This coming Friday night, I’ll be at the API Days conference in San Francisco to talk for a few minutes about my perspectives of the API economy. I am not a developer — just an observer — so my views are not deeply technical. That just means I have to ask more questions and talk to more people about APIs and what they represent.

But then I have to simmer it down, collect my thoughts, and then ask some more questions. Here are two themes I am picking up on from all these conversations.

Speed: APIs are making things faster. They connect apps. Software is eating the world. APIs connect the software so it can eat the world faster. Distribution is a driver of speed. The more distributed the API network, the better it can scale and the faster it can work to connect apps and create a mesh that is increasingly more effective than content-delivery networks.

An API distributed from a central point can slow things down considerably if the load increases on the server. API management companies are pushing APIs to the edge in order to manage the billions of calls that they get daily from service providers that connect the apps into websites, mobile devices, cars — you name it.

Data-intensive APIs are doing something else. They are slowing the network. To alleviate the issue, service providers are looking at the I/O, trying to find ways to make the data connect faster to the APIs that, in turn, connect the apps so someone can post a picture or get a text message about an update from a blog. It’s this need for speed that cloud services are built upon. Scale out the infrastructure and app developers will use it to get better performance and overall quality improvements. What’s still emerging are the advancements of the networks themselves. Again, that’s where software enters the picture and the further need for APIs. The infrastructure needs to be programmed. How that’s done is the big question.

Automation: Once one part of a system gets automated, the rest of it soon follows. APIs are the glue that makes the automation possible. People want to connect their apps. It’s why services like Zapier and IFTTT have gained such popularity.

People want to connect apps to get work done and reshape their reality. Chris Dancy uses IFTTT and Zapier to connect apps that feed into Google Calendar, Evernote and Excel. He uses these services to quantify his life. Through automation, Dancy can program himself and the things around him. He can connect his dog into the network and track its movement in the house.

In this new reality, everything becomes a node. You, me, the lamp post across the street all can have sensors and APIs to connect with other people and things. If this is the case, then the API economy is more about how this new network makes for different forms of commerce that maximize these connected, automated systems. The questions: What are these new forms of commerce? What are the infrastructure and systems needed for this new reality?

These are two themes in particular I look forward to discussing.

There’s a third but it’s an open-ended one that may be better off ruminating about in the hallways or over a beer. And that’s how this new idea about data and APIs is better understood by more than 1 percent of the people out there. It’s not just the geeks who should be able to live in the future but everyone else, too.

Article courtesy of TechCrunch

Kloudless launched at Disrupt NY 2013 today with its service for moving data from email to different cloud platforms through connectors which act like pipes that flow between the different services.

The service offers a plugin that the user installs in Outlook or as an extension through their web browser to use in Gmail or other apps, said CEO Eliot Sun. Kloudless does not store any data, nor files, the service sits in the middle, acting basically as just a pipeline.

When looking at Kloudless, think of services such as ifttt but with less automation and more ability to customize how data flows out of email and into other services. The idea is to give people more flexibility when moving data. It may be that you want some ways to customize the data when pulling into Salesforce.com or some other app. It pulls data on-demand from one cloud service to another. For example, Sun said it has the capability to pull in data points from an analytics tool to a discussion in a service such a Yammer.

Venture Capitalist Tim Draper and Yammer Co-Founder David Sacks liked the idea so much that they put a seed investment into the company. So far the company has raised $889,000. They believe that Kloudless can be a wedge in the market, offering the automation and the flexibility that companies need. Plus, it provides a level of data governance that can be developed with more customized solutions. There may be integrations that a company standardizes for reasons of compliance but also gives freedom in other ways that an automated system can’t offer.

Kloudless is, in technical parlance, a “message bus” for the cloud. The message bus is a permanent layer, an intricate event-based system — a middleware essentially. Every event, every request, goes through the message bus. The data gets normalized and sent to the right place, in the right context. Companies such as Tibco have made a fortune selling message bus technology.

Other companies like Tibco, Mulesoft and SnapLogic provide top down systems. Kloudless provides a bottom-up approach. It’s both a consumer type app and for managers, team leaders, and IT to provide dashboards for better visibility into data ownership/workflow and the ability to set cross-application policies.

Kloudless uses a consumer enterprise style pricing. It’s free with limited features. Pricing starts at $3 a month. It uses its foundation as an email platform to network. The idea is to build enough momentum so the person who makes the business decisions will see its value and buy it.

