Posted On:January 2017 - AppFerret
Are you ready for the next wave of the internet?
Since the creation of the first web page, the connected world has been constantly changing at a rapid pace, speeding its way through Web 2.0 and propelling us into the future. That future is now. The Internet of Things (IoT) is taking shape, and it’s ushering in the third major evolution of the internet.
If you don’t catch the wave, you could miss out on the Internet of Things and the huge boom that’s coming for entrepreneurs in nearly every industry.
Take a look at just a few powerful data points on the Internet of Things:
- Parks Associates analysts expect that almost 55 million smart home devices will be sold to U.S. broadband households in 2020.
- According to a study conducted by the International Data Corporation, IoT spending is expected to reach $1.29 Trillion by 2020.
While 2016 was a big year for IoT, 2017 will be even bigger. Positioning yourself early is everything when it comes to capitalizing on the next evolution of the internet. Here are the top trends you can expect to see in 2017.
Voice assistants will dominate product sales
Amazon’s success with Echo and Alexa, the speaker’s virtual voice assistant, has been astounding. There’s little doubt that Amazon has penetrated the mass market, with Echo finding its way into the hands of owners who wouldn’t even know to call it a Smart Home product.
This trend will continue in a big way. The Google Home voice-activated speaker and personal assistant is growing the product category in terms of both sales and innovation. While Amazon has the advantage of having made the first move, Google Home is offering a deep integration into digital life by syncing directly with the owner’s Google account. It also benefits from Google’s extensive experience in machine learning, artificial intelligence and data analysis. Also, look for Microsoft to make similar moves with Cortana.
Smart City will be the new Smart Home
Visions of the Smart City are starting to materialize as CTO’s for major municipalities are coming to understand how Internet of Things products and services can provide cost savings, increase quality of life and promote safety in urban environments. Keep an eye out for the appearance of smart lighting, connected streets, smart parking, smart meters, connected apartments and on-demand services in the most innovative cities.
Hardware-based hubs have a hard time
Hub-based ecosystems were all the rage three years ago. The rise in virtual-assistants, however, is threatening hub-based platforms.
There are two reasons for this. The first is that voice-driven assistants (like Amazon’s Alexa and the Google Home) connect to devices in the cloud and therefore don’t require an additional array of radios inside a separate hub. Secondly, more and more routers are being equipped with wireless capabilities like Z-wave, Zigbee and BLE, which further reduce the need for additional hardware.
The Smart Home will go mainstream
The success of Amazon’s Echo rapidly accelerated the adoption of Smart Home technology for everyday consumers, but it’s not the only reason that mass consumers are embracing the concept of the Smart Home. Smart Home product and service developers are making better products, many of which include better education and better support.
Additionally, IoT companies are continually getting better about understanding who their customers are and what they want. As consumer preferences become apparent, product companies are telling better stories that communicate real value to their customers.
Voice is the new UI
The ability to command the Echo’s speaker via Alexa’s voice-recognition system introduced a new way for consumers to interact with the electronic world around them: voice.
While Siri may have initiated voice-activation with Apple products back in 2011, Alexa’s voice capabilities (or “skills”) could very well replace the smartphone touch-screen over time. Expect this trend to continue as other connected products add to Alexa’s voice capabilities, which also allow you to control non-Amazon products–even your car.
Evolving business models (more services)
Two years ago, product companies were focused on connecting hardware (like lights, locks, doorbells, etc.) to the internet. Last year, the focus was on integrating those products with smart hubs and other connected point-solutions. This year, expect product companies to focus on providing services in an attempt to diversify their revenues and achieve recurring cash flows.
Wearables will work with the Smart Home
This will be the year that wearables converge with the Smart Home. Imagine a day when your fitness tracker won’t let you turn on your TV because you didn’t exercise yet. This convergence of industries presents a great opportunity for services and apps.
How to stay ahead
The IoT market is moving at breakneck speed; if you want to be a part of it, you need to stay ahead. Here are two ways to do that:
- Follow the top influencers in the Internet of Things for the latest news and actionable perspectives.
- Join an industry group if you have a company in the space. SkyBell (my IoT startup) is a member of the Internet of Things Consortium (IoTC), a nonprofit advocacy group that is looking to expand consumer awareness around IoT. The IoTC provides me with abundant opportunities to network with leaders in the Smart Home industry and stay on top of the latest trends.
Original article here.
Unless you have been living under the proverbial rock, you probably heard about a number of Internet of Things (IoT) attacks this fall, beginning with KrebsOnSecurity, then OVH, then the DDoS attack on Dyn DNS. All of this started with a bot called Mirai, and involved IoT devices. Why is this important? By 2020, it is estimated that the number of connected devices is expected to grow exponentially to 50 billion. A survey by HP indicates that about 70% of these devices have vulnerabilities, making them the perfect targets for botnets like Mirai.
Below is a collection of 10 blogs written by industry experts on this topic, that will help you fully understand the implications of this botnet and what it means for the future of connected devices.
- Internet of Things or Internet of Threats? IoT is the ability for devices to be connected the Internet and communicate with other devices – think a thermostat knowing automatically when to heat your home without you having to take an action. While these smart devices may seem like a brilliant idea that can save you time and money, there are also risks associated with them. This blog will walk you through the two-part dilemma that is faced when it comes to using these devices and provide a background of the IoT.
