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This document discusses artificial intelligence and provides information on what AI is, how it compares to robotics, examples of AI technologies, and some controversies surrounding AI. It defines AI as the power of a machine to copy and learn from intelligent human behavior. It describes the Turing Test, which involves conversations between a human and computer to determine if the computer can demonstrate human-level intelligence. The document also discusses how AI is advancing and will likely be integrated into many technologies people interact with on a daily basis in the future.
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Turing Test In Artificial Intelligence
This presentation explores the Turing Test, introduced by Alan Turing in 1950, to assess a machine's ability to exhibit human-like intelligence. We discuss its historical significance, technological advancements, philosophical implications, and real-world applications, highlighting the ongoing pursuit of creating AI indistinguishable from humans.
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Turing Test In Artificial Intelligence
This presentation explores the Turing Test, introduced by Alan Turing in 1950, to assess a machine's ability to exhibit human-like intelligence. We discuss its historical significance, technological advancements, philosophical implications, and real-world applications, highlighting the ongoing pursuit of creating AI indistinguishable from humans.
rr_01_artificial_intelligence.pptx information
Artificial intelligence (AI) is a branch of computer science that deals with the creation of intelligent agents, which are systems that can reason, learn, and act autonomously. AI research has been highly successful in developing effective techniques for solving a wide range of problems, from game playing to medical diagnosis.
One of the most important advances in AI research has been the development of machine learning algorithms. Machine learning algorithms allow AI systems to learn from data, without being explicitly programmed. This has led to the development of AI systems that can perform tasks such as image recognition, natural language processing, and fraud detection.
AI is also being used to develop new applications in a wide range of fields, including healthcare, finance, and manufacturing. For example, AI is being used to develop new drugs and treatments, to automate financial trading, and to improve the efficiency of manufacturing processes.
As AI continues to develop, it is likely to have a profound impact on our lives. AI systems are already being used to automate many tasks that were previously performed by humans. In the future, AI systems are likely to become even more intelligent and capable, and they could play an even greater role in our lives.
Here are some of the specific ways that AI is being used today:
In healthcare, AI is being used to develop new drugs and treatments, to diagnose diseases, and to provide personalized care to patients.
In finance, AI is being used to automate financial trading, to detect fraud, and to manage risk.
In manufacturing, AI is being used to improve the efficiency of manufacturing processes, to predict demand for products, and to develop new products.
In transportation, AI is being used to develop self-driving cars, to optimize traffic flow, and to improve safety.
In customer service, AI is being used to develop chatbots that can answer customer questions and provide support.
In education, AI is being used to develop personalized learning programs, to provide feedback to students, and to automate administrative tasks.
These are just a few examples of the many ways that AI is being used today. As AI continues to develop, we can expect to see even more innovative and groundbreaking applications of this technology.
Here are some of the challenges that AI researchers are still working to address:
Safety:
AI systems need to be designed to be safe and reliable. This means that they need to be able to handle unexpected situations and to avoid making mistakes that could have serious consequences.
Bias:
AI systems can be biased, reflecting the biases of the data that they are trained on. This can lead to unfair or discriminatory outcomes. AI researchers are working to develop methods for mitigating bias in AI systems.
Explainability:
AI systems can be complex and difficult to understand. This can make it difficult to trust them and to hold them accountable for their decisions. AI researchers are working
AnswerTuring TestCoined by computing pioneer Alan Turing in .pdf
Answer:
Turing Test:
Coined by computing pioneer Alan Turing in 1950, the Turing test was designed to be a
rudimentary way of determining whether or not a computer counts as \"intelligent\".
The test, as Turing designed it, is carried out as a sort of imitation game. On one side of a
computer screen sits a human judge, whose job is to chat to some mysterious interlocutors on the
other side. Most of those interlocutors will be humans; one will be a chatbot, created for the sole
purpose of tricking the judge into thinking that it is the real human.
Turing Test Objections:
1.The Theological Objection:
Substance dualists believe that thinking is a function of a non-material, separately existing,
substance that somehow “combines” with the body to make a person. So the argument might go
making a body can never be sufficient to guarantee the presence of thought: in themselves,
digital computers are no different from any other merely material bodies in being utterly unable
to think. Moreover to introduce the “theological” element it might be further added that, where a
“soul” is suitably combined with a body, this is always the work of the divine creator of the
universe: it is entirely up to God whether or not a particular kind of body is imbued with a
thinking soul.
