Tag Archives: machine
#431022 Robots and AI Will Take Over These 3 ...
We’re no stranger to robotics in the medical field. Robot-assisted surgery is becoming more and more common. Many training programs are starting to include robotic and virtual reality scenarios to provide hands-on training for students without putting patients at risk.
With all of these advances in medical robotics, three niches stand out above the rest: surgery, medical imaging, and drug discovery. How have robotics already begun to exert their influence on these practices, and how will they change them for good?
Robot-Assisted Surgery
Robot-assisted surgery was first documented in 1985, when it was used for a neurosurgical biopsy. This led to the use of robotics in a number of similar surgeries, both laparoscopic and traditional operations. The FDA didn’t approve robotic surgery tools until 2000, when the da Vinci Surgery system hit the market.
The robot-assisted surgery market is expected to grow steadily into 2023 and potentially beyond. The only thing that might stand in the way of this growth is the cost of the equipment. The initial investment may prevent small practices from purchasing the necessary devices.
Medical Imaging
The key to successful medical imaging isn’t the equipment itself. It’s being able to interpret the information in the images. Medical images are some of the most information-dense pieces of data in the medical field and can reveal so much more than a basic visual inspection can.
Robotics and, more specifically, artificial intelligence programs like IBM Watson can help interpret these images more efficiently and accurately. By allowing an AI or basic machine learning program to study the medical images, researchers can find patterns and make more accurate diagnoses than ever before.
Drug Discovery
Drug discovery is a long and often tedious process that includes years of testing and assessment. Artificial intelligence, machine learning and predictive algorithms could help speed up this system.
Imagine if researchers could input the kind of medicine they’re trying to make and the kind of symptoms they’re trying to treat into a computer and let it do the rest. With robotics, that may someday be possible.
This isn’t a perfect solution yet—these systems require massive amounts of data before they can start making decisions or predictions. By feeding data into the cloud where these programs can access it, researchers can take the first steps towards setting up a functional database.
Another benefit of these AI programs is that they might see connections humans would never have thought of. People can make those leaps, but the chances are much lower, and it takes much longer if it happens at all. Simply put, we’re not capable of processing the sheer amount of data that computers can process.
This isn’t a field where we’re worrying about robots stealing jobs.
Quite the opposite, in fact—we want robots to become commonly-used tools that can help improve patient care and surgical outcomes.
A human surgeon might have intuition, but they’ll never have the steadiness that a pair of robotic hands can provide or the data-processing capabilities of a machine learning algorithm. If we let them, these tools could change the way we look at medicine.
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#431000 Japan’s SoftBank Is Investing Billions ...
Remember the 1980s movie Brewster’s Millions, in which a minor league baseball pitcher (played by Richard Pryor) must spend $30 million in 30 days to inherit $300 million? Pryor goes on an epic spending spree for a bigger payoff down the road.
One of the world’s biggest public companies is making that film look like a weekend in the Hamptons. Japan’s SoftBank Group, led by its indefatigable CEO Masayoshi Son, is shooting to invest $100 billion over the next five years toward what the company calls the information revolution.
The newly-created SoftBank Vision Fund, with a handful of key investors, appears ready to almost single-handedly hack the technology revolution. Announced only last year, the fund had its first major close in May with $93 billion in committed capital. The rest of the money is expected to be raised this year.
The fund is unprecedented. Data firm CB Insights notes that the SoftBank Vision Fund, if and when it hits the $100 billion mark, will equal the total amount that VC-backed companies received in all of 2016—$100.8 billion across 8,372 deals globally.
The money will go toward both billion-dollar corporations and startups, with a minimum $100 million buy-in. The focus is on core technologies like artificial intelligence, robotics and the Internet of Things.
Aside from being Japan’s richest man, Son is also a futurist who has predicted the singularity, the moment in time when machines will become smarter than humans and technology will progress exponentially. Son pegs the date as 2047. He appears to be hedging that bet in the biggest way possible.
Show Me the Money
Ostensibly a telecommunications company, SoftBank Group was founded in 1981 and started investing in internet technologies by the mid-1990s. Son infamously lost about $70 billion of his own fortune after the dot-com bubble burst around 2001. The company itself has a market cap of nearly $90 billion today, about half of where it was during the heydays of the internet boom.
