Why the conventional deep learning model is broken
The conventional deep learning model is a supervised model. It takes months of time to develop and train the model before it is ready for the production line.
AI in Manufacturing: Reshaping the Future of the Industry
We'll take a look at just some of the ways manufacturing companies can benefit from implementing AI in their processes. Furthermore, we'll share the diverse applications of AI that will help you save costs and improve processes regardless of the product specifics.
How AI is reshaping the edge computing landscape
How much computing power is needed at the edge? How much memory and storage are enough for AI at the edge? Minimum requirements are growing as AI opens the door to innovative applications that need more and faster processing, storage, and memory.
AI-driven Composable Manufacturing's Plug-and-play Approach Gives Manufacturers the Jump on Disruptions
Composable manufacturing is an approach that uses a virtual tool to assemble - or compose - modular packages of pre-programmed processes into new workflows on a screen.
Synthetic learning - How synthetic data can help manufacturers train AI
With synthetic data providing such a useful alternative to generating real-world data, it might not seem surprising that a study by Gartner estimates that by 2024, 60 per cent of all data used in AI developments will be synthetic.
Learn How To Protect Your Business with AI for Visual Inspection - Pleora Webinar Live April 6, 2022
This webinar will discuss how two manufacturers - a distillery and an electronics assembly operation - are using camera-based visual inspection to protect their brand and make manual processes repeatable, consistent, and traceable.
Bringing AI to Electronics Assembly Inspection
Adding automated decision-support to visual inspection helps speed inspection rates, improve end-to-end product quality, and provides more qualitative product evaluation to ensure manufacturing processes are repeatable and traceable.
Private 5G Connectivity and AI Technologies Accelerate the Transformation From Automation to Autonomy
This article looks at private 5G (known as P5G) and how it supports advanced and emerging technologies, including AI cameras, enabling manufacturers to drive more functionality closer to the edge.
The Earth's environment is in code-red status, but new digital solutions can meet the challenge.
Plant controller systems based on static models are not responsive enough to adapt to changes and prescribe actions to insure optimal outcomes. As a result, set points are adjusted every now and then by operators who hunt for good conditions.
Four Ways AI Will Change Manufacturing in 2022
AI and machine learning offer manufacturing a chance for new and stable growth. When paired with traditional automation, these technologies can improve efficiency and decrease costs.
Transforming Legacy Manufacturing Enterprises With AI on the Edge
This article discusses how legacy manufacturing enterprises can harness the latest technologies, to optimize factory operations without having to ramp up infrastructure investment.
AI & Machine Vision based Automated Weld Defect Detection for Manufacturing Industry
Purpose-built solution AI and machine vision solution on Intel® edge processors are helping manufacturers successfully adapt the defect detection technology and expand it to address broader Industry 4.0 use-cases.
AI for End-to-End Quality
Artificial intelligence (AI) is gaining favor as a solution for quality problems, but many manufacturers struggle with the perceived cost and complexity of implementing new technology.
AIoT and Edge Analytics: a Powerful Combination
Swedish philosopher Nick Bostrom once said, "machine intelligence is the last invention that humanity will ever need to make". AI decision making, with real time communication and data analytics, has the ability to transform the way manufacturers understand machines.
One Hour Makes All the Difference: Automate Quickly and Effectively With AI
Automation helps companies achieve greater flexibility and planning reliability, even in the case of multi-variant production. One factor that deters many companies from switching to automated processes, however, is time.
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