May 7, 2020

15 Technologies That Will Disrupt The Industry In The Next Five Years

Five years ago, the words "artificial intelligence" and "machine learning" were on everyone's lips. Today, these technologies form a core part of how companies do business. Because technology is ever-evolving, there will always be new tech emerging on the horizon.

However, the past has shown us that not every emerging technology can remain relevant, much less disrupt entire sectors of the economy. With each new crop of technologies, there are usually a few that have that potential. Fifteen members of Forbes Technology Council discuss some of today’s emerging technologies that they expect to be game-changers in the next five years.

1. 5G Technology

The biggest disruptors are those that simplify the user experience, and 5G accomplishes just that. Even in fields like customer service, 5G can both enhance and simplify the customer experience. Voice calls will be clearer, video support more accessible and greater bandwidth will enable the widespread adoption of AI/automation. The result? Richer, easier and more helpful customer support. - Mike De La Cruz, Directly

2. Unsupervised Machine Learning

Unsupervised machine learning (UML) is disrupting how we leverage data for predictions and intelligence. Unlike traditional ML, it works without any data training or labeling, which enables it to recognize and flag unknown patterns and make more accurate predictions. UML eliminates the limitations of preexisting knowledge or human bias, and will therefore enable insights never before possible. - Yinglian Xie, DataVisor

3. Robotic Accuracy And Automation

The next game-changer will be more human intelligence-based robotics and automation. Think about drones delivering packages with human understanding: "Please place this order beside this vase on my living room table." If the vase got moved, the drone will realize that it moved at delivery time (vision recognition) and either deliver it there or ask the user for a new precise delivery location. - Ayman Shoukry, Specright Inc.

4. Intelligent Tech Revolutionizing Security

Intelligent technologies such as artificial intelligence and machine learning are already enabling us to respond more dynamically to information sharing over email. It’s possible to detect when someone is about to make a mistake, as well as detect intentionally risky behavior such as exfiltrating data. This technology will revolutionize the way organizations consume security solutions and ensure that email is safe to use. - Tony Pepper, Egress

5. Connected Telehealth Solutions

As the pandemic strains hospitals, I’m encouraged by policy changes and shifts in public opinion that will lead to widespread adoption of telehealth. New telehealth apps, when made interoperable with critical patient data in electronic health records and other platforms of engagement for healthcare providers and payers, will change the paradigm with how care can be delivered more effectively. - David Wenger, Bridge Connector

6. Augmented And Virtual Reality

Virtual reality and augmented reality devices are becoming more capable and cost-effective by the minute. The possibility of using a VR space to interact with customers or co-workers seems much more plausible, and provides a richer interaction. The virtual experience may provide another revenue stream from customers, or be a sales tool to entice them to experience it for real. - Luke Wallace, Bottle Rocket

7. Hyperautomation

Hyperautomation provides companies with a framework to use a combination of AI and MLto identify and automate any business processes. Hyperautomation can span across a range of tools that can be automated, but also refers to the overall complexity of the automation. Robust data warehousing and availability of historical data becomes integral to being able to analyze the trends and gaps in current processes. - Jahn Karsybaev, Prosource IT

8. Edge Computing

AI and ML will increase in effectiveness when moving processing closer to the user. Edge computing will transform how data is processed and delivered to the end user, along with 5G data networks. New applications and the explosion of IoT devices will drive this new paradigm. - William McSorley, WM3 Group LLC

9. Spatial Computing

Spatial computing provides a new relationship between humans and digital content. Controlling interfaces with eyes, gestures and voice in a seamless and integrative manner offers a new precedent for interaction with the world. The technology has been partially used in semi-autonomous cars, drones and robots. The digital world will become more and more seamless with the real world. - Alexandro Pando, Xyrupt Technologies

10. Quantum Computing And IoT

AI and ML will continue to be on trend, but a few other things are coming. First of all, we’re talking about quantum computing. Once this moves from prototype to practice, it will create a breakthrough similar to the invention of the computer or the launch of the internet. The second thing that is trendy now and will continue to grow is IoT. Devices and their practical application are growing daily and will continue to grow. - Boris Kontsevoi, Intetics Inc.

