Capitalogix

Happy Hanukkah 2021

It's that Holiday time of year again. 

Wow, how time flies. We're past Thanksgiving, and Christmas and the New Year will be here quickly.

It turns out that tonight was and the last night of Chanukah - which is the Jewish festival of lights. This is the holiday that involves lighting the Menorah (Chanukah candles), eating latkes (potato pancakes), exchanging gifts, playing spin the Dreidel (a gambling game), and enjoying a sense of family togetherness for eight days and nights.

That's a long time, right?! Well, sometimes it seems even longer with my family. 

As a gift to all of you, here is "The Chanukah Song," performed by comedian Adam Sandler on Saturday Night Live.  It became an instant classic (and he since released a second, third, and fourth version.)

Here is the video. And, if you're feeling left out - here's Adam Sandler's Christmas Song.

 

via SNL

It's not too different from Christmas. 

The cynic in me believes the gift part of the holiday was invented by merchants.

Regardless, the Capitalogix team has been in a festive mood, and the office has been filled with holiday cheer. We recently celebrated a Thanksgiving Potluck as well. 

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From my family to yours, Happy Holidays!

Fueling Alpha: Data In The New World

Data has long been a precious commodity - yet it’s only getting more valuable.

At the beginning of 2020, the number of bytes in the digital universe was already 40X greater than the number of stars in the observable universe. 

Data is today’s “wild west” and the battlefield of today’s tech titans; with AI, The IoT, the Blockchain, and analytics leading the forefront. 

Alphabet, Amazon, Apple, Facebook, and Microsoft all have an unprecedented amount 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 their data from prying eyes.

The trading industry has undoubtedly experienced the rapid growth of data, but it’s pervasive in every industry – and in our personal lives as well. 

Having basic data and basic analytics used to be enough, but the game is changing. Traders used to focus on price data, but now you’re seeing an influx of firms using alternative data sets 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 advantage. Understanding the game they’re playing (and the strategies and rules they follow are important), but now that’s just the table stakes.

Figuring out where you can find extra insight, or make the invisible visible, creates a moat between you and your competition – and lets you play your own game.

I shot a video in 2019 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.), and that often involves identifying what drove the old world. History has a way of repeating itself.

Before e-mails, fax machines were essential. Before cars, people were pleased with a horse and buggy.

These comparisons contextualize the importance of data in today’s new world of economics and commerce.

 

via gapingvoid

Data as the New Oil

While not the best comparison, people often default to comparing data to oil. 

Since the Industrial Revolution, petroleum has played a pivotal role in human advancement. It fueled (and still fuels) our creativity, technology advancements, and a variety of derivative products. There are direct competitors to fossil fuels that are gaining steam, but it’s more interesting to compare petroleum to data due to their parallels in effect on innovation.

The process of pumping crude oil out of the ground and transforming it into a finished product is far from simple, but anyone can understand the process at a high level. You have to locate a reservoir, drill, capture the resource, and then refine it for the desired product (e.g., heating oil, gasoline, asphalt, plastics, etc.). Then, you have to move it to where it’s needed.

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

Data can be seen as the fuel to the information economy and oil to the industrial economy. The amount of power someone has often correlates to their control of and access to resources ... and diminishing or diluting those resources can lead to extreme consequences.

Why Data Is Better Than Oil

The analogy works, but it’s just that, an analogy. The more you analyze it, the more it falls apart. Unlike a finite resource (like oil), Data is all around us and increasing at an exponential rate.  So the game is a little different:

• Data is – ultimately – 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, share it, transform it, infinitely knowing that it won’t diminish. Data is 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 essential, it’s not expensive in the same way that transporting oil is. In fact, it can be transported and replicated at light speed.
• While petroleum can be transformed into many different products - the variety of data-related products and sources is basically infinite in comparison.

On Alternative Data

In the past, investors relied on information and experience from their real lives, from counterparties, and from fastidious attention to CNBC and stock tickers. 

