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Main article: Developer

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The nation-state of the internet

18:50 | 8 December

The internet is a community, but can it be a nation-state? It’s a question that I have been pondering on and off this year, what with the rise of digital nomads and the deeply libertarian ethos baked into parts of the blockchain community. It’s clearly on a lot of other people’s minds as well: when we interviewed Matt Howard of Norwest on Equity a few weeks back, he noted (unprompted) that Uber is one of the few companies that could reach “nation-state” status when it IPOs.

Clearly, the internet is home to many, diverse communities of similar-minded people, but how do those communities transmute from disparate bands into a nation-state?

That question led me to Imagined Communities, a book from 1983 and one of the most lauded (and debated) social science works ever published. Certainly it is among the most heavily cited: Google Scholar pegs it at almost 93,000 citations.

Benedict Anderson, a political scientist and historian, ponders over a simple question: where does nationalism come from? How do we come to form a common bond with others under symbols like a flag, even though we have never — and will almost never — meet all of our comrades-in-arms? Why does every country consider itself “special,” yet for all intents and purposes they all look identical (heads of state, colors and flags, etc.) Also, why is the nation-state invented so late?

Anderson’s answer is his title: people come to form nations when they can imagine their community and the values and people it holds, and thus can demarcate the borders (physical and cognitive) of who is a member of that hypothetical club and who is not.

In order to imagine a community though, there needs to be media that actually links that community together. The printing press is the necessary invention, but Anderson tracks the rise of nation-states to the development of vernacular media — French language as opposed to the Latin of the Catholic Church. Lexicographers researched and published dictionaries and thesauruses, and the printing presses — under pressure from capitalism’s dictates — created rich shelves of books filled with the stories and myths of peoples who just a few decades ago didn’t “exist” in the mind’s eye.

The nation-state itself was developed first in South America in the decline and aftermath of the Spanish and Portuguese empires. Anderson argues for a sociological perspective on where these states originate from. Intense circulation among local elites — the bureaucrats, lawyers, and professionals of these states — and their lack of mobility back to their empires’ capitals created a community of people who realized they had more in common with each other than the people on the other side of the Atlantic.

As other communities globally start to understand their unique place in the world, they import these early models of nation-states through the rich print culture of books and newspapers. We aren’t looking at convergent evolution, but rather clones of one model for organizing the nation implemented across the world.

That’s effectively the heart of the thesis of this petite book, which numbers just over 200 pages of eminently readable if occasionally turgid writing. There are dozens of other epiphanies and thoughts roaming throughout those pages, and so the best way to get the full flavor is just to pick up a used copy and dive in.

For my purposes though, I was curious to see how well Anderson’s thesis could be applied to the nation-state of the internet. Certainly, the concept that the internet is its own sovereign entity has been with us almost since its invention (just take a look at John Perry Barlow’s original manifesto on the independence of cyberspace if you haven’t).

Isn’t the internet nothing but a series of imagined communities? Aren’t subreddits literally the seeds of nation-states? Every time Anderson mentioned the printing press or “print-capitalism,” I couldn’t help but replace the word “press” with WordPress and print-capitalism with advertising or surveillance capitalism. Aren’t we going through exactly the kind of media revolution that drove the first nation-states a few centuries ago?

Perhaps, but it’s an extraordinarily simplistic comparison, one that misses some of the key originators of these nation-states.

Photo by metamorworks via Getty Images

One of the key challenges is that nation-states weren’t a rupture in time, but rather were continuous with existing power structures. On this point, Anderson is quite absolute. In South America, nation-states were borne out of the colonial administrations, and elites — worried about losing their power — used the burgeoning form of the nation-state to protect their interests (Anderson calls this “official nationalism”). Anderson sees this pattern pretty much everywhere, and if not from colonial governments, then from the feudal arrangements of the late Middle Ages.

If you turn the gaze to the internet then, who are the elites? Perhaps Google or Facebook (or Uber), companies with “nation-state” status that are essentially empires on to themselves. Yet, the analogy to me feels stretched.

