More on Web3 & Crypto
CyberPunkMetalHead
3 years ago
I talked to ChatGPT about the adoption of cryptocurrencies.
OpenAI's ChatGPT is an amazing AI-powered chatbot. It can write poetry, fiction, and marketing ideas. I was impressed how well ChatGPT followed the interview, albeit there were a few classics “I’m afraid I can’t do that”.
Full interview below.
Me: I'm your interviewer. We'll discuss crypto. Thanks for being interviewed. What do you think about cryptocurrency?
CGPT: Cryptocurrency is an innovative technology that could transform money and financial activities. It might boost the efficiency and security of financial institutions and let consumers deal directly without banks. Cryptocurrency is still a new and untested technology with many unknowns and hurdles before it can be broadly accepted.
Me: Over 22,000 cryptocurrencies exist, and many have little use. We need how much cryptocurrencies?
CGPT: The appropriate quantity will rely on a multitude of factors, including each cryptocurrency's use cases, adoption rate, and market rivalry. Only a few cryptocurrencies will likely receive widespread adoption and be successful. Many existing cryptocurrencies may not survive since they can't deliver new or valued solutions or compete with more established cryptocurrencies.
Me: Will cryptocurrencies grow? What's next for worldwide adoption?
CGPT: It's hard to forecast the future of cryptocurrencies because the acceptance of new technologies is unpredictable. I believe cryptocurrencies will expand and acquire popularity in the future years. Regulatory ambiguity, security concerns, and scalability issues must be overcome for this to happen. Cryptocurrency companies and organizations must engage together with governments and authorities to address these obstacles and establish a growth-friendly climate. Continued innovation and improvement of the technology, including public education and awareness, will drive acceptance.
Me: Do bear markets affect bitcoin adoption?
CGPT: On the one hand, a bear market might induce uncertainty and hesitation among potential consumers. Bear markets can present opportunities for long-term investors who can acquire cryptocurrencies at cheaper prices and are more likely to hang onto their assets. A bear market can also test the tenacity and power of the underlying technology and community, which can boost long-term confidence and adoption. A bear market might have profound and nuanced effects on bitcoin adoption.
Me: What are some likely outcomes if Bitcoin reaches $100,000 by next year?
CGPT: If Bitcoin saw rapid growth, it would undoubtedly have repercussions for the cryptocurrency market and economy. Possible scenarios include increased public interest and awareness of cryptocurrency, a surge in demand for Bitcoin and other cryptocurrencies, and a growth in the cryptocurrency industry's market value. By shifting their focus and cash to the cryptocurrency market, investors and traders may also affect other asset classes, such as traditional equities and commodities. Governments and financial organizations may focus more on the cryptocurrency sector as they try to grasp Bitcoin's rapid rise.
Me: Will other countries accept crypto as currency?
CGPT: It's hard to say if additional governments will adopt cryptocurrencies as legal tender. Some countries have recognized the promise of bitcoin and are exploring its use, while others are cautious. Adoption of bitcoin as legal cash may vary by country, based on financial infrastructure, rules, and political atmosphere. As cryptocurrency technology evolves and becomes more accepted, more governments may embrace it as legal tender.
Me: Final question: will the recent cryptocurrency hacks affect long term adoption?
CGPT: Hacks might tarnish cryptocurrency's reputation and public faith in its security, the technology underpinning it is continually improving. Many cryptocurrency projects have developed strong security mechanisms to prevent hacks and other dangers, and these safeguards will undoubtedly improve over time. The decentralized nature of cryptocurrency makes it more resistant to attacks. Hacks and other security breaches are a concern, but they may not affect cryptocurrency adoption.
Yusuf Ibrahim
4 years ago
How to sell 10,000 NFTs on OpenSea for FREE (Puppeteer/NodeJS)
So you've finished your NFT collection and are ready to sell it. Except you can't figure out how to mint them! Not sure about smart contracts or want to avoid rising gas prices. You've tried and failed with apps like Mini mouse macro, and you're not familiar with Selenium/Python. Worry no more, NodeJS and Puppeteer have arrived!
Learn how to automatically post and sell all 1000 of my AI-generated word NFTs (Nakahana) on OpenSea for FREE!
