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[Source: This article was published in theverge.com By Loren Grush - Uploaded by the Association Member: Issac Avila]

Now it just needs to launch more satellites

OneWeb — an aerospace company with plans to beam internet connectivity from space — announced plans today to provide “fiber-like internet” coverage to the Arctic starting as early as 2020. Using the company’s planned mega-constellation of satellites, the company says it can provide high-speed internet to homes, boats, and planes all located above the 60th parallel north latitude.

OneWeb is one of many companies aiming to provide internet from space using a complex array of satellites and ground stations. The company plans to launch an initial constellation of 650 spacecraft that will beam internet connectivity to a series of ground terminals on Earth’s surface. These vehicles will orbit at a relatively low altitude, decreasing the time it takes to beam coverage to the surface below. With so many satellites, OneWeb says it can provide global coverage, with at least one satellite in view of any area of the Earth at all times.

That coverage extends to the Arctic, which is a difficult place to lay fiberoptic cables and provide traditional internet connectivity. OneWeb claims that its satellite constellation will be able to provide high-speed internet to the 48 percent of the Arctic that currently doesn’t have broadband coverage. Local politicians are thrilled with the idea, arguing that it will help with economic development in the area.

“Connectivity is critical in our modern economy,” Sen. Lisa Murkowski (R-AK) said in a statement. “As the Arctic opens, ensuring the people of the Arctic have access to affordable and reliable broadband will make development safer, more sustainable and create new opportunities for the next generation leading in this dynamic region of the globe.”

“CONNECTIVITY IS CRITICAL IN OUR MODERN ECONOMY.”

So far, OneWeb has only launched the first six satellites in its constellation, but the company says it was able to conduct some HD video streaming tests with the spacecraft in July. The tests proved that the satellites are operational and have a relatively low latency — under 40 milliseconds in lag time.

Other companies, notably SpaceX and Amazon, are also working to create mega-constellations of satellites that are meant to be even larger than OneWeb’s constellation. In April, Amazon detailed plans to launch a constellation of more than 3,200 satellites, while SpaceX has proposed launching two constellations that will contain nearly 12,000 satellites in total.

SpaceX has already launched the first 60 satellites in its constellation, though three of the first batch failed after reaching orbit. OneWeb argues that its constellation will be deployed “significantly earlier” than other planned constellations, allowing the company to provide coverage to the Arctic sooner than other systems. The company cites the fact that it already has two active ground stations in Norway and Alaska, which are needed to help connect OneWeb’s satellites to the current internet ground infrastructure. Those stations are supposed to be fully operational by January 2020, according to OneWeb, allowing this rollout to the Arctic by next year.

“Connectivity is now an essential utility and a basic human right,” OneWeb CEO Adrian Steckel said in a statement. “Our constellation will offer universal high-speed Arctic coverage sooner than any other proposed system meeting the need for widespread connectivity across the Arctic.”

OneWeb plans to launch its satellites in batches of 36 aboard Arianespace’s Soyuz rocket. The next launch is slated for later this year.

Categorized in Science & Tech

 [Source: This article was Published in electronicdesign.com BY William G. Wong - Uploaded by the Association Member: Jay Harris]

No overarching artificial intelligence looms on the horizon, but machine-learning tools can make applications do some magical things.

I was talking with a friend recently about artificial intelligence (AI) and machine learning (ML), and they noted that if you replaced AI or ML with the word magic, many of those discussions would be as useful and informative as before. This is due to a number of factors, including misunderstanding about the current state of affairs when it comes to AI, ML, and more specifically, deep neural networks (DNNs)—specifically, what ML models are actually doing and not comprehending how ML models are used together.

I hope that those who have been working with ML take kindly to my explanations because they’re targeted at engineers who want to understand and use ML but haven’t gotten through the hype that even ML companies are spouting. More than half of you are looking into ML, but only a fraction is actually incorporating it into products. This number is growing rapidly though.

ML is only a part of the AI field and many ML tools and models are available, being used now, and in development (Fig. 1). DNNs are just a part; other neural-network approaches enter into the mix, but more on that later.

I was talking with a friend recently about artificial intelligence (AI) and machine learning (ML), and they noted that if you replaced AI or ML with the word magic, many of those discussions would be as useful and informative as before. This is due to a number of factors, including misunderstanding about the current state of affairs when it comes to AI, ML, and more specifically, deep neural networks (DNNs)—specifically, what ML models are actually doing and not comprehending how ML models are used together.

I hope that those who have been working with ML take kindly to my explanations because they’re targeted at engineers who want to understand and use ML but haven’t gotten through the hype that even ML companies are spouting. More than half of you are looking into ML, but only a fraction is actually incorporating it into products. This number is growing rapidly though.

ML is only a part of the AI field and many ML tools and models are available, being used now, and in development (Fig. 1). DNNs are just a part; other neural-network approaches enter into the mix, but more on that later.

0711TR_Machine_Learnging_Fig_1_-_0615Wtd-Deep-Learning-Fig-2.png

1. Neural networks are just a part of the machine-learning portion of artificial-intelligence research.

Developers should look at ML models more like fast Fourier transforms (FFTs) or Kalman filters. They’re building blocks that perform a particular function well and can be combined with similar tools, modules, or models to solve a problem. The idea of stringing black boxes together is appropriate. The difference between an FFT and a DNN model is in the configuration. The former has a few parameters while DNN model needs to be trained.

Training for some types of neural networks requires thousands of samples, such as photos. This is often done in the cloud, where large amounts of storage and computation power can be applied. Trained models can then be used in the field since they normally require less storage and computation power as their training counterparts. AI accelerators can be utilized in both instances to improve performance and reduce power requirements.

Rolling a Machine-Learning Model

Most ML models can be trained to provide different results using a different set of training samples. For example, a collection of cat photos can be used with some models to help identify cats.

Models can perform different functions such as detection, classification, and segmentation. These are common chores for image-based tools. Other functions could include path optimization or anomaly detection, or provide recommendations.

A single model will not typically deliver all of the processing needed in most applications, and input and output data may benefit from additional processing. For example, noise reduction may be useful for audio input to a model. The noise reduction may be provided by conventional analog or digital filters or there may be an ML model in the mix. The output could then be used to recognize phonemes, words, etc., as the data is massaged until a voice command is potentially recognized. 

Likewise, a model or filter might be used to identify an area of interest in an image. This subset could then be presented to the ML-based identification subsystem and so on (Fig. 2). The level of detail will depend on the application. For example, a video-based door-opening system may need to differentiate between people and animals as well as the direction of movement so that the door only opens when a person is moving toward it.

0711TR_Machine_Learning_Fig_2.png

2. Different tools or ML models can be used to identify areas of interest that are then isolated and processed to distinguish between objects such as people and cars.

Models may be custom-built and pretrained, or created and trained by a developer. Much will depend on the requirements and goals of the application. For example, keeping a machine running may mean tracking the operation of the electric motor in the system. A number of factors can be recorded and analyzed from power provided to the motor to noise and vibration information.

