Posted On:December 2016 - AppFerret
Amazon’s Alexa is one of the most popular V.A. and connected home hubs out there.
Amazon Echo and Dot, the main Alexa-enabled devices, are so popular, that they are almost impossible to get online. Even Amazon’s spokesperson recommends that if you happen to see one for sale – grab it right away.
There’s no doubt that the secret to Amazon’s device’s success is in its connected-home system, Alexa.
To get the most out of your Alexa device, you can either enable 3rd party skills from the Amazon Alexa store (like News Feed, for example), but you can also use its built in skills that come natively with the device.
But wait, there’s more.
In addition to the popular uses and familiar skills, there are a bunch of hidden invocations and not-so-well-known questions you can ask it – and get great answers on.
We’ve collected 124 Amazon Alexa must-know voice commands that you might not know of.
Some will make you more productive.
Some will make you laugh.
Some will get you playing with your Echo all day long.
In any case, you’ve got a long day ahead of you.
So go ahead and dive into the 124 Alexa commands.
Original article here.
The end of year or beginning of year is always a time when we see many predictions and forecasts for the year ahead. We often publish a selection of these to show how tech-based innovation and economic development will be impacted by the major trends.
A number of trends reports and articles have bene published – ranging from investment houses, to research firms, and even innovation agencies. In this article we present headlines and highlights of some of these trends – from Gartner, GP Bullhound, Nesta and Ovum.
Artificial intelligence will have the greatest impact
GP Bullhound released its 52-page research report, Technology Predictions 2017, which says artificial intelligence (AI) is poised to have the greatest impact on the global technology sector. It will experience widespread consumer adoption, particularly as virtual personal assistants such as Apple Siri and Amazon Alexa grow in popularity as well as automation of repetitive data-driven tasks within enterprises.
Online streaming and e-sports are also significant market opportunities in 2017 and there will be a marked growth in the development of content for VR/AR platforms. Meanwhile, automated vehicles and fintech will pose longer-term growth prospects for investors.
The report also examines the growth of Europe’s unicorn companies. It highlights the potential for several firms to reach a $10 billion valuation and become ‘decacorns’, including BlaBlaCar, Farfetch, and HelloFresh.
Alec Dafferner, partner, GP Bullhound, commented, “The technology sector has faced up to significant challenges in 2016, from political instability through to greater scrutiny of unicorns. This resilience and the continued growth of the industry demonstrate that there remain vast opportunities for investors and entrepreneurs.”
Big data and machine learning will be disruptors
Advisory firm Ovum says big data continues to be the fastest-growing segment of the information management software market. It estimates the big data market will grow from $1.7bn in 2016 to $9.4bn by 2020, comprising 10 percent of the overall market for information management tooling. Its 2017 Trends to Watch: Big Data report highlights that while the breakout use case for big data in 2017 will be streaming, machine learning will be the factor that disrupts the landscape the most.
Key 2017 trends:
- Machine learning will be the biggest disruptor for big data analytics in 2017.
- Making data science a team sport will become a top priority.
- IoT use cases will push real-time streaming analytics to the front burner.
- The cloud will sharpen Hadoop-Spark ‘co-opetition’.
- Security and data preparation will drive data lake governance.
Intelligence, digital and mesh
In October, Gartner issued its top 10 strategic technology trends for 2017, and recently outlined the key themes – intelligent, digital, and mesh – in a webinar. It said that autonomous cars and drone transport will have growing importance in the year ahead, alongside VR and AR.
“It’s not about just the IoT, wearables, mobile devices, or PCs. It’s about all of that together,” said Cearley, according to hiddenwires magazine. “We need to put the person at the canter. Ask yourself what devices and service capabilities do they have available to them,” said David Cearley, vice president and Gartner fellow, on how ‘intelligence everywhere’ will put the consumer in charge.
“We need to then look at how you can deliver capabilities across multiple devices to deliver value. We want systems that shift from people adapting to technology to having technology and applications adapt to people. Instead of using forms or screens, I tell the chatbot what I want to do. It’s up to the intelligence built into that system to figure out how to execute that.”
Gartner’s view is that the following will be the key trends for 2017:
- Artificial intelligence (AI) and machine learning: systems that learn, predict, adapt and potentially operate autonomously.
- Intelligent apps: using AI, there will be three areas of focus — advanced analytics, AI-powered and increasingly autonomous business processes and AI-powered immersive, conversational and continuous interfaces.
- Intelligent things, as they evolve, will shift from stand-alone IoT devices to a collaborative model in which intelligent things communicate with one another and act in concert to accomplish tasks.
- Virtual and augmented reality: VR can be used for training scenarios and remote experiences. AR will enable businesses to overlay graphics onto real-world objects, such as hidden wires on the image of a wall.
- Digital twins of physical assets combined with digital representations of facilities and environments as well as people, businesses and processes will enable an increasingly detailed digital representation of the real world for simulation, analysis and control.
- Blockchain and distributed-ledger concepts are gaining traction because they hold the promise of transforming industry operating models in industries such as music distribution, identify verification and title registry.
- Conversational systems will shift from a model where people adapt to computers to one where the computer ‘hears’ and adapts to a person’s desired outcome.
- Mesh and app service architecture is a multichannel solution architecture that leverages cloud and serverless computing, containers and microservices as well as APIs (application programming interfaces) and events to deliver modular, flexible and dynamic solutions.
- Digital technology platforms: every organization will have some mix of five digital technology platforms: Information systems, customer experience, analytics and intelligence, the internet of things and business ecosystems.
- Adaptive security architecture: multilayered security and use of user and entity behavior analytics will become a requirement for virtually every enterprise.
The real-world vision of these tech trends
UK innovation agency Nesta also offers a vision for the year ahead, a mix of the plausible and the more aspirational, based on real-world examples of areas that will be impacted by these tech trends:
- Computer says no: the backlash: the next big technological controversy will be about algorithms and machine learning, which increasingly make decisions that affect our daily lives; in the coming year, the backlash against algorithmic decisions will begin in earnest, with technologists being forced to confront the effects of aspects like fake news, or other events caused directly or indirectly by the results of these algorithms.
- The Splinternet: 2016’s seismic political events and the growth of domestic and geopolitical tensions, means governments will become wary of the internet’s influence, and countries around the world could pull the plug on the open, global internet.
- A new artistic approach to virtual reality: as artists blur the boundaries between real and virtual, the way we create and consume art will be transformed.
