Tag: Elon Musk

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Unveiling the Untold Story of Tesla’s Q1 2023 Earnings Report: A Deeper Dive into Share Price Implications

Tesla’s Q1 2023 earnings report has captured the attention of investors and market enthusiasts alike, showcasing impressive revenue growth and a solid financial position. However, a closer inspection reveals some underlying concerns that might not be as clear on the surface. In this analysis, I will explore the hidden truths that may impact the company’s future success and share price, while offering a unique perspective on the unfolding situation.

Part 1: Financials and Profitability

The Balancing Act of Tesla’s Profitability: At first glance, Tesla’s Q1 2023 report reveals an 11.4% operating margin and $2.7B in GAAP operating income. However, this figure is down YoY, primarily due to reduced average selling prices (ASPs), higher raw material costs, and increased logistics and warranty expenses. As the company continues to expand production and launch new products, these costs may continue to escalate, potentially putting a strain on profitability.

Share Price Implications: A decline in profitability could dampen investor sentiment and lead to downward pressure on Tesla’s share price. As the electric vehicle (EV) market becomes increasingly competitive, Tesla may need to continue cutting prices to maintain its market share. This price war, along with the rising costs of production, could significantly impact the company’s profit margins and, consequently, its stock valuation.

Part 2: Product Development and Challenges

Navigating the Cybertruck Waters: Tesla’s Cybertruck has generated a significant buzz, and its production is set to begin later this year at Gigafactory Texas. However, the unconventional design and features of the Cybertruck may not resonate with traditional truck buyers. The pickup truck market is fiercely competitive, and Tesla’s entrance into this space comes with a considerable risk that may not be fully reflected in their earnings report.

The Odyssey of 4680 Cell Production: Tesla’s 4680 battery cells are crucial for their future success, as they promise increased energy density, reduced cost, and better performance. However, ramping up production for these cells has proved challenging, contributing to the decrease in operating income. If Tesla encounters additional setbacks, it could significantly delay product launches and hinder their ability to meet the 50% compound annual growth rate (CAGR) target.

Share Price Implications: Tesla’s share price is heavily influenced by investor sentiment and expectations of future growth. If the Cybertruck fails to capture a significant portion of the pickup truck market, or if the 4680 cell production encounters further delays, it could lead to a negative impact on the stock price. Furthermore, as Tesla’s valuation is based on future growth potential, any delays in product development could result in a revaluation of the company’s worth by the market.

Part 3: Energy Storage Expansion and Market Position

Tesla’s Energy Storage Ambitions: Tesla’s energy storage business showed promising growth in Q1, with the company planning to increase production capacity at their Megafactories in Lathrop and Shanghai. Despite the positive outlook, the energy storage market is becoming increasingly crowded, and Tesla may face stiff competition from both new and established players. This competition may put pressure on margins and make it more difficult for Tesla to maintain its position as a market leader.

Share Price Implications: As a significant portion of Tesla’s valuation is tied to its position as a market leader in the EV and energy storage sectors, increased competition could negatively affect investor sentiment and the company’s stock price. The energy storage market is evolving rapidly, and new technologies could emerge that challenge Tesla’s dominance. If Tesla fails to maintain its competitive edge, the market may reevaluate the company’s growth prospects, leading to potential share price

Part 4: Tesla’s Long-Term Growth Strategy and Share Price Implications

The Roadmap to Tesla’s Growth: In the earnings report, Tesla outlines plans to grow production in alignment with their 50% CAGR target, aiming to produce around 1.8 million cars in 2023. However, the automotive industry is known for its unpredictability, and Tesla’s ambitious growth plans may not be feasible in the long run. The company’s aggressive expansion may leave them vulnerable to unforeseen challenges, such as supply chain disruptions, regulatory hurdles, or shifts in consumer preferences.

Share Price Implications: Investors have high expectations for Tesla’s growth, which is reflected in the company’s stock price. Any signs of faltering growth or the inability to meet their ambitious targets may cause a loss of investor confidence and result in a decline in Tesla’s share price. The market is sensitive to changes in growth projections, and if Tesla’s growth falters, even temporarily, it could cause significant volatility in the stock price.

