odei

Construction work has started to restore and re-open a former Edinburgh southside Odeon including plans for a dancefloor and cinema.

Work begins to transform deserted Edinburgh Odeon into new cinema and nightclub - Edinburgh Live

: This article aims to clarify that the code provided is not a universal solution for all aspects of mathematical modeling. Instead, it serves as an educational tool, highlighting a specific step in the mathematical modeling process and employing Python for illustrative purposes, with the primary goal of enhancing awareness in this field. Disclaimer It is also important to remember that there are specific measures you must take when submitting/proposing a mathematical model project, such as one related to the field of biomathematics. These steps include, but are not limited to: defining the issue, selecting a model approach (two models will be discussed in this article), formulating equations, parameter estimation—often based on historical data, implementing numerical simulations by resolving differential equations analytically or using computational tools like and MATLAB, validations and sensitivity analysis, scenario testing, result interpretation, and so on. Python As I said earlier, this only highlights a specific step in the mathematical modeling process and employing Python for illustrative purposes. Content Overview Introduction The Purpose of Simulation The SIR Model What It Does / SIR Python Code Simulation Example What You Can Learn Understand Disease Spread Explore Parameter Sensitivity Evaluate Interventions The SEIR Model What It Does / SEIR Python Code Simulation Example What You Can Learn Model Latent Periods Evaluate Early Interventions Study Complex Outbreaks Conclusion 1. Introduction Understanding how infectious diseases spread is essential for maintaining the public's health because they have existed throughout human history for centuries. A potent tool for simulating and understanding the dynamics of disease spread is mathematical models. The (Susceptible-Infectious-Recovered) and (Susceptible-Exposed-Infectious-Recovered) models will be discussed in this article, along with how to simulate them using Python. SIR SEIR What Simulations Are For For public health professionals and epidemiologists, simulation is like a crystal ball. It enables us to foresee the potential spread of diseases under various circumstances and treatment options. These models aid in decision-making, effective resource allocation, and comprehension of the potential effects of various techniques. Let's examine two basic models namely; SIR Model, and SEIR Model. 2. The SIR Model What It Does / SIR Python Code Simulation Example The Susceptible, Infectious, and Recovered (SIR) model separates a population into these three categories. Based on variables like transmission rate ( ) and recovery rate ( ), it simulates how these compartments alter with time. β γ Before we exemplify a simulation using Python, it’s necessary to make “model assumptions” when working on mathematical models. In our assumption we’ll create model using LaTeX formular or code: \begin{align*}
\frac{dS}{dt} &= -\beta \cdot S \cdot I \\
\frac{dI}{dt} &= \beta \cdot S \cdot I - \gamma \cdot I \\
\frac{dR}{dt} &= \gamma \cdot I
\end{align*} Note: You can latexify this formular using Python. An example can be found on . https://github.com/google/latexify_py/blob/main/examples/examples.ipynb This article will not bother to write that Python code to convert LaTeX to a proper mathematical notation/equation, but I have used online editor such as so that you see the formula/equation assumptions glaringly below: https://latexeditor.lagrida.com/ : where S represents susceptible individuals, I represents infected individuals, R represents recovered individuals. The parameters β and γ govern the rates of transmission and recovery, respectively. The negative sign (i.e −β) indicates that the number of susceptible individuals (S) decreases over time. The dot notation indicates “multiplication.” In summary, these equations describe the dynamics of the SIR model, where the number of susceptible people decreases as they contract the disease (i.e. dS/dt), the number of infectious people rises as a result of new infections and falls as they recover (i.e. dI/dt), and the number of recovered people rises as the disease is treated (i.e. dR/dt). Because the change in each compartment depends on the multiplication of pertinent components, dots (.) is used to denote multiplication. Since all assumptions are set, we can then run a simulation using Python for  SIR Model and then visualize the dynamics: import numpy as np
from scipy.integrate import odeint
import matplotlib.pyplot as plt

# SIR model equations
def SIR_model(y, t, beta, gamma):
    S, I, R = y
    dSdt = -beta * S * I
    dIdt = beta * S * I - gamma * I
    dRdt = gamma * I
    return [dSdt, dIdt, dRdt]


"""
Initial conditions (such as S0, I0, and R0) are not to be random but I hardcoded them with specific values. These choices are typically made based on the characteristics of the disease being modeled and the context of the simulation. Initial condition are set such that S0 = 99%, which indicates the proportion of susceptible individuals when the simulation starts. I0 is set to 1%, which indicates proportion of infected individuals to be 1% when the simulation starts. R0 is set to 0% which is expected that there are are no recovered individuals when the simulations start.
"""
S0 = 0.99  
I0 = 0.01  
R0 = 0.00  
y0 = [S0, I0, R0]

# Parameters
# β (beta) is transmission rate and I chose 30%. γ (gamma) is set to 1%
beta = 0.3  
gamma = 0.1  

# Time vector
t = np.linspace(0, 200, 200)  # Simulate for 200 days

# Solve the SIR model equations using odeint()
solution = odeint(SIR_model, y0, t, args=(beta, gamma))

# Extract results
S, I, R = solution.T

# Plot the results
plt.figure(figsize=(10, 6))
plt.plot(t, S, label='Susceptible')
plt.plot(t, I, label='Infected')
plt.plot(t, R, label='Recovered')
plt.xlabel('Time (days)')
plt.ylabel('Proportion of Population')
plt.title('SIR Model Simulation')
plt.legend()
plt.grid(True)
plt.show() For differences between and , I will like to point you to and for you to make sense of it further. scipy.integrate.ode scipy.integrate.odeint odeint ode What You Can Discover Running the SIR model in Python allows you to: : Observe the epidemic curve and visualize how a disease spreads through a community. Running Python SIR Model above, you can see the outcome/result in the graph below: Understand Disease Spread Try testing various beta and gamma values to observe how they affect the length and peak of the outbreak. Explore Parameter Sensitivity: By changing the parameters, you can simulate the consequences of interventions like Evaluate Interventions: social isolation or immunization. 3. The SEIR Model What It Does / SEIR Python Code Simulation Example By adding a "Exposed" compartment, the SEIR model expands upon the SIR model. It takes into account the period of incubation during which people have been exposed but are not yet contagious. How to emulate it in Python is shown here. import numpy as np
from scipy.integrate import odeint
import matplotlib.pyplot as plt

# SEIR model equations
def SEIR_model(y, t, beta, sigma, gamma):
    S, E, I, R = y
    dSdt = -beta * S * I
    dEdt = beta * S * I - sigma * E
    dIdt = sigma * E - gamma * I
    dRdt = gamma * I
    return [dSdt, dEdt, dIdt, dRdt]

# Initial conditions
S0 = 0.99  
E0 = 0.01  
I0 = 0.00  
R0 = 0.00  
y0 = [S0, E0, I0, R0]

# Parameters
beta = 0.3    
sigma = 0.1   
gamma = 0.05 

# Time vector
t = np.linspace(0, 200, 200)  

# Solve the SEIR model equations
solution = odeint(SEIR_model, y0, t, args=(beta, sigma, gamma))

# Extract results
S, E, I, R = solution.T

# Plot the results
plt.figure(figsize=(10, 6))
plt.plot(t, S, label='Susceptible')
plt.plot(t, E, label='Exposed')
plt.plot(t, I, label='Infected')
plt.plot(t, R, label='Recovered')
plt.xlabel('Time (days)')
plt.ylabel('Proportion of Population')
plt.title('SEIR Model Simulation')
plt.legend()
plt.grid(True)
plt.show() The only difference in this case is the introduction of to explore different scenarios and understand the dynamics of infectious diseases with an “exposed” period. It demonstrates how it accounts for an incubation period before individuals become infectious. latent period rate (σ) What You Can Learn When you use Python to run the SEIR model, you can: Model Latent Periods Recognize the differences between the behaviors of immediately infectious illnesses and diseases with incubation periods. Evaluate Early Interventions Analyze the effects of isolation and early detection strategies. Study Complex Outbreaks For illnesses like COVID-19 where exposed people are a major factor in transmission, use SEIR. 4. Conclusion Python's simplicity and robust libraries, like SciPy, make it the perfect language for modeling diseases. And by performing these simulations with it, you're learning more about the dynamics of infectious diseases. This can equip you with verdicts and prowess that can help make decisions that are well-informed and improve your own ability to evaluate epidemics in the real world. There is much more to come after the SIR and SEIR models. There are other complex models such as SEIRS (Susceptible-Exposed-Infectious-Removed-Susceptible) Model, Spatial Models, Network Models, etc. Investigating intricate models, as well as real world data, such as geospatial data, epidemiological data, behavioural data, etc, and carefully examining the effects of interventions, such as vaccination strategies,  treatment availability, social distancing measures, you will develop your modeling abilities even further. Your knowledge of these modeling tools can significantly impact protecting public health in a future where understanding infectious disease transmission is vital. This is already too long, but I hope I have been able to show you how to simulate SIR and SEIR Models in mathematical model, using Python.

Simulating Infectious Disease Spread with Python: SIR and SEIR Models

পাইথনের সাহায্যে সংক্রামক রোগ ছড়ানোর অনুকরণ: SIR এবং SEIR মডেল

Simulation der Ausbreitung von Infektionskrankheiten mit Python: SIR- und SEIR-Modelle

Simulación de la propagación de enfermedades infecciosas con Python: modelos SIR y SEIR

Simuler la propagation de maladies infectieuses avec Python : modèles SIR et SEIR

पायथन के साथ फैलने वाले संक्रामक रोग का अनुकरण: एसआईआर और एसईआईआर मॉडल

Python を使用した感染症の蔓延のシミュレーション: SIR モデルと SEIR モデル

Python을 사용한 전염병 확산 시뮬레이션: SIR 및 SEIR 모델

Simulando a propagação de doenças infecciosas com Python: modelos SIR e SEIR

Моделирование распространения инфекционных заболеваний с помощью Python: модели SIR и SEIR

