It's one of the few reports that I make sure to track every year. It does a good job of explaining what technologies are reaching maturity, and which technologies are being supported by the cultural zeitgeist.
Technology has become cultural. It influences almost every aspect of everyday life.
Identifying which technologies are making real waves (and will impact the world) can be a monumental task. Gartner's report is a great benchmark to compare reality against.
2021’s trends aren’t all that different from 2020 – but you can now find NFTs, digital humans, and physics-informed AI on the list. While there have been a lot of innovations, the industry movers have stayed the same - advanced AI and analytics, post-classical computing and communication, and the increasing ubiquity of technology (sensors, augmentation, IoT, etc.).
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 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 life.
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 succinct 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 being 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 I focus on this year, it's important to remember that in 2019 Gartner shifted towards introducing new technologies at the expense of technologies that would normally persist through multiple iterations of the cycle. This change is indicative of more innovation and more technologies being introduced than in the genesis of this report. Many of the technologies from the past couple of years (like Augmented Intelligence, 5G, biochips, the decentralized web, etc.) are represented within newer modalities or distinctions.
It's also worth noting the impact of the pandemic on the prevalent technologies.
Last year, the key technologies were bucketed into 5 major trends – but this year Gartner focused on 3 major themes.
Engineering Trust represents technologies that create the infrastructure of trusted businesses. The emphasis is on security, reliability, and repeatability of practices. Change is hard, and so is the integration of new technologies into existing businesses. That’s why it’s important to do it right the first time to prevent technologies from being cost centers. Sample technologies from this year’s hype cycle include real-time incident command centers, data fabric, and sovereign cloud. If I could include a technology not on the list – I’d heavily support the blockchain as an instrumental asset in this domain.
Accelerating Growth is the second theme, and it builds on top of “Engineering Trust”. Once you have a good business core you can focus on driving organizational and industrial growth. Last year, "composite architectures" was a trend that emphasized the shift to agile/responsive architectures and decentralization. This year, many of the technologies gaining attention are AI-driven tools that can be applied to improve and accelerate human-facing support. Think HR training, customer service, and onboarding. As a culture, we’ve become more comfortable with the ubiquity of AI and technology, and while there are still ethical and societal roadblocks, you can expect many new use-cases to show up sooner rather than later. Sample technologies from this year’s hype cycle include digital humans, industry cloud, and quantum machine learning. To see more of my thoughts on Accelerating Growth check out my article on “Turning Thoughts Into Things”.
Sculpting Change is the third theme and closes off what I believe is a very strong thematic year from Gartner. The nexus of this theme is that change is disruptive and that many of the technologies we will gravitate toward will be attempting to create order from the chaos. This is especially important in the context of rapid innovation, societal changes, and Covid-19. The emphasis of these technologies is on generalized and reliable technologies that are less brittle and specific than our current uses. AI is already a massively exciting space, but many of the use cases are too specific to be useful. Sample technologies include physics-informed AI, composable applications, and influence engineering.
If we compare this year’s list to last year, I think we’ve seen a massive increase in the maturity of “Digital Me”, the integration of technology with people in both reality and virtual reality. But, we’ve seen less progress on “Beyond Silicon” despite the massive chip shortage. It’s a space I’m hoping to see more improvement in, fast, to meet increasing demand.
Of course, I’m always most interested in the intersection of AI and other spaces. Last year, many of the emerging trends were AI-centric, and this year it feels as if AI has become the underpinning of broader trends. In my opinion, this points towards the increasing maturity and adoption of AI. Models are becoming more generalized, and able to attack more problems. They're becoming integrated with human behavior and even with humans.
As we reach new echelons of AI, it's likely that you'll see over-hype and short-term failures. As you reach for new heights, you often miss a rung on the ladder... but it doesn't mean you 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, stronger, more resilient, and adaptable solutions that do what you wanted (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 is different than the adoption cycle. We often overestimate a year and underestimate 10.
Which technologies do you think will survive the hype?
On September 11, 2001, 19 extremist Al Qaeda militants hijacked four airliners and carried out suicide attacks against targets in the United States. Nearly 3000 people were killed during the attacks.
Do you remember where you were when it happened?
For most Americans, it’s easy. That moment – and its ripples – are imprinted on our minds. For my son, Zach, it was in his 3rd-grade class. They wheeled in a TV on a cart for the students to watch. One of his classmate’s uncles was killed in the attack.
A colleague of mine was supposed to be in the tower that day but rescheduled a meeting for the following day – narrowly missing it.
And now 20 years have passed. So much has changed. So much has stayed the same. We’ve analyzed the events of that morning a thousand ways from different vantage points ... and it’s still impossible to fully grasp the weight of the event.
It’s crazy to imagine that there are now full-fledged adults who have no memory of it.
And with that, Visual Capitalist put together a great chronology of the event.
