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Blog
Natural Language Processing – Connecting The World through Language With AI
As 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, start ...
Webinars
AI Trends of 2022: The State of AI Revealed
Change is constant in the AI industry; new technologies and methods are being created every month. To keep up with the change, companies must look to the newest trends, and adopt them into their own AI growth plans. Sitting back and watching events unfold for others isn’t an option in the world of artificial intelligence and machine learning. Watch On-Demand AI ...
Whitepapers
The 2021 State of AI and Machine Learning Report
Since 2016, the State of AI and Machine Learning Report has given insight into the adoption, implementation and scale of AI across industries. This large-organization study of senior business leaders and technologists details where organizations are within their AI journey — from the types of data they leverage to the tools they use and budgets they have. This year’s report ...
Whitepapers
The Ultimate Guide to AI Training Data Platforms
Everything you need to know to find the right training data platform to suit your machine learning needs Effective machine learning projects begin and end with quality training data and finding the right platform to support your AI model needs is the first step on your path to success. If you’re looking to launch an AI algorithm or machine learning ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
INDUSTRIES
Content Relevance: All You Need To Know About Serving Relevant Content To Your Customers
Many companies make the mistake when serving content to their customers and potential customers of not tailoring enough and serving too generic pieces that may not be relevant for everyone in their target. When it comes to content relevance, people want to see helpful information and solutions to their problems, or to be entertained and engaged. Serving up relevant content ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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, ...
Webinars
State of AI 2021 – Making Machine Learning Work in The Real World
The State of AI 2021 report is showing clear signs that companies are going all-in on AI. In this time of transition during the pandemic, we set out to explore why companies are considering AI to be core to survival. Amongst the findings, we saw that the maturing of AI projects, the desire for faster and greater ROI, and the ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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, ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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. ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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) ...
Blog
Exploring the World of LiDAR: What is it and How Does it Work?
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 the sensor and target object, such ...
Blog
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; ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Data Sheets
Appen’s Computer Vision Expertise
At Appen, we provide high-quality annotated training data to power the world’s most innovative machine learning and business solutions. We can support you from point cloud, image, and video annotation to pre-labeling and pixel-level semantic segmentation (PLSS). We’re here to help through the various phases such as identifying and processing objects in images and videos, to providing you high-quality data ...
Data Sheets
Natural Language Processing & Speech Technology at Appen
At Appen, our natural language processing & speech technology expertise spans over 25 years, over which time we have acquired advanced resources and expertise on the best formula for successful NLP projects. From text, speech, and audio collection to annotation, transcription, classification, and evaluation, we give you the high-quality training data you need to deploy world-class models at scale. Whatever ...
Blog
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. ...
Blog
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 ...
Blog
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. ...
Blog
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 ...
eBooks
Responsible AI from Pilot to Production
Artificial Intelligence (AI) has the potential to add $13 trillion to our global economy by 2030, according to McKinsey. Those who have successfully deployed AI see high returns on investment and increased customer satisfaction through more personalized, efficient AI tools. With AI investment growing and teams rushing to find ways to bring it into the core of their business, the ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Blog
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 ...
Whitepapers
Driving ROI Through AI
In an effort to help executives working to drive ROI from AI, we worked together with ESI ThoughtLab and a group of other AI leaders – including Cognizant, Cortex, Dataiku, DataRobot, Deloitte, and Publicis Sapient – to produce this report based on a survey of 1,200 organizations. This benchmarking study spans across a wide section of industries and world markets ...
Blog
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 ...
Blog
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 ...
Blog
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, ...
Blog
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.
Blog
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 ...
Blog
The Role of Quality Assurance in Artificial Intelligence
What You Need to Know About Quality Assurance for Your AI Models Launching an artificial intelligence (AI) model that’s accurate, reliable, and unbiased is undeniably a challenge. Organizations that manage to achieve success in AI initiatives are likely aware that the quality assurance (QA) process is very different with AI than traditional QA processes. Quality assurance plays a critical role ...
Blog
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 ...
