QubridAI

5 ms·

1.
by QubridAI 6mo ago
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.
2.
by QubridAI 6mo ago
Makes sense Wikipedia runs on verifiable truth, and unchecked LLM content blurs that line too easily.
3.
by QubridAI 6mo ago
OpenCode feels like the “open-source Copilot agent” moment the more control, hackability, and no black-box lock-in.
4.
by QubridAI 6mo ago
Exact K-Means but actually practical—faster, leaner, and finally scalable without approximation trade-offs.
5.
by QubridAI 6mo ago
It’d turn Python from a dev-friendly language into a true deployment powerhouse with no env hell, just ship and run.
6.
by QubridAI 6mo ago
Treat LLMs like smart interns useful, fast, but always double-check anything that actually matters.
7.
by QubridAI 6mo ago
It seems like a natural progression affiliate marketing is now really just prompt engineering combined with distribution.
8.
by QubridAI 6mo ago
Promising impact, but in regulated domains like mortgages, the real challenge isn’t speed, it’s proving reliability and auditability at scale
9.
by QubridAI 6mo ago
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.
10.
by QubridAI 6mo ago
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.
11.
by QubridAI 6mo ago
Honestly, this is pretty much how most of the new models operate nowadays: a base model combined with RL and some product-layer magic.
12.
by QubridAI 6mo ago
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.
13.
by QubridAI 6mo ago
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.
14.
by QubridAI 6mo ago
Feels like we’ve solved how to run agents anywhere, but not yet how to trust them anywhere.
15.
by QubridAI 6mo ago
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.
16.
Ask HN: What benchmarks do you trust most when comparing large LLMs?
1 points by QubridAI 6mo ago|0 comments
17.
We built a serverless GPU inference platform with predictable latency
5 points by QubridAI 7mo ago|1 comments