For local tasks you can only give agents delegated that execute your deterministic read or write on an allowed set of files(e.g pi does this) and execute rights only on containers with no network access. That should get you 95% unblocked for most tasks you want to do with an LLM pretty safely.
You can do a brainstorming with web on a remote container prototyping based on that brainstorm on another container with no network access.
The one thing that is less trustworthy is using local agents for service management, you definitely want to have them scoped to dev/testing. I would never trust an agent to execute any command in production or sensitive data at all
An so like if a business wanted to home in on one very specific use case that could be hyper optimized by SFT, had really good support for updating and adding new features, on-Prem etc. that’s the kind of market they are in?
Nice. I want to do the same too. What process/workflow did you use to move all the websites you had given your email addresses to, to move to your proton email? I am guessing it will take several years, but I would like to start the move of my gmail.
I would rank it quite close to The worst company to work for tech wise.
I've worked for a bit as a contract worker in their Eikon/Elektron product division(the Bloomberg equivalent).
They have "everything": silos, fiefdoms. Systems team that operated as if the devops model never happened. A CTO they hired @~2015/2016 that had no experience in tech whatsoever. A board which instituted and instructed a cost cutting policy by,for e.g. , but not limited to outsourcing every job possible with little to no tradeoff on quality of engineering. And this was way before AI was a thing.
This left staff engineers with no bargaining power to hire engineers to write good systems.
If you are considering a job there, I would recommend doing some due diligence.
If you did that then you are better off never being targeted by emails/messages by the company at all. It is in the benefit of the company to know that. Right now its a tedious unsubscribe process that requires me to keep doing it all the time and company that does not know just blasts everyone who signed up. Its a ridiculous thing to do.
Caveat here is you may not be able to use their environments or you may or may not have their kind or robots to train your roomba. But at-least you could get an idea of how RL training is done for robots like yours.
This would require an inversion of dynamics based on quantification and collective realization of a couple of things:
0. Emails suffer from a "misclassification" of intent issue on a time*attention scale. Imagine time of the day/week/year on one axis and their attention on email inbox on the other. Emails have to arrive at the right (x,y) point for a user to act on. But they rarely do.
1. Well being of a user is proportional to their current state of mind to receive an message from X. Which is proportional to how likely they are to listen what you have to say.
Both of these suggest a negotiation of messages between two parties, much like when a bartender asks you if you want a refill and you can say yes/no.
Like it seems one needs to re-think email from first principles here. One idea is to use a the idea of "theory of mind"(ToM). e.g. The ToM between me and a sender would be for both to know: "I am not as excited as you about your product launch, so sending it is a 'spam' from my PoV".
We could use two negotiating agent, e.g. my agent that knows what I care about now/today/1-week ago and negotiates with an aspirant sender's agent before they send me any messages. e.g. I could set a policy based (my ToM) for my agent like "Between 1-1:15PM every day I want to read about all product announcements I subscribed to for XYZ product type". My agent would go talk to the aspirant's sender agent and gets messages right then.
An alternative policy could be "I have some free time now, create a summary/gist of all announcements on products I might be interested in.". The agents would negotiate with the sender to do the same.
Signups emails would be to replaced by an agent which "creates" a ToM with sender on hard-stop dates. I would tell my agent : "I am interested in this logging service to compare different ones, I will not be interested once ENG-123 is closed" and mine would not just tell the sender that they are not interested when the time comes (which is when ENG-123 is closed).
Longer term policies would just age out any message negotiations because I don't like/care about those products anymore.
For indie developers like myself, I often use chat GPT desktop and Claude desktop for arbitrary tasks, though my main workhorse is a customized coding harness with CC daemons on my nas. With the apps, b I missed having access to my Nas server where my dev environment is. So I wrote a file system MCP and hosted it with a reverse proxy on my Truenas with auth0. I wanted access to it from all platforms CharGPT mobile, desktop. Same for CC.
For chatgpt desktop and Claude desktop my experience with MCPs connected to my home NAS is pretty poor. It(as in the app) often times out fetching data(even though there is no latency for serving the request in the logs), often the existing connection gets invalidated between 2 chat turns and chat gpt just moves on answering without the file in hand.
