Tag Archives: effects

#439066 Video Friday: Festo’s BionicSwift

Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We’ll also be posting a weekly calendar of upcoming robotics events for the next few months; here's what we have so far (send us your events!):

RoboSoft 2021 – April 12-16, 2021 – [Online Conference]
ICRA 2021 – May 30-5, 2021 – Xi'an, China
DARPA SubT Finals – September 21-23, 2021 – Louisville, KY, USA
WeRobot 2021 – September 23-25, 2021 – Coral Gables, FL, USA
Let us know if you have suggestions for next week, and enjoy today's videos.

Festo's Bionic Learning Network for 2021 presents a flock of BionicSwifts.

To execute the flight maneuvers as true to life as possible, the wings are modeled on the plumage of birds. The individual lamellae are made of an ultralight, flexible but very robust foam and lie on top of each other like shingles. Connected to a carbon quill, they are attached to the actual hand and arm wings as in the natural model.

During the wing upstroke, the individual lamellae fan out so that air can flow through the wing. This means that the birds need less force to pull the wing up. During the downstroke, the lamellae close up so that the birds can generate more power to fly. Due to this close-to-nature replica of the wings, the BionicSwifts have a better flight profile than previous wing-beating drives.

[ Festo ]

While we've seen a wide variety of COVID-motivated disinfecting robots, they're usually using either ultraviolet light or a chemical fog. This isn't the way that humans clean—we wipe stuff down, which gets rid of surface dirt and disinfects at the same time. Fraunhofer has been working on a mobile manipulator that can clean in the same ways that we do.

It's quite the technical challenge, but it has the potential to be both more efficient and more effective.

[ Fraunhofer ]

In recent years, robots have gained artificial vision, touch, and even smell. “Researchers have been giving robots human-like perception,” says MIT Associate Professor Fadel Adib. In a new paper, Adib’s team is pushing the technology a step further. “We’re trying to give robots superhuman perception,” he says. The researchers have developed a robot that uses radio waves, which can pass through walls, to sense occluded objects. The robot, called RF-Grasp, combines this powerful sensing with more traditional computer vision to locate and grasp items that might otherwise be blocked from view.

[ MIT ]

Ingenuity is now scheduled to fly on April 11.

[ JPL ]

The legendary Zenta is back after a two year YouTube hiatus with “a kind of freaky furry hexapod bunny creature.”

[ Zenta ]

It is with great pride and excitement that the South Australia Police announce a new expansion to their kennel by introducing three new Police Dog (PD) recruits. These dogs have been purposely targeted to bring a whole new range of dog operational capabilities known as the ‘small area urban search and guided evacuation’ dogs. Police have been working closely with specialist vets and dog trainers to ascertain if the lightweight dogs could be transported safely by drones and released into hard-to-access areas where at the moment the larger PDs just simply cannot get in due to their size.

[ SA Police ]

SoftBank may not have Spot cheerleading robots for their baseball team anymore, but they've more than made up for it with a full century of Peppers. And one dude doing the robot.

[ SoftBank ]

MAB Robotics is a Polish company developing walking robots for inspection, and here's a prototype they've been working on.

[ MAB Robotics ]

Thanks Jakub!

DoraNose: Smell your way to a better tomorrow.

[ Dorabot ]

Our robots need to learn how to cope with their new neighbors, and we have just the solution for this, the egg detector! Using cutting-edge AI, it provides incredible precision in detecting a vast variety of eggs. We have deployed this new feature on Boston Dynamics Spot, one of our fleet's robots. It can now detect eggs with its cameras and avoid them on his autonomous missions.

[ Energy Robotics ]

When dropping a squishy robot from an airplane 1,000 feet up, make sure that you land as close to people's cars as you can.

Now do it from orbit!

[ Squishy Robotics ]

An autonomous robot that is able to physically guide humans through narrow and cluttered spaces could be a big boon to the visually-impaired. Most prior robotic guiding systems are based on wheeled platforms with large bases with actuated rigid guiding canes. The large bases and the actuated arms limit these prior approaches from operating in narrow and cluttered environments. We propose a method that introduces a quadrupedal robot with a leash to enable the robot-guiding-human system to change its intrinsic dimension (by letting the leash go slack) in order to fit into narrow spaces.

[ Hybrid Robotics ]

How to prove that your drone is waterproof.

[ UNL ]

Well this ought to be pretty good once it gets out of simulation.