My NFT project — Nakahana |
NOTE: Only NFTs on the Polygon blockchain can be sold for free; Ethereum requires an initiation charge. NFTs can still be bought with (wrapped) ETH.
If you want to go right into the code, here's the GitHub link: https://github.com/Yusu-f/nftuploader
Let's start with the knowledge and tools you'll need.
What you should know
You must be able to write and run simple NodeJS programs. You must also know how to utilize a Metamask wallet.
Tools needed
- NodeJS. You'll need NodeJs to run the script and NPM to install the dependencies.
- Puppeteer – Use Puppeteer to automate your browser and go to sleep while your computer works.
- Metamask – Create a crypto wallet and sign transactions using Metamask (free). You may learn how to utilize Metamask here.
- Chrome – Puppeteer supports Chrome.
Let's get started now!
Starting Out
Clone Github Repo to your local machine. Make sure that NodeJS, Chrome, and Metamask are all installed and working. Navigate to the project folder and execute npm install. This installs all requirements.
Replace the “extension path” variable with the Metamask chrome extension path. Read this tutorial to find the path.
Substitute an array containing your NFT names and metadata for the “arr” variable and the “collection_name” variable with your collection’s name.
Run the script.
After that, run node nftuploader.js.
Open a new chrome instance (not chromium) and Metamask in it. Import your Opensea wallet using your Secret Recovery Phrase or create a new one and link it. The script will be unable to continue after this but don’t worry, it’s all part of the plan.
Next steps
Open your terminal again and copy the route that starts with “ws”, e.g. “ws:/localhost:53634/devtools/browser/c07cb303-c84d-430d-af06-dd599cf2a94f”. Replace the path in the connect function of the nftuploader.js script.
const browser = await puppeteer.connect({ browserWSEndpoint: "ws://localhost:58533/devtools/browser/d09307b4-7a75-40f6-8dff-07a71bfff9b3", defaultViewport: null });
Rerun node nftuploader.js. A second tab should open in THE SAME chrome instance, navigating to your Opensea collection. Your NFTs should now start uploading one after the other! If any errors occur, the NFTs and errors are logged in an errors.log file.
Error Handling
The errors.log file should show the name of the NFTs and the error type. The script has been changed to allow you to simply check if an NFT has already been posted. Simply set the “searchBeforeUpload” setting to true.
We're done!
If you liked it, you can buy one of my NFTs! If you have any concerns or would need a feature added, please let me know.
Thank you to everyone who has read and liked. I never expected it to be so popular.
Vitalik
4 years ago
An approximate introduction to how zk-SNARKs are possible (part 2)
If tasked with the problem of coming up with a zk-SNARK protocol, many people would make their way to this point and then get stuck and give up. How can a verifier possibly check every single piece of the computation, without looking at each piece of the computation individually? But it turns out that there is a clever solution.
Polynomials
Polynomials are a special class of algebraic expressions of the form:
- x+5
- x^4
- x^3+3x^2+3x+1
- 628x^{271}+318x^{270}+530x^{269}+…+69x+381
i.e. they are a sum of any (finite!) number of terms of the form cx^k
There are many things that are fascinating about polynomials. But here we are going to zoom in on a particular one: polynomials are a single mathematical object that can contain an unbounded amount of information (think of them as a list of integers and this is obvious). The fourth example above contained 816 digits of tau, and one can easily imagine a polynomial that contains far more.
Furthermore, a single equation between polynomials can represent an unbounded number of equations between numbers. For example, consider the equation A(x)+ B(x) = C(x). If this equation is true, then it's also true that:
- A(0)+B(0)=C(0)
- A(1)+B(1)=C(1)
- A(2)+B(2)=C(2)
- A(3)+B(3)=C(3)
And so on for every possible coordinate. You can even construct polynomials to deliberately represent sets of numbers so you can check many equations all at once. For example, suppose that you wanted to check:
- 12+1=13
- 10+8=18
- 15+8=23
- 15+13=28
You can use a procedure called Lagrange interpolation to construct polynomials A(x) that give (12,10,15,15) as outputs at some specific set of coordinates (eg. (0,1,2,3)), B(x) the outputs (1,8,8,13) on thos same coordinates, and so forth. In fact, here are the polynomials:
- A(x)=-2x^3+\frac{19}{2}x^2-\frac{19}{2}x+12
- B(x)=2x^3-\frac{19}{2}x^2+\frac{29}{2}x+1
- C(x)=5x+13
Checking the equation A(x)+B(x)=C(x) with these polynomials checks all four above equations at the same time.
