Some Professors put together IKEA-inspired instructional booklets for their algorithms and data-structures lectures. The idea was to make easy-to-understand explanations by removing words, and only using images. Ideally, this would allow them to be understood regardless of their native language or culture.
This is a pretty cool idea, or at least I thought so. My youngest son said, "I don't particularly understand IKEA directions or algorithms .... so this is basically the worst of both worlds for me." Finally, we agree about something!
Hopefully, you find it helpful. If not, there's always Wikipedia.
Data is the fastest-growing commodity, and is today’s “wild west” and the battlefield of today’s tech titans. We talk about AI as this gold rush, but data is the underpinning of it all.
A staggering 328.77 million terabytes of data are created daily, which means around 120 zettabytes of data will be generated this year.
Rapid growth means little time to create adequate rules. Everyone’s jumping to own more data than the next and to protect that data from prying eyes.
As a great example of this, I often warn people to keep their intellectual property off of ChatGPT or other hosted language models.
I also see it trading, but it’s pervasive in every industry and our personal lives as well.
Collecting basic data and using basic analytics used to be enough ... but not anymore. The game is changing.
For example, traders used to focus on price data ... but there has been an influx of firms using alternative data sets and extraordinary hardware and software investments to find an edge. If you’re using the same data sources as your competitors and competing on the same set of beliefs, it’s hard to find a sustainable edge.
Understanding the game others are playing (and the rules of that game) is important. However, that’s only table stakes.
Figuring out where you can find extra insight, or where you can make the invisible visible, creates a moat between you and your competition and lets you play your own game.
Here is a quick high-level video about Data as fuel for your business. Check it out.
It is interesting to think about what’s driving the new world (of trading, technology, AI, etc.), which often involves identifying what drove the old world.
History has a way of repeating itself. Even when it doesn’t repeat itself, it often rhymes.
With that said, the key to unlocking the pathway to the new world often comes from a new or alternative data set that lets you approach the problem, challenge, or opportunity from a different perspective.
Before e-mails, fax machines were amazing. Before cars, people were happy with horses and buggies.
These comparisons help explain the importance of data in today’s new world economics.
Petroleum has played a pivotal role in human advancement since the Industrial Revolution. It fueled (and still fuels) our creativity, technology advancements, and a variety of derivative byproducts. There are direct competitors to fossil fuels that are gaining steam, but I think it’s more interesting to compare petroleum to data due to their parallels in effect on innovation.
Pumping crude oil out of the ground and transforming it into a finished product is not a simple process. Yet, it is relatively easy for someone to understand the process at a high level. You have to locate a reservoir, drill, capture the resource, and then refine it to the desired product – heating oil, gasoline, asphalt, plastics, etc.
The same is true for data.
You've got to figure out what data you might have, how it might be useful, you have to figure out how to refine it, clean it, fix it, curate it, transform it into something useful, and then how to deliver it to the people that need it in their business. And even if you've done this, you then have to make people aware that it's there, that it's changing, or how they might use it. For people who do it well, it's an incredible edge. – Howard Getson
In a sense, data fuels the information economy much like oil fuels the industrial economy. The amount of power someone has can be correlated to their control of and access to these resources. Likewise, things that diminish or constrain access or use of these resources can lead to extreme consequences.
Why Data Is Better Than Oil
The analogy works, but it’s just that, an analogy, and the more you analyze it, the more it falls apart. Unlike the finite resource that is oil, data is all around us and increasing at an exponential rate, so the game is a little different:
Data is a renewable resource. It’s durable, it’s reusable, and it’s being produced faster than we can process it.
Because it’s not a scarce resource, there’s no urge to hoard it – you can use it, transform it, and share it knowing that it won’t diminish.
Data becomes more valuable the more you use it.
As the world’s oil reserves dwindle, and renewable resources grow in popularity and effectiveness, the relative value of oil drops. It’s unlikely that will happen to data.
Also, while data transport is important, it’s not expensive the way oil is. It can be transported and replicated at light speed.
