11 min read

My follow-up to “It is time…”

By Peter H. Diamandis on Jun 10, 2020

Last week I wrote a blog titled “It is time…” expressing my personal views (and that of my team) on the topic of social justice and anti-racism. 

Topics: social responsibility black lives matter human rights racism social justice unity
8 min read

Abundance Insider: December 21st, 2019

By Peter H. Diamandis on Dec 21, 2019

In this week's Abundance Insider: AI-induced super resolution, robotic safety inspectors, and Lamborghini’s inroads in 3D printing.

P.S. Send any tips to our team by clicking here, and send your friends and family to this link to subscribe to Abundance Insider.

P.P.S. Want to learn more about exponential technologies and home in on your MTP/ Moonshot? Abundance Digital, a Singularity University Program, includes 100+ hours of coursework and video archives for entrepreneurs like you. Keep up to date on exponential news and get feedback on your boldest ideas from an experienced, supportive community. Click here to learn more and sign up.

P.P.P.S. Want a chance to read Peter’s upcoming book before anyone else? Join the Future is Faster Than You Think launch team (applications close on December 6th)! Get an advanced digital copy, access to our private Facebook group, behind the scenes specials, a live Q&A with Peter and Steven, and hundreds of dollars in exclusive bonuses. Click here for details.

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It’s Not You. Clothing Sizes Are Broken.

What it is: Size and fit are two of the leading reasons for online returns, according to e-commerce software company Narvar Inc., translating to costs that further reduce retailers’ already slim profit margins. From 3D body-scanning apps like MTailer and My Size, to startup Shima Seiki’s machines that knit garments with less than 1% variation, a plethora of companies has recently emerged to combat the issue of inconsistent sizing. Women’s sizes in the U.S. range from 00 to 18, yet there are no standardized body metrics across these sizes. This type of variation is not represented in online sizing guides, and few explain the stretch or texture of the fabric, which may also affect fit. Solutions like those offered by True Fit Corp.—which uses a data platform and AI-driven personalized recommendation engine to help consumers find their right size and taste-tailored items—are growing in demand from major retailers. Others, like RedThread, use 3D mobile body scanning and tailoring algorithms to best determine fit.

Why it’s important: Some executives, like Levi Strauss & Co.’s CEO Chip Bergh, believe sizes will become obsolete in the next decade. Smartphone-conducted body scans will offer precise measurements that automatically populate online retail platforms. From there, fits can be matched with existing designs or tailored with programmed sewing machines. Offering an even more personalized fit, 3D-printed garments are also on the rise, changing the economics of mass manufacturing. As retail sales continue to migrate to online platforms, virtual try-on software is slated to decimate returns—now a major pain point for both the retailer and the consumer. Yet the convergence of these technologies will not only cut costs, but will also dramatically reduce the environmental toll of shipping, packaging, and textile waste.

AI super resolution lets you “zoom and enhance” in Pixelmator Pro.

What it is: For just $60, Pixelmator is making the “zoom and enhance” trope seen in movies (the ability to zoom into images and retain sharpness) a reality. Using AI algorithms, Pixelmator’s “ML Super Resolution” is a novel function that allows users to scale an image up to 3X its original resolution without pixelation or blurriness. Similar to Google’s and Nvidia’s algorithms, Pixelmator’s software is trained on a dataset containing pairs of low-resolution and high-resolution images and thereby generates rules for how the pixels change from image to image. Pixelmator, however, is about 50 times smaller (than its Google and Nvidia counterparts) at just 5MB, which is lightweight enough to run on a device and needs merely 15,000 sample images to create the tool.

Why it’s important: In just the past 12 months, we’ve seen an explosion in AI and machine learning tool sets newly democratized for accessible consumer use. Yet many have required significant computing resources for top performance. Now, however, products like Pixelmator’s “ML Super Resolution” have achieved powerful algorithms trained on significantly lighter data sets that require far less memory and power. Particularly in the art and imaging realm, the availability of such algorithms to end users will lower the barrier for artists, filmmakers, and small firms in everything from design to marketing.

Lamborghini places emphasis on additive manufacturing, extends partnership with Carbon.

