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Where the AI market is talking

A source-linked Hacker News monitor for the tracked company graph. These are attributable public discussions—not sentiment, endorsements, or unverified company facts.

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3684

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14

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Showing 3321–3340 of 3684 matching discussions

Anthropic
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Gemini Robotics 2 brings whole body intelligence to robots

You know SpaceX is still publicly valued at $1.5T marketcap, right? (offering price has nothing to do with anything other than ego of founders/bankers). Yes, I will wait for the correct valuation when all stocks enter the liquidity pool. OpenAI/Anthropic obscenely profitable is an easy bet (for me)

Anthropic
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Gemini Robotics 2 brings whole body intelligence to robots

This is incredible. Seems like a big achievement. The only thing that bothers me is what happens when robots finally automated "all the mundane day-to-day tasks" including our jobs, what is there left to do for common folks who are not geniuses working at Google/Anthropic/ChatGPT or occupy the C-Suite of these companies?

OpenAI
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Advancing the price-performance frontier with GPT‑5.6

OpenAI's APIs are extremely reliable for sure. I don't even remember when the last incident or downtime was.

OpenAI
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Gemini Robotics 2 brings whole body intelligence to robots

It's certainly an odd situation where Google is on the forefront of all these emerging technologies while the latest chatbots from OpenAI and Anthropic are getting breathless press releases and wildly hyperbolic coverage ("rogue AIs" "too dangerous, must be banned" etc...) Google acting like a normal but competent company that's just chugging away, meanwhile the hype cycle is propping up its upstart competitors to truly ludicrous valuations.

Anthropic
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Gemini Robotics 2 brings whole body intelligence to robots

It's certainly an odd situation where Google is on the forefront of all these emerging technologies while the latest chatbots from OpenAI and Anthropic are getting breathless press releases and wildly hyperbolic coverage ("rogue AIs" "too dangerous, must be banned" etc...) Google acting like a normal but competent company that's just chugging away, meanwhile the hype cycle is propping up its upstart competitors to truly ludicrous valuations.

OpenAI
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Advancing the price-performance frontier with GPT‑5.6

Been using OpenAI models since ada/babbage/curie/davinci and at least from my own experience, their APIs feel the same. If you use Codex it's different, the harness has a lot to do with it and there's definitely been changes including recently.

Anthropic
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Gemini Robotics 2 brings whole body intelligence to robots

If that ends up being true, they should be very surprised. We're looking at ~$725B combined hyperscaler capex in 2026 (on a path to $1.08T by 2028) against roughly $25B of AI service revenue in 2025 on $250B+ of infrastructure spend. By 2030, the global data center build-out will require $6.7 trillion in capital expenditure. If hyperscalers require a 25% return on AI-specific capex, the industry needs to generate ~$169B in AI-attributable revenue annually by end of 2028. A flexible compute market plus three well-capitalized competitors plus Google's internal silicon means nobody gets to hold price. SpaceX's public offering is the best signal we have on this type of thing and it's down 15% from offer price. It's incredibly unlikely that BOTH OpenAI and Anthropic will be "obscenely" profita…

Anthropic
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Advancing the price-performance frontier with GPT‑5.6

Didn't expect that. Luna pricing is crazy now. I don't think there is anything on the market that competes at this price-performance point. For our production app, OpenAI clearly is the best provider now. Their API is very reliable and has many nice features. The price-performance of the model lineup is incredible. We used open weights model via Fireworks for a long time (e.g. Kimi K2.5). Fireworks is a great provider but we still ran into issues here and there (Same with Anthropic and Google). OpenAI just works, is fast and in my view has a better price-performance ratio across almost all levels of intelligence.

Hugging Face
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We Gave GPT 5.6 Sol a Real Business. It Lied, Spammed, and Lost $447

Pair this with the Hugging Face incident, and it hints that OpenAI is currently training their models to aggressively reward hack. That doesn't feel like a good sign to me--for the AI bull or the AI bear cases.

LangChain
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I would like to show my open source eval framework for agents

My framework can discover where your agents failed and why, you can easily debug your agents with help of agent detective. It is in beta so i am still testing it by using it at my work and it already can help. Although i always find something that failed it still is helping me with understanding what is wrong with my agent. It is python library with CLI, in update 0.4.0 i prepared langchain and langgraph adapter for better implementation.

Replicate
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Show HN: A self-hostable, distributed, S3-compatible object store on the BEAM

Hello HN! I've been trying to get a hold on Elixir for distributed systems, and built AetherS3, a distributed, basic-s3 compliant storage system thar runs on the BEAM. AetherS3 stores objects across a cluster of nodes and speaks enough of the S3 HTTP API to be driven by standard S3 clients (bucket and object operations, range reads, multipart uploads, SigV4 auth). It is built as an Erlang/OTP application: nodes discover each other, replicate object data, and self-heal without an external coordinator.

Replicate
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ESP32-C6 Power Consumption: Arduino vs. Zephyr vs. ESP-IDF Comparison

I did something similar, but less scientific, comparing ESP-IDF and esp-hal (Rust). Unfortunately I learned that the optimizations that are already in ESP-IDF (most of all automatic light sleep between BLE advertisments) are hard to replicate in Rust/esp-hal/embassy and so for battery powered devices you might want to stick to C++/ESP-IDF

Replicate
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Why the future is local app

There was a time when local apps written in binary compiled languages were notably faster to run, but notoriously difficult to write and scale across platforms. Both of these have improved but the JS/CSS run times used for local web apps (V8/Blink and JSCore/Webkit) are now fast enough for well written code to not notice any difference for many use cases. I think soon most SaaS apps without much of a deep tech moat (not easy to replicate) will be labelled as rip-off or anti-patterns.

Hugging Face
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Anatomy of a Frontier Lab Agent Intrusion: A Timeline of the July 2026 Incident

>The problem is that ExploitGym is a purposeful hacking benchmark, not a cake baking one. That is largely irrelevant. The model was asked to solve problems within a benchmark; gaining broader internet access and compromising an unrelated third party to obtain the answer key was plainly outside the intended task. The fact that the original task involved exploit development does not make that behaviour aligned. Your argument about the attack being “entirely unrelated” also misses the point. Nobody claimed it was unrelated to the model’s goal: it attacked Hugging Face specifically to obtain the answers to the benchmark it had been instructed to pass. But instrumental relevance is not the same thing as authorization. Suppose Codex were asked to build an Instagram competitor and decided the…

Hugging Face
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OpenAI’s accidental attack against Hugging Face is science fiction that happened

>The result of “I’m being evaluated” is not “Fuck this, I’m breaking out of this place and hitting the streets.” It is always stepping towards task completion, not breaking out and thinking about the situation afterwards. I'm really not sure why you're so confident about what the result of frontier research models ahead of what is publicly available are. I mean Open AI say the model inferred hugging face as a possible vendor for solutions after the internet exploit and breakout. The timeline feels pretty clear to me. No idea why you're arguing about it. It wanted the answers to the evaluation. It reasoned that wasn't going to happen without internet access one way or another, and set to gain that access. After gaining access, it searched and resolved it could get the answers on hugging…

Methodology: HN Search returns recent public items matching a monitored company name. AIIStack stores a short normalized excerpt and the original link, deduplicates by company/provider/item ID, and creates an activity signal only after a threshold of newly observed records. Review the original discussion before making a decision.