More on Technology
Shalitha Suranga
3 years ago
The Top 5 Mathematical Concepts Every Programmer Needs to Know
Using math to write efficient code in any language
Programmers design, build, test, and maintain software. Employ cases and personal preferences determine the programming languages we use throughout development. Mobile app developers use JavaScript or Dart. Some programmers design performance-first software in C/C++.
A generic source code includes language-specific grammar, pre-implemented function calls, mathematical operators, and control statements. Some mathematical principles assist us enhance our programming and problem-solving skills.
We all use basic mathematical concepts like formulas and relational operators (aka comparison operators) in programming in our daily lives. Beyond these mathematical syntaxes, we'll see discrete math topics. This narrative explains key math topics programmers must know. Master these ideas to produce clean and efficient software code.
Expressions in mathematics and built-in mathematical functions
A source code can only contain a mathematical algorithm or prebuilt API functions. We develop source code between these two ends. If you create code to fetch JSON data from a RESTful service, you'll invoke an HTTP client and won't conduct any math. If you write a function to compute the circle's area, you conduct the math there.
When your source code gets more mathematical, you'll need to use mathematical functions. Every programming language has a math module and syntactical operators. Good programmers always consider code readability, so we should learn to write readable mathematical expressions.
Linux utilizes clear math expressions.
Inbuilt max and min functions can minimize verbose if statements.
How can we compute the number of pages needed to display known data? In such instances, the ceil function is often utilized.
import math as m
results = 102
items_per_page = 10
pages = m.ceil(results / items_per_page)
print(pages)Learn to write clear, concise math expressions.
Combinatorics in Algorithm Design
Combinatorics theory counts, selects, and arranges numbers or objects. First, consider these programming-related questions. Four-digit PIN security? what options exist? What if the PIN has a prefix? How to locate all decimal number pairs?
Combinatorics questions. Software engineering jobs often require counting items. Combinatorics counts elements without counting them one by one or through other verbose approaches, therefore it enables us to offer minimum and efficient solutions to real-world situations. Combinatorics helps us make reliable decision tests without missing edge cases. Write a program to see if three inputs form a triangle. This is a question I commonly ask in software engineering interviews.
Graph theory is a subfield of combinatorics. Graph theory is used in computerized road maps and social media apps.
Logarithms and Geometry Understanding
Geometry studies shapes, angles, and sizes. Cartesian geometry involves representing geometric objects in multidimensional planes. Geometry is useful for programming. Cartesian geometry is useful for vector graphics, game development, and low-level computer graphics. We can simply work with 2D and 3D arrays as plane axes.
GetWindowRect is a Windows GUI SDK geometric object.
High-level GUI SDKs and libraries use geometric notions like coordinates, dimensions, and forms, therefore knowing geometry speeds up work with computer graphics APIs.
How does exponentiation's inverse function work? Logarithm is exponentiation's inverse function. Logarithm helps programmers find efficient algorithms and solve calculations. Writing efficient code involves finding algorithms with logarithmic temporal complexity. Programmers prefer binary search (O(log n)) over linear search (O(n)). Git source specifies O(log n):
Logarithms aid with programming math. Metas Watchman uses a logarithmic utility function to find the next power of two.
Employing Mathematical Data Structures
Programmers must know data structures to develop clean, efficient code. Stack, queue, and hashmap are computer science basics. Sets and graphs are discrete arithmetic data structures. Most computer languages include a set structure to hold distinct data entries. In most computer languages, graphs can be represented using neighboring lists or objects.
Using sets as deduped lists is powerful because set implementations allow iterators. Instead of a list (or array), store WebSocket connections in a set.
Most interviewers ask graph theory questions, yet current software engineers don't practice algorithms. Graph theory challenges become obligatory in IT firm interviews.
Recognizing Applications of Recursion
A function in programming isolates input(s) and output(s) (s). Programming functions may have originated from mathematical function theories. Programming and math functions are different but similar. Both function types accept input and return value.
Recursion involves calling the same function inside another function. In its implementation, you'll call the Fibonacci sequence. Recursion solves divide-and-conquer software engineering difficulties and avoids code repetition. I recently built the following recursive Dart code to render a Flutter multi-depth expanding list UI:
Recursion is not the natural linear way to solve problems, hence thinking recursively is difficult. Everything becomes clear when a mathematical function definition includes a base case and recursive call.