Part 5: Tesla’s Long-Term Plans and Share Price Dynamics

Tesla’s Vision for the Future: Tesla has ambitious long-term plans that focus on rapid growth, expansion of its product lineup, and continuous investment in autonomy and vehicle software. The company’s strategy includes an emphasis on Full Self-Driving (FSD) technology, which could potentially revolutionize the automotive industry and create new revenue streams through ride-sharing and other applications. Tesla’s commitment to innovation and growth is part of what has propelled its share price to around $170 per share.

Cybertruck Manufacturing Optimism: Cybertruck has the potential to disrupt the pickup truck market with its unique design and advanced technology. Tesla’s Gigafactory Texas, where the Cybertruck will be produced, is expected to feature cutting-edge manufacturing techniques and innovations that could help streamline the production process. If Tesla can successfully ramp up Cybertruck production and gain a foothold in the competitive pickup truck market, it could further solidify its position as a leader in the EV industry and create a positive impact on its share price.

Full Self-Driving (FSD) Prospects: Tesla’s FSD technology is one of the key pillars of the company’s long-term strategy. The company has made significant progress in recent years, with multiple iterations of their Autopilot and FSD software being released to customers. However, the path to true autonomous driving is complex, with regulatory and technical challenges still to be overcome. If Tesla can successfully navigate these hurdles and deliver a fully functional FSD system, it could potentially unlock substantial value for the company and its shareholders.

Share Price Implications: The share price of Tesla is closely tied to the company’s long-term plans and its ability to execute them successfully. The introduction of the Cybertruck and advancements in FSD technology could potentially lead to significant upside in Tesla’s share price. However, the market will closely monitor the company’s progress in these areas. Any setbacks or delays in production, FSD development, or regulatory approval could negatively impact investor sentiment and the stock price.

Conclusion: Tesla’s long-term plans, including the Cybertruck production and Full Self-Driving technology, play a crucial role in the company’s current share price of around $170 per share. While there are risks associated with these ambitious plans, a successful execution could propel Tesla to new heights in the automotive industry and lead to potential gains in its stock valuation. As the electric vehicle market continues to evolve, Tesla’s ability to navigate these challenges and capitalize on emerging opportunities will be key to maintaining its dominance and protecting its share price.

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How ChatGPT Helped Me Visualize Global Media Funding: A Unique Application of AI on ApplyingAI.com, Featuring a Dash of Twitter Drama

Introduction

At ApplyingAI.com, we’re passionate about exploring the immense potential of artificial intelligence (AI) in global macro investing, electric vehicles (EVs), autonomy, space travel, and free markets. Our goal is to empower the future of finance and innovation by showcasing real-world AI applications that are revolutionizing industries. In this article, we’ll share a fascinating story of how OpenAI’s ChatGPT helped create an engaging visualization of global media funding, peppered with a few laughs inspired by a recent Twitter thread.

The Idea

In a world where media plays a crucial role in shaping public opinion and influencing decision-making, understanding the relationship between media companies and their funding sources is vital. We wanted to create an impactful visual representation of government funding for major media companies worldwide, including prominent names such as BBC, NHK, CCTV, and CBC, as well as US-based networks like PBS, NPR, and CNN. Little did we know that our creation would coincide with a humorous Twitter exchange!

The Twitter Drama

As fate would have it, a recent Twitter thread surfaced discussing the Canadian Broadcasting Corporation (CBC) and its government funding. The public broadcaster took issue with being labelled as “government-funded media,” arguing that it undermined their credibility. Elon Musk chimed in, suggesting a 70% government-funded label, followed by a tongue-in-cheek compromise of 69% to “give them the benefit of the doubt.” The exchange lightened the mood and highlighted the importance of accuracy (and humor) in media funding discussions.

