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AWS Announces General Availability of Amazon Managed Streaming for Apache Kafka (Amazon MSK)



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Amazon MSK provides a fully managed, highly available, secure, and
compatible service for Apache Kafka

Vonage, Secureworks, Poshmark, Nutmeg, and Compass are among
customers and partners using Amazon MSK

SEATTLE–(BUSINESS WIRE)–Today, Amazon Web Services Inc., an company (NASDAQ: AMZN),
announced the general availability of Amazon MSK, a fully managed
service for Apache Kafka that makes it easy for developers to build and
run highly available, secure, and scalable applications based on Apache
Kafka without having to worry about managing the underlying
infrastructure. Amazon MSK is fully compatible with Apache Kafka,
enabling customers to easily migrate their on-premises or Amazon Elastic
Cloud Compute (Amazon EC2) clusters to Amazon MSK with no code changes.
There are no commitments or upfront investment required to run Amazon
MSK, and customers only pay for the capacity they use. To get started
with Amazon MSK visit

Customers use Apache Kafka to capture and analyze real-time data streams
from a range of sources, including IoT devices, website clickstreams,
financial systems, and database logs. While many customers chose to
self-manage their Apache Kafka clusters, they often spend a lot of time
and expense securing, scaling, patching, and ensuring high availability
for Apache Kafka and Apache ZooKeeper clusters, which Apache Kafka
depends on for resource management. Amazon MSK gives customers all of
the attributes of Apache Kafka combined with the availability, security,
and scalability of AWS. With just a few clicks, customers can create
Apache Kafka clusters designed for high availability that span multiple
Availability Zones (AZs). Amazon MSK continuously monitors underlying
server health, automatically replacing servers when they fail and
patching servers in need of updates. Amazon MSK also runs highly
available Apache ZooKeeper nodes at no additional cost. Amazon MSK
provides multiple levels of security for Apache Kafka clusters,
including VPC network isolation, AWS Identity and Access Management
(IAM) for AWS Application Programming Interface (API) authorization,
encryption at rest, encryption in-transit, TLS based certificate
authentication, and authorization using Apache Kafka access control
lists (ACLs). Customers can easily scale out cluster storage with a few
clicks in the AWS management console to meet changes in demand. Amazon
MSK is fully compatible with Apache Kafka, allowing customers to
continue to run applications built on Apache Kafka, use Apache Kafka
compatible tools and frameworks, and take advantage of new Apache Kafka
innovations, without having to change their code.

“Customers who are running Apache Kafka have told us they want to spend
less time managing infrastructure and more time building applications
based on real-time streaming data,” said Rajesh Sheth, General Manager
of Amazon MSK, AWS. “Amazon MSK gives these customers the ability to run
Apache Kafka without having to worry about managing the underlying
hardware, and it gives them an easy way to integrate their Apache Kafka
applications with other AWS services. With Amazon MSK, customers can
stand up Apache Kafka clusters in minutes instead of weeks, so they can
spend more time focusing on the applications that impact their

Customers start by creating a cluster in Amazon MSK today using the AWS
Console or the AWS CLI, and Apache Kafka clients can connect to a
cluster using Apache Kafka’s open-source APIs. Amazon MSK is available
in the US East (N. Virginia), US East (Ohio), US West (Oregon), EU
(Ireland), EU (London), EU (Frankfurt), EU (Paris), Asia Pacific
(Tokyo), Asia Pacific (Singapore), and Asia Pacific (Sydney), and will
expand to additional AWS Regions in the coming year.

Vonage is a global business cloud communications leader providing
integrated communications solutions that improve how business gets done
by enhancing a company’s customer and employee experience. Vonage uses
Apache Kafka for real-time communication between various micro-services.
“By using Amazon MSK, we reduced our maintenance overhead and built a
micro-services-based platform that enables businesses to collaborate
more productively and engage their customers more effectively,” said
Venkatesh Ennala, a software engineer with Vonage. “We can now set up
new Kafka clusters more quickly and scale these clusters as our demands
increase. Amazon MSK has removed the complexity of set up and
maintenance, allowing us to focus on what’s most important – building
innovative new capabilities for our customers.”

Secureworks (NASDAQ: SCWX) is a technology-driven cybersecurity leader
that protects organizations in the digitally connected world. “When
developing and launching our security analytics application, Secureworks
chose Amazon MSK service to accelerate time to market and reduce
infrastructure and management overhead,” said Wendy Thomas, Senior Vice
President of Business and Product Strategy at Secureworks. “This allowed
us to focus on innovation and our unique differentiators, helping
protect our customers from cyber threats.”

