The photos I take, the movies I buy, the music I rent, the emails I write and receive, the messages I send - all of these are captive. They exist within a database controlled by Google, Netflix, Spotify, Gmail, WhatsApp. If these services disappear, so does my ownership/rentership record. In a future where digital assets are worth not $10 or $20, but hundreds or thousands of dollars, ownership that survives a company becomes an essential substrate of commerce.

A permanent ownership record that exists beyond and outside a company

Internet hegemons have decimated entire spaces: social networks, advertising technology, video streaming and rental, paid email, infrastructure. Their economies of scale and network effects mount significant barriers to competition. What’s a startup to do? Compete on a different axis: reward users with tokens. A social network rewards its most valuable users in the coin of the realm. As the network becomes more valuable, so does the user’s stake in the company. Web3 companies employ tokens to reward their customers for providing value, giving startups the upper hand.

Paying customers in “equity.”

Twenty years ago, startups IPOed after 4 years. Today, it’s 12, driven by several factors but regulatory costs present the principal one. Crypto companies access pools of capital web2 companies cannot because the regulation doesn’t exist. Where nascent rules are present, the regulation isn’t yet a warren of legalese- yet. Within this freedom to maneuver, Defi protocols invent new financial instruments. The <a href="https://research.paradigm.xyz/cartoon-guide-to-perps">perp</a>, a perpetual swap, has become the most traded crypto derivative). Perps don’t exist outside crypto.

Regulatory arbitrage.

Open-source software is arguably the most important motive force powering innovation in technology. Open-source software powers every server and most software. Crypto empowers open-source projects to monetize their innovation in a way web2 never achieved. DAOs bind the loose community of open-source software contributors through tokens. Tokens provide an ongoing financial link that aligns long-term incentives. Foundations with significant token stakes fuel the ongoing protocol development, balancing the capitalism needed to fuel progress with the benevolence of the open-source ethos.

DAO/Foundations:

The fifth cluster of innovation benefits central banks, not startups.CBDCs (Central Bank Digital Coins) are programmable money: central bank digital coins enable a government to focus stimulus as granularly or as broadly as they like. Imagine a reserve bank stimulating the electric bicycle industry in the Kansas City metropolitan area by providing residents new US digital dollars that are only valid within bike shops in Kansas City.

Bonus: great for central banks

As I’ve explored web3 I’ve been forming a mental model of the major innovations powering this enormous wave of innovation. At the moment, I see four clusters:
 A permanent ownership record that exists beyond and outside a company. The photos I take, the movies I buy, the music I rent, the emails I write and receive, the messages I send - all of these are captive. They exist within a database controlled by Google, Netflix, Spotify, Gmail, WhatsApp.

crypto

Cryptocurrency

technologyandthefuture

Technology & The Future

entrepreneurship

Entrepreneurship

startup

Startups

product

Product & Design

Four Fundamental Innovations of Web3 that Will Upend Web2 Incumbents by @ttunguz 

There was a time when the internet was seen as a source of good. It propelled progressive social movements and set information free. But today, the internet plays a vital role in steering mindsets and retreating democracy - from fake news bots to misinformation to conspiracy theories. The paradox - that the internet is both saviour and executioner of democracy - can be understood through the lenses of classical economics and cognitive science.

The shift of the internet

In traditional markets, firms make goods to satisfy the preferences of consumers. But the market on social media and the internet exists to serve the needs of the advertisers, not the consumers. These markets sell information about their users to advertisers. On social media, users"pay" for free services by giving up their data to unspecified third parties who use it to expose them to tailored ads. This economic model is driving online platforms to exploit their users' cognitive limitations and vulnerabilities.

The internet as saviour and executioner of democracy

A strategy to maximize advertising revenue when the interests of the online platform do not align with the user's interests is to present users with surprising or sensational content to keep them engaged. A study by Mozilla researchers found that YouTube actively recommends sensational content to keep users engaged. Our attention is negatively captured by either negative or awe-inspiring news. To grab our attention, digital platforms offer misinformation that feeds outrage and anger. For example, Facebook's newsfeed curation algorithm favours content eliciting anger and negative ads.

