Major upgrades for high-performance agents with the rise of GUI-G1 and Robin, alongside the notable multimodal improvements of diffusion language models Check out the top 10 papers for the week – GUI-G1: Understanding R1-Zero-Like Training for Visual Grounding in GUI
MACHINE LEARNING
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Data AI Summit Announces Visionary Sponsors for Annual Conference
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Thank you to our #DataAISummit Visionary sponsors: @astronomerio
, @AtlanHQ
, Coalesce, @Cognizant
, @dataiku
, @FireboltHQ
, @fivetran
, and @HightouchData
. Your support helps us deliver a unique, interactive experience at the world’s largest data, analytics and AI conference. -
LLaMA-Factory: Zero-Code Fine-Tuning for 100+ LLMs
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Fine tune 100+ open source LLMs with zero code
— Charly Wargnier (@DataChaz) 24 mai 2025
Meet LLaMA-Factory! 🦙🔥
a full-stack open source UI for training LLMs and VLMs (LLaMA, Mistral, Qwen, Yi, DeepSeek, Gemma)
— no boilerplate!
why it matters:
↳ 100+ model support
↳ PPO, DPO, SFT, RLHF
↳ GaLore, DoRA, PiSSA,… pic.twitter.com/orPH4wXFH7Fine tune 100+ open source LLMs with zero code Meet LLaMA-Factory! a full-stack open source UI for training LLMs and VLMs (LLaMA, Mistral, Qwen, Yi, DeepSeek, Gemma)
— no boilerplate! why it matters: ↳ 100+ model support
↳ PPO, DPO, SFT, RLHF
↳ GaLore, DoRA, PiSSA, -
Share Insights on LLMs, AI Agents, and Machine Learning
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If you found it insightful, reshare with your network. Find me → @akshay_pachaar For more insights and tutorials on LLMs, AI Agents, and Machine Learning!
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Defining ML Summarizer Agent with Guardrail Validation
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Next, we define a summarizer Agent and its Task—asking it to summarize an ML topic. We pass the Guardrail method defined above (validate_summary_length) as a parameter to the Task and kick off the Crew. Here's the code
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PyTorch vs TensorFlow: Edge Real-Time Object Detection Deep Dive
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5/ Technical deep dive with benchmarking "Compare PyTorch vs TensorFlow for deploying real-time object detection on edge devices. Provide runnable Python code snippets for model conversion, inference with OpenCV, and timing/memory benchmarks. " Claude:
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Benchmark: Gemini 2.5 Pro vs Claude 4 Sonnet on Real Prompts
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I tested Gemini 2.5 Pro vs Claude 4 Sonnet with 7 real-world prompts. The results surprised me. Here’s who dominated each category (speed, reasoning, hallucinations…) (Prompts + demo) ↓
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Learning Human Movement Kinetics with Minimal Training Data
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Outside of body language, the kinetics of efficient human movement have few free parameters, so you don’t need a lot of data to learn them. The rest can probably be done with video instruction.
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Style Transfer: The Foundational 2015 Paper That Shaped AI
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The first paper we were all enamored with in 2015 was called “style transfer,” with entire lines of work by that heading so….
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Hugging Face Download Metrics Not Reliable Early Stage
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I don’t have enough context to comment in the main point but keep in mind that download count on HF is usually not a great indicator the first few days