More on Web3 & Crypto
Isobel Asher Hamilton
3 years ago
$181 million in bitcoin buried in a dump. $11 million to get them back
James Howells lost 8,000 bitcoins. He has $11 million to get them back.
His life altered when he threw out an iPhone-sized hard drive.
Howells, from the city of Newport in southern Wales, had two identical laptop hard drives squirreled away in a drawer in 2013. One was blank; the other had 8,000 bitcoins, currently worth around $181 million.
He wanted to toss out the blank one, but the drive containing the Bitcoin went to the dump.
He's determined to reclaim his 2009 stash.
Howells, 36, wants to arrange a high-tech treasure hunt for bitcoins. He can't enter the landfill.
Newport's city council has rebuffed Howells' requests to dig for his hard drive for almost a decade, stating it would be expensive and environmentally destructive.
I got an early look at his $11 million idea to search 110,000 tons of trash. He expects submitting it to the council would convince it to let him recover the hard disk.
110,000 tons of trash, 1 hard drive
Finding a hard disk among heaps of trash may seem Herculean.
Former IT worker Howells claims it's possible with human sorters, robot dogs, and an AI-powered computer taught to find hard drives on a conveyor belt.
His idea has two versions, depending on how much of the landfill he can search.
His most elaborate solution would take three years and cost $11 million to sort 100,000 metric tons of waste. Scaled-down version costs $6 million and takes 18 months.
He's created a team of eight professionals in AI-powered sorting, landfill excavation, garbage management, and data extraction, including one who recovered Columbia's black box data.
The specialists and their companies would be paid a bonus if they successfully recovered the bitcoin stash.
Howells: "We're trying to commercialize this project."
Howells claimed rubbish would be dug up by machines and sorted near the landfill.
Human pickers and a Max-AI machine would sort it. The machine resembles a scanner on a conveyor belt.
Remi Le Grand of Max-AI told us it will train AI to recognize Howells-like hard drives. A robot arm would select candidates.
Howells has added security charges to his scheme because he fears people would steal the hard drive.
He's budgeted for 24-hour CCTV cameras and two robotic "Spot" canines from Boston Dynamics that would patrol at night and look for his hard drive by day.
Howells said his crew met in May at the Celtic Manor Resort outside Newport for a pitch rehearsal.
Richard Hammond's narrative swings from banal to epic.
Richard Hammond filmed the meeting and created a YouTube documentary on Howells.
Hammond said of Howells' squad, "They're committed and believe in him and the idea."
Hammond: "It goes from banal to gigantic." "If I were in his position, I wouldn't have the strength to answer the door."
Howells said trash would be cleaned and repurposed after excavation. Reburying the rest.
"We won't pollute," he declared. "We aim to make everything better."
After the project is finished, he hopes to develop a solar or wind farm on the dump site. The council is unlikely to accept his vision soon.
A council representative told us, "Mr. Howells can't convince us of anything." "His suggestions constitute a significant ecological danger, which we can't tolerate and are forbidden by our permit."
Will the recovered hard drive work?
The "platter" is a glass or metal disc that holds the hard drive's data. Howells estimates 80% to 90% of the data will be recoverable if the platter isn't damaged.
Phil Bridge, a data-recovery expert who consulted Howells, confirmed these numbers.
If the platter is broken, Bridge adds, data recovery is unlikely.
Bridge says he was intrigued by the proposal. "It's an intriguing case," he added. Helping him get it back and proving everyone incorrect would be a great success story.
Who'd pay?
Swiss and German venture investors Hanspeter Jaberg and Karl Wendeborn told us they would fund the project if Howells received council permission.
Jaberg: "It's a needle in a haystack and a high-risk investment."
Howells said he had no contract with potential backers but had discussed the proposal in Zoom meetings. "Until Newport City Council gives me something in writing, I can't commit," he added.
Suppose he finds the bitcoins.
Howells said he would keep 30% of the data, worth $54 million, if he could retrieve it.
A third would go to the recovery team, 30% to investors, and the remainder to local purposes, including gifting £50 ($61) in bitcoin to each of Newport's 150,000 citizens.
Howells said he opted to spend extra money on "professional firms" to help convince the council.
