K-State Data Science

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K-State Data Science

K-State Data Science

@kstate_bigdata

Part of @kstate Center for #ArtificialIntelligence & #DataScience (#CAIDS) constellation. #BigData in #research, #science, #business, #courses, #academics

Manhattan, KS Katılım Nisan 2014
71 Takip Edilen2.2K Takipçiler
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Mathelirium
Mathelirium@mathelirium·
We often hear that machine learning models "learn patterns in data". But what does that actually look like in geometry? If you dropped a little elastic mesh into a cloud of points and let it learn, how would it fold itself to match the shape of the data? In this scene we watch a self-organizing map...a simple unsupervised neural model...learn the shape of a two-dimensional dataset arranged in a spiral arm. On top of this, we lay down a square grid of neurons whose weights live in the same plane. At the start, this grid is just a flat net floating across the cloud...it knows nothing about the structure underneath. Learning is a repeated game: pick a random data point, find the neuron whose weight is closest, and then nudge that neuron and its neighbours toward the point. Do this again and again, while slowly shrinking how far the neighbourhood influence spreads. #MachineLearning #ManifoldLearning #UnsupervisedLearning #NeuralMaps #GeometricML
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Fei-Fei Li
Fei-Fei Li@drfeifei·
I can now confess that I participated in the new #TronAres movie, playing myself 😆 I had a great time working with everyone especially Greta Lee shooting the scene where “I” interviewed her character about #AI. Thank you @DisneyStudios for giving me a chance to be part of a movie making experience! 😍🎬
Walt Disney Studios@DisneyStudios

Hear from Greta Lee as she reflects on her time at TED what it was like to work with Dr. Li in this exclusive clip. Experience Tron: Ares now playing in theaters and IMAX. Get tickets now.

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Walt Disney Studios
Walt Disney Studios@DisneyStudios·
Hear from Greta Lee as she reflects on her time at TED what it was like to work with Dr. Li in this exclusive clip. Experience Tron: Ares now playing in theaters and IMAX. Get tickets now.
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K-State Salina
K-State Salina@KSU_Salina·
6️⃣0️⃣ 🥳 Help us celebrate the campus's 60th Anniversary with Willie the Wildcat at the Salina Selfie Station! There is no cost to attend! Read more about the special celebration event and our journey here: bit.ly/4oavp1l. #KStateSalina #BeWhatsNext
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Chubby♨️
Chubby♨️@kimmonismus·
This is the real deal, holy moly
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Chrome for Developers
Chrome for Developers@ChromiumDev·
Announcing our public preview of Chrome DevTools MCP! Experience the full power of DevTools in your AI coding agent → goo.gle/4pDE6Tk With Chrome DevTools MCP, your AI agent can run performance traces, inspect the DOM, & perform real-time debugging of your web pages.
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Sveta
Sveta@Sveta0971·
This new structure seems designed to please one partner: Microsoft. But what about the 700M users who built your success? Keeping beloved models like 4o accessible isn't just nonprofit mission talk. It's about user retention, a metric your IPO investors (and Microsoft) will be watching closely. Choose wisely. #keep4o #KeepStandardVoice
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OpenAI Newsroom
OpenAI Newsroom@OpenAINewsroom·
OpenAI started as a nonprofit, remains one today, and will continue to be one – with the nonprofit holding the authority that guides our future. As previously announced and as outlined in our non-binding MOU with Microsoft, the OpenAI nonprofit’s ongoing control would now be paired with an equity stake in the PBC. — Bret Taylor, Chair, on ​​our our non-binding MOU with Microsoft and evolution to a nonprofit and PBC openai.com/index/statemen…
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OpenAI Newsroom
OpenAI Newsroom@OpenAINewsroom·
OpenAI and Microsoft have signed a non-binding memorandum of understanding (MOU) for the next phase of our partnership. We are actively working to finalize contractual terms in a definitive agreement. Together, we remain focused on delivering the best AI tools for everyone, grounded in our shared commitment to safety. openai.com/index/joint-st…
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Connor Davis
Connor Davis@connordavis_ai·
The most important AI paper of 2025 might have just dropped. NVIDIA lays out a framework for Small Language Model agents that could outcompete LLMs. Here’s the full breakdown (and why it matters):
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Ray Fernando
Ray Fernando@RayFernando1337·
Goodbye Claude Code... I hate to say this but Cursor + Claude 4 Sonnet Thinking (Max) 600k context is KING!!! Latest Cursor update is blazing FAST!! The intelligence for refactors, new feature implementations, and large context window leave large enough context windows for Claude 4 Sonnet thinking to really shine. I've used 120k context and I have tons of runway to continue cooking with Cursor Agent. Cursor's IDE knows where to grab the files extremely fast and they understand what changed in my codebase. When I would clear chats with Claude Code (which I do frequently) it would take a lot of time for Claude Code to build context again to make accurate changes. The latest Cursor update feels like it is reading my mind. I'm going super duper fast with Cursor Agent.
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Avi Chawla
Avi Chawla@_avichawla·
A graph-powered all-in-one RAG system! RAG-Anything is a graph-driven, all-in-one multimodal document processing RAG system built on LightRAG. It supports all content modalities within a single integrated framework. 100% open-source.
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Avi Chawla
Avi Chawla@_avichawla·
Finally, the video shows prompting the LLM before and after fine-tuning. After fine-tuning, the model is able to generate the reasoning tokens in French before generating the final response in English. Check this 👇
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Avi Chawla
Avi Chawla@_avichawla·
6️⃣ Train With that done, we initiate training. The loss is generally decreasing with steps, which means the model is being fine-tuned correctly. Check this code and training logs 👇
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Avi Chawla
Avi Chawla@_avichawla·
5️⃣ Define Trainer Here, we create a Trainer object by specifying the training config, like learning rate, model, tokenizer, and more. Check this out 👇
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Avi Chawla
Avi Chawla@_avichawla·
4️⃣ Prepare dataset Before fine-tuning, we must prepare the dataset in a conversational format: - We standardize the dataset. - We pick the messages field. - We apply the chat template to it. Check the code and a data sample 👇
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Avi Chawla
Avi Chawla@_avichawla·
3️⃣ Load dataset We'll fine-tune gpt-oss and help it develop multi-lingual reasoning capabilities. So we load the multi-lingual thinking dataset, which has: - User query in English. - Reasoning in different languages. - Response in English. Check this 👇
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