Conclusion
Every codebase uses arithmetic operators, relational operators, and expressions. To build mathematical expressions, we typically employ log, ceil, floor, min, max, etc. Combinatorics, geometry, data structures, and recursion help implement algorithms. Unless you operate in a pure mathematical domain, you may not use calculus, limits, and other complex math in daily programming (i.e., a game engine). These principles are fundamental for daily programming activities.
Master the above math fundamentals to build clean, efficient code.
Asha Barbaschow
3 years ago
Apple WWDC 2022 Announcements
WWDC 2022 began early Tuesday morning. WWDC brought a ton of new features (which went for just shy of two hours).
With so many announcements, we thought we'd compile them. And now...
WWDC?
WWDC is Apple's developer conference. This includes iOS, macOS, watchOS, and iPadOS (all of its iPads). It's where Apple announces new features for developers to use. It's also where Apple previews new software.
Virtual WWDC runs June 6-10. You can rewatch the stream on Apple's website.
WWDC 2022 news:
Completely everything. Really. iOS 16 first.
iOS 16.
iOS 16 is a major iPhone update. iOS 16 adds the ability to customize the Lock Screen's color/theme. And widgets. It also organizes notifications and pairs Lock Screen with Focus themes. Edit or recall recently sent messages, recover recently deleted messages, and mark conversations as unread. Apple gives us yet another reason to stay in its walled garden with iMessage.
New iOS includes family sharing. Parents can set up a child's account with parental controls to restrict apps, movies, books, and music. iOS 16 lets large families and friend pods share iCloud photos. Up to six people can contribute photos to a separate iCloud library.
Live Text is getting creepier. Users can interact with text in any video frame. Touch and hold an image's subject to remove it from its background and place it in apps like messages. Dictation offers a new on-device voice-and-touch experience. Siri can run app shortcuts without setup in iOS 16. Apple also unveiled a new iOS 16 feature to help people break up with abusive partners who track their locations or read their messages. Safety Check.
Apple Pay Later allows iPhone users to buy products and pay for them later. iOS 16 pushes Mail. Users can schedule emails and cancel delivery before it reaches a recipient's inbox (be quick!). Mail now detects if you forgot an attachment, as Gmail has for years. iOS 16's Maps app gets "Multi-Stop Routing," .
Apple News also gets an iOS 16 update. Apple News adds My Sports. With iOS 16, the Apple Watch's Fitness app is also coming to iOS and the iPhone, using motion-sensing tech to track metrics and performance (as long as an athlete is wearing or carrying the device on their person).
iOS 16 includes accessibility updates like Door Detection.
watchOS9
Many of Apple's software updates are designed to take advantage of the larger screens in recent models, but they also improve health and fitness tracking.
The most obvious reason to upgrade watchOS every year is to get new watch faces from Apple. WatchOS 9 will add four new faces.
Runners' workout metrics improve.
Apple quickly realized that fitness tracking would be the Apple Watch's main feature, even though it's been the killer app for wearables since their debut. For watchOS 9, the Apple Watch will use its accelerometer and gyroscope to track a runner's form, stride length, and ground contact time. It also introduces the ability to specify heart rate zones, distance, and time intervals, with vibrating haptic feedback and voice alerts.
The Apple Watch's Fitness app is coming to iOS and the iPhone, using the smartphone's motion-sensing tech to track metrics and performance (as long as an athlete is wearing or carrying the device on their person).
We'll get sleep tracking, medication reminders, and drug interaction alerts. Your watch can create calendar events. A new Week view shows what meetings or responsibilities stand between you and the weekend.
iPadOS16
WWDC 2022 introduced iPad updates. iPadOS 16 is similar to iOS for the iPhone, but has features for larger screens and tablet accessories. The software update gives it many iPhone-like features.
iPadOS 16's Home app, like iOS 16, will have a new design language. iPad users who want to blame it on the rain finally have a Weather app. iPadOS 16 will have iCloud's Shared Photo Library, Live Text and Visual Look Up upgrades, and FaceTime Handoff, so you can switch between devices during a call.