[ Hybrid Robotics ]

MIDAS is Aurora’s AI-enabled, multi-rotor sUAV outfitted with optical sensors and a customized payload that can defeat multiple small UAVs per flight with low-collateral effects.

[ Aurora ]

The robots​ of the DFKI have the advantage of being able to reach extreme environments: they can be used for decontamination purposes in high-risk areas or inspect and maintain underwater​ structures, for which they are tested in the North Sea near Heligoland​.

[ DFKI ]

After years of trying, 60 Minutes cameras finally get a peek inside the workshop at Boston Dynamics, where robots move in ways once only thought possible in movies. Anderson Cooper reports.

[ 60 Minutes ]

In 2007, Noel Sharky stated that “we are sleepwalking into a brave new world where robots decide who, where and when to kill.” Since then thousands of AI and robotics researchers have joined his calls to regulate “killer robots.” But sometime this year, Turkey will deploy fully autonomous home-built kamikaze drones on its border with Syria. What are the ethical choices we need to consider? Will we end up in an episode of Black Mirror? Or is the UN listening to calls and starting the process of regulating this space? Prof. Toby Walsh will discuss this important issue, consider where we are at and where we need to go.

[ ICRA 2020 ]

In the second session of HAI's spring conference, artists and technologists discussed how technology can enhance creativity, reimagine meaning, and support racial and social justice. The conference, called “Intelligence Augmentation: AI Empowering People to Solve Global Challenges,” took place on 25 March 2021.

[ Stanford HAI ]

This spring 2021 GRASP SFI comes from Monroe Kennedy III at Stanford University, on “Considerations for Human-Robot Collaboration.”

The field of robotics has evolved over the past few decades. We’ve seen robots progress from the automation of repetitive tasks in manufacturing to the autonomy of mobilizing in unstructured environments to the cooperation of swarm robots that are centralized or decentralized. These abilities have required advances in robotic hardware, modeling, and artificial intelligence. The next frontier is robots collaborating in complex tasks with human teammates, in environments traditionally configured for humans. While solutions to this challenge must utilize all the advances of robotics, the human element adds a unique aspect that must be addressed. Collaborating with a human teammate means that the robot must have a contextual understanding of the task as well as all participant’s roles. We will discuss what constitutes an effective teammate and how we can capture this behavior in a robotic collaborator.

[ UPenn ] Continue reading

Posted in Human Robots

#439053 Bipedal Robots Are Learning To Move With ...

Most humans are bipeds, but even the best of us are really only bipeds until things get tricky. While our legs may be our primary mobility system, there are lots of situations in which we leverage our arms as well, either passively to keep balance or actively when we put out a hand to steady ourselves on a nearby object. And despite how unstable bipedal robots tend to be, using anything besides legs for mobility has been a challenge in both software and hardware, a significant limitation in highly unstructured environments.

Roboticists from TUM in Germany (with support from the German Research Foundation) have recently given their humanoid robot LOLA some major upgrades to make this kind of multi-contact locomotion possible. While it’s still in the early stages, it’s already some of the most human-like bipedal locomotion we’ve seen.

It’s certainly possible for bipedal robots to walk over challenging terrain without using limbs for support, but I’m sure you can think of lots of times where using your arms to assist with your own bipedal mobility was a requirement. It’s not a requirement because your leg strength or coordination or sense of balance is bad, necessarily. It’s just that sometimes, you might find yourself walking across something that’s highly unstable or in a situation where the consequences of a stumble are exceptionally high. And it may not even matter how much sensing you do beforehand, and how careful you are with your footstep planning: there are limits to how much you can know about your environment beforehand, and that can result in having a really bad time of it. This is why using multi-contact locomotion, whether it’s planned in advance or not, is a useful skill for humans, and should be for robots, too.

As the video notes (and props for being explicit up front about it), this isn’t yet fully autonomous behavior, with foot positions and arm contact points set by hand in advance. But it’s not much of a stretch to see how everything could be done autonomously, since one of the really hard parts (using multiple contact points to dynamically balance a moving robot) is being done onboard and in real time.

Getting LOLA to be able to do this required a major overhaul in hardware as well as software. And Philipp Seiwald, who works with LOLA at TUM, was able to tell us more about it.

IEEE Spectrum: Can you summarize the changes to LOLA’s hardware that are required for multi-contact locomotion?

