Neuromorphic computing shows promise for advancing computing efficiency and capabilities of AI applications using brain-inspired principles. However, the neuromorphic research field currently lacks standardized benchmarks, making it difficult to accurately measure technological advancements, compare performance with conventional methods, and identify promising future research directions. This article presents NeuroBench, a benchmark framework for neuromorphic algorithms and systems, which is collaboratively designed from an open community of researchers across industry and academia. NeuroBench introduces a common set of tools and systematic methodology for inclusive benchmark measurement, delivering an objective reference framework for quantifying neuromorphic approaches in both hardware-independent and hardware-dependent settings. For latest project updates, visit the project website (neurobench.ai).

We demonstrate a Ti₃C₂T_xMXene coated textile supercapacitor configured as five cells stacked in series with a high operating potential range of 6 V, capable of real time operation of a wireless sensor for over 90 minutes.

Today’s electronics are manufactured to provide stable functionality and fixed physical forms optimized for reliable operation over long periods and repeated use. However, even when applications don’t call for such robustness, the permanency of these electronics comes with environmental consequences. In this paper, we describe an alternative approach that utilizes sustainable transient electronics whose method of destruction is also key to their functionality. We create these electronics through three different methods: 1) by inkjet printing conductive silver traces on poly(vinyl alcohol) (PVA) substrates to create water-soluble sensors; 2) by mixing a conductive beeswax material configured as a meltable sensor; and 3) by fabricating edible electronics with 3D printed chocolate and culinary gold leaf. To enable practical applications of these devices, we implement a fully transient and sustainable chipless RF detection system.

As voice assistant usage continues to grow, their homogeneity becomes even more problematic with the UNESCO report, “I’d Blush if I could” showing that designing only feminine voice assistants encourages negative behavior, both with virtual assistants and with real people [3]. While masculine text-to-speech (TTS) voices exist, ones that cover the full range of gender presentations, such as non-binary or gender-ambiguous voices are largely missing. In this paper, we present a method of creating a non-binary TTS voice and an example voice, Sam, created with input from the non-binary and transgender communities. We have open-sourced the resulting voice, along with the process and data used to create it. Finally, we present results from a large-scale survey showing that non-binary individuals are more likely to prefer a non-binary voice assistant compared to cisgendered individuals and discuss differences across age and gender.