Exponential Technology Report – 16 October 2019

Welcome to the Exponential Technology Report – October 16th 2019

This is the weekly report focusing on the news stories for the week that focus on exponential technologies.

A reminder that the exponential technologies fall into different categories, which are 3D printing and digital fabrication, Artificial intelligence (AI), Augmented and virtual reality (AR, VR), Autonomous vehicles, Blockchain, Data Science, Digital biology and biotechnology, Digital medicine, Drone technology, Internet of things, Nanotechnology , Networks and computing systems, Quantum computing and Robotics.

For this report the format I use is to go through the exponential technologies in alphabetical order. All the links to the articles can be found by clicking on the image. I hope you enjoy it!

3D Printing and Digital Fabrication

We start this week with 3D Printing.

Article: “Watch the world’s biggest 3D printer make a 25-foot boat” - www.techradar.com

The biggest 3D printer in the world has just printed a 25-foot, 5,000-pound boat, which is the largest object that has ever been printed.

The feat achieved by the University of Maine’s Advanced Structures and Composites Center snagged no less than three Guinness World Records for the world’s largest prototype polymer 3D printer, as well as the largest solid 3D-printed object, and the largest boat which has ever been produced by a 3D printer.

The broad idea is to commercialize this sort of large-scale 3D printing for the benefit boat-builders in main, using 3D printing plastics with 50% wood for a competitive advantage.

Artificial Intelligence (AI)

Article: – “Artificial Intelligence Could Be a $14 Trillion Boon to the Global Economy—If It Can Overcome These Obstacles” – www.fortune.com

By 2035, this A.I.-powered push will provide a $14 trillion boost to the global economy, consulting giant Accenture predicts.

They’re not a threat to jobs, Accenture says, “because these systems are not very intelligent.” AI—and its many iterations: machine learning, natural language processing, machine vision, image- and voice-recognition—is well adapted at highly specialized tasks. It does a decent job telling you what the weather will be tomorrow, or ordering movie tickets or helping you find the fastest route home during the evening commute. All manner of businesses are using A.I. increasingly on the enterprise level to make sense of the vast flows of structured and unstructured data they collect to root out inefficiencies, and save costs.

Gary Marcus, professor of psychology and neural science at New York University and author of Rebooting AI calls deep learning— the subset of A.I. that can make sense of huge amounts of data with little to no oversight from human minders—a misnomer. It’s good at narrowly focused tasks, but he questions its much-ballyhooed potential to, for example, revolutionize transportation (self-driving cars) and medicine (analyzing huge volumes of MRI scans for signs of cancerous growths). “Deep learning is no substitute for deep understanding,” he says.

In order for A.I. systems to be truly effective they need to be designed to be accountable, transparent and free of bias—not just super-fast task rabbits. Only then will such systems reach their full potential.

Artificial Intelligence (AI)

Article: “Powerful computer vision algorithms are now small enough to run on your phone” - ” - https://www.technologyreview.com

Visual recognition is deep learning’s strongest skill. Computer vision algorithms are analyzing medical images, enabling self-driving cars, and powering face recognition. But training models to recognize actions in videos has grown increasingly expensive. This has fueled concerns about the technology’s carbon footprint and its increasing inaccessibility in low-resource environments.

Researchers at the MIT-IBM Watson AI Lab have now developed a new technique for training video recognition models on a phone or other device with very limited processing capacity. Typically, an algorithm will process video by splitting it up into image frames and running recognition algorithms on each of them. It then pieces together the actions shown in the video by seeing how the objects change over subsequent frames. The method requires the algorithm to “remember” what it has seen in each frame and the order in which it has seen it. This is unnecessarily inefficient.

In the new approach, the algorithm instead extracts basic sketches of the objects in each frame, and overlays them on top of one another. Rather than remember what happened when, the algorithm can get an impression of the passing of time by looking at how the objects shift through space in the sketches. In testing, the researchers found that the new approach trained video recognition models three times faster than the state of the art. It was also able to quickly classify hand gestures with a small computer and camera running only on enough energy to power a bike light.

The new technique could help reduce lag and computation costs in existing commercial applications of computer vision. It could, for example, make self-driving cars safer by speeding up their reaction to incoming visual information. The technique could also unlock new applications that previously weren’t possible, such as by enabling phones to help diagnose patients or analyze medical images.

Autonomous Vehicles

Article: “Waymo to customers: ‘Completely driverless Waymo cars are on the way’

- www.techcrunch.com

Waymo, the autonomous vehicle business under Alphabet, sent an email to customers of its ride-hailing app that their next trip might not have a human safety driver behind the wheel.

Both the early rider program and Waymo One service use self-driving Chrysler Pacifica minivans to shuttle Phoenix residents in a geofenced area that covers several suburbs, including Chandler and Tempe. All of these “self-driving rides” have a human safety driver behind the wheel.

