In 1985, Steve Jobs imagined computers enabling students to engage with the minds of history’s greatest thinkers. Nearly 40 years later, his vision is all but fully realized.

While visiting Lunds University in Sweden, Steve Jobs gave a rather prophetic speech on the rise of computing technology in the education space. At a time when portable cassette players were considered cutting edge and the personal computing industry was looking particularly bleak, Jobs managed to succinctly lay out a vision for what wonders would come.

What is more impressive, even a bit eerie, is how relevant his perspective is as applied to today’s artificial intelligence breakthroughs.

I can’t ask Aristotle a question. I mean, I can, but I won’t get an answer. And so my hope is that in our lifetimes, we can make a tool of a new kind, of an interactive kind.

Today, you can do just that. Don’t believe me? Email aristotle@signaltheory.com your burning philosophical questions and see for yourself.

In this article, I will be breaking down this three minute clip and arguing that today’s AI breakthroughs are not to be feared, but welcomed with sincere curiosity as we usher in a new era of human capability, creativity, and energy.

We’re, as you know, living in the wake of the last revolution, which was a new source of free energy. And that was the free energy of petrochemicals. And it completely transformed society.

Jobs sets the scene by alluding to the many advances we have made in this post-revolutionary world. A world that was ushered in by the emergence of a new and seemingly boundless energy resource — hydrocarbons. We now know that these energy sources are anything but boundless, but one must recognize the ripple effects of this revolution have touched every corner of our world, leaving an indelible mark on our societies, economies, and cultures.

Importantly, this revolution has allowed humanity’s focus to shift from the daily grind of manual labor and survival to the pursuit of higher goals and aspirations. The abundance of energy provided by hydrocarbons has freed us from the shackles of physical toil, allowing us to invest our time and resources into innovation, creativity, and progress. This is an outcome we see realized today through advances in computing, just as Jobs predicted.

We are now entering another revolution of free energy. Macintosh, as you know, uses less power than a few of those light bulbs, and yet can save us a few hours a day, or give us a whole new experience. And it’s free intellectual energy. It’s crude, very crude. But it’s getting more refined year after year after year.

This is where things get a bit eerie. Jobs was right: at the time, this “free intellectual energy” was indeed very crude. But now, several decades later, it has been refined into pure, automated cognition. I’m reminded of this more recent discussion with Mustafa Suleyman, CEO of Microsoft AI as well as the co-founder and former head of applied AI at DeepMind, an AI company acquired by Google.

But I digress.

Jobs showed a bit more humanity in his daydreaming of the future.

My hope is someday, when the next Aristotle is alive, we can capture the underlying world view of that Aristotle in a computer. And someday, some student will be able to not only read the words Aristotle wrote, but ask Aristotle a question and get an answer.

Students today already know this is possible. So why are we fighting it?

I’m reminded of all the times I heard, “you won’t have a calculator in your pocket everywhere you go” growing up. Today, we have the sum of all human knowledge at our fingertips — why are some institutions acting like that’s a bad thing?

So this is a beginning. I think that, as you know right now, the computer industry is in the tank. Personal computers, big computers, everything. And it’s difficult. It’s a difficult time. But I’m sure that Henry Ford had a few bad quarters back in the 1920s.

It is all too easy to get in the trap of thinking, “if the technology isn’t perfect today, it isn’t worth pursuing.” I see AI mocked every day in my position. And I get it — a lot of it is worth poking fun at. But make no mistake, the tidal wave is coming. We just have to zoom out a little bit.

I think that this year may be a delay. This year, we may look back and say, well, 1985 was a slow year. But there is such momentum behind this that it will happen.

No one thinks about 1985 being a slow year now. But what does your screen time look like this week? Steve Jobs also said in 2008, “These waves of technology, you can see them way before they happen, and you just have to choose wisely which ones you’re going to surf.” Not to be blunt, but if you are in a position to ride this wave or be buried by it, which are you going to choose?

It will happen within twenty years. It probably will happen within ten years. But it could happen within five years.

This last part of the video reminds me of something Bill Gates said: “Most people overestimate what they can do in one year and underestimate what they can do in ten years.” While I believe this is true of organizations too, it certainly is true for the individual now more than ever.

There is a lot of static in the AI space right now. Between the hype grifters and the skeptics, organizations and institutions will soon face tough decisions in a noisy environment full of conflicting information. I would advise zooming out a bit and imagining what the world might look like in 2064.

