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Big tech moves on a different timescale than the news cycle wants you to believe. What looks like a product launch is usually the public surface of an organizational bet made eighteen months earlier.

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Daft in Production: A Hard-Nosed Multimodal Pipeline Review Against Ray Data and Spark

Why We Evaluated Daft for Multimodal Pipelines The question that pushed us toward Daft was not whether it could perform another Parquet scan. We needed to know whether it could move compressed images, audio, PDFs, and video through CPU decoding and GPU inference without forcing us to hand-manage every intermediate batch. That is a materially different problem from conventional analytics. A JPEG may expand by roughly 20 times when decoded. A video can turn into thousands of multi-megabyte frames. The engine must overlap object-storage reads, decoding, preprocessing, inference, and output while keeping expanded objects from accumulating in memory. Daft approaches this as a declarative DataFrame engine with native multimodal expressions. Its Swordfish execution layer streams batches between operators and applies backpressure when a downstream operation, such as GPU inference, cannot keep up. Flotilla extends that execution model across workers. The practical appeal is straightforward: retain DataFrame and SQL-style planning while avoiding the partition-sized materialization that makes binary-heavy pipelines painful. We compared that model with two realistic alternatives: Ray Data, where resource-aware Python operators, actors, and independent CPU/GPU scaling offer considerable control, but partitioning, column retention, actor concurrency, and object-store pressure can become application responsibilities. Spark, which remains the operational default in many companies but exposes awkward global controls for Python and Arrow UDF batches. Those controls are especially blunt when one stage handles compressed bytes and another holds decoded tensors. We used the September 2025 distributed benchmark as the common reference point: Daft 0.6.2, Ray Data 2.49.2, and AWS EMR Spark 7.10.0 on eight g6.xlarge workers. The workload set covered 113,800 audio files with Whisper-tiny, 10,000 PDFs with all-MiniLM-L6-v2, 803,580 ImageNet images with ResNet18, and 1,000 videos with YOLO11n.

dev.to

Android is the best and worst thing about Googlebooks

I’ve been testing two Googlebooks: this Asus model, and HP’s too. My first week with the new Android-powered laptops has been about as rocky as anyone's, but I've slowly learned to like them, even if love still feels a ways off. Every moment that's impressed me has been thanks to Android, whether I've been accessing a native version of a useful app or quickly checking my phone notifications from the laptop user interface. But man, sometimes it just sucks. Phone connectivity is flaky, app casting is awkward, and file-sharing seems to be flat-out broken. And that's just the interaction between a Googlebook and a phone - I have a whole other set of gripes about the limitations of native Android apps on a $ … Read the full story at The Verge.

theverge.com

Meta says Muse Wonder is available to Muse app subscribers, via Meta Model API, and Muse Code; Wonder Full is available to Muse Code subscribers (Jonathan Vanian/CNBC)

Jonathan Vanian / CNBC: Meta says Muse Wonder is available to Muse app subscribers, via Meta Model API, and Muse Code; Wonder Full is available to Muse Code subscribers — Meta debuted its latest artificial intelligence model, Muse Wonder, and says it's the most advanced option for powering digital assistants.

techmeme.com

The OnePlus 16 is the company’s most interesting phone in years

Today the OnePlus 16 launched in China, the company's first flagship phone since quitting both the US and European markets this summer. As luck would have it, it also looks like the company's best phone in some time. Like most OnePlus phones, the 16 is positioned around performance, with a Snapdragon 8 Elite Extreme Gen 6 chipset, and up to 1TB of storage and 16GB of RAM. That's backed up by an enormous 9,000mAh silicon-carbon battery, one of the biggest seen in any Android flagship yet. 100W wired and 50W wireless charging complete the power setup. On the display front, the phone jumps to a 185Hz OLED panel for the first time. That'll no … Read the full story at The Verge.

theverge.com

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