Tag Archives: platform

#434658 The Next Data-Driven Healthtech ...

Increasing your healthspan (i.e. making 100 years old the new 60) will depend to a large degree on artificial intelligence. And, as we saw in last week’s blog, healthcare AI systems are extremely data-hungry.

Fortunately, a slew of new sensors and data acquisition methods—including over 122 million wearables shipped in 2018—are bursting onto the scene to meet the massive demand for medical data.

From ubiquitous biosensors, to the mobile healthcare revolution, to the transformative power of the Health Nucleus, converging exponential technologies are fundamentally transforming our approach to healthcare.

In Part 4 of this blog series on Longevity & Vitality, I expand on how we’re acquiring the data to fuel today’s AI healthcare revolution.

In this blog, I’ll explore:

How the Health Nucleus is transforming “sick care” to healthcare
Sensors, wearables, and nanobots
The advent of mobile health

Let’s dive in.

Health Nucleus: Transforming ‘Sick Care’ to Healthcare
Much of today’s healthcare system is actually sick care. Most of us assume that we’re perfectly healthy, with nothing going on inside our bodies, until the day we travel to the hospital writhing in pain only to discover a serious or life-threatening condition.

Chances are that your ailment didn’t materialize that morning; rather, it’s been growing or developing for some time. You simply weren’t aware of it. At that point, once you’re diagnosed as “sick,” our medical system engages to take care of you.

What if, instead of this retrospective and reactive approach, you were constantly monitored, so that you could know the moment anything was out of whack?

Better yet, what if you more closely monitored those aspects of your body that your gene sequence predicted might cause you difficulty? Think: your heart, your kidneys, your breasts. Such a system becomes personalized, predictive, and possibly preventative.

This is the mission of the Health Nucleus platform built by Human Longevity, Inc. (HLI). While not continuous—that will come later, with the next generation of wearable and implantable sensors—the Health Nucleus was designed to ‘digitize’ you once per year to help you determine whether anything is going on inside your body that requires immediate attention.

The Health Nucleus visit provides you with the following tests during a half-day visit:

Whole genome sequencing (30x coverage)
Whole body (non-contrast) MRI
Brain magnetic resonance imaging/angiography (MRI/MRA)
CT (computed tomography) of the heart and lungs
Coronary artery calcium scoring
Electrocardiogram
Echocardiogram
Continuous cardiac monitoring
Clinical laboratory tests and metabolomics

In late 2018, HLI published the results of the first 1,190 clients through the Health Nucleus. The results were eye-opening—especially since these patients were all financially well-off, and already had access to the best doctors.

Following are the physiological and genomic findings in these clients who self-selected to undergo evaluation at HLI’s Health Nucleus.

Physiological Findings [TG]

Two percent had previously unknown tumors detected by MRI
2.5 percent had previously undetected aneurysms detected by MRI
Eight percent had cardiac arrhythmia found on cardiac rhythm monitoring, not previously known
Nine percent had moderate-severe coronary artery disease risk, not previously known
16 percent discovered previously unknown cardiac structure/function abnormalities
30 percent had elevated liver fat, not previously known

Genomic Findings [TG]

24 percent of clients uncovered a rare (unknown) genetic mutation found on WGS
63 percent of clients had a rare genetic mutation with a corresponding phenotypic finding

In summary, HLI’s published results found that 14.4 percent of clients had significant findings that are actionable, requiring immediate or near-term follow-up and intervention.

Long-term value findings were found in 40 percent of the clients we screened. Long-term clinical findings include discoveries that require medical attention or monitoring but are not immediately life-threatening.

The bottom line: most people truly don’t know their actual state of health. The ability to take a fully digital deep dive into your health status at least once per year will enable you to detect disease at stage zero or stage one, when it is most curable.

Sensors, Wearables, and Nanobots
Wearables, connected devices, and quantified self apps will allow us to continuously collect enormous amounts of useful health information.

Wearables like the Quanttus wristband and Vital Connect can transmit your electrocardiogram data, vital signs, posture, and stress levels anywhere on the planet.

In April 2017, we were proud to grant $2.5 million in prize money to the winning team in the Qualcomm Tricorder XPRIZE, Final Frontier Medical Devices.

Using a group of noninvasive sensors that collect data on vital signs, body chemistry, and biological functions, Final Frontier integrates this data in their powerful, AI-based DxtER diagnostic engine for rapid, high-precision assessments.

