siva kumar ram shankar (27 Ergebnisse)

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Hardcover. Zustand: new. Hardcover. A robust and engaging account of the single greatest threat faced by AI and ML systems In Not With A Bug, But With A Sticker: Attacks on Machine Learning Systems and What To Do About Them, a team of distinguished adversarial machine learning researchers deliver a riveting account of the most significant risk to currently deployed artificial intelligence systems: cybersecurity threats. The authors take you on a sweeping tour from inside secretive government organizations to academic workshops at ski chalets to Googles cafeteria recounting how major AI systems remain vulnerable to the exploits of bad actors of all stripes. Based on hundreds of interviews of academic researchers, policy makers, business leaders and national security experts, the authors compile the complex science of attacking AI systems with color and flourish and provide a front row seat to those who championed this change. Grounded in real world examples of previous attacks, you will learn how adversaries can upend the reliability of otherwise robust AI systems with straightforward exploits. The steeplechase to solve this problem has already begun: Nations and organizations are aware that securing AI systems brings forth an indomitable advantage: the prize is not just to keep AI systems safe but also the ability to disrupt the competitions AI systems. An essential and eye-opening resource for machine learning and software engineers, policy makers and business leaders involved with artificial intelligence, and academics studying topics including cybersecurity and computer science, Not With A Bug, But With A Sticker is a warningalbeit an entertaining and engaging onewe should all heed. How we secure our AI systems will define the next decade. The stakes have never been higher, and public attention and debate on the issue has never been scarcer. The authors are donating the proceeds from this book to two charities: Black in AI and Bountiful Childrens Foundation. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Hardback. Zustand: New. A robust and engaging account of the single greatest threat faced by AI and ML systems In Not With A Bug, But With A Sticker: Attacks on Machine Learning Systems and What To Do About Them, a team of distinguished adversarial machine learning researchers deliver a riveting account of the most significant risk to currently deployed artificial intelligence systems: cybersecurity threats. The authors take you on a sweeping tour - from inside secretive government organizations to academic workshops at ski chalets to Google's cafeteria - recounting how major AI systems remain vulnerable to the exploits of bad actors of all stripes. Based on hundreds of interviews of academic researchers, policy makers, business leaders and national security experts, the authors compile the complex science of attacking AI systems with color and flourish and provide a front row seat to those who championed this change. Grounded in real world examples of previous attacks, you will learn how adversaries can upend the reliability of otherwise robust AI systems with straightforward exploits. The steeplechase to solve this problem has already begun: Nations and organizations are aware that securing AI systems brings forth an indomitable advantage: the prize is not just to keep AI systems safe but also the ability to disrupt the competition's AI systems. An essential and eye-opening resource for machine learning and software engineers, policy makers and business leaders involved with artificial intelligence, and academics studying topics including cybersecurity and computer science, Not With A Bug, But With A Sticker is a warning-albeit an entertaining and engaging one-we should all heed. How we secure our AI systems will define the next decade. The stakes have never been higher, and public attention and debate on the issue has never been scarcer. The authors are donating the proceeds from this book to two charities: Black in AI and Bountiful Children's Foundation.

Hardback. Zustand: New. A robust and engaging account of the single greatest threat faced by AI and ML systems In Not With A Bug, But With A Sticker: Attacks on Machine Learning Systems and What To Do About Them, a team of distinguished adversarial machine learning researchers deliver a riveting account of the most significant risk to currently deployed artificial intelligence systems: cybersecurity threats. The authors take you on a sweeping tour - from inside secretive government organizations to academic workshops at ski chalets to Google's cafeteria - recounting how major AI systems remain vulnerable to the exploits of bad actors of all stripes. Based on hundreds of interviews of academic researchers, policy makers, business leaders and national security experts, the authors compile the complex science of attacking AI systems with color and flourish and provide a front row seat to those who championed this change. Grounded in real world examples of previous attacks, you will learn how adversaries can upend the reliability of otherwise robust AI systems with straightforward exploits. The steeplechase to solve this problem has already begun: Nations and organizations are aware that securing AI systems brings forth an indomitable advantage: the prize is not just to keep AI systems safe but also the ability to disrupt the competition's AI systems. An essential and eye-opening resource for machine learning and software engineers, policy makers and business leaders involved with artificial intelligence, and academics studying topics including cybersecurity and computer science, Not With A Bug, But With A Sticker is a warning-albeit an entertaining and engaging one-we should all heed. How we secure our AI systems will define the next decade. The stakes have never been higher, and public attention and debate on the issue has never been scarcer. The authors are donating the proceeds from this book to two charities: Black in AI and Bountiful Children's Foundation.

