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In the 2015 movie “Chappie”, which is set in the near future, automated robots comprise a mechanised police force. An encounter between two rival criminal gangs severely damages the law enforcing robot (Agent 22). His creator Deon recommends dismantling and recycling the damaged police droids. However, criminals kidnap Deon and force him to upload human consciousness into the damaged robot to train it to rob banks. Chappie becomes the first robot with the human mind who can think and feel like a human. Later, in the movie when his creator Deon is dying, it’s Chappie’s turn to upload Deon’s consciousness into a spare robot through a neural helmet. Similarly, in the “Avatar” a 2009 Hollywood science fiction, a character in the film by name Grace connects with Eiwa, the collective consciousness of the planet and transfers her mind to her Avatar body, while another character Jake transfers his mind to his Avatar body rendering his human body lifeless.

Mind uploading is a process by which we relocate the mind, an assemblage of memories, personality, and attributes of a specific individual, from its original biological brain to an artificial computational substrate. Mind uploading is a central conceptual feature of many science fiction novels and films. For instance, Hanson’s book titled “The Age of Em: Work, Love and Life when Robots Rule the Earth” is a 2016 nonfiction book which explores the implications of a future world when researchers have learned to copy humans onto computers, creating “ems,” or emulated people, who quickly come to outnumber the real ones.

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.

  • 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.

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.

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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.

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.