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Carol R. Venuti

Carol R. Venuti

Use the iOS Mail app like a pro.

I can't quit the stock iOS Mail app. I've had brief dalliances with the Gmail app and a handful of other email apps that promise to improve my life, but I keep coming back to the Mail app. As a result, this long-time Mail app Gmailer has picked up a few tricks along the way.

1. Archive vs. Trash

You've got two options for getting rid of email messages: archive or trash. The former adds deleted messages to the All Mail folder where they will remain, while the latter moves them to the Trash folder, where they will remain for 30 days before being permanently deleted. To make a selection, go to Settings > Accounts & Passwords and tap on your email account. Next, tap Account > Advanced and select Deleted Mailbox or Archive Mailbox.

ios-mail-archive-delete
Screenshot by Matt Elliott/CNET

2. Get both Archive and Trash options

I set both of my Gmail accounts to trash deleted messages, but there is a way to also retain quick access to the archive action. When I swipe left on a message from my inbox, I get the trash option, but by going to Settings > Mail > Swipe Options, I can set it so I get an Archive button by swiping right. The reverse is also true; if you choose archive as the default, then the right swipe will show a trash button.

You can also access both trash and archive buttons by tapping and holding on the trash or archive button when you are viewing a message. A menu will pop up with both Trash Message and Archive Message options.

ios-mail-swipe-options
Screenshot by Matt Elliott/CNET

3. See all drafts

Need to get back to a draft you started and saved? When viewing your inbox, tap and hold the Compose button in the bottom right and you'll be presented with a list of your previous drafts.

4. Get alerts for important threads

Muting group texts are my favorite among iOS texting tips, and setting an alert for an email thread might be my favorite Mail tip. If you are anxiously awaiting an email reply, you can tell the Mail app to send you an iOS alert as soon as the reply finally arrives. From your inbox, swipe left on the message for which you want to get an alert, tap More and then tap Notify Me and then tap Notify Meagain to confirm. (You can turn off the alert by swiping left, tapping More and tapping Stop Notifying.)

ios-mail-notify-me
Screenshot by Matt Elliott/CNET

5. Add attachments

The Mail app hides the basic function of adding attachments. You won't find a paperclip icon anywhere. When composing an email, double-tap in the body of the email to bring up the Select/Select All/Quote Level menu. Tap the right arrow to get to the Add Attachment option and then you can choose to add a file from iCloud, Dropbox or Google Drive.

ios-mail-add-attachment
Screenshot by Matt Elliott/CNET

6. Insert drawing

Sometimes a picture says it best. In addition to attaching files, you can insert a drawing in an email. Double-tap in the body of an email and tap the right arrow twice to get to the Insert Drawing button, which lets you jot down your ideas and insert them.

ios-mail-insert-drawing
Screenshot by Matt Elliott/CNET

7. Mark up attachments

If you receive an email with a PDF or image attached, you can mark up the attachment without leaving Mail. To do so, open the attachment and tap anywhere on it. Tap the toolbox button in the lower-right corner. This will open a reply email and then open the attachment with edit tools that let you draw, magnify and add text to the file. With your notes added, tap Done and then send your reply with the annotated attachment.

8. Use Siri to search emails

Stop using Mail's search bar and start using Siri to find emails faster. Just ask Siri to "search" or "show" or "find" emails about a topic or from one of your contacts. You can also use Siri to remind you to come back to an email draft to finish it later. When composing an email, just tell Siri to, "Remind me to finish this later" or at a specific time and she will add it to the Reminders app.

9. See more of your inbox

The default is to show two lines of text for each email in the list of messages in the main view of your inbox. If you change it to None or 1 Line, then you'll be able to see more messages on your screen. To change this setting, go to Settings > Mail > Preview.

ios-mail-preview
Screenshot by Matt Elliott/CNET

10. Collapse read messages

It's easy to lose your place in a long email thread when attempting to navigate it on your phone. With iOS 11, Apple has added an option in Mail's preferences that help you keep your place. It's called Collapse Read Messages and it's enabled by default. You can find it by going to Settings > Mail and scrolling down to the Threading section. With it enabled, all of the messages in the thread that you've already read will be collapsed so when you open a thread, you'll be able to easily read the new, unread messages that await without needing to scroll past the read messages.

ios-mail-threading-settings
Screenshot by Matt Elliott/CNET

11. Most recent message on top

I find it's easier to keep track of long email threads by having the most recent messages added to the top rather than the bottom of a thread. Head to Settings > Mail and toggle on Most Recent Messages on Top. Now, when you tap the little blue arrow to expand a thread, you'll be able to view the most recent message without needing to scroll.

 Source: This article was published cnet.com By MATT ELLIOTT

FOR ALL THE hype about killer robots, 2017 saw some notable strides in artificial intelligence. A bot called Libratus out-bluffed poker kingpins, for example. Out in the real world, machine learning is being put to use improving farming and widening access to healthcare.

But have you talked to Siri or Alexa recently? Then you’ll know that despite the hype, and worried billionaires, there are many things that artificial intelligence still can’t do or understand. Here are five thorny problems that experts will be bending their brains against next year.

The meaning of our words

Machines are better than ever at working with text and language. Facebook can read out a description of images for visually impaired people. Google does a decent job of suggesting terse replies to emails. Yet software still can’t really understand the meaning of our words and the ideas we share with them. “We’re able to take concepts we’ve learned and combined them in different ways, and apply them in new situations,” says Melanie Mitchell, a professor at Portland State University. “These AI and machine learning systems are not.”

Mitchell describes today’s software as stuck behind what mathematician Gian Carlo-Rota called “the barrier of meaning.” Some leading AI research teams are trying to figure out how to clamber over it.

One strand of that work aims to give machines the kind of grounding in common sense and the physical world that underpins our own thinking. Facebook researchers are trying to teach software to understand reality by watching the video, for example. Others are working on mimicking what we can do with that knowledge about the world. Google has been tinkering with software that tries to learn metaphors. Mitchell has experimented with systems that interpret what’s happening in photos using analogies and a store of concepts about the world.

The reality gap impeding the robot revolution

Robot hardware has gotten pretty good. You can buy a palm-sized drone with HD camera for $500. Machines that haul boxes and walk on two legs have improved also. Why are we not all surrounded by bustling mechanical helpers? Today’s robots lack the brains to match their sophisticated brawn.