- Blockchain powers a personal data revolution: there is growing unease at the way many companies like Amazon, Facebook and Google require or encourage users to give up significant control of their personal information; 2017 will be the year when the blockchain-based hardware, software and business models that offer a viable alternative reach maturity, ensuring that it is not just companies but individuals who can get real value from their personal data.
- Next generation social movements for health: we’ll see more people uniting to fight for better health and care, enabled by digital technology, and potentially leading to stronger engagement with the system; technology will also help new social movements to easily share skills, advice and ideas, building on models like Crohnology where people with Crohn’s disease can connect around the world to develop evidence bases and take charge of their own health.
- Vegetarian food gets bloodthirsty: the past few years have seen growing demand for plant-based food to mimic meat; the rising cost of meat production (expected to hit $5.2 billion by 2020) will drive kitchens and laboratories around the world to create a new wave of ‘plant butchers, who develop vegan-friendly meat substitutes that would fool even the most hardened carnivore.
- Lifelong learners: adult education will move from the bottom to the top of the policy agenda, driven by the winds of automation eliminating many jobs from manufacturing to services and the professions; adult skills will be the keyword.
- Classroom conundrums, tackled together: there will be a future-focused rethink of mainstream education, with collaborative problem solving skills leading the charge, in order to develop skills beyond just coding – such as creativity, dexterity and social intelligence, and the ability to solve non-routine problems.
- The rise of the armchair volunteer: volunteering from home will become just like working from home, and we’ll even start ‘donating’ some of our everyday data to citizen science to improve society as well; an example of this trend was when British Red Cross volunteers created maps of the Ebola crisis in remote locations from home.
It’s clear that there is an expectation that the use of artificial intelligence and machine learning platforms will proliferate in 2017 across multiple business, social and government spheres. This will be supported with advanced tools and capabilities like virtual reality and augmented reality. Together, there will be more networks of connected devices, hardware, and data sets to enable collaborative efforts in areas ranging from health to education and charity. The Nesta report also suggests that there could be a reality check, with a possible backlash against the open internet and the widespread use of personal data.
Original article here.
Looking back is more than nostalgia. It helps us see what has changed and what hasn’t, and where we might improve. 2016 has been a momentus year for storage. Here are the top stories.
LEGACY VENDORS AND THE CLOUD
The cloud has devastated revenue, growth and margins of legacy vendors. Any CFO can look online to see what similar capacity, performance, and higher availability costs compared to the huge capital costs of traditional RAID arrays.
2016 saw the world’s largest independent storage company — EMC — bought by Dell, after shopping itself to all the big system vendors. The $60 billion price tag was excessive given the rapid obsolescence of much of EMC’s intellectual property, but a worthy capstone to CEO Joe Tucci’s brilliant leadership of the storage giant.
Tucci saw what many other CEOs denied, which is that the scale-out commodity-based storage systems and the internalization of storage have forever changed the storage industry. EMC needed a system partner to leverage their storage expertise, and Dell needed a robust enterprise sales force.
NetApp acquired SolidFire, a promising flash array vendor, that finally got them into the highest growth area of legacy storage. Plagued by years of flash misfires and infighting, NetApp has done well in the new market, but has had to lay off thousands of employees.
NetApp is touting their integration with Amazon Web Services — cloud — but that is a rear guard action as cloud vendors gobble up more enterprise dollars. Their next big problem: object storage systems are getting faster, offer much better data protection, are much more scalable, and more cost-effective than NetApp’s flagship NAS boxes. I hope their CEO, George Kurian, recognizes the threat and acts decisively in 2017.
LEGACY VENDORS AND THE UPSTARTS
Legacy vendors are getting squeezed between the cloud and aggressive storage startups. Companies like Nimble Storage, Nutanix, and Pure Storage offer modern architectures that leave the RAID paradigm in the dust. All three had successful IPOs, and now have the money to bring the fight to the legacy vendors.
Other startups have been acquired by legacy vendors to remake their products lines. DSSD, supported by Silicon Valley legend Andreas Bechtolsheim, was bought by EMC a couple of years ago. NetApp acquired SolidFire this year. HGST acquired Amplidata last year and are making a solid play for the active archive market. The storage startup scene continues to boil.
NVRAM is the Next Big Thing for servers and notebooks, as support from Intel and Microsoft shows. Some versions — there are around 10 — are almost as fast as DRAM, but use much less power and are much denser. Terabyte DIMMs, anyone? Big Data will especially benefit from high capacity NVRAM equipped servers.
2016 was supposed to be the year that Intel introduced their NVRAM 3D XPoint Optane drives, but like many ambitious engineering projects, they’ve slipped into 2017, and may be one reason the recent MacBook Pro’s were delayed. But Intel isn’t the only player, and certainly isn’t the first to market.
MRAM vendor Everspin IPO’d this year, raising funds needed to further enhance their NVRAM line. Nantero licensed their NVRAM to a couple of major fabs, putting their carbon nanotube technology on the fast track.
I’ve been a happy Thunderbolt 1 user for years. It’s a great technology that is fast, stable, and low-cost.
2016 saw it get even better, now that one Thunderbolt 3 connector supports 40 Gbit/s bandwidth with half the power consumption of Thunderbolt 2. That’s enough bandwidth to drive dual 4k displays at 60 Hz, PCIe 3.0, HDMI 2.0, DisplayPort 1.2, as well as 10 Gbit/s USB 3.1. Plus to to 100 watts of power to charge systems and up to 15W for bus-powered devices.
Using newly available and cheap PCIe switches, Thunderbolt 3 can be stretched to build large clusters at low prices. We’ll see more of that in 2017. On notebooks it offers performance and connectivity undreamed of 10 years ago. External drives with gigabyte per second performance are already here, with more on the way.
THE STORAGE BITS TAKE
I’ve been involved with storage for over 35 years, starting when a disk drive cost $40 a megabyte. For the last 15 years the industry has been on an innovation spree that has upended many companies and delivered incredible capabilities.
Storage is the basis of our digital world. Given the crisis of a post-fact world, I take comfort in the fact that a $100 billion plus industry is working hard to store and protect the data that is critical to the challenges humanity faces.
Original article here.
