Muralidhar Reddy

I did multiple small to big scall project in with real world & experimental. A few of the major projects are listed below.

Breast cancer detection:

The project's goal is to assist health-related areas such as patients' doctors, hospital administration, medicine stores, and so on, as result ROI [Return on Investment] increased, saved diagnostic time and son on. The project's methodology consists of obtaining a data set from a cancer patient from the past, doing data processing, and building an eth model on the data. We can forecast the new patient based on the model's output. Real breast cancer instances were seen in my immediate surroundings. I understand the difficulties they are experiencing, which is why I am working on the project.

AI video maker:

Ai video maker is one best way to show the voice over content with AI images. This is used for simple understanding of complex content with graphics of AI. This saves lot of time, less investment, Easy processing of graphics in AI and so on. we created AI video making website with help of professor Dr Daniel in US. Design and dsubmitted it to the USF my team and submitted into USF portal. As a continuation of project we planned to work on improving the lip moment in AI video while speaking. Most of company trying to create to better AI video maker like Adobe, google …etc.

Automatic attendance system using face recognition:

when I was a freshman in college. The professor was unable to call students up one by one to check attendance, its cause class disturbances, loss of time, error in attendance … etc. We wanted to create an automatic attendance system employing faces in class without disturbing the group to prevent or assist with taking attendance in place of the lecturer calling names. We put this automatic attendance system in place during this procedure, and it is currently a functioning project.

AI Umbrella encompasses a wide range of technologies such as machine learning, deep learning, big data, and so on. AI is the most effective human mimic automation task. The use of AI robots is growing by the day. According to the research, workers are concerned about losing their employment to automation. AI is a long-term technology inspired by human intelligence. The human effect must guide AI progress. Instead of replacing human talents, AI applications should supplement and augment them. Data science is a component of human-centered design. When developing human-centered AI solutions, privacy and ethics must be considered. Human talents and experiences are enhanced through augmented intelligence. Humans acquire, analyses, and make sense of data to develop greater intelligence.

The fast growth of Artificial Intelligence (AI) has enormous potential to shape a brighter future for humanity. However, addressing the risks and obstacles associated with AI adoption is critical. While AI has the potential to increase global economic prosperity, drive employment creation, and raise productivity, it also has the potential to displace sectors, increase economic inequity, and exacerbate education and skill gaps in the workforce. A human-centered approach is critical in managing this disruptive technology.

Human-centered AI design and deployment includes imagining the sort of future we want. It is impossible to guide a route towards a good end without a clear knowledge of our aims. Before introducing AI solutions, it is critical to examine the impact on individuals and society.

Concerns about job displacement because of automation, a subset of AI, are prevalent. According to studies, a considerable number of jobs involve operations that may be automated, thus causing employment disruption. Furthermore, the changing nature of labor because of AI implies a shift in skill requirements. Technological abilities are expected to be in higher demand, while social-emotional skills will remain important. This transition has the potential to result in a mismatch between the skills available in the labor market and those required by businesses.

Another key factor to examine is the possible influence on economic disparities. Low-skilled individuals may face the burden of relocation, while high-skilled people profit more economically. This mismatch has the potential to worsen economic inequality.

AI must be human centered to manage these hurdles. It should be inspired by human intellect, directed by its human effect, and designed to improve and complement rather than replace human talents. Teaching, training, and developing human work capability should be prioritized by AI systems. Human-centered AI practices push engineers to take these conflicts and realities into consideration, resulting in a brighter future for everybody. AI may be rebranded as enhanced intelligence by embracing privacy, ethics, and the enhancement of human skills. Businesses should cooperate with employees to provide training and meaningful employment possibilities.