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.
Introduction I often think of AI as something separate from traditional computer programming, something transcendent. However, most of the advances in modern AI are not the result of revolutionary new concepts or fields of study but rather the application of previously developed algorithms to significantly more powerful hardware and massive datasets.
Hannah Fry’s take on the world of AI covers topics ranging from justice to autonomous vehicles, crime, art and even to medicine. While the author is an expert in the field, she does a great job distilling the topics down to a level understandable by a layperson, but also keeps it interesting for someone with more background in programming and AI.
My favourite quote from the first part of the book comes on page 8, where Hannah succinctly describes the essence of what an algorithm is in only one sentence:
An algorithm is simply a series of logical instructions that show, from start to finish, how to accomplish a task.
Fry, Hannah. Hello World: Being Human in the Age of Algorithms (p. 8). W. W. Norton & Company. Kindle Edition
Once you read it, it seems obvious, but trying to describe to a first-year computer science student what an algorithm is can be a challenging task. The author manages this well. Despite the complexity and depth of the subject matter, Fry is able to bring context and relevance to a broad array of topics. The remainder of my review will speak to some of the book’s many sections and how someone with a business-facing view into the topics sees them.
Data This section covers some of the unknown giants in data-science including Peter Thiel’s Palantir. The section also touches on some very public examples where analytics has played a negative role – Cambridge Analytica’s use of private user data during the 2016 Presidential Elections.
The story here is about data brokers. Data brokers are companies who buy and collect user data and personal information and then resell it or share it for profit. A surprising fact is that some of these databases contain records of everything that you’ve ever done from religious affiliations to credit-card usage. These companies seem to know everything about just about everyone. It turns out that it is relatively simple to make inferences about a person based on their online habits.
The chapter converges to one of the major stories of 2018, the Cambridge Analytica scandal. But it begins by discussing the five personality traits that psychologists have used to quantify individuals’ personalities since the 1980s: openness to experience, conscientiousness, extraversion, agreeableness and neuroticism. By pulling data from users’ Facebook feeds, Cambridge Analytica was able to create detailed personality profiles to deliver emotionally charged and effective political messages.
Perhaps the most interesting fact though, is how small of an impact this type of manipulation actually has. The largest change reported was from 11 clicks in 1000 to 16 clicks in 1000 (less than 1 percent). But even this small effect, spread over a population of millions can cause dramatic changes to the outcome of, say, an election.
That’s the end of part 1 of this review. In Part 2, I’ll touch on some of the other sections of the book including Criminal Justice and Medicine.
These days it seems like businesses are trying to use AI to do everything. At least for startups, that isn’t far off. Anywhere there is a dataset remotely large enough and an answer that is vaguely definable, companies are putting together a business model to use machine learning to solve the problem. With some incredible successes in areas like image classification and defeating humans at video games, its hard not to be impressed.
One of the best channels for following recent breakthroughs in AI is the 2 Minute Papers YouTube Channel, started by Károly Zsolnai-Fehér, a professor at the Vienna University of Technology in Austria. Károly’s videos combine interesting clips of the programs in action with well-delivered summaries of recent papers illustrating advances in artificial intelligence.
In one of his latest videos, he covers an AI that not only can copy the most successful actions that humans take in video games but can actually improve on those actions to be better than the best human players. So does that mean that AI will be displacing office workers once it learns how to do their jobs better than them? Probably, yes. But maybe not quite how you think it might.
As much of a ‘black-box‘ as AI has been in the past, modern systems are becoming better and better at explaining how they arrived at an answer. This gives human operators predictive capabilities that we didn’t have with systems of the past that could spit out an answer but gave us no indication of how that answer was formulated.
This Forbes article on Human-Centric AI provides some examples of how modern AI systems can be implemented to train employees to do their jobs better and even enjoy their jobs more while doing it! If that doesn’t sound incredible to you, you may be a machine who is only reading this page to improve your search algorithm.
So what does this all mean? A lot of research is showing that AI is actually creating many more jobs than it destroys. So, as long as you’re willing to try and understand the systems that will one day be our overlords, you should be able to upgrade your career and stay employed.
Whether you still want the job that remains is another question entirely.
Index funds are the most highly traded equity investment vehicles, with some funds like ones created by Vanguard Group cumulatively being valued at over $4 Trillion USD. Index funds have democratized investing by allowing access to passive investments for millions of people. But what are they?
An index fund is a market-capitalization weighted basket of securities. Index funds allow retail investors to invest in a portfolio made up of companies representative of the entire market without having to create that portfolio themselves. Compared to actively managed funds like mutual funds and hedge funds, index funds tend to have much lower fees because the only balancing that happens occurs based on an algorithm to keep the securities in the fund proportional to their market cap (market capitalization, or market cap, is the number of shares that a company has on the market multiplied by the share price).
Starting in the 1970s, the first ‘index funds’ were created by companies that tried to create equally weighted portfolios of stocks. This early form of the index fund was abandoned after a few months. It quickly became apparent that it would be an operational nightmare to be constantly rebalancing these portfolios to keep them equally weighted. Soon companies settled on the market capitalization weighting because a portfolio weighted by market cap will remain that way without constant rebalancing.
