A brief and concise tutorial on how to visualize different aspects such as the loss of your neural network using tensorboard. We are going to work with a fully-connected neural network using the MNIST dataset. I'm going to use the network I have introduced in an earlier post. It achieves on the test-set an accuracy of 90%. This is not bad but we have no clue what is actually going on or how our model looks like.

Philip Koopman, professor of Carnegie Mellon Univ., believes the biggest hole in a Federal Automated Policy published late Sept. is in the regulators' failure to tangle head-on with fundamental difficulties in testing Machine Learning -- a problem already known to the scientific/engineering community. Representativeness of data Carmakers are building a fake city, for example, in Michigan to test autonomous vehicles. What's important, though, is whether the test data represents real-world driving conditions? A highly autonomous vehicle is designed to operate only in a certain designated area such as "driving only in downtown Pittsburgh." In DoT lingo, this concept is the "Operational Design Domain."

Consider a case where you search for a gadget in Google Image search. Your screen will be deluged with numerous images of it drawn from infinite quarters across world wide web. The logic behind surfacing these images is quite simple. If the image uploaded has a name, title and'alt' tag mentioned, that image will get picked by google crawlers. Another possibility is, even though the image might not have any such parameters, but if the web page content(where images reside) matches the search term, the image in that web page shows up. This works fluently if it was not been abused by black strategies.

This year legal tech companies and law firms that have developed legal AI applications will have a dedicated category for the 2nd'Global Annual Achievement Awards for Artificial Intelligence'. Those developing legal AI technology can join the competition under the: 'Best use of AI in Legal Tech' category, which is defined as an: 'Application of AI in the Legal Tech Industry. This can be applications developed by law firms themselves, technology companies or consultancies providing products and services to the legal sector.' The legal tech category is one of 20 main AI prize categories this year following a successful first year. The awards are organised by UK-based Home.AI, a forum for AI and machine learning across the entire sector, including legal tech, fin tech and more specific areas such as Natural Language Processing and AI in robotics.

Artificial Intelligence (AI) is fast becoming a buzzword in the technology industry. If you are following up technology news, you will get to read eye catching AI news almost every day. Large companies are realising that they will be at a loss if they remain behind in acquiring competence in AI. Prominent technology companies like Google, Facebook, Microsoft and IBM are investing billions of dollars in developing AI teams and technologies. Venture capitalists are investing in a number of start-ups promising to make AI products.

A baby robot designed to "invoke an emotional connection" has been unveiled in Japan, where plummeting birth rates have left many couples without children. The Kirobo Mini was created by Toyota's non-automotive department and is equiped with artificial intelligence and a camera so it can recognise the face of the person speaking to it and respond. "He wobbles a bit, and this is meant to emulate a seated baby which hasn't fully developed the skills to balance itself," said Fuminori Kataoka, Kirobo Mini's chief design engineer. "This vulnerability is meant to invoke an emotional connection." Toyota plans to sell Kirobo Mini, which blinks its eyes and speaks with a baby-like high-pitched voice, for 39,800 yen ( 300/US 390) in Japan next year.

Israeli pharmaceutical firm Teva is partnering with US chipmaker Intel to develop wearables and a machine-learning platform that can be used in the treatment of Huntington's Disease. Huntington's is a genetic and typically fatal neurodegenerative disease that causes nerve cells in the brain to deteriorate. This leads to a host of behavioral and psychological problems, including involuntary writhing movements called chorea. There is no cure for Huntington's, but Teva and Intel hope to spur the development of next-generation treatment options by better understanding the progression of the disease and how current treatments impact a patients' quality of life. The companies plan to accomplish this by combining Intel's capabilities in analytics and algorithms with Teva's work around Huntington's treatment and research.

Customer interactions with brands will soon become managed by AI via messaging platforms -- and companies need to be ready. We live in the age of mobile applications. There are currently several million apps available. This profusion of choices means it can be difficult for users not only to choose which apps to download, but to manage them all -- a phenomenon we call "app fatigue." This situation creates both a need and an opportunity to engage users on a single platform.

Amazon, DeepMind/Google, Facebook, IBM and Microsoft announced yesterday that they will create a non-profit organization that will work to advance public understanding of artificial intelligence technologies and formulate best practices on the challenges and opportunities within the field. Academics, non-profits and specialists in policy and ethics will be invited to join the Board of the organization, named the Partnership on Artificial Intelligence to Benefit People and Society (Partnership on AI). The objective of the Partnership on AI is to address opportunities and challenges with AI technologies to benefit people and society. Together, the organization's members will conduct research, recommend best practices and publish research under an open license in areas such as ethics, fairness and inclusivity; transparency, privacy and interoperability; collaboration between people and AI systems; and the trustworthiness, reliability and robustness of the technology. It does not intend to lobby government or other policymaking bodies.

Robots can do many things humans can do, often better. They mix cocktails, stand in for security guards and dispose of bombs. One thing we're sure they can never do better: care for our kids. They can't snuggle, kiss boo-boos or exhibit unconditional love, not like a mom or dad or child care worker can. But that didn't stop the makers of iPal from creating a creepy nanny robot that they're billing as a babysitter. It's a 3-foot-tall talking bot, complete with a surveillance cam, a touch screen tablet and tons of apps, you know, to keep your kid occupied and happy when you can't.