Using alternative data gives traders an advantage, but it doesn’t always have to be confidential or hard-to-find information. Traders now have access to vast amounts of structured and unstructured data. A significant source that many overlook is the data produced through their own process or the metadata from their own trades or transactions.
In the very near future, I expect these systems to be able to go out and search for different sources of information. It's almost like the algorithm becomes an omnivore. Instead of simply looking at market data or transactional data, or even metadata, it starts to look for connections or feedback loops that are profitable in sources of data that the human would never have thought of. – Howard Getson
In a word of caution, there are two common mistakes people make when making data-driven decisions. First, people often become slaves to the data, losing focus on the bigger picture. It’s the same mistake people make with AI. Both are tools, not the end goal. Second, even the most insightful data can’t predict black swans. It’s important to exercise caution. Prepare for the unexpected.
The future of data is bright, but it’s also littered with potential challenges. Privacy concerns and data misuse are hot-button topics, as are fake news and the ability of systems to generate misleading data. In addition, as we gain access to more data, our ability to separate signal from noise becomes more important.
I think one of the biggest problems facing our youth - and really all of us - is how much information is thrust at us every waking moment of the day. No previous generation has had this much access to data. As a result, many are actually less informed than in the past. Soundbites become the entire news story, and nuance gets lost in the echo chambers.
The question becomes, how do you capitalize on data without becoming a victim of it?
Figuring out how to leverage new capabilities to achieve what you want is a master skill. It is a big part of what I do. Consequently, many of my conversations revolve around new technologies and how to utilize them. Likewise, I frequently write about these types of topics in blog posts. However, I often incorporate these discussions as brief segments at the conclusion of articles on broader subjects or specific technologies.
Recently, I created a video that consolidates many of my high-level thoughts about this. Take a look.
Adapting To New Technologies
The future is scary to people who have gotten comfortable in the present. They hope the future looks like the past because, if that happens, they already have it solved.
But that's not typically how life happens.
I often say, "Standing still is moving backward," and "You're either growing or dying."
So, when I hear people pushing back against new technologies, I cringe a little.
Smart people find a way to take advantage of promising new technologies rather than avoid them.
To use a surfing metaphor, it is easier (and more fun) to ride a wave than it is to resist it.
A skilled surfer doesn't try to catch every wave. Likewise, knowing you want or need to ride doesn't mean you should blindly do it. It is OK to skip a smaller wave to ride a bigger one (or to wait for a smarter or safer starting point).
When adapting to new technologies, I think there's a 4-step model you should follow.
Improve
Innovate
Redefine
Transform
It's almost like Maslow's hierarchy of needs ... you have to deal with things like food and shelter before you can deal with affiliation or self-actualization.
The Improve phase is the most important because this is when you take what you already do and make it better. Doing this first increases productivity and revenue in your business and buys time and space for you to focus on what comes next. It's also a way to show that you're making progress in the right direction, increasing capabilities, and building confidence (which is the fuel you need to continue making progress).
Next, many try and jump straight to transformation ... but that's a mistake.
Transform is the big hairy, audacious goal that you want to make possible. It's the mountain top you're trying to climb. It's helpful to know what that is. But, when trying to climb the mountain, you still have to take the steps in front of you.
The first step on the mountain is to Innovate. It's about what you could do, and what you should do – instead of what you're already doing.
Redefine is where you start climbing the mountain and adding new capabilities to your arsenal. You're now at a stage where you can imagine a bigger future and grow your vision to match your new capabilities. In a sense, you're playing the same game, but at a different level and with different expectations.
When you finally make it to Transform, you are playing a new game (often on a different playing field) and you're likely influencing not just your company but other companies. At this point, it's common for former competitors to come to you with ideas and money, looking to collaborate.
Another key mistake entrepreneurs make is they pivot to something completely new. When you're charting a path up a new mountain, you will find unstable ground or insurmountable peaks. At that point, many people give up and look for something new. They start wandering in different directions. That's a lot of wasted movement.
My rule at Capitalogix is "This or something better." When we reach a roadblock, we're allowed to go around it, but only if it's an improvement on our current goals.
