Why do artificial neurons use a bias term? Shouldn't only using weights be enough?
Yes, only using weights is sufficient for an Artificial Neural Network (ANN) to perform its task. However, there are cases where biases can be useful.

Biases in ANNs can help to promote the activation of certain nodes and suppress the activations of others, leading to improved generalization performance and reducing overfitting. BiasedANNs have also been shown to improve network stability by preventing oscillations and reducing the likelihood of convergence to local minima.

In summary, while using only weights is often sufficient for ANNs, biases may be necessary in some situations to achieve better results or prevent issues such as instability and overfitting.