How does a complete beginner get into AI development? What learning resources does he/she use along the journey to learn about artificial neural networks, the basic AI algorithms, the simplest machine learning models and all that? “How important is a solid math background?” "And what programming language should I learn/deepen my knowledge of?” Here's a step-by-step guide for a complete beginner to AI, that should put you on the right track, so can you get started with AI software development... the right way: 1. A Solid Background in Mathematics Is Just... Crucial Just think about it: machine learning comes down to... linear algebra you need at least some basic knowledge of calculus for training neural networks And there are a few more topics that you should add to the list: probability and statistics various algorithms Learn as much math as you can before you jump into the best courses and other learning resources on AI that you can find. It will greatly help you... 2. Narrow Your Focus: What Do You Want to Build? Clearly articulate your goal, make it fit into one simple sentence: "To develop an algorithm that predicts a person's blood pressure", for instance. It's only then that you'll be able to: break your task/problem down into smaller parts narrow your focus (for AI is a discouragingly broad term) identify the specific resources that you'll need 3. Learn By Doing: Try to Solve a Simple Problem for a Start In other words: try writing a simple neural net first, then gradually focus on more complex ones. As a start, tackle an easy problem. Experiment with multiple approaches for harnessing algorithmic decision-making while trying to solve it. Get into AI software development by finding the quickest solution to a given problem: Train a simple machine learning algorithm and evaluate its performance. Next, level up your knowledge by optimizing your basic solution. Experiment with upgrading various components and monitor the resulting change. Try your hand at: building your own simulator writing the AI code for games like Sudoku or Tic Tac Toe developing code for pattern recognition 4. Get Started with Deep Learning: Learn About Artificial Neural Networks As a newcomer, you must be particularly interested in deep learning, am I right? Now, if you want to explore this machine learning method, you'll need to get familiar with the basics of artificial neural networks. In this respect, you might find this online resource here on Deep Learning enlightening enough. As for the open-source framework to use for testing the newly acquired skills you have: Google-powered TensorFlow, by far one of the most popular ones; a Python-based one Theano, Scikit-learn, Keras, all Python-based frameworks, as well Deeplearning4j, a Java framework 5. Choose Your Programming Language: Consider Performance and Libraries Availability “What programming language should I learn to get started with AI development?” Actually, choosing the language is not that important. Go for a mainstream language (although you can still do ML/AI with lesser popular languages, as well). One that: provides you with lots of tools and high-quality libraries stands out in terms of performance So, it could be either Python or C++, either Java or C or Octave. Each one has its own strengths and limitations when it comes to performance and libraries availability. 6. Learn Computational Learning Theory to Get into AI Development And this is particularly important when you delve deep into the field of Natural Language Processing. 7. Build a Powerful Computing HardWare or Use a Cloud-Based One Expect some significant hardware requirements for running artificial intelligence and implementing machine learning. A powerful hardware system, using a bundle of CPUs and high-performing GPUs is a must if you're thinking: considerably big models; you'll be testing lots of alternative models before you decide on the final one more and more complex experiments that involve harnessing the power of AI And here, you have 2 options: you either put together your own powerful enough supermachine you go with a cloud-based alternative Speaking of the latter, here are 2 cloud computing platforms to consider: Cloud TPU: a Google-powered hardware custom designed specifically for carrying out tensor operations in a more efficient way than a GPU or CPU Google CoLab: a Jupyter notebook environment that doesn't need any setup; you get quick access to the cloud-based GPU for running your scripts to 8. Get Familiar with Most Machine Learning Algorithms If you're determined to get into AI development you should be/get comfortable with: support vector machines (SVM) recurrent neural networks (RNN) deep learning (DL) a whole lot of other decision trees and random forests There's no shortcut here! 9. Enter a Kaggle Competition Put your newly acquired skills to the test! Commit to solving the problems that other AI developers are working on by participating in a Kaggle competition. Test out multiple approaches and go with the most effective solution. Not only that you will get to test your skills in AI software development but your collaboration skills, as well: You'd be joining a large community, asking questions on an AI-focused forum whenever you get stuck while learning artificial intelligence, you'd be sharing your groundbreaking ideas and so on. 10. 2 Free Online Courses to Try Your Hand At One of the questions at the beginning of this post has been: “ What learning resources does he/she use along the journey to learn...” So, here I am now, ready to give you 2 recommendations: Stanford University – Machine Learning: Google Brain's founder, Andre NG, is teaching this course; it's loaded with real-time examples of AI-driven technologies, with valuable information that will help you gain a better understanding of how neural networks learn... Learn with Google AI: a Google-powered project including a machine learning course for newcomers (incorporating the TensorFlow library as well) The END! Sure hope these 10 tips will help you grow more confident and eager to get into AI development.
