Simple KDS

simplekds

Let's say you're planning to throw an awesome party. Sounds fun, right? But how will you make sure it is successful? The indicator of success can be the profit you generate by attracting a large number of attendees to the party. Additionally, you would want to ensure that attendees will return for future parties. Who do you need to work with to coordinate all of this? At a minimum, you may want to involve: Venue owner DJ Security Bartender Promo manager Designer ...and this may not be an exhaustive list. All of these individuals will have a vested interest in the successful completion of the party. However, they may not necessarily have identical needs and expectations. For instance, the venue owner may desire to generate income by renting out the space and anticipate the venue to be cleaned without any noticeable harm after the party. Meanwhile, the DJ, for instance, anticipates an audience that will value his artistic expression, and an increase in his followers on , , etc. Spotify Instagram , meaning they are parties with a vested interest in the project. → All these individuals will be your stakeholders How to categorize your stakeholders? By classifying stakeholders into different subgroups, you will be able to develop strategies around: Communications (when and how to inform) Decision-making (who and when to involve) Project work (how to cultivate ownership and engagement in the project). Typically, stakeholders are categorized based on their , , and occasionally their . interest influence behavior/attitude Let's consider, for instance, a bartender who isn't particularly concerned about the success of the party. For him, the priority is to attract a large number of attendees and receive a commission from the bar sales. Therefore, the bartender has a low interest in the overall goal and a small level of influence, as his presence or absence does not determine whether the party will take place or not. When it comes to behavior, the bartender can sometimes act as a blocker. For instance, they might refuse to work until they have an XL shaker, stating that it is impossible to work without such equipment. While they may be correct, a bartender with a more positive work attitude would make an effort to assist in finding a solution to the problem. Based on the bartender profile and using a stakeholder categorization matrix, we can create a plan outlining how we will work with them, for example: Due to low influence, we will not include the bartender in making decisions regarding the party, such as the location, DJ, etc. Due to low interest, we are unlikely to inform the bartender about all the decisions related to the party, possibly only those that concern the bar. Knowing that there may be issues with the bartender, we will try to avoid them in advance to prevent disagreements from arising a day before the event. When working with people involved in organizing the party, you will be engaged in . stakeholder management Stakeholder management is a process that helps understand the needs and expectations of interested parties and build relationships with them. This will ultimately assist in hosting a successful party. How stakeholder management is assessed during the interview process? At interviews, this skill is assessed through the following questions: Describe a situation in which you had to work with a difficult stakeholder. How did you handle it? Share a situation in which you had to convince a stakeholder to collaborate on your project (provide feedback/resources, etc.). How do you communicate with stakeholders? Have you ever faced a situation in which your management denied you resources or the opportunity to work on a new project or change the strategy? How did you persuade them? How do you manage stakeholders' expectations?

Stakeholder Management 101 – The Simplest Explanation Ever

The Challenges of Decentralized Trading Platforms In the world of decentralized finance (DeFi), traders are often caught in a balancing act between user-friendliness and the sophisticated features that offer the best returns. On one side, traditional decentralized exchanges (DEXs) offer an alternative to centralized platforms, giving more control to users. However, the complexity of their interfaces can be daunting for many, especially newcomers. Traders are frequently met with cluttered dashboards, making the swift and intuitive execution of trades a challenging endeavor. Moreover, as users diversify their portfolios across various tokens and markets, keeping track of assets becomes an intricate task. The decentralized nature of these platforms, while ensuring security and transparency, can sometimes leave users grappling with scattered assets. Such fragmentation often leads to traders spending excessive time navigating the platform and less time making critical trading decisions. There's a clear demand in the market for an interface that seamlessly merges the power of decentralization with the simplicity of traditional trading platforms. Decentralized Finance: Navigating the Trade-Offs Between Sophistication and Simplicity remarked Berk Ozdogan, Head of Strategy at Dexalot. "Simple Swap has the potential to become the perfect conduit for the most capital-efficient liquidity to get to traders," As the DeFi sector grapples with the push and pull of advanced features and user-friendly interfaces, this sentiment captures the essence of a larger movement within the decentralized finance ecosystem. DeFi traders find themselves torn between two worlds. One offers the allure of advanced trading capabilities often seen in traditional financial markets, while the other promises a seamless and intuitive user experience. But what if there was a platform that married these two seemingly conflicting ideals? Dexalot: Pioneering the Future of Decentralized Trading Marrying DEX Simplicity with CEX Features Dexalot, an innovative decentralized exchange (DEX) functioning on an Avalanche Subnet, has unveiled its answer to this quandary with two groundbreaking features: SimpleSwap and SimpleView. Designed to elevate the trading experience, these features seamlessly merge the uncomplicated nature of a standard DEX with the advanced trading mechanisms of a centralized exchange (CEX). SimpleSwap, launching on September 19, replicates the familiarity of AMM atomic swaps predominant in the DeFi space but brings to the fore the advantages of a central limit order book (CLOB) exchange—tight spreads and unmatched pricing. Through this fusion, traders can effortlessly switch between tokens on a streamlined and clutter-free interface, enriching the existing order book model. Empowering Traders Across Platforms SimpleSwap's appeal extends beyond Dexalot's boundaries. The feature's compatibility with third-party aggregators means users aren’t confined to the Dexalot platform for their trading activities. This integration with various aggregators ensures that wherever users opt to trade, they can access the unparalleled onchain pricing that Dexalot champions for assets, including but not limited to WETH.e and BTC.b. A Bird’s Eye View of Portfolios Navigating a CLOB exchange can sometimes translate into a labyrinthine challenge for traders juggling assets across different markets. SimpleView is Dexalot's answer to this complexity. It offers traders a quick-glance account abstraction tool, streamlining portfolio management by providing a holistic snapshot of their assets. By resolving the tracking intricacies that traders face, SimpleView ensures that they can effortlessly discern their portfolio's value and composition. Endorsement and Growth Matthew Schmenk from Ava Labs lauds the endeavor, stating, "Dexalot's central limit order book architecture makes for some of the best swap pricing in all of blockchain and with SimpleSwap, Dexalot should win a lot of swap routes and volumes.” This assertion aligns with the platform's impressive growth metrics. Since its inception on the Avalanche Subnet, Dexalot has recorded over 17 million transactions and witnesses daily trading volumes reaching $5M. Spearheaded by a team of Wall Street veterans, the platform is positioned as a formidable player in the decentralized exchange arena. Their recent recognition, a significant incentive award from Avalanche’s Multiverse Fund, further underscores their rising prominence in the DeFi space. About Dexalot For those seeking the fusion of traditional centralized exchange dynamics with decentralized functionalities, Dexalot stands as a beacon. The Avalanche-driven Central Limit Order Book DEX fosters a transparent ecosystem where users can indulge in secure and efficient crypto trading, sans the challenges of slippage or custody risks. For more insights into their revolutionary approach to decentralized trading, visit . Dexalot : Vested Interest Disclosure This author is an independent contributor publishing via our . Be it through direct compensation, media partnerships, or networking, the author has a vested interest in the company/ies mentioned in this story. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR brand-as-author program

Dexalot's Dual Triumph: Elevating Decentralized Trading with SimpleSwap and SimpleView

El doble triunfo de Dexalot: elevar el comercio descentralizado con SimpleSwap y SimpleView

Le double triomphe de Dexalot : élever le trading décentralisé avec SimpleSwap et SimpleView

डेक्सलॉट की दोहरी विजय: सिंपल स्वैप और सिंपल व्यू के साथ विकेंद्रीकृत व्यापार को बढ़ाना

Dexalot の 2 つの勝利: SimpleSwap と SimpleView による分散型取引の向上

O duplo triunfo da Dexalot: elevando a negociação descentralizada com SimpleSwap e SimpleView

Chiến thắng kép của Dexalot: Nâng cao giao dịch phi tập trung với SimpleSwap và SimpleView

Dexalot 的双重胜利：通过 SimpleSwap 和 SimpleView 提升去中心化交易

Cryptography has been around long before modern computers and has been a great way to protect messages. When it comes to providing information while keeping it concealed from those who wish to use it for ill intentions, you need and codes to encrypt messages to keep them confidential. Back in the days of Rome and Julius Caesar, code was invented - a form of basic encryption and one of the earliest encryption algorithms in humanity’s recorded history - that would allow his messages of military significance to stay safe from prying eyes. This code was named after Julius himself and it was called the cipher. cryptography Caesar According to the Roman historian Suetonius, the cipher was used to shift three letters to create a new code to protect messages. For example, if you want to encrypt the word/letter A, you would shift three letters down the alphabet and translate that ‘A’ into the letter ‘D’ & you decrypt the letter by going three letters back into an A. Suetonius describes the encryption in one of his writings: "If he had anything confidential to say, he wrote it in cipher, that is, by so changing the order of the letters of the alphabet, that not a word could be made out. If anyone wishes to decipher these, and get at their meaning, he must substitute the fourth letter of the alphabet, namely D, for A, and so with the others." - Suetonius, Life of Julius Caesar 56 One of the great things about the Caesar cipher is how easy this form of encryption is to recreate with modern code. Even with basic , you can easily turn some text into a basic encrypted cipher using the following function: Python def encrypt(text,s):
    result = ""
 
    
    for i in range(len(text)):
        char = text[i]
 
