Replacing Kubernetes with systemd (2024) (Score: 150+ in 5 hours)
Link: https://readhacker.news/s/6tYuW
Comments: https://readhacker.news/c/6tYuW
Link: https://readhacker.news/s/6tYuW
Comments: https://readhacker.news/c/6tYuW
Yaakov's Blog
Replacing Kubernetes with systemd
In this post I go through the journey of overusing Kubernetes and how systemd can actually do most of what I use it for.
“An independent journalist” who won't remain nameless (❄️ Score: 151+ in 2 days)
Link: https://readhacker.news/s/6tSK5
Comments: https://readhacker.news/c/6tSK5
Link: https://readhacker.news/s/6tSK5
Comments: https://readhacker.news/c/6tSK5
The Handbasket
"An independent journalist" who won't remain nameless
Too many legacy outlets still refuse to credit indie journos. Enough is enough.
Databricks in talks to acquire startup Neon for about $1B (Score: 150+ in 11 hours)
Link: https://readhacker.news/s/6tYr2
Comments: https://readhacker.news/c/6tYr2
Link: https://readhacker.news/s/6tYr2
Comments: https://readhacker.news/c/6tYr2
Upstartsmedia
Scoop: Databricks In Talks To Acquire Startup Neon For About $1 Billion
An Upstarts paid subscriber special edition: acquisition-hungry data and AI unicorn Databricks is in advanced talks to buy the startup behind a popular open-source version of Postgres, sources say.
Google has most of my email because it has all of yours (2014) (Score: 152+ in 5 hours)
Link: https://readhacker.news/s/6tZ86
Comments: https://readhacker.news/c/6tZ86
Link: https://readhacker.news/s/6tZ86
Comments: https://readhacker.news/c/6tZ86
copyrighteous
Google Has Most of My Email Because It Has All of Yours
Republished by Slate. Translations available in French (Français), Spanish (Español), Chinese (中文) For almost 15 years, I have run my own email server which I use for all of my non-work corresponde…
The curse of knowing how, or; fixing everything (🔥 Score: 168+ in 2 hours)
Link: https://readhacker.news/s/6tZs6
Comments: https://readhacker.news/c/6tZs6
Link: https://readhacker.news/s/6tZs6
Comments: https://readhacker.news/c/6tZs6
NotAShelf
The Curse of Knowing How, or; Fixing Everything | Blog
A reflection on control, burnout, and the strange weight of technical fluency.
Sneakers (1992) – 4K makeover sourced from the original camera negative (Score: 150+ in 5 hours)
Link: https://readhacker.news/s/6tZsZ
Comments: https://readhacker.news/c/6tZsZ
Link: https://readhacker.news/s/6tZsZ
Comments: https://readhacker.news/c/6tZsZ
Blu-ray.com
Sneakers 4K Blu-ray (4K Ultra HD + Blu-ray)
Sneakers 4K Blu-ray Release Date April 22, 2025. Blu-ray reviews, news, specs, ratings, screenshots. Cheap Blu-ray movies and deals.
Show HN: TextQuery – Query CSV, JSON, XLSX Files with SQL (Score: 150+ in 19 hours)
Link: https://readhacker.news/s/6tXPj
Comments: https://readhacker.news/c/6tXPj
Link: https://readhacker.news/s/6tXPj
Comments: https://readhacker.news/c/6tXPj
TextQuery App
TextQuery: All-in-One Desktop App to Analyze Data Locally
TextQuery is a desktop app that lets you import data file as a table, query it using SQL, and create stunning charts from those results.
An appeal to Apple from Anukari (Score: 155+ in 9 hours)
Link: https://readhacker.news/s/6tZfv
Comments: https://readhacker.news/c/6tZfv
Link: https://readhacker.news/s/6tZfv
Comments: https://readhacker.news/c/6tZfv
Analyzing Modern Nvidia GPU Cores (Score: 150+ in 13 hours)
Link: https://readhacker.news/s/6tYSR
Comments: https://readhacker.news/c/6tYSR
Link: https://readhacker.news/s/6tYSR
Comments: https://readhacker.news/c/6tYSR
arXiv.org
Analyzing Modern NVIDIA GPU cores
GPUs are the most popular platform for accelerating HPC workloads, such as artificial intelligence and science simulations. However, most microarchitectural research in academia relies on GPU core...
Getting things “done” in large tech companies (🔥 Score: 153+ in 3 hours)
Link: https://readhacker.news/s/6tZVp
Comments: https://readhacker.news/c/6tZVp
Link: https://readhacker.news/s/6tZVp
Comments: https://readhacker.news/c/6tZVp
Seangoedecke
Getting things "done" in large tech companies
--
Critical CSS (Score: 152+ in 11 hours)
Link: https://readhacker.news/s/6tZdh
Comments: https://readhacker.news/c/6tZdh
Link: https://readhacker.news/s/6tZdh
Comments: https://readhacker.news/c/6tZdh
Kigo Critical CSS Generator
Critical CSS Generator | Kigo
Quickly extract the critical CSS needed to render your website's above-the-fold content instantly. Improve performance and Core Web Vitals. A tool by Kigo.