Poshmark is a leading social commerce platform for the next generation
of retailers and shoppers. “Through technology, our mission is to build
the world’s most connected shopping experience, while empowering people
to build thriving retail businesses. Amazon MSK has made it easy to
setup, maintain and scale Kafka clusters, enabling an end-to-end data
ingestion pipeline supported by a fully-managed service,” said Mahesh
Pasupuleti, Senior Director of Data Engineering at Poshmark. “As our
demands increase, we feel confident that we will be able to scale at
ease and expand our streaming ingestion pipelines for data enrichment
and real-time machine learning, providing an enhanced experience for our

Nutmeg is Europe’s largest digital wealth manager, helping consumers to
grow their wealth and reach their financial goals by using cost
effective technology to boost returns. Nutmeg uses Apache Kafka to
underpin their journey towards an event driven architecture. “Since
adopting Amazon MSK, we’ve been able to significantly increase the
efficiency of our teams and reduce time spent maintaining our cluster,”
said Matt Gatrell, CTO of Nutmeg. “As our data requirements and use
cases grew, we started to experience considerable overhead and
complexity in managing our Kafka clusters. Amazon MSK has allowed us to
manage our clusters with confidence, spend less time verifying the
performance of the clusters, scale with ease, and focus more time on
innovating and building exciting real-time applications.”

Compass is a real estate technology company with a powerful end-to-end
platform that supports the entire buying and selling workflow. Compass
uses Apache Kafka to provide its agents with quick access to fresh and
accurate data from hundreds of real estate data sources nationwide.
“Streaming technology is an important part of what we do as a business,
but managing streaming technology involves a lot of heavy lifting by our
software developers,” said Joseph Sirosh, CTO of Compass. “Amazon MSK
has allowed us to eliminate a lot of this heavy lifting. By using Amazon
MSK we no longer need to spend effort on ensuring data durability,
cluster availability, and scalability, and can now focus on building
applications. Amazon MSK relieves our team from the burden of operating
and maintaining Kafka and at the same time, we experience less downtime
as our clusters are fully-managed.”

About Amazon Web Services

For 13 years, Amazon Web Services has been the world’s most
comprehensive and broadly adopted cloud platform. AWS offers over 165
fully featured services for compute, storage, databases, networking,
analytics, robotics, machine learning and artificial intelligence (AI),
Internet of Things (IoT), mobile, security, hybrid, virtual and
augmented reality (VR and AR), media, and application development,
deployment, and management from 66 Availability Zones (AZs) within 21
geographic regions, spanning the U.S., Australia, Brazil, Canada, China,
France, Germany, Hong Kong Special Administrative Region, India,
Ireland, Japan, Korea, Singapore, Sweden, and the UK. Millions of
customer—including the fastest-growing startups, largest enterprises,
and leading government agencies—trust AWS to power their infrastructure,
become more agile, and lower costs. To learn more about AWS, visit

About Amazon

Amazon is guided by four principles: customer obsession rather than
competitor focus, passion for invention, commitment to operational
excellence, and long-term thinking. Customer reviews, 1-Click shopping,
personalized recommendations, Prime, Fulfillment by Amazon, AWS, Kindle
Direct Publishing, Kindle, Fire tablets, Fire TV, Amazon Echo, and Alexa
are some of the products and services pioneered by Amazon. For more
information, visit and
follow @AmazonNews.

Contacts, Inc.
Media Hotline, 206-266-7180


Strainprint™ Technologies Welcomes Organic Medical Cannabis Producer to Growing List of Subscribers



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Strainprint™ Technologies Ltd, the leader in cannabis data and analytics is pleased to expand their nation-wide coverage with the addition of Stewart Farms.

Stewart Farms is a late-stage applicant headquartered in Alberta that is building a 100,000 sq. ft. vertical aquaponics farm in Saint StephensNew Brunswick. They will be utilizing automation, vertical farming, and land-based aquaculture to produce medical grade organic cannabis for both recreational and medical markets in Canada. All of their products will be free of herbicides, pesticides and synthetic nutrients. At full capacity, they will reach more than 10,000 kgs per year of organically farmed cannabis and more than 200,000 kgs of organic tilapia.