The ups and downs did nothing to slake the company’s thirst for technology. It has made nine acquisitions and more than 130 investments since 1995. In 2017 alone, SoftBank has poured billions into nearly 30 companies and acquired three others. Some of those investments are being transferred to the massive SoftBank Vision Fund.
SoftBank is not going it alone with the new fund. More than half of the money—$60 billion—comes via the Middle East through Saudi Arabia’s Public Investment Fund ($45 billion) and Abu Dhabi’s Mubadala Investment Company ($15 billion). Other players at the table include Apple, Qualcomm, Sharp, Foxconn, and Oracle.
During a company conference in August, Son notes the SoftBank Vision Fund is not just about making money. “We don’t just want to be an investor just for the money game,” he says through a translator. “We want to make the information revolution. To do the information revolution, you can’t do it by yourself; you need a lot of synergy.”
Off to the Races
The fund has wasted little time creating that synergy. In July, its first official investment, not surprisingly, went to a company that specializes in artificial intelligence for robots—Brain Corp. The San Diego-based startup uses AI to turn manual machines into self-driving robots that navigate their environments autonomously. The first commercial application appears to be a really smart commercial-grade version that crosses a Roomba and Zamboni.
A second investment in July was a bit more surprising. SoftBank and its fund partners led a $200 million mega-round for Plenty, an agricultural tech company that promises to reshape farming by going vertical. Using IoT sensors and machine learning, Plenty claims its urban vertical farms can produce 350 times more vegetables than a conventional farm using 1 percent of the water.
Round Two
The spending spree continued into August.
The SoftBank Vision Fund led a $1.1 billion investment into a little-known biotechnology company called Roivant Sciences that goes dumpster diving for abandoned drugs and then creates subsidiaries around each therapy. For example, Axovant Sciences is devoted to neurology while Urovant focuses on urology. TechCrunch reports that Roivant is also creating a tech-focused subsidiary, called Datavant, that will use AI for drug discovery and other healthcare initiatives, such as designing clinical trials.
The AI angle may partly explain SoftBank’s interest in backing the biggest private placement in healthcare to date.
Also in August, SoftBank Vision Fund led a mix of $2.5 billion in primary and secondary capital investments into India’s largest private company in what was touted as the largest single investment in a private Indian company. Flipkart is an e-commerce company in the mold of Amazon.
The fund tacked on a $250 million investment round in August to Kabbage, an Atlanta-based startup in the alt-lending sector for small businesses. It ended big with a $4.4 billion investment into a co-working company called WeWork.
Betterment of Humanity
And those investments only include companies that SoftBank Vision Fund has backed directly.
SoftBank the company will offer—or has already turned over—previous investments to the Vision Fund in more than a half-dozen companies. Those assets include its shares in Nvidia, which produces chips for AI applications, and its first serious foray into autonomous driving with Nauto, a California startup that uses AI and high-tech cameras to retrofit vehicles to improve driving safety. The more miles the AI logs, the more it learns about safe and unsafe driving behaviors.
Other recent acquisitions, such as Boston Dynamics, a well-known US robotics company owned briefly by Google’s parent company Alphabet, will remain under the SoftBank Group umbrella for now.
This spending spree begs the question: What is the overall vision behind the SoftBank’s relentless pursuit of technology companies? A spokesperson for SoftBank told Singularity Hub that the “common thread among all of these companies is that they are creating the foundational platforms for the next stage of the information revolution.All of the companies, he adds, share SoftBank’s criteria of working toward “the betterment of humanity.”
While the SoftBank portfolio is diverse, from agtech to fintech to biotech, it’s obvious that SoftBank is betting on technologies that will connect the world in new and amazing ways. For instance, it wrote a $1 billion check last year in support of OneWeb, which aims to launch 900 satellites to bring internet to everyone on the planet. (It will also be turned over to the SoftBank Vision Fund.)
SoftBank also led a half-billion equity investment round earlier this year in a UK company called Improbable, which employs cloud-based distributed computing to create virtual worlds for gaming. The next step for the company is massive simulations of the real world that supports simultaneous users who can experience the same environment together(and another candidate for the SoftBank Vision Fund.)
Even something as seemingly low-tech as WeWork, which provides a desk or office in locations around the world, points toward a more connected planet.
In the end, the singularity is about bringing humanity together through technology. No one said it would be easy—or cheap.
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#430874 12 Companies That Are Making the World a ...
The Singularity University Global Summit in San Francisco this week brought brilliant minds together from all over the world to share a passion for using science and technology to solve the world’s most pressing challenges.