Python ile Bulaşıcı Hastalık Yayılımının Simülasyonu: SIR ve SEIR Modelleri

Mô phỏng sự lây lan của bệnh truyền nhiễm bằng Python: Mô hình SIR và SEIR

使用 Python 模拟传染病传播：SIR 和 SEIR 模型

Emily’s Great Moment

Various Tragedies

The 2021 AI Rewind: HackerNoon Edition

Odei Garcia-Garin et al. from the University of Barcelona have developed a deep learning-based algorithm able to detect and quantify floating garbage from aerial images. They also made a web-oriented application allowing users to identify the garbage known as floating marine macro-litter, or FMML, within images of the sea surface. Watch the video: References Odei Garcia-Garin et al., Automatic detection and quantification of floating marine macro-litter in aerial images: Introducing a novel deep learning approach connected to a web application in R, Environmental Pollution, ​. https://doi.org/10.1016/j.envpol.2021... Code & web app: https://github.com/amonleong/MARLIT Follow me for more AI content: Instagram: ​ https://www.instagram.com/whats_ai/ LinkedIn: ​ https://www.linkedin.com/in/whats-ai/ Twitter: ​ https://twitter.com/Whats_AI Facebook: ​ https://www.facebook.com/whats.artifi... Medium: ​ https://whats-ai.medium.com/ Join Our Discord channel, Learn AI Together: ​ https://discord.gg/learnaitogether The best courses in AI & Guide+Repository on how to start: ​ ​ https://www.omologapps.com/whats-ai ​ https://github.com/louisfb01/start-ma... Become a member of my YouTube community: ​ https://www.youtube.com/channel/UCUzG... Chapters: 0:00​ - Hey! Tap the Thumbs Up button and Subscribe. You'll learn a lot of cool stuff, I promise. 0:30​ - Floating marine macro-litter 2:19​ - The method 5:10​ - Conclusion Video Transcript 00:00 an ai software able to detect and count 00:03 plastic waste in the ocean 00:04 using ariel images it's both clever and 00:07 simple 00:08 and you could use this same model for 00:10 many image classification applications 00:12 let's see how it works 00:16 [Music] 00:21 this is what's ai and i share artificial 00:23 intelligence news every week 00:25 if you are new to the channel and want 00:26 to stay up to date please consider 00:28 subscribing to not miss any further news 00:31 we live on a blue planet over 70 00:35 of earth is covered by sea from space 00:38 our ocean appears pristine clean 00:42 unfortunately it's not because of poorly 00:45 controlled waste sites 00:46 illegal dumping and mishandled waste 00:49 from population centres 00:51 tourism industrial and agricultural 00:53 activities 00:54 an estimated 8 million metric tons of 00:57 plastic 00:58 waste entered the oceans 01:02 aude garcia garion et al from the 01:04 university of barcelona 01:06 have developed a deep learning based 01:08 algorithm able to detect and quantify 01:10 floating garbage from aerial images 01:13 they also made a web-oriented 01:15 application allowing users to identify 01:17 these garbages 01:18 called floating marine microliter or fml 01:21 within 01:22 images of the sea surface floating 01:25 marine macro litter is any persistent 01:27 manufactured or processed solid material 01:30 lost or abandoned in a marine 01:32 compartment as you most certainly know 01:34 these plastic wastes are dangerous for 01:36 fish turtles and marine mammals as they 01:39 can either 01:40 ingest them or get entangled and hurt 01:42 traditional approaches to detecting 01:44 these 01:45 fmls are observer-based methods 01:48 meaning that they require someone on a 01:50 vessel or airplane to look for them 01:52 yielding to precise identification but 01:55 extremely expensive and time demanding 01:57 labor 01:58 fortunately this detection can be done 02:00 using cameras or sensors on aerial 02:02 vehicles 02:03 but it also requires trained scientists 02:05 to manually look at the collected data 02:08 being again extremely time consuming 02:10 automation is clearly needed here and 02:12 could help us 02:13 improve the quality of our marine 02:15 compartments worldwide 02:16 much more effectively this is where 02:19 machine learning 02:20 and deep learning commonly deep learning 02:23 proves over and over 02:24 that it's a very powerful automation 02:26 tool and especially in the computer 02:28 vision industry 02:29 where it's known to automatically 02:31 identify the important features of an 02:33 image 02:33 without any human supervision making 02:36 this approach 02:37 less time demanding than its 02:38 predecessors for many different 02:40 applications including 02:41 this very important one as you may 02:44 suspect 02:45 they use the convolutional neural 02:46 networks to attack this problem 02:48 this type of neural network is the most 02:50 commonly used deep learning architecture 02:52 in computer vision 02:54 the idea behind this deep neural network 02:56 architecture is to mimic the human's 02:58 visual system if you want to learn more 03:00 about the foundation of convolutional 03:02 neural networks 03:03 or cnns i will refer you to their video 03:05 on the top right corner on your screen 03:07 where i'm explaining them more in depth 03:11 they train their algorithm with real 03:13 images like this one 03:15 taken by drones and aircraft with 03:17 annotations made by the same 03:19 professionals that are usually 03:20 manually analyzing them this is a 03:23 challenging task even for deep learning 03:25 because of all the possible variations 03:27 in colors and sun reflections as you can 03:29 see here 03:31 in short their model is a regular binary 03:33 classifier 03:34 cnn architecture composed of 03:36 convolutions and poolings 03:38 terms that i explained in the video i 03:40 referenced earlier 03:41 that outputs a binary response telling 03:43 us if there are fmls or not in the 03:46 picture 03:46 the depth of the network is due to these 03:48 convolution layers 03:50 compressing the image and creating many 03:52 feature maps 03:53 which are the outputs of the filters 03:55 ending with a general representation 03:57 of the image allowing us to know in 03:59 general 04:00 what the image contains such as fml in 04:03 this case 04:04 note that this exact same architecture 04:06 could have been used on 04:08 any other computer vision application 04:10 with a test to classify whether or not 04:12 something is in the image such as 04:14 putting a defect on a manufacturer part 04:16 or telling if there is a dog or not what 04:18 they did differently making it powerful 04:20 to fml detection 04:22 is that they had the idea to split the 04:24 image into 25 smaller cells 04:26 that each outputs a classification 04:28 result fml 04:30 or not yielding much better overall 04:32 accuracy 04:33 then they used the shiny package of r 04:37 to develop their application their 04:39 algorithm allows the detection and 04:41 quantification 04:42 of fmls as well as providing support to 04:45 the monitoring and assessment of this 04:47 environmental threat 04:48 however it's still not completely 04:50 automated yet and requires a human in 04:52 the loop 04:53 as of now they are still looking for 04:55 more annotated data to allow their 04:57 algorithm to also 04:58 identify the size color and type of fml 05:01 which are very relevant information for 05:03 planning well-targeted policy and 05:05 mitigation measures 05:07 this is still an amazing application of 05:09 deep learning with a great use case that 05:11 will benefit everyone 05:13 of course this was just an introduction 05:15 to this new paper 05:16 and i linked both the paper their code 05:18 and their application 05:20 in the description below if you would 05:21 like to read more about it or even 05:23 try it out yourself please leave a like 05:26 if you went this far in the video 05:28 and since there are over 80 percent of 05:30 you guys that are not subscribed yet 05:32 please consider subscribing to the 05:33 channel to not miss any further news 05:36 thank you for watching 05:40 [Music]

Using AI to Detect and Count Plastic Waste in the Ocean

Look, I don't know where you fall on the spectrum of "does emulation promote piracy?", but the idea that a video game company like Nintendo can let off its army of lawyers on a bunch of hobbyists/programers/geeks like a pack of hungry wolves and force them to shut down AND pay over 2 million in dollars just because thinks emulation promotes piracy should alarm any and every one in the tech space. it To quote Steam Founder Gabe Newell: "Piracy is not a pricing issue. It’s a service issue." Amen to that, brother, AMEN! Microsoft's Xbox understands this. Sony's PlayStation understands this. But somehow, the memo was lost on Nintendo which thought it was absolutely ok to force Tropic Haze, the company behind Switch emulator Yuzu and 3ds emulator Citra, to shut down its websites, take down its code repositories AND pay $2.4 million because, apparently, its software allowed people to illegally play Zelda. Nevermind the fact that thousands of people legally pay for Nintendo titles and emulate them on a different hardware because it plays better or because it provides more accessibility. But of course, that's the kind of rhetoric that would fall on deaf ears at Nintendo HQ. Instead, you have Nintendo coming out of the woods to protect its iNtElLeCtUaL pRoPeRtY whenever someone makes a fan project, a ROM website full of abandonware titles, or literally dozens of instances where people just want to do cool and different things with its video game titles. Ironically, except for a handful of titles that Nintendo offers through its online subscription service, there is no "legal" way to play games from the yesteryears without actually emulating them. Emulating video games also ties into video game preservation, but that's a whole different topic altogether. On top of that, Nintendo won't even port its major titles to the PC. Perhaps because it doesn't want to share revenue with others OR it wants to keep selling the Switch consoles. Whatever the case may be, it still SUCKS that Nintendo would just blatantly shut down a project like Yuzu. In some ways, one could argue that this is an attempt by one of the most successful companies in the world to make an example out of a project that is born out of passion. But what does that get the company ultimately? It's already massively rich, and all it's achieving out of these intimidation tactics is to scare off gamers and those who create emulators for them. There's no telling where the scales will tip for emulators for older Nintendo consoles like the Wii or the Wii U, but it wouldn't be surprising if more and more developers decide to not create emulator software because they don't want to fall foul of Nintendo's legal antics. So, yeah. Nintendo sucks and this is the world we live in. 👋 You’re reading HackerNoon's , a weekly collection of tech goodness that combines HackerNoon's proprietary data with internet trends to determine which companies are rising and falling in the public consciousness. Subscribe to receive the newsletter in your inbox every Tuesday. Tech Company News Brief here complete Biden Administration to Dole Out Billions in Federal Grants to Chipmakers🤑🤑 The who's who of the semiconductor manufacturing industry have put a gun to the US government's head and are trying to milk billions of taxpayer money to build their projects on American soil. OK, that's a bit of an exaggeration. The truth is that the Biden administration , REALLY wants companies like Taiwan Semiconductor Manufacturing Company, Intel and Micron Technology to build their products in the US, so much so that it's willing to throw billions of dollars at them. really How much, exactly? Well, the US government plans to dish out over $28 billion in federal grants to each of the companies plus Samsung Electronics to entice them to boost semiconductor manufacturing in the United States. Taiwan Semiconductor Manufacturing is expected to win more than $5 billion in federal grants to support the development of two fabrication facilities in Arizona. Topline numbers for the other companies continue to fluctuate but an announcement for the major advanced chipmakers is expected by the end of this month. Keep your eyes peeled for that development. 🤖 Elon Musk Takes Exception to OpenAI's Company Charter Wow, it's been quite a while since we reported on Elon Musk. But we're happy to let you know that the world's richest man is still up and about with his antics and this time, it involves his old nemesis Sam Altman's OpenAI. Yes, everyone's favorite billionaire has decided to hold OpenAI's company charter to court. He’s arguing in a lawsuit that the (former?) non-profit company, of which he apparently was a co-founder, abandoned its charge to benefit humanity by developing powerful artificial intelligence. Instead, the company rolled out generative AI products like ChatGPT that were essentially Microsoft products to make big bucks. Of course, Musk knows about benefiting humanity given that he owns Tesla; in fact, so concerned was he with humanity's benefit that he decided to burn his own money to buy X (formerly known as Twitter) for reasons that are not yet clear (but should be in a decade or two). all OpenAI is certainly not having Musk's BS, so it has hired a law firm that Elon Musk hates, to have his lawsuit thrown out. really Just another day of tech bros duking it out against each other. Sigh! In Other News.. 📰 Ethereum Finalizes 'Dencun' Upgrade, in Landmark Move to Reduce Data Fees — via CoinDesk Startups are hiring fewer workers and paying out less in equity comp — via TechCrunch EU approves landmark AI law, leapfrogging US to regulate critical but worrying new technology — via CNN US House passes bill to force ByteDance to divest TikTok or face ban — via Reuters The road map to AI's next level could be nature — via Axios Palantir CEO says short sellers bet against great companies ‘so they can pay for their coke’ — via CNBC – And that's a wrap! Don't forget to share this newsletter with your family and friends! See y'all next week. PEACE! ☮️ — Sheharyar Khan, Editor, Business Tech @ HackerNoon *All rankings are current as of Monday. To see how the rankings have changed, please visit HackerNoon's page. Tech Company Rankings

