Advances in machine learning have made it possible to automate a growing array of coding tasks, from auto-completing segments of code and fine tuning algorithms… See More.
Programs such as GPT-3 can compose convincing text. Some people are using the tool to automate software development and hunt for bugs.
In this nearly 4-hour SPECIAL EPISODE, Rob Reid delivers a 100-minute monologue (broken up into 4 segments, and interleaved with discussions with Sam) about the looming danger of a man-made pandemic, caused by an artificially-modified pathogen. The risk of this occurring is far higher and nearer-term than almost anyone realizes.
Rob explains the science and motivations that could produce such a catastrophe and explores the steps that society must start taking today to prevent it. These measures are concrete, affordable, and scientifically fascinating—and almost all of them are applicable to future, natural pandemics as well. So if we take most of them, the odds of a future Covid-like outbreak would plummet—a priceless collateral benefit.
Rob Reid is a podcaster, author, and tech investor, and was a long-time tech entrepreneur. His After On podcast features conversations with world-class thinkers, founders, and scientists on topics including synthetic biology, super-AI risk, Fermi’s paradox, robotics, archaeology, and lone-wolf terrorism. Science fiction novels that Rob has written for Random House include The New York Times bestseller Year Zero, and the AI thriller After On. As an investor, Rob is Managing Director at Resilience Reserve, a multi-phase venture capital fund. He co-founded Resilience with Chris Anderson, who runs the TED Conference and has a long track record as both an entrepreneur and an investor. In his own entrepreneurial career, Rob founded and ran Listen.com, the company that created the Rhapsody music service. Earlier, Rob studied Arabic and geopolitics at both undergraduate and graduate levels at Stanford, and was a Fulbright Fellow in Cairo. You can find him at www.after-on.
Scientists at Osaka University, in cooperation with Joanneum Research (Weiz, Austria), have developed wireless health monitoring patches that use embedded piezoelectric nanogenerators to power themselves with harvested biomechanical energy. This work may lead to new autonomous health sensors as well as battery-free wearable electronic devices.
As wearable technology and smart sensors become increasingly popular, the problem of providing power to all of these devices become more relevant. While the energy requirements of each component may be modest, the need for wires or even batteries become burdensome and inconvenient. That is why new energy harvesting methods are needed. Also, the ability for integrated health monitors to use ambient motion to both power and activate sensors will help accelerate their adoption in doctor’s offices.
Now, an international team of researchers from Japan and Austria has invented new ultraflexible patches with a ferroelectric polymer that can not only sense a patient’s pulse and blood pressure, but also power themselves from normal movements. The key was starting with a substrate just one micron thick. Using a strong electric field, ferroelectric crystalline domains in a copolymer were aligned so that the sample had a large electric dipole moment. Based on the piezoelectric effect, which is very efficient in converting natural motion into small electric voltages, the device responds rapidly to strain or pressure changes. These voltages can be transduced either into signals for the medical sensors or to directly harvest the energy. “Our e-health patches may be employed as part of screening for lifestyle-related diseases such as heart disorders, signs of stress, and sleep apnea,” first-author Andreas Petritz says.
Animals are constantly moving and behaving in response to instructions from the brain. But while there are advanced techniques for measuring these instructions in terms of neural activity, there is a paucity of techniques for quantifying the behavior itself in freely moving animals. This inability to measure the key output of the brain limits our understanding of the nervous system and how it changes in disease.
A new study by researchers at Duke University and Harvard University introduces an automated tool that can readily capture behavior of freely behaving animals and precisely reconstruct their three dimensional (3D) pose from a single video camera and without markers.
The April 19 study in Nature Methods led by Timothy W. Dunn, Assistant Professor, Duke University, and Jesse D. Marshall, postdoctoral researcher, Harvard University, describes a new 3D deep-neural network, DANNCE (3-Dimensional Aligned Neural Network for Computational Ethology). The study follows the team’s 2020 study in Neuron which revealed the groundbreaking behavioral monitoring system, CAPTURE (Continuous Appendicular and Postural Tracking using Retroreflector Embedding), which uses motion capture and deep learning to continuously track the 3D movements of freely behaving animals. CAPTURE yielded an unprecedented detailed description of how animals behave. However, it required using specialized hardware and attaching markers to animals, making it a challenge to use.