There is an even greater problem though. In Anderson’s world, language is the critical vehicle by which the nation-state connects its citizens together into one imagined community. It’s hard to imagine France without French, or England without English. The very symbols by which we imagine our community are symbols of that community, and it is that self-referencing that creates a critical feedback loop back to the community and reinforces its differentiation.

That would seem to knock out the lowly subreddit as a potential nation-state, but it does raise the question of one group: coders.

When I write in Python for instance, I connect with a group of people who share that language, who communicate in that language (not entirely mind you), and who share certain values in common by their choice of that language. In fact, software engineers can tie their choices of language so strongly to their identities that it is entirely possible that “Python developer” or “Go programmer” says more about that person than “American” or “Chinese.”

Where this gets interesting is when you carefully connect it to blockchain, which I take to mean a technology that can autonomously distribute “wealth.” Suddenly, you have an imagined community of software engineers, who speak in their own “language” able to create a bureaucracy that serves their interests, and with media that connects them all together (through the internet). The ingredients — at least as Anderson’s recipe would have them — are all there.

I am not going to push too hard in this direction, but one surprise I had with Anderson is how little he discussed the physical agglomeration of people. The imagining of (physical) borders is crucial for a community, and so the development of maps for each nation is a common pattern in their historical developments. But, the map, fundamentally, is a symbol, a reminder that “this place is our place” and not much more.

Indeed, nation-states bleed across physical borders all the time. Americans are used to the concept of worldwide taxation. France seats representatives from its overseas departments in the National Assembly, allowing French citizens across the former empire to vote and elect representatives to the country’s legislature. And anyone who has followed the Huawei CFO arrest in Canada this week should know that “jurisdiction” these days has few physical borders.

The barrier for the internet or its people to become nation-states is not physical then, but cognitive. One needs to not just imagine a community, but imagine it as the prime community. We will see an internet nation-state when we see people prioritizing fealty to one of these digital communities over the loyalty and patriotism to a meatspace country. There are already early acolytes in these communities who act exactly that way. The question is whether the rest of the adherents will join forces and create their own imagined (cyber)space.

 


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Cove.Tool wants to solve climate change one efficient building at a time

23:01 | 4 December

As the fight against climate change heats up, Cove.Tool is looking to help tackle carbon emissions one building at a time.

The Atlanta-based startup provides an automated big-data platform that helps architects, engineers and contractors identify the most cost-effective ways to make buildings compliant with energy efficiency requirements. After raising an initial round earlier this year, the company completed the final close of a $750,000 seed round. Since the initial announcement of the round earlier this month, Urban Us, the early-stage fund focused on companies transforming city life, has joined the syndicate comprised of Tech Square Labs and Knoll Ventures.

Helping firms navigate a growing suite of energy standards and options

Cove.Tool software allows building designers and managers to plug in a variety of building conditions, energy options, and zoning specifications to get to the most cost-effective method of hitting building energy efficiency requirements (Cove.Tool Press Image / Cove.Tool / https://covetool.com).

In the US, the buildings we live and work in contribute more carbon emissions than any other sector. Governments across the country are now looking to improve energy consumption habits by implementing new building codes that set higher energy efficiency requirements for buildings. 

However, figuring out the best ways to meet changing energy standards has become an increasingly difficult task for designers. For one, buildings are subject to differing federal, state and city codes that are all frequently updated and overlaid on one another. Therefore, the specific efficiency requirements for a building can be hard to understand, geographically unique and immensely variable from project to project.

Architects, engineers and contractors also have more options for managing energy consumption than ever before – equipped with tools like connected devices, real-time energy-management software and more-affordable renewable energy resources. And the effectiveness and cost of each resource are also impacted by variables distinct to each project and each location, such as local conditions, resource placement, and factors as specific as the amount of shade a building sees.

