ppt AI anusha.pptx_20240410_071422_0000.pdf

**Artificial Intelligence (AI)** refers to the simulation of human intelligence in machines programmed to think and learn like humans. This technology encompasses various fields, including machine learning, natural language processing, robotics, and computer vision, enabling computers and systems to perform tasks that typically require human intelligence.

### Key Components of AI:

1. **Machine Learning (ML)**: A subset of AI where algorithms learn from data to make predictions or decisions without explicit programming. It includes supervised learning, unsupervised learning, and reinforcement learning.

2. **Natural Language Processing (NLP)**: This enables machines to understand, interpret, and respond to human language. Applications include chatbots, language translation, and sentiment analysis.

3. **Computer Vision**: The ability of machines to interpret and make decisions based on visual data. It is used in facial recognition, object detection, and image analysis.

4. **Robotics**: The branch of AI that deals with the design and operation of robots, which can perform tasks autonomously or with minimal human intervention.

### Applications of AI:

- **Healthcare**: AI is used for diagnostics, personalized medicine, drug discovery, and robotic surgeries, improving patient outcomes and operational efficiency.

- **Finance**: AI algorithms analyze market trends, detect fraud, and automate trading, enhancing decision-making and risk management.

- **Transportation**: Autonomous vehicles use AI to navigate and make real-time decisions, improving safety and efficiency in transportation.

- **Customer Service**: AI-powered chatbots and virtual assistants provide instant support, enhancing customer experience and operational efficiency.

- **Manufacturing**: AI optimizes production processes, predicts maintenance needs, and enhances quality control, driving efficiency and reducing costs.

### Challenges and Considerations:

While AI offers significant benefits, it also poses challenges, including ethical concerns around data privacy, algorithmic bias, and job displacement. Ensuring responsible AI development and deployment requires careful consideration of these issues, including transparency, fairness, and accountability.

### Future of AI:

The future of AI holds immense potential, with advancements in general AI, enhanced machine learning algorithms, and more sophisticated human-computer interactions. As AI continues to evolve, it is expected to transform various industries, driving innovation and improving quality of life.

In summary, AI is a powerful technology reshaping our world, offering solutions to complex problems while also requiring responsible stewardship to maximize its benefits and minimize risks.

1. Presentation by
Name:Anusha Sanapathi
I'd no: S210122
Branch:ECE
Date:10-04-2024
AY:2023 to 24

2. Purpose:
Enhance efficiency and productivity
Solve complex problems
Automate repetitive tasks
Scope:
Various industries: healthcare, finance, retail, etc.
Consumer applications: virtual assistants,
recommendation systems, etc.
Research and development
Objectives:
Improve decision-making processes
Enhance user experience
Enable predictive analytics
Facilitate automation
and optimization

3. Agenda
What is AI..,?
Applications of AI
Categories of AI
About driverless cars breifly
AI in our contemporary world

5. Intelligence vs artificial intelligence
Intelligence
VS
Artificial intelligence
Artificial intelligence is created by humans to mimic human intelligence,
while human intelligence is the natural cognitive ability possessed by
humans. AI operates based on algorithms and data, while human
intelligence involves complex processes like reasoning, emotions, and
creativity.

6. Classification of AI
ARTIFICIAL INTELLIGENCE
Artificial Intelligence is a technique
which allows the machines to act like
humans by simulating their behaviour
and nature
MACHINE LEARNING
Machine Learning is a subset of artificial
intelligence. It allows the machines to learn
and make predictions based on its
experience(data) with out being explicitly
programmed
DEEP LEARNING
It’s the subset of ML based on artificial
neural networks in which multiple layers of
processing are used to extract progressively
higher level features from data.

7. Artificial intelligence
Machine learning
Deep learning
in
Driverless cars
eg: Tesla cars

8. AI in our contemporary
world
Medical field
Digitilization of health records
Early detection of diseases(IBM’s
research)
MIT’s Holicin antibiotic drug
Robots during pandemic
Industrial revolution 4.0
Digital wellbeing (thy gadget reminder)
E-commerce(gobs of orders)

9. Where is AI now?
AI
HR recruitments(key traits
of cand)
Banking sector(myriad
transactions)

10. AI based applications
All Works on AI
Adds based on our interest
Frequently watching videos
Frequently using words while typing
Displaying ads based on our searching
products
productivity apps

11. Summary
Artificial intelligence is the simulation of human behavior by machines
ML & DL are the subsets of AI
ML is nothing but machine learns itself (without exp programming)
Numerous applications in all sectors such as medical field , agri, e-
commerce, banking etc.,
One of the finest AI based tech is TESLA’s auto pilot car
Almost all applications we are using built based on AI like fb, snap ,insta
etc.,
AI playing a predominant role in our lives and AI became our part of life

12. Thank you