Do you think this technology is going to get better or worse?

There’s this sort of infamous Reddit post on a forum dedicated to people sharing retirement and financial advice. This user concludes that the currency of life is time, not money — not exactly novel, but I found myself thinking of it today.

Technology in the 21st century, namely the mass adoption of personal computing, was a monumental shift for humanity in part because it represents a major milestone in our shift away from manual labor and into cognitive labor. This technology promised to achieve what any great technology seeks: efficiency, to do what couldn’t be done otherwise, and to enable a better quality of life for all.

But the feedback I get from many of my peers is they feel overly connected with technology and seek joy in a form that is purposefully disconnected. Computing is interwoven into so many facets of our lives — work, socialization, utility — it feels as though even a momentary break from our phone is a reclamation of our humanity.

So it seems like a logical leap, particularly given the prevalence of science fiction themes in popular culture, that AI is bound to accelerate our sense of connection with technology — something I can appreciate not many people having desire for.

I’d like to suggest that AI has a non-zero chance of actually improving our relationship with technology. In fact, AI may just help us reclaim lost ground.

Reclaiming Lost Ground

When I think of parts of my own humanity I have lost to technology, even if temporarily, I think of things like: tech addiction, decreased face-to-face interaction, information overload, sedentary lifestyle, and privacy norms.

Tech Addiction & Information Overload

Anyone familiar with addiction can attest: it is not a matter of willpower. More often, the people who succeed at breaking it put themselves in situations where they don’t have to rely on willpower alone. Each time I turn off notifications for a new application on my phone, I feel a small sense of victory — a reclamation.

It is easy to feel overloaded with information from apps that were built using attention-optimizing algorithms. These systems are able to hijack your own biology, capitalizing on the reward center of your brain to keep you scrolling.

As a reaction, there is growing evidence of a wider interest in “digital detox” specifically by Gen Z and Millennials. “Dumbphones” are even on the rise.

We’re Going on a Bear Hunt

I believe if you were to zoom out on the timeline of humanity, there is a non-zero chance that the current moment AI is in marks a shift from computing directly to computing in a way that feels so natural, it is indirect by comparison. Perhaps we grapple with the growing pains of tech not by going around it, but through it.

Consider a small example like Ray Ban and Meta’s new smart glasses. There’s no display. They’re just a really good pair of glasses that happen to have AI and bone conductive headphones built in. With their built-in camera, I can leave my phone behind when I go on hikes and still enjoy sharing photos after I’m done with the activity, allowing me to remain more in the moment.

It doesn’t take a great leap of faith to imagine that kind of technology paired with a number of other new advances in the AI space. Take Groq’s invention of the LPU, for instance. When they demonstrated their ability to make large language models run in a near-instant fashion, a world of possibilities was unlocked. Imagine being able to have a conversation with an AI assistant that actually understood cadence and was able to respond without perceptual delay or direct prompting.

Or take for instance the many AI hardware products last year. One of which, the Rabbit R1, promises to build an entirely new kind of operating system (which they call a large action model, or “LAM”) which completes actions for you at request through its ability to interact with apps you use every day. Imagine being able to speak your standup notes to your digital assistant and have those automatically reported via your team’s proper channels. Or imagine never having to schedule another meeting or appointment ever again as Google demonstrated in 2019.

How long will it be before even more natural interfaces emerge? Microsoft has famously contributed to this space through their early exploration into micro-interactions. Now, 14 years later, we’re starting to see these in real products.

From Microsoft’s 2010 paper titled Interactions:

“We have progressed from batch computing with punch cards, to interactive command line systems, to mouse-based graphical user interfaces, and more recently to mobile computing. Each of these paradigm shifts has drastically changed the way we use technology for work and life, often in unpredictable and profound ways.”

What if you could compute just by thinking? Of course there’s Elon’s method of putting a chip in your brain. But did you know Apple owns a AirPods design patent featuring EEG capabilities to monitor brain activity? And that AI can now passively translate words and sentences from your real-time EEG data? What may sound creepy to some enables communication altogether for others. A computing ecosystem that you don’t have to hold in front of your face to operate allows us all to be more connected to the moment, to each other, and to our work.