In pursuit of our attention

When people use social media, they are not always aware that they are the passive subjects of commercial transactions between the platform and advertisers involving their own personal data. Users are also often unaware of how their news feed on social media is curated. Even people who are aware of algorithmic curation tend not to fully understand what that involves. However, people often object to collecting sensitive information and data for personalization.

Users are often unaware

Protecting citizens from manipulation and misinformation and protecting democracy itself requires redesigning the current online “attention economy”. The redesign must restore the signals that are available to consumers and the public in conventional markets: users need to know what platforms do and what they know, and society must have the tools to judge whether platforms act fairly and in the public interest.

Shifting the balance of power 

<ol><li>There must be greater transparency and more individual control of personal data. </li><li>Platforms must signal the quality of the information in a newsfeed so users can assess the risk of accessing it. “Endogenous” cues could alert us to emotionally charged words designed to provoke outrage.</li><li>The public should be alerted when political speech circulating on social media is part of an ad campaign. Paid ads masquerading as independent opinions distort that marketplace.</li><li>The public must know exactly how algorithms curate and rank information. The public should be able to shape their own online environment.</li></ol>

Online regulation 

There is considerable public and political scepticism about regulations. Governments that step in to regulate social media content, if done improperly, could result in censorship. In liberal democracies, regulations must not only be proportionate to the threat of harmful misinformation but also respectful of fundamental human rights. The best solution lies in shifting control of social media from unaccountable corporations to democratic agencies that operate openly, under public oversight.

Concerns with online regulation

Attaining a more transparent and less manipulative online media.

Achieving a more transparent and less manipulative online media may well be the defining political battle of the 21st century.

marketingandsales

Marketing & Sales

artsandculture

Society, Arts & Culture

softwareengineering

Software Engineering

Algorithms, lies, and social media

<ul><li class="ql-align-justify">Information could become the fifth state of matter alongside gas, plasma, liquid, and solid states.</li><li class="ql-align-justify">A scientist has proposed an experiment involving particle annihilation that could establish that information truly has mass.</li><li class="ql-align-justify">If successful, the experiment could shed light on the mysterious dark matter in our universe—and help us manage the future of data storage.</li></ul>

Key Findings

Scientists want to use an experiment to confirm that <a href="https://www.popularmechanics.com/science/a36701159/charm-mesons-particle/">elementary particles</a> have measurable mass. It would involve a matter-<a href="https://www.popularmechanics.com/space/deep-space/a34272429/how-much-matter-is-in-the-universe/">antimatter</a> annihilation process that would shoot a beam of positrons at electrons in a piece of metal. Positrons and electrons are both subatomic particles, with the same mass and magnitude of charge. However, <a href="https://www.popularmechanics.com/space/deep-space/a37224743/physicists-generate-antimatter-in-the-lab/">positrons</a> are positively charged, and electrons are negatively charged. A sheet of metal has many free electrons, increasing the probability of collision with the incoming positrons.

Information Being A Form Of Matter: The backstory

Scientists believe that the observable matter in the universe has specific information content. For example, typical atoms—containing protons, electrons, and neutrons—hold not only the combined masses of these subatomic particles, but also the minuscule masses of the information they require to interact with each other and the rest of the universe. This type of information could be considered the <a href="https://www.popularmechanics.com/science/a33327626/scientists-encoded-wizard-of-oz-in-dna/#:~:text=%22A%20teaspoon%20of%20DNA%20contains,internet%20in%20a%20shoe%20box.%22">“DNA”</a> of the particles.

A New Concept of Matter

The amount of information we have today is staggering. Each day on Earth, we generate 500 million tweets, 294 billion emails, 4 million gigabytes of Facebook data, 65 billion WhatsApp messages, and 720,000 hours of new content added daily on YouTube.The total amount of data created, captured, copied, and consumed in the world was 59 zettabytes in 2020.One zettabyte is 8,000,000,000,000,000,000,000 bits.Proving that information has mass through physical experiments is the first step toward finding a possible solution to the problem of explosive information growth.

Information Generated Every Day

Proving that information has mass can explain mysteries like dark matter. That’s because the physical properties of the bits of information mimic what dark matter appears to be—small bits of mass particles without charge or spin.Confirming that information is the fifth state of matter touches on a weird idea: that the universe is actually a computer simulation. As an academic exercise, scientists have <a href="https://watchdocumentaries.com/the-simulation-hypothesis/">suggested this idea before</a>. If information is indeed a key component of everything in the universe, then perhaps a computer somewhere is running our whole world as a simulation.