2.The ‘Heads in the Sand’ Objection:
If there were thinking machines, then various consequences would follow. First, we would lose
the best reasons that we have for thinking that we are superior to everything else in the universe
(since our cherished “reason” would no longer be something that we alone possess). Second, the
possibility that we might be “supplanted” by machines would become a genuine worry: if there
were thinking machines, then very likely there would be machines that could think much better
than we can. Third, the possibility that we might be “dominated” by machines would also
become a genuine worry: if there were thinking machines, who\'s to say that they would not take
over the universe, and either enslave or exterminate us.
3.Arguments from Various Disabilities:
Turing considers a list of things that some people have claimed machines will never be able to
do:
(1) be kind.
(2) be resourceful.
(3) be beautiful.
(4) be friendly.
(5) have initiative.
(6) have a sense of humor.
(7) tell right from wrong.
(8) make mistakes.
(9) fall in love.
(10) enjoy strawberries and cream.
(11) make someone fall in love with one.
(12) learn from experience.
(13) use words properly.
(14) be the subject of one\'s own thoughts.
(15) have as much diversity of behavior as a man; (16) do something really new.
4.Argument from Continuity of the Nervous System:
The human brain and nervous system is not much like a digital computer. In particular, there are
reasons for being skeptical of the claim that the brain is a discrete-state machine. Turing observes
that a small error in the information about the size of a nervous impulse impinging on a neuron
may make a large difference to the size of the o.
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rr_01_artificial_intelligence.pptx information
Artificial intelligence (AI) is a branch of computer science that deals with the creation of intelligent agents, which are systems that can reason, learn, and act autonomously. AI research has been highly successful in developing effective techniques for solving a wide range of problems, from game playing to medical diagnosis.
One of the most important advances in AI research has been the development of machine learning algorithms. Machine learning algorithms allow AI systems to learn from data, without being explicitly programmed. This has led to the development of AI systems that can perform tasks such as image recognition, natural language processing, and fraud detection.
AI is also being used to develop new applications in a wide range of fields, including healthcare, finance, and manufacturing. For example, AI is being used to develop new drugs and treatments, to automate financial trading, and to improve the efficiency of manufacturing processes.
As AI continues to develop, it is likely to have a profound impact on our lives. AI systems are already being used to automate many tasks that were previously performed by humans. In the future, AI systems are likely to become even more intelligent and capable, and they could play an even greater role in our lives.
Here are some of the specific ways that AI is being used today:
In healthcare, AI is being used to develop new drugs and treatments, to diagnose diseases, and to provide personalized care to patients.
In finance, AI is being used to automate financial trading, to detect fraud, and to manage risk.
In manufacturing, AI is being used to improve the efficiency of manufacturing processes, to predict demand for products, and to develop new products.
In transportation, AI is being used to develop self-driving cars, to optimize traffic flow, and to improve safety.
In customer service, AI is being used to develop chatbots that can answer customer questions and provide support.
In education, AI is being used to develop personalized learning programs, to provide feedback to students, and to automate administrative tasks.
These are just a few examples of the many ways that AI is being used today. As AI continues to develop, we can expect to see even more innovative and groundbreaking applications of this technology.
Here are some of the challenges that AI researchers are still working to address:
Safety:
AI systems need to be designed to be safe and reliable. This means that they need to be able to handle unexpected situations and to avoid making mistakes that could have serious consequences.
Bias:
AI systems can be biased, reflecting the biases of the data that they are trained on. This can lead to unfair or discriminatory outcomes. AI researchers are working to develop methods for mitigating bias in AI systems.
Explainability:
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AnswerTuring TestCoined by computing pioneer Alan Turing in .pdf
Answer:
Turing Test:
Coined by computing pioneer Alan Turing in 1950, the Turing test was designed to be a
rudimentary way of determining whether or not a computer counts as \"intelligent\".
The test, as Turing designed it, is carried out as a sort of imitation game. On one side of a
computer screen sits a human judge, whose job is to chat to some mysterious interlocutors on the
other side. Most of those interlocutors will be humans; one will be a chatbot, created for the sole
purpose of tricking the judge into thinking that it is the real human.
