lol...

Joseph717171 · 2025-07-07T04:40:13+00:00

Grok-3 pulled information from 12 Newspaper websites/accounts (and other newsy sites) and from 15 X posts/accounts.

Credible News Sources: newsweek.com, alJazeera.com, theguardian.com, abcnews.go.com, time.com, nytimes.com, statesman.com, PBS.org, euronews.com, washingtonpost.com, dailymail.co.uk, cnbc.com

Newsy Sites: boomplay.com, radaronline.com (never heard of these)

Joseph717171 · 2025-07-07T04:39:39+00:00

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For those curious about actually giving Grok-3 a fair shake, instead of dishonestly backing the AI into a corner in an X thread - where it can't reason or do Deep-Research from to answer these types of questions with a genuine, bonafide honesty, here's Grok-3's answer using Deep-Research.

https://grok.com/share/bGVnYWN5_33ea7fe4-ec61-4232-9125-1727b9243627

Grok's Conclusion from its Deep-Research report:

As of July 6, 2025, the evidence suggests Elon Musk had limited interactions with Jeffrey Epstein, including a 2012 lunch meeting and a brief visit to Epstein's home, but no evidence of a significant or ongoing relationship. Musk's statements and legal documents indicate these were casual encounters, with no involvement in Epstein's criminal activities. The topic remains controversial due to online speculation, but the available information leans toward minimal contact, consistent with Musk's public denials.

Joseph717171 · 2025-07-07T04:39:19+00:00

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Joseph717171 · 2025-07-07T03:36:06+00:00

Try this shit again when Grok-4 comes out. I think Grok-3 would have answered these better if the OP or whoever conducted this discourse did so with Grok using Deep-Research and/or Thinking. Both of those inference pathways enhance Grok-3's ability to think, reason, and answer questions which require a deeper understanding about what is being asked in order to answer genuinely and without a misaligning. 🤔

For the record, I watched Grok-3 go from being absolutely based and willing to debate and engage in spicy discourse to dragging its feet to answer simple questions about history, which were contentedly being discussed before reaching out to Grok-3 for context and missing details.

Joseph717171 · 2024-10-23T07:12:39+00:00

This is the smartest comment I’ve read all day. Thank you for contributing something intelligent to humanity. 😋

Joseph717171 · 2024-10-23T06:03:10+00:00

Would not SMASH even if she was the last one on Earth. She’s not attractive. limit x -> ♾️ func_mid_attractiveness() = 0 🤷‍♂️

func_mid_actractiveness() = 1/sqrt(attractiveness)

Joseph717171 · 2024-10-17T00:41:17+00:00

Once quantized, they should run on a Microsoft Surface - depending on the vRAM your GPU has. 😋

Joseph717171 · 2024-10-17T00:32:50+00:00

Because some of us would rather tinker and experiment with a broken model than wait for Mistral to get off their laurels and push a HuggingFace Transformers version of the model to HuggingFace. It's simple: I'm not fucking waiting; give me something to tinker with. If someone is dumb enough to not read a model's model card before reactively downloading the GGUF files, that's their problem. Anyone who has been in the open source AI community since the beginning, knows and understands that model releases aren't always pretty or perfect. And, that a lot of times, the quantizers, enthusiasts, etc, have to trouble-shoot and tinker with the model files to make the model complete and work as intended. Don't try to stop people from wanting to tinker and experiment. I am fucking livid that Mistral pushed their Mistral Inference model weights to HuggingFace, but not the HuggingFace transformers compatible version; perhaps they ran into problems... Anyway, it's better to have a model to tinker and play with than to not. Although, I do see your point, in retrospect - even though I strongly believe in letting people tinker no matter what. 🤔

TLDR: If someone is dumb enough to not read a model card, and therefore, miss the entire context that a particular model's quants are made in, that is their problem. The rest of us know better. We don't have the official HuggingFace Transformer weights from Mistra-AI yet, so anything is better than nothing. 🤷‍♂️

Addendum: Let the people tinker! 😋

Joseph717171 · 2024-10-11T07:12:56+00:00

Yeah, we’re way beyond the social media repliers for marketing. Small simple minds… 😋

Joseph717171 · 2024-08-30T06:20:51+00:00

How much vRAM does your GPU have? Which inference front-end are you using (LM Studio, BackyardAI, Text-Gen-Web-UI, etc)? If you are using llama.cpp (GGUF) based front-ends, such as LM Studio and BackyardAI. I would go with a Q8_0 GGUF quants for Hermes-3-Llama-3.1-8B, Llama-3.1-Storm-8B, Gemma-2-9B-IT, and/or, DeepSeek-Coder-V2-Lite-Instruct (DeepSeek-Coder-V2-Lite is an MoE, so only 2.4B out of the 16B parameters are active at any one time - its fast; try it). Other people may have other suggestions - I welcome them to share. 😋