Bayesian Inference is a way of combining information from data with things we think we already know. For example, if we wanted to get an estimate of the mean height of people, we could use our prior knowledge that people are generally between 5 and 6 feet tall to inform the results from the data we collect. If our prior is informative and we don’t have much data, this will help us to get a better estimate. If we have a lot of data, even if the prior is wrong (say, our population is NBA players), the prior won’t change the estimate much. You might say that including such “subjective” information in a statistical model isn’t right, but there’s subjectivity in the selection of any statistical model. Bayesian Inference makes that subjectivity explicit.
Bayesian Inference can seem complicated, but as Brandon Rohrer explains, it’s based on straighforward principles of conditional probability. Watch his video below for an elegant explanation of the basics.
Original article here.
Bridgewater Associates has a team of engineers working on a project to automate decision-making to save time and eliminate human emotional volatility
The world’s largest hedge fund is building a piece of software to automate the day-to-day management of the firm, including hiring, firing and other strategic decision-making.
Bridgewater Associates has a team of software engineers working on the project at the request of billionaire founder Ray Dalio, who wants to ensure the company can run according to his vision even when he’s not there, the Wall Street Journal reported.
“The role of many remaining humans at the firm wouldn’t be to make individual choices but to design the criteria by which the system makes decisions, intervening when something isn’t working,” wrote the Journal, which spoke to five former and current employees.
The firm, which manages $160bn, created the team of programmers specializing in analytics and artificial intelligence, dubbed the Systematized Intelligence Lab, in early 2015. The unit is headed up by David Ferrucci, who previously led IBM’s development of Watson, the supercomputer that beat humans at Jeopardy! in 2011.
The company is already highly data-driven, with meetings recorded and staff asked to grade each other throughout the day using a ratings system called “dots”. The Systematized Intelligence Lab has built a tool that incorporates these ratings into “Baseball Cards” that show employees’ strengths and weaknesses. Another app, dubbed The Contract, gets staff to set goals they want to achieve and then tracks how effectively they follow through.
These tools are early applications of PriOS, the over-arching management software that Dalio wants to make three-quarters of all management decisions within five years. The kinds of decisions PriOS could make include finding the right staff for particular job openings and ranking opposing perspectives from multiple team members when there’s a disagreement about how to proceed.
The machine will make the decisions, according to a set of principles laid out by Dalio about the company vision.
“It’s ambitious, but it’s not unreasonable,” said Devin Fidler, research director at the Institute For The Future, who has built a prototype management system called iCEO. “A lot of management is basically information work, the sort of thing that software can get very good at.”
Automated decision-making is appealing to businesses as it can save time and eliminate human emotional volatility.
“People have a bad day and it then colors their perception of the world and they make different decisions. In a hedge fund that’s a big deal,” he added.
Will people happily accept orders from a robotic manager? Fidler isn’t so sure. “People tend not to accept a message delivered by a machine,” he said, pointing to the need for a human interface.
“In companies that are really good at data analytics very often the decision is made by a statistical algorithm but the decision is conveyed by somebody who can put it in an emotional context,” he explained.
Futurist Zoltan Istvan, founder of the Transhumanist party, disagrees. “People will follow the will and statistical might of machines,” he said, pointing out that people already outsource way-finding to GPS or the flying of planes to autopilot.
However, the period in which people will need to interact with a robot manager will be brief.
“Soon there just won’t be any reason to keep us around,” Istvan said. “Sure, humans can fix problems, but machines in a few years time will be able to fix those problems even better.
“Bankers will become dinosaurs.”
It’s not just the banking sector that will be affected. According to a report by Accenture, artificial intelligence will free people from the drudgery of administrative tasks in many industries. The company surveyed 1,770 managers across 14 countries to find out how artificial intelligence would impact their jobs.
“AI will ultimately prove to be cheaper, more efficient, and potentially more impartial in its actions than human beings,” said the authors writing up the results of the survey in Harvard Business Review.
However, they didn’t think there was too much cause for concern. “It just means that their jobs will change to focus on things only humans can do.”
The authors say that machines would be better at administrative tasks like writing earnings reports and tracking schedules and resources while humans would be better at developing messages to inspire the workforce and drafting strategy.
Fidler disagrees. “There’s no reason to believe that a lot of what we think of as strategic work or even creative work can’t be substantially overtaken by software.”
However, he said, that software will need some direction. “It needs human decision making to set objectives.”
Bridgewater Associates did not respond to a request for comment.
Original article here.
You don’t need Sherlock Holmes to tell you that cloud computing is on the rise, and that cloud traffic keeps going up. However, it is enlightening to see the degree by which it is increasing, which is, in essence, about to quadruple in the next few years. By that time, 92% percent of workloads will be processed by cloud data centers; versus only eight percent being processed by traditional data centers.
Cisco, which does a decent job of measuring such things, just released estimates that shows cloud traffic likely to rise 3.7-fold by 2020, increasing 3.9 zettabytes (ZB) per year in 2015 (the latest full year data for which data is available) to 14.1 ZB per year by 2020.
The big data and associated Internet of Things are a big part of this growth, the study’s authors state. By 2020, database, analytics and IoT workloads will account for 22% of total business workloads, compared to 20% in 2015. The total volume of data generated by IoT will reach 600 ZB per year by 2020, 275 times higher than projected traffic going from data centers to end users/devices (2.2 ZB); 39 times higher than total projected data center traffic (15.3 ZB).
Public cloud is growing faster than private cloud growth, the survey also finds. By 2020, 68% (298 million) of the cloud workloads will be in public cloud data centers, up from 49% (66.3 million) in 2015. During the same time period, 32% (142 million) of the cloud workloads will be in private cloud data centers, down from 51% (69.7 million) in 2015.
As the Cisco team explains it, much of the shift to public cloud will likely be part of hybrid cloud strategies. For example, “cloud bursting is an example of hybrid cloud where daily computing requirements are handled by a private cloud, but for sudden spurts of demand the additional traffic demand — bursting — is handled by a public cloud.”
The Cisco estimates also show that while Software as a Service (SaaS, for online applications) will keep soaring, there will be less interest in Infrastructure as a Service (IaaS, for online servers, capacity, storage). By 2020, 74% of the total cloud workloads will be software-as-a-service (SaaS) workloads, up from 65% at this time. Platform as a Service (PaaS, for development tools, databases, middleware) also will see a boost — eight percent of the total cloud workloads will be PaaS workloads, down from nine percent in 2015. However, IaaS workloads will total 17% of the total cloud workloads, down from 26%.
