From drug discovery to personalized medicine, AI systems are broadly transforming how we approach health and disease. The clinical development life cycle generates enormous volumes of data, and its potential is fully realized through the strategic application of AI tools, such as data annotation for medical imaging and adverse event detection. However, the integration of AI into such a sensitive and critical field comes with an ethical imperative: ensuring the AI systems we deploy are free from bias.

As AI models like ChatGPT, other types of LLMs, and generative AI applications have integrated into our frameworks, the spotlight on ethical AI and need for standards has intensified. The adaptability of AI in human interactions requires the establishment of regulations and guidelines to ensure responsible usage

GlobalLink NEXT 2023 featured an insightful panel on the evolving landscape of generative AI. Our brilliant and entertaining speakers from Etsy, JP Morgan & Chase, TransPerfect and DataForce delved into the transformative potential of AI creativity, sparking engaging discussions with the audience. The event offered a unique exploration into the future of innovation.

From advanced driver assistance systems to autonomous navigation capabilities, AI is reshaping the automotive industry. However, automotive manufacturers and suppliers must act to ensure consistent AI functionality across diverse markets and countries. This includes issues such as data localization, language adaptability, cultural sensitivity, real-world testing, collaboration with local partners, and ethical frameworks.

In today’s fast-paced financial industry, data-driven decision-making has become increasingly important. Financial institutions are constantly looking for ways to improve their operations, better serve their customers, and stay ahead of the competition. To achieve these goals, they are turning to data to gain insights into customer behavior, market trends, and other factors that can impact their bottom line.

The world of artificial intelligence (AI) and machine learning (ML) has evolved at an unprecedented pace over the last few years. With the advent of new technologies, algorithms, and tools, businesses across industries are looking to automate tasks, make data-driven decisions, and improve efficiency.

In today's fast-paced digital era, businesses face numerous challenges when it comes to providing exceptional customer support and must stay ahead of the curve to meet the diverse needs of their global clientele. Among the countless innovations revolutionizing customer support, multilingual chatbots stand out as an indispensable asset.

In our rapidly evolving technological landscape, the introduction of Open AI’s ChatGPT, society's uptake of AI, and conversational AI (CAI) have emerged as major topics of discussion. Various AI-powered models have seamlessly integrated into our daily routines, from providing customer support to addressing our most pressing inquiries.

It’s a rookie writer’s misstep my wife and I still joke about 23 years later. Back then, we were cub reporters at the Sandusky Register newspaper in Ohio, assigned to cover the weekend Milan Melon Festival. I filed my story on Saturday, and she filed hers Sunday.

Customers are the lifeblood of any business. In today's competitive and accessible landscape, delivering exceptional customer experience is more critical than ever. A positive experience can foster loyalty and advocacy, and ultimately, drive growth. Incorporating data annotation into AI-powered processes can do just that.

Call centers play a critical role in delivering high-quality customer service, generating leads, and providing valuable insights into customer behavior and preferences. However, working through call center data/call center data preparation can be daunting, especially when dealing with large volumes of data from multiple channels, such as inbound customer calls, chat, email, and social media.