CEO Elliot Sun tells TechCrunch he had plans to develop a consumer app. They played with the idea of a cloud search engine, but it was a tough sell. The cross-file capability seemed like something that might be viable. He started talking about it at events around the Bay Area and some data architects with big companies took notice.

The Kloudless management team looks like a bunch of people assembled for a five-year high school reunion. But as Glide CEO Eli Rubel said to me last week in Portland in his youthful deadpan way: “Data does not lie.”

Article courtesy of TechCrunch

Here’s the thing about simplicity. It’s all relative. A developer’s idea of simplicity is different from a finance chief or a customer service agent.

I run across a variety of startups in my daily work at TechCrunch. But few have that innate sense of elegance or the capability to abstract complexity to such an extent that anything else seems antiquated in comparison. Here are 10 that turn traditional complex processes into simple ways to get work done. This is by no means a comprehensive list nor are these services necessarily market leaders. Instead it’s a snapshot of companies that embody what makes a great app or service and why they are so important as it becomes ever more necessary to get more done in less and less time.

CloudMunch

I thought a lot about simplicity at Cloud Connect this past week after a lunchtime chat with Pradeep Prabhu, CEO and Founder at CloudMunch. I had been skeptical of the CloudMunch service. It took me some time to understand how the company has automated the manual steps that developers have to take to get their apps ready to launch. CloudMunch offers what it calls a “GitHub to Cloud,” one-click functionality. Collaborating on code makes GitHub awesome but it’s a monstrous task when it comes to sharing code across multiple clouds. The company does this by offering a platform that allows for continuous delivery all in one SaaS app. It fixes a problem that nags at development teams. Code has to be continually tested, but in this new, distributed world, it’s a bit like herding cats. CloudMunch pulls it all together so developer teams can stay on track, do their test/development and deploy.

There is a complexity in managing code, Prabhu said in an interview last week. What works on one cloud may not work on another. The code also needs to work on multiple devices. CloudMunch simplifies the process through its continuous delivery platform. Code gets delivered, deployed and then managed through real-time analytics and monitoring.

GitHub

GitHub has simply changed the way developers work. Open-source projects now turn to GitHub for posting code. On GitHub you can copy someone’s code and fork it. To share the code, a developer can submit a pull request, asking if the code can be added to the original creator’s project. That user can then easily merge the changes. Through this process of forks, pull requests and merges, updates can be made faster than the old way of committing patches. As Klint Finley wrote last year:

These three features – fork, pull request and merge – are what make GitHub so powerful. Gregg Pollack of Code School (which just launched a class called TryGit) explains that before GitHub, if you wanted to contribute to an open source project you had to manually download the project’s source code, make your changes locally, create a list of changes called a “patch” and then e-mail the patch to the project’s maintainer. The maintainer would then have to evaluate this patch, possibly sent by a total stranger, and decide whether to merge the changes.

This is where the network effect starts to play a role in GitHub, Pollack explains. When you submit a pull request, the project’s maintainer can see your profile, which includes all of your contributions on GitHub. If your patch is accepted, you get credit on the original site, and it shows up in your profile. It’s like a resume that helps the maintainer determine your reputation. The more people and projects on GitHub, the better idea picture a project maintainer can get of potential contributors. Patches can also be publicly discussed.

GitHub abstracts the complexity of Git by turning it from a command-line tool to one with a web interface. Git, first developed by Linux Creator Linus Torvalds, has provided value to legions of developers. GitHub has made Git collaborative and an essential tool for developing apps in this increasingly distributed world.

Opscode and Puppet Labs

Opscode helps Facebook scale its infrastructure without deploying armies of IT employees. At Opscode’s heart is Chef, the cookbook of scripts that are used to automatically keep servers configured. Opscode simplifies how infrastructure is managed by automating the way machines interact. Puppet Labs IT automation software helps system administrators manage its infrastructure. It allows for the automation of repetitive tasks so administrators can deploy applications and manage change, scaling from tens of servers to thousands on-premise or in the cloud.

Without offerings from companies like Opscode and Puppet Labs, there is no way companies could manage the complexities that come with Internet scale services or massively virtualized operations.

