By Frank Antonysamy
Frank Antonysamy is Vice President of Cognizant’s Global IoT and Engineering Services
A digital transformation revolution in manufacturing is underway, and data is the primary currency paving the way for more efficient ways of doing business. Gone are the days when data analysis was left to Monday night quarterbacking by poring over static results. Today, thanks to a central wireless ecosystem which links relevant mobile devices, Internet of Things (IoT) connected machines and connected employees, data gathering and analysis in a smart factory is immediate and real-time optimization drives significant efficiencies.
But not all smart factories are created equal.
Given that enterprises are all on different points on the path to complete digital maturity, it helps to take stock of the state of IoT intelligence — where we are now and where we are headed — and what industrial organizations need to be successful.
Laying the foundation for intelligence
One of the key advantages of Industry 4.0 is the promise of the Internet of Things (IoT) or Industrial Internet of Things (IIoT). Sensors connected to raw materials, factory floor equipment and final products can relay information, over a Wi-Fi connection, about their health and usage patterns to wider enterprise asset management software and enterprise resource planning systems.
Equally important, stakeholders can access this data in real-time and on-demand. Companies can leverage this data to deliver insights across three channels:
- Product intelligence
- Service intelligence
- Operational intelligence
There is significant overlap across these three pillars but their power to deliver a smart factory with new avenues for monetization, is revolutionary.
Here’s an overview of the IoT landscape with respect to its three core pillars of intelligence.
Product intelligence shakes up traditional PLM
The smart factory runs on smart products whose intelligence can be leveraged to read the tea leaves of market demand. At its core, product intelligence is defined as intelligence derived from an intelligent (read…IoT-enabled) product. In the IoT world, traditional rules of product lifecycle management (PLM) no longer apply. Gone are the rinse-and-repeat cycles of concept, design, manufacture, marketing and sales. In traditional manufacturing, the ideation-sale stage took years if not decades and slight changes in market demand had a whiplash effect on the process.
IoT has rebooted the PLM conversation to move it away from the product and make it more about the customer. IoT-enabled products can now deliver intelligence post sales about how the product is being used (or not), how it is being disposed of, and a whole host of other downstream information. Such product intelligence is useful in two primary ways: as a method of refining the product to make it more agile and responsive to consumer needs (thereby leading to potentially more sales) and as new avenues of monetizing such product intelligence.
The future of product intelligence is a complete “closed-loop” product development, with real-time customer feedback woven into the process. It bears stressing that while customer focus groups and behaviors have always been part of the design and manufacture process, IoT has effectively compressed that time cycle and expanded the scale of parameters that might be considered — and monetized.
Service intelligence delivers customer-focused monetization
Monetization in the new smart factory landscape need not be restricted to product intelligence alone. Service intelligence, for example, is about delivering aftermarket intelligence in the form of added services to an existing or expanding customer base. A customer who buys Widget A from a manufacturing company might also be interested in understanding how to optimize the use of that widget for their own tailored environments.
While aftermarket services are not entirely new, the addition of IoT has the capability of delivering service intelligence on steroids. In the future, service intelligence providers will use IoT to tailor measurements of key performance indicators (KPIs) and delivery of data insights depending on exactly what the end customer is looking for. Tailoring service intelligence to the customer potentially leads to greater client stickiness. What’s more, IoT is capable of slicing and dicing intelligence for each and every customer, making the net results that much more insightful and leading to more bountiful monetization opportunities.
Operations intelligence squeezes the most out of machines
Monetization also comes from picking the low-hanging fruit in production processes. Arguably one of the best ways to squeeze the most out of IoT is to use it to increase manufacturing uptime. IoT is also favorably impacting the ability to fine-tune production processes by being able to connect, visualize and analyze data from a whole host of new players such as machines on the plant floor. RFID and computer vision layers also add to such intelligence.
IoT-embedded devices on the plant floor can spit out data that measures machine health, which can be fed into machine learning algorithms for predictive maintenance. If a rotor heats up past a preset temperature setting, for example, it can trigger the algorithm to send an alert to a plant worker or even proactively shut the machine down. Machine learning capabilities derived from IoT enhance KPIs such as manufacturing uptime.
In the future, expect a move toward increasingly segmented manufacturing, possibly sliced and diced into ever smaller batches. Operations intelligence will allow manufacturers to segment the production process — and fine-tune each — to fulfill a variety of specialty orders at the same time.
