The joint progress of artificial neural networks (ANNs) and domain specific hardware accelerators such as GPUs and TPUs took over many domains of machine learning research. This development is accompanied by a rapid growth of the required computational demands for larger models and more data. Concurrently, emerging properties of foundation models such as in-context learning drive new opportunities for machine learning applications. However, the computational cost of such applications is a limiting factor of the technology in data centers, and more importantly in mobile devices and edge systems. To mediate the energy footprint and non-trivial latency of contemporary systems, neuromorphic computing systems deeply integrate computational principles of neurobiological systems by leveraging low-power analog and digital technologies. SpiNNaker2 is a digital neuromorphic chip developed for scalable machine learning. The event-based and asynchronous design of SpiNNaker2 allows the composition of large-scale systems involving thousands of chips. This work features the operating principles of SpiNNaker2 systems, outlining the prototype of novel machine learning applications. These applications range from ANNs over bio-inspired spiking neural networks to generalized event-based neural networks. With the successful development and deployment of SpiNNaker2, we aim to facilitate the advancement of event-based and asynchronous algorithms for future generations of machine learning systems.

Two teams of forensic linguists have been working to track down the identity of Q, an anonymous writer claiming to be a government insider who has been fueling the conspiracy movement QAnon since 2017. The teams have used a machine learning program to identify two men as the potential origin of Q. This research was publicized in a New York Times report Saturday, and named South African software developer Paul Furber as the most likely person behind the very first Q posts. They also alleged that Furber collaborated with Ron Watkins to compose messages under the pseudonym. Furber and Watkins were already known as prominent figures in the movement before this material was released, and Watkins recently announced his intent to run for Congress in Arizona.

With help from machine learning software, computer scientists may have unmasked the identity of Q, the founder of the QAnon movement. In a sprawling report published on Saturday, The New York Times shared the findings of two independent teams of forensic linguists who claim they've identified Paul Furber, a South African software developer who was one of the first to draw attention to the conspiracy theory, as the original writer behind Q. They say Arizona congressional candidate Ron Watkins also wrote under the pseudonym, first by collaborating with Furber and then later taking over the account when it eventually moved to post on his father's 8chan message board. The two teams of Swiss and French researchers used different methodologies to come to the same conclusion. The Swiss one, made up of two researchers from startup OrphAnalytics, used software to break down Q's missives into patterns of three-character sequences.

YOU ARE MY SEDUCTIVE SYMPATHY. This was one of a number of enigmatic notes pinned to the computing department noticeboard at the University of Manchester, UK, back in August 1953. There was no great mystery about "MUC", however: that could only be "Manchester University Computer", the world's first commercial programmable electronic computer. Designed to work on atomic bombs, X-ray crystallography and other serious science, what business had this Ferranti Mark 1 writing love letters? The answer, of course, was a gifted, under-occupied programmer.

In this paper, we describe an interactive environment for the representation, interpretation, and revision of explanatory biological models. We illustrate our approach on the systems biology of aging, a complex topic that involves many interacting components, and discuss our experiences using this environment to codify an informal model of aging. We close by discussing related efforts and directions for future research.