How Artificial Intelligence and Machine Learning can be used for your project or work?

Course Discussions AI and ML for Managers
#54

Hi,

Currently working on data gathering.

Regarding project, I will like to use AI/ML to analyze the data and determine certain pattern or behavior to predict the future of buyers for an ecommerce store we’re about to launch.

Thanks
Abel

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#55

Hi,
Being a Researcher and IT professional,

  • Research Automation

AI supports in making a simulation of test cases for certain scenarios in my research dealing with huge data. Also helps in processing huge data for update and maintenance.

  • IT Programming
    Relatively automate certain steps in programming that are done redundant using AI to reduce workload and save time through automation tools. In the areas like (Data Analysis, Customer Feedback and much more)

Regards,
Simi

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#57

I’m working in an EPCM (Engineering, Procurement & Construction management) design consultancy that designs various refineries and heavy chemical industrial plants or units.
As I understand, the following 3 are few possible AI/ML applications that EPCM design consultants should try and encourage adoption :

  1. A recommendation engine that recommends shortest path for cables/ pipes to a 3D modeller
    3D model is an integral part of engineering design of a plant that involves a lot of heavy equipment and civil structures with various pipes and cables connecting each other. Completely automating model design might not be desirable but the job of a 3D modeller can be made simpler if a recommendation engine can give options of preferable shortest paths for connecting pipes or cables between any two equipment based on obstacle detection and following safe practices.

  2. Digitizing old hand drawn 2D drawings, layouts and diagrams shared by client of old plants for expansion projects
    Using image classifier models on several old drawings, diagrams and layouts that might include hand markups shared by client of old plants can give digital information that can be replicated or re used while design of expansion projects. This could improve efficiency and reduce time taken for manual efforts.

  3. Efficient disaster / fire management
    Similar to how ecommerce companies manage their inventory using modern supply chain management techniques like tracking packages using GPS, workers in a large facility with RFID tags can be tracked by an AI/ML framework that can assist during emergency response by providing live instructions to workers on field during emergencies like guiding them to nearest assembly points. The model can also provide real time monitoring of the entire facility with enhanced statistics to aid disaster relief or rescue teams with actionable insights.

Application no. 2 above regarding digitizing of old project documents to derive usable digital information is already successfully undertaken in my organization which helps in engineers skim through hundreds of documents in minutes to be able to search for specific types of symbols or equipment used and the metadata associated with those from scanned or hand drawn documents shared by client.

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#58

Hi,

I am in Clinical Trials area where-in the drug gets tested for safety and efficacy through various phases of Clinical Trials before coming to the market. Normally for drug to come to market, it takes many years and complex research and testing. Due to the amount of time it takes, there are possibilities where-in we need to make changes to the existing protocol in the middle of the study. Adaptive design is a rapidly evolving field where-in we can predict if the drug can be effective by using ML algorithms and predictive analysis. This is a case study where-in there is an extensive use of AI and ML to predict the success of the drug and adaptively changing the doses, size of population, protocol etc… which helps us save the time to produce the drug.

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#59

My company’s main focus is AI, leveraging Natural Language Processing, Text-to-Speech, and Computer Vision to generate AI chatbots.

I am a project manager and currenty do not use AI for project management, but would like to track the data model training and use this to potentially improve planning estimations for each sprint, as well as forecast and estimation of the product backlog to assist with building product timelines.

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#60

Artificial Intelligence can be used in increasing the efficiency correctness portability of various day to day projects

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#61

I want to use AI/ML to solve Insurance industry use cases, specially in underwriting and claims processes.

These are most time consuming, complex and costly tasks in Insurance life cycle.

Input to these process are customer calls (voice) and/or handwritten documents (structured, semi structured and structured).

These documents can be anything and in any format - medicine invoice, discharge summary, police report, doctor prescription, witness statement, death certificate, survey reports, accident images, just to name a few

So if we are able to identify key fields from these different inputs, then we can look at automating rest of steps in process

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#62

Hi,

I work as Training Manager, hence, I would like to use AI and ML in my vertical to predict the probable attritions during a Training Class for a specific Client. There are regular attritions during a class and hence using AI & ML we can find out what would be our Training Throughput basis the predictions to find out probable attrition numbers.

Thanks,
Sunny Suri

1 Like
#63

Machine Learning and Artificial Intelligence will be extensively used in various areas within the company. I will share a few examples:

Identifying sales leads that have potential to generate high volume sales in future is very important for business, Machine Learning and AI will be leveraged to solve this problem. Marching Learning techniques like Classification Approaches, Recommendation Engine, Natural Language Processing techniques will be used to achieve this objective.

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#64

There are many use cases and applications of AI one can think of applying while starting a business- automating tasks according to skills and proficiency- with ratings of the employees to the given task- variable in bonus on this structure is a simple one.
For myself, I would like to make a classification model that can detect an image and identify it’s copy and origin on the internet- which is then minted as an NFT with the datestamp and ownership.

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#65

Hi,
I am confident AI can be used to enhance the performance of telecom business supporting applications by monitoring and reporting any breach in defined SLAs and suggesting preventive measures.

regards
Nikhil Ingole

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#66

I am from the networking industry. Some of the ways AI/ML can be used here are:

  1. To keep track of the running systems on the network and its applications. After collecting the data for a few months on the status of the systems and the applications, this data can be used to predict the behaviour of the systems. It can be used to identify anomalies in advance and one or more actions can be configured to be executed, in case the anomaly occurs.