        # Encrypt the uppercase characters or lowercase letters as determined by an if statement
        # before adding to the result variable
        if (char.isupper()):
            result += chr((ord(char) + s-65) % 26 + 65)
 
        
        else:
            result += chr((ord(char) + s - 97) % 26 + 97)
 
    return result Unfortunately, the Caesar cipher probably would not work very well in a modern context since it is pretty easily broken since there are only so many different combinations of letter shifting you can use and, eventually, the code can be broken with brute force attacks. This is something you can also easily program in Python: def crack(message):

for i in range(len(LETTERS)):
   translated = ''
   for s in message:
      if s in LETTERS:
         num = LETTERS.find(symbol)
         num = num - i
         if num < 0:
            num = num + len(LETTERS)
         translated = translated + LETTERS[num]
      else:
         translated = translated + s

print('Potential Hacked Messages #%s: %s' % (i, translated)) Even Caesar himself worked to combine the Caesar cipher with more complicated systems in order to make more complicated encryptions. That all being said, the Caesar cipher is a pretty important part of the history of cryptography and is one of the earliest recorded encryption algorithms used in a practical context.

The Caesar Cipher: One of the Earliest, and Simplest, Encryptions

As a frontend developer, I have been working on building collaborative apps, in which the realtime performance of  multiplayer features is especially important. It needs to synchronize the state of users in less than 100ms between two users. In this article, I would like to demonstrate how " " helped me to implement these multiplayer features within 2 hours. Furthermore, presencejs is totally open source, and also does well in . Throughout my experience using this library, I have been impressed by its power and capabilities. presencejs security, low-latency, and geo-distributed deployment Therefore, I have decided to write this blog to introduce this excellent forward-looking JavaScript library to you. is a JavaScript library that enables the creation of real-time multiplayer/ collaboration web applications that supporting WebTransport. Presencejs It provides many ready-made components like Cursor-Chat, Live-Cursor, Grouphug etc. Certainly, we can create more functional custom components using the basic functions and API of presencejs. Through the ready-made components, I created a nextjs real-time web application demo in minutes. Presencejs: https://github.com/yomorun/presencejs Demo: https://cursorchat-grouphug-demo.vercel.app/ How did I create this demo? For this demo, I used the Presencejs library to create a real-time multi-user collaborative web application.  I chose a simple but effective design for the demo. I opted for a clean and modern look with a subtle color scheme that wouldn't distract from the content. Presencejs provides several pre-built components such as Cursor Chat, Realtime Cursor, and Grouphug. I used these components along with some custom features to build this demo. Here's a brief overview of how I created it: First, I installed and imported the Presencejs library into my code. npm install @yomo/cursor-chat-react
npm install @yomo/group-hug-react import CursorChat from '@yomo/cursor-chat-react';
import GroupHug from '@yomo/group-hug-react'; Next, I used the components provided by Presencejs to build my application. For this demo, I used  Cursor-Chat, and Grouphug components. // other code

import CursorChat from '@yomo/cursor-chat-react';
import GroupHug from '@yomo/group-hug-react';


export default function Home(){
// other code

return(

// other code

<CursorChat />
<Grouphug />

// other code

)
} Then, I added some custom features . I got a public_key from and created a file .env in the main path. I entered the code below: AllegroCloud.io PUBLIC_KEY=**** And I saved this file, then ran the demo locally. Finally, I deployed my application online using Next.js so that others can access it. Overall, creating a real-time web application using Presencejs is straightforward. Presencejs provides many pre-built components that allow developers to quickly build their own applications. Additionally, Presencejs supports custom development, which allows advanced developers to create more complex features. I hope this demo inspires more developers to try using Presencejs to create their own real-time web applications. The special benefits of presencejs From my experience with it, presencejs has been particularly helpful to me in the following ways: The support to WebTransport makes presencejs show better performance than other collaboration js lib. Compatible with websocket Ready-made components and customized development. Geo-distributed architecture lets me build amazing and fast response web applications. Both serverless and self-hosting. Benefits in detail: Support for WebTransport:
Presencejs supports WebTransport, which is a newer real-time application protocol based on the QUIC protocol. It establishes reliable, secure, low-latency connections without requiring handshakes and negotiations like websocket. It also supports advanced features such as multiplexing and connection migration. This provides faster connection establishment speed, data transfer speed, and latency. Compatible with websocket:
Presencejs also supports websocket. When the user's browser doesn't support WebTransport, presencejs will replace the communication protocol with websocket. Ready-made components and customized development:
Presencejs provides ready-made components like grouphug, livecursor, and cursorchat, which allow real-time web applications. For advanced developers, the complete toolkit can be used to create custom components. Geo-distributed architecture backend:
Presencejs is a serverless architecture framework using the YoMo framework for real-time data processing. This provides faster response speed, stable performance, and secure service. Both serverless and self-hosting:
Presencejs supports self-hosting, which provides greater control over data and applications. Final Notes and Thoughts In conclusion, presencejs offers a variety of benefits that make it an excellent choice for developers looking to build real-time web applications. Its support for WebTransport and websocket protocols, ready-made components, customizable development, geo-distributed architecture, and serverless or self-hosting options provide developers with a versatile toolkit to create amazing applications. By adopting presencejs, developers can ensure their applications have faster response times, greater stability, and improved security. Furthermore, as an open-source product, presencejs will continue to improve and evolve in the coming years. Overall, presencejs is a forward-thinking product that can meet the real-time needs of the web today and in the future. As a developer experience personnel of AllegroCloud and a frontend developer, I am fully aware of the shortcomings of Presence. However, as an open-source product, Presence possesses a more robust vitality and a more transparent technological reserve. In the coming years, Presence will continue to be updated and iterated, providing even higher-quality services.

PresenceJS: The Simplest Way to Power Realtime Experience in My Collaborative Apps