With the incredible advancement of AI and extraordinarily powerful computers, shouldn’t it be possible to create new types of ‘passively managed’ funds that rely on an algorithm to trade? What that could mean is that index funds might not have to be market cap weighted any longer. This push is actually happening right now and the first non-market cap weighted index funds to appear in over 40 years could be available to retail investors soon.
But this means that we need to redefine the index fund. The new definition has three criteria that must be met for a fund to meet:
It must be transparent – Anyone should be able to know exactly how it is constructed and be able to replicate it themselves by buying on the open market.
It must be investable – If you put a certain amount of money in the fund, you will get EXACTLY the return that the investment shows in the newspapers (or more likely your iPhone’s Stocks app).
It must besystematic – The vehicle must be entirely algorithmic, meaning it doesn’t require any human intervention to rebalance or create.
So, what can we do with this new type of index fund?
“Sound Mixer” board for investments with a high-risk, actively traded fund (hedge fund) on the top and lower risk, passively traded fund (index fund) on the bottom.
We can think of investing like a spectrum, with actively managed funds like hedge funds on one side and passively managed index funds on the other and all the different parameters like alpha, risk control and liquidity as sliders on a ‘mixing board’ like the one in the image above. Currently, if we wanted to control this board, we would have to invest in expensive actively managed funds and we wouldn’t be able to get much granular control over each factor. With an AI-powered index fund, the possibilities of how the board could be arranged are endless. Retail investors could engage in all sorts of investment opportunities in the middle, instead of being forced into one category or another.
An AI-powered index fund could allow an investor to dial in the exact parameters that they desire for their investment. Risk, alpha, turnover, Sharpe ratio, or a myriad of other factors could easily be tuned for by applying these powerful algorithms.
The implications of a full-spectrum investment fund are incredible. Personalized medicine is a concept that is taking the industry by surprise and could change the way that doctors interact with patients. Companies like Apple are taking advantage of this trend by incorporating new medical devices into consumer products, like with the EKG embedded into the new Apple Watch Series 4.
Personalized investing could be just as powerful. Automated portfolios could take into account factors like age, income level, expenses, and even lifestyle to create a portfolio that is specifically tailored to the individual investor’s circumstances.
So why can’t you go out and purchase one of these new AI managed, customizable index funds?
Well, unfortunately, the algorithms do not exist, yet. The hardware and software exists today to do this but we’re still missing the ability to accurately model actual human behaviour. Economists still rely on some pretty terrible assumptions about people that they then use to build the foundations of entire economic theories. One of these weak assumptions is that humans act rationally. Now, there is a lot of evidence to suggest that many people act in the way that we are programmed to by evolution. The problem is, a lot of what allowed us to evolve over the last 4 billion years of life on earth, is pretty useless for success in 2018-era financial planning and investment.
All hope is not lost, however. New research into the concept of bounded rationality, the idea that rational decision making is limited by the extent of human knowledge and capabilities, could help move this idea forward. One of the founding fathers of artificial intelligence, Herbert Simon, postulated that AI could be used to help us understand human cognition and better predict the kinds of human behaviours that helped keep us alive 8,000 years ago, but are detrimental for wealth accumulation today.
By creating heuristic algorithms that can capture these behaviours and learning from big data to understand what actions are occurring, we may soon be able to create software that is able to accentuate the best human behaviours and help us deal with the worst ones. Perhaps the algorithm that describes humanity has already been discovered.
Zero, nada, zilch, bupkiss. That’s how much your idea is worth.
But…but, my idea is brilliant! It will change the world! My new plan for how to solve snow-covered streets is worth billions!
Really? Who is willing to pay you a billion dollars for your idea? Anyone?…Anyone? Bueller?
I’m sorry to burst your bubble, but the likelihood is that any idea that you’ve had, someone smarter than you has already had. Your idea is worthless. So what? It doesn’t matter that it’s not worth anything now. What matters is what you do with your idea.
Take your idea for a product or service, and sell it to someone. See if there are people willing to put down actual money for what you’ve thought of. And don’t be afraid to tell people what your idea is. If it’s so easy to replicate that just by telling someone, they could take it and turn it into a business, then your idea wasn’t really worth anything, to begin with. How do you sell your idea? Take it to market! Start by defining the problem that you’re trying to solve. Research the hell out of it, what the pain points are that your idea addresses, who has those pain points, and how you can reach those customers. See if you can interview people with the pain. Ask them to tell you a story about the pain and see if it really bothers them enough to change what they’re already doing. This type of research costs nothing but your time and will provide valuable insight into the minds of your target audience.
Has the Lean Startup flopped?
Steve Blank, the entrepreneur responsible for customer development methodology says The Lean Startup is dead. What does that mean? Basically, there’s so much money available through angels and VCs that a young company’s success depends almost exclusively on their ability to raise huge sums of money and not on their ability to bootstrap a startup.
