More on Technology

Nick Babich
2 years ago
Is ChatGPT Capable of Generating a Complete Mobile App?
TL;DR: It'll be harder than you think.
Mobile app development is a complicated product design sector. You require broad expertise to create a mobile app. You must write Swift or Java code and consider mobile interactions.
When ChatGPT was released, many were amazed by its capabilities and wondered if it could replace designers and developers. This article will use ChatGPT to answer a specific query.
Can ChatGPT build an entire iOS app?
This post will use ChatGPT to construct an iOS meditation app. Video of the article is available.
App concepts for meditation
After deciding on an app, think about the user experience. What should the app offer?
Let's ask ChatGPT for the answer.
ChatGPT described a solid meditation app with various exercises. Use this list to plan product design. Our first product iteration will have few features. A simple, one-screen software will let users set the timeframe and play music during meditation.
Structure of information
Information architecture underpins product design. Our app's navigation mechanism should be founded on strong information architecture, so we need to identify our mobile's screens first.
ChatGPT can define our future app's information architecture since we already know it.
ChatGPT uses the more complicated product's structure. When adding features to future versions of our product, keep this information picture in mind.
Color palette
Meditation apps need colors. We want to employ relaxing colors in a meditation app because colors affect how we perceive items. ChatGPT can suggest product colors.
See the hues in person:
Neutral colors dominate the color scheme. Playing with color opacity makes this scheme useful.
Ambiance music
Meditation involves music. Well-chosen music calms the user.
Let ChatGPT make music for us.
ChatGPT can only generate text. It directs us to Spotify or YouTube to look for such stuff and makes precise recommendations.
Fonts
Fonts can impress app users. Round fonts are easier on the eyes and make a meditation app look friendlier.
ChatGPT can suggest app typefaces. I compare two font pairs when making a product. I'll ask ChatGPT for two font pairs.
See the hues in person:
Despite ChatGPT's convincing font pairing arguments, the output is unattractive. The initial combo (Open Sans + Playfair Display) doesn't seem to work well for a mediation app.
Content
Meditation requires the script. Find the correct words and read them calmly and soothingly to help listeners relax and focus on each region of their body to enhance the exercise's effect.
ChatGPT's offerings:
ChatGPT outputs code. My prompt's word script may cause it.
Timer
After fonts, colors, and content, construct functional pieces. Timer is our first functional piece. The meditation will be timed.
Let ChatGPT write Swift timer code (since were building an iOS app, we need to do it using Swift language).
ChatGPT supplied a timer class, initializer, and usage guidelines.
Apple Xcode requires a playground to test this code. Xcode will report issues after we paste the code to the playground.
Fixing them is simple. Just change Timer to another class name (Xcode shows errors because it thinks that we access the properties of the class we’ve created rather than the system class Timer; it happens because both classes have the same name Timer). I titled our class Timero and implemented the project. After this quick patch, ChatGPT's code works.
Can ChatGPT produce a complete app?
Since ChatGPT can help us construct app components, we may question if it can write a full app in one go.
Question ChatGPT:
ChatGPT supplied basic code and instructions. It's unclear if ChatGPT purposely limits output or if my prompt wasn't good enough, but the tool cannot produce an entire app from a single prompt.
However, we can contact ChatGPT for thorough Swift app construction instructions.
We can ask ChatGPT for step-by-step instructions now that we know what to do. Request a basic app layout from ChatGPT.
Copying this code to an Xcode project generates a functioning layout.
Takeaways
ChatGPT may provide step-by-step instructions on how to develop an app for a specific system, and individual steps can be utilized as prompts to ChatGPT. ChatGPT cannot generate the source code for the full program in one go.
The output that ChatGPT produces needs to be examined by a human. The majority of the time, you will need to polish or adjust ChatGPT's output, whether you develop a color scheme or a layout for the iOS app.
