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Aung Thiha
Biomedical Engineer, Scientist, Transhumanist
Biomedical Engineer, Scientist, Transhumanist


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The source code for the neural network (a generative adversarial network aka GAN) that produced the celebrity photos has been released.

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Breakthrough in efforts to 'supercharge' rice and reduce world hunger

Scientists have taken an important step in a long-term project aimed at improving photosynthesis in rice to increase crop yields and help meet the food needs of billions of people around the world.

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"Woebot: AI for mental health." "While a software chatbot will never replace a human therapist, Woebot makes it possible to inexpensively deliver counseling to millions. Woebot delivers a mood management program based on Cognitive Behavior Therapy (CBT). A Stanford University randomized controlled trial showed that Woebot reduced symptoms of depression and anxiety in 2 weeks."

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Summary of roughly related progress in 2017 (July to Sept). Theme is biology, computing, nanobots (DNA robots), data storage.


These DNA robots created at Caltech (14 Sept 2017) can arrange-sort molecules. Very handy indeed these nanobots: "...several hands and arms, for example, could be used to carry multiple molecules simultaneously."

Caltech: "In the work described in the Science paper, the Qian group built a robot that could explore a molecular surface, pick up two different molecules—a fluorescent yellow dye and a fluorescent pink dye—and then distribute them to two distinct regions on the surface. Using fluorescent molecules enabled the researchers to see if the molecules ended up in their intended locations. The robot successfully sorted six scattered molecules, three pink and three yellow, into their correct places in 24 hours. Adding more robots to the surface shortened the time it took to complete the task."

Apparently these DNA "walker" bots are energy-efficient too, The Register reported (25 Sept 2017): "Sticking and unsticking itself in this way does not consume energy since the walker is not gaining or losing any of its DNA bases."

Go search for more mews about DNA robots:


What is ribocomputing? RNA instead of DNA creates logic circuits, nano-devices, to act as computers-robots-processors. Harvard’s Wyss Institute, for Biologically Inspired Engineering, published this news on 26 July 2017.

Wyss Institute wrote: "The study’s approach resulted in a genetically encodable RNA nano-device that can perform an unprecedented 12-input logic operation to accurately regulate the expression of a fluorescent reporter protein in E. coli bacteria only when encountering a complex, user-prescribed profile of intra-cellular stimuli. Such programmable nano-devices may allow researchers to construct more sophisticated synthetic biological circuits, enabling them to analyze complex cellular environments efficiently and to respond accurately."

Science Daily (26 July 2017) introduced this topic of ribocomputing by mentioning the speed of progress: "The interdisciplinary nexus of biology and engineering, known as synthetic biology, is growing at a rapid pace, opening new vistas that could scarcely be imagined a short time ago." Science daily elaborated: "The new study dramatically improves the ease with which cellular computing may be carried out. The RNA-only approach to producing cellular nanodevices is a significant advance, as earlier efforts required the use of complex intermediaries, like proteins. Now, the necessary ribocomputing parts can be readily designed on computer. The simple base-pairing properties of RNA's four nucleotide letters (A, C, G and U) ensure the predictable self-assembly and functioning of these parts within a living cell."


Engadget, 26 Sept 2017, reported on the "Loihi" neuromorphic processor: "Intel unveils an AI chip that mimics the human brain." Intel have been working on it for the past six years...

Engadget: "Intel's Loihi chip has 1,024 artificial neurons, or 130,000 simulated neurons with 130 million possible synaptic connections. That's a bit more complex than, say, a lobster's brain, but a long ways from our 80 billion neurons."

The Verge and ExtremeTech also reported (others reported too)...

The Verge (26 Sept 2017) commenting on the as yet unproven advantages, or hype, of neuromorphic chips: "Intel knows this [they are unproven], of course, and its new Loihi chips aren’t destined for server stacks. Instead, the company will be sharing an unknown number with a few “leading university and research institutions” some time in the first half of 2018. (How many chips and who will get them are unknown.) This research will hopefully validate Intel’s designs, as well as push forward work on neuromorphic chips and AI in general."

ExtremeTech (27 Sept 2017) "Dr. Michael Mayberry claims that Loihi does not need to be trained in the traditional way and that it takes a new approach to this type of computing by using asynchronous spiking. Unlike a transistor, neurons do not constantly flip back and forth between a 0 and a 1. They trigger when signal thresholds are reached, and continue to fire so long as the number of spikes exceeds a given threshold. The strength of a muscle flex, for example, is based on the average number of spikes the muscle receives over a given unit of time."


Oxford University (15 August 2017) published news about a new method of 3D-bioprinting: "The approach could revolutionise regenerative medicine, enabling the production of complex tissues and cartilage that would potentially support, repair or augment diseased and damaged areas of the body."

Oxford University elaborated: "Printing high-resolution living tissues is hard to do, as the cells often move within printed structures and can collapse on themselves. But, led by Professor Hagan Bayley, Professor of Chemical Biology in Oxford’s Department of Chemistry, the team devised a way to produce tissues in self-contained cells that support the structures to keep their shape." The fine-tuning period should be worth waiting for: "Over the coming months they will work to develop new complementary printing techniques, that allow the use of a wider range of living and hybrid materials, to produce tissues at industrial scale."

University of Bristol’s School of Cellular and Molecular Medicine also was involved in this bioprinting research (15 August 2017), which: "...demonstrated how a range of living mammalian cells can be printed into high-resolution tissue constructs."


University of Manchester shows storing data via "single-molecule magnets" is "more feasible than previously thought."

PhysOrg (23 Aug 2017) "The result means that data storage with single molecules could become a reality because the data servers could be cooled using relatively cheap liquid nitrogen at -196°C instead of far more expensive liquid helium (-269 °C). The research provides proof-of-concept that such technologies could be achievable in the near future."

Identical report to above PhysOrg one, here is the link to the Manchester Uni "single-molecule magnets" news :

Chemical & Engineering News (30 Aug 2017) wrote: "The quest to develop smaller and more energy-efficient smartphones and supercomputers with more features and processing power hinges on increasing data storage capacity. Two research groups at the University of Manchester have reported a dysprosium molecule with switchable magnetic properties—a single-molecule magnet (SMM) with the ability to store a single bit of data—that exhibits the most promise yet for reaching what might be the ultimate limit in high-density data storage."

Digital Trends (24 Aug 2017) was cautious about the molecular storage progress, whilst nevertheless recognising the value of the breakthrough: "Don’t get too excited yet, however, as a lot more engineering work needs to be carried out to turn this into a practical technology. It is unlikely that this particular molecule will ever be commercialized but the team is working to make even better magnetic molecules which could be used to carry out this task."

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A deep learning IDE from Microsoft. "Visual Studio Code Tools for AI is an extension to build, test, and deploy Deep Learning / AI solutions in Microsoft Visual Studio Code. This allows you to develop deep learning and AI solutions across Windows and MacOS."

Works with Microsoft Cognitive Toolkit (CNTK), Google TensorFlow, and other frameworks, integrates with Azure Machine Learning, and has familiar code editor features like syntax highlighting, IntelliSense (auto-completion), text auto formatting, and step-through debugging on local variables and models.

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