The Dreamie is refreshingly compact, too. It takes up significantly less real estate on my nightstand than the Philips Wake-Up Light I've been using forever, or something like a Hatch Restore. The smaller footprint is something I appreciate as a person always battling cluttered surfaces. That also makes it better for travel. Since podcasts and sleep insights aren't available yet, I haven't been able to test those out, but they're non-critical features for me. The company has shared an estimated timeline of Q1-Q2 for these features to arrive, with podcasts likely coming first. They'll be nice to have, podcasts especially, but the Dreamie is more than able to do its main job of creating an environment that supports better sleep without those things.
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Writesonic is a free, easy-to-use AI content generator. The software is designed to help you create copy for marketing content, websites, and blogs. It's also helpful for small businesses or solopreneurs who need to produce content on a budget.
Around this time, my coworkers were pushing GitHub Copilot within Visual Studio Code as a coding aid, particularly around then-new Claude Sonnet 4.5. For my data science work, Sonnet 4.5 in Copilot was not helpful and tended to create overly verbose Jupyter Notebooks so I was not impressed. However, in November, Google then released Nano Banana Pro which necessitated an immediate update to gemimg for compatibility with the model. After experimenting with Nano Banana Pro, I discovered that the model can create images with arbitrary grids (e.g. 2x2, 3x2) as an extremely practical workflow, so I quickly wrote a spec to implement support and also slice each subimage out of it to save individually. I knew this workflow is relatively simple-but-tedious to implement using Pillow shenanigans, so I felt safe enough to ask Copilot to Create a grid.py file that implements the Grid class as described in issue #15, and it did just that although with some errors in areas not mentioned in the spec (e.g. mixing row/column order) but they were easily fixed with more specific prompting. Even accounting for handling errors, that’s enough of a material productivity gain to be more optimistic of agent capabilities, but not nearly enough to become an AI hypester.。业内人士推荐搜狗输入法2026作为进阶阅读