Philipp Seiwald: The original version of LOLA has been designed for fast biped walking. Although it had two arms, they were not meant to get into contact with the environment but rather to compensate for the dynamic effects of the feet during fast walking. Also, the torso had a relatively simple design that was fine for its original purpose; however, it was not conceived to withstand the high loads coming from the hands during multi-contact maneuvers. Thus, we redesigned the complete upper body of LOLA from scratch. Starting from the pelvis, the strength and stiffness of the torso have been increased. We used the finite element method to optimize critical parts to obtain maximum strength at minimum weight. Moreover, we added additional degrees of freedom to the arms to increase the hands' reachable workspace. The kinematic topology of the arms, i.e., the arrangement of joints and link lengths, has been obtained from an optimization that takes typical multi-contact scenarios into account.

Why is this an important problem for bipedal humanoid robots?

Maintaining balance during locomotion can be considered the primary goal of legged robots. Naturally, this task is more challenging for bipeds when compared to robots with four or even more legs. Although current high-end prototypes show impressive progress, humanoid robots still do not have the robustness and versatility they need for most real-world applications. With our research, we try to contribute to this field and help to push the limits further. Recently, we showed our latest work on walking over uneven terrain without multi-contact support. Although the robustness is already high, there still exist scenarios, such as walking on loose objects, where the robot's stabilization fails when using only foot contacts. The use of additional hand-environment support during this (comparatively) fast walking allows a further significant increase in robustness, i.e., the robot's capability to compensate disturbances, modeling errors, or inaccurate sensor input. Besides stabilization on uneven terrain, multi-contact locomotion also enables more complex motions, e.g., stepping over a tall obstacle or toe-only contacts, as shown in our latest multi-contact video.

How can LOLA decide whether a surface is suitable for multi-contact locomotion?

LOLA’s visual perception system is currently developed by our project partners from the Chair for Computer Aided Medical Procedures & Augmented Reality at the TUM. This system relies on a novel semantic Simultaneous Localization and Mapping (SLAM) pipeline that can robustly extract the scene's semantic components (like floor, walls, and objects therein) by merging multiple observations from different viewpoints and by inferring therefrom the underlying scene graph. This provides a reliable estimate of which scene parts can be used to support the locomotion, based on the assumption that certain structural elements such as walls are fixed, while chairs, for example, are not.

Also, the team plans to develop a specific dataset with annotations further describing the attributes of the object (such as roughness of the surface or its softness) and that will be used to master multi-contact locomotion in even more complex scenes. As of today, the vision and navigation system is not finished yet; thus, in our latest video, we used pre-defined footholds and contact points for the hands. However, within our collaboration, we are working towards a fully integrated and autonomous system.

Is LOLA capable of both proactive and reactive multi-contact locomotion?

The software framework of LOLA has a hierarchical structure. On the highest level, the vision system generates an environment model and estimates the 6D-pose of the robot in the scene. The walking pattern generator then uses this information to plan a dynamically feasible future motion that will lead LOLA to a target position defined by the user. On a lower level, the stabilization module modifies this plan to compensate for model errors or any kind of disturbance and keep overall balance. So our approach currently focuses on proactive multi-contact locomotion. However, we also plan to work on a more reactive behavior such that additional hand support can also be triggered by an unexpected disturbance instead of being planned in advance.

What are some examples of unique capabilities that you are working towards with LOLA?

One of the main goals for the research with LOLA remains fast, autonomous, and robust locomotion on complex, uneven terrain. We aim to reach a walking speed similar to humans. Currently, LOLA can do multi-contact locomotion and cross uneven terrain at a speed of 1.8 km/h, which is comparably fast for a biped robot but still slow for a human. On flat ground, LOLA's high-end hardware allows it to walk at a relatively high maximum speed of 3.38 km/h.

Fully autonomous multi-contact locomotion for a life-sized humanoid robot is a tough task. As algorithms get more complex, computation time increases, which often results in offline motion planning methods. For LOLA, we restrict ourselves to gaited multi-contact locomotion, which means that we try to preserve the core characteristics of bipedal gait and use the arms only for assistance. This allows us to use simplified models of the robot which lead to very efficient algorithms running in real-time and fully onboard.

A long-term scientific goal with LOLA is to understand essential components and control policies of human walking. LOLA's leg kinematics is relatively similar to the human body. Together with scientists from kinesiology, we try to identify similarities and differences between observed human walking and LOLA’s “engineered” walking gait. We hope this research leads, on the one hand, to new ideas for the control of bipeds, and on the other hand, shows via experiments on bipeds if biomechanical models for the human gait are correctly understood. For a comparison of control policies on uneven terrain, LOLA must be able to walk at comparable speeds, which also motivates our research on fast and robust walking.