What it takes to deliver on the promise of IoT
While IoT intelligence in its various forms promises a truly smart factory with a wealth of monetization opportunities, it needs a robust infrastructure to truly deliver. Elements of this winning infrastructure include, among others: a C-suite willing to address negative attitudes of incumbency; standardization of data aggregation and analytics processes such as machine learning; and future-proofing technologies through increasing reliance on open-source models.
Since data is the lifeblood of IoT, enterprises need to ensure that they don’t get mired in the data lake — that the data they’re working with is clean and structured, relevant to the KPIs they want measured, and fed to algorithms in a consistent format. Once data is clean and uniform, smart factories can leverage IoT to feed machine learning algorithms that learn from the data and eventually deliver an almost lights-out production stream.
Since the future of intelligence also involves its monetization — vendors up and down the digital supply network will pay for insights — it will be important to connect stakeholders to the central nervous system of the smart factory in new ways. Customer service agents (or even customers themselves) for example should be able to see where product orders are in the production process and fine-tune their forecasts accordingly. IoT delivers transparency to all stakeholders — within reason, keeping intellectual property concerns in mind.
IoT in manufacturing is not limited to the production floor either. IoT sensors in warehouses can detect when supplies are going bad, when inventory is low and beef up accordingly. Remote weather events that can affect vendor delivery can trigger automated backups. The IoT-driven smart factory touches many processes and products much beyond the plant floor.
Until true digitization from start to finish is a total reality, companies are figuring out stop-gap measures that will leverage the promise of IoT. A “nerve center,” which serves as a central repository for data gathering and analytics can serve to overcome the problem of data connectivity across locations and devices.
The ripple effect from IoT intelligence is not limited to the manufacturing floor alone. By placing the digital core at the center, it reshapes processes up and down key constituencies such as supply chain and asset management.
How tomorrow’s tech might impact IoT intelligence
IoT is already being incorporated in the smart factory of today. Tomorrow, expect acceleration with respect to monetizing closed-loop product intelligence, an increased focus on the customer through service intelligence and using operations intelligence by improving businesses processes on the way to a truly smart factory.
The road is expected to get even smoother with the advent of 5G technology which will decrease latency of IoT for edge computing devices. 5G will deliver even faster access to data in real time which will make real-time analysis even more accurate. The technology has special ramifications for production processes where time is of the essence. Devastating machine shutdowns can be averted in split seconds by machine learning algorithms fed through 5G connections from IoT-enabled equipment. This means smart factories of faster computing speeds and greater agility. The state of the union for IoT intelligence is strong and only expected to grow stronger as new technologies such as 5G make data competencies that much more robust.
Cognizant (Nasdaq: CTSH) is dedicated to helping the world’s leading companies build stronger businesses — helping them go from doing digital to being digital.
How to live forever: the longevity industry ramps up
The growing longevity industry may be on the verge of extending our lifespans by years or decades. Here’s an overview of the future of your health. Assuming it’s not just tech industry hype.
On September 3, Peter Diamandis sent out this provocative little tweet:
In a way, it’s encouraging: ditch the late-night deep-dish pizza, log an extra couple of miles on the treadmill, and voila — you can comfortably expect a much, much longer life than you’re probably anticipating right now.
But is there any truth to the claim?
Diamandis is well known in tech circles — maybe most notably as the Founder & Executive Chairman of XPRIZE, which offers global crowdsourcing innovation challenges, and the Executive Chairman & Co-Founder of Singularity University, which delivers executive educational programs and business consultancy services.
Diamandis is also deeply involved in the rapidly growing ‘longevity sector.’ For example, he’s also the President of Vaxxinity which has a mission to “Democratize health by pioneering the third biologic revolution.”
You’d be forgiven if you’re confused about what that means.
You’d also be right to be suspicious, as Diamandis has a checkered past on related issues. As MIT Technology Review reported, back in 2021, Diamandis hosted a conference only to see it turn into a COVID-19 super spreader event. His response was to launch a subsequent webinar to calm attendees, where they were reportedly offered “fraudulent COVID-19 treatments, from injectable peptides to amniotic fluid.”
So, yes. Consider the source.
Still, there might be something there. There are billions in venture capital now pouring into the industry, with a high of over $6 billion allocated to firms in 2021. There’s also something intuitive about the idea that as medicine and technology improve, and we gather more evidence about protecting our health, our lifespans will get longer. That’s been the general trajectory of the human race for hundreds of years now. In many western countries, human lifespan has roughly doubled over the last two hundred years.