Stewart Farms’ long term vision is to deliver tools and products to support  future customers and patients during their health and wellness journeys. “Through our partnership with Strainprint we gain direct access to their incomparable data and analytics tools. This will aid us in educating a wider audience on the medical benefits and best practices of cannabis-based medicine,” said Tanner Stewart, Co-founder & CEO of Stewart Farms. “We know our customers are looking to consume more than dried cannabis. We know Canadians of all legal ages are trying to sort through their personal engagement with cannabis as a medicine. What we want to know, on an ongoing basis, is what is and is not working for people. Strainprint’s patient-led data services will give us the insight needed to create custom products and further understand the benefits of our existing products. Finally, our goal is to partner with companies and teams that truly have people’s best interest at heart. Caring about a patient’s success is what makes up the core of the Strainprint team. We couldn’t be happier to move forward with them at our side.”

Stewart Farms will access the Strainprint Analytics web platform, the most sophisticated cannabis analytics platform available to improve product development. Strainprint Analytics is built on top of the largest and most granular scientific data set of its kind in the world, with more than 1.3 million anonymized, patient reported medical cannabis outcomes and more than 65 million data points on strain efficacy.

“We’re thrilled to provide our real-time, crowd sourced data to an environmentally conscious company that uses innovative, cutting edge farming technology to produce top-tier medical cannabis,” said Strainprint CEO, Andrew Muroff. “Our organizations are equally committed to improving lives using cannabis therapy, and our shared core motivation is to provide guidance and support to help cannabis patients achieve their health goals.”


SOURCE Strainprint Technologies Ltd.

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Field Trip Ventures Inc. Retains KCSA Strategic Communications as Public Relations Counsel



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Greenery Map, the world’s first and only cannabis search engine to allow users to search for cannabis products based on their desired mood, medicinal use, and method of consumption, is now offering users – both businesses and consumers – the opportunity to register and connect to the app in an entirely mobile way. Previously, businesses were required to access from a desktop in order to manage accounts and connect to the inventory API system, but that road block has been removed, allowing for an entirely mobile experience through the Greenery Map app.

App users turn to Greenery Map to help them decide on the strain of Cannabis and product that is right for them depending on their desired mood or medicinal effect. Following the matching, consumers are given a detailed history and description of the strain so that they can make educated purchases, cutting down on time that budtenders need to spend with patrons and speeding up the purchase process. Consumers can then see all of the ways to purchase said product, including the nearby dispensaries that have it in stock, online options, and even delivery options through the app. Greenery Map fully integrates with a dispensary’s inventory API system to update in real-time and give consumers real-time information on dispensary stock for the item they are looking for. The Greenery Map system also provides cannabis businesses in both the B2B and B2C sectors a private database to share and sell information and products. For Cannabis businesses, Greenery Map also offers the opportunity to open bank and merchant accounts through their partnership with PayHouse Consulting Group.


SOURCE Greenery Map

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WeBank, IBM and Other Organizations Jointly Held the 1st International Workshop on Federated Machine Learning in conjunction with IJCAI 2019



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Once a concept, AI is now ushering in a key stage of application. What’s the solution to the data silos among businesses? Given the enhanced regulation on data at home and abroad, what’s the solution to data privacy and security concerns? What’s the status quo of Federated Machine Learning and how to establish an ecosystem for FML in the future?

WeBank, IBM and other organizations jointly held the 1st International Workshop on Federated Machine Learning for User Privacy and Data Confidentiality (FML’19) in conjunction with the 28th International Joint Conference on Artificial Intelligence (IJCAI-19) on Aug. 12, 2019, to further discussion on these issues.

President of IJCAI, Chair of FML Steering Committee, Chief AI Officer of WeBank Professor Qiang Yang delivered opening remarks at the workshop. Dr. Shahrokh Daijavad from IBM and Dr. Jakub Konečný from Google presented keynote addresses. In the panel discussion, top scholars from WeBank, Bar-Ilan University, IBM, Squirrel AI, Google, Huawei, Clustar, Sinovation Ventures and many other renowned enterprises and universities shared and discussed their findings and experience in FML as an emerging AI technology.

This workshop received 40 papers, of which 12 were presented during the workshop, 19 presented via poster. Awards include Best Theory Paper Award, Best Application Paper Award, Best Student Paper Award, Best Presentation Award. Selected high quality papers will be invited for publication in a special issue in the IEEE Intelligent Systems journal. All these attracted numerous scholars to engage in discussions and join efforts for building the FML ecosystem.