However, fundamental discretionary traders account for just 10% of today’s trading volume. Quantitative investing based on machine intelligence and algorithms is the new normal.

While the games, the rules, and the players have all changed, the goal hasn’t... more alpha ... more money ... more reliably. 

Alternative data, to most, means tracking Twitter and Facebook sentiment, but confining your definition to that limits potential alpha. 

New sources of data are being mined everywhere, and are letting investors understand trends “before they happen.”

For example, mobile devices, low-cost sensors, and a host of new technologies have led to an explosion of new potential data sources to use directly for predictive insight or indirectly to help improve models.

In addition, private company performance, logistics data, and satellite imagery are becoming popular data sets in a data scientist’s alpha creation toolbox. 

There are often concerns about the cost and completeness of these datasets, but as we get better at creating and using them, both will improve. 

It also doesn’t always have to be confidential or challenging to find information. Traders now have access to vast amounts of structured and unstructured data. An important 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. Second, even the most insightful data can’t predict black swans. It’s important to exercise caution.

The thing about “sustainable alpha” is that while one might be able to achieve it, you can’t expect to have it doing the same thing everyone else does (or by doing what you’ve always done).

Markets change, and what worked yesterday won’t necessarily work today or tomorrow. Trading is a zero-sum game, and as we move toward the future, this only gets more apparent. 

The future of Data is bright, but it’s also littered with potential challenges. Privacy concerns and misuse of data have been hot button topics, as have 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.

The question becomes, how do you capitalize on data, without becoming a victim to it? 

Food for thought!

Thriving Through The AI Revolution

The world is poised on the cusp of an economic and cultural shift as dramatic as that of the Industrial Revolution. - Steven Levy

Artificial Intelligence is one of my favorite things to talk about ... It makes so much possible! 

In a previous article, I mentioned that forecasts expect AI to impact or eliminate up to 50% of current jobs. Nevertheless, I think that is the start of the story. The ultimate impact will be more significant and more positive than most people expect.

Freeing humans to do more has always been a boon to society. Electricity put a lot of people out of work ... but, look what it made possible.

We'd be naive to think AI isn't going to influence the job market, but that doesn't mean you can't navigate that shift. 

A Look At Industrial Revolutions

The Industrial Revolution has two phases: one material, the other social; one concerning the making of things, the other concerning the making of men. - Charles A. Beard

There are several turning points in our history where the world changed forever. Former paradigms and realities became relics of a bygone era. 

Today, we're at another turning point.

Tomorrow's workforce will require different skills and face different challenges than we do today. You can consider this a Fourth Industrial Revolution. Compare today's changes to our previous industrial revolutions. 

• First industrial revolution - Discovery of the steam engine and creation of factories
• Second industrial revolution - Introduction of the assembly line and mass production
• Third industrial revolution - The world wide web and computers connect the world together, heralding the digital age. 

Each revolution shared multiple similarities. They were disruptive. They were centered on technological innovation. They created concatenating socio-cultural impact.

The fourth shares all the same hallmarks.

We're harnessing new technologies like AI, the IoT, renewable energy, and the blockchain. Automation will reach new levels in this revolution. But there also will be an explosion of new fields, new markets, and new necessary skillsets - it's going to impact the world as holistically as electricity did. 

How will humans create value in an increasingly automated world?

I believe that, if managed well, the Fourth Industrial Revolution can bring a new cultural renaissance, which will make us feel part of something much larger than ourselves: a true global civilization. I believe the changes that will sweep through society can provide a more inclusive, sustainable and harmonious society. But it will not come easily. - Klaus Schwab

One of the distinctions I've recently made about the industrial revolutions is that for a long time, technology helped humans act like robots. Think about a plow and a farmer, or a seamstress and a sewing machine. After that, it helped robots try to act like humans, which you've seen more recently. 

I believe we're at another inflection point, where new capabilities will free up humans to be more human and to pursue more of what they really want. 

