Explore
Showing results for:
"The Hacker News"
1,284 results • Page 39 of 107
Matched "The Hacker News"Found in Description
157 points 62 comments on Hacker News · zachholman.com
Matched "The Hacker News"Found in Description
814 points 310 comments on Hacker News · christianselig.com
Matched "The Hacker News"Found in Description
486 points 152 comments on Hacker News · kimi.com
Matched "The Hacker News"Found in Description
142 points 110 comments on Hacker News · prilik.com
Matched "The Hacker News"Found in Source
Ruby on Rails has released fixes for a critical Active Storage vulnerability that could let unauthenticated attackers read arbitrary files from application servers through crafted image uploads. Tracked as CVE-2026-66066 (CVSS score: 9.5), the flaw can expose the Rails process environment and secrets such as secret_key_base, the Rails master key, database passwords, cloud storage credentials,
Matched "The Hacker News"Found in Source
I was recently laid off after 18 years, and gave myself 100 days to build soething useful in public. CheapFoodMap is a crowdsourced map of meal under $10, excluding franchises, local good eats only. It's inspried by 거지맵 (Begger's Map) a Korean crowdsourced map students use to find cheap eats. Ocverage is heaviest in Texas, since I live in Dallas, but have 1200 meals across 15 US cities. Seed data came from Google Review, 4.2 star or higher with at least 500 reviews, and verified price under $10 per menu item. Things I would love feedback on : whether the price-freshness model makes sense, and what would make you trust the price on a site like this. How to encourage people to update prices, since inflation is making food price very frequent. https://cheapfoodmap.com Any and all suggestion will be super helpful. Thank you!
Matched "The Hacker News"Found in Description
129 points 69 comments on Hacker News · blog.cryptographyengineering.com
Matched "The Hacker News"Found in Description
436 points 176 comments on Hacker News · digitalfoundry.net
Matched "The Hacker News"Found in Source
https://mitchellh.com/writing/superlogical
Matched "The Hacker News"Found in Source
Cybersecurity researchers have flagged a maximum-severity security flaw in Ruflo, an open-source agent meta-harness for Anthropic Claude Code and OpenAI Codex, that could result in unauthenticated remote code execution. The vulnerability, tracked as CVE-2026-59726 (CVSS score: 10.0), impacts all versions of the project before version 3.16.3. It has been codenamed RufRoot by Noma Security's
Matched "The Hacker News"Found in Source
Broadcom has released security updates to address multiple security flaws impacting VMware ESX, vCenter, Workstation, and Fusion, three of which have been designated as critical in severity. The first of the three critical-rated flaws is CVE-2026-59309 (CVSS score: 9.8), which has been described as an authentication bypass in VMware vCenter. "A malicious actor with network access to vCenter
Matched "The Hacker News"Found in Source
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 News
“GPT-5.5's API pricing is reshaping how startups build AI products”