The Cisco analysts explain that the lower percentage growth for IaaS may be attributable to the growing shift away from private cloud to public cloud providers. For starters, IaaS was far less disruptive to the business — a rearrangement of data center resources, if you will. As SaaS offerings gain in sophistication, those providers may offer IaaS support behind the scenes. “In the private cloud, initial deployments were predominantly IaaS. Test and development types of cloud services were the first to be used in the enterprise; cloud was a radical change in deploying IT services, and this use was a safe and practical initial use of private cloud for enterprises. It was limited, and it did not pose a risk of disrupting the workings of IT resources in the enterprise. As trust in adoption of SaaS or mission-critical applications builds over time with technology enablement in processing power, storage advancements, memory advancements, and networking advancements, we foresee the adoption of SaaS type applications to accelerate over the forecast period, while shares of IaaS and PaaS workloads decline.”
On the consumer side, video and social networking will lead the increase in consumer workloads. By 2020, consumer cloud storage traffic per user will be 1.7 GB per month, compared to 513 MB per month in 2015. By 2020, video streaming workloads will account for 34% of total consumer workloads, compared to 29% in 2015. Social networking workloads will account for 24% of total consumer workloads, up from 20 percent in 2015. In the next four years, 59% (2.3 billion users) of the consumer Internet population will use personal cloud storage up from 47% (1.3 billion users) in 2015.
Original article here.
At the AWS re:Invent event, Amazon has announced a host of new services that highlight its commitment to enterprises. Andy Jassy, CEO of AWS, emphasized on the innovation in the areas of artificial intelligence, analytics, and hybrid cloud.
Amazon has been using deep learning and artificial intelligence in its retail business for enhancing the customer experience. The company claims that it has thousands of engineers working on artificial intelligence to improve search and discovery, fulfillment and logistics, product recommendations, and inventory management. Amazon is now bringing the same expertise to the cloud to expose the APIs that developers can consume to build intelligent applications. Dubbed as Amazon AI, the new service offers powerful AI capabilities such as image analysis, text to speech conversion, and natural language processing.
Amazon Rekognition is the rich image analysis service that can identify various attributes of an image. Amazon Polly is a service that accepts text or a string and returns an MP3 audio file containing the speech. With support for 47 different voices in 23 different languages, the service exposes rich cognitive speech capabilities. Amazon Lex is the new service for natural language processing and automatic speech recognition. It is the same service that powers Alexa and Amazon Echo. The service converts text or voice to a set of actions that developers can parse to perform a set of actions.
Amazon is also investing in MXNet, a deep learning framework that can run in a variety of environments. Apart from this, Amazon is also optimizing EC2 images to run popular deep learning frameworks including CNTK, TensorFlow, and Theano.
In the last decade, Amazon has added many services and features to its platform. While customers appreciate the pace of innovation, first-time users often complain about the overwhelming number of options and choices. Even to launch a simple virtual machine that runs a blog or a development environment in EC2, users may have to choose from a variety of options. To simplify the experience of launching non-mission critical workloads in EC2, AWS has announced a new service called Amazon Lightsail. Customers can launch a VM with just a few clicks without worrying about the complex choices that they need to make. When they get familiar with EC2, they can start integrating with other services such as EBS and Elastic IP. Starting at $5 a month, this is the cheapest compute service available in AWS. Amazon calls Lightsail as the express mode for EC2 as dramatically reduces the launch time of a VM.
Amazon Lightsail competes with the VPS providers such as DigitalOcean and Linode. The sweet spot of these vendors has been developers and non-technical users who need a virtual private server to run a workload in the cloud. With Amazon Lightsail, AWS wants to attract developers, small and medium businesses, and digital agencies that typically use a VPS service for their needs.
On the analytics front, Amazon is adding a new interactive, serverless query service called Amazon Athena that can be used to retrieve data stored in Amazon S3. The service supports complex SQL queries including joins to return data from Amazon S3. Customers can use custom metadata to perform complex queries. Amazon Athena’s pricing is based on per query model.
Last month, AWS and VMware partnered to bring hybrid cloud capabilities to customers. With this, customers can run and manage workloads in the cloud, seamlessly from existing VMware tools.
Amazon claims that the customers will be able to use VMware’s virtualization and management software to seamlessly deploy and manage VMware workloads across all of their on-premises and AWS environments. This offering allows customers to leverage their existing investments in VMware skills and tooling to take advantage of the flexibility of the AWS Cloud.
Pat Gelsinger, CEO of VMware was on stage with Andy Jassy talking about the value that this partnership brings to customers.
In a surprising move, Amazon is making its serverless computing framework, AWS Lambda available outside of its cloud environment. Extending Lambda to connected devices, AWS has announced AWS Greengrass – an embedded Lambda compute environment that can be installed in IoT devices and hubs. It delivers local compute, storage, and messaging infrastructure in environments that demand offline access. Developers can use the simple Lambda programming model to develop applications for both offline and online scenarios. Amazon Greengrass Core is designed to run on hub and gateways while Greengrass runtime will power low-end, resource-constrained devices.
Extending the hybrid scenarios to industrial IoT, Amazon has also announced a new appliance called Snowball Edge that runs Greengrass Core. This appliance is expected to be deployed in environments that generate extensive offline data. It exposes an S3-compatible endpoint for developers to use the same ingestion API as the cloud. Since the device runs Lambda, developers can create functions that respond to events locally. Amazon Snowball Edge ships with 100TB capacity, hi-speed Ethernet Wi-Fi, and 3G cellular connectivity. When the ingestion process is completed, customers can send the appliance to AWS for uploading the data.
Pushing the limits of data migration to the cloud, Amazon is also launching a specialized truck called AWS Snowmobile that can move Exabytes of data to AWS. The truck carries a 48-foot long container that can hold up to 100 Petabytes of data. Customers must call AWS to open the vestibule of the truck to start ingesting the data. They just need to plug the fiber cable and the power cable to start loading the data. Amazon estimates that the loading and unloading process takes about three months on each side.
Apart from these services, Andy Jassy has also announced a slew of enhancements to Amazon EC2 and RDS.
Original article here.
IBM announced that Watson Analytics, a breakthrough natural language-based cognitive service that can provide instant access to powerful predictive and visual analytic tools for businesses, is available in beta. See Vine(vine.co/v/Ov6uvi1m7lT) for a sneak peek now.
