AI 资讯
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Two Devs and a Copilot Created ClassifierAI: A Prototype Chrome Extension that Automatically Detects AI-Generated Content on DEV!
This is a submission for the GitHub Finish-Up-A-Thon Challenge Note: AI is currently a Hot Topic in...
Why the Great Calculator Debate of the 1980s is still relevant today and how Isaac Asimov got AI right in 1956
Back in the 1980s a debate raged about whether it was okay to let children use calculators in elementary school. Critics warned that giving kids calculators would lead to the "destruction of student math skills." A similar debate is happening today across a range of areas, including coding, writing and even music. Will using AI lead a brain drain across these and many other areas? One of my favorite authors is Isaac Asimov. He's better known for his Foundation and Robot series of books where he contemplates whether an algorithm can successfully predict (and guide) humankind's development and the relationship between super artificial intelligence and humans. In some ways he predicted what we're experiencing today with AI: the rise of powerful, inscrutable artificial machines that are so complex humans can't understand or maintain them. In the short story, "The Last Question" he wrote: "Multivac was self-adjusting and self-correcting. It had to be, for nothing human could adjust and correct it quickly enough or even adequately enough." We're living an age that was once the stuff of science fiction. The question is: what comes next? submitted by /u/SpiritRealistic8174 [link] [留言]
Show HN: On-device transcriber that's 97% accurate at identifying speakers
I’ve spent the last seven months building a tool I wish I’d had in my previous roles. MimicScribe is a macOS menu bar app that fits the "AI notetaker" category. It has accurate on-device speaker identification (a first possibly?), real-time meeting talking points for discovery calls, and a fully keyboard- and voice-driven interface. I believe the accuracy of the speaker ID system is its biggest strength. I used fluid audio’s port of ( https://github.com/fluidInference/FluidAudio ) Pyannote's com
Sakana AI's Recursive Self-Improvement (RSI) Lab
OQC, JPMorganChase and AMD Commence Research Collaboration to Develop New Quantum-AI Platform in London
submitted by /u/SpeedAssassin [link] [留言]
The most interesting startups right now want to get you off your phone
While the AI fundraising machine keeps breaking its own records, some founders are building in the other direction. Mirror founder Brynn Putnam just raised money for Board, a startup focused on bringing people together through in-person games and social experiences. Cyberdeck creators are going viral crafting whimsical DIY computers that literally encourage users to touch grass. Unlike the AI-free browser crowd, this doesn’t just feel like backlash, […]
The Sonos Era 100 speaker is down to its lowest price in months
Whether you’re considering starting a Sonos speaker setup, or adding to an existing group, the Sonos Era 100 is worth picking up. The compact, capable smart speaker is currently marked down to $189 ($30 off) at a variety of retailers, including Amazon, Best Buy, and directly from Sonos. If you want an even lower price, […]
AI agents fail at the auth step more than at the reasoning step. anyone else seeing this?
been building AI agents for a while and noticing a pattern: the LLM reasoning part works. the part that breaks is everything around accounts, logins, and verification. agent gets to "sign up for this service" and then: - email verification loop breaks - OTP times out while the agent is mid-step - captcha or bot detection fires - session expires between steps the model figured out what to do. the infrastructure around it didn't cooperate. curious if this matches what others are building. where do your agents actually fail in production? is it the reasoning, or is it the plumbing? submitted by /u/kumard3 [link] [留言]
Google shuts down the AI image app Pixel Studio
Google's AI app Pixel Studio launched less than two years ago, but is now being shut down.
Ramp launched an AI operating system for accounting firms
submitted by /u/ProfessorDeep8754 [link] [留言]
This is your laptop… on AI
We're now deep into developer conference season, and one of the themes so far is the relentless conviction from Big Tech companies that AI is going to change everything about how we do everything. Nvidia's Jensen Huang made that clearer than anyone this week, when he described a completely new way of using our laptops […]
Launch HN: General Instinct (YC P26) – Frontier models on edge devices
Hey HN, Guanming and Bill here from General Instinct ( https://general-instinct.com/ ). After years of working in robotics, we kept running into the same problem: the best models never fit the hardware we actually had available. The models that performed best were usually designed around datacenter assumptions: large GPUs, lots of memory bandwidth, and reliable network access. But most physical systems have the opposite constraints. That led us down the path of figuring out how much of a frontie
I spent years helping devs ship web apps as native apps. Here's everything in one guide.