What it is: 3D printing company Carbon has just expanded its partnership with Lamborghini. Famous for its Digital Light Synthesis (DLS) technology—which prints components using a photochemical process leveraging oxygen and light—Carbon plans to use DLS to manufacture the dashboard air vents for Lamborghini’s first hybrid production car, the Sián FKP 37. This development follows Carbon’s earlier work in partnership with the car maker, whereby it produced textured fuel caps and air duct clips for the Urus Super Vehicles. Successful in reducing Lamborghini’s production time to just 12 weeks, Carbon’s DLS can produce geometric shapes that are extraordinarily difficult to mold using traditional processes, which often include multiple iterations on the design.

Why it’s important: 3D printing is transforming the manufacturing industry (literally) from the bottom-up, whether in production of minute, customized and complex automotive parts to rocket engine parts and organ tissues. We’re rapidly entering an era of programmable production, allowing for far cheaper, more versatile, and quickly prototyped goods. As 3D printing technologies move from deceptive to disruptive, what potential uses might you experiment with in your own business?

Building robotic safety inspectors nabs Gecko Robotics $40 million.

What it is: Pittsburgh-based Gecko Robotics has just landed US$40 million in additional financing, which it will use to add an additional 40 robots to its 60-bot fleet, helping meet demand for the company’s safety and infrastructure monitoring services. Gecko’s wall-climbing robots perform non-destructive testing on industrial machinery like tanks and boilers, assessing metrics like wall thickness, cracking, and pitting. Gecko’s robots can even predictively detect other issues likely to result in downtime or more serious hazards, such as explosions and emissions leaks.

Why it’s important: While much of today’s public debate on robotics centers around the replacement of human labor, one emerging phenomenon in the industry involves preventative, automated approaches to safety and compliance use cases. In many of these cases, robotics and software services like that of Gecko are augmenting human experts’ capabilities by granting them new data, which would otherwise be extremely difficult or hazardous to collect manually. Increasingly a collaborator for human practitioners, robotics and AI are beginning to tackle industrial monitoring tasks that have never before been possible, preventing infrastructural and machinery damage before it occurs.

How artificial intelligence is making health care more human.

What it is: MIT Technology Review Insights, in association with GE Healthcare, recently released survey results of over 900 healthcare professionals, revealing the ways in which AI is already being used in healthcare. Nearly 80% of respondents are set to increase their budgets on AI applications in 2020. And today, the key areas in which AI is already being deployed include: (1) AI for patient flow optimization; (2) medical imaging and diagnostics; (3) automation of electronic health records via natural language processing tools; (4) AI for predictive analytics; and (5) patient data and risk  analytics. In terms of outcomes, 78% of medical staffers report that AI deployments have already improved workflows, reducing time spent on mundane administrative tasks and thus unlocking more time for procedures and patient interactions. Even more importantly, AI is reducing clinical errors, and 75% of AI-using medical staff agree that the technology has bettered predictions in disease treatment.

Why it’s important: AI is transforming the healthcare system as we know it, touching everything from diagnostics to drug discovery. In the wake of “smart” patient scheduling tools, even the number of patients seen by doctors per day has been maximized. And AI is even helping optimize outcomes of the appointments themselves. Medical professionals typically spend 10% of their workweek taking notes or updating electronic health records. As AI begins to systematize these repetitive tasks, doctors are freed to dedicate more time to procedures and patient relations. Applying AI algorithms to medical imaging has also already improved clinical decision-making. For reference, surveyed doctors who have yet to adopt AI report clinical error as their key challenge two-thirds of the time (more than double the figure for those who have adopted AI tools). Moving forward, doctors and healthcare workers must continue to collaborate with machines, leveraging comprehensive pools of AI-mediated data to make important medical decisions. An invaluable new collaborator, AI is helping doctors and clinicians focus on what they do best, helping humanize the healthcare industry and improve the patient experience.

Want more conversations like this?

Abundance 360 is a curated global community of 360 entrepreneurs, executives, and investors committed to understanding and leveraging exponential technologies to transform their businesses. A 3-day mastermind at the start of each year gives members information, insights and implementation tools to learn what technologies are going from deceptive to disruptive and are converging to create new business opportunities. To learn more and apply, visit A360.com.

