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Ask HN: Is Gaussian Splattering useful for analyzing Pretti's death? 3 by mdnahas | 3 comments on Hacker News. It is now common to have multiple people using their smartphones to video the same event. I'm thinking Pretti and Good's killings. I've heard of Gaussian Splattering, which constructs a 3D scene from multiple cameras. Is it useful for these analyzing these events? And, if so, can someone build an easy-to-use open source tool? My speculation is that it would be useful to: (1) synchronize video, (2) get more detail than a single camera can get, (3) track objects (like Pretti's gun) that are seen by multiple cameras, and (4) identify AI generated video. The last is most important to me. There is a danger of AI generated or modified video of an event. It seems possible to me that Gaussian Splattering from N videos will be able to detect if the N+1 video is consistent or inconsistent with the scene. Is this possible?

Qwen3-Max-Thinking Drops: 36T Tokens 2 by SilasYee | 2 comments on Hacker News. Alibaba has officially launched Qwen3-Max-Thinking, a trillion-parameter MoE flagship LLM pretrained on 36T tokens—double the corpus of Qwen 2.5—and it’s already matching or outperforming top-tier models like GPT-5.2-Thinking, Claude-Opus-4.5, and Gemini 3 Pro across 19 authoritative benchmarks. Its two core technical breakthroughs are what truly set it apart. First, Adaptive Tool Calling: No manual prompts are needed—it autonomously invokes search engines, memory tools, and code interpreters based on task demands. This cuts down on hallucinations and boosts real-time problem-solving; for instance, coding tasks trigger automatic error correction loops, while research tasks combine search with context synthesis. Second, Test-Time Scaling (TTS): It outperforms standard parallel sampling by refining reasoning through iterative insights, with measurable jumps in key benchmarks—GPQA rose from 90.3 to 92.8, Li...

Ask HN: DDD was a great debugger – what would a modern equivalent look like? 10 by manux81 | 5 comments on Hacker News. I’ve always thought that DDD was a surprisingly good debugger for its time. It made program execution feel visible: stacks, data, and control flow were all there at once. You could really “see” what the program was doing. At the same time, it’s clearly a product of a different era: – single-process – mostly synchronous code – no real notion of concurrency or async – dated UI and interaction model Today we debug very different systems: multithreaded code, async runtimes, long-running services, distributed components. Yet most debuggers still feel conceptually close to GDB + stepping, just wrapped in a nicer UI. I’m curious how others think about this: – what ideas from DDD (or similar old tools) are still valuable? – what would a “modern DDD” need to handle today’s software? – do you think interactive debugging is still the right abstraction at all? I’m asking mostl...

Why is cursor / Claude Code is so bad at generating readmes? 2 by yakshithk_ | 1 comments on Hacker News.

I'm posting this from a memory safe web browser 17 by pizlonator | 2 comments on Hacker News. Hi everyone! I'm posting this from a memory safe browser: WebKitGTK MiniBrowser compiled with Fil-C, plus all dependencies compiled with Fil-C Still dealing with a tail of bugs, some of which look like overzealous optimizations leading to loss of pointer capability (leading to a filc panic). But it works well enough that I can say "hi" on here.

Ask HN: What are some good unintuitive statistics problems? 3 by ronbenton | 2 comments on Hacker News. I am compiling some statistics problems that are interesting due to their unintuitive nature. some basic/well known examples are the monty hall problem and the birthday problem. What are some others I should add to my list? thank you!