AI Quality Checks: How Good is AI at Ensuring Quality?

Table of Contents

1. Introduction
2. Who is Landing AI?
3. The Difference Between Machine Learning and Artificial Intelligence
4. How Landing AI Works for the Worker
5. The Applications of Landing AI
6. Using Landing AI for Non-conformity Checks
7. Case Study: Vision System for a Bakery
8. Strengths and Weaknesses of Landing AI
9. Pricing and Cost of Landing AI
10. Summary

Introduction

In this article, we will explore the capabilities and applications of Landing AI, a company that specializes in computer vision. We will start by understanding who Landing AI is and then Delve into the difference between machine learning and artificial intelligence. Next, we will discuss how Landing AI works for workers in various industries and take a closer look at its applications, with a focus on non-conformity checks. We will also examine a case study showcasing the use of Landing AI for a bakery. In addition, we will evaluate the strengths and weaknesses of Landing AI and discuss its pricing and costs. By the end of this article, You will have a comprehensive understanding of Landing AI and its impact on various industries.

1. Who is Landing AI?

Landing AI is a company that aims to make computer vision more accessible and easier to implement. Led by David, the head of their data science practice, Landing AI focuses on bridging the gap between subject matter experts and data scientists. Their goal is to provide an end-to-end, no-code platform for operators, quality managers, and other professionals in the digital transformation industry. By doing so, Landing AI aims to lower the barrier to entry for implementing artificial intelligence and machine learning solutions.

2. The Difference Between Machine Learning and Artificial Intelligence

Machine learning is a subset of artificial intelligence. Within the realm of artificial intelligence, there is a specific branch called deep learning, which is Landing AI's area of expertise. Deep learning involves using computer algorithms to extract valuable insights and derive meaning from visual assets such as images and videos. This is where Landing AI shines, as they specialize in harnessing the power of deep learning to provide nuanced and accurate analysis of visual data.

Pros:

• Deep learning allows for more complex and nuanced analysis compared to traditional rule-Based systems.
• Landing AI's expertise in deep learning enables them to derive valuable insights from visual assets, leading to better decision-making and improved processes.
• The use of deep learning can significantly enhance the accuracy and efficiency of non-conformity checks, among other applications.

Cons:

• Deep learning requires a significant amount of data and computational resources, making it more resource-intensive compared to other approaches.
• It may not be suitable for all use cases, especially those that involve simple rule-based systems or rely heavily on color matching.

3. How Landing AI Works for the Worker

Landing AI takes a unique approach by bringing data science directly to the subject matter experts, such as operators and quality managers, who are working on manufacturing lines or in manufacturing plants. Rather than working separately from these experts, Landing AI provides them with a user-friendly, no-code platform that enables them to benefit from AI and machine learning technologies. This platform, called Landing Lens, allows operators to train models and Create customized applications specific to their job requirements.

By using Landing Lens, operators can easily identify defects or non-conformities in their work. For example, in a classification project, operators can train a model to identify defects in printed parts by providing the platform with a dataset of images. Landing AI's platform then enables the deployment of the trained model as an API endpoint, which can be integrated with existing systems. This integration can be achieved through custom widgets or through partnerships with other platforms, such as Tulip, which provide additional functionalities and ease of use.

Pros:

• Landing AI's platform empowers operators and other workers by allowing them to leverage AI technologies without the need for extensive coding or data science knowledge.
• The no-code approach makes it easier and more accessible for workers to implement AI solutions in their job roles.
• By incorporating machine learning models into their workflow, operators can streamline processes, improve quality control, and reduce errors.

Cons:

• While the platform simplifies the implementation of AI, there may still be a learning curve for some operators who are not familiar with the technology.
• The effectiveness of the AI models largely depends on the accuracy and quality of the data used for training. Garbage in, garbage out principle applies here.

4. The Applications of Landing AI

Landing AI's applications extend beyond non-conformity checks. The versatility of their platform allows it to be utilized in various industries and scenarios. One such example is the use of Landing AI's vision system for a bakery. The system employs machine learning to identify the number of raw dough balls in trays and also checks for non-conformities, such as low dough viscosity that affects the Shape of the dough in the tray. This application demonstrates the ability of Landing AI to tackle diverse use cases and provide valuable insights in different industries.

As Landing AI continues to innovate and expand its capabilities, the potential applications are wide-ranging. From quality control in manufacturing to waste treatment and beyond, Landing AI's platform can enhance processes, improve efficiency, and reduce errors in a multitude of industries.

5. Using Landing AI for Non-conformity Checks

One specific area where Landing AI excels is in non-conformity checks. Traditionally, operators rely on their visual inspection skills to identify non-conformities in products. However, human inspection is prone to errors and inconsistencies due to factors such as fatigue or varying levels of expertise. By utilizing Landing AI's computer vision capabilities, operators can now improve the accuracy and efficiency of non-conformity checks.

Landing AI's platform allows operators to train models specifically for their non-conformity detection tasks. By analyzing visual assets, such as images of products or components, the trained models can automatically identify non-conforming items based on predefined criteria. This automation reduces the reliance on human inspection alone and ensures that non-conformities are detected consistently.

The application of Landing AI for non-conformity checks ultimately leads to improved product quality, increased customer satisfaction, and a reduction in costly errors. Additionally, it frees up operators' time, allowing them to focus on more complex tasks that require human expertise.