Abundance Digital, a Singularity University program, is an online educational portal and community of abundance-minded entrepreneurs. You’ll find weekly video updates from Peter, a curated news feed of exponential news, and a place to share your bold ideas. Click here to learn more and sign up.

Know someone who would benefit from getting Abundance Insider? Send them to this link to sign up.

(*Both Abundance 360 and Abundance Digital are Singularity University programs.)

Topics: Abundance Insider AR/VR AI machine learning Artificial Intellegence Batteries solar energy drone technology social responsibility
8 min read

Abundance Insider: December 13th, 2019

By Peter H. Diamandis on Dec 13, 2019

In this week's Abundance Insider: Coca-Cola’s autonomous truck pilot, a new approach to computer vision, and the mysterious ‘X17 particle.’

P.S. Send any tips to our team by clicking here, and send your friends and family to this link to subscribe to Abundance Insider.

P.P.S. Want to learn more about exponential technologies and home in on your MTP/ Moonshot? Abundance Digital, a Singularity University Program, includes 100+ hours of coursework and video archives for entrepreneurs like you. Keep up to date on exponential news and get feedback on your boldest ideas from an experienced, supportive community. Click here to learn more and sign up.

P.P.P.S. Want a chance to read Peter’s upcoming book before anyone else? Join the Future is Faster Than You Think launch team (applications close on December 6th)! Get an advanced digital copy, access to our private Facebook group, behind the scenes specials, a live Q&A with Peter and Steven, and hundreds of dollars in exclusive bonuses. Click here for details.

Share Abundance Insider on LinkedIn | Facebook | Twitter.

High-Tech Planes, Supercomputers and Helitankers Help Fight Wildfires.

What it is: Firefighters are increasingly adopting sophisticated technologies in the fight against blazes. Fire departments across Southern California have now partnered with Dr. llkay Altintas, head of the WIFIRE Lab and the San Diego Supercomputer Center (part of UCSD). WIFIRE combines weather data, topography, and information about the dryness of brush to model in near-real time how a wildfire might spread and at what speeds. This, in turn, helps local leaders create evacuation plans and determine where departments might deploy fire crews. Until recently, mapping fires has been a laborious, hard-drawn process that often requires as much as a day of work. Yet armed with far more accurate data, firefighters and partners such as Coulson Aviation are now using military-grade night-vision goggles to operate at night, when winds often die down and give teams an advantage over the fire. The night vision goggles allow teams to determine key geographic targets as well as hover for water refills without having to land their helitankers.

Why it’s important: As the cost of computing power plummets, converging technologies are beginning to aid in disaster relief at price tags now affordable for budget-strapped state and local governments. While AI grants fire departments far more predictive capacity and higher mapping speeds, its hardware counterparts (whether drones, sensors, or the like) are finding their way into other realms of disaster relief, and even disaster prevention.

Coca-Cola test-drives Einride’s autonomous truck in Sweden.

What it is: Coca-Cola European Partners (CCEP) will soon release a fleet of Einride autonomous electric transport vehicles onto the streets of Jordbro, Sweden. Founded in 2016, Einride has produced sleek “T-Pod” electric propulsion trucks that do not require a driver, though there are still remote drivers who can take control if needed. Currently, the T-Pods carry 200kWh batteries that allow for 124 miles of travel between charges. The fleet will transport goods from two warehouses, operated by CCEP and leading food retailer Axfood, just outside of Stockholm. Some will remain in fenced regions while others will interact on public roads.

Why it’s important: Road freight transport contributes about 7 percent of global carbon dioxide emissions each year. CCEP aims to use these Einride vehicles to meet its sustainability and efficiency goals. The company projects it could cut its carbon dioxide emissions by up to 90 percent with these new vehicles. After a hoped-for success of this pilot test, the fleet could even potentially scale across the nation of Sweden, throughout which CCEP distributes Coca-Cola products. Sustainable supply chains will grow increasingly important as consumers desire greater transparency in their purchasing decisions and place more emphasis on environmentally responsible goods.