Getting a robot to do anything requires specific programming for a particular task. They can learn operations like grasping objects from repeated trials (and errors). But the process is relatively slow. One promising shortcut is to have robots train in virtual, simulated worlds, and then download that hard-won knowledge into physical robot bodies. Yet that approach is afflicted by the reality gap—a phrase describing how skills a robot learned in simulation do not always work when transferred to a machine in the physical world.

The reality gap is narrowing. In October, Google reported promising results in experiments where simulated and real robot arms learned to pick up diverse objects including tape dispensers, toys, and combs.

Further progress is important to the hopes of people working on autonomous vehicles. Companies in the race to roboticize driving deploy virtual cars on simulated streets to reduce the time and money spent testing in real traffic and road conditions. Chris Urmson, CEO of autonomous-driving startup Aurora, says making virtual testing more applicable to real vehicles is one of his team’s priorities. “It’ll be neat to see over the next year or so how we can leverage that to accelerate learning,” says Urmson, who previously led Google parent Alphabet’s autonomous-car project.

Guarding against AI hacking

The software that runs our electrical gridssecurity cameras, and cell phones is plagued by security flaws. We shouldn’t expect software for self-driving cars and domestic robots to be any different. It may, in fact, be worse: There’s evidence that the complexity of machine-learning software introduces new avenues of attack.

Researchers showed this year that you can hide a secret trigger inside a machine-learning system that causes it to flip into evil mode at the sight of a particular signal. The team at NYU devised a street-sign recognition system that functioned normally—unless it saw a yellow Post-It. Attaching one of the sticky notes to a stop sign in Brooklyn caused the system to report the sign as a speed limit. The potential for such tricks might pose problems for self-driving cars.

The threat is considered serious enough that researchers at the world’s most prominent machine-learning conference convened a one-day workshop on the threat of machine deception earlier this month. Researchers discussed fiendish tricks like how to generate handwritten digits that look normal to humans but appear as something different to software. What you see as a 2, for example, a machine vision system would see as a 3. Researchers also discussed possible defenses against such attacks—and worried about AI being used to fool humans.

Tim Hwang, who organized the workshop, predicted using the technology to manipulate people is inevitable as machine learning becomes easier to deploy, and more powerful. “You no longer need a room full of PhDs to do machine learning,” he said. Hwang pointed to the Russian disinformation campaign during the 2016 presidential election as a potential forerunner of AI-enhanced information war. “Why wouldn’t you see techniques from the machine learning space in these campaigns?” he said. One trick Hwang predicts could be particularly effective is using machine learning to generate fake video and audio.

Graduating beyond boardgames

Alphabet’s champion Go-playing software evolved rapidly in 2017. In May, a more powerful version beat Go champions in China. Its creators, research unit DeepMind, subsequently built a version, AlphaGo Zero, that learned the game without studying human play. In December, another upgrade effort birthed AlphaZero, which can learn to play chess and Japanese board game Shogi (although not at the same time).

That avalanche of notable results is impressive—but also a reminder of AI software’s limitations. Chess, Shogi, and Go are complex but all have relatively simple rules and gameplay visible to both opponents. They are a good match for computers’ ability to rapidly spool through many possible future positions. But most situations and problems in life are not so neatly structured.

That’s why DeepMind and Facebook both started working on the multiplayer video game StarCraft in 2017. Neither have yet gotten very far. Right now, the best bots—built by amateurs—are no match for even moderately-skilled players. DeepMind researcher Oriol Vinyals told WIREDearlier this year that his software now lacks the planning and memory capabilities needed to carefully assemble and command an army while anticipating and reacting to moves by opponents. Not coincidentally, those skills would also make software much better at helping with real-world tasks such as office work or real military operations. Big progress on StarCraft or similar games in 2018 might presage some powerful new applications for AI.

Teaching AI to distinguish right from wrong

Even without new progress in the areas listed above, many aspects of the economy and society could change greatly if existing AI technology is widely adopted. As companies and governments rush to do just that, some people are worried about accidental and intentional harms caused by AI and machine learning.

How to keep the technology within safe and ethical bounds was a prominent thread of discussion at the NIPS machine-learning conference this month. Researchers have found that machine learning systems can pick up unsavory or unwanted behaviors, such as perpetuating gender stereotypes, when trained on data from our far-from-perfect world. Now some people are working on techniques that can be used to audit the internal workings of AI systems, and ensure they make fair decisions when putting to work in industries such as finance or healthcare.

The next year should see tech companies put forward ideas for how to keep AI on the right side of humanity. Google, Facebook, Microsoft, and others have begun talking about the issue, and are members of a new nonprofit called Partnership on AI that will research and try to shape the societal implications of AI. Pressure is also coming from more independent quarters. A philanthropic project called the Ethics and Governance of Artificial Intelligence Fund is supporting MIT, Harvard, and others to research AI and the public interest. A new research institute at NYU, AI Now, has a similar mission. In a recent report, it called for governments to swear off using “black box” algorithms not open to public inspection in areas such as criminal justice or welfare.

Source: This article was published wired.com By Tom

Incorporating Pinterest into your online marketing strategy is good -- getting that content to rank in Google search is better. Columnist Thomas Stern explains how to increase the search visibility of your Pinterest content.

In mid-2014, Pinterest introduced Guided Search, a feature that greatly expanded the information available to marketers by providing insight to popular keyword phrases for boards and Pins. Unfortunately, this feature requires inputting keywords on a per-board or per-Pin basis, which can be incredibly time-consuming for most marketers.

In early 2015, our team received access to the Pinterest advertising beta program. This granted our team further insight into keyword targeting opportunities around our clients’ products. While this was a great step toward ensuring visibility on the platform, the targeting and keyword insights were considerably limited, undoubtedly something that Pinterest is working to improve.

We decided to take matters into our own hands. After all, we’ve seen the tremendous performance with Pinterest when utilized correctly for clients. Similar performance has also been validated by numerous case studies, most recently by Marketing Sherpa earlier this year.

Google + Pinterest = 

After Pinterest took off in popularity a few years ago, our SEO team noticed more and more page-one Google results that included Pinterest. Most recently, we’ve come across indexed boards and Pins in image results, along with a unique mobile result that displays multiple Pin images underneath a link to the board.

SEL 2 pinterest google

Clearly, Google considers Pinterest content to be authoritative, so we decided to see exactly how Pinterest compares to other websites in terms of a unique number of keyword rankings on page one.