- Nine Questions to Ask to Determine IoT Device Safety: If you’re familiar with the IoT, then you’re aware of some of the risks that come with connected devices. From January 5-8, consumers and reporters alike will be flooding Las Vegas, Nevada for the Consumer Electronics Show to learn more about new devices making their debut in 2017. This blog by APAC Security Evangelist David Hobbs will provide nine questions you should ask the manufacturers (regardless of whether you are a consumer or reporter) about the safety of these devices.
- IoT Botnets the Fault of Manufacturers, 69 Percent of Consumers Report in Radware Survey: So you own a connected device, but it was attacked and used to launch a DDoS attack. Who is at fault? According to a survey conducted by Harris on behalf of Radware, 69% of consumers would blame the manufacturer. This blog provides additional results of that survey.
- BusyBox Botnet Mirai – the warning we’ve all been waiting for? Radware’s EMEA Security Evangelist, Pascal Geenens, takes us back to where it began – the attack on KrebsOnSecurity. As he states, “The most concerning fact, and the genius of Mirai, resides in its simplicity for victimizing IoT devices.” This blog will outline how the Mirai botnet works.
- The deplorable state of IoT security: Following the public release of Mirai, the security community began to grow extremely concerned about the potential for additional attacks of that nature. In his second blog, Pascal discusses how the state of IoT security presents a prime opportunity for more attacks.
- How Friday’s Massive DDoS Attack on the U.S. Happened: DNS servers are a like a roadmap to the internet and help users find the websites they are looking for. When an attacker ties up all of the DNS’s resources, legitimate clients are unable to resolve their request. Radware’s ERT Researcher, Daniel Smith, outlines how the attack on Dyn DNS happened in this blog.
- Let’s discuss facts: An insight into Mirai’s source-code: After three major cyber-attacks, speculation abounded on who the attackers were, what their motivation was, the exact attack vectors and the traffic volumes. In this blog post, Radware’s Snir Ben Shimol discusses what we know to be the facts about these attacks.
- Rise of the Machines: How IoT broke the Internet, and the day after tomorrow: In a guest post by Zeina Zakhour, Global CTO of Cyber Security for Atos, she discusses the repercussions of these attacks and what consumers can do to try to prevent similar attacks from occurring again.
- Is Heat Your Thermostat’s First Priority? Remember that smart thermostat that we mentioned? A hacker performed a DDoS attack on a heating distribution system that controlled the heating of two large apartment blocks in Finland back in November, shutting off heat for 20,000 residents. In the Dyn DNS attack, it was discovered that a handful of connected devices, mainly IP cameras, DVRs and routers, were the ones infected by Mirai and used in the attack. In this blog, Pascal discusses how that relates to your smart devices, like thermostats, and whether you should be concerned.
- Cyber Security Predictions: Looking Back at 2016, Peering Ahead to 2017: What do we see on the docket for 2017? We correctly predicted in the 2015–2016 Global Application and Network Security Report that we would see the rise of the Internet of Things, which spawned the largest DDoS attack in history. Radware’s Vice President of Security Solutions, Carl Herberger, discusses our predictions for 2017 in this blog post.
The conversation is still going on the record-breaking volume of the Mirai botnet attack, and doesn’t show signs of slowing. Many security executives have been warning about IoT threats such as this for years, and now the world is finally paying attention.
Original article here.
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This video by Creative Commons Aotearoa New Zealand, with support from InternetNZ, is available under a Creative Commons Attribution 3.0 New Zealand licence. A project of the Royal Society of New Zealand. Produced by Mohawk Media.
From data scooping to facial recognition, Amazon’s latest additions give devs new, wide-ranging powers in the cloud
In the beginning, life in the cloud was simple. Type in your credit card number and—voilà—you had root on a machine you didn’t have to unpack, plug in, or bolt into a rack.
That has changed drastically. The cloud has grown so complex and multifunctional that it’s hard to jam all the activity into one word, even a word as protean and unstructured as “cloud.” There are still root logins on machines to rent, but there are also services for slicing, dicing, and storing your data. Programmers don’t need to write and install as much as subscribe and configure.
Here, Amazon has led the way. That’s not to say there isn’t competition. Microsoft, Google, IBM, Rackspace, and Joyent are all churning out brilliant solutions and clever software packages for the cloud, but no company has done more to create feature-rich bundles of services for the cloud than Amazon. Now Amazon Web Services is zooming ahead with a collection of new products that blow apart the idea of the cloud as a blank slate. With the latest round of tools for AWS, the cloud is that much closer to becoming a concierge waiting for you to wave your hand and give it simple instructions.
Here are 10 new services that show how Amazon is redefining what computing in the cloud can be.
Anyone who has done much data science knows it’s often more challenging to collect data than it is to perform analysis. Gathering data and putting it into a standard data format is often more than 90 percent of the job.
Glue is a new collection of Python scripts that automatically crawls your data sources to collect data, apply any necessary transforms, and stick it in Amazon’s cloud. It reaches into your data sources, snagging data using all the standard acronyms, like JSON, CSV, and JDBC. Once it grabs the data, it can analyze the schema and make suggestions.