As we honor those that gave their lives – or had them taken from them – it’s a powerful reminder.
Last week, ESPN televised a blow-out of Ohio's Bishop Sycamore high school football program by Florida's IMG Academy. The score was 58-0. But that has little to do with this story.
The supposed school in Colombus, Ohio, is not recognized by the state's athletic association … and the department of education doesn't list a school with that name. Despite that, they somehow scammed ESPN into scheduling the game.
Here are some of the troubling data-points.
The head coach of the team, Roy Johnson, has an active warrant out for his arrest
They falsely claimed they had multiple Division 1 college prospects
ESPN couldn't verify any of the players in their scouting databases.
The director of Bishop Sycamore claims the school is not a scam, and his son is in the program. On the other hand, the “school” currently doesn't even have a working website.
It's impressive that in this era of information access, a school could defraud the nation, not once, but twice.
I even heard that Cam Newton got picked up by Bishop Sycamore after getting dropped from the Patriots.
Not really … but this is an interesting story – and reflects how easy it is for “fake” things and get real coverage.
Recently, however, it seems that we are increasingly presented with issues divided into polar opposite points of view, with little to no tolerance for disagreement.
Nonetheless, not all topics need to be debated or negotiated.
Sometimes, a fact is a fact.
Hopefully, this video won't step on any toes - but if you're a "flat earther," I wouldn't watch.
Here's a clip from Behind The Curve (a documentary on the flat earth society) that I think perfectly shows confirmation bias.
Start with the evidence and then form a conclusion. Doing that in reverse doesn't tend to work out as well.
As a polite reminder, if a conspiracy relies on millions of people (as well as different countries and organizations) to all commit to the disinformation campaign ... it's not likely true.
As Occam's razor states, the simplest explanation is often the correct one.
While the calculation is based on five factors, the primary conditions indicate a big disagreement about market conditions.
For example, two of the conditions are that a substantial number of stocks have to be at yearly highs, while a substantial number of stocks have to be at new annual lows. Ultimately, it is hard for those two conditions to be met in a short period of time unless there's uncertainty in the market. Moreover, after a rally, uncertainty is often a precursor to a decline.
In addition, technically (for the pattern to be complete), a second sighting of the five elements must occur within 36 days. Logically, lingering uncertainty is a momentum killer.
Should I Be Worried?
This week, Cumberland Advisors' shared the following from Art Cashin, Director of Floor Operations for UBS Financial Services at the New York Stock Exchange.
Art had this to say:
“I had told Carl Quintanilla on CNBC’s Squawk on the Street in an interview about 10:20 that I thought the chatroom bears were turning a bit more aggressive. Several were trying to point out that we had had two Hindenburg Omens in a row. In case you had forgotten, a Hindenburg Omen is rather arcane indicator that takes as a measurement the ratio or relationship between the new 52-week highs and the new 52-week lows. It is quite unusual to have two days back-to-back with new Hindenburg Omens.
Now, you have to be a little bit careful about the Hindenburg Omen because, over the last 35 or 40 years, we haven’t had a market ‘crash’ without the presence of the Hindenburg Omen, and that is what chatroom bears were pushing. You have to remember the other part of that, which is while there has always been a Hindenburg Omen before a crash, there has not been a crash after every Hindenburg Omen. To use a rather poor analogy, it is almost like saying, we have never had a flood without rain. But, then again, every time it rains, it doesn’t mean it is going to flood.
So, it was, nevertheless, an effective tool among the chatroom types just to make people nervous. I am not sure how many have bought into the Hindenburg aspect, but it was one of those ‘Wait a minute – should I be aggressive on the buy-side or should I wait and hold back here?’ I think it had some of that effect.” - Art Cashin
From my perspective, while this pattern may have correctly predicted every big stock market swoon of the past two decades (including the October 2008 decline), not every Hindenburg Omen has been followed by a crash. Resorting to a geometry analogy: All rectangles are squares, but not all squares are rectangles.
Times are strange - and there's reason to be wary of the markets, but indicators like this are a reason to be cautious, not a basis for trading decisions.
Each year I look forward to Camp Kotok, or as I like to call it Economists in Nature. It's basically 5 days of canoeing, fishing, and dining with economists, wealth managers, traders, investors and more.
One of few chances for people from these backgrounds to come together and talk about the world, big trends, investing, economics, politics, and more ... in an open and safe forum. The event goes by the Chatham House Rule - which basically means you can share the information you receive, but not who said it.
This year we talked about everything from China, digital currencies, the pandemic, and the state of markets.
Interestingly, for all the takeaways I could focus on, the main takeaway was uncertainty.
For all the intelligent and "in-the-know" people in the room, very few people had clear opinions of what was going to happen. There were too many variables at play, and while they posited a lot of potential paths, it feels like the general census was we're at a crossroads with many potential futures in front of us.
