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#431671 The Doctor in the Machine: How AI Is ...
Artificial intelligence has received its fair share of hype recently. However, it’s hype that’s well-founded: IDC predicts worldwide spend on AI and cognitive computing will culminate to a whopping $46 billion (with a “b”) by 2020, and all the tech giants are jumping on board faster than you can say “ROI.” But what is AI, exactly?
According to Hilary Mason, AI today is being misused as a sort of catch-all term to basically describe “any system that uses data to do anything.” But it’s so much more than that. A truly artificially intelligent system is one that learns on its own, one that’s capable of crunching copious amounts of data in order to create associations and intelligently mimic actual human behavior.
It’s what powers the technology anticipating our next online purchase (Amazon), or the virtual assistant that deciphers our voice commands with incredible accuracy (Siri), or even the hipster-friendly recommendation engine that helps you discover new music before your friends do (Pandora). But AI is moving past these consumer-pleasing “nice-to-haves” and getting down to serious business: saving our butts.
Much in the same way robotics entered manufacturing, AI is making its mark in healthcare by automating mundane, repetitive tasks. This is especially true in the case of detecting cancer. By leveraging the power of deep learning, algorithms can now be trained to distinguish between sets of pixels in an image that represents cancer versus sets that don’t—not unlike how Facebook’s image recognition software tags pictures of our friends without us having to type in their names first. This software can then go ahead and scour millions of medical images (MRIs, CT scans, etc.) in a single day to detect anomalies on a scope that humans just aren’t capable of. That’s huge.
As if that wasn’t enough, these algorithms are constantly learning and evolving, getting better at making these associations with each new data set that gets fed to them. Radiology, dermatology, and pathology will experience a giant upheaval as tech giants and startups alike jump in to bring these deep learning algorithms to a hospital near you.
In fact, some already are: the FDA recently gave their seal of approval for an AI-powered medical imaging platform that helps doctors analyze and diagnose heart anomalies. This is the first time the FDA has approved a machine learning application for use in a clinical setting.
But how efficient is AI compared to humans, really? Well, aside from the obvious fact that software programs don’t get bored or distracted or have to check Facebook every twenty minutes, AI is exponentially better than us at analyzing data.
Take, for example, IBM’s Watson. Watson analyzed genomic data from both tumor cells and healthy cells and was ultimately able to glean actionable insights in a mere 10 minutes. Compare that to the 160 hours it would have taken a human to analyze that same data. Diagnoses aside, AI is also being leveraged in pharmaceuticals to aid in the very time-consuming grunt work of discovering new drugs, and all the big players are getting involved.
But AI is far from being just a behind-the-scenes player. Gartner recently predicted that by 2025, 50 percent of the population will rely on AI-powered “virtual personal health assistants” for their routine primary care needs. What this means is that consumer-facing voice and chat-operated “assistants” (think Siri or Cortana) would, in effect, serve as a central hub of interaction for all our connected health devices and the algorithms crunching all our real-time biometric data. These assistants would keep us apprised of our current state of well-being, acting as a sort of digital facilitator for our personal health objectives and an always-on health alert system that would notify us when we actually need to see a physician.
Slowly, and thanks to the tsunami of data and advancements in self-learning algorithms, healthcare is transitioning from a reactive model to more of a preventative model—and it’s completely upending the way care is delivered. Whether Elon Musk’s dystopian outlook on AI holds any weight or not is yet to be determined. But one thing’s certain: for the time being, artificial intelligence is saving our lives.
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#431543 China Is an Entrepreneurial Hotbed That ...
Last week, Eric Schmidt, chairman of Alphabet, predicted that China will rapidly overtake the US in artificial intelligence…in as little as five years.
Last month, China announced plans to open a $10 billion quantum computing research center in 2020.
Bottom line, China is aggressively investing in exponential technologies, pursuing a bold goal of becoming the global AI superpower by 2030.
Based on what I’ve observed from China’s entrepreneurial scene, I believe they have a real shot of hitting that goal.
As I described in a previous tech blog, I recently traveled to China with a group of my Abundance 360 members, where I was hosted by my friend Kai-Fu Lee, the founder, chairman, and CEO of Sinovation Ventures.
On one of our first nights, Kai-Fu invited us to a special dinner at Da Dong Roast, which specializes in Peking duck, where we shared an 18-course meal.
The meal was amazing, and Kai-Fu’s dinner conversation provided us priceless insights on Chinese entrepreneurs.