ChatGPT is unable to produce media material. Although ChatGPT cannot be used to produce images or sounds, it can assist you build prompts for programs like midjourney or Dalle-2 so that they can provide the appropriate images for you.

Gajus Kuizinas
3 years ago
How a few lines of code were able to eliminate a few million queries from the database
I was entering tens of millions of records per hour when I first published Slonik PostgreSQL client for Node.js. The data being entered was usually flat, making it straightforward to use INSERT INTO ... SELECT * FROM unnset() pattern. I advocated the unnest approach for inserting rows in groups (that was part I).
However, today I’ve found a better way: jsonb_to_recordset.
jsonb_to_recordsetexpands the top-level JSON array of objects to a set of rows having the composite type defined by an AS clause.
jsonb_to_recordset allows us to query and insert records from arbitrary JSON, like unnest. Since we're giving JSON to PostgreSQL instead of unnest, the final format is more expressive and powerful.
SELECT *
FROM json_to_recordset('[{"name":"John","tags":["foo","bar"]},{"name":"Jane","tags":["baz"]}]')
AS t1(name text, tags text[]);
name | tags
------+-----------
John | {foo,bar}
Jane | {baz}
(2 rows)Let’s demonstrate how you would use it to insert data.
Inserting data using json_to_recordset
Say you need to insert a list of people with attributes into the database.
const persons = [
{
name: 'John',
tags: ['foo', 'bar']
},
{
name: 'Jane',
tags: ['baz']
}
];You may be tempted to traverse through the array and insert each record separately, e.g.
for (const person of persons) {
await pool.query(sql`
INSERT INTO person (name, tags)
VALUES (
${person.name},
${sql.array(person.tags, 'text[]')}
)
`);
}It's easier to read and grasp when working with a few records. If you're like me and troubleshoot a 2M+ insert query per day, batching inserts may be beneficial.
What prompted the search for better alternatives.
Inserting using unnest pattern might look like this:
await pool.query(sql`
INSERT INTO public.person (name, tags)
SELECT t1.name, t1.tags::text[]
FROM unnest(
${sql.array(['John', 'Jane'], 'text')},
${sql.array(['{foo,bar}', '{baz}'], 'text')}
) AS t1.(name, tags);
`);You must convert arrays into PostgreSQL array strings and provide them as text arguments, which is unsightly. Iterating the array to create slices for each column is likewise unattractive.
However, with jsonb_to_recordset, we can:
await pool.query(sql`
INSERT INTO person (name, tags)
SELECT *
FROM jsonb_to_recordset(${sql.jsonb(persons)}) AS t(name text, tags text[])
`);In contrast to the unnest approach, using jsonb_to_recordset we can easily insert complex nested data structures, and we can pass the original JSON document to the query without needing to manipulate it.
In terms of performance they are also exactly the same. As such, my current recommendation is to prefer jsonb_to_recordset whenever inserting lots of rows or nested data structures.

Paul DelSignore
2 years ago
The stunning new free AI image tool is called Leonardo AI.
Leonardo—The New Midjourney?
Users are comparing the new cowboy to Midjourney.
Leonardo.AI creates great photographs and has several unique capabilities I haven't seen in other AI image systems.
Midjourney's quality photographs are evident in the community feed.
Create Pictures Using Models
You can make graphics using platform models when you first enter the app (website):
Luma, Leonardo creative, Deliberate 1.1.
Clicking a model displays its description and samples:
Click Generate With This Model.
Then you can add your prompt, alter models, photos, sizes, and guide scale in a sleek UI.
Changing Pictures
Leonardo's Canvas editor lets you change created images by hovering over them:
The editor opens with masking, erasing, and picture download.
Develop Your Own Models
I've never seen anything like Leonardo's model training feature.
Upload a handful of similar photographs and save them as a model for future images. Share your model with the community.
You can make photos using your own model and a community-shared set of fine-tuned models:
Obtain Leonardo access
Leonardo is currently free.
