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    What Is Artificial Intelligence Ai

    Revision as of 14:07, 29 March 2023 by 3.22.216.250 (talk) (Created page with "For example, Merantix is a German firm that applies deep learning to medical issues. It has an software in medical imaging that “detects lymph nodes in the human physique in...")
    (diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)

    For example, Merantix is a German firm that applies deep learning to medical issues. It has an software in medical imaging that “detects lymph nodes in the human physique in Computer Tomography images.”21 According to its builders, the key is labeling the nodes and identifying small lesions or growths that might be problematic. Humans can do this, however radiologists cost $100 per hour and could possibly rigorously read solely 4 pictures an hour.















    Example duties by which this is accomplished embody speech recognition, computer vision, translation between languages, as nicely as different mappings of inputs. No, synthetic intelligence and machine learning are not the same, however they are closely related. Machine studying is the tactic to coach a computer to be taught from its inputs however without express programming for each circumstance.

    What's Intelligence?



    It is important that these and different concerns be thought-about so we acquire the total benefits of this emerging expertise. For these reasons, both state and federal governments have been investing in AI human capital. In some sectors the place there's a discernible public benefit, governments can facilitate collaboration by building infrastructure that shares information. For example, the National Cancer Institute has pioneered a data-sharing protocol the place licensed researchers can question well being knowledge it has utilizing de-identified information drawn from medical data, claims information, and drug therapies. That allows researchers to evaluate efficacy and effectiveness, and make suggestions relating to the best medical approaches, without compromising the privateness of individual sufferers. In non-transportation areas, digital platforms typically have limited legal responsibility for what happens on their websites.



    AI 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" 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    These machines acquire earlier data and proceed including it to their reminiscence. They have sufficient memory or expertise to make proper choices, but reminiscence is minimal. For instance, this machine can suggest a restaurant based on the placement knowledge that has been gathered. As to creativity, it’s quite remarkable that the power we most reward in human minds is nowhere to be found in AIMA.

    Moral Machines



    See the separate entry on logic and synthetic intelligence, which is concentrated on nonmonotonic reasoning, and reasoning about time and alter. It additionally offers a history of the early days of logic-based AI, making clear the contributions of those who based the custom (e.g., John McCarthy and Pat Hayes; see their seminal 1969 paper). Despite potential risks, there are currently few laws governing the utilization of AI tools, and the place laws do exist, they typically pertain to AI indirectly. For example, as previously mentioned, United States Fair Lending rules require monetary establishments to elucidate credit choices to potential prospects.









    • All of that material has to be analyzed instantly to avoid crashes and keep the vehicle in the correct lane.








    • In order to balance innovation with primary human values, we suggest a variety of suggestions for moving ahead with AI.








    • And it might change the place and the way students be taught, maybe even replacing some lecturers.








    • The term is often used interchangeably with its subfields, which embody machine learning and deep studying.








    • This clever processing is vital to identifying and predicting rare occasions, understanding complicated systems and optimizing distinctive situations.










    Moral reasoning is obviously wanted in robots that have the capability for lethal action. Arkin supplies an introduction to how we will control and regulate machines that have the capability for lethal behavior. Moral AI goes past obviously lethal conditions, and we will have a spectrum of ethical machines. An instance of a non-lethal but ethically-charged machine can be a lying machine. Clark uses a computational principle of the mind, the ability to characterize and purpose about other brokers, to construct a mendacity machine that successfully persuades people into believing falsehoods.