What if the council doesn't approve?
If Howells can't win the council's support, he'll sue, claiming its actions constitute a "illegal embargo" on the hard drive. "I've avoided that path because I didn't want to cause complications," he stated. I wanted to cooperate with Newport's council.
Howells never met with the council face-to-face. He mentioned he had a 20-minute Zoom meeting in May 2021 but thought his new business strategy would help.
He met with Jessica Morden on June 24. Morden's office confirmed meeting.
After telling the council about his proposal, he can only wait. "I've never been happier," he said. This is our most professional operation, with the best employees.
The "crypto proponent" buys bitcoin every month and sells it for cash.
Howells tries not to think about what he'd do with his part of the money if the hard disk is found functional. "Otherwise, you'll go mad," he added.
This post is a summary. Read the full article here.
Elnaz Sarraf
3 years ago
Why Bitcoin's Crash Could Be Good for Investors
The crypto market crashed in June 2022. Bitcoin and other cryptocurrencies hit their lowest prices in over a year, causing market panic. Some believe this crash will benefit future investors.
Before I discuss how this crash might help investors, let's examine why it happened. Inflation in the U.S. reached a 30-year high in 2022 after Russia invaded Ukraine. In response, the U.S. Federal Reserve raised interest rates by 0.5%, the most in almost 20 years. This hurts cryptocurrencies like Bitcoin. Higher interest rates make people less likely to invest in volatile assets like crypto, so many investors sold quickly.
The crypto market collapsed. Bitcoin, Ethereum, and Binance dropped 40%. Other cryptos crashed so hard they were delisted from almost every exchange. Bitcoin peaked in April 2022 at $41,000, but after the May interest rate hike, it crashed to $28,000. Bitcoin investors were worried. Even in bad times, this crash is unprecedented.
Bitcoin wasn't "doomed." Before the crash, LUNA was one of the top 5 cryptos by market cap. LUNA was trading around $80 at the start of May 2022, but after the rate hike?
Less than 1 cent. LUNA lost 99.99% of its value in days and was removed from every crypto exchange. Bitcoin's "crash" isn't as devastating when compared to LUNA.
Many people said Bitcoin is "due" for a LUNA-like crash and that the only reason it hasn't crashed is because it's bigger. Still false. If so, Bitcoin should be worth zero by now. We didn't. Instead, Bitcoin reached 28,000, then 29k, 30k, and 31k before falling to 18k. That's not the world's greatest recovery, but it shows Bitcoin's safety.
Bitcoin isn't falling constantly. It fell because of the initial shock of interest rates, but not further. Now, Bitcoin's value is more likely to rise than fall. Bitcoin's low price also attracts investors. They know what prices Bitcoin can reach with enough hype, and they want to capitalize on low prices before it's too late.
Bitcoin's crash was bad, but in a way it wasn't. To understand, consider 2021. In March 2021, Bitcoin surpassed $60k for the first time. Elon Musk's announcement in May that he would no longer support Bitcoin caused a massive crash in the crypto market. In May 2017, Bitcoin's price hit $29,000. Elon Musk's statement isn't worth more than the Fed raising rates. Many expected this big announcement to kill Bitcoin.
Not so. Bitcoin crashed from $58k to $31k in 2021. Bitcoin fell from $41k to $28k in 2022. This crash is smaller. Bitcoin's price held up despite tensions and stress, proving investors still believe in it. What happened after the initial crash in the past?
Bitcoin fell until mid-July. This is also something we’re not seeing today. After a week, Bitcoin began to improve daily. Bitcoin's price rose after mid-July. Bitcoin's price fluctuated throughout the rest of 2021, but it topped $67k in November. Despite no major changes, the peak occurred after the crash. Elon Musk seemed uninterested in crypto and wasn't likely to change his mind soon. What triggered this peak? Nothing, really. What really happened is that people got over the initial statement. They forgot.
Internet users have goldfish-like attention spans. People quickly forgot the crash's cause and were back investing in crypto months later. Despite the market's setbacks, more crypto investors emerged by the end of 2017. Who gained from these peaks? Bitcoin investors who bought low. Bitcoin not only recovered but also doubled its ROI. It was like a movie, and it shows us what to expect from Bitcoin in the coming months.
