More on Technology
Monroe Mayfield
2 years ago
CES 2023: A Third Look At Upcoming Trends
Las Vegas hosted CES 2023. This third and last look at CES 2023 previews upcoming consumer electronics trends that will be crucial for market share.
Definitely start with ICT. Qualcomm CEO Cristiano Amon spoke to CNBC from Las Vegas on China's crackdown and the company's automated driving systems for electric vehicles (EV). The business showed a concept car and its latest Snapdragon processor designs, which offer expanded digital interactions through SalesForce-partnered CRM platforms.
Electrification is reviving Michigan's automobile industry. Michigan Local News reports that $14 billion in EV and battery manufacturing investments will benefit the state. The report also revealed that the Strategic Outreach and Attraction Reserve (SOAR) fund had generated roughly $1 billion for the state's automotive sector.
Ars Technica is great for technology, society, and the future. After CES 2023, Jonathan M. Gitlin published How many electric car chargers are enough? Read about EV charging network issues and infrastructure spending. Politics aside, rapid technological advances enable EV charging network expansion in American cities and abroad.
Finally, the UNEP's The Future of Electric Vehicles and Material Resources: A Foresight Brief. Understanding how lithium-ion batteries will affect EV sales is crucial. Climate change affects EVs in various ways, but electrification and mining trends stand out because more EVs demand more energy-intensive metals and rare earths. Areas & Producers has been publishing my electrification and mining trends articles. Follow me if you wish to write for the publication.
The Weekend Brief (TWB) will routinely cover tech, industrials, and global commodities in global markets, including stock markets. Read more about the future of key areas and critical producers of the global economy in Areas & Producers.
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.
Techletters
2 years ago
Using Synthesia, DALL-E 2, and Chat GPT-3, create AI news videos
Combining AIs creates realistic AI News Videos.
Powerful AI tools like Chat GPT-3 are trending. Have you combined AIs?
The 1-minute fake news video below is startlingly realistic. Artificial Intelligence developed NASA's Mars exploration breakthrough video (AI). However, integrating the aforementioned AIs generated it.
AI-generated text for the Chat GPT-3 based on a succinct tagline
DALL-E-2 AI generates an image from a brief slogan.
Artificial intelligence-generated avatar and speech
This article shows how to use and mix the three AIs to make a realistic news video. First, watch the video (1 minute).
Talk GPT-3
Chat GPT-3 is an OpenAI NLP model. It can auto-complete text and produce conversational responses.
Try it at the playground. The AI will write a comprehensive text from a brief tagline. Let's see what the AI generates with "Breakthrough in Mars Project" as the headline.
Amazing. Our tagline matches our complete and realistic text. Fake news can start here.
DALL-E-2
OpenAI's huge transformer-based language model DALL-E-2. Its GPT-3 basis is geared for image generation. It can generate high-quality photos from a brief phrase and create artwork and images of non-existent objects.
DALL-E-2 can create a news video background. We'll use "Breakthrough in Mars project" again. Our AI creates four striking visuals. Last.
Synthesia
Synthesia lets you quickly produce videos with AI avatars and synthetic vocals.
Avatars are first. Rosie it is.
Upload and select DALL-backdrop. E-2's
Copy the Chat GPT-3 content and choose a synthetic voice.
Voice: English (US) Professional.
Finally, we generate and watch or download our video.
Synthesia AI completes the AI video.
Overview & Resources
We used three AIs to make surprisingly realistic NASA Mars breakthrough fake news in this post. Synthesia generates an avatar and a synthetic voice, therefore it may be four AIs.
These AIs created our fake news.
AI-generated text for the Chat GPT-3 based on a succinct tagline
DALL-E-2 AI generates an image from a brief slogan.
Artificial intelligence-generated avatar and speech
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Scott Hickmann
3 years ago Draft
This is a draft
My wallpape
Theresa W. Carey
3 years ago
How Payment for Order Flow (PFOF) Works
What is PFOF?
PFOF is a brokerage firm's compensation for directing orders to different parties for trade execution. The brokerage firm receives fractions of a penny per share for directing the order to a market maker.
Each optionable stock could have thousands of contracts, so market makers dominate options trades. Order flow payments average less than $0.50 per option contract.
Order Flow Payments (PFOF) Explained
The proliferation of exchanges and electronic communication networks has complicated equity and options trading (ECNs) Ironically, Bernard Madoff, the Ponzi schemer, pioneered pay-for-order-flow.
In a December 2000 study on PFOF, the SEC said, "Payment for order flow is a method of transferring trading profits from market making to brokers who route customer orders to specialists for execution."
Given the complexity of trading thousands of stocks on multiple exchanges, market making has grown. Market makers are large firms that specialize in a set of stocks and options, maintaining an inventory of shares and contracts for buyers and sellers. Market makers are paid the bid-ask spread. Spreads have narrowed since 2001, when exchanges switched to decimals. A market maker's ability to play both sides of trades is key to profitability.
Benefits, requirements
A broker receives fees from a third party for order flow, sometimes without a client's knowledge. This invites conflicts of interest and criticism. Regulation NMS from 2005 requires brokers to disclose their policies and financial relationships with market makers.