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Hardcover. Zustand: new. Hardcover. A robust and engaging account of the single greatest threat faced by AI and ML systems In Not With A Bug, But With A Sticker: Attacks on Machine Learning Systems and What To Do About Them, a team of distinguished adversarial machine learning researchers deliver a riveting account of the most significant risk to currently deployed artificial intelligence systems: cybersecurity threats. The authors take you on a sweeping tour from inside secretive government organizations to academic workshops at ski chalets to Googles cafeteria recounting how major AI systems remain vulnerable to the exploits of bad actors of all stripes. Based on hundreds of interviews of academic researchers, policy makers, business leaders and national security experts, the authors compile the complex science of attacking AI systems with color and flourish and provide a front row seat to those who championed this change. Grounded in real world examples of previous attacks, you will learn how adversaries can upend the reliability of otherwise robust AI systems with straightforward exploits. The steeplechase to solve this problem has already begun: Nations and organizations are aware that securing AI systems brings forth an indomitable advantage: the prize is not just to keep AI systems safe but also the ability to disrupt the competitions AI systems. An essential and eye-opening resource for machine learning and software engineers, policy makers and business leaders involved with artificial intelligence, and academics studying topics including cybersecurity and computer science, Not With A Bug, But With A Sticker is a warningalbeit an entertaining and engaging onewe should all heed. How we secure our AI systems will define the next decade. The stakes have never been higher, and public attention and debate on the issue has never been scarcer. The authors are donating the proceeds from this book to two charities: Black in AI and Bountiful Childrens Foundation. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

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Hardback. Zustand: New. A robust and engaging account of the single greatest threat faced by AI and ML systems In Not With A Bug, But With A Sticker: Attacks on Machine Learning Systems and What To Do About Them, a team of distinguished adversarial machine learning researchers deliver a riveting account of the most significant risk to currently deployed artificial intelligence systems: cybersecurity threats. The authors take you on a sweeping tour - from inside secretive government organizations to academic workshops at ski chalets to Google's cafeteria - recounting how major AI systems remain vulnerable to the exploits of bad actors of all stripes. Based on hundreds of interviews of academic researchers, policy makers, business leaders and national security experts, the authors compile the complex science of attacking AI systems with color and flourish and provide a front row seat to those who championed this change. Grounded in real world examples of previous attacks, you will learn how adversaries can upend the reliability of otherwise robust AI systems with straightforward exploits. The steeplechase to solve this problem has already begun: Nations and organizations are aware that securing AI systems brings forth an indomitable advantage: the prize is not just to keep AI systems safe but also the ability to disrupt the competition's AI systems. An essential and eye-opening resource for machine learning and software engineers, policy makers and business leaders involved with artificial intelligence, and academics studying topics including cybersecurity and computer science, Not With A Bug, But With A Sticker is a warning-albeit an entertaining and engaging one-we should all heed. How we secure our AI systems will define the next decade. The stakes have never been higher, and public attention and debate on the issue has never been scarcer. The authors are donating the proceeds from this book to two charities: Black in AI and Bountiful Children's Foundation.

Hardcover. Zustand: new. Hardcover. A robust and engaging account of the single greatest threat faced by AI and ML systems In Not With A Bug, But With A Sticker: Attacks on Machine Learning Systems and What To Do About Them, a team of distinguished adversarial machine learning researchers deliver a riveting account of the most significant risk to currently deployed artificial intelligence systems: cybersecurity threats. The authors take you on a sweeping tour from inside secretive government organizations to academic workshops at ski chalets to Googles cafeteria recounting how major AI systems remain vulnerable to the exploits of bad actors of all stripes. Based on hundreds of interviews of academic researchers, policy makers, business leaders and national security experts, the authors compile the complex science of attacking AI systems with color and flourish and provide a front row seat to those who championed this change. Grounded in real world examples of previous attacks, you will learn how adversaries can upend the reliability of otherwise robust AI systems with straightforward exploits. The steeplechase to solve this problem has already begun: Nations and organizations are aware that securing AI systems brings forth an indomitable advantage: the prize is not just to keep AI systems safe but also the ability to disrupt the competitions AI systems. An essential and eye-opening resource for machine learning and software engineers, policy makers and business leaders involved with artificial intelligence, and academics studying topics including cybersecurity and computer science, Not With A Bug, But With A Sticker is a warningalbeit an entertaining and engaging onewe should all heed. How we secure our AI systems will define the next decade. The stakes have never been higher, and public attention and debate on the issue has never been scarcer. The authors are donating the proceeds from this book to two charities: Black in AI and Bountiful Childrens Foundation. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Zustand: New. As we enter an era of unprecedented growth of the capacity and power of machine learning and large AI platforms, the new benefits offered by such systems will be met with a corresponding expansion of the surface area for potential risks. NOT WITH A BUG, BU.