The Future

Through more natural interactions and interfaces, might we ditch the small, bright rectangular screens we’ve all grown so accustom to these last 16 years? Ironically, integrating technology deeper into our world may carry with it the unexpected result of making technology feel more out of the way. I believe there is a chance AI enables us all to disconnect from technology and dream of a new, better future.

The big questions I think we should be asking ourselves: if we are in the middle of a shift from physical manual labor to cognitive manual labor, what’s next? What do we want to accomplish individually and together that we could not before? What kind of culture do we want to collectively build? Where is the joy in tomorrow that could not be found in the world we live in today?

The summer after I graduated from high school, my friend and I would skate through our rural town’s back roads, staying up all night. We would take breaks to smoke cheap gas station cigars we had recently come of age to purchase and discuss everything from wingsuiting to artificial intelligence. He was a big Kurzweil guy, and this was 2011 mind you.

As we entered college, we drifted apart but still shared some AI papers once in a while.

I started college studying cellular biology and even worked in a graduate lab studying prostate cancer. I have also always been fascinated by technology and innovation. So now that I work for a behavioral science focused advertising firm, it feels like a perfect time to tell the fascinating story of how today’s learning models are modeled after the human brain.

Large Language Models

A lot has changed in the last decade in AI. With the introduction of large language models (LLMs) like GPT-4, it feels like the next decade will be even wilder. Even if Bill Gates is right that generative AI has plateaued, the progress made over just the last twelve months will continue to alter society for decades to come.

While society catches up to this recent progress, I believe the real problems LLMs are solving (natural language processing, machine translation, question and answer, content generation, and much more) will continue effecting change to a wide range of businesses and social structures.

The central breakthrough that accelerated this tech’s capabilities into an exponential state of growth was first introduced by Google employees in a 2017 white paper titled “Attention Is All You Need.” By effectively open sourcing their research before developing products that leverage this newfound methodology, Google changed the game — and they did so by mimicking human behavior.

The concept of “attention” in LLMs is not just a technical innovation but a reflection of how humans prioritize sensory information. Our brains focus on what matters most at any given moment, filtering out the rest. LLMs, through attention mechanisms, emulate this process by identifying and prioritizing the most relevant pieces of information within vast datasets.

The significance of this leap cannot be overstated — it is as though AI found a new gear, propelling forward our ability to interact with and through machines in ways that were previously the domain of science fiction.

Hierarchical Temporal Memory

LLMs did not exist in 2014 when my friend and I were chatting about AI. Instead, much of the research into machine learning was in hierarchical temporal memory (HTM). This approach to AI is also inspired by the human brain. HTM tries to model the neocortex’s structure and information processing mechanisms directly, mimicking the way neurons connect and form patterns of activity based on spatial and temporal inputs.

By comparison, LLMs, through deep learning techniques, are inspired more loosely by the brain’s neural networks. Today’s AI is built with more focus on the functionality and adaptability of human cognition than the physical structure of the neocortex. This evolution marks a shift from models that excel in specific tasks to those capable of generalizing knowledge across a wide range of domains, much like the human brain.

The Structure of the Neocortex

Your neocortex is that folded mass covering your brain which accounts for the vast majority of your overall brain volume. This purely mammalian innovation offers us a significant leg up on other animals through the development of memories, identity, and intelligence.

HTM puts such emphasis on mimicking the physical structure of the human brain because of a unique trait of the neocortex’s cellular structure. If you were to take a slice of the brain, you would see the neocortex holds a uniform cellular structure across its various regions, whether it is focused on vision, hearing, or language. This uniformity hints at a common approach to processing inputs, where raw sensory data is refined into increasingly abstract concepts.

Similarly, LLMs, through their training and operational framework, have reduced problems across different modalities — images, audio, or video — to text-based representations. This approach allows LLMs to leverage their extensive text-based training to process and generate content across these modalities.

The Thousand Brains Theory of Intelligence

The process by which a network of neurons assembles for us a coherent model of our world is a puzzle which the Thousand Brains Theory of Intelligence offers a revolutionary perspective on. Traditionally, neuroscientists believed in a singular, unified model for each sense.

Take a keychain, for instance. It was assumed that sensory inputs, whether auditory or tactile, would converge onto this solitary model, enabling recognition. However, a closer examination of the neocortex reveals it to be composed of approximately 150,000 cortical columns, each functioning like a mini-brain with the capacity to generate independent models based on sensory inputs. This raises a compelling question: why do we perceive the keychain as a singular entity rather than a fragmented collection of sensory inputs?

