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The explosion of ChatGPT into the mainstream since its launch on November 30, 2022, has generated unprecedented attention and commentary. After spending a few days (and nights) having conversations with ChatGPT, these are the only questions that I think matter:
Want to learn the answers to these questions and what I foresee for this new localization tool? Read on. For more insight, read the whitepaper below.
There are things that you can’t rely on ChatGPT for:
Having gotten through what ChatGPT isn’t or can’t do, let’s look at what it can do as a text interpreter and generator. ChatGPT can:
We’ve established that you can’t rely on ChatGPT to say true things or to know what’s correct. (This means content creators would have to check whether it’s talking nonsense.) However, once we have a text containing meaning that we’re happy with, ChatGPT can manipulate or transform its form and content -- while retaining encoded meaning. This is an opportunity for localization providers because we don’t have to generate meaningful content from scratch. Let’s take a closer look at the localization activity landscape and how ChatGPT could affect what we’re doing today. This generative AI:
I’ve developed the beginning of an understanding of what type of prompting ChatGPT requires. This special technology only takes natural language as input. To use this technology in production, we’ll need to develop expertise for effective prompting. Specific transformations of content will likely require successions of prompts that will each perform different tasks: cleanup, pre-and post-processing, etc. Learning to use natural language prompts as part of our automation pipelines, in a way that is both contextually relevant and sufficiently predictable in the output, will be an interesting journey.
We now definitively know we can’t ignore this new generative AI. It’s likely to disrupt our industry. So, we must lead and drive that push to language automation, lest we get left behind. ChatGPT can transform and annotate text on par with the average human editor and likely perform these tasks more efficiently. It can perform tasks relying on a diversity of skills virtually no individual human possesses, and it can generalize its knowledge to new situations.
Most importantly, it shows potential for solving some lingering localization automation problems. Of course, it’s one thing to have a conversation with it using toy examples. It’s another thing to imagine using it at scale to perform these actions. Moving forward, we must:
One of the things that I found most striking was how ChatGPT got complex number operations almost right, but still wrong. It doesn’t cheat. It really learns everything from the language it trains on. The fact that it finds almost the correct result of an operation beyond a certain order of magnitude (and the correct result for smaller numbers) tells us that a language corpus of a sufficient scale contains statistically significant knowledge about the real world. But, it also shows that dedicated formal systems (such as mathematics) are required to produce meaningful, reliable, and accurate information about the real world.
ChatGPT offers a sobering reminder that a self-referential, self-consistent system cannot in and of itself carry the truth of the world, which exists independently. This echoes Gödel’s incompleteness theorem. As conscious beings, we can’t untether our cognition from formal and material systems grounding our understanding of the world in a reality that imposes itself on us and that we cannot define away through language alone.
Have your own translation or localization project? Need to ensure it gets done accurately, quickly, and under budget? We’ll use innovative generative AI like ChatGPT to help. Contact us today to find out more about Lionbridge’s translation and localization services.