Adriana Cacoveanu / Nov 19'2018
You're ready to turn your idea of a machine learning app using image recognition into “the next best thing”! It's going to revolutionize mobile advertising, the education sector, the automobile industry, the world of finance... you name it. But then, reality strikes you: "How do I implement image recognition functionality into my application the... easy way?" And the “easy-to-use” factor becomes particularly important if you have no machine learning background. How do you incorporate such a service/API into your app? An app that should analyze, organize, alter different images? Now, here's what you need to keep in mind when you build a machine learning-powered app, plus a selection of the best image recognition APIs. So you can compare and experiment with in order to select the one that perfectly suits your goals and your machine learning background... 1. 4 Things to Keep in Mind When Building a Machine Learning App Before you jump into enabling machine learning capabilities into your web or mobile app, make sure: that you've gained in-depth knowledge of that specific market that you're targeting that you've properly prepared your data: make sure you've selected the best data sources and data collecting techniques you've chosen the best algorithm for your app (run it, tune it, test it) you're using the right method: for on-device machine learning you'll need to pay attention to your model's size (make sure it's not oversized; otherwise, you'll need to rely on cloud services for machine learning) Note: organize your dataset ensuring that your images are of different lengths, that they feature plenty of particularities, thus helping your custom model to identify the target objects/emotions/scenes more accurately. 2. Implement Image Recognition to Your App: Choosing the Best API “What are the best image recognition APIs in the market?” you must be asking yourself right now. “What's the best solution for me to incorporate image recognition into my machine learning app if: I have little to no machine learning background I'm looking for an image analysis software that's straightforward to implement, easy to use, yet powerful … one that should enable me to quickly train a custom model" 2.1. Mobile Vision API A Google-powered framework equipped with the capability to detect objects in images and videos. For this, it uses 3 types of detectors: a face detector a text detector a barcode detector Image source: Google Developers. The “face detector” is “loaded” with some great features such as: providing information about the state of the human faces in the analyzed images/videos: eyes open/closed, smiling, crying etc. identifying parts of a face: mouth, nose, eyes analyzing multiple faces on a single image identifying human faces on recorded videos, on mobile camera and still images Note: do keep in mind that this API does not provide face recognition capabilities; it cannot tell whether 2 images, presenting human faces, are identical or not. 2.2. Google Vision API Looking for something a bit more complex, more... refined that an "object detection” service? For an image recognition software that does more than just: provide similar images “detect” faces and visual objects … and detects “details” about the uploaded images instead? One that identifies whether: the being in the picture is a human or a dog the characters are sad or happy (sentiment analysis) they're racy or engaged activities marked as “not OK” in the Google Safe Search … and labels the given images (“weather”, “autumn”, “dog walking”, “male”)? Then, the Google Vision API (or “Cloud Vision API”) is what you're looking for. Unlike other leading image recognition solutions available, it “spoils” you with: a simple REST API landmark detection functionality How does it do it? The API connects the code of your machine learning app to Google's image recognition capabilities. Now, here's how you set it up: Sign Up for a Google Compute Engine Account Select a Project (if you're a newly registered user, then the “My First Project” is selected by default) “Grab” an API key from the menu on the left side of the screen (save it to a text file) and run it in your project (just enable the API at this URL) Select your app project You're now ready to roll with your new image recognition API integrated to your app project; just save the text in a google_vision.json file: It's this JSON request that will point out to Google Vision API the specific image to parse and the detection capabilities to trigger. Note: remember that you should use this API in personal applications only! 2.3. Clarifai Here's a custom image recognition software in our list to start experimenting with if: you're looking for a visual search tool with a video-analysis functionality added to, as well you need an easy to implement and to use API for tagging images; for recognizing and understanding the content features in your images/videos you're looking for an API with a strong concept modeling you're planning to incorporate an image recognition functionality that enables you to create and to train your own custom models to test against “But how do I use Clarifai's Custom Training API to set up my own model?” It's pretty straightforward: for declaring a positive you use: clarifai.positive('https://goo.gl/1Q8W8S 'dog', callback); for predicting an image you use: clarifai.predict('https://goo.gl/xNNRJg 'dog', callback); for declaring a negative you use: clarifai.predict('https://goo.gl/xNNRJg 'lion', callback); 2.4. Einstein Vision Looking to get in on a little AI action? To build an image recognition app leveraging AI and deep learning models trained to recognize images at scale? Consider Einstein Vision then! Integrate it into your machine learning app and start to explore its two APIs: Einstein Object Detection: empowers you to train models that should recognize several distinct objects in an image (providing information such as the location and the size of each item) Einstein Image Classification: enables you to create and to train models to detect and classify images at scale “Where would I use such an AI-enabled app?” Here's one of its most common image-recognition use cases: You can use all those contextual clues stored in your images (your customers' preferences, your products/services' level of quality, your inventory levels etc.) to empower your marketing, sales and/or service teams. This way, they'll gain more accurate insights about your customers. 2.5. Amazon Rekognition What if you're not looking for the best tool for sentiment analysis, object and scene detection, but for one that rocks at facial recognition instead? Then you go with Amazon Rekognition. It's designed to: provide detailed information (e.g. beard recognition) run facial comparisons and assess the likelihood that 2 faces are of the very same person 2.6. Google Tensorflow Object Detection API A non-complicated way to integrate image recognition functionality into your machine learning app. Tensorflow Object Detection API is an open source framework designed around the idea that: Building, training and deploying of object detection models should be quick and easy. In this respect, the available guide supports the whole idea. Image source: Github Here's how to use the API: Download the frozen model (.pb — protobuf) and run it into memory Load categories, labels, visualization tools and so on using the built-in helper code Launch a new session and run the resulting model on one of your images 2 tips for incorporating and using this API in your machine learning app: figure out how you can speed up the API so you can use it for real-time object detection on mobile devices experiment with the more accurate models to see the difference The END! Have I managed to (at least partially) answer your questions: “What do I need to know for building a machine learning app?” “How do I build custom image recognition functionality into my web/mobile app?” “What are the best image recognition APIs in the market right now?” Photo by Antoine Beauvillain on Unsplash.