Solving these challenges means ensuring basic needs are met for all people. It means improving quality of life and mitigating future risks both to people and the planet.
To recognize organizations doing outstanding work in these fields, SU holds the Global Grand Challenge Awards. Three participating organizations are selected in each of 12 different tracks and featured at the summit’s EXPO. The ones found to have the most potential to positively impact one billion people are selected as the track winners.
Here’s a list of the companies recognized this year, along with some details about the great work they’re doing.
Global Grand Challenge Awards winners at Singularity University’s Global Summit in San Francisco.
Disaster Resilience
LuminAID makes portable lanterns that can provide 24 hours of light on 10 hours of solar charging. The lanterns came from a project to assist post-earthquake relief efforts in Haiti, when the product’s creators considered the dangerous conditions at night in the tent cities and realized light was a critical need. The lights have been used in more than 100 countries and after disasters, including Hurricane Sandy, Typhoon Haiyan, and the earthquakes in Nepal.
Environment
BreezoMeter uses big data and machine learning to deliver accurate air quality information in real time. Users can see pollution details as localized as a single city block, and data is impacted by real-time traffic. Forecasting is also available, with air pollution information available up to four days ahead of time, or several years in the past.
Food
Aspire Food Group believes insects are the protein of the future, and that technology has the power to bring the tradition of eating insects that exists in many countries and cultures to the rest of the world. The company uses technologies like robotics and automated data collection to farm insects that have the protein quality of meat and the environmental footprint of plants.
Energy
Rafiki Power acts as a rural utility company, building decentralized energy solutions in regions that lack basic services like running water and electricity. The company’s renewable hybrid systems are packed and standardized in recycled 20-foot shipping containers, and they’re currently powering over 700 household and business clients in rural Tanzania.
Governance
MakeSense is an international community that brings together people in 128 cities across the world to help social entrepreneurs solve challenges in areas like education, health, food, and environment. Social entrepreneurs post their projects and submit challenges to the community, then participants organize workshops to mobilize and generate innovative solutions to help the projects grow.
Health
Unima developed a fast and low-cost diagnostic and disease surveillance tool for infectious diseases. The tool allows health professionals to diagnose diseases at the point of care, in less than 15 minutes, without the use of any lab equipment. A drop of the patient’s blood is put on a diagnostic paper, where the antibody generates a visual reaction when in contact with the biomarkers in the sample. The result is evaluated by taking a photo with an app in a smartphone, which uses image processing, artificial intelligence and machine learning.
Prosperity
Egalite helps people with disabilities enter the labor market, and helps companies develop best practices for inclusion of the disabled. Egalite’s founders are passionate about the potential of people with disabilities and the return companies get when they invest in that potential.
Learning
Iris.AI is an artificial intelligence system that reads scientific paper abstracts and extracts key concepts for users, presenting concepts visually and allowing users to navigate a topic across disciplines. Since its launch, Iris.AI has read 30 million research paper abstracts and more than 2,000 TED talks. The AI uses a neural net and deep learning technology to continuously improve its output.
Security
Hala Systems, Inc. is a social enterprise focused on developing technology-driven solutions to the world’s toughest humanitarian challenges. Hala is currently focused on civilian protection, accountability, and the prevention of violent extremism before, during, and after conflict. Ultimately, Hala aims to transform the nature of civilian defense during warfare, as well as to reduce casualties and trauma during post-conflict recovery, natural disasters, and other major crises.
Shelter
Billion Bricks designs and provides shelter and infrastructure solutions for the homeless. The company’s housing solutions are scalable, sustainable, and able to create opportunities for communities to emerge from poverty. Their approach empowers communities to replicate the solutions on their own, reducing dependency on support and creating ownership and pride.
Space
Tellus Labs uses satellite data to tackle challenges like food security, water scarcity, and sustainable urban and industrial systems, and drive meaningful change. The company built a planetary-scale model of all 170 million acres of US corn and soy crops to more accurately forecast yields and help stabilize the market fluctuations that accompany the USDA’s monthly forecasts.
Water
Loowatt designed a toilet that uses a patented sealing technology to contain human waste within biodegradable film. The toilet is designed for linking to anaerobic digestion technology to provide a source of biogas for cooking, electricity, and other applications, creating the opportunity to offset capital costs with energy production.
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#430868 These 7 Forces Are Changing the World at ...
