More on Technology
M.G. Siegler
3 years ago
G3nerative
Generative AI hype: some thoughts
The sudden surge in "generative AI" startups and projects feels like the inverse of the recent "web3" boom. Both came from hyped-up pots. But while web3 hyped idealistic tech and an easy way to make money, generative AI hypes unsettling tech and questions whether it can be used to make money.
Web3 is technology looking for problems to solve, while generative AI is technology creating almost too many solutions. Web3 has been evangelists trying to solve old problems with new technology. As Generative AI evolves, users are resolving old problems in stunning new ways.
It's a jab at web3, but it's true. Web3's hype, including crypto, was unhealthy. Always expected a tech crash and shakeout. Tech that won't look like "web3" but will enhance "web2"
But that doesn't mean AI hype is healthy. There'll be plenty of bullshit here, too. As moths to a flame, hype attracts charlatans. Again, the difference is the different starting point. People want to use it. Try it.
With the beta launch of Dall-E 2 earlier this year, a new class of consumer product took off. Midjourney followed suit (despite having to jump through the Discord server hoops). Twelve more generative art projects. Lensa, Prisma Labs' generative AI self-portrait project, may have topped the hype (a startup which has actually been going after this general space for quite a while). This week, ChatGPT went off-topic.
This has a "fake-it-till-you-make-it" vibe. We give these projects too much credit because they create easy illusions. This also unlocks new forms of creativity. And faith in new possibilities.
As a user, it's thrilling. We're just getting started. These projects are not only fun to play with, but each week brings a new breakthrough. As an investor, it's all happening so fast, with so much hype (and ethical and societal questions), that no one knows how it will turn out. Web3's demand won't be the issue. Too much demand may cause servers to melt down, sending costs soaring. Companies will try to mix rapidly evolving tech to meet user demand and create businesses. Frustratingly difficult.
Anyway, I wanted an excuse to post some Lensa selfies.
These are really weird. I recognize them as me or a version of me, but I have no memory of them being taken. It's surreal, out-of-body. Uncanny Valley.
Jay Peters
3 years ago
Apple AR/VR heaset
Apple is said to have opted for a standalone AR/VR headset over a more powerful tethered model.
It has had a tumultuous history.
Apple's alleged mixed reality headset appears to be the worst-kept secret in tech, and a fresh story from The Information is jam-packed with details regarding the device's rocky development.
Apple's decision to use a separate headgear is one of the most notable aspects of the story. Apple had yet to determine whether to pursue a more powerful VR headset that would be linked with a base station or a standalone headset. According to The Information, Apple officials chose the standalone product over the version with the base station, which had a processor that later arrived as the M1 Ultra. In 2020, Bloomberg published similar information.
That decision appears to have had a long-term impact on the headset's development. "The device's many processors had already been in development for several years by the time the choice was taken, making it impossible to go back to the drawing board and construct, say, a single chip to handle all the headset's responsibilities," The Information stated. "Other difficulties, such as putting 14 cameras on the headset, have given hardware and algorithm engineers stress."
Jony Ive remained to consult on the project's design even after his official departure from Apple, according to the story. Ive "prefers" a wearable battery, such as that offered by Magic Leap. Other prototypes, according to The Information, placed the battery in the headset's headband, and it's unknown which will be used in the final design.
The headset was purportedly shown to Apple's board of directors last week, indicating that a public unveiling is imminent. However, it is possible that it will not be introduced until later this year, and it may not hit shop shelves until 2023, so we may have to wait a bit to try it.
For further down the line, Apple is working on a pair of AR spectacles that appear like Ray-Ban wayfarer sunglasses, but according to The Information, they're "still several years away from release." (I'm interested to see how they compare to Meta and Ray-Bans' true wayfarer-style glasses.)
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.
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Benjamin Lin
3 years ago
I sold my side project for $20,000: 6 lessons I learned
How I monetized and sold an abandoned side project for $20,000
The Origin Story
I've always wanted to be an entrepreneur but never succeeded. I often had business ideas, made a landing page, and told my buddies. Never got customers.
In April 2021, I decided to try again with a new strategy. I noticed that I had trouble acquiring an initial set of customers, so I wanted to start by acquiring a product that had a small user base that I could grow.