Comparing a polynomial to itself
You can even check relationships between a large number of adjacent evaluations of the same polynomial using a simple polynomial equation. This is slightly more advanced. Suppose that you want to check that, for a given polynomial F, F(x+2)=F(x)+F(x+1) with the integer range {0,1…89} (so if you also check F(0)=F(1)=1, then F(100) would be the 100th Fibonacci number)
As polynomials, F(x+2)-F(x+1)-F(x) would not be exactly zero, as it could give arbitrary answers outside the range x={0,1…98}. But we can do something clever. In general, there is a rule that if a polynomial P is zero across some set S=\{x_1,x_2…x_n\} then it can be expressed as P(x)=Z(x)*H(x), where Z(x)=(x-x_1)*(x-x_2)*…*(x-x_n) and H(x) is also a polynomial. In other words, any polynomial that equals zero across some set is a (polynomial) multiple of the simplest (lowest-degree) polynomial that equals zero across that same set.
Why is this the case? It is a nice corollary of polynomial long division: the factor theorem. We know that, when dividing P(x) by Z(x), we will get a quotient Q(x) and a remainder R(x) is strictly less than that of Z(x). Since we know that P is zero on all of S, it means that R has to be zero on all of S as well. So we can simply compute R(x) via polynomial interpolation, since it's a polynomial of degree at most n-1 and we know n values (the zeros at S). Interpolating a polynomial with all zeroes gives the zero polynomial, thus R(x)=0 and H(x)=Q(x).
Going back to our example, if we have a polynomial F that encodes Fibonacci numbers (so F(x+2)=F(x)+F(x+1) across x=\{0,1…98\}), then I can convince you that F actually satisfies this condition by proving that the polynomial P(x)=F(x+2)-F(x+1)-F(x) is zero over that range, by giving you the quotient:
H(x)=\frac{F(x+2)-F(x+1)-F(x)}{Z(x)}
Where Z(x) = (x-0)*(x-1)*…*(x-98).
You can calculate Z(x) yourself (ideally you would have it precomputed), check the equation, and if the check passes then F(x) satisfies the condition!
Now, step back and notice what we did here. We converted a 100-step-long computation into a single equation with polynomials. Of course, proving the N'th Fibonacci number is not an especially useful task, especially since Fibonacci numbers have a closed form. But you can use exactly the same basic technique, just with some extra polynomials and some more complicated equations, to encode arbitrary computations with an arbitrarily large number of steps.
see part 3
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Sanjay Priyadarshi
2 years ago
Using Ruby code, a programmer created a $48,000,000,000 product that Elon Musk admired.
Unexpected Success
Shopify CEO and co-founder Tobias Lutke. Shopify is worth $48 billion.
World-renowned entrepreneur Tobi
Tobi never expected his first online snowboard business to become a multimillion-dollar software corporation.
Tobi founded Shopify to establish a 20-person company.
The publicly traded corporation employs over 10,000 people.
Here's Tobi Lutke's incredible story.
Elon Musk tweeted his admiration for the Shopify creator.
30-October-2019.
Musk praised Shopify founder Tobi Lutke on Twitter.
Happened:
Explore this programmer's journey.
What difficulties did Tobi experience as a young child?
Germany raised Tobi.
Tobi's parents realized he was smart but had trouble learning as a toddler.
Tobi was learning disabled.
Tobi struggled with school tests.
Tobi's learning impairments were undiagnosed.
Tobi struggled to read as a dyslexic.
Tobi also found school boring.
Germany's curriculum didn't inspire Tobi's curiosity.
“The curriculum in Germany was taught like here are all the solutions you might find useful later in life, spending very little time talking about the problem…If I don’t understand the problem I’m trying to solve, it’s very hard for me to learn about a solution to a problem.”
Studying computer programming
After tenth grade, Tobi decided school wasn't for him and joined a German apprenticeship program.