The Python layer is interesting because you can use it without writing or understanding Python—although it certainly helps if you want to customize what’s going on. Glue will run these jobs as needed to keep all the data flowing. It won’t think for you, but it will juggle many of the details, leaving you to think about the big picture.
Field Programmable Gate Arrays have long been a secret weapon of hardware designers. Anyone who needs a special chip can build one out of software. There’s no need to build custom masks or fret over fitting all the transistors into the smallest amount of silicon. An FPGA takes your software description of how the transistors should work and rewires itself to act like a real chip.
Amazon’s new AWS EC2 F1 brings the power of FGPA to the cloud. If you have highly structured and repetitive computing to do, an EC2 F1 instance is for you. With EC2 F1, you can create a software description of a hypothetical chip and compile it down to a tiny number of gates that will compute the answer in the shortest amount of time. The only thing faster is etching the transistors in real silicon.
Who might need this? Bitcoin miners compute the same cryptographically secure hash function a bazillion times each day, which is why many bitcoin miners use FPGAs to speed up the search. Anyone with a similar compact, repetitive algorithm you can write into silicon, the FPGA instance lets you rent machines to do it now. The biggest winners are those who need to run calculations that don’t map easily onto standard instruction sets—for example, when you’re dealing with bit-level functions and other nonstandard, nonarithmetic calculations. If you’re simply adding a column of numbers, the standard instances are better for you. But for some, EC2 with FGPA might be a big win.
As Docker eats its way into the stack, Amazon is trying to make it easier for anyone to run Docker instances anywhere, anytime. Blox is designed to juggle the clusters of instances so that the optimum number are running—no more, no less.
Blox is event driven, so it’s a bit simpler to write the logic. You don’t need to constantly poll the machines to see what they’re running. They all report back, so the right number can run. Blox is also open source, which makes it easier to reuse Blox outside of the Amazon cloud, if you should need to do so.
Monitoring the efficiency and load of your instances used to be simply another job. If you wanted your cluster to work smoothly, you had to write the code to track everything. Many people brought in third parties with impressive suites of tools. Now Amazon’s X-Ray is offering to do much of the work for you. It’s competing with many third-party tools for watching your stack.
When a website gets a request for data, X-Ray traces as it as flows your network of machines and services. Then X-Ray will aggregate the data from multiple instances, regions, and zones so that you can stop in one place to flag a recalcitrant server or a wedged database. You can watch your vast empire with only one page.
Rekognition is a new AWS tool aimed at image work. If you want your app to do more than store images, Rekognition will chew through images searching for objects and faces using some of the best-known and tested machine vision and neural-network algorithms. There’s no need to spend years learning the science; you simply point the algorithm at an image stored in Amazon’s cloud, and voilà, you get a list of objects and a confidence score that ranks how likely the answer is correct. You pay per image.
The algorithms are heavily tuned for facial recognition. The algorithms will flag faces, then compare them to each other and references images to help you identify them. Your application can store the meta information about the faces for later processing. Once you put a name to the metadata, your app will find people wherever they appear. Identification is only the beginning. Is someone smiling? Are their eyes closed? The service will deliver the answer, so you don’t need to get your fingers dirty with pixels. If you want to use impressive machine vision, Amazon will charge you not by the click but by the glance at each image.
Working with Amazon’s S3 has always been simple. If you want a data structure, you request it and S3 looks for the part you want. Amazon’s Athena now makes it much simpler. It will run the queries on S3, so you don’t need to write the looping code yourself. Yes, we’ve become too lazy to write loops.
Athena uses SQL syntax, which should make database admins happy. Amazon will charge you for every byte that Athena churns through while looking for your answer. But don’t get too worried about the meter running out of control because the price is only $5 per terabyte. That’s about 50 billionths of a cent per byte. It makes the penny candy stores look expensive.
The original idea of a content delivery network was to speed up the delivery of simple files like JPG images and CSS files by pushing out copies to a vast array of content servers parked near the edges of the Internet. Amazon is taking this a step further by letting us push Node.js code out to these edges where they will run and respond. Your code won’t sit on one central server waiting for the requests to poke along the backbone from people around the world. It will clone itself, so it can respond in microseconds without being impeded by all that network latency.
Amazon will bill your code only when it’s running. You won’t need to set up separate instances or rent out full machines to keep the service up. It is currently in a closed test, and you must apply to get your code in their stack.
If you want some kind of physical control of your data, the cloud isn’t for you. The power and reassurance that comes from touching the hard drive, DVD-ROM, or thumb drive holding your data isn’t available to you in the cloud. Where is my data exactly? How can I get it? How can I make a backup copy? The cloud makes anyone who cares about these things break out in cold sweats.
The Snowball Edge is a box filled with data that can be delivered anywhere you want. It even has a shipping label that’s really an E-Ink display exactly like Amazon puts on a Kindle. When you want a copy of massive amounts of data that you’ve stored in Amazon’s cloud, Amazon will copy it to the box and ship the box to wherever you are. (The documentation doesn’t say whether Prime members get free shipping.)
Snowball Edge serves a practical purpose. Many developers have collected large blocks of data through cloud applications and downloading these blocks across the open internet is far too slow. If Amazon wants to attract large data-processing jobs, it needs to make it easier to get large volumes of data out of the system.