This is by (source: ). Twitter Thread Compound248 12-01-2022 Dear Media, Do you want a simple description of HOW did what he did? @SBF_FTX Why does nobody seem capable of pinning Sam down? His SECRET is, when asked pointed questions, he switches to market-plumbing speak, hiding behind lingo. Let me help you understand SBF's moves. 🧵 👇 Anytime you hear or read "Alameda," replace with, "Sam's personal account." When Alameda borrows FTX customer money, that means "Sam borrows customer money": Alameda is 100% owned by Sam & a few friends. Alameda had no clients. "Alameda's capital" is Sam's, Caroline's, etc. 👇 Sam says he poorly "risk-managed" the FTX and Alameda relationship. Recall: Alameda=Sam. What transpired? • Alameda (Sam) Had Liquidity Issues • Alameda (Sam) Organized a Loan from FTX • To Paper the Loan, Alameda Posted Collateral to FTX • The Collateral Was Pretend Money 3) Alameda (Sam) Had Issues: Nobody has nailed down what happened: was Alameda *always* a fraud or did it suffer losses at some point and then get desperate (perhaps the Terra Luna implosion in the spring)? This is a question begging for an answer. I don't know, but... https://tenor.com/bhNAA.gif?embedable=true 4)...Sam claims he was no longer closely involved in Alameda (again, Alameda = Sam's personal capital). Sam claims Caroline & Team ran it independently (other than its venture investments). This claim gives Sam cover to state he doesn't know the details about Alameda's issues. 5) Alameda (Sam) Organized a Loan from FTX: At some point - time uncertain - Alameda (Sam) needed access to liquidity. It almost certainly had margin loans from 3rd parties being called (3rd parties like Gemini or Binance...maybe FTX?). To repay these, Alameda needed liquidity. 6) To Paper the Loan, Alameda Posted Collateral to FTX: FTX client assets were the liquidity that Alameda (Sam) needed to repay its other loans. To pretend this was OK, FTX needed to hold collateral from Alameda as security against the loan (in case Alameda (Sam) didn't repay). 7) When you borrow cash on margin, you generally have to post MORE collateral than you borrow. Ex: you might borrow against your Schwab account. Schwab holds your account's assets as protection against you defaulting on the loan. This lets you turn investments into liquidity. 8) Elon's margin loan is a prominent example: $TSLA Elon can borrow $1 for every $5 of TSLA stock he posts (giving him cash to do anything, like buy , without selling TSLA). $TWTR After borrowing from the facility, if TSLA stock falls below a certain threshold (say $1 to $3)... 9)...Elon needs to either add more collateral to the margin facility (post more ) or pay down the loan. $TSLA If he does neither, the lender can liquidate the it holds as collateral and repay the loan from the proceeds. $TSLA Now back to Alameda (Sam)... 10) Together, FTX & Alameda (Sam & Sam) developed a few shitcoins...err "tokens": the most relevant are and . $FTT $SRM Both FTX & Alameda received huge grants of and (I'm just going to use going forward). $FTT $SRM $FTT F&A (Sam) controlled the VAST majority of the issuance... 11)...and only a tiny portion of / traded. Alameda was the largest trader. If you own 95% of something and then manipulate the price of the other 5%, you can make your 95% look REALLY valuable - just keep the price of that 5% up and look how valuable your 95% becomes! $FTT $SRM https://tenor.com/va2h.gif?embedable=true Guess what Alameda (Sam) used as collateral for those margin loans we were talking about? and . $FTT $SRM And it doesn't appear that FTX required a big haircut on those. Remember that Elon can borrow $1 for every $5 of stock he posts? That's an 80% haircut. But... $TSLA 13)...it doesn't appear FTX required a substantial haircut on the that Alameda (Sam) posted. Ultimately, using these shitcoins...I mean tokens, as collateral, Alameda (Sam) "borrowed" $9-$10 billion from FTX. That money was, almost by definition, FTX customer money. $FTT 14) You might recall that Sam famously described tokens like these to and as "magic money in a box." It was recognized immediately as Sam describing a Ponzi. But most of us didn't realize *Sam* was issuing these magic tokens. @TheStalwart @tracyalloway http://youtube.com/watch?v=KZYqL79GDXU&t=1292s Sam may argue this is just how banks (and brokerages) work: they take deposits, they lend them out based on credit judgments to earn a spread, and - as long as depositors don't ask for deposits back en masse - all is perfectly fine. But let me tell you what banks don't do: 16) Banks do not: • Lend 70% of their deposits to one borrower • Have that borrower be the founder of the bank • Accept made-up "tokens" as collateral - the actual worst collateral ever conceived • Have almost all that collateral be just two (made up) assets 17) • Apply de minimis haircuts to collateral • Accept derivatives of the bank itself as collateral! is not random - it relates to FTX $FTT As said, Goldman Sachs should not take equity as collateral - it is circular risk. And definitely not pretend-GS equity. @matt_levine $GS 18) This Collateral Was Pretend Money Alameda (Sam) & FTX (also Sam) invented intrinsically worthless tokens, keeping almost all of it for themselves. They traded a tiny percentage, controlling the trading price. This manipulated the implied value of all of Sam's tokens... $FTT 19)...then used the resultant implied token value as collateral to extract ("borrow") customer funds from FTX. The bogus collateral was one giant identical (non-diversified) risk, funding related-party transactions. And FTX lied about doing it via misleading Terms of Service. 20) When Sam says, "he poorly risk-managed" it means, "I, FTX's CEO Sam, should not have allowed Alameda Sam to use pretend Sam-money as collateral to take real-$$ from Sam's customers." It's like in Dumb & Dumber when Lloyd spends all the found money, but replaced it with IOUs. https://tenor.com/buMGg.gif?embedable=true This insanity could have lasted longer, except Sam made one horrible mistake. At FTX's founding, Binance/ was a seed investor. As FTX evolved into a full-fledged Binance competitor, FTX reacquired Binance's seed stake using a mix of payments. One of those was... @cz_binance https://tenor.com/bONrD.gif?embedable=true 22)... ! $FTT Amazingly, the only big part of 's float that Sam did not control was controlled by his arch-f'ing-rival: CZ. $FTT When it became public that Alameda was relying heavily on as collateral, CZ understood his wasn't worth the magic paper it wasn't written on. $FTT $FTT 23) If CZ didn't know before, he knew then: all of Sam's prior "bailouts" were attempts to prevent Alameda *itself* from being liquidated - it was built on magic token money. And CZ was the biggest independent owner of the magic money. CZ knew there were zero natural buyers. $FTT 24) CZ held the keys to killing his loudest, most annoying competitor & he used them. Good on CZ - hopefully Binance itself is sound. We don't know what's next or where the $10B of customer $$ went. Perhaps Alameda lost it fair & square, perhaps it's stolen. Time MAY tell. -END The key question is, “who at FTX approved $10B of loans to Alameda (Sam)?” Sam says he didn’t understand the exposure. He was CEO. Who approved it? My “worlds colliding” dream is for to reply to my viral true crime thread. 👆 @elonmusk @SBF_FTX Like this to make my dream come true.😅 ...or Retweet. Feature image generated via prompt of ‘The Simplest Guide of What Happened With SBF That You Will Ever Come Across’ HackerNoon Stable Diffusion

The Simplest Guide of What Happened With SBF That You Will Ever Come Across

Technical Overview of the UniswapX Protocol: Architecture, Integration Methods, and Order Execution

Authors:
(1) Nora Schneider, Computer Science Department, ETH Zurich, Zurich, Switzerland (nschneide@student.ethz.ch);
(2) Shirin Goshtasbpour, Computer Science Department, ETH Zurich, Zurich, Switzerland and Swiss Data Science Center, Zurich, Switzerland (shirin.goshtasbpour@inf.ethz.ch);
(3) Fernando Perez-Cruz, Computer Science Department, ETH Zurich, Zurich, Switzerland and Swiss Data Science Center, Zurich, Switzerland (fernando.perezcruz@sdsc.ethz.ch). Table of Links Abstract and 1 Introduction 2 Background 2.1 Data Augmentation 2.2 Anchor Regression 3 Anchor Data Augmentation 3.1 Comparison to C-Mixup and 3.2 Preserving nonlinear data structure 3.3 Algorithm 4 Experiments and 4.1 Linear synthetic data 4.2 Housing nonlinear regression 4.3 In-distribution Generalization 4.4 Out-of-distribution Robustness 5 Conclusion, Broader Impact, and References A Additional information for Anchor Data Augmentation B Experiments 4 Experiments We experimentally investigate and compare the performance of ADA. First, we use ADA in an in-distribution setting for a linear regression problem (Section 4.1), in which we show that even in this case, ADA provides improved performance in the low data regime. Second, in Section 4.2, we apply ADA and C-Mixup to the California and Boston Housing datasets as we increase the number of training samples. In the last two subsections, we replicate the in-distribution generalization (Section 4.3) and the out-of-distribution Robustness (Section 4.4) from the C-Mixup paper [49]. In [49] the authors further assess a task generalization experiment. However, the corresponding code was not publicly provided, and a comparison could not be easily made. 4.1 Linear synthetic data Using synthetic linear data, we investigate if ADA can improve model performance in an overparameterized setting compared to C-Mixup, vanilla augmentation, or classical expected risk minimization (ERM). Additionally, we analyze the sensitivity of our approach to the choice of γ and the number of augmentations. Data: The generated data follows a standard linear structure Models and Comparisons: We investigate and compare the impact of ADA using two different models with varying complexity: a linear Ridge regression and a multilayer perceptron (MLP) with one hidden layer and 10 units with ReLU activation. Using an MLP with more hidden layers shows similar results (see Appendix B.1 for details). For the Ridge regression model, we increase the dataset by a factor of 10 by sampling from the respective augmentation methods and subsequently compute the regression estimators. In contrast, for the MLP, we implement the augmentation methods on a minibatch level. Specifically, we incorporate vanilla augmentation by adding Gaussian noise to each batch, apply C-Mixup after sampling from the beta distribution in each batch, and finally, apply ADA after sampling from the defined gamma values in each batch. In summary, even in the simplest of cases, in which we should not expect gains from ADA (or C-Mixup), these data augmentation strategies provide gains in performance when the number of training examples is not sufficient to achieve the error floor. This paper is available on arxiv under CC0 1.0 DEED license. Authors: (1) Nora Schneider, Computer Science Department, ETH Zurich, Zurich, Switzerland (nschneide@student.ethz.ch); (2) Shirin Goshtasbpour, Computer Science Department, ETH Zurich, Zurich, Switzerland and Swiss Data Science Center, Zurich, Switzerland (shirin.goshtasbpour@inf.ethz.ch); (3) Fernando Perez-Cruz, Computer Science Department, ETH Zurich, Zurich, Switzerland and Swiss Data Science Center, Zurich, Switzerland (fernando.perezcruz@sdsc.ethz.ch). Authors: Authors: (1) Nora Schneider, Computer Science Department, ETH Zurich, Zurich, Switzerland (nschneide@student.ethz.ch); (2) Shirin Goshtasbpour, Computer Science Department, ETH Zurich, Zurich, Switzerland and Swiss Data Science Center, Zurich, Switzerland (shirin.goshtasbpour@inf.ethz.ch); (3) Fernando Perez-Cruz, Computer Science Department, ETH Zurich, Zurich, Switzerland and Swiss Data Science Center, Zurich, Switzerland (fernando.perezcruz@sdsc.ethz.ch). Table of Links Abstract and 1 Introduction Abstract and 1 Introduction 2 Background 2.1 Data Augmentation 2.1 Data Augmentation 2.2 Anchor Regression 2.2 Anchor Regression 3 Anchor Data Augmentation 3 Anchor Data Augmentation 3.1 Comparison to C-Mixup and 3.2 Preserving nonlinear data structure 3.1 Comparison to C-Mixup and 3.2 Preserving nonlinear data structure 3.3 Algorithm 3.3 Algorithm 4 Experiments and 4.1 Linear synthetic data 4 Experiments and 4.1 Linear synthetic data 4.2 Housing nonlinear regression 4.2 Housing nonlinear regression 4.3 In-distribution Generalization 4.3 In-distribution Generalization 4.4 Out-of-distribution Robustness 4.4 Out-of-distribution Robustness 5 Conclusion, Broader Impact, and References 5 Conclusion, Broader Impact, and References A Additional information for Anchor Data Augmentation A Additional information for Anchor Data Augmentation B Experiments B Experiments 4 Experiments We experimentally investigate and compare the performance of ADA. First, we use ADA in an in-distribution setting for a linear regression problem (Section 4.1), in which we show that even in this case, ADA provides improved performance in the low data regime. Second, in Section 4.2, we apply ADA and C-Mixup to the California and Boston Housing datasets as we increase the number of training samples. In the last two subsections, we replicate the in-distribution generalization (Section 4.3) and the out-of-distribution Robustness (Section 4.4) from the C-Mixup paper [49]. In [49] the authors further assess a task generalization experiment. However, the corresponding code was not publicly provided, and a comparison could not be easily made. 4.1 Linear synthetic data Using synthetic linear data, we investigate if ADA can improve model performance in an overparameterized setting compared to C-Mixup, vanilla augmentation, or classical expected risk minimization (ERM). Additionally, we analyze the sensitivity of our approach to the choice of γ and the number of augmentations. Data : The generated data follows a standard linear structure Data Models and Comparisons: We investigate and compare the impact of ADA using two different models with varying complexity: a linear Ridge regression and a multilayer perceptron (MLP) with one hidden layer and 10 units with ReLU activation. Using an MLP with more hidden layers shows similar results (see Appendix B.1 for details). Models and Comparisons: For the Ridge regression model, we increase the dataset by a factor of 10 by sampling from the respective augmentation methods and subsequently compute the regression estimators. In contrast, for the MLP, we implement the augmentation methods on a minibatch level. Specifically, we incorporate vanilla augmentation by adding Gaussian noise to each batch, apply C-Mixup after sampling from the beta distribution in each batch, and finally, apply ADA after sampling from the defined gamma values in each batch. In summary, even in the simplest of cases, in which we should not expect gains from ADA (or C-Mixup), these data augmentation strategies provide gains in performance when the number of training examples is not sufficient to achieve the error floor. This paper is available on arxiv under CC0 1.0 DEED license. This paper is available on arxiv under CC0 1.0 DEED license. available on arxiv

