2023 could be the year of great linguistic models

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The launch of OpenAI's ChatGPT has taken the world by storm for advanced artificial intelligence (AI) capabilities. How will it transform industries? What does this mean for Google Search? And will it automate entire professions? These are just a small sample of the questions many have about the possibilities. But while there are many unknowns about the impact of this technology, one thing is almost certain: 2023 will be the year of the Great Language Models (LLMs).

Many apps for LLMs, like writing aids and summary tools, are already here and starting to change the nature of work as we know it – and will become much more mainstream very soon. But what form this integration will take and how it will be implemented remains an open question. Here's what next year might bring.

First of all, because there is so much hype, chances are that LLMs will be extremely disappointing for some in 2023, as companies will try to market half-baked products as panaceas . LLMs are trained (in part) to give convincing answers, but those answers can be wrong and unsubstantiated. Inevitably, some people will try to rely on it, with potentially disastrous consequences, leading to the spread of misinformation.

That being said, those who are more thoughtful in their approach to LLMs have reason to be very optimistic. LLMs will further change the nature of work (even if the aforementioned disappointment tempers expectations). Writing assistants, like Jarvis, which uses AI to write marketing content quickly, will be the most obvious example of tools that easily extend their capabilities. Other document editors will likely follow suit, moving generative AI for language from the "early adopter" crowd to the "early majority" crowd.

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Perhaps even more interesting is the subtle influence these advances in AI are having on non-generative applications of LLMs. Text classification and Named Entity Recognition (NER) will improve significantly, allowing for a much wider range of applications.

Let's take for example the extraction of data from documents. With today's typical accuracy rates, applications are limited. You wouldn't want to rely entirely on AI to extract and calculate the total dollar value your business spends on SaaS. But with higher accuracy rates, you can trust that number more and more - starting out trusting it as an estimate, and eventually exceeding the level of trust you might have in another person. p> What's to come for LLMs

One of the biggest open questions about ChatGPT is whether it will lead to mass job cuts. The answer is no. But the base models will encourage challengers to adopt established business models and practices. For example, in the media world, small businesses will be able to produce high-quality content at a fraction of the cost (which Corridor Video has done with Stable Diffusion and the "Spider-Man: Into the Spiderverse