While it makes sense why the researchers are using LOLA’s arms primarily to assist with a conventional biped gait, looking ahead a bit it’s interesting to think about how robots that we typically consider to be bipeds could potentially leverage their limbs for mobility in decidedly non-human ways.

We’re used to legged robots being one particular morphology, I guess because associating them with either humans or dogs or whatever is just a comfortable way to do it, but there’s no particular reason why a robot with four limbs has to choose between being a quadruped and being a biped with arms, or some hybrid between the two, depending on what its task is. The research being done with LOLA could be a step in that direction, and maybe a hand on the wall in that direction, too. Continue reading

Posted in Human Robots

#438613 Video Friday: Digit Takes a Hike

Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We’ll also be posting a weekly calendar of upcoming robotics events for the next few months; here's what we have so far (send us your events!):

HRI 2021 – March 8-11, 2021 – [Online Conference]
RoboSoft 2021 – April 12-16, 2021 – [Online Conference]
ICRA 2021 – May 30-5, 2021 – Xi'an, China
Let us know if you have suggestions for next week, and enjoy today's videos.

It's winter in Oregon, so everything is damp, all the time. No problem for Digit!

Also the case for summer in Oregon.

[ Agility Robotics ]

While other organisms form collective flocks, schools, or swarms for such purposes as mating, predation, and protection, the Lumbriculus variegatus worms are unusual in their ability to braid themselves together to accomplish tasks that unconnected individuals cannot. A new study reported by researchers at the Georgia Institute of Technology describes how the worms self-organize to act as entangled “active matter,” creating surprising collective behaviors whose principles have been applied to help blobs of simple robots evolve their own locomotion.

No, this doesn't squick me out at all, why would it.

[ Georgia Tech ]

A few years ago, we wrote about Zhifeng Huang's jet-foot equipped bipedal robot, and he's been continuing to work on it to the point where it can now step over gaps that are an absolutely astonishing 147% of its leg length.

[ Paper ]

Thanks Zhifeng!

The Inception Drive is a novel, ultra-compact design for an Infinitely Variable Transmission (IVT) that uses nested-pulleys to adjust the gear ratio between input and output shafts. This video shows the first proof-of-concept prototype for a “Fully Balanced” design, where the spinning masses within the drive are completely balanced to reduce vibration, thereby allowing the drive to operate more efficiently and at higher speeds than achievable on an unbalanced design.

As shown in this video, the Inception Drive can change both the speed and direction of rotation of the output shaft while keeping the direction and speed of the input shaft constant. This ability to adjust speed and direction within such a compact package makes the Inception Drive a compelling choice for machine designers in a wide variety of fields, including robotics, automotive, and renewable-energy generation.

[ SRI ]

Robots with kinematic loops are known to have superior mechanical performance. However, due to these loops, their modeling and control is challenging, and prevents a more widespread use. In this paper, we describe a versatile Inverse Kinematics (IK) formulation for the retargeting of expressive motions onto mechanical systems with loops.

[ Disney Research ]

Watch Engineered Arts put together one of its Mesmer robots in a not at all uncanny way.

[ Engineered Arts ]

There's been a bunch of interesting research into vision-based tactile sensing recently; here's some from Van Ho at JAIST:

[ Paper ]

Thanks Van!

This is really more of an automated system than a robot, but these little levitating pucks are very very slick.

ACOPOS 6D is based on the principle of magnetic levitation: Shuttles with integrated permanent magnets float over the surface of electromagnetic motor segments. The modular motor segments are 240 x 240 millimeters in size and can be arranged freely in any shape. A variety of shuttle sizes carry payloads of 0.6 to 14 kilograms and reach speeds of up to 2 meters per second. They can move freely in two-dimensional space, rotate and tilt along three axes and offer precise control over the height of levitation. All together, that gives them six degrees of motion control freedom.

[ ACOPOS ]

Navigation and motion control of a robot to a destination are tasks that have historically been performed with the assumption that contact with the environment is harmful. This makes sense for rigid-bodied robots where obstacle collisions are fundamentally dangerous. However, because many soft robots have bodies that are low-inertia and compliant, obstacle contact is inherently safe. We find that a planner that takes into account and capitalizes on environmental contact produces paths that are more robust to uncertainty than a planner that avoids all obstacle contact.

[ CHARM Lab ]

The quadrotor experts at UZH have been really cranking it up recently.

