synthetic data

At NVIDIA Agentic AI Day Japan 2026 in Tokyo on November 10, NVIDIA presented two synthetic datasets for Japanese AI development. Nemotron-Personas-Finance-Japan targets financial AI and user simulation, and Nemotron-PII-Japan covers PII detection and masking across 8 domains. Both are published on Hugging Face.

Amazon has released Mitra-v2, a tabular foundation model for classification and regression that, according to Amazon, leads the single-model field on the TabArena benchmark of 51 datasets. Weights and code are available under Apache-2.0 on Hugging Face.

IBM Research introduced Palette, a 20B model fine-tuned with a single LoRA adapter to build slide decks in the IBM Design Language. IBM claims it ranks first on two of the three domains measured on PresentBench. It splits the work between a designer role and a coder role, then runs every deck through a check-and-repair harness.

Microsoft Research describes the Industry Evaluation Data Generation Platform, which generates full-scale synthetic enterprise environments to evaluate Microsoft Copilot without touching customer data. It has produced three industry-specific tenants (pharmaceutical, capital markets, IT/software) and uses a six-stage pipeline to generate evaluation queries.

NVIDIA has released Nemotron-Personas datasets for France and Belgium, built with Pleias and, for Belgium, KU Leuven. A published workflow uses them to generate synthetic conversations and fine-tune Nemotron 3.5 Lightning with LoRA on NVIDIA NeMo.

NVIDIA and IIT Madras' AI4Bharat lab announced Nemotron-pretraining-Indic-v1, a corpus of roughly 2.8 trillion tokens covering all 22 languages in India's Constitution. It is due for release soon, alongside the open GPU-accelerated pipeline used to generate it.

Microsoft Research has released Fara-7B, a 7-billion parameter small language model designed for computer automation tasks. The model, which took 2.5 days to train on 64 H100 GPUs, can navigate websites to complete tasks like booking restaurants and shopping, using screenshots as input with a 128K token context window.