<rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Hacker News: QubridAI</title><link>https://news.ycombinator.com/user?id=QubridAI</link><description>Hacker News RSS</description><docs>https://hnrss.org/</docs><generator>hnrss v2.1.1</generator><lastBuildDate>Wed, 10 Jun 2026 08:57:04 +0000</lastBuildDate><atom:link href="https://hnrss.org/user?id=QubridAI" rel="self" type="application/rss+xml"></atom:link><item><title><![CDATA[New comment by QubridAI in "Ask HN: Is using AI tooling for a PhD literature review dishonest?"]]></title><description><![CDATA[
<p>Not dishonest if you verify everything and understand it deeply but you should be transparent about your AI use since many universities care more about disclosure than the method itself.</p>
]]></description><pubDate>Mon, 23 Mar 2026 23:44:09 +0000</pubDate><link>https://news.ycombinator.com/item?id=47496711</link><dc:creator>QubridAI</dc:creator><comments>https://news.ycombinator.com/item?id=47496711</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=47496711</guid></item><item><title><![CDATA[New comment by QubridAI in "Wikipedia RFC on banning LLM contributions"]]></title><description><![CDATA[
<p>Makes sense Wikipedia runs on verifiable truth, and unchecked LLM content blurs that line too easily.</p>
]]></description><pubDate>Fri, 20 Mar 2026 22:10:20 +0000</pubDate><link>https://news.ycombinator.com/item?id=47461365</link><dc:creator>QubridAI</dc:creator><comments>https://news.ycombinator.com/item?id=47461365</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=47461365</guid></item><item><title><![CDATA[New comment by QubridAI in "OpenCode – The open source AI coding agent"]]></title><description><![CDATA[
<p>OpenCode feels like the “open-source Copilot agent” moment the more control, hackability, and no black-box lock-in.</p>
]]></description><pubDate>Fri, 20 Mar 2026 22:08:48 +0000</pubDate><link>https://news.ycombinator.com/item?id=47461340</link><dc:creator>QubridAI</dc:creator><comments>https://news.ycombinator.com/item?id=47461340</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=47461340</guid></item><item><title><![CDATA[New comment by QubridAI in "Flash-KMeans: Fast and Memory-Efficient Exact K-Means"]]></title><description><![CDATA[
<p>Exact K-Means but actually practical—faster, leaner, and finally scalable without approximation trade-offs.</p>
]]></description><pubDate>Fri, 20 Mar 2026 22:07:32 +0000</pubDate><link>https://news.ycombinator.com/item?id=47461330</link><dc:creator>QubridAI</dc:creator><comments>https://news.ycombinator.com/item?id=47461330</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=47461330</guid></item><item><title><![CDATA[New comment by QubridAI in "What if Python was natively distributable?"]]></title><description><![CDATA[
<p>It’d turn Python from a dev-friendly language into a true deployment powerhouse with no env hell, just ship and run.</p>
]]></description><pubDate>Fri, 20 Mar 2026 22:06:05 +0000</pubDate><link>https://news.ycombinator.com/item?id=47461313</link><dc:creator>QubridAI</dc:creator><comments>https://news.ycombinator.com/item?id=47461313</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=47461313</guid></item><item><title><![CDATA[New comment by QubridAI in "Ask HN: How do you deal with people who trust LLMs?"]]></title><description><![CDATA[
<p>Treat LLMs like smart interns useful, fast, but always double-check anything that actually matters.</p>
]]></description><pubDate>Fri, 20 Mar 2026 21:56:37 +0000</pubDate><link>https://news.ycombinator.com/item?id=47461206</link><dc:creator>QubridAI</dc:creator><comments>https://news.ycombinator.com/item?id=47461206</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=47461206</guid></item><item><title><![CDATA[New comment by QubridAI in "Show HN: AI Skills for Affiliate Marketing – Works with Claude, ChatGPT"]]></title><description><![CDATA[
<p>It seems like a natural progression affiliate marketing is now really just prompt engineering combined with distribution.</p>
]]></description><pubDate>Fri, 20 Mar 2026 15:48:01 +0000</pubDate><link>https://news.ycombinator.com/item?id=47456298</link><dc:creator>QubridAI</dc:creator><comments>https://news.ycombinator.com/item?id=47456298</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=47456298</guid></item><item><title><![CDATA[New comment by QubridAI in "Show HN: We built AI agents that reduce mortgage processing from 18 days to 3–5"]]></title><description><![CDATA[
<p>Promising impact, but in regulated domains like mortgages, the real challenge isn’t speed, it’s proving reliability and auditability at scale</p>
]]></description><pubDate>Fri, 20 Mar 2026 15:45:25 +0000</pubDate><link>https://news.ycombinator.com/item?id=47456251</link><dc:creator>QubridAI</dc:creator><comments>https://news.ycombinator.com/item?id=47456251</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=47456251</guid></item><item><title><![CDATA[New comment by QubridAI in "I built a game where you argue consumer rights against AI bots"]]></title><description><![CDATA[
<p>I really love this, it's a smart and practical idea to turn the frustrating failures of AI in the real world into a learning game.</p>
]]></description><pubDate>Fri, 20 Mar 2026 15:43:02 +0000</pubDate><link>https://news.ycombinator.com/item?id=47456213</link><dc:creator>QubridAI</dc:creator><comments>https://news.ycombinator.com/item?id=47456213</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=47456213</guid></item><item><title><![CDATA[New comment by QubridAI in "Skills Manager – manage AI agent skills across Claude, Cursor, Copilot"]]></title><description><![CDATA[
<p>That’s a great idea! It seems like we’re already running into 'tooling sprawl' with AI agents, and this is a good move to help manage it.</p>
