We present an adaptive scheduler for a single differencing engine (SmartDiff) with two execution modes: (i) in-memory threads and (ii) Dask based parallelism. The scheduler continuously tunes batch size and worker/thread count within fixed CPU and memory budgets to minimize p95 latency. A lightweight preflight profiler estimates bytes/row and I/O rate; an online cost/memory model prunes unsafe actions; and a guarded hill-climb policy favors lower latency with backpressure and straggler mitigation. Backend selection is gated by a conservative working-set estimate so that in-memory execution is chosen when safe, otherwise Dask is used. Across synthetic and public tabular benchmarks, the scheduler reduces p95 latency by 23 to 28 percent versus a tuned warm-up heuristic (and by 35 to 40 percent versus fixed grid baselines), while lowering peak memory by 16 to 22 percent (25 to 32 percent vs. fixed) with zero OOMs and comparable throughput.

The flight time of multirotor unmanned aerial vehicles (UAVs) is typically constrained by their high power consumption. Tethered power systems present a viable solution to extend flight times while maintaining the advantages of multirotor UAVs, such as hover capability and agility. This paper addresses the critical aspect of cable selection for tether-powered multirotor UAVs, considering both hover and forward flight. Existing research often overlooks the trade-offs between cable mass, power losses, and system constraints. We propose a novel methodology to optimize cable selection, accounting for thrust requirements and power efficiency across various flight conditions. The approach combines physics-informed modeling with system identification to combine hover and forward flight dynamics, incorporating factors such as motor efficiency, tether resistance, and aerodynamic drag. This work provides an intuitive and practical framework for optimizing tethered UAV designs, ensuring efficient power transmission and flight performance. Thus allowing for better, safer, and more efficient tethered drones.

EC2 (Elastic Compute Cloud) is the most widely-used compute service from AWS. It's also one of the oldest services launched by AWS, as it was started in 2006. In this article, I will go through some things you should consider when selecting an EC2 instance. You can think of an EC2 instance as not too different from your personal computer. These three questions should also cross your mind when selecting an EC2 instance. The difference being, you are only renting the instance from AWS, instead of buying it as you would with a personal computer.

During the pandemic, virtual conferences became the actual methodology of collaborating and connecting. It was each within and outdoors of the geographical point. A 2020 IDC report projected that the videoconferencing market would grow to $9.7 billion in 2021. And it will grow within ninetieth of North yank businesses. However in an associate degree interview with TechCrunch, the inexperienced argued that videoconferencing because it exists for many corporations nowadays.

Julian Green was explaining the big problem with meetings when our meeting started to glitch. A sentence came out as hiccups. Then he sputtered, froze, and ghosted. Green and I had been chatting on Headroom, a new video conferencing platform he and cofounder Andrew Rabinovich launched this fall. The glitch, they assured me, was not caused by their software, but by Green's Wi-Fi connection.

Videoconferencing has become a cornerstone of how many of us work these days -- so much so that one leading service, Zoom, has graduated into verb status because of how much it's getting used. But does that mean videoconferencing works as well as it should? Today, a new startup called Headroom is coming out of stealth, tapping into a battery of AI tools -- computer vision, natural language processing and more -- on the belief that the answer to that question is a clear -- no bad Wi-Fi interruption here -- "no." Headroom not only hosts videoconferences, but then provides transcripts, summaries with highlights, gesture recognition, optimised video quality and more, and today it's announcing that it has raised a seed round of $5 million as it gears up to launch its freemium service into the world. You can sign up to the waitlist to pilot it, and get other updates here. The funding is coming from Anna Patterson of Gradient Ventures (Google's AI venture fund); Evan Nisselson of LDV Capital (a specialist VC backing companies building visual technologies); Yahoo founder Jerry Yang, now of AME Cloud Ventures; Ash Patel of Morado Ventures; Anthony Goldbloom, the co-founder and CEO of Kaggle.com; and Serge Belongie, Cornell Tech associate dean and professor of Computer Vision and Machine Learning. It's an interesting group of backers, but that might be because the founders themselves have a pretty illustrious background with years of experience using some of the most cutting-edge visual technologies to build other consumer and enterprise services.