Davinci and ChatGPT
ChatGPT and it's model text-davinci-003 is yet the most powerful released by OpenAI.
Leonardo da Vinci was a true polymath, known for his talents and contributions in a wide range of fields, including art, science, engineering, and invention. He is widely considered to be one of the most brilliant minds in history, and his work in these different fields continues to inspire people today.
It makes sense that the Davinci model, which is also intended to be multi-talented and capable of doing many different things, to be named after Leonardo da Vinci. Just as Leonardo da Vinci was able to command multiple disciplines, the Davinci model is also designed to be able to generate diverse and coherent text, answer a wide range of questions and perform multiple tasks.
In essence, naming the model after Leonardo da Vinci is a way of paying tribute to his pioneering work and contributions, and highlighting the model's own capabilities to be as versatile and multi-disciplinary as the famous inventor, artist and scientist.
So where is the breakthrough?
The breakthrough of GPT-based models like the davinci model is their ability to generate human-like text through unsupervised learning on large datasets. This allows the model to learn patterns and structures in the data that enable it to generate text that is coherent, fluent, and similar to text written by humans.
The addition of human feedback reinforcement in GPT-based models is a technique that aims to improve the performance of the model by allowing human users to provide feedback on the model's generated text. This feedback can then be used to fine-tune the model's parameters, in order to improve its performance.
By incorporating human feedback, the model is able to learn from the examples provided by the users, this can help the model to generate more accurate and coherent text and also to answer a wider range of questions. The model can also be fine-tuned on other specific tasks like question-answering, dialogue generation, summarisation and more.
In summary, the breakthrough of GPT-based models like Davinci is their ability to generate human-like text through unsupervised learning on large datasets, and the ability to improve its performance through human feedback reinforcement. The model is able to learn from the examples provided by the users and to generate more accurate and coherent text.
Who are the funders of OpenAI?
OpenAI is a private artificial intelligence research laboratory consisting of the for-profit OpenAI LP and its parent company, the non-profit OpenAI Inc. It was founded in December 2015 by Elon Musk, Ilya Sutskever, Greg Brockman, Wojciech Zaremba, and Sam Altman.
OpenAI has been funded by a number of investors, including:
The company has also received funding from other venture capital firms and investment companies such as Andreessen Horowitz, Obvious Ventures, and Khosla Ventures.
A quote from ChatGPT "It is worth noting that OpenAI's mission is to ensure that AI is developed in a way that is safe for humanity and that its benefits are widely distributed, for this reason the company is also committed to making its research open and transparent."
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How to guard against biased data?
Sustainably?
ChatGPT running on a cluster of powerful computers provided by OpenAI's cloud computing provider, which is Microsoft Azure. Azure is a cloud computing platform and infrastructure created by Microsoft for building, deploying, and managing applications and services through a global network of Microsoft-managed data centers.
Microsoft Azure, like other cloud computing providers, is taking steps to make their services more sustainable and environmentally friendly.
Azure has committed to using 50% renewable energy by the end of 2020 and 60% by the end of 2023. They have also committed to using 100% renewable energy by the end of 2025. Azure also has a program called "Carbon offset program" which allows customers to offset the carbon footprint of their Azure consumption by purchasing carbon credits.
In addition, Azure is investing in research and development of new technologies to improve the energy efficiency of their data centers and servers. For example, they're working on developing new server designs that use less power, and they're experimenting with new cooling techniques that can reduce the energy required to keep servers cool.
Are there similar models in the works?
Yes, there are similar models in the works to GPT-based models like Davinci.
GPT-based models are part of a larger class of models known as language models, which are trained to generate human-like text. Many other organisations and research groups are also working on developing and improving language models, such as Google's BERT, RoBERTa, T5 and XLNet, Facebook's RoBERTa and XLM, and Hugging Face's DistilBERT and ALBERT.
These models are typically trained on large datasets and use similar techniques to GPT-based models to generate text. They also have similar capabilities, such as the ability to generate coherent and fluent text, answer questions, and complete tasks.
Some of these models focus on specific tasks such as question answering, sentiment analysis, and summarisation, while others are more general-purpose models. Some of them also try to solve the issue of scalability, meaning that they can run on less powerful machines.
It's worth noting that the field of AI and language models is rapidly evolving and new models are constantly being developed and improved, so it's likely that there will be new models in the future that will be even more advanced and capable than the current ones.
ChatGPT recommended for junior coder and university student?
The short answer is not by itself, like google revolutionised web searches and is used as part of daily life/work.
We have to challenge the responses of the model, and keep an open mind that the model is as good as the data being trained on. OpenAI does not share their training data.
It is a sharp tool to be used complemented with ones own effort where the creativity and experience gets sharpened.