Observe.ai raises $26 million for AI that monitors and coaches call center agents.

What it is: While numerous Software-as-a-service (SaaS) platforms are beginning to disrupt the customer service realm, some SaaS products are designed to augment human customer care workers. One example involves U.S.-Indian startup and Y Combinator alum Observe.ai, which just announced a $26 million series A funding round. Observe.ai uses natural language processing (NLP) to analyze conversations between human agents and customers. After transcribing each call, Observe’s platform runs sentiment analysis, draws correlations between the support agent’s verbal and behavioral data and the customer’s happiness level, and then ultimately determines overall customer satisfaction. This data is then used to benchmark top performers and find best practices across teams. Results can even be applied to other discrete use cases, such as monitoring compliance in the healthcare industry, where conversations involve sensitive and often legally protected information.

Why it’s important: Observe and a number of other companies—NICE, Verint, Cogito, Gong, Chorus.ai, among others—make up a growing number of companies using AI improve the connection between humans, as opposed to replacing it outright. While many fear the encroachment of AI and automation on our contemporary job market, in what areas might we flip this concern? How might we leverage AIs to help augment our social and professional skills, provide a better service, or gain common ground with our clients?

Machine vision that sees things more the way we do is easier for us to understand.

What it is: Researchers have devised a new method for training neural networks in image recognition. Rather than training their model on full images of birds, scientists from Duke University and MIT’s Lincoln Laboratory trained a network specifically on features of birds: beak shape, head shape, feather coloration and the like. When the algorithm is then presented with a new picture of a bird, it searches for specific features, generates predictions about the bird’s species, and uses the cumulative evidence to come to a final conclusion.

Why it’s important: Recently, the push to make neural networks more explainable and transparent has gained significant traction in both the private sector and academia. Especially in the case of high-stakes applications—such as medical image recognition—AIs that can demonstrate which features contributed to its decision will help to solve the longstanding “black box” problem associated with today’s algorithms. By engineering neural networks to devise predictions in a manner more akin to our own human thought processes, AI engineers will also be able to more easily diagnose problems when networks make incorrect predictions.

A nanotube material conducts heat in just one direction.

What it is: Scientists at the University of Tokyo have now developed a method of synthesizing aligned carbon nanotubes. Normally, producing nanotubes in a bulk material results in poorly aligned configurations of individual tubes. Yet in order to take advantage of the thermal properties of the tube, it is necessary to align the tubes end-to-end. To achieve this, the researchers used a technique known as controlled vacuum filtration, a procedure whereby nanotubes are mixed with a liquid solution whose properties induce a natural self-organization of the tubes. The liquid is then carefully removed with a vacuum, leaving a thin sheet of highly-aligned nanotubes. This sheet has some extraordinary properties: perhaps most importantly, it has one-way thermal conductivity. This means that the sheet can conduct heat about 1,000 times more efficiently in the direction of the alignment than perpendicular to the alignment.

Why it’s important: Heat leakage is a tremendous problem for electrical engineers and circuit designers. This one-way thermal conduction material could serve as a game-changing solution, as it mitigates the need for large cooling systems and can interact at the nanoscale (the size of modern-day transistors). Needless to say, more efficient cooling systems will open tremendous new possibilities in design for computer hardware engineers.

Mysterious ‘Particle X17’ Could Carry a Newfound Fifth Force of Nature, But Most Experts Are Skeptical.

What it is: Four fundamental forces—gravity, electromagnetism, the strong force, and the weak force—govern the universe as we know it. Yet the reported discovery of a particle dubbed X17 could add a fifth force to this list. Researchers at the Institute of Nuclear Research in Hungary first reported evidence of the particle in 2016, when they noticed radioactive beryllium atoms releasing pairs of electrons and their antimatter counterparts (positrons) at specific angles. Based on this evidence, the team concluded that there must be an intermediary “particle X” that the beryllium atom converts into before emitting the electron-positron pairs. With a mass of 17 megaelectronvolts, the particle earned its name X17. More recently, the team even detected a similar X17 particle of the same mass in the radioactive decay of helium. While most matter is made up of fermion particles, the X17 particle is considered a boson, meaning it carries energy and sometimes forces.