I Hate Nintendo

আমি নিন্টেন্ডোকে ঘৃণা করি

Ich hasse Nintendo

odio nintendo

Je déteste Nintendo

मुझे निनटेंडो से नफरत है

私は任天堂が嫌いです

나는 닌텐도를 싫어한다

Eu odeio Nintendo

Я ненавижу Нинтендо

Nintendo'dan Nefret Ediyorum

Tôi ghét Nintendo

我讨厌任天堂

NFTs have captured the public’s imagination over the past two years. Ironically, there’s been pushback from one of the primary communities that could benefit from NFT integration – gamers. It’s easy to understand the anti-NFT sentiment among gamers. Players have seen their hobby increasingly riddled with minefields of microtransactions and loot boxes over the past decade. Gaming NFTs may appear to further entrench predatory monetization at first glance. However, this is exactly what gamers don’t get about NFTs. In Its Current State, Gamers Are Right to be Wary of NFTs Gamers aren’t investors. Gamers won’t pay thousands of dollars to access a game, and they aren’t interested in speculating on nascent digital assets. Players want to enjoy a seamless gaming experience - something NFTs have yet to provide. In its current state, web3 gaming is an investment vehicle – which is why some refer to current blockchain gaming as “crypto staking with more steps.” That being said, NFTs will open the floodgates for new utility within gaming and ultimately benefit gamers far more than the current landscape of in-game items. While gamers are right to be wary of NFTs, they should be aware of the long-term impact the technology will have in gaming and embrace NFTs with open arms. Taking Back Ownership with NFT Gaming The gaming industry recorded an estimated $194B in revenue over 2022, despite an arduous global climate. Microtransactions alone – roughly 30% of the entire market. account for $67.94B It’s clear that gamers are happy to outlay significant capital to flex in-game assets with their online identities. However, these don’t come with true digital ownership. Once you stop playing a game, your hard earned assets disappear with it. Further, these are temporary assets. Dollars spent on assets in one edition are rendered useless once a later edition arrives. Take Call of Duty for example. What would happen if the massively popular first person shooter experienced downtime or the franchise drew to a close? Players would be left empty-handed – despite having sunk hundreds of dollars into in-game assets NFTs, on the other hand, last forever. **Even if the game should die, tokenized assets would still be tradable on the blockchain. Users have full ownership of purchased assets under this design, regardless of what happens to the game in question. It’s also safe to assume that general NFT collectors would have a strong appetite for NFTs representing rare in-game items. Simultaneously, NFT creators are incentivized to make digital items interoperable cross-game, creating more value for players. And this utility extends far beyond simple commerce. Owners could use their acquired items to amplify their social profiles as elite gamers. There’s a popular battle cry among NFT enthusiasts – “I am my NFT and my NFT is me. In much the same way, gamers are heavily invested in cultivating their online identities. Enhancing Interoperability With NFTs in Gaming At present, games are siloed by centralized servers. This fragmentation prevents gamers from using their hard-earned assets in other games once they move on. Studios could reduce the current fragmented experience for gamers by implementing NFTs and designing interoperable systems. This would result in an open, expanded ecosystem where gamers can transfer their assets and reputation between games. This technology’s diversity carries massive potential for creating a global and inclusive gaming experience. Game publishers should easily recognize the many benefits of a vastly increased network effects. Transparency and Provenance Purchasing an in-game item without NFTs is currently an opaque process. When buying a skin in Call of Duty, for instance, there are no mechanics that objectively display scarcity, rarity or history of ownership. With NFTs, gamers could freely access these metrics to inform their purchases. Viewing ownership history could in some cases add substantial value to an item. For instance, an item previously owned by an elite gamer like Ninja or PewDiePie would naturally hold far higher value than similar items for sale. Further, being able to access scarcity and attribute rarity would offer gamers increased insights into the traits and skills they desire. Reducing the Chokehold of Centralization Gaming has evolved into an online, social experience. While it may appear that hundreds of studios are producing AAA titles independently, these are all owned by a total of seven major corporations. This centralization is the polar opposite of gaming’s global, interactive nature. These slow moving monoliths remain hesitant to adopt and integrate NFTs.  This opens vast opportunities for indie studios and aspiring game developers to gain significant market share. The NFT market is to $8B by 2027 - with a global user penetration of only 0.8%. Those who take advantage of this nascent technology are primed to reap significant benefits in decades to come. projected to grow Integrating NFTs in Video Games is a Positive Inevitability The possibilities offered by NFT gaming are near-endless. Blockchain-based games like Yuga Labs’ Dookey Dash illustrate the vast benefits creators and players can reap while still enjoying an immersive gaming experience. has been tirelessly building to cater for the inbound wave of NFT innovation in gaming. By offering bespoke, project-specific platforms, Origin is laying the foundations for robust game-asset transacting. Origin Protocol branded NFT marketplaces These platforms are complemented by in-depth analytics dashboards, giving users insights into owners, listings, and more. If you are a creator or brand interested in learning more about Origin Story and Polygon, contact us at partnerships@story.xyz. FAQs How can NFT based blockchain technology benefit gamers? NFT integration allows players to gain full ownership of their digital goods. This allows players to use and trade their in-game assets even if the game is discontinued. How can NFT integration improve the social gaming experience? NFTs can bridge gaming worlds by allowing users to transfer their assets between games. This article was published by Origin Protocol. Origin Protocol has an interest in the success of NFTs in gaming, as it creates infrastructure related to NFT marketplaces for gaming, music, real estate, and beyond.

Gamers Hate Gaming NFTs But the Long-Term Impacts are Irresistible 

Los jugadores odian los juegos NFT, pero los impactos a largo plazo son irresistibles

Les joueurs détestent les NFT de jeu, mais les impacts à long terme sont irrésistibles

गेमर्स गेमिंग एनएफटी से नफरत करते हैं लेकिन दीर्घकालिक प्रभाव अप्रतिरोध्य हैं

ゲーマーはゲーム用 NFT を嫌うが、長期的な影響は避けられない

Os jogadores odeiam NFTs de jogos, mas os impactos a longo prazo são irresistíveis

Game thủ ghét NFT chơi game nhưng tác động lâu dài là không thể cưỡng lại

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“You have a meeting to make a decision, not to decide on the question.” —Bill Gates This quote perfectly summarizes all my frustrations about meetings. Many studies have highlighted the inefficiency of meetings at work. Still, meetings keep increasing in length and frequency, to the point where in them (it was less than 10 hours in the 1960s). It would not be a bad thing if meetings were all useful, but we all know how inefficient most of them are. I’ve been experimenting a lot with meetings in my company and have learned how to make the most out of them—here’s what I’ve discovered and want to share with you so you can use your time well and hold productive, effective meetings. executives spend around 23 hours a week Meetings are bad for your productivity We usually work on two different schedules: the maker's schedule and the manager's schedule. This concept was first described by Y Combinator's founder, Paul Graham, in . In this essay, Graham explains how makers are task-oriented and need a long stretch of time to focus (programmers or writers are typical examples). On the other hand, managers use mainly communication and meetings to make things progress. What’s interesting is that most of the time, we all need to combine the two schedules in our work life. his 2009 essay When you are in the maker’s schedule, a single meeting interruption could be a hard hit on your productivity. The maker’s schedule is most efficient when you are able to enter , a state of deep focus where your concentration is at its maximum and time seems to flow by without you noticing it. Going back to the flow after an interruption can ! Trying to mix your maker’s and manager’s schedule is always an indicator of inefficiency. the flow cost you up to 23 minutes The problem can also come from outside. Managers are more likely to disrupt the maker’s schedule due to the nature of their position. Because of hierarchy, managers also have the power to decide when meetings should happen. This power comes with great responsibility ( quote alert). Spiderman Interrupting the maker's schedule with a meeting is a big waste of their time. A good manager should recognize this and adopt meeting practices that let makers maximize their time. Managers should also realize that they could have fewer meetings and create more maker’s time for themselves. Paul Graham—a highly solicited person—keeps only the last hours of his day dedicated to meetings. The rest of the day is dedicated to getting things done. In modern companies, most of us need to adopt a dual schedule. So, how do you implement this in your daily work life? Recognize which type of meeting you are in In his bestseller, , Andy Grove (former chairman and CEO of Intel) describes two kinds of meetings: process-oriented and mission-oriented meetings. To make the most of your meetings, it’s important to recognize in which type of meeting you are. High Output Management Process-oriented meetings Process-oriented meetings aim at sharing knowledge and exchanging information. They usually take place on a regular basis. Classical examples of process-oriented meetings are one-on-one meetings, staff meetings, or project reviews. Most process-oriented meetings can be avoided (I will exclude the one-on-one from this affirmation). Take staff meetings, for example. It’s very common for companies to organize regular staff meetings to exchange statuses or project updates. The underlying goal is often to gain a bigger picture of how tasks are advancing in a team or company. It’s quite common nowadays to have daily standup meetings at the beginning of the day. The problem with these meetings is that most of the time, they’re an interruption for makers. Even if organized early, the meeting will always disrupt someone’s plan. And when you take this interruption company-wide, the loss of efficiency is very high. In general, process-oriented meetings can be replaced by digital updates. A written update has more value than one shared in a meeting. It can be read at any time, removes micromanagement, and builds trust across the company. Take daily or weekly updates, for instance. Apps like Basecamp or Range.co include features dedicated to eradicating daily status meetings. Every day, these tools invite your staff to enter an update. They can choose when to write it and avoid being interrupted by a meeting when they are in their maker’s schedule. The updates are shared with colleagues so they can also read them whenever they want, without being interrupted in the middle of a task. These systems keep all the benefits of a meeting while avoiding the drawbacks. Process-oriented meetings are not all bad, though. I mentioned the one-on-one as an exception because the main benefit of those meetings is the personal relationship they create between managers and team members. You can of course make the one-on-one more efficient with some techniques I will describe below, but trying to avoid the social interactions of these meetings would be an overkill. Mission-oriented meetings Mission-oriented meetings aim at solving a specific problem or producing a decision. Unlike process-oriented meetings, they are usually ad hoc and can’t be predicted in advance. The inefficiency of mission-oriented meetings comes from the fact that spontaneous decision-making involves many cognitive biases. The , for example, stipulates that when we’re in groups, we start to think the same as other people in the group. Another one, the , is very likely to happen in meetings and shows that we are more likely to listen to information that confirms our preconceptions. bandwagon bias confirmation bias The best way to remove cognitive biases from mission-oriented meetings is to go through a long preparation phase in written form. When a manager organizes a mission-oriented meeting, it’s better to not rush into it and to take the time to collect arguments, feedback, or questions beforehand. Creating a written discussion around the problem to solve it could lead to a better decision process. Rushing into a meeting as soon as a problem occurs is the best way to trigger cognitive biases. It also creates false urgency and disrupts other people’s schedules. Once all parties are well informed through preliminary documentation, a short mission-oriented meeting can happen and conclude the decision process. This is a good way to make sure that all parties agree to the decision, or at least commit to it. It could also be helpful to organize this type of meeting in case of conflicts or escalation in the decision process. Recognizing which type of meeting you are in will help you understand how to implement a better practice. In the case of process-oriented meetings, try replacing them with digital updates. For mission-oriented meetings, diligent documentation prepared in advance will help reduce the bias linked to decision-making. 7 meeting rules to live by Some meetings can’t be avoided. When this is the case, meetings should always follow the seven rules below: : A meeting without a goal is the best way to waste your time. Whether it’s a mission-oriented or a project-oriented meeting, all meetings should have a goal that is clear to all participants (for instance, a one-on-one meeting aims at reviewing the performance of an employee). Predefined goal : A meeting is not open-ended and must respect an allotted time. The shorter the allotted time is, the more efficient the meeting will be. If you plan a four-hour meeting, you can be sure that participants will find a way to fill in the time. You could reduce it to 30 minutes and have the same output if the meeting is well-prepared and includes all five other rules. Timeline : No agenda means no meeting! A meeting without agenda is just an excuse to lock people in a room (or Zoom call) for a specific period of time. Always start a meeting with an agenda of what will be discussed. Agenda : The meeting agenda should always be available in advance (at least 24 hours) so all participants can prepare their thoughts on the topic. The best practice is to engage in a written conversation before the meeting so that the issue can advance as far as possible without face-to-face interaction (and thus remove the problem of extrovert personalities taking over the discussion in meetings). Preparation : Each meeting must have an appointed leader to keep things moving along. If it’s a mission-oriented meeting, the leader should also be the one having the last word in case of indecision. Leader : Always appoint a scribe to take notes in a meeting. For fairness, the scribe should not always be the same person. Without notes, there is no trace of what’s been decided in the meeting. Notes help you in case of future memory lapses or to share the content of a meeting with people who didn’t attend. The scribe should also clean up the notes after the meeting to make them fully understandable to readers. Scribe : Jeff Bezos has a famous rule for meetings: no meeting should be so large that two pizzas can’t feed the whole group. Participants in a meeting should always bring value, otherwise, they can simply read the meeting notes and get an update on what’s been discussed. Adding more people to a meeting is a good way to slow down the decision process or just waste time that could be spent somewhere else. No more people than necessary Using this set of rules across your company will ensure that all your meetings are efficient. Still, you could find yourself being interrupted by well-organized and efficient meetings. On top of good organizational practices, healthy personal rules can also help your productivity. Reduce the time you spend in meetings Following the rules mentioned above should already reduce meetings to the most efficient ones. However, if meetings keep interrupting your maker’s schedule, they will still be a hindrance to your productivity. Below are some personal tips to help you regain your maker’s time. Written conversation is a huge time saver. Imagine the number of meetings that could be solved by a written (and detailed) conversation. I’m not talking about chaotic Slack threads, but real, in-depth details about projects, issues, and decisions to take. I’m regularly writing 200-300 updates I share with my team in our project management software. This lets me put my thoughts in order before I share them. These updates can be read at any time, so I don’t constantly interrupt my team with meetings. I would literally kill the productivity of my team if I constantly shared my thoughts in meetings instead of by writing. Write more, talk less: Calendar invitations are a good place to add metadata like the location, a call link, notes, and an agenda. This is especially true with people outside of your organization. Giving context and information to external parties is even more important, as they may have less knowledge on the topic of the meeting than your colleagues. Include metadata on calendar invite: We have all seen those people who start texting while they are in a meeting. In addition to being disrespectful, it also shows that the meeting is not relevant to them. To increase participants’ attention, you can introduce simple rules like having only one computer in the room or forbidding smartphones during meetings. It’s also important to stay focused on the agenda. Going off course is the best way to make a 30-minute meeting last hours. If the agenda needs further discussion, prepare a follow-up meeting instead of locking up your colleagues in a room for too long. Stay present and focus on the agenda: When you need to stay focused, the last thing you want is an interruption. However, some workplaces are more subject to this, and sometimes it’s your own responsibility to stop the interruptions from others. A simple method is to be transparent with your colleagues. For example, if you need long stretches of time to focus, communicate clearly with your team that you will not check emails or messages regularly. If you work in a crowded office with a lot of interruptions, you can also wear headphones to show that you are busy. Stop spontaneous interruptions: This is the most radical option, but often the best. Saying no to meetings is the best way to regain your maker’s time. You could, for instance, block your calendar with a “no meeting” event so that people can’t hijack your schedule. I regularly refuse meetings that don’t have a clear goal or agenda. Don’t forget, when you say yes to a meeting, you automatically say no to other tasks on your list. Say no to meetings: Like tasks, meetings can be batched together. This is especially useful for people with a hybrid maker’s/manager’s schedule. If all your meetings are batched on one or two afternoons per week, you totally free up the rest of your time for deep focus. Allocating a specific time window for your meetings also allows you to keep time spent in meetings to a decent level. For those who have a lot of spontaneous interruptions, you can also create “office hours” (like what professors do in universities). With office hours, you open a specific window of time in your calendar to answer questions. This is particularly helpful for people who need to regularly answer questions. Batch your meetings: Most calendar apps create one-hour events by default, but meetings don’t always have to be that long! Keep in mind that a 30-minute conversation can cover a lot of ground if the meeting is well-prepared. Ditch the one-hour slot and start having shorter meetings. It will also force participants to get to the point more rapidly. Don’t make it too long: Organizing a meeting can be complicated. It’s quite common to end up with a long email back and forth when trying to find a time that will fit all parties. One easy way to avoid this is to use tools like Calendly (it’s free). This app lets you share open time slots with external contacts. The organization process is totally automated, and you simply need to share a link for others to find a time that fits into your own agenda. Thank you, technology! Facilitate meetings with tools: The social benefits of meetings Each company is unique and has different needs when it comes to internal communication. Even though I’m convinced that most companies would benefit from reducing meetings to a strict minimum, I also acknowledge the social benefit of meetings. Sometimes, you have to let bad meetings slip through the gaps. In my company, we do one of these every week, voluntarily. Once a week, we organize a short all-hands meeting (as we are less than 10 people, this is still manageable). This meeting is dedicated to sharing two short weekly highlights, one professional and one personal. Even though this could be completely replaced by a written report (and we actually have one in parallel), the benefit of this meeting is to gather the team and have a relaxed discussion. The personal highlight also helps us bond, and quite often, laugh together. Sometimes, you have to recognize the benefit of a simple talk. But we can allow this meeting because we know that all other meetings are efficient. If you follow the advice in this post, you could easily reduce your time in meetings to a few hours per week, even if you are managing a team or a company. You don’t have to hate meetings if they are all relevant.