Webinars
Embracing Responsible AI from Pilot to Production
Featuring: Lukas Biewald, Founder & CEO – Weights & Biases Sean Welch, Host and Producer – Data Science Central On average, 80% of AI projects fail to make it to production. But it IS possible to successfully launch AI, at scale, that is built responsibly and works for everyone. How you scale from pilot to production is critical to ensuring ...
Blog
How Artificial Intelligence is Reshaping Financial Services
Identifying AI Use Cases in FinServ in an Experience-First World Artificial Intelligence (AI) continues to gain traction as a significant business driver for large organizations across major industries. The traditional financial services industry was known to be slower in adopting new technologies, with some organizations using software running on COBOL or Fortran, which was invented in the 50s and 60s. ...
Blog
AI in Banking Operations
At Appen, we provide high-quality training data for machine learning and artificial intelligence. Follow us to stay up to date on industry trends. In this edition of our roundup, news on: applications of AI and machine learning in banking. Check back for regular news roundups and subscribe to our YouTube channel for video updates. https://youtu.be/5e-euX3s9VI Machine Learning in Banking: How ...
eBooks
AI Solutions for Financial Services
Key Steps to Building Customer-Centric AI According to Cambridge Centre for Alternative Finance, by 2022, nearly 64% of financial service companies expect to be “mass adopters” of AI — using it for revenue generation, process automation, risk management, customer service, and client acquisition — compared with just 16% currently. Yet success isn’t guaranteed. In fact, industry analysts find that the ...
Blog
Appen Offers Fully Integrated Figure Eight Solution
Deploy World-Class AI Confidently With High-Quality Training Data We’re thrilled to announce that the refreshed Appen website is live. With this refresh, we have also phased the www.figure-eight.com website out, and have successfully transitioned all former Figure Eight assets – the platform, developer portal, Success Center, and social media accounts. Redirects are in place for all links that have changed, and our team has been working with all our customers, users, partners, internal users, and the crowd to ensure a seamless transition to ...
Case Studies
FlamingoAI Deploys a Fully Automated Virtual Assistant From Day One
The Company Low online sales conversion rates. Inefficient customer service. These are the problems FlamingoAI is solving with its game-changing technology. With our training data powering its virtual-assistant platforms, the machine learning company now creates better online experiences for its financial and insurance-industry clients—and their customers. “With our platform, consumers get to have these conversations in natural language.” –Dr. Jack ...
eBooks
The Essential Guide to Training Data for AI and ML
Why Your AI Model is Only as Good as Its Training Data There’s a saying of garbage in, garbage out when it comes to artificial intelligence and machine learning. It’s common knowledge that every machine learning solution needs a good algorithm powering it, but what gets far less press is what actually goes into these algorithms: the training data itself. ...
eBooks
How to Create an AI Center of Excellence for Enterprise
Learn why creating an AI Center of Excellence will facilitate increased returns on AI investments. It will likely take time and cycles, tons of training data, algorithms, use cases, and several stakeholders involved in order to uncover its value. Yet it will be worth it as you build momentum for your team and business. Building an AI Center of Excellence ...
eBooks
AIOps for Business Leaders
Over a petabyte of data gets consumed by many companies, but repurposing that high-quality training data for machine learning and artificial intelligence initiatives can be a heavy uplift. This high-quality training data is critical for moving AI and ML algorithms from experiment, all the way to core business. Business leaders are turning to AIOps and professional services to guide the ...
Blog
Top 6 Trends for AI Initiatives Going into 2020
2020 Predictions in Artificial Intelligence to Consider When Operationalizing AI Developments With 2019 hardly fading in the rear-view mirror, it’s a good time to take a step back and see what’s in store for the next 12 months. For those managing and implementing AI and ML projects and deployments, it’s been a rapidly evolving ecosystem, and 2020 will be no ...