If you’ve accumulated an exabyte of data that you need somewhere else for processing, Amazon has a bigger version called Snowmobile that’s built into an 18-wheel truck complete with GPS tracking.
Oh, it’s worth noting that the boxes aren’t dumb storage boxes. They can run arbitrary Node.js code too so you can search, filter, or analyze … just in case.
Once you’ve amassed a list of customers, members, or subscribers, there will be times when you want to push a message out to them. Perhaps you’ve updated your app or want to convey a special offer. You could blast an email to everyone on your list, but that’s a step above spam. A better solution is to target your message, and Amazon’s new Pinpoint tool offers the infrastructure to make that simpler.
You’ll need to integrate some code with your app. Once you’ve done that, Pinpoint helps you send out the messages when your users seem ready to receive them. Once you’re done with a so-called targeted campaign, Pinpoint will collect and report data about the level of engagement with your campaign, so you can tune your targeting efforts in the future.
Who gets the last word? Your app can, if you use Polly, the latest generation of speech synthesis. In goes text and out comes sound—sound waves that form words that our ears can hear, all the better to make audio interfaces for the internet of things.
Original article here.
There are a lot of visualization-related tools out there. Here’s a simple categorized collection of what’s available, with a focus on the free and open source stuff.
This site features a curated selection of data visualization tools meant to bridge the gap between programmers/statisticians and the general public by only highlighting free/freemium, responsive and relatively simple-to-learn technologies for displaying both basic and complex, multivariate datasets. It leans heavily toward open-source software and plugins, rather than enterprise, expensive B.I. solutions.
I found some broken links, and the descriptions need a little editing, but it’s a good place to start.
Also, if you’re just starting out with visualization, you might find all the resources a bit overwhelming. If that’s the case, don’t fret. You don’t have to learn how to use all of them. Let your desired outcomes guide you. Here’s what I use.
Original article here.
As we go into 2017 our IoT Analytics team is again evaluating the main IoT developments of the past year in the global “Internet of Things” arena. This article highlights some general IoT 2016 observations as well as our top 8 news stories, with a preview for the new year of opportunities and challenges for global IoT businesses. (For your reference, here is our 2015 IoT year in review article.)
In 2016 the main theme for IoT was the shift from hype to reality. While in 2015, most people only heard about IoT in the media or consumed some marketing blogs, 2016 was different. Many consumers and enterprises went out and started their own IoT endeavors or bought their own IoT devices. Both consumer IoT and enterprise IoT enjoyed record uptake, but also saw some major setbacks.
A. General IoT 2016 observations
A1. Consumer IoT
Millions of consumers bought their first IoT Device in 2016. For many of them this was Amazon Echo (see below for more details).
Image 1: The Amazon Echo Dot was a consumer IoT 2016 success (left hand side) while other devices didn’t always convince (e.g., Nest thermostat – right hand side)
Unfortunately many consumers also realized that marketing promises and reality are often still disparate. Cases of disappointed users are increasing (For example a smart thermostat user who discovered that his thermostat was disconnected for a day).
Some companies were dissolved in 2016 (like the Smart Home Hub Revolv in April – causing many angry customers), others went bankrupt (like the smart watch maker Pebble in December) or didn’t even come to life at all (such as the augmented reality helmet startup Skully that enjoyed a lot of publicity, but filed for bankruptcy in August without having sold a single product).
A2. Enterprise IoT
On the enterprise/industrial side of things, IoT 2016 will go down as the year many firms got real about their first IoT pilot projects.
A general wake-up call came in September when a massive cybersecurity attack that involved IoT devices (mainly CCTV cameras) shut down DNS provided Dyn and with it their customer’s websites (e.g., AirBnB, Netflix and Twitter). While this kind of attack didn’t directly affect most IoT companies, its implications scared many IT and IoT decision-makers. As a result, many IoT discussions have now shifted towards cybersecurity solutions.
B. Top 8 IoT 2016 Stories
For us at IoT Analytics, the IoT Security Attack on Dyn servers qualifies as the #1 story of the year. Here are our top takeaways from IoT 2016:
1. Biggest overall story: IoT Security attack on Dyn servers
The Dyn DDoS attack was the first large-scale cybersecurity attack that involved IoT devices – Dyn estimates that 100,000 infected IoT devices were involved. As a first-of-a-kind, it sent shockwaves through corporate IT and IoT.
Chinese CCTV system manufacturer, Hangzhou Xiongmai Technology Company, was at the core of the attack. Its cameras (among others) were infected with the so-called Mirai malware. This allowed the hackers to connect to the infected IoT devices and launch a flood of well-timed massive requests on Dyn servers – which led to the shutdown of their services.
2. Biggest Consumer IoT Success: Amazon Echo
Launched in June 2015, the Amazon Echo Smart Home Voice Control was undoubtedly the consumer IoT success story of the year. Recent data provided by Amazon reveals that device sales exploded by 9x (year-on-year vs. last Christmas).
Amazon sold more than 1 million Echo devices in December 2016
Our app-based Smart Home models confirm this trend suggesting that Amazon sold more than 1 million Echo devices in December 2016 and close to 4 million devices throughout the whole of 2016.
