20 Top Tech Predictions for 2017

20 Top Tech Predictions for 2017

Will Machine Learning quickly cede way to Deep Learning in 2017? What happens when Artificial Intelligence (AI) aces non-verbal voice recognition? Could that be “read my lips” meets the Minority Report? What are the implications if you and your car become emotionally interdependent? Is that even healthy? Just remember, breaking up is hard to do.

Those were some of the extraordinary and unexpected predictions shared by the experts who participated in the five-part series on Coffee Break with Game-Changers  2017 Predictions Special, presented by SAP. Host Bonnie D. Graham asked 80 leading experts, academics, and business influencers what they see in their crystal ball for 2017. Each person was given just two minutes to share their predictions for what the next year holds for their industry, business, the world, and technology.

Here’s a sample of what they had to say:

  • Dematerialization is going to continue. We’ll see hardware that is thinner and lighter. New materials are coming on the market, like stretchable electronics. Imagine what that could do for wearable technologies. Everything is going to be computing in the future, whether it’s your shoes, clothes, or the temporary tattoo that you wear to monitor your health.
    – Gray Scott, Futurist, Founder and CEO at SeriousWonder.com and techno philosopher
  • In 2017, we’re going to finally see that Artificial Intelligence components combined with highly sophisticated in-memory platforms are going to meld together. 2017 is going to be the year that brings end-to-end seamless communications and connections of consumers, public, clients, and citizens with business leaders and public officials. This will trigger leaders to take action at the speed-of-thought.
    –  Guillermo B. Vazquez, Specialist Leader / Senior Manager, Deloitte LLP
  • We’re going to see the blending of the digital and physical worlds come together. Virtual Reality and Augmented Reality are going to balloon in 2017. We’re going to see a lot more in digital twins: digital documentation of a physical thing so we can understand it better.
    – Rick Varner, Senior Executive Partner, Gartner Inc.
  • We see a lot of implications for security in the Internet of Things (IoT) – devices, medical devices, smart TVs, and (even) coffee machines. Those devices are getting more and more connected to the Internet to become smarter. But we are already seeing these devices are being used to launch attacks and to be targets. In 2017, we will see more attacks and more measures against those attacks.
    – Alon Kantor, Vice President of Business Development, Check Point
  • 2017 is the year that Isaac Asimov’s Psychohistory starts becoming real. Big Data and machine learning will combine to enhance mathematical sociology – enabling us to make sense of what happens to groups of people in society.
    – Timo Elliott, VP, Global Innovation Evangelist, SAP
  • In 2017, I see the beginnings of “cognitive” at the personal level – beyond Alexa, Cortana, and Google – by being able to access all data in the cloud in an intelligent way. For example, at the store you might see a new television and ask your phone to advise you, “Can I afford this?” An intelligent agent will go to your bank account and bring back that information.
    – Jerry Silva, Research Director, IDC Financial Insights Global Banking
  • We’re going to see a lot of drones. We’ll see drones-as-a-service in many businesses where drones are going to be put to work for us.
    – Sudha Jamthe, CEO, IoT Disruptions
  • 2017 is the year for blockchain I predict an awakening will take place on a global scale about what this technology is capable of and how it’s going to impact everyday citizens, governments, and businesses. One particular blockchain to watch is the Ethereum
    – Hilary Carter, Founder, InTune Communications
  • Business-by-voice will be a new name in 2017. Screen-based technology will go away in 2017 and will be replaced by voice. New startups will emerge to deliver voice-enabled cognitive applications that can think, learn, and talk to the users.
    – Surendra Reddy, Founder & CEO, Quantiply Corporation
  • As we grow bigger and stronger on mobile, Internet of Things, and sensors, we have to manage that information and react to it much quicker than we currently do sending it up to the cloud and then bringing it back. When we talk about connected cities, grids, and vehicles, decisions have to be happen in a millisecond. There has to be a way to access that information more quickly and manage it closer to the devices. Therefore, there’s going to be a huge investment in fog computing.
    – Laz Uriza, Senior Solution Principal, Extended Supply Chain CoE, SAP
  • Human experts are going to be assisted, not replaced, through technology advances. The correct interpretation of data, when it comes to specific businesses and people, is going to require human intelligence and expertise for years to come. Computer systems that are used to automate these processes can make recommendations; they’re a lot stronger in processing standard cases than they are in addressing exceptions. Sometimes those exceptions require a more intimate understanding of context and empathy.
    –  Dror Orbach, Chief Operating Officer, Illumiti
  • There are four big game-changers in 2017: Artificial Intelligence (AI) will help us think of cognitive as the new “smart”; augmented reality (AR) and virtual reality (VR) will go mainstream; 5G technologies will be on the road in autonomous self-driving vehicles; blockchain technology will gain broader adoption.
    – Bridget Karlin, Managing Director, IoT Strategy and Technology Office, Intel Corporation
  • AI is going to go mainstream in 2017, both in ways you can see and in ways you can’t. We know that over half of corporate executives are investing heavily in artificial intelligence. It’s showing up in visual search; enterprise operations with cognitive computing and semantic matching; retail assortment planning and offer management; and semantic recognition.
    – Jeff Goldberg, Managing Director for Retail in North America, Accenture
  • There’s no doubt that healthcare reform is going to be a topic this year. Medical identity theft is an $84 billion dollar a year problem. Payment fraud is another problem. Also, electronic medical records have 10 percent duplicate records. A combination of these issues is creating a disturbance in the quality of data that physicians have at the point of care. Solving these problems is going to have to be the focus this year if we’re really going to get serious about value-based care.
    – Thomas Foley, Global Health Solutions Strategy Manager, LenovoHealth
  • Blockchain distributed ledger technology will mature. There will be a lot of little breakthroughs this year, and recognition of its broader applicability is going to grow. Today people associate it with Bitcoin and payment technology, but there are so many ways to put the technology to use. Walmart uses blockchain to establish authentication and traceability in its food chain; a French financial services company started a blockchain project to establish compliance with customer rules; and there’s an anti-counterfeiting blockchain service that can be used for authenticating diamonds and luxury goods.
    – Robert Kugel, CFA, Senior Vice President and Research Director, Ventana Research
  • Artificial Intelligence (AI) will become a key factor as we move toward autonomous vehicles. Cars will learn how to drive. Vehicles will be conscious. The vehicle will become your partner. And your car will get emotionally attached to you. That means breaking up will be hard to do.
    – Larry Stolle, Senior Global Director of Automotive Marketing, SAP
  • We will start to see the emergence of abilities to protect information assets using AI. But hackers will also use AI to improve their attack capabilities. AI-sponsored attacks and defense could emerge. Also, AI-enabled toolkits will disrupt the traditional cyber-security products, services, and architectures. I’m seeing more startups and ventures that sponsor AI-enabled products for security.
    – Carlos Russell, Risk Management Director, Ternium
  • We’ll see incredible applications where human behavior and human meaning will intersect with AI in completely new ways. We’re starting to now see AI become better than humans at interpreting what humans mean. In the case of lip reading, or non-verbal voice recognition, AI is now almost four times better than the leading world experts. That means not only performing recognition of somebody’s lips, but also understanding the context and the meaning of what people say.
    – Rich Seltz, Vice President, Digital Transformation, SAP
  • Computers will “disappear” due to their ubiquity. For computers to disappear, first their boundaries have to blur. There are some ways we’ve seen this happening on the infrastructure side – with physical computers that a company might have owned becoming eventually dedicated, co-located boxes, becoming eventually lease servers, and now virtualized systems. Another example is Amazon’s Lambda, where you can write your software as a set of individualized functions that are each much simpler than a monolithic program running on a computer. When you have your apps using Lambda, it’s like having your software’s consciousness spread out and decomposed across dozens of different physical brains.
      Ken Redler, Chief Technology Officer and Partner, cSubs
  • Machine Learning is passé. In 2017 everybody will be talking about Deep Learning for solving big problems. Also, IoT will finally find a scalable problem to solve: we will finally find something in transportation due to all the autonomous vehicles that will be coming online.
    – Padman Ramankutty, Chief Executive Officer, Intrigo