Pinterest Keyword Ranking

Using SEMRush’s extensive database of organic listings, we see that Pinterest ranks #8 among all websites for a number of keywords ranking in Google’s top 20 results — just ahead of eBay, Yellow Pages and TripAdvisor. With nearly five million ranked keywords to evaluate, we’ve put together a method to identify the commonalities between keywords and categories.

Step 1: Identify Commonly Occurring Keywords

Considering the sheer volume of keywords, an initial filtering process is required to make sense of the data. We felt that it was easiest to identify the most commonly occurring keywords to create initial groupings. The following example includes the most frequently occurring keywords with adjectives and pronouns omitted (cool, cheap, her, him, etc.).

Pinterest Google Keywords

Step 2: Build & Prioritize Keyword Phrases

Outside of branded search, Pinterest results on Google are primarily long-tail, descriptive phrases. To help identify these phrases, an additional round of keyword insight is needed. The following example takes the “home & home furnishings” keywords from step one and aligns them with the most searched pairings that Pinterest ranks on Google.

Pinterest Keyword Combinations

When reviewing these combinations, it’s immediately clear that a theme exists across the reviewed home and furniture category: Pinterest users are interested in smaller homes and furniture that accommodates a smaller space.

Putting this into a marketing context, brands like West Elm, Ikea and CB2 could greatly benefit from creating Pinterest boards around space-saving furniture offerings. All three brands reference small spaces on a dedicated Pinterest board, but none seem to quite capture the varied intent (room type, furniture type) of Pinterest searchers.

Step 3: Optimize With Pinterest Ranking Factors In Mind

While researching ways to utilize Google data to inform Pinterest keyword strategies, we identified some slight differences between boards and Pins that rank at the top of each search engine (Pinterest vs. Google). On Google specifically, it seemed that boards and Pins with a high degree of interaction (repins) were favored. On Pinterest, it’s a bit more difficult to pin down in entirety (no pun intended), but Google’s ranking factors in addition to others are certainly in place. Regardless of search engine, it’s important to keep the following optimization principles in mind:

  • Conduct Keyword Research. As is evident in the aforementioned furniture example, there is an abundance of keyword combinations that can help brands align with how users search.
  • Be Descriptive. Authentic and utilitarian content must coincide with keyword strategies. On Pinterest, this means creating boards that are common in theme but also provide enough specificity to align with users’ needs (e.g., “Small Living Room Ideas” or “Small Space Living”). It also means Pins should have well-written descriptions that thoroughly describe what the image is about.
  • Use Markup. One of the simplest ways to ensure the content from your website and/or blog is optimized for Pinterest is to use Rich Pins in conjunction with the appropriate markup (different types of markup are supported for recipes, movies, articles, products or places). We highly recommend identifying which relevant content types are on your website and implementing markup ASAP.
  • Be Active. Just like Facebook, the level of engagement of content on Pinterest helps algorithms on the platform determine which boards and pins should rank. Brands often overlook the fact that pinning other users’ and websites’ content is common practice on the platform, and brands can be rewarded for participating.

 Source: This article was published searchengineland.com By Thomas Stern

DuckDuckGo has almost doubled its popularity in the past year, giving it the title of 400th most popular website worldwide

Let’s face it, Google probably knows everything about you.

Whether it’s through the search engine, internet browser, phone or emails, the service is learning new things about you each day. In fact, last year, Google launched an opt-in service known as “My Activity”, a page where you can see everything Google has learned about you in one place. 

But if you want this to change, there is an alternative, and it’s growing in popularity. Describing itself as “the search engine that doesn’t track you”, DuckDuckGo promises not to collect any information about its users, including their IP address.

What is DuckDuckGo?

The DuckDuckGo search engine was launched in 2008 by founder Gabriel Weinberg, who funded it himself until it secured investment with Union Square Ventures in 2011. Since then, the company has gone from strength to strength.

According to figures from the website Alexa, DuckDuckGo has almost doubled its popularity in the past year, giving it the title of 400th most popular website worldwide. In September, the website reached 19 million direct searches, a figure that has shown a gradual increase throughout the year.

Unlike other search engines, when you click on a link through DuckDuckGo the site you are sent to knows nothing about the words you used to find it. “What you search for is your own business and we’d like to keep it that way,” the company says.

DuckDuckGo recently reported that only 24% of adults care enough about their online privacy to take action to protect it while 65% would be motivated to switch search engines if they knew the search engine wouldn't collect personal data. 

DuckDuckGo features

The search engine is aimed at providing a quicker answer, requiring fewer clicks. It uses features called Instant Answers, which provide an answer without leaving the app, and !bangs, which take you straight to a particular website.

Elsewhere, the website offers a service that automatically changes the address of well-known websites to encrypted versions, if you click through its search engine.

Plus it offers fewer adverts. “Less clutter, less spam, fewer ads and an overall cleaner design,” the company says. “We can do this since we just focus on web search and therefore don't have to promote other services on our results pages.”

When it comes to advertising, DuckDuckGo makes money based on the keywords a user searches for, rather than the details of the person, meaning it does not need to collect any other information to create lucrative advertising. 

Related...

DuckDuckGo and Brave

DuckDuckGo recently partnered with the Brave browser to integrate the DuckDuckGo search within the browser's private tabs. 

The tie-in is available if you upgrade the Brave browser to 0.19.116. DuckDuckGo will be integrated in the Brave Android and iOS apps in the first quarter of 2018.

Under the partnership, when you open a private tab on Brave - the equivalent of opening an Incognito tab on Google - you'll get the option to make DuckDuckGo your default search engine. 

Many popular sites host as many as 70 trackers, following you around the web and collecting information about your habits. Brave, by default, stops ads and trackers and its private tabs are not logged in History or in browsing data.

DuckDuckGo browser extension

You can set DuckDuckGo as your default search engine and add the DuckDuckGo browser extension to Google Chrome, Firefox, Internet Explorer, Opera, Safari and Microsoft Edge. Below are the links for each extension. Click the one that applies to your browser(s).

For each of those browsers, you can also add DuckDuckGo as your default search engine directly from the homepage using the address bar. 

Go to DuckDuckGo, right-click the address in the address bar, select "Edit search engines" and find DuckDuckGo. You can now set this as your default search engine. 

You can also download the DuckDuckGo Android app or iOS App.

Source: This article was published alphr.com By Abigail Beall

Tor is a popular tool for activists, hackers, journalists, and anyone who doesn't want their actions online to be tracked to the finest detail. Wochit

Question: What exactly is the "deep Web" and how do you get to it?

