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Facebook and Twitter have left most other companies around the world far behind when it comes to using machine learning to improve their business model. And while their practices haven’t always resulted in the best reactions from end-users, there’s much to be learned from these companies on what to do–and what not to do–when it comes to scaling and applying data analytics.

Get the Data You Need First

While Facebook seemingly uses machine learning for everything — it is used for content detection and content integrity, sentiment analysis, speech recognition, and fraudulent account detection, as well as operating functions like facial recognition, language translation, and content search functions. The Facebook algorithm manages all this while offloading some computation to edge devices in order to reduce latency.

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Introduction

A few years ago, speech recognition technology was a punchline in many a sitcom’s jokes. Understandably, the technology was in its infancy prone to errors. Now, reaching new levels of maturity and wide acceptance, Amazon’s Alexa is just one example of this, the technology is now being implemented in novel ways. The need for developing APIs has now evolved from making the technology work to how it can be done conveniently and efficiently.

Accessibility

Moving beyond the technology’s threat to privacy one of the greatest virtues of speech recognition technology is its accessibility. In providing the disabled with a technology that allows interaction and interfacing with other technologies, speech recognition has become a technology at the forefront of providing accessibility and promoting inclusivity. For the workplace, the benefits range from more productive employees to promoting greater diversity amongst the workforce.

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Suppose you have an opportunity to create a project on AI. Consider these five stages before starting. These five are learning, programming language, knowledge representation, problem solving, and hardware.

1. Learning Process

Learning means adding new knowledge to the knowledge base and improving or refining previous knowledge.

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The digital world is a place of constant change. Just as you get used to a new design trend, another one appears, forcing you to rethink the way that you approach each client project. 

As a web designer, it’s up to you to make sure that you have your finger on the pulse on the latest transformations in the industry. However, it can be challenging to know for sure which trends you should be taking seriously, and which you can simply ignore. 

One option to refine and enhance your design journey is to pay attention to influencers. 

Influencers aren’t just there to guide customers into making purchasing decisions. These people are thought-leaders in their field. They spend all of their time tracking down ideas and concepts that really work. That way, they can maintain a successful reputation online.

Sourcing information and motivation from the following UX influencers could help you to create some truly amazing websites in 2020: 

1. Andrew Kucheriavy 

Andrew Kucheriavy is the phenomenal co-founder and CEO of a company named Intechnic. Andrew was one of the first people in the world to be given the “Master in User Experience” award. This means that he’s an excellent person to pay attention to if you want help understanding the ins and outs of user experience design

As one of the leading visionaries in UX, business strategy, and inbound marketing, Andrew has a lot of useful information to offer professionals and learners alike. Andrew is particularly active on Twitter, where he’s constantly sharing insights on design and marketing. You can also find input from Andrew on the Intechnic blog. 

2. Jeff Veen 

Another must-follow for designers who want to learn more about understanding their audience and their position in the marketplace, Jeff Veen is a leader in UX and product design. Veen got his start with the founding team for Wired, before he created the Adaptive Path company for UX consulting. Jeff Veen is also known for being responsible for various aspects of Google Analytics. 

Over the years, Jeff has expanded his knowledge in the design space, and mentored various companies, from WordPress to Medium. He also has a fantastic podcast that you can listen to for guidance when you’re on the go. 

3. Jared Spool 

Jared Spool has been tackling the most common issues of user experience since before the term “UX” was even a thing. Excelling in the design world since 1978, Jared has become one of the biggest and most recognizable names in the user experience environment. He’s the founder of the User Interface Engineering consulting firm. The company concentrates on helping companies to improve their site and product usability. 

Jared offers plenty of handy information to stock up on in his Twitter feed. Additionally, you can find plenty of helpful links to blogs and articles that he has published around the web on Twitter too. He’s followed by Hubgets, PICUS, and many other leading brands. Make sure that you check out his collection of industry-leading talks on UIE. 

4. Jen Romano Bergstrom

An experimental psychologist, User Experience Research coach, and UX specialist, Jen is one of the most impressive women in the web design world. She helped to create the unique experiences that customers can access on Instagram and Facebook. Additionally, she has a specialist knowledge of eye-tracking on the web. You can even check out Jen’s books on eye-tracking and usability testing

When she’s not writing books or researching user experience, Jen is blogging and tweeting about usability and researching new strategies in the web design space. It’s definitely worth keeping up with Jen on Twitter, particularly if you want to be the first to know about her upcoming seminars and learning sessions. 

5. Katie Dill 

Katie Dill is the former Director of Experience for Airbnb, so you know that she knows her way around some unique experiences. With an expertise in working with companies that harness new technologies and UX design, Katie Dill is at the forefront of the user experience landscape. Dill attends various UX conferences throughout the year, and publishes a range of fantastic videos on YouTube. 