The current Bitcoin crash isn't as bad as the last one. LUNA is causing market panic. LUNA and Bitcoin are different cryptocurrencies. LUNA crashed because Terra wasn’t able to keep its peg with the USD. Bitcoin is unanchored. It's one of the most decentralized investments available. LUNA's distrust affected crypto prices, including Bitcoin, but it won't last forever.
This is why Bitcoin will likely rebound in the coming months. In 2022, people will get over the rise in interest rates and the crash of LUNA, just as they did with Elon Musk's crypto stance in 2021. When the world moves on to the next big controversy, Bitcoin's price will soar.
Bitcoin may recover for another reason. Like controversy, interest rates fluctuate. The Russian invasion caused this inflation. World markets will stabilize, prices will fall, and interest rates will drop.
Next, lower interest rates could boost Bitcoin's price. Eventually, it will happen. The U.S. economy can't sustain such high interest rates. Investors will put every last dollar into Bitcoin if interest rates fall again.
Bitcoin has proven to be a stable investment. This boosts its investment reputation. Even if Ethereum dethrones Bitcoin as crypto king one day (or any other crypto, for that matter). Bitcoin may stay on top of the crypto ladder for a while. We'll have to wait a few months to see if any of this is true.
This post is a summary. Read the full article here.
Ashraful Islam
4 years ago
Clean API Call With React Hooks
| Photo by Juanjo Jaramillo on Unsplash |
Calling APIs is the most common thing to do in any modern web application. When it comes to talking with an API then most of the time we need to do a lot of repetitive things like getting data from an API call, handling the success or error case, and so on.
When calling tens of hundreds of API calls we always have to do those tedious tasks. We can handle those things efficiently by putting a higher level of abstraction over those barebone API calls, whereas in some small applications, sometimes we don’t even care.
The problem comes when we start adding new features on top of the existing features without handling the API calls in an efficient and reusable manner. In that case for all of those API calls related repetitions, we end up with a lot of repetitive code across the whole application.
In React, we have different approaches for calling an API. Nowadays mostly we use React hooks. With React hooks, it’s possible to handle API calls in a very clean and consistent way throughout the application in spite of whatever the application size is. So let’s see how we can make a clean and reusable API calling layer using React hooks for a simple web application.
I’m using a code sandbox for this blog which you can get here.
import "./styles.css";
import React, { useEffect, useState } from "react";
import axios from "axios";
export default function App() {
const [posts, setPosts] = useState(null);
const [error, setError] = useState("");
const [loading, setLoading] = useState(false);
useEffect(() => {
handlePosts();
}, []);
const handlePosts = async () => {
setLoading(true);
try {
const result = await axios.get(
"https://jsonplaceholder.typicode.com/posts"
);
setPosts(result.data);
} catch (err) {
setError(err.message || "Unexpected Error!");
} finally {
setLoading(false);
}
};
return (
<div className="App">
<div>
<h1>Posts</h1>
{loading && <p>Posts are loading!</p>}
{error && <p>{error}</p>}
<ul>
{posts?.map((post) => (
<li key={post.id}>{post.title}</li>
))}
</ul>
</div>
</div>
);
}
I know the example above isn’t the best code but at least it’s working and it’s valid code. I will try to improve that later. For now, we can just focus on the bare minimum things for calling an API.
Here, you can try to get posts data from JsonPlaceholer. Those are the most common steps we follow for calling an API like requesting data, handling loading, success, and error cases.
If we try to call another API from the same component then how that would gonna look? Let’s see.
500: Internal Server Error
Now it’s going insane! For calling two simple APIs we’ve done a lot of duplication. On a top-level view, the component is doing nothing but just making two GET requests and handling the success and error cases. For each request, it’s maintaining three states which will periodically increase later if we’ve more calls.
Let’s refactor to make the code more reusable with fewer repetitions.
Step 1: Create a Hook for the Redundant API Request Codes
Most of the repetitions we have done so far are about requesting data, handing the async things, handling errors, success, and loading states. How about encapsulating those things inside a hook?
