Artificial intelligence overview
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Artificial Intelligence is a way of making a computer, a computer-controlled robot, or a software think intelligently, in the similar manner the intelligent humans think.
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YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
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Autonomy in targeting is a function that could be applied to any intelligent system, in particular the rapidly expanding array of robotic systems, in the air, on land and at sea – including swarms of small robots. This is an area of significant investment and emphasis for many armed forces, and the question is not so much whether we will see more intelligent robots, but whether and by what means they will remain under human control. Today’s remote-controlled weapons could become tomorrow’s autonomous weapons with just a software upgrade. The central element of any future autonomous weapon system will be the software. Military powers are investing in AI for a wide range of applications10 and significant efforts are already underway to harness developments in image, facial and behavior recognition using AI and machine learning techniques for intelligence gathering and “automatic target recognition” to identify people, objects or patterns. Although not all autonomous weapon systems incorporate AI and machine learning, this software could form the basis of future autonomous weapon systems.Deep learning
This document discusses artificial intelligence, machine learning, deep learning, and data science. It defines each term and explains the relationships between them. AI is the overarching field, while machine learning and deep learning are subsets of AI. Machine learning allows machines to improve performance over time without human intervention by learning from examples, and deep learning uses artificial neural networks with many layers to closely mimic the human brain. The document provides an example of a fruit detection system using deep learning that trains a neural network to detect ripe fruit for automated harvesting.
Artificial intelligence
Artificial Intelligence
The document provides an overview of artificial intelligence, including its definition, history, current status, future possibilities, and challenges. It defines AI as the study of computer systems that attempt to model human intelligence. The history notes Alan Turing's seminal work in the 1950s and the founding of AI at the 1955 Dartmouth workshop by John McCarthy. Currently, AI is used in applications like mobile phones, games, GPS, robotics, and more. The future may include AI assisting in education, media, customer service, transportation, manufacturing, and healthcare. However, challenges remain around issues like data bias, storage needs, and unemployment.
Correlation does not mean causation
This document discusses how data and machine learning systems work, and some of their limitations. It makes three key points:
1. Machine learning systems are only as good as the data used to train them, and all data has some inherent bias which can negatively impact results if not addressed.
2. While large datasets and machine learning are powerful, humans still need to provide oversight to catch errors, prevent harm, and ensure systems don't behave in unexpected ways.
3. Thorough testing of systems with diverse datasets is needed to identify and address biases, anticipate problems, and ensure models are robust and represent their intended domains.
Automated Machine Learning
The document discusses automated machine learning (AutoML). It defines AutoML as providing methods to make machine learning more efficient and accessible to non-machine learning experts. AutoML aims to automate tasks like data preprocessing, feature engineering, algorithm selection and hyperparameter optimization. This can reduce costs, increase productivity for data scientists and democratize machine learning. The document also lists several AutoML tools that provide hyperparameter tuning, full pipeline optimization or neural architecture search.
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Testing machine learning, learning machine testing. EuroSTAR 2016 Rik Marselis
At the EuroSTAR conference 2016 in Stockholm I presented about the testing of artificial intelligence and machine learning. But also about testing using intelligent machines.
thetoptrendsinartificialintelligence-191016075410.pptx
The document discusses the top trends in artificial intelligence, including machine and deep learning, computer vision, cloud computing, internet of things at the edge, and automated machine learning. It provides details on each trend, noting that machine learning relies on exposure to data to get smarter, computer vision enables computers to see and understand visual information, the cloud is necessary for processing large amounts of AI data, internet of things processes data at the edge with limited bandwidth, and automated machine learning automates the machine learning process end-to-end.
The Top Trends in Artificial Intelligence
AI and its applications are not going away and will cause a significant amount of change to everyday life over the next decade. Whilst there has been a lot of buzz in the past that has not been fulfilled, advances in skills, computing power and modelling and ensuring that the hype is finally being realised. To some extent, we don’t even know what AI is capable of yet which is both exciting and scary!
Types of artificial intelligence
The document discusses different types of artificial intelligence including narrow AI, general AI, and super AI. It provides examples of narrow AI systems like Siri, Watson, self-driving cars, and algorithms for tasks like chess-playing or image recognition. General AI aims to achieve human-level intelligence across all domains but currently does not exist. Super AI could potentially surpass human abilities but is still hypothetical. The document also covers reactive systems, limited memory systems, and potential future developments in theory of mind and self-aware AI.
Artificial intelligence- The science of intelligent programs
Artificial intelligence (AI) involves creating intelligent computer programs and machines that can interact with the real world similarly to humans. AI uses techniques like machine learning, deep learning, and neural networks to allow programs to learn from data and experience without being explicitly programmed. While AI has potential benefits, some experts warn that advanced AI could pose risks if not developed carefully due to concerns it could become difficult for humans to control once a certain level of intelligence is achieved.
