A chatbot like ChatGPT, especially in the most recent version based on the GPT-4 generative model of OpenAI, offers increasingly articulated, pertinent, and extensively argued answers on any topic. Like GitHub Copilot, it is possible to program with ChatGPT: the service user can ask the artificial intelligence to produce content using a specific programming language. Present the problem to be solved, avoid being stingy in details, and obtain a working code that can be reused in your applications and projects.
The well-known journal Nature, one of the world’s most prestigious and influential scientific publications, has published some practical tips for using ChatGPT in software development. “Even if ChatGPT’s initial responses are unstable,” notes Nature,” often the chatbot eventually produces accurate results, including programming code .” As early as March 2023, Nature claimed that ChatGPT could solve 76% of the 184 tasks expected in an introductory bioinformatics course after a single attempt. However, 97% of the problems were solved within seven attempts.
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The Six Tips For Programming With ChatGPT
Having heard from many industry experts, there are six tips to keep in mind if you are about to use ChatGPT for programming. We list them below and then offer a more detailed discussion:
- Choose the field of application well
- Always verify the code provided without assuming anything
- Evaluate safety aspects
- Start a conversation with ChatGPT to refine the output gradually
- Assign ChatGPT a precise role, like in a game
- Embrace the change
ChatGPT Is A Stochastic Parrot
At first reading, this might seem like a serious offense. In reality, the “stochastic parrot” appellation could not fit more perfectly for a tool like ChatGPT.
The Quality Of ChatGPT Responses Depends On The Input Or Prompt
The answers generated by the generative models derive from the associations between the words learned during the training phase and their quality, as well as from the size of the dataset used; it also depends a lot on the level of detail of the prompt (the question posed by the user). When asking questions to ChatGPT, avoid ambiguity to get better answers. Breaking the problem into smaller and more manageable parts is also good. Encouraging the chatbot to step into a specific role is also good. Making ChatGPT assume a certain role can help the chatbot move into the right probabilistic space.
The Terms Parrot And Stochastic: Generating Content With A Probabilistic Process
The term “parrot” refers to the ability of templates, such as those used by ChatGPT, to generate coherent, flowing text, reproducing what they have been trained to do, but without an “understanding” of the meaning or context of the words. We were talking about “predictions” on new data. The term “stochastic” refers to the unpredictable nature of the responses generated by these models.
Since ChatGPT has no real understanding of the meaning of words, the answers can be very variable (and this is also the beauty of the system) and can be affected by small variations in questions or context. In general, “stochastic” refers to a process or phenomenon characterized by a certain amount of randomness or unpredictability. It is a concept widely used in mathematics, statistics, physics, computer science, and other disciplines. Stochasticity implies that the outcome of a stochastic process cannot be precisely determined but can only be described in terms of probability.
This means that, even with complete information on the initial state and the process rules, the outcome cannot be predicted with certainty. Services such as ChatGPT, and the various generative models in general, are based on a probabilistic process, certainly not deterministic. The chatbot “predicts” the most probable next words in the answer composition but in the end, they may not be the most accurate. “You shouldn’t rely on the factual accuracy of our model output,” OpenAI noted when reporting ChatGPT a few weeks ago.
Also Read: Five Ways To Earn With ChatGPT
