A Texas undergrad is investigating how to grow vegetables on Mars — and has cultivated test samples of English peas in simulated Martian soil, with fertilizer from fly larvae.
Implants and tiny machines could eventually be working inside our bodies to help treat disease or monitor activity, but letting them communicate is tricky. Now scientists at EPFL have developed a system whereby devices can communicate by releasing molecules into a patient’s bloodstream.
Biomedical implants play a key role in healthcare, monitoring activity in organs like the heart or brain, while recent research is investigating how nanoscale robots might one day swim or crawl through the body to fight disease. But these systems have a communication issue.
Running wires through the body is not only impractical, it’s an infection risk. And wireless technologies like radio, light and Bluetooth don’t travel through human tissue very efficiently, drastically limiting their range.
Designing high performance organic neuromorphic devices remains a challenge. Here, Liu et al. report the development of an organic synapse based on a semicrystalline polymer PBFCL10 with device dimension of 50 nm and integration size of 1 Kb and a mixed‐signal neuromorphic hardware system based on the organic neuromatrix and FPGA controller for decision‐making tasks.
Zero-knowledge proof (ZKP) is a cryptographic tool that allows for the verification of validity between mutually untrusted parties without disclosing additional information. Non-interactive zero-knowledge proof (NIZKP) is a variant of ZKP with the feature of not requiring multiple information exchanges. Therefore, NIZKP is widely used in the fields of digital signature, blockchain, and identity authentication.
Since it is difficult to implement a true random number generator, deterministic pseudorandom number algorithms are often used as a substitute. However, this method has potential security vulnerabilities. Therefore, how to obtain true random numbers has become the key to improving the security of NIZKP.
In a study published in PNAS, a research team led by Prof. Pan Jianwei and Prof. Zhang Qiang from the University of Science and Technology of China (USTC) of the Chinese Academy of Sciences, and the collaborators, realized a set of random number beacon public services with device-independent quantum random number generators as entropy sources and post-quantum cryptography as identity authentication.
CU Cancer Center member, Michelle Springer, MS, CGC, presents “Genetic Testing for Family Members” at the Hereditary Cancer Conference.
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Artificial general intelligence, or AGI, has become a much-abused buzzword in the AI industry. Now, Google DeepMind wants to put the idea on a firmer footing.
The concept at the heart of the term AGI is that a hallmark of human intelligence is its generality. While specialist computer programs might easily outperform us at picking stocks or translating French to German, our superpower is the fact we can learn to do both.
Recreating this kind of flexibility in machines is the holy grail for many AI researchers, and is often speculated to be the first step towards artificial superintelligence. But what exactly people mean by AGI is rarely specified, and the idea is frequently described in binary terms, where AGI represents a piece of software that has crossed some mythical boundary, and once on the other side, it’s on par with humans.
Last year Swiss Re and Waymo launched a research partnership to define a standard for assessing the risk of autonomous vehicles. One year after that announcement, they are publishing a study that uses real-world data to compare the safety performance of autonomous vs human-driven vehicles. Notably, this is the first time that a robust and significant liability claims dataset is being used to compare the safety performance of autonomous and human drivers.
In fact, Swiss Re was able to produce mileage-and zip-code-calibrated (human driver) private passenger vehicle baselines, against which Waymo’s third party liability insurance claims data were compared. Swiss Re’s baselines, for the specific areas considered, are extremely significant, as they come from over 600,000 claims and over 125 billion miles of exposure.
The results of the research are exciting both for the insurance industry and the safety community alike: in over 3.8 million miles driven without a human being behind the steering wheel in rider-only mode, the Waymo Driver (Waymo’s fully autonomous driving technology) incurred zero bodily injury claims in comparison with the human driver baseline of 1.11 claims per million miles. The Waymo Driver also significantly reduced property damage claims to 0.78 claims per million miles in comparison with the human driver baseline of 3.26 claims per million miles.
Meta is marching forward with its solution for reviving declining user numbers: introducing an array of AI-powered chatbots to its services.
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