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8/5/25 AI thread
| philosophy 101 weed discussions | 08/05/25 |
| WLMAS, btw | 08/05/25 |
| philosophy 101 weed discussions | 08/05/25 |
| philosophy 101 weed discussions | 08/05/25 |
| philosophy 101 weed discussions | 08/05/25 |
| ,.,.,.,,,.,,.,..,.,.,.,.,,. | 08/05/25 |
| philosophy 101 weed discussions | 08/05/25 |
| ,.,.,.,,,.,,.,..,.,.,.,.,,. | 08/05/25 |
| philosophy 101 weed discussions | 08/05/25 |
Poast new message in this thread
Date: August 5th, 2025 10:48 AM Author: philosophy 101 weed discussions interesting comparison of chatgpt 5 and deekseek r1's reasoning outputs. the new chatgpt5 appears to have a lot more crisp and concise and human like reasoning. tbh it reads a lot like a human taking notes. it will be a lot more cost efficient
https://x.com/jxmnop/status/1952375903658410336
local LLMs are the future
https://x.com/iotcoi/status/1952263680273289337
new hierarchical reasoning model in development
https://x.com/omarsar0/status/1951751651729060081 |
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Date: August 5th, 2025 12:20 PM Author: WLMAS, btw (🧐) can't you basically trust no models "reasoning" output though? that is, the "thinking out loud" part is itself only exposed in a manner that it was programmed to be, not some exposure of the raw inner working of the llm? (http://www.autoadmit.com/thread.php?thread_id=5758545&forum_id=2)#49158472) |
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Date: August 5th, 2025 12:41 PM Author: philosophy 101 weed discussions my understanding is that the newest models' CoT reasoning traces are actually pretty close to the actual inner workings of the model's CoT reasoning tree
after reading this thread in more detail though, i think what is being shown is not chatgpt 5's reasoning trace. it's the actual answer output that it gave. so in reality this post doesn't say anything about any changes/updates to this model's reasoning capabilities |
Date: August 5th, 2025 11:07 AM Author: philosophy 101 weed discussions Introducing Genie 3, the most advanced world simulator ever created, enabled by numerous research breakthroughs. 🤯
Featuring high fidelity visuals, 20-24 fps, prompting on the go, world memory, and more.
https://x.com/OfficialLoganK/status/1952732206176112915 |
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Date: August 5th, 2025 11:09 AM Author: philosophy 101 weed discussions https://www.youtube.com/watch?v=ysPbXH0LpIE
https://www.youtube.com/watch?v=XSZP9GhhuAc
these are actually really good videos on modern prompting methods and structure
some very useful tips here for everyone no matter what you use AI for |
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Date: August 5th, 2025 11:39 AM Author: ,.,.,.,,,.,,.,..,.,.,.,.,,. the hierarchical reasoning paper is interesting and appeared the likely direction to go in. chain of thought is a terrible way to get iterative depth computation from a transformer. recurrent circuits that compute for the necessary period of time is much more like the brain and is more likely to produce generalization benefits than using chain of thought with a verifier (that will only work in the domains you are verifying for). (http://www.autoadmit.com/thread.php?thread_id=5758545&forum_id=2)#49158304) |
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Date: August 5th, 2025 11:40 AM Author: philosophy 101 weed discussions https://xoxohth.com/thread.php?thread_id=5757240&mc=14&forum_id=2#49151205
what are your thoughts on these "moral orientation" "personas" and what exactly do you think causes them? |
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Date: August 5th, 2025 12:15 PM Author: ,.,.,.,,,.,,.,..,.,.,.,.,,. it seems like the models try to construct a consistent character to respond to a prompt. they are guessing what the best character for a particular prompt is (which can be many things since they are trained on the entire web), and sometimes it isn't appropriate. this doesn't seem surprising and is consistent with other LLM behavior. (http://www.autoadmit.com/thread.php?thread_id=5758545&forum_id=2)#49158455) |
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Date: August 5th, 2025 12:35 PM Author: philosophy 101 weed discussions so you think it's incorrect problem solving techniques being associated with "evil" persona traits in the training data? (that seems to be the explanatory mechanism behind what you're saying, imo, correct me if i'm wrong)
that is apparently the leading hypothesis for this, and it's reasonable enough. but it just doesn't seem convincing to me. is there *really* that much of a correlation between these things in the training data? it just doesn't pass the smell test imo |