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Intel® IoT Developer Kit v1.0: Learn from the IoT Libraries and Code Samples from Intel



Are you a developer who was part of our previous Student, Academic or Open Source Developer Tools program and wish to extend your existing license? If so, please email your serial number and contact information to software_tools_request@intel.com to request a license.




Intel® IoT Developer Kit v1.0 is here | Intel® Developer Zone




Computer Vision is a fast-growing technology being deployed in nearly every industry from factory floors to amusement parks to shopping malls, smart buildings, and smart homes. It is also driving the evolution of machine learning and human interactions with intelligent systems. Additional applications include drones, security cameras, robots, facial recognition on cell phones, self-driving vehicles, and more, which means these industries and more all need developers with computer vision and deep learning IoT experience.


The Enterprise Ethereum Alliance* (EEA*) announced the EEA Trusted Compute Specification v1.0 at Consensus 2019, the annual gathering of the blockchain technology world. Software developers can use the Trusted Compute Spec to extend the benefits of blockchain computational trust to off-chain assets such as data, sensors, and compute capacity. By doing so, a developer can enhance the privacy and scalability of their blockchain solutions.


However, the notion of computational trust creates privacy and scalability tradeoffs for blockchain developers. Transaction validation can be a time-consuming process, and it can become slower and require more compute power as a network grows. That is one of the reasons why Bitcoin and Ethereum operate at 3-15 transactions per second, while Visa can operate at over 24,000 transactions per second2.


A workload running off-chain in Intel SGX also can cryptographically sign the data output and return that data to the blockchain. The use of a TEE like Intel SGX can help a developer ensure that the desired off-chain workload has executed to completion by an intended workload processor, and the TEE can help validate the results of the execution, thereby helping to extend computational trust from on-chain to off-chain. 2ff7e9595c


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