What Is ChatGPT? Overview, Performance, and Underlying Technologies

ChatGPT (Chat Generative Pre-trained Transformer) is an AI model released by OpenAI in November 2022. Its human‑like conversational ability quickly attracted over 100 million users within two months, making it the most prominent AI phenomenon after AlphaGo.

360 Group founder Zhou Hongyi said that the leap in large‑model AI technology represented by ChatGPT will trigger a new industrial revolution, and that all industries will be reshaped by AI and big‑data models.

Unlike earlier chatbots, ChatGPT can understand any question and provide answers that follow human thinking patterns and language norms. It can also handle complex tasks such as text generation, document summarization, mathematical problem solving, and code assistance. Its responses are logical, fluent, and mathematically precise, while its code suggestions are useful references.

Typical use cases:

1. Daily conversation –

2. Document writing –

3. Math solving –

4. Coding assistance –

Why ChatGPT is so powerful:

1. Transformer provides the foundation for large language models. The 2017 paper “Attention Is All You Need” introduced the Transformer, a deep‑learning model based on self‑attention that enables parallel processing of all tokens and captures long‑range dependencies. This architecture underpins BERT and GPT series, with GPT‑3 reaching 175 billion parameters.

2. GPT ushered in a new era of massive‑data training. Large models require huge corpora; unsupervised pre‑training on vast natural‑language data gives the model strong language understanding. Supervised fine‑tuning then adapts the model to specific downstream tasks, often achieving excellent results with relatively little labeled data.

3. ChatGPT aligns with real human intent. It uses supervised fine‑tuning (SFT) and reinforcement learning from human feedback (RLHF). The training pipeline consists of three steps:

Step 1: Collect labeled data and fine‑tune the pretrained model with supervised learning.

Step 2: Gather comparison data for the same prompts, label which output better reflects human preference, and train a reward model that predicts this preference.

Step 3: Apply Proximal Policy Optimization (PPO) reinforcement learning, using the reward model to score generated answers and update the policy, iterating to improve response quality.

Impact of ChatGPT: The technology not only advances AI research but also offers a new paradigm for internet applications, enabling one‑click AI assistants that reduce the need for users to search for information or learn complex interfaces. Embracing this transformation is essential for staying competitive.