The GenAI problem most enterprises face is a gap between experimentation and enterprise operations. Without reproducibility, lineage, cost controls, and shared ownership, pilots stall and risk spikes. Learn to close that gap: https://
domino.buzz/49Qze5Y
GENERATIVE AI
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Closing GenAI Gap: From Pilots to Enterprise Operations
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Genie AI Tool Launching on Google Labs Platform
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It looks like Genie is getting ready to launch on Google Labs.
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Fine-tuning Resources: SFT, GRPO, and CPT Notebooks
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Text SFT: https://
colab.research.google.com/drive/1vGRg4ks
Rj__6OLvXkHhvji_Pamv801Ss?usp=sharing
…
Vision SFT: https://
colab.research.google.com/drive/1FaR2HSe
91YDe88TG97-JVxMygl-rL6vB?usp=sharing
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Text GRPO: https://
colab.research.google.com/drive/1mIikXFa
GvcW4vXOZXLbVTxfBRw_XsXa5?usp=sharing
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CPT (text completion): https://
colab.research.google.com/drive/10fm7eNM
ezs-DSn36mF7vAsNYlOsx9YZO?usp=sharing
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CPT (translation): https://
colab.research.google.com/drive/1gaP8yTl
e2_v35Um8Gpu9239fqbU7UgY8?usp=sharing
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LFM2.5 notebooks update: SFT, GRPO, CPT with vision
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We worked with @UnslothAI to bring up-to-date notebooks for LFM2.5 It covers SFT, GRPO, and CPT with text and vision (SFT-only). Continued pre-training is particularly nice with the base model for text completion and translation examples.
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Reasoning Models: The Next Leap In AI With K2-Think
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Why Reasoning Models Are The Next Leap In AI: Inside MBZUAI's K2-Think https://t.co/8u9SvKBQju
— Bernard Marr (@BernardMarr) 29 janvier 2026Why Reasoning Models Are The Next Leap In AI: Inside MBZUAI's K2-Think
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Chrome Gets Agentic AI Upgrade and Weekly AI Innovation Roundup
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Top stories in AI today: – Chrome's big agentic AI upgrade
– DeepMind’s science behind AlphaGenome
– How to install and use Moltbot (Clawdbot)
– New labs raise big to rethink how AI learns
– 4 new AI tools, community workflows, and more Read more: https://
therundown.ai/p/chrome-gets-
agentic-ai-upgrade
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Prompt Ensembling Beats Single Prompts for High-Impact Decisions
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When prompt ensembling beats single prompts: High-stakes business decisions ($100K+ impact) Medical/legal advice (where errors cost lives/money) Creative work (logo design, brand names, campaign ideas) Strategic planning (5-year roadmaps, market entry) Code
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Ask your question 5 ways and combine answers for better results
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The concept is simple: Instead of asking your question once and hoping for the best, you ask it 5 different ways and combine the answers. Think of it like getting second opinions from 5 doctors instead of trusting one diagnosis. Stanford tested this on GPT-5.2, Claude 4.5, and
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Stanford prompt ensembling: merging 5 variations improves LLMs
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Stanford researchers just published a prompting technique that makes today’s LLMs behave like better versions of themselves. It’s called “prompt ensembling” and it runs 5 variations of the same prompt, then merges the outputs. Here’s how it works
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Style-conditioned AI models with prompt engineering capabilities
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Oh yes. I liked the original Ai2 project for that reason, it's contained to a single codebase! So it can learn your style… I bet it'd be relatively easy to make it style-conditioned model as well, like a promptable feel/patterns/quality!