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Hey guys, I built a controller diagnostics tool last night - runs right in the browser, no install. Test polling rate & Latency (Any Controller) Stick Circularity & Drift (PS & Marius) Full DualSense support: recenter sticks, range-calibrate, lightbar & more Link to Github👇

27,440 görüntüleme • 3 ay önce •via X (Twitter)

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[New Xbox Controller Review] #ad Special thanks to Qrdgame_offcial for supplying me with a review unit of their Ferrox M5 Xbox & PC Controller QRD Ferrox M5 The QRD Ferrox M5 is a Wireless Xbox One–style gamepad with a transparent design. Since it targets Xbox One natively, it works automatically on PC and Xbox Series S/X. The included 2.4Ghz USB Dongle also supports Switch and Android with the right adapter (USB C), but I was not able to test those in time for this review. A Wireless Xbox Controller The QRD FERROX M5 comes in a familiar Xbox layout with Hall Effect joysticks, RGB rings around the sticks, and a magnetic & detachable clear shell that shows the internals. The controller feels very similar to a standard Xbox pad in terms of shape and size, but it’s slightly lighter at compared to the usual Xbox controller weight. The lighter weight makes it easier to hold for longer sessions without hand fatigue. The D-Pad is surprisingly good at dialing special moves feels as solid and responsive as the official Xbox controller, and that’s impressive at a lower price point. I spent a few days trying out the Mortal Kombat Legacy Kollection exclusively using this controller and I did not notice any difference at all. Capabilities From what I’ve tested, the controller performs extremely well for action games, fighting games, and shooters. The Hall Effect joysticks offer smooth movement and precise control with no drift issues. The D-Pad uses micro switches, so every input is tactile and accurate. The back triggers support an adaptive “trigger stop” mode, which shortens the travel distance for faster reaction time in FPS games or quicker blocks in Fighting Games. You also get 4 back macro buttons, turbo mode, and adjustable joystick sensitivity with deadzone options. Vibration strength and RGB lighting modes are also customizable. What can it do The FERROX M5 includes an 800mAh battery that lasts around 8 hours of gameplay. It only uses the 2.4Ghz wireless connection, not Bluetooth, so it always requires the included USB Dongle. The good thing is once you sync it with your Xbox or PC, you don’t need to sync it again—it carries over between both devices automatically. The 2.4G connection is stable and low latency, and the controller has a 3.5mm headphone jack for audio and mic support. It also features a quick calibration system to keep sticks and triggers accurate over time. The overall grip and shape feel close to the official Xbox controller, comfortable for long gaming sessions, and the transparent shell gives it a distinct look. Areas of improvement I initially had trouble charging the controller while playing because connecting it to the Xbox via USB would disable all inputs, making it unusable in wired mode. But luckily QRD Support helped and provided me with an updat - I had to connect it to a PC, download the firmware tool from QRD’s website, and update the controller manually. After installing the new firmware, the controller can now charge while being used normally on Xbox, so the issue is fully resolved. The Xbox button also behaves differently on Xbox, where the single press acts like hold and the hold acts like single press; this issue doesn’t appear on PC. Syncing with the dongle took a few attempts on both Xbox and PC, but once paired, it never needed syncing again. The wireless mode is strictly 2.4G with no Bluetooth support, so it cannot connect without the dongle, though the benefit is that one pairing works across both Xbox and PC. Final Summary ✅ Hall Effect Joystick ✅ Lights in the dark ✅ Good D-Pad for input dialing ✅ Light Controller ❌ First sync can be annoying on PC ❌ No bluetooth for phone usage - Dongle is necessary ❌ Needs an update for the Xbox Wired issues which require a PC The Controller is available on Amazon for $59.99, and will be part of the Black Friday Deals on their official website for even more discount! Amazon Link Website Link