RADU SIMILEANU / Nov 16'2018
AI, AR, VR, ML, DL... AR vs Machine Learning: is there a difference between these 2 technologies? Which one(s)? Or do these 2 acronyms refer to the very same tech? Keeping up with which tech does what, with parsing the differences between all the fancy 2-letter acronyms emerging these days becomes increasingly challenging. Especially when the terms are often used interchangeably, like artificial intelligence and machine learning. Now that's frustrating: how could you possibly distinguish a clear-cut demarcation line between such a broad concept and “catch-all” term as AI (or “machine intelligence”) and machine learning? Time to shed some light here: 1. What Is Artificial Intelligence? A more than succinct, yet descriptive enough definition would go something like this: The capability of a machine to perform tasks that require human intelligence. And here I'm referring to tasks such as: recognizing images/voices understanding languages, translating planning problem-solving learning In short: once a computer system reaches a level where it understands, analyzes, tells the difference between objects and makes decisions all by itself — based on understood criteria — then we can already talk about artificial (or machine) intelligence. Now, a more detailed definition of artificial intelligence would be: The theory and development of machines that mimic intelligent human behavior. That carry out tasks requiring human intelligence, in a more human-like way: they can reflect, make decisions, interact with humans and perform different complex tasks. 2. AI: Types and Applications We couldn't talk about a complete and accurate “AI vs machine learning” analysis without focusing on the artificial intelligence typology and its specific applications. Therefore, you should know that AI comes in two different “flavors”: 2.1. General AI It involves broader applications: A machine that learns to perform a wide range of complex tasks (that require human intelligence) and gains the ability to solve various problems in a human-like way. Therefore, being broader in scope, general AI is harder to achieve than the “applied AI” alternative: In fact, we don't yet have systems or devices capable to successfully handle any task that a human being can. That type of machine capable to mimic the human brain, to understand, interpret, respond to various stimuli... 2.2. Applied AI (or “Vertical” or “Weak” or “Narrow”) Defining the applied or “weak” AI is crucial for properly identifying the clear-cut differences between AI and machine learning: It's that type of artificial intelligence — of “smart” system — that addresses a specific need. That focuses on handling one single predefined task (e.g. personalizing ads or trading stocks). But maybe a few examples would be more appropriate for you to grasp the full meaning of applied AI: LinkedIn messaging Netflix recommendations Spotify discovery mode Siri 3. AI vs Machine Learning: What Is Machine Learning More Precisely? First of all, we should make it clear that: Machine learning is a subset of artificial intelligence. And if we are to detail this statement a bit: Machine learning is that subcategory of AI that uses statistical techniques to identify patterns of repetition in databases. Once properly trained, it can analyze loads and loads of data sets, predict accurate outputs and sort new inputs all by itself (e.g. voice search). For instance, after going through huge volumes of customer data, it can recommend the most appropriate products, based on online shoppers' past choices and search history. Or it can trigger certain functionalities of a software based on a particular user's voice. “But what do you mean by “training” a machine learning?” Here, I'm referring to “neural networks”. Basically, for each machine learning there's a neuronal network programmer (or a team of them) who builds these networks for training and learning. And what he does more precisely is choose specific factors of importance to determine the outcome of a given situation. And they keep “polishing” and further adjusting these factors (or “weighs”) in the outcome until the network reaches the proper result according to the given input. Once the machine learning reaches that level where it's capable to understand and to adjust the factors of importance on its own, to deliver accurate results (in real-time), it will keep improving itself. It will keep “learning” how to deliver more and more accurate results without any human intervention. In short: you “feed” the algorithm with huge volumes of data and it will then learn, adjust itself and continuously evolve when it comes to determining the most accurate outcome of a situation. Just think: image recognition voice recognition Now, in an AI vs machine learning debate, one where we're trying to identify the differences between the two concepts, we can say that: Artificial intelligence is the broad concept, whereas machine learning is the technology powering much of the development in the AI field. That machine learning is a type of AI that learns — while getting fed huge amounts of data — and improves all by itself. With no human intervention to keep “telling” it which is the matching rule between new inputs and the most probable outputs. 4. In Conclusion... What better way of ending this comparative analysis of the two terms/techs then by pinpointing the main differences between AI and machine learning in a shortlist? Therefore, here it goes: while machine learning can exist without AI, the latter can not exist without ML (the main reason behind the confusion when using these terms and why their definitions are often interchanged) once a machine can make a choice or any decision on its own, once it can spot the difference between 2 items, it grows into AI; then, there's more than machine learning technology that's being leveraged there The END! Is it clearer for you now which is the key difference between the two concepts? Where precisely you should draw the demarcation line between these 2 technologies?