You can find blogs and articles from Katie published on the web; however, you’ll be able to get the most input from her by following Katie on her Twitter account. 

6. Khoi Vinh 

Khoi Vinh is one of the most friendly and unique UX bloggers and influencers on the market today. He knows how to talk to people in a way that’s interesting and engaging – even about more complicated topics in UX design. Vinh is a principle designer at Adobe, and he has his own podcast called Wireframe. However, he still finds time to keep his followers engaged on Twitter. 

Over the years, Khoi has worked as a Design Director for Etsy and the New York Times. Vinh also wrote a book called “Ordering Disorder” which examines grid principles in web design. According to Fast Company, he’s one of the most influential designers in America. Additionally, Khoi has a brilliant blog where you can check out all of his latest insights into UX design. 

7. Cory Lebson

Cory Lebson is a veteran in the world of web design and user experience. With more than 2 decades of experience in the landscape, Cory has his own dedicated UX consulting firm named Lebsontech. Lebson and his company concentrate on offering UX training, mentoring, and user experience strategy support to customers. Cory also regularly speaks on topics regarding UX career development, user experience, information architecture and more. 

Cory is an excellent influencer to follow on Twitter, where you’ll find him sharing various UX tricks and tips. You can also check out Cory’s handbook on UX careers, or find him publishing content on the Lebsontech blog too. 

8. Lizzie Dyson

Another amazing woman in the industry of UX, Lizzie Dyson is changing the experience landscape as we know it. Although she’s a relatively new figure in the web design world, she’s recognized world-wide for her amazing insights into the world of web development. Lizzie also helped to create a new group specifically for women that want to get involved in web design. 

The Ladies that UX monthly meet-up welcomes a community of women into the digital landscape, helping them to learn and expand their skills. Lizzie regularly publishes content online as part of Ladies that UX. Additionally, she appears on the Talk UX feed – an annual design and tech conference held for women around the world. 

9. Chris Messina 

Chris Messina is a product designer and a technical master who understands what it takes to avoid disappointing your users. With more than a decade of experience in the UX design landscape, Messina has worked for a variety of big-name brands, including Google and Uber. He is best known as the inventor of the hashtag!

Chris is a highly skilled individual who understands the unique elements that engage customers and keep people coming back for more on a website. You can see Chris speaking at a selection of leading conferences around the world. Check out some of his talks on YouTube or track down his schedule of upcoming talks here. Chris also has a variety of fantastic articles on Medium to read too. 

10. Elizabeth Churchill

Last, but definitely not least, Elizabeth Churchill is a UX leader with an outstanding background in psychology, research science, psychology, artificial intelligence, cognitive science, human interaction with computers and more. She knows her way around everything from cognitive economics, to everyday web design. Churchill also acts as the director of UX for Google Material Design. 

A powerhouse of innovation and information, Churchill has more than 50 patents to her name. She’s also the vice president of the Association for Computing Machinery too. When she’s not sharing information on Twitter, Elizabeth also has a regular column that you can tune into on the ACM Interactions magazine. 

Who Are You Following in 2020?

Whether you’re looking for inspiration, guidance, or information, the right influencers can deliver some excellent insights into the world of web design. There are plenty of thought leaders out there in the realm of user experience that can transform the way that you approach your client projects. You might even discover a new favourite podcast to listen to, or an amazing series of videos that help you to harness new talents. 

Influencers are more than just tools for digital marketing; they’re an excellent source of guidance for growing UX designers too.

 

Featured image via Pexels.

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Artificial intelligence. Just hearing the phrase has been a trigger for many in the technology world since that creepy Haley Joel Osment film circa 2001. But more recently, artificial intelligence and machine learning strike fear into the hearts of skilled workers for an entirely different reason: job security, or lack thereof.

Smart-home devices, streaming services, self-checkouts, even Google searches are ways that artificial intelligence has seeped into everyday life, exemplifying the abilities of computers and machines to master both simple and complex tasks. In some instances, these technological advancements make our lives easier, but for some people, their proliferation has meant job loss and skill replacement. There’s no wonder that when artificial intelligence starts being mentioned along with web design and site creation, the spidey senses of designers all over the world start tingling.

designers think outside the box, something that AI just can’t do

But let’s get real about what AI and automation really mean for designers for a second. Talented designers with busy schedules should view these advancements as virtual assistants. For some small businesses on a limited budget, the websites that artificial intelligence can pump out might be fine…for a while. However, as businesses grow, change, require updating and customization to adapt to their customer base, the expertise of creative and talented designers will always be needed. Even the best AI that we see today is limited by evaluating, replicating, and revising what already exists. It may be able to mix 1,000 different color schemes into 10 million potential combinations, but great designers think outside the box, something that AI just can’t do.