Companies such as H2O.ai and XNor are providing prebuilt or customized models and training for those who don’t want to start from scratch or use open-source models that may require integration and customization. H2O.ai has packages like Enterprise Steam and Enterprise Puddle that target specific platforms and services. XNor’s AI2Go uses a menu-style approach: developers start by choosing a target platform, like a Raspberry Pi, then an industry, like automotive, and then a use case, such as In-cabin object classification. The final step is to select a model based on latency and memory footprint limitations (Fig. 3).

0711TR_Machine_Learnging_Fig_3_AI2GO.png

3. Shown is the tail end of the menu selection process for XNor’s AI2Go. Developers can narrow the search for the ideal model by specifying the memory footprint and latency time.

It’s Not All About DNNs

Developers need to keep in mind a number of factors when dealing with neural networks and similar technologies. Probability is involved and results from an ML model are typically defined in percentages. For example, a model trained to recognize cats and dogs may be able to provide a high level of confidence that an image contains a dog or a cat. The level may be lower distinguishing a dog from a cat and so on, to the point that a particular breed of animal is recognized.

The percentages can often improve with additional training, but changes usually aren’t linear. It may be easy to hit the 50% mark and 90% might be a good model. However, a lot of training time may be required to hit 99%.

The big question is: “What are the application requirements and what alternatives are there in the decision-making process?” It’s one reason why multiple sensors are used when security and safety are important design factors.

DNNs have been popular because of the availability of open-source solutions, including platforms like TensorFlow and Caffe. They have found extensive hardware and software support from the likes of Xilinx, NVIDIA, Intel, and so on, but they’re not the only types of neural-network tools available. Convolutional neural networks (CNNs), recurrent neural networks (RNNs), and spiking neural networks (SNNs) are some of the other options available.

SNNs are used by BrainChip and Eta Compute. BrainChip’s Akida Development Environment (ADE) is designed to support SNN model creation. Eta Compute augments its ultra-low-power Cortex-M3 microcontroller with SNN hardware. SNNs are easier to train than DNNs and their ilk, although there are tradeoffs for all neural-network approaches.

Neurala’s Lifelong-DNN (LDNN) is another ML approach that’s similar to DNNs with the lower training overhead of SNNs. LDNN is a proprietary system developed over many years. It supports continuous learning using an approximation of lightweight backpropagation that allows learning to continue without the need to retain the initial training information. LDNN also requires fewer samples to reach the same level of training as a conventional DNN.  

There’s a tradeoff in precision and recognition levels compared to a DNN, but such differences are similar to those involving SNNs. It’s not possible to make direct comparisons between systems because so many factors are involved, including training time, samples, etc.

LDNN can benefit for AI acceleration provided by general-purpose GPUs (GPGPUs). SNNs are even more lightweight, making them easier to use on microcontrollers. Even so, DNNs can run on microcontrollers and low-end DSPs as long as the models aren’t too demanding. Image processing may not be practical, but tracking anomalies on a motor-control system could be feasible. 

Overcoming ML Challenges

There are numerous challenges when dealing with ML. For example, overfitting is a problem experienced by training-based solutions. This occurs when the models work well with data similar to the training data, but poorly on data that’s new. LDNN uses an automatic, threshold-based consolidation system that reduces redundant weight vectors and resets the weights while preserving new, valid outliers.  

ML models can address many tasks successfully with high accuracy. However, that doesn’t mean all tasks, regardless if they’re a conventional classification or segmentation problem, can be accommodated. Sometimes changing models can help or develop new ones. This is where data engineers can come in handy, though they tend to be rare and expensive.

Debugging models can also be a challenge. ML module debugging is much different than debugging a conventional program. Debugging models that are working within an application is another issue. Keep in mind that models will often have an accuracy of less than 100%; therefore, applications need to be designed to handle these conditions. This is less of an issue for non-critical applications. However, apps like self-driving cars will require redundant, overlapping systems.

Avalanche of Advances

New systems continue to come out of academia and research facilities. For example, “Learning Sensorimotor Control with Neuromorphic Sensors: Toward Hyperdimensional Active Perception” is a paper out of the University of Maryland’s engineering department. Anton Mitrokhin and Peter Sutor Jr., Cornelia Fermüller, and Computer Science Professor Yiannis Aloimonos developed a hyperdimensional pipeline for integrating sensor data, ML analysis, and control. It uses its own hyperdimensional memory system.

ML has been progressing like no other programming tool in the past. Improvements have been significant even without turning to specialized hardware. Part of this is due to improved software support to optimizations that increase accuracy or performance while reducing hardware requirements. The challenge for developers is determining what hardware to use, what ML tools to use, and how to combine them to address their application.

It’s worth making most systems now rather than waiting for the next improvement. Some platforms will be upward-compatible; however, others may not. Going with a hardware-accelerated solution will limit the ML models that can be supported but with significant performance gains, often multiple orders of magnitude.

Systems that employ ML aren’t magic and their application can use conventional design approaches. They do require new tools and debugging techniques, so incorporating ML for the first time shouldn’t be a task taken lightly. On the other hand, the payback can be significant and ML models may often provide the support that’s unavailable with conventional programming techniques and frameworks.

As noted, a single ML model may not be what’s needed for a particular application. Combining models, filters, and other modules require an understanding of each, so don’t assume it will simply be a matter of choosing an ML model and doing a limited amount of training. That may be adequate in some instances, especially if the application matches an existing model, but don’t count on it until you try it out.

Categorized in Science & Tech

[Source: This article was Published in ibvpn.com By IBVPN TEAM - Uploaded by the Association Member: Alex Gray] 

Since when are you an Internet user? For quite a while, right?

How many times have you asked yourself which are the dangers that might hide at the other side of your connection and how a VPN software can help you? You’re about to read this article which means you’ve asked yourself this question at least once.

This article will give you all the information you need to know about the advantages of VPN plus a list of tips and tricks that will make your life easier.

Are you ready?

By the way, if you are aware of the benefits a VPN brings, it’s time to start using it!

Get ibVPN!

Let’s start at the beginning, shall we?

The VPN (Virtual Private Network) technology came as an answer to individuals’ request to protect their online activities and to maintain their online confidentiality.

Besides this functionality, the technology helps internet users access restricted content from anywhere in the world, with just a click of a mouse.

Therefore, we can say that a VPN is a secure solution that allows its users to send and receive data via the internet while maintaining the privacy and confidentiality of their data, based on its encryption level. The cherry on top is that a VPN will unblock the internet, by providing you the most-wanted Internet freedom that you deserve.

It’s obvious that because of people’s security need and especially because of the need for sending encrypted data over a network, the VPN technology has been developed. But besides the role of creating a “private scope of computer communications,” VPN technology has many other advantages:

  1. Enhanced security. When you connect to the network through a VPN, the data is kept secured and encrypted. In this way, the information is away from the hackers’ eyes.

  2. Remote control. In the case of a company, the great advantage of having a VPN is that the information can be accessed remotely even from home or from any other place. That’s why a VPN can increase productivity within a company.

  3. Share files. A VPN service can be used if you have a group that needs to share data for an extended period.

  4. Online anonymity. Through a VPN you can browse the web in complete anonymity. Compared to hide IP software or web proxies, the advantage of a VPN service is that it allows you to access both web applications and websites in complete anonymity.

  5. Unblock websites & bypass filters. VPNs are great for accessing blocked websites or for bypassing Internet filters. This is why there is an increased number of VPN services used in countries where Internet censorship is applied.

