High-bandwidth brain-computer interfaces (BCI) will become available for public use: technologist and futurist Ray Kurzweil predicted that, by the mid-2030s, we will begin connecting the human neocortex to the cloud. In this coming decade, there will be tremendous progress in that direction, first serving people with spinal cord injuries, where patients will regain sensory capability and motor control. In addition to helping people with motor function loss, several BCI pioneers are now attempting to supplement their basic cognitive abilities — a pursuit with the potential to enhance their sensory range, memory, and even intelligence. This meta-trend is fueled by the convergence of: materials science, machine learning, and robotics.
High-resolution VR will transform retail shopping and real estate: lightweight, high-resolution virtual reality headsets will allow people at home to shop for everything from clothing to real estate from the comfort of their living room. Need a new outfit? Your AI knows your detailed body measurements and can create a fashion show with your avatar wearing the latest 20 designs on the runway. Want to see how your furniture might look inside a home you're viewing online? No problem! Your AI can populate the property with your virtualized inventory and conduct a guided tour. This meta-trend is enabled by the convergence of: VR, machine learning, and high-bandwidth networks.
Greater focus on sustainability and the environment: a rise in global environmental awareness and concern over global warming will lead companies to invest in sustainability, both out of necessity and for marketing purposes. AI-enabled advances in materials science will allow companies to achieve tremendous reductions in waste and environmental contamination. One company's waste will become another company's profit center. This meta-trend is enabled by the convergence of: materials science, artificial intelligence, and broadband networks.
CRISPR and gene therapies will minimize disease: a wide variety of infectious diseases, ranging from AIDS to Ebola, are now curable. Furthermore, gene-editing technologies continue to advance in precision and ease of use, enabling families to treat and ultimately cure hundreds of inherited genetic diseases. This meta-trend is driven by the convergence of: various biotechnologies (CRISPR, gene therapy), genome sequencing, and artificial intelligence.
The ability to sense and know anything, anytime and anywhere: we are rapidly approaching an era in which 100 billion sensors (the Internet of Everything) are monitoring and sensing (imaging, listening, measuring) every facet of our environments, all the time. Global imaging satellites, drones, autonomous vehicle LIDARs, and forward-facing augmented reality (AR) cameras are part of a global sensor matrix, enabling us to know anything, anytime and anywhere. This meta-trend is driven by the convergence of: ground, atmospheric, and space-based sensors, vast data networks, and machine learning. In this future, it is not "what you know," but "the quality of the questions you ask" that will matter most.
Disruption of advertising: as AI becomes increasingly embedded in everyday life, your personalized AI will soon understand what you want better than you do. In turn, we will begin to trust and rely on our AIs to make the majority of our purchasing decisions, delegating shopping to AI-enabled personal assistants. Your AI can shop based on your past desires, current scarcity, conversations you have allowed it to listen to, or by tracking where your pupils focus on a virtual interface (i.e., what catches your attention). As a result, the advertising industry — which typically competes for your attention (whether during the Superbowl or on search engines) — will have great difficulty influencing your AI. This meta-trend is driven by the convergence of: machine learning, sensors, augmented reality, and 5G networks.
Cellular agriculture moves from the laboratory to inland cities, delivering higher-quality, cheaper, and healthier proteins: in this coming decade we will witness the birth of the most ethical, nutritious, and environmentally sustainable protein production system ever developed by humanity. Stem cell-based 'cellular agriculture' will enable the production of beef, chicken, and fish anywhere, on demand, with far higher nutritional content and a much smaller environmental footprint than traditional livestock options. This meta-trend is enabled by the convergence of: biotechnology, materials science, machine learning, and AgTech.
The insurance sector transforms from "recovery after risk" to "risk prevention": today, fire insurance pays you after your house burns down; life insurance pays your family after you die; and health insurance (which is really illness insurance) pays only after you get sick. In the next decade, a new generation of insurance providers will leverage the convergence of machine learning, ubiquitous sensors, low-cost genome sequencing, and robotics to detect risks, prevent disasters, and ensure safety before costs are incurred.
Autonomous vehicles and flying cars will redefine human travel (it will soon be much faster and cheaper): fully autonomous vehicles, car-as-a-service fleets, and aerial ride-sharing (flying cars) will be fully operational in most major metropolitan cities within the next decade. The cost of transportation will fall 3–4X, transforming real estate, finance, insurance, material economics, and urban planning. Where you live and work, and how you spend your time, will all be fundamentally reshaped by this future of human travel. Your children and elderly parents will never drive. This meta-trend will be driven by the convergence of: machine learning, sensors, materials science, improvements in battery storage, and ubiquitous gigabit connectivity.
On-demand production and on-demand delivery will give rise to an "instant economy of things": urban residents will learn to expect "instant fulfillment" of their retail orders, as last-mile drone and robotics delivery services transport products from local supply warehouses directly to their door. Beyond the deployment of regional on-demand digital manufacturing (3D printing farms), individualized products can be obtained within hours, anywhere and anytime. This meta-trend is driven by the convergence of: networks, 3D printing, robotics, and artificial intelligence.