New Relic

Last month, New Relic launched the capability to monitor mobile apps with the stated purpose of helping developers get better reviews on app stores. The service, New Relic for Mobile Apps, visualizes in realtime how an iOS or Android app is performing across services, such as Facebook, different operating systems and in the variety of ways an app can be affected as it is used. By tracking the interactions, a developer can see in realtime how the app is performing and react immediately to fix what is not working. Without this kind of monitoring, a developer will often have to wait for bad reviews to come in before making improvements. New Relic has created a service that gives developers a fast way to better their apps, allowing them to focus on what matters more than reacting to what people say.

Fancy Hands

Fancy Hands helps people get things done that they would normally have to hire someone to do or get done themselves. It now integrates with task-management and project-management tools: Basecamp, do.com, Asana and Evernote. This means you can automate your task-management service so Fancy Hands does the tasks for you. Awesome. Here’s how Fancy Hands is used by my good friend, Marshall Kirkpatrick, CEO of Little Bird:

It enables me to do things that I wouldn’t take the time to do. For example, we just found what I think is going to be our company’s new office and I’m going to ask Fancyhands to do a little research on the history of the building. I’ve been walking my dogs and listening to a podcast about something interesting, called Fancyhands to ask for additional background research and had a beautifully formatted collection of links to read in my inbox as soon as I got home. There’s something beautiful about taking a little bit of time to put a request into the system and seeing work that took more time that I invested come out the other side.

SiSense

We talk a lot about analytics but there are few services that make it as dead simple as SiSense. The platform is fast, has rich visualizations and is designed for the everyday user. Visual software tools will often integrate with expensive data-warehouse solutions that require expertise that most people don’t have. SiSense can process terabytes of data from a user’s laptop and present rich visualizations without any time-consuming integrations.

Spanning

Spanning makes it simple to back up Google Apps. Backup is not easy. Companies actually still use tape to back up their data. Spanning offers a one-click way to back up Google Apps in the original document format.

Pertino

Pertino has turned to AWS to offer companies a way to network their businesses without having to install expensive networking gear. The Pertino data plane routes internal employees or can be used to set up networks that companies can use to create micro-networks with customers. It’s managed through the company’s software defined networking (SDN) technology.

Here’s how I explained the SDN concept when I covered Pertino earlier this year:

SDN is the term for how software is abstracting and separating the elements of a network built on hardware. It symbolizes what is happening across the enterprise market. Software is replacing hardware as a means to deliver new services that are cheaper and better than what customers had the option to purchase. It’s similar to almost any market you can think of. You don’t have to go to the store anymore to rent a video. You can get it streamed over Netflix. The disc is becoming obsolete, as will, eventually, networking gear from any number of providers.

Pertino also shows the importance that AWS and other cloud services have for many startups. Pertino’s service would not be possible unless there were data centers around the world that it could leverage to offer its SDN offering.

2600hz

2600hz builds open-source software for developers to create services such as their own phone services or web apps. To do this on traditional telco infrastructure is pretty much impossible. But with data-center infrastructure, a telco or anyone else can use 2600hz to offer voice or text apps.

The telcos use 19th-century systems with a business model just as old. Make a call and the telco charges you by the minute. But with data as the core, the model is changing to one not as much measured by minutes used but usage of the data itself. With 2600hz, the software can run in any data center and so the customer can choose their own telco network. A company developing a private video network using 2600hz software may use an AT&T network in the United States and Vodafone in Germany.

2600hz makes it simpler to be a telco and act like one, too.

Conclusion

These services have a common underpinning. They all abstract complexity so customers can differentiate their businesses.  In years past, companies employed armies of IT professionals and consultants to manage heavy, custom solutions. These solutions allowed companies to grow in ways that were not possible when thousands of administrative and clerical people were needed to type letters or use calculators to crunch numbers.  That was a time when processes were heavier in human capital terms more than anything else. The business world transformed with the advent of enterprise technology but the weight had been transferred to IT. Today the weight is getting distributed to tens of thousands of servers, making the apps more lightweight and nimble. The weight is still there but just in distributed networks of horizontally scaled machines across data centers around the world. How this distributed weight is managed over the next ten years will define a new work world that we are just beginning to understand.

(Feature image source: Wikipedia)

Article courtesy of TechCrunch

AppDynamics has added a new capability to solve application issues without manual intervention.

Wit the new “Application Run Book Automation” offering, the customer pre-defines the conditions for the service to execute. For example, the user could indicate that if the server’s performance drops below a certain level, a “restart” will automatically occur. Notifications are via email or text.

