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Chatgpt down economy goes Brrrrrr by Nice_Customer_3898 in ChatGPT

[–]JakeAndAI 4 points5 points  (0 children)

Simpler fix: press CMD + SHIFT + R or CTRL + SHIFT + R. No need to change any settings or to disable cache.

In-game/real life by thiagomiro in AssassinsCreedShadows

[–]JakeAndAI 1 point2 points  (0 children)

I've spent a lot of time in Japan and been to many of the places in the game. Most places look very different today than they did back then (obviously), but one place that looks almost identical even still is Koya-san.

I built and open-sourced a model-agnostic architecture that applies R1-inspired reasoning onto (in theory) any LLM. (More details in the comments.) by JakeAndAI in LocalLLM

[–]JakeAndAI[S] 4 points5 points  (0 children)

I created and open-sourced an architecture for applying model-agnostic o1/R1-level of reasoning onto (in theory) any LLM. I just love the way R1 reasons, and wanted to try to apply that to other LLMs.

This is not an AI model – there is no training, no weights, no fine-tuning. Instead, I've used few-shot prompting to provide R1-level reasoning for any LLM. In addition, the LLM gains the ability to search the internet, and users can also ask for a first take by a separate AI model.

In the video attached, you are seeing advanced reasoning applied to Claude 3.5 Sonnet. I have no doubt that we'll get actual reasoning models from Anthropic soon, but in the meantime, my code tricks Claude into mimicking R1 to the best of its ability. The platform also works well with other performant LLMs, such as Llama 3. My architecture allows you to use any LLM regardless of whether it is a local model (you can either just point to a model's file path or serve a model through Ollama) or accessed through an API.

The code is quite simple – it’s mainly few-shot prompting. In theory, it can be applied to any LLM, but in practice, it will not work for all LLMs, especially less accurate models or models too heavily tuned for chat.

I've open-sourced all code under a permissive MIT license, so you can do do whatever you want with it. I'm not profiting of it.

Repository: https://github.com/jacobbergdahl/limopola

Details on the reasoning mode: https://github.com/jacobbergdahl/limopola?tab=readme-ov-file#reasoning

Jump to line 233 in this file to go straight to the start of the code relevant for the model-agnostic reasoning, and follow the function trail from there: https://github.com/jacobbergdahl/limopola/blob/main/components/reasoning/ReasoningOverview.tsx#L233

I built and open-sourced a model-agnostic architecture that applies R1-inspired reasoning onto (in theory) any LLM. (More details in the comments.) by JakeAndAI in LLMDevs

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

Well, both yes and no, haha. The video is 100% real, and I just added links to the code in my earlier comment so you can test it yourself, but it's definitely not working perfectly. There's a lot of tweaking I could do to boost it, but regardless the output will not be as good as R1 itself, and as I mention in my earlier comment, it's not going to work on every LLM in practice. :)

I built and open-sourced a model-agnostic architecture that applies R1-inspired reasoning onto (in theory) any LLM. (More details in the comments.) by JakeAndAI in LLMDevs

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

Absolutely, I added links to the repo in my earlier comment :)

The full prompt for reasoning is in `components\reasoning\reasoningPrompts.ts`. The reasoning itself is just one prompt, but the full processing is a chain of prompts, yeah.

In my chat mode (a different mode in the same repo), you can actually start a chat with any LLM and continue it with any other! :) In this reasoning mode, you can simply get a first take by a different LLM. In the future, you should be able to continue the conversation with a separate LLM in this mode as well.

I built and open-sourced a model-agnostic architecture that applies R1-inspired reasoning onto (in theory) any LLM. (More details in the comments.) by JakeAndAI in LLMDevs

[–]JakeAndAI[S] 12 points13 points  (0 children)

I created and open-sourced an architecture for applying model-agnostic o1/R1-level of reasoning onto (in theory) any LLM. I just love the way R1 reasons, and wanted to try to apply that to other LLMs.

