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Practical Artificial Intelligence in the Cloud
Only a couple of years ago, artificial intelligence was a cliché, a sad remnant of 1950s-style futurism. Today it’s sexy again, and that far-off future of intelligent bots is just around the corner. Consider the latest trend, AI-as-a-Service (AIaaS). Software vendors such as Google, IBM, and Amazon are rolling out sophisticated cloud-based AI and machine-learning services for a growing market of developers and users in business and academia.
Through interviews with consumers and executives of AIaaS vendors, author Mike Barlow examines the primary driver of this new approach: AI is simply too big for any single device or system. But with AIaaS, developers can build applications that perform data collection and compression on devices, while advanced processes such as natural language processing and machine learning are performed in the cloud.
When will consumers feel the impact? Fairly soon, you may be dealing with customer-service bots that know the answers before you even ask a question.
Download this report and explore how:
- AI is now a distributed phenomenon, with information passed back and forth between local devices and remote systems
- AIaaS vendors already support a diverse menu of APIs for AI developers.
- AI apps and interfaces will be designed and engineered increasingly for non-technical users
- Companies will routinely incorporate AI capabilities into new products and services
Through interviews with consumers and executives of AIaaS vendors, author Mike Barlow examines the primary driver of this new approach: AI is simply too big for any single device or system. But with AIaaS, developers can build applications that perform data collection and compression on devices, while advanced processes such as natural language processing and machine learning are performed in the cloud.
When will consumers feel the impact? Fairly soon, you may be dealing with customer-service bots that know the answers before you even ask a question.
Download this report and explore how:
- AI is now a distributed phenomenon, with information passed back and forth between local devices and remote systems
- AIaaS vendors already support a diverse menu of APIs for AI developers.
- AI apps and interfaces will be designed and engineered increasingly for non-technical users
- Companies will routinely incorporate AI capabilities into new products and services
21 pages, ebook
Published October 19, 2016
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Displaying 1 - 1 of 1 review
June 7, 2020
Short summary on the democratization of AI accelerated by the cloud. Following points are also emphasized:
1. AI capabilities will be incorporated routinely into new products and services by the companies.
2. AI can improve customer satisfaction through well-trained models.
3. For the long-term, further discussions and evident regulations are going to be required on open questions as follows:
- How much AI needs to be embedded within device(e.g: driverless car)?
- How much can be entrusted to the cloud?
- Who will decide these (e.g: manufacturers, legislators, courts, consumers or all)? etc...
1. AI capabilities will be incorporated routinely into new products and services by the companies.
2. AI can improve customer satisfaction through well-trained models.
3. For the long-term, further discussions and evident regulations are going to be required on open questions as follows:
- How much AI needs to be embedded within device(e.g: driverless car)?
- How much can be entrusted to the cloud?
- Who will decide these (e.g: manufacturers, legislators, courts, consumers or all)? etc...
Displaying 1 - 1 of 1 review