If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
TOKYO, Dec 14, 2017 - (JCN Newswire) - Lockheed Martin and NEC Corporation (TSE: 6701) today announced that Lockheed Martin will use NEC's System Invariant Analysis Technology (SIAT) in the space domain. SIAT's advanced analytics engine uses data collected from sensors to learn the behavior of systems, including computer systems, power plants, factories and buildings, enabling the system itself to automatically detect inconsistencies and prescribe resolutions. NEC's advanced Artificial Intelligence (AI) capabilities and Lockheed Martin's space domain expertise offer new opportunities in developing enhanced integrated satellite and spacecraft operations with uniquely developed prescriptive analytics. These include rapid assessments of changes in performance and the space environment, such as the potential influence of space weather on electronics. With this information, operators can improve product performance and lifecycle efficiency.
Graphcore has today announced a $50 million Series C funding round by Sequoia Capital as the machine intelligence company prepares to ship its first Intelligence Processing Unit (IPU) products to early access customers at the start of 2018. The Series C round enables Graphcore to significantly accelerate growth to meet the expected global demand for its machine intelligence processor. The funding will be dedicated to scaling up production, building a community of developers around the Poplar software platform, driving Graphcore's extended product roadmap, and investing in its Palo Alto-based US team to help support customers. Nigel Toon, CEO at Graphcore said: "Efficient AI processing power is rapidly becoming the most sought-after resource in the technological world. We believe our IPU technology will become the worldwide standard for machine intelligence compute.
Mindfire, a new foundation with the goal of "decoding the mind" to help develop true artificial intelligence (AI) is launching November 17th in Zurich, Switzerland. Futurism spoke with the founder of Starmind and president of the foundation, Pascal Kaufmann to learn more about its goals and the path to reach them. "We cannot achieve True AI until we understand actual intelligence. Intelligence has evolved as a means of nature to successfully guide us through an ever-changing environment. This gave rise to behavior, emotions, and consciousness.
Cloudera, Inc. (NYSE: CLDR), the modern platform for machine learning and analytics, optimized for the cloud, announced that Komatsu, a leading global heavy equipment manufacturer, has implemented a cloud-based Industrial Internet of Things (IIoT) analytics platform powered by Cloudera Enterprise and Microsoft Azure. The platform enables Komatsu teams to help mining customers around the world continuously monitor the performance of some of the largest equipment used in surface and underground mining, increase asset utilization and productivity, and deliver essential resources including energy and industrial minerals for the global economy. Komatsu's JoySmart Solutions is an IIoT-based service that helps customers optimize machine performance using machine data and analytics. The JoySmart platform ingests, stores and processes a wide variety of data collected from mining equipment operating around the globe, often at very remote locations in harsh conditions. Types of equipment monitored includes longwall mining systems, electric rope shovels, continuous miners and wheel loaders.
HPE Rapid Software Installation for AI: HPE introduced an integrated hardware and software solution, purpose-built for high performance computing and deep learning applications. Based on the HPE Apollo 6500 system in collaboration with Bright Computing to enable rapid deep learning application development, this solution includes pre-configured deep learning software frameworks, libraries, automated software updates and cluster management optimized for deep learning and supports NVIDIA Tesla V100 GPUs. HPE Deep Learning Cookbook: Built by the AI Research team at Hewlett Packard Labs, the deep learning cookbook is a set of tools to guide customers in selecting the best hardware and software environment for different deep learning tasks. These tools help enterprises estimate performance of various hardware platforms, characterize the most popular deep learning frameworks, and select the ideal hardware and software stacks to fit their individual needs. The Deep Learning Cookbook can also be used to validate the performance and tune the configuration of already purchased hardware and software stacks.
The first instances to include NVIDIA Tesla V100 GPUs, P3 instances are the most powerful GPU instances available in the cloud. P3 instances allow customers to build and deploy advanced applications with up to 14 times better performance than previous-generation Amazon EC2 GPU compute instances, and reduce training of machine learning applications from days to hours. With up to eight NVIDIA Tesla V100 GPUs, P3 instances provide up to one petaflop of mixed-precision, 125 teraflops of single-precision, and 62 teraflops of double-precision floating point performance, as well as a 300 GB/s second-generation NVIDIA NVLink interconnect that enables high-speed, low-latency GPU-to-GPU communication. P3 instances also feature up to 64 vCPUs based on custom Intel Xeon E5 (Broadwell) processors, 488 GB of DRAM, and 25 Gbps of dedicated aggregate network bandwidth using the Elastic Network Adapter (ENA). "When we launched our P2 instances last year, we couldn't believe how quickly people adopted them," said Matt Garman, Vice President of Amazon EC2.
DUBLIN, IRELAND--(Marketwired - October 17, 2017) - RecommenderX today announced that it won the Best Use of Data Science In A Start Up Award at the DatSci event held in Dublin on September 21, 2017. DatSci is an annual event that brings together and recognizes the best and brightest that Ireland has to offer in the expanding world of Data Science. RecommenderX is a technology company, focused on helping customers and partners improve productivity, performance, customer engagement, sales and profitability, by transforming Artificial intelligence (AI) to Business Intelligence (BI). RecommenderX is the top spin out of Europe's largest Centre for Data Analytics Insight, with deep domain knowledge in Data Analytics, Artificial Intelligence (AI), Machine Learning (ML), Personalization Technology, Recommender Systems and Explainable AI. "We are thrilled to be an award winner at DatSci 2017," stated Kevin McCarthy, Co-Founder & CTO of RecommenderX. "It is a fantastic validation of the efforts that our world-class team have been making helping companies all over the world harness their data by developing cutting edge applications and solutions that leverage data science and AI technologies."
On Tuesday, NVIDIA unveiled the world's first artificial intelligence (AI) computer designed to drive fully autonomous vehicles by mid-2018. The new system, named Pegasus, extends the NVIDIA Drive PX AI computing platform to operate vehicles with Level 5 autonomy--without steering wheels, pedals, or mirrors. New types of cars will be invented, resembling offices, living rooms or hotel rooms on wheels. "The company hasn't claimed to have developed all the software, hardware, and data needed for automated driving; it's merely announced that it plans to market a chip that in theory could support the hardware and software envisioned for such a system," Walker Smith said.
By modeling human testers, including manual and test automation tasks such as scripting, Appvance has developed algorithms and expert systems to take on those tasks, similar to how driverless vehicle software models what a human driver does. The Appvance AI technology learns from various existing data sources, including learning to map an application fully on its own, various server logs, Splunk or Sumo Logic production data, form input data, valid headers and requests, expected responses, changes in each build and others. The resulting test execution represented real user flows, data driven, with near 100% code coverage. Built from the ground up with DevOps, agile and cloud services in mind, Appvance offers true beginning-to-end data-driven functional, performance, compatibility, security and synthetic APM test automation and execution, enabling dev and QA teams to quickly identify issues in a fraction of the time of other test automation products.
In this post, I'll offer a look at data science's buzzwords from multiple perspectives, namely the theorist, the empirical data scientist, and the press release bluster, which too often is parroted by the mainstream press. Data Scientist: Unlike the toy datasets that long dominated machine learning research, today's big data is sufficiently large that it cannot fit conveniently in main memory on a single workstation. In short, big data is more data than can fit in main memory on a single machine. Theorist: Deep neural networks refer to graphical models in which data is computed upon by successive layers of nodes.