Idle/Random/whatever Thoughts of a Demented/Idle/Whatever Mind

  1. How Many Decimals of Pi Do We Really Need? - This article explains that even for NASA's highest accuracy calculations, such as interplanetary navigation, only a small number of pi's decimals are needed. For example, JPL uses pi to the 15th decimal place (3.141592653589793). The article illustrates this by calculating the circumference of Voyager 1's distance from Earth, the circumference of Earth, and even the circumference of the known universe, demonstrating that only a limited number of decimal places are necessary for accurate calculations, even at vast scales. My Take : We often get super excited about accuracy and going to crazy lengths to achieve it. But, honestly, for any everyday functional use of pi, having 3 digits after the decimal gives you really good accuracy, which is usually within the range of error from other stuff anyway. In fact, that article mentions 37 decimals would be enough to calculate the circumference of the observable universe with the ac...

After a brief hiatus I am back at publishing this. Had been heads down at getting Sudama Clinic operational. Not that I did not learn during this time, but was struggling to find time to pen down all that. Got a little breathing time now, so here is it is.    1. Dillo Browser : Dillo is a remarkably lightweight and fast web browser, prioritizing speed and efficiency above all else. Designed for minimal resource usage, it excels on older or less powerful systems. By focusing on core web functionality and avoiding complex features like JavaScript and advanced CSS, Dillo achieves a streamlined experience. This minimalism also contributes to enhanced security by reducing potential vulnerabilities. Available across various platforms, including Linux and BSD, Dillo caters to users seeking a basic, no-frills browsing experience. Its simplicity makes it ideal for specific use cases where speed and resource conservation are paramount, offering a practical solution for those who requi...

2024 was a transformative year, marked by both challenges and cherished moments. My journey began with my work on Gemini at Google, an experience that allowed me to collaborate with brilliant minds and contribute to innovative features. However, after several years, I felt a growing desire to make a more direct impact—a feeling I'd been contemplating as I wrote this blog post . This prompted the difficult decision to leave Google and embark on a new venture. I co-founded a startup called Sudama Health, driven by the mission of providing affordable and accessible healthcare to people in rural and underserved areas of India. I firmly believe that telemedicine can bridge the healthcare access gap and revolutionize the Indian healthcare landscape, where a vast population faces a shortage of healthcare professionals. To achieve this, however, telemedicine needs to evolve beyond simple video calls and incorporate a range of connected medical devices to enable true transformation. Buildi...

1. Why you should never use !! in Kotlin - Using double-bang operator(!!) is a bad practice; multiple alternatives cover every other possible case. Using it is a hack and a shortcut that will backfire while not saving you much time at the time of writing using it. You shouldn’t use it unless you're writing a short personal script. My Take : The double-bang operator (!!)  which throws null pointer exception in Kotlin might very well be considered " Billion Dollar Mistake ." While it offers a concise way to assert that a variable is not null, I believe it's preferable to have slightly more verbose code that explicitly handles nullability and avoids potential runtime exceptions. Null pointer exceptions have plagued programmers for decades, and introducing a feature that can easily lead to them seems counterproductive. I'm uncertain whether all Kotlin linters currently check for excessive or inappropriate use of the !! operator, but if yours don't, I strongly re...

1. Llama 3.3 -  Llama 3.3 70B model offering similar performance to the Llama 3.1 405B model, allowing developers to achieve greater quality and performance on text-based applications at a fraction of the cost.  My Take : Meta continues to impress with each new release. Their recent claim that the 3.3 70B model performs as well as the 3.1 405B model is particularly noteworthy. This rapid progress suggests that these powerful models could soon be running on personal computers or even directly in web browsers.Meanwhile, OpenAI's recent move to introduce a $200 monthly subscription for advanced access to its models raises questions about its long-term strategy. While the initial novelty factor might justify such a premium, it seems excessive, especially for users in regions like India. It's likely that we'll see highly capable language models running on mobile devices within the next six months, potentially even before desktop deployment. My experience with a Llama 3.2 1B mod...

1. C++ Pitfalls - this article, explains some of the pitfalls you can fall into when programming in C++ and shares their experience with them. This includes Operator precedence, Arithmetic conversion rules, Right bit-shift, Implicit conversions and Order of evaluation.  My Take : We've all read about JavaScript's quirks, leading to unexpected outputs. But let's remember that such behaviors aren't unique to JavaScript. Even languages like C and C++ have their share of ambiguities and compiler-specific behaviors. While it's tempting to dive deep into these intricacies, I've found that focusing on clear, consistent, and unambiguous code is often more practical. However, understanding these nuances is essential for any experienced programmer. It helps us avoid pitfalls and write robust, reliable code. Remember, mastering a language isn't just about writing "Hello World." It involves delving into its intricacies, including its counterintuitive and ambi...

1. AI Makes Tech Debt More Expensive - The core argument is that generative AI significantly widens the gap between codebases with low and high tech debt. Companies with clean code can leverage generative AI to write code much faster, while companies with messy legacy codebases struggle to adopt these new tools. This widens the gap between the two codebases, making tech debt even more expensive for companies with outdated systems. My Take : Legacy systems inevitably accumulate technical debt. A common analogy for this is the state of urinals over time: missed targets lead to increasing mess, keeps pushing people away from urinals and leading to more mess in turn. AI-powered coding tools could potentially accelerate the accumulation of tech debt. However, skilled engineers can leverage AI to reduce and even eliminate it. Ultimately, AI is just a tool, and human judgment remains crucial for making informed decisions. I hope AI will be used responsibly to drive positive outcomes. 2. Make...