One key reason ChatGPT is good at handling mathematical tasks and data analysis is its integration with Python, especially in its premium versions. Python not only powers the solutions provided but also allows users to see how those solutions are generated. In this post I show how you can take advantage of this.
The web interface for ChatGPT is great, but it does not always deliver what we want. In this post I want to describe how creating a simple call to the ChatGPT API can give a range of benefits. The example I am going to share in this post comes from a course I am running on how to the ChatGPT API.
In a paper published in April this year, researchers showed how speaking more collaboratively to LLMs seems to generate better responses. The paper describes how Chengrun Yang, Xuezhi Wang, Yifeng Lu, Hanxiao Liu, Quoc V. Le, Denny Zhou, and Xinyun Chen conducted a series of experiments to explore how different strategies for prompts delivered different answers.
In this post, I will highlight two approaches to getting to a better answer from ChatGPT. The first is Refining and the second is Regenerating.
In this tip I show how ChatGPT can convert the text in an image into text you an work with.
An international group has just published a new report on the safety of AI. You can download it from here. The report comprises more than 75,000 words, so I decided to use ChatGPT 4o to speed up my review of the documents. Below, I set out my process and what I found out about the report.
One of the surprises about the sudden and widespread interest in Synthetic Data is that it has forced us to revisit things we have been doing for decades. This revisiting of old practices is useful for framing where we think Synthetic Data should go and how it should be evaluated and regulated. In this post I explore why weighting is a form of synthetic data and what that means for researchers.
AI is a hot topic, and in the insight and research ecosystem, the hottest topic is Synthetic Data. In this post, I look at what Synthetic Data means, why it is such a hot topic, some of the key issues, and share some thoughts about Synthetic Data and its use.
In this post, I want to highlight one way that ChatGPT can help you be more efficient. In this example, I have taken a Focus Group Transcript from a published study and used ChatGPT to help speed up my analysis.
NewMR has recently conducted its third wave of a study on the State of Insights, focusing on Optimism/Pessimism, the main Positives and Negatives. Here is a summary of the finding and a link to the full report.
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