It was the Greek philosopher Heraclitus who first said, “The only thing that is constant is change.”
He was onto something. But even he would likely be left speechless at the scale and pace of change the world has experienced in the past 100 years—not to mention the past 10.
Since 1917, the global population has gone from 1.9 billion people to 7.5 billion. Life expectancy has more than doubled in many developing countries and risen significantly in developed countries. In 1917 only eight percent of homes had phones—in the form of landline telephones—while today more than seven in 10 Americans own a smartphone—aka, a supercomputer that fits in their pockets.
And things aren’t going to slow down anytime soon. In a talk at Singularity University’s Global Summit this week in San Francisco, SU cofounder and chairman Peter Diamandis told the audience, “Tomorrow’s speed of change will make today look like we’re crawling.” He then shared his point of view about some of the most important factors driving this accelerating change.
Peter Diamandis at Singularity University’s Global Summit in San Francisco.
Computation
In 1965, Gordon Moore (cofounder of Intel) predicted computer chips would double in power and halve in cost every 18 to 24 months. What became known as Moore’s Law turned out to be accurate, and today affordable computer chips contain a billion or more transistors spaced just nanometers apart.
That means computers can do exponentially more calculations per second than they could thirty, twenty, or ten years ago—and at a dramatically lower cost. This in turn means we can generate a lot more information, and use computers for all kinds of applications they wouldn’t have been able to handle in the past (like diagnosing rare forms of cancer, for example).
Convergence
Increased computing power is the basis for a myriad of technological advances, which themselves are converging in ways we couldn’t have imagined a couple decades ago. As new technologies advance, the interactions between various subsets of those technologies create new opportunities that accelerate the pace of change much more than any single technology can on its own.
A breakthrough in biotechnology, for example, might spring from a crucial development in artificial intelligence. An advance in solar energy could come about by applying concepts from nanotechnology.
Interface Moments
Technology is becoming more accessible even to the most non-techy among us. The internet was once the domain of scientists and coders, but these days anyone can make their own web page, and browsers make those pages easily searchable. Now, interfaces are opening up areas like robotics or 3D printing.
As Diamandis put it, “You don’t need to know how to code to 3D print an attachment for your phone. We’re going from mind to materialization, from intentionality to implication.”
Artificial intelligence is what Diamandis calls “the ultimate interface moment,” enabling everyone who can speak their mind to connect and leverage exponential technologies.
Connectivity
Today there are about three billion people around the world connected to the internet—that’s up from 1.8 billion in 2010. But projections show that by 2025 there will be eight billion people connected. This is thanks to a race between tech billionaires to wrap the Earth in internet; Elon Musk’s SpaceX has plans to launch a network of 4,425 satellites to get the job done, while Google’s Project Loon is using giant polyethylene balloons for the task.
These projects will enable five billion new minds to come online, and those minds will have access to exponential technologies via interface moments.
Sensors
Diamandis predicts that after we establish a 5G network with speeds of 10–100 Gbps, a proliferation of sensors will follow, to the point that there’ll be around 100,000 sensors per city block. These sensors will be equipped with the most advanced AI, and the combination of these two will yield an incredible amount of knowledge.
“By 2030 we’re heading towards 100 trillion sensors,” Diamandis said. “We’re heading towards a world in which we’re going to be able to know anything we want, anywhere we want, anytime we want.” He added that tens of thousands of drones will hover over every major city.
Intelligence
“If you think there’s an arms race going on for AI, there’s also one for HI—human intelligence,” Diamandis said. He explained that if a genius was born in a remote village 100 years ago, he or she would likely not have been able to gain access to the resources needed to put his or her gifts to widely productive use. But that’s about to change.
Private companies as well as military programs are working on brain-machine interfaces, with the ultimate aim of uploading the human mind. The focus in the future will be on increasing intelligence of individuals as well as companies and even countries.
Wealth Concentration
A final crucial factor driving mass acceleration is the increase in wealth concentration. “We’re living in a time when there’s more wealth in the hands of private individuals, and they’re willing to take bigger risks than ever before,” Diamandis said. Billionaires like Mark Zuckerberg, Jeff Bezos, Elon Musk, and Bill Gates are putting millions of dollars towards philanthropic causes that will benefit not only themselves, but humanity at large.
What It All Means
One of the biggest implications of the rate at which the world is changing, Diamandis said, is that the cost of everything is trending towards zero. We are heading towards abundance, and the evidence lies in the reduction of extreme poverty we’ve already seen and will continue to see at an even more rapid rate.