Adriana Cacoveanu / Nov 12'2018
Can LastPass Just Block Your Account and Withhold Your Passwords? Yes! Here Is What They Have Put Us Through
What if you lose your LastPass master password? Then you're doomed... You'll lose your password vault for good. But hey, you can still to lose all your sensitive data even if you don't forget that crucial password! I mean, if it has already happened to us... Apparently, there's no guarantee that one day, for no reason, LastPass won't: lock you out of your account and block your access for... mere fun keep advising you to use their recovery password form… one that doesn't work and that you had already tried, several times, with no success keep suggesting that you're some sort of a "liar", insisting that you had, in fact, changed your master password and that's why you can't log in now keep giving you a "suicidal" advice: delete your account and open a new one, even if this means losing all your data refuse to allow you to retrieve the data that you stored in your "old" account to export it to that new account they keep insisting to create refuse to refund you the money you had paid, in advance, for a service that apparently doesn't serve your needs: it keeps you blocked out and puts a garnishment on your passwords So, just beware of which company you choose to trust with your sensitive data! Their "The last password you'll ever need" slogan might just turn into: "The last password you'll ever have". For once they block you, you'll be left with... none. But let's rewind and go back to the day when it all started. Little did we expect for it to turn into our worst-ever scenario, considering that we had been happy LastPass users since... 2009. 1. It Started Like Just Another Ordinary Log In to Our LastPass Account... But — surprise, surprise — we couldn't sign in. And our master password was the same old one: we did NOT forget it! I mean, we had been LastPass users for almost 10 years': We were fully aware of what would happen if we ever lost that priceless password! So, we jumped straight to their “Recover Account” form, which brutally served us the following message: And it was about that time that things started to go wrong. When the “ordinary” slowly turned into... extraordinary: An extraordinarily bad experience with the LastPass support team. 2. When in Trouble, Contact LastPass Support and... Start a Deaf Dialogue This is where our deaf dialogue with lovely Michelle from LastPass's support team started. And it was such a nice and fruitful chat that we had there! I let her know that, by some mysterious reasons, that day, from all the other days in the previous 9 years, I couldn't access our account. Nor could I use their recovery account system for... it didn't work. Lovely Michelle either: suggested that I was lying when I told her about my attempts to use their recovery account form understood everything just too well, but she had a script to follow, so she decided to ignore parts of my message thought she was dealing with some a retarded person … and told me that, in fact, I had managed, somehow, to change my master password. Then she kindly advised me to... go through their recovery account steps. Even though I had told her I already had done that. But, who was I to come in between her and the script she had to follow blindly? And then came her somehow “suicidal” advice for us, the OPTASY team, one of the loyal LastPass customers: To delete my current account (for which I had already paid in advance) and create a new one! Just like that! 3. News Alert! LastPass Can Block You Out and Withhold Your Stored Data For that's what happens when they advise you to delete your account and “start over”: Your password vault goes... down the drain or gets stuck in their cloud, no matter how you want to look at it. Here's a tricky question for you: What would be a worse scenario for you? To lose all the passwords that you've trusted LastPass with? To lose all your passwords with no guarantee that no one else can access them later on? And here's charming Michelle's brutally honest answer to my legitimate question(s): “What's gonna happen with all the records in our OLD account? How can we import them into the new one?” And that reply just... sent cold shivers down our spines... 4. Being Punished Without Fault: No Refund and No Chance to Export Our Data Now, you do guess that it was about then that we reached the climax of our conversation with the LastPass support team (aka Michelle). And so, masochistically enough, we dared to pop up another question: “If you're not able to help me reset the password, please let me know how can I export all the data from my old account and refund the money I paid in advance.” The answer was a... slap in the face, like the previous ones: To sum up now: locked out from our LastPass account, after several years left to somehow make their not-working “recovery account system”... work for us forced to keep trying it over and over again given just one option: to create a new account and lose all our passwords (and the money paid in advance, as well) Can you imagine that we trusted LastPass for years? And that we ended up getting treated like this? With no fault. 5. Their Invariable Response? To Start Over and Knowingly Lose All Passwords Needless to add that I kept on explaining to the LastPass support that in vain did they point out to the recovery steps to take: I had already taken them, even before I had even contacted them in the first place. With zero success... I claimed back the money we had paid in advance for their password manager service, as well as the possibility to export our password to that new account that they insisted that we should set up. Michelle's answer: The END! No happy ending, though, to this story of our terrible experience with LastPass. Who would have thought that all these years we were trusting them with our most valuable data! And that one day they'd just... kick us out and withhold precisely that sensitive data with: no fault from our side no clear explanation on their side So, just beware, be informed, be skeptical about trusting LastPass...
