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You don’t need advanced intelligence to find meaning in the ever evolving world of data for the AI lifecycle. You just need the right partner. With technology bringing us closer together, we aim to show the value ethical data can have in creating the future we want, today.
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Revisiting The State of AI and Machine Learning 2021
Looking for the 2022 State of AI and Machine Learning Report? Click here to pre-register and get the report right in your inbox next week! In preparation to share our 8th annual State of AI Report , we’ve looked back on last year’s report to see how much the industry has progressed in a year and if our assumptions were ...
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Training Chatbots to Improve Customer Experience
When it comes to taking care of your customers, one of the most important things is showing them respect as people and respect for their time. That means being prompt and helpful during your interactions—especially if you want them to come back. Society has set the expectation that a customer can ask a question any time, 24/7, and get a ...
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Autonomous Vehicles: One of AI’s Most Challenging Tasks
Autonomous vehicles are said to be the holy grail of the automotive industry, set to revolutionize transportation. The hype for autonomous vehicles just a few years ago was as high as can be—so what happened? Where’s our driverless car revolution that so many companies touted we’d have by 2021? As it turns out, creating a self-driving car is much harder ...
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Meet the Executive: Andrea Clayton
For the past few years, companies have been shifting their rhetoric from what they’re making and selling to what they’re doing to benefit their community and their employees. But, many were just paying lip service to the cause. Not at Appen. We put our actions where our mouth is, starting with the hiring of Chief People Officer Andrea Clayton in ...
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A Healthy Planet is a Happy Planet: How AI can Help Heal the Environment
The earth, the environment, nature is entirely organic and has sustained itself since its formation. Seemingly something so organic has no need for technology, yet, with all the changes going on in this planet, we can look to AI to help put this planet back on track for happy and healthy millennia to come. A worldwide goal has been set ...
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AI Ethics: How Fair Pay Benefits Our Crowd Contributors
We’re in the data business. Crucial components in the AI lifecycle are data sourcing and data preparation–collecting, cleaning, and labeling data. We create datasets for companies all over the world and we couldn’t do it without the support of our global Crowd. Our contributors are the people who collect and label data, making AI and machine-learning solutions possible. That’s why ...
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Perfecting AI Customer Service in the Hospitality Industry with Data
Hospitality is a very human-centric field. Whether it’s a hotel, restaurant, or place of entertainment, a person will be there accompanying you every step of the way—that’s what we’ve come to expect in customer service. But, just because we’ve become accustomed to it, does that mean it’s the best possible experience? Artificial Intelligence has been taking the hospitality industry to ...
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Meet the Executive: Wilson Pang
Meet: Wilson Pang, Appen Chief Technology Officer When Wilson Pang graduated from Zhejiang University in China, where he grew up, with Bachelor’s and Master degrees in electrical engineering, his career plans didn’t include working in artificial intelligence. Mostly, that’s because artificial intelligence was still the stuff of science fiction. From his early days, Wilson fell in love with technology. In ...
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AI Can Help End World Hunger, One Crop at a Time
World hunger is on top of everyone’s mind–especially with tomorrow being World Hunger Day. The thought of everyone having enough to eat is a comforting one; One that can soon become a reality. As with the introduction of most new things, there’s some hesitation about how much of a role AI should play in something so delicate as having control ...
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Meditation & AI: Creating a Customized Relaxation Experience
It seems these days you can’t scroll a website or a social network without being touched by at least one mental health message. It’s not just you. It’s something everyone can benefit from and given the added stresses of this current constant state of change, companies are tapping into that need with smart technology that can add a little bit ...
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AI is the Key to Convenience
Anyone and everyone can benefit from new technology and who doesn’t love the idea of more convenience, more simplicity and more free time? Add a few extra free minutes to your day or enrich your hobbies with AI powered tools that add a little convenience to your everyday hobbies. From e-book readers to AI powered appliances to plant identifying applications ...
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May the 4th Be with You: The AI Behind Movie Magic
Whether you adore the Cantina Band or prefer to jam out to The Imperial March, we’d like to say… May the 4th be with you. May the 4th (Star Wars Day), is an informal holiday that honors the Star Wars legacy and its undeniable impact on modern filmmaking. Star Wars is credited with a host of innovations in cinema including ...
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Appen in the News: Q1 2022
At Appen, we have a diverse team working on a ton of different, interesting projects. Many of these projects are niche or technical and get written about in various publications across the internet. We put together the biggest hits from Q1 of 2022 to share with you. Here’s everything we’re working on and what everyone has to say about it. ...
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Synthetic Data and its Role in the World of AI
What is Synthetic Data? Synthetic data is artificially created rather than captured from real life and has evolved from machine learning needs for data. Originally, training data had to be obtained to cover every possible scenario to accurately train AI models. If a scenario had not occurred or been captured, there was no data, leaving a huge gap in the ...