Why it’s important: Studying the X17 boson-type particle could unlock important insights into the nature of dark matter and potentially even a fifth force. Dark matter constitutes 85 percent of matter in the universe, yet is only detectable through gravity and does not react to light. The globally held Standard Model of particle physics could be revolutionized by this finding. Most research in the past fifty years has relied heavily on high-energy accelerators to collide particles at rapid speeds, but this team’s work offers a lower-cost alternative to understanding our universe. While findings have not yet been peer-reviewed, several groups are working to verify the Hungarian research institute’s work, driving progress towards a more accurate understanding of the matter that makes up our universe.

Want more conversations like this?

Abundance 360 is a curated global community of 360 entrepreneurs, executives, and investors committed to understanding and leveraging exponential technologies to transform their businesses. A 3-day mastermind at the start of each year gives members information, insights and implementation tools to learn what technologies are going from deceptive to disruptive and are converging to create new business opportunities. To learn more and apply, visit A360.com.

Abundance Digital, a Singularity University program, is an online educational portal and community of abundance-minded entrepreneurs. You’ll find weekly video updates from Peter, a curated news feed of exponential news, and a place to share your bold ideas. Click here to learn more and sign up.

Know someone who would benefit from getting Abundance Insider? Send them to this link to sign up.

(*Both Abundance 360 and Abundance Digital are Singularity University programs.)

Topics: Abundance Insider AR/VR AI machine learning Artificial Intellegence Batteries solar energy drone technology social responsibility
8 min read

Abundance Insider: December 6th, 2019

By Peter H. Diamandis on Dec 6, 2019

In this week's Abundance Insider: DeepMind’s latest AI win, a promising treatment candidate for pancreatic cancer, and 5 emerging energy technologies.

P.S. Send any tips to our team by clicking here, and send your friends and family to this link to subscribe to Abundance Insider.

P.P.S. Want to learn more about exponential technologies and home in on your MTP/ Moonshot? Abundance Digital, a Singularity University Program, includes 100+ hours of coursework and video archives for entrepreneurs like you. Keep up to date on exponential news and get feedback on your boldest ideas from an experienced, supportive community. Click here to learn more and sign up.

P.P.P.S. Want a chance to read Peter’s upcoming book before anyone else? Join the Future is Faster Than You Think launch team (applications close on December 6th)! Get an advanced digital copy, access to our private Facebook group, behind the scenes specials, a live Q&A with Peter and Steven, and hundreds of dollars in exclusive bonuses. Click here for details.

Share Abundance Insider on LinkedIn | Facebook | Twitter.

Google DeepMind gamifies memory with its latest AI work.

What it is: If you’ve ever wished you could go back in time to tell your younger self a critical piece of advice, AIs may soon be able to do just that within their own networks. Google’s DeepMind unit recently announced a program that resembles the human capacity to mentally time travel by incorporating long-term consequences into machine learning. AI programs typically rely on reinforcement learning with short-term, immediate “rewards.” DeepMind’s new program, called Temporal Value Transport (TVT), transforms reinforcement learning by sending reward signals backwards from far in the future as an alternative form of neural networks. The program operates in simulated worlds, and it might “explore” a path to a certain target. If the program uses its memory of this path in a future pursuit to the same target, it is rewarded. This process, termed the “Reconstructive Memory Agent,” marks the first time memories of past events have been “encoded.”

Why it’s important: Many sociologists and economists have explored the realm of long-term human decision-making. While DeepMind’s TVT is not entirely representative of human thought, the cognitive mechanisms of the program could greatly impact human thought processes. We easily learn to avoid hot stoves after accidentally burning our hand once. Yet many of us fall into the long-term pattern of following an unfulfilling career path. Because long-term decisions lack immediate feedback, the signs pointing us in the “right direction” are difficult to detect and learn from early on. With the help of AIs that generate future pathways and then inform us of consequences in the present, humans could learn in entirely new ways. From investment decisions to government policy, wisdom from the future will undoubtedly aid our present choices.entertainment, and human interaction.

Jet-powered VTOL drone is like a quadcopter on steroids.

