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Habr12 событий апреля, которые нельзя пропуститьМы собрали для вас серию открытых уроков, которые пройдут в апреле и помогут не просто разобраться в сложных темах, а применить знания на практике. Будущее AI агентов на основе LLM, Prometheus для мониторинга, как избежать хаоса в IT-проектах и как обучить модель понимать языки — на эти и не только темы поговорим с экспертами в IT. Рассмотрим реальные кейсы, обсудим опыт и получим понимание того, как внедрять эти технологии в проекты.<a href="https://habr.com/ru/companies/otus/articles/899644/" rel="nofollow noopener noreferrer" translate="no" target="_blank">https://habr.com/ru/companies/otus/articles/899644/</a><a href="https://zhub.link/tags/AI_%D0%B0%D0%B3%D0%B5%D0%BD%D1%82%D1%8B" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#AI_агенты</a> <a href="https://zhub.link/tags/Scrum" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Scrum</a> <a href="https://zhub.link/tags/seq2seq" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#seq2seq</a> <a href="https://zhub.link/tags/%D0%B0%D0%B2%D1%82%D0%BE%D0%BC%D0%B0%D1%82%D0%B8%D0%B7%D0%B0%D1%86%D0%B8%D1%8F_%D1%82%D0%B5%D1%81%D1%82%D0%B8%D1%80%D0%BE%D0%B2%D0%B0%D0%BD%D0%B8%D1%8F" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#автоматизация_тестирования</a> <a href="https://zhub.link/tags/Docker" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Docker</a> <a href="https://zhub.link/tags/Apache_Kafka" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Apache_Kafka</a> <a href="https://zhub.link/tags/%D0%A1%D0%BC%D0%B0%D1%80%D1%82%D0%BA%D0%BE%D0%BD%D1%82%D1%80%D0%B0%D0%BA%D1%82%D1%8B" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Смартконтракты</a> <a href="https://zhub.link/tags/data_science" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#data_science</a> <a href="https://zhub.link/tags/prometheus" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#prometheus</a>