Beyond Our Earthly Problems: The Universe May Be A Simulation After All

If true, this idea could even help us understand all of the dark matter in our universe.

scienceandnature

Science & Nature

space

Space

Information Could Be the 5th State of Matter, Proving We Live in a Simulation

Are we living in a computer simulation?The question seems absurd. Yet there are plenty of smart people who are convinced that this is not only possible but perhaps likely.Just as Neo in The Matrix finds out that his whole life has been in a computer simulation, and the reality is completely different from everything he knew and experienced his whole existence, a new paper claiming that the entire universe is a computer simulation has shaken the heads of people all over the world.

We May Be Inside A Video Game

In an influential paper that laid out the theory, the Oxford philosopher <a href="https://www.simulation-argument.com/simulation.html">Nick Bostrom</a> showed that at least one of three possibilities is true:1) All human-like civilizations in the universe go extinct before they develop the technological capacity to create simulated realities;2) If any civilizations do reach this phase of technological maturity, none of them will bother to run simulations;3) Advanced civilizations would have the ability to create many, many simulations, and that means there are far more simulated worlds than non-simulated ones.

The Theory

The simulation hypothesis is the modern equivalent of an idea that’s been around for a while. For example, in Hindu culture, the world around us is called Maya, an illusion.A fresh version of the idea is that the physical world that we live in, including the Earth and the rest of the physical universe, is actually part of a computer simulation.

The Simulation Hypothesis

In The Matrix, Keanu Reeves plays the character Neo, who meets a guy named Morpheus, who is aptly named after the Greek god of dreams, and Morpheus gives him a choice of taking the red pill or the blue pill. And if he takes the red pill, he wakes up and realizes that his entire life, including his job, the building he lived in, and everything else, was part of this elaborate video game, and he wakes up in a world outside of the game.

The Matrix

There are lots of mysteries in physics that are better explained by the simulation hypothesis than by what would be a material hypothesis.There’s much we simply don’t understand about our reality. It’s more likely than not that we are in some kind of a simulated universe. Now, it’s a much more sophisticated video game than the games we produce, just like today World of Warcraft and Fortnite is way more sophisticated than Pac-Man or Space Invaders.

This World Being A Software Program

Everything we see as physical is really the result of bits of informationComputers do follow rules, but the fact that the rules always apply doesn't rule in or rule out that we could be part of a computer simulation.If we are conscious beings, we are more likely to be a simulated beings than biological ones because it’s so quick and easy to create them.

The Question Of Us Being Real Or Simulated

There are 10 stages of technology development that civilization would have to go through to get to the simulation point, which is the point at which we can create a hyperrealistic simulation like this. We’re at about stage five, which is around virtual reality and augmented reality. Stage six is about learning to render these things without us having to put on glasses, and the fact that 3D printers now can print 3D pixels of objects shows us that most objects can be broken down as information.

The Simulation Stages

We all may not be real, but just a player in an elaborate video game.

Why this computer scientist thinks we’re probably living in the Matrix.

sciencefiction

Science Fiction

Are we living in a computer simulation? I don’t know. Probably.

Arts and humanities are fundamental pillars of any education system and more important than ever. While education in Science, Technology, Engineering and math (STEM) is important, it is not enough. Tomorrow's generations need to become versed in empathy, imagination, and creativity. Integrating the arts into STEM education is a necessary strategy to reduce the skills gap of the next generation. But empathy, imagination and creativity are required to ensure that science and technology are developed in a human-centred way.

Reducing the skills gap

Art is necessary to build an emotional framework to make sense of the dialogues at the core of the Fourth Industrial Revolution. Art and culture build the trust needed to bridge conflicting views and interests, overcome obstacles with dynamic and innovative approaches and understand the value embedded in any process of technological innovation.

Trust in technology

Art and design enable us to deep dive into the consequences of futuristic “what if” scenarios. A series of artworks can express and critique values before they are embodied in technology. Art provides cognitive and emotional tools to design the future and make creative breakthroughs in unexpected and emotional ways.