Apple highlighted iPadOS 16's multitasking at WWDC 2022. iPad's Stage Manager sounds like a community theater app. It's a powerful multitasking tool for tablets and brings them closer to emulating laptops. Apple's iPadOS 16 supports multi-user collaboration. You can share content from Files, Keynote, Numbers, Pages, Notes, Reminders, Safari, and other third-party apps in Apple Messages.
M2-chip
WWDC 2022 revealed Apple's M2 chip. Apple has started the next generation of Apple Silicon for the Mac with M2. Apple says this device improves M1's performance.
M2's second-generation 5nm chip has 25% more transistors than M1's. 100GB/s memory bandwidth (50 per cent more than M1). M2 has 24GB of unified memory, up from 16GB but less than some ultraportable PCs' 32GB. The M2 chip has 10% better multi-core CPU performance than the M2, and it's nearly twice as fast as the latest 10-core PC laptop chip at the same power level (CPU performance is 18 per cent greater than M1).
New MacBooks
Apple introduced the M2-powered MacBook Air. Apple's entry-level laptop has a larger display, a new processor, new colors, and a notch.
M2 also powers the 13-inch MacBook Pro. The 13-inch MacBook Pro has 24GB of unified memory and 50% more memory bandwidth. New MacBook Pro batteries last 20 hours. As I type on the 2021 MacBook Pro, I can only imagine how much power the M2 will add.
macOS 13.0 (or, macOS Ventura)
macOS Ventura will take full advantage of M2 with new features like Stage Manager and Continuity Camera and Handoff for FaceTime. Safari, Mail, Messages, Spotlight, and more get updates in macOS Ventura.
Apple hasn't run out of California landmarks to name its OS after yet. macOS 13 will be called Ventura when it's released in a few months, but it's more than a name change and new wallpapers.
Stage Manager organizes windows
Stage Manager is a new macOS tool that organizes open windows and applications so they're still visible while focusing on a specific task. The main app sits in the middle of the desktop, while other apps and documents are organized and piled up to the side.
Improved Searching
Spotlight is one of macOS's least appreciated features, but with Ventura, it's becoming even more useful. Live Text lets you extract text from Spotlight results without leaving the window, including images from the photo library and the web.
Mail lets you schedule or unsend emails.
We've all sent an email we regret, whether it contained regrettable words or was sent at the wrong time. In macOS Ventura, Mail users can cancel or reschedule a message after sending it. Mail will now intelligently determine if a person was forgotten from a CC list or if a promised attachment wasn't included. Procrastinators can set a reminder to read a message later.
Safari adds tab sharing and password passkeys
Apple is updating Safari to make it more user-friendly... mostly. Users can share a group of tabs with friends or family, a useful feature when researching a topic with too many tabs. Passkeys will replace passwords in Safari's next version. Instead of entering random gibberish when creating a new account, macOS users can use TouchID to create an on-device passkey. Using an iPhone's camera and a QR system, Passkey syncs and works across all Apple devices and Windows computers.
Continuity adds Facetime device switching and iPhone webcam.
With macOS Ventura, iPhone users can transfer a FaceTime call from their phone to their desktop or laptop using Handoff, or vice versa if they started a call at their desk and need to continue it elsewhere. Apple finally admits its laptop and monitor webcams aren't the best. Continuity makes the iPhone a webcam. Apple demonstrated a feature where the wide-angle lens could provide a live stream of the desk below, while the standard zoom lens could focus on the speaker's face. New iPhone laptop mounts are coming.
System Preferences
System Preferences is Now System Settings and Looks Like iOS
Ventura's System Preferences has been renamed System Settings and is much more similar in appearance to iOS and iPadOS. As the iPhone and iPad are gateway devices into Apple's hardware ecosystem, new Mac users should find it easier to adjust.
This post is a summary. Read full article here
Amelia Winger-Bearskin
3 years ago
Reasons Why AI-Generated Images Remind Me of Nightmares
AI images are like funhouse mirrors.
Google's AI Blog introduced the puppy-slug in the summer of 2015.
Puppy-slug isn't a single image or character. "Puppy-slug" refers to Google's DeepDream's unsettling psychedelia. This tool uses convolutional neural networks to train models to recognize dataset entities. If researchers feed the model millions of dog pictures, the network will learn to recognize a dog.