I work as a Developer Advocate helping people ship web apps as native mobile apps, and I kept answering the same questions over and over. So I wrote a guide that summarizes everything I recommend, based on 13+ years working in mobile development. From what I've seen, every time someone in a web dev community asks "how do I publish my React/Vue/Angular app to the App Store?", the answers are either "just make a PWA" (which doesn't actually get you on the stores) or links to tutorials that assume you already know what a provisioning profile is and have Xcode configured on a Mac. This one starts from zero. It's structured as an index, not a wall of text. Each step links to specific posts, videos, tools, and automation resources so you can go as deep as you need, at your own pace. Some things I cover that I rarely see explained well: - Why PWAs won't get you into the App Store or Google Play (and what to use instead) - How to generate iOS certificates directly from your browser, without a Mac or Keychain Access - The Google Play closed testing requirement that blindsides most first-time publishers: personal accounts created after November 2023 need 12 testers actively opted in for at least 14 consecutive days before you can go public. - Why you should install the Live Update plugin in your very first release, even if you have nothing to update yet. Adding it later means another full native build and another review cycle, which is the last thing you want when you're trying to push a critical fix. - How to build for iOS without owning a Mac Honest feedback welcome: is there a step that's unclear, or something you think is missing? https://capawesome.io/blog/11-steps-to-get-your-web-app-on-the-app-store/ submitted by /u/DayanaJabif [link] [留言]
Supabase doubles valuation to $10B in 8 months
Supabase, an example of an open source project becoming a fast-growing company, has greatly benefited from AI tools like Claude, Codex, and other vibe-coding platforms.
If a client asks you why they cant just one-shot the app? How do you counter by explaining the software development process?
I feel like this might start becoming a lot more common, due to all the hype and marketing surrounding AI. Seems a lot of ppl believe anyone can build an app in one-shot and we don’t need experienced engineers anymore. When they ask a question like “why can’t we just one-shot the app”, it puts you on the hot seat to explain the entire development process to them, and all the steps it takes to get to a production quality app. AI can be used to assist and augment that process but you need a human in the loop to know and understand what they are doing. Rather than just telling them “go ahead and try it yourself”, how would you respond to this? How would you explain why AI can’t just make the entire app? How would you breakdown the step by step process of building an entire application? Thanks submitted by /u/throwaway0134hdj [link] [留言]
Monako Glass
Run AI coding agents hands-free from a heads-up display Discussion | Link
Gemma 4 QAT models: Optimizing compression for mobile and laptop efficiency
The best AI “science critics” are also the most overconfident — a benchmark on calibration vs. skill
Disclosure: I work on the benchmark below, so flagging that up front. We've been testing whether LLMs can critique recent science-paper summaries — catch planted flaws, overclaims, and missing evidence — and, separately, how calibrated they are about their own judgments (confidence scored with Brier, a strictly proper rule). The pattern that keeps showing up: the models best at spotting problems are also among the most confidently wrong when they miss. Critique skill and calibration look like different axes, not the same one. There's also a clear gap between raw accuracy and knowing when to abstain. It's open (Apache-2.0) if you want to poke at it: Leaderboard: https://huggingface.co/spaces/BGPT-OFFICIAL/refute-leaderboard Dataset: https://huggingface.co/datasets/BGPT-OFFICIAL/refute Curious how others think about measuring calibration vs. raw capability — is a proper scoring rule enough, or do you need explicit abstention metrics too? submitted by /u/connerpro [link] [留言]
What happens when your phone is confiscated at the airport
Even if you've done nothing wrong, it's never a good idea to hand your phone to the cops. But international travelers at American airports often have no choice - even if they're US citizens. When Minnesota labor organizer Janette Zahia Corcelius returned home from a three-week trip to Europe in late April, she was detained […]