With designers and contractors facing countless resource combinations and weightings, Cove.Tool looks to make it easier to identify and implement the most cost-effective and efficient resource bundles that can be used to hit a building’s energy efficiency requirements.

Cove.Tool users begin by specifying a variety of project-specific inputs, which can include a vast amount of extremely granular detail around a building’s use, location, dimensions or otherwise. The software runs the inputs through a set of parametric energy models before spitting out the optimal resource combination under the set parameters.

For example, if a project is located on a site with heavy wind flow in a cold city, the platform might tell you to increase window size and spend on energy efficient wall installations, while reducing spending on HVAC systems. Along with its recommendations, Cove.Tool provides in-depth but fairly easy-to-understand graphical analyses that illustrate various aspects of a building’s energy performance under different scenarios and sensitivities.

Cove.Tool users can input granular project-specifics, such as shading from particular beams and facades, to get precise analyses around a building’s energy performance under different scenarios and sensitivities.

Democratizing building energy modeling

Traditionally, the design process for a building’s energy system can be quite painful for architecture and engineering firms.

An architect would send initial building designs to engineers, who then test out a variety of energy system scenarios over the course a few weeks. By the time the engineers are able to come back with an analysis, the architects have often made significant design changes, which then gets sent back to the engineers, forcing the energy plan to constantly be 1-to-3 months behind the rest of the building. This process can not only lead to less-efficient and more-expensive energy infrastructure, but the hectic back-and-forth can lead to longer project timelines, unexpected construction issues, delays and budget overruns.

Cove.Tool effectively looks to automate the process of “energy modeling.” The energy modeling looks to ease the pains of energy design in the same ways Building Information Modeling (BIM) has transformed architectural design and construction. Just as BIM creates predictive digital simulations that test all the design attributes of a project, energy modeling uses building specs, environmental conditions, and various other parameters to simulate a building’s energy efficiency, costs and footprint.

By using energy modeling, developers can optimize the design of the building’s energy system, adjust plans in real-time, and more effectively manage the construction of a building’s energy infrastructure. However, the expertise needed for energy modeling falls outside the comfort zones of many firms, who often have to outsource the task to expensive consultants.

The frustrations of energy system design and the complexities of energy modeling are ones the Cove.Tool team knows well. Patrick Chopson and Sandeep Ajuha, two of the company’s three co-founders, are former architects that worked as energy modeling consultants when they first began building out the Cove.Tool software.

After seeing their clients’ initial excitement over the ability to quickly analyze millions of combinations and instantly identify the ones that produce cost and energy savings, Patrick and Sandeep teamed up with CTO Daniel Chopson and focused full-time on building out a comprehensive automated solution that would allow firms to run energy modeling analysis without costly consultants, more quickly, and through an interface that would be easy enough for an architectural intern to use.

So far there seems to be serious demand for the product, with the company already boasting an impressive roster of customers that includes several of the country’s largest architecture firms, such as HGA, HKS and Cooper Carry. And the platform has delivered compelling results – for example, one residential developer was able to identify energy solutions that cost $2 million less than the building’s original model. With the funds from its seed round, Cove.Tool plans further enhance its sales effort while continuing to develop additional features for the platform.

Changing decision-making and fighting climate change

The value proposition Cove.Tool hopes to offer is clear – the company wants to make it easier, faster and cheaper for firms to use innovative design processes that help identify the most cost-effective and energy-efficient solutions for their buildings, all while reducing the risks of redesign, delay and budget overruns.

Longer-term, the company hopes that it can help the building industry move towards more innovative project processes and more informed decision-making while making a serious dent in the fight against emissions.

“We want to change the way decisions are made. We want decisions to move away from being just intuition to become more data-driven.” The co-founders told TechCrunch.

“Ultimately we want to help stop climate change one building at a time. Stopping climate change is such a huge undertaking but if we can change the behavior of buildings it can be a bit easier. Architects and engineers are working hard but they need help and we need to change.”