Answer: Despite many representations of a nefarious underground operating out of sight, the so-called "deep Web" is actually mostly benign private databases and Web resources not meant to be accessed by the public.

The "surface Web" is essentially what can be indexed by search engines such as Google or Bing, while the deep Web consists of items that can’t be accessed using a search engine on a standard Web browser.

Protected Internet databases such as those for banks and anything past a log-in screen, such as your private files stored in the cloud and data stored by private companies, aren’t indexed by search engines. Websites can also specifically tell the search engines that they don’t want to be indexed, making them relatively "invisible" to the average user.

According to most estimates, the deep Web makes up about 90 percent of the entire Internet, because so much of what is stored online is protected information that requires some form of authentication or knowledge of a hidden Web address.

The 'dark Web'

There is a very small percentage of the deep Web where secret and sometimes nefarious activity is taking place, often referred to as the "dark Web" or the "darknet." The tools used to access the dark Web focus on anonymity by incorporating encryption and specialized privacy browsers such as Tor.

Tor, also known as "The Onion Router," uses a large network of relays to bounce Internet traffic through; it’s much like the layers of an onion, making it much more difficult for anyone conducting any type of surveillance to see who is doing what.

The core technology used in Tor was actually developed by the U.S. Naval Research Lab in the mid-1990s for the intelligence community to protect online communications. To this day, Tor and other similar tools are used by governments, activists and whistleblowers to communicate anonymously.

The Tor Project states: "Tor users include 'normal people' who wish to keep their Internet activities private from websites and advertisers, people concerned about cyber-spying, users who are evading censorship such as activists, journalists, and military professionals."

Using Tor alone doesn’t mean you’re completely anonymous and, for most users, the trade-off in slow performance isn’t worth the increase in privacy for daily surfing.

Tor's dark side

Tor and other similar tools are also used for illicit activities such as buying and selling drugs, stolen credit-card numbers and IDs; money laundering; and more via black markets only accessible on the dark Web.

One of the most famous dark-Web marketplaces was called Silk Road, which was shut down by the FBI in 2013. The site’s founder, Ross Ulbricht, was sentenced to life in prison without possibility of parole.

Despite law enforcement's attempts to control illegal underground marketplaces, when one is shut down, two more seem to pop up.

To be fair, not all dark-Web resources operate in an illegal manner, and much of the activity is vital to our law-enforcement and intelligence community’s efforts. As with any technology, it’s impossible to control its uses for only legal purposes so, as always, it’s the good with the bad.

Ken Colburn is the founder and CEO of Data Doctors Computer Services. Ask any tech question at: Facebook.com/DataDoctors or on Twitter @TheDataDoc.

Starting a business requires having a thorough plan in place, a process that takes a lot of time and research. But before you start your business, there are a number of questions and considerations you need to address. These are more than just passing thoughts, as they require lots of attention before you can even think about opening your doors. Here are nine aspects, along with a few resources, that you need to research before starting your business.

1. Select Your Type of Business, and Consider Its Effects on Your Taxes and Liability

There are many types of business entities, and you need to choose the one that’s most appropriate for your industry and tax circumstances. A sole proprietorshipis the best and simplest option if you are the only business owner. By setting yourself up as a sole proprietor, you are essentially just registering your business for tax and legal purposes, and you will also keep all the profits after taxes but are held liable for all losses and damages. Another option is setting your company up as a limited liability company (LLC), meaning you are held less liablefor damages and losses than a sole proprietor. When starting up with a partner, a general partnership is a basic entity, whereas a limited partnership allows for a “silent” or non-managerial partner to limit his or her liability. Another option is a corporation, in which your company becomes a separate legal entity from you as a business owner, which would be ideal if you have a partner or multiple investors. Corporations limit shareholder liability, but they also bring about more taxes. Depending on your industry and jurisdiction, all of these options may not be available, and in some cases, you may have even more options to choose from (e.g. limited liability partnershipsprofessional corporationsS corporations, etc.). To learn more about this process, the different types of business entities and their tax implications, visit the Small Business Administration or the Internal Revenue Service.

2. Ask Yourself “Who Is My Competition?”

The answer to this question is critical. It’s important to know who your competition is, how they conduct business and what you can learn from their successes and mistakes as a company. Besides word-of-mouth and background knowledge, there are many different ways to research your competition. Beyond a general Google search and social networks, you will perhaps want to attend some conferences or check with your suppliers. A great resource to start with is Inc.com’s article on competitive research.

3. Understand Your Target Audience

There are literally thousands of ways to reach your target audience. Depending on your demographic, some may want to be reached via Facebook, some may react to Google advertisements, and some may really just need a face-to-face interaction. Understanding your target audience is the key to successful marketing; without it, your products will be tough to sell. Who is your product or service targeting, and what unique benefits does it provide? Once you understand that, test different forms of marketing to see exactly what your target audience responds to. For example, if your target is older consumers, traditional advertising is probably your best bet, but for a younger market, you’ll need to get creative and use new media (i.e. YouTube spots, social media posts, etc.). By using a variety of market-research tools from Google, you can get started on defining and marketing to your target audience.

4. Choose Your Company’s Name

You likely already have a great name in mind. But before you launch your business, make sure someone else doesn’t already have that name trademarked; it’s also a good idea to make sure your preferred name is available for a website domain. Use the USPTO site to find out if your business name is protected by trademark, and WHOis.net is a great resource to find out if your domain name is already taken. Your name is your business’ identity, so make sure it’s right for your brand and represents it properly. It should also be easy to understand and remember for consumers, or at least have them thinking about your business name in a unique way.

5. Brand Your New Business

Getting your brand name out in the market is a necessity to starting and maintaining a successful business. Many media outlets are now online, but strong conventional methods still remain. Attend conventions, give away products at fairs or just start building business relationships to help grow your business. As mentioned above, the most important step in marketing your brand is to understand your target market. After figuring that out, your best practices for marketing, whether online or offline, should begin to reveal themselves.

6. Develop Your Overall Web Presence

In today’s market, building a web presence is almost mandatory for successful businesses. Some niche businesses may succeed without it, but the first step for many new ventures should be to set up a website. Do some research on what type of website is best for your business, and hire a web developer if you need to. Once that is established, build your social presence, maybe create a blog, and explore other online avenues. See what works for your competitors, and try to find ways to improve upon their methods. For the majority of businesses, after launching a site, a good first step is to set up multiple social media accounts; after all, it’s where the majority of consumers are, so it only makes sense for you to be there too. Once you’ve conducted your demographic research, establish yourself on the appropriate social media channels, and from there, create marketing collateral that you think will be most likely to reach and engage your target consumers.

