Avoiding Entity Key Drift in a Data Lake: Step 2, When Fuzzy Matching Stops Working
I built a matcher meant to finish the cleanup that normalization left behind. Testing it against real data showed that no version of it could be made safe. What follows is the architecture that was left once the matcher was set aside.
The post Avoiding Entity Key Drift in a Data Lake: Step 2, When F...
This Python Library Can Run Pandas Workloads Up to 20x Faster
Discover how FireDucks can speed up pandas workloads with lazy execution, compiler optimization, and multithreaded processing, delivering up to 20x faster DataFrame performance in our benchmark.
Facilitating AI integration with simplicity at scale
As companies scale, the technology supporting operations can become a liability just as quickly as it becomes an asset. Disconnected systems, site-specific tools, spreadsheets, and manual workarounds can create data silos that make it harder to spot problems early, coordinate responses, and make dec...
Most companies can only partially track what is actually running. Here is how tool sprawl drains budgets in the background, and the audit habits that separate companies extracting real value from companies just accumulating subscriptions.
Graph Neural Networks: GCN, MPNN, and GAT, Explained Simply
A visual guide to how graph neural networks work under the hood
The post Graph Neural Networks: GCN, MPNN, and GAT, Explained Simply appeared first on Towards Data Science.
OpenAI faces 30 more lawsuits tied to Tumbler Ridge shooting
Edelson PC is filing 30 new lawsuits against OpenAI over the Tumbler Ridge shooting, escalating claims to aiding and abetting and naming Chris Lehane, though evidence remains unconfirmed.
AI Agent Memory Design: What Works and What Doesn’t
In this article, you will learn how to design reliable memory systems for AI agents, covering both the patterns that work and the common architectural...
What a User Story Actually Costs in a Dark Code Factory
Between March and July 2026, I built a production application of 861,601 lines of code. This included 696 user stories and 779 merged pull requests over 105 days, but I can’t tell you what it cost. The first version of an autonomous SDLC framework driving Claude Code did the work. That generation di...
Anthropic announced Enterprise Frontier Safeguards on September 1, 2026, an architecture that stores monitoring data in the customer's own cloud account rather than Anthropic's. Detection stays automated and Anthropic-run; custody, encryption keys, and flag review stay with the customer. Built with ...
Meta Superintelligence Labs Releases Muse Voice Transcribe: One Real-Time Model for Streaming ASR, Diarization, and Endpointing
Most production voice stacks are three systems stitched together. One model transcribes, a second separates speakers, and a detector decides when the user stopped talking. Each hand-off adds latency and a new failure mode. Muse Voice Transcribe, announced by Meta Superintelligence Labs this week, co...
Perplexity Releases Hybrid Compute on Mac: Cloud Agents Orchestrate Down to a Local Model, Gated On Device
Agentic assistants have a structural problem: the context that makes them useful — deal documents, privileged files, client records — is exactly the context users cannot send to a cloud endpoint. This week, Perplexity shipped its answer for Mac. Hybrid compute splits a single Perplexity Computer tas...
Task-Specific Prompt with Global Context for Multi-Task Graph Pre-Training
arXiv:2609.00047v1 Announce Type: new
Abstract: Graph prompt learning is an effective paradigm to adapt pre-trained graph models to downstream tasks in low-resource scenarios. However, existing multi-task graph pre-training frameworks generally use randomly initialized prompts, leading to poor alig...
REAL-Q: E2E LLM Quantization via Dynamic Gradient Descent
arXiv:2609.00049v1 Announce Type: new
Abstract: Post-training quantization (PTQ) is essential for deploying large language models (LLMs) under strict resource constraints. State-of-the-art PTQ methods quantize each layer with a single closed-form second-order solver: to remain analytically tractabl...
Convergence issues in Relational Concept Analysis based on AOC-posets
arXiv:2609.00054v1 Announce Type: new
Abstract: Formal Concept Analysis (FCA) is an approach for conceptual classification building and rule discovery from a binary table describing a set of objects by a set of attributes. Extensions have been proposed to deal with non-binary and more complex data,...
DISTAL: Distillation and Self-Supervised Pretraining for Structure-Agnostic Materials Property Prediction
arXiv:2609.00059v1 Announce Type: new
Abstract: Materials property prediction remains difficult in low-data settings, where many target properties are supported by only a limited number of labeled samples. Models with the strongest predictive accuracy often depend on crystal structures, which restr...
ReNFT: Repairing Mode Collapse in Reward Post-Training via Internal Probability-Mass Recalibration
arXiv:2609.00061v1 Announce Type: new
Abstract: Reward post-training of diffusion generators inevitably concentrates probability mass on a few reward-favored modes, a mode collapse that erases within-prompt diversity. Existing methods for mitigating collapse rely on external signals or interfaces, ...
HyperWorld: Hypergraph-Structured State Serialization Improves Learned Textual World Models
arXiv:2609.00002v1 Announce Type: new
Abstract: World models enable language-model agents to predict environment dynamics and plan before acting. In text environments, the model must learn symbolic action effects from serialized state descriptions, but the role of serialization structure remains un...
I-CARE: Analysis of interference-related phenomena in a controllable, diverse and representative unlearning setting for text-to-image models
arXiv:2609.00003v1 Announce Type: new
Abstract: Machine unlearning studies the removal of knowledge from an AI model, making the system forget a concept it previously learned. Despite rapid progress in generative machine unlearning, the unintended degradation of semantically related concepts that s...
Discrete-Time MDP Modeling for Multi-Item Capacitated Lot Sizing with Stochastic Demand Timing
arXiv:2609.00004v1 Announce Type: new
Abstract: This paper studies a finite-horizon multi-item capacitated lot-sizing problem in which demand quantities are deterministic, while demand-arrival periods are stochastic. Each demand occurs once within a known time window and must be satisfied no later ...
Incremental Risk Assessment of Progressive Elder Financial Scams via Instruction-Tuned Small Language Models
arXiv:2609.00005v1 Announce Type: new
Abstract: Financial scams targeting older adults increasingly occur through text and voice channels such as email, SMS, and phone calls, unfolding over multiple conversational turns that begin with impersonation or casual contact, escalate through trust buildin...