Aerodynamic forces render accurate high-speed trajectory tracking with quadrotors extremely challenging. These complex aerodynamic effects become a significant disturbance at high speeds, introducing large positional tracking errors, and are extremely difficult to model. To fly at high speeds, feedback control must be able to account for these aerodynamic effects in real-time. This necessitates a modelling procedure that is both accurate and efficient to evaluate. Therefore, we present an approach to model aerodynamic effects using Gaussian Processes, which we incorporate into a Model Predictive Controller to achieve efficient and precise real-time feedback control, leading to up to 70% reduction in trajectory tracking error at high speeds. We verify our method by extensive comparison to a state-of-the-art linear drag model in synthetic and real-world experiments at speeds of up to 14m/s and accelerations beyond 4g.

[ Paper ]

I have not heard much from Harvest Automation over the last couple years and their website was last updated in 2016, but I guess they're selling robots in France, so that's good?

[ Harvest Automation ]

Last year, Clearpath Robotics introduced a ROS package for Spot which enables robotics developers to leverage ROS capabilities out-of-the-box. Here at OTTO Motors, we thought it would be a compelling test case to see just how easy it would be to integrate Spot into our test fleet of OTTO materials handling robots.

[ OTTO Motors ]

Video showcasing recent robotics activities at PRISMA Lab, coordinated by Prof. Bruno Siciliano, at Università di Napoli Federico II.

[ PRISMA Lab ]

Thanks Fan!

State estimation framework developed by the team CoSTAR for the DARPA Subterranean Challenge, where the team achieved 2nd and 1st places in the Tunnel and Urban circuits.

[ Paper ]

Highlights from the 2020 ROS Industrial conference.

[ ROS Industrial ]

Thanks Thilo!

Not robotics, but entertaining anyway. From the CHI 1995 Technical Video Program, “The Tablet Newspaper: a Vision for the Future.”

[ CHI 1995 ]

This week's GRASP on Robotics seminar comes from Allison Okamura at Stanford, on “Wearable Haptic Devices for Ubiquitous Communication.”

Haptic devices allow touch-based information transfer between humans and intelligent systems, enabling communication in a salient but private manner that frees other sensory channels. For such devices to become ubiquitous, their physical and computational aspects must be intuitive and unobtrusive. We explore the design of a wide array of haptic feedback mechanisms, ranging from devices that can be actively touched by the fingertips to multi-modal haptic actuation mounted on the arm. We demonstrate how these devices are effective in virtual reality, human-machine communication, and human-human communication.

[ UPenn ] Continue reading

Posted in Human Robots

#438001 How an Israeli Startup Is Using AI to ...

The first baby conceived using in-vitro fertilization (IVF) was born in the UK in 1978. Over 40 years later, the technique has become commonplace, but its success rate is still fairly low at around 22 to 30 percent. A female-founded Israeli startup called Embryonics is setting out to change this by using artificial intelligence to screen embryos.

IVF consists of fertilizing a woman’s egg with her partner’s or a donor’s sperm outside of her body, creating an embryo that’s then implanted in the uterus. It’s not an easy process in any sense of the word—physically, emotionally, or financially. Insurance rarely covers IVF, and the costs run anywhere from $12,000 to $25,000 per cycle (a cycle takes about a month and includes stimulating a woman’s ovaries to produce eggs, extracting the eggs, inseminating them outside the body, and implanting an embryo).

Women have to give themselves daily hormone shots to stimulate egg production, and these can cause uncomfortable side effects. After so much stress and expense, it’s disheartening to think that the odds of a successful pregnancy are, at best, one in three.

A crucial factor in whether or not an IVF cycle works—that is, whether the embryo implants in the uterus and begins to develop into a healthy fetus—is the quality of the embryo. Doctors examine embryos through a microscope to determine how many cells they contain and whether they appear healthy, and choose the one that looks most viable.

But the human eye can only see so much, even with the help of a microscope; despite embryologists’ efforts to select the “best” embryo, success rates are still relatively low. “Many decisions are based on gut feeling or personal experience,” said Embryonics founder and CEO Yael Gold-Zamir. “Even if you go to the same IVF center, two experts can give you different opinions on the same embryo.”

This is where Embryonics’ technology comes in. They used 8,789 time-lapse videos of developing embryos to train an algorithm that predicts the likelihood of successful embryo implantation. A little less than half of the embryos from the dataset were graded by embryologists, and implantation data was integrated when it was available (as a binary “successful” or “failed” metric).