This framework is the underpinning of two other frameworks I've shared before. In the spirit of getting it all in one place, I want to share those as well.
Understanding human behavior and what stays the same is the secret to technology adoption at scale - because it's not the best technology that wins, it's the most popular ... and you can "win the game" with fantastic usage of unadopted technology. Earlier, I mentioned you don't have to ride every wave. You just have to skillfully ride the waves you choose. This framework is meant to help you do that. It helps you turn thoughts into things and explains how ideas scale with respect to capabilities, audience, and monetization.
While the Technology Adoption Model Framework stages are important, the ultimate takeaway is that you don't have to predict what's coming, only how human nature works in response to the capabilities in front of them.
It's a bit cliche, but to paraphrase Wayne Gretzky, you have to skate to where you think the puck will be (or, at least, lean in the right direction).
Desire fuels commerce. As money fuels progress, the desire grows ... and so does the money funding that path. As such, the path forward is relatively easy to imagine.
Each stage is really about the opportunity to scale desire and adoption.
It isn't really about building the technology. Instead, it is about supporting the desire.
If you understand what is coming, you don't have to build it, but you can figure out where you want to build something that will make that more likely or benefit from it.
This model is fractal. It works on many levels of magnification or iteration. What first looks like a product is later seen as a prototype for something bigger.
For example, as a Product transforms into a Platform, it becomes almost like an industry of its own. Consequently, it becomes the seed for a new set of Capabilities, Prototypes, and Products.
SpaceX's goal to get to Mars feels like their North Star right now ... but once it's achieved, it becomes the foundation for new goals.
This Framework helps you validate capabilities before sinking resources into them.
In the video, I walk you through several examples of companies, their innovations, and how they fit into each stage. I even used Capitalogix as an example.
I'm also attaching a fillable PDF of the form we used so that you can run through this with your business as well.
Both of the above frameworks are high-level approaches to help you understand the path forward. They're strategic. The following is more tactical and best used in team discussions.
Taking Your First Steps
Innovation Activity Centers are the underpinning of each stage. They're the framework within the framework that ensures you're equipped to take decisive action. And drive your journey toward transformation.
While the stages and seasons of your business change, the activity centers and foci within your business don't have to. That's what allows you to stay steadfast in ever-changing currents.
Each of these activity centers requires a different type of person working on it, different KPIs, and different timelines.
I shot a video going into more detail on these activity centers as well.
Conclusion
Understanding these models makes it easier to understand and anticipate the capabilities, constraints, and milestones that define the path forward (regardless of how the world changes). They're a path towards technology adoption - though there are others.
We are making lots of progress refining these models, which are the basis for our plans to expand our Amplified Intelligence Platform. I look forward to improving it and sharing it with you all again.
Ultimately, frameworks aren't important if you aren't using them, and imperfect action beats perfect planning if you never act - but I hope you use these frameworks to help clear the path as you walk it.
Feel free to reach out if you have any questions or comments about the idea (or how to implement it).
It is easy to keep up – until you pause or slow down.
Being an Early Adopter was a big part of my identity. At this point in my life, I am still early with respect to new technologies, but I feel like I'm losing touch with a lot of today's culture.
Perhaps this started over a decade ago? I remember finding my sons' slang and music off-putting.
As an aside, my youngest son, Zach, went through a phase where it felt like he used the verbal tic ... "Dude" in every other sentence. Parenting trick – I broke his habit by screaming "FOOPDEEDOO!!" every time he said it, regardless of when it happened, where we were, or who we were with.
If it's crazy and it works ... it's not crazy. He certainly stopped saying "dude".
OK, back to the point. I realize that the Top 40 is basically a list of 40 songs that I don't know (and feel like I only randomly know some of the artists). Meanwhile, my staff laughingly refer to my favorite stations on SiriusXM radio as old-man music.
To make the point further, my research assistant asked me if I knew about Bad Bunny. To me, it sounded like a Disney cartoon for Halloween. But, apparently, he is a Grammy-winning recording artist who won "Album of the Year" for music that I had never heard.
