Tag Archives: brain
Each week we scour the web for great articles and fascinating advances across our core topics, from AI to biotech and the brain. But robots have a special place in our hearts. This week, we took a look back at 2017 so far and unearthed a few favorite robots for your reading and viewing pleasure.
Tarzan the Swinging Robot Could Be the Future of FarmingMariella Moon | Engadget“Tarzan will be able to swing over crops using its 3D-printed claws and parallel guy-wires stretched over fields. It will then take measurements and pictures of each plant with its built-in camera while suspended…While it may take some time to achieve that goal, the researchers plan to start testing the robot soon.”
Grasping Robots Compete to Rule Amazon’s Warehouses Tom Simonite | Wired“Robots able to help with so-called picking tasks would boost Amazon’s efficiency—and make it much less reliant on human workers. It’s why the company has invited a motley crew of mechanical arms, grippers, suction cups—and their human handlers—to Nagoya, Japan, this week to show off their manipulation skills.”
Robots Learn to Speak Body LanguageAlyssa Pagano | IEEE Spectrum“One notable feature of the OpenPose system is that it can track not only a person’s head, torso, and limbs but also individual fingers. To do that, the researchers used CMU’s Panoptic Studio, a dome lined with 500 cameras, where they captured body poses at a variety of angles and then used those images to build a data set.”
I Watched Two Robots Chat Together on Stage at a Tech EventJon Russell | TechCrunch“The robots in question are Sophia and Han, and they belong to Hanson Robotics, a Hong Kong-based company that is developing and deploying artificial intelligence in humanoids. The duo took to the stage at Rise in Hong Kong with Hanson Robotics’ Chief Scientist Ben Goertzel directing the banter. The conversation, which was partially scripted, wasn’t as slick as the human-to-human panels at the show, but it was certainly a sight to behold for the packed audience.”
How This Japanese Robotics Master Is Building Better, More Human AndroidsHarry McCracken | Fast Company“On the tech side, making a robot look and behave like a person involves everything from electronics to the silicone Ishiguro’s team uses to simulate skin. ‘We have a technology to precisely control pneumatic actuators,’ he says, noting, as an example of what they need to re-create, that ‘the human shoulder has four degrees of freedom.’”
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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.
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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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.
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).
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.
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.
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.
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.
“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.
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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Singularity University’s (SU) second annual Global Summit begins today in San Francisco, and the Singularity Hub team will be there to give you a live look inside the event, exclusive speaker interviews, and articles on great talks.
Whereas SU’s other summits each focus on a specific field or industry, Global Summit is a broad look at emerging technologies and how they can help solve the world’s biggest challenges.
Talks will cover the latest in artificial intelligence, the brain and technology, augmented and virtual reality, space exploration, the future of work, the future of learning, and more.
We’re bringing three full days of live Facebook programming, streaming on Singularity Hub’s Facebook page, complete with 30+ speaker interviews, tours of the EXPO innovation hall, and tech demos. You can also livestream main stage talks at Singularity University’s Facebook page.
Interviews include Peter Diamandis, cofounder and chairman of Singularity University; Sylvia Earle, National Geographic explorer-in-residence; Esther Wojcicki, founder of the Palo Alto High Media Arts Center; Bob Richards, founder and CEO of Moon Express; Matt Oehrlein, cofounder of MegaBots; and Craig Newmark, founder of Craigslist and the Craig Newmark Foundation.
Pascal Finette, SU vice president of startup solutions, and Alison Berman, SU staff writer and digital producer, will host the show, and Lisa Kay Solomon, SU chair of transformational practices, will put on a special daily segment on exponential leadership with thought leaders.
Make sure you don’t miss anything by ‘liking’ the Singularity Hub and Singularity University Facebook pages and turn on notifications from both pages so you know when we go live. And to get a taste of what’s in store, check out the below selection of stories from last year’s event.
Are We at the Edge of a Second Sexual Revolution?By Vanessa Bates Ramirez
“Brace yourself, because according to serial entrepreneur Martin Varsavsky, all our existing beliefs about procreation are about to be shattered again…According to Varsavsky, the second sexual revolution will decouple procreation from sex, because sex will no longer be the best way to make babies.”
VR Pioneer Chris Milk: Virtual Reality Will Mirror Life Like Nothing Else BeforeBy Jason Ganz
“Milk is already a legend in the VR community…But [he] is just getting started. His company Within has plans to help shape the language we use for virtual reality storytelling. Because let’s be clear, VR storytelling is still very much in its infancy. This fact makes it even crazier there are already VR films out there that can inspire and captivate on such a profound level. And we’re only going up from here.”