The algorithm uses geometric deep learning, a technique that takes a traditional convolutional neural network—which filters input data to create maps of its features, and is most commonly used for image recognition—and applies it to more complex data like 3D objects and graphs. Within days after fertilization, the embryo is still at the blastocyst stage, essentially a microscopic clump of just 200-300 cells; the algorithm uses this deep learning technique to spot and identify patterns in embryo development that human embryologists either wouldn’t see at all, or would require massive collation of data to validate.

On top of the embryo videos, Embryonics’ team incorporated patient data and environmental data from the lab into its algorithm, with encouraging results: the company reports that using its algorithm resulted in a 12 percent increase in positive predictive value (identifying embryos that would lead to implantation and healthy pregnancy) and a 29 percent increase in negative predictive value (identifying embyros that would not result in successful pregnancy) when compared to an external panel of embryologists.

TechCrunch reported last week that in a pilot of 11 women who used Embryonics’ algorithm to select their embryos, 6 are enjoying successful pregnancies, while 5 are still awaiting results.

Embryonics wasn’t the first group to think of using AI to screen embryos; a similar algorithm developed in 2019 by researchers at Weill Cornell Medicine was able to classify the quality of a set of embryo images with 97 percent accuracy. But Embryonics will be one of the first to bring this sort of technology to market. The company is waiting to receive approval from European regulatory bodies to be able to sell the software to fertility clinics in Europe.

Its timing is ripe: as more and more women delay having kids due to lifestyle and career-related factors, demand for IVF is growing, and will likely accelerate in coming years.

The company ultimately hopes to bring its product to the US, as well as to expand its work to include using data to improve hormonal stimulation.

Image Credit: Gerd Altmann from Pixabay Continue reading

Posted in Human Robots

#437929 These Were Our Favorite Tech Stories ...

This time last year we were commemorating the end of a decade and looking ahead to the next one. Enter the year that felt like a decade all by itself: 2020. News written in January, the before-times, feels hopelessly out of touch with all that came after. Stories published in the early days of the pandemic are, for the most part, similarly naive.

The year’s news cycle was swift and brutal, ping-ponging from pandemic to extreme social and political tension, whipsawing economies, and natural disasters. Hope. Despair. Loneliness. Grief. Grit. More hope. Another lockdown. It’s been a hell of a year.

Though 2020 was dominated by big, hairy societal change, science and technology took significant steps forward. Researchers singularly focused on the pandemic and collaborated on solutions to a degree never before seen. New technologies converged to deliver vaccines in record time. The dark side of tech, from biased algorithms to the threat of omnipresent surveillance and corporate control of artificial intelligence, continued to rear its head.

Meanwhile, AI showed uncanny command of language, joined Reddit threads, and made inroads into some of science’s grandest challenges. Mars rockets flew for the first time, and a private company delivered astronauts to the International Space Station. Deprived of night life, concerts, and festivals, millions traveled to virtual worlds instead. Anonymous jet packs flew over LA. Mysterious monoliths appeared and disappeared worldwide.

It was all, you know, very 2020. For this year’s (in-no-way-all-encompassing) list of fascinating stories in tech and science, we tried to select those that weren’t totally dated by the news, but rose above it in some way. So, without further ado: This year’s picks.

How Science Beat the Virus
Ed Yong | The Atlantic
“Much like famous initiatives such as the Manhattan Project and the Apollo program, epidemics focus the energies of large groups of scientists. …But ‘nothing in history was even close to the level of pivoting that’s happening right now,’ Madhukar Pai of McGill University told me. … No other disease has been scrutinized so intensely, by so much combined intellect, in so brief a time.”

‘It Will Change Everything’: DeepMind’s AI Makes Gigantic Leap in Solving Protein Structures
Ewen Callaway | Nature
“In some cases, AlphaFold’s structure predictions were indistinguishable from those determined using ‘gold standard’ experimental methods such as X-ray crystallography and, in recent years, cryo-electron microscopy (cryo-EM). AlphaFold might not obviate the need for these laborious and expensive methods—yet—say scientists, but the AI will make it possible to study living things in new ways.”

OpenAI’s Latest Breakthrough Is Astonishingly Powerful, But Still Fighting Its Flaws
James Vincent | The Verge
“What makes GPT-3 amazing, they say, is not that it can tell you that the capital of Paraguay is Asunción (it is) or that 466 times 23.5 is 10,987 (it’s not), but that it’s capable of answering both questions and many more beside simply because it was trained on more data for longer than other programs. If there’s one thing we know that the world is creating more and more of, it’s data and computing power, which means GPT-3’s descendants are only going to get more clever.”

