Moonshot AI Releases 𝑨𝒕𝒕𝒆𝒏𝒕𝒊𝒐𝒏 𝑹𝒆𝒔𝒊𝒅𝒖𝒂𝒍𝒔 to Replace Fixed Residual Mixing with Depth-Wise Attention for Better Scaling in Transformers
Residual connections are one of the least questioned parts of modern Transformer design. In PreNorm architectures, each layer adds its output back into a running hidden state, which keeps optimization stable and allows deep models to train. Moonshot AI researchers argue that this standard mechanism ...
IBM AI Releases Granite 4.0 1B Speech as a Compact Multilingual Speech Model for Edge AI and Translation Pipelines
IBM has released Granite 4.0 1B Speech, a compact speech-language model designed for multilingual automatic speech recognition (ASR) and bidirectional automatic speech translation (AST). The release targets enterprise and edge-style speech deployments where memory footprint, latency, and compute eff...
From Garbage to Gold: A Data-Architectural Theory of Predictive Robustness
arXiv:2603.12288v1 Announce Type: new
Abstract: Tabular machine learning presents a paradox: modern models achieve state-of-the-art performance using high-dimensional (high-D), collinear, error-prone data, defying the "Garbage In, Garbage Out" mantra. To help resolve this, we synthesize principles ...
Multi-objective Genetic Programming with Multi-view Multi-level Feature for Enhanced Protein Secondary Structure Prediction
arXiv:2603.12293v1 Announce Type: new
Abstract: Predicting protein secondary structure is essential for understanding protein function and advancing drug discovery. However, the intricate sequence-structure relationship poses significant challenges for accurate modeling. To address these, we propos...
Global Evolutionary Steering: Refining Activation Steering Control via Cross-Layer Consistency
arXiv:2603.12298v1 Announce Type: new
Abstract: Activation engineering enables precise control over Large Language Models (LLMs) without the computational cost of fine-tuning. However, existing methods deriving vectors from static activation differences are susceptible to high-dimensional noise and...
arXiv:2603.12372v1 Announce Type: new
Abstract: Large Reasoning Models (LRMs) have shown remarkable reasoning capabilities, yet they often suffer from overthinking, expending redundant computational steps on simple problems, or underthinking, failing to explore sufficient reasoning paths despite in...
Generating Expressive and Customizable Evals for Timeseries Data Analysis Agents with AgentFuel
arXiv:2603.12483v1 Announce Type: new
Abstract: Across many domains (e.g., IoT, observability, telecommunications, cybersecurity), there is an emerging adoption of conversational data analysis agents that enable users to "talk to your data" to extract insights. Such data analysis agents operate on ...
arXiv:2603.12710v1 Announce Type: new
Abstract: Developing autonomous agents for web-based tasks is a core challenge in AI. While Large Language Model (LLM) agents can interpret complex user requests, they often operate as black boxes, making it difficult to diagnose why they fail or how they plan....
Scientists discover AI can make humans more creative
Artificial intelligence is often portrayed as a tool that replaces human work, but new research from Swansea University suggests a far more exciting role: creative collaborator. In a large study with more than 800 participants designing virtual cars, researchers found that AI-generated design galler...
Google, Accel India accelerator choses 5 startups and none are ‘AI wrappers’
Google and Accel say about 70% of AI startup pitches tied to India were "wrappers" as they reviewed more than 4,000 applications for their Atoms cohort.
A Coding Implementation to Design an Enterprise AI Governance System Using OpenClaw Gateway Policy Engines, Approval Workflows and Auditable Agent Execution
In this tutorial, we build an enterprise-grade AI governance system using OpenClaw and Python. We start by setting up the OpenClaw runtime and launching the OpenClaw Gateway so that our Python environment can interact with a real agent through the OpenClaw API. We then design a governance layer that...
Meet OpenViking: An Open-Source Context Database that Brings Filesystem-Based Memory and Retrieval to AI Agent Systems like OpenClaw
OpenViking is an open-source Context Database for AI Agents from Volcengine. The project is built around a simple architectural concept: agent systems should not treat context as a flat collection of text chunks. Instead, OpenViking organizes context through a file system paradigm, with the goal of ...
The Causal Inference Playbook: Advanced Methods Every Data Scientist Should Master
Master six advanced causal inference methods with Python: doubly robust estimation, instrumental variables, regression discontinuity, modern difference-in-differences, heterogeneous treatment effects and sensitivity analysis. Includes code and a practical decision framework.
The post The Causal Infe...
LangChain Releases Deep Agents: A Structured Runtime for Planning, Memory, and Context Isolation in Multi-Step AI Agents
Most LLM agents work well for short tool-calling loops but start to break down when the task becomes multi-step, stateful, and artifact-heavy. LangChain’s Deep Agents is designed for that gap. The project is described by LangChain as an ‘agent harness‘: a standalone library built on top of LangChain...
Zhipu AI Introduces GLM-OCR: A 0.9B Multimodal OCR Model for Document Parsing and Key Information Extraction (KIE)
Why Document OCR Still Remains a Hard Engineering Problem? What does it take to make OCR useful for real documents instead of clean demo images? And can a compact multimodal model handle parsing, tables, formulas, and structured extraction without turning inference into a resource bonfire? That is t...
The Rise of Agentic AI: From Chatbots to Autonomous Coworkers
Explore the shift from Generative AI to Agentic AI in 2026. Discover how autonomous AI agents are evolving from simple chatbots into "digital coworkers" capable of independent reasoning, tool use, and complex task execution.
Google DeepMind found multi-agent networks amplify errors 17x. Learn 3 architecture patterns that separate $60M wins from the 40% that get canceled.
The post The Multi-Agent Trap appeared first on Towards Data Science.
Excel 101: IF, AND, OR Functions and Conditional Logic Explained
You reading this tells me you wish to learn more about Excel. This article continues our Excel series, where we explored the VLOOKUP function in the last iteration. The complete VLOOKUP guide demonstrated how the function works and how best to use it. This time, we shall bring the same focus to cond...
Lawyer behind AI psychosis cases warns of mass casualty risks
AI chatbots have been linked to suicides for years. Now one lawyer says they are showing up in mass casualty cases too, and the technology is moving faster than the safeguards.
The AI industry is constantly churning out news, like major acquisitions, indie developer successes, public outcry, and existentially dangerous contract negotiations.