I’m pleased to announce that I have my access, and its amazing. Uploading raw CSV data in and playing with it as a great shortcut to finding insights. It works really well and really quickly.
IBM Watson Analytics automates the once time-consuming tasks such as data preparation, predictive analysis, and visual storytelling for business professionals. Offered as a cloud-based freemium service, all business users can now access Watson Analytics from any desktop or mobile device. Since being announced on September 16, more than 22,000 people have already registered for the beta. The Watson Analytics Community, a user group for sharing news, best practices, technical support and training, is also accessible starting today.
This news follows IBM’s recently announced global partnership with Twitter, which includes plans to offer Twitter data as part of IBM Watson Analytics.
Learn more about how IBM Watson Analytics works:
As part of its effort to equip all professionals with the tools needed to do their jobs better, Watson Analytics provides business professionals with a unified experience and natural language dialogue so they can better understand data and more quickly reach business goals. For example, a marketing, HR or sales rep can quickly source data, cleanse and refine it, discover insights, predict outcomes, visualize results, create reports and dashboards and explain results in familiar business terms.
To view today’s news and access a video to be shared, visit the Watson Analytics Storybook:https://ibm.biz/WAStorybook.
Original article here.
It is the end of 2016! Tina Barr has a great roundup of all the startups we featured this year. Check it out and see if you managed to read about them all, then come back in January for when we start up all over again.
Also- I wanted to thank Elsa Mayer for her hard work in helping out with the startup posts.
What a year it has been for startups! We began the Hot Startups series in March as a way to feature exciting AWS-powered startups and the motivation behind the products and services they offer. Since then we’ve featured 27 startups across a wide range of industries including healthcare, commerce, social, finance, and many more. Each startup offers a unique product to its users – whether it’s an entertaining app or website, an educational platform, or a product to help businesses grow, startups have the ability to reach customers far and wide.
The startups we showcased this year are headquartered all over the world. Check them out on the map below!
In case you missed any of the posts, here is a list of all the hot startups we featured in 2016:
- Intercom – One place for every team in an Internet business to see and talk
to customers, personally, at scale.
- Tile – A popular key locator product that works with an app to help people find their stuff.
- Bugsnag – A tool to capture and analyze runtime errors in production web and mobile applications.
- DroneDeploy – Making the sky productive and accessible for everyone.
- Robinhood – Free stock trading to democratize access to financial markets.
- Dubsmash – Bringing joy to communication through video
- Sharethrough – An all-in-one native advertising platform.
- Shaadi.com – Helping South Asians to find a companion for life.
- Capillary– Boosting customer engagement for e-commerce.
- Monzo – A mobile-first bank.
- Depop– A social mobile marketplace for artists and friends to buy and sell products.
- Nextdoor – Building stronger and safer neighborhoods through technology.
- Branch – Provides free deep linking technology for mobile app developers to gain and retain users.
- Craftsvilla– Offering a platform to purchase ethnic goods.
- SendBird – Helping developers build 1-on-1 messaging and group chat quickly.
- Teletext.io – A solution for content management, without the system.
- Wavefront– A cloud-based analytics platform.
- Funding Circle – The leading online marketplace for business loans.
- Karhoo– A ride comparison app.
- nearbuy – Connecting customers and local merchants across India.
- Optimizely – Providing web and mobile A/B testing for the world’s leading brands.
- Touch Surgery – Building technologies for the global surgical community.
- WittyFeed – Creating viral content.
- AwareLabs – Helping small businesses build smart websites.
- Doctor On Demand– Delivering fast, easy, and cost-effective access to top healthcare providers.
- Starling Bank – Mobile banking for the next generation.
- VigLink – Powering content-driven commerce.
Thank you for keeping up with us as we shared these startups’ amazing stories throughout the year. Be sure to check back here in January for our first hot startups of 2017!
Original article here.
Apps are not just built for smartphones anymore. They are needed for homes, cars and commerce. In 2017, there is a huge entrepreneurs and consumers. It’s creating many opportunities for innovation.
What’s in store mobile app trends for 2017?
- 2017 will be the year of small businesses developing mobile apps
- Location-based services continue to rise.
- Integration of augmented reality into utility apps because they make a great couple
- Android Instant Apps to become a common trend
- Artificial Intelligence has officially gone mobile
- IoT Apps integration to continue unchallenged
- Application security to be more important than ever
- More companies see mobile apps as a way to increase sales, improved customer experience and be competitive in market
- Mobile App revenue to soar to $77 billion
Mobile Apps are now available for nearly every task imaginable.
Want to learn more? Here are 7 mobile app trends for 2017 in infographic.
Original article here.
We’re constantly reminded of the risks that come with bad passwords, yet many people persist in using obvious and easy-to-crack names, words, and patterns. Want to know if you’re at risk?
Identity theft is a serious problem: Millions of Americans are falling prey to cybercrime every year, and with more and more of our lives online the risk only increases. The key to protecting your online identity starts with the most commonly used part of accessing internet services: The password.
Using secure passwords can be difficult—I know I’m guilty of using the same password over and over again, something that has recently come back to bite me as I get email after email telling me someone has tried logging in to my accounts.
My current problem could have been far worse if I had been guilty of using some of the most common passwords that were uncovered recently by online IT training firm CBT Nuggets. It just published that and some other startling password facts that every internet user needs to know about.
Which words are widespread?
One of the fundamental rules of good password creation is to use words that other people don’t. The study found that of 50,000 passwords surveyed, there were several that were far more common than others. Love, star, girl, angel, and rock came in at the top five: If you’re guilty of including one of them it’s time to make some changes.
Dictionary attacks remain one of the most common ways hackers crack passwords in systems that don’t lock accounts out after a few tries. They simply compile lists of the most commonly used passwords and brute force accounts until they come up with a match.
It’s not just common words that are causing leaks: 42 percent of the passwords surveyed contained usernames, real names, or other publically available information. The most common offenders of name usage in passwords? Lisa, Amy, Scott, and Mark.
The demographics of getting hacked
Using your own name, your username, a pet’s name, or any other identifying feature is the perfect way to ensure you’re a target, but there are several other risk factors that can make you an easy mark.
Men are more likely to be hacked, but only by a few points (male = 53 percent; female =47 percent). Perhaps surprisingly, the most common age group of password hacking victims is 25- to 34-year olds. The study says that a possible cause is that this age group grew up along with the internet and in the earliest years weren’t taught the importance of good password use.
