Cherry Peeked

There are many ways to integrate changes in git: regular / normal git merge, git squash merge, git rebase etc. This article explains git squash merge by comparing it to regular merge. Let’s use below example: In the repository with default main branch, after two commits, a new feature branch is created. Some work happened in feature branch. feature branch now has 2 commits that it shares with main branch, and three exclusive commits (exists only in feature branch). In the meantime, others worked on main branch and added two new commits (exists only in main branch). git log output of the main branch: c72d4a9 ( HEAD - > main ) fourth commit on main 2c3dd61 third commit on main 0c2eec3 second commit on main 9b968e8 first commit on main git log output of the feature branch: 786650f ( HEAD - > feature ) third commit on feature 21cbaf1 second commit on feature 677bc7f first commit on feature 0c2eec3 second commit on main 9b968e8 first commit on mai...

As of November 2024 there are many LLM powered chatbots, such as ChatGPT by OpenAI, Gemini (formerly Bard) by Google, Claude (family of LLMs) by Anthropic and more. Majority of these chatbots have paid and free tiers. Although there are many review and comparisons of these chatbots, they mainly focus on the premium (paid) versions of these chatbots. However, not everyone is willing to shell out $20 per month. I, being broke, have been using free version of chatbots since they came out. Based on my actual use, not the benchmark results, I decided to write a comparison review of free tier of AI chatbots. I know that I can’t just say “based on my experience XY chatbot is the best, end of story”. I need to show some material so that you as a reader can confirm the results. On later section of the post, I will discuss the prompts I used in detail. Little heads-up, I tried to use prompts that have less to do with factual accuracy. I have never seen or heard of a large language model...