The answer lies in the extensive network of long-distance connections within the neocortex, facilitating communication between these cortical columns. The Thousand Brains Theory posits that these connections enable the columns to integrate their individual models, achieving a consensus that shapes our singular perception of objects and concepts.

This mechanism of consensus is not within our conscious awareness, yet it fundamentally shapes our interaction with the world. It is those cortical columns which learn and store information through the establishment of reference frames — spatial maps that organize knowledge and facilitate thinking and problem-solving. This insight not only demystifies the nature of knowledge and cognition but also outlines a blueprint for the development of truly intelligent machines, capable of reasoning and learning about the world in a manner akin to human intelligence.

The Future

I still sometimes imagine myself laying in the middle of a country road at midnight looking up at the stars wondering what the future will look like. There is so much serendipity in seeing the exponential uncovering of intelligence through the convergence of two fields I sincerely love — biology and technology.

But it also has me wondering about the value of intelligence moving forward. If intelligence ceases to be something humans are uniquely capable of, what then is the value of cognitive intelligence — a tool for labor that many of us rely on and seek out for our own enjoyment.

What happens when intelligent learning systems become embodied in advanced robotics? The era of robotics only effecting change to large industries is coming to a close. Expect to interact directly with intelligent robots in the next decade as they enter professional services. It will not be the first time humanity has adapted to great change, but this may be our grandest transformation yet.

It is as though we have created our own little aliens here on Earth. Tonight, some angsty teenager will stare up at the stars, modeling the glow of the Milky Way through visual sensory inputs and the breeze of the nighttime air through tactile sensory inputs, wondering if there is anything else out there worth exploring.

Meanwhile, there is another kind of intelligence brewing here at home.

Rediscovering self-determination via the unfettered dreams of my teen years.

When I was 17, my friend Josh and I would sit in his basement and stay up until the early hours of the morning watching the same YouTube video on repeat. Specifically this video of Loïc Jean-Albert wingsuit BASE jumping.

This was 2010. Still the very early days of YouTube and GoPro. It was hard to find videos like that unless you knew where to look. But one of us stumbled across that video of Loïc carving through the Norwegian mountains and we were both hooked.

Avatar had just come out a few months prior and the notion of flying your body through beautiful, earthy terrain fascinated us both. We agreed — this was surely what bliss and freedom felt like.

So on my 18th birthday, the first day it was legal for me to do so in the US, I went for a skydive. I even referenced the YouTube video at 8,000-ft.

At the end of that jump, with the most ridiculous hair you’ll hopefully ever see on me, I say, “I’m gonna definitely do it again.” But it would be a full decade before I jumped out of a plane again.

I specifically remember doing that cartwheel out of the plane thinking, “How much fun would it be to not be attached to someone right now.” Turns out: super fun.

My next skydive and first solo was on April 18, 2021, just a couple weeks after my 28th birthday. It was the first of 25 jumps alongside other requirements I made toward getting my license.

As of today, I have 133 skydives and each one is more fun than the last. My favorite part is the endless progression in the sport — there’s so much to learn.

I did the accelerated freefall (AFF) program at Falcon Skydiving, located just twenty minutes north of downtown Kansas City. At the time, I didn’t realize how lucky I was to have convenient access to a great dropzone.

I’ve met some really great people at Falcon. Their staff is top-notch and I’ve been blessed with access to amazing coaches, including Kevin Stone, a world-class wingsuit pilot with thousands of skydives and hundreds of BASE jumps. I’ve made some great friends: Carl, Cortland, Kaan, just to name a few.

The Missouri River holds a special place in my heart now. I’ll always hold that little bend in the river, just North of downtown Kansas City, as my favorite marker.

Nestled between that bend, guarded by railroad tracks and trees to the east and hundreds of rows of soy and corn to the north, west, and south, a private airport — Noah’s Ark Airport.

I still have a very long way to go before I try wingsuit BASE jumping in Norway. Truth is, I may never get there. But I am enjoying the hell out of the journey and that long road to get there feels more exciting than discouraging. Fulfilling that dream of flying my body feels exactly like you’d expect. When you get it right — bliss, freedom. Time dilates, you’re nowhere else.