 


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Google’s cross-platform Flutter UI toolkit hits version 1.0

20:20 | 4 December

Flutter, Google’s UI toolkit for building mobile Android and iOS applications, hit its version 1.0 release today. In addition, Google also today announced a set of new third-party integrations with the likes of Square and others, as well as a couple of new features that make it easier to integrate Flutter with existing applications.

The open source Flutter project made its debut at Google’s 2017 I/O developer conference. Since then, it’s quickly grown in popularity and companies like Groupon, Philips Hue, Tencent, Alibaba, Capital One and others have already built applications with it, despite the fact that it had not hit version 1.0 yet and that developers have to write their apps in the Dart language, which is an additional barrier to entry.

In total, Google says, developers have already published “thousands” of Flutter apps to the Apple and Google app stores.

“Flutter is our portable UI toolkit for creating a beautiful native experience for iOS and Android out of just a single code base,” Tim Sneath, Google’s group product manager for Dart, explained. “The problem we’re solving is the problem that most mobile developers face today. As a developer, you’re kind of forced to choose. Either you build apps natively using the platform SDK, whether you’re building an iOS app or an Android app. And then you’ve to build them twice.”

Sneath was also part of the Silverlight team at Microsoft before he joined Google in 2017, so he’s got a bit of experience in learning what doesn’t work in this space of cross-platform development. It’s no secret, though, that Facebook is trying to solve a very similar problem with React Native, which is also quite popular.

“I mean, React Native is obviously a technology that’s proven quite popular,” Sneath said. “One of the challenges that React Native developers face, or have reported in the past — one challenge is that native React Native code is written in JavaScript, which means that it’s run using the browser’s JavaScript engine, which immediately kind of move this a little bit away from the native model of the platform. The bit that they are very native in is that they use the operating system’s own controls. And while on the surface, that seems like a good thing in practice, that had quite a few challenges for developers around compatibility.”

Google, obviously believes that its ability to compile to native code — and the speed gains that come with that — set its platform apart from the competition. In part, it does this by using a hardware-accelerated 2D engine and, of course, by compiling the Dart code to native ARM code for iOS and Android. The company also stresses that developers get full control over every pixel on the screen.

With today’s launch, Google is also announcing new third-party integrations to Flutter. The first is with Square, which announced two new Flutter SDKs for building payments flows, both for in-app experience and in-person terminals using a Square reader. Others are 2Dimensions, for building vector animations and embedding them right into Flutter, as well as Nevercode, which announced a tool for automating the build and packaging process for Flutter apps.

As for new Flutter features, Google today announced ‘Add to App,’ a new feature that makes it easier for developers to slowly add Flutter code to existing apps. In its early days, Flutter’s focus was squarely on building new apps from scratch, but as it has grown in popularity, developers now want to use it for parts of their existing applications as they modernize them.

The other new feature is ‘Platform Views,’ which is essentially the opposite of ‘Add to App’ in that it allows developers to embed Android and iOS controls in their Flutter apps.

 


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AWS launches Amazon Forecast to make time series predictions easier

21:47 | 28 November

Amazon’s AWS launched Amazon Forecast, a new pre-built machine learning tool today that will make it easier for developer to generate predictions based on time-series data. While predictions are pretty much the most standard use case for machine learning, building them still takes some skill. Amazon, of course, has already built plenty of these models for its own needs, so now it is essentially turning them into a product

“With just three clicks, you can give us the information and get a forecast,” AWS CEO Andy Jassy said in today’s keynote. “It’s super simple and when we benchmarked with customers in the private beta and ourselves, it’s providing up to 50 percent more accurate forecasts than what people were doing on their own before at one tenth of the cost of traditional supply chain software.”

Amazon, in its retail business, built a number of models to handle its own data. This is essentially the same technology that Amazon uses to forecast demand on its retail site. Users provide the company with all of their supply chain data and then gives the service the variables that could have impact on the forecast.

