Show HN: Printnanny.ai, Monitoring for 3D Printers https://ift.tt/6dDlE4s

Show HN: Printnanny.ai, Monitoring for 3D Printers https://printnanny.ai/ May 17, 2023 at 06:39PM

Show HN: Generative wall art, running on a Raspberry Pi https://ift.tt/THctPMi

Show HN: Generative wall art, running on a Raspberry Pi https://twitter.com/adamfuhrer/status/1657070909469884429 May 17, 2023 at 06:36PM

Show HN: CounterDB, to persist your likes/dislikes counts https://ift.tt/QZdJMiY

Show HN: CounterDB, to persist your likes/dislikes counts A Solution to durably store your counts. For example number of likes/dislikes on a post. Its time complexity is O(1). Single header only C++ file for storing and retrieving numbers. It does this without increasing the file size, as its not append only DB. Which also means it can be slower on simultaneous writes to an index. Well if your task is just to store likes/dislikes counts, than it must not be much of a problem. As reads are done more than writes for such cases. https://ift.tt/pyZvdCe May 17, 2023 at 11:20AM

Show HN: A nihilist All-hands Meeting Simulator https://ift.tt/eI3YVhb

Show HN: A nihilist All-hands Meeting Simulator I was just digging through some old projects to find a link for a potential new employer and stumbled upon this reminder of how much I enjoyed middle-management office politics. https://ift.tt/8pxYCnJ May 17, 2023 at 05:03PM

Show HN: Zig Without Unused Variable Errors https://ift.tt/SenYPZt

Show HN: Zig Without Unused Variable Errors I hacked the flag --allow-unused into the Zig compiler to turn off the unused variable error. https://ift.tt/5DkfQ0x May 17, 2023 at 08:57AM

Show HN: Oblivus GPU Cloud – Affordable and scalable GPU servers from $0.29/hr https://ift.tt/xJyQzUD

Show HN: Oblivus GPU Cloud – Affordable and scalable GPU servers from $0.29/hr Greetings HN! This is Doruk from Oblivus, and I'm excited to announce the launch of our platform, Oblivus Cloud. After more than a year of beta testing, we're excited to offer you a platform where you can deploy affordable and scalable GPU virtual machines in as little as 30 seconds! https://ift.tt/rqkmaDT - What sets Oblivus Cloud apart? At the start of our journey, we had two primary goals in mind: to democratize High-Performance Computing and make it as straightforward as possible. We understand that maintaining GPU servers through major cloud service providers can be expensive, with hidden fees adding to the burden of running and maintaining servers. Additionally, the cloud can sometimes be overly complex for individuals who don't have much knowledge but still require powerful computing resources. That's why we decided to create a platform that offers affordable pricing, easy usability, and high-quality performance. - Features 1. Fully customizable infrastructure that lets you switch between CPU and GPU configurations to suit your needs. 2. Transparent and affordable per-minute-based Pay-As-You-Go pricing with no hidden fees. Plus, free data ingress and egress. (Pricing: https://ift.tt/lenH28i ) 3. Optimized cost with storage and IP address-only billing when the virtual machine is shut down. 4. Each virtual machine comes with 10Gbps to 40Gbps public network connectivity. 5. NVMe ($0.00011/GB/hr) and HDD ($0.00006/GB/hr) storage that is 3x replicated to fulfill your storage needs. 6. Choose from a variety of cutting-edge CPUs and 10 state-of-the-art GPU SKUs. (Availability: https://ift.tt/WKuFdow ) 7. OblivusAI OS images come with pre-installed ML libraries, so you can start training your models right away without the hassle of installing and configuring the necessary libraries. 8. If you're working with a team, utilize our organization feature to simplify the billing process. Everyone in your organization uses the same billing profile, so you don't need to keep track of multiple accounts. 9. No quotas or complex verification processes. Whether you represent a company, an institution, or you're a researcher, you have full access to our infrastructure without any limitations. 10. Easy-to-use API with detailed documentation so that you can integrate your code with ours. - Pricing At Oblivus Cloud, we provide pricing that is affordable, transparent, and up to 80% cheaper than major cloud service providers. Here is a breakdown of our pricing: 1. CPU-based virtual machines starting from just $0.019/hour. 2. NVIDIA Quadro RTX 4000s starting from $0.27/hour. 3. Tesla V100s starting from $0.51/hour. 4. NVIDIA A40s and RTX A6000s starting from $1.41/hour. We also offer 6 other GPU SKUs to help you accurately size your workloads and only pay for what you need. Say goodbye to hidden fees and unpredictable costs. If you represent a company, be sure to register for a business account to access even better pricing rates. - Promo Code Join us in celebrating the launch of Oblivus Cloud by claiming your $1 free credit! This may sound small, but it's enough to get started with us and experience the power of our platform. With $1, you can get over 3 hours of computing on our most affordable GPU-based configuration, or over 50 hours of computing on our cheapest CPU-based configuration. To redeem this free credit, simply use the code HN_1 on the 'Add Balance' page after registration. Register now at https://ift.tt/SyDr7Zo - Quick Links Website: https://oblivus.com/ Console: https://ift.tt/ZPazprH Company Documentation: https://ift.tt/1PJnmrg API Documentation: https://ift.tt/fWgxAcl If you have any questions, feel free to post them below and I'll be happy to assist you. You can also directly email me at doruk@oblivus.com! https://oblivus.com May 16, 2023 at 01:00PM