What it is: Texas-based FusionFlight has just invented a jet-powered drone capable of vertical take-off and landing operations. Yet rather than using propellers and electric motors like traditional drones, this drone ups the ante, using four diesel-powered microturbine jet engines and a proprietary vectoring system. Known as the H-Configuration, this latter component enables the drone to direct its engines’ thrust either vertically (for take-off and landing) or horizontally (while in flight). Reportedly capable of reaching a top speed of over 300 mph, the aircraft’s final production version includes a fuel tank sufficient for 30 minutes of hovering and 15 minutes of cruising. Down the line, FusionFlight aims to boost speed and performance with afterburners and other components.

Why it’s important: Drones are rapidly permeating our airspace. They are now used for crop monitoring, military combat, delivery services, and viral YouTube videos. FusionFlight’s newest iteration expands the range of possibilities for drones, especially in the case of time-sensitive tasks, where speed is key. Furthermore, enabled by its jets’ production of a combined 200 horsepower, the drone can carry up to 40 pounds of cargo, making it an ideal candidate for shipping and delivery applications.

Israeli scientists find a way to treat deadly pancreatic cancer in 14 days.

What it is: After just two weeks of daily injections, a new treatment reduced the number of cancerous pancreatic cells in mice by up to 90 percent. Led by Professor Malka Cohen-Armonat at Tel Aviv University, the team used a molecule called PJ34, one originally developed to treat stroke patients. After implanting human pancreatic cancer into immune-suppressed mice, the team intravenously injected the PJ34 treatment for fourteen days. During the cell replication process known as mitosis, the PJ34 molecule causes an anomaly that triggers the cell to self-destruct. In cancer cells that are duplicating uncontrollably, this type of stop signal is critical to controlling the tumor. Only 30 days after the treatment ended, an 80-90 percent reduction in cancer cells was observed, accompanied by zero negative impacts to healthy cells.

Why it’s important: Pancreatic cancer is one of the most difficult cancers to treat, and few patients survive more than five years after diagnosis. Today, most treatment options involve chemotherapy, a systemic approach aimed at halting cell division in the entire body. Yet because this form of therapy lacks discriminatory targeting, cell replication slows across the entire body, causing many patients to experience negative side effects like hair loss, inflammation of the digestive tract, and decreased blood cell production. A solution like PJ34, which specifically targets only cancer cells, could revolutionize cancer therapy and significantly enhance patient quality of life. Venturing beyond pancreatic cancer, the team even successfully tested the treatment on cell cultures of aggressive forms of breast, lung, brain and ovarian cancer. According to the team, this treatment is about two years away from human trials, potentially promising a major boost to healthy human lifespans.

5 Emerging Energy Technologies to Watch Out For in 2020.

The story: This year, technologies in solar, wind, and battery storage have achieved remarkable economies of scale and now compete almost at parity with fossil fuels. In the coming year, breakthrough after breakthrough may finally usher in a watershed moment for the energy sector, and experts recommend keeping an eye on several key areas.

What to watch: (1) Floating solar arrays have surged in popularity for use on freshwater bodies, but photovoltaic solar panels are now moving to the open ocean. (2) Static compressors, which help to maintain the constant frequency of electric power grids, are starting to see an uptick in certain countries and should help with overall incorporation of renewables into the power grid. (3) Several companies are now working to increase the power capacity of dynamic export cables. These are critical to bringing power from offshore floating wind turbines (as opposed to static turbines fixed to the seafloor) back to shore. (4) Now backed by significant funding, molten salt reactors are a new form of nuclear power that promise to emit less radiation than traditional nuclear. (5) Renewably produced hydrogen has witnessed considerable growth in at least 10 countries, with projected utility in everything from industrial heating and cooling to the integration of renewables into the grid. As plummeting renewable energy costs and improved grid storage propel us into 2020, we may soon expect dramatic shifts in the global energy economy.

SLAC scientists invent a way to see attosecond electron motions with an X-ray laser.