With these gains, Amazon has suddenly become the #1 Smart Home Hub and is leading the paradigm shift towards a voice-controlled automated home. Google jumped on the same train in October by releasing Google Home; Microsoft Home Hub is expected to follow in 2017.
3. Most overcrowded space: IoT Platforms
When we launched our coverage of IoT Platforms in early 2015, little did we know that the topic would soon become the hottest IoT area. Our count of platform providers in May 2016 showed 360 platforms. Our internal research is now well over 400. IoT Platforms is also well placed in the Gartner Hype Cycle 2016.
Companies have realized that the value of IoT lies in the data and that those that manage this data will be the ones capturing a large chunk of this value. Hence, everyone is building an IoT platform.
The frightening part is not necessarily the number but rather the fact that the sales pitches of the platform providers all sound like this: “We are the only true end-2-end platform which is device-agnostic and completely secure”.
4. Largest M&A Deal: Qualcomm/NXP
While we can see a massive expansion of global IoT software/analytics and platform offerings, we are also witnessing a consolidation among larger IoT hardware providers – notably in the chip sector. In October 2016, US-based chipmaker Qualcomm announced it would buy the leader in connected car chips NXP for $39B, making it the biggest-ever deal in the semiconductor industry.
5. Most discussed M&A Deal: Cisco/Jasper
In February, Cisco announced that it would buy IoT Platform provider Jasper Technologies for $1.4B. Journalists celebrated the acquisition as a logical next step for Cisco’s “Internet of Everything” story – combining Cisco’s enterprise routers with Jasper’s backend software for network operators and hopefully helping Cisco put an end to declining hardware sales.
6. Largest startup funding: Sigfox
Sigfox already made it into our 2015 IoT news list with their $100M Series D round. Their momentum and the promise of a global Low Power Wide Area Network led to an even larger funding round in 2016. In November, the French-based company received a record $160M in a Series E that involved Intel Capital and Air Liquide among others.
Another notable startup funding during IoT 2016 involved the IoT Platform C3IoT. The Redwood City based company received $70M in their Series D funding.
7. Investment story of the year: IoT Stocks
For the first time IoT stocks outperformed the Nasdaq significantly. The IoT & Industry 4.0 stock fund (Traded in Germany under ISIN: DE000LS9GAC8) is up 17.5% year-on-year, beating the Nasdaq which is up 9.6% in the same time frame. Cloud service providers Amazon and Microsoft are up 14% for the year, IoT Platform provider PTC is up 35%. Even communication hardware firm Sierra Wireless started rebounding in Q4/2016.
Some of the IoT 2016 outperformance is due to an increasing number of IoT acquisitions (e.g., TDK/Invensense). At the beginning of 2016 we asked if the underperformance of IoT stocks in 2015 was an opportunity in 2016. In hindsight, the answer to that question is “Yes”. Will the trend continue in 2017?
8. Most important government initiative: EU Data Protection policy
In May, the European Union passed the General Data Protection Regulation (“GDPR”) which will come into effect on 25 May 2018. The new law has a wide range of implications for IoT technology vendors and users. Among other aspects:
- Security breaches must be reported
- Each IoT user must provide explicit consent that their data may be processed
- Each user must be given the right to object to automated decision making
- Data coming from IoT Devices used by children may not be processed
C. What to expect in 2017:
- War for IoT platform leadership. The large IoT platform providers are gearing up for the war for IoT (platform) leadership. After years of organic development, several larger vendors started buying smaller platform providers in 2016, mainly to close existing technology gaps (e.g., GE-Bitstew, SAP-Plat.one, Microsoft-Solair)
- War for IoT connectivity leadership. NB-IoT will finally be introduced in 2017. The new low-power standard that is heavily backed by major telco technology providers will go head-to-head with existing LPWAN technology such as Sigfox or LoRa.
- AR/VR becoming mainstream. IoT Platform providers PTC (Vuforia) and Microsoft (Hololens) have already showcased a vast range of Augmented Reality / Virtual Reality use cases. We should expect the first real-life use cases emerging in 2017.
- Even more reality and less hype. The attention is shifting from vendor/infrastructure topics such as what the next generation of platforms or connectivity standards will look like and towards actual implementations and use cases. While there are still major developments the general IoT audience will start taking some of these technology advancements for granted and focus on where the value lies. We continue to follow that story and will update our list of IoT projects
Our IoT coverage in 2017: Subscribe to our newsletter for continued coverage and updates. In 2017, we will keep our focus on important IoT topics such as IoT Platforms, Security and Industry 4.0 with plenty of new reports due in Q1/2017. If you are interested in a comprehensive IoT coverage you may contact us for an enterprise subscription to our complete IoT research content.
Much success for 2017 from our IoT Analytics Team to yours!
Original article here.
Most of the attention around automation focuses on how factory robots and self-driving cars may fundamentally change our workforce, potentially eliminating millions of jobs. But AI that can handle knowledge-based, white-collar work are also becoming increasingly competent.
One Japanese insurance company, Fukoku Mutual Life Insurance, is reportedly replacing 34 human insurance claim workers with “IBM Watson Explorer,” starting by January 2017.