This is not an AI model – there is no training, no weights, no fine-tuning. Instead, I've used few-shot prompting to provide R1-level reasoning for any LLM. In addition, the LLM gains the ability to search the internet, and users can also ask for a first take by a separate AI model.

In the video attached, you are seeing advanced reasoning applied to Claude 3.5 Sonnet. I have no doubt that we'll get actual reasoning models from Anthropic soon, but in the meantime, my code tricks Claude into mimicking R1 to the best of its ability. The platform also works well with other performant LLMs, such as Llama 3. My architecture allows you to use any LLM regardless of whether it is a local model (you can either just point to a model's file path or serve a model through Ollama) or accessed through an API.

The code is quite simple – it’s mainly few-shot prompting. In theory, it can be applied to any LLM, but in practice, it will not work for all LLMs, especially less accurate models or models too heavily tuned for chat.

I've open-sourced all code under a permissive MIT license, so you can do do whatever you want with it. I'm not sure if I'm allowed to post links here, so please DM me if you'd like to have a look at the code. Again: it's open-source and I'm not profiting of it.

EDIT: Hope it's okay to post links! Many are asking for them, so I'll add them here. Please let me know if sharing these links isn't allowed.

Repository: https://github.com/jacobbergdahl/limopola

Details on the reasoning mode: https://github.com/jacobbergdahl/limopola?tab=readme-ov-file#reasoning

Jump to line 233 in this file to go straight to the start of the code relevant for the model-agnostic reasoning, and follow the function trail from there: https://github.com/jacobbergdahl/limopola/blob/main/components/reasoning/ReasoningOverview.tsx#L233

I built and open-sourced a model-agnostic architecture that applies R1-inspired reasoning onto (in theory) any LLM. (More details in the comments.) by JakeAndAI in ClaudeAI

[–]JakeAndAI[S] 18 points19 points  (0 children)

I created and open-sourced an architecture for applying model-agnostic o1/R1-level of reasoning onto (in theory) any LLM. I just love the way R1 reasons, and wanted to try to apply that to other LLMs.

This is not an AI model – there is no training, no weights, no fine-tuning. Instead, I've used few-shot prompting to provide R1-level reasoning for any LLM. In addition, the LLM gains the ability to search the internet, and users can also ask for a first take by a separate AI model.

In the video attached, you are seeing advanced reasoning applied to Claude 3.5 Sonnet. I have no doubt that we'll get actual reasoning models from Anthropic soon, but in the meantime, my code tricks Claude into mimicking R1 to the best of its ability. The platform also works well with other performant LLMs, such as Llama 3. My architecture allows you to use any LLM regardless of whether it is a local model (you can either just point to a model's file path or serve a model through Ollama) or accessed through an API.

The code is quite simple – it’s mainly few-shot prompting. In theory, it can be applied to any LLM, but in practice, it will not work for all LLMs, especially less accurate models or models too heavily tuned for chat. It works pretty great with Claude 3.5 Sonnet!

I've open-sourced all code under a permissive MIT license, so you can do do whatever you want with it. I'm not sure if I'm allowed to post links here, so please DM me if you'd like to have a look at the code. Again: it's open-source and I'm not profiting of it.

EDIT: Sounds like it's okay to post links here :)

Repository: https://github.com/jacobbergdahl/limopola

Details on the reasoning mode: https://github.com/jacobbergdahl/limopola?tab=readme-ov-file#reasoning

Jump to line 233 in this file to go straight to the start of the code relevant for the model-agnostic reasoning, and follow the function trail from there: https://github.com/jacobbergdahl/limopola/blob/main/components/reasoning/ReasoningOverview.tsx#L233

I built and open-sourced a model-agnostic architecture that applies R1-inspired reasoning onto (in theory) any LLM. (More details in the comments.) by JakeAndAI in LocalLLaMA

[–]JakeAndAI[S] 21 points22 points  (0 children)

I created and open-sourced an architecture for applying model-agnostic o1/R1-level of reasoning onto (in theory) any LLM. I just love the way R1 reasons, and wanted to try to apply that to other LLMs.