Their engine combines learnings from clinical emergency medicine and data analysis from actual patients.

Google is developing a full range of internal and external sensors (e.g. smart contact lenses) that can monitor the wearer’s vitals, ranging from blood sugar levels to blood chemistry.

In September 2018, Apple announced its Series 4 Apple Watch, including an FDA-approved mobile, on-the-fly ECG. Granted its first FDA approval, Apple appears to be moving deeper into the sensing healthcare market.

Further, Apple is reportedly now developing sensors that can non-invasively monitor blood sugar levels in real time for diabetic treatment. IoT-connected sensors are also entering the world of prescription drugs.

Last year, the FDA approved the first sensor-embedded pill, Abilify MyCite. This new class of digital pills can now communicate medication data to a user-controlled app, to which doctors may be granted access for remote monitoring.

Perhaps what is most impressive about the next generation of wearables and implantables is the density of sensors, processing, networking, and battery capability that we can now cheaply and compactly integrate.

Take the second-generation OURA ring, for example, which focuses on sleep measurement and management.

The OURA ring looks like a slightly thick wedding band, yet contains an impressive array of sensors and capabilities, including:

Two infrared LED
One infrared sensor
Three temperature sensors
One accelerometer
A six-axis gyro
A curved battery with a seven-day life
The memory, processing, and transmission capability required to connect with your smartphone

Disrupting Medical Imaging Hardware
In 2018, we saw lab breakthroughs that will drive the cost of an ultrasound sensor to below $100, in a packaging smaller than most bandages, powered by a smartphone. Dramatically disrupting ultrasound is just the beginning.

Nanobots and Nanonetworks
While wearables have long been able to track and transmit our steps, heart rate, and other health data, smart nanobots and ingestible sensors will soon be able to monitor countless new parameters and even help diagnose disease.

Some of the most exciting breakthroughs in smart nanotechnology from the past year include:

Researchers from the École Polytechnique Fédérale de Lausanne (EPFL) and the Swiss Federal Institute of Technology in Zurich (ETH Zurich) demonstrated artificial microrobots that can swim and navigate through different fluids, independent of additional sensors, electronics, or power transmission.

Researchers at the University of Chicago proposed specific arrangements of DNA-based molecular logic gates to capture the information contained in the temporal portion of our cells’ communication mechanisms. Accessing the otherwise-lost time-dependent information of these cellular signals is akin to knowing the tune of a song, rather than solely the lyrics.

MIT researchers built micron-scale robots able to sense, record, and store information about their environment. These tiny robots, about 100 micrometers in diameter (approximately the size of a human egg cell), can also carry out pre-programmed computational tasks.

Engineers at University of California, San Diego developed ultrasound-powered nanorobots that swim efficiently through your blood, removing harmful bacteria and the toxins they produce.

But it doesn’t stop there.

As nanosensor and nanonetworking capabilities develop, these tiny bots may soon communicate with each other, enabling the targeted delivery of drugs and autonomous corrective action.

Mobile Health
The OURA ring and the Series 4 Apple Watch are just the tip of the spear when it comes to our future of mobile health. This field, predicted to become a $102 billion market by 2022, puts an on-demand virtual doctor in your back pocket.

Step aside, WebMD.

In true exponential technology fashion, mobile device penetration has increased dramatically, while image recognition error rates and sensor costs have sharply declined.

As a result, AI-powered medical chatbots are flooding the market; diagnostic apps can identify anything from a rash to diabetic retinopathy; and with the advent of global connectivity, mHealth platforms enable real-time health data collection, transmission, and remote diagnosis by medical professionals.

Already available to residents across North London, Babylon Health offers immediate medical advice through AI-powered chatbots and video consultations with doctors via its app.

Babylon now aims to build up its AI for advanced diagnostics and even prescription. Others, like Woebot, take on mental health, using cognitive behavioral therapy in communications over Facebook messenger with patients suffering from depression.

In addition to phone apps and add-ons that test for fertility or autism, the now-FDA-approved Clarius L7 Linear Array Ultrasound Scanner can connect directly to iOS and Android devices and perform wireless ultrasounds at a moment’s notice.

Next, Healthy.io, an Israeli startup, uses your smartphone and computer vision to analyze traditional urine test strips—all you need to do is take a few photos.

With mHealth platforms like ClickMedix, which connects remotely-located patients to medical providers through real-time health data collection and transmission, what’s to stop us from delivering needed treatments through drone delivery or robotic telesurgery?

