Article by Laszlo Varga and Yulia Akhulkova. In November 2022, OpenAI released ChatGPT, gaining 100 million users within two months and setting a record for fastest-growing user base. Arguably, never before have we seen such an event get so much hype in the history of technology. Language technology suddenly got propelled into the center of the wider public’s attention in a way unheard of since Google Translate entered the scene. ChatGPT has become part of the public discourse, talked about at business meetings and at the dinner table, discussed both by mainstream news outlets and on social media. Some relish the debate, others are sick of it by now, and Nimdzi is listening to both sides — and all sides in between — weighing perspectives and offering the analyst’s take on just how this technology is transforming both our professional and personal lives. The first wave of LLM adoption, and what’s coming next Nimdzi has been tracking the transformation of large language models (LLMs) into real-life use cases and applications within the language industry, and nearly half a year into the age of ChatGPT, we’re bringing you the key findings from our ongoing research. These observations are based on fieldwork conducted by Nimdzi over the past two months and include over two dozen interviews, discussions, and demo sessions with a wide range of industry players ranging from language service and technology providers to enterprise language service buyers. While this is an open-ended research project, some clear themes have already emerged that we wanted to share before the next tech disruption knocks on the door. The following are some of the research questions we’ve been looking to find answers to: How is the “ChatGPT disruption” different from previous technological disruptions the language industry has quite well adapted to, especially the advent of neural machine translation (NMT)? Does ChatGPT lead to fewer work opportunities for language professionals? Or, inversely, does it expand the horizons of work for language talent and service providers, perhaps even creating vast new opportunities not normally within the purview of language services? Is the tool driving cost-efficiencies, increasing revenue, or opening new revenue streams? How does it compare with the tried-and-tested language tech stack in terms of implementation and customization? In what ways do LLMs change the industry’s customer-vendor relationships? What are the key benefits, shortcomings, constraints, and best practices for the use of ChatGPT-like models right now, and what is the outlook? Five months, five key insights (plus one extra) Are you as excited about LLMs as we are? Contact us at [email protected] to participate in our research.