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Google claims to have demonstrated something called “quantum supremacy”, in a paper published in Nature. This would mark a significant milestone in the development of a new type of computer, known as a quantum computer, that could perform very difficult calculations much faster than anything possible on conventional “classical” computers. But a team from IBM …

A quantum computer may have solved a problem in minutes that would take the fastest conventional supercomputer more than 10,000 years. A draft of a paper by Google researchers laying out the achievement leaked in recent days, setting off an avalanche of news coverage and speculation. While the research has not yet been peer-reviewed – …

A new disruptive technology is on the horizon and it promises to take computing power to unprecedented and unimaginable heights. And to predict the speed of progress of this new “quantum computing” technology, the director of Google’s Quantum AI Labs, Hartmut Neven, has proposed a new rule similar to the Moore’s Law that has measured …

AI continues to transform industries across the globe, and business decision makers of all kinds are taking notice. But there’s a problem: although 80% of today’s enterprises recognize that AI is critical to their future, only 14% succeed in harnessing it (source). In other words, a gap remains between the potential of AI and its …

We are currently witnessing a rapidly growing adoption of artificial intelligence (AI) in our everyday lives, which has the potential to translate into a variety of societal changes, including improvements to economy, better living conditions, easier access to education, well-being, and entertainment. Such a much anticipated future, however, is tainted with issues related to privacy, …

Google I/O 2019 | Cutting Edge TensorFlow: New Techniques There’s lots of great new things available in TensorFlow since last year’s IO. This session will take you through 4 of the hottest from Hyperparameter Tuning with Keras Tuner to Probabilistic Programming to being able to rank your data with learned ranking techniques and TF-Ranking. Finally, …

Google I/O 2019 | Cloud TPU Pods: AI Supercomputing for Large Machine Learning Problems Cloud Tensor Processing Unit (TPU) is an ASIC designed by Google for neural network processing. TPUs feature a domain specific architecture designed specifically for accelerating TensorFlow training and prediction workloads and provides performance benefits on machine learning production use. Learn the …

Google I/O 2019 | TF-Agents: A Flexible Reinforcement Learning Library for TensorFlow TF-Agents is a clean, modular, and well-tested open-source library for Deep Reinforcement Learning with TensorFlow. This session will cover recent advancements in Deep RL, and show how TF-Agents can help to jump start your project. You will also see how TF-Agent library components …

Google I/O 2019 | Federated Learning: Machine Learning on Decentralized Data Meet federated learning: a technology for training and evaluating machine learning models across a fleet of devices (e.g. Android phones), orchestrated by a central server, without sensitive training data leaving any user’s device. Learn how this privacy-preserving technology is deployed in production in Google …

Google I/O 2019 | Machine Learning Zero to Hero This is a talk for people who know code, but who don’t necessarily know machine learning. Learn the ‘new’ paradigm of machine learning, and how models are an alternative implementation for some logic scenarios, as opposed to writing if/then rules and other code. This session will …