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Augmented reality examples: 9 ways companies are putting AR to work

AR meets real worldImage by Getty Images
When your team works in the belly of an aircraft or inside a computer design, they all having the same sci-fi daydream: Augmented reality (AR) that can layer information onto the job to cut out their frustration and inevitable errors. Being able to walk through a design in three-dimensional space can make it easier to identify flaws that are hard to see in two dimensions. And looking at a schematic of the thing you are trying to fix, while you are working on it, could eliminate hours of frustrating back and forth with drawings and keyboards.
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U.S. Treasury: Regulators should back off FinTech, allow innovation

The Treasury Department recently released a report urging state and federal regulators to revamp outdated statutes and support technological innovations such as AI, machine learning and blockchain that could make the U.S. financial system more nimble and competitive.
The 222-page report, commissioned by the Trump Administration 18 months ago, focused on non-bank financial services firms, such as credit lending, servicing organizations and payments networks, as well as fintech companies – tech vendors focused on innovation.
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U.S. Treasury: Regulators should back off FinTech, allow innovation

The Treasury Department recently released a report urging state and federal regulators to revamp outdated statutes and support technological innovations such as AI, machine learning and blockchain that could make the U.S. financial system more nimble and competitive.
The 222-page report, commissioned by the Trump Administration 18 months ago, focused on non-bank financial services firms, such as credit lending, servicing organizations and payments networks, as well as fintech companies – tech vendors focused on innovation.
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Oracle offers GraphPipe spec for machine learning data transmission

Oracle has developed an open source specification for transmitting tensor data, which the company wants to become a standard for machine learning.
Called GraphPipe, the specification provides a protocol for network data transmission. GraphPipe is intended to bring the efficiency of a binary, memory-mapped format while being simple and light on dependencies. There also are clients and servers for deploying and querying machine learning models from any framework.
It includes:
A set of flatbuffer definitions. Flatbuffers are similar to Google protocol buffers, with an additional benefit of avoiding memory copy during deserialization. Flatbuffer definitions provide a request message that includes input, tensors, input names, and output names. Guidelines for serving models. Examples of serving models from various machine learning frameworks. Client libraries for querying models served through GraphPipe. Clients are available for Python, Go, and Java. There’s a plugin for Google’s TensorFlo..

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Oracle offers GraphPipe spec for machine learning data transmission

Oracle has developed an open source specification for transmitting tensor data, which the company wants to become a standard for machine learning.
Called GraphPipe, the specification provides a protocol for network data transmission. GraphPipe is intended to bring the efficiency of a binary, memory-mapped format while being simple and light on dependencies. There also are clients and servers for deploying and querying machine learning models from any framework.
It includes:
A set of flatbuffer definitions. Flatbuffers are similar to Google protocol buffers, with an additional benefit of avoiding memory copy during deserialization. Flatbuffer definitions provide a request message that includes input, tensors, input names, and output names. Guidelines for serving models. Examples of serving models from various machine learning frameworks. Client libraries for querying models served through GraphPipe. Clients are available for Python, Go, and Java. There’s a plugin for Google’s TensorFlo..

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Patch Tuesday fallout: Bad docs, but so far no major problems

Microsoft may have fixed July’s horrible, no good, very bad patches. Although the initial documentation for this month’s patches included warnings about many of the bugs that persisted from July, it ends up that the docs were wrong, and most of the known problems seem to be fixed.
As of early Reboot Wednesday morning, the patches seem to be behaving themselves. Of course, it frequently takes days or even weeks for bugs to appear, so you’d be well advised to avoid jumping into the unpaid battle zone for now.
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