Predictably, Yahoo users are the most likely to have their passwords leaked—nearly half of hacked password surveyed came from Yahoo. Many of these probably came from this year’s leak of 500 million Yahoo passwords.
Wondering which website has the least secure users? AOL, Yahoo, and Hotmail are the most likely places to find passwords containing a username or real name.
How to stay safe
The password is a ubiquitous, and entirely unreliable, security method. Cracking methods are constantly becoming more sophisticated, machines used to perform brute force attacks keep getting faster, and there’s no solution for the weakest part of the system: The humans using it.
Truly secure passwords need to be long, random, and changed frequently. The best way to do that is by using an encrypted password management app. These apps store credentials to any number of websites, can create secure randomized passwords, and use a single sign-on to unlock your accounts.
You can remove all the Amy, love, Scott, star, and 123s from your passwords you want but if you make them out of names and words you’re still a predictable human. Security means using a machine to trick a machine.
The 3 big takeaways for TechRepublic readers
- Nearly half of passwords surveyed contained a username or real name. The most common were Amy, Lisa, Scott, and Mark.
- The most commonly hacked age group is the 25-34 year old range, which many may find surprising. Growing up in the early days of the internet, the study argues, has led many people to become complacent.
- The most effective way to secure internet accounts is with a randomized password containing upper- and lowercase letters, numbers, and symbols. This is best done using a password manager that can generate and securely store passwords.
Original article here.
Outsourcing giant to axe 2,000 jobs and use ‘proprietary robotic solutions’ after clients cut spending following Brexit vote.
A British outsourcing company whose contracts include collecting the BBC licence fee is to replace staff with robots as it slashes costs.
Capita, a FTSE 100-listed firm that also runs the London congestion charge, said it needed to axe 2,000 jobs as part of a cost-cutting drive in response to poor trading.
It said it would use the money it saved from sacking thousands of staff to fund investment in automated technology across all of the company’s divisions. The announcement will fuel growing fears that human workers will have to make way for robots, as companies turn to technology to boost profits.
The Apple and Samsung supplier Foxconn was reported to have replaced 60,000 workers with robots earlier this year, while the former chief executive of McDonald’s suggested a similar tactic in response to low-paid workers’ demands for better pay and conditions.
In a gloomy statement that sent its shares to a 10-year low at one stage, Capita said it had been hit by “headwinds” as its corporate clients reined in their spending. The company unveiled plans to shore up its finances, saving £50m a year via austerity measures, including greater use of “proprietary robotic solutions” and moving around 200 jobs to India.
The chief executive, Andy Parker, said Capita, which made a pre-tax profit of £186m in the first six months of this year, would use robots to help eliminate human error and make decisions faster. The company employs 78,000 people.
“It doesn’t remove the need for an individual but it speeds up how they work, which means you need less [sic] people to do it.”
He said a human assisted by automated robotic technology could do a 40-minute job in much less time.
“They [human staff members] can then do 10 times the amount they used to, so you need less [sic] people to do the same amount of work.”
Parker said this would make the company more efficient by “taking away some of the decision-making and cutting down potential errors”.
Capita, which provides services ranging from electronic tagging for offenders to store card services for retailers, will also move some of its IT operation abroad. Parker said this would involve “a couple of hundred” jobs being shifted to India.
The company’s decisions on staffing are part of an attempt to reduce costs without causing shareholders any financial pain. Parker said the cost cuts – coupled with asset sales – would allow Capita to avoid reducing its annual dividend, which was worth £200m last year and £180m the year before.
But despite the effort to protect investors, shares in the company finished down more than 4%, having fallen more than 14% during the day, as investors were left stunned by the company’s pessimistic outlook.
Parker said he “would have thought there’d be a more positive reaction”.
Rehana Azam, the national secretary for public services at the GMB union, said: “Public services are predominantly delivered by people so it’s hard to see how they’re going to provide a cost-efficient service from call centres in another country.
“We’d want to sit down with Capita and make sure people are treated fairly in any process that ends with them losing jobs.”
Azam cast doubt on whether using robots to automate some of its systems would work. “We’ve never had a good track record with private providers delivering computerised systems. I’d like to see where there have been good examples of that kind of automation.”
Capita has struggled as its clients, which include O2, M&S, John Lewis and Dixons Carphone, have looked to cut costs in areas such as corporate travel and recruitment.
The company refused to blame the Brexit vote for the disappointing update but said earlier this year that uncertainty over the UK’s relationship with the European Union had hit its business, delaying key contracts.
Capita is predominantly UK-based, unlike bigger rivals, such as G4S and Serco, which have been sheltered to a large degree from the Brexit-related fallout by their bigger geographical footprint.
Original article here.
Over the last several years, stories of the technologies making up an Internet of Things have started to slip into public consciousness. As this is occurring, we believe the whole story of Smart Systems and the Internet of Things is not being told. Many of the dispatches coming in from the “front lines” of technology innovation are but fragments of a much larger narrative.
From our perspective, this story is not just about people communicating with people or machines communicating with machines. Smart, connected systems are a technological and economic phenomenon of unprecedented scale, encompassing potentially billions if not trillions of nodes — an Internet of infinite interactions and values…
Original article here.
Microsoft Research’s female contingent makes their calls for AI breakthroughs to come.
Seventeen Microsoft researchers—all of whom happen to be women this year—have made their calls for what will be hot in the burgeoning realm of artificial intelligence (AI) in the next decade.
Ripping a page out of the IBM IBM -0.48% 5 for 5 playbook, Microsoft MSFT -0.37% likes to use these annual predictions to showcase the work of its hotshot research brain trust. Some of the picks are already familiar. One is about how advances in deep learning—which endows computers with human-like thought processes—will make computers or other smart devices more intuitive and easier to use. This is something we’ve all heard before, but the work is not done, I guess.
For example, “the search box” most of us use on Google or Bing search engines will disappear, enabling people to search for things based on spoken commands, images, or video, according to Susan Dumais, distinguished scientist and deputy managing director of Microsoft’s Redmond, Wash. research lab. That’s actually already happening with products like Google GOOG -0.10% Now, Apple Siri AAPL 0.26% , and Microsoft Cortana—but there’s more to do.
Dumais says the box will go away. She explains:
That is more ubiquitous, embedded and contextually sensitive. We are seeing the beginnings of this transformation with spoken queries, especially in mobile and smart home settings. This trend will accelerate with the ability to issue queries consisting of sound, images or video, and with the use of context to proactively retrieve information related to the current location, content, entities or activities without explicit queries.