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Earth Day 2022: Appen’s Commitment to a Better Environment
It may seem a strange change for the global leader in Data for the AI Lifecycle to pause from our usual AI insights and Data for the AI Lifecycle content to recognize an organic moment such as Earth Day. After all, does data really have an impact on our planet? The short answer is, yes, it does—but we also have an ...
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How Microwork Opportunities and Stablecoin Use Can Benefit People Around the World
One of the center points of technological innovation today is data. But, to gather and annotate that data takes thousands of hours of work. Work that can be done by anyone, anywhere in the world. The internet makes it possible to break up these tasks into thousands of micro-tasks which can then be distributed to workers around the globe. This ...
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What is MLOps?
The exciting wave of developments in AI and machine learning applications might lead you to believe that organizations are also advancing rapidly in their ability to deliver ML products. The reality is, ML internal processes are having trouble catching up with the overall evolution of the industry… but there’s hope in the form of MLOps! MLOps, which stands for machine ...
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Machine Learning Model Validation – The Data-Centric Approach
When it comes to building a machine learning model, all the excitement and energy gets channeled into collecting the data and training the model. What often gets less time in the spotlight is testing the model and validating the results. The right validation techniques help to estimate unbiased generalized model performance and give a better understanding of how the model ...
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Meet the Executive Series: Sujatha Sagiraju
One of our core values at Appen is recognizing and celebrating the people that make the work we do possible. For us, that means writing about and talking about the accomplishments of our people so you can see just how awesome they are. To celebrate our staff, we’ve started a series highlighting a day in the life of an Appen ...
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Make your Speech Recognition System Sing
Your data can be the difference between an efficient and cost-effective voice recognition system and one that doesn’t work very well. When it comes to machine learning, one of the most important components for a successful launch and return on investment is data. If you’re planning to build a voice recognition system or conversational AI, you’ll need a big speech ...
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Machine Learning in Advertising – Predictive Targeting and Moderation
The job of marketers is to get the right product in front of the right consumer at the moment that they’re most likely to buy that product. The ability for marketers to do just that and to drill down to more and more specific niches of customers has grown exponentially over time. AI technology is now being used to help ...
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A Foundation of Women In Tech
This year, the world will be celebrating International Women’s Day on March 8 honoring the impact of women under the theme of #BreaktheBias. While we all celebrate on March 8, at Appen, we strive to take steps every day to make the workplace and tech space more diverse, equitably, and free of bias. We know that the more diverse people ...
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How Artificial Intelligence Data Reduces Overhead Costs for Organizations
When it comes to AI, many companies think of these as projects, with limited scope and short term. They see the high cost of development and deployment and aren’t sure that AI is right for their company. What they don’t recognize off the bat is the long-term goal of reducing costs that may result from applying AI to the right ...
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How Data and Machine Learning Model Choices Impact Deployment Rates
When you’re building a machine learning model, there are a few critical components to consider: calculation power, the algorithm, and the data. Often, a company will focus most of its resources on developing the right, bias-free algorithm and investing in more calculation power. Data is often an after-thought or forgotten entirely until it’s time to run the model. When data ...
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How Data Annotation Platforms Help Improve Machine Learning Models
In recent years, AI has become less of a flashy new idea and more mainstream with a wide variety of businesses implementing AI technology and machine learning models into their business practices. And, as the world generates ever-growing amounts of data, the data you need for your specific use case is likely already out there just waiting for you to ...
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Introducing the New Era of Data for the AI Lifecycle
Data for the AI Lifecycle encompasses four main steps in the continuous cycle to deliver high quality data needed for any AI project. The steps are: data sourcing, data preparation, model training and deployment, and model evaluation by humans. Data sourcing, data preparation and model evaluation are the most laborious and data intense and if not done well, can lead ...
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Expert, Secure and Timely Transcription Services for Conference Calls
Searching online for dial-in conference call transcription reveals countless ‘cheap and cheerful’ DIY options. But if quality matters as well as cost, you’ll need an experienced, specialist transcription provider. Developments in recording technology and speech to text conversion software mean there are plenty of DIY solutions out there if you want to create a written record of your important conference ...
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Meet the Executive Series: Jen Cole
At Appen, we know that we couldn’t do it without the people who work on and in the company each and every day. As a thank you for their hard work, we’re featuring one of our contributors each month through a series of blog posts and we’re introducing you to our executive team. At Appen, we enable the most innovative ...
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Search Relevance — Why No Website or App Should Be Without It
Set the scene: you’re looking for a new item of clothing, so you navigate to your favorite online store. You hop up to the search bar to type in what you’re looking for. What results do you expect? Highly accurate, relevant, and instantaneous results. Customers expect high-quality results no matter what website they’re searching on, what they’re looking for, and ...