7. Prepare a Business Plan

In order to raise capital, you’ll need a business plan written out to show to investors. Your business plan is a roadmap to success. It demonstrates how your business plans on generating revenue, and it outlines what makes your team and its offerings unique and worth an investor’s time and money. How you write your business plan will vary according to your industry, so, again, research your competitors and use their plans to shape yours. For further help with creating a business plan, refer to the Small Business Administration site.

8. Find Sources of Funding

Unless you just won the lottery, you most likely don’t have the out-of-pocket funds to launch your business. Research whether to take out a loan, get certain investors to buy equity, or look into what business grants are available for your business. The SBA has many resources to help you find the best funding options for your company.

9. Licensing and Legal Documentation

There are certain legal documentations and licenses you will need to obtain in order to lawfully run your business. After the initial documentation of registering your business, you’ll also need to consider industry- and/or location-specific licenses. For example, if you are a restaurant that will be serving alcohol, you will need a liquor license. For help with finding your business’ license requirements, a good place to start is the SBA’s licensing portal.

As you’ll soon find out, this is just the tip of the iceberg when it comes to starting your own business. Luckily, there are many resources out there to help you in your endeavors. Not surprisingly, the best place to get started is the Small Business Administration.

Source: This article was published quickbooks.intuit.com

Bing for business has launched a preview of new search features designed for internal organization search. Here is a quick overview.

Bing has announced a new feature named “Bing for business” for their Office 365 and Microsoft 365 business customers.

Bing for business gives employees across a company search results within the organizational context of the business, be it an enterprise, school or organization. It uses artificial intelligence and the “Microsoft Graph” to tailor the search results to employees and the content within an organization.

Bing for business will search company data, people, documents, sites and locations, as well as public web results, and list them in a unified search results experience for company staff. This, of course, works across any browser, on any device within the organization.

Today, Bing released a private preview of this to their Office 365 Enterprise E1, E3, E5, F1, Business Essentials, Business Premium and Education E5 subscriptions customers.

Here, an example of Bing for business search for “Thomas” returns employee information:

Here is one calendar related to scheduling time off:

It can also surface documents only available for to the specific user:

Here is a feature list:

  • Enterprise Bookmarks — Bookmarks provide the fastest way for you to find sites, tools and other information within the enterprise. Bookmarks can range from timely topics with a short life span like a company event to more permanent bookmarks, such as linking to the internal time and reporting tool.
  • People Search — With Bing for business, people search is a quick way to help you search and find a person and understand their role within the company, who they work for, see what they are working on, find out where they are located and get directions through integrated building and office floor maps.
  • Organizational Chart — Quick access to the organizational chart to understand a person’s place within the company and further browse their peers, management and direct reports.
  • Building and Floor Plans — Buildings and floor plans help you quickly find your way or locate where a colleague is sitting or learn your way around a new building.
  • Document Search — Allows you to search and find contextual and relevant documents saved on SharePoint and other sources within the Microsoft Graph.
  • Office 365 Groups — You will be able to explore the Groups a person belongs to as part of people search and browse their contents. Additionally, they will be able to search for groups by their name.
  • Bing for business Industry News — Bing works with your company to understand your job and tasks. Over time, Bing learns which business news matters to you — such as news about your company, competitors and industry.  This feature is a personalized newsfeed on Bing.com, helping you make timely, informed decisions.
  • Management and Analytics –IT admins can quickly configure, create bookmarks and define the search triggers, words or phrases. IT admins will also have a better understanding on how people within the organization are searching the web.

Source: This article was published searchengineland.com By Barry Schwartz

We explain the Dark Web, how it differs from the Deep Web, and how to access the Dark Web using Tor.

The internet is a much, much bigger place than you probably realise. You know about Facebook, Google, BBC iPlayer and Amazon, but do you really know what's lurking beyond those user-friendly and respectable websites? 

This is but a tiny corner of the internet, and the Dark Web and the Deep Web loom in much shadier corners. Using Tor you can access them, but should you even want to visit the Dark Web or the Deep Web?

Let's take a tour to help you make up your mind.

What is the Dark Web?

The Dark Web is a term that refers specifically to a collection of websites that exist on an encrypted network and cannot be found by using traditional search engines or visited by using traditional browsers.

Almost all sites on the so-called Dark Web hide their identity using the Tor encryption tool. You may know Tor for its ability to hide your identity and activity. You can use Tor to spoof your location so it appears you're in a different country to where you're really located, making it much like using a VPN service.

When a website is run through Tor it has much the same effect.

Indeed, it multiplies the effect. To visit a site on the Dark Web that is using Tor encryption, the web user needs to be using Tor. Just as the end user's IP address is bounced through several layers of encryption to appear to be at another IP address on the Tor network, so is that of the website.

There are several layers of magnitude more secrecy than the already secret act of using Tor to visit a website on the open internet - for both parties.

Thus, sites on the Dark Web can be visited by anyone, but it is very difficult to work out who is behind the sites. And it can be dangerous if you slip up and your identity is discovered.

You can also read our in-depth guide to using Tor if you want to know more about using the web anonymously and sending messages securely. 

What is the Dark Web used for?

Not all Dark Web sites use Tor. Some use similar services such as I2P, for example the Silk Road Reloaded. But the principle remains the same. The visitor has to use the same encryption tool as the site and - crucially - know where to find the site, in order to type in the URL and visit.

Infamous examples of Dark Web sites include the Silk Road and its offspring. The Silk Road was (and maybe still is) a website for the buying and selling of recreational drugs, and a lot more scary things besides. But there are also legitimate uses for the Dark Web. (Also see: Is it legal to buy drugs online?)

People operating within closed, totalitarian societies can use the Dark Web to communicate with the outside world. And given recent revelations about US- and UK government snooping on web use, you may feel it is sensible to take your communication on to the Dark Web. (I'll stick to Facebook, but I like the attention.)

The Dark Web hit the headlines in August 2015 after it was reported that 10GB of data stolen from Ashley Madison, a site designed to enable bored spouses to cheat on their partners, was dumped on to the Dark Web.