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Cloud computing was once at the forefront of emerging data center technology. But now, it’s the backbone of digital businesses worldwide. “The cloud” is no longer just a corporate buzzword — it powers everything from mobile apps to billion-dollar enterprises. And it’s not done growing yet! Visionary leaders like Obinna Odirionye, CEO and creator of Clouddley, believe it will define the next generation of technologies like artificial intelligence, machine learning, and the Internet of Things. However, cloud computing also has inherent complexities that can hinder innovation. To combat this, Obinna is improving accessibility and simplicity in cloud technologies, making these tools available to more people than ever before. Cloud Computing: Powerful Tech with a High Barrier to Entry Setting up and maintaining cloud infrastructure can be quite a chore. You must have a firm understanding of networking, security protocols, resource optimization, and many other complicated concepts. Even feature-rich cloud platforms like AWS don’t exactly make it easy for a relative beginner to launch a cloud app. This means there’s a steep barrier for small companies and startups that could greatly benefit from cloud computing but lack the resources to hire trained professionals. But this is one area where these businesses can’t afford to fall behind. 85% of organizations are expected to take a cloud-first approach by 2025. 95% of all new digital workloads are predicted to be deployed on cloud-native platforms by then as well. This means even small businesses must leverage cloud technologies if they hope to keep up with the competition. That’s why Obinna aims to democratize the cloud, empowering organizations big and small to use the cloud in simple but powerful ways. Simplifying the Cloud — the Clouddley Way Ever since he was a teenager, Obinna was fascinated with “The Cloud.” As he developed his tech skills and learned the ins and outs of cloud computing, he only came to love it more. Now, he calls the cloud “the heart of the internet.” After starting his career as a DevOps engineer for Deimos, a cloud developer and security operations company, Obinna noticed how complicated cloud platforms have become. He realized just how many talents a developer has to have in order to create a smooth cloud experience, and he also learned how many ways cloud computing can go wrong. But rather than accept it as the status quo, Obinna decided to do something about it. Enter Clouddley. Clouddley is Obinna’s baby, the new kid on the block. It’s a reimagining of the cloud, a simple, cost-effective approach that any organization can use to develop robust cloud apps with a fraction of the complexity. All you have to do is connect Clouddley to your GitHub account, configure your app, and then deploy it. So, instead of having to worry about load balancing, IAM roles, policies, etc., you can let Clouddley handle it all, allowing you to focus on the code and shipping a successful product. The latest iteration of Clouddley includes a product called Triggr, a continuous deployment platform. Like the base Clouddley platform, it’s designed to simplify a developer’s work — by auto-detecting your programming language and framework, deploying to the server/VM of your choice without you having to lift a finger, it dramatically expedites the deployment workflow. As you can see, Clouddley vastly eliminates many of the complexities that come with cloud computing. It makes the process straightforward, allowing you to deploy an app without needing extensive cloud training. It’s the culmination of Obinna’s dream: democratizing the cloud and making the heart of the internet accessible to everyone. A Cloudy Future Never Looked So Bright Despite achieving his goal of simplifying the cloud, Obinna isn’t done. He’s already hard at work with version 2 of Clouddley, which aims to give users even more flexibility in how they deploy their apps. In this version, Triggr users will be able to easily add team members, deploy databases on the fly in seconds, and run LLMs like Llama 2 and Mixtral 8x22b on top of their virtual machines with OpenAI-compatible endpoints provided by Clouddley Triggr to chat with these models. After that, Obinna has plans for a Heroku alternative that vastly simplifies containerized app development. Like the Clouddley platform as a whole, his goal for the project is to reduce the barrier to entry when running a production-managed app. Despite Clouddley’s impressive capabilities, Obinna insists on offering these top-flight solutions at a fraction of what he could realistically sell them for. In his words, “If you can afford a Starbucks coffee, you can use the Clouddley platform.” As cloud computing continues to evolve, leaders like Obinna will be at the forefront. By making cloud development more accessible, Obinna is empowering a more diverse group of developers and entrepreneurs to create and implement innovative cloud-based solutions. He’s paving the way for this next generation of developers — innovators who will enjoy a more inclusive and user-friendly cloud computing environment. This story was distributed by Jon Stojan Media under HackerNoon’s Brand As An Author Program. Learn more about the program here: https://business.hackernoon.com/brand-as-author Cloud computing was once at the forefront of emerging data center technology. But now, it’s the backbone of digital businesses worldwide. “The cloud” is no longer just a corporate buzzword — it powers everything from mobile apps to billion-dollar enterprises. And it’s not done growing yet! Visionary leaders like Obinna Odirionye, CEO and creator of Clouddley, believe it will define the next generation of technologies like artificial intelligence, machine learning, and the Internet of Things. However, cloud computing also has inherent complexities that can hinder innovation. To combat this, Obinna is improving accessibility and simplicity in cloud technologies, making these tools available to more people than ever before. Cloud Computing: Powerful Tech with a High Barrier to Entry Setting up and maintaining cloud infrastructure can be quite a chore. You must have a firm understanding of networking, security protocols, resource optimization, and many other complicated concepts. Even feature-rich cloud platforms like AWS don’t exactly make it easy for a relative beginner to launch a cloud app. This means there’s a steep barrier for small companies and startups that could greatly benefit from cloud computing but lack the resources to hire trained professionals. But this is one area where these businesses can’t afford to fall behind. 85% of organizations are expected to take a cloud-first approach by 2025 . 95% of all new digital workloads are predicted to be deployed on cloud-native platforms by then as well. This means even small businesses must leverage cloud technologies if they hope to keep up with the competition. 85% of organizations are expected to take a cloud-first approach by 2025 85% of organizations are expected to take a cloud-first approach by 2025 That’s why Obinna aims to democratize the cloud, empowering organizations big and small to use the cloud in simple but powerful ways. Simplifying the Cloud — the Clouddley Way Ever since he was a teenager, Obinna was fascinated with “The Cloud.” As he developed his tech skills and learned the ins and outs of cloud computing, he only came to love it more. Now, he calls the cloud “the heart of the internet.” Obinna Obinna After starting his career as a DevOps engineer for Deimos, a cloud developer and security operations company, Obinna noticed how complicated cloud platforms have become. He realized just how many talents a developer has to have in order to create a smooth cloud experience, and he also learned how many ways cloud computing can go wrong. But rather than accept it as the status quo, Obinna decided to do something about it. Enter Clouddley . Clouddley Clouddley Clouddley is Obinna’s baby, the new kid on the block. It’s a reimagining of the cloud, a simple, cost-effective approach that any organization can use to develop robust cloud apps with a fraction of the complexity. All you have to do is connect Clouddley to your GitHub account, configure your app, and then deploy it. So, instead of having to worry about load balancing, IAM roles, policies, etc., you can let Clouddley handle it all, allowing you to focus on the code and shipping a successful product. The latest iteration of Clouddley includes a product called Triggr , a continuous deployment platform. Like the base Clouddley platform, it’s designed to simplify a developer’s work — by auto-detecting your programming language and framework, deploying to the server/VM of your choice without you having to lift a finger, it dramatically expedites the deployment workflow. Triggr Triggr As you can see, Clouddley vastly eliminates many of the complexities that come with cloud computing. It makes the process straightforward, allowing you to deploy an app without needing extensive cloud training. It’s the culmination of Obinna’s dream: democratizing the cloud and making the heart of the internet accessible to everyone. A Cloudy Future Never Looked So Bright A Cloudy Future Never Looked So Bright Despite achieving his goal of simplifying the cloud, Obinna isn’t done. He’s already hard at work with version 2 of Clouddley, which aims to give users even more flexibility in how they deploy their apps. In this version, Triggr users will be able to easily add team members, deploy databases on the fly in seconds, and run LLMs like Llama 2 and Mixtral 8x22b on top of their virtual machines with OpenAI-compatible endpoints provided by Clouddley Triggr to chat with these models. Clouddley Triggr Clouddley Triggr After that, Obinna has plans for a Heroku alternative that vastly simplifies containerized app development. Like the Clouddley platform as a whole, his goal for the project is to reduce the barrier to entry when running a production-managed app. Despite Clouddley’s impressive capabilities, Obinna insists on offering these top-flight solutions at a fraction of what he could realistically sell them for. In his words, “If you can afford a Starbucks coffee, you can use the Clouddley platform.” As cloud computing continues to evolve, leaders like Obinna will be at the forefront. By making cloud development more accessible, Obinna is empowering a more diverse group of developers and entrepreneurs to create and implement innovative cloud-based solutions. He’s paving the way for this next generation of developers — innovators who will enjoy a more inclusive and user-friendly cloud computing environment. This story was distributed by Jon Stojan Media under HackerNoon’s Brand As An Author Program. Learn more about the program here: https://business.hackernoon.com/brand-as-author This story was distributed by Jon Stojan Media under HackerNoon’s Brand As An Author Program. Learn more about the program here: https://business.hackernoon.com/brand-as-author This story was distributed by Jon Stojan Media under HackerNoon’s Brand As An Author Program. Learn more about the program here: https://business.hackernoon.com/brand-as-author https://business.hackernoon.com/brand-as-author