7 Key Factors Driving the Artificial Intelligence RevolutionBy David Hill
“Jacobstein calmly and optimistically assures that this revolution isn’t going to disrupt humans completely, but usher in a future in which there’s a symbiosis between human and machine intelligence. He highlighted 7 factors driving this revolution.”
Are There Other Intelligent Civilizations Out There? Two Views on the Fermi ParadoxBy Alison Berman
“Cliché or not, when I stare up at the sky, I still wonder if we’re alone in the galaxy. Could there be another technologically advanced civilization out there? During a panel discussion on space exploration at Singularity University’s Global Summit, Jill Tarter, the Bernard M. Oliver chair at the SETI Institute, was asked to explain the Fermi paradox and her position on it. Her answer was pretty brilliant.”
Engineering Will Soon Be ‘More Parenting Than Programming’By Sveta McShane
“In generative design, the user states desired goals and constraints and allows the computer to generate entire designs, iterations and solution sets based on those constraints. It is, in fact, a lot like parents setting boundaries for their children’s activities. The user basically says, ‘Yes, it’s ok to do this, but it’s not ok to do that.’ The resulting solutions are ones you might never have thought of on your own.”
Biohacking Will Let You Connect Your Body to Anything You WantBy Vanessa Bates Ramirez
“How many cyborgs did you see during your morning commute today? I would guess at least five. Did they make you nervous? Probably not; you likely didn’t even realize they were there…[Hannes] Sjoblad said that the cyborgs we see today don’t look like Hollywood prototypes; they’re regular people who have integrated technology into their bodies to improve or monitor some aspect of their health.”
Peter Diamandis: We’ll Radically Extend Our Lives With New TechnologiesBy Jason Dorrier
“[Diamandis] said humans aren’t the longest-lived animals. Other species have multi-hundred-year lifespans. Last year, a study “dating” Greenland sharks found they can live roughly 400 years. Though the technique isn’t perfectly precise, they estimated one shark to be about 392. Its approximate birthday was 1624…Diamandis said he asked himself: If these animals can live centuries—why can’t I?” Continue reading
When it comes to biomolecules, RNA doesn’t get a lot of love.
Maybe you haven’t even heard of the silent workhorse. RNA is the cell’s de facto translator: like a game of telephone, RNA takes DNA’s genetic code to a cellular factory called ribosomes. There, the cell makes proteins based on RNA’s message.
But RNA isn’t just a middleman. It controls what proteins are formed. Because proteins wiz around the cell completing all sorts of important processes, you can say that RNA is the gatekeeper: no RNA message, no proteins, no life.
In a new study published in Nature, RNA finally took center stage. By adding bits of genetic material to the E. Coli bacteria, a team of biohackers at the Wyss Institute hijacked the organism’s RNA messengers so that they only spring into action following certain inputs.
The result? A bacterial biocomputer capable of performing 12-input logic operations—AND, OR, and NOT—following specific inputs. Rather than outputting 0s and 1s, these biocircuits produce results based on the presence or absence of proteins and other molecules.
“It’s the greatest number of inputs in a circuit that a cell has been able to process,” says study author Dr. Alexander Green at Arizona State University. “To be able to analyze those signals and make a decision is the big advance here.”
When given a specific set of inputs, the bacteria spit out a protein that made them glow neon green under fluorescent light.
But synthetic biology promises far more than just a party trick—by tinkering with a cell’s RNA repertoire, scientists may one day coax them to photosynthesize, produce expensive drugs on the fly, or diagnose and hunt down rogue tumor cells.
Illustration of an RNA-based ‘ribocomputing’ device that makes logic-based decisions in living cells. The long gate RNA (blue) detects the binding of an input RNA (red). The ribosome (purple/mauve) reads the gate RNA to produce an output protein. Image Credit: Alexander Green / Arizona State University
The software of life
This isn’t the first time that scientists hijacked life’s algorithms to reprogram cells into nanocomputing systems. Previous work has already introduced to the world yeast cells that can make anti-malaria drugs from sugar or mammalian cells that can perform Boolean logic.
Yet circuits with multiple inputs and outputs remain hard to program. The reason is this: synthetic biologists have traditionally focused on snipping, fusing, or otherwise arranging a cell’s DNA to produce the outcomes they want.
But DNA is two steps removed from proteins, and tinkering with life’s code often leads to unexpected consequences. For one, the cell may not even accept and produce the extra bits of DNA code. For another, the added code, when transformed into proteins, may not act accordingly in the crowded and ever-changing environment of the cell.
What’s more, tinkering with one gene is often not enough to program an entirely new circuit. Scientists often need to amp up or shut down the activity of multiple genes, or multiple biological “modules” each made up of tens or hundreds of genes.