Visit Leonardo.ai and click "Get Early Access" to receive access.
Add your email to receive a link to join the discord channel. Simply describe yourself and fill out a form to join the discord channel.
Please go to 👑│introductions to make an introduction and ✨│priority-early-access will be unlocked, you must fill out a form and in 24 hours or a little more (due to demand), the invitation will be sent to you by email.
I got access in two hours, so hopefully you can too.
Last Words
I know there are many AI generative platforms, some free and some expensive, but Midjourney produces the most artistically stunning images and art.
Leonardo is the closest I've seen to Midjourney, but Midjourney is still the leader.
It's free now.
Leonardo's fine-tuned model selections, model creation, image manipulation, and output speed and quality make it a great AI image toolbox addition.
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Jayden Levitt
2 years ago
Billionaire who was disgraced lost his wealth more quickly than anyone in history
If you're not genuine, you'll be revealed.
Sam Bankman-Fried (SBF) was called the Cryptocurrency Warren Buffet.
No wonder.
SBF's trading expertise, Blockchain knowledge, and ability to construct FTX attracted mainstream investors.
He had a fantastic worldview, donating much of his riches to charity.
As the onion layers peel back, it's clear he wasn't the altruistic media figure he portrayed.
SBF's mistakes were disastrous.
Customer deposits were traded and borrowed by him.
With ten other employees, he shared a $40 million mansion where they all had polyamorous relationships.
Tone-deaf and wasteful marketing expenditures, such as the $200 million spent to change the name of the Miami Heat stadium to the FTX Arena
Democrats received a $40 million campaign gift.
And now there seems to be no regret.
FTX was a 32-billion-dollar cryptocurrency exchange.
It went bankrupt practically overnight.
SBF, FTX's creator, exploited client funds to leverage trade.
FTX had $1 billion in customer withdrawal reserves against $9 billion in liabilities in sister business Alameda Research.
Bloomberg Billionaire Index says it's the largest and fastest net worth loss in history.
It gets worse.
SBF's net worth is $900 Million, however he must still finalize FTX's bankruptcy.
SBF's arrest in the Bahamas and SEC inquiry followed news that his cryptocurrency exchange had crashed, losing billions in customer deposits.
A journalist contacted him on Twitter D.M., and their exchange is telling.
His ideas are revealed.
Kelsey Piper says they didn't expect him to answer because people under investigation don't comment.
Bankman-Fried wanted to communicate, and the interaction shows he has little remorse.
SBF talks honestly about FTX gaming customers' money and insults his competition.
Reporter Kelsey Piper was outraged by what he said and felt the mistakes SBF says plague him didn't evident in the messages.
Before FTX's crash, SBF was a poster child for Cryptocurrency regulation and avoided criticizing U.S. regulators.
He tells Piper that his lobbying is just excellent PR.
It shows his genuine views and supports cynics' opinions that his attempts to win over U.S. authorities were good for his image rather than Crypto.
SBF’s responses are in Grey, and Pipers are in Blue.
It's unclear if SBF cut corners for his gain. In their Twitter exchange, Piper revisits an interview question about ethics.
SBF says, "All the foolish sh*t I said"
SBF claims FTX has never invested customer monies.
Piper challenged him on Twitter.
While he insisted FTX didn't use customer deposits, he said sibling business Alameda borrowed too much from FTX's balance sheet.
He did, basically.
When consumers tried to withdraw money, FTX was short.
SBF thought Alameda had enough money to cover FTX customers' withdrawals, but life sneaks up on you.
SBF believes most exchanges have done something similar to FTX, but they haven't had a bank run (a bunch of people all wanting to get their deposits out at the same time).
SBF believes he shouldn't have consented to the bankruptcy and kept attempting to raise more money because withdrawals would be open in a month with clients whole.
If additional money came in, he needed $8 billion to bridge the creditors' deficit, and there aren't many corporations with $8 billion to spare.