Artificial General Intelligence: Are We Close, and Does It Even Make Sense to Try?
Will Douglas Heaven | MIT Technology Review
“A machine that could think like a person has been the guiding vision of AI research since the earliest days—and remains its most divisive idea. …So why is AGI controversial? Why does it matter? And is it a reckless, misleading dream—or the ultimate goal?”

The Dark Side of Big Tech’s Funding for AI Research
Tom Simonite | Wired
“Timnit Gebru’s exit from Google is a powerful reminder of how thoroughly companies dominate the field, with the biggest computers and the most resources. …[Meredith] Whittaker of AI Now says properly probing the societal effects of AI is fundamentally incompatible with corporate labs. ‘That kind of research that looks at the power and politics of AI is and must be inherently adversarial to the firms that are profiting from this technology.’i”

We’re Not Prepared for the End of Moore’s Law
David Rotman | MIT Technology Review
“Quantum computing, carbon nanotube transistors, even spintronics, are enticing possibilities—but none are obvious replacements for the promise that Gordon Moore first saw in a simple integrated circuit. We need the research investments now to find out, though. Because one prediction is pretty much certain to come true: we’re always going to want more computing power.”

Inside the Race to Build the Best Quantum Computer on Earth
Gideon Lichfield | MIT Technology Review
“Regardless of whether you agree with Google’s position [on ‘quantum supremacy’] or IBM’s, the next goal is clear, Oliver says: to build a quantum computer that can do something useful. …The trouble is that it’s nearly impossible to predict what the first useful task will be, or how big a computer will be needed to perform it.”

The Secretive Company That Might End Privacy as We Know It
Kashmir Hill | The New York Times
“Searching someone by face could become as easy as Googling a name. Strangers would be able to listen in on sensitive conversations, take photos of the participants and know personal secrets. Someone walking down the street would be immediately identifiable—and his or her home address would be only a few clicks away. It would herald the end of public anonymity.”

Wrongfully Accused by an Algorithm
Kashmir Hill | The New York Times
“Mr. Williams knew that he had not committed the crime in question. What he could not have known, as he sat in the interrogation room, is that his case may be the first known account of an American being wrongfully arrested based on a flawed match from a facial recognition algorithm, according to experts on technology and the law.”

Predictive Policing Algorithms Are Racist. They Need to Be Dismantled.
Will Douglas Heaven | MIT Technology Review
“A number of studies have shown that these tools perpetuate systemic racism, and yet we still know very little about how they work, who is using them, and for what purpose. All of this needs to change before a proper reckoning can take pace. Luckily, the tide may be turning.”

The Panopticon Is Already Here
Ross Andersen | The Atlantic
“Artificial intelligence has applications in nearly every human domain, from the instant translation of spoken language to early viral-outbreak detection. But Xi [Jinping] also wants to use AI’s awesome analytical powers to push China to the cutting edge of surveillance. He wants to build an all-seeing digital system of social control, patrolled by precog algorithms that identify potential dissenters in real time.”

The Case For Cities That Aren’t Dystopian Surveillance States
Cory Doctorow | The Guardian
“Imagine a human-centered smart city that knows everything it can about things. It knows how many seats are free on every bus, it knows how busy every road is, it knows where there are short-hire bikes available and where there are potholes. …What it doesn’t know is anything about individuals in the city.”

The Modern World Has Finally Become Too Complex for Any of Us to Understand
Tim Maughan | OneZero
“One of the dominant themes of the last few years is that nothing makes sense. …I am here to tell you that the reason so much of the world seems incomprehensible is that it is incomprehensible. From social media to the global economy to supply chains, our lives rest precariously on systems that have become so complex, and we have yielded so much of it to technologies and autonomous actors that no one totally comprehends it all.”

The Conscience of Silicon Valley
Zach Baron | GQ
“What I really hoped to do, I said, was to talk about the future and how to live in it. This year feels like a crossroads; I do not need to explain what I mean by this. …I want to destroy my computer, through which I now work and ‘have drinks’ and stare at blurry simulations of my parents sometimes; I want to kneel down and pray to it like a god. I want someone—I want Jaron Lanier—to tell me where we’re going, and whether it’s going to be okay when we get there. Lanier just nodded. All right, then.”

