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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 ...
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 ...
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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 ...
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 ...
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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, ...
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 ...
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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 ...
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
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
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 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
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
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 ...
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
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 ...
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 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
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 ...
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
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
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 ...
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
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 ...
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
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
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
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. ...
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
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 ...
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Crowd’s Collective Wisdom vs. Experts: Who Makes IBM Watson Smarter?
Understanding natural language is one of the great aspirations of artificial intelligence. While solving it could have exciting implications for society, it’s going to take an unprecedented volume of training data to make it happen. This is especially true in the interpretation of health data from a seemingly infinite array of sources — and a big reason why we’re so ...
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How Artificial Intelligence Will Reshape the Auto Industry in an Experience-First World
Consumer-Experience AI for Automotive Artificial intelligence’s impact continues to expand rapidly across all major industries, with companies around the globe investing heavily in AI technologies to advance their competitive edge. Future trends suggest that without adopting an AI strategy now, organizations are likely to fall far behind their competitors. When implemented correctly, AI and machine learning (ML) will deliver wide-sweeping ...
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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 ...
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How to Build a Successful Task for the Crowd
I built my first job on Mechanical Turk more than seven years ago. I immediately saw the power of the crowd, but the process was difficult enough that I started CrowdFlower, now Appen, to give people like me a better experience and more accurate results. Since then I’ve created thousands of jobs myself and looked at countless microtasks built by ...
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Artificial Intelligence and Machine Learning Industry News: AI in Patient Care and Operations, AI as a Preventive Tool, and How Major Hospitals are Already Using AI
Expect to see dramatic changes in both patient health outcomes and in the operational efficiency of hospitals.
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
Using AI to Transform the Banking Experience
At the FinovateSpring 2019 conference in San Francisco, AI was a hot topic. From financial institutions using AI to power everything from personalized customer experiences to underwriting, to fintech providers showcasing AI solutions, the technology was on everyone’s mind. In a panel titled “Which Artificial Intelligence Technologies Will Really Change Financial Services?”, we heard from experts who are harnessing this technology in ...
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What New Jobs Will AI Create?
The boom in deep learning technologies such as Artificial Intelligence (AI) and Machine Learning (ML) can cause varying degrees of excitement or anxiety — largely depending on how you earn your paycheck. Advances in this field are creating exciting opportunities for companies seeking to maximize efficiency and quality, while minimizing costs traditionally associated with a mostly-human workforce. In manufacturing, implementation ...
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Appen’s Top Five Blog Posts from 2018
2018 was an exciting year here at Appen. We expanded into nine offices worldwide, and our global crowd of skilled annotators has grown to over 1 million people, working in over 130 countries and 180 languages. Our readers subscribe to Appen’s blog to stay on top of machine learning use cases, industry news, and best practices for getting high-quality training ...
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Executive Insights from AI Summit NYC
At the 2018 AI Summit in New York City, we heard from a panel of executives representing multiple organizations across the AI ecosystem, including our own Mark Brayan, CEO of Appen. The panelists shared their perspectives on the usage of AI in different organizations, issues that need to be addressed, and what the future holds. Perspectives on AI Applications Clayton ...
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How AI Is Driving Innovation In eCommerce And Retail
Companies across a range of industries are adopting machine learning technologies — and as early adopters, eCommerce and retail companies have seen the biggest wins from investing in machine learning. By applying artificial intelligence to key business problems, eCommerce companies are using machine learning models to drive higher sales, predict demand, and personalize the shopping experience through more relevant search ...
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Machine Learning is Here to Stay
Welcome to the fourth industrial revolution—a world where artificial intelligence (AI) drives today’s technological disruption, blurring the lines between tangible and digital realities. Companies continue to shift toward AI and machine learning (ML) processes, and business leaders are quickly realizing the potential gains from investing in them. These gains include faster, smarter automation, predictive analytics, and new-and-improved ways to establish ...
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Artificial Intelligence and Machine Learning Industry News: London Metropolitan Police, MIT Drug Research, and AI Art at Auction
In this edition of our roundup, news on: London Metropolitan Police, MIT Drug Research, and AI Art at Auction.
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Insights From O’Reilly Media’s Artificial Intelligence 2018 Conference
Appen exhibited at the September 5–7 O’Reilly Media Artificial Intelligence 2018 conference in San Francisco to showcase its high-quality data services. The event hosts industry experts and features case studies about the future of artificial intelligence and machine learning. The Appen team attended a variety of sessions at The AI Conference, San Francisco including: Have we reached peak human? The ...
