Verity Hartley , Marketing Specialist, LanguageWire || Reading Time: 3 minutes
With the meteoric rise of generative AI and Large Language Models (LLM) such as ChatGPT into the cultural zeitgeist this year our customers have had many questions about how these new technological developments will affect the future of translation services.
LanguageWire has long been an early adopter of technological advancements in the field and a strong advocate for the benefits of tools such as Machine Translation and automation.
To address our customer's questions head-on, we hosted a Customer Advisory Board (CAB) to create awareness around LLMs and their impact on the language industry, while also collecting feedback and inspiring about future ways of working with LLMs.
With representatives attending from 28 companies ranging in different AI experiences, the event proved to be a great success and fostered lots of conversations, and provided a great deal of insight into everyone's hopes and concerns for the future of the technology.
The CAB consisted of two hosted sessions led by our Chief Product & Technology Officer Roeland Hofkens that explored what LLMs are as well as the future of the technology within the LanguageWire ecosystem and how it will be used to improve our service offerings. An expert panel debate deep-dived into the current state of LLMs and how they are influencing the state of machine translation in the industry.
In the hosted sessions we learnt that Large Language Models are a recent development in the realm of machine learning that leverage the power of generative AI to make interactions between person and machine appear more human. LLMs can be trained on large text-based sources which they will be able to analyse but more importantly, used to generate brand new content via predictive technology.
Many of our customers were keen to gain inspiration about the new technology and ways to use it to improve and streamline their business practices. Overall, there was a considerable amount of curiosity about how LLMs could be used to enhance LanguageWire's services and add a greater level of automation and autonomy for the customer.
By integrating this newer technology users will be able to interact with our systems in a more natural language using prompts that will train the LLM to generate content in a more personalised fashion. LLMs will be able to use custom data sources such a termbases to create even more accurate content using terminology individual to a user’s business.
Our customers were given several opportunities to raise their insights and concerns in breakout sessions that discussed a large range of topics. The greatest concern raised was about data security and privacy, a topic that is always at the forefront of our minds here at LanguageWire.
LLMs like ChatGPT offer little in ways of data protection and do not yet meet some of the legal requirements set by the European Union to ensure data privacy. Currently, when working within LanguageWire's platform, your data is compliant with numerous industry-level standards. Any future developments in using an LLM would need to continue to work within these parameters.
Additionally, a challenge faced by all LLMs currently is the danger of hallucinations. A hallucination is an incorrect answer provided by an LLM and presented in a way that appears correct. Hallucinations can be overcome by pre and post training of the model and ensuring that the data provided is as clean as possible.
Our CPTO Roeland Hofkens assured our customers that security will always remain our number one priority as we integrate any future technologies into our systems.
LanguageWire will continue to enhance and increase its tech stack with the new developments from LLMS. Additionally with fine-tuning at both the start and end of the process AI should be able to provide even greater returns in terms of data personalisation, workflow speeds, and data quality.
Stay tuned to our blog for further updates and articles on generative AI and the impact that LLMs will have on the language service industries in the future.
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