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AI vs. Deep Learning vs. Machine Learning: Everything You’ve Ever Wanted to Know
If you’ve spent any time reading articles about tech in the last few years, you’ve likely bumped into some new terms such as artificial intelligence or AI, machine learning or ML, and deep learning. These trending tech terms are often used without explanation of what makes them different. And, to be clear, they’re not interchangeable. As technology becomes more and ...
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The Rise in Computer Vision Datasets & How It Benefits Organizations
One of the most exciting subfields in AI and machine learning today is Computer Vision or CV. CV is used in a diverse number of applications to improve our daily lives, as well as advance science and technology research. These use cases include: Autonomous driving Automatic image captioning Facial recognition and tagging on social media Medical imaging analysis and diagnostics ...
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Top 5 Predictions About the Future of AI and Data
For the past few years, overarching goals with AI have been aspirational. As this new technology exists in the realm of literature and academia and is applied to real-world problems and bent to real-world solutions, there has to be a reckoning with its true capabilities and use cases. For AI, 2021 was a year of over-promising. While potentially underwhelming and ...
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What are Managed Services in AI?
Deploying a well-performing AI model is a complicated, resource-intensive task, so it’s no surprise companies are turning to managed services for assistance. Generally speaking, managed services refers to any end-to-end white glove service. A company can partner with a managed service provider (MSP) for all or part of a given operation via managed services. This concept is now frequently being ...
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Apache Log4J Security Update
The Appen team has taken quick action in relation to resolving the vulnerability advisory related to Log4shell (CVE-2021-44228) which may affect organizations that use vulnerable versions of the Log4j package. The vulnerability is a remote code execution issue in the Apache Log4j logging services application which may affect Java applications. During our security team’s review, malicious or suspicious activity has ...
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What is Synthetic Data?
Everything You Need to Know About Synthetic Data Companies launching artificial intelligence (AI) face a major hurdle in collecting sufficient data for their models. For many use cases, the right data simply isn’t available or is very difficult and expensive to acquire. Missing, or incomplete, data isn’t desirable when creating AI models, but even larger tech companies misstep in this ...
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Natural Language Processing – Connecting The World through Language With AI
As very young children, before we can even walk or talk, we’re listening. We’re hearing the sounds and vocalizations made by other people. We’re attaching those combinations of sounds to meanings, such as ‘mother’ and ‘door’, and learning to read the facial expressions of those around us to deepen our understanding of blocks of words. Then we go to school, ...
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What is Automatic Speech Recognition?
Advances in AI in conjunction with the global pandemic have motivated businesses to enhance their virtual interactions with customers. Increasingly, they’re turning to virtual assistants, chatbots, and other speech technology to power these interactions efficiently. These forms of AI rely on a process known as Automatic Speech Recognition, or ASR. ASR involves the conversion of speech into text; it enables ...
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What is Active Learning?
When and Why You Should Select an Active Learning Approach The key to training any machine learning (ML) model is data. Yet data remains one of the biggest barriers to success for organizations and teams investing in artificial intelligence (AI). For one, you need a lot of it to create high-performing models. And what’s more, you need data that’s accurately ...
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25 Year Anniversary
This year, Appen is celebrating its 25th Anniversary in helping people access reliable training data to deploy their projects with confidence. As we look to the future, we’re also reflecting on the past. Looking back on where we’ve come from is how we can see our growth and can get a clear picture of how many people and companies we’ve ...
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Data Labeling Tools: How to Level up Your Process
From spam filtering to personalized chat bot experiences, AI innovations are becoming a facet of our everyday lives. Most companies, if they haven’t already, are considering adopting AI and machine learning tools in their internal and external processes. What many people don’t realize if they haven’t worked with AI and machine learning technology before is that you can’t just go ...
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Augmented and Virtual Reality AI Data: Powering the Next Big Thing
Augmented reality and virtual reality (AR/VR) are two promising technologies that businesses are keeping an eye on. In fact, nearly three-quarters of industry leaders report that they expect these immersive technologies to be mainstream within the next five years and Goldman Sachs reports that the AR/VR industry will be worth $95 billion by 2025. At the same time, running in parallel ...
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Navigating the World of Machine Learning Datasets: Where to Find the Best Machine Learning Datasets
Many companies are turning to external datasets to launch AI successfully. We are now in an age where finding datasets is getting easier than ever before, and they are getting more and more important for the performance of machine learning models. There are many sites that host repositories for data that covers an incredible range of topics—from images of rare ...
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What is Sensor Fusion?
