My take is that “ChatGPT” has never been a profitable enterprise for OpenAI, and it was initially intended as a research experiment that has since been turned into a “product.” The global attention it has received, coupled with limited resources to scale, has led to some tough decisions. Indeed, the newest model available on chat.openai.com performs differently—worse in some aspects and better in others, with some changes being intentional and others not.
However, OpenAI has made the previous model checkpoints accessible via their API, and most developers can qualify to access them now as we head into 2024. While it’s not an easy or inexpensive solution, you can certainly still use those models through user projects like “BetterChatGPT,” which replicates the ChatGPT interface, though at your own expense.
Regarding coding, the changes in how the 128k model processes input tokens—likely using a cross-attention model—and the limitation to 4K tokens for output means the model tends to provide summaries rather than full outputs. This might give the impression that it’s being “lazy.” OpenAI has acknowledged this behavior and is actively working on improvements. However, it’s unrealistic to expect performance on par with the 8K GPT-4 model in these specific terms.
For coding purposes, you can use platforms like phind.com, which provides access to the 32K GPT-4 “classic” model from the June checkpoint, better suited for coding tasks. However, be aware that you’ll still be dealing with outdated training data and a knowledge cutoff date, which limits you to older libraries and coding methods.
You may perceive OpenAI’s actions as “disrespecting” customers, but it’s likely that “hardcore ChatGPT users” are not considered their primary user base. It’s worth noting that before these changes, there were complaints about the 8K GPT-4 model’s tendency to “forget” conversations too quickly, which is now largely a resolved issue due to the longer context length.