Most people will adopt a JARVIS-like "software shell" to enhance their quality of life: as services like Alexa, Google Home, and Apple HomePod expand in functionality, these services will ultimately travel outside the home and become your 24/7 cognitive prosthetic. Imagine a secure JARVIS software shell to which you grant permission to listen to all your conversations, read your email, monitor your blood chemistry, etc. With access to this data, these AI-enabled software shells will learn your preferences, anticipate your needs and behavior, shop for you, monitor your health, and help solve problems in support of your medium- and long-term goals.
Cheap and abundant renewable energy worldwide: continued advances in solar, wind, geothermal, hydroelectric, nuclear, and localized grid technologies will lead humanity toward cheap, abundant, and ubiquitous renewable energy. The price per kilowatt-hour will fall below 1 cent per kilowatt-hour for renewables, just as storage falls below a mere 3 cents per kilowatt-hour, resulting in the majority displacement of fossil fuels worldwide. And since the world's poorest countries are also the world's sunniest, the democratization of both new and traditional storage technologies will ensure energy abundance for those already bathed in sunlight.
AI-humanity collaboration will surge across all professions: the rise of "AI as a service" (AIaaS) platforms will enable humans to partner with AI in every aspect of their work, at every level, across every sector. AIs will become deeply embedded in daily business operations, serving as cognitive collaborators for employees — supporting creative tasks, generating new ideas, and driving previously unattainable innovations. In some fields, partnering with AI will become a requirement. For example: in the future, making certain diagnoses without AI consultation may be considered negligence.
AI will reach human-level intelligence: as predicted by technologist and futurist Ray Kurzweil, artificial intelligence will achieve human-level performance this decade (by 2030). In the 2020s, AI algorithms and machine learning tools will become increasingly open-source and cloud-available, allowing anyone with an internet connection to supplement their cognitive capacity, enhance their problem-solving ability, and build new ventures at a fraction of the current cost. This meta-trend will be driven by the convergence of: high-bandwidth global connectivity, neural networks, and cloud computing. Every sector, spanning industrial design, healthcare, education, and entertainment, will be impacted.
Everything becomes smart, embedded with intelligence: the price of specialized machine learning chips is falling rapidly with rising global demand. Combined with the explosion of low-cost microscopic sensors and the deployment of high-bandwidth networks, we are entering a decade where every device becomes intelligent. Your child's toy remembers faces and names. Your child's drone safely and diligently follows and films every child at the birthday party. Appliances respond to voice commands and anticipate your needs.
Augmented Reality and the Spatial Web will achieve ubiquitous deployment: the combination of Augmented Reality (producing Web 3.0 or the Spatial Web) and 5G networks (offering connection speeds of 100Mb/s – 10Gb/s) will transform how we live our everyday lives, impacting every sector from retail and advertising to education and entertainment. Consumers play, learn, and shop throughout the day in a newly intelligent and virtually overlaid world. This meta-trend will be driven by the convergence of: hardware advances, 5G networks, artificial intelligence, materials science, and growing computational power.
An era of capital abundance will see increasing access to capital everywhere: from 2016 to 2018 (and likely in 2019), humanity reached all-time highs in global flows of seed capital, venture capital, and sovereign wealth fund investments. While this trend will experience some ups and downs following future recessions, it is expected to continue its general upward trajectory. An abundance of capital leads to the funding and testing of 'crazy' entrepreneurial ideas, which in turn accelerates innovation. $300 billion in crowdfunding is already projected by 2025, democratizing access to capital for entrepreneurs worldwide. This meta-trend is driven by the convergence of: global connectivity, dematerialization, demonetization, and democratization.
Average human healthspan will increase by more than 10 years: a dozen innovative biotechnology and pharmaceutical solutions (currently in clinical trial phases 1, 2, or 3) will reach consumers this decade, adding an extra decade to the human healthspan. The technologies include stem cell supply restoration, untreated pathway manipulation, senolytic drugs, a new generation of Endo vaccines, GDF-11, NMD/NAD+ supplementation, among several others. And as machine learning continues to mature, AI is expected to unlock countless new drug candidates ready for clinical testing. This meta-trend is driven by the convergence of: genome sequencing, CRISPR technologies, AI, quantum computing, and cellular medicine.
Gigabit global connectivity will connect everyone and everything, everywhere, at ultra-low cost: the deployment of licensed and unlicensed 5G, together with the launch of a multitude of global satellite networks (OneWeb, Starlink, etc.), enables ubiquitous, low-cost communications for everyone, everywhere — not to mention connecting trillions of devices. And today's surging connectivity is bringing another 3 billion individuals online, channeling tens of trillions of dollars into the global economy. This meta-trend is driven by the convergence of: low-cost space launches, hardware advances, 5G networks, artificial intelligence, materials science, and growing computational capacity.
1 – The End of Shopping Malls
Artificial intelligence is making retail cheaper, faster, and more efficient, spanning everything from customer service to product delivery.
