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andy_ng

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Actually many people criticizw Apple's AI power, but they forget that the reason Siri is stupid because Apple want to (or at least they explicitly show) protect your privacy.

Iphone AI core is basically Edge AI, which means they deploy it inside the Iphone, not relying on a remote cloud. This can help protect customer data, but it also means they can not update their AI with new training data, and the Chip is kinda small so the model is not smart.

Just know this fact so ppl won't criticize Apple without knowing the sacrifice to protect their privacy

It's kinda useless to raise this point unless we can think of some action to do about it.

Should people avoid the sun? Probably not. Sunlight is proven to have a lot benefit in regulating mood and biological clock.

Should people wear sunscream. Maybe yes, maybe no. I'm not sure. I myself prefer sunlight touch my skin. So unless the UV rate is too high, I won't put on sunscreen.

What are the actions that normal everyday ppl can take in your opinion?

I guess one comment I have would be related to value propositioning. I read through your site, haven't tried it yet, but I don't immediately see why would I use it. Like "Create AI Blog that learn" is too vague to know what your product actually help my usecase. What does it learn, what problem does it show.

Hope it helpful

I also benefit a lot on open sourcing my AI product. It actually creates trust as people can see the code and set it up by themselves.

Good work btw!

I think we shouldn't over think this kind of stuff. Just obssessed with being so good at what you do, occasionally go to clubs or events in the fields you are interested, and people will notice you if you're good.

In my case, I was simply invited by people who already know my ability. I don't even actively find it.

That's what I've saying forever. All of a sudden, everyone's thinking being a software engineer is just all about writing code. In fact, coding is easiest thing for devs. And to be honest, I think everyone's misunderstanding the term "vibe coding" so much that if you use any AI tools in your workflow, you're labeled a vibe coder. That's not Andrej karpathy meant when he coined this term.

Love your work, but pairwise scoring also skips the bigger group context—benchmarks vs list‑wise or MMR methods would highlight trade‑offs. And I’m curious what the compute and latency hit looks like when you run all those pair comparisons in production.

I love the vision of a privacy‑first, open‑source browser that runs AI agents locally, but shipping a custom Chromium fork is a huge maintenance lift so how will you handle timely CVE patches? And the demo video on your website is a bit too generic, can you show a more task-specific one?

I hear your concern, and you're absolutely right to be thinking about this. It's true that AI development involves intense competition, and that can feel overwhelming - like we're all just passengers on a train we can't control. But I don't think we're as powerless as it might seem.

Throughout history, we've found ways to guide powerful technologies toward better outcomes, even when there were strong economic incentives pushing in other directions. Think about how we've developed safety standards for cars, regulations for medicines, or international agreements around nuclear technology. It took time and effort, but people working together made a real difference.

When it comes to AI, we still have meaningful choices. We can support leaders who take these issues seriously, back companies that are genuinely trying to develop AI responsibly, and speak up when we see problems. We can also stay informed and help others understand what's happening - sometimes the most important thing is just having honest conversations about what we want our future to look like.

What validation approaches are on the table? A syscall extractor + LLVM libFuzzer? Harnessing KVM/QEMU for syscall replay? It’d be incredible to see how practical these tests are integrated into CI pipelines.

Congrats on shipping this—memstop looks incredibly useful for anyone diagnosing memory usage regressions in long-running Python apps or ML workflows. I especially appreciate the simplicity: one function call, no external agents, and integration with stdlib tracemalloc for context. Clean and focused.

Any plans to support tracking across async tasks or threads?

What does a “vision deck” for AI‑driven design orgs actually include? Budd suggests pitching a proactive strategy to execs—what visuals, KPIs, or success metrics have worked in your organizations? A clear before/after case could inspire others.

Being technical is actually a huge advantage in building startup, because you can quickly figure out how to solve a problem, and you can execute.

I think you should just need to be resilient in finding problems to solve, or area of problem that you are uniquely positioned to work on (we called "founder fit)

Common mistake of many people when they first started is to follow what others people are building, instead of reflecting deeply on their own advantage, their interests.

You can watch several YC videos about startup ideas. I think they will be useful for you to figure out how to start now.

Furthermore, you are seasoned, and experienced professionally. I think you should reflect deep about problems occurred in your previous work or companies.