Evaluating ADA: Experimental Results on Linear and Housing Datasets

As a Product Manager, you have great ideas! Ideas that could change the way people do things, ideas that could solve the world’s most pressing problems. And all you need to do now, is go ahead and build it! Let’s build an MVP (minimum viable product), sell the hell out of it (because the idea is super-disruptive in your mind) and then iterate. Soon to realize 6–8 months down the line that your product no longer has that level of adoption that you had expected, or that you now have to pivot to cater to the needs of your ‘revised’ audience because the initial market definition was too narrow. Product Managers are nothing but entrepreneurs, trying to launch their startup, pitching a business plan to internal stakeholders (your investors), gathering resources (creating a startup team), launching and selling to customers (marketing and launching your product). Thus, as we all know the fact that more than 80% of startups fail, the path to building a successful product should mimic the approach to launching a successful company. The Lean-product approach The Lean Startup approach discoursed by Eric Ries, has popularized the ‘fail fast, iterate often’ notion. This involves evaluating the problem the customer has with a prototype and then iterating with measured data from the feedback loop, using minimum resources. A core component of lean-startup methodology is the build-measure-learn feedback loop. I take this methodology and apply it to defining, validating and iterating to achieve the right product-market fit and create a rock-solid product strategy. Problem definition Innovative ideas lead to great solutions, however, without a deep understanding of the problem space, you are at a risk of getting ahead of yourself and building capabilities which do not receive customer traction. Defining your problem statement involves understanding of the problem space, the sense of urgency to solve the problem, the existing solutions in the market that have attempted to solve the problem all in the context of your target audience. “If I were given one hour to save the planet, I would spend 59 minutes defining the problem and one minute resolving it,” Albert Einstein said. One example of the many ways of framing a problem statement is by defining: What is the problem?
Who is facing this problem?
How often?
Why do you need to solve it? In your initial level surveys or focus group interviews, these are a few statements that could be derived: “I am a salesperson, constantly on the road and am always struggling with managing and submitting tiny paper receipts for reimbursement as I keep losing them.” Using our above framework we have our problem statement e.g. “Business travelers or salespersons (who) need a way to capture and manage their travel expenses (what) because they are always on the road (how often). We need a solution to make this process less-time consuming and less-cumbersome (why).” This, by the way, is the problem as identified by DePasquale, founder of Outtask that made an online tool, Cliqbook, that allowed workers to book and manage their online travel and which in 2006, was acquired by Concur. Target Audience In the problem definition we have identified who is facing the problem you are trying to solve. This is where you identify the core audience who will be using your product. Your user as well as buyer personas. It is important to be honest about sizing your market here. This is not your $2B TAM pitch to investors. Be realistic and as specific as possible. Core Value Proposition A value-proposition is not simply a list of your benefits. It explains what benefit you provide for who and how you do it uniquely well. It should be a single statement articulating what is the value promised to the customer? There are tons of frameworks to define and state your value prop in a concise way. The simplest, perhaps is the template from Steve Blank, “We help [X] to [Y] by [Z]” Some great examples are: Dollar Shave Club*: “A Great Shave for a Few Bucks a Month”*
Stripe*: “Scale faster by building your business on Stripe’s payment processing platform.”*
Uber*: “Everyone’s private Driver”* Once you have your value prop defined, it is extremely important to continuously evaluate and test it with potential customers, even before you start building your MVP. Why is your product offering unique? This is probably the most important question you need to ask while determining the customer’s ‘willingness to pay’ for your product. Why should the customer go for your product vs the competitors? This becomes even more important when you are trying to displace a largely incumbent or crowded space such as enterprise productivity tools or online food delivery. Also, remember, you do not need to differentiate on a fancy feature or capability. Sometimes the simplest of things such as a clean design and user experience is what customers may need the most. Figuring out what matters to your customers the most and then choosing to differentiate on that aspect should be the approach. There is a reason why Zoom has completely disrupted the video conferencing market with their focus on creating virtual experiences when it comes to digitizing the workspace. The current space consisted of a stack of products, some wider and some narrower and some part of a larger ecosystem (Skype and Cisco Webex). Zoom clearly understood the need to converge video, web and mobile. Zoom’s offering that integrated audio, web conferencing and mobile integration was a simple, straightforward solution to what customers needed. Also, their willingness to work with most platforms and devices coupled with their all-inclusive fremium model was different from how all the other players went to market. Product quality, technology, user experience, price, go-to-market model and customer-service are just a handful of factors that you can think of and choose to base your differentiation upon. Metrics Ries’s lean framework follows a build, measure, learn loop. However, defining what to measure and how to evaluate the success for your product needs to be done as early as possible. You should be able to answer the question “How is the product doing?” at any point in time. And defining the response in clear KPIs (Key Performance Indicators) helps you evaluate the progress in a very objective way. The AARM method defined by Lewis Lin is a good framework to pick your metrics in each of the areas of acquisition, activation, retention and monetization. However, you need to go beyond frameworks, pick the appropriate metrics and customize them for your product and growth stage. Metrics creation and measurement is a highly iterative process and hence you constantly need to set KPI goals, evaluate and track these goals, and create new ones as your product grows. Apart from coming up with metrics for areas of acquisition, engagement and monetization, what needs to be agreed upon from an early stage is the ‘North-Star Metric’ that is going to drive most product decisions. This topic needs a separate article so watch out for another blog from me, deep diving into defining and evaluating metrics. Example Uber is a classic example where there was instant product market fit. Uber quickly realized their problem statement was “Limited, inconvenient access to taxis and transportation options in urban areas”. To solve this problem, Uber used GPS-enabled mobile apps to match drivers with riders, providing a reliable, real-time way to find and book a ride. Uber built their technical architecture  focused on real-time data processing and location-based services, which supported their rapid request-response model. Geolocation Services: Built using Google Maps API and Mapbox for precise location tracking and route optimization.
Dispatch System: Microservices handling real-time dispatching of drivers based on location and demand, with APIs for matching, pricing, and tracking.
Data Layer: Uses Cassandra for high-availability, fault-tolerant storage and MySQL for relational data.
Queueing: RabbitMQ or Kafka for asynchronous communication between services, handling surge pricing, availability, and ride requests. Uber’s use of microservices and a modular data architecture helps ensure that their systems remain responsive and scalable in real-time. Conclusion In conclusion, a successful product identifies and tests the product-market fit hypothesis from the get go and throughout the process of building the MVP. The Lean Startup message sums it up well. “What differentiates the success stories from the failures is that the successful entrepreneurs had the foresight, the ability, and the tools to discover which parts of their plans were working brilliantly and which were misguided, and adapt their strategies accordingly”. As a Product Manager, you have great ideas! Ideas that could change the way people do things, ideas that could solve the world’s most pressing problems. And all you need to do now, is go ahead and build it! Let’s build an MVP (minimum viable product), sell the hell out of it (because the idea is super-disruptive in your mind) and then iterate. Soon to realize 6–8 months down the line that your product no longer has that level of adoption that you had expected, or that you now have to pivot to cater to the needs of your ‘revised’ audience because the initial market definition was too narrow. Product Managers are nothing but entrepreneurs, trying to launch their startup, pitching a business plan to internal stakeholders (your investors), gathering resources (creating a startup team), launching and selling to customers (marketing and launching your product). Thus, as we all know the fact that more than 80% of startups fail, the path to building a successful product should mimic the approach to launching a successful company. The Lean-product approach The