AI News, AI adoption: When will it be too late for you?

8 Industrial IoT Trends in 2019

It’s no surprise that worldwide technology spending on the Internet of Things is forecasted to reach $1.2 trillion by 2022 (IDC).

If 2018 was the year of IIoT proof of concepts, 2019 will be the year manufacturers move from early proof of concepts to deploying pilots for Industry 4.0 solutions, such as predictive maintenance, digital twin, and predictive quality.

Machine learning algorithms for manufacturing are being formulated and tailored to specific production line challenges — such as reducing production waste, improving process stability, minimizing unplanned downtime, and eliminating process disturbances What does this mean on a practical level?

OT and IT have been converging for some time, and ‘collaboration’ used to be the goal — but many manufacturers are taking their operational and IT data a step further to improve the relevance and accuracy of data-driven insights.

The only way for manufacturers to measure the right data, and reach accurate conclusions, is by combining all the relevant operational data from the plant or line environment with business context data from the IT systems.

food and beverage manufacturer deploys software with machine learning algorithms applied to OT data from one production line, searching for patterns that predict asset breakdown.

In the coming year, manufacturers will be budgeting for systems that help them glean manufacturing excellence insights through the lens of process and business data that influence the production environment.

In the manufacturing world, digital twins support many industry 4.0 solutions, from automated root cause analysis, to predictive quality, predictive maintenance, inventory intelligence, and supply chain optimization.

In 2019, we will not only see greater adoption of the digital twin in general, but also an expansion in their popular use: more digital twins used to optimize production processes rather than the individual assets in day-to-day operations and processes.

These ‘full’ digital twins’ will incorporate process data that will help manufacturers reach more accurate insights, whether by deep-diving into individual machines or viewing the high-level process architecture to identify and address manufacturing inefficiencies.

Manufacturers are for the most part already collecting data, but managing it via cloud computing puts a financial strain on manufacturers — not to mention the security risks of storing all your raw data in the cloud.

Edge computing helps businesses by analyzing and storing data close to its source decrease time and expenses related to data analytics, as well as improving data security.

The edge computer not only processes vibration data, for example, but also performs feature extraction to select a predefined amount and type of vibration data — highs and lows within a given time frame, for example — to go to the cloud.

Despite this, the gain to businesses in developing smart production lines is clear enough that securing data is becoming less of a deterrent to manufacturers who want to increase yield and improve operational efficiency through AI.

We’re seeing more and more deployment of Industrial IoT solutions that are revolutionizing the manufacturing landscape digitally — transforming customer relationships, differentiating offerings, and driving massive operational improvements to meet the growing demands on production.

Lutz Announces 2019 Lutz Learning Live Schedule

Lutz, a Nebraska-based business solutions firm, is excited to announce its 2019 Lutz Learning Live seminar schedule!

Beyond the hype and the heightened media attention, the numerous startups and the internet giant’s racing to acquire them, there is a significant increase in investment and adoption by enterprises.

In this webinar, Chris Wagner of Lutz Financial will cover the step by step process for making fiduciary decisions and administering a prudent retirement plan, as well as discuss current hot topics in the Finance Industry.

Beyond the hype and the heightened media attention, the numerous startups and the internet giant’s racing to acquire them, there is a significant increase in investment and adoption by enterprises.

Beyond the hype and the heightened media attention, the numerous startups and the internet giant’s racing to acquire them, there is a significant increase in investment and adoption by enterprises.

In the second half of our seminar, Chris Bouchard of Lutz Talent, will discuss the benefits of hiring temporary staff, as well as some downfalls that can lead to a less-than-ideal experience for both parties.

Chris will cover the right way and a wrong way to go about temp workers including the screening process and “to-do’s” once the temporary employee is hired.

In the second half of our seminar, Chris Bouchard of Lutz Talent, will discuss the benefits of hiring temporary staff, as well as some downfalls that can lead to a less-than-ideal experience for both parties.

Chris will cover the right way and a wrong way to go about temp workers including the screening process and “to-do’s” once the temporary employee is hired.

In the second half of our seminar, Chris Bouchard of Lutz Talent, will discuss the benefits of hiring temporary staff, as well as some downfalls that can lead to a less-than-ideal experience for both parties.

Chris will cover the right way and a wrong way to go about temp workers including the screening process and “to-do’s” once the temporary employee is hired.

In this seminar, Scott Carrico and Ryan McGregor will discuss multiple long and short term strategies to help prepare your business for success and a potential greater value.

In this seminar, Ryan Cook and Ashley Englund will discuss multiple long and short term strategies to help prepare your business for success and a potential greater value.

In this seminar, Ryan Cook and Ashley Englund will discuss multiple long and short term strategies to help prepare your business for success and a potential greater value.

In this interactive workshop, Taylor Pugh and Aimee Trumbull will take participants through the basics of understanding and using a business financial statement, teach you how to read a balance sheet, and offer tips on utilizing the data to better evaluate your business financials and focus on growth.

In this interactive workshop, Taylor Pugh and Aimee Trumbull will take participants through the basics of understanding and using a business financial statement, teach you how to read a balance sheet, and offer tips on utilizing the data to better evaluate your business financials and focus on growth.

In this interactive workshop, Taylor Pugh and Aimee Trumbull will take participants through the basics of understanding and using a business financial statement, teach you how to read a balance sheet, and offer tips on utilizing the data to better evaluate your business financials and focus on growth.

Three Generations of AI: From Data Warehouses to Machine Learning

For years, data unification has been a roadblock to effective data analytics.

Data scientists report spending 80% of their time locating data, unifying it from multiple sources, and cleaning it before they can begin their analytics work in earnest.

In the mid-to-late 90s, enterprises began adopting data warehouses, and needed a way to load data from disparate sources into these warehouses.

For example, some did not have dedicated features for data cleaning, making it difficult to detect and remove errors and inconsistencies to improve data quality.

However, as the volume and variety of data continued to expand, time-consuming manual scripting began impeding organizations’ ability to quickly derive critical insights needed to drive business decisions.

However, although they represent an advancement on first-generation AI, they are at their core human-generated deterministic rules that are unable to scale to meet the data variety challenge of today’s enterprise data unification requirements.

When humans discover an error, they correct it and add the correction to the training set, improving the accuracy of the model through active learning.

The innovations presented by 3rd generation data unification enable organizations to harness big data to solve their most pressing issues and drive significant business impact.

Canadian companies slow to adopt AI technologies, report says

Canadian companies are taking cautious steps towards implementation of AI with sourcing the right talent and redesigning workflows cited as some of the practical barriers to overcome (Illustration by Drew Shannon) Canadian businesses are behind those of other countries when it comes to adoption of artificial intelligence technologies, according to a Forbes Insights report published late last year.

According to the report, which surveyed 305 global executives in 10 countries in July 2018, Canada ranked last for successful deployment of narrow AI technologies such as deep learning and machine learning.

Canadian businesses have practical barriers to overcome, says Sarah Villeneuve, policy analyst at the Brookfield Institute for Innovation + Entrepreneurship, a think tank founded in 2015 to advance innovation in Canada.

In 2017, The Vector Institute, an independent institution associated with the University of Toronto, announced a scholarship program to fund master’s students in their AI research at one of 10 approved university programs in Ontario, with the goal of boosting the number of artificial intelligence graduates to 1,000 annually.

According to the report, while 68 per cent of Canadian companies have deployed AI, only 31 per cent of Canadian adopters said their implementation was a real success, compared to 59 per cent in India, 58 per cent in Germany and 55 per cent in China.

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