The AI will scan hospital records and other documents to determine insurance payouts, according to a company press release, factoring injuries, patient medical histories, and procedures administered. Automation of these research and data gathering tasks will help the remaining human workers process the final payout faster, the release says.
Fukoku Mutual will spend $1.7 million (200 million yen) to install the AI system, and $128,000 per year for maintenance, according to Japan’s The Mainichi. The company saves roughly $1.1 million per year on employee salaries by using the IBM software, meaning it hopes to see a return on the investment in less than two years.
Watson AI is expected to improve productivity by 30%, Fukoku Mutual says. The company was encouraged by its use of similar IBM technology to analyze customer’s voices during complaints. The software typically takes the customer’s words, converts them to text, and analyzes whether those words are positive or negative. Similar sentiment analysis software is also being used by a range of US companies for customer service; incidentally, a large benefit of the software is understanding when customers get frustrated with automated systems.
The Mainichi reports that three other Japanese insurance companies are testing or implementing AI systems to automate work such as finding ideal plans for customers. An Israeli insurance startup, Lemonade, has raised $60 million on the idea of “replacing brokers and paperwork with bots and machine learning,” says CEO Daniel Schreiber.
Artificial intelligence systems like IBM’s are poised to upend knowledge-based professions, like insurance and financial services, according to the Harvard Business Review, due to the fact that many jobs can be “composed of work that can be codified into standard steps and of decisions based on cleanly formatted data.” But whether that means augmenting workers’ ability to be productive, or replacing them entirely remains to be seen.
“Almost all jobs have major elements that—for the foreseeable future—won’t be possible for computers to handle,” HBR writes. “And yet, we have to admit that there are some knowledge-work jobs that will simply succumb to the rise of the robots.”
Original article here.
The CRM market serving the large enterprise is mature. The market has consolidated in the past five years. For example, Oracle has built its customer experience portfolio primarily by acquisition. SAP, like Oracle, aims to support end-to-end customer experiences and has made acquisitions — notably, Hybris in 2013 — to bolster its capabilities. Salesforce made a series of moves to strengthen the Service Cloud. It used this same tactic to broaden its CRM footprint with the acquisition of Demandware for eCommerce in 2016.
These acquisitions broaden and deepen the footprints of large vendors, but these vendors must spend time integrating acquired products, offering common user experiences as well as common business analyst and administrator tooling — priorities that can conflict with core feature development.
What this means is that these CRM vendors increasingly offer broader and deeper capabilities which bloat their footprint and increase their complexity with features that many users can’t leverage. At the same time, new point solution vendors are popping up at an unprecedented rate and are delivering modern interfaces and mobile-first strategies that address specific business problems such as sales performance management, lead to revenue management, and digital customer experience.
The breadth and depth of CRM capabilities available from vendor solutions makes it increasingly challenging to be confident of your CRM choice. In the Forrester Wave: CRM Suites For Enterprise Organizations, Q4 2016. we pinpoint the strengths of leading vendors that offer solutions suitable for enterprise CRM teams. Here are some of our key findings:
- The shift to software-as-a-service (SaaS) is well underway. Forrester Data shows that 1/3 enterprises are using SaaS CRM, and another 1/3 complement their existing solutions with SaaS. We expect SaaS to become the primary deployment model for CRM and that newer SaaS solutions will replace most on-premises installations in the next five years.
- Intelligence takes center stage. Large organizations that manage huge volumes of data struggle to pinpoint optimal offers, discount levels, product bundles, and next best steps for customer engagement. They increasingly turn to analytics to uncover insight and prescribe the right action for the business user to take. Today, leading vendors offer a range of packaged capabilities to infuse decisioning in customer-facing interactions.
- Vendors increasingly invest in vertical editions. Horizontal CRM can only take you so far, as different industries have different requirements for engaging with customers. CRM vendors increasingly offer solutions — templates, common process flows, data model extensions, and UI labels — pertinent to specific industries.
- Customer success rises to the top. In a mature market, you have to dig deep to find real differences between vendor offerings. CRM success depends on the right choice of consulting partners to implement and integrate your solution. CRM vendors are maturing their consulting services, deeply investing in growing regional and global strategic services partners, and investing in customer success to properly onboard customers and actively manage customer relationships. This preserves a company’s revenue stream by reducing churn, expands revenue by increasing customer lifetime value, and can influence new sales via customer advocacy efforts.
Original article here.
Operator and vendor revenues across the main cloud services and infrastructure market segments hit $148 billion (£120.5bn) in 2016 growing at 25% annually, according to the latest note from analyst firm Synergy Research.
Infrastructure as a service (IaaS) and platform as a service (PaaS) experienced the highest growth rates at 53%, followed by hosted private cloud infrastructure services, at 35%, and enterprise SaaS, at 34%. Amazon Web Services (AWS) and Microsoft lead the way in IaaS and PaaS, with IBM and Rackspace on top for hosted private cloud.
In the four quarters ending September (Q3) 2016, total spend on hardware and software to build cloud infrastructure exceeded $65bn, according to the researchers. Spend on private cloud accounts for more than half of the overall total, but public cloud spend is growing much more rapidly. The note also argues unified comms as a service (UCaaS) is growing ‘steadily’.