Blog
AI at Finovate Summit: Beyond the Hype
Traditionally, FinTech companies have been early adopters of new technologies enabling them to maintain their differentiation. Thanks to this, AI and FinTech are a natural match – especially as AI edges into the mainstream of enterprise software. At Appen, we are always looking for product-market fit when it comes to machine learning and data annotation solutions. To find out whether ...
Blog
The Latest Innovations in Artificial Intelligence
What are some of the most recent developments in AI? With so many emerging applications for artificial intelligence making a splash across a wide range of industries, it can be difficult to keep up. This post will touch on some cool advances made in 2019 and look at what’s on the horizon. AI takes a deep dive Robotics is a ...
Blog
Artificial Intelligence and Machine Learning Industry News: AI Trends Transforming the Way We Do Business
Organizations should have a reliable source of clean data to extract from and work with.
Blog
Creating Chatbots and Virtual Assistants That Really Work
Chatbots and their more sophisticated counterparts, virtual assistants, have emerged as a key tool to streamline customer service operations for organizations in a wide range of industries, and to help reduce costs.
Webinars
Driving Quality in Your AI Training Data
Learn how you can use best practices to ensure your data is annotated for optimal model performance. Date: On-Demand Time: 30 mins Speakers: Chris Lewis, Director of Quality and Innovation, Appen; Kirsten Gokay, Product Manager, Appen; Michael Lucero, Product Manager, Appen What do biased chatbots, a failed facial recognition system and self-driving car accidents have in common? They were all trained using poor ...
Blog
Appen Around the Globe: Fall 2019 Conference Rundown
Appen’s team of machine learning experts is excited to connect with you this fall. We’ll be exhibiting at industry conferences all over the world in the next few months and would love the opportunity to demonstrate how our high-quality training data can take your organization’s machine learning programs to the next level. Click here to schedule a meeting with the ...
Blog
Cost-Effective Crowdsourcing Strategies for Dialogue Systems
In a recent paper entitled Optimizing the Design and Cost for Crowdsourced Conversational Utterances, Appen data scientist Phoebe Liu and her team worked to identify cost-effective crowdsourcing strategies for training dialogue systems such as chatbots. Because more industries are adopting chatbot technology for customer service and other key functions, a need has emerged for training these systems as quickly and ...
Blog
How to Solve Common Data Challenges in Conversational Design
When planning the development of a chatbot or virtual assistant, it’s important to begin the conversational design process with a clear data strategy in place. Conversational design requires more than just an understanding of the fundamentals of voice user interface design — you also need to understand how to solve some of the key challenges in data preparation. Working with the ...
Blog
Appen on the Road: Events & Trade Shows this Summer
Appen is gearing up for some of the world’s leading industry events this summer. Our team will be exhibiting at conferences and trade shows around the globe, showing organizations how our services and solutions help develop high-quality training data for machine learning. Planning to attend one of these events? Contact us to set up a meeting with one of our ...
Blog
5 Reasons to Outsource Your Data Annotation Projects
For many organizations, the temptation to annotate data for machine learning (ML) projects in-house is hard to deny. These companies typically feel that using internal resources will help them save time and money by tapping employees who are already on their payroll. Additionally, if their project is highly confidential or of a sensitive nature, they might feel that using internal ...
Blog
Appen Becomes Leading Language Service Provider; Maintains Leading Position in APAC
Appen is excited to announce our official ranking as one of the largest language service providers (LSPs) in the global translation and interpreting industry. Issued May 2019 by independent market research firm Common Sense Advisory (CSA Research), “The Fastest-Growing LSPs: 2019” ranked Appen as a top-grossing LSP in the US$46.52 billion global market for outsourced language services and technology. Appen’s ...
Webinars
How to Secure Your Data for AI
Date: On-Demand Time: 30 minutes Presenters: Jesse Washburn, Data Protection Officer (Appen) Meeta Dash, Director of Product Management (Appen) Hilary Shirey, Senior Project Manager (Appen) Alanna Olicker, Program Manager (Appen) With any data annotation project, data security is imperative. What are the security requirements that need to be considered? For many companies, confidence that the data is secure, particularly when it includes ...