Articles liés à Microprediction: Building an Open AI Network
Synopsis
How a web-scale network of autonomous micromanagers can challenge the AI revolution and combat the high cost of quantitative business optimization.
The artificial intelligence (AI) revolution is leaving behind small businesses and organizations that cannot afford in-house teams of data scientists. In Microprediction, Peter Cotton examines the repeated quantitative tasks that drive business optimization from the perspectives of economics, statistics, decision making under uncertainty, and privacy concerns. He asks what things currently described as AI are not “microprediction,” whether microprediction is an individual or collective activity, and how we can produce and distribute high-quality microprediction at low cost. The world is missing a public utility, he concludes, while companies are missing an important strategic approach that would enable them to benefit—and also give back.
In an engaging, colloquial style, Cotton argues that market-inspired “superminds” are likely to be very effective compared with other orchestration mechanisms in the domain of microprediction. He presents an ambitious yet practical alternative to the expensive “artisan” data science that currently drains money from firms. Challenging the machine learning revolution and exposing a contradiction at its heart, he offers engineers a new liberty: no longer reliant on quantitative experts, they are free to create intelligent applications using general-purpose application programming interfaces (APIs) and libraries. He describes work underway to encourage this approach, one that he says might someday prove to be as valuable to businesses—and society at large—as the internet.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l'auteur
Peter Cotton is a Senior Vice President and Chief Data Scientist at Intech Investment Management LLC.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Microprediction: Building an Open AI Network
Edité par
MIT Press Ltd, 2022
ISBN 10 : 0262047322
ISBN 13 : 9780262047326
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Hardback. Etat : Good. How a web-scale network of autonomous micromanagers can challenge the AI revolution and combat the high cost of quantitative business optimization. The artificial intelligence (AI) revolution is leaving behind small businesses and organizations that cannot afford in-house teams of data scientists. In Microprediction, Peter Cotton examines the repeated quantitative tasks that drive business optimization from the perspectives of economics, statistics, decision making under uncertainty, and privacy concerns. He asks what things currently described as AI are not "microprediction," whether microprediction is an individual or collective activity, and how we can produce and distribute high-quality microprediction at low cost. The world is missing a public utility, he concludes, while companies are missing an important strategic approach that would enable them to benefit-and also give back. In an engaging, colloquial style, Cotton argues that market-inspired "superminds" are likely to be very effective compared with other orchestration mechanisms in the domain of microprediction. He presents an ambitious yet practical alternative to the expensive "artisan" data science that currently drains money from firms. Challenging the machine learning revolution and exposing a contradiction at its heart, he offers engineers a new liberty: no longer reliant on quantitative experts, they are free to create intelligent applications using general-purpose application programming interfaces (APIs) and libraries. He describes work underway to encourage this approach, one that he says might someday prove to be as valuable to businesses-and society at large-as the internet. N° de réf. du vendeur CIN0262047322G
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Microprediction: Building an Open AI Network
Edité par
MIT Press Ltd, 2022
ISBN 10 : 0262047322
ISBN 13 : 9780262047326
Ancien ou d'occasion
Couverture rigide
Vendeur : World of Books Inc, Montgomery, IL, Etats-Unis
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Hardback. Etat : Good. How a web-scale network of autonomous micromanagers can challenge the AI revolution and combat the high cost of quantitative business optimization. The artificial intelligence (AI) revolution is leaving behind small businesses and organizations that cannot afford in-house teams of data scientists. In Microprediction, Peter Cotton examines the repeated quantitative tasks that drive business optimization from the perspectives of economics, statistics, decision making under uncertainty, and privacy concerns. He asks what things currently described as AI are not "microprediction," whether microprediction is an individual or collective activity, and how we can produce and distribute high-quality microprediction at low cost. The world is missing a public utility, he concludes, while companies are missing an important strategic approach that would enable them to benefit-and also give back. In an engaging, colloquial style, Cotton argues that market-inspired "superminds" are likely to be very effective compared with other orchestration mechanisms in the domain of microprediction. He presents an ambitious yet practical alternative to the expensive "artisan" data science that currently drains money from firms. Challenging the machine learning revolution and exposing a contradiction at its heart, he offers engineers a new liberty: no longer reliant on quantitative experts, they are free to create intelligent applications using general-purpose application programming interfaces (APIs) and libraries. He describes work underway to encourage this approach, one that he says might someday prove to be as valuable to businesses-and society at large-as the internet. N° de réf. du vendeur CIN0262047322G
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Microprediction: Building an Open AI Network
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Microprediction: Building an Open AI Network
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Microprediction: Building an Open AI Network
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The MIT Press, 2022
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ISBN 13 : 9780262047326
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Couverture rigide
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