Prepare for a future in which shopping is dematerialized, demonetized, democratized, and delocalized — also known as "the end of shopping malls."
Perhaps it is not quite the end of shopping malls if they adapt into spaces for more engaging and intelligent experiences that draw us out of the house to enjoy them — since for actual shopping, you can simply ask Alexa.
Either way, it is a complete transformation of the retail world.
In upcoming posts, we will continue our discussion about the future of retail. Stay tuned to learn about new implications for your business and how to future-proof your company in an era of smart, ultra-efficient, and experiential retail.
2 – Customer Service
But AI is disrupting more than just personalized fashion and e-commerce. Its next major opportunity will be in the customer service arena.
According to a recent study by Zendesk, good customer service increases the likelihood of purchase by 42%, while poor customer service translates into a 52% chance of losing the sale forever. This means that more than half of us will stop shopping at a store due to a single disappointing customer service interaction.
These are significant financial stakes. They are also problems perfectly suited to an AI solution.
During Google's I/O conference in 2018, CEO Sundar Pichai demonstrated Google Duplex, its next-generation digital assistant. Pichai presented the audience with a series of pre-recorded phone calls made by Google Duplex. The first call made a restaurant reservation; the second scheduled a haircut appointment, entertaining the audience with a lengthy "hmm" in the middle of the call.
In neither case did the person on the other end of the phone have any idea they were talking to an AI.
The system's success speaks to how seamlessly AI can blend into our retail lives and how much more convenient it will continue to make them.
The same technology that Pichai demonstrated can make calls to consumers can also answer calls for retailers — a development that unfolds in two distinct ways:
(1) Customer service coaches:
First, for organizations interested in keeping humans in the loop, there is Beyond Verbal, a Tel Aviv-based startup that has built an AI customer service coach.
Simply by analyzing the customer's vocal intonation, the system can tell whether the person on the phone is about to blow a fuse, is genuinely excited, or something in between.
Based on research involving more than 70,000 individuals across more than 30 languages, Beyond Verbal's application can detect 400 different markers of human moods, attitudes, and personality traits.
It has already been integrated into call centers to help human sales agents understand and respond to customers' emotions, making those calls more pleasant and also more profitable.
For example, by analyzing word choice and vocal style, Beyond Verbal's system can determine what kind of buyer the person on the line really is. If they are early adopters, the AI alerts the sales agent to offer the best and latest. If they are more conservative, it suggests more tried-and-tested items.
(2) Replacing customer service agents:
Second, companies like New Zealand's Soul Machines are working to fully replace human customer service agents.
Developed on IBM's Watson, Soul Machines creates realistic customer service avatars designed for empathy, making them one of many helping to pioneer the field of emotionally intelligent computing.
With their technology, 40% of all customer service interactions are now resolved with a high degree of satisfaction, without any need for human intervention. And since the system is built using neural networks, it is continuously learning from each interaction — meaning that percentage will keep improving.
The number of these interactions also continues to grow. Software maker Autodesk now includes a Soul Machines avatar called AVA (Autodesk Virtual Assistant) in all its new offerings. She lives in a small window on screen, ready to defuse tensions, troubleshoot issues, and banish long technical support hold times forever.
For Daimler Financial Services, Soul Machines built an avatar called Sarah, who helps customers with three of modernity's most frustrating tasks: financing, leasing, and insuring a car.
It is not just about AI — it is about AI converging with additional exponentials. Add networks and sensors to the story and it escalates the scale of disruption, raising the FQ — the Friction Quotient — in our frictionless shopping adventure.
3 – Digital Assistants
Let us start with the basics: the act of turning desire into purchase.
Many of us browse shopping malls or online marketplaces alone, hoping to find the right item in good shape. But if you are fortunate enough to hire a personal assistant, you can afford to describe what you want to someone who knows you well enough to buy exactly the right thing most of the time.
For most of us who don't, enter the digital assistant.
At present, the four horsemen of the retail apocalypse are at war over our wallets. Amazon's Alexa, Google Now, Apple's Siri, and Alibaba's Tmall Genie are locked in a battle to become the go-to platform for AI-assisted, voice-activated commerce.
For baby boomers who grew up watching Captain Kirk talk to the Enterprise's computer on Star Trek, digital assistants feel a bit like science fiction. But for millennials, it is simply the next logical step in a world that is self-magical.
And as those millennials enter their peak consumer years, revenue from products purchased via voice-activated commands is projected to leap from the current $2 billion to $8 billion by 2023.
We are already seeing a major shift in purchasing habits. On average, consumers using Amazon Echo spent more than standard Amazon Prime customers: $1,700 versus $1,300.
And when it comes to an AI fashion consultant, they are also already here, courtesy of Alibaba and Amazon.
During the annual Singles' Day shopping festival (November 11), Alibaba's FashionAI concept store uses deep learning to make suggestions based on human fashion expert advice and store inventory, generating a significant portion of the day's $25 billion in sales.