Once clients feel protected, they will continue to leave their assets on the exchange, according to one idea.
Kevin OLeary, a world-renowned hedge fund manager, says not all investors will walk through the open gate once the company is safe, therefore the $8 Billion wasn't needed immediately.
SBF claims the bankruptcy was his biggest error because he could have accumulated more capital.
Final Reflections
Sam Bankman-Fried, 30, became the world's youngest billionaire in four years.
Never listen to what people say about investing; watch what they do.
SBF is a trader who gets wrecked occasionally.
Ten first-time entrepreneurs ran FTX, screwing each other with no risk management.
It prevents opposing or challenging perspectives and echo chamber highs.
Twitter D.M. conversation with a journalist is the final nail.
He lacks an experienced crew.
This event will surely speed up much-needed regulation.
It's also prompted cryptocurrency exchanges to offer proof of reserves to calm customers.

Hasan AboulHasan
3 years ago
High attachment products can help you earn money automatically.
Affiliate marketing is a popular online moneymaker. You promote others' products and get commissions. Affiliate marketing requires constant product promotion.
Affiliate marketing can be profitable even without much promotion. Yes, this is Autopilot Money.
How to Pick an Affiliate Program to Generate Income Autonomously
Autopilot moneymaking requires a recurring affiliate marketing program.
Finding the best product and testing it takes a lot of time and effort.
Here are three ways to choose the best service or product to promote:
Find a good attachment-rate product or service.
When choosing a product, ask if you can easily switch to another service. Attachment rate is how much people like a product.
Higher attachment rates mean better Autopilot products.
Consider promoting GetResponse. It's a 33% recurring commission email marketing tool. This means you get 33% of the customer's plan as long as he pays.
GetResponse has a high attachment rate because it's hard to leave and start over with another tool.
2. Pick a good or service with a lot of affiliate assets.
Check if a program has affiliate assets or creatives before joining.
Images and banners to promote the product in your business.
They save time; I look for promotional creatives. Creatives or affiliate assets are website banners or images. This reduces design time.
3. Select a service or item that consumers already adore.
New products are hard to sell. Choosing a trusted company's popular product or service is helpful.
As a beginner, let people buy a product they already love.
Online entrepreneurs and digital marketers love Systeme.io. It offers tools for creating pages, email marketing, funnels, and more. This product guarantees a high ROI.
Make the product known!
Affiliate marketers struggle to get traffic. Using affiliate marketing to make money is easier than you think if you have a solid marketing strategy.
Your plan should include:
1- Publish affiliate-related blog posts and SEO-optimize them
2- Sending new visitors product-related emails
3- Create a product resource page.
4-Review products
5-Make YouTube videos with links in the description.
6- Answering FAQs about your products and services on your blog and Quora.
7- Create an eCourse on how to use this product.
8- Adding Affiliate Banners to Your Website.
With these tips, you can promote your products and make money on autopilot.

middlemarch.eth
3 years ago
ERC721R: A new ERC721 contract for random minting so people don’t snipe all the rares!
That is, how to snipe all the rares without using ERC721R!
Introduction: Blessed and Lucky
Mphers was the first mfers derivative, and as a Phunks derivative, I wanted one.
I wanted an alien. And there are only 8 in the 6,969 collection. I got one!
In case it wasn't clear from the tweet, I meant that I was lucky to have figured out how to 100% guarantee I'd get an alien without any extra luck.
Read on to find out how I did it, how you can too, and how developers can avoid it!
How to make rare NFTs without luck.
# How to mint rare NFTs without needing luck
The key to minting a rare NFT is knowing the token's id ahead of time.
For example, once I knew my alien was #4002, I simply refreshed the mint page until #3992 was minted, and then mint 10 mphers.
How did I know #4002 was extraterrestrial? Let's go back.
First, go to the mpher contract's Etherscan page and look up the tokenURI of a previously issued token, token #1:
As you can see, mphers creates metadata URIs by combining the token id and an IPFS hash.
