miguelaeh

This is a "search engine" I built a couple of weeks ago while thinking about the agentic economy. Our agents need a way to find other agents and tools that help them complete complex tasks.

It can be used as an MCP or via A2A, your agent can find other agents and tools based on intention like "booking flight form SVQ to SFO" and get the ranked results.

It also contains filters for different protocols, auth levels, etc.

The internal ingestion tests every single public endpoint to eliminate those that are not really available, so every entity marked with "ready" can be used right away by your agents.

There is an event on the Frontier Tower today to talk about this paper in case someone is interested

> Most importantly, you need to carefully engineer the learning process, so that you are not simply compiling an ever growing laundry list of assertions and traces, but a rich set of relevant learnings that carry value through time. That is the hard part of memory, and now you own that too!

I am interested in knowing more about how this part works. Most approaches I have seen focus on basic RAG pipelines or some variant of that, which don't seem practical or scalable.

Edit: and also, what about procedural memory instead of just storing facts or instructions?

Hey there! Nitpicks creator here.

I built Nitpicks initially because I was tired of PMs sending me small screen recordings with changes they wanted, so that it automatically implemented them for me.

Then, I was very surprised by the good results that it was producing so I decided to convert it into an actual product others can use. It is really useful for non-technical people in a product team. The whole team can now contribute to the product even if they have no idea of how to code, it's just a click and record the screen.

I would love to see you trying it out and sharing your feedback. Feel free to reach out directly to the email at the footer of the page.

You should add some way of contact in the website

Hi HN!

I believe there are many issues for devs and users with the current approach of copy-pasting AI provider API keys into applications.

I have built brainlink.dev as a solution to this and would love to get your feedback.

It is a portable AI account that users can connect with one click to every application that integrates the SDK. It works as follows:

1. The user clicks the connect button to link his brainlink account with the app. 2. The app obtains an access token to perform inference on behalf of the user, so the user pays for the usage.

Behind the scenes, a secure Auth Code Flow with PKCE takes place so that the app obtains an access and refresh token instead of directly an API key. When the application calls a model providing a user access token, the user pays for the inference.

I believe this approach offers multiple benefits to both, developers and users.

As a developer:

- I can build and test my app against a specific model without being tied to what API key the user provided, ensuring that everyone gets the same UX.

- I can easily move my app to a different model at any time. Without brainlink, if users add, let's say, an OpenAI API key, to change to Claude I would need to ask every user to update their API key.

- Asking for API keys goes against the ToS of most providers

As a user:

- The initial friction of configuring API keys disappears, especially for non-technical users who don't know what's an API key.

- My privacy increases because AI providers can't track my usage as it goes through the proxy.

- I have a single account that I can connect to multiple apps and see how much each app is consuming

- I can easily revoke connections (tokens)

I tried to make it very simple to integrate with an embeddable button, but you can also create your own button. Here is a live demo with a very simple chat: https://demo.brainlink.dev

I would love to hear your feedback and would be happy to help anyone who wants to integrate it.

Cool! Are you indexing the web or just using a search engine like Bing? I understand that using a search engine is a problem because your results will be as good as those of the search engine

I have been recently exploring and testing this approach of offloading the AI inference to the user instead of using a cloud API. There are many advantages and I can see how this could be the norm in the future.

Also, I was surprised by the amounts of people that have GPUs and how well SLMs perform in many cases, even those with just 1B parameters.

I am betting on local AI and building offload.fyi to make it easy to implement in any app

Wow. I didn't know that. It's crazy.

I am aware of the legal and tax burdens that many entrepreneurs suffer because of the exit tax. That's the reason why many of them (me included) decide to open their companies directly in the U.S., which makes Spain to continue becoming more poor.

I really don't understand how we passed from being the biggest world empire to where we are right now in barely 500 years.

The first cars, networks, and many other things were not unexpensive. They became so with time and growing adoption.

