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The evolution of AI: understanding the role of NLP technologies

Artificial intelligence (AI) has long been a controversial topic, with some people fearing its potential consequences. This has been exacerbated by popular culture, with movies such as "The Terminator" and "2001: A Space Odyssey" depicting AI systems becoming self-aware and turning against humans. Similarly, "The Matrix" portrayed a dystopian future where AI systems had enslaved humanity.

Fast forward to 2023- AI has become a normal part of our everyday life, whether we realise it or not. From virtual assistants like Siri and Alexa to personalized movie and product recommendations, AI-powered technologies have revolutionized the way we interact with technology. AI also plays a critical role in industries such as healthcare, finance, and transportation, with algorithms helping to analyse data, identify patterns, and make predictions that lead to better decision-making.

As with any industry, the AI industry is very much prone to evolution. In fact, this is especially relevant for the AI industry, given that it engages user habits to learn and redefine its understanding. This has led to the introduction of unforeseen technologies.

One of the most studied and developed AI modelling techniques, Natural Language Processing (NLP), has been particularly placed under focus recently with the emergence of technologies such as Open AI’s ChatGPT, Google’s Bard AI and Microsoft’s Bing AI.

ChatGPT in particular, was one of the first technologies of this kind to garner significant fame. Within its first year of release, the GPT-3 model had more than 10,000 registered developers and over 300 applications built on its API. In addition, Microsoft acquired OpenAI's exclusive license to the GPT-3 technology in 2020, further solidifying its position as a leading language model in the industry.

ChatGPT works as an advanced artificial intelligence technology designed to understand and process human language. Built on the GPT-3.5 architecture, it uses natural language processing (NLP) to comprehend and generate responses that simulate human conversation. ChatGPT is classified as a large language model, which means it has been trained on vast amounts of data and can generate high-quality text that is both coherent and relevant to the input provided.

While concerns have been raised about the potential impact of natural language processing (NLP) technologies, there are several reasons why we should not fear their emergence. Firstly, NLP has already enabled a wide range of useful applications that have the potential to improve efficiency, convenience, and accessibility. Furthermore, the development and deployment of NLP technologies is subject to ethical considerations and regulations that aim to ensure their responsible use.

NLP technologies are not designed to replace humans, but rather to complement and enhance human capabilities. While some jobs may be impacted by automation, new jobs are likely to emerge that require human skills that are not easily replicated by machines.

Ultimately, the impact of NLP technologies depends on how they are developed and used. There are always likely to be risks, but by taking a proactive approach to their development and deployment, we can ensure that they are used to benefit society and advance human progress.

By Jaspreet Mann

 

REFERENCES

  • Hirschberg, Julia, and Christopher D. Manning. “Advances in Natural Language Processing.” Science, vol. 349, no. 6245, July 2015, pp. 261–66. DOI.org (Crossref), https://doi.org/10.1126/science.aaa8685.

  • What Is Natural Language Processing? | IBM. https://www.ibm.com/topics/natural-language-processing. Accessed 1 May 2023.

  • Biswas, Som S. “Role of Chat GPT in Public Health.” Annals of Biomedical Engineering, vol. 51, no. 5, May 2023, pp. 868–69. Springer Link, https://doi.org/10.1007/s10439-023-03172-7.

  • Davenport, T.H. (2018). The AI Advantage: How to Put the Artificial Intelligence Revolution to Work. MIT Press.

  • Bird, S., Klein, E., & Loper, E. (2009). Natural Language Processing with Python. O'Reilly Media.

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