More on Technology
CyberPunkMetalHead
2 years ago
I made ChatGPT copy itself.
OpenAI's ChatGPT is an amazing AI-powered chatbot. It can write poetry, stories, and marketing campaigns, and it's also adept at coding. ChatGPT's coding is so amazing that it replicated itself. What happened:
Me: Hi
Hello! Can I help? I'll answer any inquiries you have.
Me: Build a python and flask AI chatbot that responds to user messages on the frontend.
CGPT:
from flask import Flask, request, jsonify
import openai
openai.api_key = "YOUR_API_KEY"
@app.route('/chatbot', methods=['POST'])
def chatbot():
user_message = request.get_json()['message']
response = chatbot_response(user_message)
return jsonify({'response': response})
def chatbot_response(user_message):
response = openai.Completion.create(
engine="text-davinci-002",
prompt=user_message,
max_tokens=1024,
n = 1,
temperature=0.5
)
return response['choices'][0]['text']
if __name__ == '__main__':
app.run()To integrate a chatbot with a frontend, use Flask to serve an HTML page with a form for user messages and the chatbot's answer. AJAX can submit the form to the /chatbot route, and JavaScript can show the chatbot's response.
I imported code snippets at the top of the file.
Let's add a frontend interface, I said.
CGPT:
<!DOCTYPE html>
<html>
<head>
<title>AI Chatbot</title>
</head>
<body>
<h1>AI Chatbot</h1>
<form id="chatbot-form">
<label for="message">Message:</label><br>
<input type="text" id="message" name="message"><br>
<input type="submit" value="Submit">
</form>
<div id="chatbot-response"></div>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.5.1/jquery.min.js"></script>
<script>
$(document).ready(function() {
$("#chatbot-form").submit(function(e) {
e.preventDefault();
var userMessage = $("#message").val();
$.ajax({
type: "POST",
url: "/chatbot",
data: JSON.stringify({message: userMessage}),
contentType: "application/json; charset=utf-8",
dataType: "json",
success: function(response) {
$("#chatbot-response").text(response.response);
}
});
});
});
</script>
</body>
</html>To serve this HTML page using Flask, build a new route that returns the page as a GET response.
So far, so good.
Looked quite basic so I got chatGPT to add some tailwind to the project.
Me: Tailwind the chatbot.html page, please. Give it a futuristic style with purple and neon
After a few more prompts, Talk GPT aligned the form to the center, changed some colors, and added padding.
CGPT:
<!DOCTYPE html>
<html>
<head>
<title>AI Chatbot</title>
<link href="https://unpkg.com/tailwindcss@^1.0/dist/tailwind.min.css" rel="stylesheet">
</head>
<body class="bg-black flex flex-col justify-center items-center">
<h1 class="sm:text-center text-purple-500">AI Chatbot</h1>
<form id="chatbot-form" class="border-purple-500 bg-purple-800 rounded">
<label for="message">Message:</label><br>
<input type="text" id="message" name="message" class="min-w-30 rounded"><br>
<input type="submit" value="Submit" class="bg-purple-500 border-red-500 transform hover:scale-110 rounded">
</form>
<div class="flex justify-center">
<div id="chatbot-response" class="text-white rounded"></div>
</div>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.5.1/jquery.min.js"></script>
<script>
var colors = ['red', 'orange', 'yellow', 'green', 'blue', 'indigo', 'violet'];
var colorIndex = 0;
$(document).ready(function() {
setInterval(function() {
$("#chatbot-form").css('border-color', colors[colorIndex]);
colorIndex = (colorIndex + 1) % colors.length;
}, 1000);
$("#chatbot-form").submit(function(e) {
e.preventDefault();
var userMessage = $("#message").val();
$.ajax({
type: "POST",
url: "/chatbot",
data: JSON.stringify({message: userMessage}),
contentType: "application/json; charset=utf-8",
dataType: "json",
success: function(response) {
$("#chatbot-response").text(response.response);
}
});
});
});
</script>
</body>
</html>Improved:
A few more prompts like “Add more vertical and horizontal padding to the submit button and vertical margin, and vertically align this file's body.”
The result:
Is it effective? Now, I'll chat with ChatGPT's AI Chatbot. I intervened minimally throughout construction. Chat GPT created numerous files, connected and interacted with its own API, and presented the user request response on the front end by itself.