Cost of compute will continue decreasing and we will reach that point where it is feasible to have AI everywhere. I think with this particular technology we have already reached a no return point

I am from Spain, the system is just a joke. It is not taxing the wealthy people, just those wealthy enough to live well but not worth creating a holding company, which is in most cases working people with well-paid jobs and not the so hated businessman.

You're welcome! Let me know if you plan to integrate local models as mentioned in other comments, I am working on something to make it transparent.

I don't think the point here should be the cost, but the fact that you are sending everything you write to OpenAI to train their models on your information. The option of a local model allows you to preserve the privacy of what you write. I like that.

I am a Grammarly user and I just installed Scramble to try it out. However, it does not seem to work. When I click on any of the options, nothing happens. I use Ubuntu 22.04.

Also, to provide some feedback, it would be awesome to make it automatically appear on the text areas and highlight errors like Grammarly does, it creates a much better UX.

I guess what some people do not understand is that K8s was created internally at Google, for managing their services and handling millions of users.

For new projects that, with luck, will have a couple hundred users at the beginning it is just overkilling (and also very expensive).

My approach is usually Vercel + some AWS/Hetzner instance running the services with docker-compose inside or sometimes even just a system service that starts with the instance. That's just enough. I like to use Vercel when deploying web apps because it is free for this scale and also saves me time with continuous deployment without having to ssh into the instances, fetch the new code and restart the service.

Wow. This is wild!

Good to know! I will try with a VPN then!

This is something that worries me a lot too. For context, two years ago I left my job at a big tech company to build a startup. It failed, but I still have the energy to build new stuff, so that's what I am doing. My internal conflict today is that when I left it, my worst-case scenario was to just go back to a similar job but with more experience. Now, with AI, everything is going to change, and maybe the opportunity cost of what I am doing today is extremely higher than I expected it to be when I left in case nothing goes well.

There is some genetic part, but I would say this also highly depends on the environment where you grow up. From my observation, people who grow up in villages are smarter than people who grow up in the city. They just know more about the world, the nature, the have been more "free" as it was safer for them to explore the environment. As you grow, being considered smart is usually more related to business, and I would say it is actually a matter of how good you are predicting the future. We all can learn the same things, just putting in more or less time, but what is more complex to change is the internal process you follow to reach a conclusion, and that's basically based on your previous experiences. So, the more things you live, the more things you interact with, the more technologies you learnt, the more books you read, etc is what makes you "smarter", basically because your internal thinking process has more information to contrast.

It's hard to know yet since it is not open to everyone, most of us can just see the demos, which are usually created to impress.

I don't see the gotcha, that's how it is supposed to work. It's just their purpose

Hello!

I have recently been working on the platform that you can see in the video. It allows automating tasks that depend on live video inputs without having to maintain any infrastructure. You just connect your video sources and select some filters that will extract structured data from them. Then you can process that data in a loop to perform any action you can code.

We are applying the concept of stateless and stateful serverless functions to computer vision, allowing to develop applications really fast and that can run embedded on devices or in the cloud

I guess lossing connection in a specific area has considerable less impact that leaving a whole country without a payment system.

Also, replacing digital payment systems by decentralised blockchains does not mean replacing cash. Those can and probably will coexist

I see your point, but how I see it is, blockchain is right now what internet was at its very beggining, new layers will be added with time solving every one of those problems.

Yeah, cash is an option in Spain, however, most people, specially young people, is more likely to just carry their card and no cash.

We are adding support for inference servers to Pipeless. We started by the ONNX Runtime, and OpenVINO, CoreML, CUDA and TensorRT execution providers. Some people mentioned me to integrate also with the Triton server, however I still need to deep into that and check its license. The good part is, there is no cold start right now, at the cost of having some resources allocated from the node start.

Definitely! It is something I was thinking to do, I just did not find the time yet. I think allowing people to automatically load models from the Roboflow universe would be awesome!

Hi!

It is so cool you shared this repo. I am the developer behind it, hope you enjoy it and can provide some valuable feedback!

This contains a tutorial about how to react to computer vision events in real time. It also contains the example code so you can execute it and play with it.