  6. Change IP address. If you need an IP address from another country, then a VPN can provide you this.

  7. Better performance. Bandwidth and efficiency of the network can generally be increased once a VPN solution is implemented.

  8. Reduce costs. Once a VPN network is created, the maintenance cost is very low. More than that, if you opt for a service provider, the network setup and surveillance is no more a concern.

Here is how your connection looks while using a VPN!

Advantages of VPN_your connection

Other things you need to know:

The advantages and benefits of a VPN are clear, let’s find out how to choose your VPN service and your new VPN service provider.

As a future VPN user, keep something in mind: the process of choosing and buying a VPN service should work the same as the process of doing a regular purchase.

Public networks are a real threat. The private networks are not very safe either because your internet service provider can throw an eye on anything you do. You can never be sure if you’re about to connect to a secured network unless you keep your internet activity safe.

So, no matter if you are looking for a VPN to encrypt your traffic while browsing the internet, to bypass geo-restrictions or you’re just the kind of person who likes to save some bucks while buying plane tickets, here’s what you future VPN should provide:

  • Free VPN Trial. Yes, maybe you’ve done some research on your own and saw those Five Best VPN articles all around the web. These articles are useful because are providing you information about VPN services at affordable prices, their performance, and features. When you can test these services by yourself, the experience is even better. That’s why is important to choose a VPN that provides you with a Free VPN Trial.

  • Speed. Do you have the patience to wait tons of seconds for your page to load while using a VPN? No, who has? Always look for the VPN that improves your internet connectivity, not slows it down!

  • Connectivity and reliability. Before buying a VPN service, you have to make sure that it assures you a safe/without drops connection.

  • The number of servers. The number of servers is an important thing for you to look into a VPN service. Before subscribing to a VPN provider, make sure it provides you a large number of servers around the globe.

  • Apps is compatible with various operating systems. I’m sure about one thing – you have more than one device you use to surf the web. There’s a significant probability for your devices do have different operating systems. An important thing that you should keep in mind is that your VPN provider should be able to meet your need by providing you with apps compatible with as many operating systems as possible.

  • The number of simultaneous connections. We are (almost) always online from more than one device, that’s why the number of concurrent connection is important.

  • Customer support. Not all of us are tech-savvy and, from time to time, even the experienced ones need help and guidance. Choosing a VPN provider with outstanding customer support is mandatory. Look for a VPN that allows you to contact the support via e-mail, support ticket systems and live chat. You will thank us later for this tip! ?

  • Privacy policy. One of the primary purposes of a VPN is to keep your online activities away from the curious eyes of any third party. If you don’t allow your ISP to spy on you, why would you let your VPN service provider do it? Choose a VPN service that has a transparent way of saying and doing things and make sure it won’t keep any connection logs. So, always check their Privacy Policy first, before subscribing!

  • Check their reviews page. We were mentioning above some things about the VPN reviews websites. Those websites are doing their reviews based on some tests. Wouldn’t be awesome to be able to find out what the actual customers of a VPN provider have to say about the service and its performance? Here’s a tip: if your future VPN service provider has its own reviews page, throw an eye on it.

Are you ready for some action?

Now that you know which are the advantages of a VPN, their value, and how you should choose one, it’s time for some action.

If you’re curious to test on your own the benefits of a VPN, you can do it for free, right now.
ibVPN is the perfect choice for those who care about their online privacy and freedom.

What do you have to do? It’s easy:

  1. Create a trial account – no credit card required

  2. Download a suitable app for your device(s)

  3. Enjoy a secure and open internet by connecting to one of the 180+ servers we are providing.

If you’re happy with the performance of our service, you can always subscribe to one of our premium plans.

Go Premium!

Keep in mind that a VPN has its limitations too!

Just like any other thing in this world, a VPN service has its advantages and disadvantages.

So, if you’re not an experienced technician or if you’re trying a security solution aka a VPN for the very first time, make sure you won’t dig that deep into the VPN’s settings. Before doing advanced settings into your app, please make sure you know what you’re doing otherwise, you might risk having leaks or your activity exposed.

Another thing that you should know if that, from time to time, a VPN can have connection drops. These drops are perfectly normal, that’s why you should make sure you’re connecting to a server that’s not overloaded.

Tips and tricks.

We want to make sure you make the most out of your VPN service, that’s why we have a list of tips and tricks which will help you a lot.

We have over 15 years of experience in providing our customers with security solutions so, listen to the old ones this time. ?

  1. KillSwitch. To assure the safety of your network connection, a VPN offers (or it should provide) features that enhance your level of security. One of these features is the KillSwitch. If you have never heard about it before, this feature assures your safety in case of connection drops. There are two kinds of KillSwitches: The Internet KillSwitch which will block your internet traffic in case of VPN drops and the Application Killswitch which ensures you that a list of selected apps will be closed, in case your VPN connection drops. So, for a secure connection, always use the KillSwitch!

  2. Use P2P servers. Some of you might use a VPN service to download torrents safely. To avoid any problems with your ISP, use only the P2P server for such activities!

  3. Use Double VPN. If you’re lucky enough to have Double VPN servers in your list, make sure you use them. Double VPN technology allows you to browse anonymously by connecting to a chain of VPN servers. In simple words: VPN on top of VPN (or VPN tunnel inside another VPN tunnel). Double VPN is all about VPN tunnels and levels of security and encryption. Isn’t it awesome?

  4. Use Stealth VPN or SSTP protocols. If you’re living in a country with a high censorship level and your connection gets blocked even if you use a VPN, make sure you change the protocol and try to use Stealth VPN or SSTP. These two VPN protocols are high-speed and secure and, for example, Stealth VPNwill mask your VPN traffic and will make it look like regular web traffic. In this way, you can bypass any restriction or firewall.

  5. Use VPN + Tor. Since Tor is used to mask very sensitive information, the frequent use of this browser might light the bulb of your ISP and mark you for surveillance. That’s why the safe way is to connect to a VPN server while using the Tor browser.

  6. Leak protection. Check your VPN app’s settings and, if it allows you, make sure you check all the options that keep you away from any leak (DNS leaks, IPv6 leak protection, etc.).

  7. Use the VPN on your mobile devices too. It’s not enough to keep it safe only when you use a laptop. Public wifis are real threats that’s why you should always be connected to a VPN.

  8. Test the server network before connecting. Why are we saying this? Well, this practice assures you that you will connect to the fastest server for you. And who doesn’t love a fast server?

  9. Use browser extensions. A browser extension is a super useful tool. There are cases when you need to change your IP fast and easy and to open your app, entering your details and choosing the desired server is somehow complicated, and it takes time. If your VPN provider provides you not only VPN clients compatible with different operating systems but browser extensions too, make sure you use them…

  10. Smart DNS. This neat and useful technology allows you to access blocked streaming channels, regardless of your region. If your VPN provider has such an option, make sure you use it to watch your favorite media content while you’re far away from home.

  11. Save money by using a VPN. Who doesn’t like traveling? Here’s a piece of advice: search online for a flight, compare the prices and then go back to the page you have initially accessed. There are 80% chances that the rates have been increased. If you’re wondering how this is even possible, let us explain. Some online ticket agencies have preferential prices for different countries. Save some extra bucks using a VPN!