Me to AI Chatbot: Hey, can you give me 6 name suggestions for a black horse?
Me to AI Chatbot: Write a poem in the style of Jim Morrison. Make sure to mention cacti and black holes
ChatGPTs Chatbot:
In the desert night, I am confronted by cacti,
Their arms reaching out, As if to grab me and take me away.
The stars in the sky, Beckon me to come,
To a world of black holes, Where I can be free.
I am in a trance, My body and mind,
In a state of limbo, As I wander the night.
I hear a voice, Calling me to the unknown,
I cannot resist, The lure of the black hole.
The cacti watch, As I take my leave,
To a place of mystery, Where I can find peace.
Of course, the next question I gave it was to build a chatbot!
Me: Build a python and flask AI chatbot that responds to user messages on the frontend.
ChatbotGPTs:
import os from flask
import Flask, request, jsonify
from chatterbot
import ChatBot
from chatterbot.trainers
import ListTrainer
# Create a new chatbot
bot = ChatBot(
"My Bot",
storage_adapter="chatterbot.storage.SQLStorageAdapter",
logic_adapters=[
"chatterbot.logic.BestMatch",
{ "import_path": "chatterbot.logic.BestMatch",
"statement_comparison_function": "chatterbot.comparisons.levenshtein_distance",
"response_selection_method": "chatterbot.response_selection.get_first_response" }
],
database_uri="sqlite:///database.sqlite3" )
# Train the chatbot with a few sample conversations
conversation = [ "Hello", "Hi there!", "How are you doing?", "I'm doing great.", "That is good to hear", "Thank you.", "You're welcome." ]
trainer = ListTrainer(bot) trainer.train(conversation)
# Create a Flask app
app = Flask(__name__)
# Define a route for the default URL
@app.route("/") def index(): return "<h1>Chatbot</h1>"
# Define a route for the /get_response URL
@app.route("/get_response", methods=["POST"])
def get_response():
# Get the user's message
user_message = request.form["user_message"]
# Get the bot's response
bot_response = bot.get_response(user_message)
# Return the bot's response
return str(bot_response)
# Run the Flask
app if __name__ == "__main__": app.run()No matter how many times I tried, the second generation always used chatterbot instead of the ChatGPT API. Even when I told it to use the ChatGPT API, it didn't.
ChatGTP's ability to reproduce or construct other machine learning algorithms is interesting and possibly terrifying. Nothing prevents ChatGPT from replicating itself ad infinitum throughout the Internet other than a lack of desire. This may be the first time a machine repeats itself, so I've preserved the project as a reference. Adding a requirements.txt file and python env for easier deployment is the only change to the code.
I hope you enjoyed this.
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.
Nikhil Vemu
2 years ago
7 Mac Apps That Are Exorbitantly Priced But Totally Worth It
Wish you more bang for your buck
By ‘Cost a Bomb’ I didn’t mean to exaggerate. It’s an idiom that means ‘To be very expensive’. In fact, no app on the planet costs a bomb lol.
So, to the point.
Chronicle
(Freemium. For Pro, $24.99 | Available on Setapp)
You probably have trouble keeping track of dozens of bills and subscriptions each month.
Try Chronicle.
Easy-to-use app
Add payment due dates and receive reminders,
Save payment documentation,
Analyze your spending by season, year, and month.
Observe expenditure trends and create new budgets.
Best of all, Chronicle features an integrated browser for fast payment and logging.
iOS and macOS sync.
SoundSource
($39 for lifetime)
Background Music, a free macOS program, was featured in #6 of this post last month.
It controls per-app volume, stereo balance, and audio over its max level.
Background Music is fully supported. Additionally,
Connect various speakers to various apps (Wow! ),
change the audio sample rate for each app,
To facilitate access, add a floating SoundSource window.
Use its blocks in Shortcuts app,
On the menu bar, include meters for output/input devices and running programs.
PixelSnap
($39 for lifetime | Available on Setapp)
This software is heaven for UI designers.
It aids you.
quickly calculate screen distances (in pixels) ,
Drag an area around an object to determine its borders,
Measure the distances between the additional guides,
screenshots should be pixel-perfect.
What’s more.
You can
Adapt your tolerance for items with poor contrast and shadows.
Use your Touch Bar to perform important tasks, if you have one.
