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In a new report published on Scientific Reports, Milan M. Milošević and an international research team at the Zepler Institute for Photonics and Nanoelectronics, Etaphase Incorporated and the Departments of Chemistry, Physics and Astronomy, in the U.S. and the U.K. Introduced a hyperuniform-disordered platform to realize near-infrared (NIR) photonic devices to create, detect and manipulate light. They built the device on a silicon-on-insulator (SOI) platform to demonstrate the functionality of the structures in a flexible, silicon-integrated circuit unconstrained by crystalline symmetries. The scientists reported results for passive device elements, including waveguides and resonators seamlessly integrated with conventional silicon-on-insulator strip waveguides and vertical couplers. The hyperuniform-disordered platform improved compactness and enhanced energy efficiency as well as temperature stability, compared to silicon photonic devices fabricated on rib and strip waveguides.

Academic and commercial efforts worldwide in the field of silicon photonics have led to engineer optical data communications at the Terabit-scale at increasingly lower costs to meet the rapidly growing demand in data centers. Explosive growth in cloud computing and entertainment-on-demand pose increasingly challenging costs and energy requirements for , processing and storage. Optical interconnects can replace traditional copper-based solutions to offer steadily increasing potential to minimize latency and , while maximizing the bandwidth and reliability of the devices. Silicon photonics also leverage large-scale, complementary metal-oxide semiconductor (CMOS) manufacturing processes to produce high-performance optical transceivers with high yield at low-cost. The properties allow applications of optical transceivers (fiber optical technology to send and receive data) to be increasingly compelling across shorter distances.

More than three decades ago, physicist Richard Soref identified silicon as a promising material for photonic integration. Leading to the present-day steady development and rapid production of increasingly complex photonic integrated circuits (PICs). Researchers can integrate large numbers of massively-parallel compact energy-efficient optical components on a single chip for cloud computing applications from deep learning to artificial intelligence and the internet of things. Compared to the limited scope of commercial silicon photonic systems, photonic crystal (PhC) architectures promise smaller device sizes, although they are withheld by layout constraints imposed by waveguide requirements along the photonic crystal’s axis. Until recently, photonic band gap (PBG) structures that efficiently guide light were limited to photonic crystal platforms. Now, newer classes of PBG structures include photonic quasicrystals, hyperuniform disordered solids (HUDs) and local self-uniform structures.

Brain cancer remains challenging to diagnose, due to nonspecific symptoms and a lack of cost-effective tests. A new blood test that uses attenuated total reflection (ATR)-Fourier transform infrared (FTIR) spectroscopy in conjunction with machine learning technology, may help advance the detection of brain cancer.

The patented technology, developed by a team at the University of Strathclyde, uses infrared light to produce a “bio-signature” of a blood sample and applies artificial intelligence to check for the signs of cancer.

The research is published in Nature Communications in a paper titled, “Development of high-throughput ATR-FTIR technology for rapid triage of brain cancer.

One of the new products unveiled at CES this year is a new kind of home security system — one that includes drones to patrol your property, along with sensors designed to mimic garden light and a central processor to bring it all together.

Sunflower Labs debuted their new Sunflower Home Awareness System, which includes the eponymous Sunflowers (motion and vibration sensors that look like simple garden lights but can populate a map to show you cars, people and animals on or near your property in real time); the Bee (a fully autonomous drone that deploys and flies on its own, with cameras on board to live-stream video); and the Hive (a charging station for the Bee, which also houses the brains of the operation for crunching all the data gathered by the component parts).

Roving aerial robots keeping tabs on your property might seem a tad dystopian, and perhaps even unnecessary, when you could maybe equip your estate with multiple fixed cameras and sensors for less money and with less complexity. But Sunflower Labs thinks its security system is an evolution of more standard fare because it “learns and reacts to its surroundings,” improving over time.

Drastic miniaturization of electronics and ingression of next-generation nanomaterials into space technology have provoked a renaissance in interplanetary flights and near-Earth space exploration using small unmanned satellites and systems. As the next stage, the NASA’s 2015 Nanotechnology Roadmap initiative called for new design paradigms that integrate nanotechnology and conceptually new materials to build advanced, deep-space-capable, adaptive spacecraft. This review examines the cutting edge and discusses the opportunities for integration of nanomaterials into the most advanced types of electric propulsion devices that take advantage of their unique features and boost their efficiency and service life. Finally, we propose a concept of an adaptive thruster.

Recent AI lecture by Stanford University.