Obinna Odirionye: How This Founder Is Reimagining Cloud Computing in 2024

Part 1: Odell vs Saylor It was only last week, exact date and time unknown given how well-protected is the individual data. A Nostr client and Cypherpunk going by ODELL, unleashed a seething post from the depths of his Post Office. The post started by saying it was not controversial, in capital letters. Then proceeded to say something controversial. This, in addition to other, capital-lettered posts. In brief, Odell claims that Michael Saylor, a prominent Bitcoin whale and renowned hodler, is against the funding of Bitcoin developers. Let Bitcoin “ossify”, believes Saylor (says people on his side). So the code can become something so usual humans sing it in an anthem. Like, unchanged. *** Meanwhile, Mr. Saylor hasn't said anything to either deny or verify the aforementioned claims nee sayings in his name. The Advantage of Not Funding Bitcoin Developers Aside from the snide remarks and memes on X comparing BTC Devs to busybodies, the biggest threat of the ‘Dev Funding Race’, goes the argument, is that it incentivizes fiat overlords to bulldoze Bitcoin into the shape and form that they want. Masked as “maintenance” and “upgrades”, perpetual changes to Bitcoin's code could leave vulnerabilities. Currently, Bitcoin is still struggling, and the price won't stop dancing around $69k. It is barely a trillion-dollar asset. Meanwhile, the fiat world boasts hundreds of trillions of dollars, and Bitcoin ETF companies alone are bench-pressing north of 100 billion dollars. And they want to dangle all those carrots in front of our developers. Evil. But it might be true. Jack Dorsey mentioned names. Bitcoin developers have lived for years like the Fremen of Dune. Modestly quenching their financial thirst with drops of donated water-satoshis. Recycling each sat they get their hands on while leveraging more circularity than a hamster on a new wheel. Yes, while we all reap the benefits. Now, the promise of big money raining down on their well-honed skills is a big threat to the core code. Like lawyers, they are itching to change the Constitution. But hey, what is a developer who does not develop new tools? The devs in the wider cryptocurrency community must be cracking their ribs with laughter. And counting their lucky altcoins, grateful for the fact that they can buidl. A Developer Shall Develop. What do you call a developer who does not develop on a whim? A Watcher. A Waiter. Waiting for the call to help. Like a Lone Ranger in a Western. But that is painfully lonely. And sounds segregative af if we enforce it on other people. Honestly? Developing is a form of free speech. So no one can actually stop developers from speaking their speech. Go ahead, develop. It is the highest form of individual autonomy known to humans in this digital age. Paid or Not paid. For if you can develop, you can maintain your digital privacy (which is just privacy), maximum autonomy, and making a few bucks for people who want features isn't too bad either. Win-win-win. I dare say, if we could all develop (We cannot. It is a vocation some of us shall only inch towards. Slowly), this would not even be an issue. It would be strange for Saylor, anybody, to even suggest that Bitcoin developers try not to develop too much. However, Bitcoin being what it is, a global community project of extreme importance, actually constrains hacker ethos so much there won't be any cypherpunks like the pre-Bitcoin OGs. Forget flipping it to centralized systems anymore by engineering some arcane codex. Now, it is a game of sitting and waiting and watching. Praying that the price stops dancing around $69k. Saylor and his crew imply that the price of freedom is to follow the majority. And the majority says just sit, wait, and watch. But do they? The conversation is still evolving. Here is more data so that you have an informed opinion. How Odell and His Crew Are Right Here is a listicle of all the good points supporting Mr. Odell and his band of merry devs. The First Bitcoiner was a Bitcoin Developer. He was called Satoshi Nakamoto. You might have heard of him. 2. The Last Bitcoiner will be a Bitcoin Developer. When the Bitcoin is finally dead (a nuclear holocaust will end it), only a developer listening for its faint signals in the cold dark nuclear winter shall help keep the flame of freedom alive. 3. When in doubt, we ask Bitcoin Developers. Don't know why Michael Saylor is so confident that the US government cannot hack his bitcoins? Ask a Bitcoin Developer. 4. Developer Wars birth great stuff. Like the Lightning Network. Once Upon a Time, Bitcoin Developers fought for 2 bitter years over how much storage space should be held by Bitcoin. In the end, they doubled the storage space from 1MB to 2MB, invented Segwit which kept fees very low for a long time, and work on Segwit helped birth the Lightning Network. When developers fight, good things happen. When politicians fight, … 5. If ETF people want arcane-looking wallets with features from the year 3000, they have a right to pay for them. I think the key problem in this battle between Odell and Saylor is the fear that deep-pocket ETF funds may corrupt most Bitcoin developers. Otherwise, Bitcoin developers have been funded forever, and no one has been complaining. Indeed, Ark Invest should tell us what they need to pay OG Bitcoin developers some eye-popping sums of money for. If they want features, they could pay this to anybody else who is into UI. Bitcoin core devs are OUR lawyers, and they unravel weird shit like weird fee hikes and why LN nodes need a balance before any money can be received at all from other nodes. Bullshit. OG Bitcoin core devs have a right to build what they want and that does not mean they are corrupt. If a job developing UIs pays more than one developing arcane zk proofs, I'm taking the UI job. Let's not put evil intent into people's praxeologic actions. Give Ark and Bitcoin devs a chance. Then judge them when they mess shit up. Coz it could be magic. It can always be unmessed up. It is software, and we have all the commits in the GitHub repo. (It is not the same as giving Ark your money. That is on you. DYOR). Basically, let's all have some balls and break some dev rules. 6. ETFs paying Developers does not mean we shall be bought as well. Point 5 above feels like if the OG Bitcoiner developers are bought, doom and gloom for the rest of us non-dev plebs. But I assure you, if Bitcoin drops its 21 million coin supply cap for any reason, I will not follow it. That will not be Bitcoin but some silly hard fork. Call it BFD - Bitcoin For Devs. It will be worth exactly 0 US dollars after a few days. 7. Developing is greater speech than English. Last for today, but certainly not least. We should all aim to be Bitcoin developers, AI developers, Quantum Developers, and Math gurus creating an alternative universe free from the greed and psyop pervasive in this universe. But on the same planet earth. Orthogonal to this one in cyberspace. Bitcoin has done it for money. But planting a seed and watering it are two different things. And it will start by paying devs and supporting the right to pay devs. 100 years from today, Bitcoin should look like it is 100 years from today. Developing is how that happens. If developers break something we can always cancel them on X. Then unbreak it back. Part 1: Odell vs Saylor It was only last week, exact date and time unknown given how well-protected is the individual data. A Nostr client and Cypherpunk going by ODELL, unleashed a seething post from the depths of his Post Office. The post started by saying it was not controversial, in capital letters. Then proceeded to say something controversial. This, in addition to other, capital-lettered posts. In brief, Odell claims that Michael Saylor, a prominent Bitcoin whale and renowned hodler, is against the funding of Bitcoin developers. Let Bitcoin “ossify”, believes Saylor (says people on his side). So the code can become something so usual humans sing it in an anthem. Like, unchanged . unchanged *** Meanwhile, Mr. Saylor hasn't said anything to either deny or verify the aforementioned claims nee sayings in his name. The Advantage of Not Funding Bitcoin Developers Aside from the snide remarks and memes on X comparing BTC Devs to busybodies, the biggest threat of the ‘Dev Funding Race’, goes the argument, is that it incentivizes fiat overlords to bulldoze Bitcoin into the shape and form that they want. Masked as “maintenance” and “upgrades”, perpetual changes to Bitcoin's code could leave vulnerabilities. Currently, Bitcoin is still struggling, and the price won't stop dancing around $69k. It is barely a trillion-dollar asset. Meanwhile, the fiat world boasts hundreds of trillions of dollars, and Bitcoin ETF companies alone are bench-pressing north of 100 billion dollars. And they want to dangle all those carrots in front of our developers. Evil. But it might be true. Jack Dorsey mentioned names. Bitcoin developers have lived for years like the Fremen of Dune. Modestly quenching their financial thirst with drops of donated water-satoshis. Recycling each sat they get their hands on while leveraging more circularity than a hamster on a new wheel. Yes, while we all reap the benefits. Now, the promise of big money raining down on their well-honed skills is a big threat to the core code. Like lawyers, they are itching to change the Constitution. But hey, what is a developer who does not develop new tools? The devs in the wider cryptocurrency community must be cracking their ribs with laughter. And counting their lucky altcoins, grateful for the fact that they can buidl. A Developer Shall Develop. What do you call a developer who does not develop on a whim? A Watcher. A Waiter. Waiting for the call to help. Like a Lone Ranger in a Western. But that is painfully lonely. And sounds segregative af if we enforce it on other people. Honestly? Developing is a form of free speech. So no one can actually stop developers from speaking their speech. Go ahead, develop. It is the highest form of individual autonomy known to humans in this digital age. Paid or Not paid. For if you can develop, you can maintain your digital privacy (which is just privacy), maximum autonomy, and making a few bucks for people who want features isn't too bad either. Win-win-win. I dare say, if we could all develop (We cannot. It is a vocation some of us shall only inch towards. Slowly), this would not even be an issue. It would be strange for Saylor, anybody, to even suggest that Bitcoin developers try not to develop too much. However, Bitcoin being what it is, a global community project of extreme importance, actually constrains hacker ethos so much there won't be any cypherpunks like the pre-Bitcoin OGs. Forget flipping it to centralized systems anymore by engineering some arcane codex. Now, it is a game of sitting and waiting and watching. Praying that the price stops dancing around $69k. Saylor and his crew imply that the price of freedom is to follow the majority. And the majority says just sit, wait, and watch. But do they? The conversation is still evolving. Here is more data so that you have an informed opinion. How Odell and His Crew Are Right Here is a listicle of all the good points supporting Mr. Odell and his band of merry devs. The First Bitcoiner was a Bitcoin Developer. The First Bitcoiner was a Bitcoin Developer. He was called Satoshi Nakamoto. You might have heard of him. 2. The Last Bitcoiner will be a Bitcoin Developer. When the Bitcoin is finally dead (a nuclear holocaust will end it), only a developer listening for its faint signals in the cold dark nuclear winter shall help keep the flame of freedom alive. 3. When in doubt, we ask Bitcoin Developers. Don't know why Michael Saylor is so confident that the US government cannot hack his bitcoins? Ask a Bitcoin Developer. 4. Developer Wars birth great stuff. Like the Lightning Network. Once Upon a Time, Bitcoin Developers fought for 2 bitter years over how much storage space should be held by Bitcoin. In the end, they doubled the storage space from 1MB to 2MB, invented Segwit which kept fees very low for a long time, and work on Segwit helped birth the Lightning Network. When developers fight, good things happen. When politicians fight, … 5. If ETF people want arcane-looking wallets with features from the year 3000, they have a right to pay for them. I think the key problem in this battle between Odell and Saylor is the fear that deep-pocket ETF funds may corrupt most Bitcoin developers. Otherwise, Bitcoin developers have been funded forever, and no one has been complaining. Indeed, Ark Invest should tell us what they need to pay OG Bitcoin developers some eye-popping sums of money for. Ark Invest If they want features, they could pay this to anybody else who is into UI. Bitcoin core devs are OUR lawyers, and they unravel weird shit like weird fee hikes and why LN nodes need a balance before any money can be received at all from other nodes. Bullshit. OG Bitcoin core devs have a right to build what they want and that does not mean they are corrupt. If a job developing UIs pays more than one developing arcane zk proofs, I'm taking the UI job. Let's not put evil intent into people's praxeologic actions. Give Ark and Bitcoin devs a chance. Then judge them when they mess shit up. Coz it could be magic. It can always be unmessed up. It is software, and we have all the commits in the GitHub repo. (It is not the same as giving Ark your money. That is on you. DYOR). Basically, let's all have some balls and break some dev rules. 6. ETFs paying Developers does not mean we shall be bought as well. Point 5 above feels like if the OG Bitcoiner developers are bought, doom and gloom for the rest of us non-dev plebs. But I assure you, if Bitcoin drops its 21 million coin supply cap for any reason, I will not follow it. That will not be Bitcoin but some silly hard fork. Call it BFD - Bitcoin For Devs. It will be worth exactly 0 US dollars after a few days. 7. Developing is greater speech than English. Last for today, but certainly not least. We should all aim to be Bitcoin developers, AI developers, Quantum Developers, and Math gurus creating an alternative universe free from the greed and psyop pervasive in this universe. But on the same planet earth. Orthogonal to this one in cyberspace. Bitcoin has done it for money. But planting a seed and watering it are two different things. And it will start by paying devs and supporting the right to pay devs. 100 years from today, Bitcoin should look like it is 100 years from today. Developing is how that happens. If developers break something we can always cancel them on X. Then unbreak it back.