Lean Startup approach discoursed by Eric Ries, has popularized the ‘fail fast, iterate often’ notion. This involves evaluating the problem the customer has with a prototype and then iterating with measured data from the feedback loop, using minimum resources. A core component of lean-startup methodology is the build-measure-learn feedback loop. Lean Startup I take this methodology and apply it to defining, validating and iterating to achieve the right product-market fit and create a rock-solid product strategy. Problem definition Innovative ideas lead to great solutions, however, without a deep understanding of the problem space, you are at a risk of getting ahead of yourself and building capabilities which do not receive customer traction. Defining your problem statement involves understanding of the problem space, the sense of urgency to solve the problem, the existing solutions in the market that have attempted to solve the problem all in the context of your target audience. “If I were given one hour to save the planet, I would spend 59 minutes defining the problem and one minute resolving it,” Albert Einstein said. “If I were given one hour to save the planet, I would spend 59 minutes defining the problem and one minute resolving it,” Albert Einstein said. “If I were given one hour to save the planet, I would spend 59 minutes defining the problem and one minute resolving it,” Albert Einstein said. One example of the many ways of framing a problem statement is by defining: What is the problem? Who is facing this problem? How often? Why do you need to solve it? What is the problem? Who is facing this problem? How often? Why do you need to solve it? In your initial level surveys or focus group interviews, these are a few statements that could be derived: “I am a salesperson, constantly on the road and am always struggling with managing and submitting tiny paper receipts for reimbursement as I keep losing them.” “I am a salesperson, constantly on the road and am always struggling with managing and submitting tiny paper receipts for reimbursement as I keep losing them.” Using our above framework we have our problem statement e.g. “Business travelers or salespersons (who) need a way to capture and manage their travel expenses (what) because they are always on the road (how often). We need a solution to make this process less-time consuming and less-cumbersome (why).” “Business travelers or salespersons (who) need a way to capture and manage their travel expenses (what) because they are always on the road (how often). We need a solution to make this process less-time consuming and less-cumbersome (why).” This, by the way, is the problem as identified by DePasquale, founder of Outtask that made an online tool, Cliqbook, that allowed workers to book and manage their online travel and which in 2006, was acquired by Concur. Target Audience In the problem definition we have identified who is facing the problem you are trying to solve. This is where you identify the core audience who will be using your product. Your user as well as buyer personas. It is important to be honest about sizing your market here. This is not your $2B TAM pitch to investors. Be realistic and as specific as possible. Core Value Proposition A value-proposition is not simply a list of your benefits. It explains what benefit you provide for who and how you do it uniquely well. It should be a single statement articulating what is the value promised to the customer? There are tons of frameworks to define and state your value prop in a concise way. The simplest, perhaps is the template from Steve Blank , “ We help [X] to [Y] by [Z]” Steve Blank We help [X] to [Y] by [Z]” Some great examples are: Dollar Shave Club*: “A Great Shave for a Few Bucks a Month”* Stripe*: “Scale faster by building your business on Stripe’s payment processing platform.”* Uber*: “Everyone’s private Driver”* Dollar Shave Club *: “A Great Shave for a Few Bucks a Month”* Dollar Shave Club Dollar Shave Club Stripe *: “Scale faster by building your business on Stripe’s payment processing platform.”* Stripe Stripe Uber *: “Everyone’s private Driver”* Uber Uber Once you have your value prop defined, it is extremely important to continuously evaluate and test it with potential customers, even before you start building your MVP. Why is your product offering unique? This is probably the most important question you need to ask while determining the customer’s ‘willingness to pay’ for your product. Why should the customer go for your product vs the competitors? This becomes even more important when you are trying to displace a largely incumbent or crowded space such as enterprise productivity tools or online food delivery. Also, remember, you do not need to differentiate on a fancy feature or capability. Sometimes the simplest of things such as a clean design and user experience is what customers may need the most. Figuring out what matters to your customers the most and then choosing to differentiate on that aspect should be the approach. There is a reason why Zoom has completely disrupted the video conferencing market with their focus on creating virtual experiences when it comes to digitizing the workspace. The current space consisted of a stack of products, some wider and some narrower and some part of a larger ecosystem (Skype and Cisco Webex). Zoom clearly understood the need to converge video, web and mobile. Zoom’s offering that integrated audio, web conferencing and mobile integration was a simple, straightforward solution to what customers needed. Also, their willingness to work with most platforms and devices coupled with their all-inclusive fremium model was different from how all the other players went to market. Product quality, technology, user experience, price, go-to-market model and customer-service are just a handful of factors that you can think of and choose to base your differentiation upon. Metrics Ries’s lean framework follows a build, measure, learn loop. However, defining what to measure and how to evaluate the success for your product needs to be done as early as possible. You should be able to answer the question “How is the product doing?” at any point in time. And defining the response in clear KPIs (Key Performance Indicators) helps you evaluate the progress in a very objective way. The AARM method defined by Lewis Lin is a good framework to pick your metrics in each of the areas of acquisition, activation, retention and monetization. However, you need to go beyond frameworks, pick the appropriate metrics and customize them for your product and growth stage. Metrics creation and measurement is a highly iterative process and hence you constantly need to set KPI goals, evaluate and track these goals, and create new ones as your product grows. Apart from coming up with metrics for areas of acquisition, engagement and monetization, what needs to be agreed upon from an early stage is the ‘North-Star Metric’ that is going to drive most product decisions. This topic needs a separate article so watch out for another blog from me, deep diving into defining and evaluating metrics. AARM method Example Uber is a classic example where there was instant product market fit. Uber quickly realized their problem statement was “Limited, inconvenient access to taxis and transportation options in urban areas”. To solve this problem, Uber used GPS-enabled mobile apps to match drivers with riders, providing a reliable, real-time way to find and book a ride. Uber built their technical architecture  focused on real-time data processing and location-based services, which supported their rapid request-response model. Geolocation Services: Built using Google Maps API and Mapbox for precise location tracking and route optimization. Dispatch System: Microservices handling real-time dispatching of drivers based on location and demand, with APIs for matching, pricing, and tracking. Data Layer: Uses Cassandra for high-availability, fault-tolerant storage and MySQL for relational data. Queueing: RabbitMQ or Kafka for asynchronous communication between services, handling surge pricing, availability, and ride requests. Geolocation Services : Built using Google Maps API and Mapbox for precise location tracking and route optimization. Geolocation Services Dispatch System : Microservices handling real-time dispatching of drivers based on location and demand, with APIs for matching, pricing, and tracking. Dispatch System Data Layer : Uses Cassandra for high-availability, fault-tolerant storage and MySQL for relational data. Data Layer Queueing : RabbitMQ or Kafka for asynchronous communication between services, handling surge pricing, availability, and ride requests. Queueing Uber’s use of microservices and a modular data architecture helps ensure that their systems remain responsive and scalable in real-time. Conclusion In conclusion, a successful product identifies and tests the product-market fit hypothesis from the get go and throughout the process of building the MVP. The Lean Startup message sums it up well. “What differentiates the success stories from the failures is that the successful entrepreneurs had the foresight, the ability, and the tools to discover which parts of their plans were working brilliantly and which were misguided, and adapt their strategies accordingly”. “What differentiates the success stories from the failures is that the successful entrepreneurs had the foresight, the ability, and the tools to discover which parts of their plans were working brilliantly and which were misguided, and adapt their strategies accordingly”. “What differentiates the success stories from the failures is that the successful entrepreneurs had the foresight, the ability, and the tools to discover which parts of their plans were working brilliantly and which were misguided, and adapt their strategies accordingly”.