Mate Translation
($3.99 a month / $29.99 a year | Available on Setapp)
Mate Translate resembles a roided-up version of BarTranslate, which I wrote about in #1 of this piece last month.
If you translate often, utilize Mate Translate on macOS and Safari.
I'm really vocal about it.
It stays on the menu bar, and is accessible with a click or ⌥+shift+T hotkey.
It lets you
Translate in 103 different languages,
To translate text, double-click or right-click on it.
Totally translate websites. Additionally, Netflix subtitles,
Listen to their pronunciation to see how close it is to human.
iPhone and Mac sync Mate-ing history.
Swish
($16 for lifetime | Available on Setapp)
Swish is awesome!
Swipe, squeeze, tap, and hold movements organize chaotic desktop windows. Swish operates with mouse and trackpad.
Some gestures:
• Pinch Once: Close an app
• Pinch Twice: Quit an app
• Swipe down once: Minimise an app
• Pinch Out: Enter fullscreen mode
• Tap, Hold, & Swipe: Arrange apps in grids
and many more...
After getting acquainted to the movements, your multitasking will improve.
Unite
($24.99 for lifetime | Available on Setapp)
It turns webapps into macOS apps. The end.
Unite's functionality is a million times better.
Provide extensive customization (incl. its icon, light and dark modes)
make menu bar applications,
Get badges for web notifications and automatically refresh websites,
Replace any dock icon in the window with it (Wow!) by selecting that portion of the window.
Use PiP (Picture-in-Picture) on video sites that support it.
Delete advertising,
Throughout macOS, use floating windows
and many more…
I feel $24.99 one-off for this tool is a great deal, considering all these features. What do you think?
CleanShot X
(Basic: $29 one-off. Pro: $8/month | Available on Setapp)
CleanShot X can achieve things the macOS screenshot tool cannot. Complete screenshot toolkit.
CleanShot X, like Pixel Snap 2 (#3), is fantastic.
Allows
Scroll to capture a long page,
screen recording,
With webcam on,
• With mic and system audio,
• Highlighting mouse clicks and hotkeys.
Maintain floating screenshots for reference
While capturing, conceal desktop icons and notifications.
Recognize text in screenshots (OCR),
You may upload and share screenshots using the built-in cloud.
These are just 6 in 50+ features, and you’re already saying Wow!
You might also like
Esteban
3 years ago
The Berkus Startup Valuation Method: What Is It?
What Is That?
Berkus is a pre-revenue valuation method based exclusively on qualitative criteria, like Scorecard.
Few firms match their financial estimates, especially in the early stages, so valuation methodologies like the Berkus method are a good way to establish a valuation when the economic measures are not reliable.
How does it work?
This technique evaluates five key success factors.
Fundamental principle
Technology
Execution
Strategic alliances in its primary market
Production, followed by sales
The Berkus technique values the business idea and four success factors. As seen in the matrix below, each of these dimensions poses a danger to the startup's success.
It assigns $0-$500,000 to each of these beginning regions. This approach enables a maximum $2.5M pre-money valuation.
This approach relies significantly on geography and uses the US as a baseline, as it differs in every country in Europe.
A set of standards for analyzing each dimension individually
Fundamental principle (or strength of the idea)
Ideas are worthless; execution matters. Most of us can relate to seeing a new business open in our area or a startup get funded and thinking, "I had this concept years ago!" Someone did it.
The concept remains. To assess the idea's viability, we must consider several criteria.
The concept's exclusivity It is necessary to protect a product or service's concept using patents and copyrights. Additionally, it must be capable of generating large profits.
Planned growth and growth that goes in a specific direction have a lot of potential, therefore incorporating them into a business is really advantageous.
The ability of a concept to grow A venture's ability to generate scalable revenue is a key factor in its emergence and continuation. A startup needs a scalable idea in order to compete successfully in the market.
The attraction of a business idea to a broad spectrum of people is significantly influenced by the current socio-political climate. Thus, the requirement for the assumption of conformity.
Concept Validation Ideas must go through rigorous testing with a variety of audiences in order to lower risk during the implementation phase.
Technology (Prototype)
This aspect reduces startup's technological risk. How good is the startup prototype when facing cyber threats, GDPR compliance (in Europe), tech stack replication difficulty, etc.?