Why would things stop now?
What is the longevity industry?
Fundamentally, the longevity sector is new enough (it’s less than a decade old) and poorly understood enough to be the subject of a debate about what it actually is. The most common way to describe it is a sector that is focused on extending human lifespan — or human healthspan, depending on who you talk to or what company is being hyped.
The real confusion hits when you get to the details.
The longevity industry incorporates multiple poorly understood sectors like biomedicine and biotech, geroscience (effectively, the study of the risks of aging), and agetech (which addresses the needs of aging people). Recent advancements in AI are also part of the reason the sector is suddenly so intriguing. They may unlock some of the exciting possibilities of human healthspan expansion.
This is probably a good place to make the distinction between lifespan and healthspan. Lifespan is fairly obvious. But healthspan refers to the period of time someone can live without suffering from chronic or debilitating disease. Live to 87 while golfing, traveling, and living your best life until the day you die? Great. Live to 95 but spend the last 20 years of your life being shuttled in and out of hospitals? Less great.
The longevity industry is looking beyond both of these horizons. Prognosticators like Diamandis are forecasting the ability for humans to live to the age of 120, 130, or even longer with healthspans that extend just as long.
How big a leap is this longevity movement from where we are today?
If you’ve been tracking the digital transformation of the healthcare sector, the longevity movement may seem a bit far-fetched.
The stories of modern digital health tend to be focused on more prosaic issues: the efforts to digitize health records, the struggle to share information across health care providers, and the privacy implications of both.
We have seen advances in cancer treatments, telehealth, and considerable focus on what digital healthcare delivery can do for rapidly aging populations around the world.
But the narrative has not focused on ‘moonshot-style’ health outcomes.
However, there has been a simultaneous and significant shift going on amongst innovators and scientists in the healthcare industry, as Deloitte noted:
“We are beginning to see a paradigm shift from disease-focused treatments to those that address the underlying mechanisms of aging, biological systems, and wellness. In fact, a growing community of scientific researchers believe they have the tools to extend healthy human life, transforming health care as we know it today.”
This reframing of the opportunity could be the significant unlock for longevity. Global spending on healthcare runs to about $9 trillion USD which feels even bigger when you see it with all its attendant digits: $9,000,000,000,000.
This is about 11% of the total GDP of all nations on Earth.
If the focus of that spending shifted primarily to eliminating the underlying causes of aging and disease instead of treating them, what would that mean for the future of the longevity industry — and the lives of everyday people?
Retro Biosciences & other notable companies that may extend your life — and health
In 2022, a company called Retro Biosciences emerged with $180 million in venture capital and a mission to ‘add 10 years to the healthy human lifespan’ by ‘focusing on the cellular drivers of aging to design therapeutics eventually capable of multi-disease prevention.’
MIT Technology Review then revealed that all Retro Biosciences’ money came from Sam Altman, the CEO of OpenAI, which created ChatGPT.
Retro Biosciences is a useful analog for many longevity companies. It’s extraordinarily capital intensive and its timeline to commercialize and scale its outputs is much longer than many investors could tolerate. This is especially true, given the need for regulatory approvals for some of the potential treatments or products that would affect human health.
As Samuel Gil, Partner at JME Ventures told TechCrunch: “The main challenge of the space is that the most audacious approaches and products have to be clinically tested in large samples of the population for very long periods of time.”
But Gil is ultimately a longevity optimist: “Although the target market for most products is still very niche at the moment, I do believe that they will go mainstream in the medium term. The opportunities are endless, as the space is only getting started now and will infiltrate all aspects of our life in the next five to 10 years.”
Retro Biosciences is one of a handful of notable new companies focused on longevity. Others include the Jeff Bezos-co-founded Alto Labs, which seeks to reverse disease, injury, and disabilities through cellular rejuvenation programming; Juvenescence, which is developing therapeutic interventions that will enable people worldwide to live longer, healthier lives; and Unity Biotechnology, which is developing medicines to slow, halt, or revere diseases of aging.
Ultimately, there are real reasons to be very cynical about big claims coming out of Silicon Valley, especially those that haven’t been proven out. But expanding human longevity and healthspan is one of tech’s more noble missions. And that could kick off a new era of human flourishing, both physically and financially.
To wit: Christian Angermayer, Founder of Aperion Investment Group, told TechCrunch that while there are no current products in-market that have been proven to delay aging, once there are, everything will change.