I found a SaaS marketplace called MicroAcquire.com where you could buy and sell SaaS products. I liked Shareit.video, an online Loom-like screen recorder.
Shareit.video didn't generate revenue, but 50 people visited daily to record screencasts.
Purchasing a Failed Side Project
I eventually bought Shareit.video for $12,000 from its owner.
$12,000 was probably too much for a website without revenue or registered users.
I thought time was most important. I could have recreated the website, but it would take months. $12,000 would give me an organized code base and a working product with a few users to monetize.
I considered buying a screen recording website and trying to grow it versus buying a new car or investing in crypto with the $12K.
Buying the website would make me a real entrepreneur, which I wanted more than anything.
Putting down so much money would force me to commit to the project and prevent me from quitting too soon.
A Year of Development
I rebranded the website to be called RecordJoy and worked on it with my cousin for about a year. Within a year, we made $5000 and had 3000 users.
We spent $3500 on ads, hosting, and software to run the business.
AppSumo promoted our $120 Life Time Deal in exchange for 30% of the revenue.
We put RecordJoy on maintenance mode after 6 months because we couldn't find a scalable user acquisition channel.
We improved SEO and redesigned our landing page, but nothing worked.
Despite not being able to grow RecordJoy any further, I had already learned so much from working on the project so I was fine with putting it on maintenance mode. RecordJoy still made $500 a month, which was great lunch money.
Getting Taken Over
One of our customers emailed me asking for some feature requests and I replied that we weren’t going to add any more features in the near future. They asked if we'd sell.
We got on a call with the customer and I asked if he would be interested in buying RecordJoy for 15k. The customer wanted around $8k but would consider it.
Since we were negotiating with one buyer, we put RecordJoy on MicroAcquire to see if there were other offers.
We quickly received 10+ offers. We got 18.5k. There was also about $1000 in AppSumo that we could not withdraw, so we agreed to transfer that over for $600 since about 40% of our sales on AppSumo usually end up being refunded.
Lessons Learned
First, create an acquisition channel
We couldn't discover a scalable acquisition route for RecordJoy. If I had to start another project, I'd develop a robust acquisition channel first. It might be LinkedIn, Medium, or YouTube.
Purchase Power of the Buyer Affects Acquisition Price
Some of the buyers we spoke to were individuals looking to buy side projects, as well as companies looking to launch a new product category. Individual buyers had less budgets than organizations.
Customers of AppSumo vary.
AppSumo customers value lifetime deals and low prices, which may not be a good way to build a business with recurring revenue. Designed for AppSumo users, your product may not connect with other users.
Try to increase acquisition trust
Acquisition often fails. The buyer can go cold feet, cease communicating, or run away with your stuff. Trusting the buyer ensures a smooth asset exchange. First acquisition meeting was unpleasant and price negotiation was tight. In later meetings, we spent the first few minutes trying to get to know the buyer’s motivations and background before jumping into the negotiation, which helped build trust.
Operating expenses can reduce your earnings.
Monitor operating costs. We were really happy when we withdrew the $5000 we made from AppSumo and Stripe until we realized that we had spent $3500 in operating fees. Spend money on software and consultants to help you understand what to build.
Don't overspend on advertising
We invested $1500 on Google Ads but made little money. For a side project, it’s better to focus on organic traffic from SEO rather than paid ads unless you know your ads are going to have a positive ROI.
Ben Carlson
3 years ago
Bear market duration and how to invest during one
Bear markets don't last forever, but that's hard to remember. Jamie Cullen's illustration
A bear market is a 20% decline from peak to trough in stock prices.
The S&P 500 was down 24% from its January highs at its low point this year. Bear market.
The U.S. stock market has had 13 bear markets since WWII (including the current one). Previous 12 bear markets averaged –32.7% losses. From peak to trough, the stock market averaged 12 months. The average time from bottom to peak was 21 months.
In the past seven decades, a bear market roundtrip to breakeven has averaged less than three years.
Long-term averages can vary widely, as with all historical market data. Investors can learn from past market crashes.
Historical bear markets offer lessons.