Sensor Fusion Shapes the Future of Connected Devices Sensors are used in almost every industry now: they’re found in our cars, in our factories, and even in our smartphones. While an individual sensor may provide useful data on its own, imagine the information that could be extracted from combining output from multiple sensors at once. This would give us a ...
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What is Audio Transcription?
How AI is Making Transcription More Efficient Human transcription has been around in some form for hundreds, if not thousands, of years. Recently, it’s getting a boost with AI. Transcriptions themselves are the text form of the audio content; they enable a reader to comprehend what was said or what happened during a period of time without having to listen ...
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What is Human-centered AI?
The Future of AI Needs a Human Touch The rapid evolution of AI technology has generated much excitement around its potential to enhance our daily lives. As a result, AI experts are having frequent conversations around the best ways to leverage AI in our society and out of this dialogue has emerged the human-centered AI approach. Human-centered AI isn’t about ...
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What are Data Collection Solutions?
How to Collect Data Efficiently and Responsibly for Your AI Initiatives Data collection continues to be a major bottleneck for teams building artificial intelligence (AI). The reasons vary: there may be a lack of sufficient data for a use case, new machine learning (ML) techniques like deep learning require more data, or teams don’t have the right processes in place ...
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The Basics of Small Data: Actionable Data Provide a New Path Forward in AI
You may have heard the buzzword “big data” in the context of AI, but what about small data? Whether you’re aware of it or not, small data is all around you: it powers online shopping experiences, airline recommendations, weather reports, and more. Small data is data that’s in an accessible and actionable format and easily comprehensible by humans. Data scientists ...
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Verbatim vs. Intelligent Verbatim: Which Transcript Style to Choose, and When
Transcripts can be created in a range of styles and formats, depending on the scenario. Verbatim and intelligent verbatim are the two most common, but in order to choose the right one, it’s important to understand the differences between them. When it comes to creating a written record of the spoken word, the finished transcript can vary greatly depending on ...
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Data Science and Machine Learning Automation: What to Know About the State of Automation in AI
In the last decade, there have been many developments in the automation of artificial intelligence (AI) building. Frequently in dialogue about the future of AI, you may hear reference to data science automation and machine learning automation used interchangeably. In reality, these terms have distinct definitions: the current automated machine learning (known as AutoML) goals refer specifically to the automation ...
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Navigating the Transcription Process
Seven Simple Steps to Getting the Best Written Record As remote working becomes increasingly prevalent, more and more organizations are finding they need accurate written records of their virtual meetings and conference calls. Whether you are a first-timer or an existing customer, have you ever wondered how the transcription process works? Here’s Appen’s guide to what happens when. 1. Identify ...
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Don’t Start from Scratch When Building Machine Learning Models
How Leveraging Training Data with Pre-Trained Models Can Accelerate Your AI Projects It would probably be a safe bet to assume that most of the AI you’ve interacted with was built using supervised learning. Supervised learning, which is essentially building machine learning (ML) models from scratch, has been the key driver of artificial intelligence (AI) development so far, motivated by ...
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The Role of Data in Responsible AI: Data Decisions that Shape the Future of Ethical AI
There’s no question that artificial intelligence (AI) will continue its rapid evolution in the coming years and become increasingly interconnected with our daily lives. The onus is now on companies to approach AI with a responsible lens in order to maximize transparency, reduce bias, and guide ethical applications of the technology. AI that works well, after all, works equitably for ...
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What is Optical Character Recognition?
How Artificial Intelligence Gives OCR a Boost Artificial intelligence is transforming the capabilities of optical character recognition (OCR) tools. An area of computer vision, OCR processes images of text and converts that text into machine-readable forms. In other words, it takes handwritten or typed text within physical documents and converts them into digital formats. In the 1990s, many business owners ...
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What is AutoML?
Automated Machine Learning Uses and Approaches Explained As organizations seek to use machine learning in more diverse use cases, the amount of pre and post data processing and optimization scales exponentially. The difficulty to hire enough people to do all the tasks associated with advanced machine learning models makes automated tools for machine learning a critical component for the future ...
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Where eBay Went Right—and Wrong—With AI: What You Measure Matters
The following is adapted from Real World AI. I joined eBay back in 2006, and in 2009, the company was in very bad shape. Its share price was at a historical low, well off its near-$24 historical high; it was cutting costs, growth was negative, market share was shrinking, and the technology team wasn’t empowered to innovate. Put simply, the ...
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The Current State of AI 2021: Report Now Available
What You Need to Know About the Seventh Annual Industry Report In our seventh edition of the State of AI and Machine Learning Report, we continue to evaluate an industry that is changing rapidly year-over-year. Our goal with the report is to provide a current picture of the trends, priorities, and challenges faced by businesses building AI technology. Once again, ...