The service can be set to automatically fix the following:

• Application Run Book Automation can be set to:
• Initiate a thread dump
• Restart a server
• Execute scripts from Chef or Puppet
• Run existing run books or scripts
• Create an incident/ticket in service management consoles such as Jira or ServiceNow
• Trigger PagerDuty workflows

According to AppDynamics, Application Run Book Automation unifies monitoring and management. It provides a way for operations and development teams to resolve problems. For example, issues such as thread dumps can be triggered automatically based on a series of pre-set conditions.

AppDynamics is in the increasingly competitive application performance management space where analytics is a core differentiator. AppDynamics uses byte-code instrumentation to map the topology of an application. This draws a “map” of the application that adjusts automatically with each code release. The effect is to eliminate the “black box” nature of an application and let the user see all dependencies and identify problems quickly.

New Relic uses analytics for its APM service and is expected to extend its capabilities as this sector of the development tool market gets increasingly competitive.

Article courtesy of TechCrunch

When co-founder and CEO Mikael Berner first showed me his app EasilyDo last year, he pitched it as a tool for increasing productivity and “making life simpler.” The company is taking another step in that direction today with the launch of the EasilyDo Builder.

The initial version of the app provided users with a list of basic tasks (pulled from their Facebook accounts, iPhone contact lists, and other accounts that they’ve connected) that they can accomplish within a couple of taps — things like wishing friends a happy birthday on Facebook or merging duplicate contacts in their address book. Berner said EasilyDo has already performed 750,000 actions for its users.

With the new Builder, users can customize the app to perform certain tasks automatically. I didn’t get to see the Builder in action, but Berner and his co-founder Hetal Pandya said the structure is pretty simple — you identify a trigger, and then the task that you want the app to perform when that trigger occurs. For example, you could tell the app to post a birthday message any time one of your Facebook friends has a birthday. Or you could tell it to alert you when you have to leave for a meeting.

The task can either occur automatically, or the app can ask you for approval first. And the creation of “Do Its” occurs on the EasilyDo website, but they work on the iPhone app.

Since many of EasilyDo’s tasks occur in a social context, I wondered whether some people might see the automation as distasteful. For example, I might be a little peeved if I found out that my friend sent me a birthday message on Facebook without writing a word himself, or even knowing that it was my birthday. Ultimately, Berner and Pandya said that sort of thing will be up to the individual users.

Berner also predicted that EasilyDo will follow “a Wikipedia sort of model,” meaning that most users won’t create Do Its themselves. However, there’s a small group of power users that will, and they can share their tasks with other users. You could also follow specific task makers, allowing you to check out any new Do Its they create and add the ones that you like to your own account.

Berner and Pandya are hoping to extend the platform even further by allowing developers to build their own tasks using the same basic model. To jump start those efforts, they’re holding a hackathon in Redwood City on March 15 and 16.

Article courtesy of TechCrunch

Just months after relocating from San Francisco to Detroit, Stik is relaunching its Facebook-powered recommendation service and announcing a new round of funding. The $2.3 million Series A round was co-led by Detroit Venture Partners and North Coast Technology Investors. Draper Associates, First Step Fund, MEDC and Automation Alley also participated in the round. Stik originally launched in 2010 on the back of a $500,000 seed round led by Draper Associates.

Co-founder Nathan Labenz explained to me that the new cash will go towards acquiring new talent. “We are hiring developers first and foremost, but also looking for great designers, product managers, community managers, and eventually salespeople — essentially the classic web startup profile.”

Ahead of this announcement, Stik relaunched with an overhaul of the website. “It’s a complete redesign and re-build of the front-end, complete with a deep Facebook timeline integration,” Labenz told TechCrunch, adding the whole service is now mobile friendly.

Despite the relaunch, the focus is still the same. Stik launched with the goal of bringing word-of-mouth referrals online and they tapped Facebook vast social graph to personalize the experience. Co-founder Nathan Labenz discovered while attending Harvard and running a business on the side that word of mouth referrals are very valuable. Together with Jay Gierak, a hometown friend from Detroit and Harvard classmate, the pair launched Stik in San Francisco in November 2010.

Stik made headlines in 2012 when the startup relocated from the Valley back to the founders’ home of Detroit. The young company quickly moved into the region’s startup epicenter of The M@dison Building, home of other startups, Detroit Venture Partners, and Bizdom.