It didn't take long to get to the list of top Spotify artists. For the record, I do know most of those artists – but admittedly few of their songs.
But as I said, listening to the Top 40 is getting harder for me. Where's the rock (or songs with discernable melodies)?!
Meanwhile, I'm about to start a new art exhibit. I call it "Jen Sleeps At Pop Concerts"
So far, we've got Taylor Swift, Coldplay, Beyoncé, Ariana Grande, Bob Seger, the Eagles, and the Rolling Stones. In case you're curious, she did not fall asleep at John Legend, Queen, or Ed Sheeran.
We talk a lot about automation – but tend to focus on the less tangible robots. Meaning, we talk about algorithms and AI, quantum computing, and how entrepreneurs can benefit from these new technologies.
However, a significant segment of automation is industrial (and often robotic process automation). Henry Ford and the assembly line revolutionized the world when they took the time to make a car from over 12 hours to just over 90 minutes.
It's interesting to think about more classic automation, and how different it is today from 1913 ... Of course, the level of machinery has grown exponentially, but so have the processes and the capabilities we expect. I flashback to Kanban and Toyota and what that did not only for the automobile industry ... but for corporations and small businesses around the globe.
New industries are also creating new jobs. With that said, recognize that people are increasingly resistant to doing the work we tend to automate. That is part of why it got automated in the first place. Another reason is that birth rates are dropping globally, and we always strive to do more with less.
Think about countries like Japan - which rely heavily on manufacturing ... but are seeing their already small populations decline. What do they do when their plants sit empty due to labor shortages?
Or, what about agriculture? We've already seen an exodus of youth who don't want to be involved in farming due to the long hours and grueling work... How do you keep up with the production necessary to feed the world?
We often think about robotics as taking our jobs, but the reality underpinning today (and the paradigm that will drive the future) is that automation sustains industries.
When labor can't keep up with demand, robotics fills the gap, whether it occurs in manufacturing, agriculture, or medicine.
As robotics get more capable, it won't be long before that's robotic surgeons are a normal part of a hospital's medical suite.
The same is true for AI. It will supplement gaps in countless industries.
These technologies are coming to your industry. It's inevitable. If you fight it, you'll feel strife and stress about the changing workforce. If you get ahead of it, you'll find endless opportunities to pursue your passions. As society shifts, I hope we see an influx of entrepreneurs to help drive the next era of innovation.
What do you think will happen?
P.S. Do you get my weekly round-up of links and thoughts on AI, exponential technologies, markets, and other interesting stuff? Or my new AI-curated newsletter? I believe you'll find them useful and fun. Happy to add you or anyone else you want to get it. Click here for the sign-up link.
I love football. As such, it is fun for me to watch the games. But I also like the business of the game as well.
Over time, I've become a fan of the league ... and how deliberate they are about building teams and developing players.
Last week, I got to give a series of talks to a high-level entrepreneur group called Breakthrough Mastermind. Some of the other speakers included NFL Hall of Famer Mike Singletary and a starter on the league-leading Dallas Cowboys Defense, Osa Odighizuwa. Here is a picture of us from the event.
Let me know if you want a link to the actual presentations. I talked about AI and how it frees you to be your best. Osa spoke about what it takes to be a Pro, and Mike talked about teamwork and building teams.
It is Football Season. And, if you know me, then you know I'm a Cowboys fan (despite being raised in Philly, with season tickets to the Eagles – and Boston, with season tickets to the Patriots).
So, the week one 40-0 victory over the NY Giants was fun to watch.
It was even more fun after I saw some stats about this loss.
The 40-0 win was the largest shutout victory in Dallas's history.
Dallas is the fifth team in NFL history to open their season with a 40-plus-point shutout on the road, and the first since the 1999 Steelers.
The Cowboys are the first team in NFL history to open the season with a 40-plus-point shutout of a team that made the playoffs the previous season.
But feeding my occasional need for Schadenfreude ... the stats get worse for the Giants.
