Story Ends, Technicals Begin...

Sui's native token is $SUI.It's a utility token -it is used to pay the gas fees.It's also used for governance in the ecosystem.$SUI is also used to incentivize engagements in the Blockchain.

Let's get back to the technicalities...

Of course, if you can recall, last week Friday we treated Arbitrum (an L2), SUI is L1. Use this analogy, Arbitrum is a L2 built on a L1, Ethereum. So Ethereum is the baseblockchain. It's not built on any other blockchain, that's why it's layer 1. The same way, Sui is layer 1. It was not built on any blockchain.

Layer

Their consensus mechanism is the dPOS. Delegated Proof of Stake. Basically, it functions like POS in that validators (NB not miners this time, miners operate in POW) stake their tokens in order to validate and approve transactions with the accompanied addition of blocks to the Blockchain. However, this time ie in dPOS, validators need to be delegated.

Consensus

This is how it works... Validators are chosen in each epoch. An epoch is 24hrs in the Sui ecosystem. They're chosen by users who delegate their staked coins (in this case $SUI). First, users stake their $SUI, and secondly they delegate it to a particular validator. Every epoch -24hrs- (a) user(s) can delegate entirely different validators or same validator(s)

dPOS

From my POV and myDYOR... Sui is geared at ensuring that web3 is largely scaled and massively adopted. They have several mechanisms put in place to achieve this purpose. Talk about <ul><li>Byzantine fault proof systems. bla bla bla 😂😂</li><li>Directed-acyclic-graph-mempools you don't want me to go into it...it's maths and all</li><li>narwhals and bullshark</li><li> sponsored gas fees enabling gasless transactions </li><li>object-centric...and horizontal transactions processing mechanisms...</li></ul> It's a whole lot

Why Sui?

For me, Bitcoin is the King, Ethereum is the Queen, Core is The Prince, I don't know which is the Princess. Libra beget Aptos and Sui.

crypto

Cryptocurrency

product

Product & Design

Backcasting is a research method in future research to plan the future, which involves envisaging alternative futures.

Essence of backcasting

Backcasting involves envisioning a desirable future and then working backward from that future to the present. This approach helps determine the feasibility of ideas or projects. Essentially, it’s about planning for the future by starting from the end goal and figuring out the steps needed to get there. 🌟

How does it work?

Backcasting is a research method that plans the future, which starts with defining a desirable future and then works backward to identify policies and programs that will connect that specified future to the present. It is used to assess the feasibility of an idea or project.

Unlike forecasting, which predicts the future based on current trends, backcasting envisions a specific future outcome and determines the steps needed to achieve it.

Forecasting vs Backcasting

Typically backcasting is applied on long-term complex issues, involving many aspects of society as well as technological innovations and change.

<ul><li class="ql-align-justify">the problem to be studied is complex, affecting many sectors and levels of society</li><li class="ql-align-justify">there is a need for major change, ie. when marginal changes within the prevailing order will not be sufficient</li><li class="ql-align-justify">dominant trends are part of the problem, these trends are often the cornerstones of forecasts</li></ul>

Use backasting when...

The result of a backcasting study is usually an alternative images of the future, thoroughly analysed as to their feasibility and consequeces. For example, they are made to high-light polarities, like solar Sweden VS unclear Sweden.

Result of a backcasting study

A backcasting study is meant to provide input to a policy-forming process, with many actors. It is addressed to many actors such as political parties, governmental authorities, municipalities, organisations, private enterprises, and an informed general public.

Stakeholders of a backcasting study

Backcasting studies should aim for a widening perception of possible solutions among various actor, and highlight consequences of strategic choices in society.

Aim of study

Dreborg, K.H. (1996) ‘Essence of backcasting’, Futures, 28(9), pp. 813–828.

Discover the world of business and economics.

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Economics

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Strategy

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Politics

Altruism, or ethical altruism, is a moral philosophy that advocates for individuals to aid, serve, or benefit others, potentially at the expense of their own interests. Specifically, an action is considered morally right if its outcomes are more beneficial than harmful to everyone but the person performing the action.

Altruism

The term "altruism" (initially derived from the Latin "alter" meaning "other") was coined by Auguste Comte, the French founder of Positivism, in order to describe his ethical doctrine, which he summed up in the phrase: "Live for others". In more general terms, Altruism is selfless concern for the welfare of others (although its common usage does not necessarily entail any ethical obligation).

Etymology Of Altruism

Altruism is frequently viewed as a subset of consequentialism because it evaluates the ethical correctness of an action based on its beneficial consequences for others. While similar to utilitarianism, which advocates for actions that maximize positive outcomes for all of society, altruism specifically calls for actions that maximize benefits for everyone but the individual taking the action.

Philosophize

“If you can't feed a hundred people, then just feed one.”

Altruism promotes the well-being of others and can lead to a more cooperative and harmonious society by encouraging acts of kindness and support.

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History

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