20 Top Tech Predictions for 2017

Advertisements

Five Resolutions to Simplify Your Tech Life

Five Resolutions to Simplify Your Tech Life

In 2017, why not try a new kind of New Year’s resolution? Instead of just hitting the gym and dropping some pounds, consider changing some personal habits to simplify the tech in your life.

If you are like most people, there are things you do with tech that could use some tweaking. Strengthening your password security, for one, would benefit you tremendously in an era when hacks are rampant. For another, purging the e-junk you have accumulated over the years would help the environment and your sanity. While you’re at it, start doing maintenance on your electronics to make sure they work smoothly this year.

Here are my top recommendations for resolutions to abide by to make tech less frustrating in the new year.

Clean Up Your Password Hygiene

P.U. — what’s that smell? It’s your bad password hygiene. You are probably using the same password across multiple websites for banking, shopping, social media and email.

That’s understandable: A person can only memorize so many passwords. But in 2016, Yahoo reminded everybody that reusing passwords is a very bad idea, after it revealed that 500 million Yahoo accounts were compromised in 2014, in addition to 1 billion accounts that were hacked in 2013. If your Yahoo account password was the same as ones you used elsewhere, those accounts were vulnerable, too.

Start off 2017 by spending a few hours logging into each of your accounts and creating unique, strong passwords. To make this easier, use applications like LastPass or 1Password, which are password-managing apps that let you use one master password to unlock a vault of passwords to log in to all of your internet accounts. They also automatically generate strong passwords for you.

Then add an extra layer of protection by enabling two-factor verification on your accounts whenever the option is available. When you enter your password, you will receive a message (usually a text) with a one-time code that you must enter before logging in.

Taking these two simple steps will help safeguard you from the inevitable hacks that arise this year.

Maintain Your Devices

25techfix-web-articlelarge

After regular use, our smartphones and computers start to feel sluggish and short-lived, but a bit of maintenance can make them feel brand new.

First, check the condition of your batteries. With iPhone and iPads, you can hook the devices up to a Mac and run the app coconutBattery, which reveals battery statistics. With Android devices, you can use the app Battery by MacroPinch.If your battery is on its last legs, it’s time to order a new one or schedule an appointment at a repair shop to replace it.

If your devices feel sluggish, freeing up some storage can also make a dramatic difference. Start by purging apps you never use anymore. Then do something about those photos you never look at: back up all your photos to the cloud using services like Google Photos and then delete them from your device to start the new year with a fresh photo roll.

Show your gadgets some physical love, too.Give your screens a good wipe with a wetted cloth. If you own a desktop computer, open it up and use compressed air to blow out the dust.

Do this basic maintenance every six months and your devices will run smoothly for many years.

Mind Your Infrastructure

30techfixillo-articlelarge

We don’t hesitate to buy new smartphones every two years — but that neglected, ugly Wi-Fi router tucked away in the corner of the living room may be the most important tech product to upgrade every few years. Among all tech headaches, there is nothing more annoying than a sluggish, spotty internet connection.

Start off each new year by doing some checks on your internet infrastructure. If your router is more than three years old, you probably need a new one that is compatible with today’s faster, smarter wireless standards. If you are relying on a router provided by your broadband provider, you should probably buy a more powerful stand-alone router.

The Wirecutter, the product recommendations website owned by The New York Times, recommends TP-Link’s Archer C7 as the best router for most people. (If you have less technical know-how, I recommend the Wi-Fi system from Eero, which offers a smartphone app that holds your hand through the network setup.)

Be Less Wasteful

03techfix-illo-articlelarge

Unused gadgets and power cables take up lots of space in drawers and attics. This e-waste would be better off sold or donated to someone in need, or recycled for their precious metals.

