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Website links that automatically improve its accuracy by using assistance from a Large Language Model (LLM)
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1Jean Louis PRO
JLouisBiz
AI & ML interests
- LLM for sales, marketing, promotion
- LLM for Website Revision System
- increasing quality of communication with customers
- helping clients access information faster
- saving people from financial troubles
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Website links that automatically improve its accuracy by using assistance from a Large Language Model (LLM)
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Website links that automatically improve its accuracy by using assistance from a Large Language Model (LLM)
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universeofml/DeepFocus-X3:If it is fork of a DeepSeek, why do you choose different license and ask people to register first?
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Article
Website links that automatically improve its accuracy by using assistance from a Large Language Model (LLM)
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If it is fork of a DeepSeek, why do you choose different license and ask people to register first?
#2 opened about 7 hours ago
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JLouisBiz
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**Video**: https://www.youtube.com/watch?v=jRKRsGsLfW0
**Integrating large language model with file manager to describe your illegally downloaded movies.**
When you have a bunch of movies downloaded by Torrent, you maybe want a description and description is missing. This video shows how you can use the script to invoke the large language model. And then you get a description of a movie in a second or three.
**Integrating large language model with file manager to describe your illegally downloaded movies.**
When you have a bunch of movies downloaded by Torrent, you maybe want a description and description is missing. This video shows how you can use the script to invoke the large language model. And then you get a description of a movie in a second or three.
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🚀 We tried something new!
We just published a dataset using a new (for us) preference modality: direct ranking based on aesthetic preference. We ranked a couple of thousand images from most to least preferred, all sampled from the Open Image Preferences v1 dataset by the amazing @data-is-better-together team.
📊 Check it out here:
Rapidata/2k-ranked-images-open-image-preferences-v1
We're really curious to hear your thoughts!
Is this kind of ranking interesting or useful to you? Let us know! 💬
If it is, please consider leaving a ❤️ and if we hit 30 ❤️s, we’ll go ahead and rank the full 17k image dataset!
We just published a dataset using a new (for us) preference modality: direct ranking based on aesthetic preference. We ranked a couple of thousand images from most to least preferred, all sampled from the Open Image Preferences v1 dataset by the amazing @data-is-better-together team.
📊 Check it out here:
Rapidata/2k-ranked-images-open-image-preferences-v1
We're really curious to hear your thoughts!
Is this kind of ranking interesting or useful to you? Let us know! 💬
If it is, please consider leaving a ❤️ and if we hit 30 ❤️s, we’ll go ahead and rank the full 17k image dataset!
- 4 replies
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nomadicsynth's
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1 day ago
And here's a thought: What if the rich, instead of hoarding these tools, actually had something more to offer? Could it be that they've honed their skills in the crucible of privilege? Because after all, you can't take intelligence from a Harvard-educated billionaire and simply give it to the next-door neighbor.
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What if intelligence didn’t belong to the rich?
What if insight, planning, and innovation were available to everyone?
What if we actually leveled the playing field — not by force, but by toolset?
What if insight, planning, and innovation were available to everyone?
What if we actually leveled the playing field — not by force, but by toolset?
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🎨 Designers, meet OmniSVG! This new model helps you create professional vector graphics from text/images, generate editable SVGs from icons to detailed characters, convert rasters to vectors, maintain style consistency with references, and integrate into your workflow.
@OmniSVG
@OmniSVG
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Do chatbots lie about Céline Dion? We now have answers, not speculation.
Ai2 just released OLMoTrace and it's a game-changer for transparency. You can literally see where an AI's responses come from in its training data - in real time.
The demo shows results about Céline. So I tried it out myself! Watch what happens in the video.
For journalists, researchers studying hallucinations and anyone who needs to trust their AI, this is like getting X-ray vision into AI systems. When the model made claims, I could instantly verify them against original sources. When it hallucinated, I could see why.