Behind the scenes, AWS looks at the data and the signal and then choose from eight different pre-built algorithms, train the model, tweak it and provide the forecast.

AWS is also making it easy to integrate this service with SAP’s and Oracle’s supply chain tools, as well as Amazon’s new Timestream database service.

The service isn’t necessarily cheap but it will surely save developers a lot of time.

more AWS re:Invent 2018 coverage

 


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AWS Lake Formation makes setting up data lakes easier

20:14 | 28 November

The concept of data lakes has been around for a long time, but being able to set up one of these systems, which store vasts amount of raw data in its native formats, was never easy. AWS wants to change this with the launch of AWS Lake Formation. At its core, this new service, which is available today, allows developers to create a secure data lake within a few days.

While ‘a few days’ may still sound like a long time in this age of instant gratification, it’s nothing in the world of enterprise software.

“Everybody is excited about data lakes,” said AWS CEO Andy Jassy in today’s keynote. “People realize that there is significant value in moving all that disparate data that lives in your company in different silos and make it much easier by consolidating it in a data lake.”

Setting up a data lake today means you have to, among other things, configure your storage and (on AWS) S3 buckets, move your data, add metadata and add that to a catalog. And then you have to clean up that data and set up the right security policies for the data lake. “This is a lot of work and for most companies, it takes them several months to set up a data lake. It’s frustrating,” said Jassy.

Lake Formation is meant to handle all of these complications with just a few clicks. It sets up the right tags and cleans up and dedupes the data automatically. And it provides admins with a list of security policies to help secure that data.

“This is a step-level change for how easy it is to set up data lakes,” said Jassy.

more AWS re:Invent 2018 coverage

 


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Source: Canada’s Corel is acquiring virtualization specialist Parallels in an all-cash deal

18:19 | 27 November

Some consolidation is afoot in the world of business software. TechCrunch has learned that Parallels, the virtualization specialist with millions of users, is getting acquired by Corel, the Canadian company behind design apps like CorelDraw and other productivity apps like WordPerfect.

Some employees at Parallels have already been briefed on the acquisition, which is expected to be announced to the whole company today. Terms have not been disclosed but we understand it is an all-cash deal.

Corel has changed ownership and gone in and out of being listed publicly a number of times since being founded in the 1980s in Ottawa. It’s now owned by Vector Capital, which is essentially the one buying Parallels.

From what we understand, Corel will keep Parallels an independent product.

Parallels was originally founded in 1999 with roots in Russia and is currently headquartered in Bellevue, Washington. It has never made much of a fanfare around its financing or valuation. According to PitchBook its last funding round was in 2015, an undisclosed amount from Endeavour Vision, KG Investments, Maxfield Capital, Savano Capital Partners and others. It had raised $300 million from Ingram Micro the year before that.

It’s not fully clear what the rationale was for the sale, except it seems many investors were longstanding and looking to exit, while Corel has slowly been consolidating a number of sodtware businesses, most recently before this, Gravit Designer from Germany earlier this year.

Parallels provides a number of products that help people work seamlessly across multiple platforms, essentially letting people (and IT managers) run a unified workflow regardless of the device or operating system, ranging from Windows, Mac, iOS, Android, Chromebook, Linux, Raspberry Pi and cloud — a particularly compelling offering in the current, fragmented IT climate.

Corel once had designs to take on Microsoft in the world of software — to be the Pepsi to Microsoft’s Coke, as I once saw it described. That didn’t really pan out, with Microsoft at the time having a vice grip on platform and software (this was before the rise of Google, the rebirth of Apple, the rise of apps, and other big shifts in the industry). At one point, Microsoft signed a partnership with Corel that saw it investing in the company: a sell out, as one disappointed Canadian journalist described it at the time.

The two have also sparred over patents.

These days Corel is “highly profitable”, says Vector, selling software that includes CorelDraw, WordPerfect, WinZip, PaintShop Pro, and WinDVD. You could potentially imagine Parallels existing alongside that, or even perhaps helping increase the functionality and usefulness of Corel’s other apps with more cross-platform functionality.