6. Case Study: Vision System for a Bakery

A compelling case study for Landing AI's capabilities is the development of a vision system for a bakery. The system utilizes machine learning and artificial intelligence to identify the number of raw dough balls in trays. This application eliminates the need for manual counting, which can be time-consuming and error-prone.

Additionally, the vision system also checks for non-conformities in the dough, such as low viscosity. By analyzing the visual data of the dough in the tray, the system can detect deviations from the desired shape or consistency. This ensures that only conforming products proceed to the next phase of production, maintaining the quality standards of the bakery.

The use of Landing AI's platform in this bakery demonstrates the adaptability and effectiveness of their computer vision technologies in real-world scenarios. By streamlining the inspection process and enhancing quality control, Landing AI contributes to increased productivity and improved overall efficiency for businesses in various industries.

7. Strengths and Weaknesses of Landing AI

Landing AI, with its focus on computer vision and deep learning, has several notable strengths. Firstly, their platform enables operators and non-data scientists to leverage AI and machine learning technologies easily. This accessibility empowers workers by allowing them to harness the power of AI without extensive coding or data science knowledge.

Secondly, Landing AI's expertise in deep learning enables them to handle complex and nuanced analysis of visual assets. This ability to derive valuable insights from images and videos sets them apart, especially when compared to traditional rule-based systems.

However, it is crucial to consider the potential weaknesses of Landing AI's technology. Deep learning, while powerful, requires significant amounts of data and computational resources. This aspect makes it more resource-intensive compared to other approaches. Additionally, there may be situations where simple rule-based systems or color matching techniques can achieve similar or even better results compared to Landing AI's deep learning models.

Overall, Landing AI's strengths lie in its ability to simplify the implementation of AI and its expertise in deep learning. These strengths contribute to improved productivity and enhanced decision-making for businesses. However, careful consideration of the specific use case is essential to ensure that Landing AI's technology aligns with the requirements and objectives of the application.

8. Pricing and Cost of Landing AI

The pricing model for Landing AI is consumption-based. This means that the cost is determined by the number of inspections performed using their platform. The platform is fully cloud-based, with the option to download and deploy models on edge devices for high-throughput use cases.

In terms of cost breakdown, the commercial model charges one credit per image for training and inference. The exact pricing details may vary, but assuming a Scenario where 30,000 units are inspected per month and three non-conformities are classified, the estimated cost would be around $700 to $800 per month. This cost covers both the platform and the elastic cloud costs required by Landing AI.

It's important to highlight that the absence of infrastructure costs, thanks to Landing AI's cloud-based platform, should be taken into account when considering the total cost of ownership. The cost of infrastructure, which is often overlooked, can be substantial when deploying custom AI solutions independently.

9. Summary

In conclusion, Landing AI is a company that aims to make computer vision accessible and easy to implement. By bridging the gap between subject matter experts and data scientists, Landing AI provides a no-code platform that allows workers to leverage artificial intelligence and machine learning without extensive coding knowledge.

Landing AI excels in non-conformity checks and offers various applications that enhance quality control, streamline processes, and enable more accurate and efficient decision-making. Their deep learning expertise enables them to derive nuanced insights from visual assets, leading to improved processes and enhanced productivity.

However, it's crucial to consider the strengths and weaknesses of Landing AI's technology. While deep learning is a powerful tool, it requires substantial amounts of data and computational resources. Additionally, there may be situations where simpler rule-based systems are more appropriate.

The pricing of Landing AI is consumption-based and covers both usage of the platform and the necessary cloud resources. It offers a cost-effective solution compared to building and maintaining infrastructure independently.

In conclusion, Landing AI provides a user-friendly and efficient tool for implementing AI and machine learning in various industries. By leveraging their platform, businesses can enhance quality control, optimize processes, and achieve improved productivity and accuracy in their operations.

Highlights

• Landing AI aims to make computer vision more accessible and easier to implement.
• Their platform, Landing Lens, provides a no-code solution for operators and non-data scientists to leverage AI and machine learning.
• Landing AI specializes in deep learning, allowing for complex and nuanced analysis of visual assets.
• Non-conformity checks are a significant strength of Landing AI, offering improved productivity and quality control.
• Landing AI's pricing model is consumption-based, covering both platform usage and elastic cloud costs.
• Infrastructure costs are eliminated as the platform is fully cloud-based.

FAQ

Q: What is Landing AI?

A: Landing AI is a company that focuses on making computer vision more accessible through their user-friendly platform, Landing Lens. They specialize in deep learning and offer a range of applications for various industries.

Q: How does Landing AI work for workers?

A: Landing AI's platform allows operators and non-data scientists to harness the power of AI without extensive coding knowledge. They can train models specific to their job requirements and create customized applications to streamline processes.

Q: What are the strengths of Landing AI's technology?

A: Landing AI excels in non-conformity checks, offering accurate and efficient inspection processes. Their deep learning expertise enables nuanced analysis of visual assets, leading to improved decision-making and productivity.

Q: What are the pricing and costs of Landing AI?

A: Landing AI follows a consumption-based pricing model. The cost is determined by the number of inspections performed using their platform, covering both usage and elastic cloud costs. The absence of infrastructure costs should also be considered.

Q: Are there any limitations to Landing AI's technology?

A: While Landing AI's deep learning technology is powerful, it requires significant data and computational resources. Additionally, simpler rule-based systems may be more appropriate for certain use cases, especially those involving color matching.