Despite the general uncertainty in the room, it wasn't fear-laden. The general mood was optimistic, and for the most part, everyone sees paths toward economic success post-COVID.
With that said, when and what "post-COVID" means is another issue.
One of the other key discussions that came up often was the new generation of workers and their changing relationship with work. It's plain to see the rate of quitting is higher, that wages are rising, and it's getting hard to fill minimum wage jobs. It's hard to get employees back in an office space, and many are willing to take pay cuts or switch to other companies to stay at home.
The long-term impact on our economy (and our culture) is yet to be seen.
At a mastermind meeting last week, Landon Downs from 1Qbit spoke on the state of technology. Landon and I agree on a lot of things - and one of those things he emphasized heavily. AI is in a period of massive innovation. It's a renaissance, or springtime, or whatever euphemism you want to use. But it's only springtime for AI if you can take advantage of it.
Adding to that, he explained that a current constraint might become a big short-term limitation to how widespread AI can grow. The constraint is that there is a global chip shortage (and it could be an issue until 2023).
The chip shortage is probably a bigger problem than you imagine because microchips are in everything from refrigerators to toothbrushes - not just high-tech computers. This has the potential to be a massive disruptor, especially in the tech industry.
Building and running smart AI systems takes a lot of computing power, and as more competitors enter the scene, not only will the cost to play increase, but so will the potential you get turned away at the door.
To a certain extent, the AI arms race becomes a chip arms race.
As I thought about the chip shortage, and its impact on the next few years, it also made me brainstorm what else I thought would be the most influential shifts that would influence me and my business (and potentially the world).
Here's my top 5, and I'd love to hear yours.
Compute Power is going to increase, and the ability to brute force problems will create new possibilities. Quantum computing will become more important and likely available for commercial use.
New and better AI platforms will transition AI from a tool for specialists to a commodity for everyday people - it won't just be Artificial Intelligence, it will be Amplified Intelligence (helping people make better decisions, take smarter actions, and continually measure and improve performance).
Blockchain and authenticated provenance are going to become more important as the world becomes increasingly digital. Trust and transparency will be important as indelible logs are needed for finance, medical, armies, etc.
IoT will become more pervasive, enabling near digital omniscience as everything becomes a sensor that transmits data up the chain.
Mass customization will become the norm instead of simple mass production as hardware, data, and AI continues to improve products, medicine, custom supplements, and just about everything else.
The mood was pretty optimistic and bullish. As you might expect, there was a growing interest in crypto and blockchain … and a growing sense of “us versus them” directed at China and Russia. We live in interesting times!
If you want to download my presentation slides, you can do that here.
Happiness is a complex concept comprised of positive emotions, lack of negative emotions, comfort, freedom, wealth, and more.
Regardless of how hard it is to quantify ... humans strive for it.
Likewise, it is hard to imagine a well-balanced and objective "Happiness Report" because so much of the data required to compile it seems subjective and requires self-reporting.
Nonetheless, the World Happiness Report does a good job with its annual look at quantifiable factors (like health, wealth, GDP, and life expectancy) and more intangible factors (like social support, generosity, emotions, and perceptions of local government and businesses). Click the image below to view the Report.
In their 2021 report, there was a significant focus on the effect of COVID-19 on happiness levels and mental health.
As you might expect, the pandemic caused a significant increase in negative emotions reported. Specifically, there was a significant increase in reports of worry and sadness across the ninety-five countries surveyed. Moreover, the decline in mental health was higher in groups that already had mental health problems - women, young people, and poorer people.
What's interesting about this is the resilience and bounce-back seen within the data. Considering the amount of disruption to households this past year, it's remarkable how stable the averages for countries have been.
Ultimately, globally, humans persevered in the face of economic insecurity, anxiety, and challenges to mental and physical health.
Despite the changes in emotions in 2020, overall life satisfaction rebounded quickly after March of 2020.
While there was a decrease in overall happiness, the relative balance in the face of such adversity may point towards the existence of a hedonic treadmill - or set point of happiness. I'm always impressed by what people can get used to, and how you can find pockets of joy in even the hardest times ... or how people with everything they could ever ask for can still feel profound unhappiness.
It's oddly beautiful and a great reminder that happiness comes from within. Obviously, our environment and circumstances play a part. It's easier to be content with a roof over your head and a stable job. But, after a certain point, it's on us to create our realities.
Last week, we talked about the future of AI and the potential for AI to start taking over some jobs (freeing humans to raise their chins and do something better and more meaningful).
One of the key factors I talked about was "mindset." For example, consider whether you’re in a scarcity or abundance mindset? If you are in a scarcity mindset, that probably means you see life as a finite pie with only so many slices ... and if someone else gets a big slice (or something new interrupts you getting your slice), you worry that you might not get what you deserve. On the other hand, an abundance mindset recognizes that there’s plenty out there for everybody, and if there’s no more pie, we can always create new pies (or something better).