Bear market duration
A bear market can cost investors money and time. Most of the pain comes from stock market declines, but bear markets can be long.
Here are the longest U.S. stock bear markets since World war 2:
Stock market crashes can make it difficult to break even. After the 2008 financial crisis, the stock market took 4.5 years to recover. After the dotcom bubble burst, it took seven years to break even.
The longer you're underwater in the market, the more suffering you'll experience, according to research. Suffering can lead to selling at the wrong time.
Bear markets require patience because stocks can take a long time to recover.
Stock crash recovery
Bear markets can end quickly. The Corona Crash in early 2020 is an example.
The S&P 500 fell 34% in 23 trading sessions, the fastest bear market from a high in 90 years. The entire crash lasted one month. Stocks broke even six months after bottoming. Stocks rose 100% from those lows in 15 months.
Seven bear markets have lasted two years or less since 1945.
The 2020 recovery was an outlier, but four other bear markets have made investors whole within 18 months.
During a bear market, you don't know if it will end quickly or feel like death by a thousand cuts.
Recessions vs. bear markets
Many people believe the U.S. economy is in or heading for a recession.
I agree. Four-decade high inflation. Since 1945, inflation has exceeded 5% nine times. Each inflationary spike caused a recession. Only slowing economic demand seems to stop price spikes.
This could happen again. Stocks seem to be pricing in a recession.
Recessions almost always cause a bear market, but a bear market doesn't always equal a recession. In 1946, the stock market fell 27% without a recession in sight. Without an economic slowdown, the stock market fell 22% in 1966. Black Monday in 1987 was the most famous stock market crash without a recession. Stocks fell 30% in less than a week. Many believed the stock market signaled a depression. The crash caused no slowdown.
Economic cycles are hard to predict. Even Wall Street makes mistakes.
Bears vs. bulls
Bear markets for U.S. stocks always end. Every stock market crash in U.S. history has been followed by new all-time highs.
How should investors view the recession? Investing risk is subjective.
You don't have as long to wait out a bear market if you're retired or nearing retirement. Diversification and liquidity help investors with limited time or income. Cash and short-term bonds drag down long-term returns but can ensure short-term spending.
Young people with years or decades ahead of them should view this bear market as an opportunity. Stock market crashes are good for net savers in the future. They let you buy cheap stocks with high dividend yields.
You need discipline, patience, and planning to buy stocks when it doesn't feel right.
Bear markets aren't fun because no one likes seeing their portfolio fall. But stock market downturns are a feature, not a bug. If stocks never crashed, they wouldn't offer such great long-term returns.
Dung Claire Tran
3 years ago
Is the future of brand marketing with virtual influencers?
Digital influences that mimic humans are rising.
Lil Miquela has 3M Instagram followers, 3.6M TikTok followers, and 30K Twitter followers. She's been on the covers of Prada, Dior, and Calvin Klein magazines. Miquela released Not Mine in 2017 and launched Hard Feelings at Lollapazoolas this year. This isn't surprising, given the rise of influencer marketing.
This may be unexpected. Miquela's fake. Brud, a Los Angeles startup, produced her in 2016.
Lil Miquela is one of many rising virtual influencers in the new era of social media marketing. She acts like a real person and performs the same tasks as sports stars and models.
The emergence of online influencers
Before 2018, computer-generated characters were rare. Since the virtual human industry boomed, they've appeared in marketing efforts worldwide.
In 2020, the WHO partnered up with Atlanta-based virtual influencer Knox Frost (@knoxfrost) to gather contributions for the COVID-19 Solidarity Response Fund.
Lu do Magalu (@magazineluiza) has been the virtual spokeswoman for Magalu since 2009, using social media to promote reviews, product recommendations, unboxing videos, and brand updates. Magalu's 10-year profit was $552M.
In 2020, PUMA partnered with Southeast Asia's first virtual model, Maya (@mayaaa.gram). She joined Singaporean actor Tosh Zhang in the PUMA campaign. Local virtual influencer Ava Lee-Graham (@avagram.ai) partnered with retail firm BHG to promote their in-house labels.