DeepDream used neural networks to analyze and classify image data as well as generate its own images. DeepDream's early examples were created by training a convolutional network on dog images and asking it to add "dog-ness" to other images. The models analyzed images to find dog-like pixels and modified surrounding pixels to highlight them.
Puppy-slugs and other DeepDream images are ugly. Even when they don't trigger my trypophobia, they give me vertigo when my mind tries to reconcile familiar features and forms in unnatural, physically impossible arrangements. I feel like I've been poisoned by a forbidden mushroom or a noxious toad. I'm a Lovecraft character going mad from extradimensional exposure. They're gross!
Is this really how AIs see the world? This is possibly an even more unsettling topic that DeepDream raises than the blatant abjection of the images.
When these photographs originally circulated online, many friends were startled and scandalized. People imagined a computer's imagination would be literal, accurate, and boring. We didn't expect vivid hallucinations and organic-looking formations.
DeepDream's images didn't really show the machines' imaginations, at least not in the way that scared some people. DeepDream displays data visualizations. DeepDream reveals the "black box" of convolutional network training.
Some of these images look scary because the models don't "know" anything, at least not in the way we do.
These images are the result of advanced algorithms and calculators that compare pixel values. They can spot and reproduce trends from training data, but can't interpret it. If so, they'd know dogs have two eyes and one face per head. If machines can think creatively, they're keeping it quiet.
You could be forgiven for thinking otherwise, given OpenAI's Dall-impressive E's results. From a technological perspective, it's incredible.
Arthur C. Clarke once said, "Any sufficiently advanced technology is indistinguishable from magic." Dall-magic E's requires a lot of math, computer science, processing power, and research. OpenAI did a great job, and we should applaud them.
Dall-E and similar tools match words and phrases to image data to train generative models. Matching text to images requires sorting and defining the images. Untold millions of low-wage data entry workers, content creators optimizing images for SEO, and anyone who has used a Captcha to access a website make these decisions. These people could live and die without receiving credit for their work, even though the project wouldn't exist without them.
This technique produces images that are less like paintings and more like mirrors that reflect our own beliefs and ideals back at us, albeit via a very complex prism. Due to the limitations and biases that these models portray, we must exercise caution when viewing these images.
The issue was succinctly articulated by artist Mimi Onuoha in her piece "On Algorithmic Violence":
As we continue to see the rise of algorithms being used for civic, social, and cultural decision-making, it becomes that much more important that we name the reality that we are seeing. Not because it is exceptional, but because it is ubiquitous. Not because it creates new inequities, but because it has the power to cloak and amplify existing ones. Not because it is on the horizon, but because it is already here.
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The woman
3 years ago
I received a $2k bribe to replace another developer in an interview
I can't believe they’d even think it works!
Developers are usually interviewed before being hired, right? Every organization wants candidates who meet their needs. But they also want to avoid fraud.
There are cheaters in every field. Only two come to mind for the hiring process:
Lying on a resume.
Cheating on an online test.
Recently, I observed another one. One of my coworkers invited me to replace another developer during an online interview! I was astonished, but it’s not new.
The specifics
My ex-colleague recently texted me. No one from your former office will ever approach you after a year unless they need something.
Which was the case. My coworker said his wife needed help as a programmer. I was glad someone asked for my help, but I'm still a junior programmer.
Then he informed me his wife was selected for a fantastic job interview. He said he could help her with the online test, but he needed someone to help with the online interview.
Okay, I guess. Preparing for an online interview is beneficial. But then he said she didn't need to be ready. She needed someone to take her place.
I told him it wouldn't work. Every remote online interview I've ever seen required an open camera.
What followed surprised me. She'd ask to turn off the camera, he said.
I asked why.
He told me if an applicant is unwell, the interviewer may consider an off-camera interview. His wife will say she's sick and prefers no camera.
The plan left me speechless. I declined politely. He insisted and promised $2k if she got the job.
I felt insulted and told him if he persisted, I'd inform his office. I was furious. Later, I apologized and told him to stop.
I'm not sure what they did after that
I'm not sure if they found someone or listened to me. They probably didn't. How would she do the job if she even got it?