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Types of Errors We See with Training Data: How to Recognize and Avoid Common Data Error
It’s helpful to contrast AI development with traditional software development. In traditional software, you write code that’s deterministic (i.e., every time you run it with the same inputs, you’ll receive the same outputs). But with AI development, it’s not the code that’s most important, it’s the data. Specifically, the labeling of the data. High-quality, accurately-labeled data is crucial to building ...
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Responsible AI Across the Value Chain: Ethical Approaches to AI from Data to Deployment—and Beyond
It can’t be stated enough: it’s the responsibility of every organization creating artificial intelligence (AI) to do so ethically. Responsible, or ethical, AI is AI that’s unbiased, equitable, and improves the quality of life of everyone it touches. In practice, it requires AI practitioners to apply an ethical framework to every AI endeavor they pursue, ensuring the people, processes, and ...
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What is Training Data?
Machine Learning algorithms learn from data. They find relationships, develop understanding, make decisions, and evaluate their confidence from the training data they’re given. And the better the training data is, the better the model performs. In fact, the quality and quantity of your machine learning training data has as much to do with the success of your data project as ...
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Five AI Market Trends for 2021: Shifting Approaches to Data, Use Cases, and More
The field of artificial intelligence (AI) continues to evolve at a rapid pace as companies learn and grow from their challenges and successes. More and more, companies are aligning on the foundational role that data plays in AI implementation. As a consequence, there are numerous exciting trends emerging within the data subdomain worth watching. These trends illustrate both the barriers ...
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What is Data Annotation?
Text, audio, image, or video becomes training data for machine learning through data annotation, with the help of people and technology. Building an AI or ML model that acts like a human requires large volumes of training data. For a model to make decisions and take action, it must be trained to understand specific information via data annotation. But what ...
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What is Data Labeling?
Everything You Need to Know About Data Labeling – Featuring Meeta Dash Artificial intelligence (AI) is only as good as the data it is trained with. With the quality and quantity of training data directly determining the success of an AI algorithm, it’s no surprise that, on average, 80% of the time spent on an AI project is wrangling training data, ...
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How to Get Started: Building Trustworthy AI in the European Union
Artificial Intelligence (AI) has tremendous potential to increase productivity, uncover new insights and create new experiences. But such a high potential technology demands that organizations build AI with a responsible lens in mind to make sure it nets a positive impact. The European Commission (EC) has taken steps to transform such recommendations into law and has recently expanded its product ...
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How to Reduce Bias in AI
Top Eight Ways to Overcome and Prevent AI Bias Algorithmic bias in AI is a pervasive problem. You can likely recall biased algorithm examples in the news, such as speech recognition not being able to identify the pronoun “hers” but being able to identify “his” or face recognition software being less likely to recognize people of color. While entirely eliminating ...
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Overcoming AI Deployment Challenges
5 Tips for Handling the Biggest AI Obstacles You may have heard the stat: over 80% of artificial intelligence (AI) projects never make it to deployment. While we expect to see that number decrease in the coming years, in the meantime companies face very real, and common, barriers to success. Lack of high-quality data, insufficient technical expertise, misalignment within the ...
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Machine Vision vs. Computer Vision — What’s the Difference?
Artificial Intelligence is an umbrella term that covers several specific technologies. In this post, we will explore machine vision (MV) vs. computer vision (CV). They both involve the ingestion and interpretation of visual inputs, so it’s important to understand the strengths, limitations, and best use case scenarios of these overlapping technologies. The Beginning of Computer Vision Researchers began developing computer-enabled ...
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3 Things Business Decision-Makers Must Do to Create Better AI
The following is adapted from Real World AI. It’s becoming increasingly clear that AI is the future for business. AI models can save time, increase efficiency, and drive revenue. As more and more businesses adopt AI, it soon won’t be a nice-to-have, but a must-have in order to compete in the marketplace. As a business decision-maker, that can be overwhelming. ...
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What is Text Annotation in Machine Learning?
Everything You Need to Know About Text Annotation with Yao Xu Every day, we interact with different media (such as text, audio, images, and video), relying on our brain to process what media we are seeing and make meaning out of it to influence what we do. One of the most common types of media is text, which makes up ...
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Secure Transcription Services for Sensitive Data
Maintaining the Highest Levels of Confidentiality During COVID-19 COVID-19 restrictions are challenging all service providers to come up with imaginative new ways to meet their clients’ needs. Appen is offering a two-part approach to transcribing confidential material that delivers high levels of confidentiality and protects our employees. Most transcription providers offer basic security measures, like staff vetting and agreed data ...
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AI in Police Work
Can AI Help Police Officers Solve Crimes? Law enforcement is in charge of public safety, and must handle all of the challenges that come with that. Luckily, police officers are able to rely on technology for many parts of their job. In recent years, artificial intelligence in law enforcement has become an important aspect of police work globally. As AI-based ...
