Counting years backwards unlocks faster speed. The first date algorithm to use only 4 multiplications, instead of 7+

A diabetes medication that lowers brain fluid pressure has cut monthly migraine days by more than half

From desktop to datacenter: how Scaleway turns Apple's Mac mini into a fully managed, high-performance cloud server for macOS and iOS developers.

Now is a great time to join Optery. Optery is profitable, and we 3x-ed sales last year. Our product was awarded “Editors’ Choice” by PCMag as the most outstanding in the personal data removal category for the 4th year in a row (2022 - 2025), Optery was ranked the #1 most effective of all personal data removal services tested in 2024 study by Consumer Reports, Optery was named one of Business Insider’s Top 30 Future Unicorns of 2025, and we’re changing the game in the world of consumer data in a way that puts individuals in control. Optery is automated opt out software, and we serve individuals, families and businesses. Our mission is to empower people to take control of their personal data, and we have a vision for a safer world through data privacy. Hundreds of thousands of people rely on Optery to prevent attacks and keep their personal information off the Internet. Optery has raised $9M+ in funding from world-class investors such as Y Combinator, Alumni Ventures, Bayhouse Capital, Flex Capital, Global Founders Capital, Goodwater Capital, Pioneer Fund, Soma Capital, TRAC, Tribe Capital, and Uncorrelated Ventures. Optery is headquartered in the San Francisco Bay Area, but operates as a fully-remote global team.

Yet again, another global IT outage happen (deja vu strikes again in our industry). This time at cloudflare(Prince 2025). Again, taking down large swats of the internet with it(Booth 2025). And yes, like my previous analysis of the GCP and CrowdStrike’s outages, this post critiques Cloudflare’s root cause analysis (RCA), which — despite providing a great overview of what happened — misses the real lesson. Here’s the key section of their RCA:

Read this for a breakdown of new runC CVEs, their exploitability, affected versions, and how to patch and mitigate.

A burning platform

Qiskit is an open-source SDK for working with quantum computers at the level of extended quantum circuits, operators, and primitives. - Qiskit/qiskit

I am sorry, brethren, for I have failed our craft, and disappointed those who have placed their trust in me. Today, after 15 years, I finall...

The newly described microbe represents a world of parasitic, intercellular biodiversity only beginning to be revealed by genome sequencing.

We’re excited to announce that Kagi Hub Belgrade ( https://hub.kagi.com ) is now open! Our first office doubles as a free coworking space for all Kagi members.

Is DWPD still a valid SSD endurance metric—or marketing smoke? We break down what it means, what it hides, and what to trust instead.

Python’s async model is misunderstood, especially by engineers coming from JS or C#. In Python, awaiting a coroutine doesn’t yield to the event loop. Only tasks create concurrency. This post explains why that distinction matters and how it affects locking, design, and correctness.

Image diffusion models, though originally developed for image generation, implicitly capture rich semantic structures that enable various recognition and localization tasks beyond synthesis. In this work, we investigate their self-attention maps can be reinterpreted as semantic label propagation kernels, providing robust pixel-level correspondences between relevant image regions. Extending this mechanism across frames yields a temporal propagation kernel that enables zero-shot object tracking via segmentation in videos. We further demonstrate the effectiveness of test-time optimization strategies-DDIM inversion, textual inversion, and adaptive head weighting-in adapting diffusion features for robust and consistent label propagation. Building on these findings, we introduce DRIFT, a framework for object tracking in videos leveraging a pretrained image diffusion model with SAM-guided mask refinement, achieving state-of-the-art zero-shot performance on standard video object segmentation benchmarks.

Your online textbook for learning reliability and six sigma techniques in R and Python! Made for Cornell University Course SYSEN 5300.