In this game, they lost 40-0, got sacked seven times, to the Dallas Cowboys zero, they also lost the turnover margin 3-0, and had their opening drive field goal attempt blocked (and then returned for a touchdown), and their QB, Daniel Jones, then threw a pick-six.
Supposedly, no team has done that in a single season - let alone a single game.
And for some additional contrast and dynamic tension ... ponder this!
Jerry Jones Is Going to Live Forever.
As if the Cowboy's experience wasn't enough to bring people in, Jerry has now immortalized himself as the mirror from Sleeping Beauty, excuse me, I mean as a virtual AI screen at AT&T Stadium.
It's a truly interactive experience where you can ask Jerry questions, and get responses in his voice - from an AI trained on the real Jerry Jones.
NEW at #ATTStadium: Meet Jerry Jones – An Interactive Experience. Ask @dallascowboys' Owner Jerry Jones questions and get his responses generated by AI technology for a unique, interactive experience.
People joke that new technologies are always adopted by porn first, gambling second, and then the entertainment industry after. These technologies have made their way to the NFL which means they are on their way to much broader adoption sooner than you might expect.
I'm launching a new newsletter - with a twist. The newsletter will be fully automated and produced by an AI we are training to pick out the articles to highlight and share.
Don't Let the Past Get In the Way of the New.
Even though a lot of what I think and write about is innovation, exponential technologies, and automation ... until now, what we write and send has been the result of human effort rather than artificial intelligence or technology.
Sure, portions of the process leverage technology ... but humans have written the vast majority of what you read here.
It takes many hours a week. Frankly, many more hours than you would guess!
We currently send out two weekly e-mails. The one that comes out on Fridays is a hand-curated list of links that I found interesting during the week. The Sunday edition has two articles written by me and my son, Zach, along with a few more links.
Deep down, I know that AI is now good enough to curate a high-quality list of articles in a more efficient, effective, and certain way than what I produce.
I know that I will lose ... But I also know that I will win. And so will you!
This does not have to be an "either-or" decision. This is a "both-and" decision. Meaning ... I don't have to decide whether to stop producing by hand, in order to also produce with AI.
One of the challenges with AI is that the fitness function you choose significantly impacts the result you achieve.
If the purpose of the newsletter was only to produce a quality newsletter in less time, with less effort, and with greater certainty that readers engage ... then the result is inevitable. The AI newsletter wins.
However, I didn't choose to produce the newsletter for the newsletter. The newsletter is a natural result of my nature. I did the research because I wanted to do the research.
I am naturally curious and passionate about these things. It's what I think about. It's who I am ... and what I do.
One of my beliefs about AI is that you shouldn't use it to replace your Unique Ability. In other words, don't try to automate, delegate, or outsource something you are great at, if it gives you energy. The goal is to magnify "magic," not replace it. The goal is to spotlight and support those areas by taking away things that are frustrating, bothersome, distracting, or taking cycles away from something that would produce a greater result with less energy.
The point is, I can do both. I will still do research because it gives me pleasure, knowledge, and a greater likelihood of continuing to learn and grow. I will continue to write and curate.
Why? Because it's also an important part of my thinking process. I think when I speak. I think when I write. But more importantly, I think when I am preparing to speak or write. I wouldn't be me if I didn't go through that process. I also don't believe my ideas or opinions would continue evolving without the challenge and effort.
And I will also enjoy evolving new and different channels of communication.
Hopefully, we all benefit.
So, I hope you sign up for the new newsletter. We'll be sending out the first e-mail within the next week or two.
As I've said, I love writing and researching. I'm an innovator at heart.
Many read my articles because of my commitment to AI, new technologies, and the future. Most of my exploration has been centered on Capitalogix and our Amplified Intelligence Platform. But there are a lot of exciting new use cases of AI, and I'm exploring many of those apps right now.
A Thousand Mile Journey Starts With a Single Step.
Hopefully, you are excited about the new newsletter and the value you will get from it.
I'm confident it will only improve – because it learns from what you value.
To start, the newsletter will focus on these three topic areas:
How to build a resilient business in a fast-changing world
The Psychology of technology & technology addiction
Business ethics and AI ethics in today's world.