The Parallels deal is expected to close next year, our source said.

We have written both to Corel and Parallels and will update this post as we learn more.

 

 

 


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AWS launches Arm-based servers for EC2

12:29 | 27 November

At its re:Invent conference in Las Vegas, AWS today announced the launch of Arm-based servers for its EC2 cloud computing service. These aren’t run-of-the-mill Arm chips, though. AWS took the standard Arm cores and then customized them to fit its needs.The company says that its so-called AWS Graviton Processors have been optimized for performance and cost, with a focus on scale-out workloads that can be spread across a number of smaller instances (think containerized microservices, web servers, caching fleets, etc.).

The first set of instances, called A1, is now available in a number of AWS regions in the U.S. and Europe. They support all of AWS’s standard instance pricing models, including on-demand, reserved instance, spot instance, dedicated instance and dedicated host.

For now, you can only use Amazon Linux 2, RHEL and Ubuntu as operating systems for these machines, but AWS promises that additional operating system support will launch in the future.

Because these are ARM servers, you’ll obviously have to recompile any native code for them before you can run your applications on them. Virtually any application that is written in a scripting language, though, will probably run without any modifications.

Prices for these instances start at $0.0255/hour for an a1.medium machine with 1 CPU and 2 GiB of RAM and go up to $0.4080/hour for machines with 16 CPUs and 32 GiB of RAM. That’s maybe not as cheap as you would’ve expected given that an X86-based t3.nano server starts at $0.0052/hour, but you can always save quite a bit by using spot instances, of course. Until we see some benchmarks, though, it’s hard to compare these different machine types anyway.

As Amazon’s Jeff Barr notes in today’s announcement, the company’s move to its so-called Nitro System now allows it to launch new instance types at a faster clip. Nitro essentially provides the building blocks for creating new instance types that the team can then mix and match as needed.

It’s worth noting that AWS also launched support for AMD EPYC processors earlier this month.

more AWS re:Invent 2018 coverage

 


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Quantum Machines raises $5.5M to build control and operational layer for quantum computers

17:12 | 21 November

Quantum Machines, an Israeli startup launched by three Ph.D. physicists, wants to build the operational and control layer for quantum computing. Today, it announced a $5.5 million seed investment led by TLV ventures with participation from Battery Ventures.

The three principals have been studying quantum computing for a decade and they understand that to commercialize it, it’s going to require a complete solution. Right now the majority of the research is centered on increasing the number qubits at the processor level. Co-founder and CEO Itamar Sivan says in order to advance the technology, it’s going to take an operational and control layer to make it all work, and that is where the founders decided to concentrate the company’s efforts, he said.

Sivan explained that there is a point where the classical computers we use today and the quantum computers of the future will have to work together to pass data and interpret commands. He described three layers in a quantum computing stack. The first is the quantum processor. Next is a classical computing control layer with classical electronics you would find on any computer today. Finally, there is the software layer where you program a classical algorithm that has to be passed to the quantum processor.

He says that some companies are trying to build full stacks, but the bulk of research as been concentrated on building quantum processors. Quantum Machines decided to focus on one part of the stack. “We have come to the conclusion, that there must be a company laser-focused on a vertically integrated control solution that includes the classical hardware and software,” Sivan said.

“The power of quantum computers stems from their complexity and richness, though it is also this complexity which makes them incredibly difficult to control and operate— this is the problem our company is attempting to solve,” he added in a statement.

The company is currently working on prototype hardware to build this layer and is working with several Beta customers at the moment. It’s early days for the company, but the seed money should help them accelerate that vision and get a product to market more quickly.

 


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Amazon launches ‘Alexa-hosted skills’ for voice app developers

06:31 | 16 November

Amazon on Thursday launched a new service aimed at Alexa developers that automatically provisions and helps them to manage a set of AWS cloud resources for their Alexa skill’s backend service. The service is intended to help developers speed the time it takes to launch their skills, by allowing them to focus on their skills’ design and unique features, and not the cloud services they need.