The Solution

With the assistance of ChatGPT, we generated a Python script that utilized popular visualization libraries such as matplotlib and seaborn. The script produced a striking horizontal bar chart that showcased the percentage of government funding received by each media company, along with the country they are based in. The visualization, complete with vibrant colors and annotations, allowed for an easy comparison of the government funding landscape across the globe – and a subtle nod to the ongoing Twitter debate.



import matplotlib.pyplot as plt

import seaborn as sns



# Data

media_companies = [

    "BBC", "NHK", "CCTV", "France Télévisions", "ARD",

    "RAI", "RTVE", "ABC", "SABC", "CBC/Radio-Canada",

    "PBS", "NPR", "FOX", "CNBC", "CNN"

]

government_funding = [

    75, 95, 100, 80, 85, 70, 90, 95, 20, 65,

    15, 10, 0, 0, 0

]

countries = [

    "United Kingdom", "Japan", "China", "France", "Germany",

    "Italy", "Spain", "Australia", "South Africa", "Canada",

    "United States", "United States", "United States", "United States", "United States"

]



# Set seaborn style

sns.set(style="whitegrid")



# Create a horizontal bar plot

plt.figure(figsize=(12, 8))

ax = sns.barplot(x=government_funding, y=media_companies, palette="viridis")



# Add title and labels

plt.title("Major Media Companies and Their Government Funding Percentages")

plt.xlabel("Government Funding (%)")

plt.ylabel("Media Companies")



# Annotate the bars with the percentage values and country names

for i, (value, country) in enumerate(zip(government_funding, countries)):

    ax.text(value + 1, i, f"{value}% ({country})", va="center")



# Show the plot

plt.show()

The Impact

The resulting bar chart, generated with the help of ChatGPT, has garnered attention and sparked discussions among our audience, as well as some chuckles inspired by the Twitter thread. By understanding the connection between media companies and their funding sources, investors, policymakers, and the general public can make more informed decisions about the future of media, finance, and innovation – and perhaps share a laugh or two along the way.

Conclusion

This unique application of AI demonstrates the power of tools like ChatGPT in simplifying complex tasks and generating insightful outputs, with a sprinkle of humour to keep things light-hearted. We at ApplyingAI.com aim to continue empowering the future of finance and innovation in various domains, such as global macro investing, EVs, autonomy, space travel, and free markets. Stay tuned for more exciting stories, insights, and a few laughs as we continue to explore the captivating world of AI applications!

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A Glimpse into the Future of Space Travel: A Trip to South Padre Island for SpaceX’s Starship Launch

Witnessing History in the Making at the SpaceX Starship Launch Attempt

Introduction:

I am passionate about empowering the future of finance and innovation, and that’s why I started ApplyingAI.com. I believe in the potential of AI to revolutionize global macro investing, electric vehicles, autonomy, space travel, and free markets. Recently, I had the unique opportunity to experience one such transformative moment firsthand: a trip to South Padre Island to watch SpaceX attempt to launch their colossal Starship rocket.

An Unforgettable Experience:

I joined thousands of spectators gathered at various coastal locations on the Gulf of Mexico, including South Padre Island, to witness this historic event. The anticipation in the air was palpable as we eagerly awaited the launch of SpaceX’s Starship, the most powerful rocket ever built. Unfortunately, the launch was postponed due to a frozen pressurant valve, as announced by Elon Musk on Twitter. However, the attempt is expected to resume later this week.

A Game-Changer in Space Travel:

SpaceX’s Starship has the potential to revolutionize the rocket business completely. Designed to be fully and rapidly reusable, it can fly people and satellites to orbit multiple times a day, much like a jet airliner crisscrossing the Atlantic. Elon Musk envisions an era of interplanetary travel for ordinary humans, made possible by this groundbreaking vehicle.

A First for Starship:

Although the top segment of Starship has been tested on short hops, this would have been the first time it would go up with its lower stage, the mammoth booster called Super Heavy. If the launch proceeds as planned later this week, SpaceX will aim for 90% thrust, delivering a force equivalent to propelling almost 100 Concorde supersonic airliners at takeoff.

The Future of SpaceX and Starship:

With the support of a $3 billion investment from NASA, SpaceX is developing a variant of Starship designed to land astronauts on the Moon. The company’s long-term vision includes controlled landings for both the booster and the ship, allowing for refuelling and relaunching. SpaceX’s ultimate goal is to facilitate large-scale human travel to Mars.