During spring cleaning season, make plans to get this unwanted junk out of your life. Companies like Amazon and Gazelle offer headache-free trade-in services for selling used electronics. Just punch in the gadget you are trying to trade in, like a used iPhone or Samsung Galaxy device, and the sites offer a quote for how much money or Amazon store credit you can get in exchange for the gear. Then pack up the outdated hardware, slap on a shipping label, drop it off at a shipping center and wait for the money to roll in.

There is bound to be unsellable e-junk in your pile. Fortunately, all Best Buy locations will take your used electronics and recycle them for free. Just bag the items up and drop them off at the store’s customer-service counter, and the retailer will take care of the rest.

Be a Smarter Shopper

26techfix-web-articlelarge

To get great deals on electronics, there is no need to wait until Black Friday or Cyber Monday. Carefully research high-quality, long-lasting items you want and buy them when their prices drop a significant amount. This technique can be used when online shopping for just about anything, but especially for tech products that decrease in price as they age.

Web tools like Camel Camel Camel and Keepa make price tracking on Amazon.com easy. On their websites, just do a search on the name of the item, and the sites will pull up a price history. From there, you can create a tracker to alert you via email whenever a price drops to a desired amount.

Many deals that emerge throughout the year are as good, or better, than the ones on Black Friday. You just have to know how to spot them.

Another way to save money is to consider buying used products whenever possible. Be on the lookout for sales of used or refurbished electronics from reputable brands like Apple, GameStop, Amazon and Gazelle. Before you buy a used item, read about its condition carefully: Often, products sold as used were barely touched before they were returned by a customer, or they were restored to good-as-new condition by a refurbishing center.

Five Resolutions to Simplify Your Tech Life

The Data Center Can’t Scale, But That’s Changing With Hyperconvergence

The Data Center Can’t Scale, But That’s Changing With Hyperconvergence

The Data Center Can’t Scale, But That’s Changing With Hyperconvergence

Hyperconvergence can help companies of all sizes reach new levels of data center speed and resilience. It’s become the “go to” solution for any organization looking to simplify, streamline, and lower IT costs. Here’s why.

In the rapid-paced digital economy, business interactions and decision-making happen instantly, enabled by access to a range of resources, from group messaging apps and data analytics to social media tools and cloud services. Such exchanges are at the heart of the dynamic nature of business today, which has evolved quickly while the data centers that provide the support to make these interactions possible have remained static.

IT’s usual approach has been to build a unified data center infrastructure using diverse network, server, and storage components sourced from multiple vendors—a process that’s not only time-consuming and expensive but also out of sync with the increasing demand for data center simplicity and agility.

Research from IDC has shown that global spending on big data infrastructure, which consists of compute, network, storage, and security, will grow at a CAGR of 21.7 percent, and will account for roughly half of all spending in the big data and technology services market through 2019.1 What’s surprising, however, is that a significant portion of that investment is focused on merely keeping up with growing end-user and application demands.

Many organizations face other obstacles, including budgetary constraints as well as scalability challenges and management issues.

Converged infrastructure (CI) and hyperconverged infrastructure (HCI) offer dynamic flexibility and performance levels to meet the needs of enterprises. Both are modular-based deployments that integrate separate data-center elements to deliver higher density and improved availability. They offer the advantage of simply adding clusters to meet the processing needs of a growing business.

In addition to gaining consistent application and data access, HCI adoption enables organizations to quickly scale from maintaining relatively small, traditional workloads to achieving high performance computing affordably. HCI in particular solves the limitations of traditional legacy infrastructures by eliminating information and infrastructure silos, simplifying overall management, and ensuring new levels of data center responsiveness.

Benefits of Converged and Hyperconverged Infrastructure

Companies are being seriously impacted by exponential data increases and the constant demand for applications and services. They regularly face a complex range of IT demands from the inside and the outside. For example, internal end users require a high degree of data access and application responsiveness from any device while customers and partners expect those same levels of always-on availability.

Moreover, IT managers are constrained by outmoded approaches to providing support, such as manual provisioning and deployments, which are time-consuming and resource intensive. However, simply adding new infrastructure won’t solve the problem. It only increases costs, management complexity, and data center sprawl.

Converged infrastructure answers that need by combining compute and storage elements into one physical appliance preconfigured by the manufacturer. Organizations can simply plug the appliance into the fabric of their existing data center to achieve desired performance levels, enabling fast workload provisioning and new deployments in a matter of hours and days instead of weeks and months.

Hyperconverged infrastructure takes that integration one step further by extracting the physical controls and making them operable in software running on low-cost, standardized x86 hardware. With virtual compute, storage, and networking, IT can create systems from similar server-based building blocks, expand by adding new clusters, and manage everything from one interface. HCI not only eliminates the need for IT specialists, it also strengthens overall performance by:

  • Reducing data center footprint
  • Optimizing resource allocation
  • Improving failover capabilities
  • Integrating automation, orchestration, and analytics

As IT leaders confront the unique set of demands brought about by the growth of third platform technologies (i.e., mobility, social media, big data, cloud services, etc.), they’re looking to hyperconverged infrastructure to provide much-needed resource consistency.

Overcoming Data Center Deficits With Hyperconverged Infrastructure

Remote office and branch office (ROBO) environments can be a critical part of many enterprise operations, but they often lack specialized IT support. Hyperconvergence enables dynamic, easily managed compute and storage to meet that changing demand. For example, instead of complex, high-cost traditional server and storage architecture, HCI can provide inexpensive, instantly scalable multinode deployments.

Such affordability is especially important in the public sector, such as state and local governments and education (SLED). Frequently tasked with handling diverse, complicated workloads on a limited budget, these institutions require locally accessible resources for a broad variety of use cases. Hyperconvergence can simplify these deployments as well as natively integrate data protection to ensure fast and comprehensive disaster recovery.

It’s difficult to overstate the seriousness of unplanned downtime due to a data center outage. Besides the financial impact, loss in worker productivity, and decline in customer confidence, brand reputation can suffer long-term consequences. Hyperconverged solutions contain built-in resiliency features, including virtual machine (VM) snapshots, advanced analytics, deduplication, and automation that can offset the risk of downtime caused by data center outages or human error.

