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Why there are no shortcuts to machine learning

Big data remains a game for the 1 percent. Or the 15 percent, as new O’Reilly survey data suggests. According to the survey, most enterprises (85 percent) still haven’t cracked the code on AI and machine learning. A mere 15 percent “sophisticated” enterprises have been running models in production for more than five years. Importantly, these same companies tend to give more time and attention to critical areas like model bias and data privacy, whereas comparative newbies are still trying to find the On button.
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(Insider Story)

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Introducing the Kubernetes Operator for TiDB

Shuan Deng and Greg Weber are cloud product engineers at PingCAP.
The rise of Kubernetes has significantly simplified the deployment and operation of cloud-native applications. An important part of that experience is the ease of running a cloud-native distributed database like TiDB. TiDB is an open-source, MySQL-compatible “NewSQL” database that supports hybrid transactional and analytical processing (HTAP).
In this tutorial, we’ll discuss how to use the TiDB Operator, a new open-source project by PingCAP to leverage Kubernetes to deploy the entire TiDB Platform and all of its components. The TiDB Operator allows you to monitor a TiDB deployment in a Kubernetes cluster and provides a gateway to administrative duties.
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Hack mobile point-of-sale systems? Researchers count the ways

Ever since the infamous and massive security breach at retailer Target nearly five years ago, more and more attention has focused on the potential flaws that can make payment systems vulnerable to digital attack.
And now, with payments increasingly shifting to mobile platforms, it appears that the potential for hacking the mobile point-of-sale (mPOS) systems that make it possible for merchants to accept card and even cryptocurrency payments on-the-go is also shifting.
[ Keep up with 8 hot cyber security trends (and 4 going cold). Give your career a boost with top security certifications: Who they're for, what they cost, and which you need. | Sign up for CSO newsletters. ] Presenting at the Black Hat USA information security conference last week in Las Vegas, prominent U.K. security researchers showcased recent research detailing the inherent vulnerabilities they discovered among four of the most popular mPOS systems operating in both the United States and Europe. In what is believ..

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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.
To read this article in full, please click here

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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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