“We thought there was a culture in Detroit where we could build a long-term company that was going to win,” co-founder Jay Gierak explained to me late last year. “Thus far it’s been true and we’ve hired terrific people who are motivated, talented, and skilled.”

“When we looked around Silicon Valley, we felt we couldn’t build a long-term company there because of the turnover – not only to get people in the door but retain them.” Jay stated, “It’s hard to compete with Facebook and Airbnb but also the YC’s of the world where there are people whispering in your ear to start a two-person app company.”

“We thought there was a culture in Detroit where we could build a long-term company that was going to win,” Stik co-founder Jay Gierak

Stik is committed to Detroit, and judging from the various Michigan funds which participated in the Series A, Michigan is committed to Sik as well. As mentioned above the round included North Coast Technology Investors, an early stage fund based  Ann Arbor, Michigan that seemingly focuses on technology-focused manufacturing and fabrication companies — you know, companies normally associated with the Midwest. And Detroit Venture Partners CEO and Manager Partner Josh Linkner is quickly becoming a major VC force in the Midwest (isn’t that right, UpTo?).

“We are thrilled to support the passionate and creative leaders of Stik. They have identified a very compelling void in the market, and we believe Stik will become the dominant source for professional referrals and own the category,” said Josh Linkner, CEO & Managing Partner at Detroit Venture Partners, in a released statement “The company’s momentum, combined with its leaders’ vision and focus, will ensure Stik becomes one of the most valuable and recognized platforms online.”

With the notable exception of Tim Draper’s Draper Associates, Stik tapped Michigan funds around metro Detroit for funding.  Local investors First Step Fund, MEDC and Automation Alley all participated in Stik’s funding as well, showing that despite headlines of physical and fiscal doom and gloom, Detroit is hungry for great ideas — and has the money to invest.

Article courtesy of TechCrunch

Puppet Labs, a data center automation company, is announcing today that virtualization giant (and previous investor) VMware has invested $30 million in the company. This brings the company’s total funding to $46 million. Puppet Labs’ other investors include True Ventures, Cisco, Google Ventures, Kleiner Perkins Caufield & Byers, and Radar Partners. The company declined to reveal the valuation in the round, but we hear it was a “healthy increase” from the last round in 2011.

Puppet Labs provides systems management and datacenter automation software for the enterprise and the cloud. Puppet Labs’ flagship product, Puppet is an open source data center automation and configuration management framework that provides system administrators with an easy to use platform for transparent and flexible systems management.

The company also offers Puppet Enterprise, a commercial version of Puppet that makes the provisioning, configuring, and managing of virtualized and cloud infrastructure easier for system administrators. Customers include Zynga, Twitter, NYSE, Disney, Citrix, Oracle/Sun, Constant Contact, Match.com, Shopzilla, Los Alamos National Laboratory, and Stanford University. Puppet Labs also acquired the Mcollective, a framework to build server orchestration or parallel job execution systems.

Considering that VMware offers data center virtualization services, the relationship between the enterprise giant and Puppet Labs makes sense. In addition to the funding, the companies agreed to a strategic partnership for delivering IT management solutions that will enable customers to reap the benefits of virtualization and cloud in heterogeneous, multi-vendor IT environments. The company will be working jointly with VMware to deliver, market and sell its solutions, as well as VMware’s offerings.

Puppet Labs’ CEO and founder Luke Kanies says that clients are already using products like Puppet Enterprise with VMware’s vSphere® API. Additionally customers use the integration of VMware vFabric Application Director with Puppet to provision private cloud services. As part of the strategic partnership, going forward VMware and Puppet Labs will collaborate on additional product integrations, including VMware vCloud Automation Center, VMware vCenter Operations Manager, and VMware vCenter Configuration Manager.

“Puppet Labs is at the forefront of IT automation, and is a catalyst in the DevOps movement – accelerating service delivery and business agility” said Ramin Sayar, Vice President and General Manager, Virtualization & Cloud Management, VMware. “This strategic investment and partnership will further accelerate the software-defined data center, and will allow a more extensive automation and orchestration solution across infrastructure and application elements for VMware-based private and public clouds, physical infrastructures, OpenStack and Amazon Web Services.”

