Why edge computing is so crucial for IIoT

The invention of the Printed Circuit Board (PCB) in the 1950s changed the world of automation. Prior to the PCB, electronic circuit boards were assembled exclusively by hand, a laborious process that greatly limited global production.

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Siemens updates NX Software with Artificial Intelligence and Machine Learning to increase productivity

Siemens announced an expansion of the Digital Innovation Platform with the introduction of the latest version of NX software, which has been enhanced with Machine Learning (ML) and Artificial Intelligence (AI) capabilities.

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IoT: Preparing our future workforce

Data scientists have often been compared to the heart and soul of the running of Internet of Things (IoT) projects, says Anthony Sayers, IoT Evangelist at Software AG. As the gatekeeper to every organisations capability to make more informed decisions with their data, these individuals are considered vital for successful IoT projects.

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PTC buys Frustum for US$70mn adding AI and generative design skills to expand CAD Portfolio

PTC has acquired Frustum Inc., “an advanced generative design software company”, for approximately $70 million (€61.36 million). Frustum’s technology for generative design — an approach that leverages Artificial Intelligence (AI) to generate

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Skills gap hits the IoT market

Although the exact numbers of the market potential of IoT varies between various estimates, McKinsey sets it to be between $2.7(€2.19) to $6.2(€5.04) trillion by 2025. It is estimated that the number of connected devices is set to increase approximately five fold, from 27 billion in 2017 to 125 billion by 2030. However, this potential can be leveraged only

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IoT platform collaborations and consolidation are coming

The Internet of Things (IoT) is hotter than ever and in 2018 there will be more collaboration between market leaders, even as the community of 300+ platforms begins inevitable consolidation. According to Matt Smith, CTO at Software AG, artificial intelligence (AI) and machine learning (ML) will begin to infiltrate IoT platforms and devices and new

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Number of consumers considering Artificial Intelligence–enabled devices for holiday shopping doubles

SAP SE reports that nearly four out of 10 consumers who own in-home assistants are considering using them for holiday shopping this year — to purchase gifts for others (16%), research deals and savings for gifts (15%), and for their own purchases (7%). These findings derive from a survey commissioned by SAP of 1,000 U.S.

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Dataiku achieves AWS machine learning competency status

Dataiku, an enterprise solution for collaborative advanced analytics and machine learning, announced that it has achieved Amazon Web Services (AWS) Machine Learning (ML) Competency status. This designation recognises Dataiku for enabling machine learning for everyone,

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Qualcomm and SenseTime to collaborate to drive on-device artificial intelligence

Qualcomm Technologies, Inc., a subsidiary of Qualcomm Incorporated, and SenseTime Group Limited announced plans to collaborate on artificial intelligence (AI) and machine learning (ML) for future mobile and IoT products.

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Cisco to buy artificial intelligence company MindMeld for $125 million

Cisco, has announced its intent to acquire MindMeld Inc., a privately held artificial intelligence (AI) company based in San Francisco. MindMeld has pioneered the development of a unique AI platform that enables customers to build intelligent and human-like conversational interfaces for any application or device.

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Machine learning is cybersecurity’s latest pipe dream – Part 2

What is normal? It’s important to remember there is no silver bullet in security, and there is no evidence at all that tools such as ML and AI can solve the problem. ML is good at finding similarities between things (such as spam emails), but it is not so good at locating anomalies.

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Machine learning is cybersecurity’s latest pipe dream – Part 1

A recurring claim at security conferences is that “security is a big data / machine learning (ML) / artificial intelligence (AI) problem”. This is unfortunately wildly optimistic, and wrong in general. While certain security problems can be addressed by ML/AI algorithms, in general the problem of detecting a malicious actor amidst the vast trove of

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