Virtual reality will become more ubiquitous as researchers enhance better “body tracking” capabilities, says Mar Gonzalez Franco, a researcher at the Redmond research lab. That will enable such rich, multi-sensorial experiences that could actually cause subjects to hallucinate. That doesn’t sound so great to some, but that capability could help people with disabilities “retrain” their perceptual systems, she notes.
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There’s but one mention on this list of the need for ethical or moral guidelines for the use of AI. That comes from Microsoft distinguished scientist Jennifer Chayes.
Chayes, who is also managing director of Microsoft’s New England and New York City research labs, thinks AI can be used to police the ethical application of AI.
Our lives are being enhanced tremendously by artificial intelligence and machine learning algorithms. However, current algorithms often reproduce the discrimination and unfairness in our data and, moreover, are subject to manipulation by the input of misleading data. One of the great algorithmic advances of the next decade will be the development of algorithms which are fair, accountable and much more robust to manipulation.
Microsoft experienced the mis-use of AI’s power first-hand earlier this year when its experimental Tay chatbot offended many Internet users with racist and sexist slurs that the program was taught by others. Microsoft chose to focus on female researchers to stress that, while women and girls make up half of the world’s population, they account for less than 20% of computer science graduates.
This is particularly true for women and girls who comprise 50% of the world’s population, but account for less than 20 percent of computer science graduates, according to the Organization for Economic Cooperation and Development. The fact that the U.S. Bureau of Labor Statistics expects that there will be fewer than 400,000 qualified applicants to take on 1.4 million computing jobs in 2020 means there is great opportunity for women in technology going forward.
Original article here.
Artificial intelligence, machine learning, and smart things promise an intelligent future.
Today, a digital stethoscope has the ability to record and store heartbeat and respiratory sounds. Tomorrow, the stethoscope could function as an “intelligent thing” by collecting a massive amount of such data, relating the data to diagnostic and treatment information, and building an artificial intelligence (AI)-powered doctor assistance app to provide the physician with diagnostic support in real-time. AI and machine learning increasingly will be embedded into everyday things such as appliances, speakers and hospital equipment. This phenomenon is closely aligned with the emergence of conversational systems, the expansion of the IoT into a digital mesh and the trend toward digital twins.
Three themes — intelligent, digital, and mesh — form the basis for the Top 10 strategic technology trends for 2017, announced by David Cearley, vice president and Gartner Fellow, at Gartner Symposium/ITxpo 2016 in Orlando, Florida. These technologies are just beginning to break out of an emerging state and stand to have substantial disruptive potential across industries.
AI and machine learning have reached a critical tipping point and will increasingly augment and extend virtually every technology enabled service, thing or application. Creating intelligent systems that learn, adapt and potentially act autonomously rather than simply execute predefined instructions is primary battleground for technology vendors through at least 2020.
Trend No. 1: AI & Advanced Machine Learning
AI and machine learning (ML), which include technologies such as deep learning, neural networks and natural-language processing, can also encompass more advanced systems that understand, learn, predict, adapt and potentially operate autonomously. Systems can learn and change future behavior, leading to the creation of more intelligent devices and programs. The combination of extensive parallel processing power, advanced algorithms and massive data sets to feed the algorithms has unleashed this new era.
In banking, you could use AI and machine-learning techniques to model current real-time transactions, as well as predictive models of transactions based on their likelihood of being fraudulent. Organizations seeking to drive digital innovation with this trend should evaluate a number of business scenarios in which AI and machine learning could drive clear and specific business value and consider experimenting with one or two high-impact scenarios..
Trend No. 2: Intelligent Apps
Intelligent apps, which include technologies like virtual personal assistants (VPAs), have the potential to transform the workplace by making everyday tasks easier (prioritizing emails) and its users more effective (highlighting important content and interactions). However, intelligent apps are not limited to new digital assistants – every existing software category from security tooling to enterprise applications such as marketing or ERP will be infused with AI enabled capabilities. Using AI, technology providers will focus on three areas — advanced analytics, AI-powered and increasingly autonomous business processes and AI-powered immersive, conversational and continuous interfaces. By 2018, Gartner expects most of the world’s largest 200 companies to exploit intelligent apps and utilize the full toolkit of big data and analytics tools to refine their offers and improve customer experience.
Trend No. 3: Intelligent Things
New intelligent things generally fall into three categories: robots, drones and autonomous vehicles. Each of these areas will evolve to impact a larger segment of the market and support a new phase of digital business but these represent only one facet of intelligent things. Existing things including IoT devices will become intelligent things delivering the power of AI enabled systems everywhere including the home, office, factory floor, and medical facility.
As intelligent things evolve and become more popular, they will shift from a stand-alone to a collaborative model in which intelligent things communicate with one another and act in concert to accomplish tasks. However, nontechnical issues such as liability and privacy, along with the complexity of creating highly specialized assistants, will slow embedded intelligence in some scenarios.
The lines between the digital and physical world continue to blur creating new opportunities for digital businesses. Look for the digital world to be an increasingly detailed reflection of the physical world and the digital world to appear as part of the physical world creating fertile ground for new business models and digitally enabled ecosystems.
Trend No. 4: Virtual & Augmented Reality
Virtual reality (VR) and augmented reality (AR) transform the way individuals interact with each other and with software systems creating an immersive environment. For example, VR can be used for training scenarios and remote experiences. AR, which enables a blending of the real and virtual worlds, means businesses can overlay graphics onto real-world objects, such as hidden wires on the image of a wall. Immersive experiences with AR and VR are reaching tipping points in terms of price and capability but will not replace other interface models. Over time AR and VR expand beyond visual immersion to include all human senses. Enterprises should look for targeted applications of VR and AR through 2020.
Trend No. 5: Digital Twin
Within three to five years, billions of things will be represented by digital twins, a dynamic software model of a physical thing or system. Using physics data on how the components of a thing operate and respond to the environment as well as data provided by sensors in the physical world, a digital twin can be used to analyze and simulate real world conditions, responds to changes, improve operations and add value. Digital twins function as proxies for the combination of skilled individuals (e.g., technicians) and traditional monitoring devices and controls (e.g., pressure gauges). Their proliferation will require a cultural change, as those who understand the maintenance of real-world things collaborate with data scientists and IT professionals. Digital twins of physical assets combined with digital representations of facilities and environments as well as people, businesses and processes will enable an increasingly detailed digital representation of the real world for simulation, analysis and control.