The only unique things we are doing inside handleComments and handlePosts are calling different endpoints. The rest of the things are pretty much the same. So we can create a hook that will handle the redundant works for us and from outside we’ll let it know which API to call.
500: Internal Server Error
Here, this request function is identical to what we were doing on the handlePosts and handleComments. The only difference is, it’s calling an async function apiFunc which we will provide as a parameter with this hook. This apiFunc is the only independent thing among any of the API calls we need.
With hooks in action, let’s change our old codes in App component, like this:
500: Internal Server Error
How about the current code? Isn’t it beautiful without any repetitions and duplicate API call handling things?
Let’s continue our journey from the current code. We can make App component more elegant. Now it knows a lot of details about the underlying library for the API call. It shouldn’t know that. So, here’s the next step…
Step 2: One Component Should Take Just One Responsibility
Our App component knows too much about the API calling mechanism. Its responsibility should just request the data. How the data will be requested under the hood, it shouldn’t care about that.
We will extract the API client-related codes from the App component. Also, we will group all the API request-related codes based on the API resource. Now, this is our API client:
import axios from "axios";
const apiClient = axios.create({
// Later read this URL from an environment variable
baseURL: "https://jsonplaceholder.typicode.com"
});
export default apiClient;
All API calls for comments resource will be in the following file:
import client from "./client";
const getComments = () => client.get("/comments");
export default {
getComments
};
All API calls for posts resource are placed in the following file:
import client from "./client";
const getPosts = () => client.get("/posts");
export default {
getPosts
};
Finally, the App component looks like the following:
import "./styles.css";
import React, { useEffect } from "react";
import commentsApi from "./api/comments";
import postsApi from "./api/posts";
import useApi from "./hooks/useApi";
export default function App() {
const getPostsApi = useApi(postsApi.getPosts);
const getCommentsApi = useApi(commentsApi.getComments);
useEffect(() => {
getPostsApi.request();
getCommentsApi.request();
}, []);
return (
<div className="App">
{/* Post List */}
<div>
<h1>Posts</h1>
{getPostsApi.loading && <p>Posts are loading!</p>}
{getPostsApi.error && <p>{getPostsApi.error}</p>}
<ul>
{getPostsApi.data?.map((post) => (
<li key={post.id}>{post.title}</li>
))}
</ul>
</div>
{/* Comment List */}
<div>
<h1>Comments</h1>
{getCommentsApi.loading && <p>Comments are loading!</p>}
{getCommentsApi.error && <p>{getCommentsApi.error}</p>}
<ul>
{getCommentsApi.data?.map((comment) => (
<li key={comment.id}>{comment.name}</li>
))}
</ul>
</div>
</div>
);
}
Now it doesn’t know anything about how the APIs get called. Tomorrow if we want to change the API calling library from axios to fetch or anything else, our App component code will not get affected. We can just change the codes form client.js This is the beauty of abstraction.
Apart from the abstraction of API calls, Appcomponent isn’t right the place to show the list of the posts and comments. It’s a high-level component. It shouldn’t handle such low-level data interpolation things.
So we should move this data display-related things to another low-level component. Here I placed those directly in the App component just for the demonstration purpose and not to distract with component composition-related things.
Final Thoughts
The React library gives the flexibility for using any kind of third-party library based on the application’s needs. As it doesn’t have any predefined architecture so different teams/developers adopted different approaches to developing applications with React. There’s nothing good or bad. We choose the development practice based on our needs/choices. One thing that is there beyond any choices is writing clean and maintainable codes.
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Ray Dalio
3 years ago
The latest “bubble indicator” readings.
As you know, I like to turn my intuition into decision rules (principles) that can be back-tested and automated to create a portfolio of alpha bets. I use one for bubbles. Having seen many bubbles in my 50+ years of investing, I described what makes a bubble and how to identify them in markets—not just stocks.
A bubble market has a high degree of the following:
- High prices compared to traditional values (e.g., by taking the present value of their cash flows for the duration of the asset and comparing it with their interest rates).
- Conditons incompatible with long-term growth (e.g., extrapolating past revenue and earnings growth rates late in the cycle).
- Many new and inexperienced buyers were drawn in by the perceived hot market.
- Broad bullish sentiment.
- Debt financing a large portion of purchases.
