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Artificial
Intelligence
intelligence by machines
Submitted by Group-3
Artificial intelligence
Artificial intelligence refers to systems or machines that mimic
human intelligence to perform tasks and can iteratively improve
themselves based on the information they collect.
Examples
Medical diagnosis
Voice or Handwriting recognition
Chatbox
Computer Search Engines
Self-driving Cars
Automated Financial Assistant
Components of AI
Learning
Reasoning
Problem Solving
Perception
Language
MACHINE LEARNING
It is branch of artificial intelligence that enables
computer to "self learn" from training data &
improves over time, without being explicitly
programmed
Learning
Predicts
Ordinary
system
Machine
Learning
With AI
Improves
Techniques in M L
Supervised Learning Reinforcement Learning
This type of machine learning
comprises three major
In this type labeled data is used
for the training data. Supervised
learning technique helps us to
predict future events with the
help of past experience
components: the agent, the
environment, and the actions.
Unsupervised Learning
A machine is trained with some
input samples, while output is
not known. Thus machine may
not always provide correct
output
How AI & ML are Integrated
Data mapping powered by AI can automate
data transformation mapping by providing
advanced features and agile data mapping
predictions with machine learning algorithms.
01
02 The autonomous learning capability of AI and
machine learning enable enterprises to learn
more about hidden patterns and trends from
large datasets, so that accurate business
intelligence and insights are derived from them
through applying statistical models.
Data processing with machine learning-powered data
integration tools can parse big data generating precise
data models that require less human intervention
03
Tesla cars come standard with advanced hardware capable of providing
Autopilot features, and full self-driving capabilities—through software updates
designed to improve functionality over time
Tesla's Autopilot AI enables your car to steer, accelerate and brake.
Navigate on Autopilot - All you will need to do is get in and tell your car where to go. Don’t
say anything, your car will look at your calendar and take you there as the assumed
destination.
Standard Safety Features like Automatic Emergency Braking, Front Collision Warning, Side
Collision Warning, Auto High Beams
Eight cameras and powerful vision processing provide 360
degrees of visibility at up to 250 meters of range.
Each Tesla car has a powerful set of vision processing tools
developed by Tesla. Built on a deep neural network, Tesla Vision
deconstructs the car's environment at greater levels of
reliability than those achievable with classical vision processing
techniques
Apple stands out compared to other tech companies, given its family of proprietary softwares,
i.e., the iOS operating system in-built with Safari, Maps, Photos, iMessage, FaceTime and more.
Apple’s services go beyond these to leverage AI, ML, deep learning and neural networks to provide
you with the smart tech you didn’t even know you needed.
FaceID uses facial recognition patterns to generate a specific model for your face. This
way, it’s easier to identify your face so you can unlock or perform functions on your device.
Siri - Siri is built on large-scale machine learning algorithms that combine speech
recognition and natural language processing (NLP)
Apple watch - Detecting sleep patterns, Heartbeat, irregular
movements
Apple TV - Suggests content based on user preferences.
Smart HDR photo mode - like Automatic Emergency Braking, Front
Collision Warning, Side Collision Warning, Auto High Beams
SOPHIA -THE AI ROBOT
Social human like AI Capable of displaying
humanlike expressions
and interacting with
people.
robot developed by
Hong Kong based
company Hanson
Robotics
Designed for
World 1st robot
citizen & 1st robot
Innovation
research,
education, and
entertainment,
promote discussion
about AI ethics and
future of robotics
Ambassador for UN
Develpment
Programme
Health-Care
Detecting Skin Cancer
Recognise Depression
Reading CT scan
Drug development
This technology provides
the surgeon with a 10x
magnified, high-definition,
3D-image of the body’s
intricate anatomy.
Less Tissue damage
Minimal blood loss
Reduce risk of infection
Associated Risks
Unclear liability for
Action
Humans can be prosecuted for
their mistakes but in the case of
machines, it will be termed an
accident.
Threat to Jobs:
AI itself is a big threat to
traditional jobs.
Transparency is
not Ensured
Dangerous to
privacy
Many AI systems were
created using neural networks
that are less capable of
showing the intentions for its
decision making them less
transparent.
AI recognizes our personal
data, and it can be a threat to
our privacy and personal data
Future of AI and ML
Creating the Future
The Future of Neural technology Auto-ML- Facilitate end-to-end
01
02
03 model development
04 Health care and pharma
Quantum machine learning
Thank You

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IT presentation -AI and ML.pptx

  • 2.
