What is Galactica AI Assistance?

Galactica is the first step toward creating a perfect scientific neural network helper

Large language models have advanced significantly in recent years (LLMs). Impressive LLMs have been revealed one after the other, beginning with OpenAI's GPT-3, which generates exceptionally correct texts and ends with its open-source counterpart BLOOM. Language-related problems that were previously unsolvable had become simply a challenge for these systems.

All of this progress is made possible by the vast amount of data available on the Internet and the accessibility of powerful GPUs. As appealing as they may sound, training an LLM is an incredibly expensive procedure in terms of both data and technology needs. We're talking about AI systems with billions of parameters, so feeding these models with enough data isn't easy. However, once you do it, they give you a stunning performance.

Have you ever wondered where the development of "computing" gadgets began? Why did individuals devote so much time and energy to designing and constructing the first computers? We can presume it was not for the purpose of amusing people with video games or YouTube videos.

It all began with the purpose of resolving scientific information overload. Computers are presented as a way for managing the expanding amount of data. They would have completed regular activities such as storage and retrieval, clearing the space for discoveries and conclusions in scientific reasoning. Can we truly claim this when finding an answer to a scientific question on Google is becoming increasingly difficult?

Furthermore, the sheer volume of scientific publications released each day exceeds what a human being can process. In May 2022, for example, arXiv received an average of 516 publications every day. Furthermore, the volume of scientific data is rising beyond our processing capacities.

We have tools for accessing and filtering this data. The first place you go to study a topic is Google. Although it will not always provide the solution you need, Google will send you in the right direction, such as Wikipedia or Stackoverflow. Yes, we can discover the answers there, but the difficulty is that these resources necessitate costly human contributions, and updates can be delayed.

What if we had a better model for accessing and filtering the vast amount of scientific data available? Search engines can simply store data; they cannot reason about it. What if we all had a Google Search that could interpret the data it stores and directly answer our queries? It's finally time to meet Galactica.

Language systems, unlike search engines, have the potential to store, combine, and reason about scientific understanding. They can connect research papers, uncover hidden knowledge, and deliver those insights to you. They can also provide relevant information for you by connecting content they are familiar with. Creating a literature review on a certain issue, a course lecture note, responses to your inquiries, and wiki articles. All of this is achievable using language models.

Galactica is the first step toward creating a perfect scientific neural network helper. The ultimate scientific aid will be the interface via which we obtain knowledge. It will handle the time-consuming information overload procedure while you concentrate on making decisions based on this knowledge.

So, how does Galactica function? Since it is a LARGE language model, it has billions of parameters that have been trained on billions of data points. Because Galactica is intended to be a scientific helper, research publications are an obvious source of training data. In this regard, almost 48 million research papers, 2 million scripts, 8 million lecture notes, and textbooks were used to create Galactica's training data. Finally, a dataset of 106 billion tokens is used.

Galactica was utilized in the writing of its own paper, making it one of the first AI models to be introduced. We anticipate that it will be used to write a large number of articles in the near future.