11. DataOps

Given how many technologies we have gathering and transmitting data, I feel that DataOps will become more essential going forward. Organizations will need to adopt agile approaches and increase collaboration to manage and analyze the data. When they do, they'll unleash a wave of insights that will drive transformations at all levels, big and small. - Thomas Griffin, OptinMonster

12. Natural Language Processing

Natural language processing (NLP) seems to be a game-changer these days. We want robots to be able to process human speech and be able to intelligently react to it. A minor change in a sentence can dramatically change the intent, so we want to make sure robots can handle them! - Gev Balyan, UCRAFT

13. Value Stream Management

Value stream management (VSM) is definitely a game-changer, because this breakthrough technology is now seen through a different lens—a lens of an (almost) completely remote workforce. You now need VSM to maintain visibility, which is a critical component of successful software development in the new world. - Bob Davis, Plutora

14. Additive Manufacturing

Complex geometries unsupported by traditional machining and injection molding can now be created on demand with a single print. As 3D printing becomes increasingly integral to the manufacturing zeitgeist, more businesses will have access to rapid prototyping, tooling and direct manufacturing, and acquire new core competencies. The world is on the cusp of fully embracing this disruptive technology. - Christopher Yang, Corporate Travel Management

15. Regulatory Tech Coming To Government

I'm interested in seeing how regulation tech develops. This category of technology enables governments to implement enforcement and monitoring activities required by law. This trend has the potential to make it easier for businesses and individuals to comply with regulations. There is also a dark side to this trend—how will it impact privacy and freedom? - Nelson Cicchitto, Avatier Corporation

This article was originally published on Forbes.com.

February 15, 2018

What You Need To Know About AI

Lately, when clients come to me as a consultant, Artificial Intelligence (AI) usually comes up in our conversation. And when I’m asked, “How do I use it?” that tends to actually mean “What is it?” Let’s reach a basic understanding of AI so when you’re ready to explore what AI can offer, your discussion can be as productive as it can be.

What Is Artificial Intelligence?

As the name implies, AI is the intelligent behavior of machines. Most companies could utilize AI to interpret complex data. Here’s how it works (in a very simple way): The AI model asks a set of data a question and returns an answer. To accomplish this task, an AI model needs to understand the data it’s interpreting. So, for AI to deliver accurate, useful information, an AI model needs to be trained on the data it’s given. We’ll get into that soon, but first let’s talk about that data.

Learning From Data

For Artificial Intelligence to work, it needs to learn from specific kinds of data. With organized, not random, data, an AI platform can learn what it needs to. Let’s say you want to train an AI model to identify dogs in images. Organized data would consist of animal images, including dogs, to help the AI discern what is and what is not a dog. Random data (in this case, images of tables, lawnmowers, anything not reasonably close to our concept of a dog) doesn’t help the AI distinguish dogs from other animals. Know what’s in your data and you should be able to avoid any randomness.

At this point, I should clarify that AI isn’t actually telling you what something is — AI tells you what something probably is not. This is determined through a prediction percentage -- you’re not teaching an AI model to know an animal is a dog but rather training it to tell you it’s a certain percentage confident it recognized a dog. If you’ve been feeding your AI model with images of only dogs and cats, then introduce an image of a squirrel, your AI will be less certain of what it sees. But, once you teach the AI model what a squirrel looks like, the AI can discern with more certainty.

How To Train Your AI

Machine learning, the ability for computers to learn without being programmed, can take place a couple different ways. One way is supervised learning, where an AI model infers a function from labeled training data. Those images of animals I mentioned earlier would be labeled “dog,” “cat,” "hippopotamus,” etc. to help the AI learn. The other machine learning method is unsupervised learning. This is where machine learning draws inferences from data sets consisting of input data without labeled responses — you provide a bunch of pictures of animals with no descriptions and let the AI figure out what is and what is not a dog. Remember to, with either approach, provide organized data that your AI will learn from.

Going With Google

Google provides a lot of data sets and pre-trained AI models for purchase. But, they’re all about object recognition and will only do a good job of recognizing things that existed when the model was trained. So, a Google AI model may have learned what a bike and pogo stick are at some point, but a newer invention, like a Segway, could confuse it.

Beyond Cats And Dogs

I’ve led or been on some teams that have worked on training data for tasks other than image recognition, like classifying audio samples or, during an innovation session, recognizing what restaurant is delivering food by identifying food service workers and recognizing what was being delivered. The latter is an excellent example of what can happen when you train very specific models. In this application, the AI model learned from uniforms, not beverage cups, cars or even people. The data set provided in this case included shapes of what delivery drivers could be carrying and the clothes they wore.