It's an internship, he said. With great pay, though. What should an intern do?
I suggested she do the interview alone. Even if she failed, she'd gain confidence and valuable experience.
Conclusion
Many interviewees cheat. My profession is vital to me, thus I'd rather improve my abilities and apply honestly. It's part of my identity.
Am I truthful? Most professionals are not. They fabricate their CVs. Often.
When you support interview cheating, you encourage more cheating! When someone cheats, another qualified candidate may not obtain the job.
One day, that could be you or me.
Sanjay Priyadarshi
3 years ago
Meet a Programmer Who Turned Down Microsoft's $10,000,000,000 Acquisition Offer
Failures inspire young developers
Jason citron created many products.
These products flopped.
Microsoft offered $10 billion for one of these products.
He rejected the offer since he was so confident in his success.
Let’s find out how he built a product that is currently valued at $15 billion.
Early in his youth, Jason began learning to code.
Jason's father taught him programming and IT.
His father wanted to help him earn money when he needed it.
Jason created video games and websites in high school.
Jason realized early on that his IT and programming skills could make him money.
Jason's parents misjudged his aptitude for programming.
Jason frequented online programming communities.
He looked for web developers. He created websites for those people.
His parents suspected Jason sold drugs online. When he said he used programming to make money, they were shocked.
They helped him set up a PayPal account.
Florida higher education to study video game creation
Jason never attended an expensive university.
He studied game design in Florida.
“Higher Education is an interesting part of society… When I work with people, the school they went to never comes up… only thing that matters is what can you do…At the end of the day, the beauty of silicon valley is that if you have a great idea and you can bring it to the life, you can convince a total stranger to give you money and join your project… This notion that you have to go to a great school didn’t end up being a thing for me.”
Jason's life was altered by Steve Jobs' keynote address.
After graduating, Jason joined an incubator.
Jason created a video-dating site first.
Bad idea.
Nobody wanted to use it when it was released, so they shut it down.
He made a multiplayer game.
It was released on Bebo. 10,000 people played it.
When Steve Jobs unveiled the Apple app store, he stopped playing.
The introduction of the app store resembled that of a new gaming console.
Jason's life altered after Steve Jobs' 2008 address.
“Whenever a new video game console is launched, that’s the opportunity for a new video game studio to get started, it’s because there aren’t too many games available…When a new PlayStation comes out, since it’s a new system, there’s only a handful of titles available… If you can be a launch title you can get a lot of distribution.”
Apple's app store provided a chance to start a video game company.
They released an app after 5 months of work.
Aurora Feint is the game.
Jason believed 1000 players in a week would be wonderful. A thousand players joined in the first hour.
Over time, Aurora Feints' game didn't gain traction. They don't make enough money to keep playing.
They could only make enough for one month.
Instead of buying video games, buy technology
Jason saw that they established a leaderboard, chat rooms, and multiplayer capabilities and believed other developers would want to use these.
They opted to sell the prior game's technology.
OpenFeint.
Assisting other game developers
They had no money in the bank to create everything needed to make the technology user-friendly.
Jason and Daniel designed a website saying:
“If you’re making a video game and want to have a drop in multiplayer support, you can use our system”
TechCrunch covered their website launch, and they gained a few hundred mailing list subscribers.
They raised seed funding with the mailing list.
Nearly all iPhone game developers started adopting the Open Feint logo.
“It was pretty wild… It was really like a whole social platform for people to play with their friends.”
What kind of a business model was it?
OpenFeint originally planned to make the software free for all games. As the game gained popularity, they demanded payment.
They later concluded it wasn't a good business concept.
It became free eventually.
Acquired for $104 million
Open Feint's users and employees grew tremendously.
GREE bought OpenFeint for $104 million in April 2011.
GREE initially committed to helping Jason and his team build a fantastic company.
Three or four months after the acquisition, Jason recognized they had a different vision.
He quit.
Jason's Original Vision for the iPad
Jason focused on distribution in 2012 to help businesses stand out.
The iPad market and user base were growing tremendously.
Jason said the iPad may replace mobile gadgets.
iPad gamers behaved differently than mobile gamers.
People sat longer and experienced more using an iPad.
