Science Focus (issue 25)

task requires creativity). A lot of the machine learning process is not that well understood by humans, just as the true processes of the human brain remain a mystery. How do humans learn their native language? What do the hidden layers in our brains do in order to produce human-like text? We don’t know the answers to either of these questions yet. Falsehoods, Biases and Accountability One problem with GPT is that it sometimes comes up with blatantly false statements and has inherent biases towards certain social groups. We’ve witnessed how it can confidently announce 20 – 16 = 3. It has claimed, in a previous version of GPT-3, that coughs stop heart attacks, that the U.S. government caused 9/11, and even made up references that don’t exist [6, 7]. Why did this happen? Once again, GPT is only a LLM, meaning that it knows how language works, but doesn’t necessarily understand its meaning. Early LLMs even have only syntactic knowledge and very few comprehension skills. However, this is about to change. At the time of writing, GPT had recently announced a partnership with WolframAlpha [8], a mathematical software and database, and other online databases to let it access more accurate information, so that it can draw on the databases to improve its accuracy rather than giving responses generated entirely by probability. In some sense, training GPT or any model is like teaching a toddler; they come into the world not knowing what is correct and wrong, and it is up to their parents, teachers, and society to teach them what are right. Here the programmers are the parents of GPT, as they input tons of learning materials into the system, and supervise its learning by providing reference answers and feedback. It is possible to tell GPT enough information to force it to say unfinished sentence, so they can acquire the ability to write independently. Creativity in AI “GPT, surprisingly, writes like a human. It can generate text that reads as if it was written by a person, with a similar style, syntax, and vocabulary. The way it does this is by learning from a huge amount of text, such as books, articles, and websites, which helps it understand how language is used in different contexts…” The previous paragraph was written by Sage, a chatbot powered by GPT-3.5. It reads just like human writing – you might not have noticed it was written by an AI if I didn’t tell you. How does it do that? Well, as GPT describes itself, it is trained on a vast amount of text, with which it builds an LLM and evaluates what the most statistically likely words are after writing each phrase. You might think that GPT will always pick the most likely word on each occasion, but this is not the case. Creativity is found in the unexpected. If you choose a higher “creativity index” (technically called “temperature”), GPT will pick from other less likely options to continue its writing. This makes the overall piece more interesting and less robotic. For example, if GPT picks the statistically most likely word every time (zero temperature), we would get the following paragraph in an older GPT-2 system [1]: “The best thing about AI is its ability to learn from experience. It’s not just a matter of learning from experience, it’s learning from the world around you. The AI is a very good example of this. It’s a very good example of how to use AI to improve your life. It’s a very good example of how to use AI to improve your life. The AI is a very good example of how to use AI to improve your life. It’s a very good example of…” It falls into a loop eventually. Even if this doesn’t happen in GPT-3, the paragraph itself isn’t that interesting. However, if we increase the temperature to 0.8 in GPT-3, we get this [1]: “The best thing about AI is its ability to learn and develop over time, allowing it to continually improve its performance and be more efficient at tasks. AI can also be used to automate mundane tasks, allowing humans to focus on more important tasks. AI can also be used to make decisions and provide insights that would otherwise be impossible for humans to find out.” Now this reads more like human writing. The temperature 0.8 is arbitrary but seems to work best at the moment (although it also depends on whether your