Similarly, Amazon's shopping algorithm makes personalized clothing recommendations based on user preferences and social media behavior.
A Day in the Life of 2029
Welcome to April 21, 2029, a sunny day in Dallas. You have a fundraising luncheon tomorrow but nothing to wear. The last thing you want to do is spend the day at the mall.
No sweat. Your body image data is still current, since you were scanned just a week ago. Put on your VR headset and chat with your AI.
"Time to buy a dress for tomorrow's event" is all you need to say.
In a moment, you are teleported to a virtual clothing store. Zero travel time. No road traffic, parking hassles, or furious hordes wielding strollers.
Instead, you have entered your own personal clothing store. Everything is in your exact size … and I mean everything. The store has access to virtually every designer and style on the planet.
Ask your AI to show you what is trending in Shanghai and voilà — instant fashion show. All the models walking the runway look exactly like you, dressed only in Shanghai's latest offerings.
When you finish selecting an outfit, your AI pays the bill. And since your new clothes are 3D-printed in a warehouse — before being rushed by drone delivery — a digital version has been added to your personal inventory for use at future virtual events.
The cost? Thanks to a disintermediated era, less than half of what you pay in stores today.
Yet this future is not so far away…
South Australia's home batteries keep the lights on in Queensland after a coal unit fails.
What it is: last month, after a major power plant suddenly went offline in Queensland, Australia, an unlikely and renewable candidate came to the rescue. A distributed solar and battery energy project, the VPP (South Australia Virtual Power Plant) — led by US Battery and Tesla — aggregates stored solar resources from hundreds of homes with rooftop solar photovoltaic (or rooftop PV) plants. On October 9, when the Kogan Creek coal power plant in Queensland tripped, reducing supply by 784 MW and placing the grid at risk, the VPP had the chance to prove its worth. Detecting the drop in frequency, the VPP immediately injected energy from its 900-plus systems back into the grid, helping stabilize the system.
Why it matters: Kogan Creek is Australia's largest coal-fired power station; therefore, the ability of a distributed renewable energy network to intervene immediately drew significant praise across the country and beyond. Today, energy storage is an essential limiting reagent in our efforts to mainstream renewable sources, critical for buffering the variability of solar and wind energy. Demonstrated successes in grid-scale distributed storage may therefore have a considerable impact on the widespread adoption of solar and micro-grid technologies, particularly in the case of residential rooftop solar PV systems.
Quantum computers learn to mark their own work.
What it is: researchers at the University of Warwick have developed a method to verify the answers of a quantum computer. Using problems for which the answers are already known, the team is able to quantify the effect of noise on the computer, creating two percentage-based metrics to determine accuracy. The first metric is an estimate of how close the quantum computer's answer is to the real answer, while the second is a confidence score for that closeness. In this way, quantum computing engineers can further refine the machines by identifying sources of error, paving the way for future applications.
Why it matters: by definition, quantum computers are designed for problems that would take classical computers an exponential amount of time to solve. In the past, researchers therefore required exorbitant classical computational resources to check their answers — a task that quickly becomes infeasible for applications designed for quantum computers. However, with the researchers' newly developed protocol, quantum computing systems can verify themselves independently of large servers, thereby providing far greater utility.
Playing hide-and-seek, machines invent new tools.
What it is: OpenAI programming researchers recently taught a group of AI bots to play hide-and-seek, releasing them in teams of up to three agents across hundreds of millions of consecutive games. While the AI seekers and hiders started with a blank slate and no game instructions, they quickly learned to chase and hide, build fortifications (around the 25-million-game mark), and even discover unexpected uses for unusual tools. Engaged in a cat-and-mouse battle, OpenAI's bots gradually learned increasingly complex attack and defense strategies. After nearly 390 million games, for example, the seekers learned to use virtual boxes to "surf" around the arena and gain visibility — a strategy quickly thwarted by the hiders, who learned to lock those boxes and prevent surfing after approximately 458 million games.
Why it matters: the rapid progression of OpenAI bots' game strategies across millions of iterations, producing advantageous traits, has been compared by some to the evolution of human intelligence. More importantly, OpenAI's algorithms demonstrated the remarkable ability to identify creative uses for undefined tools, paving the way for AIs that will soon be able to solve far more complex strategy-related problems in unstructured contexts. According to Danny Lange, Vice President of AI at Unity Technologies (a game engine company), "there is nothing here that prevents this […] from following a path where tool use becomes increasingly complex." This complex tool use — a hallmark of human intelligence — appears to be further stimulated by AI gameplay, as competitive environments drive algorithms to learn from and work around their own mistakes over time.
Bill Gates-backed solar startup announces a major breakthrough.