“We tagged 2015 as the year when cloud became mainstream and I’d say that 2016 is the year that cloud started to dominate many IT market segments,” said Jeremy Duke, Synergy Research Group founder and chief analyst in a statement. “Major barriers to cloud adoption are now almost a thing of the past, especially on the public cloud side.
“Cloud technologies are now generating massive revenues for technology vendors and cloud service providers and yet there are still many years of strong growth ahead,” Duke added.
The most recent examination of the cloud infrastructure market by Synergy back in August argued AWS, Microsoft, IBM and Google continue to grow more quickly than their smaller competitors and, between them, own more than half of the global cloud infrastructure service market.
Original article here.
FEI-FEI LI IS a big deal in the world of AI. As the director of the Artificial Intelligence and Vision labs at Stanford University, she oversaw the creation of ImageNet, a vast database of images designed to accelerate the development of AI that can “see.” And, well, it worked, helping to drive the creation of deep learning systems that can recognize objects, animals, people, and even entire scenes in photos—technology that has become commonplace on the world’s biggest photo-sharing sites. Now, Fei-Fei will help run a brand new AI group inside Google, a move that reflects just how aggressively the world’s biggest tech companies are remaking themselves around this breed of artificial intelligence.
Alongside a former Stanford researcher—Jia Li, who more recently ran research for the social networking service Snapchat—the China-born Fei-Fei will lead a team inside Google’s cloud computing operation, building online services that any coder or company can use to build their own AI. This new Cloud Machine Learning Group is the latest example of AI not only re-shaping the technology that Google uses, but also changing how the company organizes and operates its business.
Google is not alone in this rapid re-orientation. Amazon is building a similar group cloud computing group for AI. Facebook and Twitter have created internal groups akin to Google Brain, the team responsible for infusing the search giant’s own tech with AI. And in recent weeks, Microsoft reorganized much of its operation around its existing machine learning work, creating a new AI and research group under executive vice president Harry Shum, who began his career as a computer vision researcher.
Oren Etzioni, CEO of the not-for-profit Allen Institute for Artificial Intelligence, says that these changes are partly about marketing—efforts to ride the AI hype wave. Google, for example, is focusing public attention on Fei-Fei’s new group because that’s good for the company’s cloud computing business. But Etzioni says this is also part of very real shift inside these companies, with AI poised to play an increasingly large role in our future. “This isn’t just window dressing,” he says.
The New Cloud
Fei-Fei’s group is an effort to solidify Google’s position on a new front in the AI wars. The company is challenging rivals like Amazon, Microsoft, and IBM in building cloud computing services specifically designed for artificial intelligence work. This includes services not just for image recognition, but speech recognition, machine-driven translation, natural language understanding, and more.
Cloud computing doesn’t always get the same attention as consumer apps and phones, but it could come to dominate the balance sheet at these giant companies. Even Amazon and Google, known for their consumer-oriented services, believe that cloud computing could eventually become their primary source of revenue. And in the years to come, AI services will play right into the trend, providing tools that allow of a world of businesses to build machine learning services they couldn’t build on their own. Iddo Gino, CEO of RapidAPI, a company that helps businesses use such services, says they have already reached thousands of developers, with image recognition services leading the way.
When it announced Fei-Fei’s appointment last week, Google unveiled new versions of cloud services that offer image and speech recognition as well as machine-driven translation. And the company said it will soon offer a service that allows others to access to vast farms of GPU processors, the chips that are essential to running deep neural networks. This came just weeks after Amazon hired a notable Carnegie Mellon researcher to run its own cloud computing group for AI—and just a day after Microsoft formally unveiled new services for building “chatbots” and announced a deal to provide GPU services to OpenAI, the AI lab established by Tesla founder Elon Musk and Y Combinator president Sam Altman.
The New Microsoft
Even as they move to provide AI to others, these big internet players are looking to significantly accelerate the progress of artificial intelligence across their own organizations. In late September, Microsoft announced the formation of a new group under Shum called the Microsoft AI and Research Group. Shum will oversee more than 5,000 computer scientists and engineers focused on efforts to push AI into the company’s products, including the Bing search engine, the Cortana digital assistant, and Microsoft’s forays into robotics.
The company had already reorganized its research group to move quickly into new technologies into products. With AI, Shum says, the company aims to move even quicker. In recent months, Microsoft pushed its chatbot work out of research and into live products—though not quite successfully. Still, it’s the path from research to product the company hopes to accelerate in the years to come.
“With AI, we don’t really know what the customer expectation is,” Shum says. By moving research closer to the team that actually builds the products, the company believes it can develop a better understanding of how AI can do things customers truly want.
The New Brains
In similar fashion, Google, Facebook, and Twitter have already formed central AI teams designed to spread artificial intelligence throughout their companies. The Google Brain team began as a project inside the Google X lab under another former Stanford computer science professor, Andrew Ng, now chief scientist at Baidu. The team provides well-known services such as image recognition for Google Photos and speech recognition for Android. But it also works with potentially any group at Google, such as the company’s security teams, which are looking for ways to identify security bugs and malware through machine learning.
