Lifeboat Foundation

Coca-Cola is ditching flesh and blood creatives in favour of software algorithms in an experiment to see whether AI bots have what it takes to beat their human masters.

Mariano Bosaz, Coca-Cola’s global senior digital director, is spearheading the move as part of wider efforts to push the bounds of technology to see what they are capable of.

In an interview with Adweek at Mobile World Congress in Barcelona Bosaz said: “Content creation is something that we have been doing for a very long time—we brief creative agencies and then they come up with stories that they audio visualize and then we have 30 seconds or maybe longer. In content, what I want to start experimenting with is automated narratives.”

Continue reading “Coca-Cola chooses AI over brains to generate latest adverts” »

How do molecules rotate in a solvent? Answering this question is complicated, since molecular rotation is perturbed by a very large number of surrounding atoms. For a long time, large-scale computer simulations have been the main approach to model molecule-solvent interactions. However, they are extremely time consuming and sometimes infeasible. Now, Mikhail Lemeshko from the Institute of Science and Technology Austria (IST Austria) has proven that angulons—a certain type of quasiparticle he proposed two years ago—do, in fact, form when a molecule is immersed in superfluid helium. This offers a quick and simple description for rotation of molecules in solvents.

In physics, the concept of quasiparticles is used as a technique to simplify the description of many-particle systems. Namely, instead of modeling strong interactions between trillions of individual particles, one identifies building blocks of the system that are only weakly interacting with one another. These building blocks are called quasiparticles and might consist of groups of particles. For example, to describe air bubbles rising up in water from first principles, one would need to solve an enormous set of equations describing the position and momentum of each water molecule. On the other hand, the bubbles themselves can be treated as individual particles—or quasiparticles—which drastically simplifies the description of the system. As another example, consider a running horse engulfed in a cloud of dust. One can think of it as a quasiparticle consisting of the horse itself and the dust cloud moving along with it.

We can even use a vacuum to explain how Quantum is in all things while solving one of the remaining discrepancies in physics.

In the observable universe, number of particles are estimated to be 10⁸⁰ and if there were some discrepancy in Physics with the explanations of the observable universe or with its each particle then it should confine to factor 10⁸⁰. I submit that 10⁸⁰ is a huge figure that forms if one puts eighty zeros after 1. But if the discrepancy is of the factor 10¹²⁰ then either it is beyond the total number of particles constituting the universe or the physicists might have gravely erred in their calculations. It might be a freak happening that resulted in such a huge quantity. After all, freaks are also the creations of nature or probably the nature itself has erred here. This discrepancy of 10¹²⁰ is the largest and worst cosmological confusion which can be abbreviated CC and rightly so for cosmological constant as it is the cosmological constant based on Quantum mechanical model. Quantum mechanical model says, energy density of the vacuum is in the range of 10¹¹³ Joules per metre cube whereas General Relativity calculates it in the range of 10^−9 Joule per metre cube. An attempt is made to resolve this discrepancy using Spacetime transformation and gravitational gamma Г. Gravitational gamma Г is a term that appears in Schwarzschild solution of general relativity equations.

I submit that vacuum is not nothing but is everything and quantum mechanical model of the vacuum has very large energy density. In the words of John Archibald Wheeler, “Empty space is not empty… The density of field fluctuation energy in the vacuum argues that elementary particles represent percentage‐ wise almost completely negligible change in the locally violent conditions that characterise the vacuum.” That means there are violent conditions or fluctuations although vacuum on large scale appears smooth. Spacetime model has the capability of creating matter, forces, fields and particles. In fact, matter even the entire universe is assumed as spacetime as has been explained in my earlier article, “Matter Is No More Than Fluctuations In Vacuum*.”

Continue reading “Resolution Of Largest Numerical Discrepancy In All Of Physics” »

What deep learning algorithms can tell us about the visual narratives of the world’s news imagery, from depictions of violence to the importance of people to visual context – a look inside what we see about the world around us.

From digital currency to machine learning, the financial industry is being rocked by exponential technologies. Blockchain, artificial intelligence, big data, robotics, quantum computing, crowdfunding, and computing systems are allowing startups to solve consumer needs in new ways.

The downfall of the world’s largest institutions may not be imminent, but these new technologies are breaking up the previously rock solid foundation of finance, and allowing the fintech world to spring through the cracks. What’s happening now will rewrite the future of finance for years to come. By recognizing this reality and planning for it now, financial professionals can learn to thrive in an increasingly uncertain global economy.

Continue reading “Financial Leaders: Make Your Mark on the Future at Exponential Finance” »

BMI is coming fast and will replace many devices we have today. Advances we making in deep brain development are huge markers that pushes the BMI needle forward for the day when IoT, Security, and big data analytics is a human brain’s and a secured Quantum Infrastructure and people (not servers sitting somewhere) owns and manages their most private of information. I love calling it the age of people empowerment as well as singularity.

Small study in 16 people suggests technique is safe and might help improve mood, anxiety and wellbeing, while increasing weight.

Deep brain stimulation might alter the brain circuits that drive anorexia nervosa symptoms and help improve patients’ mental and physical health, according to a small study published in The Lancet Psychiatry.

Continue reading “Deep brain stimulation for patients with chronic anorexia is safe and might improve symptoms” »

(Phys.org)—Physicists are getting a little bit closer to answering one of the oldest and most basic questions of quantum theory: does the quantum state represent reality or just our knowledge of reality?

George C. Knee, a theoretical physicist at the University of Oxford and the University of Warwick, has created an algorithm for designing optimal experiments that could provide the strongest evidence yet that the quantum state is an ontic state (a state of reality) and not an epistemic state (a state of knowledge). Knee has published a paper on the new strategy in a recent issue of the New Journal of Physics.

While physicists have debated about the nature of the quantum state since the early days of quantum theory (with, most famously, Bohr being in favor of the ontic interpretation and Einstein arguing for the epistemic one), most modern evidence has supported the view that the quantum state does indeed represent reality.

Continue reading “Proposed test would offer strongest evidence yet that the quantum state is real” »

Interestingly, Seager, who studies bio signatures in exoplanet atmospheres, has suggested that two inhabited planets could reasonably turn up during the next decade, based on her modified version of the Drake equation, Space.com notes. Her equation focuses on the search for planets with biosignature gases — gases produced by life that can accumulate in a planet atmosphere to levels that can be detected with remote space telescopes.

Continue reading “NASA announces Wed. news conference on ‘discovery beyond our solar system’” »

It wasn’t that long ago that building and training neural networks was strictly for seasoned computer scientists and grad students. That began to change with the release of a number of open-source machine learning frameworks like Theano, Spark ML, Microsoft’s CNTK, and Google’s TensorFlow. Among them, TensorFlow stands out for its powerful, yet accessible, functionality, coupled with the stunning growth of its user base. With this week’s release of TensorFlow 1.0, Google has pushed the frontiers of machine learning further in a number of directions.

TensorFlow isn’t just for neural networks anymore

In an effort to make TensorFlow a more-general machine learning framework, Google has added both built-in Estimator functionality, and support for a number of more traditional machine learning algorithms including K-means, SVM (Support Vector Machines), and Random Forest. While there are certainly other frameworks like SparkML that support those tools, having a solution that can combine them with neural networks makes TensorFlow a great option for hybrid problems.

Continue reading “Google gives everyone machine learning superpowers with TensorFlow 1.0” »