This is a weird thing to call out, when there's so much else to talk about (price, specs, etc) buuuuuut-
Check out the gameplay video partway down the page, where the two people are on the couch playing Cuphead. Right under "Your Steam library in more places."
It's just... a real clip of real people playing a real game and reacting in a real way. It's funny. I know it's stupid to call out, but how many exaggerated versions of this scene have you seen before? And Valve is smart enough to say "Let's just film two people playing a real game and snip a nice, realistic reaction shot from it."
I've used Hermes Agent in a container, and it worked ok. Little rought around the edges, but that's to be expected.
But what I didn't understand... what benefit does it actually bring? On a default loadout, even after disabling tons of skills in the setup wizard, there were lots of useless garbage skills enabled, over 10k of context used just to list them all.
I vibe-coded my own harness that uses ACP so it supports any coding CLI that exposes ACP (copilot cli, opencode, basically every popular one with official or non-official wrappers). And I was able to achieve basically exactly what I wanted from any Claw-like agent, in like a few hours.
I know there's way, way more to these self-sufficient agents (compaction, memory system, etc) but in my mind, it feels like the closer you can be to a barebones "coding agent core" plus "gateways that point to it" the better.
I've been wondering about adaptive decoding! It seems obvious to me that at some points during decoding (reasoning, "creative thinking") you would want a higher temperature, while at other points (emitting syntactically correct code, following a plan that was already established) you would want lower temperature.
Not really? If you read it, there is no validation, no correctness signal, no verification, none of that. They're just passing in benchmark inputs, collecting the outputs (regardless of their quality), training on those outputs, and then sweeping the decode settings (temp, topk) of the resulting model. Their conclusion is that this results in a better model than the original - even when taking into consideration the same temp/topk sweep of the original.
So no, they are not fine-tuning a general purpose model to produce "valid benchmark code results."
I find the branding to be a little odd. Like, it should be a github page with a README that says "here's how to use this." Like, the full explanation of this project is right there in the HN title: "The free AI already on your Mac."
I guess LLMs have made it too simple to instantly build startup landing page slop, which causes this? Like, do we need to see the github star count chart? Do we need all the buzzwords and stuff? You'd think this was a startup trying to get a billion dollar evaluation. It feels disingenuous.
> x402 is an open, neutral standard for Internet-native payments. It lets anyone on the Internet easily charge, and any client pay on-demand, on a pay-per-use basis. A client, such as an agent, sends a HTTP request and receives a HTTP 402 Payment Required status code. In response, the client pays for access on-demand, and the server can let the client through to the requested content.
Fascinating. Cloudflare is envisioning a future where agents are given debit cards by their owners, so they can autonomously send microtransactions to website owners to scrape content or possibly purchase goods on the owner's behalf. I don't know how I feel about that but there's no doubt it's a fascinating concept.
Brb, setting up a honeypot that always responds with HTTP 402 Payment Required demanding 10cents per visit... That's the next "selling 1 million pixels on my website for $1 each", I guess
How much of these sorts of patches are specifically checking if a certain application is running, and then changing behavior to match what that application expects? And how much of it is simply better emulating the Windows API in general?
I think there are benefits to both approaches, not criticizing either one. I'm just curious if the implementation of a patch like this is "We fixed an inconsistency between Wine and Windows" vs "We're checking if Photoshop is running and using a different locking primitive" or whatever.
if I'm not mistaken (and I very well may be!) my primary confusion with closures comes from the fact that: the trait they implement (FnOnce / Fn / FnMut) depends entirely upon what happens inside the closure.
It will automatically implement the most general, relaxed version (FnMut I think?) and only restrict itself further to FnOnce and Fn based on what you do inside the closure.
So, it can be tricky to know what's going on, and making a code change can change the contract of the closure and therefore where and how it can be used.
(I invite rust experts to correct me if any of the above is mistaken - I always forget the order of precedence for FnOnce/Fn/FnMut and which implies which)
no payoff whatsoever? I just asked Claude to do a task that would have previously taken me four days. Then I got up and got lunch, and when I was back, it was done.
I would never make the argument that there are no risks. But there's also no way you can make the argument there are no payoffs!
> former Dean of Electronics Engineering and Computer Science at Peking University, has noted that Chinese data makes up only 1.3 percent of global large-model datasets (The Paper, March 24). Reflecting these concerns, the Ministry of State Security (MSS) has issued a stark warning that “poisoned data” (数据投毒) could “mislead public opinion” (误导社会舆论) (Sina Finance, August 5).
from a technical point of view, I suppose it's actually not a problem like he suggests. You can use all the pro-democracy, pro-free-speech, anti-PRC data in the world, but the pretraining stages (on the planet's data) are more for instilling core language abilities, and are far less important than the SFT / RL / DPO / etc stages, which require far less data, and can tune a model towards whatever ideology you'd like. Plus, you can do things like selectively identify vectors that encode for certain high-level concepts, and emphasize them during inference, like Golden Gate Claude.
I truly, genuinely wanted to like Liquid Glass. I think the default reaction to ANY change in UX, even changes that are generally improvements, is: "I don't like this, it's different!"
I thought that'd be the case for ios 26. But after installing it... yeesh. I can barely see anything. It's just awful.
I set up pi-hole recently after hearing about it for years. I was kind of surprised at a lack of really basic features (imo):
There isn't any kind of "dry run" or "phantom" mode, where requests are not actually blocked, but appear marked in the log UI as "would be blocked". This is super important because I want to see all the things my home network is doing that would be blocked before I actually hit the big red button. I want to fix up the allow/denylist before going live.
It's also not possible (or not clear) how to have different behavior for different clients. For my "smart tv" which I begrudgingly have to allow on my network occasionally for software updates, I want to treat it with the strictest possible list. But for my phone, I don't want that same list. There's a concept of "groups" so perhaps this is user error on my part, but the UI does not make this clear.
Check out the gameplay video partway down the page, where the two people are on the couch playing Cuphead. Right under "Your Steam library in more places."
It's just... a real clip of real people playing a real game and reacting in a real way. It's funny. I know it's stupid to call out, but how many exaggerated versions of this scene have you seen before? And Valve is smart enough to say "Let's just film two people playing a real game and snip a nice, realistic reaction shot from it."