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Sponsor Posts Subquadratic: the LLM built for 12M-token reasoning — SubQ can reason across entire codebases and document sets in one pass with no RAG workarounds. Read how SubQ 1.1 Small holds near-perfect retrieval out to 12M tokens. Stop vibe coding analytics — Equals AI turns questions about your business into
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Financial fraud has evolved significantly over the past decade. What once consisted primarily of stolen credit cards and simple phishing scams has expanded into sophisticated attacks involving synthetic identities, AI-generated phishing emails, deepfake voice impersonation, account takeover (ATO), and coordinated fraud rings. These threats are becoming increasingly difficult to detect
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Break free from hardcoded integrations and empower your AI assistant to manage your Notion workspace dynamically using TypeScript, the MCP SDK, and standard I/O. As AI agents transition from simple conversational assistants to active partners in our development workflows, a critical bottleneck has emerged: how do they interact with
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Internally, it felt like momentum. Users were active, the interview feedback sounded positive, and feature requests kept piling up fast enough to create the impression that the market was pulling the product forward. Commercially, very little underneath was compounding properly. Users struggled through onboarding, disappeared after testing, and rarely converted
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Cost per token is an infrastructure metric. Cost per successful task is a business metric. Here's the one equation that connects them — and why it flips the model you should deploy. Every model you can call — GPT, Gemini, Claude, Qwen, DeepSeek — is sold on cost per token and
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*The festival-to-deal pipeline is dead for 99% of creators. The audience you don’t have yet is the real budget line.* I finished a Lost Garden episode last month and did the thing every indie filmmaker has done at least once: I sat there refreshing a blank analytics page, waiting
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Anthropic's Claude Fable 5 returned to public attention almost immediately after coming back online. Within days, another jailbreak claim appeared, forcing the discussion back to a familiar question: can frontier AI models stay useful while also being hard to abuse? This is not just another "model got
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Why enterprise AI platforms must evolve beyond workflow automation toward reasoning, governance, observability, and trustworthy autonomous operations. Enterprise AI has entered a new phase. Success is no longer determined solely by increasingly capable language models, but but by the platforms that operate them securely, govern their behavior, observe their decisions,
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Today’s AI-geopolitical signal is not a single breakthrough; it is a stack-deepening pattern. Frontier AI actors are trying to reduce dependence on external bottlenecks by controlling more of the infrastructure beneath their models: inference chips, model-routing systems, cloud financing, platform distribution, and compliance interfaces. The clearest example is DeepSeek’
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Coding agents imitate a healthy codebase well but bring no judgment to an empty one — so I built a spec-driven framework to supply the discipline I won't. A postmortem, a pivot, a retrofit test, and whether you actually need any of it. I have a bad habit. I
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Overview Krea-2-Realism-LoRA is a Low-Rank Adaptation module trained by gokaygokay that specializes in pushing Krea 2 toward natural, candid, photorealistic imagery of everyday subjects without requiring explicit style keywords like "photorealistic" or "8k DSLR." The model was trained using the FAL Krea LoRA Trainer on krea/
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Every AI project assumes the data underneath it is already aligned. It almost never is. Before a model trains, before a dashboard loads, before a retrieval pipeline returns anything useful, someone has to answer a question that sounds trivial and is not: do these two columns actually mean the same