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The Value of AI: Exploring Opportunities and Challenges in AI Technology
Demand for Artificial Intelligence (AI) practitioners and budgets for AI initiatives have never been higher. Digital transformation brought about by driving forces like the global pandemic have greatly accelerated development of AI and machine learning (ML) technology. More and more companies are figuring out how to unlock the value of AI and make it work in the real world, often to ...
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Response: Concerns regarding contractor onboarding
Recently, concerns have been expressed regarding one of our contractor onboarding questionnaires which included a voluntary demographic question about skin color. Appen’s role is to provide training data for AI that represents all users of the product so that the product is unbiased and works in the real world. Key to that is providing training data from diverse populations of ...
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What is Human-in-the-Loop Machine Learning?
Human-in-the-loop (HITL) is a branch of artificial intelligence that leverages both human and machine intelligence to create machine learning models. In a traditional human-in-the-loop approach, people are involved in a virtuous circle where they train, tune, and test a particular algorithm. Generally, it works like this: First, humans label data. This gives a model high quality (and high quantities of) ...
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What is LiDAR?
AI Unlocks Untapped Potential of LiDAR LiDAR has served as a useful tool in many industries for decades, but only recently are we starting to realize its true potential with the introduction of artificial intelligence (AI)-powered solutions. LiDAR, also known as light detection and ranging, is a remote sensing technology. It uses laser scanners to measure distances and dimensions between ...
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Spelling Standardization: How Many Ways Can You Spell a Word?
Here's a topic that's near and dear to our hearts here at Appen: spelling standardization. How hard can that be? Oh boy. Follow us down the rabbit hole.
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You Can’t Just Use AI – You Must Lead With AI
The following is adapted from Real World AI. AI will soon be a necessary part of doing business. Every company will have an AI strategy in the same way that they have a social media strategy, branding strategy, talent strategy, etc. So if you want to stand out from the competition and gain an edge, you can’t just use AI; ...
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An Introduction to Audio, Speech, and Language Processing
Applying Machine Learning to Everyday Scenarios Human-machine-interaction is increasingly ubiquitous as technologies leveraging audio and language for artificial intelligence evolve. For many of our interactions with businesses—retailers, banks, even food delivery providers—we can complete our transactions by communicating with some form of AI, such as a chatbot or virtual assistant. Language is the foundation of these communications and, as a ...
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To Launch AI Successfully, Be Prepared to Scale
The following is adapted from Real World AI. When I worked in IBM’s Watson division, my team’s first demo quickly turned into a disaster, due to scaling issues. We were creating a visual-recognition application programming interface (API). Our first demo was a simple website that allowed users to drag-and-drop images, press a button, and be presented with a list of ...
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AI Data Acquisition and Governance
Best Practices for Deploying Successful AI If you aren’t working with artificial intelligence, you will be soon. We interact with AI nearly every day, forcing many companies to experiment in the space. No matter where you’re at, you will likely encountered some challenges along the way. Two of the more complex elements for successfully implementing AI within your business are ...
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Four Tips to Pick Your Goldilocks Problem for AI
Why Selecting The Right Business Problem to Use AI to Solve is Essential The Following is Adapted from Real World AI. When your company is just starting to explore AI, picking the first problem to solve is just as important as coming up with the AI solution itself. Pick a problem that’s too big or difficult, and your AI project ...
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ML Techniques: Active Learning vs Weak Supervision
A Comparison of Two Popular Machine Learning Techniques Machine learning (ML) has grown exponentially as a field, but a familiar roadblock remains for many businesses: data. Training ML algorithms traditionally requires enormous amounts of manually-labeled data. The sheer size of data needed is often not available at scale and costly, not to mention the time and effort required to label ...
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Video Annotation: What Is It and How Automation Can Help
The Benefits of Automated Video Annotation for Your AI Models Similar to image annotation, video annotation is a process that teaches computers to recognize objects. Both annotation methods are part of the wider Artificial Intelligence (AI) field of Computer Vision (CV), which seeks to train computers to mimic the perceptive qualities of the human eye. In a video annotation project, a ...
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AI Model Maintenance: A Guide to Managing a Model Post-Production
Managing Models Beyond the Initial Deployment You’ve built your artificial intelligence model, trained it, tested it, tuned it, deployed it to production – you’re even receiving great feedback from customers! It’s time to move on to your next challenge, right? Not quite. The reality is it’s only the beginning: the lifecycle of a machine learning model continues long after deployment. ...
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What is AI-Powered Search Relevance?
Search Relevance Optimization with Machine Learning Techniques When you type a query into your favorite online retailer’s search bar, what kind of results do you expect? Most customers today expect search engines to be highly accurate, relevant, and instantaneous in delivery. Search engines should offer a personalized experience and predict your needs – even if your wording or spelling is ...
