5 Open Source companies to watch in 2017

As if getting venture funding themselves isn’t exciting enough for open source-oriented startups, seeing an open source-focused company like Deis get snapped up by Microsoft must be a thrill as well.

While it would be more thrilling, perhaps, if Microsoft disclosed how much it paid, I’m sure those in the startup world and their backers have ways of finding out that information. Not that the acquisition path is necessarily the exit route that all of these startups envision for themselves, but such money can obviously talk.

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Open source tool manages AWS Lambda apps

A new open source project from Express and Node.js-canvas creator TJ Holowaychuk lets developers create, deploy, and manage AWS Lambda functions from a command-line tool.

Apex, written in Google’s Go language, also makes it possible to run applications in languages not directly supported by AWS Lambda, such as Golang itself.

Apex deploys AWS Lambda functions via projects, aka collections of function definitions described with JSON. It bundles all the needed dependencies and uploads them to AWS, and it automatically cleans up older or outdated versions of functions. In a nod to building versioned APIs, Apex allows users to manually specify which versions of a given function to retain.

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Samsung Open Source IoT Platform Aims to Bridge Connected Devices Gap

samsung artik 300x171 Samsung Open Source IoT Platform Aims to Bridge Connected Devices GapSamsung challenge Intel and Qualcomm with the announcement of three new chips aim at the Internet of Things market. Samsung also announced the launch of SmartThings Open Cloud, which will help developers create the applications using their connected devices.

The Korean manufacturer new Artik platform includes software, development boards, drivers, tools, security features and connectivity cloud, or everything you need to create innovative products and services for the IoT. The line Artik is composed of three SoC chips of different sizes. The whole family of modules, Samsung ARTIK, is characterized by the presence of built-in memory and high computing power as well as advanced safety technologies.

The smaller, Artik 1, measuring about 12 × 12 cm and is powered by a button battery. The chip integrates a dual core processor at 250 MHz, 4 GB of flash memory and a 9-axis motion sensor. It combines an MIPS32-based dual-core processor, 1 MB SRAM, 4MB Flash memory, power management, an encryption engine and a Bluetooth LE Module. It is designed for low-power devices, such as Bluetooth tags, beacons and wearable.

A clocked at 250MHz processor core takes care of demanding workloads while a low-power core with 80 MHz takes less compute-intensive tasks. In addition, the Artik 1 integrated 9-axis motion sensor with a gyroscope, accelerometer, and magnetometer. According to Samsung, it is intended for IoT devices like beacon transmitter, fitness tracker or smart bracelets.

The Artik 5 is manufactured in particular for smart home hubs. It has a dual-core processor on ARM A7 base with 1 GHz, 512 MB ??of DDR3 RAM and 4 GB of flash memory. There are also several security features, wireless support (802.11b/g/n), and encoding and decoding of video.

The most powerful model Artik 10 will power, especially Home Server and personal clouds. It integrates an octa core processor at 1.3 GHz, 2 GB of RAM, and 16 GB of flash memory and can perform the encoding/decoding of 1080p video with 5.1 audio. These chips are already used in mobile products and soon will also be used in smart TV, household appliances connected to the Internet and in all SmartThings devices.

The company says, “These modules focus on device manufacturers and allow a manufacturer to easily create a connected device by using one of a line of ARTIK modules. The combination of ARTIK + SmartThings Open Cloud provides the necessary hardware, software, and services for device makers to build connected devices easily without having to build and operate the entire stack.”

Like other manufacturers, Samsung also sets high hopes for the Internet of Things. Gartner analysts predict that the number of connected devices will rise to 26 billion by 2020, from 900 million in 2009. IDC expects that the IoT market will reach a volume of 3.04 trillion dollars by 2020.

Back in January at the Consumer Electronics Show in Las Vegas, Samsung had announced that 90 percent of all devices manufactured by Samsung – from smartphones to refrigerators – to connect to the Internet by 2017. However, the Artik chip platform aims not only to Samsung’s own devices. Other manufacturer’s processors are also integrating them into their products.


IBM Strengthens Effort to Support Open Source Spark for Machine Learning

Spark 300x251 IBM Strengthens Effort to Support Open Source Spark for Machine LearningIBM is providing substantial resources to the Apache Software Foundation’s Spark project to prepare the platform for machine learning tasks, like pattern recognition and classification of objects. The company plans to offer Bluemix Spark as a service and has dedicated 3,500 researchers and developers to assist in its preservation and further development.

In 2009, AMPLab of the University of Berkeley developed the Spark framework that went open source a year later as an Apache project. This framework, which runs on a server cluster, can process data up to 100 times faster than Hadoop MapReduce. Given that the data and analyzes are embedded in the corporate structure and society – from applications to the Internet of Things (IoT) – Spark provides essential advancements in large-scale data processing.

First, it significantly improves the performance of applications dependent data. Then it radically simplifies the development process of intelligence, which are supplied by the data. Specifically, in its effort to accelerate innovation on Spark ecosystem, IBM decided to include Spark in its own platforms of predictive analysis and machine learning.

IBM Watson Health Cloud will use Spark to healthcare providers and researchers as they have access to new health data of the population. At the same time, IBM will make available its SystemML machine learning technology open source. IBM is also collaborating with Databricks in changing Spark capabilities.

IBM will hire more than 3,500 researchers and developers to work on Spark-related projects in more than a dozen laboratories worldwide. The big blue company plans to open a Spark Technology Center in San Francisco for the Data Science and the developer community. IBM will also train Spark to more than one million data scientists and data engineers through partnerships with DataCamp, AMPLab, Galvanize, MetiStream, and Big Data University.

A typical large corporation will have hundreds or thousands of data sets that reside in different databases through their computer system. A data scientist can design an algorithm using to plumb the depths of any database. But is needs 90 working days of scientific data to develop the algorithm. Today, if you want to implement another system, it is a quarter of work to adjust the algorithm so that it works. Spark eliminates that time in half. The spark-based system can access and analyze any database, without development and no additional delay.

Spark has another virtue of ease of use where developers can concentrate on the design of the solution, rather than building an engine from scratch. Spark brings advances in data processing technology on a large scale because it improves the performance of data-dependent applications, radically simplifies the process of developing intelligent solutions and enables a platform capable of unifying all kinds of information on real work schemes.

Many experts consider Spark as the successor to Hadoop, but its adoption remains slow. Spark works very well for machine learning tasks that normally require running large clusters of computers. The latest version of the platform, which recently came out, extends to the machine learning algorithms to run.


How the cloud will devour open source

In one of the most colossal understatements ever, Cloudera co-founder Mike Olson declared, “It’s pretty hard to build a successful, stand-­alone open source company.”

Having spent 15 years trying to do exactly that, I would go one step further: It’s impossible.

Yes, we have Red Hat. But that’s all we have. Investor (and former open source executive) Peter Levine insists that “we will never have another Red Hat,” and he’s right. But this may be because the Amazons of the world are increasingly eating the Red Hats of the world — one SaaS business at a time.

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