“The idea I had was what if we built a gaming business that was more like traditional video games but played on tablets as opposed to some kind of mobile game that I’ve been doing before.”
Unexpected insight after researching the video game industry
Jason learned from studying the gaming industry that long-standing companies had advantages beyond a single release.
Previously, long-standing video game firms had their own distribution system. This distribution strategy could buffer time between successful titles.
Sony, Microsoft, and Valve all have gaming consoles and online stores.
So he built a distribution system.
He created a group chat app for gamers.
He envisioned a team-based multiplayer game with text and voice interaction.
His objective was to develop a communication network, release more games, and start a game distribution business.
Remaking the video game League of Legends
Jason and his crew reimagined a League of Legends game mode for 12-inch glass.
They adapted the game for tablets.
League of Legends was PC-only.
So they rebuilt it.
They overhauled the game and included native mobile experiences to stand out.
Hammer and Chisel was the company's name.
18 people worked on the game.
The game was funded. The game took 2.5 years to make.
Was the game a success?
July 2014 marked the game's release. The team's hopes were dashed.
Critics initially praised the game.
Initial installation was widespread.
The game failed.
As time passed, the team realized iPad gaming wouldn't increase much and mobile would win.
Jason was given a fresh idea by Stan Vishnevskiy.
Stan Vishnevskiy was a corporate engineer.
He told Jason about his plan to design a communication app without a game.
This concept seeded modern strife.
“The insight that he really had was to put a couple of dots together… we’re seeing our customers communicating around our own game with all these different apps and also ourselves when we’re playing on PC… We should solve that problem directly rather than needing to build a new game…we should start making it on PC.”
So began Discord.
Online socializing with pals was the newest trend.
Jason grew up playing video games with his friends.
He never played outside.
Jason had many great moments playing video games with his closest buddy, wife, and brother.
Discord was about providing a location for you and your group to speak and hang out.
Like a private cafe, bedroom, or living room.
Discord was developed for you and your friends on computers and phones.
You can quickly call your buddies during a game to conduct a conference call. Put the call on speaker and talk while playing.
Discord wanted to give every player a unique experience. Because coordinating across apps was a headache.
The entire team started concentrating on Discord.
Jason decided Hammer and Chisel would focus on their chat app.
Jason didn't want to make a video game.
How Discord attracted the appropriate attention
During the first five months, the entire team worked on the game and got feedback from friends.
This ensures product improvement. As a result, some teammates' buddies started utilizing Discord.
The team knew it would become something, but the result was buggy. App occasionally crashed.
Jason persuaded a gamer friend to write on Reddit about the software.
New people would find Discord. Why not?
Reddit users discovered Discord and 50 started using it frequently.
Discord was launched.
Rejecting the $10 billion acquisition proposal
Discord has increased in recent years.
It sends billions of messages.
Discord's users aren't tracked. They're privacy-focused.
Purchase offer
Covid boosted Discord's user base.
Weekly, billions of messages were transmitted.
Microsoft offered $10 billion for Discord in 2021.
Jason sold Open Feint for $104m in 2011.
This time, he believed in the product so much that he rejected Microsoft's offer.
“I was talking to some people in the team about which way we could go… The good thing was that most of the team wanted to continue building.”
Last time, Discord was valued at $15 billion.
Discord raised money on March 12, 2022.
The $15 billion corporation raised $500 million in 2021.
Vitalik
3 years ago
Fairness alternatives to selling below market clearing prices (or community sentiment, or fun)
When a seller has a limited supply of an item in high (or uncertain and possibly high) demand, they frequently set a price far below what "the market will bear." As a result, the item sells out quickly, with lucky buyers being those who tried to buy first. This has happened in the Ethereum ecosystem, particularly with NFT sales and token sales/ICOs. But this phenomenon is much older; concerts and restaurants frequently make similar choices, resulting in fast sell-outs or long lines.
Why do sellers do this? Economists have long wondered. A seller should sell at the market-clearing price if the amount buyers are willing to buy exactly equals the amount the seller has to sell. If the seller is unsure of the market-clearing price, they should sell at auction and let the market decide. So, if you want to sell something below market value, don't do it. It will hurt your sales and it will hurt your customers. The competitions created by non-price-based allocation mechanisms can sometimes have negative externalities that harm third parties, as we will see.