thethiny 🐰🍉

16,864 görüntüleme • 9 ay önce

I built a macOS app for benchmarking local LLMs. 6 test suites. Multiple providers. One workspace. Open source. There are hundreds of local models now. New ones every week. How do you actually pick one? Leaderboards test for general ability. But if you're building an agent that chains tool calls, or a pipeline that extracts structured data, or a code assistant that needs to debug Rust, you need to know if the model handles that specific thing. Not in theory. On your hardware. With your prompts. The benchmarks that exist are either locked behind papers, too abstract to map to real failures, or impossible to extend. You can't add your own test cases. You can't test what matters to your use case. That's what BenchLocal is for. It's a benchmark platform where every test is practical, deterministic, and built around real-world tasks. And you can build your own tests. It ships with 6 Bench Packs TODAY: → ToolCall-15 — tool-use accuracy → BugFind-15 — debugging capabilities → DataExtract-15 — structured data extraction → InstructFollow-15 — constraint-heavy instruction following → ReasonMath-15 — practical reasoning and math → StructOutput-15 — validator-backed structured output Every pack has 15 fixed scenarios. Every score is deterministic and verifiable. Some of you saw ToolCall-15 and BugFind-15 — the individual test packs I open-sourced over the past few weeks. People ran them, filed issues, sent PRs. But managing separate repos, separate scripts, separate results doesn't scale. BenchLocal puts everything in one place. What the app does: > Workspace with tabs — run BugFind-15 in one tab, ToolCall-15 in another. > Any provider — Ollama, llama.cpp, OpenRouter, any OpenAI-compatible endpoint. Local and cloud, same interface. > Run modes — serial, batch per model, batch per test case, or fully parallel. > Test histories — every run saved. Compare any previous session. But the part I'm most excited about isn't the app. It's the ecosystem. BenchLocal is a platform. Each Bench Pack is a plugin. I'm shipping an SDK so anyone can build their own — test what matters to you, package it, share it. Install and uninstall packs right inside the app, same way you'd manage extensions in VS Code. The registry is GitHub-based, fully public. I built 6 packs. I want the community to build the next 60. Theme system built in too — because if I'm staring at benchmark results for hours, it should at least look good. v0.1.0 is macOS only. Windows and Linux are coming. MIT licensed. Everything — the app, the bench packs, the SDK — is open. PRs welcome. Bench Packs even more welcome.

stevibe

50,584 görüntüleme • 4 ay önce

Let's reverse engineer Disney's adorable, lifelike robot! I couldn't find a whitepaper, but this is how I think it's trained: 1. The emotional behaviors are curated by Disney animation artists, keyframe by keyframe. But it cannot be "rendered" directly on the robot because it doesn't take into account the complex real-world physics. 2. Reinforcement learning (RL) is a great tool for training low-level robot controllers. RL needs a reward function to optimize, and it's typically a task reward (e.g. walk in a straight line as fast as possible). The problem is that RL doesn't know what counts as "natural behavior", and often produces weird-looking body postures that somehow still maximize the reward. This is a human alignment problem just like ChatGPT. 3. Enters Adversarial Motion Prior (AMP): a technique that learns the human preference by training a classifier on what we consider "emotional & cute". In GAN literature, this is called a discriminator. Disney artists are good at creating such a dataset. You can then add AMP as an auxiliary reward in simulation to nudge the robot towards desired behaviors. AMP was developed by Peng et al. 2021 and Escontrela et al. 2022. 4. Add lots of data augmentation to make the controller robust to physical disturbances. In RL, it's called "domain randomization". This is a very powerful technique that bridges the gap between simulator and reality. Previously, OpenAI used domain randomization to train a 5-finger robot hand to manipulate a Rubik's Cube: IEEE news article gave hints about the pipeline: Finally, praying for world peace 🙏. I hope robotics like this will bring more joy to the world.