Show HN: My passion project for the last 6 months https://ift.tt/4Xl3Wrn

Show HN: My passion project for the last 6 months https://ift.tt/3YKAyRT May 16, 2023 at 10:27AM

Show HN: Query Hacker News via ChatGPT https://ift.tt/NRJq4hG

Show HN: Query Hacker News via ChatGPT https://ift.tt/1sRr9VP May 16, 2023 at 09:58AM

Show HN: dreamGPT: What if LLM hallucinations were a feature and not a bug? https://ift.tt/CrxTlfE

Show HN: dreamGPT: What if LLM hallucinations were a feature and not a bug? The first GPT-based solution that uses hallucinations from LLMs for divergent thinking to generate new and novel ideas. Hallucinations are often seen as a negative thing, but what if they could be used for our advantage? dreamGPT is here to show you how. The goal of dreamGPT is to explore as many possibilities as possible, as opposed to most other GPT-based solutions which are focused on solving specific problems. https://ift.tt/bhnrUHM May 16, 2023 at 04:32AM

Show HN: Legend-State 1.0 – The fastest React state library https://ift.tt/9WMsVnd

Show HN: Legend-State 1.0 – The fastest React state library After almost a year of development and iterating, we just released Legend-State 1.0. It's the fastest React state library and is very easy to use, based on Observables (Signals) with fine-grained reactivity and built-in persistence. I'd love to know what you think, and I'm also happy to answer any general JavaScript performance questions if you want since I've gone very deep into optimizing . https://ift.tt/PsJZX1A https://ift.tt/YIBUwz0 May 16, 2023 at 04:36AM

Show HN: Hat-syslog – Syslog Server with real time web UI https://ift.tt/9WMTgbf

Show HN: Hat-syslog – Syslog Server with real time web UI https://ift.tt/Jxb5RBO May 16, 2023 at 03:35AM

Show HN: Openlayer – Test, fix, and improve your ML models https://ift.tt/zn6tUXa

Show HN: Openlayer – Test, fix, and improve your ML models Hey HN, my name is Vikas, and my cofounders Rish, Gabe and I are building Openlayer: http://openlayer.com/ Openlayer is an ML testing, evaluation, and observability platform designed to help teams pinpoint and resolve issues in their models. We were ML engineers experiencing the struggle that goes into properly evaluating models, making them robust to the myriad of unexpected edge cases they encounter in production, and understanding the reasons behind their mistakes. It was like playing an endless game of whack-a-mole with Jupyter notebooks and CSV files — fix one issue and another pops up. This shouldn’t be the case. Error analysis is vital to establishing guardrails for AI and ensuring fairness across model predictions. Traditional software testing platforms are designed for deterministic systems, where a given input produces an expected output. Since ML models are probabilistic, testing them reliably has been a challenge. What sets Openlayer apart from other companies in the space is our end-to-end approach to tackling both pre- and post-deployment stages of the ML pipeline. This "shift-left" approach emphasizes the importance of thorough validation before you ship, rather than relying solely on monitoring after you deploy. Having a strong evaluation process pre-ship means fewer bugs for your users, shorter and more efficient dev-cycles, and lower chances of getting into a PR disaster or having to recall a model. Openlayer provides ML teams and individuals with a suite of powerful tools to understand models and data beyond your typical metrics. The platform offers insights about the quality of your training and validation sets, the performance of your model across subpopulations of your data, and much more. Each of these insights can be turned into a “goal.” As you commit new versions of your models and data, you can see how your model progresses towards these goals, as you guard against regressions you may have otherwise not picked up on and continually raise the bar. Here's a quick rundown of the Openlayer workflow: 1. Add a hook in your training / data ingestion pipeline to upload your data and model predictions to Openlayer via our API 2. Explore insights about your models and data and create goals around them [1] 3. Diagnose issues with the help of our platform, using powerful tools like explainability (e.g. SHAP values) to get actionable recommendations on how to improve 4. Track the progress over time towards your goals with our UI and API and create new ones to keep improving We've got a free sandbox for you to try out the platform today! You can sign up here: https://ift.tt/JVA2Rml . We are also soon adding support for even more ML tasks, so please reach out if your use case is not supported and we can add you to a waitlist. Give Openlayer a spin and join us in revolutionizing ML development for greater efficiency and success. Let us know what you think, or if you have any questions about Openlayer or model evaluation in general. [1] A quick run-down of the categories of goals you can track: - Integrity goals measure the quality of your validation and training sets - Consistency goals guard against drift between your datasets - Performance goals evaluate your model's performance across subpopulations of the data - Robustness goals stress-test your model using synthetic data to uncover edge cases - Fairness goals help you understand biases in your model on sensitive populations https://ift.tt/9eST8RW May 15, 2023 at 11:05PM