I am not confident that Steve is correct, especially if you live outside of the Silicon Valley bubble, or are creating a startup that doesn’t immediately scream ‘FUND ME’ to Angels and VCs. It’s still possible to build a company without raising a hundred million dollars, it’s just difficult. I’ve been building my company, InOrbis Intercity for over three and a half years now. It started off as a worthless idea, just like yours. But it has grown to be more than that. We’ve just had our first profitable quarter, and we’re still only in Alberta. The vision I have for the company is beyond large. It will be a billion dollar company. But it takes time for great things to happen.
In order to change the way that people travel, we have to reinvent the model of a transportation company. We can’t rely on what companies like Uber did for intra-city ridesharing, and we definitely can’t copy what the airline and bus industries have done (RIP Greyhound). Our vision involves fleets of autonomous vehicles bringing business travellers, vacationers and more between the hundreds of cities that are within a few hundred kilometres of each other. So far, we have connected 6 cities with a combined population of nearly 3 million people. If we provide to access 100 times that number in 5 years, then we’ll be well on our way.
If you have an idea, and you want to talk to someone who also had one, and has tried to turn their idea into a reality, I am always open. Send me a message, I’ll happily sit down with you for a coffee to tell you my story and ask you about yours. I want you to succeed just as much as I want to succeed.
Think your idea is worth it? Let’s make it happen.
Tiger Woods won his 80th PGA tour title this Sunday, September 23. I was planning to delve deeper into my MIT course on AI and study the details of natural language processing, specifically syntactic parsing and the value of training data. Instead, I found myself glued to a browser window for four and a half hours this afternoon, watching my favourite golfer relive his glory days, winning by 2 shots and capturing the Tour Championship. It was totally worth every minute.
You see, even though humans are being vastly outpaced by AI and machines at every turn, humans are still better at many nuanced tasks. Sure, you can program a robot to swing a golf club and hit repeatable shots, but even the best golf robots still can’t beat the best humans over 18 holes with all the nuanced shots required for a round. Still, they can make a hole-in-one from time to time:
Despite humanity’s increasing incompetence compared to machines, it is still incredibly fun to watch a talented person, who has worked their entire life to perfect their craft, get out there and show the world what they’ve got. Doubly so if that person has recently recovered from spinal fusion surgery and hasn’t won for over five years on tour. Yeah, it’s just putting a little white ball in a hole, but the crowds and excitement that Tiger Woods is able to generate while he plays are unparalleled in golf, and possibly even in sports.
Tiger didn’t win the FedEx Cup, the PGA Tour’s season-long points-based title, but he came really close. If he had, he would’ve made $10,000,000 on the spot. Not too shabby. Regardless, with the highest viewership numbers in the history of the tournament and crowds so large that commentators said they’d never seen anything like it, Tiger Woods undoubtedly made the tour, its sponsors and network partners well over $10 Million this weekend. The amount of value that he generates for the tour and for golf is almost incalculable.
Of course, if you’re not a golf fan, you probably think that it’s boring to watch. That can be said about just about any sport or event that one doesn’t understand. Something is boring to us because we don’t understand the context, the history, and the implications of a certain event happening. Once we understand the subject and can opine and converse with other people about the topic then it becomes much more real and tangible.
I think the same principle applies to artificial intelligence as well as finance. Few understand the topic. It takes time to learn and understand the nuances that make the topics interesting and valuable. Once one does build the knowledge and expertise to apply skills in these areas, the results can be extraordinary.
So I’m going to pose a question for my future self and any would-be AI experts. In 2 years, will we be able to build software that can perfectly predict the outcome of major events in sports, specifically golf tournaments, with better results than the best human statisticians and algorithms?
My name is Rosario Fortugno. I’m an electrical engineer, MBA, and clean-tech entrepreneur making my way into the worlds of finance and AI.
This website is meant to provide some insight into my journey. My hope is that it communicates some of what I learn as I pursue my CFA (Chartered Financial Analyst) designation, highlighting examples from my business, as well as what I’m learning through the courses I’m taking in AI and machine learning from MIT and Udacity.
Basically, this is a way for me to show off my knowledge to the world…
Every day, I’m going to summarize what I’ve learned. The source of the material will either be from my CFA prep material, my own business, InOrbis Intercity, my MIT and Udacity AI courses, or just something I picked up along the way.
You’ll get a deep dive into the inner workings of my mind. The mind of a person who is probably trying to do too many things at once, but who is going to try to do them anyways, because, What the heck! Right?
Not only will you be learning alongside me, you will be joining me as I wade neck-deep into two of the most confusing and challenging spaces that the 21st century has to explore: artificial intelligence, and financial analysis.
A lot of what I discuss will be sourced from my other courses, so I’ll always try to provide links and images for reference to the source material. While I’ve always considered myself to be relatively creative, my propensity for original thought is limited by my expertise, so where I share something that isn’t my own work, I will try to give credit where credit is due.
Here we go! Let’s dive right in and get started. Today’s topic is Understanding Machine Learning. An undoubtedly simple subject. Let’s see how it goes 😀
