PULP Platform Youtube channel (subscribe it!): PULP-DroNet is a deep learning-powered visual navigation engine that enables autonomous navigation of a pocket-size quadrotor in a previously unseen environment. Thanks to PULP-DroNet the nano-drone can explore the environment, avoiding collisions also with dynamic obstacles, in complete autonomy -- no human operator, no ad-hoc external signals, and no remote laptop! This means that all the complex computations are done directly aboard the vehicle and very fast. The visual navigation engine is composed of both a software and a hardware part.

Intelligent automation has a massive potential to streamline the complex trading process by precisely capturing the market patterns. FREMONT, CA: The capital market landscape is on the path to transformation with the emergence of new technologies. Investment firms are aiming to enhance their business and operational strategies. Technologies such as artificial intelligence (AI), with robotic process automation (RPA), is being considered the torchbearer in this regard. In fact, the above-mentioned technologies are often collectively referred to as intelligent automation.

As AI continues to evolve, it will offer more benefits to the public sector. The governments have to keep up with the speed at which AI is evolving. FREMONT, CA: Artificial Intelligence (AI) has started to find its way in various governmental operations. According to IDC, it is expected that worldwide spending on AI systems will hit almost $98 billion by 2023. The demand for AI will increase as nobody else is more conscious than the government organizations about the difficulties of the traditional procedure.

Intelligent software is replacing humans doing repetitive and routine machine-focused jobs such as switchboard operators, front-desk hotel assistants, typists, manufacturing production and packaging operatives. We are even starting to see robots take and deliver orders at restaurants, provide banking assistance, serve coffee and drive cars. Increasingly, artificial intelligence (AI) is encroaching into knowledge worker roles. In the legal sector, AI is carrying out routine contract review work. In the financial and insurance sectors, intelligent apps are creating new business models that replace many of the activities of sales representatives, by cross-selling to consumers through the app, for example.

Oracle has a holistic AI/ML strategy, embedding intelligence at every layer of the cloud. According to Oracle, AI/Ml is resonating more with businesses. AI has come of age Why AI/Ml is resonating more with businesses? Andrew Sutherland, SVP Technology, Oracle EMEA and JAPAC, said there is a lot of focus on AI. He said: "We were a multi-discliplinary team. We worked in speech recognition. We digitised data and gave it to computers. We did learning of patterns. That was the beginning of AI in the form of machine learning. The key was the amount of data. The more data, the more accurate was the speech recognition. You start constructing a lot of new rules. The machine learns from the data presented."

Argonne researchers have created a neural architecture search that automates the development of deep-learning-based predictive models for cancer data. While increasing swaths of collected data and growing scales of computing power are helping to improve our understanding of cancer, further development of data-driven methods for the disease's diagnosis, detection and prognosis is necessary. There is a particular need to develop deep-learning methods -- that is, machine learning algorithms capable of extracting science from unstructured data. Researchers from the U.S. Department of Energy's (DOE) Argonne National Laboratory have made strides toward accelerating such efforts by presenting a method for the automated generation of neural networks. As detailed in a paper for presentation at the SC19 conference, the researchers, utilizing resources from the Argonne Leadership Computing Facility (ALCF), a DOE Office of Science User Facility, have established a neural architecture search (NAS) that, for a class of representative cancer data, automates the development of deep-learning-based predictive models.

While optimistic about the future, Steve Wozniak is not ready to turn over his identity (nor his Tesla) to artificial intelligence anytime soon. At a conference in Budapest I attended, he referenced deleting his Facebook account because of privacy concerns, and that he no longer believes that a totally autonomous car will happen in his lifetime. But Wozniak retains the passion and enthusiasm for technology and innovation that made him a household name as Apple's co-founder. When he and Steve Jobs started Apple, they were trying to develop a new kind of computer that would improve the user experience beyond what was available at the time. Today, "The Woz" is a brilliant engineer, who keeps his eye on what is happening in technology, digital transformation and entrepreneurship.

AUSTIN, Texas--(BUSINESS WIRE)--InfiniteIO, the world's fastest metadata platform to reduce application latency, today announced the new Application Accelerator, which delivers dramatic performance improvements for critical applications by processing file metadata independently from on-premises storage or cloud systems. The new platform provides organizations across industries the lowest possible latency for their mission-critical applications, such as AI/machine learning, HPC and genomics, while minimizing disruption to IT teams. "Bandwidth and I/O challenges have been largely overcome, yet reducing latency remains a significant barrier to improving application performance," said Henry Baltazar, vice president of research at 451 Research. "Metadata requests are a large part of file system latency, making up the vast majority of requests to a storage system or cloud. InfiniteIO's approach to abstracting metadata from file data offers IT managers a nondisruptive way to immediately accelerate application performance."

Google LLC today launched an enterprise version of TensorFlow, the popular open-source artificial intelligence framework it created to run machine learning, deep learning and other statistical and predictive analytics workloads. Common use cases include training algorithms for image recognition and recurrent neural networks, as well as sequence-to-sequence models for machine translation and natural language processing. In a launch at the O'Reilly TensorFlow World conference in Santa Clara, California, Craig Wiley (pictured), director of product management at Google Cloud AI Platform, said the launch of TensorFlow Enterprise was necessary to meet the "higher demands and expectations" of enterprises that need to scale up their machine learning projects. TensorFlow Enterprise customers will be able to take advantage of what Google says is enterprise-grade support, including long-term support for older versions of the framework. Although TensorFlow is updated regularly, not everyone is able to upgrade to the newest releases immediately.

It may not be common knowledge, but the automotive industry is in deep discussions to find out how aeronautic technology can benefit the next generation of road vehicles. More specifically, satellite imaging firms are using their expertise to assist the creation of high-definition (HD) maps, which can optimise autonomous vehicle (AV) navigation, ride-share operations and last-mile delivery services. Maxar is based in Westminster, Colorado. From here, it runs a global business you've never heard of, but will almost certainly have used. Its constellation of satellites circles the earth once every 90 minutes--that's 16 revolutions per day--on what is called a sun-synchronous orbit.