Robots can do many things, but they've yet to match the creativity and emotional insight of humanity. As automation spreads to more jobs, the need for management, creativity, and decision-making won't go anywhere ... they may be bolstered by data analytics, but they won't disappear. 

Our uniqueness and flexibility rightly protect our usefulness. AI and automation free us up to be our best selves and to explore new possibilities. 

These are exciting times!

The Promise And Peril of AI with Alan Olsen

In 2017, I shot my first video with Alan Olsen. Alan is a wealth manager to the ultra-affluent.  His American Dreams show is immensely popular with the High-Net-Worth demographic in Silicon Valley.

Alan's show is about finding your path in life, and what it takes to make businesses thrive through adversity and challenging times. 

In my first video with him, we talked about defining a meaningful life. We started by talking about my career path from a young lawyer to spending over 25 years running tech companies ... and the lessons learned along the way.

I recently shot a new video with him – this time on the promise and peril of AI. It has over 3,500 Likes on YouTube.  Watch it here.

 

via The American Dreams Show

The main issue addressed during the video is how you can best get what you want as the world changes and forces like AI terraform the world and your role in it. 

It's worth watching.

Ultimately, I believe AI is simply another vehicle freeing human nature. As AI does what humans used to ... you have an opportunity to choose what to do with the freedom you get.  Will you relax or lift your gaze to something better?  The choice is yours.

Similarly, some will want to direct new AI capabilities towards things they want to monetize better.  Others will want to weaponize AI.  Still others will use it to spread peace and love. 

You've seen it with nuclear power (and a host of other technological capabilities) ... tools aren't good or bad in and of themselves - it is what people use those capabilities for that determines their impact. 

Here Are Some Links For Your Weekly Reading - October 24th, 2021

Here are some of the posts that caught my eye. Hope you find something interesting.

Lighter Links:

• Resilience Is About How You Recharge, Not How You Endure. (HBR)
• Can this Company Take Pet Cloning Mainstream? (TexasMonthly)
• China's Test of Orbital Hypersonic Missile Is a Big Deal. (Dailysignal)
• AI 2041: Ten Visions For Our Future. (NextBigIdea)
• The Head of NASA Says Life Probably Exists Outside Earth. (Quartz)

 

Trading Links:

• Denver Airport's Jobs Fair Hoped For 5K Visitors – Only 100 People Showed Up. (FoxBusiness)
• Trump SPAC Skyrockets As Much As 1,657% Since Deal Was Announced. (CNN)
• Hedge Funds Slash FAANG Exposure to Two-Year Low Before Earnings. (Bloomberg)
• Scoop: Facebook Exec Warns of "More Bad Headlines". (Axios)
• Tesla CFO: Profound Awakening of EV Desirability Has Caught Company Off-Guard. (GCR)

Here Are Some Links For Your Weekly Reading - October 10th, 2021

 

Here are some of the posts that caught my eye. Hope you find something interesting.

Lighter Links:

• 5 Key Ways Zoom is Shifting From Merely a Product to a Dominant Platform. (MotleyFool)
• You Can Now Communicate With William Shatner Through Interactive AI. (CBR)
• What Makes Us Human? The Answer May Be Found In Overlooked DNA. (EurasiaReview)
• Why China Sends Warplanes Into Taiwan's Airspace But Doesn't Attack Analysis. (EurasiaReview)
• Russia Tells Its Space Reporters to Stop Reporting on the Space Program. (ArsTechnica)

 

 

 

Trading Links:

• Global Artificial Intelligence (AI) Robots Market to Reach $21.4 Billion By 2026. (Finance)
• Xi Jinping Aims to Rein-In Chinese Capitalism, Hew to Mao's Socialist Vision. (Wall Street Journal)
• Central Bankers are Spooked By Signs that Inflation is Lingering for Longer. (Bloomberg)
• SEC Chief to Wall Street: The Everything Crackdown is Coming. (News)
• DeFi Picks Up the Pace as Alternate Blockchains and NFTs Boom. (CoinTelegraph)

 

 

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:

1. Innovation Trigger (potential technology breakthrough kicks off),
2. Peak of Inflated Expectations (Success stories through early publicity),
3. Trough of Disillusionment (waning interest),
4. Slope of Enlightenment (2nd & 3rd generation products appear), and
5. 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. 