Adriana Cacoveanu / Oct 12'2018
“Trust LastPass at your own risk!” would be our answer. One based both on: this password manager's own “beefy” record of critical security vulnerabilities, cross-site scripting bugs, breaches and major architectural issues our bad experience with LastPass, as a client And before we dig into the heavy load of evidence that we base our “case” on, allow us to expose some of their former clients' testimonials: “I lost my entire LastPass passwords in March 2017. It was a disaster for me. I have had LastPass since the beginning, can you imagine all the passwords saved over the years? I think you should do some research on LastPass and the changes, the bad changes that have happened with LastPass” (Barbara's comment, 5 Best LastPass Alternatives to Manage Your Passwords) “About a month ago when I tried to log in to LastPass I got the message that I had entered the wrong vault password - but I can assure you that nor I, nor my cat has changed it... When I contacted LastPass, they in a rude manner "taught" me that what I hadn't experienced what I had in fact had experienced, since it is "impossible", and their "help" consisted in giving me the clue to the main password to LastPass - i.e. the password, which I explained to them isn't valid anymore... “ (Robert's comment, You Should Probably Stop Using LastPass Temporarily) “Around a month ago I switched from LastPass to Bitwarden as my password manager. To make sure my passwords were protected I deleted my LastPass account, now I get an email asking me to renew my subscription for my DELETED LastPass account. I wonder what else they stored about me... “ (user/dumah310, LastPass storing email from deleted account) 1. But First: How Does LastPass Work? In plain language: LastPass stores your encrypted passwords (and secure notes) in the cloud and secures them via a master password. And the “master password” is both the strength and the main vulnerability of this password management service. Now before I back up the above statement with our own experience with LastPass, here's an excerpt of an “enlightening” HackerNews post: “Users must also devise a “master password” to retrieve the encrypted passwords stored by the password management software. This “master password” is a weak point. If the “master password” is exposed, or there is a slight possibility of potential exposure, confidence in the passwords are lost.“ 2. 5 Security Vulnerabilities Over the Last 7 Years... and Still Counting “How secure is LastPass from being hacked?” I'll leave it to you to evaluate it while going through its “impressive” record of security flaws and vulnerabilities reached over the last years: 2.1. In 2011 a Cross-Site Scripting Vulnerability Was Detected In February 2011 Mike Cardwell, a security researcher, tracked down an XSS bug on the company's website. Once “exploited”, this vulnerability could basically enable attackers to steal: hashed passwords the list of websites that users log into (along with the IP addresses, time and dates of their logins) their email addresses underlying cryptographic salts LastPass fixed that bug within hours. 2.2. That Same Year A Second “Likely” Security Breach Was Identified Later on that year, in May, the company's team spotted a new “anomaly” in both their incoming and outgoing network traffic. Therefore, suspicions arose that a hacker might have accessed their servers. What kind of risks did this “abnormal activity” entail? Well, the attacker could check thousands of passwords in a short period of time, using a combination of user emails, guesses on their master password and the salt. As LastPass CEO confirmed it himself back then, in an interview for PCWorld.com: “ You can combine the user's e-mail, a guess on their master password, and the salt and do various rounds of one-way mathematics against it. When you do all of that, what you're potentially left with is the ability to see from that data whether a guess on a master password is correct without having to hit our servers directly through the website.” 2.3. In 2015 A Hacker Attack Compromised the Company's Servers Here's another answer to your “Can we trust LastPass?” question: In June 2015 a post on the company's blog announced that their team had detected suspicious behavior on their network. The result? LastPass servers got hacked and the cryptographically protected content compromised. And we're talking here about: user passwords password reminders cryptographic salts email addresses 2.4. In 2016 A Vulnerability that Enabled Reading Plaintext Passwords Was Exposed Within a year, in July 2016, a new security vulnerability in the autofill functionality was identified and then detailed by the representative of DETECTIFY, an independent online security firm. Basically, the article raised new suspicions about whether one could trust LastPass with their passwords: The URL-parsing code of the LastPass browser extension — the HTML piece of code that was added to every page that the “victim” would visit — was poorly written. Sloppy enough to enable a potential attacker to read plaintext passwords once the user landed on a malicious website. 2.5. In 2017 a “Major Architectural Problem” Was Discovered In June 2017 Google's security researcher Tavis Ormandy made a new discovery: A security vulnerability in the LastPass Chrome extension (that applied to Firefox and Edge, as well), which, once exploited, could enable a hacker to steal passwords or engage in remote code execution. He described it as a “major architectural problem” to point out that this time we weren't facing some... signs of carelessness, but a hole in LastPass' security shield instead. “How safe is LastPass?” Users started to ask themselves again and many even started looking for alternatives. 3. About Our Own Unexpectedly Bad Experience as a LastPass Client Let us share with you some glimpses of our rough experience as LastPass users. I would start by saying that: Yes, the worst-possible scenario did happen to us. We've apparently lost all the passwords “safely” stored in our LastPass account. There are zero chances to retrieve them, to export them to another password manager or/and to get a refund, considering that we had paid for one year in advance. How did it all begin? With us trying to log into our account, as usual. But, we got this “welcome” message instead: “Invalid password” We next tried to reset our master password, using their reset password form. With no success, though: “LastPass account recovery failed for... Your current web browser did not save account recovery data on this computer. Please try account recovery again with every browser and on every computer you...” And then the “dialogue of the deaf” began, with: Us stating that we did NOT reset our password, for it was not possible and the LastPass support team claiming that we did restart it. And telling us that there's no option but to: create a whole new account say goodbye to all our passwords "safely" stored there for good; there's no chance to export that user sensitive data to another password manager service lose all hope of getting a refund for the money we had paid in advance, due to their “No refund policy” In short: if for some mysterious reasons, one day LastPass doesn't recognize your current master password anymore and you're not allowed to reset it either... you're doomed. Now, can you guess what's our answer to this question: “Can we trust LastPass?” 4. Bottom Line: Should You Trust LastPass? “Trust this service at your own risk!” For one day, no matter whether you've: disabled the auto-fill functionality enabled a two-factor authentication (for both LastPass and your other critical accounts) chosen an "invincible” master password for your LastPass account kept both your software and your machine “spotless clean” and up-to-date used one different password per account … you still run the risk to find yourself locked out! Just talking from experience...
