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Searchable, clear educational resource explaining what data breaches are, how they happen, and practical steps individuals should take if their data is compromised. [Trending: "what is a data breach" with 100+ searches in BR]
Google Trends1mo agoToolFinanceBR
I use separate Claude Code accounts for work and personal projects. Having to log out and go through the login flow every time I switched accounts became annoying, so I built a small CLI to solve it.The commands are intentionally simple:claude account add myworkaccount claude account add mypersonalaccount claude account use myworkaccount claude account currentAfter switching, Claude Code works normally:claude claude "fix this bug in main.py" Repository: https://github.com/hamzarehmandeveloper/claude-accountGive it a try
Hacker News1mo agoToolAI
Hacker News1mo agoToolOther
Hacker News1mo agoToolOther
Hacker News1mo agoToolOther
Hi HN,I built a specialized inference engine for running 4-bit Gemma 4 26B-A4B-IT on any M-series Mac using about 2 GB of RAM. It is called TurboFieldfare and is written in Swift and Metal.I have always adored on-device AI. It feels like magic that you can run a powerful NN on your Mac or iPhone. So I wanted to push the limits a bit and run a model whose weights don’t fit in memory.The model’s 4-bit quantized weights occupy roughly 14 GB, which makes running it with conventional inference tools almost impossible on an 8 GB or even 16 GB Mac once the OS, applications, and KV cache are included.The trick is to keep the shared part of the model and the KV cache in RAM, then stream only the routed experts needed for each token from SSD. An SSD is way slower than RAM, so the runtime uses a small expert cache and bounded parallel `pread`. While those reads are in flight, the GPU runs the shared part of the layer.I ran more than 100 experiments. Most didn’t work. A few got me here. The experiments are described in the GitHub repo.It currently generates 5–6 tok/s on an 8 GB M2 MacBook Air and 31–35 tok/s on an M5 MacBook Pro.I also added an experimental OpenAI-compatible local server. It supports streaming and tool calls, and reuses one prompt prefix from the KV cache.Try it! The Mac app is easy to install. On the first run, it will download 15 GB of weights from Hugging Face. The model is surprisingly capable.I would love any kind of feedback!
Hacker News1mo agoToolAI
Hi HN,I built an Android file viewer that opens PDF, Word, Excel, PowerPoint, images, video, audio, Markdown and code, and asks for no permissions at all.I have always been uneasy about opening files people send me. On Android you either install a 400 MB office suite and sign in or use a small free viewer that wants storage access and ends up uploading your file to a server to render it. Also the hassle of having to download different apps for different file formats was really annoying.Gander holds no permissions, not even INTERNET so the OS itself guarantees the file cannot leave the phone.PDFs use Pdfium, media uses Media3, and Office formats are rendered by bundled JS libraries in a WebView and so no request goes to any server.It is a viewer only. Complex PowerPoint decks come out approximately right, spreadsheet charts are not drawn, and old binary .doc and .ppt are unsupported. I'll work on it as issues come up :PIt is 14 MB, MIT licensed and uploaded on Github releases.Do try it! I would love some feedback especially on files that render badly or need new support.
Hacker News1mo agoToolDev
I have been pushing up to 90 commits a day on a MacBook Air via 4-5 parallel agents. As you can imagine when all the agents try to build, test and run dev servers on an 8GB machine it is the fast lane to a force quit and restart. I also did not want to pay the CI minutes on 90 pushes a day.So I designed a local merge queue to have all commits land one at a time and fully tested. Hopefully this helps other folks with more modest machines. Appreciate any feedback.
Hacker News1mo agoToolAI
Sifting through Reddit 1-star reviews, founder complaints, and user frustrations to find validated ideas is time-intensive and requires active searching.
X8mo agoToolVC & Startups
Products force users through extra layers like creating folders before accessing the main functionality, creating non-obvious obstacles that delay the 'aha' moment and reduce engagement.
X1y agoToolDev
When asking community members what problem a product solves yields inconsistent answers, indicating lack of clarity rather than marketing issues.
X1mo agoOtherMarketing & Sales
Manually searching for relevant threads to promote projects is inefficient and time-consuming for founders building in public.