What it is: Researchers at Stanford University have developed a method to measure electrons at an unfathomable timescale: 280 attoseconds, to be precise. For reference, an attosecond is to a second what a second is to roughly 31.71 billion years, longer than the age of the universe. To achieve this, the researchers developed a procedure involving X-ray bursts generated by fast-moving electron bursts. To see at smaller and smaller timescales, scientists needed to create shorter and more intense bursts. These bursts, in turn, create the requisite intense and fast X-rays when they are passed through a magnet. Ultimately, the Stanford scientists were able to develop a more capable beam using a technique called XLEAP, first proposed about 14 years ago but now finally coming to fruition.

Why it’s important: This is a tremendous boost for ultrafast science. “Until now, we could precisely observe the motions of atomic nuclei, but the much faster electron motions that actually drive chemical reactions were blurred out,” explained SLAC scientist James Cryan, one of the paper’s lead authors and an investigator with the Stanford PULSE Institute (a joint institute of SLAC and Stanford University). “With this advance, we’ll be able to use an X-ray laser to see how electrons move around and how that sets the stage for the chemistry that follows. It pushes the frontiers of ultrafast science.” What does this mean? Now capable of observing at infinitesimal scales, we may soon probe some of the world’s most fundamental mysteries, particularly in photosynthesis and biochemistry.

Want more conversations like this?

Abundance 360 is a curated global community of 360 entrepreneurs, executives, and investors committed to understanding and leveraging exponential technologies to transform their businesses. A 3-day mastermind at the start of each year gives members information, insights and implementation tools to learn what technologies are going from deceptive to disruptive and are converging to create new business opportunities. To learn more and apply, visit A360.com.

Abundance Digital, a Singularity University program, is an online educational portal and community of abundance-minded entrepreneurs. You’ll find weekly video updates from Peter, a curated news feed of exponential news, and a place to share your bold ideas. Click here to learn more and sign up.

The Future is Faster Than You Think: Want a chance to read my new book before anyone else? Join the Future is Faster Than You Think launch team (applications close on December 6th)! Get an advanced digital copy, access to our private Facebook group, behind the scenes specials, a live Q&A with Steven and me, and hundreds of dollars in exclusive bonuses. Click here for details.

Know someone who would benefit from getting Abundance Insider? Send them to this link to sign up.

(*Both Abundance 360 and Abundance Digital are Singularity University programs.)

Topics: Abundance Insider AR/VR AI machine learning Artificial Intellegence Batteries solar energy drone technology social responsibility
7 min read

Abundance Insider: November 29th, 2019

By Peter H. Diamandis on Nov 29, 2019

In this week's Abundance Insider: New haptic device for VR, socially aware algorithms, and NASA’s supermassive black hole finding.

P.S. Send any tips to our team by clicking here, and send your friends and family to this link to subscribe to Abundance Insider.

P.P.S. Want to learn more about exponential technologies and home in on your MTP/ Moonshot? Abundance Digital, a Singularity University Program, includes 100+ hours of coursework and video archives for entrepreneurs like you. Keep up to date on exponential news and get feedback on your boldest ideas from an experienced, supportive community. Click here to learn more and sign up.

P.P.P.S. Want a chance to read Peter’s upcoming book before anyone else? Join the Future is Faster Than You Think launch team (applications close on December 6th)! Get an advanced digital copy, access to our private Facebook group, behind the scenes specials, a live Q&A with Peter and Steven, and hundreds of dollars in exclusive bonuses. Click here for details.

Share Abundance Insider on LinkedIn | Facebook | Twitter.

New virtual reality interface enables “touch” across long distances.

What it is: A Northwestern University team has created a lightweight wearable patch that vibrates when activated by another user’s touch— from miles away. Using this technology, a mother was able to remotely “pat” her son on the back while video chatting him. As she touched a screen interface, this data was communicated through a haptic device on her son’s back, stimulating identical touch patterns. Most of today’s haptic feedback devices rely on batteries, requiring bulky containers that cannot fit snugly against the skin. By contrast, this new patch consists of a vibrating disk—only a few millimeters thick—that is powered by near-field communication, a wireless power transfer typically used in ID card locks. External silicone sheets protect the two inner layers of the device: one containing the near-field communication technology to power the device, and another holding miniature actuators that simulate various degrees of touch pressure. Led by physical chemist and materials scientist John A. Rogers, the team now aims to make the patch more flexible and lightweight before commercializing the device through their newly established startup.