Facebook, meanwhile, runs its own AI research lab as well as a Brain-like team known as the Applied Machine Learning Group. Its mission is to push AI across the entire family of Facebook products, and according chief technology officer Mike Schroepfer, it’s already working: one in five Facebook engineers now make use of machine learning. Schroepfer calls the tools built by Facebook’s Applied ML group “a big flywheel that has changed everything” inside the company. “When they build a new model or build a new technique, it immediately gets used by thousands of people working on products that serve billions of people,” he says. Twitter has built a similar team, called Cortex, after acquiring several AI startups.
The New Education
The trouble for all of these companies is that finding that talent needed to drive all this AI work can be difficult. Given the deep neural networking has only recently entered the mainstream, only so many Fei-Fei Lis exist to go around. Everyday coders won’t do. Deep neural networking is a very different way of building computer services. Rather than coding software to behave a certain way, engineers coax results from vast amounts of data—more like a coach than a player.
As a result, these big companies are also working to retrain their employees in this new way of doing things. As it revealed last spring, Google is now running internal classes in the art of deep learning, and Facebook offers machine learning instruction to all engineers inside the company alongside a formal program that allows employees to become full-time AI researchers.
Yes, artificial intelligence is all the buzz in the tech industry right now, which can make it feel like a passing fad. But inside Google and Microsoft and Amazon, it’s certainly not. And these companies are intent on pushing it across the rest of the tech world too.
Original article here.
Robots are going to take a seat at the conference room table in 2017.
Humans are going to be more stressed than ever.
And to stay competitive with their new robot colleagues, workers are going to start taking smart drugs.
That’s according to futurist Faith Popcorn, the founder and CEO of the consultancy Faith Popcorn’s BrainReserve. Since launching in 1974, she has helped Fortune 500 companies including MasterCard, Coca-Cola, P&G and IBM.
Here are five trends you can expect to see in the workplace in 2017, according to Popcorn.
1.Coffee alone won’t keep you competitive.
Employees are going to start taking a burgeoning class of cognitive enhancers called nootropics, or “smart drugs.” These nutritional supplements don’t all have the same ingredients but they reportedly increase physical and mental stamina.
Silicon Valley has been an early adopter of the bio-hacking trend. That’s perhaps unsurprising, as techies were also the first to try the likes of food substitute Soylent. There’s an active sub-reddit page dedicated to the topic.
Nootropics will go mainstream in 2017 because “the robots are edging us out,” says Popcorn. “When you come to work you have to be enhanced, you have to be on the edge, you have to be able to work longer and harder. You have to be able to become more important to your company.”
2.Robots will rise.
Unskilled blue-collar workers will be the first to lose their jobs to automation, but robots will eventually replace white-collar workers, too, says Popcorn, pointing to an Oxford University study that found 47 percent of U.S. jobs are at risk of being replaced.
“Who would you rather have do your research? A cognitive computer or a human?” says Popcorn. “Human error is a disaster. … Robots don’t make mistakes.”
3.Everyone will start doing the hustle.
Already, more than a third of the U.S. workforce are freelancers and will generate an estimated $1 trillion in revenue, according to a survey released earlier this fall by the Freelancers Union and the freelancing platform Upwork. The percentage of freelancers will increase in 2017 and beyond, she believes. “It’s accelerating every year,” says Popcorn.
She also points to some large companies that are building offices with fewer seats than employees. Citibank built an office space in Long Island City, Queens, with 150 seats for 200 employees and no assigned desks to encourage a fluid-feeling environment.
And Popcorn points to the rise of the side hustle: People “need more money than they are being paid,” she says. And they don’t trust their employers. “People are saying, ‘I want to have two or three hooks in the water. I don’t want to devote myself to one company.'”
Younger employees in particular are not interested in working for large, legacy companies like those their parents worked for, according to research Popcorn has done. “We are really turned off on ‘big.'”
4.There will be tears.
While people have always been emotional beings, historically emotions haven’t belonged inside the office. That’s basically because workplaces have largely been run by men. But that’s changing.
“The female entry into the workplace has brought emotional intelligence into the workplace and that comes with emotion,” says Popcorn. “There is a lot of anxiety about the future, there is a lot of stress-related burnout and we are seeing more emotion being displayed in the workplace.”
That doesn’t mean you should start crying on your boss’s shoulder, though. Especially if your boss is male. While women tend to be more comfortable with their feelings, men are still uncomfortable with elevated levels of emotion, says Popcorn, admitting that these gender-based observations are generalizations.
“WE ARE SEEING MORE EMOTION BEING DISPLAYED IN THE WORKPLACE.”
-Faith Popcorn, futurist
Going forward, the futurist expects to see more stress rooms in office buildings and “more of a recognition that people are living under a crushing amount of anxiety.” A stress room would be a welcoming space for employees to go to take a break and perhaps drink kava, a relaxing, root-based tea.
Open floor plans don’t give employees any place to breathe, Popcorn points out: “It’s like being watched 24/7.” Employees put in earbuds to approximate privacy, but sitting in open spaces is not conducive to employee mental health. “It is very stressful to work in the open floors,” she says. “It’s good for real estate, you can do it with fewer square feet, but it’s not particularly good for people.”
5.The boundary between work and play will crumble.
“People are going to be working 24 hours a day,” says Popcorn. Technology has enabled global, constant communication. The WeLive spaces that WeWork launched are indicative of this trend towards work and life integration, she says. “There is no line between work and play.”
Original article here.