AI for Large Language Models

Note: This is another in a series of articles from PKA tackling tech topics

AI for large language models help provide more precise results than those using traditional methods

Although artificial intelligence (AI) has been with us both conceptually and in practice for quite a while, 2023 seems to be the year where AI for the masses has taken root. An area of AI that is in ongoing development is AI for large language models (AI/LLM). AI/LLM is a field of computer science that uses AI techniques to train and deploy LLMs. What’s a large language model? It is a type of artificial neural network used to generate text, translate languages, write different kinds of creative content, and answer your queries in a clear and informative manner. In short, it’s a type of AI that can mimic human behavior.

AI/LLM is growing rapidly as an area of study. AI/LLM encompasses a number of different AI techniques that are used to train and deploy LLMs. Three of the most common AI techniques for LLMs are:

  • Deep learning: Deep learning is a type of machine learning that uses artificial neural networks to learn from data. Deep learning is often used to train LLMs because it can learn complex patterns from large amounts of data.
  • Natural language processing: Natural language processing (NLP) deals with the interaction between computers and human (natural) languages. NLP helps LLMs understand and generate human language.
  • Transfer learning: Transfer learning is a technique that uses a model that has been trained on one task to train a model on a different task. Transfer learning is often used to train LLMs because it can help them to learn from a large amount of data without having to train the model from scratch.

What are the Benefits of AI/LLM?

AI in general has been the source of both excitement in the marketplace and trepidation. Current HPE CEO Antonio Neri is on the record with a charge to practitioners of AI to be responsible in utilizing this incredible technology.

AI/LLM promises several benefits for users and the market in general. These benefits include:

  • Increased accuracy: LLMs that are trained using AI techniques can be more accurate than those trained using traditional methods. This is because AI techniques can learn more complex patterns from data. It’s the old adage of “garbage in, garbage out.” AI/LLM reduces the “garbage” in and produces a a more accurate result out.
  • Improved performance: LLMs that are trained using AI techniques can perform better than LLMs that are trained using traditional methods. This is because AI techniques can learn to optimize their performance for specific tasks.
  • Reduced costs: LLMs that are trained using AI techniques can be less expensive to train than those that are trained using traditional methods. Note that AI techniques that are used to train LLMs on large datasets could prove too costly to train using traditional methods.

What’s next for AI/LLM?

AI/LLM is a rapidly growing field with several potential benefits. As AI techniques continue to improve, LLMs will become even more powerful, versatile, and valuable. This will lead to a number of new and innovative applications for LLMs, many of which are already in place using AI with traditional methods. These include:

  • Generative text: LLMs can generate text, such as news articles, blog posts, and even creative fiction.
  • Language translation: LLMs can translate languages, such as English to Hindi or Urdu to Portuguese.
  • More precise answers to queries: LLMs answer questions in an informative way, even if the original intent or wording isn’t quite fully developed.

AI/LLM will continue to evolve, develop, improve, and change our world. As AI techniques keep pace, LLMs will become even more powerful, versatile, and begin to become indispensable. This will likely lead to several new and innovative applications for LLMs that will no doubt take the changed world and change it even more.

Curious how AI or AI/LLM can help your business? We’re listening. Contact us today to further the conversation.