Experts from IBM and Google Share Groundbreaking Findings with a Focus on the Theory and Application of FML

Privacy and security are becoming a key concern in our digital age. On 25th May last year, the implementation of General Data Protection Regulation (GDPR) by the EU, the toughest Act on data privacy protection, stressed that user data collection must be open and transparent. A series of laws and regulations from China and overseas also pose new challenges to the traditional way of handling data and model for cooperation. Seeking ways for AI to adapt to this new reality became top priority, a demand that led to this workshop on FML.

A wealth of solutions and breakthroughs were shared by Dr. Shahrokh Daijavad from IBM and Dr. Jakub Konečný from Google in their speech on FML.

Besides how FML can help tackle challenges in the business world, Dr. Shahrokh Daijavad also shared the concept of Fusion AI, which means to train models on widely distributed data sets, but fuse them to produce one equivalent to what centralized training would yield. “Unlike traditional machine learning, in Fusion AI, model parameters are shared and data is not transferred, which makes Fusion AI model better than models that moving data centrally.” Given the widely distributed data, the development of Fusion AI and FML became ever important and imminent.

“FML enables machine learning engineers and data scientists to work productively with decentralized data with privacy by default,” said Dr. Jakub Konečný from Google. He also shared with us how FML works and its use cases at Google. In the case of Gboard, as on-device data is privacy sensitive or large or is more relevant than server-side proxy data, and labels can be inferred naturally via user interaction, the application of Federated RNN compared to prior n-gram model can increase the accuracy of next-word prediction by 24%, and the click rate of prediction strip by 10%.

Major Figure Panelists Discuss the Way Ahead for FML

The moderator of the panel discussion, AI Principal Scientist of WeBank Dr. Lixin Fan joined panelists including Professor Benny Pinkas from Bar-Ilan University, Dr. Shahrokh Daijavad of IBM Academy of Technology, Chief Architect of Squirrel AI Dr. Richard Tong, Research Scientist of Google Dr. Jakub Konečný, Dr. Baofeng Zhang from CTO Office of CBG Software in Huawei, Executive VP of Clustar Dr. Junxue Zhang, VP of AI Institute in Sinovation Ventures Dr. Ji Feng and other experts in a host of in-depth exchanges with attendees, to shed light on the way ahead for FML.

Experts shared thoughts in the panel discussion on questions including but not limited to: How to meet the security and compliance requirements? Is there a way to extend the value of data while observing user privacy and data security? Given the classic trade-off between data regulation and development of AI, how to achieve the long-term goal of establishing a stable and win-win business ecosystem?

List of Award-Winners

Best Theory Paper Award, Best Application Paper Award, Best Student Paper Award and Best Presentation Award selected by all attendees were announced at the closing of the workshop.

Best Theory Paper Award: 
Preserving User Privacy for Machine Learning: Local Differential Privacy or Federated Machine Learning? By Huadi Zheng, Haibo Hu & Ziyang Han;

Best Application Paper Award: 
FedHealth: A Federated Transfer Learning Framework for Wearable Healthcare. By Yiqiang ChenJindong WangChaohui YuWen Gao & Xin Qin;

Best Student Paper Award: 
Quantifying the Performance of Federated Transfer Learning. By Qinghe JingWeiyan Wang, Junxue Zhang, Han Tian & Kai Chen;

Best Presentation Award: 
Federated Generative Privacy. By Aleksei Triastcyn and Boi Faltings.

President of IJCAI, Chief AI Officer of WeBank Professor Qiang Yang, Chief Architect of Squirrel AI Dr. Richard TongandVP of AI Institute in Sinovation Ventures Dr. Ji Feng presented the awards.

“The mission of this International Federated Machine Learning Workshop is to facilitate further understanding in the academia, business community as well as legal and regulatory institutions by promoting the establishment of FML ecosystem in the hope that more businesses will join and build a platform for students aspired to work in FML to find research teams that suit them,” said Professor Qiang Yang.

Held Aug. 10-16, 2019 in Macao, China, IJCAI-19 is one of the leading International Academic Conference on AI, attracting over 3000 AI research personnel and experts. The 1st International Workshop on Federated Machine Learning (FML’19) was a highlight for experts joining this event. Visionaries in the academia and industrial sector expressed the willingness to be part of the effort for academic research, application of FML in the future, and the development and boom of AI ecosystem.

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