Embedding art and design into prototyping

The Fourth Industrial Revolution is transforming health. It has the potential to make it more patient-centric, affordable and accessible. Agi Haines designed a series of speculative designs that imagine which parts of various animals could be used in combination with human tissue to solve common health problems. Circumventive Organs show the messy reality behind commoditizing biological material, and its potential to help people in need.

Shaping the future of health

We need the arts to stimulate debate over the impact of technological breakthroughs on society

Here’s how art is inspiring the Fourth Industrial Revolution

The next wave of digital tech, or “smart tech,” has the potential and power to help us rehumanize work. Smart tech creates an opportunity to redesign jobs and re-engineer workflows to enable people to focus on the parts of work that humans are particularly well-suited for, such as relationship building, intuitive decision making, empathy, and problem solving. But it will require organizational leaders to make informed, strategic decisions to ensure the technology is used to enhance our humanity and enable people to do the kinds of relational, empathetic, and problem-solving activities.

Human Tech: The Potential

The Great Resignation wasn’t created by the pandemic so much as supersized by it. The unwillingness of workers to rush back into cubicles, behind counters, onto assembly lines, and behind the wheel is a direct result of work cultures that too often default to suspicion, inflexible schedules, and unrealistic workloads. The virtual and flexible work arrangements necessitated by the pandemic were revelatory for many people, but didn’t free them from the 24/7 onslaught of tasks, back-to-back meetings, and <a href="https://hbr.org/2016/03/actually-you-should-check-email-first-thing-in-the-morning#:~:text=Despite%20studies%20showing%20that%20the,re%20emailing%20more%20than%20ever.">emails</a> created by <a href="https://www.microsoft.com/en-us/worklab/work-trend-index/brain-research">always-on cultures and technologies</a>.

The Scenario As Of Today

There will be parts of jobs that are <a href="https://www.aeaweb.org/articles?id=10.1257/pandp.20181019">suitable for automation</a>, but few, if any, that can (or should!) be completely replaced by smart tech. What automation can change for the better is the experience of work. Rather than doing the same work faster and with fewer people, smart tech creates an opportunity to redesign jobs and reengineer workflows to enable people to focus on the parts of work that humans are particularly well-suited for, such as relationship building, intuitive decision making, empathy, and problem solving.

What To Automate, What To Assist

Companies will be making many choices about automation in the next few years. And those decisions will influence how employees, customers, and other stakeholders perceive your company going forward. Should your company choose:<ul><li>Bossware — technology that’s lurking in the background of screens watching employees all day to catch, and presumably punish, anyone taking an unscheduled break?</li><li>Software like CultureX, which can measure and improve workplace culture so that it’s less toxic, increasing employee work-life balance while decreasing the levels of burnout that lead to turnover?</li></ul>

The Choice Of Technology

Organizational leaders are going to face many choices when it comes to smart tech in the near future. Commercial applications using smart tech are available off-the-shelf for every department from communications to accounting to service delivery. It will require informed, careful, strategic thought to ensure the technology is used to enhance our humanity and enable people to do the kinds of relational, empathetic, problem-solving activities we do best.

Leaders Have To Choose

So how do you get started introducing smart tech within your own organization? Here are a few initial steps you can take:Identifying Key Pain Points: These should focus on areas where smart tech can take over rote tasks that can streamline unmanageable workloads and reduce worker stress. Outline exactly what tasks and decision-making people will retain and what tasks will be automated when the system is implemented. This includes identifying how automation will be supervised by someone with subject matter expertise.

Getting Started: Identifying Key Pain Points

Make sure the product or system you choose will create the right human-tech balance. Ensure that the assumptions built into the smart tech align with your values. And be sure that the tasks that require empathy and intuition will be assigned to people, while tasks such as data entry or analyzing huge swaths of data will be assigned to smart tech — and not the other way around.

Choose the Right Smart Tech for The Job

Step carefully and slowly, because it can be difficult to undo the harms of automation once the smart tech is in place. Pilot test the new system and workflow to ensure that your hopes and assumptions are correct.