Achieving Product-Market Fit: How the Startups Did It

For a long time, smaller businesses and entrepreneurs have been held back by the rigid constraints of the traditional banking sector, which imposes burdensome requirements on those seeking capital. With DeFi, small businesses can benefit from a more efficient and streamlined approach to financial transactions, with seamless payments, simpler lending and borrowing processes and much easier access to all-important capital. The innovations found in DeFi boost access while eliminating cumbersome approval processes and high transaction fees, and can potentially become a catalyst for much faster business growth. Let’s take a look at how some of the most innovative DeFi protocols can shake up the small business world. Aave: Generate yield on your crypto holdings Aave is one of the best known DeFi protocols of all, and in many ways it can be thought of as a decentralized bank, as it provides an array of services that can be utilized by small businesses to streamline their financial operations. Its core functions include interest generation, where businesses can deposit cryptocurrency to earn interest. It also acts as a source of funding, giving users the option to borrow a range of crypto assets through collateralized loans. The platform is notable for its flexibility, with features like collateral swapping ensuring businesses can utilize a variety of crypto assets. For small businesses that already accept crypto payments, Aave provides a way for them to unlock the value of those holdings without having to swap them all for fiat. Businesses can deposit a range of crypto assets into Aave’s lending pools, with the potential interest adjusting automatically based on demand. If more people want to borrow a certain kind of asset, the rate increases to encourage more lenders to deposit, creating opportunities for businesses to generate substantial yield on previously idle crypto assets. Centrifuge: Obtain credit fast using physical assets as collateral Finding funding can be a major challenge for small businesses, as there are very few options available in traditional finance, besides wealth investors and conventional banks. Centrifuge gives businesses another option – the ability to tokenize real-world assets and use them as collateral to obtain credit in an instant at very competitive rates. To borrow money from Centrifuge, businesses can use its associated decentralized application Tinlake, which is a marketplace for tokenized RWAs. It provides businesses with a streamline way to tokenize assets, such as invoices that have not yet been settled, or real estate owned by the business, so these can be used as collateral to obtain funding. With Tinlake, investors can also trade these RWAs over its decentralized marketplace, and businesses can even participate as small investors, depositing crypto into its liquidity pools for other businesses to borrow against. The great thing about Centrifuge is that its tokenization process is fast and efficient, meaning businesses can obtain capital in a fraction of the time it would take to secure a loan from a bank. It’s all about fast access to liquid funds, enabling entrepreneurs to obtain the capital they need to stock up on their inventories or invest in key parts of their business at just the right time. Fuse.io: Grow your business globally with scalable crypto payments The Fuse Network can be thought of as a business-to-business payments infrastructure network that supports the development of blockchain applications that can provide more streamlined and transparent services to users. The platform achieves blazing-fast transaction speeds thanks to its delegated proof-of-stake architecture, which enhances decentralization and security. Payment transactions are offloaded to a layer-2 network to ensure rapid execution. The business model is similar in many ways to Visa and Mastercard, only its focused on Web3 payments, enabling businesses to create new applications that support crypto payments, or add this support to existing apps. There are two key elements of Fuse that businesses need to know about, beginning with the Fuse SDK, which provides the tools to integrate crypto payments into existing client apps. It provides one of the simplest and fastest ways for businesses to upgrade legacy apps, saving on development costs. Next is Fuse Charge, which can be thought of as a kind of merchant bank for Web3 businesses, providing access to various crypto and fiat-related payment services. Using Charge, businesses have a way to process payments, create invoices and manage cross-border transactions. It paves the way for companies to integrate crypto payments alongside traditional fiat and manage everything under one hood, without worrying about complex installations and high development costs. What’s more, it’s a truly borderless platform, enabling companies to transact across different countries with complete autonomy in a compliant way. Businesses benefit from more certainty too, with a flat fee of just 0.5% on every transaction, crypto or fiat, so they understand the cost of doing business. As a non-custodial platform, businesses always retain complete control over their funds. Celo: Explore new business models powered by micro-transactions A mobile-friendly crypto payments platform, Celo is aiming to make DeFi accessible to everyone, so businesses have a way to tap into markets where many people remain unbanked. Perhaps the biggest advantage of Celo is the way it allows businesses to access new markets, with its focus on mobile wallets and low-cost transactions giving them a way to interact with the millions of people in the world that don’t own a bank account. In this way, Celo opens the door to new customer segments for businesses that are willing to try and tap into such audiences. The other aspect of Celo is its support for frictionless micro-transactions. Businesses can take advantage of this to create new business models around micropayments, such as extremely low-cost pay-per-use services and content monetization, which have traditionally been cost-prohibitive beyond a certain level. In support of this, Celo is focused on borderless efficiency, with its low-fees and rapid settlement times dramatically reducing the hassle of international payments. This can benefit businesses in many ways, such as helping them to create international supply chains to save on costs, hire remote workers or tap into new customers in foreign markets. In addition, Celo aims to open the door to sustainable microfinance. Businesses can generate new revenue models by using their capital to provide small-scale loans to entrepreneurs and underserved communities. It’s about more than just generating interest, and such activities can fuel economic development and create new opportunities for growth by establishing links with up-and-coming markets. MakerDAO: Deal in crypto payments without volatility Many businesses reject crypto payments due to the volatility of digital assets, but doing so means missing out on what is likely to one of the fastest-growing financial markets of our times, and a key enabler of borderless payments. MakerDAO provides businesses with a solution through DAI, an algorithmic stablecoin that’s designed to maintain a stable, one-to-one peg with the U.S. dollar. The advantage of DAI is that companies can deal in a range of cryptocurrencies, and quickly trade their holdings for the stablecoin to eliminate the risks associated with crypto’s volatility. DAI remains stable because it relies on complex algorithms that ensure it retains its U.S. dollar peg no matter what the market conditions are in the crypto industry. Key to this is MakerDAO’s lending protocol, which enables users to obtain loans paid out in DAI by depositing other cryptocurrencies as collateral. The loans are overcollateralized, which means users have to deposit more money than they take out. This enables MakerDAO to protect the value of DAI when the tokens backing it, such as ETH and Wrapped Bitcoin or wBTC, experience high volatility. The major benefit of DAI is that it enables businesses to transact using almost any cryptocurrency. Businesses no longer have to immediately convert their crypto funds into fiat and pay excessive transaction fees to do so. Instead, they can immediately swap their crypto for DAI at negligible costs, to avoid holding funds that could be subject to wild price swings. In addition, the wide acceptance of DAI means that businesses have a way to transact across borders with low, predictable costs. DeFi will define small business success Running a small business is a hard thing to do and it has become progressively more difficult due to the restrictions of the traditional banking industry. In 2022, banks reached a new, all-time low in terms of lending activity, with tightened credit restrictions making it harder than ever for small businesses to obtain reasonably priced credit. Businesses need access to credit. In a 2020 study, the U.S. Small Business Administration found that more than 80% of business failures occurred due to cash flow issues. By tapping into the world of DeFi, businesses more opportunities to access the funds they need to maintain their cash flow, even when they’re waiting on customers to pay invoices. At the same time, they can benefit from streamlined payments with lower costs and expand their reach into new, global markets. Don’t forget to like and share the story! Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR For a long time, smaller businesses and entrepreneurs have been held back by the rigid constraints of the traditional banking sector, which imposes burdensome requirements on those seeking capital. With DeFi, small businesses can benefit from a more efficient and streamlined approach to financial transactions, with seamless payments, simpler lending and borrowing processes and much easier access to all-important capital. The innovations found in DeFi boost access while eliminating cumbersome approval processes and high transaction fees, and can potentially become a catalyst for much faster business growth. Let’s take a look at how some of the most innovative DeFi protocols can shake up the small business world. Aave: Generate yield on your crypto holdings Aave is one of the best known DeFi protocols of all, and in many ways it can be thought of as a decentralized bank, as it provides an array of services that can be utilized by small businesses to streamline their financial operations. Aave Aave Its core functions include interest generation, where businesses can deposit cryptocurrency to earn interest. It also acts as a source of funding, giving users the option to borrow a range of crypto assets through collateralized loans. The platform is notable for its flexibility, with features like collateral swapping ensuring businesses can utilize a variety of crypto assets. For small businesses that already accept crypto payments, Aave provides a way for them to unlock the value of those holdings without having to swap them all for fiat. Businesses can deposit a range of crypto assets into Aave’s lending pools, with the potential interest adjusting automatically based on demand. If more people want to borrow a certain kind of asset, the rate increases to encourage more lenders to deposit, creating opportunities for businesses to generate substantial yield on previously idle crypto assets. Centrifuge: Obtain credit fast using physical assets as collateral Finding funding can be a major challenge for small businesses, as there are very few options available in traditional finance, besides wealth investors and conventional banks. Centrifuge gives businesses another option – the ability to tokenize real-world assets and use them as collateral to obtain credit in an instant at very competitive rates. Centrifuge Centrifuge To borrow money from Centrifuge, businesses can use its associated decentralized application Tinlake, which is a marketplace for tokenized RWAs. It provides businesses with a streamline way to tokenize assets, such as invoices that have not yet been settled, or real estate owned by the business, so these can be used as collateral to obtain funding. With Tinlake, investors can also trade these RWAs over its decentralized marketplace, and businesses can even participate as small investors, depositing crypto into its liquidity pools for other businesses to borrow against. The great thing about Centrifuge is that its tokenization process is fast and efficient, meaning businesses can obtain capital in a fraction of the time it would take to secure a loan from a bank. It’s all about fast access to liquid funds, enabling entrepreneurs to obtain the capital they need to stock up on their inventories or invest in key parts of their business at just the right time. Fuse.io: Grow your business globally with scalable crypto payments The Fuse Network can be thought of as a business-to-business payments infrastructure network that supports the development of blockchain applications that can provide more streamlined and transparent services to users. Fuse Network Fuse Network The platform achieves blazing-fast transaction speeds thanks to its delegated proof-of-stake architecture, which enhances decentralization and security. Payment transactions are offloaded to a layer-2 network to ensure rapid execution. The business model is similar in many ways to Visa and Mastercard, only its focused on Web3 payments, enabling businesses to create new applications that support crypto payments, or add this support to existing apps. There are two key elements of Fuse that businesses need to know about, beginning with the Fuse SDK, which provides the tools to integrate crypto payments into existing client apps. It provides one of the simplest and fastest ways for businesses to upgrade legacy apps, saving on development costs. Next is Fuse Charge, which can be thought of as a kind of merchant bank for Web3 businesses, providing access to various crypto and fiat-related payment services. Using Charge, businesses have a way to process payments, create invoices and manage cross-border transactions. It paves the way for companies to integrate crypto payments alongside traditional fiat and manage everything under one hood, without worrying about complex installations and high development costs. What’s more, it’s a truly borderless platform, enabling companies to transact across different countries with complete autonomy in a compliant way. Businesses benefit from more certainty too, with a flat fee of just 0.5% on every transaction, crypto or fiat, so they understand the cost of doing business. As a non-custodial platform, businesses always retain complete control over their funds. Celo: Explore new business models powered by micro-transactions A mobile-friendly crypto payments platform, Celo is aiming to make DeFi accessible to everyone, so businesses have a way to tap into markets where many people remain unbanked. Celo Celo Perhaps the biggest advantage of Celo is the way it allows businesses to access new markets, with its focus on mobile wallets and low-cost transactions giving them a way to interact with the millions of people in the world that don’t own a bank account. In this way, Celo opens the door to new customer segments for businesses that are willing to try and tap into such audiences. The other aspect of Celo is its support for frictionless micro-transactions. Businesses can take advantage of this to create new business models around micropayments, such as extremely low-cost pay-per-use services and content monetization, which have traditionally been cost-prohibitive beyond a certain level. In support of this, Celo is focused on borderless efficiency, with its low-fees and rapid settlement times dramatically reducing the hassle of international payments. This can benefit businesses in many ways, such as helping them to create international supply chains to save on costs, hire remote workers or tap into new customers in foreign markets. In addition, Celo aims to open the door to sustainable microfinance. Businesses can generate new revenue models by using their capital to provide small-scale loans to entrepreneurs and underserved communities. It’s about more than just generating interest, and such activities can fuel economic development and create new opportunities for growth by establishing links with up-and-coming markets. MakerDAO: Deal in crypto payments without volatility Many businesses reject crypto payments due to the volatility of digital assets, but doing so means missing out on what is likely to one of the fastest-growing financial markets of our times, and a key enabler of borderless payments. MakerDAO provides businesses with a solution through DAI, an algorithmic stablecoin that’s designed to maintain a stable, one-to-one peg with the U.S. dollar. The advantage of DAI is that companies can deal in a range of cryptocurrencies, and quickly trade their holdings for the stablecoin to eliminate the risks associated with crypto’s volatility. MakerDAO MakerDAO DAI remains stable because it relies on complex algorithms that ensure it retains its U.S. dollar peg no matter what the market conditions are in the crypto industry. Key to this is MakerDAO’s lending protocol, which enables users to obtain loans paid out in DAI by depositing other cryptocurrencies as collateral. The loans are overcollateralized, which means users have to deposit more money than they take out. This enables MakerDAO to protect the value of DAI when the tokens backing it, such as ETH and Wrapped Bitcoin or wBTC, experience high volatility. The major benefit of DAI is that it enables businesses to transact using almost any cryptocurrency. Businesses no longer have to immediately convert their crypto funds into fiat and pay excessive transaction fees to do so. Instead, they can immediately swap their crypto for DAI at negligible costs, to avoid holding funds that could be subject to wild price swings. In addition, the wide acceptance of DAI means that businesses have a way to transact across borders with low, predictable costs. DeFi will define small business success Running a small business is a hard thing to do and it has become progressively more difficult due to the restrictions of the traditional banking industry. In 2022, banks reached a new, all-time low in terms of lending activity, with tightened credit restrictions making it harder than ever for small businesses to obtain reasonably priced credit. all-time low all-time low Businesses need access to credit. In a 2020 study, the U.S. Small Business Administration found that more than 80% of business failures occurred due to cash flow issues. 80% of business failures 80% of business failures By tapping into the world of DeFi, businesses more opportunities to access the funds they need to maintain their cash flow, even when they’re waiting on customers to pay invoices. At the same time, they can benefit from streamlined payments with lower costs and expand their reach into new, global markets. Don’t forget to like and share the story! Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program . HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR Vested Interest Disclosure: business blogging program business blogging program

