Star Wars Zero Company's developers released a gameplay trailer, which features a short appearance by Anakin Skywalker.

Unpopular opinion: most AI tools don’t actually save time. They just move the work around. You still have to prompt it, check it, edit it, and sometimes redo it. That’s not automation — that’s just a different kind of work. The only ones I’ve seen genuinely cut time are search tools like Perplexity and coding tools like Cursor. Everything else feels like it’s optimized for the demo, not real use. Change my mind submitted by /u/aiprotivity_ [link] [留言]

Hi! I’ve been working in IT for over seven years now, and my office is next to some healthcare professionals. During a lunch break sitting on a bench in the sun, one of them asked me: If I enter my patients’ personal information into ChatGPT, is that a problem? I wasn’t sure how to answer him, in my opinion, yes, but what do you think? I’d be curious to hear your thoughts, and if there are any studies on the subject, I’d love to see them too! Thanks in advance for your responses! Have a great day, everyone ☀️ Alex submitted by /u/No_Computer_1247 [link] [留言]

I don’t know if this is the right sub-reddit to ask this type of question. I am quite ignorant about hardcore technical stuff. I want to say that I love the idea of an agnostic approach to AI and being able to understand and decide which model is best suited for a specific task. As well as the ability to have citations, being able to have it look through health research and stuff for queries regarding health, etc. Now I do not know if this is just in a general sense people just complaining or something else entirely, but I am seeing a lot of negative stuff on the Perplexity sub-reddit. In terms of like how the quality has gone down, asking how such a company is still even in business. I was just wondering if any of this holds any water or is overly exaggerated submitted by /u/No-Main6695 [link] [留言]

I’ve been improving imagor’s handling of streamed image sources and its libvips image loading path, and updated the benchmark page with current releases. If you work on image delivery, dynamic resizing, or URL-based image processing in web stacks, the updated benchmark summary is here: Benchmark page: https://docs.imagor.net/benchmarks imagor repo: https://github.com/cshum/imagor These results use released versions of imagor, imgproxy, and thumbor. The benchmark page includes summary charts, and the benchmark repo includes committed result summaries for anyone who wants to inspect the setup more closely. Happy to discuss the implementation changes, benchmark setup, or what additional scenarios would be useful to measure. submitted by /u/cshum [link] [留言]

Created a Google Chrome extension that instantly turns any highlighted text on a webpage into a Google Calendar event

Cloudflare recently described how a slowdown in its billing pipeline was traced to contention inside the query planning stage of ClickHouse. The team profiled the bottleneck and patched ClickHouse to replace an exclusive lock with a shared lock, drop the per-query copy of the parts list, and improve part filtering. By Renato Losio

For context, I am a final-year math + CS undergraduate considering pursuing a career in theoretical robotics, particularly in continual learning and the development of robots that can learn from and adapt to / navigate their environments in a human-like manner. One concern I have, however, is that such research might advance AGI timelines. Specficially, it seems possible that architectures developed for continual learning in robots could transfer to general AGI systems (even if the AGI systems a

submitted by /u/chunmunsingh [link] [留言]

Just wanted to share this Drake Equation exploration I've been working on. You tweak the parameters and it updates the civilization count instantly, with a 3D Milky Way you can explore, charts, NASA exoplanet data, and bilingual EN/ES. Built with vanilla JS + Three.js, no frameworks. https://mendiak.github.io/drake.equation/ submitted by /u/mendiak_81 [link] [留言]