But that is just the starting point. It is set up to consider the same type of offshoots as I normally would. So, it will remain diverse and educational.
What happens doesn't matter nearly as much as what you make it mean ... and what you choose to do.
For example, Dallas has been 100+ degrees almost all summer, and nothing stops. You'll see people running outside, dogs walking, sports being played. My son plays 8+ hour rugby tournaments in that heat, and no one bats an eye.
Growing up in New England, we were woefully underprepared for that heat. The world would stop. On the other hand, 8 inches of snow was nothing, but a little bit of ice ... and Texas shuts down.
Snow isn't 'good' or 'bad' … and neither was the change of plans.
Perspective.
Fund managers recognize the importance of sensibly diversifying risks and opportunities.
Be that as it may, as Mother Jonesreported in the wake of the 2009 financial crisis, the nation's ten largest financial institutions held 54% of our total financial assets (compared to the 20% they held in 1990). Meanwhile, the number of banks has dropped from almost 15,000 to barely 4,000.
Many people are shocked by a chart like this. It must be 'bad' to have so much controlled by so few, right?
But it isn't hard to find a version of this story playing out in other industries: Print Media, Music, Broadcast Channels, and Consumer Products … this type of consolidation happens for a reason.
A firm that marshals more resources gains a competitive advantage and has more ways to win.
They benefit from economies of scale, transactional leverage, better distribution and partners, and more ways to diversify risks. In addition, if they work to communicate, collaborate, and coordinate their actions (and data), they can unlock opportunities that others don't have (or can't see).
Here is a Chart Showing Some of the 'Winners' at that Game.
Here is a more specific example. You probably think you are familiar with Nestlé. It is famous for chocolate. But did you realize it was an almost $300 billion corporation … and the biggest food company in the world? Nestlé owns nearly 8,000 different brands worldwide and takes a stake in (or is partnered with) many others. This network includes shampoo company L'Oreal, baby food giant Gerber, clothing brand Diesel, and pet food makers Purina and Friskies.
I share an article about Gartner’s Hype Cycle for Emerging Technologies each year. It does a great job of documenting what technologies are reaching maturity and which technologies’ ascents are being enhanced by the cultural zeitgeist (hype, momentum, great timing, etc.).
Creating a report like this requires a unique mixture of technological analysis and insight, an acute understanding of human nature, and a lot of common sense.
Identifying which technologies are making real waves (and thus will impact the world more) is a monumental task. Gartner’s report is a great benchmark to compare with your perception of reality.
A quick look back at past reports shows that 2021 saw the inclusion of NFTs and advancements in AI. It also focused on the increasing ubiquity of technology. 2022 built on those trends, recognizing that we were moving towards immersive experiences, faster digital transformations, and the adoption of exponential AI capabilities. For reference, click here to see what Gartner predicted last year.
Meanwhile, let’s look at the 2023 version of Gartner’s Hype Cycle for Emerging Technologies report. 2023 has some meaningful changes – and is best understood by where things are placed on Gartner’s framework called the “Hype Cycle.”
What’s a “Hype Cycle”?
As technology advances, it is human nature to get excited about the possibilities ... and to get disappointed when those expectations aren’t met.
At its core, the Hype Cycle tells us where in the product’s timeline we are – and how long it likely will take the technology to hit maturity. It attempts to tell us which technologies will survive the hype and have the potential to become a part of our daily lives.
Gartner’s Hype Cycle Report is a considered analysis of market excitement, maturity, and the benefit of various technologies. It aggregates data and distills more than 2,000 technologies into a concise and contextually understandable snapshot of where various emerging technologies sit in their hype cycle.
Peak of Inflated Expectations (Success stories through early publicity),
Trough of Disillusionment (waning interest),
Slope of Enlightenment (2nd & 3rd generation products appear), and
Plateau of Productivity (Mainstream adoption starts).
Understanding this hype cycle framework enables you to ask important questions like “How will these technologies impact my business?” and “Which technologies can I trust to stay relevant in 5 years?”