Adriana Cacoveanu / Oct 09'2018
Why Magento 2 and not Shopify, WooCommerce, Joomla, BigCommerce, Volusion and the list of popular e-commerce platforms could go on? Why is Magento 2 the best choice for mobile commerce? After all, they all provide responsive product pages design, right? Yes, but that's just the “tip of the iceberg”.There are lots of other factors to consider, as well, when striving to ensure your e-store's success on mobile: the shopping cart the checkout experience the page load times (considering the high level of unpredictability specific to mobile connectivity) the admin UI the “manage your store on the go” functionality … and so on. Magento 2's built to meet all your mobile commerce-specific expectations, plus a few more. Now, out of all the most obvious reasons why you should consider it as your platform of choice for your mobile e-store, we've selected the 7 most compelling ones: 1. Intuitive and Easier to Use Admin UI A huge “leap” forward from Magento's discouragingly complex and confusing former admin panel. How is it better? it's cleaner it's more (non-technical) user-friendly it's easier to use Practically, in Magento 2 store admins are no longer dependent on developers for every little change they need to make in their online stores. From finding precisely the tools they need to adding new product listings, admins can now perform all the common tasks in their dashboards much quicker. 2. A Simple Checkout Process: It Makes Magento 2 the Best Choice for Mobile Commerce And this is that part of your mobile e-store that can make or break its reputation for good. A cumbersome, overly complex, lengthy checkout experience will only make your customers “run for the hills” and never come back to... pick up their abandoned carts (and maybe even spread the news about the frustrating checkout experience they had in your store). Do you see my point here, right? This platform's simple, frictionless checkout process is directly responsible for the success of any e-commerce website using Magento 2. 3. All Magento 2 Themes and Templates Are Responsive by Default Magento 2 comes jam-packed with free, responsive themes for you to just scan through, select from and use to deliver mobile-friendly shopping experiences. That, of course, in addition to the always available options of: going with a third-party theme having a Magento 2 developer build a custom theme for you, from scratch, and to tailor it to your store's specific needs 4. Easy to Manage Your Magento 2 Store Right On Your Smartphone Another enhancement that makes Magento 2 the best choice for mobile commerce. Just imagine that as a store admin you'll get to manage all its features: catalog management features CMS SEO and marketing features order management … on the go, right from your mobile phone, right from your admin panel. And it's this type of convenience that turns Magento 2 into the most popular platform among e-commerce business owners. 5. Caching Capabilities And you need to consider how unpredictable a mobile connectivity can get. Luckily, Magento 2's got your back: its catching capabilities are the “safety net” you need when your online store's visitors are facing issues of limited connectivity. It supports Varnish Full Cache, which makes it easy for developers in your team to boost your Magento store's performance despite the internet connectivity's limitations. 6. Powerful Built-In Marketing Features Speaking of conveniences, Magento 2 provides you with a heavy load of robust marketing features right out of the box. I'm talking here about: visual merchandising optimized product category pages sharing an email drag and drop functionality wishlist creation feature customer segmentation In short: all the modern features you could possibly think of for “fueling” your mobile marketing strategy with. The END! What do you think, can these 6 reasons here stand for 6 clear answers to your question: “What makes Magento 2 the best choice for mobile commerce?”
Adriana Cacoveanu / Sep 20'2018
Lots of helpful tips and tricks, tons of best practices, plenty of great advice on how to prevent missed deadlines on your web projects. And yet: all these “how to's” are targeting project managers, team leaders and, overall, web development teams. But what about you, the client? What can you do to help the teams working on your web projects avoid missing deadlines? What best practices should you adopt in order to streamline the development process? And what bad client habits should you break to avoid scope creep and, implicitly, delaying your own project? Now that we've gone through all your possible questions and dilemmas as a client regarding the “deadline issue”, let's dig for some answers, too. In this respect, here are the 6 best practices that you should stick to when working with a web development team, to ensure that they'll meet their deadline: 1. Clearly Articulate all Your Project Requirements — Ideas, Vision, Expectations Do speak now or forever hold your peace! In other words: share your detailed specifications, your requirements, even just your glimpses of ideas in a very early phase of your project's development life-cycle. This way, you'll empower your contacted team to come up with an accurate project estimate. And thus, to ensure that they'll meet the deadline you will have agreed upon. What's your vision for the project? What do you expect your software product to do? What features should it incorporate? What are your predictions in terms of website traffic? Be sure to express all your requirements as accurately as possible, whether under the form of: drawings on a sheet of paper detailed specifications verbal explanations screenshots 2. Over the Budget? Discuss Prioritization of the Key Features Another best practice to prevent missed deadlines on your web projects, as a client, is to prioritize specific tasks included in the project. And this practice gets particularly helpful when you find yourself budget-constrained. What are the essential features and functionalities that your website/application should have? Identify them, then discuss prioritizing those specific implementations with the development team. This way you: stay on budget (still) meet the deadline set some realistic expectations draft an updated roadmap for your development team to follow Tip: are you familiar with the MVP (minimum viable product) philosophy? 3. Give Them Timely Access to Materials They Need to Move Forward More often than not, it's clients' failure to carry out their own parts of the projects (on time) that lead to significant delays in the development process. And forgetting/overlooking/refusing/being out of reach to give your development team timely access to those materials that are crucial for their work is one such example. I'm talking here about materials such as: project-specific content data brand fonts … and other resources they might need to advance in their work. Which leads us to another best practice that clients (too) often fail to follow: 4. Be Reachable: Stay Active on Communication Channels It's crucial that you be available on (all) communication channels. The team of web developers working on your project might need: your approval on certain tasks that they will have completed before they can focus on the next development phases your input to the next-in-line deliverable your decision regarding a multi-solution challenge they're facing So, you do get the point: the more difficult it'll be for them to reach you, the higher are the chances that they miss their deadline. 