Odell Vs Saylor - Should Bitcoin Devs Dev?

Scientific American Supplement, No. 365, December 30, 1882 by Various, is part of the HackerNoon Books Series. You can jump to any chapter in this book . THE ABA OR ODIKA. here THE ABA OR ODIKA. By W.H. Bacheler, M.D. Among the many luxuriant and magnificent forest trees of equatorial West Africa, none can surpass, for general beauty and symmetry, that which is called by the natives the "aba." When growing alone and undisturbed, its conical outline and dark green foliage remind one very much of the white maples of the northern United States, by a distant view, but, on a nearer approach, a dissimilarity is observed. Wherever, in ravines or near the banks of rivers, the soil is moist the most part of the year, there the aba chooses to grow, and during the months of June and July the falling fruits permeate the atmosphere with a delicious fragrance not similar to any other. This, in form, size, and general appearance, is very much like mango apples, so that the natives call mangoes the "white man's aba;" but the wild aba is not much eaten as a fruit, one or two being sufficient for the whole season. The kernel, or seed, is the important and useful part. When the fallen fruit covers the ground, much as apples do in America, the natives go in canoes to gather it, and the number harvested will be in proportion to the industry of the women. The aba plum is about the size of a goose's egg, of a flattened, ovoid shape, and, when ripe, a beautiful golden color. It consists of three distinct parts: the rind, the pulp, and the seed. The pulp consists of a mass extensively interwoven with strong filaments, which apparently grow out of the seed and are with great difficulty separated from it. The seed, reniform in shape, is bivalved, and constitutes about two-thirds of the bulk of the entire plum, and the inner kernel two-thirds the bulk of the seed. In consequence of it being such a high tree and growing in such inconvenient places, I have been unable to procure a specimen of the flowers. As soon as the fruit is brought to the village, all the inhabitants assemble with cutlasses and engage in the work of opening the plums and removing the kernels. The former are thrown away as useless. The seeds are evenly spread on the top of a rack of small sticks, under which a fire is built in the morning, and subjected to the smoke and heat of an entire day. Toward evening the heat is greatly augmented, and in a couple of hours the process is completed. The kernels are now soft, and the oil oozing from them, and while yet in this condition they are thrown into an immense trough and throughly beaten and mashed with a pestle. Baskets, with banana leaves spread in the inside to prevent the escape of the product, are in readiness, and it is put into them and pressed down. The next day these baskets are suspended in the sun, and at night are brought into the houses to congeal. The process is now finished. The cakes are removed by inversion of the baskets and "bushrope" tied around them, by which the pieces are carried. As thus prepared, odika is highly esteemed by the natives as an article of food, being made into a kind of thick gravy and eaten with boiled plantains. While at an interior mission station on the Ogowe River, I made some experiments in soap making. With palm oil I succeeded very well, using for an alkali the old-fashioned lye of ashes. But I was disappointed with the odika, though I learned some peculiar characteristics of it as a grease. By boiling the crude odika, I was unable, as I hoped, to separate the oleaginous from the extraneous matter, of which it contains a large proportion, but when the above-mentioned lye was used instead of water, the mass, instead of saponifying, merely separated; the grease, resembling very much in all particulars ordinary beef tallow, rising to the top of the caldron, while the refuse was precipitated. After clarifying this, it answers instead of oil of theobroma very nicely, and I have used it considerably in making ointments and suppositories with pleasing results. Gaboon, W. Africa, Aug., 1882.— New Remedies. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Various (2006). Scientific American Supplement, No. 365, December 30, 1882. Urbana, Illinois: Project Gutenberg. Retrieved https://www.gutenberg.org/cache/epub/18763/pg18763-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at , located at . www.gutenberg.org https://www.gutenberg.org/policy/license.html

THE ABA OR ODIKA

The Oedipus Problem

Moe "Moechievous" Odele, is the Founding Partner at Vazi Legal and the founder of Scale My Hustle. Vazi Legal is a foremost tech-focused law firm with practices in Nigeria and the United States. They provide legal services to tech startups, venture capital funds, and other organisations. Scale My Hustle is a social enterprise focused on helping entrepreneurs build better-structured businesses by providing educational content and an online community for current and aspiring entrepreneurs. In this interview, Moe shares her life and her career journey. From her experience growing up in a polygamous family to studying Law, delving into tech law, and being a human rights advocate. Watch the video https://www.youtube.com/watch?v=R-PMvGQ2rgY&t=28s Video timestamps - Introduction 0:00 - Moe's Background, Childhood, Early Independence, Polygamy 1:47 - Fondest memory as a child 4:19 - School, Studying Law, her Father 6:14 - Anything from Law school or Uni that sticks with her. 9:19 - Finishing Law School and Starting her Career 10:00 - First introduction into tech, getting into Tech Law. 15:42 - Going to Columbia Law School, Gaining more insight into Tech Law 19:45 - The inception of VaziLegal 23:40 - The inception of ScaleMyHustle 24:41 - Where VaziLegal and ScaleMyHustle meet. 26:08 - Building a Personal Brand 27:27 - How she will like to be known, on Impact 30:42 - Why Tech Law matters in her Impact 33:34 - What makes VaziLegal stand out, and what challenges she faced when starting her firm. 37:16 - What she is most proud of 42:11 - Two experiences that have shaped who she has. 44:42 - On Travelling. 48:59 - Lessons from Travelling. 51:56 - The most difficult thing about being Moe. 55:30 - Takeaway points 57:03

#FoundersConnect: Moe Odele - Tech Lawyer, Human Rights Advocate & Travel Enthusiast

As organizations deploy and maintain modern applications and microservices, Observability technologies (eBPF & OpenTelemetry) are needed to expose their health & security. If you’re using these technologies for Tracing, Metrics or Logs in a production software system, you’re either sending telemetry data directly from you application or using a collector. Configuring OpenTelemetry to send traces and metrics directly from your app to your desired destination has the benefit of not running any additional software (no ports to configure, no processes to manage). The downside is that your application must manage the entire workload of sending your data in a production environment (running resource-intensive services), as well as the as you scale (or add new applications). need to continuously configure and update your code Offloading the job of sending data directly from the application can be a huge help. Deploying collectors allows you to process telemetry and send it out to any destination. The OpenTelemetry Collector, an open-source project backed by the CNCF, offers a vendor-agnostic implementation that uses pipelines to receive, process, and export trace data. It is a stand-alone service chaining together plugins to form an observability pipeline that buffers data, scrubs it, and sends to one or more open-source or commercial back-ends. The OpenTelemetry Collector is configurable. When tasked with deploying Collectors in a production environment, Devops team will find two repositories containing dozens of modules, with many integration possibilities. The problem is that it’s hard to know what module will best fit your changing requirements. Without proper implementation and continuous configuration of your collectors, observability tools will be limited at best and many times ineffectual. There are solutions out there. Many of the large commercial observability tool vendors provide different open-source solutions that will ease implementation. Often, implementation will include vendor specific API’s that are not compatible with other tools, further complicating any efforts of working with more than one vendor. Actual implementation and integration are still a lengthy process that requires knowledge and experience to get done right. It’s enough to take a quick look at the “getting started” pages of the different observability vendors out there to see how complicated this integration still is. Odigos, an open-source observability control plane just released in July ’22, provides auto-instrumentation as well as a collector management capabilities. The platform is actually comprised of four fundamental parts: an Instrumentor, Scheduler, Auto-scaler & the UI. This is the way it works: First, Odigos the different programming languages used in each application recognizes Then it each application using different (open-source) tools for each programming language auto-instruments The deploys and configures the OpenTelemetry collectors auto-scaler The assigns applications discovered by the instrumentor to the collector’s pipeline create by the auto-scaler scheduler Finally, a provides a simple interface to manage the whole process UI Odigos’s advantages include its easy installation and its ability to continuously adapt as well as scale to size. The auto-instrumentation will allow Odigos to recognize new application the minute it starts running on your system, and automatically deploy the appropriate collectors. A new application will produce signals without any additional interventions needed. No changes to the code, no developer action needed and no Devops team required! Summary Integrating Observability Tools require companies to make several changes and configurations to their applications and infrastructure. Current solutions still demand tech teams to continuously deploy, configure and update collectors, as well as learn SDK’s, add auto-instrumentation, change application code – all requiring new and different developer skillsets. With the latest advancements in observability technologies (eBPF & OpenTelemetry), companies can now build their observability pipeline with complete end-to-end open-source solution. Using open-source (Jaeger, Grafana, etc.) or commercial back-ends together with the open-source Odigos observability control plane, companies can get full end-to-end visibility. Ultimately, Odigos provides a simple installation that allows companies to get traces, metrics, and logs within minutes – and takes care of managing (configuring, deploying and scaling) your OpenTelemetry collectors. Also published . here