Gemini 2.5 Pro Preview: even better coding performance (🔥 Score: 159+ in 1 hour)
Link: https://readhacker.news/s/6u2E4
Comments: https://readhacker.news/c/6u2E4
Link: https://readhacker.news/s/6u2E4
Comments: https://readhacker.news/c/6u2E4
Googleblog
Google for Developers Blog - News about Web, Mobile, AI and Cloud
Explore the new Gemini 2.5 Pro I/O Edition, featuring enhanced coding performance, video to code capabilities, and improvements for front-end web development.
OpenAI reaches agreement to buy Windsurf for around $3B (Score: 151+ in 4 hours)
Link: https://readhacker.news/s/6u26b
Comments: https://readhacker.news/c/6u26b
Link: https://readhacker.news/s/6u26b
Comments: https://readhacker.news/c/6u26b
Bloomberg.com
OpenAI Reaches Agreement to Buy Startup Windsurf for $3 Billion
OpenAI has agreed to buy Windsurf, an artificial intelligence-assisted coding tool formerly known as Codeium, for about $3 billion, according to people familiar with the matter, marking the ChatGPT maker’s largest acquisition to date.
Show HN: Clippy – 90s UI for local LLMs (🔥 Score: 157+ in 1 hour)
Link: https://readhacker.news/s/6u2CG
Comments: https://readhacker.news/c/6u2CG
Link: https://readhacker.news/s/6u2CG
Comments: https://readhacker.news/c/6u2CG
Nnd – a TUI debugger alternative to GDB, LLDB (Score: 150+ in 4 hours)
Link: https://readhacker.news/s/6u2pb
Comments: https://readhacker.news/c/6u2pb
Link: https://readhacker.news/s/6u2pb
Comments: https://readhacker.news/c/6u2pb
GitHub
GitHub - al13n321/nnd: A debugger for Linux
A debugger for Linux. Contribute to al13n321/nnd development by creating an account on GitHub.
Memory-safe sudo to become the default in Ubuntu (Score: 151+ in 7 hours)
Link: https://readhacker.news/s/6tZXp
Comments: https://readhacker.news/c/6tZXp
Link: https://readhacker.news/s/6tZXp
Comments: https://readhacker.news/c/6tZXp
trifectatech.org
Memory-safe sudo to become the default in Ubuntu - Trifecta Tech Foundation
OpenAI reaches agreement to buy Windsurf for $3B (Score: 155+ in 18 hours)
Link: https://readhacker.news/s/6tZ2f
Comments: https://readhacker.news/c/6tZ2f
Link: https://readhacker.news/s/6tZ2f
Comments: https://readhacker.news/c/6tZ2f
Bloomberg.com
OpenAI Reaches Agreement to Buy Startup Windsurf for $3 Billion
OpenAI has agreed to buy Windsurf, an artificial intelligence-assisted coding tool formerly known as Codeium, for about $3 billion, according to people familiar with the matter, marking the ChatGPT maker’s largest acquisition to date.
Curl: We still have not seen a single valid security report done with AI help (🔥 Score: 155+ in 1 hour)
Link: https://readhacker.news/s/6u36i
Comments: https://readhacker.news/c/6u36i
Link: https://readhacker.news/s/6u36i
Comments: https://readhacker.news/c/6u36i
Linkedin
#hackerone #curl | Daniel Stenberg | 184 comments
That's it. I've had it. I'm putting my foot down on this craziness.
1. Every reporter submitting security reports on #Hackerone for #curl now needs to answer this question:
"Did you use an AI to find the problem or generate this submission?"
(and if they…
1. Every reporter submitting security reports on #Hackerone for #curl now needs to answer this question:
"Did you use an AI to find the problem or generate this submission?"
(and if they…
Matt Godbolt sold me on Rust (by showing me C++) (🔥 Score: 153+ in 1 hour)
Link: https://readhacker.news/s/6u3ee
Comments: https://readhacker.news/c/6u3ee
Link: https://readhacker.news/s/6u3ee
Comments: https://readhacker.news/c/6u3ee
Collabora | Open Source Consulting
Matt Godbolt sold me on Rust (by showing me C++)
Looking at C++ from another angle can create new possibilities using Rust.
Launch HN: Exa (YC S21) – The web as a database (🔥 Score: 153+ in 3 hours)
Link: https://readhacker.news/c/6u2UK
Hey HN! We’re Will and Jeff from Exa (https://exa.ai). We recently launched Exa Websets, an embeddings-powered search engine designed to return exactly what you’re asking for. You can get precise results for complex queries like “all startups working on open-source developer tools based in SF, founded 2021-2025”.