X1mo agoToolVC & Startups
Founders waste time manually hunting across platforms for places to promote or share their building-in-public updates and projects instead of having an automated way to discover them.
X1mo agoToolVC & Startups
Founders lack quick, high-quality feedback on their X (Twitter) posts before publishing, leading to suboptimal engagement or messaging.
X1mo agoToolMarketing & Sales
Users need easy, low-cost access to earnings call transcripts and APIs to integrate them into AI tools and existing workflows.
X1mo agoToolFinance
Tool to track and aggregate layoff impacts at major tech companies, showing affected roles, locations, and severity trends to help job seekers understand market disruption patterns. [Trending: "visa layoffs" with 200+ searches in IN]
Google Trends1mo agoToolHR & CareerIN
Hey HN, I’m Shreyash from Feyn. We help companies build custom models from their data.Today, we’re releasing FeyNoBg, an automatic background removal model. Alongside it, we're open-sourcing NoBg, the Python library we built to train and run it.Try the model here: https://huggingface.co/spaces/feyninc/feynobg. Check out the library here: https://github.com/feyninc/nobgSome sample outputs:(1) Soccer Freekick: https://drive.google.com/file/d/1MZkAGLwbhNVOZ0Oi7XvpCfSEu9Q...(2) Hair in wind: https://drive.google.com/file/d/1Odc2m0XMVH9uZtvI_KjaRbXzhLL...(3) Bicycle with visible spokes: https://drive.google.com/file/d/1h99ahjfrtS1MFQJJgiKE2fuM3HZ...(4) Live Demo video: https://youtu.be/b1heHPvY8BMBackground removal separates an image's subject from its surrounding. We've all tried it at some point. Often it is to reuse the subject in a different artifact. Nowadays, it is common to make chat stickers out of it. It is one of the most common but under-appreciated uses of AI. It is also surprisingly complex. Models can be easily confused by camouflage, motion blur, or fine structures like hair.The task requires two skills. First, a model has to identify the foreground. Second, it has to trace the foreground’s boundary and estimate an opacity value for each pixel. Generally, these skills are taught with different datasets. That creates a failure point. A poor training mix can improve one skill at the expense of the other. We saw this in our controlled evaluation. A training run with just the MaskFactory dataset improved on the CAMO benchmark but regressed on DIS5K.For FeyNoBg, we took an interpretability-first approach to training. We first studied how BiRefNet’s stages contribute to finding the foreground and reconstructing its boundary. We discovered that the third stage of it's feature extractor holds a lot of informatio
Hacker News1mo agoToolAI
Hi HN, we're Marinos and Hudson, founders of Prized (https://prized.dev)! Prized lets non-engineer employees describe the internal tool they need and get a full-stack app, wired to their company’s data and deployed behind the company’s sign-in, without them ever juggling API keys or connectors.Here's a demo: https://www.youtube.com/watch?v=730MuYOfZTYThe way Prized provides security is by limiting what the agent can reach at the network layer and by keeping credentials out of the sandbox entirely. The sandbox never holds any keys or connector secrets, it only uses scoped session tokens that are stored as opaque placeholders. The real values are swapped into the request headers on our egress proxy. When production data is connected, the sandbox's network policy is set to deny by default so the only path out is via the proxy. Any call the agent makes to an external connector is reviewed by an LLM judge to prevent dangerous operations.Prized is meant for the internal workflows that start as notebooks or spreadsheets but never become real tools because engineering has more important things to work on. One customer’s data scientist pasted in his personal fraud-detection notebook with hardcoded thresholds and all. After a few prompts, it became a published risk console connected to the company’s data with those thresholds turned into UI controls. Earlier today, we got off a call with them and most of their company is using it.To do this, you need to give people the freedom to build without having unaudited access to company systems. We allow admins to scope data to specific users or teams and data access is recorded in an audit log. Each tool is built with its own Postgres schema and role, with queries running via an authenticated SQL gateway as that role.We think Prized sits between products like Lovable and Retool. Lovable makes it easy to generate and host software, but it isn’t designed around distribution with permissions. Reto
Hacker News1mo agoToolAI