Managing Collectors on K8 – Why We Chose the OpenTelemetry Collector for Odigos

J.P Morgan says the crypto bottom is in. The Treasury Department just banned a DeFi protocol. Jim Cramer says now is a good time to buy Ethereum. What do all of these things have in common? They’re the latest symptoms of crypto’s troubling Wall-street-ification – more signs that an industry founded in the wake of the worst financial crisis since the Great Depression has veered off its intended course. Of the top 15 crypto projects , two are dog coins that do nothing, three are Ethereum-killers that nobody uses, and most of the others are stablecoins. At the same time, crypto YouTubers are sharing clickbait videos with absurd predictions about low-cap coins they plan on dumping on their viewers. And Satoshi rolls over in his grave. by market cap Where has our courage gone? Or is this systematic filtering out of meaning the fate that every new technology experiences? Is there anything we can do about it? Let’s think it through together. Noble Foundations This is the first public thing that was ever said about Bitcoin – the asset that finally brought the idea of cryptocurrency to the masses. It was posted before the bottom of the 2008 financial crisis. just a month Satoshi immediately highlights the problems with conventional currency and central banks. Then he goes on to talk about the importance of privacy for privacy’s sake. His/her/their vision was immediately clear right from the beginning. Satoshi intended for Bitcoin to be different. It was a middle finger to the establishment from day one, and that remained the predominant spirit of the Bitcoin community for over five years. 2017 – The Beginning of the End Bitcoin and the other cryptocurrencies that it inspired remained a niche trend until 2017 when the price of BTC exploded to nearly $20,000, and early adopters became rich. Suddenly, millions of new people were hearing about Bitcoin on the news for the first time. And what began as a punk expression of dissatisfaction with existing financial systems was suddenly being discussed by the very people who maintained and fueled those systems. Most people who were exposed to Bitcoin for the first time during this cycle saw the flagship cryptocurrency as a way to get rich, not as the that Satoshi envisioned. artful middle finger Then, like a fire that burned too high, too fast, the crypto market collapsed under its weight and went through a deep, ashen winter from early 2018 until just after the economic collapse spurred by COVID-19. Ethereum and DeFi When it was founded in 2015, Ethereum promised to build upon Satoshi’s vision by pioneering the use of decentralized smart contracts. This opened up entirely new possibilities for the world of decentralized finance. Maker, the protocol behind the decentralized stablecoin DAI, was one of the first key DeFi innovators to take advantage of Ethereum’s network. After that, a string of key DeFi protocols launched during the 2017 market cycle and ICO mania, including: Aave – the number one decentralized borrowing and lending protocol Synthetix – a liquidity protocol for derivatives 0x – an open protocol that allowed for the peer-to-peer exchange of assets These innovations eventually led to even more impactful decentralized finance applications, like Compound and Uniswap, which sparked DeFi summer in 2020, and introduced the term to the world. Where Are We Now? Since 2017, we’ve gone through another full market cycle. Ethereum has continued chugging along to achieve its long-term usability goals. Bitcoin has remained largely unchanged. And a trillion dollars have come in and out of the crypto ecosystem as new participants attempt to stake their claims to the digital age’s gold rush. There’s an incredible amount of speculation happening. There are virtual worlds worth billions of dollars that nobody uses. New DeFi protocols launch tokens that are purposeless and rise by 10,000%. VC bros are funding new layer 1s with billion-dollar valuations that no one will use— and they know it. Everybody wants to be first to the next big crypto innovation so they can get rich, too. Now, OG DeFi protocols like Aave are limiting who can use their “decentralized services” based on arbitrary decisions made by the U.S. government and institutions that Bitcoin was designed to circumvent. Decentralized finance? Can we really say that anymore? We’re clearly at an inflection point. The government is starting to take crypto regulation seriously. It’s likely to continue limiting what protocols can legally do. How will they respond? Early indications point to total and complete compliance. But even if some resist, it’s become abundantly clear that crypto’s OG culture of defiance is largely gone. It’s been replaced by, Blackrock and Jay Powell and, The S&P 500 and hypebeasts and, NFT scammers and Facebook and, Anthony Pompliano and Bored Ape Yacht Club and, KYC requirements and Walmart, and . The perpetrators of the Great Financial Crisis Internet Culture as a Measuring Stick If there’s any point of comparison to be made about what’s happening to crypto culture right now, it’s the invention of the internet. First made available to the wider public in , internet culture has shifted dramatically over time. 1993 In its earliest days, the internet was a way for academics and researchers to easily share ideas with one another. Even then, it was obvious that it would change the world. People wrote about the internet opening up new channels of communication between economic and geographic borders, and how the open flow of information would spawn a renaissance the likes of which the world had never seen. That’s happened. The internet has fundamentally changed our culture. It’s enabled people to learn and become masters of things they might’ve never discovered otherwise. But it’s also been overrun by corporations who prey upon user data and social media platforms that leverage our biology to keep us addicted to continually scrolling even as our health deteriorates from doing so. There are beautiful pockets of culture and meaning to be found on the internet. But there’s a dark side, too. And it’s up to us, as users, to limit the impact that it has on our minds and bodies. Where Do We Go From Here? Crypto culture started as a pure punk expression of anger and disenchantment in the wake of a banker-fueled economic collapse. That’s not what it is today, just like the internet isn’t what it was in its early years. The lesson, at least to me, is that when new technological networks become widespread, rent-seekers will always demand a cut. They are vultures waiting for an opportunity to wet their beaks on the latest step in humanity’s journey. But it’s worth pointing out that niche cultures like the early cypherpunks are, by definition, small subsets of the population. When world-changing innovations explode out from these small groups into broader society, people with different views must continue buying in order for them to hit exit velocity. That leads us to the sad truth, which is that as more and more people join the cryptocurrency industry, its purpose and meaning — the values that it was founded on — will continue diluting. But that doesn’t mean that DeFi is dead. It doesn’t mean that crypto is going to zero. And it doesn’t mean that OG crypto culture is dead and gone. Crypto is becoming something that everyone can use, like the internet before it – rent-seekers and bankers included. Many of us may not want them here, but a decentralized technology has no method or basis for being picky. Those of us who value the founding principles of cryptocurrency must fight to keep them alive as the culture expands. We’ll do that by putting our money where our mouth is and voting with our wallets for protocols and apps that keep Satoshi’s middle finger pointed high in the sky long enough for the next generation to do the same. Also published here

DeFi Without Defiance. An Ode to Lost Crypto Culture

DeFi sin desafío. Una oda a la criptocultura perdida

DeFi sans défi. Une ode à la culture crypto perdue

डेफी विदाउट डिफेन्स। क्रिप्टो संस्कृति को खोने के लिए एक ओड

反抗のないDeFi。失われた暗号文化への頌歌

DeFi sem desafio. Uma ode à cultura criptográfica perdida

DeFi Không có Defiance. Ode to Lost Crypto Culture

没有反抗的 DeFi。对失落的加密文化的颂歌

This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license.
Authors:
(1) Ehud Shapiro,  Department of Computer Science and Applied Math, Weizmann Institute of Science, Israel and ehud.shapiro@weizmann.ac.il. Table of Links Abstract and Introduction
Grassroots Protocols
Grassroots Implementation of Grassroots Dissemination
Applications of Grassroots Dissemination Supporting Digital Sovereignty
Future Work & Discussion
References
A. Preliminaries: Asynchronous Distributed Multiagent Transition Systems
B. All-to-All Dissemination is not Grassroots
C. Proofs 5 Future Work & Discussion Grassroots dissemination for sovereign cryptocurrencies. While the Grassroots Dissemination protocol GD is better-suited for implementing sovereign cryptocurrencies than the All-to-All Dissemination protocol AD, it should be refined to support a genuinelypractical implementation, allowing an agent to: (i) Follow another agent starting from an arbitrary block (not from its initial block), in particular from the first block recording a transaction between the two agents. (ii) Unfollow an agent, for example when financial relations between the two have ended, permanently or temporarily. Such extensions to GD are possible with little additional implementation effort and with some additional mathematical effort for specifying them and proving them correct. Grassroots and the Internet. Formally, the underlying Internet protocol stack is not grassroots, as IP addresses are allocated top-down, with a central entity (IANA) at the top. Does this mean that striving for grassroots protocols is futile? We do not think so. First, the full benefits of grassroots protocols can be reaped as long as IANA does not abuse IP address allocation and Internet access is not restricted or abused. Second, if the local regime restricts access to servers/services, but does not shut-down the Internet, grassroots protocols may still operate. Third, mobile mesh networks or SPANs (Smartphone ad-hoc networks) [1] allow communities to communicate in times of strife (e.g. demonstrations against the regime) without an Internet provider (but current designs are vulnerable [1]). Extending the UDP-based Cordial Grassroots Dissemination protocol to a mobile mesh protocol is a goal of our future research. Achieving it would realize the original vision of Xerox PARC’s Bayou [10] project, of peer-to-peer update upon physical proximity. Acknowledgements. Ehud Shapiro is the Incumbent of The Harry Weinrebe Professorial Chair of Computer Science and Biology at the Weizmann Institute. I thank Nimrod Talmon and Oded Naor for their comments on an earlier version of the manuscript and Idit Keidar for pointing me to related work. This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: (1) Ehud Shapiro,  Department of Computer Science and Applied Math, Weizmann Institute of Science, Israel and ehud.shapiro@weizmann.ac.il. This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: Authors: (1) Ehud Shapiro,  Department of Computer Science and Applied Math, Weizmann Institute of Science, Israel and ehud.shapiro@weizmann.ac.il. Table of Links Abstract and Introduction Grassroots Protocols Grassroots Implementation of Grassroots Dissemination Applications of Grassroots Dissemination Supporting Digital Sovereignty Future Work & Discussion References A. Preliminaries: Asynchronous Distributed Multiagent Transition Systems B. All-to-All Dissemination is not Grassroots C. Proofs Abstract and Introduction Abstract and Introduction Grassroots Protocols Grassroots Protocols Grassroots Implementation of Grassroots Dissemination Grassroots Implementation of Grassroots Dissemination Applications of Grassroots Dissemination Supporting Digital Sovereignty Applications of Grassroots Dissemination Supporting Digital Sovereignty Future Work & Discussion Future Work & Discussion References References A. Preliminaries: Asynchronous Distributed Multiagent Transition Systems A. Preliminaries: Asynchronous Distributed Multiagent Transition Systems B. All-to-All Dissemination is not Grassroots B. All-to-All Dissemination is not Grassroots C. Proofs C. Proofs 5 Future Work & Discussion Grassroots dissemination for sovereign cryptocurrencies. While the Grassroots Dissemination protocol GD is better-suited for implementing sovereign cryptocurrencies than the All-to-All Dissemination protocol AD, it should be refined to support a genuinelypractical implementation, allowing an agent to: (i) Follow another agent starting from an arbitrary block (not from its initial block), in particular from the first block recording a transaction between the two agents. (ii) Unfollow an agent, for example when financial relations between the two have ended, permanently or temporarily. Such extensions to GD are possible with little additional implementation effort and with some additional mathematical effort for specifying them and proving them correct. Grassroots and the Internet. Formally, the underlying Internet protocol stack is not grassroots, as IP addresses are allocated top-down, with a central entity (IANA) at the top. Does this mean that striving for grassroots protocols is futile? We do not think so. First, the full benefits of grassroots protocols can be reaped as long as IANA does not abuse IP address allocation and Internet access is not restricted or abused. Second, if the local regime restricts access to servers/services, but does not shut-down the Internet, grassroots protocols may still operate. Third, mobile mesh networks or SPANs (Smartphone ad-hoc networks) [1] allow communities to communicate in times of strife (e.g. demonstrations against the regime) without an Internet provider (but current designs are vulnerable [1]). Extending the UDP-based Cordial Grassroots Dissemination protocol to a mobile mesh protocol is a goal of our future research. Achieving it would realize the original vision of Xerox PARC’s Bayou [10] project, of peer-to-peer update upon physical proximity. Grassroots and the Internet. Acknowledgements. Ehud Shapiro is the Incumbent of The Harry Weinrebe Professorial Chair of Computer Science and Biology at the Weizmann Institute. I thank Nimrod Talmon and Oded Naor for their comments on an earlier version of the manuscript and Idit Keidar for pointing me to related work. Acknowledgements.