Three topics opened my eyes. Here’s the wisdom I’d like to share with you.
1. The Entrepreneurial Culture in China
Chinese entrepreneurship has exploded onto the scene and changed significantly over the past 10 years.
In my opinion, one significant way that Chinese entrepreneurs vary from their American counterparts is in work ethic. The mantra I found in the startups I visited in Beijing and Shanghai was “9-9-6”—meaning the employees only needed to work from 9 am to 9 pm, 6 days a week.
Another concept Kai-Fu shared over dinner was the almost ‘dictatorial’ leadership of the founder/CEO. In China, it’s not uncommon for the Founder/CEO to own the majority of the company, or at least 30–40 percent. It’s also the case that what the CEO says is gospel. Period, no debate. There is no minority or dissenting opinion. When the CEO says “march,” the company asks, “which way?”
When Kai-Fu started Sinovation (his $1 billion+ venture fund), there were few active angel investors. Today, China has a rich ecosystem of angel, venture capital, and government-funded innovation parks.
As venture capital in China has evolved, so too has the mindset of the entrepreneur.
Kai -Fu recalled an early investment he made in which, after an unfortunate streak, the entrepreneur came to him, almost in tears, apologizing for losing his money and promising he would earn it back for him in another way. Kai-Fu comforted the entrepreneur and said there was no such need.
Only a few years later, the situation was vastly different. An entrepreneur who was going through a similar unfortunate streak came to Kai Fu and told him he only had $2 million left of his initial $12 million investment. He informed him he saw no value in returning the money and instead was going to take the last $2 million and use it as a final push to see if the company could succeed. He then promised Kai-Fu if he failed, he would remember what Kai-Fu did for him and, as such, possibly give Sinovation an opportunity to invest in him with his next company.
2. Chinese Companies Are No Longer Just ‘Copycats’
During dinner, Kai-Fu lamented that 10 years ago, it would be fair to call Chinese companies copycats of American companies. Five years ago, the claim would be controversial. Today, however, Kai-Fu is clear that claim is entirely false.
While smart Chinese startups will still look at what American companies are doing and build on trends, today it’s becoming a wise business practice for American tech giants to analyze Chinese companies. If you look at many new features of Facebook’s Messenger, it seems to very closely mirror TenCent’s WeChat.
Interestingly, tight government controls in China have actually spurred innovation. Take TV, for example, a highly regulated industry. Because of this regulation, most entertainment in China is consumed on the internet or by phone. Game shows, reality shows, and more will be entirely centered online.
Kai-Fu told us about one of his investments in a company that helps create Chinese singing sensations. They take girls in from a young age, school them, and regardless of talent, help build their presence and brand as singers. Once ready, these singers are pushed across all the available platforms, and superstars are born. The company recognizes its role in this superstar status, though, which is why it takes a 50 percent cut of all earnings.
This company is just one example of how Chinese entrepreneurs take advantage of China’s unique position, market, and culture.
3. China’s Artificial Intelligence Play
Kai-Fu wrapped up his talk with a brief introduction into the expansive AI industry in China. I previously discussed Face++, a Sinovation investment, which is creating radically efficient facial recognition technology. Face++ is light years ahead of anyone else globally at recognition in live videos. However, Face++ is just one of the incredible advances in AI coming out of China.
Baidu, one of China’s most valuable tech companies, started out as just a search company. However, they now run one of the country’s leading self-driving car programs.
Baidu’s goal is to create a software suite atop existing hardware that will control all self-driving aspects of a vehicle but also be able to provide additional services such as HD mapping and more.
Another interesting application came from another of Sinovation’s investments, Smart Finance Group (SFG). Given most payments are mobile (through WeChat or Alipay), only ~20 percent of the population in China have a credit history. This makes it very difficult for individuals in China to acquire a loan.
SFG’s mobile application takes in user data (as much as the user allows) and, based on the information provided, uses an AI agent to create a financial profile with the power to offer an instant loan. This loan can be deposited directly into their WeChat or Alipay account and is typically approved in minutes. Unlike American loan companies, they avoid default and long-term debt by only providing a one-month loan with 10% interest. Borrow $200, and you pay back $220 by the following month.
Artificial intelligence is exploding in China, and Kai-Fu believes it will touch every single industry.
The only constant is change, and the rate of change is constantly increasing.
In the next 10 years, we’ll see tremendous changes on the geopolitical front and the global entrepreneurial scene caused by technological empowerment.
China is an entrepreneurial hotbed that cannot be ignored. I’m monitoring it closely. Are you?
