Turn on the heating – from Hopfield networks to Boltzmann machines

In my recent post on Hopfield networks, we have seen that these networks suffer from the problem of spurious minima and that the deterministic nature of the dynamics of the network makes it difficult to escape from a local minimum. A possible approach to avoid this issue is to randomize the update rule. Intuitively, we want to … Continue reading Turn on the heating – from Hopfield networks to Boltzmann machines

On the road again – serializing and deserializing bitcoin transactions

In this post, I will show you how a bitcoin transaction presented in the raw format is to be interpreted and how conversely a bitcoin transaction stored in a C++ (and later Python) object can be converted into a hexadecimal representation (a process called serialization). Ultimately, the goal of this and subsequent posts will be … Continue reading On the road again – serializing and deserializing bitcoin transactions

The Ising model and Gibbs sampling

In the last post in the series on AI and machine learning, I have described the Boltzmann distribution which is a statistical distribution for the states of a system at constant temperature. We will now look at one of the most important applications of this distribution to an actual model, the Ising model. This model was proposed … Continue reading The Ising model and Gibbs sampling

Transactions in the bitcoin network

In my previous posts on the bitcoin protocol, I have described those objects that constitute participants - private and public keys and bitcoin addresses. Now we will look at those objects that represent actual transfers of bitcoins between these participants, namely at transactions. Essentially, a bitcoin transaction consists of two parts. First, a transaction contains … Continue reading Transactions in the bitcoin network