Yes to Tech Optimism. And Pessimism.
Shira Ovide | The New York Times
“Technology is not something that exists in a bubble; it is a phenomenon that changes how we live or how our world works in ways that help and hurt. That calls for more humility and bridges across the optimism-pessimism divide from people who make technology, those of us who write about it, government officials and the public. We need to think on the bright side. And we need to consider the horribles.”

How Afrofuturism Can Help the World Mend
C. Brandon Ogbunu | Wired
“…[W. E. B. DuBois’] ‘The Comet’ helped lay the foundation for a paradigm known as Afrofuturism. A century later, as a comet carrying disease and social unrest has upended the world, Afrofuturism may be more relevant than ever. Its vision can help guide us out of the rubble, and help us to consider universes of better alternatives.”

Wikipedia Is the Last Best Place on the Internet
Richard Cooke | Wired
“More than an encyclopedia, Wikipedia has become a community, a library, a constitution, an experiment, a political manifesto—the closest thing there is to an online public square. It is one of the few remaining places that retains the faintly utopian glow of the early World Wide Web.”

Can Genetic Engineering Bring Back the American Chestnut?
Gabriel Popkin | The New York Times Magazine
“The geneticists’ research forces conservationists to confront, in a new and sometimes discomfiting way, the prospect that repairing the natural world does not necessarily mean returning to an unblemished Eden. It may instead mean embracing a role that we’ve already assumed: engineers of everything, including nature.”

At the Limits of Thought
David C. Krakauer | Aeon
“A schism is emerging in the scientific enterprise. On the one side is the human mind, the source of every story, theory, and explanation that our species holds dear. On the other stand the machines, whose algorithms possess astonishing predictive power but whose inner workings remain radically opaque to human observers.”

Is the Internet Conscious? If It Were, How Would We Know?
Meghan O’Gieblyn | Wired
“Does the internet behave like a creature with an internal life? Does it manifest the fruits of consciousness? There are certainly moments when it seems to. Google can anticipate what you’re going to type before you fully articulate it to yourself. Facebook ads can intuit that a woman is pregnant before she tells her family and friends. It is easy, in such moments, to conclude that you’re in the presence of another mind—though given the human tendency to anthropomorphize, we should be wary of quick conclusions.”

The Internet Is an Amnesia Machine
Simon Pitt | OneZero
“There was a time when I didn’t know what a Baby Yoda was. Then there was a time I couldn’t go online without reading about Baby Yoda. And now, Baby Yoda is a distant, shrugging memory. Soon there will be a generation of people who missed the whole thing and for whom Baby Yoda is as meaningless as it was for me a year ago.”

Digital Pregnancy Tests Are Almost as Powerful as the Original IBM PC
Tom Warren | The Verge
“Each test, which costs less than $5, includes a processor, RAM, a button cell battery, and a tiny LCD screen to display the result. …Foone speculates that this device is ‘probably faster at number crunching and basic I/O than the CPU used in the original IBM PC.’ IBM’s original PC was based on Intel’s 8088 microprocessor, an 8-bit chip that operated at 5Mhz. The difference here is that this is a pregnancy test you pee on and then throw away.”

The Party Goes on in Massive Online Worlds
Cecilia D’Anastasio | Wired
“We’re more stand-outside types than the types to cast a flashy glamour spell and chat up the nearest cat girl. But, hey, it’s Final Fantasy XIV online, and where my body sat in New York, the epicenter of America’s Covid-19 outbreak, there certainly weren’t any parties.”

The Facebook Groups Where People Pretend the Pandemic Isn’t Happening
Kaitlyn Tiffany | The Atlantic
“Losing track of a friend in a packed bar or screaming to be heard over a live band is not something that’s happening much in the real world at the moment, but it happens all the time in the 2,100-person Facebook group ‘a group where we all pretend we’re in the same venue.’ So does losing shoes and Juul pods, and shouting matches over which bands are the saddest, and therefore the greatest.”

Did You Fly a Jetpack Over Los Angeles This Weekend? Because the FBI Is Looking for You
Tom McKay | Gizmodo
“Did you fly a jetpack over Los Angeles at approximately 3,000 feet on Sunday? Some kind of tiny helicopter? Maybe a lawn chair with balloons tied to it? If the answer to any of the above questions is ‘yes,’ you should probably lay low for a while (by which I mean cool it on the single-occupant flying machine). That’s because passing airline pilots spotted you, and now it’s this whole thing with the FBI and the Federal Aviation Administration, both of which are investigating.”

Image Credit: Thomas Kinto / Unsplash Continue reading

Posted in Human Robots