Trend No. 6: Blockchain
Blockchain is a type of distributed ledger in which value exchange transactions (in bitcoin or other token) are sequentially grouped into blocks. Blockchain and distributed-ledger concepts are gaining traction because they hold the promise of transforming industry operating models in industries such as music distribution, identify verification and title registry. They promise a model to add trust to untrusted environments and reduce business friction by providing transparent access to the information in the chain. While there is a great deal of interest the majority of blockchain initiatives are in alpha or beta phases and significant technology challenges exist.
The mesh refers to the dynamic connection of people, processes, things and services supporting intelligent digital ecosystems. As the mesh evolves, the user experience fundamentally changes and the supporting technology and security architectures and platforms must change as well.
Trend No. 7: Conversational Systems
Conversational systems can range from simple informal, bidirectional text or voice conversations such as an answer to “What time is it?” to more complex interactions such as collecting oral testimony from crime witnesses to generate a sketch of a suspect. Conversational systems shift from a model where people adapt to computers to one where the computer “hears” and adapts to a person’s desired outcome. Conversational systems do not use text/voice as the exclusive interface but enable people and machines to use multiple modalities (e.g., sight, sound, tactile, etc.) to communicate across the digital device mesh (e.g., sensors, appliances, IoT systems).
Trend No. 8: Mesh App and Service Architecture
The intelligent digital mesh will require changes to the architecture, technology and tools used to develop solutions. The mesh app and service architecture (MASA) is a multichannel solution architecture that leverages cloud and serverless computing, containers and microservices as well as APIs and events to deliver modular, flexible and dynamic solutions. Solutions ultimately support multiple users in multiple roles using multiple devices and communicating over multiple networks. However, MASA is a long term architectural shift that requires significant changes to development tooling and best practices.
Trend No. 9: Digital Technology Platforms
Digital technology platforms are the building blocks for a digital business and are necessary to break into digital. Every organization will have some mix of five digital technology platforms: Information systems, customer experience, analytics and intelligence, the Internet of Things and business ecosystems. In particular new platforms and services for IoT, AI and conversational systems will be a key focus through 2020. Companies should identify how industry platforms will evolve and plan ways to evolve their platforms to meet the challenges of digital business.
Trend No. 10: Adaptive Security Architecture
The evolution of the intelligent digital mesh and digital technology platforms and application architectures means that security has to become fluid and adaptive. Security in the IoT environment is particularly challenging. Security teams need to work with application, solution and enterprise architects to consider security early in the design of applications or IoT solutions. Multilayered security and use of user and entity behavior analytics will become a requirement for virtually every enterprise.
Original article here.
Like everything in enterprise technology, pricing can be a bit complicated. Here’s an analysis from RightScale looking at how discounts alter the cloud pricing equation. Google comes out cheapest in most scenarios.
With Amazon Web Services hosting its annual conference this week, talk about the price for performance and agility equation will be everywhere.
Knowing AWS’ re:Invent is kicking off this week, the largest cloud service provider has been busy cutting prices for various instances. Rest assured that Google and Microsoft are likely to toss in their own price cuts, as AWS speaks to its base.
But the cloud pricing equation is getting complicated for compute instances. Not so shockingly, these price discussions have to include discounts. Like everything in enterprise technology, there’s the street price and your price. Comparing the cloud providers on pricing is tricky given Microsoft, Google, and AWS all have different approaches to discounts.
Fortunately, RightScale on Monday will outline a study on cloud compute prices. Generally speaking, AWS won’t be your cheapest option for compute. AWS typically lands in the middle between Microsoft Azure and Google Cloud.
The bottom line is that AWS uses reserved instances in one-year and three-year terms to offer discounts. Microsoft requires an enterprise agreement for its Azure discounts. Google has sustained usage discounts that are relatively easy to follow.
Overall, RightScale found that Google will be cheapest in most scenarios because sustained usage discounts are automatically applied. Among the key takeaways:
- If you need solid state drive performance instead of attached storage, Google will charge you a premium.
- Azure matches or beats AWS for on-demand pricing consistently.
- AWS won’t be the cheapest alternative in many scenarios. Then again — AWS has a bigger menu, more advanced cloud services, and the customer base where it doesn’t have to go crazy on pricing. AWS just has to be fair.
- Your results will vary based on the level of your Microsoft enterprise agreement and what reserved instances were purchased on AWS.
Here are three slides to ponder from RightScale.
Add it up and you’d be advised to make your own comparisons; check out RightScale’s SlideShare, and then crunch some numbers. In the end, enterprises may have to have all three cloud providers in their company — if only to play them off each other.
Original article here.
Elon Musk has said that there’s a “pretty good chance” that automation will entirely replace workers in the future, meaning governments will have to make up for lost wages by paying people.
The billionaire founder of Tesla and SpaceX said that rapid changes to the workforce from automation is likely to force us to introduce a “universal basic income” in which people will have to be supported by a stipend instead of working for a living.
Musk has been vocal in his warnings about the potential downside of the rise of the robots. He has invested millions in OpenAI, a project to ensure that artificial intelligence benefits mankind, rather than destroys it, and last week he said that it was only a matter of time before AI was used to take down the internet.
The idea of a universal income – an unconditional government payment – has gained traction in recent years amid growing concerns about the effect that robots will have on employment.
Customer service agents, builders and leisure industry workers are just a few jobs where opportunities may be erased or severely diminished over the coming decades, and some economists and researchers believe the majority of jobs that exist today will be done by robots in 30 years.
ABOUT | The robots are taking over… or are they?
10 professions that will almost certainly be automated…
- Loan officers
- Bank tellers
- Credit analysts
- Office clerks
- Legal secretaries
- Estate agents
…and 10 professions that probably won’t
- Social workers
- Human resources managers
- Fashion designers
- Public relations
- Computer scientists
- Health and safety engineers
Musk said this presented an opportunity rather than a threat, however. “People will have time to do other things, more complex things, more interesting things. Certainly more leisure time,” he said.
The billionaire has previously said we need to embellish our brains with artificial intelligence to avoid being left behind by robots. He has floated the idea that humans should become cyborgs if we don’t want to become the equivalent of a pet for robots, backing the idea of a “neural lace”, a new electronic layer of the brain.
Original article here.