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Category: robotics/AI – Page 2,048

We (TIRIAS Research) recently had an opportunity to evaluate the latest Jetson platform from Nvidia. At just 45mm x 70mm the Jetson Nano is the smallest Artificial Intelligence (AI) platform form factor Nvidia has produced to date. The Jetson Nano is powered by the Tegra X1 SoC, which features quad 1.43 GHz Cortex-A57 CPU cores and the 128-core Maxwell GPU. The Jetson Nano also uses the same Jetpack Software Development Kit (SDK) as the other Jetson platforms, the TX2 and AGX Xavier, allowing for cross platform development. For only $99, plus a little extra for accessories, the Jetson Nano is an amazing platform.

In addition to the Tegra X1 SoC, the Nano developer kit comes configured with 4GB of LPDDR4 memory and plenty on I/O options, including a MIPI CSI connector, four USB 3.0 Type-A ports, one USB 2.0 Micro-B, one gigabit ethernet port, and 40 GPIO pins. The Nano is capable of driving dual displays through single DisplayPort and HDMI ports, it has an microSD card slot for storage, and a somewhat hidden M.2 Key E connection for expansion modules/daughter cards for optional functions like wireless connectivity. The Jetson Nano developer kit comes with a sizable heatsink for passive cooling, but has holes drilled for add-on fans. For our evaluation, we used a Noctua NF-A4x20 5V PWM fan and a Raspberry Pi MIPI Camera Module v2 from RS Components and Allied Electronics.

For development software, the Nano runs an Ubuntu Linux OS and uses the Jetpack SDK, which supports Nvidia’s CUDA developer environment, as well as other common AI frameworks, such as TensorRT, VisionWorks, and OpenCV.

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  • Fraud detection techniques mostly stem from the anomaly detection branch of data science.
  • If the dataset has sufficient number of fraud examples, supervised machine learning algorithms for classification like random forest, logistic regression can be used for fraud detection.
  • If the dataset has no fraud examples, we can use either the outlier detection approach using isolation forest technique or anomaly detection using the neural autoencoder.
  • After the machine learning model has been trained, it’s evaluated on the test set using metrics such as sensitivity and specificity, or Cohen’s Kappa.

With global credit card fraud loss on the rise, it is important for banks, as well as e-commerce companies, to be able to detect fraudulent transactions (before they are completed).

According to the Nilson Report, a publication covering the card and mobile payment industry, global card fraud losses amounted to $22.8 billion in 2016, an increase of 4.4% over 2015. This confirms the importance of the early detection of fraud in credit card transactions.

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Several companies, like SignAll and Kintrans, have created hand-tracking software that tries, with little success so far, to allow the millions of people that use sign language and an app to easily communicate with anyone.

Now, a new hand-tracking algorithm from Google’s AI labs might be a big step in making this ambitious software everything it originally promised.

RELATED: THIS SMARTPHONE APP CAN SAVE YOUR LIFE WITH JUST 3 WORDS

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Some call it “strong” AI, others “real” AI, “true” AI or artificial “general” intelligence (AGI)… whatever the term (and important nuances), there are few questions of greater importance than whether we are collectively in the process of developing generalized AI that can truly think like a human — possibly even at a superhuman intelligence level, with unpredictable, uncontrollable consequences.

This has been a recurring theme of science fiction for many decades, but given the dramatic progress of AI over the last few years, the debate has been flaring anew with particular intensity, with an increasingly vocal stream of media and conversations warning us that AGI (of the nefarious kind) is coming, and much sooner than we’d think. Latest example: the new documentary Do you trust this computer?, which streamed last weekend for free courtesy of Elon Musk, and features a number of respected AI experts from both academia and industry. The documentary paints an alarming picture of artificial intelligence, a “new life form” on planet earth that is about to “wrap its tentacles” around us.

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NEW DELHI (AP) — An unmanned spacecraft India launched last month began orbiting the moon Tuesday as it approaches the lunar south pole to study previously discovered water deposits.

The Indian Space Research Organization said it successfully maneuvered Chandrayaan-2, the Sanskrit word for “moon craft,” into lunar orbit, nearly a month after it left Earth. The mission is led by two female scientists.

Chandrayaan will continue circling the moon in a tighter orbit until reaching a distance of about 100 kilometers (62 miles) from the moon’s surface.

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WASHINGTON — If you’ve ever tried to swat a fly, you know that insects react to movement extremely quickly. A newly created biologically inspired compound eye is helping scientists understand how insects use their compound eyes to sense an object and its trajectory with such speed. The compound eye could also be used with a camera to create 3D location systems for robots, self-driving cars and unmanned aerial vehicles.

In The Optical Society (OSA) journal Optics Letters, researchers from Tianjin University in China report their new bio-inspired compound eye, which not only looks like that of an insect but also works like its natural counterpart. Compound eyes consist of hundreds to thousands of repeating units known as ommatidia that each act as a separate visual receptor.

“Imitating the vision system of insects has led us to believe that they might detect the trajectory of an object based on the light intensity coming from that object rather than using precise images like human vision,” said Le Song, a member of the research team. “This motion-detection method requires less information, allowing the insect to quickly react to a threat.”

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