Welcome to the age of smartphone-as-a-medical-device.

Conclusion
With these DIY data collection and diagnostic tools, we save on transportation costs (time and money), and time bottlenecks.

No longer will you need to wait for your urine or blood results to go through the current information chain: samples will be sent to the lab, analyzed by a technician, results interpreted by your doctor, and only then relayed to you.

Just like the “sage-on-the-stage” issue with today’s education system, healthcare has a “doctor-on-the-dais” problem. Current medical procedures are too complicated and expensive for a layperson to perform and analyze on their own.

The coming abundance of healthcare data promises to transform how we approach healthcare, putting the power of exponential technologies in the patient’s hands and revolutionizing how we live.

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Posted in Human Robots

#434637 AI Is Rapidly Augmenting Healthcare and ...

When it comes to the future of healthcare, perhaps the only technology more powerful than CRISPR is artificial intelligence.

Over the past five years, healthcare AI startups around the globe raised over $4.3 billion across 576 deals, topping all other industries in AI deal activity.

During this same period, the FDA has given 70 AI healthcare tools and devices ‘fast-tracked approval’ because of their ability to save both lives and money.

The pace of AI-augmented healthcare innovation is only accelerating.

In Part 3 of this blog series on longevity and vitality, I cover the different ways in which AI is augmenting our healthcare system, enabling us to live longer and healthier lives.

In this blog, I’ll expand on:

Machine learning and drug design
Artificial intelligence and big data in medicine
Healthcare, AI & China

Let’s dive in.

Machine Learning in Drug Design
What if AI systems, specifically neural networks, could predict the design of novel molecules (i.e. medicines) capable of targeting and curing any disease?

Imagine leveraging cutting-edge artificial intelligence to accomplish with 50 people what the pharmaceutical industry can barely do with an army of 5,000.

And what if these molecules, accurately engineered by AIs, always worked? Such a feat would revolutionize our $1.3 trillion global pharmaceutical industry, which currently holds a dismal record of 1 in 10 target drugs ever reaching human trials.

It’s no wonder that drug development is massively expensive and slow. It takes over 10 years to bring a new drug to market, with costs ranging from $2.5 billion to $12 billion.

This inefficient, slow-to-innovate, and risk-averse industry is a sitting duck for disruption in the years ahead.

One of the hottest startups in digital drug discovery today is Insilico Medicine. Leveraging AI in its end-to-end drug discovery pipeline, Insilico Medicine aims to extend healthy longevity through drug discovery and aging research.

Their comprehensive drug discovery engine uses millions of samples and multiple data types to discover signatures of disease, identify the most promising protein targets, and generate perfect molecules for these targets. These molecules either already exist or can be generated de novo with the desired set of parameters.

In late 2018, Insilico’s CEO Dr. Alex Zhavoronkov announced the groundbreaking result of generating novel molecules for a challenging protein target with an unprecedented hit rate in under 46 days. This included both synthesis of the molecules and experimental validation in a biological test system—an impressive feat made possible by converging exponential technologies.

Underpinning Insilico’s drug discovery pipeline is a novel machine learning technique called Generative Adversarial Networks (GANs), used in combination with deep reinforcement learning.

Generating novel molecular structures for diseases both with and without known targets, Insilico is now pursuing drug discovery in aging, cancer, fibrosis, Parkinson’s disease, Alzheimer’s disease, ALS, diabetes, and many others. Once rolled out, the implications will be profound.

Dr. Zhavoronkov’s ultimate goal is to develop a fully-automated Health-as-a-Service (HaaS) and Longevity-as-a-Service (LaaS) engine.

Once plugged into the services of companies from Alibaba to Alphabet, such an engine would enable personalized solutions for online users, helping them prevent diseases and maintain optimal health.

Insilico, alongside other companies tackling AI-powered drug discovery, truly represents the application of the 6 D’s. What was once a prohibitively expensive and human-intensive process is now rapidly becoming digitized, dematerialized, demonetized and, perhaps most importantly, democratized.

Companies like Insilico can now do with a fraction of the cost and personnel what the pharmaceutical industry can barely accomplish with thousands of employees and a hefty bill to foot.

As I discussed in my blog on ‘The Next Hundred-Billion-Dollar Opportunity,’ Google’s DeepMind has now turned its neural networks to healthcare, entering the digitized drug discovery arena.

