IT’S TIME TO MAKE HUMAN-CHIMP HYBRIDS
It is a bit of a stretch, but by no means impossible or even unlikely that a hybrid or a chimera combining a human being and a chimpanzee could be produced in a laboratory. After all, human and chimp (or bonobo) share, by most estimates, roughly 99 percent of their nuclear DNA. Granted this 1 percent difference presumably involves some key alleles, the newgene-editing tool CRISPR offers the prospect (for some, the nightmare) of adding and deleting targeted genes as desired.
Read moreFACEBOOK’S BET ON AN AUGMENTED REALITY FUTURE
Today, Facebook is fighting its fellow technology powerhouses, Apple AAPL +1.72% and Google — and still to some extent, Snap — in a high-stakes battle to rule as the platform of choice for AR developers. The technology itself, while still in its infancy, has exploded in popularity, confirming Zuckerberg’s more recent intuition that AR could sprint toward mass adoption even while VR remained an awkward technology whose appeal is largely limited to hardcore gamers. AR’s key advantage is that it doesn’t depend on a pricey, bulky headset that isolates its users.
Read moreSTUDYING HOW THE BRAIN RELINQUISHES CHILDHOOD MEMORIES
We called them fairy rocks. They were just colorful specks of gravel—the kind you might buy for a fish tank—mixed into my preschool’s playground sand pit. But my classmates and I endowed them with magical properties, hunted them like treasure, and carefully sorted them into piles of sapphire, emerald, and ruby. Sifting the sand for those mystical gems is one of my earliest memories. I was no older than 3 at the time. My memory of kindergarten has likewise been reduced to isolated moments: tracing letters on tan paper with pink dashed lines; watching a movie about ocean creatures; my teacher slicing up a giant roll of parchment so we could all finger-paint self-portraits.
Read moreDIVING INTO DEEP CONVOLUTIONAL SEMANTIC SEGMENTATION NETWORKS AND DEEPLAB_V3
Deep Convolutional Neural Networks (DCNNs) have achieved remarkable success in various Computer Vision applications. Like others, the task of semantic segmentation is not an exception to this trend. Source: freecodecamp.org
REPTILE: A SCALABLE META-LEARNING ALGORITHM
We’ve developed a simple meta-learning algorithm called Reptile which works by repeatedly sampling a task, performing stochastic gradient descent on it, and updating the initial parameters towards the final parameters learned on that task. This method performs as well as MAML, a broadly applicable meta-learning algorithm, while being simpler to implement and more computationally efficient. Source: openai.com
WILL THE QUANTUM NATURE OF GRAVITY FINALLY BE MEASURED?
In 1935, when both quantum mechanics and Albert Einstein’s general theory of relativity were young, a little-known Soviet physicist named Matvei Bronstein, just 28 himself, made the first detailed study of the problem of reconciling the two in a quantum theory of gravity. This “possible theory of the world as a whole,” as Bronstein called it, would supplant Einstein’s classical description of gravity, which casts it as curves in the space-time continuum, and rewrite it in the same quantum language as the rest of physics.
Read moreANNA: A CRAZY FAST, SUPER-SCALABLE, FLEXIBLY CONSISTENT KVS
There’s fast and there’s fast. This post is about Anna*, a key/value database design from our team at Berkeley that’s got phenomenal speed and buttery smooth scaling, with an unprecedented range of consistency guarantees. Details are in our upcoming ICDE18 paper on Anna. Source: wordpress.com
ADVANCED NUCLEAR TECHNOLOGY JUST GOT A BIG GREEN LIGHT FROM CONGRESS
The US Senate has passed a bill that could accelerate thedevelopment of advanced nuclear reactors, providing a boost to technologies that promise to make nuclear power cheaper, safer, and easier to build. Source: technologyreview.com
GOOGLE THINKS IT’S CLOSE TO ‘QUANTUM SUPREMACY’.HERE’S WHAT THAT REALLY MEANS.
Hopes of reaching quantum supremacy have been dashed before. For some time, researchers thought that a 49-qubit machine would be enough, but last year researchers at IBM were able to simulate a 49-qubit quantum system on a conventional computer (see “New twists in the road to quantum supremacy”). Nor are conventional computers standing still: China, in particular, has been investing heavily in the technology and now boasts the world’s two most powerful machines.
Read moreCAPSULE NEURAL NETWORKS ARE HERE TO FINALLY RECOGNIZE SPATIAL RELATIONSHIPS
Neural Networks may be the hottest field in Machine Learning. In recent years, there were many new developments improving neural networks and building making them more accessible. However, they were mostly incremental, such as adding more layers or slightly improving the activation function, but did not introduce a new type of architecture or topic. Geoffery Hinton is one of the founding fathers of many highly utilized deep learning algorithms including many developments to Neural Networks — no wonder, for having Neurosciences and Artificial Intelligence background. At late October 2017, Geoffrey Hinton, Sara Sabour, and Nicholas Frosst Published a research paper under Google Brain named “Dynamic Routing Between Capsules”, introducing a true innovation to Neural Networks.
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