Are you still here?

As you can see, the discussion about VPN technology and its advantages is so complicated. We could talk about it for days.

What you should keep in mind after reading this article is that no matter if you’re looking for the best option to browse anonymously, to unblock your favorite online content, to download torrents or to watch for the cheapest plane tickets, a VPN can always help you.

Besides its disadvantages, a VPN has tons of advantages, and it allows you to keep your personal information safe in the first place.

There are lots of fishes in the sea, make sure you choose the one that meets your needs.

Always browse safely!

Categorized in Internet Privacy

Source: This article was Published waterworld.com - Contributed by Member: Mercedes J. Steinman

Access to the BWinnovate database is open to the worldwide web but is much more focused than a regular search engine.

LONDON, UK, SEPT 11, 2018 -- An innovation search engine that can help match utilities, industrial users and contractors with the water technologies they need has been launched by British Water. BWinnovate complements the trade association's popular onsite Innovation Exchanges with utilities and other client organizations and the supply chain.

The searchable portal is hosted on the trade association's website and seamlessly integrates with its member database. Members are invited to post as many innovative 'solutions' as they wish along with images, documents, and video links.

Access to the searchable database is open to the world wide web. A facility for member utilities and end-users to post their technology 'needs' in a section visible only to other members is also included.

Paul Mullord, UK director, British Water said, "BWinnovate is a natural extension of our popular Innovation Exchanges where supply chain companies present their services and technologies to potential clients. It allows our members to present to a global audience and facilitates detailed searches to help identify the most appropriate solutions available.

"BWinnovate is much more focused than a regular search engine and the benefit goes both ways. Those searching for innovations can find them all in one place and at their convenience."

British Water has worked closely with its members to identify the most effective search criteria for the solutions. Prescribed categories include whether the solutions enhance health and safety, productivity and sustainability or whether they are water, wastewater or environmental solutions.

Doug Workman, president of Modern Water Monitoring said, "The water industry needs innovation, but it is not always easy for busy project managers and consultancies to identify the most appropriate technologies. Modern Water will certainly be making use of BWinnovate and the more companies that get involved, the greater the benefit for customers."

Dr. Stephen Bird, managing director, South West Water said, "BWinnovate is a very useful search engine for utilities. It creates an easily accessible library of innovation across multiple companies. It sits in one place, can be accessed at any time and is continually updated. It could save businesses valuable time and contribute to major cost savings across all operations."

Mullord added, "The industry is under considerable pressure to cut costs while conserving water and reducing carbon footprint. BWinnovate can help stakeholders identify solutions that can truly benefit their customers. I believe it will prove particularly beneficial in the new retail market."

Categorized in Search Engine

 Source: This article was published econsultancy.com By Rebecca Sentance - Contributed by Member: William A. Woods

What does the future hold for voice search? If you search the web for these words – or a version of them – you’ll encounter no shortage of grand predictions.

“By 2020, 30% of web browsing sessions will be done without a screen.” Or, “By 2020, 50% of all searches will be conducted via voice.” (I’ll come back to that one in a second). Or, “2017 will be the year of voice search.” Oops, looks like we might have missed the boat on that last one.

The great thing about the future is that no-one can know exactly what’s going to happen, but you can have fun throwing out wild predictions, which most people will have forgotten about by the time we actually get there.

That’s why you get so many sweeping, ambitious, and often contradictory forecasts doing the rounds – especially with a sexy, futuristic technology like voice. It doesn’t do anyone any real harm unless for some reason your company has decided to stake its entire marketing budget on optimizing for the 50% of the populace who are predicted to be using voice search by 2020.

However, in this state of voice search series, I’ve set out to take a realistic look at voice search in 2018, beyond the hype, to determine what opportunities it really presents for marketers. But when it comes to predicting the future, things get a little murkier.

I've made some cautious predictions to the tune of assuming that if smart speaker ownership increases over the coming years, voice search volume will also likely increase; or that mobile voice search might be dropping away as smart speaker voice search catches on.

In this article, though, I'll be looking at where voice search as a whole could be going: not just on mobile, or on smart speakers, but of any kind. What is the likelihood that voice search will go "mainstream" to the point that it makes up as substantial a portion of overall search volume as is predicted? What are the obstacles to that? And what does this mean for the future of voice optimisation?

Will half of all searches by 2020 really be voice searches?

I'm going to start by looking at one of the most popular predictions that is cited in relation to voice search: "By 2020, 50% of all searches will be carried out via voice."

This statistic is popularly attributed to comScore, but as is often the case with stats, things have become a little distorted in the retelling. The original prediction behind this stat actually came from Andrew Ng, then Chief Scientist at Baidu. In an exclusive interview with Fast Company in September 2014, he stated that "In five years' time, at least 50% of all searches are going to be either through images or speech."

The quote was then popularised by Mary Meeker, who included it on a timeline of voice search in her Internet Trends 2016 Report, with "2020" as the year by which this prediction was slated to come true.

So, not just voice search, but voice and visual search. This makes things a little trickier to benchmark, not least because we don't have any statistics yet on how many searches are carried out through images. (I'm assuming this would include the likes of Google Lens and Pinterest Lens, as well as Google reverse image search).

Let's assume for the sake of argument that 35% of Ng's predicted 50% of searches will be voice search, since voice technology is that bit more widespread and well-supported, while a visual search is largely still in its infancy. How far along are we towards reaching that benchmark?

I'm going to be generous here and count voice queries of every kind in my calculations, even though as I indicated in Part 1, only around 20% of these searches can actually be ranked for. Around 60% of Google searches are carried out on mobile (per Hitwise), so if we use Google's most recent stat that 1 in every 5 mobile searches is carried out via voice, that means about 12% of all Google searches (420 million searches) are mobile voice queries.

In Part 2 I estimated that another 26.4 million queries are carried out via smart speakers, which is an additional 0.75% - so in total that makes 12.75% of searches, or if we're rounding up, 13% of Google searches that are voice queries.

This means that the number of voice queries on Google would need to increase by another 22 percentage points over the next year and a half for Ng's prediction to come true. To reach 50% - the stat most often cited by voice enthusiasts as to why voice is so crucial to optimise for - we would need to find an additional 1.3 billion voice searches per day from somewhere.

That's nearly ten times the number of smart speakers predicted to ship to the US over the next three years. Even if you believe that smart speakers will single-handedly bring voice search into the mainstream, it's a tall order.

So okay, we've established that voice enthusiasts might need to cool their jets a bit when it comes to the adoption of voice search. But if we return to (our interpretation of) Andrew Ng's prediction that 35% of searches by 2020 will be voice, what is going to make the volume of voice search leap up those remaining 22 percentage points in less than two years?

Is it sheer volume of voice device ownership? Is it the increasing normalisation of speaking aloud to a device in public? Or is it something else?

Ng made another prediction, via Twitter this time, in December 2016 which gives us a clue as to his thinking in this regard. He wrote, "As speech-recognition accuracy goes from 95% to 99%, we'll go from barely using it to using all the time!"

