Insights & Innovations: Navigating AI, Cybersecurity, and Geopolitical Risks
Unveiling the Power of Chebyshev Polynomials in Modern Challenges
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Newsletter rundown:
Humans Anonymous: Not so Anonymous Anymore
Yoodli: A Unique Use Case of AI
Chebyshev Polynomials in Cybersecurity
Final Word
Humans Anonymous: Not so Anonymous Anymore
Long-time readers are aware of my enthusiasm for beta testing new and intriguing projects. Companies like Jasper.ai, Podmatch, ListenNotes, and others began as slow beta versions, yet I was willing to try firsthand.
I'm always open to beta testing things for free and providing honest feedback to founders. (RIP my inbox). One such discovery was Humans Anonymous, which I found back in early 2022 while exploring new apps on Apple’s Test Flight. It's an anonymous live audio platform fostering safe spaces for communities with similar life experiences. I liked it because it was a blend between Twitter spaces and YikYak (the relaunch version). I would jump on and talk about the highs and lows of running a growing business, without the fear of judgement from others. It was a casual version of talk therapy for me.
In October 2022, I ran into Nate Tepper, one of the co-founders, at a Combinations networking event. I’ll never forget the look on his face when I told him I was using the app. He was so surprised to find a real life user of his app in the wild! He rushed to pull out his phone and record an on-the-spot testimonial of the product.
Build. Learn. Share. Grow.
Yoodli: A Unique Use Case of AI
I’m stoked about real life use cases of AI that actually provide real value.
Yoodli is one of those companies.
A couple weeks ago, I realized my presentation skills needed some work.
I have been focused on removing all the “you knows”, and “ums” when I speak on camera.
So I hired Michael Davis from Speaking CPR to coach me up on how to get better.
Not only has Michael help me turn a corner on filler words, he introduced me to Yoodli, which is a private, real-time, AI coach — with stats to improve your speaking performance.
I particularly enjoyed the ability to record and then analyze the statistics afterward, akin to reviewing game footage as a collegiate athlete.
And I could chat back and forth with my human coach Michael, along different timestamps in the video.
The company is led by Varun Puri, a personable guy who generously shared with me insights into what it takes to build practical AI tools.
Here's a TED talk with Varun’s story.
I’m excited about the future of the company.
Build. Learn. Share. Grow.
Chebyshev Polynomials in Cybersecurity
A key problem between the digital and physical world is how to best contextualize movements through space.
Give me a second and I’ll explain how this all relates back to cybersecurity…which starts with my obsession with geopolitics.
When you consider geopolitics, I’m in the camp of Jacob Shapiro and take to Kjellén’s fundamental definition:
Defined simply, geopolitics is the belief that geography exerts a significant influence on states’ behavior.
When you expand this idea to geopolitical risks in financial markets, you cannot hedge a risk which you cannot measure, let alone define.
You need a physical map of the territory. (Notice the emphasis on physical)
Most analysts use geopolitical risk as a buzzword for any spat with a foreign country. The Federal Reserve’s definition of geopolitical risk (which is the most popular) looks at sentiment readings— text extracted from news headlines.
I believe that’s a poor measure of fundamental geopolitical risk.
We would never recommend an investment strategy based on what you read in the news!
I believe its important to have geopolitical models which support the pattern of the physical world in which we live — this should be the basis of geopolitical risk measurement.
This is how we get to Chebyshev Polynomials.
You must have precise mathematical measurements across space to replicate any model systematically.
From what I have studied, Chebyshev Polynomials do a really good job of going from Point A to Point B, by focusing on the absolute magnitude of the differences between coordinates of a pair of objects.
This captures the reference points necessary to build your model.
Back in August 2023 I wondered, “What if a discrete Chebyshev distance could be applied to NYU V-Lab’s COVOL and GJR-GARCH volatility analysis?”
Perhaps a risk event could use geographical coordinates as an input and applied to other capital market nodes in a risk weighted model.
This could solve the geopolitical measurement problem and be replicated systematically within sound mathematical parameters based on a physical world.
Since Robert Engel has been helpful in the past, I decided to ask him about the idea back but its been been on the backburner as other projects have come up.
So long story short, this is why I have an open Google alert for Chebyshev Polynomials…isn’t math beautiful sometimes?
Ok, now for the latest work of Chebshev Polynomial’s which applies to Cybersecurity.
A new study found that privacy and security of the information exchanged between automobiles in 5G-enabled vehicular networks is at risk.
Many of the smartest people in the world are all working hard to solve this cybersecurity issue.
Intruders can alter a vehicle’s transmitted message. This could wreak havoc for millions of future autonomous vehicles.
In order to solve these problems, various researchers have developed an authentication strategy for vehicular networks.
And this solutions have to apply math through space.
Academics have offered a solution to these problems in the form of an authentication technique that uses an elliptic curve or bilinear pair to sign messages and verify the signature through physical space.
But we know that there is a better way…
And this is where Chebyshev Polynomials come in.
The study found that greater performance and cost efficiency than would otherwise be possible when compared to an elliptic curve or bilinear pair had been employed.
The efficiency of their work in signing messages and verifying signatures is compared to other relevant systems in the figure compares the computational costs for the proposal with other schemes.
Chebyshev Polynomials are not only beautiful but also cost-effective to protect your 5G car from bad guys.
Could it do the same for measuring geopolitical risk?
Final Word
Thank you for reading and I am grateful and humbled to be able to learn, grow, and invest alongside you at Tuttle Ventures.
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Best,
Darin Tuttle, CFA
This is not investment advice. Do your own due diligence. Past performance is no guarantee of future results. Investing in the stock market involves gains and losses and may not be suitable for all investors. Information presented herein is subject to change without notice and should not be considered as a solicitation to buy or sell any security. Investors are encouraged to perform due diligence, consider their risk tolerance, investment goals, and consult with financial advisors before making investment decisions. I make no representation, warranty or undertaking, express or implied, as to the accuracy, reliability, completeness, or reasonableness of the information contained in this report. Any assumptions, opinions and estimates expressed in this report constitute my judgment as of the date thereof and is subject to change without notice. Any projections contained in the report are based on a number of assumptions as to market conditions. There is no guarantee that projected outcomes will be achieved.
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