Hackers stole the data and threatened to upload it to the web if the site did not close down, and they eventually acted on that threat. Now the spouses of Ashley Madison users have received blackmail letters demanding they pay $2500 in Bitcoin or have the infidelity exposed.

In March 2015 the UK government launched a dedicated cybercrime unit to tackle the Dark Web, with a particular focus on cracking down on serious crime rings and child pornography. The National Crime Agency (NCA) and UK intelligence outfit GCHQ are together creating the Joint Operations Cell (JOC).

What is the Deep Web?

Although all of these terms tend to be used interchangeably, they don't refer to exactly the same thing. An element of nuance is required. The 'Deep Web' refers to all web pages that search engines cannot find.

Thus the 'Deep Web' includes the 'Dark Web', but also includes all user databases, webmail pages, registration-required web forums, and pages behind paywalls. There are huge numbers of such pages, and most exist for mundane reasons.

We have a 'staging' version of all of our websites that is blocked from being indexed by search engines, so we can check stories before we set them live. Thus for every page publicly available on this website (and there are literally millions), there is another on the Deep Web.

The content management system into which I am typing this article is on the Deep Web. So that is another page for every page that is on the live site. Meanwhile our work intranet is hidden from search engines, and requires a password. It has been live for nearly 20 years, so there are plenty of pages there.

Use an online bank account? The password-protected bits are on the Deep Web. And when you consider how many pages just one Gmail account will create, you understand the sheer size of the Deep Web.

This scale is why newspapers and mainstream news outlets regularly trot out scare stories about '90 percent of the internet' consisting of the Dark Web. They are confusing the generally dodgy Dark Web with the much bigger and generally more benign Deep Web.

What is the Dark Internet?

Confusingly, 'Dark Internet' is also a term sometimes used to describe further examples of networks, databases or even websites that cannot be reached over the internet. In this case either for technical reasons, or because the properties contain niche information that few people will want, or in some cases because the data is private.

A basic rule of thumb is that while the phrases 'Dark Web' or 'Deep Web' are typically used by tabloid newspapers to refer to dangerous secret online worlds, the 'Dark Internet' is a boring place where scientists store raw data for research.

How to access the Dark Web

Technically, this is not a difficult process. You simply need to install and use Tor. Go to www.torproject.org and download the Tor Browser Bundle, which contains all the required tools. Run the downloaded file, choose an extraction location, then open the folder and click Start Tor Browser. That's it.

The Vidalia Control Panel will automatically handle the randomised network setup and, when Tor is ready, the browser will open; just close it again to disconnect from the network.

Depending on what you intend to do on the Dark Web, some users recommend placing tape over your laptop's webcam to prevent prying eyes watching you. A tinfoil hat is also an option. If you're reading this to find out about torrent files, check out our separate guide on how to use torrent sites in the UK.

The difficult thing is knowing where to look on the Dark Web. There, reader, we leave you to your own devices and wish you good luck and safe surfing. And a warning before you go any further. Once you get into the Dark Web, you *will* be able to access those sites to which the tabloids refer. This means that you could be a click away from sites selling drugs and guns, and - frankly - even worse things.

Aggregation sites such as Reddit offer lists of links, as do several Wikis, including http://thehiddenwiki.org/  - a list that offers access to some very bad places. Have a quick look by all means, but please don't take our linking to it as an endorsement. It really isn't.

Also, Dark Web sites do go down from time to time, due to their dark nature. But if you want good customer service, stay out of the dark!

And do heed our warning: this article is intended as a guide to what is the Dark Web - not an endorsement or encouragement for you to start behaving in illegal or immoral behaviour.

Source: This article was published techadvisor.co.uk By Matt Egan

Wednesday, 20 September 2017 05:55

Amazon is the New Search Engine for Products

Wait, you say that Amazon is an eCommerce retailer, not a search engine. So what gives with the headline to this story?

A recent study commissioned by marketing technology company Kenshoo found some interesting results. And Google may need to pay attention as this survey was conducted in four countries and included in-store usage.

ALMOST 3/4 OF BUYERS SEARCH AMAZON FOR PRODUCT INFORMATION

72 percent of shoppers go to Amazon to learn more about a product before they make buying decision. This research includes product details, pricing, and reviews.

Over 26 percent of shoppers browsing in a retail store admit to using Amazon to learn more about a product, its features, reviews, and pricing when in a physical store.

Over half (56%) of Amazon users stated they visit Amazon first to research products.

But Google still ranks top at 85% for product research, followed by Amazon (72%), with eBay ranked third at 38%, and all other eCommerce sites at 36%. But the gap might be closing rapidly.

previous story we wrote about U.S. consumer behavior suggested a higher rate by U.S. shoppers using Amazon for product search and only included online consumer shopping.

This new study took an international approach by including three other large eCommerce markets and physical store engagement.

1,000 consumers completed the survey in the USA, and 700 in each of Germany, UK, and France and the study was conducted through Toluna QuickSurveys during August 2017.

IS RETAIL SALES CONSULTATION DEAD?

As the retail industry continues to see the erosion of their physical space, now one of its main selling points, knowledgeable sales staff, maybe the next victim of eCommerce.

Smartphones are changing the way we shop and Smart Grocery store concepts such as Alibaba’s Hema store, show that more shoppers are adapting quickly to mobile research.

In turn, this puts pressure on the need of retail salespeople as they become less a source of product information.

Consumer behavior changed to the point where a shopper is more likely to trust reviews and information found online versus sales staff.

RETAILERS NEED TO CHANGE

In the United States, Best Buy provides QR codes on most products displays in their stores.

These codes make it easy for shoppers to access the bestbuy.com product page on their smartphone quickly. And of course, by keeping them on their site, they are less likely to check Amazon or other competitors.

With Amazon becoming a “product search engine,” this type of in-store strategy may be necessary for retailers to avoid sales leakage and comparison shopping on Amazon.

Therefore, if you own an eCommerce store and a physical shop, this could be a strategy to employ as well.

Just today we posted a story on how Shopify has a new app to generate QR codes, but similar apps should be available for Magento, WooCommerce and other eCommerce Platforms.

What do you think about Amazon is now the new “search engine” for products? We love to hear your thoughts in the comments section below.

 

Source: This article was published esellercafe.com By Richard Meldner

 

How the growth of IoT is impacted by Moore’s Law, Cooper’s Law and Metcalfe’s Law.

