Panasonic Press Releases

Panasonic Acquired Arimo Inc. for the Core Data Science Element to Continue Developing Further Sophisticated Artificial Intelligence-Based Solutions for the B2B Customers

The following video presents Democratizing Big Data: Riding the Curve from Descriptive to Prescriptive Intelligence:
Data scientists are a scarce resource. Yet we are told the modern data-driven business needs to embrace data science. To resolve this paradox, we need tools that leverage the data scientist, empower the business user, and democratize access to machine learning. In this talk, I will explore the possibilities of doing so through a combination of: 1.Natural User Interfaces 2. Collaborative Workflows 3. Accessible Machine Learning…

Tushar Shanbhag is the Vice President of Products at Arimo, the leader in Enterprise Big Apps….

The following video presents Christopher T. Nguyen, Arimo, Inc – Spark Summit 2016 – #SparkSummit #theCUBE:
01. Christopher T. Nguyen, Arimo, Visits #theCUBE!.(00:20)
02. What Are Your Thoughts Around The Enthusiasm At Spark.(00:58)
03. What Was It That You Saw That Made You Put All Your Chips On The Table With Spar.(02:06)
04. What Were The Announcements That You Made Here.(04:40)
05. What Is Intelligence Augmentation.(06:15)
06. What Is The Difference In Intelligence Augmentation And Artificial Intelligence.(09:23)
07. Who’s Using IA Now And How Is It Being Applied.(12:20)
08. Can You Apply This To Health Care.(13:57)
09. Is This Like The New Cyber Security Software.(14:48)….
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Can you apply machine learning to machine learning? | #SparkSummit

by Gabriel Pesek | Jun 8, 2016

As the Spark Summit 2016 event continues in San Francisco this week, attendees are getting to learn about the latest uses for Spark in the tech world, as well as getting exclusive glimpses of its effect on future developments.

Christopher Cuong T. Nguyen, cofounder and CEO of Arimo, Inc., joined cohosts John Walls and George Gilbert (@ggilbert41) of theCUBE, from the SiliconANGLE Media team, during Spark Summit to discuss what his company is doing with Spark to create more effective and powerful work environments, along with the importance of keeping things accessible for all users.

Information and interactions
Nguyen, who described himself as “a very early adopter of Spark,” was confident in his company’s investment in Spark, saying, “If you are familiar with technology evolution, and then you understand architecture, and you have a sense of timing, then [an investment in Spark is] actually not a very risky bet.”

He also provided a deeper look at their motivations for using Spark specifically. “The information asymmetry that we had looking at Spark is that we looked at a whole bunch of different compute architectures, specifically in memory, and … we knew that what had to happen is that you need to have what’s called a distributed dataset that exists outside of the compute cycle,” he said.

Nguyen added, “Spark is unique in that it has the concept of RDDs [Resilient Distributed Dataset], and RDDs exist whether there’s compute cycle or not, and what we wanted to do was to build an interactive application on top of such a compute system, and you can’t do that without having the distributed dataset. So that’s one of the key things about the Spark architecture that we knew was necessary.”

He continued to explain that the other key was timing and referred to Moore’s Law in finding a viable point between evolution and affordability with memory.

Easy tuning
Nguyen continued by exploring some of Arimo’s goals and ways of making its results available to customers.

“For the most part, when a data-scientist [adjusts hyper-parameters of algorithms], it’s pretty much a manual process; it’s a lot of guess-work based on experience,” he explained. “And so, it turns out that takes a lot of time. The training itself is run by large-scale computing … but the choice of parameters … that, if there’s a way to automate it, then that could save a lot of time and effort.” Arimo’s overarching goal is “intelligent augmentation … and what that means is that we augment human intelligence with machine intelligence in the enterprise.” Nguyen said.

