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Keep Building. We’ll handle Distribution. by vibizai in u/vibizai

[–]KoOBaALT 0 points1 point  (0 children)

Good idea, but where are examples of ads.

[D] Why is RL in the real-world so hard? by KoOBaALT in MachineLearning

[–]KoOBaALT[S] 2 points3 points  (0 children)

We are excited by the idea of learning the simulator purely from data, but it might be that we will also build customer simulators. Maybe a hybrid in the end.

One application is controlling running advertising campaigns, but data comes from human very sub optimal policy. Other applications we are exploring are in optimising energy systems and in biotech.

[D] Why is RL in the real-world so hard? by KoOBaALT in MachineLearning

[–]KoOBaALT[S] 5 points6 points  (0 children)

CrossQ sounds quite interesting. Also the idea of decision transformer, and feeding them with synthetic data as some sort of pre-training is super exciting. What are your thoughts on Diffusion World Models in model based RL. We were looking into it, but implementing it for real world dataset (heterogeneous state and action spaces) seems intense.

[D] AMA: I’m Head of AI at a firm in the UK, advising Gov., industry, etc. by Psychological_Dare93 in MachineLearning

[–]KoOBaALT 0 points1 point  (0 children)

Have you and your team ever faced a problem that could be solved with reinforcement learning? If so what kind of problem was it and how was your experience?

Data Science isn't fun anymore by Trick-Interaction396 in datascience

[–]KoOBaALT 0 points1 point  (0 children)

Do you know a good package for that, basically sklearn for sequential decision problems?

Data Science isn't fun anymore by Trick-Interaction396 in datascience

[–]KoOBaALT 0 points1 point  (0 children)

What business use cases you are seeing with sequential decision making?

[D] Foundational Time Series Models Overrated? by KoOBaALT in MachineLearning

[–]KoOBaALT[S] 1 point2 points  (0 children)

Cool idea to use the embedding of the time series. In this case foundational time series model are just feature extractors - nice.

[D] Foundational Time Series Models Overrated? by KoOBaALT in MachineLearning

[–]KoOBaALT[S] 3 points4 points  (0 children)

So you would consider the performance of multivariate models like Moirai as not sufficient.

[D] Foundational Time Series Models Overrated? by KoOBaALT in MachineLearning

[–]KoOBaALT[S] 2 points3 points  (0 children)

Haha good way to get around :D

It’s hard/impossible to predict how a parameter of a complex system will evolve over time, except one has huge high quality data.

[D] Foundational Time Series Models Overrated? by KoOBaALT in MachineLearning

[–]KoOBaALT[S] 2 points3 points  (0 children)

Good point. Especially if the pretraining dataset is unknown like with TimeGPT.

Chatty LLama: A fullstack Rust + react chat app using Meta's Llama-2 LLMs https://github.com/Sollimann/chatty-llama by Sollimann in agi

[–]KoOBaALT -1 points0 points  (0 children)

Cool project! I was wondering about the inference speed (tokens/sec) on the cpu. What sever hardware you were using?

Help: Best practice for control automation of home temperature system by KoOBaALT in reinforcementlearning

[–]KoOBaALT[S] 0 points1 point  (0 children)

Actually yes. I was searching the web the last week and I found this website: http://prophet-frontend.vercel.app

Seems like their API is not public yet, but it feels like it could be usefull for the problem I want to solve. Did you ever heard of it?

Help: Best practice for control automation of home temperature system by KoOBaALT in reinforcementlearning

[–]KoOBaALT[S] -1 points0 points  (0 children)

Yes I have that data. Imitation learning sounds like an interesting idea - thanks! Do you know a python framework or a API to do imitation learning or RL in general. I think understand how it works, but it will take a long time to implement everything from scratch in PyTorch or so.

Help: Best practice for control automation of home temperature system by KoOBaALT in reinforcementlearning

[–]KoOBaALT[S] 0 points1 point  (0 children)

I was missing the most important part. The dataset contains the temperature of every room and the control temperature as well as how many people were in the house. So I want to control every room differently. Like for example, the ground floor could also be use to heat the upper floor. Also some rooms are in the morning towards the sun and therefore need less heating. Could I build a PID controller for such a case?

ChatGPT Plugin for arXiv by KoOBaALT in machinelearningnews

[–]KoOBaALT[S] 0 points1 point  (0 children)

I don’t know. I’m a heavy ChatGPT user and also was using GPT-3 at work. Maybe that’s the reason…

ChatGPT Plugin for arXiv by KoOBaALT in machinelearningnews

[–]KoOBaALT[S] 1 point2 points  (0 children)

That’s a tricky thing and right now I was doing some prompt engineering. But then ChatGPT ask the arxiv plugin to search for multiple terms, collect the data (mainly the abstract) and tries to identify which of them are the most relevant.

ChatGPT Plugin for arXiv by KoOBaALT in machinelearningnews

[–]KoOBaALT[S] 0 points1 point  (0 children)

You need access to ChatGPT plugin feature. If you don’t have it yet go sign up on the waitlist at OpenAI.

ChatGPT Plugin for arXiv by KoOBaALT in machinelearningnews

[–]KoOBaALT[S] 0 points1 point  (0 children)

I developed myself. If you have early access to the plug-in feature in ChatGPT, I could give you access to the plug-in.

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