In 2017, DeepMind achieved a phenomenal feat by matching the fidelity of medical experts in correctly diagnosing over 50 eye disorders.

And just a year later, DeepMind announced a new deep learning tool called AlphaFold. By predicting the elusive ways in which various proteins fold on the basis of their amino acid sequences, AlphaFold may soon have a tremendous impact in aiding drug discovery and fighting some of today’s most intractable diseases.

Artificial Intelligence and Data Crunching
AI is especially powerful in analyzing massive quantities of data to uncover patterns and insights that can save lives. Take WAVE, for instance. Every year, over 400,000 patients die prematurely in US hospitals as a result of heart attack or respiratory failure.

Yet these patients don’t die without leaving plenty of clues. Given information overload, however, human physicians and nurses alone have no way of processing and analyzing all necessary data in time to save these patients’ lives.

Enter WAVE, an algorithm that can process enough data to offer a six-hour early warning of patient deterioration.

Just last year, the FDA approved WAVE as an AI-based predictive patient surveillance system to predict and thereby prevent sudden death.

Another highly valuable yet difficult-to-parse mountain of medical data comprises the 2.5 million medical papers published each year.

For some time, it has become physically impossible for a human physician to read—let alone remember—all of the relevant published data.

To counter this compounding conundrum, Johnson & Johnson is teaching IBM Watson to read and understand scientific papers that detail clinical trial outcomes.

Enriching Watson’s data sources, Apple is also partnering with IBM to provide access to health data from mobile apps.

One such Watson system contains 40 million documents, ingesting an average of 27,000 new documents per day, and providing insights for thousands of users.

After only one year, Watson’s successful diagnosis rate of lung cancer has reached 90 percent, compared to the 50 percent success rate of human doctors.

But what about the vast amount of unstructured medical patient data that populates today’s ancient medical system? This includes medical notes, prescriptions, audio interview transcripts, and pathology and radiology reports.

In late 2018, Amazon announced a new HIPAA-eligible machine learning service that digests and parses unstructured data into categories, such as patient diagnoses, treatments, dosages, symptoms and signs.

Taha Kass-Hout, Amazon’s senior leader in health care and artificial intelligence, told the Wall Street Journal that internal tests demonstrated that the software even performs as well as or better than other published efforts.

On the heels of this announcement, Amazon confirmed it was teaming up with the Fred Hutchinson Cancer Research Center to evaluate “millions of clinical notes to extract and index medical conditions.”

Having already driven extraordinary algorithmic success rates in other fields, data is the healthcare industry’s goldmine for future innovation.

Healthcare, AI & China
In 2017, the Chinese government published its ambitious national plan to become a global leader in AI research by 2030, with healthcare listed as one of four core research areas during the first wave of the plan.

Just a year earlier, China began centralizing healthcare data, tackling a major roadblock to developing longevity and healthcare technologies (particularly AI systems): scattered, dispersed, and unlabeled patient data.

Backed by the Chinese government, China’s largest tech companies—particularly Tencent—have now made strong entrances into healthcare.

Just recently, Tencent participated in a $154 million megaround for China-based healthcare AI unicorn iCarbonX.

Hoping to develop a complete digital representation of your biological self, iCarbonX has acquired numerous US personalized medicine startups.

Considering Tencent’s own Miying healthcare AI platform—aimed at assisting healthcare institutions in AI-driven cancer diagnostics—Tencent is quickly expanding into the drug discovery space, participating in two multimillion-dollar, US-based AI drug discovery deals just this year.

China’s biggest, second-order move into the healthtech space comes through Tencent’s WeChat. In the course of a mere few years, already 60 percent of the 38,000 medical institutions registered on WeChat allow patients to digitally book appointments through Tencent’s mobile platform. At the same time, 2,000 Chinese hospitals accept WeChat payments.

Tencent has additionally partnered with the U.K.’s Babylon Health, a virtual healthcare assistant startup whose app now allows Chinese WeChat users to message their symptoms and receive immediate medical feedback.

Similarly, Alibaba’s healthtech focus started in 2016 when it released its cloud-based AI medical platform, ET Medical Brain, to augment healthcare processes through everything from diagnostics to intelligent scheduling.

Conclusion
As Nvidia CEO Jensen Huang has stated, “Software ate the world, but AI is going to eat software.” Extrapolating this statement to a more immediate implication, AI will first eat healthcare, resulting in dramatic acceleration of longevity research and an amplification of the human healthspan.