In fact, rather than being scared of automation, designers ought to embrace automation and artificial intelligence as a way to unleash their creative thinking. Delegate repetitive, straightforward tasks to the right software, and suddenly you have time to bring your best ideas to the table and push the boundaries of your own innovation. 

Where AI has Failed in Design

The ultimate goal of artificial intelligence and automation in design work is a grand vision that has yet to be realised.

Consider the case of The Grid, which began as a crowdfunding campaign in 2014. The “revolutionary” product posed itself as an artificial intelligence solution for building thoughtfully, yet automatically, designed websites in five minutes. Research “Reviews of the Grid” in any search engine and you’ll be met with scathing criticism with only some small praise sprinkled in. Most of the initial users cite underwhelming results, the feeling of being duped by the Grid’s marketing tactics, nonsensical placement of text, and ultimately, the Grid being a complete waste of money for the resulting product. Even at the low cost of $100, compared to hiring a talented designer, most users felt their investment was wasted.

For the AI capabilities that exist now, most small business owners, or those looking to put together a simple website, are better off using drag and drop site builders (Wix, Squarespace, Weebly, etc) that have been around for ages. Even so, there are plenty of businesses still willing to hire designers to take this simple task off their plate due to a lack of technical expertise or lack of time. And let’s be honest, are there even enough talented (keyword here!) designers out there to keep up with the millions of websites created every year, without each one working themselves to death? 

Where Automation Shines for Designers

Fortunately for good designers, it appears for now that the days of artificial intelligence completely taking over their jobs is a fantasy. However, what AI and automation do offer designers is a solid starting point for success, eliminating much of the lower-level grunt work that most designers would rather skip anyway.

Even well-received AI website builders like Firedrop still require a basic eye for design and specialised knowledge to produce truly unique, high-converting, and user-friendly websites. Tools and practices that designers should adopt are the artificial intelligence and automation resources that will help them do their jobs better, faster, and leave them with more time to focus on project elements that AI cannot accomplish on its own.

Bridging the Gap Between Designers and Developers

Well-established brands are likely to already have design systems in place that guide the creation of new elements across their digital profiles whether on social media, various mobile apps, or different sections of a website. But even in large corporations — excepting those who have perfected the process — there’s often a breakdown between a designer’s vision and resulting product from the developers. It stems from the basic difference in how they each approach their work and the limitations of the systems they use.

While component libraries — or even full design systems for that matter — won’t reconcile every question, they provide both developers and designers a source of truth to work from that both parties can understand. Design collaboration tools like Invision and Visme, specifically, keep designers and developers on the same page with automated version saving and code-friendly workflows.  

Understanding the Consumer

I don’t suggest using artificial intelligence to produce content for your site

Digging into and understanding the behaviours and habits of site users is a relatively new component of site design, but offers invaluable insights. Tools like HotJar, Mouseflow, or Smartlook make it simple to see holes or leaks in your conversion funnels, detect which page elements users are interacting with, and which they’re not interested in to refine the look and feel of a page for maximum conversions. Even though these tools provide the data, it still takes a keen eye and understanding of design to implement the right changes to improve site performance.

Site content is another way that artificial intelligence has the potential to improve our understanding of customer behaviour and improve site performance for individual users. I don’t suggest using artificial intelligence to produce content for your site, no matter how much the results have improved. However, static landing pages or a single set of further reading recommendations are unlikely to appeal to the majority of site visitors. Artificial intelligence tools like CliClap and Personyze instantly collect and analyse consumer data to provide dynamic, personalised experiences that drive more leads and encourage conversions. Creative designers will also learn from this data to improve customer experience with other pages or elements throughout the site.

Removing Distracting, Time-Sucking Administrative Tasks

Because “artificial intelligence” has become a term with such negative connotations, we often overlook the simple way that AI actually makes our work lives better and easier. Machine learning in email filtering is a great example of this. Consider a simple interface like a Gmail inbox. We have the option to mark certain senders as spam or as important, and our inbox learns that type of communication is and isn’t useful to the user. Pandora, Spotify, Apple Music, and more all take cues from the user behaviour of liking a certain song, artists, or genre of music to build customised playlists. There are a myriad of ways that artificial intelligence and its branches of disciplines merge with our everyday lives. 