I am not using it for writing code, its mostly read only access to Fs. Has anyone surmounted these problems for this access patterns and written about how to build mcps to be reliable?
One thing I have always wanted to do is cancel an AI Agent executing remotely that I kicked off as it streamed its part by part response(part could words, list of urls or whatever you want the FE to display). A good example is web-researcher agent that searches and fetches web pages remotely and sends it back to the local sub-agent to summarize the results. This is something claude-code in the terminal does not quite provide. In Instant would this be trivial to build?
Here is how I built it in a WUI: I sent SSE events from Server -> Client streaming web-search progress, but then the client could update a `x` box on "parent" widget using the `id` from a SSE event using a simple REST call. The `id` could belong to parent web-search or to certain URLs which are being fetched.
And then whatever is yielding your SSE lines would check the db would cancel the send(assuming it had not sent all the words already).
For people like me — who are kind of familiar with how react/jetpack compose/flutter like frameworks work — I recall using react-widget/composables which seamlessly update when these register to receive updates to the underlying datamodel. The persistence boundary in these apps was the app/device where it was running. The datamodel was local. You still had to worry about making the data updates to servers and back to get to other devices/apps.
Instant crosses that persistence boundary, your app can propagate updates to any one who has subscribed to the abstract datastore — which is on a server somewhere, so you the engineer don't have to write that code. Right?
But how is this different/better than things like, i wanna say, vercel/nextjs or the like that host similar infra?
I read the TCP patch they submitted for BSD linux. Maybe I don't understand it well enough, but optimizing the use of a fuzzer to discover vulnerabilities — while releasing a model is a threat for sure — sounds something reducible/generalizable to maze solving abilities like in ARC. Except here the problem's boundaries are well defined.
Its quite hard to believe why it took this much inference power ($20K i believe) to find the TCP and H264 class of exploits. I feel like its just the training data/harness based traces for security that might be the innovation here, not the model.
Here is thought, this is a fixed 3d environment and you lack training data or at least an algorithm to train. Why not use RL to learn good trajectories?
Like build a 3d environment of your home/room and generate images and trajectories in a game engine to generate image data to pretrain/train it, then for each run hand label only promising trajectories i.e. where the robot actually did better cleaning. That might make it a good RL exercise. You could also place some physical flags in the room that when the camera gets close enough it gets rewarded to automate these trajectory rewards.
So my home router, all my iot devices attached to it from printers to projectors, not to mention custom stacks like Lutron. BLE based locks, car key fobs.
All of these technically could have zero day vulnerabilities and people/companies who made it don't have the resources to buy 20000$ of tokens to go debug them... Maybe they don't care but if they do, what if they can't afford such models or get access in time.
I would like to know how can someone like me defend against them?
If you want to get a feel of what brutalist architecture is like up close, go to the Barbican in london if you can.
Its quite surreal. Very much in-your-face concrete exposure. Yet, to walk and experience it with your eyes is a study of contrasts: a giant, comparitively modern, greenhouse, has a glass roof open to the sky and yet many floors have no light or windows at all. And in the outdoor spaces, like the fountain/canal running through the complex the concrete will sort of be in the background and lets you focus on everything else: the water, the swans and the people around.
Juxtapose that to low hanging exposed concrete roofs and walls in closed passages could make one feel constrained/claustrophobic/yearning for light.
I've been using handy since a month and its awesome. I mainly use it with coding agents or when I don't want to type into text boxes. How is this different?
Part of the reason handy is awesome is because it uses some of the same rust infra for integrating with the model, so that actually makes it possible to use the code as a library in android or iOS. I have an android app that runs on a local model on the phone too using this.
For postgres there are pg containers, we use them in pytest fixtures for 1000's of unit-tests running concurrently. I imagine you could run them for integration test purposes too. What kind of testing would you run with these that can't be run with pg containers or not covered by conventional testing?
I'll say this is still quite useful win for browser control usecases and also for debugging their crashes.
You can do a brainstorming with web on a remote container prototyping based on that brainstorm on another container with no network access.
The one thing that is less trustworthy is using local agents for service management, you definitely want to have them scoped to dev/testing. I would never trust an agent to execute any command in production or sensitive data at all