At $89.99, the latest Go is the most affordable Polaroid camera available, with film that costs just a little more than Fujifilm’s Instax Mini shots (a 16-sheet pack runs $21.99). The new Go sports a few upgrades over the last-gen model, including USB-C support, and Polaroid claims the camera produces clearer stills than its predecessor. Photos are slightly brighter, though the original Go produced warmer images that felt more true to life. Still, the photos are charming in the way only a Polaroid photo can be. Contrast and color saturation levels are still low, but in a way that exudes the vintage, almost dreamy look of the photos taken with the Flip.
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As a data scientist, I’ve been frustrated that there haven’t been any impactful new Python data science tools released in the past few years other than polars. Unsurprisingly, research into AI and LLMs has subsumed traditional DS research, where developments such as text embeddings have had extremely valuable gains for typical data science natural language processing tasks. The traditional machine learning algorithms are still valuable, but no one has invented Gradient Boosted Decision Trees 2: Electric Boogaloo. Additionally, as a data scientist in San Francisco I am legally required to use a MacBook, but there haven’t been data science utilities that actually use the GPU in an Apple Silicon MacBook as they don’t support its Metal API; data science tooling is exclusively in CUDA for NVIDIA GPUs. What if agents could now port these algorithms to a) run on Rust with Python bindings for its speed benefits and b) run on GPUs without complex dependencies?
从项目实质来看，此次扩产并非新建主体，而是对公司控股子公司广芯微的现有业务进行产能扩容，核心是提升高压、大功率功率半导体的代工能力。按照公司披露，核心项目达产后将新增月产6万片的代工能力，产品覆盖高压IGBT、特高压VDMOS、700V高压BCD等主流品类。