This curriculum taught Tobi software engineering.
He was an apprentice in a small Siemens subsidiary team.
Tobi worked with rebellious Siemens employees.
Team members impressed Tobi.
Tobi joined the team for this reason.
Tobi was pleased to get paid to write programming all day.
His life could not have been better.
Devoted to snowboarding
Tobi loved snowboarding.
He drove 5 hours to ski at his folks' house.
His friends traveled to the US to snowboard when he was older.
However, the cheap dollar conversion rate led them to Canada.
2000.
Tobi originally decided to snowboard instead than ski.
Snowboarding captivated him in Canada.
On the trip to Canada, Tobi encounters his wife.
Tobi meets his wife Fiona McKean on his first Canadian ski trip.
They maintained in touch after the trip.
Fiona moved to Germany after graduating.
Tobi was a startup coder.
Fiona found work in Germany.
Her work included editing, writing, and academics.
“We lived together for 10 months and then she told me that she need to go back for the master's program.”
With Fiona, Tobi immigrated to Canada.
Fiona invites Tobi.
Tobi agreed to move to Canada.
Programming helped Tobi move in with his girlfriend.
Tobi was an excellent programmer, therefore what he did in Germany could be done anywhere.
He worked remotely for his German employer in Canada.
Tobi struggled with remote work.
Due to poor communication.
No slack, so he used email.
Programmers had trouble emailing.
Tobi's startup was developing a browser.
After the dot-com crash, individuals left that startup.
It ended.
Tobi didn't intend to work for any major corporations.
Tobi left his startup.
He believed he had important skills for any huge corporation.
He refused to join a huge corporation.
Because of Siemens.
Tobi learned to write professional code and about himself while working at Siemens in Germany.
Siemens culture was odd.
Employees were distrustful.
Siemens' rigorous dress code implies that the corporation doesn't trust employees' attire.
It wasn't Tobi's place.
“There was so much bad with it that it just felt wrong…20-year-old Tobi would not have a career there.”
Focused only on snowboarding
Tobi lived in Ottawa with his girlfriend.
Canada is frigid in winter.
Ottawa's winters last.
Almost half a year.
Tobi wanted to do something worthwhile now.
So he snowboarded.
Tobi began snowboarding seriously.
He sought every snowboarding knowledge.
He researched the greatest snowboarding gear first.
He created big spreadsheets for snowboard-making technologies.
Tobi grew interested in selling snowboards while researching.
He intended to sell snowboards online.
He had no choice but to start his own company.
A small local company offered Tobi a job.
Interested.
He must sign papers to join the local company.
He needed a work permit when he signed the documents.
Tobi had no work permit.
He was allowed to stay in Canada while applying for permanent residency.
“I wasn’t illegal in the country, but my state didn’t give me a work permit. I talked to a lawyer and he told me it’s going to take a while until I get a permanent residency.”
Tobi's lawyer told him he cannot get a work visa without permanent residence.
His lawyer said something else intriguing.
Tobis lawyer advised him to start a business.
Tobi declined this local company's job offer because of this.
Tobi considered opening an internet store with his technical skills.
He sold snowboards online.
“I was thinking of setting up an online store software because I figured that would exist and use it as a way to sell snowboards…make money while snowboarding and hopefully have a good life.”
What brought Tobi and his co-founder together, and how did he support Tobi?
Tobi lived with his girlfriend's parents.
In Ottawa, Tobi encounters Scott Lake.
Scott was Tobis girlfriend's family friend and worked for Tobi's future employer.
Scott and Tobi snowboarded.
Tobi pitched Scott his snowboard sales software idea.
Scott liked the idea.
They planned a business together.
“I was looking after the technology and Scott was dealing with the business side…It was Scott who ended up developing relationships with vendors and doing all the business set-up.”
Issues they ran into when attempting to launch their business online
Neither could afford a long-term lease.
That prompted their online business idea.
They would open a store.
Tobi anticipated opening an internet store in a week.
Tobi seeks open-source software.
Most existing software was pricey.
Tobi and Scott couldn't afford pricey software.
“In 2004, I was sitting in front of my computer absolutely stunned realising that we hadn’t figured out how to create software for online stores.”