Your broker must tell you if it's paid to send your orders to specific parties. This must be done at account opening and annually. The firm must disclose whether it participates in payment-for-order-flow and, upon request, every paid order. Brokerage clients can request payment data on specific transactions, but the response takes weeks.
Order flow payments save money. Smaller brokerage firms can benefit from routing orders through market makers and getting paid. This allows brokerage firms to send their orders to another firm to be executed with other orders, reducing costs. The market maker or exchange benefits from additional share volume, so it pays brokerage firms to direct traffic.
Retail investors, who lack bargaining power, may benefit from order-filling competition. Arrangements to steer the business in one direction invite wrongdoing, which can erode investor confidence in financial markets and their players.
Pay-for-order-flow criticism
It has always been controversial. Several firms offering zero-commission trades in the late 1990s routed orders to untrustworthy market makers. During the end of fractional pricing, the smallest stock spread was $0.125. Options spreads widened. Traders found that some of their "free" trades cost them a lot because they weren't getting the best price.
The SEC then studied the issue, focusing on options trades, and nearly decided to ban PFOF. The proliferation of options exchanges narrowed spreads because there was more competition for executing orders. Options market makers said their services provided liquidity. In its conclusion, the report said, "While increased multiple-listing produced immediate economic benefits to investors in the form of narrower quotes and effective spreads, these improvements have been muted with the spread of payment for order flow and internalization."
The SEC allowed payment for order flow to continue to prevent exchanges from gaining monopoly power. What would happen to trades if the practice was outlawed was also unclear. SEC requires brokers to disclose financial arrangements with market makers. Since then, the SEC has watched closely.
2020 Order Flow Payment
Rule 605 and Rule 606 show execution quality and order flow payment statistics on a broker's website. Despite being required by the SEC, these reports can be hard to find. The SEC mandated these reports in 2005, but the format and reporting requirements have changed over the years, most recently in 2018.
Brokers and market makers formed a working group with the Financial Information Forum (FIF) to standardize order execution quality reporting. Only one retail brokerage (Fidelity) and one market maker remain (Two Sigma Securities). FIF notes that the 605/606 reports "do not provide the level of information that allows a retail investor to gauge how well a broker-dealer fills a retail order compared to the NBBO (national best bid or offer’) at the time the order was received by the executing broker-dealer."
In the first quarter of 2020, Rule 606 reporting changed to require brokers to report net payments from market makers for S&P 500 and non-S&P 500 equity trades and options trades. Brokers must disclose payment rates per 100 shares by order type (market orders, marketable limit orders, non-marketable limit orders, and other orders).
Richard Repetto, Managing Director of New York-based Piper Sandler & Co., publishes a report on Rule 606 broker reports. Repetto focused on Charles Schwab, TD Ameritrade, E-TRADE, and Robinhood in Q2 2020. Repetto reported that payment for order flow was higher in the second quarter than the first due to increased trading activity, and that options paid more than equities.
Repetto says PFOF contributions rose overall. Schwab has the lowest options rates, while TD Ameritrade and Robinhood have the highest. Robinhood had the highest equity rating. Repetto assumes Robinhood's ability to charge higher PFOF reflects their order flow profitability and that they receive a fixed rate per spread (vs. a fixed rate per share by the other brokers).
Robinhood's PFOF in equities and options grew the most quarter-over-quarter of the four brokers Piper Sandler analyzed, as did their implied volumes. All four brokers saw higher PFOF rates.
TD Ameritrade took the biggest income hit when cutting trading commissions in fall 2019, and this report shows they're trying to make up the shortfall by routing orders for additional PFOF. Robinhood refuses to disclose trading statistics using the same metrics as the rest of the industry, offering only a vague explanation on their website.
Summary
Payment for order flow has become a major source of revenue as brokers offer no-commission equity (stock and ETF) orders. For retail investors, payment for order flow poses a problem because the brokerage may route orders to a market maker for its own benefit, not the investor's.
Infrequent or small-volume traders may not notice their broker's PFOF practices. Frequent traders and those who trade larger quantities should learn about their broker's order routing system to ensure they're not losing out on price improvement due to a broker prioritizing payment for order flow.
This post is a summary. Read full article here
Julie Plavnik
3 years ago
Why the Creator Economy needs a Web3 upgrade
Looking back into the past can help you understand what's happening today and why.
"Creator economy" conjures up images of originality, sincerity, and passion. Where do Michelangelos and da Vincis push advancement with their gifts without battling for bread and proving themselves posthumously?
Creativity has been as long as humanity, but it's just recently become a new economic paradigm. We even talk about Web3 now.
Let's examine the creative economy's history to better comprehend it. What brought us here? Looking back can help you understand what's happening now.
No yawning, I promise 😉.
Creator Economy's history
Long, uneven transition to creator economy. Let's examine the economic and societal changes that led us there.
1. Agriculture to industry
Mid-18th-century Industrial Revolution led to shift from agriculture to manufacturing. The industrial economy lasted until World War II.