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#431377 The Farms of the Future Will Be ...
Swarms of drones buzz overhead, while robotic vehicles crawl across the landscape. Orbiting satellites snap high-resolution images of the scene far below. Not one human being can be seen in the pre-dawn glow spreading across the land.
This isn’t some post-apocalyptic vision of the future à la The Terminator. This is a snapshot of the farm of the future. Every phase of the operation—from seed to harvest—may someday be automated, without the need to ever get one’s fingernails dirty.
In fact, it’s science fiction already being engineered into reality. Today, robots empowered with artificial intelligence can zap weeds with preternatural precision, while autonomous tractors move with tireless efficiency across the farmland. Satellites can assess crop health from outer space, providing gobs of data to help produce the sort of business intelligence once accessible only to Fortune 500 companies.
“Precision agriculture is on the brink of a new phase of development involving smart machines that can operate by themselves, which will allow production agriculture to become significantly more efficient. Precision agriculture is becoming robotic agriculture,” said professor Simon Blackmore last year during a conference in Asia on the latest developments in robotic agriculture. Blackmore is head of engineering at Harper Adams University and head of the National Centre for Precision Farming in the UK.
It’s Blackmore’s university that recently showcased what may someday be possible. The project, dubbed Hands Free Hectare and led by researchers from Harper Adams and private industry, farmed one hectare (about 2.5 acres) of spring barley without one person ever setting foot in the field.
The team re-purposed, re-wired and roboticized farm equipment ranging from a Japanese tractor to a 25-year-old combine. Drones served as scouts to survey the operation and collect samples to help the team monitor the progress of the barley. At the end of the season, the robo farmers harvested about 4.5 tons of barley at a price tag of £200,000.
“This project aimed to prove that there’s no technological reason why a field can’t be farmed without humans working the land directly now, and we’ve done that,” said Martin Abell, mechatronics researcher for Precision Decisions, which partnered with Harper Adams, in a press release.
I, Robot Farmer
The Harper Adams experiment is the latest example of how machines are disrupting the agricultural industry. Around the same time that the Hands Free Hectare combine was harvesting barley, Deere & Company announced it would acquire a startup called Blue River Technology for a reported $305 million.
Blue River has developed a “see-and-spray” system that combines computer vision and artificial intelligence to discriminate between crops and weeds. It hits the former with fertilizer and blasts the latter with herbicides with such precision that it can eliminate 90 percent of the chemicals used in conventional agriculture.
It’s not just farmland that’s getting a helping hand from robots. A California company called Abundant Robotics, spun out of the nonprofit research institute SRI International, is developing robots capable of picking apples with vacuum-like arms that suck the fruit straight off the trees in the orchards.
“Traditional robots were designed to perform very specific tasks over and over again. But the robots that will be used in food and agricultural applications will have to be much more flexible than what we’ve seen in automotive manufacturing plants in order to deal with natural variation in food products or the outdoor environment,” Dan Harburg, an associate at venture capital firm Anterra Capital who previously worked at a Massachusetts-based startup making a robotic arm capable of grabbing fruit, told AgFunder News.
“This means ag-focused robotics startups have to design systems from the ground up, which can take time and money, and their robots have to be able to complete multiple tasks to avoid sitting on the shelf for a significant portion of the year,” he noted.
Eyes in the Sky
It will take more than an army of robotic tractors to grow a successful crop. The farm of the future will rely on drones, satellites, and other airborne instruments to provide data about their crops on the ground.
Companies like Descartes Labs, for instance, employ machine learning to analyze satellite imagery to forecast soy and corn yields. The Los Alamos, New Mexico startup collects five terabytes of data every day from multiple satellite constellations, including NASA and the European Space Agency. Combined with weather readings and other real-time inputs, Descartes Labs can predict cornfield yields with 99 percent accuracy. Its AI platform can even assess crop health from infrared readings.
The US agency DARPA recently granted Descartes Labs $1.5 million to monitor and analyze wheat yields in the Middle East and Africa. The idea is that accurate forecasts may help identify regions at risk of crop failure, which could lead to famine and political unrest. Another company called TellusLabs out of Somerville, Massachusetts also employs machine learning algorithms to predict corn and soy yields with similar accuracy from satellite imagery.