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What Is Image Annotation and How Is It Used To Build AI Models?
How Companies Use Image Annotation to Produce High-Quality Training Data Image annotation is the foundation behind many Artificial Intelligence (AI) products you interact with and is one of the most essential processes in Computer Vision (CV). In image annotation, data labelers use tags, or metadata, to identify characteristics of the data you want your AI model to learn to recognize. ...
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Leveraging AI and Machine Learning for Content Moderation
How Machine Learning Optimizes Content Moderation The internet has over 4.5 billion users and growing, generating billions of images, video, messages, posts, and other content types every day. This content must be regulated in some way, as most of these internet users want to visit their favorite social media platforms or online retailers and have a safe, positive experience. Content ...
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The Four Key Challenges of AI in Financial Services
Financial Service Providers Should Plan for AI Roadblocks An influx of artificial intelligence (AI) investment in the financial services space has brought forward new questions around data security and transparency. These, among other challenges of AI in financial services, are particularly essential to address as data management practices evolve with the introduction of new AI solutions. Organizations must be aware of ...
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Where to Focus Artificial Intelligence Investments in Financial Services
Using a Customer-Centric Approach to Drive Revenue Artificial intelligence investments in financial services is no longer just an option for organizations looking to compete in the financial services space. Finance organizations that have invested in AI are already seeing widespread benefits in revenue increase, reduced costs, and greater security compliance. This is especially important given the financial services industry faces mounting ...
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AI Ethics: The Guide to Building Responsible AI
Ethical AI Techniques to Minimize Bias Throughout the Model Build Process Artificial intelligence ethics are often thought of in the context of the model itself. Meaning, the focus is on the ethical quality of a model’s prediction and outcome, as well as the impact it has. Even though most companies focus on reducing bias in their models, that’s not enough to ...
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How to Approach Data Collection for Conversational AI Agents
Training Conversational AI Agents on Noisy Data Chatbots, virtual assistants, robots, and more: conversational artificial intelligence (AI) is already highly visible in our daily lives. Companies looking to increase engagement with customers while reducing costs are investing heavily in the space. The numbers are clear: the conversational AI agents industry is expected to grow 20% year over year through at least ...
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How to Build Successful Computer Vision Applications at Scale
Navigating Computer Vision Projects From Prototype to Production Computer vision is quickly gaining traction in several industries as the availability of image data grows, and artificial intelligence (AI) becomes increasingly paramount to companies worldwide. Computer vision, or CV, is a form of machine learning (ML) that helps computers see and interpret images similar to the human eye. By classifying images ...
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Five Challenges of Artificial Intelligence for Automotive Applications
What to Watch For When Scaling AI Applications in the Auto Industry As more companies invest in automotive artificial intelligence (AI) solutions, we come ever closer to the large-scale deployment of a Level 5, fully-automatic self-driving car. Automotive organizations looking to be part of this AI disruption should already be thinking ahead about how to deploy their artificial intelligence for automotive ...
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AI and Data Protection: Certifications and Regulations
Regulations You and Your Training Data Partner Need to Be Aware of to Minimize Risk It’s no secret that successful AI initiatives require time, money, and effort. But, a big roadblock to many models moving beyond experimentation has to do with data. High-quality training data often makes people think of very accurate data annotations, however, another important aspect of data ...
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How to Deploy AI with Confidence
Approaches to AI that Unlock Business Value Artificial intelligence (AI) is already transforming business, driving down costs, maximizing revenue, and enhancing customer experience. And many organizations are taking notice: The AI market size is expected to grow to $390.9 billion by 2025, and industries within the space show a similar trend—automotive AI, for example, is expected to grow by 35% year over year, and manufacturing ...
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What is Computer Vision?
Everything You Need to Know About Computer Vision With its recent surge in popularity, computer vision (CV) has become one of the fastest-growing fields of artificial intelligence (AI). The intended purpose of computer vision technology is to mimic the complexity of the human vision system, which includes eyes, receptors, and the visual cortex. This intricate system, when duplicated, gives machines ...
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Conversational AI: Making Smarter and more Scalable Models
Trends and Challenges in Conversational Artificial Intelligence Conversational artificial intelligence (AI) is already present in many families’ living rooms, cars, and online shopping experiences. Chatbots, voice assistants, smart speakers, interactive voice recognition systems: all of these are examples of conversational AI. It’s an area that’s attracting significant investment given the increased accessibility it offers through enhanced customer experiences. In the ...
