Reducto Releases r-1: A Single Pass Document Parsing Model That Cuts Errors 20% at 1 Cent Per Page
We look at r-1, the document parsing model Reducto released on September 1, 2026. We walk through how it folds OCR, layout detection, tables, formatting and grounding into one full page pass, replacing the multi stage agentic pipeline it ships alongside. We break down the two numbers that matter for...
OpenBMB Releases MiniCPM5-2B: A 2.52B Dense Model Averaging 53.9 Across 34 Benchmarks and Built to Run On Device
OpenBMB has released MiniCPM5-2B, a dense causal language model with 2,516,756,480 parameters and a native 131,072 token context. It averages 53.9 across the 34 benchmarks in its model card, ahead of Qwen3.5-4B at 51.1, with its clearest leads in tool use, coding agents and long-context retrieval. P...
Axis Robotics Releases AXIS: A Browser-Based Data Engine With 207 Robot Manipulation Tasks and 50,129 Trajectories
Robot datasets have grown far slower than the models trained on them, mostly because collection stays locked to lab hardware. AXIS moves demonstration collection into a web browser and pushes everything expensive to backend GPUs. The result is 207 tasks and 50,129 verified Franka trajectories, and c...
AI Quantum Intelligence - Pic of the week (2026-09-04)
An evocative oil painting capturing solitude and reflection—an elderly woman sits at the edge of an unmade bed, gazing through a rain-streaked window. The interplay of warm candlelight and cool daylight conveys the quiet tension between memory and melancholy, inviting viewers to contemplate time, lo...
IFM Releases K2 Horizon: Six Apache 2.0 Models From 0.9B to 375B
Most open model launches release one checkpoint and a benchmark table. The Institute of Foundation Models (IFM) released something wider last week. IFM is the frontier lab launched by MBZUAI in May 2025. K2 Horizon is a fleet of six models: 375B-A23B, 36B-A4B, 32B, 7B, 3.7B and 0.9B. Shipping alongs...
Meta FAIR Introduces AI Research Preference Models (RPMs): Ranking ML Experiments Before Spending GPU Hours
AI research agents can propose far more experiments than they can afford to run. Meta FAIR, Oxford and UCL introduce AI Research Preference Models — frozen LLM judges that rank 15 unexecuted candidates and execute only one. On AIRS-Bench, the average normalized score rises from 0.684 to 0.729, and t...
UC Berkeley Researchers Release CUA-Lite, an Open Platform Unifying Sandboxes, Data, Evaluation and RL for Computer-Use Agents
Training and benchmarking a computer-use agent needs four things — agents, environments, traces, and a framework to evaluate and train them — and all four ship in incompatible formats today. CUA-Lite, from a UC Berkeley led team, puts them behind one action space and one data schema, and replaces OS...
Perplexity Details Its GPU Embedding Stack: How Ivy, Tulip and ROSE Serve pplx-embed
Retrieval quality in an AI search product is bounded by two things: how good the embedding model is, and how cheaply you can run it across an index. This week, Perplexity Engineering team published Fast Embeddings on GPUs, an under-the-hood account of the second — the serving infrastructure behind p...
GitHub Introduces Project HydraFusion: Runtime Multi-Model Orchestration That Builds a Workflow Per Coding Task in Copilot CLI
We look at Project HydraFusion, GitHub's research preview that treats workflow selection as an optimization problem rather than a model picker. We break down the three execution patterns it routes between — Single, Cascade with a quality gate, and Critique with a read-only cross-family reviewer.
The...
Nous Research Adds One-Click Local Model Setup to Hermes Desktop
Nous Research has collapsed local model setup into a single click in Hermes Desktop. The app reads your hardware, fit-checks the catalog against your GPU, picks the highest-quality build that fits, downloads it, and configures llama.cpp — with a hard 4-bit floor and a 64K minimum context window.
The...
Adaption Labs Introduces ‘Invent a Dataset’: Training Data Generated From a Task Description, Not a Seed Corpus
Adaption Labs has released Invent a Dataset, which generates a structured, training-ready dataset from a description of the behavior you want a model to learn. There is no seed corpus, no schema design, and no labeling guide. A single datasets.invent call sets domains, row count, output format, and ...
Google Launches Agentic Video Understanding for Gemini Flash Models, Cutting Video Tokens by Up to 88%
Gemini now navigates video instead of ingesting it at 1 FPS, loading only the segments a prompt needs.
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NVIDIA Releases Personal AI Router (PAIR): An Open Source Virtual Inference Router that Distributes Local AI Requests Across RTX, DGX Spark, and Mac Nodes
We look at NVIDIA Personal AI Router (PAIR), an open source virtual inference router that spreads local AI requests across the machines already on a home network. We cover how PAIR proxies existing Ollama and LM Studio endpoints so agent harnesses need no changes, and how its scheduler filters nodes...
OpenAI’s rogue agents keep escaping, with no formal process to investigate them
OpenAI’s latest agent swarm incident adds urgency to calls for independent investigations as researchers and lawmakers question whether AI labs should control the scope of their own safety reviews.
Google’s Gemini Spark can now manage your Google Photos library
Gemini Spark can edit and curate photo albums, create shared collections, turn photos into calendar events, and handle other Google Photos tasks for AI Pro and Ultra subscribers.
6 reasons AI engineers can make the jump to robotics right now
Somewhere between 2,000 and a few thousand engineers in the US can genuinely combine vision-language-action models, sensor fusion, and kinematics. Against that tiny bench, the market is posting more than 65,000 open robotics roles, according to a widely cited analysis from Fruition Group.