Do you use ChatGPT? If so, what do you use it for?
I have used it for doing code mockups. It is really good to draw sketches of functions. And, in teaching, for generating new problem statements.
I have used it to find words that describe a condition, i.e., give it a phrase and see if there is a word that has that meaning. Similar to a thesaurus, but the input has multiple words, not just a single word.However, I asked ChatGPT what it has been used for:
ChatGPT has been used for a variety of applications since its release. Here are some examples:
Chatbots and virtual assistants: ChatGPT has been used to develop chatbots and virtual assistants for various industries, such as healthcare, finance, e-commerce, and education. These chatbots can handle customer queries, provide personalized recommendations, and offer support services.
Language translation: ChatGPT has been used to develop language translation systems that can translate text between multiple languages with high accuracy.
Content creation: ChatGPT has been used to generate content for websites, social media, and other digital platforms. It can create articles, blog posts, and even poetry and fiction.
Text summarization: ChatGPT has been used to summarize large amounts of text data, such as news articles, research papers, and legal documents.
Question answering: ChatGPT has been used to develop question-answering systems that can provide accurate answers to user queries in various domains.
Sentiment analysis: ChatGPT has been used to analyze social media data and other text data to determine the sentiment of users towards various products, services, or issues.
Personalized recommendations: ChatGPT has been used to develop recommendation systems that can provide personalized recommendations to users based on their interests, preferences, and behavior.
Overall, ChatGPT has been used in various applications and has shown great potential in the field of natural language processing and artificial intelligence.
After I saw this post, I decided to use it to do some soul searching and asked ChatGPT this: "what can you tell me about oktay gunluk?". The response did not look very precise about our timeline, but, who knows, maybe ChatGPT has secret predictive capabilities:Oktay Günlük is a computer science professor at the University of California, Berkeley. He received his Ph.D. in Operations Research from Cornell University in 1997. His research focuses on optimization and decision-making under uncertainty, with applications in transportation systems, energy markets, and healthcare. Günlük is known for his contributions to the development of stochastic programming models and algorithms, which are used to solve complex optimization problems with uncertain parameters. He has published numerous research papers in top academic journals and conferences in the fields of optimization, operations research, and computer science. He is also a Fellow of the Institute for Operations Research and the Management Sciences (INFORMS) and has received several prestigious awards for his research, including the George Dantzig Dissertation Award and the INFORMS Optimization Society Khachiyan Prize.
ChatGPT gives some very good replies to questions, but it also has serious errors. I asked a question about treatment of psychopathy and it gave an answer that indicated its database was not up-to-date. Another question about the physical state of Gallium gave an answer with conflicting information.
As an aside, there seems no discussion of whether AI is simply algorithms written by fallible humans or a discipline that has not yet reached maturity. It's important for us to be clear on this.
In class (and unrehearsed), I asked ChatGPT to produce Python code for a Monte Carlo simulation for a small newsvendor-type problem from a textbook. It produced some really nice code, but with some important mistakes. It miscalculated revenue - it used demand when demand exceeded orders and vice versa. After spending class time to explain and correct the mistakes, the students requested "a clean slate" for the next example!I had a similar experience with AMPL code for a network flow model. It produced a near-complete model but with some important mistakes. So it looks like ChatGPT can make some interesting exam questions ("What is wrong with this code?")!
That's very clever, Paul!I'm teaching logistics online in the Fall. for my Discussion questions, I plan to post a GPT answer and tell students they have to do better than the GPT answer.Are we better than GPT, or not?
Hello Paul,I experienced the same thing when I asked ChatGPT to perform a simple Python optimization, and to calculate the change in enthalpy for water going from ice at - 10 C to liquid at 10 C (I was a chemical engineer in my prior career). In both cases it made simple mistakes, the kinds one would expect of an undergraduate who is just learning the material. This led me to two observations:1. I may need to vet my assignments through ChatGPT to have a basis of comparison for work that students turn in. I also noticed that ChatGPT keeps logs of the questions that have been asked, which could be useful (I suppose) when administering exams. 2. There may be a good pedagogical application: take a solution provided by ChatGPT and ask students to determine where it made mistakes and how to correct them.
I like #2. One of my faculty suggested assignments where students turn in their prompt, the AI response, and their evaluation of the response. Along the lines of Bob's suggestion, they could also turn in a record of asking the AI to correct its mistakes.
Try following up by describing a mistake and asking the chatbot to fix it. At least in one case, it gave me a complete corrected version.
Interactions with ChatGPT foster inclusive synergy and harness cyber-human collective intelligence to enable efficient decision-making.
Not sure I would quality this as fun, but I played around withChatGPT to create a vehicle routing optimization model using natural language, and then refined it in an iterative fashion (adding and removing constraints). This appears in a (small) part of a presentation I gave here: http://www.ipam.ucla.edu/abstract/?tid=17988&pcode=AID2023 (the ChatGPT part appears around minute 19).
While I believe the created model has some errors, the opportunities this has for quickly getting up and running with an optimization models are very interesting (as long as the models are verified by an expert)
I am completely in awe and (borderline) addicted to LLMs like ChatGPT & Claude-2. I have used ChatGPT heavily to understand, troubleshoot, generate, and improve code blocks, especially during my Master's Capstone. ChatGPT was instrumental in figuring out how to deploy and tune the hyperparameters of DeBERTa-Large for my project, which had to understand contextual phrase similarities in patent documents.
Additionally, I've used them to refine my resume and cover letters. In fact, after making the requisite modifications myself, I get ChatGPT to rate them and, subsequently, suggest improvements. If I choose to act upon it and after making the said improvement, I have Claude-2 to do the same exercise. So, I am using one LLM to rate the other, and in the process, I am improving or discovering new ways to do the same task.
As a creative writer, I use these models to brainstorm, edit, and develop novel manuscript ideas.
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