Execution
Check the management team's efficacy. A potential angel investor must verify the founders' experience and track record with previous ventures. Good leadership is needed to chart a ship's course.
Strategic alliances in its primary market
Existing and new relationships will play a vital role in the development of both B2B and B2C startups. What are the startup's synergies? potential ones?
Production, followed by sales (product rollout)
Startup success depends on its manufacturing and product rollout. It depends on the overall addressable market, the startup's ability to market and sell their product, and their capacity to provide consistent, high-quality support.
Example
We're now founders of EyeCaramba, a machine vision-assisted streaming platform. My imagination always goes to poor puns when naming a startup.
Since we're first-time founders and the Berkus technique depends exclusively on qualitative methods and the evaluator's skill, we ask our angel-investor acquaintance for a pre-money appraisal of EyeCaramba.
Our friend offers us the following table:
Because we're first-time founders, our pal lowered our Execution score. He knows the idea's value and that the gaming industry is red-hot, with worse startup ideas getting funded, therefore he gave the Basic value the highest value (idea).
EyeCaramba's pre-money valuation is $400,000 + $250,000 + $75,000 + $275,000 + $164,000 (1.16M). Good.
References
https://medium.com/humble-ventures/how-angel-investors-value-pre-revenue-startups-part-iii-8271405f0774#:~:text=pre%2Drevenue%20startups.-,Berkus%20Method,potential%20of%20the%20idea%20itself.%E2%80%9D
https://eqvista.com/berkus-valuation-method-for-startups/
https://www.venionaire.com/early-stage-startup-valuation-part-2-the-berkus-method/
Thomas Tcheudjio
3 years ago
If you don't crush these 3 metrics, skip the Series A.
I recently wrote about getting VCs excited about Marketplace start-ups. SaaS founders became envious!
Understanding how people wire tens of millions is the only Series A hack I recommend.
Few people understand the intellectual process behind investing.
VC is risk management.
Series A-focused VCs must cover two risks.
1. Market risk
You need a large market to cross a threshold beyond which you can build defensibilities. Series A VCs underwrite market risk.
They must see you have reached product-market fit (PMF) in a large total addressable market (TAM).
2. Execution risk
When evaluating your growth engine's blitzscaling ability, execution risk arises.
When investors remove operational uncertainty, they profit.
Series A VCs like businesses with derisked revenue streams. Don't raise unless you have a predictable model, pipeline, and growth.
Please beat these 3 metrics before Series A:
Achieve $1.5m ARR in 12-24 months (Market risk)
Above 100% Net Dollar Retention. (Market danger)
Lead Velocity Rate supporting $10m ARR in 2–4 years (Execution risk)
Hit the 3 and you'll raise $10M in 4 months. Discussing 2/3 may take 6–7 months.
If none, don't bother raising and focus on becoming a capital-efficient business (Topics for other posts).
Let's examine these 3 metrics for the brave ones.
1. Lead Velocity Rate supporting €$10m ARR in 2 to 4 years
Last because it's the least discussed. LVR is the most reliable data when evaluating a growth engine, in my opinion.
SaaS allows you to see the future.
Monthly Sales and Sales Pipelines, two predictive KPIs, have poor data quality. Both are lagging indicators, and minor changes can cause huge modeling differences.
Analysts and Associates will trash your forecasts if they're based only on Monthly Sales and Sales Pipeline.
LVR, defined as month-over-month growth in qualified leads, is rock-solid. There's no lag. You can See The Future if you use Qualified Leads and a consistent formula and process to qualify them.
With this metric in your hand, scaling your company turns into an execution play on which VCs are able to perform calculations risk.
2. Above-100% Net Dollar Retention.
Net Dollar Retention is a better-known SaaS health metric than LVR.
Net Dollar Retention measures a SaaS company's ability to retain and upsell customers. Ask what $1 of net new customer spend will be worth in years n+1, n+2, etc.
Depending on the business model, SaaS businesses can increase their share of customers' wallets by increasing users, selling them more products in SaaS-enabled marketplaces, other add-ons, and renewing them at higher price tiers.
If a SaaS company's annualized Net Dollar Retention is less than 75%, there's a problem with the business.
Slack's ARR chart (below) shows how powerful Net Retention is. Layer chart shows how existing customer revenue grows. Slack's S1 shows 171% Net Dollar Retention for 2017–2019.