Next week, I’ll continue to explore this concept of AI systems in healthcare.

Particularly, I’ll expand on how we’re acquiring and using the data for these doctor-augmenting AI systems: from ubiquitous biosensors, to the mobile healthcare revolution, and finally, to the transformative power of the health nucleus.

As AI and other exponential technologies increase our healthspan by 30 to 40 years, how will you leverage these same exponential technologies to take on your moonshots and live out your massively transformative purpose?

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Posted in Human Robots

#434636 Using Advanced Technology to Increase ...

Image Source The 1SHIFT Logistics platform, developed by LiteLink Technologies, shows what can happen when the technology industry meets the logistics industry. 1SHIFT Logistics uses advanced technology such as artificial intelligence and geolocation to coordinate all three major parts of the logistics process: the shipper, the carrier and the delivery site. When most people think …

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Posted in Human Robots

#434569 From Parkour to Surgery, Here Are the ...

The robot revolution may not be here quite yet, but our mechanical cousins have made some serious strides. And now some of the leading experts in the field have provided a rundown of what they see as the 10 most exciting recent developments.

Compiled by the editors of the journal Science Robotics, the list includes some of the most impressive original research and innovative commercial products to make a splash in 2018, as well as a couple from 2017 that really changed the game.

1. Boston Dynamics’ Atlas doing parkour

It seems like barely a few months go by without Boston Dynamics rewriting the book on what a robot can and can’t do. Last year they really outdid themselves when they got their Atlas humanoid robot to do parkour, leaping over logs and jumping between wooden crates.

Atlas’s creators have admitted that the videos we see are cherry-picked from multiple attempts, many of which don’t go so well. But they say they’re meant to be inspirational and aspirational rather than an accurate picture of where robotics is today. And combined with the company’s dog-like Spot robot, they are certainly pushing boundaries.

2. Intuitive Surgical’s da Vinci SP platform
Robotic surgery isn’t new, but the technology is improving rapidly. Market leader Intuitive’s da Vinci surgical robot was first cleared by the FDA in 2000, but since then it’s come a long way, with the company now producing three separate systems.

The latest addition is the da Vinci SP (single port) system, which is able to insert three instruments into the body through a single 2.5cm cannula (tube) bringing a whole new meaning to minimally invasive surgery. The system was granted FDA clearance for urological procedures last year, and the company has now started shipping the new system to customers.

3. Soft robot that navigates through growth

Roboticists have long borrowed principles from the animal kingdom, but a new robot design that mimics the way plant tendrils and fungi mycelium move by growing at the tip has really broken the mold on robot navigation.

The editors point out that this is the perfect example of bio-inspired design; the researchers didn’t simply copy nature, they took a general principle and expanded on it. The tube-like robot unfolds from the front as pneumatic pressure is applied, but unlike a plant, it can grow at the speed of an animal walking and can navigate using visual feedback from a camera.

4. 3D printed liquid crystal elastomers for soft robotics
Soft robotics is one of the fastest-growing sub-disciplines in the field, but powering these devices without rigid motors or pumps is an ongoing challenge. A variety of shape-shifting materials have been proposed as potential artificial muscles, including liquid crystal elastomeric actuators.

Harvard engineers have now demonstrated that these materials can be 3D printed using a special ink that allows the designer to easily program in all kinds of unusual shape-shifting abilities. What’s more, their technique produces actuators capable of lifting significantly more weight than previous approaches.

5. Muscle-mimetic, self-healing, and hydraulically amplified actuators
In another effort to find a way to power soft robots, last year researchers at the University of Colorado Boulder designed a series of super low-cost artificial muscles that can lift 200 times their own weight and even heal themselves.

The devices rely on pouches filled with a liquid that makes them contract with the force and speed of mammalian skeletal muscles when a voltage is applied. The most promising for robotics applications is the so-called Peano-HASEL, which features multiple rectangular pouches connected in series that contract linearly, just like real muscle.

6. Self-assembled nanoscale robot from DNA

While you may think of robots as hulking metallic machines, a substantial number of scientists are working on making nanoscale robots out of DNA. And last year German researchers built the first remote-controlled DNA robotic arm.

They created a length of tightly-bound DNA molecules to act as the arm and attached it to a DNA base plate via a flexible joint. Because DNA carries a charge, they were able to get the arm to swivel around like the hand of a clock by applying a voltage and switch direction by reversing that voltage. The hope is that this arm could eventually be used to build materials piece by piece at the nanoscale.