Benefits of Lenovo and Nutanix Together

The Lenovo and Nutanix partnership is built on long-standing reputations and offers a hyperconverged solution that combines Nutanix Xpress software with Lenovo’s System x servers. According to a recent Gartner Research report, “HCIS will be the fastest-growing segment of the overall market for integrated systems, reaching almost $5 billion, which is 24 percent of the market, by 2019.”2

The growing popularity of hyperconvergence demonstrates just how quickly the current data center is changing. For small and medium-sized businesses (SMBs), the attraction to HCI is based not only on affordability, but also on finding a solution that offers comprehensive support services in a complete package.

As one of the largest suppliers of x86 servers in the world, Lenovo offers customers a high level of support as well as HCI upgrade services and maintenance, including hardware warranty, 24×7 software support, and onsite coverage to ensure successful HCI deployments. Customer confidence in Lenovo is based on the company’s heritage of extensive x86 deployments within data centers globally and a well-established portfolio outside of hyperconverged systems. The Lenovo 1U (1-node) and 2U (4-node) form factors provide a hyperconverged system with a simple management framework in an open, modular book design that can be easily serviced and upgraded in the rack.

At its core, HCI is about configuring traditional data center infrastructure (compute, storage, networking) into one single package. The Lenovo Converged HX Series Nutanix Appliance pools resources into a single shared virtual structure that increases utilization and ensures greater availability while at the same time reducing the IT burden. Natively integrated data protection includes simple virtual machine (VM) backup, disaster recovery, and replication, eliminating the need for traditional storage area network (SAN) and network area storage (NAS).

Taking the Next Step

Today, companies of all sizes are confronting the limitations of traditional, legacy infrastructures as they try to modernize their data centers to embrace digital transformation. Trends such as cloud computing, data analytics, and new levels of user mobility along with application delivery, to name a few, are placing heavy demand on these IT environments.

Lenovo is shaping the next generation data center to help companies reduce complexity to meet these ever-changing demands while lowering costs. For more information on how to achieve new performance levels through hyperconvergence, please visit the lenovo website.

The Data Center Can’t Scale, But That’s Changing With Hyperconvergence

Serverless is the new multitenancy

Serverless is the new multitenancy

Serverless is the new multitenancy

Multitenancy was the single-biggest technology breakthrough in SaaS. Consider this: With more than 100,000 customers, a company like Salesforce would need 100,000-plus servers and databases to serve their needs, essentially wiping out its margins.

Multitenancy not only allowed for higher gross margins, it made it viable to serve small and medium businesses with world-class software  —  at a profit. It was not just a new architecture, but also changed the way we thought of paying for enterprise software —  not by number of CPUs or servers but by users and usage. Similarly, serverless compute is both a new way of building apps and a new way of consuming and paying for it.

Serverless takes the promise of multitenancy to a whole new level. Serverless compute is a computational model where no dedicated server or VM needs to be up and running, as the platform activates and then shuts down the processing, scaling it as needed. You truly pay for only what you need.

unnamed (1)

Multitenancy won — everyone else lost

In the first decade of SaaS, companies like Salesforce and NetSuite were hardcore proponents of multitenancy, while legacy vendors portrayed it as a compromise, often calling it “risky commingling of customer data.”

The No. 1 leader in enterprise applications software, SAP, invented its own architecture, called mega-tenancy, to compete with multitenancy, while Oracle, the leading database vendor, tried to sell virtualized private databases and other innovations as an alternative. Today, these companies have acquired the likes of Ariba, Concur and NetSuite for tens of billions of dollar and committed to the winning architecture —  multitenancy.

Serverless architecture

With serverless architecture, we are seeing a whole new range of applications emerging. When it comes to IoT, mobile apps and real-time big data, serverless architecture can be a huge advantage.

 Amazon Lambda is seen as a clear leader in this space, while other products like PubNubBlocks and Azure Functions are also building on the same idea. In a few years, every cloud platform will have to support some form of serverless architecture.

Just like the move to multitenancy, you can’t take your existing code and simply make itserverless; you must rethink your applications and rewrite to use these new frameworks.

Making the impossible cheap and possible

Multitenancy allowed SMBs to get enterprise-grade applications for CRM (Salesforce), accounting (NetSuite), marketing (Marketo), hiring (SmartRecruiters), etc. at prices they could afford.

With the deluge of data, especially real-time data, it is cost-prohibitive for many use cases to process it and act on it. Serverless computing makes it much more inexpensive by charging you only for the fraction of the time it takes to run your functions.

I look forward to new applications being unleashed by this new architecture and business model over the next 10 years. What Salesforce- and NetSuite-sized companies will this newarchitecture make possible?

Serverless is the new multitenancy

How Blockchain Technology Is Disrupting Everything

How Blockchain Technology Is Disrupting Everything

How Blockchain Technology Is Disrupting Everything

Blockchain technology is best known for being the magic behind Bitcoin, but there are scores of other industries that are benefiting from this revolutionary technology. Before we take a look at the industries and companies innovating in these spaces, let’s break down this technology so we are all on the same page.

Blockchain technology is a big fancy word that describes the act of recording events in a database. The database itself is referred to as the blockchain. Once data is added to the blockchain, it cannot be removed from the database or altered in any way. The blockchain therefore contains a verifiable record of history.

The technology is fairly simple yet very profound. You might already be thinking of a business idea that could utilize such a system, and many visionaries are in the same boat. Steve Wozniak, co-founder of Apple, has joined a blockchain firm. But before you go start a round of fundraising for your own blockchain-based company check out the disruption the blockchain is creating in these industries.

1. Voting

The voting industry has gone essentially unchanged for centuries. Many would say that it is in dire need of innovation! Even “modern” electronic voting systems offer little improvements. In the past few years many states have actually de-certified voting machines due to certain vulnerabilities. By design, blockchain technology eliminates the need for paper ballots and provides unparalleled security.