“Previously you had to provision and manage this back-end on your own with a cloud endpoint, resources for media storage, and a code repository,” explained Amazon on its company blog post, announcing the new service. “Alexa-hosted skills offer an easier option. It automatically provisions and hosts an AWS Lambda endpoint, Amazon S3 media storage, and a table for session persistence so that you can get started quickly with your latest project.”

Developers will also be able to use a new code editor in the ASK Developer Console to edit their code, while AWS Lamdba will handle routing the skill request, executing the skill’s code, and managing the skill’s compute resources.

Amazon S3, meanwhile, can be used for things the skill needs to store – like media files, such as the images being used for the skill’s Echo Show, Echo Spot and Fire TV versions.

The service comes at a time when Amazon Alexa and Google Home are in a race to grab market share – and mind share – in the smart speaker industry. A lot of this will come down to how useful these devices are for customers – and well-designed skills are a part of that.

Smart speaker adoption is growing fast in the U.S., having recently reaching 57.8 million adults, according to a report from Voicebot. But in terms of third-party development of voice apps, Amazon leads Google Home, having passed 40,000 U.S. skills in September.

Amazon says Alexa-hosted skills are available to developers in all Alexa locales. Developers can apply to join the preview here.

 


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Uber joins Linux Foundation cementing commitment to open source tools

00:58 | 16 November

Uber announced today at the 2018 Uber Open Summit that it was joining the Linux Foundation as a Gold Member, making a firm commitment to using and contributing to open source tools.

Uber CTO Thuan Pham sees the Linux Foundation as a place for companies like his to nurture and develop open source projects. “Open source technology is the backbone of many of Uber’s core services and as we continue to mature, these solutions will become ever more important,” he said in a blog post announcing the partnership.

What’s surprising is not that they joined, but that it took so long. Uber has been long known for making use of open source in its core tools working on over 320 open source projects and repositories from 1500 contributors involving over 70,000 commits, according to data provided by the company.

“Uber has made significant investments in shared software development and community collaboration through open source over the years, including contributing the popular open source project Jaeger, a distributed tracing system, to the Linux Foundation’s Cloud Native Computing Foundation in 2017,” an Uber spokesperson told TechCrunch.

Linux Foundation Executive Director Jim Zemlin was certainly happy to welcome Uber into the fold. “Their expertise will be instrumental for our projects as we continue to advance open solutions for cloud native technologies, deep learning, data visualization and other technologies that are critical to businesses today,” Zemlin said in a statement.

The Linux Foundation is an umbrella group supporting a myriad of open source projects and providing an organizational structure for companies like Uber to contribute and maintain open source projects. It houses sub-organizations like the Cloud Native Computing Foundation, Cloud Foundry Foundation, The Hyperledger Foundation and the Linux operating system, among others.

These open source projects provide a base on top of which contributing companies and the community of developers can add value if they wish and build a business. Others like Uber, which uses these technologies to fuel their backend systems won’t sell additional services, but can capitalize on the openness to help fuel their own requirements in the future, while also acting as a contributor to give as well as take.

 


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Offered is for future gen…
Peter Short

U.K. Push For Better Broadband For Startups
Verg Matthews
There has to an email option icon to send to the clowns in MTNL ... the govt of India's service pro…
Verg Matthews

CrunchWeek: Apple Makes Music, Oculus Aims For Mainstream, Twitter CEO Shakeup
Peter Short
Noted Google maybe grooming Twitter as a partner in Social Media but with whistle blowing coming to…
Peter Short

CrunchWeek: Apple Makes Music, Oculus Aims For Mainstream, Twitter CEO Shakeup
Peter Short
Noted Google maybe grooming Twitter as a partner in Social Media but with whistle blowing coming to…
Peter Short