Automated mobility and more lv lions - 29 dec16
1. The document discusses how artificial intelligence and deep learning will be key technologies enabling automated vehicles. Deep learning may lead to a winner-take-all market where the first company to solve challenges like interpreting ambiguous situations takes the entire market.
2. As mobility shifts to a shared, on-demand model enabled by self-driving cars, the traditional auto industry will likely decline steeply within 10 years. New network models of collaboration between companies may replace traditional internal research and development approaches.
3. Mobility will be delivered increasingly as a service through ride-sharing and fewer privately-owned vehicles, which will require only 20-30% of the current vehicle fleet in urban areas.
Reinforcement Learning In AI Powerpoint Presentation Slide Templates Complete...
Showcase how machines are built to perform intelligent tasks by using our content-ready Reinforcement Learning In AI PowerPoint Presentation Slide Templates Complete Deck. Take advantage of these artificial intelligence PowerPoint visuals, and describe how machine learning models are trained to make sequences of decisions in a complex environment. Showcase the types of artificial intelligence such as deep learning, machine learning. Explain the concept of machine learning which delivers predictive models based on the data fed into machine learning algorithms. Take the assistance of our visually attention-grabbing reinforcement learning PowerPoint templates and discuss the effective uses of artificial intelligence in various areas such as supply chain, human resources, fraud detection, knowledge creation, research, and development, etc. You can also present the usage of AI in healthcare. This includes treatment, diagnosis, training and research, early detection, etc. Explain the working of machine learning by downloading our attention-grabbing supervised learning PowerPoint presentation. https://bit.ly/3kQBnEZ
Artificial Intelligence.pptx learn and practice
This document provides an overview of artificial intelligence (AI) and machine learning. It begins with definitions of AI and discusses how people commonly interact with AI systems like search engines and virtual assistants. It then describes the three phases of computing and the shift to the current AI computing era. The document outlines why AI is important for automation, decision making, personalization and other applications. It also discusses the main types of AI as strong/narrow AI and weak/general AI. The relationship between AI, machine learning, and deep learning is explained. The document concludes with introductions to machine learning and its key concepts like data, features, labels and common Python libraries. It also covers the main types of machine learning as supervised, unsupervised and
Introduction to Machine Learning
This document provides an introduction to machine learning. It discusses key machine learning concepts like supervised learning, unsupervised learning, reinforcement learning, batch learning, online learning, instance-based learning, and model-based learning. It also discusses applications of machine learning like spam filtering, clustering, and anomaly detection. Machine learning algorithms like artificial neural networks and deep learning are also introduced. The document aims to explain machine learning concepts and techniques in a clear and intuitive manner using examples.
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Artificial intelligence overview
- 2. • What is Artificial Intelligence (AI)? • Using computers to solve problems • Or make automated decisions • For tasks that, when done by humans, • Typically require intelligence Artificial Intelligence (AI)
- 3. • Computers thinking at a level that meets or surpasses people • Computers engaging in abstract reasoning & thinking • This is not what we have today • There is no evidence that we are close to Strong AI “Strong” Artificial Intelligence
- 4. • Computers solve problems by detecting useful patterns • Pattern-based AI is an Extremely powerful tool • Has been used to automate many processes today • Driving, language translation • This is the dominant mode of AI today “Weak” Pattern-Based Artificial Intelligence
- 5. • Logic and Rules-Based Approach • Machine Learning (Pattern-Based Approach) Two Major AI Techniques
- 6. • Representing processes or systems using logical rules • Top-down rules are created for computer • Computers reason about those rules • Can be used to automate processes Logic and Rules-Based Approach
- 7. • Algorithms find patterns in data and infer rules on their own • ”Learn” from data and improve over time • These patterns can be used for automation or prediction • ML is the dominant mode of AI today Machine Learning (ML)
- 8. • Self-Driving Vehicles • Automated recommendations • Computer Translation Machine Learning Uses
- 9. • Many successful AI systems are hybrids of • Machine learning & Rules-Based Hybrids • e.g. Self-driving cars employ both approaches Hybrid Systems
- 10. • Also, many successful AI systems work best when • They work with human intelligence • AI systems supply information for humans Human intelligence + AI Hybrids
- 11. • Artificial Intelligence Accomplishments • Automate many things that couldn’t do before Limits on Artificial Intelligence
- 12. • Many things still beyond the realm of AI • No thinking computers • No Abstract Reasoning • Often AI systems Have Accuracy Limits • Many things difficult to capture in data • Sometimes Hard to interpret Systems Limits
- 13. Kindly Visit us at www.auquall.com FOR MORE INFORMATION