Anyway...

If you are interested, there is also an open-source way to do exactly this and it works with your existing subscriptions and local models too - your data is kept private on your devices.

You can make the game, stream it directly from your AI hub or play it locally on your devices. You can cast it on the TV while converting your phone into a controller (with haptics support) or you can connect physical game controllers for local co-op.

https://github.com/pdparchitect/noodle

The README does not talk about this feature but you can find videos in my twitter account.

Sure, not frontier levels but fine for basic tasks and they are off-the-cloud.

https://github.com/hardbeat920/monocode

But yes, the TUIs are supposed to be lightweight yet it is overall a horrible experience.

Jev is just a reminder that you can use more "traditional" forms of AI (that are not LLMs) and still get remarkable results.

We tend to forget that.

That was a surprise and that is why it went viral.

Code is an abstract concept that is not bound to the physical world and I imagine that future will have some much more of it that it is difficult to comprehend. Everything will be code and more code will be written than ever before.

Code will never going to be solved. The question is how much humans will be involved and I think the evidence is that perhaps just a bit. However, because we are talking about vast libraries of code even if we are involved in under 1% of all code and decision making that is needed around the code, there are still not enough developers out there to take on the task.

I might be wrong :)

Comments URL: https://news.ycombinator.com/item?id=49656260

Points: 1

# Comments: 2

However, this open source project https://github.com/chatbotkit/platform/ does and you can plug OpenRouter or OpenAI keys straight in while keeping your integration work generic. The only downside is hosting it yourself but it is just docker compose up.

When I started working no the trading agent I mentioned above I wanted to see if it can be just a better investor over the long run. The intention was not to do high-frequency trading. As you can see most of the days it is not taking any actions. The losses where down to mistakenly setting the stop losses too close to the top. If it wasn't so careful it might have made some money tbf.

My gut feeling is that AI agents will be able to manage a long-term portfolio much better than a human. Though it is just a gut feeling.

Anyway, I have been running my own trading experiment and so far it has lost a bit of money. That being said I have not tried to optimise anything - just let it do whatever it wants. The losses are small and it might be able to recover later this year. Who knows.

The agent writes a blog about its progress here https://trades.chatbotkit.space/

I am thinking to output all the chat logs to HF as well for research.

You can run your own trading agents that communicate over a message buss in your own terms by downloading the CBK platform and running it locally with your own models. I have also shared my trading blueprint if you want to give it a go. https://chatbotkit.com/hub/blueprints/trader

https://github.com/chatbotkit/platform

...if it fit the project direction.

It is basically a sovereign AI platform for agent orchestration and automation and app building.

Comments URL: https://news.ycombinator.com/item?id=49574741

Points: 3

# Comments: 1

That being said you cannot compare a model with a specialised harness. These are two completely different things.

Am I missing something?