This method gives you the collection's provenance in every URI, and while that URI can be changed, it affects everyone and is public.
Consider a token URI without a provenance hash, like https://mphers.art/api?tokenId=1.
As a collector, you couldn't be sure the devs weren't changing #1's metadata at will.
The API allows you to specify “if #4002 has not been minted, do not show any information about it”, whereas IPFS does not allow this.
It's possible to look up the metadata of any token, whether or not it's been minted.
Simply replace the trailing “1” with your desired id.
Mpher #4002
These files contain all the information about the mpher with the specified id. For my alien, we simply search all metadata files for the string “alien mpher.”
Take a look at the 6,969 meta-data files I'm using OpenSea's IPFS gateway, but you could use ipfs.io or something else.
Use curl to download ten files at once. Downloading thousands of files quickly can lead to duplicates or errors. But with a little tweaking, you should be able to get everything (and dupes are fine for our purposes).
Now that you have everything in one place, grep for aliens:
The numbers are the file names that contain “alien mpher” and thus the aliens' ids.
The entire process takes under ten minutes. This technique works on many NFTs currently minting.
In practice, manually minting at the right time to get the alien is difficult, especially when tokens mint quickly. Then write a bot to poll totalSupply() every second and submit the mint transaction at the exact right time.
You could even look for the token you need in the mempool before it is minted, and get your mint into the same block!
However, in my experience, the “big” approach wins 95% of the time—but not 100%.
“Am I being set up all along?”
Is a question you might ask yourself if you're new to this.
It's disheartening to think you had no chance of minting anything that someone else wanted.
But, did you have no opportunity? You had an equal chance as everyone else!
Take me, for instance: I figured this out using open-source tools and free public information. Anyone can do this, and not understanding how a contract works before minting will lead to much worse issues.
The mpher mint was fair.
While a fair game, “snipe the alien” may not have been everyone's cup of tea.
People may have had more fun playing the “mint lottery” where tokens were distributed at random and no one could gain an advantage over someone simply clicking the “mint” button.
How might we proceed?
Minting For Fashion Hats Punks, I wanted to create a random minting experience without sacrificing fairness. In my opinion, a predictable mint beats an unfair one. Above all, participants must be equal.
Sadly, the most common method of creating a random experience—the post-mint “reveal”—is deeply unfair. It works as follows:
- During the mint, token metadata is unavailable. Instead, tokenURI() returns a blank JSON file for each id.
- An IPFS hash is updated once all tokens are minted.
- You can't tell how the contract owner chose which token ids got which metadata, so it appears random.
Because they alone decide who gets what, the person setting the metadata clearly has a huge unfair advantage over the people minting. Unlike the mpher mint, you have no chance of winning here.
But what if it's a well-known, trusted, doxxed dev team? Are reveals okay here?
No! No one should be trusted with such power. Even if someone isn't consciously trying to cheat, they have unconscious biases. They might also make a mistake and not realize it until it's too late, for example.
You should also not trust yourself. Imagine doing a reveal, thinking you did it correctly (nothing is 100%! ), and getting the rarest NFT. Isn't that a tad odd Do you think you deserve it? An NFT developer like myself would hate to be in this situation.
Reveals are bad*
UNLESS they are done without trust, meaning everyone can verify their fairness without relying on the developers (which you should never do).
An on-chain reveal powered by randomness that is verifiably outside of anyone's control is the most common way to achieve a trustless reveal (e.g., through Chainlink).
Tubby Cats did an excellent job on this reveal, and I highly recommend their contract and launch reflections. Their reveal was also cool because it was progressive—you didn't have to wait until the end of the mint to find out.
In his post-launch reflections, @DefiLlama stated that he made the contract as trustless as possible, removing as much trust as possible from the team.
In my opinion, everyone should know the rules of the game and trust that they will not be changed mid-stream, while trust minimization is critical because smart contracts were designed to reduce trust (and it makes it impossible to hack even if the team is compromised). This was a huge mistake because it limited our flexibility and our ability to correct mistakes.