Human Security cybersecurity specialists reveal the finding of a massive botnet made up of compromised Android devices. This malicious operation, identified as Pareto, would aim to conduct advertising fraud related to payment connected television (CTV) services and would so far be made up of about one million infected devices.
As you will recall, the term botnet refers to a network of computer systems committed to a specific malware variant, executed autonomously and automatically and under remote control by attack operators.
Experts say hackers have used dozens of mobile apps to mimic the image of over 6000 CTV apps, equivalent to around 650 million ad requests per day. This botnet was first identified in 2020 and since then companies such as Google and Roku have tried to mitigate their progress, although operators have managed to grow inordinately.
There is no putting the genie back in the bottle. The AI arms race is well underway and leading militaries worldwide do not want to be in second place or worse. Where this will lead is subject to conjecture. Clearly, however, the wars of the future will be fought and determined by AI more than traditional “military might.” The ethical use of AI in these applications remains an open-ended issue. It was within the mandate of the NSCAI report to recommend restrictions on how the technology should be used, but this was unfortunately deferred to a later date.
The AI arms race is speeding ahead in militaries around the world.
AI squad mates. Called this a few years ago. It’s too annoying getting strangers to join up on some online task for a game.
Who wouldn’t want an A.I.to sit there and play backseat gamer? That’s exactly what looks to be happening thanks to a recently revealed Sony patent. The patent is for an automated Artificial Intelligence (A.I.) control mode specifically designed to perform certain tasks, including playing a game while the player is away.
In the patent, as spotted by SegmentNext, it’s detailed that this A.I. will involve assigning a default gameplay profile to the user. This profile will include a compendium of information detailing the player’s gaming habits, play styles, and decision-making processes while sitting down for a new adventure. This knowledge can then be harnessed to simulate the player’s gaming habits, even when said gamer is away from their platform of choice.
“The method includes monitoring a plurality of game plays of the user playing a plurality of gaming applications,” reads the patent itself. “The method includes generating a user gameplay profile of the user by adjusting the default gameplay style based on the plurality of game plays, wherein the user gameplay profile incudes a user gameplay style customized to the user. The method includes controlling an instance of a first gaming application based on the user gameplay style of the user gameplay profile.”
Pepper update:
Italian researchers have programmed a humanoid robot named Pepper, made by SoftBank Robotics in Japan, to “thinks out loud” so that users can hear its thought process. Hearing a robot voice its decision-making process increases the transparency and trust between humans and machines.
Arianna Pipitone and Antonio Chella at the University of Palermo, Italy, built an ‘inner speech model’ based on a cognitive architecture that allowed the robot to speak aloud its inner decision-making process, just like humans when faced with a challenge or a dilemma. With the inner speech, users can hear its thought process and better understand the robot’s motivations and decisions.
The European Union today proposed rules governing the use of artificial intelligence that could wind up becoming a de facto standard for how the technology is governed in much of the globe.
Or is it about to consign itself to also-ran status, as the U.S. tech lobby is arguing?
A team of researchers working at Barcelona Institute of Science and Technology has developed a skeletal-muscle-based, biohybrid soft robot that can swim faster than other skeletal-muscle-based biobots. In their paper published in the journal Science Robotics, the group describes building and testing their soft robot.
As scientists continue to improve the abilities of soft robots, they have turned to natural materials such as animal tissue. To date, most efforts in this area have involved the use of skeletal or cardiac muscles—each have their strengths and weaknesses. Skeletal-muscle-based biobots have, for example, suffered from lack of mobility and strength. In this new effort, the researchers in Spain have developed a new design for a tinyskeletal-muscle-based soft robot that overcomes both issues and is therefore able to swim faster than others of its kind.
To make their biobot, the researchers used a simulation to create a spring-based spine for a swimming creature shaped like an eel. The simulation allowed the researchers to optimize its shape. They then 3D printed the skeleton (which was made of a polymer called PDMS) and used it as a scaffold for growing skeletal muscles. The finished robot was approximately 260 micrometers long—its shape allowed for propulsion in just one direction. The biobot moves when given electrical stimulation; the charge incites the muscle to contract, which compresses the skeletal spring inside. When the stimulation is removed, the energy in the spring is released, pushing the biobot forward.
