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 …

Person shopping on tablet

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. …

Appen Staff at Finovate

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 …

CVPR 2019: Progress and Challenges in the Field of Computer Vision

The annual Computer Vision & Pattern Recognition conference is packed with insightful presentations and top industry experts. With nearly 10,000 attendees and 1,200 papers, CVPR 2019 in Long Beach, CA was no exception. In this post, we’ll take a brief look at some notable presentations delivered at the conference for solving numerous computer vision and pattern recognition challenges. Data augmentation …

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 …

Conversational design

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 …

Outsourcing data annotation projects

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 …

Three of the Most Innovative Automotive AI Applications at AutoSens Detroit

Appen recently exhibited at AutoSens Detroit, where we shared our approach to data collection and annotation for in-car navigation, infotainment, and monitoring, as well as autonomous vehicle solutions. Here are some of the coolest innovations in automotive AI, as spotted by our team: Mercedes Benz’s Intelligent Interior Volker Entenmann, Senior Manager of UI Functions at Daimler AG, shared how Mercedes-Benz …

Engineers working in an office

How to Remove Bias in Training Data

Machine learning (ML) algorithms are generally only as good as the data they are trained on. Bias in ML training data can take many forms, but the end result is that it can cause an algorithm to miss the relevant relations between features and target outputs. Whether your organization is a small business, global enterprise, or governmental agency, it’s essential …

Bluetooth call controls on a car steering wheel

How a Top Automotive OEM Localizes Its In-Car Experience with Appen

The Situation With the proliferation of mobile devices, consumers expect to stay connected, no matter where they are — especially in their car. Voice recognition in cars, however, continues to be the leading complaint among new vehicle owners. Global automotive manufacturers recognize the demand for better connectivity but face added complexities associated with localizing in-car systems for multiple languages. Data …

Crowd of blurred people at a trade show

Solving ML Training Data Challenges at Google Cloud Next

Appen recently exhibited at Google Cloud Next in San Francisco, our first event with our new colleagues from Figure Eight. Joining over 30,000 developers, product managers, data scientists, and more, we spent three days networking, learning, and problem solving. The event covered diverse topics ranging from data analytics and DevOps to networking, security, and storage. But we on the Appen …

Machine Vision vs. Computer Vision

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 …

Illustration of AI

RE·WORK’s Q&A with Wilson Pang, CTO of Appen

This week, Appen is exhibiting at RE•WORK’s Deep Learning in Finance Summit in London. The summit helps business leaders, data scientists, and engineers discover advances in AI & machine learning tools and techniques from the world’s leading innovators across the financial sector. RE•WORK spoke with Appen CTO Wilson Pang to learn about his current work, the challenges of implementing AI, …

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 …

China-Flag

Recent AI Developments in China

China is now a leading global hub for AI development. Startups and major tech companies like Baidu, Alibaba, Tencent, and DiDi Chuxing are developing cutting edge products, solutions, and services using artificial intelligence. The AI market in China is massive. China’s AI Development Report 2018, a study from Tsinghua University, says, “The market value of China’s AI industry reached 23.7 …

Woman with shopping bags looking at smartphone

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 …

How top financial services companies transform their business with AI

In 2018, the financial services industry is using artificial intelligence (AI) and machine learning to drive greater speed and accuracy across business processes. Using AI and machine learning technology, financial services companies are reducing risk, managing fraud, optimizing investment strategies, improving operational efficiency, and delivering more personalized customer service, at scale. Why is the financial industry seeing so much benefit …

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 …

Artificial Intelligence and Machine Learning Adoption by Industry

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 …