Kanies, founder and CEO of Puppet Labs, says that the company has seen 3 and a half million downloads of its software in the past year. He explains that the time is right for Puppet Labs’ offering to bring SaaS into the data center. “There’s a demand for speed and IT teams need to ship products in hours or weeks, and we’re making sure customers have the technology in place to satisfy these needs,” he explains.

He adds that Puppet Labs is putting the new funding into product development as well as sales and marketing efforts.

Article courtesy of TechCrunch

Founded in 2008 after more than a decade of research at Stanford, Silicon Valley-based startup, Ayasdi, is on a mission to reinvent the methods by which we transform Big Data into actionable knowledge. Essentially, Ayasdi aims to automate the insight discovery process, allowing end users to find valuable intelligence within massive datasets almost instantaneously. Backed by the Defense Advanced Research Projects Agency (DARPA) and the National Science Foundation, the startup’s novel synthesis of machine learning and data analysis technologies has not gone unnoticed by investors.

Today, the startup announced that it has raised $10 million in series A financing, led by Khosla Ventures and Floodgate. The new round brings the startup’s total funding to $13.25 million, which includes contributions both from its current investors as well as angel investors like Michael Ovitz, Steve Blank and The Data Collective’s Matt Ocko, to name a few.

The investment comes at a time when venture capital is beginning to shift from consumer businesses to the enterprise, as investors look to capitalize on the rise of the big data app and the growing demand for a new data infrastructure.

In fact, Research firm IDC recently predicted that the Big Data market is poised for exponential growth over the next few years, with total revenue projected to reach $24 billion by 2016. What’s more, following Derrick Harris’ logic, if one includes analytics software (arguably an essential segment of the Big Data market) in that definition, then the total is actually upwards of $75 billion.

Yet, in spite of this enormous new market opportunity, the emergence of Big Data doesn’t necessarily directly translate into a net positive for business, humankind, etc. In other words, people tend to conflate information and data, such that we end up believing that more data inherently means (proportionately) more information, which in turn means (proportionately) more intelligence, insight and value. However, as Dr. Michael Wu points out, it’s quite literally the opposite: “The more data you have, the less information you gain as a proportion of the data.”

The true value of Big Data is derived from the insights hidden within, yet, while all insights are information, not all information produces insight. Big Data is comprised of enormous amounts of unstructured data, a wide array of data types and media, but the amount of insight that can be extracted from that data is proportionately tiny.

Big Data continues to grow, yet, while governments, businesses and scientists have spent years (and millions of dollars) attempting to address the world’s biggest problems by analyzing Big Data, progress has been incremental. Although Big Data tools have improved over time, Ayasdi is of the mindset that they are still failing to yield the kind of breakthrough insights that lead to true innovation.

The Ayasdi co-founders attribute this to the prevailing reliance among data scientists on old models — finding insights by asking questions and writing queries. The problem with this is that queries are inherently based on human assumptions and biases, and, in turn, query results tend to only reveal slices of data, rather than providing visibility into the relationships between similar groups of data. This method of discovering insight in Big Data tends to be rely heavily on iterative guesswork and chance, and thus takes time to produce real results.

To address this problem, Ayasdi is today officially launching its cloud-based insight discovery platform, which aims to deliver insight derived from massive datasets quickly, without relying on queries. The machine learning platform combines computer science with a branch of mathematics called “Topological Data Analysis,” which allows Ayasdi to visualize entire datasets at once.

The startup’s platform uses hundreds of machine learning algorithms to explore these complex datasets — the goal being the automatic discovery of insights that could not be discovered through ad hoc or query-based methods. The platform, which is designed for domain experts, data scientists and researchers, requires no coding or modeling and offers the kind of scalability that more demanding processing requires. It also is built to complement other Big Data solutions companies might already be using and is able to work with datasets of any size or type, the co-founders tell us.

The startup is currently working with enterprise customers in financial services, life sciences, oil and gas and the public sector, with these companies employing its platform to help discover new drugs, for example, improve cancer therapy by discovering new insights from an 11-year old breast cancer dataset that included new sub-populations of breast cancer survivors, for example. It’s also being used to explore new energy sources, identifying patterns that can lead to more accurate drilling, predict fraud and help prevent terrorist attacks.

“The answers to today’s most important scientific, business and social problems lie in data,” saus Ayasdi CEO Gurjeet Singh. “The biggest challenge in Big Data today is asking the right questions of data, so the real opportunity in Big Data lies in the automation of insight discovery — regardless of the complexity of that data — without requiring users to ask questions. The goal is for Ayasdi to provide users with answers to questions that they didn’t know to ask in the first place.”