So, Andrew Ng believes that sheer accuracy of recognition is what will take voice search into the mainstream. 95% word recognition is actually the same threshold of accuracy as human speech (Google officially reached this threshold last year, to great excitement), so Ng is holding machines to a higher standard than humans – which is fair enough, since we tend to approach new technology and machine interfaces with a higher degree of scepticism, and are less forgiving of errors. In order to win us over, they have to really wow us.

But is a pure vocal recognition the only barrier to voice search going mainstream? Let's consider the user experience of voice search.

The UX problems with voice

As I mentioned in our last installment of natural language and conversational search, when using voice interfaces, we tend to hold the same expectations that we have for a conversation with a human being.

We expect machines to respond in a human way, seamlessly and intuitively carrying on the exchange; when they don't, bringing us up short with an "I'm sorry, I don't understand the question," we're thrown off and turned off.

This explains why voice recognition is weighted so highly as a measure of success for voice interfaces, but it's not the only important factor. Often, understanding you still isn't enough to produce the right response; many voice commands depend on specific phrasing to activate, meaning that you can still be brought up short if you don't know exactly what to utter to achieve the result you want.

The internet is full of examples of what happens when our voice assistants don't quite understand the question.

Or what about if you misspeak – the verbal equivalent of a typo? When typing, you can just delete and retype your query before you submit, but when speaking, there's no way to take back the last word or phrase you uttered. Instead, you have to wait for the device to respond, give you an error, and then start again.

If this happens multiple times, it can prompt the user to give up in exasperation. Writing for Gizmodo, Chris Thomson paints a vivid picture of the frustration experienced by users with speech impediments when trying to use voice-activated smart speakers.

One of the major reasons that voice interfaces are heralded as the future of technology is because speaking your query or command aloud is supposed to be so much faster and more frictionless than typing it. At the moment, though, that's far from being the case.

However, while they might be preventing the uptake of voice interfaces (which is intrinsically linked to the adoption of voice search) at the moment, these are all issues that could reasonably be solved in the future as the technology advances. None of them are deal-breakers.

For me, the real deal-breaker when it comes to voice search, and the reason why I believe it will never see widespread adoption in its present state, is this: it doesn't do what it's supposed to.

One result to rule them all?

Think back for a moment to what web search is designed to do. Though we take it for granted nowadays, before search engines came along, there was no systematic way to find web pages and navigate the world wide web. You had to know the web address of a site already in order to visit it, and the early "weblogs" (blogs) often contained lists of interesting sites that web users had found on their travels.

Web search changed all that by doing the hard work for users – pulling in information about what websites were out there, and presenting it to users so that they could navigate the web more easily. This last part is the issue that I'm getting at, in a sidelong sort of way: so that they could navigate the web.

Contrast that with what voice search currently does: it responds to a query from the user with a single, definitive result. It might be possible to follow up that query with subsequent searches, or to carry out an action (e.g. ordering pizza, hearing a recipe, receiving directions), but otherwise, the voice journey stops there. You can't browse the web using your Amazon Echo. You can use your smartphone, but for all intents and purposes, that's just mobile search. Nothing about that experience is unique to voice search.

This is the reason why voice search is only ever used for general knowledge queries or retrieving specific pieces of information: it's inherently hampered by an inability to explore the web.

It's why voice search in its present state is mostly a novelty: not just because voice devices themselves are a novelty, but because it's difficult to really search with it.

One result to rule them all?

Even when voice devices like smart speakers catch on and become part of people's daily lives, it's because of their other capabilities, not because of search. Search is always incidental.

This is also why Google, Amazon and other makers of smart speakers are more interested in expanding the commands that their devices respond to and the places they can respond to them. For them, that is the future of voice.

What does this mean for voice search?

What true voice search could sound like

I see two possible future scenarios for voice search.

One, voice search remains as a "single search result" tool which is mostly useful for fact-finding exercises and questions that have a definitive answer, in which case there will always be a limit to how big voice search can get, and voice will only ever be a minor channel in the grand scheme of search and SEO. Marketers should recognise the role that it plays in their overall search strategy (if any), think about the use cases realistically, and optimise for those – or not – if it makes sense to.

Or two, voice search develops into a genuine tool for searching the web. This might involve a user being initially read the top result for their search, and then being presented with the option to hear more search results – perhaps three or four, to keep things concise.

If they then want to hear content from one of the results, they can instruct the voice assistant to navigate to that webpage, and then proceed to listen to an audio version of the news article, blog post, Wikipedia page, or other websites that they've chosen.

Duane Forrester, VP Insights at Yext, envisages just such an eventuality during a wide-ranging video discussion on the future of voice search with Stone Temple Consulting's Eric Enge and PeakActivity's Brent Csutoras. The whole discussion is excellent and well, well worth a watch or a read (the transcript is available beneath the video).

Duane Forrester: We may see a resurgence in [long-form content] a couple of years from now if our voice assistants are now reading these things out loud.

Brent Csutoras: Sure. Like an audible.

Duane: Exactly, like a built-in native audible, like “I’m on this page, do you want me to read it? “Yes, read it out loud to me.” There we go.

Brent: Yes because in that sense, I’m going to want to hear more. I’m driving down the street and want to hear about what’s happening and I want to hear follow up pieces.

Duane: It immediately converts every single website, every page of content, every blog, it immediately converts all of those into on-demand podcasts. That’s a cool idea, it’s a cool adaptation. I’m not sure if we’ll get there. We will when we get to the point of having a digital agent. But that’s still years in the future.

At first, I was sceptical of the idea that people would ever want to consume web content primarily via audio. Surely it would be slower and less convenient than visually scanning the same information?

Then I thought about the fast-growing popularity of podcasts and audiobooks and realized that the audio web could fit into our lives in many of the same ways that other types of audio have – especially if voice devices become as omnipresent as many techs and marketing pundits are predicting they will.

Is this a distant future? Perhaps. But this is how I imagine voice search truly entering the mainstream, the same way that web search did: as a means of exploring the web.

The future of voice search might not be Google

What surprises me is that for all the hype surrounding voice search and its possibilities, hardly anyone has pointed out the obvious drawback of the single search result or considered what it could mean for voice adoption.

An article by Marieke van de Rakt of Yoast highlights it as an obstacle but believes that screen connectivity is the answer. This is a possibility, especially as Google and Amazon are now equipping their smart speakers with screens - but I think that requiring a screen removes some of the convenience of voice as a user interface, one that can be interacted with while doing other things (like driving) without pulling the user's attention away.

For the most part, however, it seems to me that marketers and SEOs have been too content to just follow Google's lead (and Bing's, because realistically, where Google goes, Bing will follow) when it comes to things like voice search. Is Google presenting the user with a single search result? Everyone optimize for single search results; the future of search will be one answer!

Why? What about that makes for a good user experience? Is this what search was meant to do?

I understand letting Google set the agenda when it comes to SEO more broadly because realistically it's so dominant that any SEO strategy has to mainly cater to Google. However, I don't think we should assume that Google will remain the leader of the search in every new, emerging area like voice or visual search.

Oh, Google is doing its best to stay on top, and there's no denying that it's taken an early lead; its speech recognition and conversational search capabilities are currently second to none. But Google isn't the hot young start-up that it was when it came along and challenged the web search status quo. It's much bigger now, and has investors to answer to.