How DeFi Is Creating New Avenues For Small Business Success

Kunjams DeFi ukax Machaq Avenidas Jisk’a Empresanakan Éxito ukar uñstayaski

Cómo las finanzas descentralizadas están creando nuevas vías para el éxito de las pequeñas empresas

DeFi कैसे छोटे व्यवसायों की सफलता के लिए नए रास्ते बना रहा है

Hogyan teremt a DeFi új utakat a kisvállalkozások sikeréhez?

DeFi が中小企業の成功に新たな道を切り開く

DeFi ກໍາລັງສ້າງເສັ້ນທາງໃຫມ່ສໍາລັບຄວາມສໍາເລັດຂອງທຸລະກິດຂະຫນາດນ້ອຍແນວໃດ

कसरी DeFi सानो व्यापार सफलता को लागी नयाँ अवसरहरु सिर्जना गर्दैछ

Jak DeFi tworzy nowe ścieżki do sukcesu małych firm

Jinsi DeFi Inatengeneza Njia Mpya za Mafanikio ya Biashara Ndogo

کس طرح DeFi چھوٹے کاروبار کی کامیابی کے لیے نئی راہیں پیدا کر رہا ہے۔

DeFi đang tạo ra những con đường mới cho sự thành công của doanh nghiệp nhỏ như thế nào

I-DeFi iyenza njani iiAvenues eziNtsha zeMpumelelo yamaShishini amaNcinci

Authors:
(1) Shih-Tang Su, University of Michigan, Ann Arbor (shihtang@umich.edu);
(2) Vijay G. Subramanian, University of Michigan, Ann Arbor and (vgsubram@umich.edu);
(3) Grant Schoenebeck, University of Michigan, Ann Arbor (schoeneb@umich.edu). Table of Links Abstract and 1. Introduction 2. Problem Formulation 2.1 Model of Binary-Outcome Experiments in Two-Phase Trials 3 Binary-outcome Experiments in Two-phase Trials and 3.1 Experiments with screenings 3.2 Assumptions and induced strategies 3.3 Constraints given by phase-II experiments 3.4 Persuasion ratio and the optimal signaling structure 3.5 Comparison with classical Bayesian persuasion strategies 4 Binary-outcome Experiments in Multi-phase trials and 4.1 Model of binary-outcome experiments in multi-phase trials 4.2 Determined versus sender-designed experiments 4.3 Multi-phase model and classical Bayesian persuasion and References 3 Binary-outcome Experiments in Two-phase Trials In this section the sender’s optimization problem presented in (2) Section 2.1, is solved starting with the simplest non-trivial case. There are only two phases in the trial studied here, and from this we will develop more insight into how different types of experiments (determined versus sender-designed) influence the optimal signaling strategy of the sender. To be more specific, we will analyze how two determined experiments (in phase II) and one sender-designed experiment (in phase I) will impact the sender’s optimal signaling strategy. Before we present the general case, we discuss a subset class of two-phase trials that are similar to single-phase trials. In this class of two-phase trials, in one of the phase-II experiments, called a trivial experiment, the outcome distribution is independent of the true state. Trivial experiments [2], also called (Blackwell) non-informative experiments in some literature, are frequently used as benchmarks to compare the agents’ expected utility change under different signaling schemes/mechanisms, e.g., [22,20,21]. This two-phase model with a trivial experiment tries to capture real-world problems with one actual (and costly) experiment, e.g., clinical trials, venture capital investments, or space missions. Since the experiment is costly, a screening procedure is provided to decide whether it is worth conducting the experiment. We will then analyze the optimal signaling strategy in the general scenario, where both experiments in phase II are non-trivial. 3.1 Experiments with screenings We start by analyzing the sender’s optimal strategy (signaling structure) in a simple scenario where there is one non-trivial experiment conducted in phase II. The sender’s authority on choosing the probability pair (p1, p2) controls the screening process. To avoid any ambiguity, we first define what a trivial experiment is. When a trivial experiment (in phase II) is conducted, the posterior belief of the state stays the same as the interim belief derived in (1). When there exists a trivial experiment in the two phase-II trial options, then Lemma 1 states that the sender and the receiver’s expected utility under the optimal signaling strategy is the same as in the (single-phase) classical Bayesian persuasion problem. Lemma 1. When the state space is binary, both sender and receiver’s expected utilities are the same in the following two Bayesian persuasion schemes under each scheme’s optimal signaling strategy: Bayesian persuasion in a single-phase trial,


