More on Technology
CyberPunkMetalHead
3 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.
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.
Duane Michael
3 years ago
Don't Fall Behind: 7 Subjects You Must Understand to Keep Up with Technology
As technology develops, you should stay up to date
You don't want to fall behind, do you? This post covers 7 tech-related things you should know.
You'll learn how to operate your computer (and other electronic devices) like an expert and how to leverage the Internet and social media to create your brand and business. Read on to stay relevant in today's tech-driven environment.
You must learn how to code.
Future-language is coding. It's how we and computers talk. Learn coding to keep ahead.
Try Codecademy or Code School. There are also numerous free courses like Coursera or Udacity, but they take a long time and aren't necessarily self-paced, so it can be challenging to find the time.
Artificial intelligence (AI) will transform all jobs.
Our skillsets must adapt with technology. AI is a must-know topic. AI will revolutionize every employment due to advances in machine learning.
Here are seven AI subjects you must know.
What is artificial intelligence?
How does artificial intelligence work?
What are some examples of AI applications?
How can I use artificial intelligence in my day-to-day life?
What jobs have a high chance of being replaced by artificial intelligence and how can I prepare for this?
Can machines replace humans? What would happen if they did?
How can we manage the social impact of artificial intelligence and automation on human society and individual people?
Blockchain Is Changing the Future
Few of us know how Bitcoin and blockchain technology function or what impact they will have on our lives. Blockchain offers safe, transparent, tamper-proof transactions.
It may alter everything from business to voting. Seven must-know blockchain topics:
Describe blockchain.
How does the blockchain function?
What advantages does blockchain offer?
What possible uses for blockchain are there?
What are the dangers of blockchain technology?
What are my options for using blockchain technology?
What does blockchain technology's future hold?
Cryptocurrencies are here to stay
Cryptocurrencies employ cryptography to safeguard transactions and manage unit creation. Decentralized cryptocurrencies aren't controlled by governments or financial institutions.
Bitcoin, the first cryptocurrency, was launched in 2009. Cryptocurrencies can be bought and sold on decentralized exchanges.
Bitcoin is here to stay.
Bitcoin isn't a fad, despite what some say. Since 2009, Bitcoin's popularity has grown. Bitcoin is worth learning about now. Since 2009, Bitcoin has developed steadily.
With other cryptocurrencies emerging, many people are wondering if Bitcoin still has a bright future. Curiosity is natural. Millions of individuals hope their Bitcoin investments will pay off since they're popular now.
Thankfully, they will. Bitcoin is still running strong a decade after its birth. Here's why.
The Internet of Things (IoT) is no longer just a trendy term.
IoT consists of internet-connected physical items. These items can share data. IoT is young but developing fast.
20 billion IoT-connected devices are expected by 2023. So much data! All IT teams must keep up with quickly expanding technologies. Four must-know IoT topics:
Recognize the fundamentals: Priorities first! Before diving into more technical lingo, you should have a fundamental understanding of what an IoT system is. Before exploring how something works, it's crucial to understand what you're working with.
Recognize Security: Security does not stand still, even as technology advances at a dizzying pace. As IT professionals, it is our duty to be aware of the ways in which our systems are susceptible to intrusion and to ensure that the necessary precautions are taken to protect them.
Be able to discuss cloud computing: The cloud has seen various modifications over the past several years once again. The use of cloud computing is also continually changing. Knowing what kind of cloud computing your firm or clients utilize will enable you to make the appropriate recommendations.
Bring Your Own Device (BYOD)/Mobile Device Management (MDM) is a topic worth discussing (MDM). The ability of BYOD and MDM rules to lower expenses while boosting productivity among employees who use these services responsibly is a major factor in their continued growth in popularity.
IoT Security is key
As more gadgets connect, they must be secure. IoT security includes securing devices and encrypting data. Seven IoT security must-knows:
fundamental security ideas
Authorization and identification
Cryptography
electronic certificates
electronic signatures
Private key encryption
Public key encryption
Final Thoughts
With so much going on in the globe, it can be hard to stay up with technology. We've produced a list of seven tech must-knows.
You might also like
Tim Denning
3 years ago
I Posted Six Times a Day for 210 Days on Twitter. Here's What Happened.
I'd spend hours composing articles only to find out they were useless. Twitter solved the problem.
