In this tutorial, we explore NVIDIA tile-based GPU programming with TileGym, building a Colab workflow that runs across different hardware. We probe the CUDA environment, try the real cuTile backend, and fall back to Triton when standard Colab GPUs lack the cuTile stack. We learn the core tile idea: operate on whole data tiles instead of single threads, then load, compute, and store them. We implement vector addition, fused GELU, row-wise softmax, tiled matrix multiplication, and flash attention, checking each against PyTorch.

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Thinking Machines Lab published “The Future Worth Building Is Human.” The essay frames human participation, model ownership, and decentralized alignment as technical challenges. It ties them to interaction models and Tinker’s LoRA fine-tuning, where teams train and keep their own model weights.

The post Mira Murati’s Thinking Machines Lab Makes The Technical Case For Human-Centered AI Built On Customizable Model Weights appeared first on MarkTechPost.

Ant Group’s Robbyant has released the LingBot-VA 2.0 technical report — a Physical AI video-action foundation model built from scratch for embodiment rather than fine-tuned from a video generator. It predicts future states ahead of execution through Foresight Reasoning, re-grounds on every real observation, and reaches 225 Hz asynchronous control. We break down the causal DiT, the sparse-MoE video stream, the semantic visual-action tokenizer, and where the paper’s own numbers don’t line up.

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We build an autonomous data science agent around DeepAnalyze-8B and run it end to end. We prepare a stable Colab runtime, install the machine-learning dependencies, and load the tokenizer and model in 4-bit mode to fit limited GPU memory. We add a sandboxed execution environment that lets the model generate Python, run it safely, observe results, and continue in an agentic loop. We then hand the agent a multi-file e-commerce workspace and let it clean, join, analyze, visualize, and summarize the data as an analyst-grade report.

The post How to Build a T4-Friendly Autonomous Data Science Agent with DeepAnalyze-8B, Sandboxed Code Execution, and Iterative Analysis appeared first on MarkTechPost.

MuScriptor is an open-weight, decoder-only Transformer from Kyutai and Mirelo. Trained on 170k real recordings plus 1.45M synthetic MIDIs, it transcribes full multi-instrument mixes into MIDI. The article covers its three-stage pipeline, benchmarks against YourMT3+, instrument conditioning, and setup, with an interactive explainer demo.

The post Kyutai Releases MuScriptor: An Open-Weight Decoder-Only Transformer for Multi-Instrument Music Transcription to MIDI appeared first on MarkTechPost.

Robbyant, Ant Group’s embodied-intelligence unit, has released LingBot-World-Infinity (LingBot-World 2.0). It is a 14B causal video generation model that behaves as an interactive world simulator. The core idea is the Mixture of Bidirectional and Autoregressive (MoBA) attention mask, paired with distribution matching distillation applied over long self-rollout trajectories. Together they target long-horizon drift, the failure mode that smears textures and warps geometry in most interactive world models. A Director-Pilot agentic harness wraps the generator, where a VLM proposes events and the Diffusion Transformer renders them. The report shows a single 60-minute uninterrupted session covering 20 scenarios. But the release is thinner than the paper: one checkpoint, a 480P reference script, no deployment code, no quantitative benchmarks, and a non-commercial CC BY-NC-SA 4.0 license.

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