Google makes a huge amount of revenue from its search and advertising empire; its primary interest is in maintaining that. One search result suits Google just fine, if it means that users won't leave its walled garden.

Marketers and SEOs should remember that Google wasn't always the king of web search; other web search engines entered the game first, and were very popular – but Google changed the game because the way it had of doing the search was so much better, and users loved it. Eventually, the other search engines couldn't compete.

The same thing could easily happen with voice search.

The logos of some of the early search engines that Google out-competed in its quest for web search dominance.

The future of voice optimisation

So where does that leave the future of voice optimisation?

Many of these eventualities seem like far-off possibilities at best, and there’s no way of being certain how they will pan out. How should marketers go about optimising for voice now and in the near future?

Though I’ve taken a fairly sceptical stance throughout this series, I do believe that voice is worth optimising for. However, the opportunity around voice search specifically is limited, and so I believe that brands should consider all the options for being present on voice as a whole – whether that’s on mobile, as a mobile voice search result, or on smart speakers, as an Alexa Skill or Google Home Action – and pursue whatever strategy makes most sense for their brand.

I’m interested in seeing us move away from thinking about voice and voice devices as a search channel, and more as a general marketing channel that it’s possible to be present on in various different ways – like social media.

It’s still extremely early days for this technology, and while the potential is huge, there are still many things we don’t know about what the future of voice will look like, so it’s important not to jump the gun.

Brent Csutoras sums things up extremely well in the future of voice search discussion:

This is an important technology I really think you should pay attention to. What I worry about is that people start feeling like they have to be involved, right? It’s like, “Oh crap, I don’t want to be left behind.”

What I would say is that in this space, it’s like the example of Instagram. Everybody wanted to have an Instagram account and they had nothing visual to show, so they just started creating crap to show it. If you have something that fits for voice search right now, then you should absolutely take the steps that you can to participate with it. If you don’t, then definitely just pay attention to it.

This space is going to open up, it is going to provide an opportunity for just about everyone, so stay abreast of what’s happening in this space, what’s the technology, and start envisioning your company in that space, and then wait until you have that opportunity to make that a reality. But don’t overstress yourself and feel like you’re failing because you’re not in the space right now.

Categorized in Search Engine

Source: This article was published techcrunch.com By Frederic Lardinois - Contributed by Member: Carol R. Venuti

One of Google’s first hardware products was its search appliance, a custom-built server that allowed businesses to bring Google’s search tools to the data behind their firewalls. That appliance is no more, but Google today announced the spiritual successor to it with an update to Cloud Search. Until today, Cloud Search only indexed G Suite data. Now, it can pull in data from a variety of third-party services that can run on-premise or in the cloud, making the tool far more useful for large businesses that want to make all of their data searchable by their employees.

“We are essentially taking all of Google expertise in search and are applying it to your enterprise content,” Google said.

One of the launch customers for this new service is Whirlpool, which built its own search portal and indexed more than 12 million documents from more than a dozen services using this new service.

“This is about giving employees access to all the information from across the enterprise, even if it’s traditionally siloed data, whether that’s in a database or a legacy productivity tool and make all of that available in a single index,” Google explained.

To enable this functionality, Google is making a number of software adapters available that will bridge the gap between these third-party services and Cloud Search. Over time, Google wants to add support for more services and bring this cloud-based technology on par with what its search appliance was once capable of.

The service is now rolling out to a select number of users. Over time, it’ll become available to both G Suite users and as a standalone version.

Categorized in Search Engine

 Source: This article was published thebusinesstactics.com By Carl Sanford - Contributed by Member: Bridget Miller

The Global Internet of Things (IoT) Fleet Management Market report is organized by executing a phenomenal research process to collect key information of the Internet of Things (IoT) Fleet Management industry. The Internet of Things (IoT) Fleet Management research study is based on two parts, especially, the Internet of Things (IoT) Fleet Management primary research and outstanding secondary research. Internet of Things (IoT) Fleet Management market secondary research provides a dynamic Internet of Things (IoT) Fleet Management market review and classification of the worldwide Internet of Things (IoT) Fleet Management market. It also lamps on leading players in the Internet of Things (IoT) Fleet Management market. Likewise, the primary Internet of Things (IoT) Fleet Management research highlights the major region/countries, transportation channel, and the Internet of Things (IoT) Fleet Management product category.

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Categorized in Internet of Things

 Source: This article was published prweb.com - Contributed by Member: Barbara Larson

An NYC area IT consultant and MSP reviews the dangers of the dark web and how to stay safe online in a new article from eMazzanti Technologies.

The informative article first clarifies common misconceptions about the dark web then lists steps to protect personal data and business assets. Readers are urged to work with data security professionals to achieve the best results.

“Understanding the dark web is helpful in protecting valuable business data,”

stated Jennifer Mazzanti, CEO, eMazzanti Technologies. “Modern cyber-security technology and best practices are designed to keep sensitive information from falling into the hands of the bad actors lurking there.”

Dark Web vs. Deep Web

“Contrary to some reports, the dark web does not include over 90 percent of the internet. This common misconception arises from confusion between two related terms. In reality, the internet includes several layers.”

“Deep web – Also known as the invisible web, this is by far the largest layer of the internet, with over 90 percent of all internet content. The bulk of this information involves perfectly legal content that is not indexed by the standard search engines. Your medical records, banking information and other member-only websites live here.”

“Dark web – Sites on the dark web are accessible only with special software that allows users to communicate and transact business anonymously. While this creates a haven for criminals, it also serves a legitimate purpose for whistleblowers, activists, and victims who need to remain anonymous.”

Identity Theft and the Dark Web

“If the dark web includes only about three percent of the internet, do I need to be concerned? Yes. Remember Equifax and Target? Whenever a website experiences a data breach involving personally identifiable information, that information will almost certainly appear for sale on the dark web, likely within hours.”

Navigate the Web with Expert Guides

Business leaders should keep in mind that a breach of company systems means not only data loss but also potentially a loss of reputation. To guard critical data, employ multi-layer security. For merchants, if EMV chip technology not already been implemented for point of sale (POS) systems, they should do that now.

As with any potentially dangerous territory, the internet is a much safer place when working with an experienced guide. The experts at eMazzanti build strategies to keep personal and business data safe. Whether implementing secure cloud solutions or tapping into eMazzanti’s considerable retail security expertise, business leaders can count on getting the protection they need.

About eMazzanti Technologies

eMazzanti’s team of trained, certified IT experts rapidly deliver retail and payment technology, digital marketing services, cloud and mobile solutions, multi-site implementations, 24×7 outsourced network management, remote monitoring and support to increase productivity, data security and revenue growth for clients ranging from law firms to high-end global retailers.

eMazzanti has made the Inc. 5000 list eight years running, is a 2015, 2013 and 2012 Microsoft Partner of the Year, 2016 NJ Business of the Year, 5X WatchGuard Partner of the Year and one of the TOP 200 U.S. Microsoft Partners! Contact: 1-866-362-9926, info(at)emazzanti.net or http://www.emazzanti.net Twitter: @emazzanti Facebook: Facebook.com/emazzantitechnologies.

Categorized in Deep Web

LONDON - Smartphones rule our lives. Having information at our fingertips is the height of convenience. They tell us all sorts of things, but the information we see and receive on our smartphones is just a fraction of the data they generate. By tracking and monitoring our behavior and activities, smartphones build a digital profile of shockingly intimate information about our personal lives.