The accuracy of your AI model is really about the bucket of data you give it. You need a lot of pictures, and they need to be of a similar quality. The more similar they are, the less training you likely need.

What Could Go Wrong?

Okay, our hypothetical AI is up and running. What is at stake if it’s wrong? Within your own organization, determine the impact of a false positive or false negative. AI that determines what is and isn’t email spam could afford to let some spam through but could create problems if it marks something important as spam. Imagine the consequences of AI providing results of x-rays with a false negative cancer diagnosis.

Now, if you feel more comfortable with how AI works, you can begin the challenging task of figuring out where it fits in your organization.

For information about Artificial Intelligence and Google Assistant, download our Google Assistant POV by filling out the form below.

Originally published on Forbes on Jan 8, 2018.

March 20, 2017

SXSW 2017: The Big Stuff

We sent Rocketeers across disciplines to SXSW this year to learn what the future has in store for technology and users. Art directors, client and sales executives, and our top brass absorbed all they could. They came away with a lot of information, but here’s the big stuff we found most interesting.

 

The end of "user,” a new start for “experience”

SXSW was populated with experiences. Whether to entertain or inform or possibly both, attendees were immersed in brands and concepts that sought to provide certain feelings or an understanding of something by engaging as many senses as possible. The experiences weren't about UI or overtly tactical things, but about understanding context and how to properly use that to impact people. So, we can move from "user" to “experience," because that's what is truly meaningful to people.

An overwhelming desire to create experiences that connect people

Brands and technologies use the screen to find each other and themselves. There are so many things attempting to replace human interactions- self-driving cars, robots, smart agents, virtual assistants, but we must remember we are all humans and nothing can replace what happens when humans band together. Vint Cerf, one of the internet’s creators, explained that he feels that the internet isn’t currently a safe place, but we need it to connect to one another. One of the more interesting points he made: internet architecture should be implemented alongside roads and bridges, because it is just as vital and important.

Even NASA is using the power of connection by crowd sourcing solutions to long-pondered problems. Recently, they reimagined exploration with the help of robotics and hackathons. Explorers used to take everything they needed with them in their boat or rocket ship. This only allowed us to go so far and see so much. NASA realized their travel limitations and determined reaching the farthest depths of space required sending our supplies ahead of time. With the help of a robot that unpacks our suitcases, we can take a six-month journey to a faraway planet with the hope of returning someday.

Futuristic Experiences

Remember when most of the things we use daily now were once visions of the future? There was a lot of that at SXSW. NASA showed off their use of AR/VR, including 360 video to not only deliver space experiences to the public, but also train astronauts for future missions to Mars and space. NASA, with one of the largest exhibition booths at SXSW, let visitors wear a HoloLens to experience a simulated walk on Mars.

Hiroshi Ishiguro from Osaka University and Ryuichiro Higashinaka from NTT demoed human-robot conversation. This was a mind-blowing change from task-based bots (e.g. Alexa, Siri). These engineers posed a question, “Is sushi better than ramen?” The robots and humans went on to have a discussion with no script, and robots only responded based on their subject matter expertise. To witness this was extremely fun!

The Reality of AR/VR

From NASA to Home Depot, SXSW held many AR/VR branded experiences. We learned of Home Depot’s virtual reality experience that helps create efficiencies in their supply chain by teaching users how to maximize cargo space for shipping goods to stores. One of the most interesting examples of this was at the National Geographic Base Camp bar, featuring a Microsoft HoloLens AR experience that blended our physical surroundings with digital educational representations of Albert Einstein’s theory of relativity right before our eyes.

 

What educational, entertainment, or brand experiences will we see in the future from this technology? That’s up to brands and the partners that help them make those ideas a reality (however you want to qualify that).

March 9, 2017

MWC Barcelona 2017: Jamon, Chaos, and Mobility

For those of you who couldn’t make it to MWC this year, we can catch you up with the first-person experience of Director of Strategy and Design (EMEA), Greg Flory. Here’s Greg’s run down from MWC Barcelona:

It’s Sunday and I’m still recovering from last week in Barcelona at Mobile World Congress. If you haven’t been, I totally get why that sounds a little ridiculous—after all, you’re in one of the nicest cities on the planet, constantly eating jamon Iberico, quaffing tasty Rioja and nibbling on that amazing bread with tomatoes and olive oil. And it’s all lovely. Seriously, you should go. But the reality is that MWC has you running around all day, and most nights, trying to make sense of the chaos created by the collision of technology, vision, globalization, the rapidly advancing future, and the rippling impact of mobile innovation on adjacent industries and technologies. It’s overwhelming. And exhausting.