A Testament to Human Ingenuity:

My trip to South Padre Island to witness the SpaceX Starship launch attempt was a testament to human ingenuity and the power of innovation. Despite the postponement, the excitement and anticipation I felt during this historical moment are undeniable. As I continue to explore the endless possibilities AI offers in global macro investing, electric vehicles, autonomy, space travel, and free markets, I remain inspired by the incredible strides being made in these fields.

Stay tuned for my coverage of the rescheduled SpaceX Starship launch, and join me in my journey to empower the future of finance and innovation.

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When Stocks Stop Being Sexy – Why I’m Buying Tesla

These are scary times. The market is the most volatile that it’s been since the crash in march 2020 during the first lockdown. Tesla is down over 25% from its high share price to below $660 as of this video. Friends keep asking me: Is it time to sell? Is this the end of the run?

Well, something big is happening and I want to share it with you. 

Tesla is one of the most talked-about companies in the market and one of the most popular to trade. There are hundreds of YouTube channels dedicated to their cars and many dedicated to their stock.

So why should you listen to me?

Please don’t take it lightly when I say that I’m VERY familiar with Tesla. I’ve been following the company since they released the first roadster in 2008. I actually founded a company, InOrbis Intercity, that uses exclusively Tesla vehicles for city-to-city travel, in 2015. During that time I have owned several models of Tesla and have driven and ridden in virtually every model and trim that has been released to-date. We’ve had cars with upwards of 400,000km of use and we’ve driven nearly 3 million km in total with travelers in the past 5 years. We gather feedback from our drivers and our customers on the safety, comfort, maintenance, energy costs, and reliability of Teslas every single day.

I know a lot about these cars and about the company. Let me tell you, until about 5 days ago, I thought Tesla’s share price has been overvalued. And I’ve thought that since 2018.

This is not easy for me. But I’m here to tell you that I was wrong and that I’ve changed my mind about Tesla and also what I’m going to do about it.

Here’s how I changed my mind. And trust me, it wasn’t easy. 

Full disclosure, I’ve been bullish on Tesla’s products for a long time. In my opinion, Tesla makes the best cars on the market. Full Stop. And they only get better every day. We’ve had nothing but positive feedback and experiences in our fleet with the vehicles. There certainly are downsides to owning a Tesla but the software and driving experience make up for any of the negative experiences with the company that we’ve had to this point.

Unfortunately for me (and my wallet), I’ve been bearish on their stock price until now, thinking that it was just the ‘popular kid on the block’ and eventually, the price would come back down to earth. I was sure that Tesla would eventually get bought up by Apple or another large auto-manufacturer and their cars would live on as a sub-brand. I even created an extremely detailed valuation model and wrote a 30-page report on why Tesla was overvalued back in January of 2018 when their stock price was $200 (pre-stock split).

I was absolutely positive that Tesla was not going to make it. They’d soon run out of money and that the only way for them to keep going was if they got bought out.

In my defence, I was almost right! Tesla almost went bankrupt. Apple ALMOST bought them. Elon almost had to give up leading his dream of electrification (twice).

But then they delivered; first on the Model 3, and then the Model Y. They’ve hit target after target and even delivered very nearly half a million cars in 2020, during one of the most difficult years in recent memory for many of us. Tesla has been on an absolute tear for so long that I finally bought in around the time that their stock split. I didn’t buy much though. I still thought they were overvalued and that the run would end.

To summarize, I’ve thought Tesla stock was overvalued for a LONG time.

Lots of people are saying that Tesla would have to have a 50% market share of the entire automotive industry to hit its current valuation. I believed them. Until now.

It turns out that’s just not true!

I won’t go into detail here but in future posts and videos on my YouTube channel, I’m going to show you how, even with an extremely conservative (high) discount rate, Tesla is actually undervalued. And it’s probably undervalued at $800 per share, too. You can check out my valuation by clicking this link.

I’ve changed my mind on Tesla. I’m now bullish on the product AND on the stock.