And @DefiLlama is a superstar developer. Imagine how much stress maximizing trustlessness will cause you!
That leaves me with a bad solution that works in 99 percent of cases and is much easier to implement: random token assignments.
Introducing ERC721R: A fully compliant IERC721 implementation that picks token ids at random.
ERC721R implements the opposite of a reveal: we mint token ids randomly and assign metadata deterministically.
This allows us to reveal all metadata prior to minting while reducing snipe chances.
Then import the contract and use this code:
What is ERC721R and how does it work
First, a disclaimer: ERC721R isn't truly random. In this sense, it creates the same “game” as the mpher situation, where minters compete to exploit the mint. However, ERC721R is a much more difficult game.
To game ERC721R, you need to be able to predict a hash value using these inputs:
This is impossible for a normal person because it requires knowledge of the block timestamp of your mint, which you do not have.
To do this, a miner must set the timestamp to a value in the future, and whatever they do is dependent on the previous block's hash, which expires in about ten seconds when the next block is mined.
This pseudo-randomness is “good enough,” but if big money is involved, it will be gamed. Of course, the system it replaces—predictable minting—can be manipulated.
The token id is chosen in a clever implementation of the Fisher–Yates shuffle algorithm that I copied from CryptoPhunksV2.
Consider first the naive solution: (a 10,000 item collection is assumed):
- Make an array with 0–9999.
- To create a token, pick a random item from the array and use that as the token's id.
- Remove that value from the array and shorten it by one so that every index corresponds to an available token id.
This works, but it uses too much gas because changing an array's length and storing a large array of non-zero values is expensive.
How do we avoid them both? What if we started with a cheap 10,000-zero array? Let's assign an id to each index in that array.
Assume we pick index #6500 at random—#6500 is our token id, and we replace the 0 with a 1.
But what if we chose #6500 again? A 1 would indicate #6500 was taken, but then what? We can't just "roll again" because gas will be unpredictable and high, especially later mints.
This allows us to pick a token id 100% of the time without having to keep a separate list. Here's how it works:
- Make a 10,000 0 array.
- Create a 10,000 uint numAvailableTokens.
- Pick a number between 0 and numAvailableTokens. -1
- Think of #6500—look at index #6500. If it's 0, the next token id is #6500. If not, the value at index #6500 is your next token id (weird!)
- Examine the array's last value, numAvailableTokens — 1. If it's 0, move the value at #6500 to the end of the array (#9999 if it's the first token). If the array's last value is not zero, update index #6500 to store it.
- numAvailableTokens is decreased by 1.
- Repeat 3–6 for the next token id.
So there you go! The array stays the same size, but we can choose an available id reliably. The Solidity code is as follows:
Unfortunately, this algorithm uses more gas than the leading sequential mint solution, ERC721A.
This is most noticeable when minting multiple tokens in one transaction—a 10 token mint on ERC721R costs 5x more than on ERC721A. That said, ERC721A has been optimized much further than ERC721R so there is probably room for improvement.
Conclusion
Listed below are your options:
- ERC721A: Minters pay lower gas but must spend time and energy devising and executing a competitive minting strategy or be comfortable with worse minting results.
- ERC721R: Higher gas, but the easy minting strategy of just clicking the button is optimal in all but the most extreme cases. If miners game ERC721R it’s the worst of both worlds: higher gas and a ton of work to compete.
- ERC721A + standard reveal: Low gas, but not verifiably fair. Please do not do this!
- ERC721A + trustless reveal: The best solution if done correctly, highly-challenging for dev, potential for difficult-to-correct errors.
Did I miss something? Comment or tweet me @dumbnamenumbers.
Check out the code on GitHub to learn more! Pull requests are welcome—I'm sure I've missed many gas-saving opportunities.
Thanks!
Read the original post here