Worth for customers
Nguyen’s next focus was to explicate the “two major human targets” of Arimo’s product suite. “One is the business user, the other is the data scientist. … For the business user, we allow the business user to go to a web interface, a document (we call it a narrative), and type in a natural-language question … and have the answer come back within 10 seconds,” he explained. “In order to answer that question, you need a lot of predictive models and the computing power and the data processing required to do that.”

He continued, “But [for] the data-scientist … we provide ways to make the data centers a lot more productive, and we also work on deep-learning algorithms so that there are new ways that the data scientist can use, for example, time-series processing. The third value proposition that we give to the business user and the data scientist is the collaboration between these two. … The value to the enterprise is expressed, or is most leveraged, when these two have a common environment and express their unique skills.” Describing the current structuring of question-answering software, particularly in regards to how it verifys input and identities as being what they truly are, Nguyen characterized it as “dumb” because “there’s no learning behind it.” What Arimo is aiming for is to change that by applying machine learning to machine learning itself.

Panasonic announced today that it has acquired Arimo Inc., a Mountain View, California-based leader in deep learning and behavioral artificial intelligence (AI) to leverage Arimo’s data science expertise in solutions it provides to its B2B customers (including manufacturers) as well as in the housing business.

The following video presents Transferring Data with a Touch | #Panasonic LIVE@CEATEC 2016
This communication module employs electric-field communication technology to achieve “thing-to-thing, human-to-human and human-to-thing” communication.


Oct 23, 2017

Panasonic Acquires Arimo, Deep Learning Innovator, to Accelerate the Growth of its AI/IoT-based Solution Businesses

Osaka, Japan – Panasonic Corporation today announced that it has acquired Arimo Inc., a Mountain View, California-based leader in deep learning and behavioral artificial intelligence (AI). Ranked among the ten most innovative companies in data science by Fast Company Magazine in 2016, Arimo is developing IoT-centric AI products for commercial and manufacturing applications, which is supports Big Data and Deep Learning applications. Through this acquisition, Panasonic plans to leverage Arimo’s data science expertise in solutions it provides to its B2B customers (including manufacturers) as well as in the housing business.

Panasonic has developed the Panasonic Digital Platform, which aggregates and utilizes sensor data from factories, housing, cold-chain, and HVAC applications. By combining Arimo’s strength in data science and especially predictive analytics, Panasonic plans to accelerate the growth of its AI/IoT-based solution business and further promote the company’s digital transformation.

“The acquisition of Arimo provides Panasonic with a much-needed core data science element that will greatly reinforce our efforts to continue developing further sophisticated AI-based solutions for our B2B customers,” said Yoshiyuki Miyabe, Panasonic Corporation Chief Technology Officer. “We are very pleased to have Arimo founder Christopher Nguyen and his team of data scientists join us in this mission.”

【Profile of Arimo】

Company Name : Arimo Inc.
Address : 888 Villa St., Suite 400, Mountain View, CA 94041
Representative directors : Christopher Nguen and 3 others
Established : 2013
Business operations : Data analytics solution using deep learning

About Panasonic

Panasonic Corporation is a worldwide leader in the development of diverse electronics technologies and solutions for customers in the consumer electronics, housing, automotive, and B2B businesses. Celebrating its 100th anniversary in 2018, the company has expanded globally and now operates 495 subsidiaries and 91 associated companies worldwide, recording consolidated net sales of 7.343 trillion yen for the year ended March 31, 2017. Committed to pursuing new value through innovation across divisional lines, the company uses its technologies to create a better life and a better world for its customers.
To learn more about Panasonic:

The following video presents Panasonic Smart Factory Solutions:
posted on on: Sep, 05, 2017 Panasonic’s Smart Factory Solutions realize higher productivity using network technologies. Panasonic is improving the manufacturing process of electronic component mounting production lines, with Smart Factory Solutions centered on the integrated line management system “iLNB”. In this video, we will introduce a case study of how a production line in the Philippines has become more efficient thanks to the introduction of iLNB. Product Info: Factory Automation…”