They required software to:
to upload snowboard images to the website.
people to look up the types of snowboards that were offered on the website. There must be a search feature in the software.
Online users transmit payments, and the merchant must receive them.
notifying vendors of the recently received order.
No online selling software existed at the time.
Online credit card payments were difficult.
How did they advance the software while keeping expenses down?
Tobi and Scott needed money to start selling snowboards.
Tobi and Scott funded their firm with savings.
“We both put money into the company…I think the capital we had was around CAD 20,000(Canadian Dollars).”
Despite investing their savings.
They minimized costs.
They tried to conserve.
No office rental.
They worked in several coffee shops.
Tobi lived rent-free at his girlfriend's parents.
He installed software in coffee cafes.
How were the software issues handled?
Tobi found no online snowboard sales software.
Two choices remained:
Change your mind and try something else.
Use his programming expertise to produce something that will aid in the expansion of this company.
Tobi knew he was the sole programmer working on such a project from the start.
“I had this realisation that I’m going to be the only programmer who has ever worked on this, so I don’t have to choose something that lots of people know. I can choose just the best tool for the job…There is been this programming language called Ruby which I just absolutely loved ”
Ruby was open-source and only had Japanese documentation.
Latin is the source code.
Tobi used Ruby twice.
He assumed he could pick the tool this time.
Why not build with Ruby?
How did they find their first time operating a business?
Tobi writes applications in Ruby.
He wrote the initial software version in 2.5 months.
Tobi and Scott founded Snowdevil to sell snowboards.
Tobi coded for 16 hours a day.
His lifestyle was unhealthy.
He enjoyed pizza and coke.
“I would never recommend this to anyone, but at the time there was nothing more interesting to me in the world.”
Their initial purchase and encounter with it
Tobi worked in cafes then.
“I was working in a coffee shop at this time and I remember everything about that day…At some time, while I was writing the software, I had to type the email that the software would send to tell me about the order.”
Tobi recalls everything.
He checked the order on his laptop at the coffee shop.
Pennsylvanian ordered snowboard.
Tobi walked home and called Scott. Tobi told Scott their first order.
They loved the order.
How were people made aware about Snowdevil?
2004 was very different.
Tobi and Scott attempted simple website advertising.
Google AdWords was new.
Ad clicks cost 20 cents.
Online snowboard stores were scarce at the time.
Google ads propelled the snowdevil brand.
Snowdevil prospered.
They swiftly recouped their original investment in the snowboard business because to its high profit margin.
Tobi and Scott struggled with inventories.
“Snowboards had really good profit margins…Our biggest problem was keeping inventory and getting it back…We were out of stock all the time.”
Selling snowboards returned their investment and saved them money.
They did not appoint a business manager.
They accomplished everything alone.
Sales dipped in the spring, but something magical happened.
Spring sales plummeted.
They considered stocking different boards.
They naturally wanted to add boards and grow the business.
However, magic occurred.
Tobi coded and improved software while running Snowdevil.
He modified software constantly. He wanted speedier software.
He experimented to make the software more resilient.
Tobi received emails requesting the Snowdevil license.
They intended to create something similar.
“I didn’t stop programming, I was just like Ok now let me try things, let me make it faster and try different approaches…Increasingly I got people sending me emails and asking me If I would like to licence snowdevil to them. People wanted to start something similar.”
Software or skateboards, your choice
Scott and Tobi had to choose a hobby in 2005.
They might sell alternative boards or use software.
The software was a no-brainer from demand.
Daniel Weinand is invited to join Tobi's business.
Tobis German best friend is Daniel.
Tobi and Scott chose to use the software.
Tobi and Scott kept the software service.
Tobi called Daniel to invite him to Canada to collaborate.
Scott and Tobi had quit snowboarding until then.
How was Shopify launched, and whence did the name come from?
The three chose Shopify.
Named from two words.
First:
Shop
Final part:
Simplify
Shopify
Shopify's crew has always had one goal:
creating software that would make it simple and easy for people to launch online storefronts.
Launched Shopify after raising money for the first time.
Shopify began fundraising in 2005.
First, they borrowed from family and friends.
They needed roughly $200k to run the company efficiently.
