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

Course Discussions AI and ML for Managers
#91

Currently, my research focuses on formulating a mathematical model using a partial differential equation to predict the growth of solid malignant tumours. As I am learning AI and ML, I aim to design an ML pipeline to integrate growing tumour imaging data (such as Magnetic resonance imaging (MRI) scan, Computed tomography (CT) scan, and Mammography, etc) with the mathematical model.

Consider a scenario where we aim to predict the growth of a solid tumour, such as a brain tumour, breast cancer, liver cancer, etc. To achieve this, we will start by collecting MRI data, including multiple tumour size measurements taken over time. Then, we will create a partial differential equation (PDE) using the provided clinical data, typically a form of reaction-diffusion equation. This equation will encompass parameters like cell proliferation rate, diffusion coefficients, and nutrient availability. Subsequently, we will develop a machine-learning pipeline to combine the MRI data with the mathematical model. Integrating AI, ML, and mathematical modelling based on PDEs presents a robust approach to forecasting cancer growth and enhancing the treatment. By harnessing expertise from multiple fields, such as mathematics, computer science, and oncology, this methodology has significant potential to advance precision medicine in cancer care.

#92

I am working for an IT company in Bangalore, India. We are US based company with about 16000 employees across globe.
I would like to use AI/ML technology in my company for the below use case:
Use case:- To create a dynamic internal platform that connects with the employees with open opportunities within the company based on skills, interests and career aspirations.
Profile manager- Employees to create their profile highlighting their skills with proficiency levels, Identify career preferences, target roles, preferred functions & ideal work locations. This information is used by the platform to match with the suitable opportunities and notify the employees so that they can apply for the position.This will help employees to change the job within the company, take higher role to grow and meet the career aspirations.
Thanks & Regards
Manjunath Bhat

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#93

I would like make a progress using AI and ML for the healthcare domain with having patient experience
with the alerts on disease , medication and do and don’t’s based on the climate condition and lot of things because it a sector where very large space is available to make a innovation

thanks
kamil shaikh

1 Like
#94

I work at one of the world’s largest US-based marketplace product companies. I am currently using AI across 2 workstreams:

  1. A conversational chatbot using OpenAI APIs to help users arrive at the desired inventory and offer a curated list of results that serves their affinity
  2. Realtime curation of inventory based on trending tags (trending here are inventory categories that are trending in a given geo radius) to offer users a locally relevant user experience
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#95

In my day-to-day work there are many repeatitive task which doesn’t need any intelligence to perform it. For example, I need to refer few documents and answers queries from developers accordingly. I think AI can be used to understand the query from developer, read the documents to find the required info and post it back to the developers.
Also there are few defects which gets high priority just if the title has mention of ‘Submission failure’. This also can be done by AI by reading and recognizing the title as ‘Submission failure’

1 Like
#96

AI/ML for image perception for sign recognition in source data, translating to geospatial data

AI/ML for natural language processing to identify key geospatial information from digital articles.

AI/ML for natural language processing of customer feedback for faster integration to geospatial data

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#97

Dear All
In Our Company , We collect a huge amount of Data through our Inhouse App.
The Data Includes Pictures and Datas taken from the field by the field staff.
I would like AI and ML to analyse the image and give details about

  1. Client’s product visibility Vs their’s Competitors visibility,
    2.Availability of Products in the shelf and give stock out reports
  2. Analyse the coverage pattern of the field team and provide them a optimal route plan that will minimise their travel
  3. Give Visit Report and deviation visit report for the field team
  4. Automate PPT from the images taken
  5. Live dashboard from the Data
    Regards,
    Arunkumar S
1 Like
#98

Hello,

ML is our project is helping us to reduce junk data from products. Additionally, it also helps us in drafting MoMs, emails and summarizing the content from the pages. It also helps us to make product decision, thou not extensively.

Thanks.

#99

Scope of AI and ML is manifold.we have an AI and ML practice as well. specifically for my products and my role. i am trying to understand the use cases better by understanding AI better via this course so that i will be able to understand and support initatives on AI. we have vast amounts of data being collected.

#100

Hi everyone,
Currently working on how AI recommend the spam or ham mails.