Twitter is wrinkled, say critics.
Nope. Writing is different. It won't make sense until you write there.
Twitter is resurgent. People are reading again. 15-second TikToks overloaded our senses.
After nuking my 20,000-follower Twitter account and starting again, I wrote every day for 210 days.
I'll explain.
I came across the strange world of microblogging.
Traditional web writing is filler-heavy.
On Twitter, you must be brief. I played Wordle.
Twitter Threads are the most popular writing format. Like a blog post. It reminds me of the famous broetry posts on LinkedIn a few years ago.
Threads combine tweets into an article.
Sharp, concise sentences
No regard for grammar
As important as the information is how the text looks.
Twitter Threads are like Michael Angelo's David monument. He chipped away at an enormous piece of marble until a man with a big willy appeared.
That's Twitter Threads.
I tried to remove unnecessary layers from several of my Wordpress blog posts. Then I realized something.
Tweeting from scratch is easier and more entertaining. It's quicker and makes you think more concisely.
Superpower: saying much with little words. My long-form writing has improved. My article sentences resemble tweets.
You never know what will happen.
Twitter's subcultures are odd. Best-performing tweets are strange.
Unusual trend: working alone and without telling anyone. It's a rebellion against Instagram influencers who share their every moment.
Early on, random thoughts worked:
My friend’s wife is Ukrainian. Her family are trapped in the warzone. He is devastated. And here I was complaining about my broken garage door. War puts everything in perspective. Today is a day to be grateful for peace.
Documenting what's happening triggers writing. It's not about viral tweets. Helping others matters.
There are numerous anonymous users.
Twitter uses pseudonyms.
You don't matter. On sites like LinkedIn, you must use your real name. Welcome to the Cyberpunk metaverse of Twitter :)
One daily piece of writing is a powerful habit.
Habits build creator careers. Read that again.
Twitter is an easy habit to pick up. If you can't tweet in one sentence, something's wrong. Easy-peasy-japanese.
Not what I tweeted, but my constancy, made the difference.
Daily writing is challenging, especially if your supervisor is on your back. Twitter encourages writing.
Tweets evolved as the foundation of all other material.
During my experiment, I enjoyed Twitter's speed.
Tweets get immediate responses, comments, and feedback. My popular tweets become newspaper headlines. I've also written essays from tweet discussions.
Sometimes the tweet and article were clear. Twitter sometimes helped me overcome writer's block.
I used to spend hours composing big things that had little real-world use.
Twitter helped me. No guessing. Data guides my coverage and validates concepts.
Test ideas on Twitter.
It took some time for my email list to grow.
Subscribers are a writer's lifeblood.
Without them, you're broke and homeless when Mark Zuckerberg tweaks the algorithms for ad dollars. Twitter has three ways to obtain email subscribers:
1. Add a link to your bio.
Twitter allows bio links (LinkedIn now does too). My eBook's landing page is linked. I collect emails there.
2. Start an online newsletter.
Twitter bought newsletter app Revue. They promote what they own.
I just established up a Revue email newsletter. I imported them weekly into my ConvertKit email list.
3. Create Twitter threads and include a link to your email list in the final tweet.
Write Twitter Threads and link the last tweet to your email list (example below).
Initial email subscribers were modest.
Numbers are growing. Twitter provides 25% of my new email subscribers. Some days, 50 people join.
Without them, my writing career is over. I'd be back at a 9-5 job begging for time off to spend with my newborn daughter. Nope.
Collect email addresses or die trying.
As insurance against unsubscribes and Zucks, use a second email list or Discord community.
What I still need to do
Twitter's fun. I'm wiser. I need to enable auto-replies and auto-DMs (direct messages).
This adds another way to attract subscribers. I schedule tweets with Tweet Hunter.
It’s best to go slow. People assume you're an internet marketer if you spam them with click requests.
A human internet marketer is preferable to a robot. My opinion.
210 days on Twitter taught me that. I plan to use the platform until I'm a grandfather unless Elon ruins it.
Jared Heyman
3 years ago
The survival and demise of Y Combinator startups
I've written a lot about Y Combinator's success, but as any startup founder or investor knows, many startups fail.
Rebel Fund invests in the top 5-10% of new Y Combinator startups each year, so we focus on identifying and supporting the most promising technology startups in our ecosystem. Given the power law dynamic and asymmetric risk/return profile of venture capital, we worry more about our successes than our failures. Since the latter still counts, this essay will focus on the proportion of YC startups that fail.