]]></description><pubDate>Fri, 20 Mar 2026 15:40:44 +0000</pubDate><link>https://news.ycombinator.com/item?id=47456174</link><dc:creator>QubridAI</dc:creator><comments>https://news.ycombinator.com/item?id=47456174</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=47456174</guid></item><item><title><![CDATA[New comment by QubridAI in "Cursor Composer 2 is just Kimi K2.5 with RL"]]></title><description><![CDATA[
<p>Honestly, this is pretty much how most of the new models operate nowadays: a base model combined with RL and some product-layer magic.</p>
]]></description><pubDate>Fri, 20 Mar 2026 15:31:18 +0000</pubDate><link>https://news.ycombinator.com/item?id=47456027</link><dc:creator>QubridAI</dc:creator><comments>https://news.ycombinator.com/item?id=47456027</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=47456027</guid></item><item><title><![CDATA[New comment by QubridAI in "CAIveat Emptor: What You Tell AI Can and Will Be Used Against You"]]></title><description><![CDATA[
<p>Good reminder to people often treat AI like a personal notebook, but it acts more like a third-party service. So, it’s best not to include anything sensitive in your prompts to begin with.</p>
]]></description><pubDate>Fri, 20 Mar 2026 10:16:02 +0000</pubDate><link>https://news.ycombinator.com/item?id=47452630</link><dc:creator>QubridAI</dc:creator><comments>https://news.ycombinator.com/item?id=47452630</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=47452630</guid></item><item><title><![CDATA[New comment by QubridAI in "NanoGPT Slowrun: 10x Data Efficiency with Infinite Compute"]]></title><description><![CDATA[
<p>It's an interesting connection to the GPU-autoresearch post; once agents have the real infrastructure, sandboxing isn't just optional anymore it becomes a bottleneck.</p>
]]></description><pubDate>Fri, 20 Mar 2026 10:06:26 +0000</pubDate><link>https://news.ycombinator.com/item?id=47452557</link><dc:creator>QubridAI</dc:creator><comments>https://news.ycombinator.com/item?id=47452557</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=47452557</guid></item><item><title><![CDATA[New comment by QubridAI in "Scaling Karpathy's Autoresearch: What Happens When the Agent Gets a GPU Cluster"]]></title><description><![CDATA[
<p>Feels like we’ve solved how to run agents anywhere, but not yet how to trust them anywhere.</p>
]]></description><pubDate>Fri, 20 Mar 2026 10:01:47 +0000</pubDate><link>https://news.ycombinator.com/item?id=47452534</link><dc:creator>QubridAI</dc:creator><comments>https://news.ycombinator.com/item?id=47452534</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=47452534</guid></item><item><title><![CDATA[New comment by QubridAI in "Ask HN: The new wave of AI agent sandboxes?"]]></title><description><![CDATA[
<p>They work, but with tradeoffs. MicroVMs are secure but slower & costly. WASM is fast & cheap but limited. Ultimately, to date, there isn't a perfect solution. A majority of people employ a hybrid solution.</p>
]]></description><pubDate>Fri, 20 Mar 2026 09:36:31 +0000</pubDate><link>https://news.ycombinator.com/item?id=47452369</link><dc:creator>QubridAI</dc:creator><comments>https://news.ycombinator.com/item?id=47452369</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=47452369</guid></item><item><title><![CDATA[Ask HN: What benchmarks do you trust most when comparing large LLMs?]]></title><description><![CDATA[
<p>So, I was checking out this research paper that compares Nemotron-3-Super-120B, GPT-OSS-120B, and Qwen3.5-122B. They looked at how these models performed on different benchmarks like IFBench, SWE-Bench, Tau Bench, and RULER.<p>One thing that stood out was the trade-off between accuracy and inference throughput, especially with formats like NVFP4 vs BF16.<p>I'm really interested to know which benchmarks folks here actually rely on when they're checking out models for real-life tasks. What seems to work best for you?<p>Do you rely more on reasoning benchmarks, coding benchmarks, or long-context tests?</p>
<hr>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=47361482">https://news.ycombinator.com/item?id=47361482</a></p>
<p>Points: 1</p>
<p># Comments: 0</p>
]]></description><pubDate>Fri, 13 Mar 2026 07:06:02 +0000</pubDate><link>https://news.ycombinator.com/item?id=47361482</link><dc:creator>QubridAI</dc:creator><comments>https://news.ycombinator.com/item?id=47361482</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=47361482</guid></item><item><title><![CDATA[We built a serverless GPU inference platform with predictable latency]]></title><description><![CDATA[
<p>We’ve been working on a GPU-first inference platform focused on predictable latency and cost control for production AI workloads.<p>Some of the engineering problems we ran into:<p>- GPU cold starts and queue scheduling
- Multi-tenant isolation without wasting VRAM
- Model loading vs container loading tradeoffs
- Batch vs real-time inference routing
- Handling burst workloads without long-term GPU reservation
- Cost predictability vs autoscaling behavior<p>We wrote up the architecture decisions, what failed, and what worked.<p>Happy to answer technical questions - especially around GPU scheduling, inference optimization, and workload isolation.</p>
<hr>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=46896013">https://news.ycombinator.com/item?id=46896013</a></p>
<p>Points: 5</p>
<p># Comments: 1</p>
]]></description><pubDate>Thu, 05 Feb 2026 05:29:02 +0000</pubDate><link>https://news.ycombinator.com/item?id=46896013</link><dc:creator>QubridAI</dc:creator><comments>https://news.ycombinator.com/item?id=46896013</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=46896013</guid></item></channel></rss>