#101

We integrated a speech-to-text API into our workflow, significantly improving productivity and turnaround times for transcribing legal recordings. This automation allowed us to handle more projects with faster delivery and reduced the team size without compromising accuracy. The AI system, capable of understanding various accents, helped maintain high-quality transcriptions, enabling us to scale and take on additional projects efficiently.

#102

AI/ML with natural language processing to ease access/queries to internal daashboards

#103

Hi,

I’m working in mapping industry and I believe ML can help to detect change in reality hence we can maintain map freshness which reflect with reality

Regards,
Triawan

#104

I work in financial instituion, where we are using AI/ML models can be used in the following cases

We receive notifications from other financial institutions like exchanges, despositories etc. Example, Change in exhange codes, symbols, trade settlement time etc. We receive close to 100 notifications in day (average) from other financial insitution. Right now, these notifications are manually read by an employee to understand the impact of the Change Notification. We can develop ML model, which would digest different notifications received and help to classify them as Impact/Non Impact notification

#105

Hi All,

I belong from healthcare recruitment sector, I would recommend using AI and ML in day to day manual activities we do on internal tools which can automated to reduce time and increase productivity. With the help of ML we will be able to identify the weeks or months where revenue is low and how we can work on converting those durations.

#106

In my work, I use AI and ML to make everyday tasks easier and more efficient. For example, I use machine learning to analyze customer feedback and spot trends, helping me decide on improvements faster. AI tools also automate routine tasks, so I can focus on creative problem-solving. This technology feels like a helpful partner that makes my work smoother and my decisions smarter.

Thanks
Sakshi Rai

#107

Hi,

I am working as a software tester. Right now we are not using AI or ML. But kept hearing about Gen AI, AWS. My thought about ML and AI in software testing could be used in test case creation, regression testing, automation test suite preparation etc.

The disadvantage could be testing the software as there could be frequent changes in functionality, UI.

#108

Hello All,

I work as Cybersecurity Architect in one of the MNC.

Introduction:
Below is the case study and I want to build a project, My company is Automation solution provider which is using AWS, Azure and GCP and On-premises solution to deliver the Client needs.

They help customers build automations and has to handle sensitive / PII Data and can experiencing a surge in cyberattacks, including sophisticated phishing attempts, ransomware, and attempted data exfiltration. Goal is to enable company to maintain adequate security posture for various clouds and on-prem solutions. Also provide proactive and intelligent approach to SOC and SecOps and cloud security teams.

Challenges:

  1. Since it’s a multiple cloud environments, we find it difficult to get candidates which has expertise in all CSPs.
  2. Security Service available in every cloud is different and finding a common solution or standard for all cloud is difficult.
  3. If we ingest all available cloud logs in SIEM, it has all the logs but building alert based on the logs to get a genuine security issue is difficult because of bulk of data.
  4. Threat landscape is increasing day by day, now with sophisticated and state sponsored attacks it’s becoming difficult to protect the infrastructure. So we need rapid and latest threat intel to build such protections.
  5. Vulnerabilities in the deployed code / library, OS or infra component can cause exploit, so performing Applicability analysis based on deployment is difficult.
  6. Obtaining Compliance certifications (GDPR, PCI DSS, HIPPA, HITRUST, SOC1, SOC2, ISO 27001/17/18, ISO 42001) needs readiness and evidence collection and happens every year or in two years can be tedious.

Solution:
We can utilize AI to overcome some of the above challenges and obtain enhanced security operations.

  1. AI Based CSPM:
  2. AI Based SIEM:
  3. AI Based Threat Intelligence:
  4. AI Based UEBA (User and Entity Behaviour Analytics):
  5. AI Based vulnerabilities triaging:
  6. AI Based Compliance Agent:
#109

Hi,

As Software Engineering Manager, one use case that I can think of is to potentially see the value in using AI-Powered code generation tools like GitHub copilot to assist developers. in writing code more efficiently, writing test cases, providing suggestions on best practices as well as code refactoring.

Thanks,
Deepu

#110

Hi,

In my role as a Technical Project Manager, I see potential value in AI-powered tools in predicting project timelines, assess risks, and suggest optimal project schedules based on historical data from similar projects. ML Algorithms could be used to analyze past projects to forecast delays, resource allocation and potential bottlenecks.

Using documentation summarization via NLP techniques, we could also figure out a way to reduce the time spent on manually reviewing and understanding large sets of project documentation.

Thanks,
Anju