One company out of Blacksburg, Virginia is disrupting the voting industry with blockchain technology.Follow My Vote is a non-partisan organization on a mission to restore faith in the democratic process. This is being done through a revolutionary voting platform built on a blockchain.  To take on this project Follow My Vote has partnered with BitShares, a leader in blockchain technology and development.

This means convenient and secure voting from your smart phone, tablet, or computer. Follow My Vote sees this as a great way to increase voter turnout by appealing to tech-savvy millennials. Skeptics can be at ease due to the record checking ability of the blockchain. Blockchain technology also offers advancements in transparency, by providing voters with the ability to confirm that their vote was counted. The company has also developed a revolutionary way to let users check their vote yet retain the secrecy of the ballot. And rest assured, voters will still be anonymous in the system to other voters. Check out their blockchain technology infographic for a more in depth look at blockchain technology and how they use it within their system.  The company is also proud to say that the system features state-of-the-art ID verification. Follow My Vote does not see an immediate and complete migration to online voting. The fact is that not every state is ready for online voting. The system will hopefully be introduced simply as an option to conventional voting methods. However, new reports on online voting by organizations such as the U.S. Vote Foundation are promising and show that companies like Follow My Vote are on the right path.

2. Finance

For many, the financial industry is the first that comes to mind when thinking about blockchain technology. Bitcoin is one of the best-known applications of the technology and has a very strong brand in the digital currency space. Bitcoin has simply been a game changer for many people around the world. The book The Age of Cryptocurrency: How Bitcoin and Digital Money Are Challenging the Global Economic Order by Paul Vigna and Michael J. Casey breaks down the digital currency movement and is a perfect intro to the blockchain. Bitcoin Magazine described the book in the following way:

“The book opens with an implemented use case for Bitcoin. Because of Bitcoin young women in Afghanistan are able to write blogs and do social media and video production. In exchange for this work, they are paid in Bitcoin. Bank wires required a lot of fees. And PayPal wasn’t supported. With Bitcoin, these young women could be paid instantly.”

Blockchain technology provides cryptocurrencies, such as Bitcoin, with a verifiable ledger of transactions. This ledger, paired with the security of a distributed network allows people to leave middlemen and banks behind and fully take control of their digital money.

Blockchain technology also allows for smart contracts and market-pegged assets. The developers behindBitShares have pioneered these blockchain innovations. Smart contracts are essentially computer programs that can automatically execute the terms of a contract. Instead of money just going from A to B, now you can choose to send or not to send money if certain constraints are met. For example, a payment will not be recorded on the blockchain unless the receiving party signs a contract, or a certain date has passed. Currently you can set recurring and scheduled payments on the BitShares smart contract platform. The BitShares ecosystem also hosts several market-pegged assets. This is revolutionary due to the fact that many crypto currencies are subject to price fluctuations. BitShares provides stable cryptocurrencies that have their value pegged to another asset. Some of the most popular assets on BitShares are pegged to the US Dollar, gold, and the Chinese Yuan. These price stable crypto currencies always have 100% of their value or more backed by the BitShares core currency.

Mainstream financial enterprises are also taking advantage of this technology. In May, NASDAQ announceda blockchain initiative to help improve its platform. NASDAQ CEO Bobo Greifeld stated,”Our initial application of NASDAQ’s blockchain technology-enabled offering will modernize, streamline, and secure typically cumbersome administrative functions, and will simplify the overwhelming challenges private companies face with manual ledger record-keeping.”

3. Music

The music industry has some really cool companies trying to transform the scene with blockchain technology. What if you could use your awesome music finding skills to make money and support musicians? This is essentially what Peertracks is creating. With Peertracks, people can buy equity in an artist or song similar to crowdfunding models. The idea is, you would find out about Taylor Swift before she got famous. If you had bought Taylor Swift tokens, you would be supporting her music career in the beginning and later on reap the benefits of increased token value when she has a number one hit.

The blockchain can also be used for music streaming. A recent report by Rethink Music suggests that blockchain technology could be used to ensure musicians are paid fairly and quickly for sales and streams of their work. The blockchain adds a great deal of transparency. This would be beneficial for artist and industry leaders to see into the process of splitting royalties, as it would be obvious if publishers and record labels were holding on to royalties before giving them to the artist.

4. Ownership

The blockchain is perfect for keeping records of ownership. Factom is using the blockchain to help businesses and governments manage data and keep records. Financial records secure our money. Real estate records secure our property. And citizen records secure our credit and identities. All these records can be hacked or maliciously changed if they exist in a centralized location. With blockchain technology, all the information is replicated across the servers that run the system. It is nearly impossible to hack a distributed processing network. This is one of the blockchain’s greatest assets.  You will now have undisputable proof and records of ownership. And to top it off, you own the records and share them with those you trust.

5. Fighting counterfeits

Another blockchain-based company is using this revolutionary technology to build an anti-counterfeit solution. Blockverify is bringing transparency from the blockchain to supply chains.  Blockverify can verify counterfeit products, diverted goods, stolen merchandise, and fraudulent transactions. Some of the best use cases the solution will target include pharmaceuticals, luxury items, diamonds, and electronics.

Now that you have an idea of the industries being taken by storm by the blockchain, you too can create your own blockchain company! Or at least invest in one.

How Blockchain Technology Is Disrupting Everything

How data science fights modern insider threats

How data science fights modern insider threats

How data science fights modern insider threats

Insider threats are the biggest cybersecurity threats to firms, organizations and government agencies. This is something you hear a lot at security conference keynotes and read about in data breach reports, white papers and surveys — and these insider threats are becoming increasingly more difficult to detect and prevent, as well as more frequent.

This seemingly unstoppable growth accentuates the problem and shortcomings of current solutions, and warrants the need for new defensive technologies to detect and stop the digital daggers aimed at our backs.