“Once the first ones are proven in a clinical trial, we expect that to go from zero to a trillion-dollar industry within a decade. It will be that fast.”
DX Journal covers the impact of digital transformation (DX) initiatives worldwide across multiple industries.
Self-driving car revolution is coming, but slowly
In Munich, where this week’s IAA motor show is taking place, an interactive street survey elicits an overwhelming “yes” when asking passers-by if they would take a self-driving taxi from the station to the Oktoberfest beer festival.
But while the number of coloured balls placed in the “yes” column shows no shortage of enthusiasm, experts say the long-promised future of autonomous cars remains some way off.
“Five years ago, we thought that by 2025 we would have significant autonomy in many vehicles, which is not the case,” said Christophe Aufrere, chief technical officer of car-parts maker Forvia.
Pandemic-related disruptions to the car industry, a shift towards investing in electrification and the sheer complexity of the technology have all contributed to keeping the autonomous-driving revolution stuck in the slow lane.
Now, “we’re more inclined to say it will happen by 2030,” Aufrere told AFP.
Ahead of the pack, German luxury carmaker Mercedes-Benz has received international approval for its “level three” autonomous driving system in accordance with United Nations standards.
The hands-free level three allows for autonomous driving in certain conditions such as heavy traffic or motorway speeds up to 60 kilometres per hour (37 mph). The driver can take their eyes off the road but must be ready to intervene if needed.
The system is available as an option on the flagship Mercedes S-Class, which has a six-figure price tag.
Honda won a world-first approval to sell level three autonomous cars in Japan in 2021.
But the vast majority of today’s commercially available cars come equipped with “level two” partial automation at best.
That includes Tesla’s well-known “autopilot” and offers features such as adaptive cruise control or automated parking — while the driver remains alert at all times.
– ‘Step by step’ –
But the driverless “robotaxis” teased by the Munich survey remain a futuristic dream in most cities, with Europe lagging behind the United States and China in trialling such services in the real world.
These “level four” vehicles, like the robot cabs from Waymo or Cruise used in San Francisco, can operate without human intervention within designated areas.
The uneven deployment in Europe wasn’t down to regulations or technological challenges but rather a matter of funding that was harder to come by on the continent, according to Christophe Perillat, CEO of French automotive supplier Valeo.
Nevertheless, “autonomous vehicles are making progress year after year,” Perillat said at the IAA.
Professor Lutz Eckstein from RWTH Aachen University agreed, saying “significant advances” were on the horizon.
So-called level 2+ systems that also monitor the driver’s attentiveness and fatigue are expected to become more widespread, he said, predicting that the number of level three systems on the market would also increase.
“By the end of the decade, we want to achieve the ability to drive on the motorway at speeds of 130 kilometres per hour,” a Mercedes spokesperson told AFP.
The company aims to offer level four highly-automated driving by the same deadline.
“The idea is to proceed step by step,” confirmed Forvia’s CTO Aufrere. “Because we want to be sure it works.”
Where will AI go next?￼
This year’s Collision conference featured a wide range of buzzy AI solutions — both B2B and for consumers.
The buzzy topic of AI was not in short supply at this year’s annual Collision conference in Toronto. The list of applications using the technology was seemingly endless — from both the presenters and exhibitors.
It comes at a unique time, as analysis of the industry reveals that we’ve crossed into the “era of deployment.” At the same time, it’s imperative that we think critically and ask questions about said deployment.
In June, Research and Markets revealed a study demonstrating how the AI industry has experienced immense expansion and maturation in recent years, from a $62B market in 2020, to projections saying 40% growth annually until 2026.
Meanwhile, the 2023 AI Index, an independent initiative at the Stanford Institute for Human-Centered Artificial Intelligence (HAI), reports that:
- AI systems can both have a large carbon footprint (when training), and be “used to optimize energy use”
- Incidents of AI misuse is “rapidly” on the rise. As the Stanford team explains, ‘more AI, more problems”
- There was a 27% decrease in Global AI private investment (year-over-year) from 2021 to 2022. At the same time, over the last decade, investment has increased — in 2022, it was 18 times greater than in 2013.
- Companies that have adopted AI are pulling ahead, while the proportion of those adopting AI has actually plateaued.
- Only 35% of Americans surveyed agree that “products and services using AI had more benefits than drawbacks,” compared to 78% of Chinese respondents, 76% from Saudi Arabia, and 71% from India.
It seems clear that the sector is at something of a crossroads.