Jim Fan

314,694 görüntüleme • 2 yıl önce

Introducing PhoneLLM, an open model for voice agents. GPT 5.6 Terra performance on typical voice agent tasks at 1/3 the latency and 1/18 the cost. For voice agents, we need models that are both very low latency and very good at tool calling and instruction following. There's a trade-off here, and we often have to compromise on either latency or capability when building voice agents. With PhoneLLM (and the training and data stack that made this model possible) we're fixing this problem. For the last couple of years, most of the effort in frontier model development has gone towards leveraging test-time compute. Which is awesome! Models of all shapes and sizes are available that perform really, really well ... if you have "thinking" turned on for your model. But if you need your agent to respond at voice conversation speed, you can't use thinking models. PhoneLLM is a full-weights fine-tune of NVIDIA Nemotron Nano 30B. We trained on a wide range of real-world telephone and customer support use cases. The training focused on taking the excellent Nano 30B base capabilities and teaching the model to do typical voice agent tasks with thinking disabled. The results are really good: accurate tool calling and concise, on-topic responses in long conversations. And fast: TTFAT measured server-side is <100ms if you run PhoneLLM on a lightly loaded B200. :-) But seriously, when we characterize model latency, we do it with full, end-to-end, batched request simulations using real Pipecat voice agent pipelines. You can serve more than 80 concurrent agents on a single B200 with P95 end-to-end TTFAT <600ms. Including network overhead. That's an LLM cost-per-minute around $0.0025. (1/4 of a cent.) At a latency lower than any third-party API offers today. More details about this model, including weights on Hugging Face, how to spin it up with one click on Modal, and a starter project repo you can clone, are in the thread ...

kwindla

314,586 görüntüleme • 3 gün önce

M64 is to the Nintendo 64 what the iPhone was to the 3310 Developed by ModRetro, the M64 is presented as the ultimate alternative to the original hardware, featuring the most advanced components on the market and the highest-quality finish that enhances every little detail of the system you remember. Presented in packaging with a ’90s aesthetic, this console comes in a dual-textured plastic case (frosted translucent in any of the five available colors or clear). It’s capable of playing original cartridges, reproductions, backups, homebrew, and, of course, remastered releases and new titles from ModRetro. Through its HDMI output, it supports resolutions of 720p, 1080p, 1440p, and 4K, as well as displaying images at their original resolution on a CRT TV via its own adapter. As you’d expect, the system has no region lock, so you can enjoy your NTSC-USA, NTSC-JAP, and PAL-EUR cartridges like never before. Additionally, both the Expansion Pak and—coming soon—the Controller Pak are emulated by the console, ensuring that the entire original catalog is available in the best possible quality. Its architecture is open-source, easy to disassemble, with no degradable electronics, and gold-plated traces and connectors that ensure optimal preservation of the system over the years. Of course, just like with the Chromatic, its firmware is updatable via Wi-Fi or USB cable, and it features a front-end menu that allows, among other things, for detailed on-the-fly customization of resolutions and filters, as well as the implementation of different overclocking levels that take the 64-bit experience to unprecedented heights. And I can’t forget one of its main selling points: the Pro Controller. A controller that stays true to the original form factor but incorporates improved ergonomic solutions, a ceramic-coated aluminum finish, high-end PBT crystalline polymer buttons, and a state-of-the-art TMR joystick coated in soft polymer and free of any drift; which offers a wider travel range, with four levels of spring tension and a greater degree of tilt, achieving unbeatable precision with no dead zones. Additionally, the stick gates are interchangeable, allowing you to customize your experience by installing the classic octagonal, equidistant hexagonal, or circular models. It also features an ERM vibration motor. You can play with the controller connected via cable or wirelessly using Bluetooth 6.2, which reduces response latency to below 0.65 microseconds. It is powered by a rechargeable battery with a USB-C port or by two AA batteries housed in an included module. Like the console, its firmware is updatable and it’s available in the same colors. You can purchase the M64 for $229.99 and the Pro Controller separately (since the system supports your old N64 or third-party controllers) for $89.99. I can guarantee that with this new ModRetro ecosystem, you’ll not only dust off games you may not have touched in decades, but it will also serve as the perfect incentive to dive into one of the most interesting and iconic game libraries—featuring both single-player and multiplayer titles—with undeniable appeal.

Pre-Rendered Backgrounds Aesthetics

23,444 görüntüleme • 19 gün önce