What it is: Bill Gates-backed startup Heliogen recently unveiled its solar concentration technology, which is expected to "commercially replace fuels with high-temperature, carbon-free solar heat from the sun." Founder Bill Gross (who also founded Idealab) works on the company within his own incubator, alongside several other clean energy startups. The first of its kind, the Heliogen system consists of computer vision software that coordinates a large array of mirrors to reflect sunlight onto a single target, which can deliver up to 1,000 degrees Celsius of heat. This extreme level of heat is required for industrial processes such as those used in the manufacturing of cement, steel, and other materials, the production of which contributes to one-fifth of global fossil fuel emissions, according to Bill Gates. If companies purchase Heliogen's system, however, Gross claims the technology could pay for itself within 2–3 years, reducing companies' fossil fuel emissions by up to 60%.
Why it matters: electricity accounts for less than a quarter of global energy demand. Heliogen's technology addresses a large share of the remaining 75%, providing an alternative energy supply for major industrial needs. Sunlight is a free commodity, and that simple fact offers a tremendous economic incentive for companies to invest in effective concentrated solar energy. While our individual daily energy decisions impact the environment, large corporations can profit from and contribute to the shared pursuit of a zero-emissions future. While most heavy industry participants rely solely on fossil fuels to reach high temperatures, systems like Heliogen's can provide long-term energy alternatives, capitalizing on an essentially free asset: the Sun.
The shoe made from algae
Kanye West's Yeezy line is now diving into algae foam. West's latest shoe, unveiled at the Fast Company Innovation Festival this week, is an algae-based creation modeled after the Yeezy foam runner. While its khaki color may not turn heads, the shoe's design team and engineering crew are working to refine the color with eco-friendly dyes. Meanwhile, Yeezy now plans to relocate its headquarters to a 4,000-acre farm in Wyoming, enabling the company to grow algae on a hydroponic farm to iterate and launch the new footwear product. The line's transition to sustainable materials aligns with the parent brand's eco-friendly initiatives. Driven by similar motivations, Adidas recently committed to manufacturing solely with recycled plastics by 2024 and has already launched the 100% recyclable Futurecraft Loop shoe.
Why it matters: second only to oil, the clothing and textile industry is the world's largest polluter. Even once garments reach shoppers' carts, consumer textile waste further compounds the problem. The average American, for example, discards approximately 100 kg of used clothing each year, much of which could be recycled but instead goes to landfill. However, major brands hold tremendous power to mainstream sustainable fashion and reduce production waste by innovating in materials science. By raising consumer awareness, Yeezy's transition marks a fundamental step toward ecologically responsible footwear, helping to reduce fast-fashion waste.
DNA is just one of more than one million 'possible genetic molecules,' scientists discover.
DNA
What it is: a new study published in the Journal of Chemical Information and Modeling suggests that more than 1 million identical chemicals could encode biological information, just as DNA does. Until now, DNA, RNA, and a few man-made molecules were the only known nucleic acids capable of linking, storing, and relaying data, depending on their sequence. By designing a computer program capable of generating chemical formulas, researchers at Emory University tested countless generated molecules to determine whether they resembled nucleotides. In a surprise to all, their results identified more than 1,160,000 molecules that could couple into distinct pairs and cluster into a line, similar to DNA and RNA.
Why it matters: leading us to fundamentally rethink the ideal means of genetic data transmission, this discovery carries vast new implications. Since several current nucleotide-like drugs are effective in combating viruses and some malignant cancer cells, the list generated by the team may pave the way for new pharmaceuticals. In evolutionary biology, the discovery that DNA and RNA have many companions may generate new truths about how life first evolved on Earth.
Apple plans standalone AR and VR gaming headset by 2022, with glasses to follow.
APPLE
What it is: Apple recently announced its latest plan to release a series of AR/VR devices over the next four years. Next year, the company will introduce 3D sensors into the iPad Pro, allowing users to reconstruct rooms, people, and objects in three dimensions. Following their initial debut, these sensors will be rolled out in iPhones (expected by the end of 2020), building on the current Face ID technology. Over the following two years, Apple intends to launch its standalone AR/VR headset for use in virtual meetings, gaming, and entertainment. And by 2023, Apple's lightweight glasses will reach consumers for everyday use. While Apple's launch dates are later than anticipated, the tech giant's 1,000 AR/VR engineers are pressing forward to deliver finely tuned devices. The resulting technology will represent the beginning of Apple's next major hardware push, building on the wearables segment that is now compensating for a decline in iPhone sales.
Why it matters: adding AR/VR glasses to a growing list of wearables — including Apple Watch, AirPods, and Beats headphones — Apple is now making the leap from the iPhone revolution to far more accessible smart interfaces, seamlessly integrated into our daily lives. Steadily advancing through the deceptive growth phase, augmented reality glasses will soon allow you to navigate the streets of a new city without glancing at your phone screen. Learn about the history of a new location, stay up to date on news alerts, and keep in touch with your favorite contacts — no intermediate 2D digital portal required. Apple's wearable revolution will transform the way we interact with our physical environment, converting every surface into an opportunity to work, learn, or play.
Specific neurons that map memories have now been identified in the human brain.