The “Internet of Things” or IoT for short is increasingly getting a lot of attention around the world from various stakeholders including from no less than the U.S. Congress (see, for instance, the recent Bill introduced in the Senate, i.e., Internet of Things (IoT) Cybersecurity Improvement Act of 2017).

Since there is not an internet uniquely dedicated to things, the expression “Internet of Things” has come to be used as a metaphor or paradigm to describe a broad movement, still in its early stages, which is sweeping a wide array of economic sectors. In essence, it is broadly viewed as relating to the interconnection of intelligent things, i.e., endpoints with various degrees of smartness. These things, for most of them “out of scope” until now, are progressively inserted in the communications space thanks to the timely convergence of scientific, technological and societal advances and trends.

The IoT will bring about a “pulsating world” emerging from data being constantly sent to and received from IoT devices. As the IoT unfolds, products will be manufactured, as a matter of course, with embedded intelligence capabilities, spawning new ecosystems and related business models. It is bound to transform society and the economy on a scale not experienced before. If we add to these transformational powers the growing pervasive cybersecurity vulnerabilities, it is not hard to comprehend the scrutiny that it is currently enjoying.

The purpose of this article is to reflect on key engines of the IoT growth. While there are admittedly many, three well-known so-called “laws”, which should be perhaps better defined as “empirical observation”, “trend description”, or “educated projection” stand out. They all are influencing the IoT expansion, with distinct degrees of immediacy and impact, but have not yet enabled the Internet of things to reach its critical mass.

 

Moore’s Law
The September 2015 report produced by the Semiconductor Industry Association and the Semiconductor Research Corporation with support from the National Science Foundation about “rebooting the IT revolution” through realizing the “full benefits of the Internet of Things and Big Data” underscores the importance of Moore’s law in “insight technologies”: “Over those fifty years, the ability to reduce the size of the individual transistors by half roughly every 18 months has led to increased performance at lower cost and greater functionality in ever smaller form factors.” (Gordon Moore, Intel’s co-founder, used 24 months in his seminal 1965 article).

While there are legitimate concerns about Moore’s law “running out of room" and the battle to keep it afloat is getting harder, technological prowess has not been deterred. In June 2017, IBM, Samsung and Global Foundries announced that they had developed an industry-first process to build silicon nanosheet transistors that will enable 5nanometer(nm)chips, paving the way for 30 billion switches on a fingernail-sized chip. This is a remarkable feat given that, as a point of comparison, the most recent study of the brain shows that on average the human brain has 86 billion neurons.

Demonstrating that “there is a lot more room to shrink our electronics,” researchers at the Lawrence Berkeley National Laboratory reported in October 2016 that they proved the possibility (proof of concept) of a working 1nm transistor. While these transistors have not yet been packed onto a chip and mass production is still on the drawing board (in and of themselves gigantic milestones for sure), we may fairly anticipate that incredible computing power dwarfing the impressive capabilities already available today could be put on a sensor the size of a quarter in the near future.

It is no wonder therefore that, in the IoT community, edge computing, i.e., data processing at the border between the physical and digital worlds, is viewed as an optimal option.

Incidentally, concomitant to the striking reduction in size of sensors, actuators and wireless transmitters necessitated by the Internet of Things, the field of nanoenergy, i.e., the study of the small-scale, highly efficient energy harvesting, storage, and applications by using nanomaterials and nanodevices, has also greatly expanded within the last decade or so. “Nanogenerators” (at the core of self-powered IoT applications), which harvest small-scale energies in the ambient environment, have been invented in 2006 by a Georgia Institute of Technology team led by Professor Zhong Lin Wang.

In sum, enormous computing power within reach at a Lilliputian scale on site thanks to the continuing unfolding of the now-struggling-but-yet-still-alive Moore’s law stands at the ready to serve the emerging IoT space.

Cooper’s Law
Martin Cooper is an iconic figure in the telecommunications world. He is perhaps best remembered as the father of the cell phone who, as a vice president of Motorola, playfully placed the first mobile call to Joel S. Engel, a rival working at the headquarters of the Bell Labs in New Jersey on April 3, 1973 (as the story goes, Joel Engel does not remember taking the call). A true visionary, innovator and entrepreneur, Martin Cooper’s impact is far reaching.

For instance, in July 2003 he wrote an article for “Scientific American about how adaptive antenna arrays can vastly improve wireless communications by connecting mobile users with virtual wires. Titled “Antennas Get Smart,” the article describes how directional wireless antennas can improve the efficiency of mobile networks and reduce the amount of radio frequency exposure people endure,” as posted on the website of Dyna, a company that he and his wife, serial entrepreneur and inventor, Arlene Harris founded in 1986.

In 2010, Martin Cooper wrote a famous position paper on “The Myth of Spectrum Scarcity” and why “Shuffling Existing Spectrum among Users Will Not Solve America’s Wireless Broadband Challenge.” In it, he argues that the best and most economic solution is to use current allocations more efficiently, and underlines again what was already known as “Cooper’s law”, i.e., “technological progress has doubled the amount of available spectrum available for telecommunications since 1897 with a concomitant reduction in the cost of information delivery.” Subsequently, a presidential advisory committee concurred with him in a report published in 2012, which concludes that the radio spectrum could be used as much as 40,000 times as efficiently as it is currently, and increase capacity a thousand-fold.

As spectral efficiency is improving, networks may be able to absorb the demands for capacity of the spectrum-hungry Internet of Things.

Thomas Hazlett in his new book on “The Political Spectrum: The Tumultuous Liberation of Wireless Technology, from Herbert Hoover to the Smartphone” (Yale University Press, 2017), concisely summarizes the strength of this performance gain; “we today enjoy one trillion times the wireless capacity of networks a century ago. This furious pace is not slackening.” (p. 2). That the pace is not abating is vividly demonstrated by the announcement in August 2017 that international researchers from Brown University (United States) and University of Lille (France) “have demonstrated the transmission of two separate video signals through a terahertz multiplexer at a data rate more than 100 times faster than today’s fastest cellular data networks.”

Metcalfe’s Law
Metcalfe’s Law is named after Robert Metcalfe, the co-inventor of Ethernet and co-founder of the networking company 3Com Corp., in Santa Clara, California. Many times restated (initially, around 1980, it was about devices), as reportedly formulated by George Gilder in 1993, it claims that the value of a network grows as the square of the number of its users — or stipulated somewhat differently, the value of a telecommunications network is proportional to the square of the number of connected users of the system. It also points to an enticing proposition that once the network gets past a critical mass of early users it can snowball into very profitable territory where the benefits expand faster and bigger than the costs.