7. DelFly nimble bioinspired robotic flapper

Robotics doesn’t only borrow from biology—sometimes it gives back to it, too. And a new flapping-winged robot designed by Dutch engineers that mimics the humble fruit fly has done just that, by revealing how the animals that inspired it carry out predator-dodging maneuvers.

The lab has been building flapping robots for years, but this time they ditched the airplane-like tail used to control previous incarnations. Instead, they used insect-inspired adjustments to the motions of its twin pairs of flapping wings to hover, pitch, and roll with the agility of a fruit fly. That has provided a useful platform for investigating insect flight dynamics, as well as more practical applications.

8. Soft exosuit wearable robot

Exoskeletons could prevent workplace injuries, help people walk again, and even boost soldiers’ endurance. Strapping on bulky equipment isn’t ideal, though, so researchers at Harvard are working on a soft exoskeleton that combines specially-designed textiles, sensors, and lightweight actuators.

And last year the team made an important breakthrough by combining their novel exoskeleton with a machine-learning algorithm that automatically tunes the device to the user’s particular walking style. Using physiological data, it is able to adjust when and where the device needs to deliver a boost to the user’s natural movements to improve walking efficiency.

9. Universal Robots (UR) e-Series Cobots
Robots in factories are nothing new. The enormous mechanical arms you see in car factories normally have to be kept in cages to prevent them from accidentally crushing people. In recent years there’s been growing interest in “co-bots,” collaborative robots designed to work side-by-side with their human colleagues and even learn from them.

Earlier this year saw the demise of ReThink robotics, the pioneer of the approach. But the simple single arm devices made by Danish firm Universal Robotics are becoming ubiquitous in workshops and warehouses around the world, accounting for about half of global co-bot sales. Last year they released their latest e-Series, with enhanced safety features and force/torque sensing.

10. Sony’s aibo
After a nearly 20-year hiatus, Sony’s robotic dog aibo is back, and it’s had some serious upgrades. As well as a revamp to its appearance, the new robotic pet takes advantage of advances in AI, with improved environmental and command awareness and the ability to develop a unique character based on interactions with its owner.

The editors note that this new context awareness mark the device out as a significant evolution in social robots, which many hope could aid in childhood learning or provide companionship for the elderly.

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Posted in Human Robots

#434260 The Most Surprising Tech Breakthroughs ...

Development across the entire information technology landscape certainly didn’t slow down this year. From CRISPR babies, to the rapid decline of the crypto markets, to a new robot on Mars, and discovery of subatomic particles that could change modern physics as we know it, there was no shortage of headline-grabbing breakthroughs and discoveries.

As 2018 comes to a close, we can pause and reflect on some of the biggest technology breakthroughs and scientific discoveries that occurred this year.

I reached out to a few Singularity University speakers and faculty across the various technology domains we cover asking what they thought the biggest breakthrough was in their area of expertise. The question posed was:

“What, in your opinion, was the biggest development in your area of focus this year? Or, what was the breakthrough you were most surprised by in 2018?”

I can share that for me, hands down, the most surprising development I came across in 2018 was learning that a publicly-traded company that was briefly valued at over $1 billion, and has over 12,000 employees and contractors spread around the world, has no physical office space and the entire business is run and operated from inside an online virtual world. This is Ready Player One stuff happening now.

For the rest, here’s what our experts had to say.

DIGITAL BIOLOGY
Dr. Tiffany Vora | Faculty Director and Vice Chair, Digital Biology and Medicine, Singularity University

“That’s easy: CRISPR babies. I knew it was technically possible, and I’ve spent two years predicting it would happen first in China. I knew it was just a matter of time but I failed to predict the lack of oversight, the dubious consent process, the paucity of publicly-available data, and the targeting of a disease that we already know how to prevent and treat and that the children were at low risk of anyway.

I’m not convinced that this counts as a technical breakthrough, since one of the girls probably isn’t immune to HIV, but it sure was a surprise.”

For more, read Dr. Vora’s summary of this recent stunning news from China regarding CRISPR-editing human embryos.

QUANTUM COMPUTING
Andrew Fursman | Co-Founder/CEO 1Qbit, Faculty, Quantum Computing, Singularity University

“There were two last-minute holiday season surprise quantum computing funding and technology breakthroughs:

First, right before the government shutdown, one priority legislative accomplishment will provide $1.2 billion in quantum computing research over the next five years. Second, there’s the rise of ions as a truly viable, scalable quantum computing architecture.”