Farmers don’t have to reach orbit to get insights on their cropland. A startup in Oakland, Ceres Imaging, produces high-resolution imagery from multispectral cameras flown across fields aboard small planes. The snapshots capture the landscape at different wavelengths, identifying insights into problems like water stress, as well as providing estimates of chlorophyll and nitrogen levels. The geo-tagged images mean farmers can easily locate areas that need to be addressed.
Growing From the Inside
Even the best intelligence—whether from drones, satellites, or machine learning algorithms—will be challenged to predict the unpredictable issues posed by climate change. That’s one reason more and more companies are betting the farm on what’s called controlled environment agriculture. Today, that doesn’t just mean fancy greenhouses, but everything from warehouse-sized, automated vertical farms to grow rooms run by robots, located not in the emptiness of Kansas or Nebraska but smack dab in the middle of the main streets of America.
Proponents of these new concepts argue these high-tech indoor farms can produce much higher yields while drastically reducing water usage and synthetic inputs like fertilizer and herbicides.
Iron Ox, out of San Francisco, is developing one-acre urban greenhouses that will be operated by robots and reportedly capable of producing the equivalent of 30 acres of farmland. Powered by artificial intelligence, a team of three robots will run the entire operation of planting, nurturing, and harvesting the crops.
Vertical farming startup Plenty, also based in San Francisco, uses AI to automate its operations, and got a $200 million vote of confidence from the SoftBank Vision Fund earlier this year. The company claims its system uses only 1 percent of the water consumed in conventional agriculture while producing 350 times as much produce. Plenty is part of a new crop of urban-oriented farms, including Bowery Farming and AeroFarms.
“What I can envision is locating a larger scale indoor farm in the economically disadvantaged food desert, in order to stimulate a broader economic impact that could create jobs and generate income for that area,” said Dr. Gary Stutte, an expert in space agriculture and controlled environment agriculture, in an interview with AgFunder News. “The indoor agriculture model is adaptable to becoming an engine for economic growth and food security in both rural and urban food deserts.”
Still, the model is not without its own challenges and criticisms. Most of what these farms can produce falls into the “leafy greens” category and often comes with a premium price, which seems antithetical to the proposed mission of creating oases in the food deserts of cities. While water usage may be minimized, the electricity required to power the operation, especially the LEDs (which played a huge part in revolutionizing indoor agriculture), are not cheap.
Still, all of these advances, from robo farmers to automated greenhouses, may need to be part of a future where nearly 10 billion people will inhabit the planet by 2050. An oft-quoted statistic from the Food and Agriculture Organization of the United Nations says the world must boost food production by 70 percent to meet the needs of the population. Technology may not save the world, but it will help feed it.
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#431371 Amazon Is Quietly Building the Robots of ...
Science fiction is the siren song of hard science. How many innocent young students have been lured into complex, abstract science, technology, engineering, or mathematics because of a reckless and irresponsible exposure to Arthur C. Clarke at a tender age? Yet Arthur C. Clarke has a very famous quote: “Any sufficiently advanced technology is indistinguishable from magic.”
It’s the prospect of making that… ahem… magic leap that entices so many people into STEM in the first place. A magic leap that would change the world. How about, for example, having humanoid robots? They could match us in dexterity and speed, perceive the world around them as we do, and be programmed to do, well, more or less anything we can do.
Such a technology would change the world forever.
But how will it arrive? While true sci-fi robots won’t get here right away—the pieces are coming together, and the company best developing them at the moment is Amazon. Where others have struggled to succeed, Amazon has been quietly progressing. Notably, Amazon has more than just a dream, it has the most practical of reasons driving it into robotics.
This practicality matters. Technological development rarely proceeds by magic; it’s a process filled with twists, turns, dead-ends, and financial constraints. New technologies often have to answer questions like “What is this good for, are you being realistic?” A good strategy, then, can be to build something more limited than your initial ambition, but useful for a niche market. That way, you can produce a prototype, have a reasonable business plan, and turn a profit within a decade. You might call these “stepping stone” applications that allow for new technologies to be developed in an economically viable way.
You need something you can sell to someone, soon: that’s how you get investment in your idea. It’s this model that iRobot, developers of the Roomba, used: migrating from military prototypes to robotic vacuum cleaners to become the “boring, successful robot company.” Compare this to Willow Garage, a genius factory if ever there was one: they clearly had ambitions towards a general-purpose, multi-functional robot. They built an impressive device—PR2—and programmed the operating system, ROS, that is still the industry and academic standard to this day.
