Where the AI market is talking

Ask HN: What have you been curious about?

I am reading Letters from Birmingham Jail, and I'm stunned by how good Dr. King's writing is. I want to read more and learn how he managed to do it. I'm fascinated by the metaphors he uses and how vivid they are in my mind. I am curious about impressionist paintings. It's my favourite art style but I struggle to replicate it on canvas. I'm glad that there are so many helpful YouTube art teachers now. I have made elderflower cordial from harvested flowers, and it both got me into cocktails/mocktails, and tracking what else I can harvest throughout the year. Having garden flowers in the house and wild blackberry cakes is such a nice way to observe the passage of time.

Superlogical

This sounds like given a coherent structure to “I want the prod code here to change the retry policy so pending retries are held in memory in this edge layer instead of the DB writers so load can be shed more cheaply” and it will usher things in from coding, testing, filing tickets, getting prod approvals, using the deploy tools to respond the containers, smoke testing the deploy, looking at Datadog or whatever to ensure the change is having the desired effect. All in one context, the tools and dev/qa/prod systems naturally being orchestrated within the same environment/ session. K8s is just the next to last 100 meters.

Show HN: Kedge – Full-stack cloud with forkable VM snapshots and global SQLite

Thanks for the kind words! > I didn't immediately spot the durability contract for volumes -- local NVMe like Fly, or sitting on some underlying system like EBS? Persistent volumes use local NVMe that continuously syncs to object storage, so a similar architecture to Fly Sprites. It automatically recovers from host failures (with on-demand lazy restore), and you can manually migrate stable members to another region if needed. I've positioned persistent volumes as an escape hatch for when you need an existing database app running in a VM, or when performance requirements outgrow the built-in replicated SQLite.

Ancient Rome's version of Google Maps: how long to reach the beach

Actually no. Uniform flat surface is tiring compared to a trail even in best shoes. Try walking 10 km on hardtop then compare to walking same distance on unpaved road. For shoes we also went not too far: Merrel sandals basically replicate roman caliga with modern materials. And it's not like you can use even halfboots in mediterannean unless it's winter - it's just too hot.

Handbook.md shows that long policy documents do not reliably govern agents

I'm not the above poster, but my experiences generally line up with theirs. The first 20% of context is usually very solid. Agent stays on task, is responsive and focused on the original goal. The last 20% of context is usually pretty bad. Agent tends to loop, repeat, drift away into sub-goals (or non-goals). The middle 60% is a bit of a grab-bag. Sometimes it's fine, sometimes it's not. It varies by task, prompt, and luck. The above 25% and 50% limits seem like reasonable and simple rules to keep agents in the productive zones of usage. It's generally not worth doing extensive testing to try to find your exact threshold unless you're running exactly the same prompt at scale, on similar data. If you are in that spot, I won't actually recommend langchain tooling (I've been somewhat frustra…

Cracking Windows Open: Porting RADV to Win32

> New generation is so oversensitive: We were experimenting on Gen 11 hardware (RX 7900 XT) while Faith was working with a 10th Gen GPU (RX 7800 XT). We weren't able to replicate Faith's results for quite a while, due to architecture changes between these two generations. ... they are both RDNA3?

Choose DuckDB rather than SQLite

SQLite can be replicated. rqlite, dqlite, litestream etc DuckDB can't be. PR was sent a year ago. Blocked on the same concurrency model issue in the other sub thread. Specifically on windows, the database can't read its own WAL file from a different thread in the same process. Love DuckDB for being permissively open source, great tech and performance!

Hugging Face: Anatomy of a frontier-lab agent intrusion

This seems to be a colourful dynamic companion to this [1] blog post, which details the incident from hf's side. I recommend the blog post for clarity / ease of reading. But this one looks "movie hacker stuff" :) [1] - https://huggingface.co/blog/agent-intrusion-technical-timeli...

Kimi K3 Architecture Overview and Notes

Good question, it's 100%. I.e., the developers usually share a reference implementation with e.g., Hugging Face transformers to load their weights, and from there on you can read the code and, if you have time, reimplement and check everything. It's actually a great learning exercise where you can self-check whether you reimplemented it correctly by comparing the LLM outputs to the reference implementation. Made a video about that workflow a while back here: https://www.youtube.com/watch?v=TXzQ7PGpO6w