Turing Test Objections:
1.The Theological Objection:
Substance dualists believe that thinking is a function of a non-material, separately existing,
substance that somehow “combines” with the body to make a person. So the argument might go
making a body can never be sufficient to guarantee the presence of thought: in themselves,
digital computers are no different from any other merely material bodies in being utterly unable
to think. Moreover to introduce the “theological” element it might be further added that, where a
“soul” is suitably combined with a body, this is always the work of the divine creator of the
universe: it is entirely up to God whether or not a particular kind of body is imbued with a
thinking soul.
2.The ‘Heads in the Sand’ Objection:
If there were thinking machines, then various consequences would follow. First, we would lose
the best reasons that we have for thinking that we are superior to everything else in the universe
(since our cherished “reason” would no longer be something that we alone possess). Second, the
possibility that we might be “supplanted” by machines would become a genuine worry: if there
were thinking machines, then very likely there would be machines that could think much better
than we can. Third, the possibility that we might be “dominated” by machines would also
become a genuine worry: if there were thinking machines, who\'s to say that they would not take
over the universe, and either enslave or exterminate us.
3.Arguments from Various Disabilities:
Turing considers a list of things that some people have claimed machines will never be able to
do:
(1) be kind.
(2) be resourceful.
(3) be beautiful.
(4) be friendly.
(5) have initiative.
(6) have a sense of humor.
(7) tell right from wrong.
(8) make mistakes.
(9) fall in love.
(10) enjoy strawberries and cream.
(11) make someone fall in love with one.
(12) learn from experience.
(13) use words properly.
(14) be the subject of one\'s own thoughts.
(15) have as much diversity of behavior as a man; (16) do something really new.
4.Argument from Continuity of the Nervous System:
The human brain and nervous system is not much like a digital computer. In particular, there are
reasons for being skeptical of the claim that the brain is a discrete-state machine. Turing observes
that a small error in the information about the size of a nervous impulse impinging on a neuron
may make a large difference to the size of the o.
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See My Other Reviews Article:
(1) AI Genie Review: https://sumonreview.com/ai-genie-review
(2) SocioWave Review: https://sumonreview.com/sociowave-review
(3) AI Partner & Profit Review: https://sumonreview.com/ai-partner-profit-review
(4) AI Ebook Suite Review: https://sumonreview.com/ai-ebook-suite-review
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Zoom is a comprehensive platform designed to connect individuals and teams efficiently. With its user-friendly interface and powerful features, Zoom has become a go-to solution for virtual communication and collaboration. It offers a range of tools, including virtual meetings, team chat, VoIP phone systems, online whiteboards, and AI companions, to streamline workflows and enhance productivity.
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AI.PDF
- 1. Artificial Intelligence By Anna Fryling and Kayla Akombi
- 2. What is Artificial Intelligence? Answer: The power of a machine to copy intelligent human behavior. Right???
- 3. Robots at Artemis Are they really intelligent? A robot is only as smart as its initial program. Answer: The power of a machine to copy and learnfrom intelligent human behavior.
- 4. Artificial Intelligence VS. Robot AI Robot Programmed to think Programmed to do Social Interaction Low level interaction Learns Only as smart as program
- 5. Artificial Intelligence Tests Turing Test Developed by Alan Turing Involves an interpreter, a human, and a computer. The computer and human have separate conversations with the interpreter. If the interpreter can’t guess which is the computer or if the interpreter gets it wrong then the computer has Artificial Intelligence.
- 6. Artificial Intelligence Tests Involves two tests First test involves an interpreter, a male, and a female. Female pretends to be male Interpreter tries to figure out who is who Second test is similar to turing test Compares both tests Imitation Game
- 7. Artificial Intelligence Tests Turing Test Imitation Game Turing test the computer results to itself and not to humans Imitation game compares the robots results to human results
- 9. Problems Although AI is advancing it can still be problematic.
- 10. AI Controversies Growing laziness Robot Relationships? Growing Cost Potential job takeover Priority Argument
- 11. Why it Matters In the future AI is going to be everywhere. It is important to know about it and understand it. This is because we may be interacting with it on a day to day basis. We learned at Artemis about the different robots that use AI We also learned when robots need AI and when they don’t.
- 12. Thank You!!