Software Engineering

The concept: The basic concept is to build trained AI model for each role separately in scalable fashion within a private cloud. As an example to train a scrum master as an AI component, we have to probably feed good knowledge of day to day tasks of a scrum master. Apart from that the model need to aware how scrum master manage the SCRUM board in the relevant tool stack eg: JIRA. One pod within the Kubernetes cluster can be considered as a one scrum master per a team. Likewise we have some sort of ability to maintain a good knowledge base as a source of training data. Apart from these steps, we need to think about how to simulate speaking and handling, commanding and escalating in the meetings, The end goal of this conceptual project is to fully automate the software life cycle and fine grain the each responsibilities of scrum masters, project managers, software architects, CTO and CEO. however the each role should be backed by a single human being. The ultimate goal of this project to...

 The newly introduced PrivateGPT is a production ready and most suitable for the organisations who handles extremely sensitive data as per their documentation. To be carefully considered. To find out more information.  https://github.com/imartinez/privateGPT/tree/main

 Problem Statement: Suppose the Government plans to issue up to $10,000 of Savings Bonds. Four individuals applied for a total of $18,000 of Savings Bonds: A ($2,000), B ($4,000) C ($5,500) and D ($6,500). The available bonds will be spread out among as many investors as possible in the following manner: Applications are filled in denominations of $500 upwards. After Round 4, $8,000 of Savings Bonds have been allotted, and Investor A's application has been fully met. $2,000 of Savings Bonds are left. In Round 5, $1,500 of Savings Bonds are allotted. In Round 6, the remaining $500 is insufficient to fill all applications. One person among Investor B, Investor C and Investor D is randomly allotted the remaining $500. In this case, Investor C gets it. The cutoff amount in this case is $2,500. In the final allotment: Investor A is allotted $2,000. Investor B and Investor D get $2,500 each. Investor C gets $3,000. limitations: 1. The minimum individual investment amount is $500 2. The m...

Quarkus gRPC Service Implementation from the scratch Requirement In order to produce most reliable, fast and maintainable products we can use Quarkus ( Supersonic, Subatomic Cloud Native Java Framework) as a foundational technology for our backend services. Our task it to use [Quarkus](https://quarkus.io/) and [gRPC](https://grpc.io/) to build a microservice running in [Kubernetes](https://kubernetes.io/) with the following capabilities: 1. The microservice should expose APIs for Smart Models and Smart Features 2. Smart Model is a generic model which can be used to describe your favourite Services and IoT    Devices. Think about the following examples for: - Devices: Smart Watch, Remotely Controllable Camera, etc - Services: Open Weather Map, IMDB Movie Database, etc 3. Smart Feature is a specific feature of this smart model which describes one functionality. we can    consider following examples for: - Devices: Take Camera Screenshot, Get Camera Live Video URL, Get ...