$200k was a lot then.
When questioned why they require so much money. Tobi told them to trust him with their goals. The team raised seed money from family and friends.
Shopify.com has a landing page. A demo of their goal was on the landing page.
In 2006, Shopify had about 4,000 emails.
Shopify rented an Ottawa office.
“We sent a blast of emails…Some people signed up just to try it out, which was exciting.”
How things developed after Scott left the company
Shopify co-founder Scott Lake left in 2008.
Scott was CEO.
“He(Scott) realized at some point that where the software industry was going, most of the people who were the CEOs were actually the highly technical person on the founding team.”
Scott leaving the company worried Tobi.
Tobis worried about finding a new CEO.
To Tobi:
A great VC will have the network to identify the perfect CEO for your firm.
Tobi started visiting Silicon Valley to meet with venture capitalists to recruit a CEO.
Initially visiting Silicon Valley
Tobi came to Silicon Valley to start a 20-person company.
This company creates eCommerce store software.
Tobi never wanted a big corporation. He desired a fulfilling existence.
“I stayed in a hostel in the Bay Area. I had one roommate who was also a computer programmer. I bought a bicycle on Craiglist. I was there for a week, but ended up staying two and a half weeks.”
Tobi arrived unprepared.
When venture capitalists asked him business questions.
He answered few queries.
Tobi didn't comprehend VC meetings' terminology.
He wrote the terms down and looked them up.
Some were fascinated after he couldn't answer all these queries.
“I ended up getting the kind of term sheets people dream about…All the offers were conditional on moving our company to Silicon Valley.”
Canada received Tobi.
He wanted to consult his team before deciding. Shopify had five employees at the time.
2008.
A global recession greeted Tobi in Canada. The recession hurt the market.
His term sheets were useless.
The economic downturn in the world provided Shopify with a fantastic opportunity.
The global recession caused significant job losses.
Fired employees had several ideas.
They wanted online stores.
Entrepreneurship was desired. They wanted to quit work.
People took risks and tried new things during the global slump.
Shopify subscribers skyrocketed during the recession.
“In 2009, the company reached neutral cash flow for the first time…We were in a position to think about long-term investments, such as infrastructure projects.”
Then, Tobi Lutke became CEO.
How did Tobi perform as the company's CEO?
“I wasn’t good. My team was very patient with me, but I had a lot to learn…It’s a very subtle job.”
2009–2010.
Tobi limited the company's potential.
He deliberately restrained company growth.
Tobi had one costly problem:
Whether Shopify is a venture or a lifestyle business.
The company's annual revenue approached $1 million.
Tobi battled with the firm and himself despite good revenue.
His wife was supportive, but the responsibility was crushing him.
“It’s a crushing responsibility…People had families and kids…I just couldn’t believe what was going on…My father-in-law gave me money to cover the payroll and it was his life-saving.”
Throughout this trip, everyone supported Tobi.
They believed it.
$7 million in donations received
Tobi couldn't decide if this was a lifestyle or a business.
Shopify struggled with marketing then.
Later, Tobi tried 5 marketing methods.
He told himself that if any marketing method greatly increased their growth, he would call it a venture, otherwise a lifestyle.
The Shopify crew brainstormed and voted on marketing concepts.
Tested.
“Every single idea worked…We did Adwords, published a book on the concept, sponsored a podcast and all the ones we tracked worked.”
To Silicon Valley once more
Shopify marketing concepts worked once.
Tobi returned to Silicon Valley to pitch investors.
He raised $7 million, valuing Shopify at $25 million.
All investors had board seats.
“I find it very helpful…I always had a fantastic relationship with everyone who’s invested in my company…I told them straight that I am not going to pretend I know things, I want you to help me.”
Tobi developed skills via running Shopify.
Shopify had 20 employees.
Leaving his wife's parents' home
Tobi left his wife's parents in 2014.
Tobi had a child.
Shopify has 80,000 customers and 300 staff in 2013.
Public offering in 2015
Shopify investors went public in 2015.
Shopify powers 4.1 million e-Commerce sites.
Shopify stores are 65% US-based.
It is currently valued at $48 billion.