- Lots of forward and speculative purchases to profit from price rises (e.g., inventories that are more than needed, contracted forward purchases, etc.).
I use these criteria to assess all markets for bubbles. I have periodically shown you these for stocks and the stock market.
What Was Shown in January Versus Now
I will first describe the picture in words, then show it in charts, and compare it to the last update in January.
As of January, the bubble indicator showed that a) the US equity market was in a moderate bubble, but not an extreme one (ie., 70 percent of way toward the highest bubble, which occurred in the late 1990s and late 1920s), and b) the emerging tech companies (ie. As well, the unprecedented flood of liquidity post-COVID financed other bubbly behavior (e.g. SPACs, IPO boom, big pickup in options activity), making things bubbly. I showed which stocks were in bubbles and created an index of those stocks, which I call “bubble stocks.”
Those bubble stocks have popped. They fell by a third last year, while the S&P 500 remained flat. In light of these and other market developments, it is not necessarily true that now is a good time to buy emerging tech stocks.
The fact that they aren't at a bubble extreme doesn't mean they are safe or that it's a good time to get long. Our metrics still show that US stocks are overvalued. Once popped, bubbles tend to overcorrect to the downside rather than settle at “normal” prices.
The following charts paint the picture. The first shows the US equity market bubble gauge/indicator going back to 1900, currently at the 40% percentile. The charts also zoom in on the gauge in recent years, as well as the late 1920s and late 1990s bubbles (during both of these cases the gauge reached 100 percent ).
The chart below depicts the average bubble gauge for the most bubbly companies in 2020. Those readings are down significantly.
The charts below compare the performance of a basket of emerging tech bubble stocks to the S&P 500. Prices have fallen noticeably, giving up most of their post-COVID gains.
The following charts show the price action of the bubble slice today and in the 1920s and 1990s. These charts show the same market dynamics and two key indicators. These are just two examples of how a lot of debt financing stock ownership coupled with a tightening typically leads to a bubble popping.
Everything driving the bubbles in this market segment is classic—the same drivers that drove the 1920s bubble and the 1990s bubble. For instance, in the last couple months, it was how tightening can act to prick the bubble. Review this case study of the 1920s stock bubble (starting on page 49) from my book Principles for Navigating Big Debt Crises to grasp these dynamics.
The following charts show the components of the US stock market bubble gauge. Since this is a proprietary indicator, I will only show you some of the sub-aggregate readings and some indicators.
Each of these six influences is measured using a number of stats. This is how I approach the stock market. These gauges are combined into aggregate indices by security and then for the market as a whole. The table below shows the current readings of these US equity market indicators. It compares current conditions for US equities to historical conditions. These readings suggest that we’re out of a bubble.
1. How High Are Prices Relatively?
This price gauge for US equities is currently around the 50th percentile.
2. Is price reduction unsustainable?
This measure calculates the earnings growth rate required to outperform bonds. This is calculated by adding up the readings of individual securities. This indicator is currently near the 60th percentile for the overall market, higher than some of our other readings. Profit growth discounted in stocks remains high.
Even more so in the US software sector. Analysts' earnings growth expectations for this sector have slowed, but remain high historically. P/Es have reversed COVID gains but remain high historical.
3. How many new buyers (i.e., non-existing buyers) entered the market?
Expansion of new entrants is often indicative of a bubble. According to historical accounts, this was true in the 1990s equity bubble and the 1929 bubble (though our data for this and other gauges doesn't go back that far). A flood of new retail investors into popular stocks, which by other measures appeared to be in a bubble, pushed this gauge above the 90% mark in 2020. The pace of retail activity in the markets has recently slowed to pre-COVID levels.
4. How Broadly Bullish Is Sentiment?
The more people who have invested, the less resources they have to keep investing, and the more likely they are to sell. Market sentiment is now significantly negative.
5. Are Purchases Being Financed by High Leverage?
Leveraged purchases weaken the buying foundation and expose it to forced selling in a downturn. The leverage gauge, which considers option positions as a form of leverage, is now around the 50% mark.