5. Ask Your Questions to Prevent Missing Deadlines on Your Web Projects Do dare to ask the project manager, the customer service manager or team lead all your questions. Whether technical or not. For you do not need to be a Drupal, Magento, WordPress, React, Laravel, Angular or any other technology expert. Yet, you must ask your development team any inquiries that you might have regarding the used tools and platforms. ... regarding their specific procedures, internal processes and, overall, their particular approach to project management. Ask your questions and allow them to shed light on any “blurriness” that you might be facing. Otherwise, confusions will only lead to last minute changes of scope and missed deadlines. 6. Set Realistic Deadlines to Accommodate Your Last-Minute Requirements, Too Are there any last minute changes, unplanned requirements or off-the-plan tasks that you need to integrate into your project's development cycle? Talk about them with the project manager and maybe you'll reach an agreement to add a few more developers to your project. And also, keep in mind to set a realistic deadline to accommodate all these emergencies, as well. What's a Scope Creep More Precisely? Something that many clients are guilty of, I must say. It comes down to: Changing the scope of a project. And there are multiple causes for this: urgent, last-minute requests coming from the client, that imply high volumes of extra work poor scheduling poor budgeting lack of cooperation The END! These are the 5 most effective best practices to adopt, as a client, in order to prevent missed deadlines on your web projects.
Adriana Cacoveanu / Sep 18'2018
Repetitive (not to say boring), time-consuming... And it all gets even more cumbersome when you add more authors to the equation and you increase frequency to more than just 2 posts a week. Yes, I am talking about regularly sharing your blog posts on your social media. But what if you could just schedule them and create your own calendar? And automate the whole process? Then, the question that arises is: “What is the best WordPress plugin for posting to social media?” One perfectly equipped to: cope with an above-the-average posting frequency work in the context of a multi-author WordPress blog re-post old posts, as well track the overall success of your posts And there sure are lots and lots of “luring” WordPress plugins to schedule posts, so: Which one best meets all your particular requirements? Let me give you some clues here. 5, to be more specific: WordPress' Default Feature for Scheduling Posts: Main Limitations Let's not jump straight to the WordPress plugins to schedule posts for social media before we've evaluated what the platform's built-in feature offers us, in this respect. For, you can very easily schedule your blog posts to social media in WordPress without the need of a plug-in solution. Here's how this out-of-the-box functionality works: you go to Settings > General, in your admin panel you set your Timezone (since WordPress uses Universal Time by default) next, once you're ready to hit the “Publish” button and launch your blog post “out into the wild”, just hit the “Edit” button next to it … and set the time and date that you'd like your post to be shared on social media then, you click the “Schedule” button And that's it! Your post will get automatically published according to your preferences of time and date. But what if: you'd need to go through this process several times... a day? there are several authors posting on the same blog and, implicitly, sharing content on the same social media accounts? For more complex expectations about your scheduler, you go with a plugin. With the best WordPress plugin for posting to social media, that should meet all your requirements. 1. Blog2Social A hands-off solution to rely on for both: automating your posting on social media; from your WordPress blog straight to your social media networks scheduling their publishing; you get to set a specific time for your posts to go live It will automatically share your content on LinkedIn, Pinterest, Medium, Twitter... Screenshot: WordPress.org Features you'll love: automated posting to several social media networks setting the time and date that you want your posts to be published tracking and monitoring your posts' success on each network tailoring your posts' templates so that they fit each network's specifications you're allowed to select the right images for your posts automated re-publishing of your scheduled old posts 2. Social Auto Poster If this is not the best WordPress plugin for posting to social media, then it's definitely the most flexible one: You get to configure it to the slightest detail; to fine-tune it till it meets even your “overly” specific needs. Moreover, it enables you to auto-share both new and older blog posts. Screenshot: Codecanyon.net Top features: choosing the post type to be shared auto-sharing new blog posts to those specific social networks that you will have selected custom scheduling: set the most suitable days and hours for sharing content on social media auto-posting to all your linked Facebook accounts supporting any kind of format: post, eCommerce products, page, custom post type A social auto-poster WordPress plugin that's conveniently compatible with a whole “plethora” of networks: Tumblr, Facebook, Twitter, Pinterest, Instagram... 3. NextScripts Here's another “must-check” WordPress plugin that's loaded with social media integrations. Screenshot: WordPress.org Let us look over some of its “hard-to-resist-to” features: automatically sharing both new and older posts you're free to configure which posts should and which ones shouldn't get published … and also the time and date for publishing them you're also free to delay your scheduled posts auto-importing mentions/comments from your social media accounts as WordPress comments 4. Revive Old Post Is keeping the same level of consistency — through regular posting at... regular times of the day/week — getting a bit challenging? Maybe, at times, you have no fresh content to share with your visitors... Screenshot: Revive.Social Then how about bringing some of your old articles back into the spotlight? Especially since you have Revive Old Post at hand, probably the best WordPress plugin for posting to social media. Once you've set everything up, the plugin turns into a 100% hands-off solution. You'll be putting the whole process of re-posting old content on... autopilot. But, let us go through some of this plugin's key features. Basically, it empowers you to set: the age of the posts to be re-published the number of posts to be posted per day the posting frequency how many times the same old post can be posted the format of the posts to be shared on social media Note: once plugged in, the Revive Old Post enables you to track the traffic that re-sharing these old posts will bring on your blog, right in Google Analytics. 5. Auto Post Scheduler It makes the best WordPress plugin for posting to social media especially in the case of a multi-author blog. One with a high volume of content drafted for being published on a daily basis. Screenshot: WordPress.org Basically, it's one of those few WordPress plugins to schedule posts that takes the full process, with all its particularities, off your back: From sharing scheduled posts, to recycling old posts to be published, it will automate all posting to social media-related operations. The END! These are the top 5 WordPress plugins to schedule posts for social media that you should evaluate first when looking for the best social auto poster for your own website.