That said - it’s worth acknowledging that the hype cycle can’t predict which technologies will survive the trough of disillusionment and which ones will fade into obscurity.
What’s exciting this year?
Before focusing on this year, it’s important to remember that, in 2019, Gartner shifted towards spotlighting new technologies at the expense of technologies that would normally persist through multiple iterations of the cycle. This change helps account for the increasing number of innovations and technology introductions we are exposed to compared to the norm when they first started producing this report. As a result, many of the technologies highlighted over the past couple of years (like Augmented Intelligence, 5G, biochips, the decentralized web, etc.) are now represented within newer modalities or distinctions.
It’s also worth noting the impact of the pandemic on the prevalent technologies.
This year, the key technologies were bucketed into four major themes.
Emergent AI represents the technologies that increase workforce productivity and differentiation from competitors. The hallmark technology of this theme is Generative AI, but another exciting one is AI Simulation - where environments and people can be replicated virtually to run simulations and ask questions. Imagine being able to create a digital replica of yourself (or a specialist in different disciplines) to bounce ideas off of ... or to create a virtual advisory board to help process tough issues or test the response to various situations, opportunities, or challenges.
Developer Experience (DevX) is precisely what it sounds like. Enhancing the developer suite of technologies not only enhances your engineering team but also helps attract and retain high-level employees. Value Stream Management Platforms (VSMP) is a good example of this. VSMP is intended to optimize product delivery from end to end.
Pervasive Cloud focuses on how cloud computing is evolving. This theme is also focused on creating an end-to-end use case. In an ideal world, this enables easy and automated operational scaling, lots of cloud-native tools, and stability improvements. A sample technology under this umbrella would be WebAssembly, a lightweight virtual machine and binary code format that would enable secure, high-performance applications on your web pages.
Last but not least, we have Human-Centric Security and Privacy. In response to growing security concerns, this theme recognizes the pressure companies face to create cultures and systems that value and protect security. AI Trust, risk, and security management (AI TRiSM) is the culmination of this effort and represents a holistic approach to governance, reliability, efficacy, and more. This will be an important frontier to develop as we innovate faster.
Last year, the main focus was on the spread of emerging technologies. Last year’s themes focused on the ubiquity of AI in all facets of life – and the increasing immersiveness of these technologies.
This year, the focus seems to be on responding to that increasing ubiquity. It’s about building systems that help adopt these new technologies efficiently ... while also protecting yourself from making mistakes at lightspeed.
Of course, I’m always most interested in the intersection of AI and other spaces. Last year, AI became a lighthouse for businesses to work toward. It’s continued to shine a light this year. In my opinion, this points towards the increasing maturity and adoption of AI. The opportunity cost of adopting AI into your business is continuing to decrease.
Meanwhile, these systems are also becoming more autonomic, self-managing, and self-learning. I’m excited to see Gartner emphasizing what this does for humans - not what it takes away from them. Remember, the heart of artificial intelligence is human - and it continues to free us up to be more human.
As we reach new echelons of AI, you’ll likely see increasing examples of over-hype and short-term failures. You often miss a rung on the ladder as you reach for new heights, but it doesn’t mean you should stop climbing. More importantly, it doesn’t mean failure or even a lack of progress. Challenges and practical realities act as force functions that forge better, more robust, resilient, and adaptable solutions that do what you want (or something better). It just takes longer than you initially wanted or hoped.
To paraphrase a quote I have up on the wall in my office from Rudiger Dornbusch ... Things often take longer to happen than you think they will, and then they happen faster than you thought they could.
Many of these technologies have been hyped for years - but the hype cycle differs from the adoption cycle. We often overestimate what we can do in a year and underestimate what we can do in ten years.
I say it often ... we live in interesting times!
Which technologies do you think will survive the hype?
Riding The Data Wave - Data Is Becoming a New Asset Class
Data is the fastest-growing commodity, and is today’s “wild west” and the battlefield of today’s tech titans. We talk about AI as this gold rush, but data is the underpinning of it all.