Some of the most useful automations for business, and especially for designers, are related to the administrative tasks that frequently take time away or distract from more pressing projects. A perfect example of automation that can relieve stress and cut down on mindless work is an email autoresponder. I’ve always found that having time blocked off in my calendar to tackle complex or important projects helps me to focus on the task at hand and be more efficient. In order to more effectively block out my time, closing my email and setting an autoresponder to reply to all incoming emails serves two purposes: 

  1. Lets those trying to get in touch with me know that I only check my email at certain times of the day and that my response may not be immediate — tempering their expectations of when they might hear from me.
  2. Relieves my personal stress of being tethered to my inbox, splitting my focus, and also saves the time of having to initially respond to each email individually. 

This is just one simple way to use automation in your email, although there are many others to explore.

While Zapier isn’t the only workflow automation service on the market, it’s probably the most well known. Workflow automation reduces time spent on mind-numbing, repetitive tasks and helps designers connect apps that might not natively work together. Do you keep a task list in Todoist? Set up a Zap, then create a task in Todoist anytime someone mentions you on Asana or assigns you a task in Trello.

This is especially helpful for freelance designers who work with multiple clients across various project management platforms. The potential for automation to relieve unnecessary mental overhead for designers is nearly limitless.

Don’t be Afraid of AI, Embrace It

The bottom line of this brief overview of artificial intelligence and automation in design is that this emerging technology isn’t something designers should be scared of. In fact, it’s something to welcome with open arms because ultimately it can make our jobs, and our lives, better. Leave the monotonous tasks of collecting and analysing huge amounts of data or administrative minutiae to the machines; they can handle it.

Save the interesting, creative, abstract work for the talented designers who can turn AI recommendations into unique and intuitive digital experiences. Making the relationship between artificial intelligence and design symbiotic will yield the best results for every entity involved: the business, the AI, and yes, even the designer.

 

Featured image via Unsplash.

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AI has been a revolutionary technology in the Tech world. The demand for artificial intelligence-related professions is increasing at an incredibly rapid rate. Similarly, the demand for an Azure AI Engineer is on buzz and at an all-time high. Many other AI-concerned accreditations could also be good alternatives for IT professionals. But, MS Azure assures a rapidly growing Artificial Intelligence landscape with innovative service offerings and advanced technologies. Hence, the demand for Microsoft Azure AI Engineer Associate Certification has increased to a large extent over the past few decades.

The future platform of the IT accreditation, AZURE AI mainly assists you to scrutinize AI services which count bots, agents, language, vision, speech, by adopting knowledge mining, cognitive services, and machine learning. AI solutions are required to satisfy scalability and performance to meet end-to-end solutions, for that we need to have advanced technologies and tools for analyzing and recording timely operation. 

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Artificial Intelligence is a growing industry powered by advancements from large tech companies, new startups, and university research teams alike. While AI technology is advancing at a good pace, the regulations and failsafes around machine learning security are an entirely different story.

Failure to protect your ML models from cyber attacks such as data poisoning can be extremely costly. Chatbot vulnerabilities can even result in the theft of private user data. In this article, we’ll look at the importance of machine learning cyber security. Furthermore, we’ll explain how Scanta, an ML security company, protects Chatbots through their Virtual Assistant Shield. 

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Artificial intelligence which gives machines the ability to think and behave like humans are gaining traction since the last decade. These features of artificial intelligence are only there because of its ability to predict certain things accurately, these predictions are based upon one certain technology which we know as machine learning (ML). Machine learning as the name suggests is the computer’s ability to learn new things and improve its functionality over time. The main focus of machine learning is on the development of computer programs that are capable of accessing data and using it to learn for themselves. 

To implement machine learning algorithms, two programming languages, R and Python for machine learning are normally used. Generally, selecting features for training data on machine learning in python is a very complex and technical process. But here we will go over some basic techniques and details regarding what is machine learning and how it works. So, let us start by going into detail regarding what ML is, what feature selection is and how can one select feature using python.

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Introduction

According to a 2016 research by Mckinsey, it was revealed that the total annual external investment in AI ranged between $8billion to $12billion in. Statistically, this is a clear sign that AI is making a great impact in the global industries especially the financial sector. In other words, it’s a revolutionary impact in the financial industry can not be underestimated.

Blockchain, on the other hand, has also shown its immense potential in so many industries especially in the finance industry. In fact, it’s digital disruption is greatly impacting how so many businesses operate in our contemporary world. While so many industries are beginning to embrace the amazing options these technologies – Artificial intelligence and Blockchain technology offer – helping them to create more value,  boosting sales, and so on,  it’s interesting to know that the combination of both will positively revolutionize the future of the fintech industry.

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Yupoo Picture Manager serves tens of millions of users and manages tens of billions of pictures. As its user gallery is growing larger, Yupoo has an urgent business need for a solution that can quickly locate the image. In other words, when a user inputs an image, the system should find its original image and similar images in the gallery. The development of the search by image service provides an effective approach to this problem.

The search by image service has undergone two evolutions:

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