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.

• 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?

Learning from What Pro Sports Teams Do Right

I am writing this while flying back from watching a Cincinnati Reds game in their Owner’s Box.

It was a great experience – and reminded me of how much you can learn from watching what professional sports teams do.  

Frankly, the whole business of professional sports fascinates me.  

They have to do so many things right … just to compete. This includes how they build and manage their team, cultivate their brand, support their communities and causes … as well as how well they handle the practical realities of the logistical, operational, and financial challenges they deal with constantly.  

It is more than a business.  For the most successful, it is a mission or stewardship.

Personally, I pay attention to football more than other sports.

In 2017, I lightheartedly questioned the future of the NFL as a result of bad press around concussions, crimes, and more.  I questioned it as a fan that's been a season ticket holder for as long as I can remember.  My Dad and I had season tickets to the Eagles when I was young, and to the Patriots when I was a teenager. Recently, I’ve been a Cowboys season ticket holder for over 30 years. I questioned it knowing that the NFL wasn't really at risk. To support that assessment of the NFL’s stability, consider that (despite quarantine) the league-wise Season Ticket renewal rate is at 92%… equaling a 5-yr high. 

Part of the stability stems from doing so many things right (or at least well).  Which takes us back to the point that you can learn a lot from how sports teams thrive. 

There's a lot to learn not only from the NFL's longevity, but from what it's like to be a part of a team, from the coaching, and the management side of things. 

Some of these lessons stem back to youth football ... which I’m reminded of each time I get to  watch a Dallas Cowboys practice at The Star.

Think about it, even in middle school, the coaches have a game plan. There are team practices and individual drills. They have a depth chart, which lists the first, second, and third choice to fill certain roles. In short, they focus on the fundamentals in a way that most businesses don't.

The picture, below, is of my brother's high school team way back in 1989.

 

Is it possible that most businesses are less prepared to win than an 8th-grade football team? At first, that may sound like hyperbole, but if you think about it ... it's likely true. 

Losing to an 8th-Grade Team

 

Even middle school and high school teams have a playbook for offense, defense, and special teams.  They scout opponents and create game plans.  They think about how to improve and coach the team … and each player.  They strategize and drill to perform well each game.  Meanwhile, they also work to string together wins to achieve a higher goal. 

Contrast that with many businesses.

Entrepreneurs often get myopic ... they get focused on today (or survival), and they often lose sight of the bigger picture and how all the pieces fit together. 

The amount of thought that goes into football - which is ultimately a game - is a valuable lesson for business. 

If an 8th-grade football team is equivalent to a normal business, what would happen to a business that operated similar to an NFL team?

Practice Makes Perfect

How you do one thing is how you do everything. So, they try to do everything right. 

Each time I've watched a Cowboys practice session, I've come away impressed by the amount of preparation, effort, and skill displayed.

During practice, there's a scheduled agenda. The practice is broken into chunks, and each chunk has a designed purpose and a desired intensity. There's a rhythm, even to the breaks.

Every minute is scripted. There's a long-term plan to handle the season ... but, there was also a focus on the short-term details and their current opponent.

They alternate between individual and group drills. Moreover, the drills run fast ... but for shorter time periods than you'd guess. It is bang-bang-bang – never longer than a millennial's attention span. And they move from drill to drill – working not just on plays, but the skillsets as well (where are you looking, which foot do you plant, how do you best use your hands, etc.).

They use advanced technology (including advanced player monitoring, biometric tracking, and medical recovery devices ... but also things like robotic tackling dummies and virtual reality headsets). 