Marcus Lu
3 years ago
The Brand Structure of U.S. Electric Vehicle Production
Will Tesla be able to maintain its lead in the EV market for very long?
This is one of the most pressing issues in the American auto sector today. One positive aspect of Tesla is the company's devoted customer base and recognizable name recognition (similar to Apple). It also invests more in research and development per vehicle than its rivals and has a head start in EV production.
Conversely, established automakers like Volkswagen are actively plotting their strategy to surpass Tesla. As the current market leaders, they have decades of experience in the auto industry and are spending billions to catch up.
We've visualized data from the EPA's 2022 Automotive Trends Report to bring you up to speed on this developing story.
Info for the Model Year of 2021
The full production data used in this infographic is for the 2021 model year, but it comes from a report for 2022.
Combined EV and PHEV output is shown in the table below (plug-in hybrid electric vehicle).
It is important to note that Toyota and Stellantis, the two largest legacy automakers in this dataset, only produced PHEVs. Toyota's first electric vehicle, the bZ4X, won't hit the market until 2023.
Stellantis seems to be falling even further behind, despite having enormous unrealized potential in its Jeep and Ram brands. Stellantis CEO Carlos Tavares said in a recent interview that the firm has budgeted $36 billion for electrification and software.
Legacy Brands with the Most Momentum
In the race to develop electric vehicles, some long-standing manufacturers have gotten the jump on their rivals.
Volkswagen, one of these storied manufacturers, has made a significant investment in electric vehicles (EVs) in the wake of the Dieselgate scandal. The company plans to roll out multiple EV models, including the ID.3 hatchback, ID.4 SUV, and ID. Buzz, with the goal of producing 22 million EVs by 2028. (an electric revival of the classic Microbus).
Even Ford is keeping up, having just announced an EV investment of $22 billion between 2021 and 2025. In November of 2022, the company manufactured their 150,000th Mustang Mach-E, and by the end of 2023, they hoped to have 270,000 of them in circulation.
Additionally, over 200,000 F-150 Lightnings have been reserved since Ford announced the truck. The Lightning is scheduled to have a production run of 15,000 in 2022, 55,000 in 2023, and 80,000 in 2024. Ford's main competitor in the electric pickup truck segment, Rivian, is on track to sell 25,000 vehicles by 2022.
Amelia Winger-Bearskin
3 years ago
Hate NFTs? I must break some awful news to you...
If you think NFTs are awful, check out the art market.
The fervor around NFTs has subsided in recent months due to the crypto market crash and the media's short attention span. They were all anyone could talk about earlier this spring. Last semester, when passions were high and field luminaries were discussing "slurp juices," I asked my students and students from over 20 other universities what they thought of NFTs.
According to many, NFTs were either tasteless pyramid schemes or a new way for artists to make money. NFTs contributed to the climate crisis and harmed the environment, but so did air travel, fast fashion, and smartphones. Some students complained that NFTs were cheap, tasteless, algorithmically generated schlock, but others asked how this was different from other art.
I'm not sure what I expected, but the intensity of students' reactions surprised me. They had strong, emotional opinions about a technology I'd always considered administrative. NFTs address ownership and accounting, like most crypto/blockchain projects.
Art markets can be irrational, arbitrary, and subject to the same scams and schemes as any market. And maybe a few shenanigans that are unique to the art world.
The Fairness Question
Fairness, a deflating moral currency, was the general sentiment (the less of it in circulation, the more ardently we clamor for it.) These students, almost all of whom are artists, complained to the mismatch between the quality of the work in some notable NFT collections and the excessive amounts these items were fetching on the market. They can sketch a Bored Ape or Lazy Lion in their sleep. Why should they buy ramen with school loans while certain swindlers get rich?
I understand students. Art markets are unjust. They can be irrational, arbitrary, and governed by chance and circumstance, like any market. And art-world shenanigans.
Almost every mainstream critique leveled against NFTs applies just as easily to art markets
Over 50% of artworks in circulation are fake, say experts. Sincere art collectors and institutions are upset by the prevalence of fake goods on the market. Not everyone. Wealthy people and companies use art as investments. They can use cultural institutions like museums and galleries to increase the value of inherited art collections. People sometimes buy artworks and use family ties or connections to museums or other cultural taste-makers to hype the work in their collection, driving up the price and allowing them to sell for a profit. Money launderers can disguise capital flows by using market whims, hype, and fluctuating asset prices.
