explain

In high-stakes settings like medical diagnostics, users often need to know what...

A couple of decade ago, artificial intelligence was split between image recognition and language understanding. Vision models could spot objects but couldn’t describe them, and language models generate text but couldn’t “see.” Today, that...

When there are more features than model dimensionsIt could be ideal if the world of neural network represented a one-to-one relationship: each neuron prompts on one and just one feature. In such a world,...

Machine-learning models could make mistakes and be difficult to make use of,...

OpenAI has released a framework for training large language models (LLMs) to have the ability to clarify things to users. It features the introduction of the previously introduced ‘game theory’ to elaborate the reasons...

Explaining the behavior of trained neural networks stays a compelling puzzle, especially...

As you may see, vector embeddings are pretty cool.Let’s return to our example and say we embed the content of each book within the library and store these embeddings in a vector database. Now,...

As you may see, vector embeddings are pretty cool.Let’s return to our example and say we embed the content of each book within the library and store these embeddings in a vector database. Now,...