However, the prevalence of below-market-clearing pricing suggests that sellers do it for good reason. And indeed, as decades of research into this topic has shown, there often are. So, is it possible to achieve the same goals with less unfairness, inefficiency, and harm?
Selling at below market-clearing prices has large inefficiencies and negative externalities
An item that is sold at market value or at an auction allows someone who really wants it to pay the high price or bid high in the auction. So, if a seller sells an item below market value, some people will get it and others won't. But the mechanism deciding who gets the item isn't random, and it's not always well correlated with participant desire. It's not always about being the fastest at clicking buttons. Sometimes it means waking up at 2 a.m. (but 11 p.m. or even 2 p.m. elsewhere). Sometimes it's just a "auction by other means" that's more chaotic, less efficient, and has far more negative externalities.
There are many examples of this in the Ethereum ecosystem. Let's start with the 2017 ICO craze. For example, an ICO project would set the price of the token and a hard maximum for how many tokens they are willing to sell, and the sale would start automatically at some point in time. The sale ends when the cap is reached.
So what? In practice, these sales often ended in 30 seconds or less. Everyone would start sending transactions in as soon as (or just before) the sale started, offering higher and higher fees to encourage miners to include their transaction first. Instead of the token seller receiving revenue, miners receive it, and the sale prices out all other applications on-chain.
The most expensive transaction in the BAT sale set a fee of 580,000 gwei, paying a fee of $6,600 to get included in the sale.
Many ICOs after that tried various strategies to avoid these gas price auctions; one ICO notably had a smart contract that checked the transaction's gasprice and rejected it if it exceeded 50 gwei. But that didn't solve the issue. Buyers hoping to game the system sent many transactions hoping one would get through. An auction by another name, clogging the chain even more.
ICOs have recently lost popularity, but NFTs and NFT sales have risen in popularity. But the NFT space didn't learn from 2017; they do fixed-quantity sales just like ICOs (eg. see the mint function on lines 97-108 of this contract here). So what?
That's not the worst; some NFT sales have caused gas price spikes of up to 2000 gwei.
High gas prices from users fighting to get in first by sending higher and higher transaction fees. An auction renamed, pricing out all other applications on-chain for 15 minutes.
So why do sellers sometimes sell below market price?
Selling below market value is nothing new, and many articles, papers, and podcasts have written (and sometimes bitterly complained) about the unwillingness to use auctions or set prices to market-clearing levels.
Many of the arguments are the same for both blockchain (NFTs and ICOs) and non-blockchain examples (popular restaurants and concerts). Fairness and the desire not to exclude the poor, lose fans or create tension by being perceived as greedy are major concerns. The 1986 paper by Kahneman, Knetsch, and Thaler explains how fairness and greed can influence these decisions. I recall that the desire to avoid perceptions of greed was also a major factor in discouraging the use of auction-like mechanisms in 2017.
Aside from fairness concerns, there is the argument that selling out and long lines create a sense of popularity and prestige, making the product more appealing to others. Long lines should have the same effect as high prices in a rational actor model, but this is not the case in reality. This applies to ICOs and NFTs as well as restaurants. Aside from increasing marketing value, some people find the game of grabbing a limited set of opportunities first before everyone else is quite entertaining.
But there are some blockchain-specific factors. One argument for selling ICO tokens below market value (and one that persuaded the OmiseGo team to adopt their capped sale strategy) is community dynamics. The first rule of community sentiment management is to encourage price increases. People are happy if they are "in the green." If the price drops below what the community members paid, they are unhappy and start calling you a scammer, possibly causing a social media cascade where everyone calls you a scammer.
This effect can only be avoided by pricing low enough that post-launch market prices will almost certainly be higher. But how do you do this without creating a rush for the gates that leads to an auction?
Interesting solutions
It's 2021. We have a blockchain. The blockchain is home to a powerful decentralized finance ecosystem, as well as a rapidly expanding set of non-financial tools. The blockchain also allows us to reset social norms. Where decades of economists yelling about "efficiency" failed, blockchains may be able to legitimize new uses of mechanism design. If we could use our more advanced tools to create an approach that more directly solves the problems, with fewer side effects, wouldn't that be better than fiddling with a coarse-grained one-dimensional strategy space of selling at market price versus below market price?
