A Few-Shot LLM Framework for Extreme Day Classification in Electricity Markets
arXiv:2602.16735v1 Announce Type: new
Abstract: This paper proposes a few-shot classification framework based on Large Language Models (LLMs) to predict whether the next day will have spikes in real-time electricity prices. The approach aggregates system state information, including electricity dem...
Quantifying LLM Attention-Head Stability: Implications for Circuit Universality
arXiv:2602.16740v1 Announce Type: new
Abstract: In mechanistic interpretability, recent work scrutinizes transformer "circuits" - sparse, mono or multi layer sub computations, that may reflect human understandable functions. Yet, these network circuits are rarely acid-tested for their stability acr...
DeepVision-103K: A Visually Diverse, Broad-Coverage, and Verifiable Mathematical Dataset for Multimodal Reasoning
arXiv:2602.16742v1 Announce Type: new
Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has been shown effective in enhancing the visual reflection and reasoning capabilities of Large Multimodal Models (LMMs). However, existing datasets are predominantly derived from either small-scal...
Retrieval Augmented (Knowledge Graph), and Large Language Model-Driven Design Structure Matrix (DSM) Generation of Cyber-Physical Systems
arXiv:2602.16715v1 Announce Type: new
Abstract: We explore the potential of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Graph-based RAG (GraphRAG) for generating Design Structure Matrices (DSMs). We test these methods on two distinct use cases -- a power screwdriver and ...
Contextuality from Single-State Representations: An Information-Theoretic Principle for Adaptive Intelligence
arXiv:2602.16716v1 Announce Type: new
Abstract: Adaptive systems often operate across multiple contexts while reusing a fixed internal state space due to constraints on memory, representation, or physical resources. Such single-state reuse is ubiquitous in natural and artificial intelligence, yet i...
Mobility-Aware Cache Framework for Scalable LLM-Based Human Mobility Simulation
arXiv:2602.16727v1 Announce Type: new
Abstract: Large-scale human mobility simulation is critical for applications such as urban planning, epidemiology, and transportation analysis. Recent works treat large language models (LLMs) as human agents to simulate realistic mobility behaviors using struct...
Gemini 3.1 Pro: A Hands-On Test of Google’s Newest AI
Just 3 months after the release of their state-of-the-art model Gemini 3 Pro, Google DeepMind is here with its latest iteration: Gemini 3.1 Pro. A radical upgrade in terms of capabilities and safety, Gemini 3.1 Pro model strives to be accessible and operable by all. Regardless of your preference, pl...
Google AI Releases Gemini 3.1 Pro with 1 Million Token Context and 77.1 Percent ARC-AGI-2 Reasoning for AI Agents
Google has officially shifted the Gemini era into high gear with the release of Gemini 3.1 Pro, the first version update in the Gemini 3 series. This release is not just a minor patch; it is a targeted strike at the ‘agentic’ AI market, focusing on reasoning stability, software engineering, and tool...
The Missing Curriculum: Essential Concepts For Data Scientists in the Age of AI Coding Agents
AI can write the code, but you have to steer the ship. Master the knowledge to keep you relevant in the age of AI.
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A Coding Implementation to Build Bulletproof Agentic Workflows with PydanticAI Using Strict Schemas, Tool Injection, and Model-Agnostic Execution
In this tutorial, we build a production-ready agentic workflow that prioritizes reliability over best-effort generation by enforcing strict, typed outputs at every step. We use PydanticAI to define clear response schemas, wire in tools via dependency injection, and ensure the agent can safely intera...
247 Labs Achieves Dual ISO 9001 and ISO 27001 Certifications
247 Labs, a premier Canadian custom software and AI development firm, today announced its successful achievement of both ISO 9001:2015 and ISO/IEC 27001:2022 certifications. This significant milestone reinforces the company’s deep commitment to providing the highest standards of quality management a...
ThoughtSpot announced the launch of the next generation of Analyst Studio
New Analyst Studio capabilities—including SpotCache and agent-augmented data modeling—transform how data teams profile, mash up, and secure data for the next generation of AI workloads ThoughtSpot, the Agentic Analytics Platform company, today announced the launch of the next generation of Analyst S...
Luma Health Advances Operational AI Across Health System Workflows
Operational AI gains momentum as health systems deploy Luma’s platform to run operations end to end Health systems face labor shortages, fragmented workflows, and rising patient demand—challenges incremental automation has not solved. Luma Health shared new momentum from its Operational AI platform ...
FastMCP: The Pythonic Way to Build MCP Servers and Clients
Learn how to build MCP servers and clients using FastMCP, which is comprehensive, complete with error handling, best practices, and deployment strategies, making it ideal for both beginners and intermediate developers.
Microsoft has a new plan to prove what’s real and what’s AI online
AI-enabled deception now permeates our online lives. There are the high-profile cases you may easily spot, like when White House officials recently shared a manipulated image of a protester in Minnesota and then mocked those asking about it. Other times, it slips quietly into social media feeds and ...
Building Production-Ready AI Agents with Agent Development Kit
ADK from Google addresses a critical gap in the agentic AI ecosystem by providing a framework that simplifies the construction and deployment of multi-agent systems. Learn more.
DBMS Data Models Explained: Types, Abstraction Levels, and SQL Examples
Modern applications rely on structured storage systems that can scale, stay reliable, and keep data consistent. At the heart of all of it sits the data model. It defines how information is organized, stored, and retrieved. Get the model wrong and performance suffers, integrity breaks down, and futur...