  2. AI/ML can be used to observe user behaviour on the use of the applications(for example observe how the user uses or browses the GUI), and a customized experience can be provided to each user. This will help users in Enterprise class applications where there are a large number of features available on the GUI and not all users may need all features. So, by observing each users’ browsing behaviour, the most commonly used features may be provided on the first page and other features can be relegated to other pages.

  3. In wireless network security, the behaviour of the network can be observed and data collected. If one or more users/devices are trying to access the network without authorization, that user or device can be classified as a rogue-device or a rogue-user. More insights can be identified as to the location of the rogue-devices, the timing of unauthorized access, the category of the users, the type of probes sent…etc

Thanks
SG

1 Like
#67

In my view AI and ML can be used in this vertical in many ways like:
Navigation
Train the drones for autonomous flights
Track objects with precision
Mapping areas

2 Likes
#68

I work as Technical Associate Architect in Fintech company where we sell customized portfolios to our HNI Clients depending upon their risk appetite.

Below are the use cases that can be used

  1. Calculating the risk profiles

  2. Asset Allocation depending upon customer’s profile

  3. Market View or Direction

  4. Optimal / Automated Portfolio Generation

  5. Rebalancing the Portfolio

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#69

Hi All,
AI and ML can be used for creating BOT application

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#70

Hi,

I am a Trader, Investor and Analyst of Equity Markets and financial instruments.

In regards to project, I will like to use AI/ML to analyze data and determine certain pattern or behavior to predict the future in equity investments and financial management and forecasting of economic circumstances across the world.

Thanks
Kunal

1 Like
#71

AI and ML can be used to understand the patterns that gets triggered on the daily basis for cloud operations and start leveraging this to solve those problems without the human interventions with this we can completely cut down the Mean Time To Resolve the issue and availability of the applications will be very high for the customers.

Also, we can use this methodolody to analyse the patterns and come up with a permanent fix for the problem that we face.

#72

I work in a think-tank focusing on various aspects of civilization studies, including geopolitics, impact of technology on society, mind sciences, history of Indian science and technology etc.

Some use cases on AI/ ML that come to my mind:

  1. Domain specific information retrieval and summarizer
  2. Predicting geopolitical/ war/ economic impact scenarios
  3. Translation of existing domain specific corpus of knowledge to different Indian languages
  4. Mapping and interpreting Indian knowledge systems to contemporary paradigms and design solutions for the present day.
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#73

Predictive Defect Assignment using AI in a Software Development Environment

Introduction

Software development is a complex and challenging process, involving many teams and components. One of the key challenges faced by organizations is accurately assigning defects to the correct component. This process can be time-consuming and prone to human error, leading to longer resolution times and increased costs. In this case study, we will examine how the use of Artificial Intelligence (AI) can improve the accuracy and efficiency of defect assignment in a software development environment.

Problem Statement

A large software development organization face several challenges in the defect assignment process. The manual process is time-consuming, with team members having to spend significant amounts of time reviewing each defect to determine the correct component. This leads to longer resolution times and increased costs. Additionally, the manual process is prone to human error, with defects sometimes being assigned to the wrong component, leading to further delays. Defect hoping leads to additional costs.

Solution

To address these challenges, we implemented an AI-based solution for predictive defect assignment. The solution utilized natural language processing and machine learning algorithms to analyze the description and details of each defect and predict the most likely component to which it should be assigned. The solution is integrated into the organization’s defect tracking system, JIRA tool, allowing team members to quickly and easily assign defects to the correct component.

Implementation

The implementation of the AI-based solution involved several key steps:

  1. Data Collection: The first step is to collect data on past defect assignments, including the description and details of each defect, as well as the final assignment. This data is used to train the AI algorithms.
  2. Algorithm Development: The next step is to develop the AI algorithms that would be used for predictive defect assignment. This involved using natural language processing and machine learning techniques to analyze the data and identify patterns and relationships that could be used to predict the correct component for each defect.
  3. Integration with Defect Tracking System: Once the AI algorithms are developed, they are integrated into the organization’s defect tracking system. This allows team members to easily access the solution and assign defects to the correct component.
  4. User Testing: The solution is then tested by a small group of users to ensure that it is accurate and easy to use. Based on their feedback, the solution is refined and improved to ensure that it met the needs of the organization.

Results

The implementation of the AI-based solution for predictive defect assignment has a significant impact on the software development process. The solution significantly reduces the time required to assign defects to the correct component, reducing resolution times and costs. Additionally, the solution greatly reduces the risk of human error, leading to fewer defects being assigned to the wrong component and fewer delays.

Conclusion

In conclusion, the use of AI in predictive defect assignment can provide significant benefits for software development organizations. By reducing the time required to assign defects and reducing the risk of human error, AI-based solutions can help organizations improve their overall efficiency and reduce costs. Additionally, by integrating AI algorithms into existing systems, organizations can easily and quickly benefit from the advantages of AI without having to make major changes to their processes or infrastructure.

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#74

Hello Everybody,

I am looking forward to use Artificial Intelligence and Machine Learning to create Generative AI for 3D generation of simple, daily-life objects inspired from real-life object data and recreate everything in a Virtual 3D form and make it accessible to public with imaginitive prompts and a wide-application in Generative AI.

Regards,
Pranay Kumar Panda

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