Data science — the application of mathematics, big data analytics and machine learning to extract knowledge and detect patterns — is an emergent, advanced technology area that is proving its effectiveness in the realm of cybersecurity, including fighting insider threats. Here’s how it succeeds where legacy solutions fail.

The need to focus on user behavior

The wide adoption of cloud services and mobile technology in companies has transformed IT infrastructures considerably.

With physical boundaries of corporate networks and digital assets not as clearly defined as they once used to be, the focus in fighting insider threats needs to shift toward protecting user accounts. “Now that the traditional security perimeter has been erased by mobile and cloud computing, identities have become both an attack vector and security perimeter,” says Tom Clare, VP of marketing at cybersecurity startup Gurucul.

“What has changed recently is the fact that control of user accounts has become far more valuable than control of devices,” says Jarno Niemelä, lead researcher at F-Secure Labs. “Years back, we were fighting against keeping computers clean from infection just to keep the computers clean. Nowadays, we are protecting computers just to be able to protect the user accounts that are on the computer.”

Organizations try hard to protect user identities by adopting different security solutions and training employees on the basics of cybersecurity, but it’s not enough.

“Good data hygiene is critical, but it is not enough,” says Stephan Jou, CTO at Interset. “A negligent employee is unlikely to change regardless of training, and a third-party attacker often can operate outside employee-focused processes. More importantly, the insider stealing for espionage is motivated to break rules.”

Insider threats are becoming increasingly more difficult to detect and prevent, as well as more frequent.

The truth is that credential theft does happen, and it happens a lot. In fact, a Verizon 2015 data breach report found that the majority of confirmed security incidents occur as a result of compromised user accounts. Massive lists of user credentials and passwords are being sold on the Dark Web at low prices, and, for a small fee, anyone can obtain access to all sorts of enterprise networks and cloud services, and impersonate legitimate users.

Therefore, fighting insider attacks hinges on detecting anomalous user behavior. But this again presents its own set of challenges, because defining normal and malicious behavior is not an exact science and involves a lot of intricacies.

Traditional security defenses rely on setting static rules and alerts on user activities in order to define and identify indicators of compromise (IoCs). But when applied to tens, hundreds and thousands of users, this model ends up generating a noisy flood, and security teams have to struggle with wasted time and must sort through tons of unimportant events that are mostly false positives. Meanwhile, actions don’t necessarily explain intents, and savvy attackers will be able to cloak their malicious activities by keeping them within the defined set of rules.

The use of data science can help move away from static models toward dynamic ones that are able to define normal user behavior based on identities, roles and working circumstances. This approach is very effective in reducing false positives and highlighting behavior that truly accounts for malicious activities.

Cybersecurity firms are increasingly leveraging this technology to deal with insider threats.

Analyzing user behavior through machine learning

Gurucul’s Risk Analytics security platform combines machine learning models with big data to understand normal baselines of behavior and uncover anomalies, and to provide visibility that spans identities, accounts, access and activity. “This behavioral analytics approach, sometimes called user behavior analytics or UBA, can detect excess access permissions and activity, define roles and detect unknown threats,” says Gurucul’s Clare.

The wide adoption of cloud services and mobile technology in companies has transformed IT infrastructures considerably.

Gurucul’s Risk Analytics also gathers and monitors identity-based data and activity from both on-premises and cloud environments. Its machine learning algorithms, including self-learning and training behavioral profile algorithms, look at every new transaction and risk scores it. Using clustering and outlier machine learning makes suspicious behavior stand out from other benign activities.

One of the features of Gurucul is its concept of dynamic peer groups. The system automatically groups users based on the types of activities they typically perform and the types of identities and privileges they hold. This allows for a tighter clustering of behavior and better chances in highlighting outlier activities in behavior patterns.

So if a sales employee is downloading large amounts of company data for the purpose of later surrendering it to a competitor, they will stand out and be marked for investigation even if they have legitimate access to the information, because their behavior deviates from that of their peers.

The math behind insider threat detection

Interset is another cybersecurity platform that relies on semi-supervised machine learning and advanced behavioral analytics to examine and correlate scattered bits of data in order to find insider threats. Its platform analyzes data from multiple sources related to the movement of data across or within a network, while also gathering information about the entities involved, which include users, endpoints and applications.

The math behind Interset’s data science model is based on three key ideas. First, it replaces traditional boolean alerts with probabilistic models or risk factors. Models that emit probabilities are more effective than true/false alerts and allow the use of math to combine multiple pieces of evidence across different data sets to define the likelihood of a user account having been compromised or engaged in illicit activities.

Second, it uses machine learning to define dynamic thresholds for each actor based on gathered data, a much more flexible model than globally applied rules such as “how many megabytes of attachments are allowed.” The “mathematical fingerprint” that results from the analysis of user-generated data makes it much easier to identify anomalous behavior.

Shifting to new technologies such as data science can help find the needle in the haystack.

Third, the platform moves away from the event level and uses math to correlate, corroborate and aggregate events to attribute risk to the higher-level actors involved. What results from this model is the ability to name names, i.e. determine who is stealing data instead of figuring out which of the hundreds of transactional events indicate data is being stolen.

This is the platform that, according to Interset’s Jou, “would have detected and surfaced Edward Snowden’s activities in a matter of hours.”

Complementing analytics with human expertise

“From a technical point of view, we are looking at actions conducted by user accounts,” F-Secure’s Niemelä explains, “and it doesn’t really matter that much whether the malicious operations being carried out are by the original owner of the account, or has someone been able to compromise said account.”

The Finnish firm’s latest security offering, Rapid Detection Service (RDS), is a platform that protects against both inside and outside threats. Niemelä calls it “a system that is capable of detecting both insiders and attackers who have been able to compromise some user account and are, in effect, an ‘insider’.”

The managed service uses a combination of threat intelligence, big data analytics, machine learning and security experts to deliver accurate, actionable data about security alerts and detect anomalies and signs of insider threats.

