It's an interactive video that uses your webcam to walk you through the various assessments on BMI, emotion, beauty, etc. At the end, it'll give you your life expectancy, and then your "normal score".
It's not the most complex use of AI, but it provides interesting insights, and is becoming increasingly prevalent.
Governments, police stations, retail stores, etc. all use this technology to track individuals, and if you remember one of my previous articles - there are plenty of cameras to go around.
If you did the demo, were you surprised by the results?
The ubiquity of Machine Learning algorithms remains a topic of interest because we, as a society, still haven't come to terms with what "acceptable" use looks like, and what privacy looks like in the post-AI world.
Algorithms are helping you pick out your next gift on Amazon, controlling what you find on Google, they're suggesting new music for you on Spotify, and they're doing their best to keep you on their website.
They're following you in stores, on the streets, and many would argue they're tracking your phone calls, text messages, and more.
With all that being said, I do think it's important to have a cursory knowledge of the things that impact our lives ... so, even if you're not an AI-aficionado, I think it's important to somewhat understand how machines learn, and how powerful they're becoming.
The video is a bit simple in its explanations, but it describes some important concepts.
The video focuses on Genetic Algorithms, which is one type of machine learning – and neglects some of the other more complicated approaches.
As machine learning gets more complicated and evolved, it gets harder for a human to understand what makes it good … and that's okay. Understanding the direction AI is heading is more important than truly understanding the intricacies.
It's human nature to feel safer when we understand something. It's human nature to envision machines as making human-like decisions, just faster.
Of course, just because it suits human nature to believe something, that doesn't make it true.
Part of what makes machine learning exciting is that it can do a lot of things well that humans are really bad at.
In reality, it doesn't matter why a bot is making a decision, or what inputs the bot is making the decision on. What matters is the performance and level of decision-making in relation to itself and to other options (and whether the bot is biased).
With respect to trading, focusing on the markets is a distraction.
For the most part, I don't care how markets are doing.
I care how our systems are doing and I care how the portfolio is doing.
It's a brave new world, and not only is big brother watching, but algorithms are too.
We take for granted a lot of the technology we have today. Computers and phones have evolved so fast that it's hard to remember that they haven't been around for many years. When my youngest son was born in 1993, cassette tapes and the Sony Walkman were still popular, I had a wired phone in my car, and we had a Macintosh-II in the study.
Everything in this photo now exists in the cheapest of smartphones.
For a blast from the past and a look back at what used to be top-of-the-line ... here's a video of people buying a computer in 1994.
Partially as a result of the quarantine, you're seeing an increase in digital cash transfers with tools like Venmo, an increase in e-commerce shops like Shopify, and an increase in (you guessed it) collaboration tools like Zoom or Microsoft Teams.
This year, DOMO also created a chart that shows the services that have appeared in the graphic since 2012. It's an interesting way to look at the relevancy and staying power of different companies and technologies.
We're currently in a time period of massive competition and turnover. Innovation means incumbents are being challenged every day, and the status quo doesn't stay that way for long. Even within the S&P 500, you're seeing companies stay a member for shorter periods of time.
You have to stay on your toes to maintain an edge. I think you can expect increased competition, increased volume, and as a result, increased noise vying for your attention or fueling your distraction.
One of the biggest lies on the internet (and there are too many lies to count) is "I have read and agree to the terms of service(ToS)."
There is a plug-in that might help.
Terms of Service Didn't Read has summaries of most ToS, ratings for their user-friendliness and a browser plug-in so when you're about to sign one you can make sure it's safe.
Unfortunately, many of the ToS tell you that they're going to use your data, sell it to spammers, etc. For example, I talked about how a shadowy Russian company was behind FaceApp and owned the rights to photos you uploaded.
Luckily, not every clause in a ToS is legal, and won't necessarily hold up in court - but that doesn't mean you shouldn't be protecting yourself.
So, check out TOSDR, it's not perfect ... but it's probably better than nothing.
Worldwide, health & fitness app downloads have grown by 46%. With a mass majority of that being in India. On top of downloads, daily active users have also increased by 24% worldwide.
Is Home Fitness Here to Stay?
Health & fitness apps have been a big part of my arsenal, far before social distancing was a thing, and they'll continue to be an important part of my future fitness plans.
Many people prefer the gym/class environment for workouts, so home workouts will never represent a major proportion of the market, but it's non-trivial and continues to grow.
More likely to continue to grow in use are the tracking and mindfulness apps.
Each year, I share an article about Gartner's Hype Cycle for Emerging Technologies. 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, but which technologies are being supported by the cultural zeitgeist.
Technology has become cultural. It influences almost every aspect of every-day life, and it's also a massive differentiator in today's competitive landscape.
Sorting through which technologies are making real waves (and will impact the world) and which technologies are a flash in the pan, can be a monumental task. Gartner's report is a great benchmark to compare reality against.
2019's trends lead nicely into 2020's trends. 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 last year Gartner shifted towards introducing new technologies at the expense of technologies that would normally persist through multiple iterations of the cycle. This points toward more innovation and more technologies being introduced than in the genesis of this report. Many of the technologies from last year (like Augmented Intelligence, 5G, biochips, the decentralized web, etc.) are represented within newer modalities.
It's also worth noting the impact of the pandemic on the prevalent technologies.
This year's ~30 key technologies were selected from over 2000 technologies and bucketed into 5 major trends:
Composite Architectures represent the organizational shift to agile and responsive architectures due to decentralization and increased volatility. Emphasis is on modularity, continuous improvement, and adaptive innovation to respond to changing market conditions (like in trading, or in businesses rapidly shifting to remote). Sample technologies include embedded AI and private 5G
Algorithmic Trust is a direct result of increasing data exposure, fake news, and biased algorithms. As a result, technologies have been built to "ensure" identities, privacy, and security. A great example is more technologies being created on the blockchain. Other examples include explainable AI and authenticated provenance
Beyond Silicon is in its infancy, but represents the limitations of Moore's law and the physical of silicon. This has led to new advanced materials with enhanced capabilities being used, and other simple materials being used. Examples of this technology can be seen in DNA computing and storage, quantum computing, and biodegradable sensors.
Formative AI is the shift towards more responsive AI; models that adapt over time and models that can create novel solutions to solve specific problems. Sample technologies include generative AI, self-supervising learning, and composite AI.
Digital me represents the integration of technology with people, both in reality and virtual reality. Past hype cycles have introduced implants and wearables, but the potential applications of the technology are growing, especially in response to social distancing. Examples are health passports, Two-way BMI, and social distancing technologies.
I'm always most interested in the intersection of AI and advanced analytics. This year, it looks like many of the fledgling AI technologies have become integrated and more advanced. Much like the formative years for children, formative AI represents a new era in AI maturity. Models are becoming more generalized, and able to attack more problems. They're becoming integrated with human behavior (and even with humans as seen in digital me).
As we reach new echelons of AI, it's actually more 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?
Here Are Some Links For Your Weekly Reading - October 10th, 2020
Here are some of the posts that caught my eye recently. Hope you find something interesting.
Lighter Links:
Trading Links:
Posted at 08:23 PM in Business, Current Affairs, Gadgets, Games, Ideas, Just for Fun, Market Commentary, Science, Trading, Trading Tools, Travel, Web/Tech | Permalink | Comments (0)
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