Python

Auto Added by WPeMatico

Liquid AI Releases d1-ultra: A Multimodal Decision Model That Scores 65 on the AA Decision Index

Liquid AI has released d1-ultra, its most capable decision model to date. The Liquid AI d1-ultra decision model reads text, images, or both. It answers typed questions with a probability for each possible answer. It does this in one forward pass and generates no output tokens. For developers, that means classification, routing and scoring calls

Liquid AI Releases d1-ultra: A Multimodal Decision Model That Scores 65 on the AA Decision Index Read More »

▶

Meet Grok Voice 3.0: SpaceXAI Voice Agent Model Ranks #1 on Artificial Analysis

SpaceXAI just released Grok Voice 3.0. Grok Voice 3.0 is a SpaceXAI speech-to-speech model that listens, reasons, calls tools and speaks. It now ranks first on the Artificial Analysis Speech-to-Speech Index with a score of 86.9. For developers, the endpoint, events and $0.08 per minute price are unchanged from Grok Voice 2.0. TL;DR Runs on:

Meet Grok Voice 3.0: SpaceXAI Voice Agent Model Ranks #1 on Artificial Analysis Read More »

Microsoft AI Releases Microsoft-Decision-1: A Qwen3.5-9B Decision-Scoring Model

Microsoft has released Microsoft-Decision-1, a decision model for routing, classification, verification and agent control. Microsoft-Decision-1 is a decision-scoring model that returns a calibrated probability for each fixed answer option instead of generated text. It is post-trained from Alibaba’s Qwen3.5-9B and available now in Microsoft Foundry and OpenRouter. . TL;DR Size: Built on Qwen3.5-9B; exact parameter

Microsoft AI Releases Microsoft-Decision-1: A Qwen3.5-9B Decision-Scoring Model Read More »

Nace AI Open-Sources Drex 1.5: A 9B Decision Model That Scores Options, Not Text

Nace.AI has open-sourced Drex 1.5, a 9B decision model for agents and backend workflows. The Drex 1.5 decision model does not write text. It reads a state and typed questions, then returns a probability for every option. Nace reports 58.08 on the public Decision Index 0.3.1, the top score under 10B parameters. Weights are on

Nace AI Open-Sources Drex 1.5: A 9B Decision Model That Scores Options, Not Text Read More »

▶

NVIDIA PivotOPD Teaches Multi-Turn AI Agents to Recover From Pivotal Mistakes

NVIDIA researchers, with Princeton University and the University of Maryland, have introduced PivotOPD, an on-policy distillation method for multi-turn LLM agents. PivotOPD on-policy distillation trains an agent to avoid its most damaging early mistake, and to recover when it happens anyway. Against 13 baselines, it posts the best average on ALFWorld, WebShop and Search-based QA

NVIDIA PivotOPD Teaches Multi-Turn AI Agents to Recover From Pivotal Mistakes Read More »

↔

Meta AI Open-Sources Rebalancer: A C++ Assignment Solver That Runs About 40 Million Placement Problems a Day

Meta has open-sourced Rebalancer, a C++ library with a Python interface for solving assignment problems. It decides which objects go into which bins under constraints and objectives. According to the Engineering at Meta’s post, Rebalancer has handled resource allocation across Meta for over 9 years. The release ships under Apache 2.0 with documentation, a PyPI

Meta AI Open-Sources Rebalancer: A C++ Assignment Solver That Runs About 40 Million Placement Problems a Day Read More »

Datalab Introduces OmniExtractBench to Fix Bias and Opacity in Extraction Benchmarks

Datalab has released OmniExtractBench, an open benchmark for structured document extraction. It tests how accurately a system fills a JSON schema from a PDF. The benchmark pools 620 documents from 4 existing benchmarks. One deterministic scorer grades all of them and explains each decision. The release lands while extraction vendors publish their own leaderboards. Datalab

Datalab Introduces OmniExtractBench to Fix Bias and Opacity in Extraction Benchmarks Read More »

NVIDIA Releases Kumo Tabular: Open Tabular Foundation Models That Predict New Rows in a Single Forward Pass

NVIDIA has released Kumo Tabular, a new family of tabular foundation models (TFMs) for classification and regression. If you have followed TabPFN or TabICL, the setup will look familiar. The model takes labeled rows as context and predicts new rows in one forward pass. There is no training, no hyperparameter tuning, and no feature engineering.

NVIDIA Releases Kumo Tabular: Open Tabular Foundation Models That Predict New Rows in a Single Forward Pass Read More »

Black Forest Labs Releases FLUX 3 Action: A 7B Open-Weights World Action Model That Tops RoboLab-120

Black Forest Labs (BFL), the lab behind the FLUX image models, has released FLUX 3 Action. It is a 7B open-weights World Action Model (WAM) for robot control. The model reads camera frames, robot state and a text instruction. It then predicts future video frames and the next chunk of actions together. On the RoboLab-120

Black Forest Labs Releases FLUX 3 Action: A 7B Open-Weights World Action Model That Tops RoboLab-120 Read More »

Nokia Open-Sources AnyJev: A Training-Free Layer That Turns Any Open LLM Into a Calibrated Decision Model

Nokia’s applied research team has open-sourced AnyJev, a Python library that turns an open LLM into a decision model. It needs no training. It targets a common production job: picking one answer from a fixed set instead of writing a sentence. Is it deployable? Yes, it installs from PyPI, ships under Apache-2.0, and has transformers

Nokia Open-Sources AnyJev: A Training-Free Layer That Turns Any Open LLM Into a Calibrated Decision Model Read More »