*Read this Gizmodo profile on an exciting startup in the space to learn more about this type of quantum computing

ENERGY
Ramez Naam | Chair, Energy and Environmental Systems, Singularity University

“2018 had plenty of energy surprises. In solar, we saw unsubsidized prices in the sunny parts of the world at just over two cents per kwh, or less than half the price of new coal or gas electricity. In the US southwest and Texas, new solar is also now cheaper than new coal or gas. But even more shockingly, in Germany, which is one of the least sunny countries on earth (it gets less sunlight than Canada) the average bid for new solar in a 2018 auction was less than 5 US cents per kwh. That’s as cheap as new natural gas in the US, and far cheaper than coal, gas, or any other new electricity source in most of Europe.

In fact, it’s now cheaper in some parts of the world to build new solar or wind than to run existing coal plants. Think tank Carbon Tracker calculates that, over the next 10 years, it will become cheaper to build new wind or solar than to operate coal power in most of the world, including specifically the US, most of Europe, and—most importantly—India and the world’s dominant burner of coal, China.

Here comes the sun.”

GLOBAL GRAND CHALLENGES
Darlene Damm | Vice Chair, Faculty, Global Grand Challenges, Singularity University

“In 2018 we saw a lot of areas in the Global Grand Challenges move forward—advancements in robotic farming technology and cultured meat, low-cost 3D printed housing, more sophisticated types of online education expanding to every corner of the world, and governments creating new policies to deal with the ethics of the digital world. These were the areas we were watching and had predicted there would be change.

What most surprised me was to see young people, especially teenagers, start to harness technology in powerful ways and use it as a platform to make their voices heard and drive meaningful change in the world. In 2018 we saw teenagers speak out on a number of issues related to their well-being and launch digital movements around issues such as gun and school safety, global warming and environmental issues. We often talk about the harm technology can cause to young people, but on the flip side, it can be a very powerful tool for youth to start changing the world today and something I hope we see more of in the future.”

BUSINESS STRATEGY
Pascal Finette | Chair, Entrepreneurship and Open Innovation, Singularity University

“Without a doubt the rapid and massive adoption of AI, specifically deep learning, across industries, sectors, and organizations. What was a curiosity for most companies at the beginning of the year has quickly made its way into the boardroom and leadership meetings, and all the way down into the innovation and IT department’s agenda. You are hard-pressed to find a mid- to large-sized company today that is not experimenting or implementing AI in various aspects of its business.

On the slightly snarkier side of answering this question: The very rapid decline in interest in blockchain (and cryptocurrencies). The blockchain party was short, ferocious, and ended earlier than most would have anticipated, with a huge hangover for some. The good news—with the hot air dissipated, we can now focus on exploring the unique use cases where blockchain does indeed offer real advantages over centralized approaches.”

*Author note: snark is welcome and appreciated

ROBOTICS
Hod Lipson | Director, Creative Machines Lab, Columbia University

“The biggest surprise for me this year in robotics was learning dexterity. For decades, roboticists have been trying to understand and imitate dexterous manipulation. We humans seem to be able to manipulate objects with our fingers with incredible ease—imagine sifting through a bunch of keys in the dark, or tossing and catching a cube. And while there has been much progress in machine perception, dexterous manipulation remained elusive.

There seemed to be something almost magical in how we humans can physically manipulate the physical world around us. Decades of research in grasping and manipulation, and millions of dollars spent on robot-hand hardware development, has brought us little progress. But in late 2018, the Berkley OpenAI group demonstrated that this hurdle may finally succumb to machine learning as well. Given 200 years worth of practice, machines learned to manipulate a physical object with amazing fluidity. This might be the beginning of a new age for dexterous robotics.”

MACHINE LEARNING
Jeremy Howard | Founding Researcher, fast.ai, Founder/CEO, Enlitic, Faculty Data Science, Singularity University

“The biggest development in machine learning this year has been the development of effective natural language processing (NLP).

The New York Times published an article last month titled “Finally, a Machine That Can Finish Your Sentence,” which argued that NLP neural networks have reached a significant milestone in capability and speed of development. The “finishing your sentence” capability mentioned in the title refers to a type of neural network called a “language model,” which is literally a model that learns how to finish your sentences.