These records aren’t just a log of our activities. The digital profiles they create are traded between companies and used to make inferences and decisions that affect the opportunities open to us and our lives. What’s more, this typically happens without our knowledge, consent or control.

New and sophisticated methods built into smartphones make it easy to track and monitor our behavior. A vast amount of information can be collected from our smartphones, both when being actively used and while running in the background. This information can include our location, internet search history, communications, social media activity, finances and biometric data such as fingerprints or facial features. It can also include metadata – information about the data – such as the time and recipient of a text message.

Your emails can reveal your social network. David Glance

Each type of data can reveal something about our interests and preferences, views, hobbies and social interactions. For example, a study conducted by MIT demonstrated how email metadata can be used to map our lives, showing the changing dynamics of our professional and personal networks. This data can be used to infer personal information including a person’s background, religion or beliefs, political views, sexual orientation and gender identity, social connections, or health. For example, it is possible to deduce our specific health conditions simply by connecting the dots between a series of phone calls.

Different types of data can be consolidated and linked to build a comprehensive profile of us. Companies that buy and sell data – data brokers – already do this. They collect and combine billions of data elements about people to make inferences about them. These inferences may seem innocuous but can reveal sensitive information such as ethnicity, income levels, educational attainment, marital status, and family composition.

A recent study found that seven in ten smartphone apps share data with third-party tracking companies like Google Analytics. Data from numerous apps can be linked within a smartphone to build this more detailed picture of us, even if permissions for individual apps are granted separately. Effectively, smartphones can be converted into surveillance devices.

The result is the creation and amalgamation of digital footprints that provide in-depth knowledge about your life. The most obvious reason for companies collecting information about individuals is for profit, to deliver targeted advertising and personalized services. Some targeted ads, while perhaps creepy, aren’t necessarily a problem, such as an ad for the new trainers you have been eyeing up.

Payday load ads. UpturnCC BY

But targeted advertising based on our smartphone data can have real impacts on livelihoods and well-being, beyond influencing purchasing habits. For example, people in financial difficulty might be targeted for ads for payday loans. They might use these loans to pay for unexpected expenses, such as medical bills, car maintenance or court fees, but could also rely on them for recurring living costs such as rent and utility bills. People in financially vulnerable situations can then become trapped in spiraling debt as they struggle to repay loans due to the high cost of credit.

Targeted advertising can also enable companies to discriminate against people and deny them an equal chance of accessing basic human rights, such as housing and employment. Race is not explicitly included in Facebook’s basic profile information, but a user’s “ethnic affinity” can be worked out based on pages they have liked or engaged with. Investigative journalists from ProPublica found that it is possible to exclude those who match certain ethnic affinities from housing ads, and certain age groups from job ads.

This is different to traditional advertising in print and broadcast media, which although targeted is not exclusive. Anyone can still buy a copy of a newspaper, even if they are not the typical reader. Targeted online advertising can completely exclude some people from information without them ever knowing. This is a particular problem because the internet, and social media especially, is now such a common source of information.

Social media data can also be used to calculate creditworthiness, despite its dubious relevance. Indicators such as the level of sophistication in a user’s language on social media and their friends’ loan repayment histories can now be used for credit checks. This can have a direct impact on the fees and interest rates charged on loans, the ability to buy a house, and even employment prospects.

There’s a similar risk with payment and shopping apps. In China, the government has announced plans to combine data about personal expenditure with official records, such as tax returns and driving offenses. This initiative, which is being led by both the government and companies, is currently in the pilot stage. When fully operational, it will produce a social credit score that rates an individual citizen’s trustworthiness. These ratings can then be used to issue rewards or penalties, such as privileges in loan applications or limits on career progression.

These possibilities are not distant or hypothetical – they exist now. Smartphones are effectively surveillance devices, and everyone who uses them is exposed to these risks. What’s more, it is impossible to anticipate and detect the full range of ways smartphone data is collected and used and to demonstrate the full scale of its impact. What we know could be just the beginning.

Source: This article was published enca.com

Categorized in Science & Tech

Pipl has raised $19 million from IGP. Founder and CEO Matthew Hertz tells "Globes" about the search engine's ability to find people.

On November 15, 2016, the Detroit Police Department was notified that Savannah Rayford, an 11 month-old baby suffering from life-threatening anemia, had been kidnapped. The kidnapper was known: Marquita Dupree, her biological mother, who was deprived of custody because of her mental state. Dupree got on line to see the doctor to whom Savannah's adoptive mother had taken him, and took advantage of the car stopping on the return journey to grab the infant and escape.

The Detroit police were in a race against the clock. The main clue for finding the mother quickly was the mobile telephone number that she used from time to time, but it was not registered in her name. The police investigators fed the number into Thomson Reuters Clear online investigative computer program, and located several addresses linked to the owner of the telephone number. The mother and baby were found within a few hours at one of these addresses.

The event in Detroit is one of many that has made Clear very popular with the FBI, many US police units, the tax authorities, and other government agencies. Feeding an item of information into the program, such as a telephone number, accesses a full portrait of the person linked to it: residential addresses, e-mail addresses, businesses, relatives, social network profiles, and criminal records. In 2015, the program helped bring about the arrest of a former member of the armed forces who threatened to shoot up a school in San Bernardino, California, and a wanted sex offender in Vermont was caught by using the program.

US law enforcement authorities are probably unaware that a large proportion of Clear's database was created in the Petah Tikva industrial zone at a company named Pipl. Company founder and CEO Matthew Hertz have taken great care to stay under the radar since founding the company in 2005. "I like anonymity," he explains in his first Israeli media interview.

"I agreed to this interview only because I realized that the company is paying a price for its anonymity. Most of our customers in Israel didn't know that we were here before they started working with us. Now that we are trying to recruit employees here in competition with companies like Google and Facebook, we need people to know who and what we are; otherwise, it will be hard for us."

"Google doesn't know how to find people"

Anyone who has tried using Google to search for particulars about another person through a telephone number or e-mail address knows how useless the effort is. Hertz spotted this weak point already in 2005 and decided to build a search engine that would do more thorough work. He was only 27 years old at the time but was already an experienced entrepreneur who had sold two companies. "This was a difficult development project. I took my time at first. After two exits, I thought that I would work part-time - only 30% - but it quickly became interesting, and since then, I have been working time and a half."

Pipl's main asset is a focused identities search engine that has generated profiles to date for over three billion people with some online presence. In addition to the information gathered from open online sources, the profiles are enriched with billions of information items from offline sources, such as telephone directories and lists of professionals. "We thought that we would make a depth engine for everything that Google doesn't find, but we very quickly realized that the product was excellent mainly in finding people. We were far beyond the technology that people expected at the time, and we found things that no other engine found. Google has made no progress in this area, called deep web, or in searching for people, for the past 10 years. You will never be able to get such profiles on Google."

The beginning was modest. "We started as three people, and simply sat down and concentrated on development. Once we came out with the product, we very rapidly reached millions of users. We didn't spend a shekel on marketing, but there was exposure through TechCrunch, and things spread by word of mouth. In late 2007, less than a year after we came out with the product, we were breaking even financially. It turned out it not only worked, but that a lot of people wanted it, and as soon as you have five million users, advertisements generate a significant amount of money," Hertz recalls.