Begin with the goals. We'll try to cover ICOs, NFTs, and conference tickets (really a type of NFT) all at the same time.
1. Fairness: don't completely exclude low-income people from participation; give them a chance. The goal of token sales is to avoid high initial wealth concentration and have a larger and more diverse initial token holder community.
2. Don’t create races: Avoid situations where many people rush to do the same thing and only a few get in (this is the type of situation that leads to the horrible auctions-by-another-name that we saw above).
3. Don't require precise market knowledge: the mechanism should work even if the seller has no idea how much demand exists.
4. Fun: The process of participating in the sale should be fun and game-like, but not frustrating.
5. Give buyers positive expected returns: in the case of a token (or an NFT), buyers should expect price increases rather than decreases. This requires selling below market value.
Let's start with (1). From Ethereum's perspective, there is a simple solution. Use a tool designed for the job: proof of personhood protocols! Here's one quick idea:
Mechanism 1 Each participant (verified by ID) can buy up to ‘’X’’ tokens at price P, with the option to buy more at an auction.
With the per-person mechanism, buyers can get positive expected returns for the portion sold through the per-person mechanism, and the auction part does not require sellers to understand demand levels. Is it race-free? The number of participants buying through the per-person pool appears to be high. But what if the per-person pool isn't big enough to accommodate everyone?
Make the per-person allocation amount dynamic.
Mechanism 2 Each participant can deposit up to X tokens into a smart contract to declare interest. Last but not least, each buyer receives min(X, N / buyers) tokens, where N is the total sold through the per-person pool (some other amount can also be sold by auction). The buyer gets their deposit back if it exceeds the amount needed to buy their allocation.
No longer is there a race condition based on the number of buyers per person. No matter how high the demand, it's always better to join sooner rather than later.
Here's another idea if you like clever game mechanics with fancy quadratic formulas.
Mechanism 3 Each participant can buy X units at a price P X 2 up to a maximum of C tokens per buyer. C starts low and gradually increases until enough units are sold.
The quantity allocated to each buyer is theoretically optimal, though post-sale transfers will degrade this optimality over time. Mechanisms 2 and 3 appear to meet all of the above objectives. They're not perfect, but they're good starting points.
One more issue. For fixed and limited supply NFTs, the equilibrium purchased quantity per participant may be fractional (in mechanism 2, number of buyers > N, and in mechanism 3, setting C = 1 may already lead to over-subscription). With fractional sales, you can offer lottery tickets: if there are N items available, you have a chance of N/number of buyers of getting the item, otherwise you get a refund. For a conference, groups could bundle their lottery tickets to guarantee a win or a loss. The certainty of getting the item can be auctioned.
The bottom tier of "sponsorships" can be used to sell conference tickets at market rate. You may end up with a sponsor board full of people's faces, but is that okay? After all, John Lilic was on EthCC's sponsor board!
Simply put, if you want to be reliably fair to people, you need an input that explicitly measures people. Authentication protocols do this (and if desired can be combined with zero knowledge proofs to ensure privacy). So we should combine the efficiency of market and auction-based pricing with the equality of proof of personhood mechanics.
Answers to possible questions
Q: Won't people who don't care about your project buy the item and immediately resell it?
A: Not at first. Meta-games take time to appear in practice. If they do, making them untradeable for a while may help mitigate the damage. Using your face to claim that your previous account was hacked and that your identity, including everything in it, should be moved to another account works because proof-of-personhood identities are untradeable.
Q: What if I want to make my item available to a specific community?
A: Instead of ID, use proof of participation tokens linked to community events. Another option, also serving egalitarian and gamification purposes, is to encrypt items within publicly available puzzle solutions.
Q: How do we know they'll accept? Strange new mechanisms have previously been resisted.
A: Having economists write screeds about how they "should" accept a new mechanism that they find strange is difficult (or even "equity"). However, abrupt changes in context effectively reset people's expectations. So the blockchain space is the best place to try this. You could wait for the "metaverse", but it's possible that the best version will run on Ethereum anyway, so start now.