Essentially, this rule of thumb is about the network effects familiar to any graph theorist, economist, or industrial system engineer. Trying to see the statement as a strict representation of reality may be a futile exercise (how is value defined? Is it really proportional to the square of users? – pitfalls and possibilities are an ever-present topic of research and other “laws” have been proposed to ascertain the value of a network), but viewing it as the catalyst of network success can be very helpful.

It is easy to see that with a starting point of 100 users, 4950 unique connections between the network members (i.e. = (100 x 99)/ 2) can be established and when the number of users in the network augment to 150, the possible links jump to 11,175 (i.e. = (150 x 149)/ 2). Consequently, while the network has increased by 50 percent, the number of potential relations has now grown by 126 percent, i.e., more than double, which shows that the “value” of the network, however it is defined, increases faster than its size.

Of course, such network effects (as captured in Metcalfe’s law) are inherent to the success of social medial companies (SMCs).

SMCs are digital billboards that promote their fast-growing number of captive eyeballs to advertisers willing to pay good money to reach selected targets. In order to secure these eyeballs, SMCs provide free appealing services, which could be construed as “anchor magnets”, in return for keeping the advertising rights. This business model can perhaps find its roots in (or at least similarities with) the innovative concept JCDecaux introduced to French city mayors in 1964, which consisted in providing and maintaining bus shelters, fully financed by advertising.

A side of Metcalfe’s law that may be overlooked is the incremental value potential generated by newcomers, a key element of the SMCs’ growth that is not related to pre-existing network residents. Metcalfe’s law rests on every new user/node in the network connecting with every pre-existing user/node and creating, as a result, more than a linear increase in the overall value of the network. However, new entrants will not only connect with existing network members, but also bring with them “fresh nodes” into the network, i.e., individuals who are not already in, and at the same time, can create the conditions for a positive feedback loop regarding the usage intensity since more members are likely to generate novel (if not more of the same) ways to connect with the whole network.

As it has been highlighted many times, a telephone, fax machine, or social media account have, by themselves, absolutely no value. They need companions. Non-users of social media can attest to the nudge, sometimes pressure put on them by friends, colleagues and family to join them in the network. This is a non-trivial point. Growth is inherent to the very nature of the SMCs’ business. Their leaders don’t have to market their freebies (anchor magnets) to their captive eyeballs (the product), the expansion, by and large, takes care of itself. While we are only interested in this article in exploring the growth phase, it is clear that adverse effects, based on the same principle, can play in reverse.

In their growth phase, successful SMCs have been able to leverage the explosive force of Metcalfe’s law. By designing extremely attractive offerings (anchor magnets) they have been able to trigger a self-sustaining chain reaction, thereby allowing them to approach advertisers with an effective threefold value proposition i.e., we have a sticky user base; we know it well (multi-dimensional segments); and our network is getting bigger.

By contrast, on the IoT side, companies are still in search of scale and must find ways to bring Metcalfe’s law to bear; as a whole, the IoT space is still far from having reached critical mass beyond which it can sustain self-reinforcing growth.

As a case in point, IoT Analytics, a Hamburg, Germany-based provider of market insights for the Internet of Things (IoT), M2M, and Industry 4.0, reported in July 2017 that only 7 percent of the 450 IoT platform companies they had identified around the world generated revenues in excess of $10 million with their IoT platforms in 2016.

Conclusion
Erik Brynjolfsson and Andrew McAfee, respectively Director and Associate Director of the Center for Digital Business at the Massachusetts Institute of Technology, have noted the importance of such growth engines in their well-received book The Second Machine Age: Work, Progress, and Prosperity in a Future of Brilliant Technologies(Norton, 2014) — p. 37. For Brynjolfsson and McAfee, the fundamental characteristics of technological progress are exponential (i.e., constant rate of increase and not constant amount of increase as in the linear case); digital (i.e., product does not diminish or disappear when it is used, and is extremely cheap, i.e., close to zero, to reproduce; hence the term zero-marginal cost society that Jeremy Rifkin advances to describe an IoT-framed society); and combinatorial (i.e., recombining things that already exist; a perspective, which echoes the view on innovation – or, at a minimum, its spirit - of Professor Joseph Schumpeter, one of the greatest economists of the first half of the twentieth century, summed up in his book on Business Cycles in 1939 as “in short, any ‘doing things differently’ in the realm of economic life”).

While everything seems to be set to propel the Internet of Things to oft-announced dizzying heights, the IoT — albeit undeniably rapidly taking off — has not enjoyed thus far the same astonishing growth witnessed on the social media side (“the Internet of People”).

Moore’s and Cooper’s (exponential) laws have continued to deploy their wings with remarkable fidelity to their original concept and today provide solid foundations for the IoT expansion, but Metcalfe’s (or any version of this law centered on the critical positive non-linear repercussion of additional members on the network’s value) has still to make an impact.

This is of vital importance for the IoT space since mass induces value.

As emphasized above, exponential growth is a key feature of SMCs’ success and, more generally, technological progress. However, exponential growth functions display different behaviors depending on a range of parameters. Some grow faster than others.

We saw that the fast growth of SMCs’ platforms may be due to some extent to the extra value new entrants/social media accounts add by bringing with them potential not-yet-in-the-network users (as in the case of telephone or fax machine networks). There is some type of codependency that serves as a growth accelerant. When individual “A” joins, he/she may bring with him/her individuals “B” and “C” who in turn may add their own followers, i.e., all newcomers who may also spur network intensity usage. Growth is a built-in component of the SMC product.

There is no denying that the Internet of Things is on the rails and has, for all intents and purposes, already “left the station.” But, when IoT applications will foster by design the incorporation of new connections, pulled in at wildfire speed by existing nodes whose network membership is closely intertwined with those new connections (i.e., one connection begets another connection that begets another etc., in the manner of social media), the Internet of Things will grow beyond critical mass and reach a size that we can barely fathom now. This possibility may take some time to materialize but has certainly already moved out of the science fiction realm.

The views expressed in this article are solely the author’s and do not necessarily represent those of the Georgia Institute of Technology (“Georgia Tech”), the Georgia Tech CDAIT members, the University System of (U.S. State of) Georgia or the (U.S.) State of Georgia.

Source: This article was published automationworld.com By Alain Louchez

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