The field of 3D medical vision self-supervised learning lacks consistency and standardization. While many methods have been developed it is impossible to identify the current state-of-the-art, due to i) varying and small pre-training datasets, ii) varying architectures, and iii) being evaluated on differing downstream datasets. In this paper we bring clarity to this field and lay the foundation for further method advancements: We a) publish the largest publicly available pre-training dataset comprising 114k 3D brain MRI volumes and b) benchmark existing SSL methods under common architectures and c) provide the code of our framework publicly to facilitate rapid adoption and reproduction. This pre-print \textit{only describes} the dataset contribution (a); Data, benchmark, and codebase will be made available shortly.

Nowadays, much of humanity's hopes are placed in the development of Artificial Intelligence (AI), which is seen as a way to cure diseases, improve diagnostics or care for the environment. However, there are also many fears motivated by the possibility that the algorithms could end up escaping human control. In fact, some intellectual figures of the stature of the late physicist Stephen Hawking have reflected on the apocalyptic risk of these technologies, a warning that has been joined by others such as tech magnate Elon Musk and UN High Commissioner for Human Rights Michelle Bachelet. While the debate continues, here is a series of developments in recent years that will neither save the world nor bring about its demise, but rather serve to entertain us with the more curious side of AI. Can the sexual orientation of people be detected by their appearance?

As businesses are increasingly depending on mobile footprints, competition is getting fierce to remain visible and discoverable in the app marketplace. Effortless and smooth user experience remains to be the key for most apps to stand out in the competition. This is why intelligent Chatbots equipped with the power of Artificial Intelligence (AI) have emerged as the most important mechanism for superb user experience. AI-powered Chatbots continue to make a transforming appearance for an increasing number of mobile apps across the niches. AI as a deeply embedded technology fetches most relevant business data and insights that businesses can use for replying to customer queries in the most contextual and relevant manner.

AI is continuing to permeate every aspect of human society, and the field of healthcare is no different. In fact, AI is already shaping this incredibly impactful and lucrative sector in such aspects as early-intervention scans, prediction models, and in the monitoring of patients with particular diagnoses. President Trump recently signed an Executive Order prioritizing the regulation and development of AI, and with this important development firmly in mind, it is time to take a look at the future advantages and disadvantages that will likely play out as AI continues to impact upon the healthcare sector. Costs in healthcare are already spiraling out of control as costly research practices, equipment and medicines escalate the financial impact upon ordinary people. Yet the way in which costs most greatly manifest in healthcare is through human resources.

Since 1953, when the term Artificial Intelligence was coined byJohn McCarthyin the Dartmouth Conference, we have achieved unthinkable highs: we have taught machines to see, to recognize images or text; we have taught them to read, to listen, speak, or translate.In spite of all of that, they are not even close to achieving full human-capacities; they don't comprehend, they don't understand or learn further beyond the environment in which they are placed. They have unmatched computing power, but little to none true creativity; a superb ability to combine and analyze probabilities, but not a single spark of unsupervised creativity. If someone tells you that the "singularity", the moment in which Artificial Intelligence achieves a definitive human-like character and overpasses our own biological limits on intelligence, is around the corner they are a bit too optimist -the consensus among experts in thatwe are still decades away from a singularity point, and some think we might never get to a true human-like intelligence-. Regardless of the time to a future in which we have to address machines as intellectually equal or superior, the revolution of AI is unstoppable in so many other ways. The amount of resources and talent devoted by the largest global corporations is accelerating a new industrial revolution in which the speed of adoption is increasingly faster than the pace of adaptation.

Two robotic arms that each hold a pen begin to draw with short strokes on two sheets of paper-- two eyes, a mouth and the silhouette of a face. They portray the front and profile view of Eliseo Carrera Bustillo, a 26-year-old student sitting on a stool while two cameras observe and analyse him closely. Both machines imitate the style of their creator--the French artist Patrick Tresset--and it only takes half an hour to finish the portrait and sign it. Nowadays, more and more artificial intelligence systems paint pictures, compose music, create poetry and write novels. But what difference is there between a work created by a machine and by a human?

In 1951, the Russian chemist Boris Belousov sent to a scientific journal a study in which he described an astonishing discovery: while trying to simulate a metabolic process in the laboratory, he had discovered a chemical reaction that occurred and then reversed itself on its own, alternating between a yellow colour and a colourless state. Belousov couldn't find any journal willing to publish his results, since they appeared to violate a fundamental law of nature. However, his work--which only came to light in 1959 through a brief presentation at a symposium--has become, half a century later, the foundation stone of a new discipline: chemical computing. This technological path is an alternative to quantum computing and conventional computing, capable of processing in parallel based on the same operating principles as our brain, promising futuristic applications, such as integrating in our body in the form of intelligent biosensors. Computing is based on the use of logic gates, which process a data input--usually in binary code--to produce a result or output.

During the last five years, the rise of AI has been truly astounding. From highly sophisticated robots and driverless cars, to a wide range of "under the bonnet" techniques that use AI, the market in AI is predicted to explode. According to a new report from market research firm Tractica [1], it is likely to grow from $643.7 million at the present time, to $36 billion by 2025. This represents a 57-fold increase over that time period. Yet, this is only the beginning.

The fact that increasingly complex automation is applied to problems that were solved entirely by humans opens the door to great opportunities but also to fallouts and shortcomings. According to consulting firm Accenture, American companies are expected to invest 35 trillion dollars in cognitive technologies before 2035, and that does not take into account other big players, such us Europe, China or Japan. Governments, such the French, are recognizing the importance of AI for the economy and the society. In Spain, the Ministry of Digital Agenda (Minetad) has created a group of experts that is working on a White Paper on AI.

Since the Enigma code was cracked using computers, humans have been forced to talk to machines in a way the latter could understand. Several languages were created, from assembler to Fortran, C, C, Java, Perl and Ruby, to name just a few. Most of these contained English keywords, but the syntax was still rigid and required high-level programming knowledge. What if you could talk to any computer or smart device in natural language and have it understand you? This is the bet behind NLP (Natural Language Processing). Right now, it is still about translating language into something a machine can process, but as the system incorporates more AI and learns from interactions, it will become more independent.