Have you ever wanted to write two lines and have the computer complete the rest of an essay or journal?
Technological advancements are making programming a more important skill in various industries. It takes a lot of time and effort to learn any programming language from scratch, even for experts who have been in the field for decades.
Couldn't you just tell your computer to follow your instructions if it understood plain English? AI may be the key to simpler and faster communication between computers instead of hacking away at a terminal for hours on end.
OpenAI is an AI research and development company that conducts research in Artificial Intelligence (AI). It's made possible by using AI-powered programs and machine learning algorithms that computers can do various tasks, such as creating images from text and solving Rubik's Cubes through robotic hands.
The final goal is to ensure that AI contributes to the betterment of humanity through the development of highly autonomous systems that can perform work better than humans at the most economically valuable times and in most economic conditions.
Happy birthday dear GPT-3!
Language models have never been more potent than GPT-3, which was introduced in May 2020. With an opening sentence, GPT-2 already produced convincing streams of text in a variety of styles. However, GPT-3 represents a significant leap forward. With 175 billion parameters (values that a neural network attempts to optimize during training), the model is more comprehensive than GPT-2's 1.5 billion.
GPT-3 can create a wide range of applications due to its powerful text generation capabilities. Writing in the style of Shakespeare, Edgar Allen Poe, and other famous authors can be generated using GPT-3, such as blog posts, advertising copy, and even poetry.
Because programming code is just a text form, GPT-3 can generate workable code using only a few snippets of example code. Mocking up websites has also been accomplished with GPT-3. Developers can create websites simply by describing them in a few sentences using the UI prototyping tool Figma and GPT-3. Even cloning websites have been done using GPT-3, which provides a suggested text based on a URL. There are several ways in which developers use GPT-3, including generating code snippets, formulas, graphs, and charts from text descriptions, Excel functions, and other development tools.
The GPT-3 model predicts languages. As a result, it can transform input text into what it predicts will be the most helpful result using a neural network machine learning model. The system is trained to spot patterns using the vast amount of internet text. GPT-3 is the third version of a text generation model based on pre-trained models on a massive amount of text.
A text predictor is used to create the most likely output when a user provides text input. Despite the model's lack of additional tuning or training, it produces high-quality text that mimics what humans would write.
Surprise! chatGPT is here
As a result of ChatGPT's announcement a few weeks ago, it has become a big topic of discussion in the tech world for a good reason.
Those who have been following along may be wondering what the difference is between ChatGPT, which is a new implementation of this technology, and GPT-3, which has been in use in a number of settings for decades.
There are some key differences between ChatGPT and GPT-3, both of which were trained using OpenAI. As one of the most powerful language models available today, GPT-3 is OpenAI's third-generation GPT language model. As well as language translation, text summarization, and question answering, it can be tailored to perform a wide range of natural language processing tasks.
In contrast to GPT-3, ChatGPT is a variant of GPT-3 that has been tailored specifically for chatbots. Since the bot has been trained based on a large set of conversational texts, it can now generate responses that are more appropriate to use in a chatbot context since it has been trained upon a large dataset of conversation. In addition, ChatGPT can insert context-specific responses into conversations to maintain coherence.
ChatGPT does not have the same performance as GPT-3 when it comes to performance. However, it is better suited for chatbot applications than GPT-3. Moreover, it is generally faster and more efficient than GPT-3, so it is a better choice for use in real-time chatbot systems since it can provide much higher performance. As a whole, ChatGPT and GPT-3 are both highly effective language models; however, they serve different purposes.
Checkmate - A 1.75 trillion parameter Monster has arrived
Language is probably the best vehicle to model intelligence or emulate it. It's not about making a powerful artificial intelligence but about seeing strong artificial intelligence in front of humans.
While GPT-3 shocked the world, it didn't take long for it to meet its match!
China's first super-scale intelligent model system, Wu Dao 2.0, was launched in June 2021 by the Beijing Academy of Artificial Intelligence (BAAI). In terms of human-level thinking, Wu Dao is intended to surpass OpenAI's GPT-3.
Let's have a comparison these two deeply:
An integrated approach
Multimodality is a feature of Wu Dao 2.0. In addition to learning from text, Wu Dao 2.0 can handle tasks involving images and text (something GPT-3 cannot do). As AI systems specialize in managing one mode of information, we have seen a shift toward multimodal systems in recent years.
A parameter or a dataset
GPT-3's training dataset (570GB) is dwarfed by Wu Dao 2.0's 4.9TB of high-quality text and image data reported for the South China Morning Post. It is noteworthy, however, that OpenAI researchers curated 45TB of data to collect that 570 GB of clean data from the internet.
Experts from a variety of fields
A similar system was used to train Wu Dao 2.0: FastMoE (Mixture of Experts). Each modality is trained within a larger model. For each type of task, the larger model can consult different models through a gating system.
Open-source FastMoE is more democratic than Google's MoE since it doesn't require specific hardware. By solving training bottlenecks, BAAI (Beijing Academy of Artificial Intelligence) researchers were able to reach the 1-trillion-parameter milestone for models such as GPT-3. These training frameworks will certainly shape the future of large AI systems.
In current limited beta development, GPT3 has only just begun to produce demonstrations, and early access developers have just begun to provide more details about how the technology will work. It is expected that the technology will be applied in a lot more exciting and profound ways as the limited Beta program expands. Essentially, It will influence the future of the internet and how we are going to use technology and software going forward.