Анатомія ШІ: дизайн концепти та процес розробки з нуля
Manage episode 480213207 series 3015412
محتوای ارائه شده توسط Fwdays Tech Talks. تمام محتوای پادکست شامل قسمتها، گرافیکها و توضیحات پادکست مستقیماً توسط Fwdays Tech Talks یا شریک پلتفرم پادکست آنها آپلود و ارائه میشوند. اگر فکر میکنید شخصی بدون اجازه شما از اثر دارای حق نسخهبرداری شما استفاده میکند، میتوانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal
Зустрічайте восьмий випуск Fwdays Architecture Talks! Наші постійні спікери — Олександр Савченко, Йожеф Гісем та гість випуску Дмитро Овчаренко, AI CTO of Ministry of Digital Transformation, обговорять теми: — Reference Architecture(s), Patterns, Styles для AI — Процес створення кастомної LLM - Тренування моделей - Основні quality attributes (performance, caching, availability, security, ethical aspects) — Як з'являються AI/GenAI інженери та де їх шукати? Запрошуємо вас на конференцію Highload fwdays'25: https://bit.ly/3DitOVr Корисні посилання: — AI Enterprise Architecture: - https://opea-project.github.io/latest/framework/framework.html - https://www.nvidia.com/en-us/data-center/products/ai-enterprise/ - FTI - https://learning.oreilly.com/library/view/llm-engineers-handbook/9781836200079/ — What are Large Language Models (LLMs)? by Databricks - https://www.databricks.com/glossary/large-language-models-llm — Continius pre-training vs finetuning - https://www.linkedin.com/pulse/teaching-old-dog-new-tricks-difference-between-lewis-ms-ccrp-ches-3abqc/ — Inference high-load and LLM in production - https://www.youtube.com/watch?v=NJ1jAfWR84k&list=WL&index=11&t=134s, — Recommended Book by O.Savchenko: Build a Large Language Model (From Scratch) by Sebastian Raschka - https://www.amazon.com/Build-Large-Language-Model-Scratch/dp/1633437167 - Code for developing and videos from Book - https://github.com/rasbt/LLMs-from-scratch - Author Youtube - https://www.youtube.com/@SebastianRaschka — Thoughtworks Tech Radar - AI items from ON-HOLD - https://www.thoughtworks.com/radar/techniques — ISO/IEC 42001:2023 - https://www.iso.org/ru/standard/81230.html — EU Artificial Intelligence Act - https://artificialintelligenceact.eu/ — Custom LLMs - https://er.ucu.edu.ua/server/api/core/bitstreams/1b205c1b-226c-4021-86e7-29a6063a46e6/content - GPT-NL (Netherlands) - Modello Italia (Italy, 9B parameters) - ALLaM (Saudi Arabia, 70B parameters) - SEA-Lion (Singapore, 7B parameters) - TAIDE (Taiwan, 13B parameters) - UAE’s Falcon models — Datasets info: - Malyuk Corpus: https://huggingface.co/datasets/lang-uk/malyuk - A large Ukrainian web corpus useful for pretraining foundational models. - NER-UK: https://github.com/lang-uk/ner-uk - A dataset for Named Entity Recognition (NER) covering people, organizations, and locations. - UA-GEC (Grammarly Corpus): https://github.com/grammarly/ua-gec - Focused on grammatical error correction—useful for fine-tuning language correctness models. - БрУК (Brown Ukrainian Corpus): https://github.com/brown-uk/corpus - A balanced Ukrainian text corpus for linguistic analysis and text classification tasks. - ZNO Corpus: https://huggingface.co/datasets/osyvokon/zno - Extracted from Ukrainian standardized exam texts, beneficial for educational AI applications. - Eval-UA-tion Benchmark: https://aclanthology.org/2024.unlp-1.13/ - A standardized benchmarking suite for evaluating Ukrainian LLMs across multiple NLP tasks. - UNLP-2024 Shared Task: https://github.com/unlp-workshop/unlp-2024-shared-task - A leaderboard and challenge dataset for fine-tuning Ukrainian LLMs. - Awesome Ukrainian NLP: https://github.com/osyvokon/awesome-ukrainian-nlp - A collection of Ukrainian NLP resources, pretrained models, datasets, and tools. На що варто підписатися: – Більше цікавого для розробників: https://fwdays.com – Телеграм-канал Fwdays: https://t.me/fwdays – Телеграм-канал Олексія: https://t.me/OleksiiTheArchitect – LinkedIn Олексія: https://www.linkedin.com/in/alexhelkar/ – LinkedIn Олександра: https://www.linkedin.com/in/o-savchenko/ – LinkedIn Дмитра: https://www.linkedin.com/in/dmytroovcharenko/?originalSubdomain=ua
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