6. To What Extent Have Buyers Made Exceptionally Extended Forward Purchases?
Looking at future purchases can help assess whether expectations have become overly optimistic. This indicator is particularly useful in commodity and real estate markets, where forward purchases are most obvious. In the equity markets, I look at indicators like capital expenditure, or how much businesses (and governments) invest in infrastructure, factories, etc. It reflects whether businesses are projecting future demand growth. Like other gauges, this one is at the 40th percentile.
What one does with it is a tactical choice. While the reversal has been significant, future earnings discounting remains high historically. In either case, bubbles tend to overcorrect (sell off more than the fundamentals suggest) rather than simply deflate. But I wanted to share these updated readings with you in light of recent market activity.
Glorin Santhosh
3 years ago
In his final days, Steve Jobs sent an email to himself. What It Said Was This
An email capturing Steve Jobs's philosophy.
Steve Jobs may have been the most inspired and driven entrepreneur.
He worked on projects because he wanted to leave a legacy.
Steve Jobs' final email to himself encapsulated his philosophy.
After his death from pancreatic cancer in October 2011, Laurene Powell Jobs released the email. He was 56.
Read: Steve Jobs by Walter Isaacson (#BestSeller)
The Email:
September 2010 Steve Jobs email:
“I grow little of the food I eat, and of the little I do grow, I do not breed or perfect the seeds.” “I do not make my own clothing. I speak a language I did not invent or refine,” he continued. “I did not discover the mathematics I use… I am moved by music I did not create myself.”
Jobs ended his email by reflecting on how others created everything he uses.
He wrote:
“When I needed medical attention, I was helpless to help myself survive.”
The Apple co-founder concluded by praising humanity.
“I did not invent the transistor, the microprocessor, object-oriented programming, or most of the technology I work with. I love and admire my species, living and dead, and am totally dependent on them for my life and well-being,” he concluded.
The email was made public as a part of the Steve Jobs Archive, a website that was launched in tribute to his legacy.
Steve Jobs' widow founded the internet archive. Apple CEO Tim Cook and former design leader Jony Ive were prominent guests.
Steve Jobs has always inspired because he shows how even the best can be improved.
High expectations were always there, and they were consistently met.
We miss him because he was one of the few with lifelong enthusiasm and persona.
Bart Krawczyk
2 years ago
Understanding several Value Proposition kinds will help you create better goods.
Fixing problems isn't enough.
Numerous articles and how-to guides on value propositions focus on fixing consumer concerns.
Contrary to popular opinion, addressing customer pain rarely suffices. Win your market category too.
Core Value Statement
Value proposition usually means a product's main value.
Its how your product solves client problems. The product's core.
Answering these questions creates a relevant core value proposition:
What tasks is your customer trying to complete? (Jobs for clients)
How much discomfort do they feel while they perform this? (pains)
What would they like to see improved or changed? (gains)
After that, you create products and services that alleviate those pains and give value to clients.
Value Proposition by Category
Your product belongs to a market category and must follow its regulations, regardless of its value proposition.
Creating a new market category is challenging. Fitting into customers' product perceptions is usually better than trying to change them.
New product users simplify market categories. Products are labeled.
Your product will likely be associated with a collection of products people already use.
Example: IT experts will use your communication and management app.
If your target clients think it's an advanced mail software, they'll compare it to others and expect things like:
comprehensive calendar
spam detectors
adequate storage space
list of contacts
etc.
If your target users view your product as a task management app, things change. You can survive without a contact list, but not status management.
Find out what your customers compare your product to and if it fits your value offer. If so, adapt your product plan to dominate this market. If not, try different value propositions and messaging to put the product in the right context.
Finished Value Proposition
A comprehensive value proposition is when your solution addresses user problems and wins its market category.
Addressing simply the primary value proposition may produce a valuable and original product, but it may struggle to cross the chasm into the mainstream market. Meeting expectations is easier than changing views.
Without a unique value proposition, you will drown in the red sea of competition.
To conclude:
Find out who your target consumer is and what their demands and problems are.
To meet these needs, develop and test a primary value proposition.
Speak with your most devoted customers. Recognize the alternatives they use to compare you against and the market segment they place you in.
Recognize the requirements and expectations of the market category.
To meet or surpass category standards, modify your goods.
Great products solve client problems and win their category.