Listening to Diamandis’ optimism, it’s hard not to find it contagious.
“The world is becoming better at an extraordinary rate,” he said, pointing out the rises in literacy, democracy, vaccinations, and life expectancy, and the concurrent decreases in child mortality, birth rate, and poverty.
“We’re alive during a pivotal time in human history,” he concluded. “There is nothing we don’t have access to.”
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#430855 Why Education Is the Hardest Sector of ...
We’ve all heard the warning cries: automation will disrupt entire industries and put millions of people out of jobs. In fact, up to 45 percent of existing jobs can be automated using current technology.
However, this may not necessarily apply to the education sector. After a detailed analysis of more than 2,000-plus work activities for more than 800 occupations, a report by McKinsey & Co states that of all the sectors examined, “…the technical feasibility of automation is lowest in education.”
There is no doubt that technological trends will have a powerful impact on global education, both by improving the overall learning experience and by increasing global access to education. Massive open online courses (MOOCs), chatbot tutors, and AI-powered lesson plans are just a few examples of the digital transformation in global education. But will robots and artificial intelligence ever fully replace teachers?
The Most Difficult Sector to Automate
While various tasks revolving around education—like administrative tasks or facilities maintenance—are open to automation, teaching itself is not.
Effective education involves more than just transfer of information from a teacher to a student. Good teaching requires complex social interactions and adaptation to the individual student’s learning needs. An effective teacher is not just responsive to each student’s strengths and weaknesses, but is also empathetic towards the student’s state of mind. It’s about maximizing human potential.
Furthermore, students don’t just rely on effective teachers to teach them the course material, but also as a source of life guidance and career mentorship. Deep and meaningful human interaction is crucial and is something that is very difficult, if not impossible, to automate.
Automating teaching is an example of a task that would require artificial general intelligence (as opposed to narrow or specific intelligence). In other words, this is the kind of task that would require an AI that understands natural human language, can be empathetic towards emotions, plan, strategize and make impactful decisions under unpredictable circumstances.
This would be the kind of machine that can do anything a human can do, and it doesn’t exist—at least, not yet.
We’re Getting There
Let’s not forget how quickly AI is evolving. Just because it’s difficult to fully automate teaching, it doesn’t mean the world’s leading AI experts aren’t trying.
Meet Jill Watson, the teaching assistant from Georgia Institute of Technology. Watson isn’t your average TA. She’s an IBM-powered artificial intelligence that is being implemented in universities around the world. Watson is able to answer students’ questions with 97 percent certainty.
Technologies like this also have applications in grading and providing feedback. Some AI algorithms are being trained and refined to perform automatic essay scoring. One project has achieved a 0.945 correlation with human graders.
All of this will have a remarkable impact on online education as we know it and dramatically increase online student retention rates.
Any student with a smartphone can access a wealth of information and free courses from universities around the world. MOOCs have allowed valuable courses to become available to millions of students. But at the moment, not all participants can receive customized feedback for their work. Currently, this is limited by manpower, but in the future that may not be the case.
What chatbots like Jill Watson allow is the opportunity for hundreds of thousands, if not millions, of students to have their work reviewed and all their questions answered at a minimal cost.
AI algorithms also have a significant role to play in personalization of education. Every student is unique and has a different set of strengths and weaknesses. Data analysis can be used to improve individual student results, assess each student’s strengths and weaknesses, and create mass-customized programs. Algorithms can analyze student data and consequently make flexible programs that adapt to the learner based on real-time feedback. According to the McKinsey Global Institute, all of this data in education could unlock between $900 billion and $1.2 trillion in global economic value.
Beyond Automated Teaching
It’s important to recognize that technological automation alone won’t fix the many issues in our global education system today. Dominated by outdated curricula, standardized tests, and an emphasis on short-term knowledge, many experts are calling for a transformation of how we teach.
It is not enough to simply automate the process. We can have a completely digital learning experience that continues to focus on outdated skills and fails to prepare students for the future. In other words, we must not only be innovative with our automation capabilities, but also with educational content, strategy, and policies.
Are we equipping students with the most important survival skills? Are we inspiring young minds to create a better future? Are we meeting the unique learning needs of each and every student? There’s no point automating and digitizing a system that is already flawed. We need to ensure the system that is being digitized is itself being transformed for the better.
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