In Japan, Imma (@imma.gram) is the face of Nike, PUMA, Dior, Salvatore Ferragamo SpA, and Valentino. Imma's bubblegum pink bob and ultra-fine fashion landed her on the cover of Grazia magazine.
Lotte Home Shopping created Lucy (@here.me.lucy) in September 2020. She made her TV debut as a Christmas show host in 2021. Since then, she has 100K Instagram followers and 13K TikTok followers.
Liu Yiexi gained 3 million fans in five days on Douyin, China's TikTok, in 2021. Her two-minute video went viral overnight. She's posted 6 videos and has 830 million Douyin followers.
China's virtual human industry was worth $487 million in 2020, up 70% year over year, and is expected to reach $875.9 million in 2021.
Investors worldwide are interested. Immas creator Aww Inc. raised $1 million from Coral Capital in September 2020, according to Bloomberg. Superplastic Inc., the Vermont-based startup behind influencers Janky and Guggimon, raised $16 million by 2020. Craft Ventures, SV Angels, and Scooter Braun invested. Crunchbase shows the company has raised $47 million.
The industries they represent, including Augmented and Virtual reality, were worth $14.84 billion in 2020 and are projected to reach $454.73 billion by 2030, a CAGR of 40.7%, according to PR Newswire.
Advantages for brands
Forbes suggests brands embrace computer-generated influencers. Examples:
Unlimited creative opportunities: Because brands can personalize everything—from a person's look and activities to the style of their content—virtual influencers may be suited to a brand's needs and personalities.
100% brand control: Brand managers now have more influence over virtual influencers, so they no longer have to give up and rely on content creators to include brands into their storytelling and style. Virtual influencers can constantly produce social media content to promote a brand's identity and ideals because they are completely scandal-free.
Long-term cost savings: Because virtual influencers are made of pixels, they may be reused endlessly and never lose their beauty. Additionally, they can move anywhere around the world and even into space to fit a brand notion. They are also always available. Additionally, the expense of creating their content will not rise in step with their expanding fan base.
Introduction to the metaverse: Statista reports that 75% of American consumers between the ages of 18 and 25 follow at least one virtual influencer. As a result, marketers that support virtual celebrities may now interact with younger audiences that are more tech-savvy and accustomed to the digital world. Virtual influencers can be included into any digital space, including the metaverse, as they are entirely computer-generated 3D personas. Virtual influencers can provide brands with a smooth transition into this new digital universe to increase brand trust and develop emotional ties, in addition to the young generations' rapid adoption of the metaverse.
Better engagement than in-person influencers: A Hype Auditor study found that online influencers have roughly three times the engagement of their conventional counterparts. Virtual influencers should be used to boost brand engagement even though the data might not accurately reflect the entire sector.
Concerns about influencers created by computers
Virtual influencers could encourage excessive beauty standards in South Korea, which has a $10.7 billion plastic surgery industry.
A classic Korean beauty has a small face, huge eyes, and pale, immaculate skin. Virtual influencers like Lucy have these traits. According to Lee Eun-hee, a professor at Inha University's Department of Consumer Science, this could make national beauty standards more unrealistic, increasing demand for plastic surgery or cosmetic items.
Other parts of the world raise issues regarding selling items to consumers who don't recognize the models aren't human and the potential of cultural appropriation when generating influencers of other ethnicities, called digital blackface by some.
Meta, Facebook and Instagram's parent corporation, acknowledges this risk.
“Like any disruptive technology, synthetic media has the potential for both good and harm. Issues of representation, cultural appropriation and expressive liberty are already a growing concern,” the company stated in a blog post. “To help brands navigate the ethical quandaries of this emerging medium and avoid potential hazards, (Meta) is working with partners to develop an ethical framework to guide the use of (virtual influencers).”
Despite theoretical controversies, the industry will likely survive. Companies think virtual influencers are the next frontier in the digital world, which includes the metaverse, virtual reality, and digital currency.
In conclusion
Virtual influencers may garner millions of followers online and help marketers reach youthful audiences. According to a YouGov survey, the real impact of computer-generated influencers is yet unknown because people prefer genuine connections. Virtual characters can supplement brand marketing methods. When brands are metaverse-ready, the author predicts virtual influencer endorsement will continue to expand.