  • 3. Artificial intelligence Artificial intelligence refers to systems or machines that mimic human intelligence to perform tasks and can iteratively improve themselves based on the information they collect. Examples Medical diagnosis Voice or Handwriting recognition Chatbox Computer Search Engines Self-driving Cars Automated Financial Assistant
  • 4. Components of AI Learning Reasoning Problem Solving Perception Language
  • 5.
  • 6. MACHINE LEARNING It is branch of artificial intelligence that enables computer to "self learn" from training data & improves over time, without being explicitly programmed Learning Predicts Ordinary system Machine Learning With AI Improves
  • 7. Techniques in M L Supervised Learning Reinforcement Learning This type of machine learning comprises three major In this type labeled data is used for the training data. Supervised learning technique helps us to predict future events with the help of past experience components: the agent, the environment, and the actions. Unsupervised Learning A machine is trained with some input samples, while output is not known. Thus machine may not always provide correct output
  • 8. How AI & ML are Integrated Data mapping powered by AI can automate data transformation mapping by providing advanced features and agile data mapping predictions with machine learning algorithms. 01 02 The autonomous learning capability of AI and machine learning enable enterprises to learn more about hidden patterns and trends from large datasets, so that accurate business intelligence and insights are derived from them through applying statistical models. Data processing with machine learning-powered data integration tools can parse big data generating precise data models that require less human intervention 03
  • 9. Tesla cars come standard with advanced hardware capable of providing Autopilot features, and full self-driving capabilities—through software updates designed to improve functionality over time Tesla's Autopilot AI enables your car to steer, accelerate and brake. Navigate on Autopilot - All you will need to do is get in and tell your car where to go. Don’t say anything, your car will look at your calendar and take you there as the assumed destination. Standard Safety Features like Automatic Emergency Braking, Front Collision Warning, Side Collision Warning, Auto High Beams Eight cameras and powerful vision processing provide 360 degrees of visibility at up to 250 meters of range. Each Tesla car has a powerful set of vision processing tools developed by Tesla. Built on a deep neural network, Tesla Vision deconstructs the car's environment at greater levels of reliability than those achievable with classical vision processing techniques
  • 10.
  • 11. Apple stands out compared to other tech companies, given its family of proprietary softwares, i.e., the iOS operating system in-built with Safari, Maps, Photos, iMessage, FaceTime and more. Apple’s services go beyond these to leverage AI, ML, deep learning and neural networks to provide you with the smart tech you didn’t even know you needed. FaceID uses facial recognition patterns to generate a specific model for your face. This way, it’s easier to identify your face so you can unlock or perform functions on your device. Siri - Siri is built on large-scale machine learning algorithms that combine speech recognition and natural language processing (NLP) Apple watch - Detecting sleep patterns, Heartbeat, irregular movements Apple TV - Suggests content based on user preferences. Smart HDR photo mode - like Automatic Emergency Braking, Front Collision Warning, Side Collision Warning, Auto High Beams
  • 12. SOPHIA -THE AI ROBOT Social human like AI Capable of displaying humanlike expressions and interacting with people. robot developed by Hong Kong based company Hanson Robotics Designed for World 1st robot citizen & 1st robot Innovation research, education, and entertainment, promote discussion about AI ethics and future of robotics Ambassador for UN Develpment Programme
  • 13. Health-Care Detecting Skin Cancer Recognise Depression Reading CT scan Drug development
  • 14. This technology provides the surgeon with a 10x magnified, high-definition, 3D-image of the body’s intricate anatomy. Less Tissue damage Minimal blood loss Reduce risk of infection
  • 15. Associated Risks Unclear liability for Action Humans can be prosecuted for their mistakes but in the case of machines, it will be termed an accident. Threat to Jobs: AI itself is a big threat to traditional jobs. Transparency is not Ensured Dangerous to privacy Many AI systems were created using neural networks that are less capable of showing the intentions for its decision making them less transparent. AI recognizes our personal data, and it can be a threat to our privacy and personal data
  • 16. Future of AI and ML Creating the Future The Future of Neural technology Auto-ML- Facilitate end-to-end 01 02 03 model development 04 Health care and pharma Quantum machine learning