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    <title>法人別リリース</title>
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        <title>LeapMind Inc. Announces &amp;quot;DeLTA-Lite,&amp;quot; Building Solution for Embedded Deep Learning Models ...</title>
        <link>https://kyodonewsprwire.jp/index.php/release/201807125959</link>
        <pubDate>Tue, 17 Jul 2018 15:00:00 +0900</pubDate>
                <dc:creator>LeapMind</dc:creator>
        <description>- Additional Service for FPGA and Quick Evaluation Available with &amp;quot;DE10-Nano&amp;quot; Board - LeapMind Inc.,...</description>
                <content:encoded><![CDATA[
TOKYO, July 17, 2018 /Kyodo JBN/ --&lt;br /&gt;


LeapMind Inc.&lt;br /&gt;


LeapMind Inc. Announces &quot;DeLTA-Lite,&quot; Building Solution&lt;br /&gt;
for Embedded Deep Learning Models without Programming,&lt;br /&gt;
to Officially Support &quot;Cyclone (R) V SoC&quot;&lt;br /&gt;


- Additional Service for FPGA and Quick Evaluation Available with &quot;DE10-Nano&quot; Board -&lt;br /&gt;
&lt;br /&gt;
LeapMind Inc., a leading deep learning solution provider for enterprises, announced on July 17 that &quot;DeLTA-Lite,&quot; a building solution for embedded deep learning models without programming, to officially support &quot;Cyclone (R) V SoC&quot; delivered by Intel Corporation of the United States. &quot;DeLTA-Lite&quot; started to provide an additional, FPGA-oriented service from July 2, 2018.&lt;br /&gt;
&lt;br /&gt;
The said FPGA is loaded in &quot;DeLTA-Kit,&quot; a hardware kit for easily evaluating deep learning released on June 27, 2018.&lt;br /&gt;
&lt;br /&gt;
(Image: &lt;a href=&quot;https://kyodonewsprwire.jp/img/201807125959-O1-5m81xYZ9&quot; target=&quot;_blank&quot; rel=&quot;nofollow&quot;&gt;https://kyodonewsprwire.jp/img/201807125959-O1-5m81xYZ9&lt;/a&gt;)&lt;br /&gt;
&lt;br /&gt;
At the release of &quot;DeLTA-Lite&quot; in April 2018, the scope of its support was for CPUs and FPGAs, but now expanded its scope to &quot;Cyclone (R) V SoC&quot; as well to reach out to more clients. LeapMind is planning to diversify hardware support for &quot;DeLTA-Lite&quot; in the future.&lt;br /&gt;
&lt;br /&gt;
The kit released in June will enhance usability of &quot;DeLTA-Lite&quot; by enabling an additional feature where it generates downloadable binary and configuration files after training deep learning models. Those outputs can be executed on FPGAs.&lt;br /&gt;
&lt;br /&gt;
About &quot;DeLTA-Lite&quot;&lt;br /&gt;
&quot;DeLTA-Lite&quot; is a cutting-edge solution to make it possible to build and deploy embedded deep learning models for practical use.&amp;nbsp;&amp;nbsp;Until now, introducing embedded deep learning has required highly specialized knowledge and skills both for model designing and hardware implementation. However, by using &quot;DeLTA-Lite,&quot; only a few steps are required to build embedded deep learning models. It also significantly reduces time and cost to deploy those models onto a small edge device, allowing the implementation of a detection function into a small machine or a robot, which otherwise could not be realized without them.&lt;br /&gt;
&lt;br /&gt;
DeLTA-Lite official website: &lt;a href=&quot;https://delta.leapmind.io/lite/en/&quot; target=&quot;_blank&quot; rel=&quot;nofollow&quot;&gt;https://delta.leapmind.io/lite/en/&lt;/a&gt;&lt;br /&gt;
&lt;br /&gt;
About LeapMind Technology&lt;br /&gt;
LeapMind provides one-stop solutions from model building and model compression to model implementation onto hardware so that deep learning technology can be enjoyed within a small computing environment where access to electricity is limited.&lt;br /&gt;
&lt;br /&gt;
(1) Unique Deep Learning Algorithm&lt;br /&gt;
LeapMind conducts research on its own innovative algorithms that can reduce the computational complexity of deep learning to use within a small computing environment such as FPGAs.&lt;br /&gt;
&lt;br /&gt;
(2) Optimal Hardware Architecture for Deep Learning&lt;br /&gt;
LeapMind also conducts research on original chip architectures that can efficiently implement deep neural networks on a circuit such as FPGAs with low power and limited memory.&lt;br /&gt;
&lt;br /&gt;
LeapMind is making continuous efforts to make deep learning “small and compact” and accessible across a broad spectrum of applications, evolving the Internet of Things into the “Deep Learning of Things (DoT).” &lt;br /&gt;
&lt;br /&gt;
About LeapMind&lt;br /&gt;
Head Office: Shibuya-ku, Tokyo&lt;br /&gt;
Representative: Soichi Matsuda, CEO&lt;br /&gt;
Established: December 2012&lt;br /&gt;
URL: &lt;a href=&quot;https://leapmind.io/en/&quot; target=&quot;_blank&quot; rel=&quot;nofollow&quot;&gt;https://leapmind.io/en/&lt;/a&gt;&lt;br /&gt;

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