Who knows? Maybe we have more intuitive, unfettered access to our truest dreams and deepest desires as a kid.

I remember sitting in my room and having the realization that I could pursue a skydiving license if I wanted to. I wasn’t 18 anymore, I had money to spend. “Skydiving courses near me.”

I believe there are certain pivotal moments when life becomes enriched with opportunity, only requiring a foot on the pedal to actualize. For me, that Google search was one of those moments.

If you find yourself lost, unsure of what you want out of life, I recommend asking your younger self. It may seem counterintuitive. I wouldn’t trust a 17 year old with much. But this isn’t any 17 year old. This is you. I trust myself with my own dreams and I’m so glad I’m pursuing this one.

Follow me on Instagram @elijah.io for short clips from my latest leaps!

In May 2000, my family moved from Omaha, NE to a small town in Southwest Missouri called Nixa. I was seven and my brother was two.

Six years later, my father was diagnosed with Parkinson’s Disease (PD) after initially going to see the doctor about a slight tremor he had on one side.

He went two days without telling anyone. Even Mom.

Let me start by saying my father is alive. I am lucky to still have both of my parents in my life. I just saw them last weekend for Mother’s Day and my brother’s birthday. I am so thankful for that time.

But he has changed. His voice has changed as happens with many Parkinson’s patients. Many living with PD exhibit a muted vocal expression, speaking in a monotonous tone and conveying limited emotional range. But it’s been a slow burn — thank goodness.

We moved for work, which was the very thing that drove my father to get out of bed every morning. And when this new, young hotshot school Superintendent came in from Omaha, the local news took note.

The first time my brother saw this footage was in 2017 at my father’s retirement roast. I was sitting right next to him. The look on his face as he watched and listened has stuck with me over the years.

He doesn’t remember my dad’s voice sounding like that.

He was excited and also, I think, a little bit disappointed that he didn’t get more time with this more charismatic-seeming version of our father.

AI will never replace that, of course, but in the whirlwind of dystopic AI predictions, there does seem to be promise for good as well.

Bank Your Voice

It’s shockingly easy to clone voices now with just a few seconds of audio.

When I heard about ElevenLabs’ VoiceLab, a voice cloning tool, this idea immediately came to mind. I isolated my father’s voice from the interview and then simply uploaded that audio export (.mp3) to ElevenLabs and bam.

It was my father’s voice from 2000, saying anything I typed into a box.

Obviously there are a ton of ethical questions here, which is why you should always ensure you’ve obtained explicit and informed permission before using someone’s voice. But I was able to create an audio book version of his children’s book, Golf Ball Envy, in his former voice. Sharing this with my family brought about laughter and genuine interest.

I asked him to read a short note to my brother, Jacob.

Here’s the 2000 version of him reading it.

It sort of permanently sounds like he’s giving an interview to a TV station to me, but given better audio quality inputs, you can make it sound identical.

Like in this sample I created using audio from an iPhone video shot in an empty room. It’s my brother’s real voice as he records this for Mother’s Day.

Now here’s the AI version of him saying hi to my girlfriend, Julia.

It even allows you to hear what your voice would sound like in another language, as though you spoke it fluently. Here’s Jacob in Japanese.

I’m not the first person to think about this. Intel has a new project called I Will Always Be Me which “banks” the voices of those affected by motor neurone diseases so that they can communicate using their own voice.

More “AI for Good” News

Neural networks, like the voice cloning tool I used here, show real promise of predicting Parkinson’s Disease before symptoms show up.

I first saw this on Twitter:

Rowan Cheung on Twitter: "Published in ACS Central Science, the study analyzed biomarkers in bodily fluids using neural networks.CRANK-MS showed 96% accuracy in detecting Parkinson's.Researchers also found correlations between certain metabolites and Parkinson's, which could help future studies. pic.twitter.com/pR1ScQy0hx / Twitter"

Published in ACS Central Science, the study analyzed biomarkers in bodily fluids using neural networks.CRANK-MS showed 96% accuracy in detecting Parkinson's.Researchers also found correlations between certain metabolites and Parkinson's, which could help future studies. pic.twitter.com/pR1ScQy0hx

I uploaded the full white paper to ChatPDF.com, which uses the power of GPT to allow users to ask PDF files questions about its content.

Me: What is difference between the neural network models and the traditional machine learning models?