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Investing in AI: The Time is Now
According to industry research firm TechEmergence, Artificial Intelligence (AI) technology will have the single most radical, transformational impact on business and society. AI is driving the fourth industrial revolution or 4IR—the newest industrial era, which is characterized by emerging technological disruption and increasingly blurred lines between the physical and digital worlds. Organizations are rapidly exploring the business gains that can ...
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Machine Learning Adoption by Industry: A Q&A with Stephen Woodard
As artificial intelligence and machine learning become a greater part of the business landscape, it’s interesting to see how different vertical industries are putting it to use. How does healthcare compare to the technology sector? Do geography and location play a role? To answer some of these questions, I caught up with our own Stephen Woodard from our business development ...
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Where Retailers Should Invest in AI
Several weeks ago, we shared a detailed report from the McKinsey Global Institute that analyzes hundreds of use cases for artificial intelligence (AI), and provides a perspective on how firms across a variety of industries can most benefit from this exciting technology. One area featured in the report is AI in the retail industry. According to the research highlights, use ...
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Key Considerations; Getting Started With Machine Learning
When implementing any strategic initiative, it’s important for organizations to build a considered plan upfront taking in a number of variables. This principle certainly holds true in the fast emerging areas of artificial intelligence (AI) and machine learning (ML).
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AI Use Cases; Which Can Have the Most Impact on Your Business?
With all the hype around AI, how can organizations determine where best to apply the technology?
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Great Machine Learning Data: It’s Not About Quantity or Quality — It’s About Both
To build a successful solution, you need the right data – and a lot of it.
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Insights from AI NextCon 2018: How LinkedIn Uses AI to Optimize the User Experience
When it comes to building its AI platform, the LinkedIn team’s goal has been to make end-to-end machine learning easy, fast, robust and automatic.
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Here’s How Machine Learning Will Impact Healthcare
With $150 billion expected to be spent by the healthcare industry on AI deployment and tools over the next decade, machine learning in healthcare is on the rise. Healthcare innovators see the potential for machine learning use cases in healthcare to dramatically improve administrative functions, pharmaceutical research, clinical decision making, and patient monitoring. These enhancements will lead to more positive ...
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5 Machine Learning Use Cases that are Making a Difference in the Business World
Companies that are using machine learning are starting to reap the rewards and transform the way they do business. Machine learning is allowing businesses to optimize operations, deliver better customer experiences, enhance security and more. As enterprises race to stand out from the competition and do more with the same resources, machine learning is becoming an important investment. Here are ...
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Insights from AI Expo 2017: Deep Learning in the Enterprise
I recently attended a keynote session at the AI Expo 2017 called “The Application of Deep Learning within an Enterprise”, a panel featuring speakers across a variety of industries. The executives on the panel highlighted a wide variety of use cases for machine learning in their organizations, beyond what one would expect. For example, Vadim Kutsyy, Distinguished Architect, Data Science from ...
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How does machine learning work? An interview with Appen CEO
Appen CEO, Mark Brayan, shares his thoughts on artificial intelligence, machine learning and the high-quality data they both rely on.
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Insights from LocWorld China 2017 | Data is Key
Key takeaways from this year's LocWorld China, one of the leading conferences for translation, localization and global website management.
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Going Global: The Value of Local Market Research & Resources
Companies entering multiple markets can create better customer experiences using in-market resources for testing, data collection and more.
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Insights from AI World 2016 | Top Takeaways
While the concept of AI is not new, the technology is experiencing a rebirth in the form of machine learning and cognitive computing.
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Making AI work for your business
When it comes to the future of doing business, AI and machine learning are the hottest topics around. For all the discussion of AI’s promise, though, something is still lacking — straightforward information about how to make AI work for you. If you approach your solution in the wrong way your results won’t make sense, but if you go about ...
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Crowdsourced Data: When to Use Curated Crowds vs. Crowdsourcing
“When should I use crowdsourcing and when should I use a managed crowd?” Find out which is best for you human annotated data needs.
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7 Advances That Are Pushing the Boundaries of Computer Vision
Before we can think critically about computer vision, we need to take a moment to appreciate our own human vision system. Just think what we have been able to do in our lives as humans with eyeballs! We have analyzed, sorted, made sense of arbitrary objects in arbitrary situations, effortlessly tracked the movement of things, recalled perfect 3D models of ...