A driverless ride is what it sounds like. No safety driver behind the wheel, although a Waymo employee would likely be present in the vehicle initially.

Waymo, formerly known as the Google self-driving project, first began testing its technology in 2009 in and around its Mountain View, Calif., headquarters. It’s been a slow and steady roll ever since. The company has expanded its test area to other cities, spun out into its own business and iterated the vehicle design and the sensors around it.

Waymo opened a testing and operations center in Chandler, Ariz. in 2016. Since then, the company has ramped up its testing in Chandler and other Phoenix suburbs, launched an early rider program and slowly crept toward commercial deployment. The early rider program, which required vetted applicants to sign non-disclosure agreements to participate, launched in April 2017.

In December, the company launched Waymo One, a commercial self-driving car service and accompanying app. Waymo One signaled that the company was starting to open up its service. Members of the early rider program were transferred to Waymo One, which allowed them to bring guests and even talk publicly about their rides. More recently, Waymo opened another technical service center in the Phoenix area in preparation to double its capacity and grow its commercial fleet.

While driverless Waymo vehicles have been spotted periodically, they have never been used to shuttle the general public. The introduction of driverless vehicles would be milestone for the company.


Article: “A Revolutionary Blockchain Solution for Cross-Border Business” - www.prnewswire.com

This article talks about the cryptocurrency created for the organisation that I am a member – OpenExO.

Currently, the OpenExO community has 2,291 exponential growth specialists across 101 countries. These innovators help clients leverage emerging technologies and exponential attributes to emulate the world's fastest-growing companies.

OpenExO is like the sharing economy; it operates in a massive global cooperative to achieve a common goal and transform the world for a better future. Open ExO leverages their community of on-demand specialists to help companies prosper around the globe; however, ExO does not directly employ these specialists. Instead, OpenExO helps clients connect to specialists within the ExO community and economy.

For example, someone in Medellín working on a drone project might need a drone guru who might be in Switzerland. However, sending a payment from Columbia to Switzerland can be a nightmare when it comes to transaction fees and settlement time.

That is why the ExO team decided to implement a stand-alone public blockchain and its own cryptographic token, EXOS. EXOS are a tool that helps facilitate the exchange of services throughout the network and reduce friction--especially when it comes to cross-border payments. As a Proof-of-Stake blockchain, the community members actually run the blockchain economy's infrastructure on behalf of the network.

When the individual in Medellín goes to contract the individual in Switzerland for their drone project, The EXOS token allows the individual in Medellín to retain the drone expert directly with tokens. This eliminates the need for a financial intermediary and the expensive fees that are known to come with that service. The ExO Economy also allows these individuals to easily find each other and contract for their services as well as operate freely with very little transactional and cross-border friction.

By using the EXOS blockchain to reduce friction in payments—especially when it comes to cross-border transactions and cross-border talent acquisition—the ExO economy allows individuals globally to connect and catalyze exponential growth in their organizations.


Article: “The wheels may be coming off Facebook’s digital currency project Libra” – www.technologyreview.com

Facebook’s digital currency plans took a major hit today as Visa, Mastercard, eBay, and Stripe have followed PayPal’s example and backed out of the nonprofit Facebook set up to manage the currency.

When Facebook unveiled its plans in June for the currency it calls Libra, it also revealed that 27 other firms—including big names like Visa, Mastercard, PayPal, Uber, and Spotify—had signed on to participate in the Libra Association, a Switzerland-based nonprofit Facebook has set up to develop and maintain the currency. The company said it would have 100 members on the list by the time of Libra’s launch, which is still planned for next year.

But last week, after rumors surfaced that some members were considering backing out, PayPal became the first to announce its departure. Now it’s beginning to look like a mass exodus.

The proposal for Libra has received a chilly reception from policymakers and central bankers around the world, which may be contributing to the departures.

The Libra Association’s founding members (what remains of them) are scheduled to meet on October 14 in Geneva, Switzerland, where the group will review a charter and appoint a board of directors, according to the Wall Street Journal. And Facebook CEO Mark Zuckerberg is scheduled to testify about Libra in front of the House Financial Services Committee on October 23.

Drone Technology

Article: “China's stealth drones and hypersonic missiles surpass — and threaten — the U.S.” - www.nbcnews.com

The celebration of the 70th anniversary of the founding of the People’s Republic of China at the beginning of this month promised plenty of pomp and power projection. In the days leading up to the grandiose parade through Beijing’s Tiananmen Square, Chinese citizens began sharing photos of tarp-covered vehicles and missiles being rolled into Beijing for a rehearsal.

The event Oct. 1 didn’t disappoint. The People’s Liberation Army unveiled brand new high-tech drones, robot submarines and hypersonic missiles — none of which have an equivalent in operational service elsewhere on the planet.

Despite starting technologically well behind the United States, China has developed new s