You will find information about our upcoming conference on "(Clinical) Neurotechnology meets Artificial Intelligence". The event takes place from May 8-10, 2019 in Munich (Germany). Project partners are located in Hamburg, Granada and Montreal. The project is funded by the Federal Ministry of Education and Research, as part of the ERANET Neuron program. In the upcoming months, we will fill this website with information about the program, travel and lodging and many more information about what we love to explore: the philosophy and ethics of neurotechnology and AI! Stay tuned!

Lael Brainard, a member of the Board of Governors of the Federal Reserve System, recently gave a speech titled What Are We Learning about Artificial Intelligence in Financial Services? Before I tell you what her answers were, I'll tell you what I think they're learning: Not enough. Brainard started her speech with the now-customary breathtaking "OMG, AI and data are transforming the world at an alarming rate!" intro that, apparently, all speakers are required to make these days when talking about AI. "The potential breadth and power of these new AI applications inevitably raise questions about potential risks to bank safety and soundness, consumer protection, or the financial system. The question, then, is how should we approach regulation and supervision? It is incumbent on regulators to review the potential consequences of AI, including the possible risks, and take a balanced view about its use by supervised firms."

Every day sees strides across the field of artificial intelligence, and healthcare is just one of the many industries looking to smart automation as a means to reduce burden and improve results. The last year in particular has brought a wealth of new healthcare focused software tools to the forefront, and as such has ignited debate on how these algorithms are being reviewed and regulated by the FDA. "FDA is lagging in the production of guidance to explain its approach for these newer products. This is a problem, because Commissioner Gottlieb himself in a blog post noted well over a year ago that individual decision-making by FDA is not enough for digital therapeutics to thrive," Bradley Merrill Thompson, a lawyer at Epstein Becker & Green who also leads CDS Coalition, an industry group, wrote in an email on the subject. "Industry has been asking since 2015 for better guidance on the use of software-based algorithms in connection with drug administration. The commissioner, starting in April 2018, has been promising new guidance focused on the use of software with drugs, and in fact reiterated that promise only a couple weeks ago. But the concern is that the new guidance may not be focused on the issues of greatest concern to industry. We shall have to wait to see." Thompson also noted that while the agency is relying on its 510(k) regulatory pathways in the meantime, the heterogeneity of these nontraditional tools has resulted in an ever-growing number of De Novo clearances and device classifications.

HALIFAX, Nova Scotia – The top U.S. military officer says it's problematic that American tech companies don't want to work with the Pentagon but are willing to engage with the Chinese market. U.S. Chairman of the Joint Chiefs of Staff Joseph Dunford told the Halifax International Security Forum on Saturday that the U.S. and its allies are the "good guys." Dunford avoided mentioning Google by name. But worker unrest at the company helped scuttle Google's Maven project to help the U.S. military scan battlefields using drones and artificial intelligence. Dunford says companies that share intellectual property with Chinese entrepreneurs are essentially sharing it with the Chinese military.

Researchers say hackers could weaponize artificial intelligence to conceal and accelerate cyberattacks, and potentially escalate their damage. Scientists warn that hackers could weaponize artificial intelligence (AI) to conceal and accelerate cyberattacks and potentially escalate their damage. IBM researchers last month demonstrated "DeepLocker" AI-powered malware designed to hide its damaging payload until it reaches a specific victim, identifying its target with indicators like facial- and voice-recognition and geolocation. IBM's Marc Stoecklin said with DeepLocker, "AI becomes the decision maker to determine when to unlock the malicious behavior." Meanwhile, the Stevens Institute of Technology's Giuseppe Ateniese has investigated the use of generative adversarial networks (GANs), which contain two neural networks that collaborate to deceive safeguards like passwords; he designed a GAN that fed leaked passwords found online into an AI model, to analyze patterns and narrow down likely passwords faster than brute-force attacks.

Germany will spend €3 billion to boost its artificial intelligence capabilities over the next six years, as part of a belated effort by Berlin to catch up with leading AI nations such as China and the United States. The spending pledge is part of a national AI strategy approved by Angela Merkel's cabinet on Thursday, following a two-day seminar on digital challenges attended by the chancellor and her ministers. Berlin expects federal funding to be matched by the private sector, taking investment to at least €6 billion. "Today, Germany cannot claim to be among the world leaders in artificial intelligence," Ms Merkel told journalists after the meeting. "Our aspiration is to make'Made in Germany' a trademark also in artificial intelligence, and to ensure that Germany takes its place as one of the leading [AI] countries in the world."

The idea of an artificial intelligence (AI) arms race between China and the United States is ubiquitous. Before 2016, there were fewer than 300 Google results for "AI arms race" and only a handful of articles that mentioned the phrase. Today, an article on the subject gets added to LexisNexis virtually every week, and Googling the term yields more than 50,000 hits. Some even warn of an AI Cold War. One question that looms large in these discussions is if China has, or will soon have, an edge over the United States in AI technology.

Amazon boss Jeff Bezos has warned staff not to be complacent, claiming the firm'is not too big to fail' At an all-hands meeting last Thursday in Seattle, days before the firm announced the winners of its HQ2 contest, Bezos was asked about the recent failures of giant retailers like Sears. 'Amazon is not too big to fail,' Bezos said, in a recording of the meeting CNBC said it had heard. 'In fact, I predict one day Amazon will fail. If you look at large companies, their lifespans tend to be 30-plus years, not a hundred-plus years.' Bezos told the meeting the key to survival is to'obsess over customers'.

Facial recognition is being used to identify American Civil War soldiers who may have otherwise been lost in the sands of time. Computer scientist and history buff Kurt Luther created a free-to-use website, called Civil War Photo Sleuth, that uses facial recognition technology to cross-reference vintage photographs with a database and hopefully assign a name to unknown subjects. Luther was inspired to launch the website after he stumbled upon a wartime portrait of his great-great-uncle, who was a Union corporal in the Civil War. Then, the site's facial recognition technology goes to work, mapping as many as 27 'facial landmarks.' It uses those facial landmarks to compare the photo to the more than 10,000 identified photos in the site's archive.

Chemical structure elucidation is a serious bottleneck in analytical chemistry today. We address the problem of identifying an unknown chemical threat given its mass spectrum and its chemical formula, a task which might take well trained chemists several days to complete. Given a chemical formula, there could be over a million possible candidate structures. We take a data driven approach to rank these structures by using neural networks to predict the presence of substructures given the mass spectrum, and matching these substructures to the candidate structures. Empirically, we evaluate our approach on a data set of chemical agents built for unknown chemical threat identification. We show that our substructure classifiers can attain over 90% micro F1-score, and we can find the correct structure among the top 20 candidates in 88% and 71% of test cases for two compound classes.