I am going to buy shares of Tesla, and keep buying until they hit my price target, and maybe even more after that depending on a few factors. I bought shares in after-hours today at a price of $651. If they keep dropping, I’ll keep buying.

As meet Kevin says, I’m throwing my money into the fireplace! As the price of Tesla falls I’ll be Buyin’… The… Dip…!!!

Numbers don’t lie, and I am confident in my numbers.

There’s also a move that Tesla could make that would double my price target. Sign up to my Patreon to find out what that is.

My targets are not based on any dreams of a full-autonomous revolution and of Tesla taking the MaaS (Mobility-as- a-Service) market over with their Tesla Network app (although that certainly wouldn’t hurt my valuation).

My targets are based solely on EV sales and on Tesla’s planned expansion of production. Not on a guess, but on their actual, stated manufacturing targets.

Before I tell you why I’m doing this. Please don’t JUST listen to what I’m saying and start buying because I said so!!! Do your homework! Make your own decisions! I am not a financial advisor so please don’t sue me if I’m wrong!

If you decide you want to buy too. Click this link to get Wealthsimple and get $10 to start trading on top of being able to make trades absolutely free!

OK, here’s what you CAN do and what I did: Make a valuation spreadsheet and understand what the intrinsic value of Tesla is. If you want to learn how to do this, I have a course that I’m building on how to value a company, get more info on that in my Patreon group. 

To get a good head start today, though, just Google discounted cash flow statements and fundamental valuation.

Learn about the business you want to value. Learn what they do and how they do it. Learn about its competitors and the technology that they use. Learn everything you can because you need to know what you’re investing in if you want to be successful. Then, build your model. Predict how much they’re going to make over the next several years and decide if the company is worth investing in. Invest until the business hits your target valuation or until you get new information that changes your mind.

So why is Tesla undervalued?

For me, this all comes down to something that many people glossed over at the time it was announced back in September. The media barely talked about it, because, I think it was too abstract for most people. What is was is Tesla’s internal battery production goal. That’s right. The key factor is how many batteries Tesla is going to manufacture in-house. That number is 3-Terawatt-hours by 2030. That’s huge! It’s 3000x more than what they produced in 2020. And that’s purely for cars and energy storage.

Because that’s their internal production target, and they’ve stated that they’re going to buy every battery their existing partners can make for the foreseeable future. I think it’s fairly conservative to use that 3TWh/year production target as a benchmark for calculating Tesla’s share price. All I had to do from there is work backward to find the size of each car battery and divide to find the number of cars they plan to produce. If Tesla can keep selling as many cars as they can produce (and I think they can because the demand for autonomous EVs is enormous), then this tells me exactly what Tesla’s sales curve is going to look like over the next years. Peek over a few Elon tweets and stats on their expenses and margin targets and we’ve got our future cash flow statement.

Fundamentally, Tesla is leading the way in EVs and in autonomous tech. Those two technologies ARE the future of transportation. They have the technology, they have the manufacturing capacity and they have the talent and the plan to make it happen.

I now think that this will happen and that it’s a great bet. Whether you do is up to you.

Remember: Do your research. If you’re confident in what you’ve found. Take a deep breath and make your call. You can do this.

For now, that’s all.

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Real Life Is Not Like Billions

Bobby Axelrod, the main character on the popular Finance drama, Billions, is a lot like Tesla CEO Elon Musk. They’re both billionaires. They both draw substantial public praise and criticism and are highly divisive figures who have a large impact on their respective industries. They were also both investigated and charged by the SEC (and in Axelrod’s case, the US Justice Department) for actions related to securities law. The main difference between the two? Bobby Axelrod is a fictional character whose proclivity for conflict is only superceded by his complete lack of restraint when his life and freedom are on the line. In real life, the consequences of your actions are permanent and making deals in the business world often means compromising, negotiating, and settling.

Today (September 29, 2018) Elon Musk settled with the SEC. He will no longer be chairman of Tesla, for at least three years, and will pay a fine in excess of $20 Million. In all, it is a relatively lesser penalty than the lifetime ban from being CEO of a publicly traded company that the SEC was seeking. It is also a larger punishment than someone who has not committed any wrongdoing deserves. Depending on your perspective, Musk either got away easy or was unfairly chastised by the state for a 60 character tweet.

