Advancements in gesture recognition algorithms have led to a significant growth in sign language translation. By making use of efficient intelligent models, signs can be recognized with precision. The proposed work presents a novel one-dimensional Convolutional Neural Network (CNN) array architecture for recognition of signs from the Indian sign language using signals recorded from a custom designed wearable IMU device. The IMU device makes use of tri-axial accelerometer and gyroscope. The signals recorded using the IMU device are segregated on the basis of their context, such as whether they correspond to signing for a general sentence or an interrogative sentence. The array comprises of two individual CNNs, one classifying the general sentences and the other classifying the interrogative sentence. Performances of individual CNNs in the array architecture are compared to that of a conventional CNN classifying the unsegregated dataset. Peak classification accuracies of 94.20% for general sentences and 95.00% for interrogative sentences achieved with the proposed CNN array in comparison to 93.50% for conventional CNN assert the suitability of the proposed approach.

Our business audience is buyer supplier focused and comprised of Enterprise decision makers / CxOs, allied to AI Cloud platform providers, Tier 1 / 2 deployment & service providers, AI start ups / innovators, investors, educators, government and AI ecosystem community builders. AI Expo Africa 2020 will have 4 main online speaking tracks, expo hall, poster wall & networking zone. You will learn about real Enterprise case studies and the application of AI and Data Science in Business TODAY, available technology and cloud platforms, deployment challenges, ethical considerations allied to the vibrant innovation and start up ecosystem driving the industry in Africa. "AI Expo Africa was nothing less then inspirational. "What an amazing few days spent with like minded individuals, organizations, startups, enthusiasts and those just plainly curious!" Izak De Beer, SAP "Talking to the smaller vendors, particularly the ones in the Innovation Cafe was the highlight for me" Gordon Inggs, City of Cape Town "I learnt so much at this year's AI Expo Africa and cannot wait to return next year" Khumoetsile Khumalo, Absa Bank "It was great the see a diverse field of innovators across business, academia and social enterprises take on our continents challenges" Francis Mumbi, Stanbic Bank My brain has been opened to a whole new exciting world for me" John Morison, Polyoak Packaging "Great event, had a fantastic panel discussion regarding youth and woman" Brigitte Binneman, Technology Innovation Agency, South Africa We are helping lay the foundations for an AI Powered Future for Africa, fostering B2B trade and investment around 6 key themes with a strong business development and growth narrative.

Apple and Google's common coronavirus contact tracing solution for smartphones has continued to attract a lot of attention and debate over the past week, and understandably so. It's an unprecedented partnership between the world's dominant smartphone operating system makers, but people are worried about privacy and the notion that tracking tools deployed in the name of coronavirus will outlive the crisis. Debate over Apple and Google's contact tracing solution seems to have opened up an old argument between people who see a tech solution for every problem and those who say tech can't solve all our problems, and can even cause new ones. These debates certainly carry over to the kind of AI being deployed right now and the important question of when a company should ship or shelve a coronavirus solution. A lot of AI solutions are being rushed out in an attempt to save lives and speed up the day when we'll return to something resembling normal life, and you've been able to read about many of these in our coverage.

Companies using artificial intelligence (AI) across their business units should consider creating a C-suite position to oversee how AI is used and guard against the risk of making bad decisions based on biased algorithms, experts say. Only a few companies, like Levi Strauss & Co, have established a chief artificial intelligence officer (CAIO) position, and fewer have created a C-level position dedicated solely to AI ethics. Brian Kropp, chief of research in the HR practice at Gartner, said chief technology officers and chief information officers will struggle with handling AI-related decisions and ethical dilemmas. "CTOs and CIOs are going to be thinking about the role through the lens of how they can make the technology work," Kropp said. However, "artificial intelligence is not a question of how you get the technology to work; it's a question of how do you think through the implications of the technology?"

I am worried if killing the economies is worth it if we so laxly approach the support for the most affected populations? The economical lockdown around the world has resulted in an increase in violence, a lack of food supply, overloaded healthcare systems, and global panic response that will trigger mental health consequences long after the pandemic is over. Experts agree that government policies need to balance overcoming both the health and economic crisis. In the short run, economic policies should mitigate the impact of lockdowns and ensure that the current crisis does not trigger financial, debt or currency crises. It should facilitate a quick recovery once the economy is taken out of the deep freeze.

Hyperdimensional (HD) computing is built upon its unique data type referred to as hypervectors. The dimension of these hypervectors is typically in the range of tens of thousands. Proposed to solve cognitive tasks, HD computing aims at calculating similarity among its data. Data transformation is realized by three operations, including addition, multiplication and permutation. Its ultra-wide data representation introduces redundancy against noise. Since information is evenly distributed over every bit of the hypervectors, HD computing is inherently robust. Additionally, due to the nature of those three operations, HD computing leads to fast learning ability, high energy efficiency and acceptable accuracy in learning and classification tasks. This paper introduces the background of HD computing, and reviews the data representation, data transformation, and similarity measurement. The orthogonality in high dimensions presents opportunities for flexible computing. To balance the tradeoff between accuracy and efficiency, strategies include but are not limited to encoding, retraining, binarization and hardware acceleration. Evaluations indicate that HD computing shows great potential in addressing problems using data in the form of letters, signals and images. HD computing especially shows significant promise to replace machine learning algorithms as a light-weight classifier in the field of internet of things (IoTs).

Organizers of the International Conference on Learning Representations (ICLR) shared details about what will be one of the largest-ever all-digital AI research conferences. The weeklong, online-only affair will feature more than 650 machine learning works. ICLR will include live chat, live Zoom video calls for Q&As and research author meetings, and the ability to upvote questions or vote for speakers using Slido. ICLR was initially scheduled to take place next month in Addis Ababa, Ethiopia, but with a global pandemic underway and shelter in place orders asking one in five people worldwide to stay home, the conference will now take place entirely online. ICLR organizers told VentureBeat they're treating the cancellation as an opportunity to develop a model for remote conferences.

Customers of any type of business expect help instantly and access to their services in a growing number of ways. Banks are turning to chatbots to help deal with massive volumes of customer interactions. Conversational banking frees up agents for more complex issues, while the move to app-based and web banking sees customers more used to dealing with digital interfaces, of which chatbots and AI virtual assistants are just the latest step. Established banks and their challenger rivals are all keen to develop a conversational banking strategy. Those that have been experimenting for some years find themselves with key advantages over banks stepping fresh into the conversational customer service arena.

Artificial intelligence is transforming how we design and build. By 2050, the effects of AI adoption will be widely felt across all aspects of our daily lives. As the world faces a number of urgent and complex challenges, from the climate crisis to housing, AI has the potential to make the difference between a dystopian future and a livable one. By looking ahead, we're taking stock of what's happening, and in turn, imagining how AI can shape our lives for the better. Artificial intelligence is broadly defined as the theory and development of computer systems to perform tasks that normally require human intelligence.

Advancements in the power of machine learning have brought with them major data privacy concerns. This is especially true when it comes to training machine learning models with data obtained from the interaction of users with devices such as smartphones. So the big question is, how do we train and improve these on-device machine learning models without sharing personally-identifiable data? That is the question that we'll seek to answer in this look at a technique known as federated learning. The traditional process for training a machine learning model involves uploading data to a server and using that to train models.