7 Infra Improvement Strategies to Prevent Next.js Deployment Build Failures in 2026 Recently, our team's deployment pipeline started showing serious instability. Specifically, we encountered recurring build failures related to the chat build. As a result, the entire development team was preoccupied with battling these build failures. Attempts and Pitfalls Initially, I thought the --preload detection logic was the problem. I modified it to detect only specific lines, but this ended up causing issues in other areas. The recurring chat build failures were actually caused by the next.config file not properly recognizing file extensions. I modified it to allow extensions like .mjs , .js , .ts , and .cjs , but even that didn't work correctly at first, leading to some wasted effort. # .github/workflows/deploy.yml (Excerpt from initial version) - name : Run Preload Detection run : | # ... existing logic ... if [[ "$LINE" == *"some_pattern"* ]]; then echo "Preload detected" # ... fi I modified it to detect only specific lines like the above, which led to unintended behavior. // next.config.js (Initial configuration) module . exports = { // ... experimental : { // ... }, // ... }; Regarding extensions, I initially allowed only a few types, and only after experiencing chat build failures did I modify it to support more extensions. Root Causes In the end, it was a combination of several complex issues. There were flaws in the --preload detection logic, and the range of supported extensions in the next.config file was too narrow, which was the direct cause of the chat build failures. Additionally, there was confusion arising from the chat server builds being inconsistent between P1/P2 and P0 stages. Problems also occurred because the .next directory was not preserved, and the smoke gate was too lenient, failing to catch build failures. Finally, there was an unexpected side effect where the next/font/google library caused GCE outbound connection errors. Solutions To address these

What I Built I'm thrilled to present Chrono Shift: Time Weaver – a time-bending puzzle platformer that challenges players to manipulate time itself to overcome obstacles and solve environmental puzzles. The Concept Imagine being able to see two versions of the same level simultaneously – the past and the present. In Chrono Shift, you don't just play through a level once; you play through it twice, switching between timelines to create pathways that wouldn't exist in either timeline alone. A bridge that collapsed in the present might be intact in the past. A door that's locked now might be open in the past. By strategically shifting between eras, you create a path forward that exists only through your mastery of time. What Makes It Special Dual-Timeline Mechanics : Switch between past and present with the press of a button, watching as the world transforms around you 10 Unique Levels : Each level introduces new mechanics and challenges, gradually building your time-weaving skills Pixel Art Beauty : Vibrant, hand-crafted pixel art with parallax scrolling backgrounds that bring each era to life Collectible Time Crystals : Find hidden crystals in each level to unlock challenges and achievements Responsive Controls : Smooth platforming with jump, dash, and time-shift abilities that feel tight and satisfying Ambient Soundtrack : Era-reactive music that shifts with your timeline changes, immersing you deeper in the experience Mobile-Friendly : Touch controls mean you can weave time on any device The Journey This game was born from a simple question: what if platformers could teach us about perspective? By forcing players to see the same space from two different temporal viewpoints, Chrono Shift becomes more than just a game – it's a meditation on how our choices in the past shape our present, and how understanding both can unlock possibilities we never saw before. Play it here: https://lovable.dev/projects/bcaa0de3-f14c-4bad-9616-405c896d19bc Video Demo While there's no vi

Search results look simple from the outside. You type a keyword into Google, Bing, or another search engine, and you get a page of links, snippets, ads, maps, news, images, videos, and sometimes AI-generated answers. But if you have ever tried to collect search results at scale, you know it gets messy quickly. A result page is not just a list of links. It changes by country, language, device, location, query intent, and search engine. The same keyword can show different rankings in New York, London, Singapore, or Berlin. A page may include organic results, paid ads, local packs, shopping results, People Also Ask, news results, images, videos, or other SERP features. For humans, that is just a search page. For SEO teams, AI teams, data teams, and developers, it is a data source. That is where a SERP API becomes useful. What is a SERP API? SERP stands for Search Engine Results Page . A SERP API is an API that lets you collect search engine results in a structured format, usually JSON and sometimes HTML. Instead of manually searching a keyword or building a scraper to parse search result pages, you send a request to a SERP API with parameters such as: keyword search engine country language location device type output format The API then returns structured search data. A simplified response might look like this: { "query" : "best project management software" , "organic_results" : [ { "position" : 1 , "title" : "Best Project Management Software Tools" , "link" : "https://example.com" , "snippet" : "Compare features, pricing, and reviews..." } ] } This is much easier to work with than raw HTML. You can store it in a database, send it to a dashboard, compare rankings over time, feed it into an AI workflow, or generate automated reports. Why not just scrape search results yourself? You can build your own scraper. For a small test, that may be enough. You can send a request, parse the HTML, extract titles and links, and save the data. The problem starts when the workflow bec