GPT-4: The Next Generation AI That Can ‘See’😎
OpenAI, the research organization behind some of the most advanced artificial intelligence systems in the world, has recently announced its latest creation: GPT-4. GPT-4 is a natural language processing (NLP) model that can generate coherent and diverse texts on almost any topic, given some input. But unlike its predecessor, GPT-3.5, which was mainly focused on text generation, GPT-4 can also process images and use them as additional input or output.
What makes GPT-4 so powerful and versatile is its internal architecture, which is based on a transformer-style neural network. A transformer is a type of neural network that uses an attention mechanism to learn how to focus on the most relevant parts of the input data, whether it is text or images. This allows the model to capture long-range dependencies and complex relationships between different modalities.
GPT-4 consists of two main components: an encoder and a decoder. The encoder takes an input sequence of tokens (words or pixels) and transforms it into a high-dimensional vector representation. The decoder then takes this vector and generates an output sequence of tokens, either text or images. The encoder and decoder are both composed of multiple layers of transformer blocks, each with self-attention and cross-attention modules.
Self-attention is a technique that allows each token in the input sequence to attend to every other token in the same sequence. This helps the model learn contextual information and semantic meaning from the input data. Cross-attention is a technique that allows each token in the output sequence to attend to every token in the input sequence. This helps the model align the output with the input and generate relevant and coherent responses.
GPT-4 has several advantages over previous NLP models:
* It can handle multimodal inputs and outputs, such as text-to-image, image-to-text, image captioning, image completion, etc.
* It can perform multiple tasks with minimal fine-tuning or domain adaptation, such as question answering, summarization, translation, dialogue generation, etc.
* It can generate longer texts with more diversity and creativity than ChatGPT.
* It can solve structured problems that require logic and reasoning skills, such as passing exams or playing games.
According to OpenAI’s tests, GPT-4 outperforms existing large-scale NLP models on various benchmarks and tasks. For example:
— On simulated exams designed for humans, such as bar exam questions or SAT math problems, GPT-4 achieves average accuracy scores between 70% and 80%, while ChatGPT scores around 50%.
— On natural language understanding tasks, such as GLUE (General Language Understanding Evaluation) or SuperGLUE, which measure how well a model can perform common NLP tasks like sentiment analysis or natural language inference, GPT-4 achieves state-of-the-art results.
- On natural language generation tasks, such as LAMBADA (Large-scale Autoregressive Model Benchmark for Automatic Data Analysis) or DART (Dataset for Aspect-based Reasoning Tasks), which measure how well a model can generate fluent and coherent texts given some context or query, GPT-4 surpasses ChatGPT by generating longer texts with more diversity and creativity.
However, GPT-4 also has some limitations and challenges:
- It still suffers from hallucination errors , which means it sometimes generates false or misleading information that is not supported by the input data.
- It still requires large amounts of data and computational resources to train effectively. According to OpenAI’s estimates, training GPT-4 took about 10 times more data than ChatGPT (1 trillion words vs 100 billion words) and about 100 times more compute power (10 exaflops vs 100 petaflops).
- It still poses ethical and social risks if used maliciously or irresponsibly. For example, it could be used to spread misinformation or propaganda online; it could be used to impersonate people or entities without their consent; it could be used to manipulate people’s emotions or opinions; etc.
Therefore, OpenAI has decided to release GPT-4 under strict conditions and regulations[²^. They have created an API service that allows selected researchers and developers to access GPT-4
If you like the article and would like to support me make sure to:
- 👏 Clap for the story (50 claps) and follow me 👉
- 📰 View more content on my medium profile
- 🔔 Follow Me: LinkedIn | Medium | GitHub | Twitter