I have a picture in my conference room that says energy might be the most important thing to measure.
Yes, it means what it sounds like - but, for us, it also means more.
We use A.I. to trade. So, measuring performance is important. But so are all sorts of production, efficiency, and effectiveness measures.
There are hundreds of important metrics we track day-to-day. Energy impacts many of them (and absolutely affects your ability to respond to change).
Energy affects how you feel, what you do, and what you make things mean. Consequently, energy is an effective way to measure your values too.
We’ve seen numerous inflection points in the past with the introduction of electricity, and then the assembly line and the industrial revolution, with the internet, and now with AI.
There’s always disruption, and there’s always pain, but your mindset and energy can radically change what that means to you ... and what you choose to do.
AI is coming. Disruption is coming! It's no longer simply possible; it's not even just probable; it is inevitable. With that said, what you make it mean and how you respond is up to you.
In a prior post, I shared a mindset scorecard I created at Genius Network.
Normally, Genius Network is private, and these recordings are for internal use only; but I asked permission to share my impromptu session with you.
Check it out. In the first 5 minutes, I introduce the scorecard concept. For the next 10 minutes, you'll get an extra look at the resulting group discussion.
Think of each comparison as a spectrum. They're not necessarily "one-or-the-other," but they can help identify where you are on the scale of "what to avoid" versus "what you want."
Blaming <-----> Encouraging
Insistent <-----> Inspirational
Fearful <-----> Abundant
Steadfast <-----> Curious
Clogging <-----> Cleansing
Resentful <-----> Grateful
Zero-Sum <-----> Relational
Small-Minded <-----> Visionary
These words mean something to me, but they may need tooling to work for you. Changing the names, the order of the comparisons, the number of comparisons, etc., can have a profound effect on the usefulness of this scorecard to you.
I encourage you to think about how you could use this scorecard and how you can bring attention to those people and actions that best embody the traits that are important to you or your business.
Identifying the words you want to embody and the person you want to be can help make you responsive to change and a better version of yourself.
Gartner's 2021 Hype Cycle For Emerging Technologies
Each year, I share an article about Gartner's Hype Cycle for Emerging Technologies. Here’s last year’s.
It's one of the few reports that I make sure to track every year. It does a good job of explaining what technologies are reaching maturity, and which technologies are being supported by the cultural zeitgeist.
Technology has become cultural. It influences almost every aspect of everyday life.
Identifying which technologies are making real waves (and will impact the world) can be a monumental task. Gartner's report is a great benchmark to compare reality against.
2021’s trends aren’t all that different from 2020 – but you can now find NFTs, digital humans, and physics-informed AI on the list. While there have been a lot of innovations, the industry movers have stayed the same - advanced AI and analytics, post-classical computing and communication, and the increasing ubiquity of technology (sensors, augmentation, IoT, etc.).
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 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 life.
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 succinct and contextually understandable snapshot of where various emerging technologies sit in their hype cycle.
Here are the five regions of Gartner's Hype Cycle framework:
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 being 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 I focus on this year, it's important to remember that in 2019 Gartner shifted towards introducing new technologies at the expense of technologies that would normally persist through multiple iterations of the cycle. This change is indicative of more innovation and more technologies being introduced than in the genesis of this report. Many of the technologies from the past couple of years (like Augmented Intelligence, 5G, biochips, the decentralized web, etc.) are represented within newer modalities or distinctions.
It's also worth noting the impact of the pandemic on the prevalent technologies.
For comparison, here's my article from 2019, and here's my article from 2015. Click on the chart below to see a larger version of this year's Hype Cycle.
via Gartner
Last year, the key technologies were bucketed into 5 major trends – but this year Gartner focused on 3 major themes.
If we compare this year’s list to last year, I think we’ve seen a massive increase in the maturity of “Digital Me”, the integration of technology with people in both reality and virtual reality. But, we’ve seen less progress on “Beyond Silicon” despite the massive chip shortage. It’s a space I’m hoping to see more improvement in, fast, to meet increasing demand.
Of course, I’m always most interested in the intersection of AI and other spaces. Last year, many of the emerging trends were AI-centric, and this year it feels as if AI has become the underpinning of broader trends. In my opinion, this points towards the increasing maturity and adoption of AI. Models are becoming more generalized, and able to attack more problems. They're becoming integrated with human behavior and even with humans.
As we reach new echelons of AI, it's likely that you'll see over-hype and short-term failures. As you reach for new heights, you often miss a rung on the ladder... but it doesn't mean you 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, stronger, more resilient, and adaptable solutions that do what you wanted (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 is different than the adoption cycle. We often overestimate a year and underestimate 10.
Which technologies do you think will survive the hype?
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