HUMAN BRAIN
What it is: scientists at Columbia University have discovered the first evidence that individual neurons target specific memories during intentional memory retrieval — think: recalling navigation details when a stranger asks you for directions. In their experiment, neuroengineers used electrodes implanted in neurosurgical patients to track brain signals. In particular, they monitored signals that were active when patients searched for objects from memory in a virtual reality game. They ultimately found that specific patterns of neural activity were matched to specific memories.
Why it matters: researchers have long known that certain activated neurons correspond to specific geographic locations, demonstrated by a Nobel Prize-winning discovery linking "grid cells" and "place cells" to spatial location. However, prior to this experiment, it was not clear how spatial cells relate to memories formed (through events or experiences) at that location. As explained by the study's lead author, Salman E. Qasim, "This finding may provide a potential mechanism for our ability to selectively recall different experiences from the past and highlight how these memories may influence the brain's spatial map."
Drone company Iris Automation completes first FAA-approved 'blind' drone flight.
What it is: in partnership with the Kansas Department of Transportation, drone startup Iris Automation successfully completed the first FAA-approved BVLOS ("beyond visual line of sight") drone flight. Until now, the FAA and most other jurisdictions required human observers and ground-based radar systems to test new services, costing companies up to $50 million and thereby impeding the development of viable drone services. However, with the recent FAA approval, Iris Automation relied solely on onboard detect-and-avoid systems. The flight follows the company's successful test in Alaska earlier this year, in which its autonomous systems outperformed human-operated drones 95% of the time, avoiding head-on collisions with other vehicles.
Why it matters: we are now witnessing a massive increase in the rate of development and approval of autonomous drone use for critical supply delivery and commerce. Meanwhile, several regulatory agencies — including government departments at the state level, even in technologically underserved regions — continue to define and refine correct operating guidelines. As the immediacy of retail interactions, aid delivery, and small-scale cargo transport continues to rise rapidly, expect a proliferation of drone manufacturers, complex sensors, and AI navigation software systems.
Japan is reinventing Fukushima as a renewable energy hub.
FUKUSHIMA
What it is: Japan is now working to redevelop the Fukushima nuclear collapse zone to generate electricity once again, but this time using solar and wind energy. Thanks to a loan from the Japan Development Bank and Mizuho Bank, the region will soon produce approximately 600 megawatts of electricity, courtesy of 11 new solar plants and 10 new wind farms. With completion scheduled for March 2024 at a cost of $2.7 billion, the plants are projected to generate enough energy for approximately 114,000 average American homes.
Why it matters: nearly 43,000 Japanese citizens remain displaced by the Fukushima disaster, while approximately 143 square kilometers of the prefecture lie within a permanent evacuation zone. However, Japan is now seeking to capitalize on this apparent "dead zone," leveraging the expanse of uninhabitable land to power residential regions. Contributing to the prefecture's goal of achieving 100% renewably derived energy by 2040, this energy infrastructure will help pave the way for similar initiatives worldwide.
Artificial Intelligence and Predictive Mapping
When it comes to rapid responses in emergency situations, accurate information is worth its weight in gold.
The meteoric rise of space networks, balloons hovering in the stratosphere, and 5G telecommunications infrastructure is on track to enable connectivity for every individual on the planet.
Beyond democratizing the world's information, this surge in connectivity will soon grant anyone the ability to transmit detailed data such as geographic location — which can be decisive in relaying information from the most vulnerable people in areas about to be struck by a natural disaster.
Armed with the power of data transmission and the strength of the crowd, disaster victims now play a vital role in emergency response, transforming a historically one-directional, blind rescue operation into a two-way dialogue between connected crowds and intelligent response systems.
Yet with a dizzying volume of data comes a new paradigm: one in which we no longer face a scarcity of answers. Instead, it will be the quality of our questions that matters most.
This is where AI enters: our mining mechanism.
In the case of emergency response, what if we could strategically map a nearly infinite volume of incoming data points? Or predict the dynamics of a flood and identify the most vulnerable targets of a tsunami before it even makes landfall? Or even amplify critical signals to trigger automatic assistance from surveillance drones and immediately alert crowdsourcing volunteers?
Currently, several key players are leveraging AI, crowdsourcing intelligence, and cutting-edge visualizations to optimize crisis response and multiply relief speeds.
Take One Concern, for example.
Born at Stanford under the guidance of leading AI expert Andrew Ng, One Concern harnesses AI through analytical disaster assessment and calculated damage estimates.
In partnership with the city of Los Angeles, San Francisco, and several cities in San Mateo County, the platform assigns verified, unique 'digital fingerprints' to every element of the city. Creating robust models of each system, One Concern's AI platform can monitor the site-specific impacts not only of climate change, but of each individual natural disaster — from radical thermal shifts to seismic movements.
This data, combined with city infrastructure data and records of past disasters, is used to predict future damage across a range of disaster scenarios, informing the prevention methods and structures that need reinforcement.
In just four years, One Concern can now make accurate predictions at an 85% accuracy rate in under 15 minutes.
And as IoT-connected devices and smart hardware continue to grow, a trillion-sensor economy will only amplify AI's predictive capacity, offering us immediate and preventive strategies well before disaster strikes.
