Why did humans evolve the eyes we have today? While scientists can’t go back in time to study the environmental pressures that shaped the evolution of the diverse vision systems that exist in nature, a new computational framework developed by MIT researchers allows them to explore this evolution in artificial intelligence agents. The framework they…
In this article, you will learn three reliable techniques — ordinal encoding, one-hot encoding, and target (mean) encoding — for turning categorical features into model-ready numbers while preserving their meaning. Topics we will cover include: When and how to apply ordinal (label-style) encoding for truly ordered categories. Using one-hot encoding safely for nominal features and…
Most languages use word position and sentence structure to extract meaning. For example, “The cat sat on the box,” is not the same as “The box was on the cat.” Over a long text, like a financial document or a novel, the syntax of these words likely evolves. Similarly, a person might be tracking variables…
A language model is a probability distribution over sequences of tokens. When you train a language model, you want to measure how accurately it predicts human language use. This is a difficult task, and you need a metric to evaluate the model. In this article, you will learn about the perplexity metric. Specifically, you will…
“At MIT, innovation ranges from awe-inspiring technology to down-to-Earth creativity,” noted Chronicle, during a campus visit this year for an episode of the program. In 2025, MIT researchers made headlines across print publications, podcasts, and video platforms for key scientific advances, from breakthroughs in quantum and artificial intelligence to new efforts aimed at improving pediatric health…
Language model training is slow, even when your model is not very large. This is because you need to train the model with a large dataset and there is a large vocabulary. Therefore, it needs many training steps for the model to converge. However, there are some techniques known to speed up the training process….
This web scraper runs entirely in your browser and is perfect for creating training data for AI models. It works by reading the website’s sitemap.xml file, making it particularly well-suited for modern platforms like Squarespace and Shopify that automatically generate sitemaps. The scraper preserves the structure of your content, including headings, paragraphs, lists, and tables,…
Even networks long considered “untrainable” can learn effectively with a bit of a helping hand. Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have shown that a brief period of alignment between neural networks, a method they call guidance, can dramatically improve the performance of architectures previously thought unsuitable for modern tasks. Their…
In this article, you will learn five practical prompt compression techniques that reduce tokens and speed up large language model (LLM) generation without sacrificing task quality. Topics we will cover include: What semantic summarization is and when to use it How structured prompting, relevance filtering, and instruction referencing cut token counts Where template abstraction fits…
Time to get philosophical, because why not? At the core of this cheeky question, “Is AI better than bacon?” lies a deeper inquiry: What do we value more, the power of the mind or the pleasures of the flesh (the delicious, smoked flesh of a pig in this case)? It’s a classic brain-vs-belly showdown, Socrates…