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Where to Focus Automotive Artificial Intelligence Investments Part Two: Out-of-Car Experience
Autonomous Vehicles: A Critical Focus for AI In Part One, we talked about how the market for AI-powered automotive solutions is expected to increase over ten-fold by 2025, the areas of opportunity for advancing the in-cabin experience, and the importance of having unbiased training data for AI models. In Part Two, we’ll cover key components of the out-of-car experience, rounding out ...
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Should You Build or Buy a Data Annotation Tool?
Key Considerations for Developing a Data Annotation Solution for Your AI Models You want to use artificial intelligence (AI) within your business, but how do you make sure you choose the best strategy moving forward? First, you’ve likely determined a business problem, an AI-based solution, and the use cases of that solution. But the next step is a little more ...
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How Off-the-Shelf Training Datasets Can Save Your ML Teams Time and Money
New Off-the-Shelf Datasets from Appen Creating a high-quality dataset with the right degree of accuracy for training machine learning (ML) algorithms can be a difficult uplift for getting AI and ML projects off the ground. Not every company has a specialized team of ML PhDs, data engineers, and human annotators at their disposal. This is largely due to the expense ...
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Where to Focus Automotive AI Investments: In-Cabin Experience
Automotive AI as an Instrument of Change and Profitability Never before has it been more critical for automotive companies to invest in artificial intelligence (AI) solutions. Tractica forecasts that the market for automotive AI hardware, software, and services will reach $26.5 billion by 2025, up from $1.2 billion in 2017. The potential for change is tremendous, with shifts from traditional to disruptive ...
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What is Natural Language Processing?
A Brief Introduction to NLP with Phoebe Liu Have you ever interacted with a chatbot? Or requested something from a virtual assistant like Siri, Alexa, or your car’s infotainment system? What about translating something online? Most of us have interacted with these types of artificial intelligence (AI) before, and never stopped to contemplate the ease with which we could communicate ...
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Train AI Summit 2020: Speakers and Sessions Announced
Registration Open for the Free 2020 Virtual Train AI Summit The annual Train AI Summit is just around the corner. It will continue to pair our experts with speakers from leading technology companies to share their experiences building and deploying AI. In this year’s virtual format, you’ll learn strategy and implementation tools available to you to help your organization deploy ...
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What Does Interoperability Mean for the Future of Machine Learning?
Interoperability, or the ability for two systems to communicate effectively, is a key factor in the future of machine learning. For banking, healthcare, and other everyday industries, we’ve come to expect that the platforms we use to exchange information can communicate seamlessly whenever we need them to. Because we all have hundreds of thousands of data points associated with our ...
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What is Text Annotation in Machine Learning?
Everything You Need to Know About Text Annotation with Yao Xu Every day, we interact with different media (such as text, audio, images, and video), relying on our brain to process what media we are seeing and make meaning out of it to influence what we do. One of the most common types of media is text, which makes up ...
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Is Your Organization AI-Ready?
New AI Readiness Assessment Tool Now Available Many companies overestimate whether they are AI-ready. In the 2020 CIO Survey, Gartner stated that only 19% of CIOs claimed their AI projects to be in production. Meaning that when it comes to deploying AI initiatives all the way to production, a whopping 80% don’t make it. At Appen, we’ve seen our customers ...
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How to Get Started with AIOps
What is AIOps, and Why is it the Future for IT Teams? As executives across industries evaluate the variety of ways that artificial intelligence (AI) can transform their businesses, one area garnering an increasing amount of attention is the evolution of IT systems to meet the demands of modern businesses, as AI migrates from the fringes to the center of ...
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What is Data Labeling?
Everything You Need to Know About Data Labeling – Featuring Meeta Dash Artificial intelligence (AI) is only as good as the data it is trained with. With the quality and quantity of training data directly determining the success of an AI algorithm, it’s no surprise that, on average, 80% of the time spent on an AI project is wrangling training data, ...
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Common Sense AI: Making Deep Learning Technologies More Human
Whether through devices we use to enable convenience at home or in the way products we use all the time are manufactured, AI's impact is everywhere, driving innovation in just about every aspect of our lives. But there are missing pieces to this puzzle that still cause frustration for end-users and present significant challenges for researchers trying to improve how AI technology performs.
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AI in E-commerce
AI in E-commerce and the New Era of Personalization As society chases convenience and turns increasingly to online shopping over the traditional brick and mortar retail model, e-commerce took center stage, evolving how customers shop. The idea of a personalized shopping experience for each customer has been around for a long time, but a new era of personalization is underway. ...
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State of AI 2020: Report Now Available
What You Need to Know About the Sixth Annual Industry Report We introduced the State of AI and Machine Learning Report over six years ago when AI and machine learning adoption was still in its infancy. Since then, the industry has grown significantly, with budgets, executive visibility, and ownership all increasing year-over-year. Despite rapid growth, there is more room for ...