The industrial economy's principal goal was to provide more affordable, accessible commodities.
Unlike today, products were scarce and inaccessible.
To fulfill its goals, industrialization triggered enormous economic changes, moving power from agrarians to manufacturers. Industrialization brought hard work, rivalry, and new ideas connected to production and automation. Creative thinkers focused on that then.
It doesn't mean music, poetry, or painting had no place back then. They weren't top priority. Artists were independent. The creative field wasn't considered a different economic subdivision.
2. The consumer economy
Manufacturers produced more things than consumers desired after World War II. Stuff was no longer scarce.
The economy must make customers want to buy what the market offers.
The consumer economic paradigm supplanted the industrial one. Customers (or consumers) replaced producers as the new economic center.
Salesmen, marketing, and journalists also played key roles (TV, radio, newspapers, etc.). Mass media greatly boosted demand for goods, defined trends, and changed views regarding nearly everything.
Mass media also gave rise to pop culture, which focuses on mass-market creative products. Design, printing, publishing, multi-media, audio-visual, cinematographic productions, etc. supported pop culture.
The consumer paradigm generated creative occupations and activities, unlike the industrial economy. Creativity was limited by the need for wide appeal.
Most creators were corporate employees.
Creating a following and making a living from it were difficult.
Paul Saffo said that only journalists and TV workers were known. Creators who wished to be known relied on producers, publishers, and other gatekeepers. To win their favor was crucial. Luck was the best tactic.
3. The creative economy
Consumer economy was digitized in the 1990s. IT solutions transformed several economic segments. This new digital economy demanded innovative, digital creativity.
Later, states declared innovation a "valuable asset that creates money and jobs." They also introduced the "creative industries" and the "creative economy" (not creator!) and tasked themselves with supporting them. Australia and the UK were early adopters.
Individual skill, innovation, and intellectual property fueled the creative economy. Its span covered design, writing, audio, video material, etc. The creative economy required IT-powered activity.
The new challenge was to introduce innovations to most economic segments and meet demand for digital products and services.
Despite what the title "creative economy" may imply, it was primarily oriented at meeting consumer needs. It didn't provide inventors any new options to become entrepreneurs. Instead of encouraging innovators to flourish on their own, the creative economy emphasized "employment-based creativity."
4. The creator economy
Next, huge IT platforms like Google, Facebook, YouTube, and others competed with traditional mainstream media.
During the 2008 global financial crisis, these mediums surpassed traditional media. People relied on them for information, knowledge, and networking. That was a digital media revolution. The creator economy started there.
The new economic paradigm aimed to engage and convert clients. The creator economy allowed customers to engage, interact, and provide value, unlike the consumer economy. It gave them instruments to promote themselves as "products" and make money.
Writers, singers, painters, and other creators have a great way to reach fans. Instead of appeasing old-fashioned gatekeepers (producers, casting managers, publishers, etc.), they can use the platforms to express their talent and gain admirers. Barriers fell.
It's not only for pros. Everyone with a laptop and internet can now create.
2022 creator economy:
Since there is no academic description for the current creator economy, we can freestyle.
The current (or Web2) creator economy is fueled by interactive digital platforms, marketplaces, and tools that allow users to access, produce, and monetize content.
No entry hurdles or casting in the creative economy. Sign up and follow platforms' rules. Trick: A platform's algorithm aggregates your data and tracks you. This is the payment for participation.
The platforms offer content creation, design, and ad distribution options. This is platforms' main revenue source.
The creator economy opens many avenues for creators to monetize their work. Artists can now earn money through advertising, tipping, brand sponsorship, affiliate links, streaming, and other digital marketing activities.
Even if your content isn't digital, you can utilize platforms to promote it, interact and convert your audience, and more. No limits. However, some of your income always goes to a platform (well, a huge one).
The creator economy aims to empower online entrepreneurship by offering digital marketing tools and reducing impediments.
Barriers remain. They are just different. Next articles will examine these.
Why update the creator economy for Web3?
I could address this question by listing the present creator economy's difficulties that led us to contemplate a Web3 upgrade.
I don't think these difficulties are the main cause. The mentality shift made us see these challenges and understand there was a better reality without them.
Crypto drove this thinking shift. It promoted disintermediation, independence from third-party service providers, 100% data ownership, and self-sovereignty. Crypto has changed the way we view everyday things.
Crypto's disruptive mission has migrated to other economic segments. It's now called Web3. Web3's creator economy is unique.
Here's the essence of the Web3 economy:
Eliminating middlemen between creators and fans.
100% of creators' data, brand, and effort.
Business and money-making transparency.
Authentic originality above ad-driven content.
In the next several articles, I'll explain. We'll also discuss the creator economy and Web3's remedies.
Final thoughts
The creator economy is the organic developmental stage we've reached after all these social and economic transformations.
The Web3 paradigm of the creator economy intends to allow creators to construct their own independent "open economy" and directly monetize it without a third party.
If this approach succeeds, we may enter a new era of wealth creation where producers aren't only the products. New economies will emerge.
This article is a summary. To read the full post, click here.