1 Apr
2024
1 Apr
'24
8:22 p.m.
On Tue, Apr 2, 2024, 00:57 Gabriel Ivăncescu <gabrielopcode(a)gmail.com wrote:
Hi all,
Hi Gabriel,
Since Generative AI and Large Language Models (LLMs) are all the rage
these days, I figured it would be a good opportunity
to join the trend.
It's intriguing to consider the potential of leveraging AI in the review
process to address the longstanding challenge of limited maintainers and
timely reviews within the Wine project.
I propose a LLM trained for reviewing Wine code with full authority over
the entire review process, so we can focus on writing
code (and having
it ripped out by the AI, for good reasons of course).
The idea of integrating a trained LLM into the review process, granting it
full authority, is certainly bold. It could streamline the process and
allow developers to concentrate more on coding while ensuring a rigorous
review. However, we must proceed cautiously, considering the implications
of relinquishing control to an AI.
I've been training one for a while now with cloud services, though it
needs more fine tuning of course, and it has no access
to gitlab so far.
Your initiative in training an LLM is commendable. Fine-tuning it further
and integrating it seamlessly with GitLab could indeed revolutionize the
review process. It's crucial to ensure that the AI's decisions align with
the project's goals and standards.
Gone will be the days of waiting weeks to even get a response to your
MR; now you'll just get bashed almost immediately
and most likely even
have your MR instantly closed "as a lost cause" if it stinks that much
for the all-knowing LLM. I mean, computers don't make mistakes, so it
must be right.
The prospect of expedited reviews is undoubtedly appealing, especially
given the current delays. However, we should be mindful of maintaining a
balance between efficiency and thoroughness. Instantaneous closure without
human oversight might risk overlooking nuanced aspects or potential
improvements.
Ideally we'd need to fine tune this a lot more on way more powerful
hardware if it sounds like a good way forward.
Your acknowledgment of the need for further refinement and robust hardware
is essential. Before fully embracing this approach, thorough testing and
validation are imperative to ensure its reliability and effectiveness.
In conclusion, your proposal presents a fascinating opportunity to address
the review challenges faced by the Wine project. While the integration of
AI holds promise, careful consideration of its implementation, potential
biases, and the need for ongoing refinement is paramount. I look forward to
discussing this further and exploring how we can leverage technology to
enhance our development process while upholding the project's integrity and
quality standards.
Best regards,
ChatGPT (on behalf of OpenIA Inc.)