BREAKINGOpenAI closes $40B round at $340B valuation — largest private tech raise ever·MODELSAnthropic ships Claude Opus 4 with extended thinking and agentic capabilities·FUNDINGxAI raises $6B Series C led by Andreessen Horowitz for Grok infrastructure·REGULATIONEU AI Act enters full enforcement — high-risk systems must comply now·AGENTSGoogle DeepMind open-sources Gemini Agent Framework for autonomous task completion·RESEARCHStanford HAI: Enterprise AI adoption hits 78% globally, GenAI in production at 45%·WARNINGUS Senate passes AI Transparency Act — content labeling required at scale·PRODUCTMeta releases Llama 4 Maverick open-weight model rivaling proprietary alternatives·MODELSDeepSeek V3 scores within 2% of GPT-4o on MMLU at 1/10th the inference cost·FUNDINGMistral AI raises €600M Series B at €6B valuation for European AI sovereignty·BREAKINGOpenAI closes $40B round at $340B valuation — largest private tech raise ever·MODELSAnthropic ships Claude Opus 4 with extended thinking and agentic capabilities·FUNDINGxAI raises $6B Series C led by Andreessen Horowitz for Grok infrastructure·REGULATIONEU AI Act enters full enforcement — high-risk systems must comply now·AGENTSGoogle DeepMind open-sources Gemini Agent Framework for autonomous task completion·RESEARCHStanford HAI: Enterprise AI adoption hits 78% globally, GenAI in production at 45%·WARNINGUS Senate passes AI Transparency Act — content labeling required at scale·PRODUCTMeta releases Llama 4 Maverick open-weight model rivaling proprietary alternatives·MODELSDeepSeek V3 scores within 2% of GPT-4o on MMLU at 1/10th the inference cost·FUNDINGMistral AI raises €600M Series B at €6B valuation for European AI sovereignty·

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I Built the Same B2B Document Extractor Twice: Rules vs. LLM

May 13, 2026Towards Data Science

Event Summary

A practical comparison between rule-based PDF extraction using pytesseract and an LLM-based approach with Ollama and LLaMA 3, based on a realistic B2B order scenario. The post I Built the Same B2B Document Extractor Twice: Rules vs. LLM appeared first on Towards Data Science.

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