Why it’s important: While today’s audiovisual interfaces have long captured our eyes and ears, incorporating the dimension of touch into our devices will add another layer of immersion in tomorrow’s digitally augmented world. For VR and AR devices, this haptic technology could transform virtual simulations into tactile physical environments—without any real materials. The Northwestern team’s device currently conveys only perpendicular pressure against the skin, but eventually the patch may be able to simulate even twisting motions or temperature changes. The technology will also likely expand beyond simple patches into full body suits, capable of translating touch interactions between individuals, or between game worlds and reality. The ability to see, hear, and feel in a digital simulation will drastically disrupt travel, entertainment, and human interaction.

New Amazon capabilities put machine learning in reach of more developers.

What it is: Amazon has just announced a new approach that will make machine learning models more accessible to both developers and business users. By taking advantage of tools like Amazon QuickSight, Aurora and Athena, anyone who can write in basic SQL can now make and use predictions in one’s applications without having to generate custom code. To make the process even easier, these machine learning models themselves can come pre-built from Amazon Web Services (AWS), be developed by an in-house data science team, or purchased in AWS’s ML marketplace.

Why it’s important: As explained by AWS cloud and open source executive Matt Asay, “there is often a large amount of fiddly, manual work required to take these predictions and make them part of a broader application, process or analytics dashboard.” Amazon’s initiative marks a significant step towards machine learning’s User Interface moment, removing friction and making AI’s predictive power more accessible to a large set of users. Keep on the lookout for a surge in easy-to-build applications and experiments as sophisticated Software as a Service (SaaS) products hit the marketplace.

Socially aware algorithms are ready to help.

What it is: In light of growing concern about AI’s obscure inner workings, software engineers and data scientists responsible for many of the algorithms involved in our everyday online activity have increasingly used more socially aware algorithmic structures. For instance, data scientists now use a technique known as “differential privacy” to add random “noise” to data sets, preserving the overall structure whilst obscuring individual data. This, in turn, helps to anonymize our data and thereby protect user privacy. Other techniques include the addition of fairness criteria, such that predictive models’ output—from creditworthiness to insurance-related decisions—minimize bias where possible.

Why it’s important: As machine learning algorithms are granted greater responsibility over socially consequential decisions (think: our ability to take out loans or a legal decision to grant bail), problems of privacy, bias, disinformation, filter bubbles, and transparency abound. As a result, AI engineers have begun working on algorithms’ ability to explain their decisions, overcoming their status as mysterious “black boxes.” Meanwhile, the above fairness conditions are a promising start in our pursuit to build equitable, unbiased, and evidence-based algorithms: predictive models that prove accurate without perpetuating “fake news,” racial inequalities, and a slew of other social challenges. Differential privacy, fairness conditions, and similar tweaks do result in some costs to algorithmic “utility” and error rate in the short-term. However, such initiatives will be essential for a future wherein machine learning helps safeguard equitable, systemic decision-making and privacy, while protecting against some of today’s worst institutional tendencies.

NASA finds supermassive black hole birthing stars at “furious rate.”

What it is: Scientists have now discovered a supermassive blackhole at the center of a distant galaxy cluster “furiously” birthing stars at a rate about 500 times that of the Milky Way Galaxy. Using data from the Hubble Space Telescope and NASA’s Chandra X-Ray Observatory, the team of astronomers was able to observe the equivalent of trillions of Suns’ worth of hot gas cooling around the black hole within the Phoenix Cluster, some 5.8 billion light years away.

Why it’s important: Typically, the supermassive blackholes at the center of galaxy clusters are too active for star formation. They usually blow powerful streams of gas around the region, heating up interstellar hydrogen and preventing the gas from cooling down enough to trigger the creation of new stars. However, as this blackhole in the Phoenix Cluster is smaller than others, its jets are not as powerful, allowing for prolific star formation. From a scientific perspective, observations like this enable us to better understand and characterize the lifecycle of galaxy clusters and the role that blackholes play in both preclusion and creation of new stars.

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