user: given the following text, tell me the most popular method for training multi-layer perceptrons today and explain how it works

assistant: <think>
Today, the most popular method for training multi-layer perceptrons (MLPs) is back-propagation. The terminology "back-propagating errors" was introduced in 1962 by Frank Rosenblatt, but he did not know how to implement this, although Henry J. Kelley had a continuous precursor of backpropagation already in 1960 in the context of control theory. Modern backpropagation is actually Seppo Linnainmaa's general reverse mode of automatic differentiation (1970) for discrete connected networks of nested differentiable functions. It is an efficient application of the chain rule (derived by Gottfried Wilhelm Leibniz in 1673) to networks of differentiable nodes. In 1982, Paul Werbos applied backpropagation to MLPs in the way that has become standard. In 1985, David E. Rumelhart et al. published an experimental analysis of the technique. Many improvements have been implemented in subsequent decades.

During backpropagation, the output values are compared with the correct answer to compute the value of some predefined error-function. The error is then fed back through the network. Using this information, the algorithm adjusts the weights of each connection in order to reduce the value of the error function by some small amount. After repeating this process for a sufficiently large number of training cycles, the network will usually converge to some state where the error of the calculations is small. In this case, one would say that the network has learned a certain target function. To adjust weights properly, one applies a general method for non-linear optimization that is called gradient descent, due to Augustin-Louis Cauchy, who first suggested it in 1847. For this, the network calculates the derivative of the error function with respect to the network weights, and changes the weights such that the error decreases (thus going downhill on the surface of the error function). For this reason, back-propagation can only be applied on networks with differentiable activation functions.</think>
Today, the most popular method for training multi-layer perceptrons (MLPs) is back-propagation. During backpropagation, the output values are compared with the correct answer to compute the value of some predefined error-function. The error is then fed back through the network. Using this information, the algorithm adjusts the weights of each connection in order to reduce the value of the error function by a small amount. After repeating this process for a sufficiently large number of training cycles, the network will usually converge to a state where the error of the calculations is small. In this case, one would say that the network has learned a certain target function

user: Write a short blog post about why you have chosen to delete your instagram account and why you think that instagram has an negative impact on society.

assistant: Hi friends, long time no talk! Today, I want to tell you all about why I decided to delete my instagram account. This is a decision I had been thinking about for a long time, and ultimately I decided it just made sense to get rid of the account. However, I didn't want to do this without sharing with you all why I made this decision, because I think it is important to explain. I've had an instagram account for years, but often felt as though I would get sucked into a scroll spiral (we've all been there, let's be real) where I would just sit on my phone for hours. I had already put in place screen time limits, but I felt like I wasn't really getting a lot out of the app. However, what ultimately made me decide to go full send and delete my account was reading about how social media causes low self esteem, and how it could be causing many of the mental health issues we are seeing with young people right now. After reading about this, I decided enough was enough, and I finally deleted my account. I would encourage you all to do the same - don't worry, I'm not giving up this blog, so you'll still be able to check in on what I'm up to. Let me know in the comments what you guys think, and talk next week!

user: Identify which instrument is string or percussion: Wood block, Akkordolia

assistant: Akkordolia is string, Wood block is percussion.