Demo here - https://youtu.be/Unt8hJmCxd4
We started working on Exa because we were frustrated that while LLM state-of-the-art is advancing every week, Google has gotten worse over time. The Internet used to feel like a magical information portal, but it doesn’t feel that way anymore when you’re constantly being pushed towards SEO-optimized clickbait.
Websets is a step in the opposite direction. For every search, we perform dozens of embedding searches over Exa’s vector database of the web to find good search candidates, then we run agentic workflows on each result to verify they match exactly what you asked for.
Websets results are good for two reasons. First, we train custom embedding models for our main search algorithm, instead of typical keyword matching search algorithms. Our embeddings models are trained specifically to return exactly the type of entity you ask for. In practice, that means if you search “startups working in nanotech”, keyword-based search engines return listicles about nanotech startups, because these listicles match the keywords in the query. In contrast, our embedding models return actual startup homepages, because these startup homepages match the meaning of the query.
The second is that LLMs provide the last-mile intelligence needed to verify every result. Each result and piece of data is backed with supporting references that we used to validate that the result is actually a match for your search criteria. That’s why Websets can take minutes or even hours to run, depending on your query and how many results you ask for. For valuable search queries, we think this is worth it.
Also notably, Websets are tables, not lists. You can add “enrichment” columns to find more information about each result, like “# of employees” or “does author have blog?”, and the cells asynchronously load in. This table format hopefully makes the web feel more like a database.
A few examples of searches that work with Websets:
- “Math blogs created by teachers from outside the US”: https://websets.exa.ai/cma1oz9xf007sis0ipzxgbamn
- "research paper about ways to avoid the O(n^2) attention problem in transformers, where one of the first author's first name starts with "A","B", "S", or "T", and it was written between 2018 and 2022”: https://websets.exa.ai/cm7dpml8c001ylnymum4sp11h
- “US based healthcare companies, with over 100 employees and a technical founder": https://websets.exa.ai/cm6lc0dlk004ilecmzej76qx2
- “all software engineers in the Bay Area, with experience in startups, who know Rust and have published technical content before”: https://youtu.be/knjrlm1aibQ
You can try it at https://websets.exa.ai/ and API docs are at https://docs.exa.ai/websets. We’d love to hear your feedback!
Link: https://readhacker.news/c/6u2UK
Hey HN! We’re Will and Jeff from Exa (https://exa.ai). We recently launched Exa Websets, an embeddings-powered search engine designed to return exactly what you’re asking for. You can get precise results for complex queries like “all startups working on open-source developer tools based in SF, founded 2021-2025”.
Demo here - https://youtu.be/Unt8hJmCxd4
We started working on Exa because we were frustrated that while LLM state-of-the-art is advancing every week, Google has gotten worse over time. The Internet used to feel like a magical information portal, but it doesn’t feel that way anymore when you’re constantly being pushed towards SEO-optimized clickbait.
Websets is a step in the opposite direction. For every search, we perform dozens of embedding searches over Exa’s vector database of the web to find good search candidates, then we run agentic workflows on each result to verify they match exactly what you asked for.
Websets results are good for two reasons. First, we train custom embedding models for our main search algorithm, instead of typical keyword matching search algorithms. Our embeddings models are trained specifically to return exactly the type of entity you ask for. In practice, that means if you search “startups working in nanotech”, keyword-based search engines return listicles about nanotech startups, because these listicles match the keywords in the query. In contrast, our embedding models return actual startup homepages, because these startup homepages match the meaning of the query.
The second is that LLMs provide the last-mile intelligence needed to verify every result. Each result and piece of data is backed with supporting references that we used to validate that the result is actually a match for your search criteria. That’s why Websets can take minutes or even hours to run, depending on your query and how many results you ask for. For valuable search queries, we think this is worth it.
Also notably, Websets are tables, not lists. You can add “enrichment” columns to find more information about each result, like “# of employees” or “does author have blog?”, and the cells asynchronously load in. This table format hopefully makes the web feel more like a database.
A few examples of searches that work with Websets:
- “Math blogs created by teachers from outside the US”: https://websets.exa.ai/cma1oz9xf007sis0ipzxgbamn
- "research paper about ways to avoid the O(n^2) attention problem in transformers, where one of the first author's first name starts with "A","B", "S", or "T", and it was written between 2018 and 2022”: https://websets.exa.ai/cm7dpml8c001ylnymum4sp11h
- “US based healthcare companies, with over 100 employees and a technical founder": https://websets.exa.ai/cm6lc0dlk004ilecmzej76qx2
- “all software engineers in the Bay Area, with experience in startups, who know Rust and have published technical content before”: https://youtu.be/knjrlm1aibQ
You can try it at https://websets.exa.ai/ and API docs are at https://docs.exa.ai/websets. We’d love to hear your feedback!