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An article by Murakami

 I came across a very interesting article by Haruki Murakami published 17 years ago in New Yorker. In this article, Mr. Murakami explained his transition from a jazz music bar owner to a novelist and how running, among other things, contributed to this dramatic career and life change. He started running daily to maintain healthy so that he can write novels, which are the ultimate gift he present to his readers and he considers his relationships with his readers the most important one in his social life   It is a very inspiring read for people stepping into a transition stage, be it career or life. https://www.newyorker.com/magazine/2008/06/09/haruki-murakami-the-running-novelist
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A base model based off of gpt-oss

Noticed this base model release:   https://huggingface.co/jxm/gpt-oss-20b-base As a base model, there is no safeguard in place. Not sure what is the implications of this release in terms of security. The size of this model (20gb) is smaller enough to run some powerful laptops and make it accessible to many users.  This kind of engineering are potentially threatening. 
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Google Colab

After tracking Nvidia’s RTX 50-series cards for a while, I still feel they are too expensive and likely not powerful enough to fully support my AI enthusiasm. As a result, I’ve decided to explore alternatives, particularly cloud solutions. Google Colab has turned out to be a very appealing option for now. It provides a Jupyter Notebook interface backed by CPUs, GPUs, and TPUs managed by Google. There is a free tier that offers limited GPU access (availability-based). During my test run this Sunday morning, I was able to access a GPU with 16 GB of memory. Paid users receive access to more powerful GPU and CPU resources. This makes Colab a viable alternative to running an on-premise AI lab—provided you’re comfortable with Google hosting your data and models. I haven’t checked AWS’s GPU offerings yet, but based on my prior EC2 experience, I feel Colab is much more convenient. Colab simplifies many aspects (from billing to system management), allowing you, as an AI scientist, to focus on m...
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First Impression about Claude Code

I was really impressed by Claude Code. For just $5 and under an hour, Claude scanned my project repository and generated the skeleton of a new functionality based on my prompt. While the code wasn’t error-free, the overall logic was sound. Reaching that point on my own would have taken me hours, if not days. About half of the errors could be resolved with additional prompting, and I spent roughly another hour fixing the remaining bugs and testing. In total, I had working, productive code in about four hours—work that would normally take me closer to twenty hours. In other words, that $5 effectively saved me 15 hours of effort!
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