What is GPT?

What Is GPT?

GPT stands for Generative Pre-trained Transformer, a specific architecture and family of AI models developed by OpenAI. Each word in the name describes a key characteristic:

• Generative: The model creates new content rather than simply classifying or analyzing existing content
• Pre-trained: The model is trained on vast amounts of text data before being adapted for specific tasks
• Transformer: The underlying neural network architecture that enables the model to process and understand relationships within text

GPT has become one of the most recognized names in artificial intelligence, largely due to the success of ChatGPT, which brought generative AI into mainstream business and consumer use starting in late 2022.

The Evolution of GPT Models

Understanding the progression of GPT models helps business leaders grasp the pace of AI advancement:

GPT-3 (2020): The model that first demonstrated that large language models could generate remarkably human-like text. It had 175 billion parameters and could write essays, answer questions, and even generate basic code.

GPT-3.5 (2022): The model behind the original ChatGPT launch. It was more conversational and better at following instructions, sparking the global generative AI boom.

GPT-4 (2023): A major leap in capability, with significantly improved reasoning, accuracy, and ability to handle complex tasks. GPT-4 could pass professional exams including the bar exam and medical licensing tests.

GPT-4o (2024): An optimized version of GPT-4 that introduced native multimodal capabilities, processing text, images, and audio in a single model with faster response times and lower costs.

Each generation has brought substantial improvements in accuracy, reasoning ability, and the range of tasks the model can handle effectively.

How GPT Is Used in Business

GPT models are accessed by businesses through several channels:

ChatGPT (Consumer and Business Product)

The most accessible way to use GPT technology. ChatGPT Plus and ChatGPT Enterprise offer enhanced features including longer conversations, file uploads, data analysis, and web browsing. Many SMBs start their AI journey here.

OpenAI API

For businesses that want to build GPT capabilities into their own products and workflows. The API allows developers to send prompts to GPT models and receive responses programmatically, enabling custom chatbots, content generation pipelines, document processing systems, and more.

Microsoft Copilot

GPT powers Microsoft's Copilot products integrated into Office 365, GitHub, and Azure. For companies already in the Microsoft ecosystem, this is often the most natural way to deploy GPT capabilities across the organization.

Custom GPTs

OpenAI allows businesses to create custom versions of ChatGPT tailored to specific tasks, loaded with company-specific knowledge and instructions. A logistics company could create a custom GPT that knows its shipping routes, pricing, and policies.

GPT for Southeast Asian Businesses

GPT models offer several advantages for companies operating in ASEAN markets:

Multilingual Capabilities GPT-4 and GPT-4o handle major Southeast Asian languages including Bahasa Indonesia, Thai, Vietnamese, Malay, and Tagalog. While performance in English remains strongest, the gap is narrowing with each model generation, making GPT increasingly practical for multilingual business operations.

Cost-Effective Expertise For SMBs that cannot afford to hire specialists in every domain, GPT can serve as a versatile assistant for tasks ranging from market research and competitive analysis to drafting legal documents and creating financial models. A small company in Bangkok can access analytical capabilities that were previously available only to large enterprises.

Rapid Prototyping Startups and SMBs across Southeast Asia are using GPT to rapidly prototype products, generate business plans, create pitch decks, and develop MVPs. The speed at which GPT can produce first drafts accelerates the entire product development cycle.

Understanding GPT's Limitations

While GPT is remarkably capable, business leaders should be aware of its limitations:

• Knowledge cutoff: GPT models have a training data cutoff date and may not know about very recent events or developments
• Hallucination: GPT can generate plausible-sounding but incorrect information, particularly on niche or specialized topics
• Context window: There are limits on how much text the model can process in a single conversation, though these limits are expanding with each generation
• Consistency: Given the same prompt, GPT may produce slightly different outputs each time, which can be managed through API parameters
• Bias: The model's training data includes biases present in internet text, which can occasionally surface in outputs

GPT vs. Alternatives

GPT is not the only option for businesses exploring large language models. Key alternatives include:

• Claude (Anthropic): Strong at analysis, safety, and handling very long documents
• Gemini (Google): Tightly integrated with Google services and strong at multimodal tasks
• Llama (Meta): Open-source, can be self-hosted for maximum data control
• Mistral: Efficient European-developed models with strong performance-to-cost ratios

The best choice depends on your specific requirements, existing technology ecosystem, and data governance needs. Many businesses use multiple models for different tasks.