Large Language Models (LLMs) recently became a bit of a hype in discussions related to AI. While there is a clear connection, they should still be considered separately.
Large Language Models recently gained significant attention in relation to AI, becoming part of the same hype. It is important to consider them as distinct components within the broader AI landscape.
While Large Language Models (LLMs) sounds like a recent development, the underlying concept is around for quite some time. Before 2017, LLMs were part of the broader development of neural networks.
In August 2024, LLMs and AI have once again become more closely intertwined, with the largest and most advanced LLMs being based on Artificial Neural Networks (ANNs).
This demonstrates the interdependence of LLMs and AI. One of the most well-known examples is OpenAI’s GPT model, which powers ChatGPT and Microsoft’s Copilot.
From an engineering perspective, it is crucial to understand the broader capabilities of Large Language Models (LLMs).
In the field of CyberSecurity, LLMs are increasingly used for reverse engineering. Rather than employing LLMs to build new concepts, they are utilized to gain deeper insights into existing data.
For example, LLMs can be used to identify hidden information within data distributed across the internet. Which can often be harmful or used with malicious intent. By leveraging continuously evolving LLMs, the detection and recognition of such hidden threats become more efficient and accurate.
In today’s world, Large Language Models are becoming increasingly prevalent, and their influence is far from reaching its peak.
2. Discuss how Large Language Models are continually evolving and the impact this evolution has on the proposed solution.
LLMs are still in their early stages of development, which naturally drives significant interest in learning more about them. However, the abundance of information available online can easily lead to confusion. It’s crucial to focus on clearly communicating the specific value and benefits that LLMs bring to your solution to avoid any misunderstandings.
1. Avoid overhyping Large Language Models in your offering, as potential customers may not fully understand the context or implications.