Adriana Cacoveanu / Sep 14'2018
Let's just say that the default product review system in Magento 2 is... well... not 100% satisfactory for you. It does have its limitations; there might be some particular product reviewing and rating features that it can't provide you with. So, you start looking for an extension to compensate for this... inconvenience. But which one to go with? What is the most suitable Magento 2 product reviews extension for your own eCommerce store's needs? And it takes just a brief scanning of the large “pile” of Magento 2 extensions to start experiencing choice overload: How do you know which one's the best for your eStore? Which one suits your own idea of an “ideal” reviews system? But what if we narrowed them down to 5 choices only? The 5 best Magento 2 review extensions to start your searches with: But First: The “Ideal” Magento 2 Reviews System — Main Characteristics What features should the reviews system on your eStore have to meet all your expectations? Let me guess: reviews should be accompanied by the customers' real names, photos and maybe even a link to their social media accounts, as well customers should be able to rate products on a “pros & cons” scale the reviews section should be easily noticeable on page the reviews system should empower you with the proper tools to use for encouraging customers to insert informative, relevant reviews only … needless to add that the UI of the add review screen should be highly intuitive the reviews should show product photos, as well the reviews system would enable you, the admin, to easily sort product reviews by relevance/helpfulness The Default Magento Product Reviews Feature: How Does It Work? Before we delve right into the mini pile of Magento 2 product reviews extensions that I've prepared for you here, let's see: How does the default reviews functionality work in Magento 2? On the user's side, he/she writes down his review in the text description field popping up once he's rated the product from 1 to 5. Whereas on the admin's side, you get to configure those ratings at Stores > Attributes > Rating, right in your Magento 2 admin dashboard. Images: Potatocommerce.com The Advanced Review for Magento 2 Extension You cannot run your evaluation of the best rated Magento 2 product reviews extensions and skip this module here. Why? Here are the top reasons for considering it: it provides a detailed product reviews system, with pros and cons it makes it possible for the published reviews to be rated as helpful/unhelpful … and to be shared across social media networks, as well it features review captcha and report reviews, helping you minimize the risk of fraud and spam it boosts the product reviews system with custom rating values (quality, price and so on) The Import/Export Product Reviews Extension A handy Magento 2 extension if you're “juggling with” multiple online stores. Basically, it enables you to import/export product reviews from one eStore to another via CSV file. Note: while importing them, you, the admin, get to set their status using the CSV file The extension's most valuable features: it makes it possible for reviews to get transferred along with their titles and descriptions via CSV file it supports a multi-store environment it empowers you, the admin to approve/disapprove the submitted reviews Magento 2 Review Booster: The Best Magento 2 Product Reviews Extension? Another product reviews and rating extension for Magento 2 that you shouldn't overlook while determining your best option. And here are some of its main functionalities: pros and cons reviewing the written feedback's helpfulness uploading images to product reviews the possibility to “lure” customers with different discounts/coupons for reviewing the products they buy review reminders adding comments to product reviews sorting product reviews by rating The Magento 2 Product Reviews Extension Another extension that has the potential to get you closer to that “ideal” Magento 2 reviews system of yours. Here's how precisely: it enables customers to upload images of the product review form (no registration required) it's ideally easy to install & manage you get to integrate the product review functionality through a widget you, the admin, get to review the uploaded images' widths & heights The Magento 2 Review Reminder Extension Now, could you imagine the reviews system on your Magento 2 website without a powerful review reminder type of tool plugged in? I didn't think so... They make such handy tools to help you encourage customers, via email reminders, to post reviews for the products they've bought. Now, here are the key features of this specific tool here, an essential Magento 2 product reviews extension: targeting specific groups of customers that you'd send your email reminders to sending automated reminder emails using coupons to entice customers to share their first product reviews and even choosing its template cleaning log records automatically, after a specific no. of days setting up the right time for sending the first reminder email The END! These are the 5 best Magento 2 review extensions to add to your shortlist and start your “research” with. feature-rich powerful easy to set up and customize on your side easy to use on your customers' side … each module, taken separately, injects those product reviews functionalities into your store to help you enhance the built-in reviews system that the platform provides you with.
Silviu Serdaru / Sep 13'2018