Top accomplishments include release of Akida intellectual property for licensing to ASIC suppliers, the development of a neural network converter for CNN to event-based CNN and native SNN translation, and an agreement with Socionext, formerly known as the Fujitsu Semiconductor business, for Akida development and manufacturing. In November 2019, BrainChip was granted a U.S. patent for its dynamic neural networks which are a valuable feature of its Akida AI processing chip used to power biometric and AI applications on devices at the network edge. Unlike other solutions, Akida does not need a host processor, external memory and a math accelerator device. It will be available in a Flip-Chip Ball Grid Array (FCBGA324) that is 15mm x 15mm. In 2019, the Akida logic and layout designs have been finalized.

The European Patent Office (EPO) has rejected two patent applications in which artificial intelligence (AI) was designated as the inventor. EP 18 275 163 and EP 18 275 174, described as a food container based on advanced geometry and light-based "devices and methods for attracting enhanced attention" in rescue scenarios, are patents submitted to the office and signed off with an inventor called DABUS. Created by Stephen Thaler, chief executive of Imagination Engines, DABUS is described as an AI made up of a "swarm of many disconnected neural nets, each containing interrelated memories, perhaps of a linguistic, visual, or auditory nature." These "nets" continually combine and detach, leading to the generation of complex concepts -- such as the ideas described in the patent applications. The applications were submitted last August in the UK, US, and Europe by the Artificial Inventor project team, led by Professor Ryan Abbott from the UK's University of Surrey. Current rules dictate that humans must be attributed as inventors behind a patent application in order to prevent full corporate inventorship from becoming a recognized practice for ideas.

If the hallmark of intelligence is problem solving, then it should be no surprise that artificial intelligence is being called on to solve complex problems that human intelligence alone cannot. Intellectual property laws exist to reward intelligence, creativity and problem solving; yet, as society adapts to a world immersed in artificial intelligence, the nation's intellectual property laws have yet to do the same. The Constitution seems to only contemplate human inventors when it says, in Article I, Section 8, Clause 8, "The Congress shall have Power … To promote the Progress of Science and useful Arts, by securing for limited Times to Authors and Inventors the exclusive Right to their respective Writings and Discoveries." The Patent Act similarly seems to limit patents to humans when it says, at 35 U.S.C. § 100(f), "The term'inventor' means the individual or, if a joint invention, the individuals collectively who invented or discovered the subject matter of the invention." Recognizing the need to adapt, the U.S. Patent and Trademark Office (PTO) recently issued notices seeking public comments on intellectual property protection related to artificial intelligence.

There has been a big debate about this in the patent space over the last year, mainly lead by AI developers who want to be able to secure patents on AI generated ideas. The patent offices in the EU and the US have been exploring the issue, and asking for feedback, while they plot out a strategy, but some AI folks decided to force the matter sooner. Over the summer they announced that they had filed for two patents in the EU for inventions that they claim were "invented" by an AI named DABUS without the assistance of a human inventor. And now, the EU Patent Office has rejected both patents, since they don't have a human inventor. The EPO has refused two European patent applications in which a machine was designated as inventor.

Based on our interactions and the results of this study, we expect to see organizations not only adopt AI – but scale it across their enterprises, by building/developing their own AI, or putting ready-made AI applications to work. For example, according to the survey, 40% of respondents currently deploying AI said they are developing proof-of-concepts for specific AI-based or AI-assisted projects, and 40% are using pre-built AI applications, such as chatbots and virtual agents. I see the excitement building with clients every day. Consider just a couple of recent examples. Legal software developer LegalMation has leveraged IBM Watson and our natural language processing technology to help attorneys automate some of the most mundane litigation tasks, speeding, for example, the written discovery process from multiple hours to a few minutes.

After a U.S. airstrike kills Iranian Gen. Qassem Soleimani in Iraq, Secretary of State Mike Pompeo tells'Fox & amp; Friends' that President Trump's decision was necessary to deter further aggression. The U.N. special rapporteur on extrajudicial killing on Friday said the President Trump-approved drone strike against Qassem Soleimani, Iran's top general, violated international human rights law. In a lengthy Twitter thread, Agnès Callamard said that "outside the context of active hostilities, the use of drones or other means for targeted killing is almost never likely to be legal," adding that the U.S. would need to prove the person targeted constituted an imminent threat to others. She also took issue with the justification for using drones in another country on the basis of self-defense. "Under customary international law States can take military action if the threatened attack is imminent, no other means would deflect it, and the action is proportionate," she wrote.

Face-scanning technology is inspiring a wave of privacy fears as the software creeps into every corner of life in the United States and Europe -- at border crossings, on police vehicles and in stadiums, airports and high schools. But efforts to check its spread are hitting a wall of resistance on both sides of the Atlantic. One big reason: Western governments are embracing this technology for their own use, valuing security and data collection over privacy and civil liberties. And in Washington, U.S. President Donald Trump's impeachment and the death of a key civil rights and privacy champion have snarled expectations for a congressional drive to enact restrictions. The result is an impasse that has left tech companies largely in control of where and how to deploy facial recognition, which they have sold to police agencies and embedded in consumers' apps and smartphones.

The world's first artificially intelligent "inventor" has been rejected by British and European patent authorities, marking an historic moment in an ongoing debate around the role of creative machines. In July last year, an international squad of legal experts challenged patent authorities around the world to recognise the "inventorship" of artificial intelligence, arguing that the current regimes were outdated and do not protect machines' creative output. The nine-strong group, led by University of Surrey professor Ryan Abbott, made headlines after submitting patents designed by an artificially intelligent machine with the US, UK and European authorities. They have since filed more applications in Germany, Israel, Taiwan and China. The team is battling for recognition of a particular AI inventor called Dabus.

Artificial intelligence (AI) is now receiving unprecedented global attention as it finds widespread practical application in multiple spheres of activity. But what are the human rights, social justice and development implications of AI when used in areas such as health, education and social services, or in building "smart cities"? How does algorithmic decision making impact on marginalised people and the poor? This edition of Global Information Society Watch (GISWatch) provides a perspective from the global South on the application of AI to our everyday lives. It includes 40 country reports from countries as diverse as Benin, Argentina, India, Russia and Ukraine, as well as three regional reports.

Artificial intelligence programmers are developing bots that can identify digital bullying and sexual harassment. Known as "#MeTooBots" after the high-profile movement that arose after allegations against the Hollywood producer Harvey Weinstein, the bots can monitor and flag communications between colleagues and are being introduced by companies around the world. Bot-makers say it is not easy to teach computers what harassment looks like, with its linguistic subtleties and grey lines. Jay Leib, the chief executive of the Chicago-based AI firm NexLP, said: "I wasn't aware of all the forms of harassment. I thought it was just talking dirty. It comes in so many different ways. It might be 15 messages … it could be racy photos."