“Most users have rather clean and repeating patterns in their work from a statistics point of view,” Niemelä says. “Thus, alarming changes in the users’ behavior can be detected with suitable near real-time statistics analysis tools, supported by heuristics and machine learning systems.”

Organizations try hard to protect user identities by adopting different security solutions and training employees on the basics of cybersecurity, but it’s not enough.

RDS collects data from different sources, including behavioral information from corporate endpoints, and detects when a user account starts behaving in an unusual manner. The use of near-real-time analytics, stored data analytics and big data analytics enables the RDS platform to compare user behavior against baseline standards, historical data and known threats in order to detect signs of malicious activities while filtering out false positives.

What’s unique about F-Secure’s approach is the team of human experts who verify and provide incident response on anomalies detected by its machine learning engine. When a breach is confirmed, the client is contacted and informed.

Amplifying malicious insider activity to ease detection

LogRhythm tackles insider threats from a slightly different perspective, and takes the mindset that the adversary has already likely breached the perimeter, explains Greg Foss, Security Operations Lead at the security vendor, “so our detections primarily focus on tracking attacker activity once they are inside.”

The company’s User Threat Detection module provides insider threat detection capabilities through honeypot analytics and open-source honeypot solutions. Honeypots are decoys or cyber traps that lure malicious hackers and enable security software to detect, deflect or counteract their nefarious activities.

LogRhythm has researched honeypots, deception and sensitive file tracking to determine ways to trick attackers and track them as they move through an organization. “The trick is not to make compromise impossible but to ensure that it is loud and noticeable so that the SOC can detect and respond to the threat,” Foss explains.

Foss also stresses network flow analysis as another key piece of the puzzle when it comes to detecting insider threats. “A lot of people ask what threat feeds they should use to help find bad guys on their network,” Foss says. “I often inform them that they already have everything they need right in front of them, they just need to start looking closely at the data they are already collecting.”

LogRhythm uses Deep Packet Analytics to investigate huge amounts of network traffic and catch malicious insiders when they want to exfiltrate sensitive information, and also to detect compromised network nodes such as machines conducting packet capturing activities.

Dealing with the threats of the future

With organizations using more online services and generating more data than ever, insider threats will become increasingly complicated and harder to find. Shifting from traditional methods to new approaches and technologies such as data science can help find the needle in the haystack and speed the process of detecting and blocking insider threats before they cause irreversible damage.

How data science fights modern insider threats

These are the best laptops for under $200

These are the best laptops for under $200

These are the best laptops for under $200

Great news! If you only have $200 to spend on a laptop, your options are far better than they used to be. While these machines aren’t built for hardcore gaming or video editing, they’re more than enough for web browsing and writing papers.

These days, sub-$200 laptops commonly ship with HD displays, full Windows 10 (rather than something more limited, like Google’s Chrome OS), and a decent chunk of internal storage. Many also come with a free year of Microsoft Office 365—perfect for the students they’re targeting.

To find the best of this affordable bunch, we put the most popular models through a series of performance and display tests in our state-of-the-art labs. Then we put them to the test at our desks, to get a feel for real-world factors like keyboard feel, trackpad responsiveness, and build quality.

The result? We can tell you with authority that if you want the best affordable laptops available today, these are the ones to buy.

This article was originally published on Reviewed.com. See more at Reviewed.com’s best laptops for every kind of student. Also see their recommendations for the best laptops.

Best Overall: Asus E402SA

fg-asus-.jpg

The Asus E402SA (also known as the EeeBook E402SA) won us over right away. While it’s not much faster than its competition, its 14-inch screen is bigger than most. The display is a mere 1366 x 768 pixels, but it’s glossy, looks great, and isn’t a major drain on the battery. Its $249 MSRP is a little above our target price, but we’ve seen it on sale as low as $179.

Under the hood, the E402SA has the same Intel Celeron N3050 processor as most of the best sub-$200 laptops, but it’s one of the few to offer both VGA and ethernet jacks. It also includes a full-sized SD memory card slot and two USB ports (one is even USB 3.0). Its trackpad is mediocre, but the full-sized keyboard is very comfortable to type on. Our favorite feature is the E402SA’s expandability; turn one screw to remove the bottom panel and you can upgrade your storage with any 2.5-inch laptop hard drive or SSD.

Dell Inspiron 11 3000 (2016)

Who says a cheap laptop can’t be pretty? This Dell offers up an attractive design, solid build quality, and the port selection we expect from a new laptop these days (USB 3.0, HDMI, and a microSD slot). Based around Intel’s ubiquitous Celeron N3050 dual-core processor, it performs pretty much like any other laptop in its class. It also sports a decent trackpad, but its keyboard feels a bit cramped.

The Inspiron 11 3000’s ($180) biggest flaw is the included McAfee install, which can be a real hog on system resources and annoys with frequent popups. But all things considered, Dell offers up a package that’s colorful, modern, and just fast enough for schoolwork or surfing the web. It may not be inspiring, but this Inspiron is worth its asking price.

Acer Aspire One Cloudbook 11

This Acer isn’t a looker, but it’s got what it takes on the inside. Its cramped keyboard has a weird layout, but on the positive side, the Aspire One Cloudbook 11 ($180) has a very responsive trackpad that works well with gestures. Sporting an Intel Celeron N3050 dual-core chip, this small laptop fits the bill if you have limited needs. It might keep you waiting from time to time, but it’s got just enough oomph for Word, Excel, a few Chrome tabs, or older games.

While you can find a 16GB version, you should avoid that one at all costs; our test model had 32GB of storage and even that filled up right away. You can add more memory with an SD card, but since it’s not microSD, it’ll stick out the side of the machine. In our opinion, your best bet for inconspicuous extra storage on the Acer Aspire One Cloudbook 11 is probably a low profile USB drive.

Lenovo Ideapad 100s (Windows)

Lenovo’s Ideapad 100s ($200) impressed us as a Chromebook, but the Windows 10 version falls short of expectations. Its mediocre keyboard, basic trackpad (don’t expect scrolling or zooming gestures), and plasticky feel don’t do it any favors. It’s available in a bunch of different colors, but that does little to distract from its underwhelming performance.