Since YC's launch in 2005, the figure below shows the percentage of active, inactive, and public/acquired YC startups by batch.
As more startups finish, the blue bars (active) decrease significantly. By 12 years, 88% of startups have closed or exited. Only 7% of startups reach resolution each year.
YC startups by status after 12 years:
Half the startups have failed, over one-third have exited, and the rest are still operating.
In venture investing, it's said that failed investments show up before successful ones. This is true for YC startups, but only in their early years.
Below, we only present resolved companies from the first chart. Some companies fail soon after establishment, but after a few years, the inactive vs. public/acquired ratio stabilizes around 55:45. After a few years, a YC firm is roughly as likely to quit as fail, which is better than I imagined.
I prepared this post because Rebel investors regularly question me about YC startup failure rates and how long it takes for them to exit or shut down.
Early-stage venture investors can overlook it because 100x investments matter more than 0x investments.
YC founders can ignore it because it shouldn't matter if many of their peers succeed or fail ;)
Antonio Neto
3 years ago
Should you skip the minimum viable product?
Are MVPs outdated and have no place in modern product culture?
Frank Robinson coined "MVP" in 2001. In the same year as the Agile Manifesto, the first Scrum experiment began. MVPs are old.
The concept was created to solve the waterfall problem at the time.
The market was still sour from the .com bubble. The tech industry needed a new approach. Product and Agile gained popularity because they weren't waterfall.
More than 20 years later, waterfall is dead as dead can be, but we are still talking about MVPs. Does that make sense?
What is an MVP?
Minimum viable product. You probably know that, so I'll be brief:
[…] The MVP fits your company and customer. It's big enough to cause adoption, satisfaction, and sales, but not bloated and risky. It's the product with the highest ROI/risk. […] — Frank Robinson, SyncDev
MVP is a complete product. It's not a prototype. It's your product's first iteration, which you'll improve. It must drive sales and be user-friendly.
At the MVP stage, you should know your product's core value, audience, and price. We are way deep into early adoption territory.
What about all the things that come before?
Modern product discovery
Eric Ries popularized the term with The Lean Startup in 2011. (Ries would work with the concept since 2008, but wide adoption came after the book was released).
Ries' definition of MVP was similar to Robinson's: "Test the market" before releasing anything. Ries never mentioned money, unlike Jobs. His MVP's goal was learning.
“Remove any feature, process, or effort that doesn't directly contribute to learning” — Eric Ries, The Lean Startup
Product has since become more about "what" to build than building it. What started as a learning tool is now a discovery discipline: fake doors, prototyping, lean inception, value proposition canvas, continuous interview, opportunity tree... These are cheap, effective learning tools.
Over time, companies realized that "maximum ROI divided by risk" started with discovery, not the MVP. MVPs are still considered discovery tools. What is the problem with that?
Time to Market vs Product Market Fit
Waterfall's Time to Market is its biggest flaw. Since projects are sliced horizontally rather than vertically, when there is nothing else to be done, it’s not because the product is ready, it’s because no one cares to buy it anymore.
MVPs were originally conceived as a way to cut corners and speed Time to Market by delivering more customer requests after they paid.
Original product development was waterfall-like.
Time to Market defines an optimal, specific window in which value should be delivered. It's impossible to predict how long or how often this window will be open.
Product Market Fit makes this window a "state." You don’t achieve Product Market Fit, you have it… and you may lose it.
Take, for example, Snapchat. They had a great time to market, but lost product-market fit later. They regained product-market fit in 2018 and have grown since.
An MVP couldn't handle this. What should Snapchat do? Launch Snapchat 2 and see what the market was expecting differently from the last time? MVPs are a snapshot in time that may be wrong in two weeks.
MVPs are mini-projects. Instead of spending a lot of time and money on waterfall, you spend less but are still unsure of the results.
MVPs aren't always wrong. When releasing your first product version, consider an MVP.
Minimum viable product became less of a thing on its own and more interchangeable with Alpha Release or V.1 release over time.
Modern discovery technics are more assertive and predictable than the MVP, but clarity comes only when you reach the market.
MVPs aren't the starting point, but they're the best way to validate your product concept.