Take wildfires, for example.
University of Utah atmospheric scientist Adam Kochanski and a team of researchers are refining a computer model with new data to predict how fires will spread and what weather events will follow.
By igniting a "prescribed fire" — a controlled burn typically intended for habitat restoration in forested regions — the team used multiple infrared drones, laser scanning, and infrared camera-equipped sensors to collect data while Kochanski tested the predictions of his predictive model.
While the generated data is still being processed, the experiment is contributing to 'coupled fire-atmosphere models,' which use data to determine how wildfires influence local weather conditions and the interaction between the two. Even so, Kochanski's model was already quite predictive of actual experimental fire behavior.
In conjunction with robust sensor networks and autonomous drone fleets, computer models that incorporate weather conditions into AI wildfire mapping can help us contain fires before they gain momentum, saving forests, lives, and entire habitats.
As mobile connectivity and abundant sensors converge with AI-mined crowd intelligence, real-time awareness only multiplies in speed and scale.
Imagining the future….
Over the next 10 years, spatial web technology may even allow us to access mesh networks.
As I explored in a previous blog on the implications of the spatial web, while traditional networks rely on a limited set of wired access points (or wireless hotspots), a wireless mesh network can connect entire cities through hundreds of dispersed nodes that communicate with each other and share a network connection non-hierarchically.
In short, this means that individual mobile users can collectively establish a local mesh network using only the computing power on their own devices.
Take it a step further and a local population of strangers could collectively broadcast countless 360-degree feeds over a local mesh network.
Imagine a scenario in which armed attacks break out across disconnected urban districts, with each group of eyewitnesses and at-risk civilians broadcasting a set of 360-degree videos, all fed by photogrammetry AIs constructing a live hologram in real time, giving family members and first responders complete information.
Or picture a coastal community amid heavy torrential rain and failing infrastructure. Now enabled by a collective live feed, verification of data reports takes seconds, and layered data informs first responders and AI platforms with incredible precision and specificity about relief needs.
By linking all the right technological pieces together, we may even see the rise of automated drone deliveries. Imagine: crowdsourcing intelligence is first cross-referenced with sensor data and algorithmically verified. AI is then leveraged to determine specific needs and the degree of urgency at ultra-precise coordinates. Within minutes, once approved by personnel, swarm robots rush to collect the required supplies, equipping appropriately sized drones with the right aid for rapid frontline delivery.
This brings us to a second critical convergence: robots and drones.
While cutting-edge drone technology is revolutionizing the way we deliver aid, new advances in AI-driven robotics are paving the way for superhuman emergency responses in some of today's most dangerous environments.
Let us explore some of the most disruptive examples to reach the testing phase.
First….
Autonomous Robot and Swarm Solutions
As hardware advances converge with explosive AI capabilities, disaster relief robots are transitioning from assistive functions to fully autonomous first responders at a dizzying pace.
Born at MIT's Biomimetic Robotics Laboratory, Cheetah III is just one of many robots that could form our first line of defense in everything from earthquake search-and-rescue missions to high-risk operations in hazardous radiation zones.
Now capable of running at 6.4 meters per second, Cheetah III can even leap to a height of 60 centimeters, autonomously determining how to avoid obstacles and jump over barriers as they arise.
Source: Massachusetts Institute of Technology (MIT)
Initially designed to perform spectral inspection tasks in hazardous environments (think: nuclear power plants or chemical factories), the various Cheetah iterations have focused on increasing its payload capacity, range of motion, and even an exciting feature with enhanced dexterity.
But as explained by the laboratory director and MIT associate professor Sangbae Kim, Cheetah III and future versions aim to save lives in virtually any environment: "Say there is a fire or high radiation that nobody can enter. [In those circumstances, we will send a robot in to check if people are inside. And even before doing all of that, the short-term goal will be to send the robot places where we don't want to send humans, for […] example, toxic areas or [people with] mild radiation."
And Cheetah III is not alone.
Last February, the Tokyo Electric Power Company (TEPCO) put one of its own robots to the test.
For the first time since the devastating 2011 Japan tsunami, which led to three nuclear meltdowns at the Fukushima nuclear plant, a robot successfully examined reactor fuel.
By transmitting the process via its onboard camera, the robot was able to recover small pieces of radioactive fuel at five of six test sites, offering tremendous promise for long-term plans to clean up the still-deadly interior.
Also out of Japan, Mitsubishi Heavy Industries (MHI) is using robots to combat fires with full autonomy. In a remarkable new feat, MHI's Water Cannon Bot can now independently deploy to difficult-to-reach or highly dangerous fire sites.
Delivering foam or water at 4,000 liters per minute and 1 megapascal (MPa) of pressure, the Cannon Bot and its accompanying Hose Extension Bot are part of a larger artificial intelligence system for conducting reconnaissance and surveillance aboard larger transport vehicles.
