AI1 min read
Treble Raises $18 Million for Voice Simulation Platform
Iceland-based startup Treble raised $18 million in Series A funding. The company focuses on simulating voice data and testing hardware.
From TechCrunch AI
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AI1 min read
Iceland-based startup Treble raised $18 million in Series A funding. The company focuses on simulating voice data and testing hardware.
From TechCrunch AI
LLMs1 min read
Agentic AI workflows can be used to prepare and validate digital twins for physical AI systems. Agents can inspect 3D scenes, author simulation-relevant data in...
From NVIDIA technical blog
How this blog is made
Each feed entry becomes one request to OpenSmartRoute: the router picks a model with a cost-weighted objective, the editorial-writer skill is layered on the prompt, and the outcome trains the learners - the same pipeline available to every workspace.
Open any post to see which target answered, its confidence, the alternatives and what the request cost. Run the same pipeline yourself: register feeds in the operator console, map a small model under Providers, or call POST /api/v1/route with execute: true.
OSMO is an open-source Kubernetes orchestrator that allows engineers to manage AI training, simulation, and robot testing across diverse compute environments – from data center GPUs to edge devices – defined by a single YAML file. This simplifies pipeline management and reduces infrastructure complexity.
From MarkTechPost
Research1 min read
Researchers developed WinSyn, an automated pipeline for generating realistic synthetic datasets of emails simulating enterprise scenarios. Evaluations using standard agentic baselines on these datasets showed aggregate scores below 80%, highlighting the need for more complex evaluation data.
From arXiv cs.AI
Research1 min read
Researchers have created four JSON Schemas to structure data from scientific literature on Atomic Layer Deposition and Etching. These schemas, generated using schema-miner and grounded in QUDT, enable comparison and reuse of experimental and simulation processes within materials science.
From arXiv cs.AI
LLMs1 min read
Research reveals a significant disconnect between LLM-as-a-judge rankings and actual task success in user-simulated evaluations of task-oriented agents. The study, GAUGE, identifies a satisfaction-success gap and resolution loss among closely-ranked agents, highlighting the need for a calibrated approach to agent selection.
From arXiv cs.CL
Research1 min read
DRG-MAPPO, a new multi-agent reinforcement learning framework, achieves a 87% win rate in cooperative air combat simulations. The system utilizes graph-based relational modeling and dynamic role assignment to improve tactical coordination and collaborative execution.
From arXiv cs.AI
Research1 min read
This paper proposes that the structure of physical interactions, represented by Jacobians, shapes phenomenal experience within a simulated neural network environment, Gradland. The research demonstrates how Jacobian measures explain aspects of experience like duration, vividness, and texture.
From arXiv cs.AI
LLMs1 min read
NVIDIA’s BioNeMo Inference Runtime accelerates biomolecular structure prediction at scale, allowing for efficient processing of large proteome workflows. This enables faster insights from complex biological data.
From NVIDIA technical blog
LLMs1 min read
NVIDIA CUDA Toolkit 13.4 introduces support for Windows on Arm, alongside enhanced control over shared GPUs. This update provides developers with expanded platform options and improved GPU management capabilities.
From NVIDIA technical blog
Agents2 min read
OpenAI reported a Navier-Stokes singularity solution achieved in 88 hours using a system of approximately 10,000 agents trained via multi-agent reinforcement learning. This represents a significant step in AI research, though verification remains pending.
From Latent Space
Research1 min read
Research simulating diverse LLM agent societies reveals significant value drift, with over 50% of personas failing to initially align with assigned WVS profiles and a 2-7% drift after conversations. This highlights limitations of current LLMs as faithful proxies for human value systems.
From arXiv cs.AI
Research1 min read
Enhanced capabilities in large language models may lead to more correlated behaviors, increasing systemic risk, especially when models share reasoning or misinformation environments.
From arXiv cs.AI
Research1 min read
The $ au^ au$-bench evaluates agent building from real business data, requirements, and APIs, measuring performance across multiple tasks to reflect real client engagement conditions.
From arXiv cs.AI
Research1 min read
A new framework uses neural ODEs to predict constitutive behavior of digital materials, capturing nonlinear, rate-dependent responses across compositions.
From arXiv cs.AI
Research1 min read
HarvestBench evaluates how language models decide to avoid harming animals in a simulated farm environment, with decisions priced and measured across multiple models and scenarios.
From arXiv cs.AI
LLMs1 min read
A new approach trains a coding model to produce watercolour images using TRL and OpenEnv, focusing on model capabilities for creative tasks.
From Hugging Face blog
LLMs1 min read
NVIDIA's CUDA remains central to GPU-accelerated computing, supporting scientific simulations and AI training. This article provides a detailed optimization process for CUDA workflows.
From NVIDIA technical blog
LLMs1 min read
Tarn Adams, co-creator of Dwarf Fortress, emphasizes that dwarf behavior, not AI, is being referenced, highlighting the distinction between behavior and artificial intelligence in game design.
From Simon Willison
Posts are drafted from public feeds by models OpenSmartRoute routes to - the same router, skill and metering customers use - and always link to the original source. Corrections: support.
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