Almost every mainstream critique leveled against NFTs applies just as easily to art markets.
Art has always been this way. Edward Kienholz's 1989 print series satirized art markets. He stamped 395 identical pieces of paper from $1 to $395. Each piece was initially priced as indicated. Kienholz was joking about a strange feature of art markets: once the last print in a series sells for $395, all previous works are worth at least that much. The entire series is valued at its highest auction price. I don't know what a Kienholz print sells for today (inquire with the gallery), but it's more than $395.
I love Lee Lozano's 1969 "Real Money Piece." Lozano put cash in various denominations in a jar in her apartment and gave it to visitors. She wrote, "Offer guests coffee, diet pepsi, bourbon, half-and-half, ice water, grass, and money." "Offer real money as candy."
Lee Lozano kept track of who she gave money to, how much they took, if any, and how they reacted to the offer of free money without explanation. Diverse reactions. Some found it funny, others found it strange, and others didn't care. Lozano rarely says:
Apr 17 Keith Sonnier refused, later screws lid very tightly back on. Apr 27 Kaltenbach takes all the money out of the jar when I offer it, examines all the money & puts it all back in jar. Says he doesn’t need money now. Apr 28 David Parson refused, laughing. May 1 Warren C. Ingersoll refused. He got very upset about my “attitude towards money.” May 4 Keith Sonnier refused, but said he would take money if he needed it which he might in the near future. May 7 Dick Anderson barely glances at the money when I stick it under his nose and says “Oh no thanks, I intend to earn it on my own.” May 8 Billy Bryant Copley didn’t take any but then it was sort of spoiled because I had told him about this piece on the phone & he had time to think about it he said.
Smart Contracts (smart as in fair, not smart as in Blockchain)
Cornell University's Cheryl Finley has done a lot of research on secondary art markets. I first learned about her research when I met her at the University of Florida's Harn Museum, where she spoke about smart contracts (smart as in fair, not smart as in Blockchain) and new protocols that could help artists who are often left out of the economic benefits of their own work, including women and women of color.
Her talk included findings from her ArtNet op-ed with Lauren van Haaften-Schick, Christian Reeder, and Amy Whitaker.
NFTs allow us to think about and hack on formal contractual relationships outside a system of laws that is currently not set up to service our community.
The ArtNet article The Recent Sale of Amy Sherald's ‘Welfare Queen' Symbolizes the Urgent Need for Resale Royalties and Economic Equity for Artists discussed Sherald's 2012 portrait of a regal woman in a purple dress wearing a sparkling crown and elegant set of pearls against a vibrant red background.
Amy Sherald sold "Welfare Queen" to Princeton professor Imani Perry. Sherald agreed to a payment plan to accommodate Perry's budget.
Amy Sherald rose to fame for her 2016 portrait of Michelle Obama and her full-length portrait of Breonna Taylor, one of the most famous works of the past decade.
As is common, Sherald's rising star drove up the price of her earlier works. Perry's "Welfare Queen" sold for $3.9 million in 2021.
Imani Perry's early investment paid off big-time. Amy Sherald, whose work directly increased the painting's value and who was on an artist's shoestring budget when she agreed to sell "Welfare Queen" in 2012, did not see any of the 2021 auction money. Perry and the auction house got that money.
Sherald sold her Breonna Taylor portrait to the Smithsonian and Louisville's Speed Art Museum to fund a $1 million scholarship. This is a great example of what an artist can do for the community if they can amass wealth through their work.
NFTs haven't solved all of the art market's problems — fakes, money laundering, market manipulation — but they didn't create them. Blockchain and NFTs are credited with making these issues more transparent. More ideas emerge daily about what a smart contract should do for artists.
NFTs are a copyright solution. They allow us to hack formal contractual relationships outside a law system that doesn't serve our community.
Amy Sherald shows the good smart contracts can do (as in, well-considered, self-determined contracts, not necessarily blockchain contracts.) Giving back to our community, deciding where and how our work can be sold or displayed, and ensuring artists share in the equity of our work and the economy our labor creates.