As wildfires become increasingly uncontrollable, large-scale production of these robots could be a genuine lifesaver. Paired with AI predictive wildfire mapping and autonomous transport vehicles, solutions like MHI's Cannon Bot not only save countless lives, but prevent population displacement and devastating damage to our natural environment before disaster has the chance to spread.
But even in cases where emergency shelter is needed, innovative robotics solutions (literally) are quick to the rescue.
After several iterations by Fastbrick Robotics, the end-to-end bricklaying robot Hadrian X can now autonomously build a fully habitable 180-square-meter home in under 3 days. Using a laser-guided robotic attachment, the all-in-one brick-loaded truck simply drives to a construction site and channels blocks through the robotic arm according to a 3D model.
Source: Fastbrick Robotics
Meeting verified construction standards, Hadrian and similar solutions show long-term promise for deployment at post-conflict refugee sites and regions recovering from natural catastrophes.
But what if we need to build emergency shelters from locally available ground material? Marking an extraordinary convergence between robotics and 3D printing, the Institute for Advanced Architecture of Catalonia (IAAC) is already working on a solution.
In a major feat for low-cost construction in remote zones, IAAC has found a way to convert almost any soil into a building material with three times the tensile strength of industrial clay. Offering numerous benefits including natural insulation, low GHG emissions, fire protection, air circulation, and thermal mediation, IAAC's new 3D-printed native soil can build homes on-site for as little as $1,000.
But while cutting-edge robotics is opening extraordinary new frontiers for large-scale, low-cost emergency construction, new advances in hardware and computing are also enabling robotic scale at the opposite end of the spectrum.
Again inspired by biological phenomena, robotics experts in the US have begun piloting tiny robotic prototypes to locate trapped individuals and assess infrastructure damage.
Consider RoboBees, tiny bots developed at Harvard that use electrostatic adhesion to "land" on walls and even ceilings, assessing structural damage following an earthquake.
Or the Snakebot, a Carnegie Mellon prototype capable of navigating entry points that would otherwise be completely inaccessible to human responders. Powered by AI, the Snakebot can maneuver through even the densest rubble to locate survivors, using cameras and microphones for communication.
But when it comes to accelerated reconnaissance in inaccessible regions, miniature robot swarms have good company.
Next-Generation Drones for Instant Relief Supplies
Particularly in the case of wildfires and conflict zones, autonomous drone technology is fundamentally revolutionizing the way we identify survivors in need and automate the delivery of relief.
It is not just drones that enable high-resolution imagery for real-time mapping and damage assessment — preliminary research shows that UAVs outperform ground-based rescue teams in locating isolated survivors.
As presented by a team of electrical engineers from the University of Science and Technology of China, drones can even build a wireless mobile broadband network in record time, using a "drone-assisted multi-hop device-to-device" program.
And as demonstrated during Hurricane Harvey in Houston, drones can provide predictive information on everything from future flooding to damage estimates.
Among several others, a team led by Texas A&M computer science professor and director of the university's Center for Robot-Assisted Search and Rescue, Dr. Robin Murphy, conducted a total of 119 drone missions across the city, ranging from small quadcopters to military unmanned aircraft. These were critical not only for monitoring levee infrastructure, but for identifying those left behind by human rescue teams.
But beyond surveillance, UAVs have begun delivering life-saving supplies to some of the world's most remote regions.
One of the most inspiring examples to date is Zipline.
Founded in 2014, Zipline has completed 12,352 life-saving drone deliveries to date. While the drones are designed, tested, and assembled in California, Zipline operates primarily in Rwanda and Tanzania, employing local operators and providing more than 11 million people with instant access to medical supplies.
Delivering everything from vaccines and HIV medication to blood and intravenous tubes, Zipline's drones outpace ground transport, in many cases delivering red blood cells, plasma, and platelets within their viable lifespan in under an hour.
Source: Zipline
But drone technology is beginning to transcend the limited scale of medical supplies and food.
Now developing its drones under contracts with DARPA and the US Marine Corps, Logistic Gliders, Inc. has built autonomously navigating drones capable of transporting 1,800 pounds of cargo over unprecedented long distances.
Built from plywood, Logistic Gliders' drones are designed to cost only a few hundred dollars each, making them ideal candidates for high-volume remote deliveries, whether piloted by a human or operating on their own according to real-time disaster zone mapping.
As hardware continues to advance, autonomous drone technology, combined with real-time mapping algorithms, offers countless opportunities for aid delivery, disaster monitoring, and previously unimaginable richly layered information for humanitarian assistance.
Final Thoughts
Perhaps one of the most important and impactful applications of converging technologies is the transformation of disaster relief methods.
While AI-driven intelligence platforms collect firsthand experiential data from those on the ground, mobile connectivity and drone-provided networks are granting a newfound narrative power to those most in need.
And as a wave of new hardware advances gives rise to robotic responders, swarm technology, and aerial drones, we are rapidly approaching an era of instant and efficiently distributed responses, amid conflicts and natural catastrophes.
Empowered by these new tools, what can we create when everyone on the planet has equal access to immediate supplies and resources? In a new era of prevention and rapid recovery, what future can you envision?