In today’s rapidly evolving technology landscape, leveraging advanced AI models like Generative Pre-trained Transformers (GPT) has become imperative for businesses aiming to stay competitive. With multiple flavors of GPTs available, deciding which one best suits your needs can be a daunting and risky task for any enterprise leader. Understanding the factors that influence this decision is crucial for business leaders seeking to harness the power of AI, especially Generative AI.
To help us, lets first understand the difference between GenAI, GPT and LLMs. GenAI has become a widely recognized term or acronym in the field of artificial intelligence for natural language processing.
| Term | Definition |
|---|---|
| GenAI | Based on LLMs (Large Language Models) which are a class of artificial intelligence models designed to understand and generate human-like text. |
| GPT | A specific type of large language model. |
| LLM | A broader category of models that includes GPT and others. |
| Common understanding of GPTs | Specific LLMs that have been customized and/or trained on different data to address specific business challenges. |
Some of the most advanced and widely adopted GPTs are:
| AI Models |
|---|
| GPT-4 (OpenAI) |
| BERT |
| Gemeni (Google) |
| CoPilot (Microsoft) |
| Claude 3 (Anthropic) |
| MetaAI (LLaMA-Meta) |
| Falcon (open source) |
For example, BERT is trained using a masked language model, meaning certain words are masked, which helps train the model and makes it more contextually accurate. Conversely, GPT-4 was trained on, a large-scale corpus containing web pages from sources like Wikipedia, books, and articles of publicly available web content, making it more generic but with a boarder set of information.
Business Challenges and Considerations for choosing the right GPT:
1.Challenges
Start with identifying suitable business challenges followed by evaluating GPTs based on the strengths of each GPT and what they are specifically designed for.2.Complexity
Consider the scale and complexity of your business challenges. For simpler tasks such as text generation, summarization, or basic language understanding, smaller models like GPT-2 might suffice.
3.Nuances
If your business demands intricate language comprehension, nuanced context understanding, or complex natural language processing tasks, opting for larger models like GPT-3, GPT-4, could be beneficial.4.Specialization
For generic needs, choose GPTs based on their foundational and broad language models. For example, specialized and narrow variants like medical GPTs are tailored for healthcare applications. Multilingual GPTs are designed to handle diverse languages. Both offer niche solutions for specific industries.AI vendors are rapidly developing a variety of custom GPTs to address the most common business challenges today. Eventually GPTs will become as common as desktop software by addressing a breadth of business challenges for all industries. Until then, businesses will need to adopt an approach of GPT composability. This utilizes a combination of baseline LLMs along with a set of customized/trained GPTs with RAG (retrieval augmented generation) capabilities to address your bespoke business challenges and improve the accuracy of outputs.
Apart from the above,
- evaluate the computational resources and infrastructure available to your organization.
- larger GPT models require substantial computational power and memory to function optimally.
- if your business lacks the necessary resources, choosing a smaller, more resource-efficient model would be prudent.
- moving computing needs to the cloud, can also vastly derive computational efficiencies and reduce your in-house infrastructure needs.
- cost of operating GPTs is another crucial consideration that most organizations overlook. As your enterprise user base increases, the amount of text or data generated by the GPTs will increase exponentially, leading to ongoing and ever-increasing cost. Factoring this into your overall strategic budget will prevent unnecessary surprises in the future.
End-to-end GPT adoption and rollout process:
In summary, selecting the right GPT for your business entails a thoughtful analysis of task complexity, available resources, and specialized requirements. Cortico-X can support you in this journey, to ensure your business considerations, are evaluated and a fit-for-purpose strategy is developed. Whether it’s the comprehensive capabilities of a particular GPT, the efficiency of the GPT, or specialized variants tailored to specific industries, understanding your business needs is key. By considering these factors, business leaders can confidently make informed decisions to select the ideal GPT for their organization’s AI endeavors, unlock new possibilities, and stay ahead in today’s dynamic and competitive digital landscape.
Rishi Thukral
As a Principal and Digital lead at Acquis Cortico-X, Rishi is an accomplished AI and Digital Innovation Leader with deep background and expertise in technology.
