PCWorld reports that Canva's new Magic Layers AI feature converts images into editable templates, allowing users to modify text, remove objects, and edit individual elements within photos. The tool poses significant disinformation risks by enabling easy manipulation of news content while preserving credible visual elements like logos and matching original fonts seamlessly. Magic Layers requires a Canva Pro subscription and can make AI-generated fake content appear more polished than originals, complicating detection efforts. I know that there is indeed something good and useful about Canva's Magic Layers tool, which uses AI to transform an image into an editable template. But all I can think of it is how people can and will use it for nefarious purposes. Canva's Magic Layers tool was launched last week .

New silicon technology is enabling large-scale electrophysiological recordings in vivo from hundreds to thousands of channels. Interpreting these recordings requires scalable and accurate automated methods for spike sorting, which should minimize the time required for manual curation of the results. Here we introduce KiloSort, a new integrated spike sorting framework that uses template matching both during spike detection and during spike clustering. KiloSort models the electrical voltage as a sum of template waveforms triggered on the spike times, which allows overlapping spikes to be identified and resolved. Unlike previous algorithms that compress the data with PCA, KiloSort operates on the raw data which allows it to construct a more accurate model of the waveforms. Processing times are faster than in previous algorithms thanks to batch-based optimization on GPUs. We compare KiloSort to an established algorithm and show favorable performance, at much reduced processing times. A novel post-clustering merging step based on the continuity of the templates further reduced substantially the number of manual operations required on this data, for the neurons with near-zero error rates, paving the way for fully automated spike sorting of multichannel electrode recordings.

In these frameworks, templates are constructed using an iterative process of template estimation and alignment, which is often computationally very expensive. Due in part to this shortcoming, most methods compute asingle template for the entire population of images, or a few templates for specific sub-groups of the data.

A.1 Data sources We describe the full license of the original datasets and the URL for download.

Among potential attacks against FR systems [Galbally et al., 2014, Biggio et al., 2015, Hadid et al., 2015, Mai et al., 2018, Marcel et al., 2023], the template inversion (TI) attack significantly jeopardizes the users' privacy. In a TI attack, the adversary gains access to templates stored in the FR system's database and aims

LLMs with improved chemical reasoning capabilities in the other two sub-tasks.

Empirical results show consistent and significant performance gains afforded by a singleround structurization.

However, many previous works studied textual and relational retrieval tasks as separate topics.