What do web search, speech recognition, face recognition, machine translation, autonomous driving, and automatic scheduling have in common? These are all complex real-world problems, and the goal of artificial intelligence (AI) is to tackle these with rigorous mathematical tools.

In this course, you will learn the foundational principles that drive these applications and practice implementing some of these systems. Specific topics include machine learning, search, game playing, Markov decision processes, constraint satisfaction, graphical models, and logic. The main goal of the course is to equip you with the tools to tackle new AI problems you might encounter in life.

Instructors:

Tesla vehicles are apparently going to talk to people not only inside the car but also outside. CEO Elon Musk even released a quick preview video.

It’s no secret that Tesla wants to use more artificial intelligence in its business.

Two years ago, Tesla hired Andrej Karpathy to lead its computer vision and AI team and they have been expanding their team since then.

“A new model based on the blood-vessel network in a rat brain shows that the vessel position within its circulatory network does not influence the blood flow nor how nutrients are transported. Instead, transport is controlled mostly by the dilation of vessels. As well as providing new insights into the circulatory system, the model could lead to better artificial tissues and brain-scanning techniques – and might even improve the performance of solar panels.”

Nutrient flow in the brain is controlled by blood-vessel dilation, reveals network model

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New understanding of blood transport could lead to better solar panels.

Interesting research paper on a new nanobot technology. I’m watching for ways in which suitable substrates for mind uploading can be constructed, and DNA self-guided assembly has potential.

Here are some excerpts and a weblink to the paper:

“…Chemical approaches have opened synthetic routes to build dynamic materials from scratch using chemical reactions, ultimately allowing flexibility in design…”

… As a realization of this concept, we engineered a mechanism termed DASH—DNA-based Assembly and Synthesis of Hierarchical materials—providing a mesoscale approach to create dynamic materials from biomolecular building blocks using artificial metabolism. DASH was developed on the basis of nanotechnology that uses DNA as a generic material ranging from nanostructures to hydrogels, for enzymatic substrates, and as linkers between nanoparticles…”

“…Next, to illustrate the potential uses of self-generated materials, we created various hybrid functional materials from the DASH patterns. The DASH patterns served as a versatile mesoscale scaffold for a diverse range of functional nanomaterials beyond DNA, ranging from proteins to inorganic nanoparticles, such as avidin, quantum dots, and DNA-conjugated gold nanoparticles (AuNPs) (Fig. 4D, figs. S37 and S38, and Supplementary Text). The generated patterns were also rendered functional with catalytic activity when conjugated with enzymes (figs. S39 and S40 and Supplementary Text). We also showed that the DNA molecules within the DASH patterns retained the DNA’s genetic properties and that, in a cell-free fashion, the materials themselves successfully produced green fluorescent proteins (GFPs) by incorporating a reporter gene for sfGFP (Fig. 4E and figs. S9 and S41) (40). The protein production capability of the materials established the foundation for future cell-free production of proteins, including enzymes, in a spatiotemporally controlled manner.

…” Our implementation of the concept, DASH, successfully demonstrated various applications of the material. We succeeded in constructing machines from this novel dynamic biomaterial with emergent regeneration, locomotion, and racing behaviors by programming them as a series of FSAs. Bottom-up design based on bioengineering foundations without restrictions of life fundamentally allowed these active and programmable behaviors. It is not difficult to envision that the material could be integrated as a locomotive ele-ment in biomolecular machines and robots. The DASH patterns could be easily recognized by naked eyes or smartphones, which may lead to better detection technologies that are more feasible in point-of-care settings. DASH may also be used as a template for other materials, for example, to create dynamic waves of protein expression or nanoparticle assemblies. In addition, we envision that further expansion of artificial metabolism may be used for self-sustaining structural components and self-adapting substrates for chemical production pathways. Ultimately, our material may allow the construction of self-reproducing machines through the production of enzymes from generated materials that, in turn, reproduce the material. Our biomaterial powered by artificial metabolism is an important step toward the creation of “artificial” biological systems with dynamic, life-like capabilities.”…


Zume Pizza, the Mountain View company that used robots to make its pizzas, has made its last delivery.

In filings with the state Employment Development Department, Zume said it is cutting 172 jobs in Mountain View, and eliminating another 80 jobs at its facility in San Francisco. Zume Chief Executive Alex Garden made the annoucement about Zume in an email to company employees on Wednesday.

“With admiration and sadness, we are closing Zume Pizza today,” Garden said in his email “Over the last four years this business has been our invention test bed and has been our inspiration for many of the growth businesses we have at Zume today.”