Lifeboat Foundation

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Has human level AI been reached in 2022? What are the best Artificial Intelligences released by the biggest AI companies so far? All of this in the top 5 best AI’s in 2022.
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TIMESTAMPS:
00:00 Intro.
00:19 #5 GPT-3
03:10 #4 Gopher.
04:40 #3 Codex.
06:01 #2 DALL-E 2
07:33 #1 Flamingo.
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#ai #top5 #futurism

A new technique for measuring the shadows cast by a black hole binary could enable astronomers to glean details about these massive systems.

During its first keynote at Google I/O 2022, Google detailed its latest language model, LaMDA 2, and an app called AI Test Kitchen.

During its first keynote at Google I/O 2022, Google detailed its latest language model, LaMDA 2, and an app called AI Test Kitchen.

For instance, when training a gestational age clock model from placental methylation, a sample can only be collected after delivery of the baby and the placenta. So most samples have a gestational age greater than 30 weeks, which corresponds to moderate preterm and full-term births. For samples with a further younger gestational age, they are scarce, which makes the sample distribution seriously biased to large gestational ages and impairs the ability of the trained model to predict small ones. However, differences in gestational age as small as one week can significantly influence neonatal morbidity and mortality and long-term outcomes [18 – 23]. Hence, the model’s accuracy across the whole gestational age range becomes essential.

To solve this problem, we developed the R package eClock (ensemble-based clock). It improves the traditional machine learning strategy in handling the imbalance problem of category data [24], and combines bagging and SMOTE (Synthetic Minority Over-sampling Technique) methods to adjust the biased age distribution and predict DNAm age with an ensemble model. This is the first time applying these techniques to the clock model, bringing a new framework for clock model construction. eClock also provides other functions, such as training the traditional clock model, displaying features, and converting methylation probe/gene/DMR (DNA methylation region) values. To test the performance of the package, we used 3 different datasets, and the results show that the package can effectively improve the clock model performance on rare samples.

After launching our warehouse robot Stretch at #MODEX2022, we heard from a lot of warehouse and materials handling professionals. Check out our biggest takeaway… See more.

Launching Stretch, our autonomous warehouse robot, at MODEX 2022, we found consistent themes about the state of warehouse automation and material handling.

Summary

The human brain has the, remarkable ability to learn patterns from small amounts of data and then recognize novel instances of those patterns despite distortion and noise. Although advances in machine learning algorithms have been weakly informed by the brain since the 1940’s, they do not yet rival human performance.

On account of the improvement the Internet of things (IoTs) and smart devices, our lives have been noticeably facilitated in the past few years. Machines and devices are becoming more ingenious with the help of artificial intelligence and various sensors^1,2. So, integrated circuits are necessary to provide convenient and effectual communication³ Since the first report on TENG by Wang’s group in 2012⁴, triboelectric systems have been recognized as a proper choice to harvest and convert the energy from the environment^5,6. Photodetectors, as one of the most significant types of sensors that can precisely convert incident light into electrical signals have attracted increasing attention in recent years. Various applications including photo-sensors, spectral analysis^7,8, environment monitoring⁹, communication devices¹⁰, imaging¹¹, take advantage of narrow band or broad band photodetectors from ultraviolet to terahertz wavelenght. Literature reviews show that the heterojunction/heterostructure based on 2D/3D materials have been widely used in PD applications. In fact, to attain high performance of PDs based heterojunction, the built-in electrical field is needed to suppress the photogenerated recombination and stimulating collection¹². Although, Si based PDs offer reliably high performance results, their complexity and expensive manufacturing process have limited their expansion and adoptability for industrial purposes^13,14,15. Hence, most available PDs are designed based on external power supplies such as electrochemical batteries for signal production and processing, their design not only increases the sensor’s dimension and weight, but also creates limitations for sensor maintenances¹⁶ which is not proper in the IoTs. In 2014, ZH Lin et al. and Zheng et al. represented an investigation on the self-powered PD based on TENG system^3,17, and since then, self-driven PDs have been extensively investigated^{2,5,9,18,19,20}. These devices can find potential applications in health monitoring systems such as heart checking²¹ and health protection from some detrimental radiation such as high levels of UV radiance²².

But in the other hand, even though TENGs could be promise for using in wearable electronics, they still inevitably have limitations in power generation, sensing range, sensitivity, and also the sensing domain for the intrinsic limitations of electrification^23,24,25. Moreover, due to high voltage, low current, and alternating current output of the TENGs, they cannot be used in order to supply power to electronic devices effectively without using power management circuits (PMCs) based on the LC modules. There are several reports that describe the importance of the impedance matching of the TENG and PMC units for better energy storage efficiency of the pulsed-TENG^26,27. Without using the PMC unit, there are some challenges as a result of synching the TENG, as the power supply, and the consumption element such as the PD device. These challenges include the process of matching the resistance of the device and the impedance of the TENG to achieve effective performance of the self-powered system^6,28.

In this study an efficient battery-free photodetector based on bulk heterojunction SnS₂ nanosheets and perovskite materials has been designed and powered employing three different TENGs (GO paper/ Kapton, FTO/Kapton and hand/ FTO). In the first step for circuit designing to have better performance of the photodetector in coupling with TENG, the effect load resistance amount in the circuit on the impedance matching the TENG and the inner resistance of the photodetector, has been investigated through output current amplitude. The investigation, shows that to achieve the high amount of the photocurrent, the load resistance should be positioned in both critical zone of the out-put voltage of the TENG and the resistance range of high power density production of the TENG. In the second step, for investigation the effect of the dark resistance of the photodetector on out-put current of the self-powered photodetector, a device with very lower initial resistance (All-oxide Cu₂O/ZnO photodetector) has been used with and without different load resistance in the circuit; in this regard, it is concluding that the initial resistance is too important to have proper design impedance matching circuit.

EPFL scientists have developed a digital model of the fruit fly, Drosophila melanogaster, that realistically simulates the movements of the animal. The twin is a big step towards reverse engineering the neuromechanical control of animal behavior, and developing bioinspired robots.

“We used two kinds of data to build NeuroMechFly,” says Professor Pavan Ramdya at EPFL’s School of Life Sciences. “First, we took a real fly and performed a CT scan to build a morphologically realistic biomechanical model. The second source of data were the real limb movements of the fly, obtained using pose estimation software that we’ve developed in the last couple of years that allow us to precisely track the movements of the animal.”

Ramdya’s group, working with the group of Professor Auke Ijspeert at EPFL’s Biorobotics Laboratory, has published a paper in Nature Methods showcasing the first ever accurate “digital twin” of the fly Drosophila melanogaster, dubbed “NeuroMechFly”.

Recent technological advances have enabled the creation of increasingly sophisticated sensors that can track movements and changes in real-world environments with remarkable levels of precision. Many engineers are now working to make these sensors thinner so that they can be embedded in a variety of devices, including robotic limbs and wearable devices.

Researchers at Hong Kong University of Science and Technology have recently developed a thin sensor for computer vision applications, which is based on a micro lens array (MLA). MLAs are 1D or 2D arrays comprising several small lenses, which are generally arranged in either squared or hexagonal patterns.

“In this study, we combined an old technology, a micro lens array, with vision-based tactile sensors,” Xia Chen, one of the researchers who carried out the study, told TechXplore. “This work builds on the work using the pinhole arrays to capture the image. We wanted to achieve a thin-format vision-based tactile sensor, as few studies so far focused on changing the imaging system of vison-based tactile sensor.”