Article courtesy of TechCrunch

The Playsurface, a spin-off project from Templeman Automation that aims to provide a low-cost alternative to interactive touch table devices like Microsoft’s PixelSense (formerly known as the surface), was at CES showing off their functioning units in action, which the company will be shipping out to 40 or so Kickstarter backers this month. The Playsurface made headlines when it launched on Kickstarter back in May, reaching almost double its $40,000 funding goal.

Playsurface’s goal, unlike a lot of the large-sized shared touchscreen surfaces we’ve seen, is to be as affordable  open and hackable as possible, with the aim of being a legitimate option for use in education even in situations where budget might otherwise prohibit the use of such technologies. Templeman Automation teamed up with Tufts University to help boost its education mission, and target applications for schools and students more effectively. To help with that goal, they’re looking into just what kind of “smart tangible” accessories  like the one that replicates an X-ray/microscope device seen in the video, would be most useful to K-12 educators. These accessories could be what turns the Playsurface from a great tech demo into a genuinely useful and widely used way for schools all around the world to replace not just computing devices, but a variety of expensive and hard to source teaching objects that might not otherwise be an option.

Just under $3,000, goal is to get it under $1,000 and TA believes that’s entirely possible, thanks to improvements in manufacturing efficiencies and materials. The Playsurface is available for general pre-order now, with shipments to retail customers ready to begin after the first devices roll out to the company’s Kickstarter supporters.

Article courtesy of TechCrunch

Apple, Microsoft and Google may all be vying for the attention of a single startup, according to a new report yesterday from The Wall Street Journal. That startup is id8 Group R2 Studios Inc., a company with a rather obtuse name that flies primarily under the radar, tackling home automation software for mobile devices. So why are the biggest sharks in the tech industry circling R2 Studios right now? Because after building location, social and intelligent assistant features into gadgets powered by mobile operating systems like Android and iOS, home automation is the next big opportunity to add yet another layer of use value to portable devices.

R2′s first project is an Android app that allows users to control their heating and lighting systems via their smartphone devices. The company, founded by Blake Krikorian who previously founded the Slingbox, also holds some patents related to control of electronic devices and control interfaces. Apple, Google and Microsoft are all very much interested in making connections between mobile tech and the traditional household entertainment hub, the living room, and have all introduced technology to prove it. Apple’s AirPlay and Apple TV, for instance; Google’s TV efforts, Nexus Q (which, while shelved, showed its interest in this at least) and media streaming in Android 4.2; and Microsoft’s Xbox/Windows 8/Windows Phone 8 home media integration services all reflect this trend.

The talks between R2 and these coompanies are still in very early stages, WSJ reports, but all of the big three are already thinking about ways to tap into the living room, and the next logical step goes beyond just the confines of media and entertainment. Already, both Google and Apple at least are also taking steps to make their mobile devices more full-featured personal assistants: Apple with Siri and Google with Google Now. But why limit these to just finding good restaurants nearby or serving local movie show times or box scores from the baseball game? Why not have the phone use all of its contextual information to also help with home automation, but in a way that makes those features tied to the OS as a service layer, rather than something people need dedicated apps to handle?

The paradigm here is the same as it was for streaming media: it makes much more sense for Apple to build AirPlay and have it work across its lineup of devices, independent of individual media app settings, than to let each content source try to table their own solution. Likewise, a home automation control system that you can then make available to hardware makers (as Apple has done with AirPlay) to make sure they work with iOS (or Android, or whoever ends up going forward with this first) devices out of the box makes more sense, and will engender greater general adoption, than relying on manufacturer-specific solutions.

We’ve got Nest, Philips Hue and the new Lumawake as jus a few recent high-profile examples of how home automation is getting smarter and better than the basic, smartphone-connected remotes of the past. Devices like these would all benefit from having access to a user’s smartphone that goes beyond communicating with a specific app, and gets into mining contextual information about a user to truly inform their automation patterns. Google, Apple and Microsoft could just continue to let home automation remain the province of third parties, but they’d be leaving a lot on the table in terms of added value for their users, especially now that we seem to be approaching a turning point for broader mass adoption of this kind of tech.

Article courtesy of TechCrunch