Of course, the civil settlement does not preclude the Justice Department from filing criminal charges against Elon at a future date. However, a criminal trial has a much higher burden of proof than a civil case, which can be decided based on a balance of probabilities. In a criminal case, the prosecution must prove, beyond a reasonable doubt, that the defendant committed the alleged crimes, whereas, in a civil suit, all that is required is a greater than 50% probability that the act took place.

In a previous post from September 27, we discussed whether AI could play a role in predicting the outcome of cases like this, perhaps assisting traders in making appropriate investment decisions surrounding companies with legal troubles. Despite a strong performance in short-term volume trading, automation has not yet played a large role in the fundamental analysis of a stock’s long-term viability. Most AIs that trade today are relying on purely technical analysis, not looking at any of the traits that make a company likely to succeed, but instead relying on historical price data to predict trading and movement patterns.

Fundamental analysis is complex and subjective. Even the smartest deep neural networks would have a difficult time distinguishing between the very human aspects that go into valuing a company. The problem with AI, in this particular application, is that it would require a broad knowledge of various domains to be combined in order to predict with any degree of accuracy. Right now, even the best deep neural networks are still very narrowly defined. They are trained to perform exceptionally well within certain contexts, however, beyond the confines of what they ‘understand’ they are unable to function at even a basic level.

Screenshot 2018-09-29 19.52.57.png
Complexity in neural networks results in ‘overfitting’ – networks specify the training set well but fail at more generalized tasks.

In the above example, we can see how more complicated neural networks might fail to understand topics that are even slightly different from what they have seen in the past. The model fits the data that the network has already encountered, however, this data does not reflect what could happen in the future. When something happens that they haven’t encountered before (a CEO tweets something about 420, for example), a human can immediately put that into context with our everyday experience and understand that he’s likely talking about smoking weed. However, an AI trained to predict share prices based on discounted cash flow analysis would have absolutely no clue what to do with that information.

It is likely that there are companies working on technology to help train neural networks to deal with the idiosyncratic information present in everyday business interactions. One possible answer is to have multiple neural networks working on different subsets of the problem. Similar to how deep neural networks have enabled advances in fields ranging from medical diagnosis to natural language processing, new organizations of these systems could enable the next generation of AI that is able to handle multiple tasks with a high level of competency. As we continue to build this technology, we’ll keep speculating on whether or not an executive is guilty, and traders and short-sellers will continue to make and lose billions based on the result.

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Elon Musk Indicted by SEC, Can AI Help?

The big news from the tech and finance world on September 27, 2018, is that Elon Musk has been sued by the US Securities and Exchange Commission (SEC) for his tweets about taking Tesla private at $420 per share. 

The SEC is seeking to have Musk banned from serving as an officer or director of any public company. Their reasoning? Musk was lying about having funding secured. This implies that he was trying to manipulate Tesla’s share price in an upward direction. Well, it worked, for about a day, that is. On the day of the tweet, Tesla’s share price rose to a high of $379.87 US per share from its previous price of around $350 per share, before falling back to $352 the next day (August 8, 2018). If the markets had actually believed Musk’s Tweet, Tesla’s share price likely would have climbed closer and closer to the mythical $420 price as the take-private day neared.

Tesla’s share price peaking after Musk’s announcement.

Instead, Tesla’s share price dropped like a rock because every savvy investor realized that Musk’s statement was either pure fanciful bluster, a joke about weed, or both. Of course, today has been much worse for Tesla’s share price than any of Musk’s recent ill-advised tweets. In after-hours trading, Tesla’s share price is down as much as 13%. That’s a lot and it is falling dangerously close to their 52 week low. This is all especially troubling considering that Tesla is expected to announce their best quarter ever, in terms of cash flow, in a few days.

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So, what is the SEC doing, was it possible to predict this, and could AI make this type of situation any better? The answer to the first question is unclear, however, the answer to the second two questions is likely, yes.