You can finally 1) understand how LLMs actually work and 2) verify if what they're saying is true. No more blind trust.
This pushes the open data movement to the next level.
👉 Blog post: https://allenai.org/blog/olmotrace
👉 Paper: https://www.datocms-assets.com/64837/1743890415-olmotrace.pdf
P.S.: A word of caution: never use a chatbot as a knowledge base. It's not Google. Better use it with a connection to the internet.
Ai2 just released OLMoTrace and it's a game-changer for transparency. You can literally see where an AI's responses come from in its training data - in real time.
The demo shows results about Céline. So I tried it out myself! Watch what happens in the video.
For journalists, researchers studying hallucinations and anyone who needs to trust their AI, this is like getting X-ray vision into AI systems. When the model made claims, I could instantly verify them against original sources. When it hallucinated, I could see why.
You can finally 1) understand how LLMs actually work and 2) verify if what they're saying is true. No more blind trust.
This pushes the open data movement to the next level.
👉 Blog post: https://allenai.org/blog/olmotrace
👉 Paper: https://www.datocms-assets.com/64837/1743890415-olmotrace.pdf
P.S.: A word of caution: never use a chatbot as a knowledge base. It's not Google. Better use it with a connection to the internet.
- 1 reply
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1 day ago
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https://www.youtube.com/watch?v=84iS3atFQdI
**Speech typing in Emacs** by using NVIDIA Canary 1B model in multiple languages
This video showcases a demonstration of speech-to-text capabilities within the popular text editor, Emacs, utilizing the advanced NVIDIA Canary 1 Billion parameter (1B) language model. The presentation highlights how users can effectively type and edit documents across various programming or markup languages using spoken commands.
The demo likely illustrates seamless integration between cutting-edge AI technology from NVIDIA's Canary series—known for its powerful natural language processing capabilities—and Emacs, a highly customizable text editor favored by developers worldwide. By leveraging the 1B model, which is capable of understanding context and nuances in multiple human languages, users can dictate their code or prose directly into Emacs with impressive accuracy.
The video probably covers how this setup supports several different programming languages as well as natural language typing tasks, showcasing its versatility across various domains such as software development and content creation. Additionally, the demonstration may include examples of real-time transcription performance in diverse linguistic contexts to emphasize the model's multilingual proficiency.
Overall, viewers can expect insights into enhancing productivity by integrating AI-driven speech recognition directly within their text editing workflow using Emacs paired with NVIDIA’s advanced language models.
**Speech typing in Emacs** by using NVIDIA Canary 1B model in multiple languages
This video showcases a demonstration of speech-to-text capabilities within the popular text editor, Emacs, utilizing the advanced NVIDIA Canary 1 Billion parameter (1B) language model. The presentation highlights how users can effectively type and edit documents across various programming or markup languages using spoken commands.
The demo likely illustrates seamless integration between cutting-edge AI technology from NVIDIA's Canary series—known for its powerful natural language processing capabilities—and Emacs, a highly customizable text editor favored by developers worldwide. By leveraging the 1B model, which is capable of understanding context and nuances in multiple human languages, users can dictate their code or prose directly into Emacs with impressive accuracy.
The video probably covers how this setup supports several different programming languages as well as natural language typing tasks, showcasing its versatility across various domains such as software development and content creation. Additionally, the demonstration may include examples of real-time transcription performance in diverse linguistic contexts to emphasize the model's multilingual proficiency.
Overall, viewers can expect insights into enhancing productivity by integrating AI-driven speech recognition directly within their text editing workflow using Emacs paired with NVIDIA’s advanced language models.
This model IS NOT Apache 2.0 as you derived it from Gemma, which is proprietary model
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#2 opened 3 days ago
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JLouisBiz
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I don't see why such are better. They consume more power, delay with the actual answer, they are twice as bad for local LLM users. I will test it again, but what I tested so far doesn't seem there is special benefit in my use cases.
What is your practical use cases and reason, why do you like reasoning models?