Slack S-1
3. $1.5m ARR in the last 12-24 months.
According to Point 9, $0.5m-4m in ARR is needed to raise a $5–12m Series A round.
Target at least what you raised in Pre-Seed/Seed. If you've raised $1.5m since launch, don't raise before $1.5m ARR.
Capital efficiency has returned since Covid19. After raising $2m since inception, it's harder to raise $1m in ARR.
P9's 2016-2021 SaaS Funding Napkin
In summary, less than 1% of companies VCs meet get funded. These metrics can help you win.
If there’s demand for it, I’ll do one on direct-to-consumer.
Cheers!
Sam Hickmann
3 years ago
Nomad.xyz got exploited for $190M
Key Takeaways:
Another hack. This time was different. This is a doozy.
Why? Nomad got exploited for $190m. It was crypto's 5th-biggest hack. Ouch.
It wasn't hackers, but random folks. What happened:
A Nomad smart contract flaw was discovered. They couldn't drain the funds at once, so they tried numerous transactions. Rookie!
People noticed and copied the attack.
They just needed to discover a working transaction, substitute the other person's address with theirs, and run it.
In a two-and-a-half-hour attack, $190M was siphoned from Nomad Bridge.
Nomad is a novel approach to blockchain interoperability that leverages an optimistic mechanism to increase the security of cross-chain communication. — nomad.xyz
This hack was permissionless, therefore anyone could participate.
After the fatal blow, people fought over the scraps.
Cross-chain bridges remain a DeFi weakness and exploit target. When they collapse, it's typically total.
$190M...gobbled.
Unbacked assets are hurting Nomad-dependent chains. Moonbeam, EVMOS, and Milkomeda's TVLs dropped.
This incident is every-man-for-himself, although numerous whitehats exploited the issue...
But what triggered the feeding frenzy?
How did so many pick the bones?
After a normal upgrade in June, the bridge's Replica contract was initialized with a severe security issue. The 0x00 address was a trusted root, therefore all messages were valid by default.
After a botched first attempt (costing $350k in gas), the original attacker's exploit tx called process() without first 'proving' its validity.
The process() function executes all cross-chain messages and checks the merkle root of all messages (line 185).
The upgrade caused transactions with a'messages' value of 0 (invalid, according to old logic) to be read by default as 0x00, a trusted root, passing validation as 'proven'
Any process() calls were valid. In reality, a more sophisticated exploiter may have designed a contract to drain the whole bridge.
Copycat attackers simply copied/pasted the same process() function call using Etherscan, substituting their address.
The incident was a wild combination of crowdhacking, whitehat activities, and MEV-bot (Maximal Extractable Value) mayhem.
For example, 🍉🍉🍉. eth stole $4M from the bridge, but claims to be whitehat.
Others stood out for the wrong reasons. Repeat criminal Rari Capital (Artibrum) exploited over $3M in stablecoins, which moved to Tornado Cash.
The top three exploiters (with 95M between them) are:
$47M: 0x56D8B635A7C88Fd1104D23d632AF40c1C3Aac4e3
$40M: 0xBF293D5138a2a1BA407B43672643434C43827179
$8M: 0xB5C55f76f90Cc528B2609109Ca14d8d84593590E
Here's a list of all the exploiters:
The project conducted a Quantstamp audit in June; QSP-19 foreshadowed a similar problem.
The auditor's comments that "We feel the Nomad team misinterpreted the issue" speak to a troubling attitude towards security that the project's "Long-Term Security" plan appears to confirm:
Concerns were raised about the team's response time to a live, public exploit; the team's official acknowledgement came three hours later.
"Removing the Replica contract as owner" stopped the exploit, but it was too late to preserve the cash.
Closed blockchain systems are only as strong as their weakest link.
The Harmony network is in turmoil after its bridge was attacked and lost $100M in late June.
What's next for Nomad's ecosystems?
Moonbeam's TVL is now $135M, EVMOS's is $3M, and Milkomeda's is $20M.
Loss of confidence may do more damage than $190M.
Cross-chain infrastructure is difficult to secure in a new, experimental sector. Bridge attacks can pollute an entire ecosystem or more.
Nomadic liquidity has no permanent home, so consumers will always migrate in pursuit of the "next big thing" and get stung when attentiveness wanes.
DeFi still has easy prey...
Sources: rekt.news & The Milk Road.