Create a Virtuous Cycle of Testing, Learning, and Improving

The Trevor Project is an example of what we call a "Smart Nonprofit" - an organization that has stepped carefully and wisely into automation by understanding "cobotting," the combination of people and smart tech that brings out the best in both.They created Riley, a chatbot that helps train counselors by providing real-life simulations of conversations with potentially suicidal teens.Riley expands the training capacity of the organization enormously by always being available for a training session with volunteers.

The Trever Project

Smart tech and automation can make work and workplaces more fulfilling and less exhausting. But doing so requires leaders to dig into the implications of automation and make smart, ethical choices about using tech that enhances our humanity and makes work better, healthier, and happier for everyone.

The Bottom Line

Technology needs to assist, not replace humans.

Automation can free us up to focus on the parts of our jobs we find most meaningful.

problemsolving

Problem Solving

artificialintelligence

Artificial Intelligence

Using Technology to Make Work More Human

Some neural networks are very expensive to train. This led to the popularization of an approach known as pre-training, whereby a neural network is first trained on a large general-purpose dataset using significant amounts of computational resources, and then fine-tuned for the task at hand using a much smaller amount of data and compute resources.

Expensive to train?

The use of pre-trained networks allows a startup, for example, to build a product with much less data and compute resources than would otherwise be needed if starting from scratch. This approach is also becoming popular in academia, where researchers can quickly fine-tune a pre-trained network for a new task, and then publish the results.

Pre-trained networks give smaller teams a leg up


Pre-training has continued to evolve with the emergence of foundation models such as <a href="https://ai.googleblog.com/2018/11/open-sourcing-bert-state-of-art-pre.html">BERT</a>, GPT, <a href="https://openai.com/blog/dall-e/">DALL-E</a>, <a href="https://openai.com/blog/clip/">CLIP</a>, and others. These models are pre-trained on large general-purpose datasets (often in the order of billions of training examples) and are being released as open source by well-funded AI labs such as the ones at Google, Microsoft, and OpenAI.  They allow startups, researchers, and others to quickly get up to speed on the latest machine learning approaches without having to spend the time and resources needed to train these models from scratch.

Foundational models

One of the risks associated with foundation models is their ever-increasing scale. Neural networks such as <a href="https://github.com/google-research/text-to-text-transfer-transformer">Google’s T5-11b</a> (open sourced in 2019) already require a cluster of expensive GPUs simply to load and make predictions. Fine-tuning these systems requires even more resources. More recent models created in 2021-2022 by Google/Microsoft/OpenAI are often so large that these companies are not releasing them as open source – they now require tens of millions of dollars to create and are increasingly viewed as significant IP investments even for these large companies.

The risks of foundation models: Size & Cost

Dataset alignment can also be a challenge for those using foundation models. Pre-training on a large general-purpose dataset is no guarantee that the network will be able to perform a new task on proprietary data. The network may be so lacking in context or biased based on its pre-training, that even fine-tuning may not readily resolve the issue.  Any startup leveraging foundation models in its machine learning efforts should pay close attention to these types of issues.

The risks of foundation models: Outsourced innovation

The opportunities and risk around using hosted and pre-trained models has led many companies to leverage cloud APIs in the “experimentation phase” to kickstart product development. ﻿Once a company has determined it has a product-market fit, it often transitions to self-hosted or self-trained models in order to gain more control over data, process, and intellectual property. This transition can be difficult, as the company needs to be able to scale its infrastructure to match the demands of the model, as well as manage the costs associated with data collection, annotation, and storage.

The tradeoff 

Foundation models and cloud APIs bring opportunities, risks, and limitations for startups that want to innovate in AI and machine learning.

How to Use Massive AI Models (Like GPT-3) in Your Startup

As software and algorithms become an increasingly pervasive part of our lives, there’s growing interest and concern about how they are affecting society, the economy, and politics.Yet, most social studies of algorithms perceive them as obscure black boxes that function autonomously. This isolated look at algorithms, which separates them from their human elements leads us to the wrong understanding and conclusions.

The World Of Algorithms

When a group of computer scientists, researchers, or engineers gather to create an algorithm, they are initially driven by a set of elements.These elements define the problem they want to solve and determine the type of data they need to validate their algorithm.Once the problem is formulated, the researchers must establish the ground truth by collecting the right material that enables them to verify their algorithms and the models they will build in the future.