But since they were unable to sell their robot for much less than $250,000, it was never likely to be a profitable business. This is why Willow Garage is no more, and many workers at the company went into telepresence robotics. Telepresence is essentially videoconferencing with a fancy robot attached to move the camera around. It uses some of the same software (for example, navigation and mapping) without requiring you to solve difficult problems of full autonomy for the robot, or manipulating its environment. It’s certainly one of the stepping-stone areas that various companies are investigating.
Another approach is to go to the people with very high research budgets: the military.
This was the Boston Dynamics approach, and their incredible achievements in bipedal locomotion saw them getting snapped up by Google. There was a great deal of excitement and speculation about Google’s “nightmare factory” whenever a new slick video of a futuristic militarized robot surfaced. But Google broadly backed away from Replicant, their robotics program, and Boston Dynamics was sold. This was partly due to PR concerns over the Terminator-esque designs, but partly because they didn’t see the robotics division turning a profit. They hadn’t found their stepping stones.
This is where Amazon comes in. Why Amazon? First off, they just announced that their profits are up by 30 percent, and yet the company is well-known for their constantly-moving Day One philosophy where a great deal of the profits are reinvested back into the business. But lots of companies have ambition.
One thing Amazon has that few other corporations have, as well as big financial resources, is viable stepping stones for developing the technologies needed for this sort of robotics to become a reality. They already employ 100,000 robots: these are of the “pragmatic, boring, useful” kind that we’ve profiled, which move around the shelves in warehouses. These robots are allowing Amazon to develop localization and mapping software for robots that can autonomously navigate in the simple warehouse environment.
But their ambitions don’t end there. The Amazon Robotics Challenge is a multi-million dollar competition, open to university teams, to produce a robot that can pick and package items in warehouses. The problem of grasping and manipulating a range of objects is not a solved one in robotics, so this work is still done by humans—yet it’s absolutely fundamental for any sci-fi dream robot.
Google, for example, attempted to solve this problem by hooking up 14 robot hands to machine learning algorithms and having them grasp thousands of objects. Although results were promising, the 10 to 20 percent failure rate for grasps is too high for warehouse use. This is a perfect stepping stone for Amazon; should they crack the problem, they will likely save millions in logistics.
Another area where humanoid robotics—especially bipedal locomotion, or walking, has been seriously suggested—is in the last mile delivery problem. Amazon has shown willingness to be creative in this department with their notorious drone delivery service. In other words, it’s all very well to have your self-driving car or van deliver packages to people’s doors, but who puts the package on the doorstep? It’s difficult for wheeled robots to navigate the full range of built environments that exist. That’s why bipedal robots like CASSIE, developed by Oregon State, may one day be used to deliver parcels.
Again: no one more than Amazon stands to profit from cracking this technology. The line from robotics research to profit is very clear.
So, perhaps one day Amazon will have robots that can move around and manipulate their environments. But they’re also working on intelligence that will guide those robots and make them truly useful for a variety of tasks. Amazon has an AI, or at least the framework for an AI: it’s called Alexa, and it’s in tens of millions of homes. The Alexa Prize, another multi-million-dollar competition, is attempting to make Alexa more social.
To develop a conversational AI, at least using the current methods of machine learning, you need data on tens of millions of conversations. You need to understand how people will try to interact with the AI. Amazon has access to this in Alexa, and they’re using it. As owners of the leading voice-activated personal assistant, they have an ecosystem of developers creating apps for Alexa. It will be integrated with the smart home and the Internet of Things. It is a very marketable product, a stepping stone for robot intelligence.
What’s more, the company can benefit from its huge sales infrastructure. For Amazon, having an AI in your home is ideal, because it can persuade you to buy more products through its website. Unlike companies like Google, Amazon has an easy way to make a direct profit from IoT devices, which could fuel funding.
For a humanoid robot to be truly useful, though, it will need vision and intelligence. It will have to understand and interpret its environment, and react accordingly. The way humans learn about our environment is by getting out and seeing it. This is something that, for example, an Alexa coupled to smart glasses would be very capable of doing. There are rumors that Alexa’s AI will soon be used in security cameras, which is an ideal stepping stone task to train an AI to process images from its environment, truly perceiving the world and any threats it might contain.
It’s a slight exaggeration to say that Amazon is in the process of building a secret robot army. The gulf between our sci-fi vision of robots that can intelligently serve us, rather than mindlessly assemble cars, is still vast. But in quietly assembling many of the technologies needed for intelligent, multi-purpose robotics—and with the unique stepping stones they have along the way—Amazon might just be poised to leap that gulf. As if by magic.
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