Show HN: Sha2git brings code hosting to secure SHA-2 Git repositories https://ift.tt/9b1XJNk

Show HN: Sha2git brings code hosting to secure SHA-2 Git repositories https://sha2git.com/ May 15, 2023 at 08:44AM

Show HN: Terminal Notifications for Long Processes over Slack and Discord -Nudge https://ift.tt/QDbNEe3

Show HN: Terminal Notifications for Long Processes over Slack and Discord -Nudge Hi HN! Nudge is an effortless notifier for long-running terminal commands. No prompt needed, you can set it up to automatically notify you for completion of commands running over X minutes over Mac, Slack, and Discord. It can even notify you of commands running over ssh without installing it on the remote host. I built it to notify me of long, monolithic builds at my workplace. Check out Nudge Notifier at NudgeNotifier.com https://ift.tt/OQHUZ96 May 14, 2023 at 11:51PM

Show HN: Online and CLI Tool to backup password protected data with QR codes https://ift.tt/Hqmladn

Show HN: Online and CLI Tool to backup password protected data with QR codes https://ift.tt/yafvNOH May 14, 2023 at 11:47PM

Show HN: Run AWS Cedar Policy Like OPA https://ift.tt/ipejmnt

Show HN: Run AWS Cedar Policy Like OPA https://ift.tt/iP9IYk7 May 15, 2023 at 02:55AM

Show HN: I built my first Cyberdeck https://ift.tt/JHxRcm8

Show HN: I built my first Cyberdeck https://ift.tt/xGBviKP May 15, 2023 at 12:08AM

Show HN: Tack, a fast lightweight scripting language for games and embedding https://ift.tt/1L9ztUa

Show HN: Tack, a fast lightweight scripting language for games and embedding https://ift.tt/i2HoaCt Hi HN! Tack is a scripting language I've been working on sporadically for the past year or so, and intensely for the past few weeks. It originated out of a desire for something that was like Lua, but with a more familiar syntax, and without some of the other surprises in Lua such as the 1-indexed tables. It's also been a great learning project, and a very satisfying challenge! While the current version is early beta at best, I hope to continue working on it and maybe see some adoption. Despite the relative lack of optimization, I'm very pleased with the performance so far - although I haven't done a huge amount of benchmarking, it seems to be significantly faster than the stock Lua 5.4 interpreter for the quicksort test, and the btrees test (copied from the Computer Language Benchmarks Game). The language is designed for embedding in C++ programs, and is written in C++ more or less from scratch including the handwritten recursive descent parser, and a register-based compiler/interpreter. The only dependency other than the standard library is my C++ adaptation of the khash library used for the object type - a from-scratch hashmap seemed not worth the trouble. Quick code example - more examples in the repo! fn quicksort(arr) { const n = #arr if n <= 1 { return arr } " find the midpoint " let l = min(arr) let r = max(arr) if r == l { return arr } const mid = (l + r) / 2 " split array into upper and lower " const upper = filter(arr, fn(x) { return x < mid }) const lower = filter(arr, fn(x) { return x >= mid }) " recursively sort the upper and lower sub-arrays and join the result" return quicksort(lower) + quicksort(upper) } let A = [] for i in 0, 1000000 { A << random() } let before = clock() let B = quicksort(A) let after = clock() print("Time taken: ", after - before, "seconds") Building requires just cmake and a C++20 compiler - tested with MSVC 2022, g++11 on WSL and Clang 15 on M1 https://craftinginterpreters.com was a great help with implementing closures, as I had gone down a blind alley with my first approach for locating the closed-over variables. However I have taken a slightly different approach towards boxing. As I do intend to use this for some small games myself going forward, there is a standard library already, and plans to expand it. I also intend to release a GLFW-based mini game framework along with precompiled binaries, so hobbyists (and younger relatives!) may use it without needing a full compiler toolchain. I would love if anyone is interested enough to try it out! James https://github.com/PlumeCat/tack May 14, 2023 at 11:09PM

Show HN: Torquigen,create symmetrical animated GIFs from your images https://ift.tt/Xg0d1sE

Show HN: Torquigen,create symmetrical animated GIFs from your images This is the first code I've written in WebGL2. It supports Chrome, Firefox, and Safari (macOS or ipadOS). https://torquigen.app May 14, 2023 at 10:09PM

Show HN: ts-npm-template – Template to bootstrap NPM package with TypeScript https://ift.tt/Arpk9LN

Show HN: ts-npm-template – Template to bootstrap NPM package with TypeScript https://ift.tt/6wmqlnp May 14, 2023 at 06:06PM