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Researchers at the Research Center for IT Innovation of Academia Sinica, in Taiwan, have recently developed a novel generative adversarial network (GAN) that has binary neurons at the output layer of the generator. This model, presented in a paper pre-published on arXiv, can directly generate binary-valued predictions at test time.

So far, GAN approaches have achieved remarkable results in modeling continuous distributions. Nonetheless, applying GANs to discrete data has been somewhat challenging so far, particularly due to difficulties in optimizing the model distribution toward the target data distribution in a high-dimensional discrete space.

Hao-Wen Dong, one of the researchers who carried out the study, told Tech Xplore, “I am currently working on music generation in the Music and AI Lab at Academia Sinica. In my opinion, composing can be interpreted as a series of decisions—for instance, regarding the instrumentation, chords and even the exact notes to use. To move toward achieving the grand vision of a solid AI composer, I am particularly interested in whether deep generative models such as GANs are able to make decisions. Therefore, this work examined whether we can train a GAN that uses binary neurons to make binary decisions using backpropagation, the standard training algorithm.”

Continue reading “BinaryGAN: a generative adversarial network with binary neurons” »

Many A.I. experts are concerned that Facebook, Google and a few other big companies are hoarding talent in the field. The internet giants also control the massive troves of online data that are necessary to train and refine the best machine learning programs.

Several start-ups hope to use the technology introduced by Bitcoin to give broader access to the data and algorithms behind artificial intelligence.

The pace of AI change continues to accelerate, so for example, say hello to Google’s children.

Google Brain’s researchers created the AutoML, an AI algorithm capable of generating its own AIs, thereby eliminating the need to hire human experts.

MIT will reshape itself to shape the future, investing $1 billion to address the rapid evolution of computing and AI — and its global effects. At the heart of this effort: a $350 million gift to found the MIT Stephen A. Schwarzman College of Computing.

Photo: Christopher Harting

Perhaps physicists should leave human intuition at the laboratory door when designing quantum experiments too.

An Australian crew enlisted the help of a neural network — a type of artificial intelligence — to optimise the way they capture super-cold atoms.

Usually, physicists smoothly tune lasers and magnetic fields to gradually coax atoms into a cloud, according to study co-author Ben Buchler from the Australian National University.

Continue reading “Artificial intelligence better than physicists at designing quantum science experiments” »

Earlier this year, we hosted the Ending Age-Related Diseases 2018 conference at the Cooper Union, New York City. This conference was designed to bring together the best in the aging research and biotech investment worlds and saw a range of industry experts sharing their insights.

Joe Betts Lacroix of Y Combinator and Vium discusses the different ways in which entrepreneurs can focus on overcoming the diseases of aging, namely direct, indirect, and money-first approaches, and the strengths and weakness of each.

Continue reading “Joe Betts Lacroix – Entrepreneurial Focuses on Aging” »

A new tool using data and AI is hoping to better predict famine and help millions experiencing food insecurity.

Two of the methods he said humans might use were “body part renewal” and linking bodies with machines so that people are living their lives through an android.

But after Dr Pearson’s predictions, immortality may now be a step nearer following the launch of a new start-up.

Human is hoping to make the immortality dream a reality with an ambitious plan.

Continue reading “Humans beings on the brink of IMMORTALITY, top scientist claims” »

Judging by the breathless coverage, it can seem as if the only countries developing A.I. are the United States and China. But while companies in those two countries are leading the way in cutting-edge research and products, it’s still early for the industry and other nations are working hard to become major A.I. players. Here are six that could challenge the two juggernauts.

From Singapore to Israel, countries besides the United States and China are striving to play a role in the field of artificial intelligence.