Bayesian persuasion in a two-phase trial with a sender-designed phase-I experiment and a trivial experiment in phase II. In the single-trial classical Bayesian persuasion setting, the optimal signaling strategy only mixes the two possible states in one outcome (e.g., when the prosecutor claims the suspect is guilty). On the other outcome, the sender reveals the true state with probability one (e.g., when the prosecutor says the suspect is innocent). When there is a trivial experiment in phase II, the other experiment (supposing that it will be conducted at outcome ωB) will be rendered defunct by the sender’s choice of experiments in phase I. This phenomenon occurs because the sender can always choose to reveal the true state when the non-trivial experiment is to be conducted, i.e., by setting P(θ1|EB) = 1 or P(θ2|EB) = 1; and the classical Bayesian persuasion strategy can be replicated. In essence, having a trivial experiment in the phase-II trial does not constrain the sender. This paper is available on arxiv under CC 4.0 license. Authors: (1) Shih-Tang Su, University of Michigan, Ann Arbor (shihtang@umich.edu); (2) Vijay G. Subramanian, University of Michigan, Ann Arbor and (vgsubram@umich.edu); (3) Grant Schoenebeck, University of Michigan, Ann Arbor (schoeneb@umich.edu). Authors: Authors: (1) Shih-Tang Su, University of Michigan, Ann Arbor (shihtang@umich.edu); (2) Vijay G. Subramanian, University of Michigan, Ann Arbor and (vgsubram@umich.edu); (3) Grant Schoenebeck, University of Michigan, Ann Arbor (schoeneb@umich.edu). Table of Links Abstract and 1. Introduction Abstract and 1. Introduction 2. Problem Formulation 2. Problem Formulation 2.1 Model of Binary-Outcome Experiments in Two-Phase Trials 2.1 Model of Binary-Outcome Experiments in Two-Phase Trials 3 Binary-outcome Experiments in Two-phase Trials and 3.1 Experiments with screenings 3 Binary-outcome Experiments in Two-phase Trials and 3.1 Experiments with screenings 3.2 Assumptions and induced strategies 3.2 Assumptions and induced strategies 3.3 Constraints given by phase-II experiments 3.3 Constraints given by phase-II experiments 3.4 Persuasion ratio and the optimal signaling structure 3.4 Persuasion ratio and the optimal signaling structure 3.5 Comparison with classical Bayesian persuasion strategies 3.5 Comparison with classical Bayesian persuasion strategies 4 Binary-outcome Experiments in Multi-phase trials and 4.1 Model of binary-outcome experiments in multi-phase trials 4 Binary-outcome Experiments in Multi-phase trials and 4.1 Model of binary-outcome experiments in multi-phase trials 4.2 Determined versus sender-designed experiments 4.2 Determined versus sender-designed experiments 4.3 Multi-phase model and classical Bayesian persuasion and References 4.3 Multi-phase model and classical Bayesian persuasion and References 3 Binary-outcome Experiments in Two-phase Trials In this section the sender’s optimization problem presented in (2) Section 2.1, is solved starting with the simplest non-trivial case. There are only two phases in the trial studied here, and from this we will develop more insight into how different types of experiments (determined versus sender-designed) influence the optimal signaling strategy of the sender. To be more specific, we will analyze how two determined experiments (in phase II) and one sender-designed experiment (in phase I) will impact the sender’s optimal signaling strategy. Before we present the general case, we discuss a subset class of two-phase trials that are similar to single-phase trials. In this class of two-phase trials, in one of the phase-II experiments, called a trivial experiment, the outcome distribution is independent of the true state. Trivial experiments [2], also called (Blackwell) non-informative experiments in some literature, are frequently used as benchmarks to compare the agents’ expected utility change under different signaling schemes/mechanisms, e.g., [22,20,21]. This two-phase model with a trivial experiment tries to capture real-world problems with one actual (and costly) experiment, e.g., clinical trials, venture capital investments, or space missions. Since the experiment is costly, a screening procedure is provided to decide whether it is worth conducting the experiment. We will then analyze the optimal signaling strategy in the general scenario, where both experiments in phase II are non-trivial. 3.1 Experiments with screenings We start by analyzing the sender’s optimal strategy (signaling structure) in a simple scenario where there is one non-trivial experiment conducted in phase II. The sender’s authority on choosing the probability pair (p1, p2) controls the screening process. To avoid any ambiguity, we first define what a trivial experiment is. When a trivial experiment (in phase II) is conducted, the posterior belief of the state stays the same as the interim belief derived in (1). When there exists a trivial experiment in the two phase-II trial options, then Lemma 1 states that the sender and the receiver’s expected utility under the optimal signaling strategy is the same as in the (single-phase) classical Bayesian persuasion problem. Lemma 1. When the state space is binary, both sender and receiver’s expected utilities are the same in the following two Bayesian persuasion schemes under each scheme’s optimal signaling strategy: Lemma 1. When the state space is binary, both sender and receiver’s expected utilities are the same in the following two Bayesian persuasion schemes under each scheme’s optimal signaling strategy: Bayesian persuasion in a single-phase trial, Bayesian persuasion in a two-phase trial with a sender-designed phase-I experiment and a trivial experiment in phase II. Bayesian persuasion in a single-phase trial, Bayesian persuasion in a single-phase trial, Bayesian persuasion in a single-phase trial, Bayesian persuasion in a two-phase trial with a sender-designed phase-I experiment and a trivial experiment in phase II. Bayesian persuasion in a two-phase trial with a sender-designed phase-I experiment and a trivial experiment in phase II. Bayesian persuasion in a two-phase trial with a sender-designed phase-I experiment and a trivial experiment in phase II. In the single-trial classical Bayesian persuasion setting, the optimal signaling strategy only mixes the two possible states in one outcome (e.g., when the prosecutor claims the suspect is guilty). On the other outcome, the sender reveals the true state with probability one (e.g., when the prosecutor says the suspect is innocent). When there is a trivial experiment in phase II, the other experiment (supposing that it will be conducted at outcome ωB) will be rendered defunct by the sender’s choice of experiments in phase I. This phenomenon occurs because the sender can always choose to reveal the true state when the non-trivial experiment is to be conducted, i.e., by setting P(θ1|EB) = 1 or P(θ2|EB) = 1; and the classical Bayesian persuasion strategy can be replicated. In essence, having a trivial experiment in the phase-II trial does not constrain the sender. This paper is available on arxiv under CC 4.0 license. This paper is available on arxiv under CC 4.0 license. available on arxiv

Analyzing Optimal Signaling with Binary-outcome Experiments in Two-phase Trials

Ontleed optimale sein met binêre uitkoms-eksperimente in twee-fase proewe

Análisis de la señalización óptima con experimentos de resultados binarios en ensayos de dos fases

تجزیه و تحلیل سیگنال دهی بهینه با آزمایش های باینری نتیجه در آزمایشات دو فازی

Analiza optimalnog signaliziranja s eksperimentima s binarnim ishodom u dvofaznim ispitivanjima

2段階試験におけるバイナリ結果実験による最適なシグナル伝達の分析

ოპტიმალური სიგნალიზაციის ანალიზი ორფაზიან ცდებში ორფაზიანი ექსპერიმენტებით

Екі фазалық сынақтардағы екілік нәтиже эксперименттерімен оңтайлы сигналды талдау

Go sekaseka Matshwao a Mabotse ka Diteko tša dipoelo tša Binary ka Ditekong tša Megato ye Mebedi

Анализ оптимальной сигнализации с помощью экспериментов с бинарным результатом в двухфазных испытаниях

Gusesengura Ibimenyetso Byiza hamwe na Binary-ibisubizo Ubushakashatsi Mubice bibiri

Анализа оптималне сигнализације са експериментима са бинарним исходом у двофазним испитивањима

دو فیز ٹرائلز میں بائنری نتائج کے تجربات کے ساتھ بہترین سگنلنگ کا تجزیہ کرنا

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