Elements Of An Algorithm: Ground Truthing

Eventually, an algorithm moves to the programming phase, where a set of modules and a list of instructions are created to solve the defined problem.While this phase is usually reduced to pure source code, there is a lot more to programming than that. The most overlooked aspect of programming practices is all the small provisionary inscriptions that accompany the writing of programs.A better understanding of the whys and wherefores of programming practices would perhaps make it possible to try to infuse this specialness into the algorithmic design communities.

Elements Of An Algorithm: Programming

<ul><li>When an algorithm is implemented and verified against the ground truth, it becomes formulated into a mathematical object that can be later used in other algorithms. </li><li> Once proven, these algorithms become abstracted, taken as proven claims that need no further investigation.</li><li>Algorithms, once formulated, become the foundation of other algorithms, where they will contribute to ground-truthing, programming, formulation, and other practices. </li><li>They become the basis and components of other algorithms and contribute to further work in science.</li></ul>

The Formulation Of The Algorithm

This was always in our minds but we didn't know whom to ask.

Most social studies of algorithms perceive them as obscure black boxes that function autonomously. This isolated look at algorithms leads us to the wrong understanding and conclusions.

computerscience

Computer Science

Here’s how algorithms are made

Google is the most powerful tool in the world if you know how to use it properly. Let me show you how to get better at Googling.

How to use Google - Search tips for better results

You can use quotes to force an exact-match search. This is super useful if you know exactly the search phrase you're looking for. You'll simply get more accurate results if you do this.eg. "what is javascript"

Use Quotes for Exact-Match Search

The AND operator will return only results related to both terms. In the example below you can see the perfect use-case of this operator.eg. html AND css

Use the AND Operator

You can use the OR operator to get results related to one of the search terms you enter.eg. (javascript OR python) free course

Use the OR Operator

The -﻿ operator will exclude results that contain a term or phrase. Let's say we want to get JavaScript-related results, but exclude any CSS results from them.eg. javascript -css

Use the - (minus) Operator

You can use the (*) wildcards as placeholders, which will be replaced by any word or phrase.You can use it when you know almost the whole search phrase. Just replace the part you don't know with an asterisk. eg. "how to start * in 6 months"

Use (*) wildcards as placeholders

If you want to search for something in particular on a specific website, this should be your approach.eg. site:freecodecamp.org

Search Inside a Single Website

You can also use this very useful feature to help you find a specific file type. It's handy if you're looking for some materials like PDFs. If you haven't used it before, from now on you will.eg. filetype:pdf learn css

Find a Specific File Type

This can be anything at all. If you're looking to buy something that falls within a specific price range, or you're searching for results that include a specific range of years, this is for you.eg. ecmascript 2016..2018

Search for a Range of Numbers

Use the before operator to return only results before a given date.You must provide year-month-day dates or only a year. eg. javascript before:2020

Use the before Operator

Use the after operator to return only results after a given date. You must provide year-month-day dates or only a year. Super useful if you want to exclude outdated results.eg. web development after:2020

Use the after Operator

As someone who has to search a lot of materials for my day to day affairs, this simple but effective hacks are a time saver!

Google is the most powerful tool in the world if you know how to use it properly. Let me show you how to get better at Googling. 1. Use Quotes for Exact-Match Search You can use quotes to force an exact-match search. This is super useful if you know exactly

How to Use Google – Search Tips for Better Results

Recurrences take place due to ascertainable circumstances and chains of causality.An example is the phenomenon of multiple independent discovery in science and technology, . Indeed, recurrences, in the form of reproducible findings obtained through experiment or observation, are essential to the natural and social sciences; and, in the form of chance observations rigorously studied via the comparative method, are essential to the humanities. If history has lessons to impart, they are to be found par excellence in such recurring patterns. The reason why I like history.

The repetition of similar events in history

In the field of observation, chance favors only the prepared mind." Discovery, like learning, is a phenomena that takes place in the human brain. The brain configures an event as a new pattern based on previous assumptions that were present at the onset of the event.

Chance Observation. 

History repeats itself. it's all about patterns. 

Understand yourself and those around you.

psychology

Psychology

philosophy

Philosophy

history

History

Historic recurrences. 

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