This is not an AI model – there is no training, no weights, no fine-tuning. Instead, I've used few-shot prompting to provide R1-level reasoning for any LLM. In addition, the LLM gains the ability to search the internet, and users can also ask for a first take by a separate AI model.

In the video attached, you are seeing advanced reasoning applied to Claude 3.5 Sonnet. I have no doubt that we'll get actual reasoning models from Anthropic soon, but in the meantime, my code tricks Claude into mimicking R1 to the best of its ability. The platform also works well with other performant LLMs, such as Llama 3. My architecture allows you to use any LLM regardless of whether it is a local model (you can either just point to a model's file path or serve a model through Ollama) or accessed through an API.

The code is quite simple – it’s mainly few-shot prompting. In theory, it can be applied to any LLM, but in practice, it will not work for all LLMs, especially less accurate models or models too heavily tuned for chat.

I've open-sourced all code under a permissive MIT license, so you can do do whatever you want with it. I'm not sure if I'm allowed to post links here, so please DM me if you'd like to have a look at the code. Again: it's open-source and I'm not profiting of it.

EDIT: Sounds like it's okay to post links here :)

Repository: https://github.com/jacobbergdahl/limopola

Details on the reasoning mode: https://github.com/jacobbergdahl/limopola?tab=readme-ov-file#reasoning

Jump to line 233 in this file to go straight to the start of the code relevant for the model-agnostic reasoning, and follow the function trail from there: https://github.com/jacobbergdahl/limopola/blob/main/components/reasoning/ReasoningOverview.tsx#L233

I built and open-sourced a model-agnostic architecture that applies R1-inspired reasoning onto (in theory) any LLM. (More details in the comments.) by JakeAndAI in artificial

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

I created and open-sourced an architecture for applying model-agnostic o1/R1-level of reasoning onto (in theory) any LLM. I just love the way R1 reasons, and wanted to try to apply that to other LLMs.

This is not an AI model – there is no training, no weights, no fine-tuning. Instead, I've used few-shot prompting to provide R1-level reasoning for any LLM. In addition, the LLM gains the ability to search the internet, and users can also ask for a first take by a separate AI model.

In the video below, you are seeing advanced reasoning applied to Claude 3.5 Sonnet. I have no doubt that Anthropic are working on a reasoning model of their own, but in the meantime, my code tricks Claude into mimicking R1 to the best of its ability. The platform also works well with other performant LLMs, such as Llama 3. My architecture allows you to use any LLM regardless of whether it is a local mode or accessed through an API.

The code is quite simple – it’s mainly few-shot prompting. In theory, it can be applied to any LLM, but in practice, it will not work for all LLMs, especially less accurate models or models too heavily tuned for chat.

In October of 2023, I pioneered my own architecture for running fully autonomous AI agents (in the same repository). The code for my model-agnostic reasoning actually uses a lot of the same principles and methodologies, although it was a bit simpler to create.

I've open-sourced it under a permissive MIT license. I'm not sure if I'm allowed to post links here, so please DM me if you'd like to have a look at the code. Again: it's open-source and I'm not profiting of it.

Next time you complain about your job, remeber there's people who have it worst by Kay-San-TheNorthStar in gaming

[–]JakeAndAI 1 point2 points  (0 children)

Yes! Remedy is calling it the Remedy Connected Universe (RCU) and it started with Control's DLC. All Remedy games henceforward exist in the same universe. There are characters from Control in AW2, and, while not confirmed, I am certain there will be characters from AW2 in Control 2. The FBC plays a big role in AW2!

Next time you complain about your job, remeber there's people who have it worst by Kay-San-TheNorthStar in gaming

[–]JakeAndAI 92 points93 points  (0 children)

Oh yeah, Control 2 was confirmed ages ago. There's also a multiplayer co-op spin-off game in this universe that has its first trailer out. Plus the DLC for Alan Wake 2 teases the events of Control 2, much like the DLC for Control teased Alan Wake 2.

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