Grassroots Distributed Systems for Digital Sovereignty: Future Work & Discussion

This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license.
Authors:
(1) Ehud Shapiro,  Department of Computer Science and Applied Math, Weizmann Institute of Science, Israel and ehud.shapiro@weizmann.ac.il. Table of Links Abstract and Introduction
Grassroots Protocols
Grassroots Implementation of Grassroots Dissemination
Applications of Grassroots Dissemination Supporting Digital Sovereignty
Future Work & Discussion
References
A. Preliminaries: Asynchronous Distributed Multiagent Transition Systems
B. All-to-All Dissemination is not Grassroots
C. Proofs References 1 Martin R Albrecht, Jorge Blasco, Rikke Bjerg Jensen, and Lenka Mareková. Mesh messaging in large-scale protests: Breaking bridgefy. In Cryptographers’ Track at the RSA Conference, pages 375–398. Springer, 2021. 2 Juan Benet. Ipfs-content addressed, versioned, p2p file system. arXiv preprint arXiv:1407.3561, 2014. 3 Sonja Buchegger, Doris Schiöberg, Le-Hung Vu, and Anwitaman Datta. Peerson: P2p social networking: early experiences and insights. In Proceedings of the Second ACM EuroSys Workshop on Social Network Systems, pages 46–52, 2009. 4 Vitalik Buterin et al. A next-generation smart contract and decentralized application platform. white paper, 3(37), 2014. 5 Manuel Castells. The city and the grassroots: a cross-cultural theory of urban social movements. Number 7. Univ of California Press, 1983. 6 Miguel Castro, Barbara Liskov, et al. Practical byzantine fault tolerance. In OsDI, volume 99, pages 173–186, 1999. 7 Gregory Chockler, Roie Melamed, Yoav Tock, and Roman Vitenberg. Constructing scalable overlays for pub-sub with many topics. In Proceedings of the twenty-sixth annual ACM symposium on Principles of distributed computing, pages 109–118, 2007. 8 Gregory Chockler, Roie Melamed, Yoav Tock, and Roman Vitenberg. Spidercast: a scalable interest-aware overlay for topic-based pub/sub communication. In Proceedings of the 2007 inaugural international conference on Distributed event-based systems, pages 14–25, 2007. 9 Bram Cohen. Incentives build robustness in bittorrent. In Workshop on Economics of Peer-to-Peer systems, volume 6, pages 68–72. Berkeley, CA, USA, 2003. 10 Alan Demers, Karin Petersen, Mike Spreitzer, Doug Terry, Marvin Theimer, and Brent Welch. The bayou architecture: Support for data sharing among mobile users. In 1994 First Workshop on Mobile Computing Systems and Applications, pages 2–7. IEEE, 1994. 11 Bitcoin Developer. P2p network, Retrieved 20222. URL: https://developer.bitcoin.org/ devguide/p2p_network.html. 12 Ethereum Developer. go-ethereum/params/bootnodes.go, Retrieved 2023. URL: https://github.com/ethereum/go-ethereum/blob/master/params/bootnodes.go. 13 Adem Efe Gencer, Soumya Basu, Ittay Eyal, Robbert van Renesse, and Emin Gün Sirer. Decentralization in bitcoin and ethereum networks. In International Conference on Financial Cryptography and Data Security, pages 439–457. Springer, 2018. 14 Gabriele Goldacker. Digitale souveränität [white paper of kompetenzzentrum öffentliche it (öfit)]. retrieved april 20, 2021, 2017. 15 Idit Keidar, Eleftherios Kokoris-Kogias, Oded Naor, and Alexander Spiegelman. All you need is dag, 2021. arXiv:2102.08325. 16 Idit Keidar, Oded Naor, and Ehud Shapiro. Cordial miners: A family of simple and efficient consensus protocols for every eventuality. arXiv preprint arXiv:2205.09174, 2022. 17 Antony Lewis. A gentle introduction to self-sovereign identity. 2017. URL: https://bitsonblocks.net/2017/05/17/a-gentle-introduction-to-self-sovereign-identity/. 18 Satoshi Nakamoto. Bitcoin: A peer-to-peer electronic cash system, 2019. 19 Romualdo Pastor-Satorras, Claudio Castellano, Piet Van Mieghem, and Alessandro Vespignani. Epidemic processes in complex networks. Reviews of modern physics, 87(3):925, 2015. 20 Julia Pohle and Thorsten Thiel. Digital sovereignty. Internet Policy Review: Journal on Internet Regulation, 9(4):1–19, 2020. 21 Aravindh Raman, Sagar Joglekar, Emiliano De Cristofaro, Nishanth Sastry, and Gareth Tyson. Challenges in the decentralised web: The mastodon case. In Proceedings of the Internet Measurement Conference, pages 217–229, 2019. 22 Vinay Setty, Maarten van Steen, Roman Vitenberg, and Spyros Voulgaris. Poldercast: Fast, robust, and scalable architecture for p2p topic-based pub/sub. In ACM/IFIP/USENIX International Conference on Distributed Systems Platforms and Open Distributed Processing, pages 271–291. Springer, 2012. 23 Devavrat Shah et al. Gossip algorithms. Foundations and Trends® in Networking, 3(1):1–125, 2009. 24 Ehud Shapiro. Multiagent transition systems: Protocol-stack mathematics for distributed computing. arXiv preprint arXiv:2112.13650, 2021. 25 Ehud Shapiro. Sovereign personal cryptocurrencies: A grassroots foundation for a digital economy. arXiv preprint arXiv:2202.05619, 2022. 26 Marc Shapiro, Nuno Preguiça, Carlos Baquero, and Marek Zawirski. Conflict-free replicated data types. In Symposium on Self-Stabilizing Systems, pages 386–400. Springer, 2011. 27 Robert Shostak, Marshall Pease, and Leslie Lamport. The byzantine generals problem. ACM Transactions on Programming Languages and Systems, 4(3):382–401, 1982. 28 Ion Stoica, Robert Morris, David Karger, M Frans Kaashoek, and Hari Balakrishnan. Chord: A scalable peer-to-peer lookup service for internet applications. ACM SIGCOMM computer communication review, 31(4):149–160, 2001. 29 Maofan Yin, Dahlia Malkhi, Michael K Reiter, Guy Golan Gueta, and Ittai Abraham. Hotstuff: Bft consensus with linearity and responsiveness. In Proceedings of the 2019 ACM Symposium on Principles of Distributed Computing, pages 347–356, 2019. 30 Shoshana Zuboff. The age of surveillance capitalism: The fight for a human future at the new frontier of power: Barack Obama’s books of 2019. Profile books, 2019. This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: (1) Ehud Shapiro,  Department of Computer Science and Applied Math, Weizmann Institute of Science, Israel and ehud.shapiro@weizmann.ac.il. This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: Authors: (1) Ehud Shapiro,  Department of Computer Science and Applied Math, Weizmann Institute of Science, Israel and ehud.shapiro@weizmann.ac.il. Table of Links Abstract and Introduction Grassroots Protocols Grassroots Implementation of Grassroots Dissemination Applications of Grassroots Dissemination Supporting Digital Sovereignty Future Work & Discussion References A. Preliminaries: Asynchronous Distributed Multiagent Transition Systems B. All-to-All Dissemination is not Grassroots C. Proofs Abstract and Introduction Abstract and Introduction Grassroots Protocols Grassroots Protocols Grassroots Implementation of Grassroots Dissemination Grassroots Implementation of Grassroots Dissemination Applications of Grassroots Dissemination Supporting Digital Sovereignty Applications of Grassroots Dissemination Supporting Digital Sovereignty Future Work & Discussion Future Work & Discussion References References A. Preliminaries: Asynchronous Distributed Multiagent Transition Systems A. Preliminaries: Asynchronous Distributed Multiagent Transition Systems B. All-to-All Dissemination is not Grassroots B. All-to-All Dissemination is not Grassroots C. Proofs C. Proofs References 1 Martin R Albrecht, Jorge Blasco, Rikke Bjerg Jensen, and Lenka Mareková. Mesh messaging in large-scale protests: Breaking bridgefy. In Cryptographers’ Track at the RSA Conference, pages 375–398. Springer, 2021. 2 Juan Benet. Ipfs-content addressed, versioned, p2p file system. arXiv preprint arXiv:1407.3561, 2014. 3 Sonja Buchegger, Doris Schiöberg, Le-Hung Vu, and Anwitaman Datta. Peerson: P2p social networking: early experiences and insights. In Proceedings of the Second ACM EuroSys Workshop on Social Network Systems, pages 46–52, 2009. 4 Vitalik Buterin et al. A next-generation smart contract and decentralized application platform. white paper, 3(37), 2014. 5 Manuel Castells. The city and the grassroots: a cross-cultural theory of urban social movements. Number 7. Univ of California Press, 1983. 6 Miguel Castro, Barbara Liskov, et al. Practical byzantine fault tolerance. In OsDI, volume 99, pages 173–186, 1999. 7 Gregory Chockler, Roie Melamed, Yoav Tock, and Roman Vitenberg. Constructing scalable overlays for pub-sub with many topics. In Proceedings of the twenty-sixth annual ACM symposium on Principles of distributed computing, pages 109–118, 2007. 8 Gregory Chockler, Roie Melamed, Yoav Tock, and Roman Vitenberg. Spidercast: a scalable interest-aware overlay for topic-based pub/sub communication. In Proceedings of the 2007 inaugural international conference on Distributed event-based systems, pages 14–25, 2007. 9 Bram Cohen. Incentives build robustness in bittorrent. In Workshop on Economics of Peer-to-Peer systems, volume 6, pages 68–72. Berkeley, CA, USA, 2003. 10 Alan Demers, Karin Petersen, Mike Spreitzer, Doug Terry, Marvin Theimer, and Brent Welch. The bayou architecture: Support for data sharing among mobile users. In 1994 First Workshop on Mobile Computing Systems and Applications, pages 2–7. IEEE, 1994. 11 Bitcoin Developer. P2p network, Retrieved 20222. URL: https://developer.bitcoin.org/ devguide/p2p_network.html. 12 Ethereum Developer. go-ethereum/params/bootnodes.go, Retrieved 2023. URL: https://github.com/ethereum/go-ethereum/blob/master/params/bootnodes.go. 13 Adem Efe Gencer, Soumya Basu, Ittay Eyal, Robbert van Renesse, and Emin Gün Sirer. Decentralization in bitcoin and ethereum networks. In International Conference on Financial Cryptography and Data Security, pages 439–457. Springer, 2018. 14 Gabriele Goldacker. Digitale souveränität [white paper of kompetenzzentrum öffentliche it (öfit)]. retrieved april 20, 2021, 2017. 15 Idit Keidar, Eleftherios Kokoris-Kogias, Oded Naor, and Alexander Spiegelman. All you need is dag, 2021. arXiv:2102.08325. 16 Idit Keidar, Oded Naor, and Ehud Shapiro. Cordial miners: A family of simple and efficient consensus protocols for every eventuality. arXiv preprint arXiv:2205.09174, 2022. 17 Antony Lewis. A gentle introduction to self-sovereign identity. 2017. URL: https://bitsonblocks.net/2017/05/17/a-gentle-introduction-to-self-sovereign-identity/. 18 Satoshi Nakamoto. Bitcoin: A peer-to-peer electronic cash system, 2019. 19 Romualdo Pastor-Satorras, Claudio Castellano, Piet Van Mieghem, and Alessandro Vespignani. Epidemic processes in complex networks. Reviews of modern physics, 87(3):925, 2015. 20 Julia Pohle and Thorsten Thiel. Digital sovereignty. Internet Policy Review: Journal on Internet Regulation, 9(4):1–19, 2020. 21 Aravindh Raman, Sagar Joglekar, Emiliano De Cristofaro, Nishanth Sastry, and Gareth Tyson. Challenges in the decentralised web: The mastodon case. In Proceedings of the Internet Measurement Conference, pages 217–229, 2019. 22 Vinay Setty, Maarten van Steen, Roman Vitenberg, and Spyros Voulgaris. Poldercast: Fast, robust, and scalable architecture for p2p topic-based pub/sub. In ACM/IFIP/USENIX International Conference on Distributed Systems Platforms and Open Distributed Processing, pages 271–291. Springer, 2012. 23 Devavrat Shah et al. Gossip algorithms. Foundations and Trends® in Networking, 3(1):1–125, 2009. 24 Ehud Shapiro. Multiagent transition systems: Protocol-stack mathematics for distributed computing. arXiv preprint arXiv:2112.13650, 2021. 25 Ehud Shapiro. Sovereign personal cryptocurrencies: A grassroots foundation for a digital economy. arXiv preprint arXiv:2202.05619, 2022. 26 Marc Shapiro, Nuno Preguiça, Carlos Baquero, and Marek Zawirski. Conflict-free replicated data types. In Symposium on Self-Stabilizing Systems, pages 386–400. Springer, 2011. 27 Robert Shostak, Marshall Pease, and Leslie Lamport. The byzantine generals problem. ACM Transactions on Programming Languages and Systems, 4(3):382–401, 1982. 28 Ion Stoica, Robert Morris, David Karger, M Frans Kaashoek, and Hari Balakrishnan. Chord: A scalable peer-to-peer lookup service for internet applications. ACM SIGCOMM computer communication review, 31(4):149–160, 2001. 29 Maofan Yin, Dahlia Malkhi, Michael K Reiter, Guy Golan Gueta, and Ittai Abraham. Hotstuff: Bft consensus with linearity and responsiveness. In Proceedings of the 2019 ACM Symposium on Principles of Distributed Computing, pages 347–356, 2019. 30 Shoshana Zuboff. The age of surveillance capitalism: The fight for a human future at the new frontier of power: Barack Obama’s books of 2019. Profile books, 2019.

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