PDF: Neural network (NN) models differ from traditional machine learning (ML) models in their ability to learn complex non-linear relationships between input features and output variables. NN models are composed of multiple layers of interconnected nodes that can learn and extract features from raw data without the need for manual feature engineering. In contrast, traditional ML models typically require manual feature selection and engineering to extract relevant information from raw data. NN models can also handle high-dimensional data with many correlated features, which can be challenging for traditional ML models. Additionally, NN models can provide interpretable results by identifying significant biomarkers that contribute to disease prediction, which is important for clinical applications. Overall, NN models offer a powerful tool for analyzing large metabolomics data sets and developing accurate prediction models for disease diagnosis.

Me: Does it mention commercial availability of testing?

PDF: No, the file does not mention anything about the commercial availability of testing. It mainly focuses on the development of an interpretable neural network (NN) framework to accurately predict Parkinson’s disease (PD) from blood plasma metabolomics data using machine learning (ML) approaches. The study aims to provide opportunities for early diagnosis of disease by analyzing metabolite biomarkers and to develop accurate prediction models for disease diagnosis using large metabolomics data sets.

Last year’s digital security mishaps brought privacy to the forefront of our attention. Ironically, some of the most notable digital security unravellings of 2016 could have been mitigated by following basic privacy practices.

At Evolve, most of my normal work is as far away from “mission-critical” as it gets—building brochure websites and running social campaigns for local businesses. Still, I consider the below list “standard procedure” when it comes to protecting my client’s data.

1. Use 2-Factor Authentication

Mitigate brute-force attempts on your password authentication.

Just about every major platform—from social platforms like Facebook and Twitter to business services like cloud hosting providers and distributed network solutions—provide some variation of 2-factor authentication (2FA).

If this is your first time hearing about 2FA, here’s the down-n-dirty: when you enter your password on a website or application, said service will then prompt you for an additional “one-time password” (OTP). These OTPs can be sent to your phone via SMS, generated on your phone via a 2FA app, or even generated on a hardware solution like YubiKey.

Yes, activating 2FA on your accounts will mean that you are entering essentially double the number of passwords to access your account; digital security and convenience are not necessarily mutually exclusive, but they are often at odds with one-another, trading-off as you scale one or the other. My next suggestion, however, will increase both security and convenience.

2. Use a Reputable Password Manager

Increase security and convenience for yourself and your business.

I prefer LastPass, but there are a plethora of other personal and enterprise-ready password managers out there; most have a free version. Essentially, a password manager does exactly what the name would imply—it helps manage all the different passwords you may have across various social platforms, forums, and even sensitive accounts like online banking portals.

Some software, like LastPass, will even filter through all of your account information to look for security weaknesses (shown above). This makes it extraordinarily easy for the average user to set one universal password, while maintaining a diverse set of unique passwords for each account—and the best part is you never have to remember more than one password again.

3. Encrypt Your Online Communication

You don’t have to be a cypherpunk to use Signal and encrypted email.

I think most people would be surprised at how accessible strong encryption can be. I would be willing to bet the word “encryption” scares away a good chunk of people from even trying—it sounds complex.

Encryption is for everyone now.

Why not get setup with professional-grade encrypted instant messaging and email right now? Download the ultra-secure Signal, for Android or iOS, then have your friends download it; you can even share photos and video securely.

After that, create an account on ProtonMail to easily encrypt your email for free. It is just as easy as Gmail to setup, but leaps and bounds more secure. Your inbox will be encrypted by default, while your messages have an option to be encrypted with a password. The message can be sent to any email address, including non-ProtonMail accounts, and the password can be communicated using a separate secure channel like Signal (or courier bird). The photo above shows what receiving an encrypted message from ProtonMail looks like—your message even has an expiration date for added security.

Okay, I get it—maybe not all of you need “this much” digital security—your OpSec game is as strong as needed for protecting your cat photos and meme library. But if you could increase your security by factors of ten, while, at worst, encountering nominal inconvenience, wouldn’t you?

Let me know by emailing me directly at elijah@eyi.io or tweeting at me @elijah_io—thanks for reading!

Elijah Kleinsmith is a digital producer living in Kansas City, Missouri. He is also the Founder of Evolve Your Identity. In his free time, Elijah flies drones, builds websites, and researches digital security. Visit his personal website.