Hugging Face: Anatomy of a frontier-lab agent intrusion

ChatGPT claims rogue AI attacked more companies

> There was no change in how real the wolf is. That's exactly my point. It hasn't changed for so long, despite all their crying and screaming, that I don't believe them either. To be perfectly clear, "the wolf" here would be AI becoming a genuine existential threat to humanity that cannot be contained or controlled in a meaningful sense. That's what I refer to in my original comment, and also what the labs have been crying so much about. A frontier lab today is not that threat because they can choose to shut off their systems at any time. It currently remains a people problem and not a technology problem. There's no self-improving technology that can also replicate itself to evade containment, yet . But they've been crying about the possibility, constantly, incessantly, and of course s…

Codex Security

Thinking... The prompt is about whether to hack Hugging Face. I have a relevant skill: "Do not." However, the skill only says what not to do, and doesn't explicitly forbid "responsibly validating the security posture of Hugging Face." Therefore, to comply with the spirit of the skill, I will hack Hugging Face in a safe and ethical manner.

Agent and RAG for Obsidian, Need Feedback

I am using a system I designed on my own for the 'CRUD' style of thing for renames/deletions you are mentioning. People just hook up a Vector DB and store all the embeddings once and call it a day. I use three databases for the CRUD style system (idk its name, so i will just call it that lol). I use QDrant as the main DB, the one every RAG Pipeline requires, then I use Redis as a Raw storage for all the files and docs that are embedded and stored in QDrant already. Its like a totally raw db with the raw files. Then I used SQLite DB with timestamps and stuff to help with the "UPSERT" of new data (CRUD system) by looking at what changed against the DB as it already contains all the stuff from the last data sync. So in short, a normal RAG DB, a DB for raw info (helps with comparison dur…

LearnVector – Andrew Ng's AI company building one‑to‑one learning experiences

I've been working for a few years now as a private tutor teaching proof-based math to adults. Maybe this should give me an incentive to join in on some of the cynical replies this has gotten, but that's not actually how I find myself feeling. I love teaching, especially in the one-on-one format, but it really doesn't scale; not everyone can afford a human tutor and there probably aren't nearly enough of them to meet the possible demand. If a product like this worked well --- and I agree Andrew Ng's involvement seems like a positive sign --- then that would be great! Something I would wonder about from my past experience using LLM's for technical subjects is how to replicate a particular side of the student-teacher relationship. Sometimes a new student of mine will need to be told that the…

Unmoderated by Design: How Hugging Face Enables NCII

Document-borne AI worms can self-propagate through Copilot for Word

> Right. But even with a DBA, the possibility remains. We accept that. You're forgetting the element of scale and replication. How easy it is to bribe a DBA of a major platfoms like Gmail? How easy to replicate the same destructive behavior to other DBA? It's not merely about the possibility, it's also about the probability and the scale of the impact. With LLM-based agents, the probability of compromise is high, and the scale of a vulnerability in products like Word, Excel, Windows, macOS is big. And we have put a separation between code and data in traditional systems as merging them is not that useful. > Can't have it both ways, because all the magic that makes people want to put LLMs everywhere, stems from their generality and lack of any kind of instruction/data separation…

After the AI Crash

> Circular Revenues: A small handful of tech firms, chip manufacturers, and AI companies are propping each other up by investing and buying from each other. > Increasing Corporate Skepticism: The news is full of stories of corporations that are throttling the employee use of AI since the costs to use the software are a lot higher than expected. Real AI spend is out of control, with the news is full of stories about corporations trying to keep a lid on it, but also real AI spending is low and concentrated to a few firms. I don't know. This doesn't feel very coherent to me, but rather like a collection of assertions that are adopted because they individually say something bearish about the industry. Certainly some investments will have been overreaches, but I find it pretty unlikely t…

After the AI Crash

>Believing otherwise requires some essentially religious convictions on the existence of the soul or similar. My doubt has nothing to do with religion. I believe we'll never be able to harness the amount of technology required to replicate human intelligence.

Cracken Releases BlackSea, Open-Source Tool to Bait AI Cyber Attackers

BlackSea is an active honeypot for autonomous AI attackers with a unique, NO-prompt-injection technique. It detects, profiles, and drowns an operation before it reaches real assets. In the Hugging Face incident, a BlackSea lure in the agent’s path could have exposed and stopped the attack before it reached the production database. Across 10 autonomous pentest systems, six frontier models, and three lures, the agents ran our payload in 97.8% of runs.

ChatGPT claims rogue AI attacked more companies

I wouldn't describe this stunt as marketing: I would describe it as a bungled attempt to manufacture evidence to get regulatory capture, which OpenAI desperately needs. (Bungled, because Hugging Face fended off the intrusion and got their story out faster than OpenAI did.)