Memristor

A memristor is a hypothetical non-linear passive two-terminal electrical componentrelating electric charge and magnetic flux linkage. It was envisioned, and its name coined, in 1971 by circuit theorist Leon Chua.^[1] According to the characterizing mathematical relations, the memristor would hypothetically operate in the following way: The memristor's electrical resistance is not constant but depends on the history of current that had previously flowed through the device, i.e., its present resistance depends on how much electric charge has flowed in what direction through it in the past; the device remembers its history — the so-called non-volatility property.^[2] When the electric power supply is turned off, the memristor remembers its most recent resistance until it is turned on again.^[3][4]

In 2008, a team at HP Labs claimed to have found Chua's missing memristor based on an analysis of a thin film of titanium dioxide thus connecting the operation of RRAM devices to the memristor concept; the HP result was published in Nature.^[3] Following this claim, Leon Chua has argued that the memristor definition could be generalized to cover all forms of two-terminal non-volatile memory devices based on resistance switching effects.^[2] There are, however, some serious doubts as to whether the memristor can actually exist in physical reality.^[5][6][7]Additionally, some experimental evidence contradicts Chua's generalization since a non-passive nanobattery effect is observable in resistance switching memory.^[8] Chua also argued that the memristor is the oldest known circuit element, with its effects predating the resistor, capacitor and inductor.^[9]

These devices are intended for applications in nanoelectronic memories, computer logic and neuromorphic/neuromemristive computer architectures.^[10] Commercial availability of memristor memory has been estimated as 2018.^[11] In March 2012, a team of researchers from HRL Laboratories and the University of Michigan announced the first functioning memristor array built on a CMOSchip.^[12]

Electronic nose

An electronic nose is a device intended to detect odors or flavors.

Over the last decade, "electronic sensing" or "e-sensing" technologies have undergone important developments from a technical and commercial point of view. The expression "electronic sensing" refers to the capability of reproducing human senses using sensor arrays and pattern recognition systems. Since 1982,^[2] research has been conducted to develop technologies, commonly referred to as electronic noses, that could detect and recognize odors and flavors. The stages of the recognition process are similar to human olfaction and are performed for identification, comparison, quantification and other applications, including data storage and retrieval. However, hedonic evaluation is a specificity of the human nose given that it is related to subjective opinions. These devices have undergone much development and are now used to fulfill industrial needs.

Ferroelectric liquid crystal display

Ferroelectric Liquid Crystal Display (FLCD) is a display technology based on the ferroelectric properties of chiral smectic liquid crystals. It has been proposed in 1980 by Clark and Lagerwall.^[1]

As direct-view displays, the FLCD could not displace the LCDs based on nematic liquid crystals using the Twisted nematic field effector In-Plane Switching. Today, the FLCD is not used as direct-view display but in microdisplays based on Liquid Crystal on Silicon devices. Used in LCoS the dot pitch of such displays can be as low as 8 µm giving a very high resolution display on a small area. To produce color and grey-scale, time multiplexing is used, exploiting the sub-millisecond switching time. These find applications in 3D head mounted displays (HMD), image insertion in surgical microscopes and electronic view finders where direct-view LCDs fail to provide more than 600 ppi resolution.

Ferroelectric LCoS find commercial use also in Structured illumination in 3D-Metrology and Super-resolution microscopy.

Artificial Intelligence Can Predict How Scenes Will Play Out .

A new artificial intelligence system can take still images and generate short videos that simulate what happens next similar to how humans can visually imagine how a scene will evolve, according to a new study.

Humans intuitively understand how the world works, which makes it easier for people, as opposed to machines, to envision how a scene will play out. But objects in a still image could move and interact in a multitude of different ways, making it very hard for machines to accomplish this feat, the researchers said. But a new, so-called deep-learning systemwas able to trick humans 20 per cent of the time when compared to real footage.

Researchers at the Massachusetts Institute of Technology (MIT) pitted two neural networks against each other, with one trying to distinguish real videos from machine-generated ones, and the other trying to create videos that were realistic enough to trick the first system. [Super-Intelligent Machines: 7 Robotic Futures]

This kind of setup is known as a "generative adversarial network" (GAN), and competition between the systems results in increasingly realistic videos. When the researchers asked workers on Amazon’s Mechanical Turk crowdsourcing platform to pick which videos were real, the users picked the machine-generated videos over genuine ones 20 percent of the time, the researchers said.

Innovative Scratchpad

Paper and pencil are one of the main instruments for the materialization of thoughts and expressions of creativity, and therefore not all are willing to part with the usual notebook and writing “pen.” Developers of remarkable still took a chance and created an electronic analog, which, in their view, is able to become a worthy replacement with a mass of additional advantages.
The gadget that combines a tablet, e-reader and a notebook / sketch pad, equipped with a 10.3-inch E-ink carta touchscreen display with a resolution of 1872 x1404 points (226 pixels per inch). The screen is not covered with a protective or any other glass, so break the device will be extremely difficult. The manufacturer claims that when using remarkable there is a feeling as if writing on real paper. Electronic Marker Pen supports the recognition of degrees in 2048 presses and different angles of inclination, and does not require charging. All that is displayed with the stylus, instantly displayed – you can draw, make notes in books and documents, create sketches and handwritten notes. Any changes are automatically synchronized with the cloud and available on all user devices.
remarkable consists of a processor ARM Cortex-A9 processor with a clock frequency of 1.0 GHz, 512 MB RAM and 8 GB of internal flash memory, which is enough to store 100,000 pages of the module Wi-Fi wireless connection, the battery capacity of 3000 mah and port micro usb. As the OS performs Codex on the Linux kernel. Dimensions of the device are 177 x 256 x 6.7 mm and weighs 350 grams.