How NotebookLM Works:

Unlike general-purpose chatbots that draw on vast, public datasets, NotebookLM focuses on your uploaded files. You can add PDFs, Google Docs, or link directly to specific websites. NotebookLM then creates a personalized AI model based on this information, allowing for more focused and relevant responses. This personalized approach is a key differentiator, ensuring that the AI’s understanding is grounded in your specific research materials.

AI-powered coding assistants have become increasingly popular, promising to boost developer productivity and streamline the coding process. Tools like GitHub Copilot and Cursor offer impressive capabilities, generating code snippets, suggesting completions, and even creating entire functions based on prompts. However, alongside these benefits come potential pitfalls that developers need to be aware of, as highlighted in recent discussions on the Cursor forum.

The Allure of AI Assistance:

The appeal of AI coding assistants is undeniable. They can:

Well, it depends! Let’s start with the models.

It feels like a new model is released pretty much every month claiming to be “best in class” and having superior results to competitor models.

Can Large Language Models (LLMs) Write Compilable Code?

Large language models (LLMs) have demonstrated impressive capabilities in generating human-like text, translating languages, and even writing different kinds of creative content. But can these powerful AI tools also write code that’s actually compilable and functional? The answer, in short, is a qualified yes, but with important caveats.

Large language models (LLMs) have become synonymous with cutting-edge AI, capable of generating realistic text, translating languages, and writing different kinds of creative content. But what if you could leverage this power on your own machine, with complete privacy and control?

Running LLMs locally might seem daunting, but it’s becoming increasingly accessible. Here’s a breakdown of why you might consider it, and how it’s easier than you think:

The Allure of Local LLMs

Artificial intelligence (AI) is rapidly transforming our world, but it comes with a hidden cost: carbon emissions.

According to a recent study by the Allen Institute for AI, training a single large language model can produce up to 550 tons of carbon dioxide, equivalent to the emissions of five cars over their lifetime.

This is because AI training requires massive amounts of computing power, which in turn relies on electricity generated by fossil fuels.