A staggering 328.77 million terabytes of data are created daily, which means around 120 zettabytes of data will be generated this year.
Video is still growing rapidly, but so is IoT, with more than 15% annual growth. There are now almost 20 billion connected devices.
Alphabet, Amazon, Apple, Facebook, and Microsoft all have unprecedented amounts of data (and power).
Rapid growth means little time to create adequate rules. Everyone’s jumping to own more data than the next and to protect that data from prying eyes.
As a great example of this, I often warn people to keep their intellectual property off of ChatGPT or other hosted language models.
I also see it trading, but it’s pervasive in every industry and our personal lives as well.
Collecting basic data and using basic analytics used to be enough ... but not anymore. The game is changing.
For example, traders used to focus on price data ... but there has been an influx of firms using alternative data sets and extraordinary hardware and software investments to find an edge. If you’re using the same data sources as your competitors and competing on the same set of beliefs, it’s hard to find a sustainable edge.
Understanding the game others are playing (and the rules of that game) is important. However, that’s only table stakes.
Figuring out where you can find extra insight, or where you can make the invisible visible, creates a moat between you and your competition and lets you play your own game.
Here is a quick high-level video about Data as fuel for your business. Check it out.
It is interesting to think about what’s driving the new world (of trading, technology, AI, etc.), which often involves identifying what drove the old world.
History has a way of repeating itself. Even when it doesn’t repeat itself, it often rhymes.
With that said, the key to unlocking the pathway to the new world often comes from a new or alternative data set that lets you approach the problem, challenge, or opportunity from a different perspective.
Before e-mails, fax machines were amazing. Before cars, people were happy with horses and buggies.
These comparisons help explain the importance of data in today’s new world economics.
gapingvoid
Data as the New Oil
Petroleum has played a pivotal role in human advancement since the Industrial Revolution. It fueled (and still fuels) our creativity, technology advancements, and a variety of derivative byproducts. There are direct competitors to fossil fuels that are gaining steam, but I think it’s more interesting to compare petroleum to data due to their parallels in effect on innovation.
Pumping crude oil out of the ground and transforming it into a finished product is not a simple process. Yet, it is relatively easy for someone to understand the process at a high level. You have to locate a reservoir, drill, capture the resource, and then refine it to the desired product – heating oil, gasoline, asphalt, plastics, etc.
The same is true for data.
In a sense, data fuels the information economy much like oil fuels the industrial economy. The amount of power someone has can be correlated to their control of and access to these resources. Likewise, things that diminish or constrain access or use of these resources can lead to extreme consequences.
Why Data Is Better Than Oil
The analogy works, but it’s just that, an analogy, and the more you analyze it, the more it falls apart. Unlike the finite resource that is oil, data is all around us and increasing at an exponential rate, so the game is a little different:
Using alternative data gives traders an advantage, but it doesn’t always have to be confidential or hard-to-find information. Traders now have access to vast amounts of structured and unstructured data. A significant source that many overlook is the data produced through their own process or the metadata from their own trades or transactions.
In a word of caution, there are two common mistakes people make when making data-driven decisions. First, people often become slaves to the data, losing focus on the bigger picture. It’s the same mistake people make with AI. Both are tools, not the end goal. Second, even the most insightful data can’t predict black swans. It’s important to exercise caution. Prepare for the unexpected.
The future of data is bright, but it’s also littered with potential challenges. Privacy concerns and data misuse are hot-button topics, as are fake news and the ability of systems to generate misleading data. In addition, as we gain access to more data, our ability to separate signal from noise becomes more important.
I think one of the biggest problems facing our youth - and really all of us - is how much information is thrust at us every waking moment of the day. No previous generation has had this much access to data. As a result, many are actually less informed than in the past. Soundbites become the entire news story, and nuance gets lost in the echo chambers.
The question becomes, how do you capitalize on data without becoming a victim of it?
Food for thought!
Posted at 03:58 PM in Business, Current Affairs, Gadgets, Ideas, Market Commentary, Science, Trading, Trading Tools, Web/Tech | Permalink | Comments (0)
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