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

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.

DataForce, TransPerfect’s AI data solutions division, today announced its platform support for Digital Imaging and Communication in Medicine (DICOM), which simplifies the process of identifying pathologies or diseases. The new tool processes and annotates medical data provided by pharmaceutical and biotechnology organizations that utilize artificial intelligence.

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.

NLP use cases are shifting the way everyday consumers behave in society at a startling pace. Consider the prolific NLP models like BERT and GPT-3 which have taken the business world by storm. Notice the dazzling displays of machine learning such as the AI generated images from text snippets that have so many demonstrably amazed everyday people, making their way into pop culture. NLP is so commonplace that we no longer even notice it as we craft a sentence in an email that finishes itself for us. This panel will gather NLP technical leaders to share the most exciting use cases and strategies for effective AI today.

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.

As OEMs buy in ready-made solutions for in-car infotainment systems, it is important to emphasize how these solutions can benefit from customization based on additional speech data, annotations of real data or user testing. Making speech recordings for the specific car functions, transcribing user utterances, or doing end-to-end user testing of the interface can greatly improve the usability and user experience. In this presentation we will describe a number of relevant data services as well as present some case studies to support our message.