Buch. Zustand: Neu. Neuware - A robust and engaging account of the single greatest threat faced by AI and ML systemsIn Not With A Bug, But With A Sticker: Attacks on Machine Learning Systems and What To Do About Them, a team of distinguished adversarial machine learning researchers deliver a riveting account of the most significant risk to currently deployed artificial intelligence systems: cybersecurity threats. The authors take you on a sweeping tour - from inside secretive government organizations to academic workshops at ski chalets to Google's cafeteria - recounting how major AI systems remain vulnerable to the exploits of bad actors of all stripes.Based on hundreds of interviews of academic researchers, policy makers, business leaders and national security experts, the authors compile the complex science of attacking AI systems with color and flourish and provide a front row seat to those who championed this change. Grounded in real world examples of previous attacks, you will learn how adversaries can upend the reliability of otherwise robust AI systems with straightforward exploits.The steeplechase to solve this problem has already begun: Nations and organizations are aware that securing AI systems brings forth an indomitable advantage: the prize is not just to keep AI systems safe but also the ability to disrupt the competition's AI systems.An essential and eye-opening resource for machine learning and software engineers, policy makers and business leaders involved with artificial intelligence, and academics studying topics including cybersecurity and computer science, Not With A Bug, But With A Sticker is a warning--albeit an entertaining and engaging one--we should all heed.How we secure our AI systems will define the next decade. The stakes have never been higher, and public attention and debate on the issue has never been scarcer.The authors are donating the proceeds from this book to two charities: Black in AI and Bountiful Children's Foundation.

Hardback. Zustand: New. A robust and engaging account of the single greatest threat faced by AI and ML systems In Not With A Bug, But With A Sticker: Attacks on Machine Learning Systems and What To Do About Them, a team of distinguished adversarial machine learning researchers deliver a riveting account of the most significant risk to currently deployed artificial intelligence systems: cybersecurity threats. The authors take you on a sweeping tour - from inside secretive government organizations to academic workshops at ski chalets to Google's cafeteria - recounting how major AI systems remain vulnerable to the exploits of bad actors of all stripes. Based on hundreds of interviews of academic researchers, policy makers, business leaders and national security experts, the authors compile the complex science of attacking AI systems with color and flourish and provide a front row seat to those who championed this change. Grounded in real world examples of previous attacks, you will learn how adversaries can upend the reliability of otherwise robust AI systems with straightforward exploits. The steeplechase to solve this problem has already begun: Nations and organizations are aware that securing AI systems brings forth an indomitable advantage: the prize is not just to keep AI systems safe but also the ability to disrupt the competition's AI systems. An essential and eye-opening resource for machine learning and software engineers, policy makers and business leaders involved with artificial intelligence, and academics studying topics including cybersecurity and computer science, Not With A Bug, But With A Sticker is a warning-albeit an entertaining and engaging one-we should all heed. How we secure our AI systems will define the next decade. The stakes have never been higher, and public attention and debate on the issue has never been scarcer. The authors are donating the proceeds from this book to two charities: Black in AI and Bountiful Children's Foundation.

Buch. Zustand: Neu. Not with a Bug, But with a Sticker | Attacks on Machine Learning Systems and What to Do about Them | Ram Shankar Siva Kumar (u. a.) | Buch | 224 S. | Englisch | 2023 | Wiley | EAN 9781119883982 | Verantwortliche Person für die EU: Wiley-VCH GmbH, Boschstr. 12, 69469 Weinheim, product-safety[at]wiley[dot]com | Anbieter: preigu.