It’s like trying to fit new Lego pieces in a specific order into a room full of Lego constructions. Each new piece has the potential to wander off track and click onto something it’s not supposed to touch.
Getting every moving component to work in sync—as you might have guessed—is a giant headache.
The RNA way
With “ribocomputing,” Green and colleagues set off to tackle a main problem in synthetic biology: predictability.
Named after the “R (ribo)” in “RNA,” the method grew out of an idea that first struck Green back in 2012.
“The synthetic biological circuits to date have relied heavily on protein-based regulators that are difficult to scale up,” Green wrote at the time. We only have a limited handful of “designable parts” that work well, and these circuits require significant resources to encode and operate, he explains.
RNA, in comparison, is a lot more predictable. Like its more famous sibling DNA, RNA is composed of units that come in four different flavors: A, G, C, and U. Although RNA is only single-stranded, rather than the double helix for which DNA is known for, it can bind short DNA-like sequences in a very predictable manner: Gs always match up with Cs and As always with Us.
Because of this predictability, it’s possible to design RNA components that bind together perfectly. In other words, it reduces the chance that added RNA bits might go rogue in an unsuspecting cell.
Normally, once RNA is produced it immediately rushes to the ribosome—the cell’s protein-building factory. Think of it as a constantly “on” system.
However, Green and his team found a clever mechanism to slow them down. Dubbed the “toehold switch,” it works like this: the artificial RNA component is first incorporated into a chain of A, G, C, and U folded into a paperclip-like structure.
This blocks the RNA from accessing the ribosome. Because one RNA strand generally maps to one protein, the switch prevents that protein from ever getting made.
In this way, the switch is set to “off” by default—a “NOT” gate, in Boolean logic.
To activate the switch, the cell needs another component: a “trigger RNA,” which binds to the RNA toehold switch. This flips it on: the RNA grabs onto the ribosome, and bam—proteins.
String a few RNA switches together, with the activity of each one relying on the one before, and it forms an “AND” gate. Alternatively, if the activity of each switch is independent, that’s an “OR” gate.
“Basically, the toehold switches performed so well that we wanted to find a way to best exploit them for cellular applications,” says Green. They’re “kind of the equivalent of your first transistors,” he adds.
Once the team optimized the designs for different logic gates, they carefully condensed the switches into “gate RNA” molecules. These gate RNAs contain both codes for proteins and the logic operations needed to kickstart the process—a molecular logic circuit, so to speak.
If you’ve ever played around with an Arduino-controlled electrical circuit, you probably know the easiest way to test its function is with a light bulb.
That’s what the team did here, though with a biological bulb: green fluorescent protein, a light-sensing protein not normally present in bacteria that—when turned on—makes the microbugs glow neon green.
In a series of experiments, Green and his team genetically inserted gate RNAs into bacteria. Then, depending on the type of logical function, they added different combinations of trigger RNAs—the inputs.
When the input RNA matched up with its corresponding gate RNA, it flipped on the switch, causing the cell to light up.
Their most complex circuit contained five AND gates, five OR gates, and two NOTs—a 12-input ribocomputer that functioned exactly as designed.
That’s quite the achievement. “Everything is interacting with everything else and there are a million ways those interactions could flip the switch on accident,” says RNA researcher Dr. Julies Lucks at Northwestern University.
The specificity is thanks to RNA, the authors explain. Because RNAs bind to others so predictably, we can now design massive libraries of gate and trigger units to mix-and-match into all types of nano-biocomputers.
Although the technology doesn’t have any immediate applications, the team has high hopes.
For the first time, it’s now possible to massively scale up the process of programming new circuits into living cells. We’ve expanded the library of available biocomponents that can be used to reprogram life’s basic code, the authors say.
What’s more, when freeze-dried onto a piece of tissue paper, RNA keeps very well. We could potentially print RNA toehold switches onto paper that respond to viruses or to tumor cells, the authors say, essentially transforming the technology into highly accurate diagnostic platforms.
But Green’s hopes are even wilder for his RNA-based circuits.
“Because we’re using RNA, a universal molecule of life, we know these interactions can also work in other cells, so our method provides a general strategy that could be ported to other organisms,” he says.
Ultimately, the hope is to program neural network-like capabilities into the body’s other cells.
Imagine cells endowed with circuits capable of performing the kinds of computation the brain does, the authors say.
Perhaps one day, synthetic biology will transform our own cells into fully programmable entities, turning us all into biological cyborgs from the inside. How wild would that be?
Image Credit: Wyss Institute at Harvard University Continue reading