Earlier this year, two systems (one, called ELMO, is from the Allen Institute for AI, and the other, called ULMFiT, was developed by me and Sebastian Ruder) showed that such a model could be fine-tuned to dramatically improve the state-of-the-art in nearly every NLP task that researchers study. This work was further developed by OpenAI, which in turn was greatly scaled up by Google Brain, who created a system called BERT which reached human-level performance on some of NLP’s toughest challenges.

Over the next year, expect to see fine-tuned language models used for everything from understanding medical texts to building disruptive social media troll armies.”

DIGITAL MANUFACTURING
Andre Wegner | Founder/CEO Authentise, Chair, Digital Manufacturing, Singularity University

“Most surprising to me was the extent and speed at which the industry finally opened up.

While previously, only few 3D printing suppliers had APIs and knew what to do with them, 2018 saw nearly every OEM (or original equipment manufacturer) enabling data access and, even more surprisingly, shying away from proprietary standards and adopting MTConnect, as stalwarts such as 3D Systems and Stratasys have been. This means that in two to three years, data access to machines will be easy, commonplace, and free. The value will be in what is being done with that data.

Another example of this openness are the seemingly endless announcements of integrated workflows: GE’s announcement with most major software players to enable integrated solutions, EOS’s announcement with Siemens, and many more. It’s clear that all actors in the additive ecosystem have taken a step forward in terms of openness. The result is a faster pace of innovation, particularly in the software and data domains that are crucial to enabling comprehensive digital workflow to drive agile and resilient manufacturing.

I’m more optimistic we’ll achieve that now than I was at the end of 2017.”

SCIENCE AND DISCOVERY
Paul Saffo | Chair, Future Studies, Singularity University, Distinguished Visiting Scholar, Stanford Media-X Research Network

“The most important development in technology this year isn’t a technology, but rather the astonishing science surprises made possible by recent technology innovations. My short list includes the discovery of the “neptmoon”, a Neptune-scale moon circling a Jupiter-scale planet 8,000 lightyears from us; the successful deployment of the Mars InSight Lander a month ago; and the tantalizing ANITA detection (what could be a new subatomic particle which would in turn blow the standard model wide open). The highest use of invention is to support science discovery, because those discoveries in turn lead us to the future innovations that will improve the state of the world—and fire up our imaginations.”

ROBOTICS
Pablos Holman | Inventor, Hacker, Faculty, Singularity University

“Just five or ten years ago, if you’d asked any of us technologists “What is harder for robots? Eyes, or fingers?” We’d have all said eyes. Robots have extraordinary eyes now, but even in a surgical robot, the fingers are numb and don’t feel anything. Stanford robotics researchers have invented fingertips that can feel, and this will be a kingpin that allows robots to go everywhere they haven’t been yet.”

BLOCKCHAIN
Nathana Sharma | Blockchain, Policy, Law, and Ethics, Faculty, Singularity University

“2017 was the year of peak blockchain hype. 2018 has been a year of resetting expectations and technological development, even as the broader cryptocurrency markets have faced a winter. It’s now about seeing adoption and applications that people want and need to use rise. An incredible piece of news from December 2018 is that Facebook is developing a cryptocurrency for users to make payments through Whatsapp. That’s surprisingly fast mainstream adoption of this new technology, and indicates how powerful it is.”

ARTIFICIAL INTELLIGENCE
Neil Jacobstein | Chair, Artificial Intelligence and Robotics, Singularity University

“I think one of the most visible improvements in AI was illustrated by the Boston Dynamics Parkour video. This was not due to an improvement in brushless motors, accelerometers, or gears. It was due to improvements in AI algorithms and training data. To be fair, the video released was cherry-picked from numerous attempts, many of which ended with a crash. However, the fact that it could be accomplished at all in 2018 was a real win for both AI and robotics.”

NEUROSCIENCE
Divya Chander | Chair, Neuroscience, Singularity University

“2018 ushered in a new era of exponential trends in non-invasive brain modulation. Changing behavior or restoring function takes on a new meaning when invasive interfaces are no longer needed to manipulate neural circuitry. The end of 2018 saw two amazing announcements: the ability to grow neural organoids (mini-brains) in a dish from neural stem cells that started expressing electrical activity, mimicking the brain function of premature babies, and the first (known) application of CRISPR to genetically alter two fetuses grown through IVF. Although this was ostensibly to provide genetic resilience against HIV infections, imagine what would happen if we started tinkering with neural circuitry and intelligence.”

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