Multiverse: Language-Conditioned Multi-Game Level Blending via Shared Representation
arXiv:2603.26782v1 Announce Type: new
Abstract: Text-to-level generation aims to translate natural language descriptions into structured game levels, enabling intuitive control over procedural content generation. While prior text-to-level generators are typically limited to a single game domain, ex...
Neuro-Symbolic Learning for Predictive Process Monitoring via Two-Stage Logic Tensor Networks with Rule Pruning
arXiv:2603.26944v1 Announce Type: new
Abstract: Predictive modeling on sequential event data is critical for fraud detection and healthcare monitoring. Existing data-driven approaches learn correlations from historical data but fail to incorporate domain-specific sequential constraints and logical ...
Your Code is Your Schema: Weaviate Managed CClient
Use semantic search and RAG in C# with the Weaviate Managed .NET client — attribute-driven schema, type-safe queries, and safe migrations, all in idiomatic .NET.
AI Weekly Issue #477: Jensen Huang says we've achieved AGI. The benchmarks say 0.37%.
💡 Insights
AI is superhuman at exams but can't figure out a simple game. ARC-AGI-3 gave frontier models interactive environments with no rules and no goals — just figure it out. Humans solve 100%. The best AI scored 0.37%. Current architectures can pattern-match anything in their training data but c...
15% of Americans say they’d be willing to work for an AI boss, according to new poll
According to a Quinnipiac University poll, 15% of Americans say they'd be willing to have a job where their direct supervisor was an AI program that assigned tasks and set schedules.
Microsoft AI Releases Harrier-OSS-v1: A New Family of Multilingual Embedding Models Hitting SOTA on Multilingual MTEB v2
Microsoft has announced the release of Harrier-OSS-v1, a family of three multilingual text embedding models designed to provide high-quality semantic representations across a wide range of languages. The release includes three distinct scales: a 270M parameter model, a 0.6B model, and a 27B model. T...
15% of Americans say they’d be willing to work for an AI boss
Your human manager may soon be a chatbot. Across organizations, AI is being used to replace layers of management in what some are calling "The Great Flattening."
From Prompt to Prediction: Understanding Prefill, Decode, and the KV Cache in LLMs
This article is divided into three parts; they are: • How Attention Works During Prefill • The Decode Phase of LLM Inference • KV Cache: How to Make Decode More Efficient Consider the prompt: Today’s weather is so .
As more Americans adopt AI tools, fewer say they can trust the results
AI adoption is rising in the U.S., but trust remains low, with most Americans concerned about transparency, regulation, and the technology’s broader societal impact, according to a new Quinnipiac poll.
There are more AI health tools than ever—but how well do they work?
Earlier this month, Microsoft launched Copilot Health, a new space within its Copilot app where users will be able to connect their medical records and ask specific questions about their health. A couple of days earlier, Amazon had announced that Health AI, an LLM-based tool previously restricted to...
Mantis Biotech is making ‘digital twins’ of humans to help solve medicine’s data availability problem
Mantis takes disparate sources of data to make synthetic datasets that can be used to build so-called "digital twins" of the human body, representing anatomy, physiology and behavior.
20+ Solved ML Projects to Build Your Portfolio and Boost Your Resume
Projects are the bridge between learning and becoming a professional. While theory builds fundamentals, recruiters value candidates who can solve real problems. A strong, diverse portfolio showcases practical skills, technical range, and problem-solving ability. This guide compiles 20+ solved proje...
Explainable AI in Production: A Neuro-Symbolic Model for Real-Time Fraud Detection
SHAP needs 30 ms to explain a fraud prediction. That explanation is stochastic, runs after the decision, and requires a background dataset you have to maintain at inference time. This article benchmarks a neuro-symbolic model that produces a deterministic, human-readable explanation in 0.9 ms — as a...
Salesforce AI Research Releases VoiceAgentRAG: A Dual-Agent Memory Router that Cuts Voice RAG Retrieval Latency by 316x
In the world of voice AI, the difference between a helpful assistant and an awkward interaction is measured in milliseconds. While text-based Retrieval-Augmented Generation (RAG) systems can afford a few seconds of ‘thinking’ time, voice agents must respond within a 200ms budget to maintain a natura...
MAGNET: Autonomous Expert Model Generation via Decentralized Autoresearch and BitNet Training
arXiv:2603.25813v1 Announce Type: new
Abstract: We present MAGNET (Model Autonomously Growing Network), a decentralized system for autonomous generation, training, and serving of domain-expert language models across commodity hardware. MAGNET integrates four components: (1) autoresearch, an autonom...
BeSafe-Bench: Unveiling Behavioral Safety Risks of Situated Agents in Functional Environments
arXiv:2603.25747v1 Announce Type: new
Abstract: The rapid evolution of Large Multimodal Models (LMMs) has enabled agents to perform complex digital and physical tasks, yet their deployment as autonomous decision-makers introduces substantial unintentional behavioral safety risks. However, the absen...
AutoB2G: A Large Language Model-Driven Agentic Framework For Automated Building-Grid Co-Simulation
arXiv:2603.26005v1 Announce Type: new
Abstract: The growing availability of building operational data motivates the use of reinforcement learning (RL), which can learn control policies directly from data and cope with the complexity and uncertainty of large-scale building clusters. However, most ex...
AIRA_2: Overcoming Bottlenecks in AI Research Agents
arXiv:2603.26499v1 Announce Type: new
Abstract: Existing research has identified three structural performance bottlenecks in AI research agents: (1) synchronous single-GPU execution constrains sample throughput, limiting the benefit of search; (2) a generalization gap where validation-based selecti...