Over the years, the company continued to attract relatively little public interest. Pipl yesterday announced that it had completed a $19 million financing round from the Israel Growth Partners (IGP) fund, which invests in companies with at least $10 million in revenue. Following this investment, IGP general partner Moshe Lichtman and partner Assaf Harel will join Pipl's board of directors. This is the first substantial investment in Pipl, which Hertz has financing almost by himself to date, with a little help from family members. Hertz plans to leverage the money raised in order to increase the number of the company's customers from 1,000 to 5,000 this year, and to diversify its products. As of now, Pipl has 75 employees in its development center in Petah Tikva and 30 more in Idaho, where Piple is incorporated for tax reasons. Hertz, who still interviews every new employee, plans to reach 300 employees within a year and close to 1,000 within two or three years.

"How we discovered jewelry fraud"

Like other companies in its sector, Piple's model raises quite a few troublesome questions about privacy. Not everyone wants strangers to know where they live, their telephone number, and their children's names, even if this information is circulating on the web. The combination of such databases with government agencies, despite its contribution to crime prevention, is likely to make people shudder. Many people are unaware of the existence of Pipl and services of this type, and in the post-Edward Snowden era, with Facebook and Google having to deal with the question of their effect on privacy, Pipl's product may be effective, but it is also causing alarm.

Hertz, of course, tries to soothe the criticism. He says that he has refrained from selling advanced functions of systems to dictatorial regimes, carefully selects his company's business customers in order to prevent misuse, and adds that the company refrains from displaying especially sensitive information, such as criminal records that do not appear on the Internet. "We're very aware of the fact that despite all the open sources, in the end, this is information about people, and there has to control over it. If someone wants to remove information, we'll do it, for example, to disconnect a Facebook account from his profile. We explain, however, that such removal has a price. If a risk management company or a company that wants to prevent financial fraud uses our services, certain deals you make are liable not to pass," he warns.

"Globes": How many people ask you to remove information?

Hertz: "Maybe 10 a day."

Up until 2014, the company generated most of its revenue from the version of its search engine open for public use, which includes only basic profiles. Since then, however, it has accumulated nearly 1,000 business customers that generate over 95% of its revenue. The customers use Pipl's engine to verify identities, prevent eCommerce fraud, enrich information in customer relations management (CRM) systems, conduct inquiries, provide financial services, and recruit personnel. In addition to the US government, many other governments use the system, among other things through the company's strategic partnership with Verint Systems Inc. (Nasdaq: VRNT) (when we asked about the Israeli government, Hertz refused to answer). In the business sphere, nearly 200 online websites use the product, in addition to companies such as Microsoft, IBM, Walmart, eBay, Twitter, BBC, and Oracle.

"In the past, when you ordered a delivery from overseas, and the address you gave was different from the credit card company's address, the delivery was stopped in most cases. They had to call you or the credit card company in order to add the address - a complicated process that caused a huge loss. This almost never happens now, for a simple reason: as soon as you type in your telephone number, they know who you are, and realize that the address is your work address or your mother's address. All of this takes place behind the scenes. An enormous number of transactions went through us on Black Friday," Hertz says.

The use of the system to prevent fraud is not confined to verifying the purchaser's identify on the web. Hertz mentions cases in which swindlers saying that their credit cards were used without their permission and demanding a refund were caught by cross-referencing information. In one case, customers claimed that the jewelry that they bought had not reached them, but the program found a photograph of the jewelry on one of the social networks. In another case, a person was photographed in the Caribbean Islands who claimed that someone else had used his card to order a plane ticket.

Another use of Pipl is in customer management systems. Companies like American Airlines and Oracle use the system in order to discover whether a new customer is a young student or an employee of a large company, to whom an experienced salesperson should be assigned. Among other things, Twitter uses Pipl's technology to obtain information about users behaving like trolls or threatening their friends.

"I studied in yeshiva, and then I cooked shrimp"

Throughout the conversation, Hertz tries to avoid talking about himself but gives in after several attempts. "I come from a haredi family in Bnei Brak. We are nine brothers and sisters. I'm the middle one. Several of my siblings are no longer religiously observant. My older brother is a brain surgeon. My younger brother worked at Pipl when he was a student at the Technion Israel Institute of Technology, and built the previous version of the search engine. I'm not concealing this. Everyone around me knows where I came from, but it is very easy to make this the main story, and I don't want that."

Hertz left the yeshiva (Jewish religious seminary) and religion when he was 17. He moved to Tel Aviv and studied for his matriculation exams. "I learned nothing in the haredi education system, but my mother was an enlightened type - one of the few haredi women with a degree at that time, and I learned a lot by myself from books with her help. I was exposed to geography and mathematics. I became a child who asked questions. She taught me to think. My first job after I left yeshiva was an assistant chef in a French restaurant because I knew how to cook. I spent time in the kitchen with my mother since I was nine years old."

Was the restaurant kosher?

"It wasn't. They had shrimps and steak in cream sauce. It was the Tamara restaurant."

That is a big change.

"It was something that I had been thinking about for a long time. At age 12, I already had questions and doubts. And you know, there is no answer. You can put it off again and again, but in the end, a point will come when you can stand on your own two feet. While I was still at the yeshiva, the IDF decided not to draft me. They considered me to have only four years of schooling, and considered putting me in a unit for dropouts."

Just before his 19th birthday, Hertz decided to study computer science at the Open University and to work as a salesperson for human resources management software. At one of his work meetings at Flying Cargo, when then represented FedEx in Israel, he thought about founding an e-commerce website for deliveries in Israel, on which the delivery companies would compete for offering the best price. He managed to get to the global IT manager at UPS and raised a little money from the companies, but gave it back after he discovered that there was not enough activity to justify the website's existence. "Keep in mind that this was in 1999. Internet then was like bitcoin is now - you got money right away. When I look at this now, it really wasn't logical to give a 20-year-old entrepreneur money on his first attempt."

In that same period, during which he spent a large part of his time in the US, he changed his name from Moti to Matthew. While going back and forth between Israel and the US, he completed his degree in computer science at Tel Aviv University. He founded his first mature startup, Ombek when he was 23. The company developed a service for transmitting SMS messages between different networks at a time when it was not yet taken for granted. "The exit was a merger into WSC, and it later underwent more mergers and acquisitions. We succeeded in reaching three mobile providers in the US three or four months after launching the product. When I left, it was installed in Sprint, Nextel, and other companies."

He founded his second startup, Mail-Info, together with former ICQ CEO Ariel Yarnitsky. The company developed a product capable of determining whether an e-mail sent was received or rejected as spam. The company was acquired by Speedbit in 2005.

You said that you couldn't be an employee. Why is that?

"Being an entrepreneur is not being a soloist. I'm still in a company, and I can't things by myself. But if things have to move, then they move. If you have a dream and you want something to happen, you don't have to persuade a great many people who may or may not agree. You simply go to the end with your vision and make things happen, even if they laugh at you and tell you to stop smoking whatever you're smoking."

 Source: This article was published globes.co.il By Nati Yefet

Categorized in Search Engine
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