AI is already being used in the legal profession to help identify responsive documents that must be turned over to the opposing party during a lawsuit. MIT Professor Emeritus Frank Levy leads a research that helps law firms apply machine learning software to the practice of law. 

If AI can predict what documents will be useful in a lawsuit, then whenever the CEO of a publicly traded company does something suspicious, it should be possible to use these same programs to parse historical cases and see what precedent there is for a lawsuit to be filed. At the very least, it could provide some insight into the likelihood of an indictment and, in the future, could even suggest potential courses of action for a company to take if it found itself in this type of situation.

Would the AI be able to help predict whether or not Elon will be convicted? Possibly. While I am not aware of any AIs currently being used to predict the outcome of legal matters, in my September 24, 2018 column, I covered the AI that perfectly predicted the outcome of last year’s Superbowl. While legal cases may be more complicated than a football score, there is likely several orders of magnitude more data about the outcome of various lawsuits than there is about football players, simply because there are WAY more lawsuits than there are football teams.

From a financial perspective, we could use this type of AI to predict potential lawsuits and their results and train the AI to make trades based on these predictions. If these types of AI were already in use, we could expect much smoother and more predictable share prices as the effect/implications of a particular news story would become apparent almost immediately after the information surfaces.

For now, I’ve programmed a simple AI for Elon Musk to help him decide if he should tweet something or not. You can try it, too, if you’d like. It’s posted below:


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What is Collective Intelligence?

Something fascinating to me about the world is how so many billions of people can act for their own self interests, and yet we’re all able to eat. Fewer and fewer of us are dying from preventable illnesses and medical technology has evolved to a point where we’re thinking about extending and enhancing human life past a century.

Collective intelligence describes the apparatus by which groups of individuals act collectively in ways that seem intelligent. For centuries, at least around 8000 years, humanity has demonstrated some form of collective intelligence. We’ve formed civilizations, shaped the landscape around us, and even touched the surface of the moon. However, recently, the definition of collective intelligence is expanding to include non-human machines. The whole is becoming more than the sum of its parts and that whole contains robots.

Many people, including very smart people like Elon Musk and the late Stephen Hawking, are afraid of the impending artificial intelligence revolution. They’re scared that once the proverbial chicken has hatched, and we create an AI that can act on its own, we may already be too late to stop it. There’s a great article that a friend shared with me about how a simple handwriting robot could cause the death of all life on earth and eventually the entire observable universe, check it out here. So, there’s no shortage of doom and gloom abound about artificial intelligence and why it’s going to pee in our cheerios and make us all subservient to its whims #hailSkynet. Luckily, not everyone is so negative about the prospects for AI. In fact, there’s one way that even if the experts are right, and we can’t beat a true AGI (artificial general intelligence), we may be able to become one ourselves. 

The MIT Center for Collective intelligence is an organization devoted to exploring how people and computers can be connected so that – collectively – they act more intelligently than any person, group, or computer has ever done before.

That’s the answer! If we are afraid that AI is going to destroy us, we have to merge with it before it can. The good news is that there is a lot of evidence to suggest that Humans + Computers >> Computers alone. 

Leaving the negativity behind, many experts are demonstrating that Artificial Intelligence will help improve millions of lives. It will create meaningful work for people and let us focus on what we’re great at instead of what we must do to survive. Companies in industries ranging from Finance to Transportation, to Medicine, are using AI to make life better for their customers, and for their employees. Let’s hope that this trend continues.

I’ll be working on finding applications in my business for artificial intelligence, specifically one narrow piece of it, machine learning. I’m going to take you along with me as I dive into the conceptual and technical aspects of the technology. We’ll be learning together and exploring how existing AI can be used in business while beginning to understand how to create new AIs from the ground up. So far, I’ve learned to program with Python and I’ve even created software that uses convolutional neural networks able to identify images of certain animals (mainly dogs) and classify them into breeds with surprising accuracy. Soon I’ll be using these techniques to create financial modelling software to predict some market movement and make trades. If you are interested in joining me on this journey, sit back, grab a coffee, or a beer, and let’s get smarter together!