 The controversy between radical and implementational connectionists is complicated by the invention of what are called hybrid connectionist architectures. Here elements of classical symbolic processing are included in neural nets (Wermter &amp; Sun 2000). For example, Miikkulainen (1993) champions a complex collection of neural net modules that share data coded in activation patterns. Since one of the modules acts as a memory, the system taken as a whole resembles a classical processor with separate mechanisms for storing and operating on digital “words”. Smolensky (1990) is famous for inventing so called tensor product methods for simulating the process of variable binding, where symbolic information is stored at and retrieved from known “locations”. More recently, Eliasmith (2013) has proposed complex and massive architectures that use what are called semantic pointers, which exhibit features of classical variable binding. Once hybrid architectures such as these are on the table, it becomes more difficult to classify a given connectionist model as radical or merely implementational. This opens the interesting prospect that whether symbolic processing is actually present in the human brain may turn out to be a matter of degree.