Hang on, can someone help me understand how these benchmarks work? The post alleges that at least some computer use benchmarks are broken because the model is making direct CDP calls instead of actually interacting with the UI. But the major frontier models' computer use interfaces don't work that way; the model only gets access to a virtual display, and can only provide virtual keyboard and mouse inputs. There are separate browser-use interfaces that offer a CDP connection, but presumably you wouldn't use those if you're specifically designing a computer use benchmark? Is the post just claiming that a lot of impressive demos that people think are of computer use are actually of browser use? I wish it'd been clearer about this.
You lost me at the annoying trail on mouse movement.<p>You advocate for good UI and immediately make some crap that makes it hard to read/use your site. It's kind of ironic.<p>Please stop messing with: selection, mouse cursor, copy/paste, etc.
Lost me even before I realized what was going on. My computer is too slow to handle the tricks they are pulling. I think you are right, but their "cool" things were too slow and made a mess of my screen without having any relation to what I am doing now (because I did it seconds ago)
They work on real-time computer use input. One of the areas in this space, mouse movement, is sophisticated enough there are people with PhDs working on the problem of human-like mouse movement, which requires you to record time-series (trailing) data of physical mouse movement based on human hand, wrist, and arm movement and replicating position, acceleration, and velocity data.<p>It's also just a mouse trail, get over it. It's not an interesting comment.
Meta: I like that the first comments are not about the model at all but the website's mouse trail. One is in favor and one is against. Sums up society pretty well hahaha.<p>On the model. Really cool that it can act every 70ms. That's more than 10x faster than TTFT in most inference APIs. It HAS to be a local model. No idea which family or which one it is or what hardware it runs in. These would be nice details to tease!
We have 2 paths here:<p>- either evolve our UI systems for computers and let them operate efficiently, i.e. converting everything to API calls
. Frontier labs are pushing for this, starting with the Chrome plugin that Claude Cowork mandates.<p>- or make AI systems use the screen like humans do - what the article is arguing for<p>Both of these paths are possible. One of them is much more efficient than the other in the long term. Another one may be inevitable.
> - either evolve our UI systems for computers and let them operate efficiently, i.e. converting everything to API calls . Frontier labs are pushing for this, starting with the Chrome plugin that Claude Cowork mandates.<p>Yea, hasn't worked so far, devs and orgs have been pushing for APIs ages, same with structured data, eg schema.org<p>The third option is agent to agent communication, mcp, etc.
Looking how much agents like to use and push to have functional a11y trees, we may accidentally solve accessibility as well
Is no benchmark properly sandboxed? It feels like every single the logs are provided for a benchmark run the LLM is cheating in a way that should have been clearly blocked by a sandbox or the harness.
that's what a lot of 'a.i' companies miss - unless you've formerly QA devs deployed as Forward Automation Engineers - writing scripts to automate most tasks done by humans in a service economy - by the time the a.i bubble busts it will all about the promise about a.i to transform the economy while it was near achieved.<p>browser automation, RPA etc can bring us closer to agentic workflows since most software doesn't provide an API.
Agreed and a lot of companies seem to have their head in the sand, just hoping AI agents will magic their way through the legacy<p>But I don't think RPA is the way. Or at least, not in the current state. I think AI agents with proper computer use are what RPA should be. Usual RPA is too brittle and maintaining it often requires more work than just doing the work
The little pencil effect is a nice touch.
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every decade someone rediscovers that the bottleneck was never the model, it was the mouse. we built APIs to avoid this exact problem and then asked the AI to ignore them and click buttons like an intern