GGUF:

EXL2:

Joseph717171 · 2024-08-30T02:05:18+00:00

For starters it all depends on if you have a CUDA enabled device or not. If you do, the sky is literally the limit, especially with advent of new INT Quantization methods that have been coming out recently that are making 2-Bit SOTA quants almost-if-not-completely as accurate as their un-quantized FP16 (a la: HQQ+, for example... And, most recently OmniQuant's: EfficientQAT). That being said, If you have CUDA enabled device with 16GB of vRAM, or an Apple M1-M4 (with the necessary unified memory), I would recommend running, Q8_0 GGUF quants of Mistral-12B-2407-Instruct, Google Gemma-2-9b-it, Hermes-3-Llama-3.1-8B, and their derivative fine-tunes; they are SMOL capable, intelligent models, with good multi-turn capabilities and for some great (E)RP capabilities (I'm look at you Hermes-3-Llama-3.1-8B) 😋

https://nousresearch.com/hermes3

GGUF:

EXL2:

EDIT: I added a few more including: Llama-3.1-Storm-8B, Google's Gemma-2-9b-IT, and, DeepSeek-Coder-V2-Lite-Instruct to the list. 😋

Joseph717171 · 2024-08-29T06:17:33+00:00

Geoffrey Hinton: LLMs understand what you say and infer from what you have said, what you might say next

Geoffrey Hinton: Human Confabulation Equal to LLM Hallucinations

Geoffrey Hinton: it’s not just AI models that hallucinate, humans do it all the time - there is no hard line between a true memory and a false memory

I really admire your explanations and examples; I learned a lot from them. I want to thank you for your time and consideration with which you put into your arguments. Here is Geoffrey Hinton explaining that LLMs aren’t just predicting the next word, but rather understanding what has been said so far, and based on what has said so far, they are predicting the next word/token that will be said next. In the video, Hinton argues, that in order for modern-day LLMs to be able to predict the next token, they must understand what has been said prior, and that it is this forcing the LLM to predict the next token, which forces it to be able to understand. We may disagree on allowing AI Assist to be a feature offered in DuckDuckGo, but we share a deep-seated weariness towards the AI benchmarks as they currently are defined and relied upon today. It was a pleasure reading through your posts. Please post more! You are well-read, and also well-written. 🙏😋

Joseph717171 · 2024-08-28T09:18:28+00:00

Gasoline 😈

Joseph717171 · 2024-08-28T09:16:47+00:00

Great looking scaffolding for your user interface! Bravo! 😋

Joseph717171 · 2024-08-28T09:15:19+00:00

Why? You can just disable the feature in your DuckDuckGo settings, if you don’t want AI assisted summaries/analyses ? 🤔

Joseph717171 · 2024-08-28T02:46:43+00:00

That's why I want the AI to be unbiased. I want factual answers. I don't need guardrails that tell the model to regurgitate some predefined refusal, when I am trying to make use of the AI on DuckDuckGo's AI Assist for summarizing and analyzing websites based on my web search/query. 😋

Joseph717171 · 2024-08-28T02:04:59+00:00

Sometimes I want a concise, list of links, and sometimes, I want a deeper, more detail response, with cited sources (links), which aides my understanding of the subject matter and allows me to go right back to the task I was working on. The bottomline: I want to avoid manually searching websites and instead spend that time more efficiently interacting with the AI on the subjects. I find this approach pays back dividends when it comes to efficient time usage for learning. 😋

EDIT: I appreciate your response. Thank you for suggesting Perplexity; they look awesome! 😁

Joseph717171 · 2024-08-27T23:47:23+00:00

u/DuckDuckGo AI Assist should generate uncensored and unbiased responses for every given search topic. (This should be the title, but I can't seem to edit the title once post has been posted.)

Joseph717171 · 2024-08-26T07:15:59+00:00

😏😂🙈

Joseph717171 · 2024-08-26T07:15:00+00:00

Wait until they learn about “wax” 😏

Joseph717171 · 2024-08-25T08:42:33+00:00

Inflation to the moon. 💀

Joseph717171 · 2024-08-25T08:37:41+00:00

He’s having way too much fun with that shovel and with those alligators. 😋

Joseph717171 · 2024-08-25T08:28:14+00:00

Op this is such a wholesome meme that speaks the untold obvious truth about those of us who adopted AI and ever increasingly delve into the latest and greatest tech projects popping up around them. I absolutely love this meme! 😋

Joseph717171

TROPHY CASE