So, as I gradually emerge from the dreamy Catalan fog, there are several takeaways that I’d like to quickly share:

  • Autonomy is a thing. We tend to think of this in terms of smart objects or connected cars—and there were cars everywhere throughout the exhibition halls—but it’s the impact on human experience that is truly interesting. We have arrived at a point where tools and information can remove uncertainty and the mundane, allowing us to invest our energy in what we care about the most. AI-powered bots will get better, giving us immediate access to precise solutions. Autonomous drones will inspect, map, and deliver to locations quicker, and more safely and efficiently than we can today. Even lighting, championed by Philips, will change dramatically, moving beyond simple illumination to help us heal physically and make sense of our environment in new ways.
  • Data is your business. Or your next business. Investing in mobile ensures that you will have access to information about your customers that you never knew was available. Brands such as Spotify are working with companies to help find better ways to engage their customers. Connected devices, aligned with connected cars, houses, and cities will create even more data, while revealing services and products that we couldn’t have imagined or seen previously. And there’s no excuse for not knowing your customer—the actual people—with names, preferences and an increasing array of options.
  • We all need partners. Now more than ever. Having worked exclusively in mobile for the past six years, I thought I was pretty aware of my limitations. But there are entire parts of the ecosystem that I didn’t know existed. It is expansive and there is opportunity across the spectrum. And wherever you are on the mobility journey, it is an enormous benefit to have the right people to help you manage all of the moving parts. And believe me, there is no shortage. For every one person I saw and/or bumped into on the conference floor, there were 20 trying to get through passport control on Friday morning. And obviously, I think Bottle Rocket is an excellent choice. If you think the partner suggestion contradicts my first point about autonomy, I’d just say that having the right partner allows you to focus on the areas of your unique expertise, ceding certain specialties to people best prepared to manage.

When I wasn’t speaking my unique brand of broken, largely unintelligible Tex-Mex Spanish to patient and accommodating Catlan cab drivers, I was most likely wandering around Halls 8.0, 8.1 and 3 of the Fira Gran Via prepping for and/or leading a technology tour with WPP’s Data Alliance. The tour may have been the best thing that could have happened since it forced me to explore and engage with a lot of people I would normally have avoided. It challenged some of my assumptions and confirmed others.

You can expect a healthy dose of what’s next at the world’s largest mobile gathering, but there seemed to be quite a few brands and manufacturers pushing back against the future, trying their best to pluck our taught little, nostalgic heartstrings. Here are two headliners and one wild card:

  • Nokia, with its 3310, demonstrates that you don’t really need a good reason to dredge up the past (unless this is intended for the developing world) and plenty of people crowded the table to get their paws on the retro hand candy. Looks fun. Feels great in the hand. But the proprietary OS is very much a drill down—endlessly—to take simple actions, then drill back out. This was an instant reminder that UX in the pre-smartphone era was painfully slow and often unrewarding. The 3310 has 22 hours of talk time (not that anyone really does that on their phone anymore), plus about a month of standby between charges. Seems just about right considering how infrequently anyone in the developing world would be likely to use this phone. But easily one of the most crowded stands at the show. I guess it’s kind of like stalking your old crush on Facebook. Nice to see how they’ve done over the years, but probably still pretty happy you’ve moved on.
  • BlackBerry's KEYone brings its CrackBerry heritage to the Android OS, delivering a physical keyboard to the brand's long-suffering addicts. If this quickens your pulse, enjoy, but I found the physical keyboard with its tiny buttons harder and less forgiving than a typical touchscreen. I was never a huge fan and easily moved on almost a decade ago. So, are we facing a resurgent BlackBerry that will draw legions of former obsessives out of the smartphone forest (much like the gobs of zombies in the near certain impending apocalypse)? I wouldn’t bet on it.
  • Moscow-based, Elari, producer of the self-proclaimed “anti-smartphone” Cardphone 3G, has an interesting array of products for people looking to simplify. Their phones are generally small, with the Cardphone looking like a minimalist calculator that can fit in your wallet. I think this is the phone that Walter “Heisenberg” White wishes he'd had as his second “business" phone.

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