They don't just film games, they film the practices ... and each individual drill. Coaches and players get a cut of the film on their tablets as soon as they leave. It is a process of constant feedback, constant improvement, or constant renewal. Everything has the potential to be a lesson. 

Beyond The Snap

The focus is not just internal, on the team. They focus on the competition as well. Before a game, the coaches prepare a game plan and have the team watch tape of their opponent in order to understand the tendencies and mentally prepare for what's going to happen.

During the game, changes in personnel groups and schemes keep competitors on their toes and allow the team to identify coverages and predict plays. If the offense realizes a play has been predicted, they call an audible based on what they see in front of them. Coaches from different hierarchies work in tandem to respond faster to new problems. 

After the game, the film is reviewed in detail. Each person gets a grade on each play, and the coaches make notes for each person about what they did well and what they could do better.

Think about it ... everyone knows what game they are playing ... and for the most part, everybody understands the rules, and how to keep score (and even where they are in the standings). Even the coaches get feedback based on performance, and they look to others for guidance. 

Imagine how easy that would be to do in business. Imagine how much better things could be if you did those things.

Challenge accepted!

GPT-3: Boom or Bust?

GPT-3 was released by OpenAI in 2020 - and was considered by many a huge jump in natural language processing. 

GPT stands for Generative Pre-trained Transformer. It uses deep learning to generate text responses based on an input text. Even more simply, it's a bot that creates a quality of text so high that it can be difficult to tell whether it's written by a human or an AI.

GPT-3 is 100x bigger than any previous language AI model and comes pre-trained on 45TB of training text (499 billion words). It cost at least 4.6 million US dollars (some estimated as high as $12 million) to train on GPUs. The resulting model has 175 billion parameters. On top of that, it can be tuned to your specific use after the fact. 

via Towards Data Science

Here are some interesting GPT-3 based tools: 

• Frase - AI-Curated SEO Content 
• Emerson - AI Chatbot
• Viable - Customer Feedback Analytics Platform
• Sapling- Customer Service

Practically, GPT-3 was a huge milestone. It represents a huge jump in NLP's capabilities and a massive increase in scale. That being said, there was a frenzy in the community that may not match the results. To the general public, it felt like a discontinuity; like a big jump toward general intelligence.  

To me, and to others I know in the space, GPT-3 represents a preview of what's to come. It's a reminder that Artificial General Intelligence (AGI) is coming and that we need to be thinking about the rules of engagement and ethics of AI before we get there. 

Especially with Musk unveiling his intention to build 'friendly' robots this week. 

On the scale of AI's potential, GPT-3 was a relatively small step. It's profoundly intelligent in many ways - but it's also inconsistent and not cognitively concrete enough.

Take it from me, the fact that an algorithm can do something amazing isn't surprising to me anymore ... but neither is the fact that an amazing algorithm can do stupid things more often than you'd suspect.  It is all part of the promise and the peril of exponential technologies.

It's hard to measure the intelligence of tools like this because metrics like IQ don't work.  Really it comes down to utility.  Does it help you do things more efficiently, more effectively, or with more certainty? 

For the most part, these tools are early. They show great promise, and they do a small subset set of things surprisingly well. If I think about them simply as a tool, a backstop, or a catalyst to get me moving when I'm stuck ... the current set of tools is exciting.  On the other hand, if you compare current tools to your fantasy of artificial general intelligence, there are a lot of things to be improved upon. 

Clearly, we are making progress. Soon, GPT-4 will take us further. In the meantime, enjoy the progress and imagine what you will do with the capabilities, prototypes, products, and platforms you predict will exist for you soon.

Onwards. 

What Technologies Are Going To Most Impact The Next 5-10 Years?

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. 

1. 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. 
2. 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). 
3. 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.
4. IoT will become more pervasive, enabling near digital omniscience as everything becomes a sensor that transmits data up the chain. 
5. 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. 

 

What do you think?  I'd love to hear your list.