Inside, it has an older Intel Atom Z3735F chip. It may be quad core, but it’s still slower than the Celeron N3050 dual-core processor found in rival machines. The 100s is also stuck with USB 2.0 ports, which can’t keep up with the 3.0 ports on better machines. It’s not all bad though. You can add storage through the compact microSD slot, the hinge rotates a full 180 degrees, and it had the best battery life of any of the sub-$200 models we tested.

HP Stream 11 (2016)

str11_Enhanced_productivity_1900X953.jpg

We liked the HP Stream last year, and are happy to see the line continue with this year’s updated model ($200). Revamped from the ground-up, the playful Stream 11 is a little bigger than its 11-inch competition, but that makes for a keyboard that’s much more pleasant to use. Its keys are almost full-sized, and the typing feel is pretty good for this part of the market. With Intel’s Celeron N3050 inside, the Stream isn’t great at multitasking, but can tackle lighter work without breaking a sweat.

The worst part of using the Stream 11 is its iffy trackpad, which isn’t nearly as responsive as we’d like. The screen also seemed a little duller than the rest of our test group. Unfortunately, HP also bundles McAfee with this computer; it’s a pain, but you can uninstall it to speed things up.

Lenovo IdeaPad 100s (Chromebook)

If you’re shopping for a Chromebook, we thought that the affordably-priced Lenovo IdeaPad 100s ($180) was pretty solid. Even though you won’t be able to run Android apps, for only around $175, we can’t get too upset. It’s a lot like the Windows-based IdeaPad 100s we tested for this article, but it has a slightly better trackpad and, of course, runs Google’s ChromeOS.

It’s competitively spec’d thanks to an Intel N2840 processor, 2 GB of RAM, and 16 GB of storage. It’s the right price for a simple Chromebook, without spending more than $200.

These are the best laptops for under $200

34 Most Disruptive Technologies of the Next Decade

34 Most Disruptive Technologies of the Next Decade

34 Most Disruptive Technologies of the Next Decade

Research firm Gartner released its annual report this week on hype in technology, sharing which technologies are up-and-coming, which are at peak hype, and which have moved well into mainstream territory.

You probably won’t be surprised to learn that machine learning is riding the highest crest of the “peak of inflated expectations” wave. You might be surprised, though, by the technologies coming up behind it.

For those who associate the term “hype” with failure, realize that that’s what this report is bringing into focus. Instead, it highlights “the set of technologies that is showing promise in delivering a high degree of competitive advantage over the next five to 10 years,” Mike J. Walker, research director at Gartner, said in a statement.

The phases of the hype cycle, as outlined in a graph created by Gartner, are as follows: Innovation Trigger, Peak of Inflated Expectations, Trough of Disillusionment, Slope of Enlightenment, and finally, Plateau of Productivity.

Basically: There’s a breakthrough, a flurry of press coverage touting successes, a bunch of failures that ultimately contribute to disillusionment, then people start to understand the technology more, and it goes mainstream. Some examples of the timeline from the report: Augmented reality is currently in the Trough of Disillusionment, and virtual reality is on its way up the Slope of Enlightenment. But no matter where they are on the cycle, these technologies all are important to keep on your radar, whether your business currently intersects with them or not.

Now for some technologies you might never have heard of that Gartner predicts are going to be pretty big:

1. Smart Dust

This refers to little things called “motes,” which Gartner defines in a research note for the report as “tiny wireless micro-electromechanical systems (MEMS), robots, or other devices that can detect everything from light, temperature, and pressure to vibration, magnetism, and chemical composition.” CNN put it this way in 2010: Smart dust aims to monitor everything.

2. 4-D Printing

You’ve heard of 3-D printing, the quick fabrication of three-dimensional products with a machine that essentially “prints” the products. The fourth dimension in this next-gen fabrication process is the encoding in the end product of “a dynamic capability–either function, confirmation, or properties–that can change via the application of chemical, electronic, particulate, or nanomaterials,” according to Gartner. Examples the firm offers: “printed pipe valves that can expand or contract and printed cubes that unfold.”

3. 802.11ax

What is this? It looks like a random series of numbers and letters. Will people be referring to this verbally, talking about the promise of eight-oh-two-point-eleven-ay-ex? Not unless they’re already talking about eight-oh-two-point-eleven-ay-see (802.11ac), to which 802.11ax is the successor. What we’re talking about here is technology aimed at improving performance of Wi-Fi-enabled devices and supporting a larger number of them. Development of this technology is still in early stages according to Gartner, but expect it to be important as the number of connected “Internet of Things” devices continues to grow.

These are just three items on Gartner’s list of technologies moving through the hype cycle, and the 34 technologies on the list may not include ones the firm included in past years.

Here are all the technologies in the report:

  • Smart Dust
  • 4-D Printing
  • General-Purpose Machine Intelligence
  • 802.11ax
  • Context Brokering
  • Neuromorphic Hardware
  • Data Broker PaaS (dbrPaaS)
  • Quantum Computing
  • Human Augmentation
  • Personal Analytics
  • Smart Workspace
  • Volumetric Displays
  • Conversational User Interfaces
  • Brain-Computer Interface
  • Virtual Personal Assistants
  • Smart Data Discovery
  • Affective Computing
  • Commercial UAVs (Drones)
  • IoT Platform
  • Gesture Control Devices
  • Micro Data Centers
  • Smart Robots
  • Blockchain
  • Connected Home
  • Cognitive Expert Advisors
  • Machine Learning
  • Software-Defined Security
  • Autonomous Vehicles
  • Nanotube Electronics
  • Software-Defined Anything (SDx)
  • Natural-Language Question Answering
  • Enterprise Taxonomy and Ontology Management
  • Augmented Reality
  • Virtual Reality

34 Most Disruptive Technologies of the Next Decade