DX Journal spoke to four AI startups at Collision, covering areas like filing taxes, DIY home and appliance repair, game building, and building work teams — all showing how AI can have an impact both at home and the workplace.
DIY home maintenance, with a little AI help
Collision presenter Eradj Khaidarov, Chief Technology Officer of IrisCX, spoke on the topic of “Delivering a more human experience through visual intelligence and AI.” He transitioned from twenty years in the video conferencing field to IrisCX, a video-based troubleshooting app that helps users with DIY repair. Anything from appliances to home devices, AI determines the make, model, problem, and spits out possible solutions.
“All of us hate dealing with manuals from 10 years ago and only keep them around when we truly need them — and we also hate dealing with YouTube videos that may not necessarily answer all our questions,” he explained. “The interactions with our product can help you get to an answer faster, without having someone come to your home. It’s just the little bit of guidance that can help us solve a problem quickly and efficiently.”
AI allows the app to summarize certain markers in the conversation, to formulate what was truly the problem.
Let AI help find your next hire
Meanwhile, Raphael Ouzan, co-founder & CEO of A.Team, wants AI to revolutionize how people build teams.
Prior to helping found the startup, he served in the Israeli military for five years in cyberwarfare and cryptology, “finding the power-people you could work with, even in impossible missions.”
Later, he built teams as he built start-ups, and realized he wanted to build something that would enable anyone to find the right teammate — or teammates — to accomplish a greater goal.
When a user logs in to A.Team, they will do a search for their preferred skill and industry, while the AI will detect keywords, suggesting the relevant team that matches the work desired.
“I would describe it as a platform that enables the formation, management, and scaling of elite tech teams that drive massive change for companies,” he said.
“You can look at it like a high-end UpWork, for teams.”
A.Team has raised $55 million, funded by the likes of rapper Jay-Z, and has advisors that include Fiverr founder Shai Wininger and former UpWork CEO Stephane Kasriel.
Creativity + AI
One very popular area where AI is being leveraged is for imagery, game creation, and video creation.
Unity offers tools and solutions for game developers, industrial customers, and professional artists. And as Chief Marketing Officer Carol Carpenter explains, “what we are seeing is that every pixel, every piece of art, every frame will be compacted on the creative side by AI.”
“If you draw two frames, then ask: ‘hey, draw ten more for me like this.’ Or, I want a scene in a digital twin or game, with snowing mountains. AI can offer some art to choose from.”
One of their newest products, Unity Muse, launched during Collision. As Carpenter describes, it “has a feel like ChatGPT, where programmers can type in an image request, and either see it animated or developed on-demand.”
For example, the user could input the text: “Ferrari driving down a steep hill,” and what would pop out would be AI’s creation based on the request. The user could decide to keep it as a standalone graphic, or instruct Unity Muse to make the image animate.
From there, the sky’s the limit, although a human hand — and creativity — will always play a part.
To build a game today with real time 3D, she explains, what’s required is experience and coding knowledge. “It’s not something you just pick up and do easily.”
With Unity, there’s an “ability to use natural language to create, to accelerate the process,” said Carpenter. “We still very much believe the creator needs to have ideas; they need to have the spark of imagination. AI is good for getting started or a prototype. Then there needs to be polish and human element of judgment.”
Your taxes, automated
Many believe that the best place to deploy AI is for truly mundane tasks that make sense to automate.
In that vein, Ben Borodach and his team have brought it to tax filing.
April is touted as the first AI-powered tax system that both optimizes and files taxes, via a large language model and proprietary generative AI that reads tax law.
“It doesn’t matter if you’re an Uber driver, an e-commerce seller, or a family with two jobs, you still get the same experience,” explained the co-founder and CEO. “A personalized leveraging of AI, where we serve up 1.2 septillion unique paths to filing returns. So every single person gets a customized flow for their specific experience.”
There are, Borodach explained, thousands of possible tax questions across federal, state, and local jurisdictions that a taxpayer could be asked. Each time the user answers a question, the program learns more about the user.
As AI technologies evolve, its growth is poised to reshape virtually every field it touches.
It is already entering our lives in an accessible, individualized way, catering to the unique needs of each user. From healthcare and education to finance and entertainment, its capabilities will soon permeate unexpected areas, transforming our lives in profound ways.
Dave is a journalist whose work has appeared in more than 100 media outlets around the world, including BBC, National Post, Washington Times, Globe and Mail, New York Times, Baltimore Sun.
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