HabrВедущий разработчик ChatGPT и его новый проект — Безопасный СверхинтеллектМногие знают об Илье Суцкевере только то, что он выдающийся учёный и программист, родился в СССР, соосновал OpenAI и входит в число тех, кто в 2023 году изгнал из компании менеджера Сэма Альтмана. А когда того вернули, Суцкевер уволился по собственному желанию в новый стартап Safe Superintelligence («Безопасный Сверхинтеллект»). Илья Суцкевер действительно организовал OpenAI вместе с Маском, Брокманом, Альтманом и другими единомышленниками, причём был главным техническим гением в компании. Ведущий учёный OpenAI сыграл ключевую роль в разработке ChatGPT и других продуктов. Сейчас Илье всего 38 лет — совсем немного для звезды мировой величины.<a href="https://habr.com/ru/companies/ruvds/articles/892646/" rel="nofollow noopener noreferrer" translate="no" target="_blank">https://habr.com/ru/companies/ruvds/articles/892646/</a><a href="https://zhub.link/tags/%D0%98%D0%BB%D1%8C%D1%8F_%D0%A1%D1%83%D1%86%D0%BA%D0%B5%D0%B2%D0%B5%D1%80" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Илья_Суцкевер</a> <a href="https://zhub.link/tags/Ilya_Sutskever" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Ilya_Sutskever</a> <a href="https://zhub.link/tags/OpenAI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#OpenAI</a> <a href="https://zhub.link/tags/10x_engineer" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#10x_engineer</a> <a href="https://zhub.link/tags/AlexNet" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#AlexNet</a> <a href="https://zhub.link/tags/Safe_Superintelligence" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Safe_Superintelligence</a> <a href="https://zhub.link/tags/ImageNet" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#ImageNet</a> <a href="https://zhub.link/tags/%D0%BD%D0%B5%D0%BE%D0%BA%D0%BE%D0%B3%D0%BD%D0%B8%D1%82%D1%80%D0%BE%D0%BD" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#неокогнитрон</a> <a href="https://zhub.link/tags/GPU" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#GPU</a> <a href="https://zhub.link/tags/GPGPU" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#GPGPU</a> <a href="https://zhub.link/tags/CUDA" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#CUDA</a> <a href="https://zhub.link/tags/%D0%BA%D0%BE%D0%BC%D0%BF%D1%8C%D1%8E%D1%82%D0%B5%D1%80%D0%BD%D0%BE%D0%B5_%D0%B7%D1%80%D0%B5%D0%BD%D0%B8%D0%B5" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#компьютерное_зрение</a> <a href="https://zhub.link/tags/LeNet" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#LeNet</a> <a href="https://zhub.link/tags/Nvidia_GTX" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Nvidia_GTX</a> 580 <a href="https://zhub.link/tags/DNNResearch" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#DNNResearch</a> <a href="https://zhub.link/tags/Google_Brain" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Google_Brain</a> <a href="https://zhub.link/tags/%D0%90%D0%BB%D0%B5%D0%BA%D1%81_%D0%9A%D1%80%D0%B8%D0%B6%D0%B5%D0%B2%D1%81%D0%BA%D0%B8" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Алекс_Крижевски</a> <a href="https://zhub.link/tags/%D0%94%D0%B6%D0%B5%D1%84%D1%84%D1%80%D0%B8_%D0%A5%D0%B8%D0%BD%D1%82%D0%BE%D0%BD" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Джеффри_Хинтон</a> <a href="https://zhub.link/tags/Seq2seq" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Seq2seq</a> <a href="https://zhub.link/tags/TensorFlow" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#TensorFlow</a> <a href="https://zhub.link/tags/AlphaGo" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#AlphaGo</a> <a href="https://zhub.link/tags/%D0%A2%D0%BE%D0%BC%D0%B0%D1%88_%D0%9C%D0%B8%D0%BA%D0%BE%D0%BB%D0%BE%D0%B2" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Томаш_Миколов</a> <a href="https://zhub.link/tags/Word2vec" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Word2vec</a> <a href="https://zhub.link/tags/fewshot_learning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#fewshot_learning</a> <a href="https://zhub.link/tags/%D0%BC%D0%B0%D1%88%D0%B8%D0%BD%D0%B0_%D0%91%D0%BE%D0%BB%D1%8C%D1%86%D0%BC%D0%B0%D0%BD%D0%B0" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#машина_Больцмана</a> <a href="https://zhub.link/tags/%D1%81%D0%B2%D0%B5%D1%80%D1%85%D0%B8%D0%BD%D1%82%D0%B5%D0%BB%D0%BB%D0%B5%D0%BA%D1%82" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#сверхинтеллект</a> <a href="https://zhub.link/tags/GPT" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#GPT</a> <a href="https://zhub.link/tags/ChatGPT" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#ChatGPT</a> <a href="https://zhub.link/tags/ruvds_%D1%81%D1%82%D0%B0%D1%82%D1%8C%D0%B8" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#ruvds_статьи</a>

HabrОбработка текста. Модель Sequence-to-sequenceСегодня мы рассмотрим принцип работы модели seq2seq, модификации, как верно подготовить данные для модели.<a href="https://habr.com/ru/articles/803815/" rel="nofollow noopener noreferrer" translate="no" target="_blank">https://habr.com/ru/articles/803815/</a><a href="https://zhub.link/tags/data_science" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#data_science</a> <a href="https://zhub.link/tags/seq2seq" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#seq2seq</a> <a href="https://zhub.link/tags/%D1%82%D0%BE%D0%BA%D0%B5%D0%BD%D0%B8%D0%B7%D0%B0%D1%86%D0%B8%D1%8F" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#токенизация</a> <a href="https://zhub.link/tags/embeddings" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#embeddings</a> <a href="https://zhub.link/tags/llm" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#llm</a> <a href="https://zhub.link/tags/%D1%83%D0%B8%D0%B8" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#уии</a>

HabrПредсказать ошибку. Как методы оценки неопределенности помогают повышать качество seq2seq-моделейВсем привет! Меня зовут Артём Важенцев , я аспирант в Сколтехе и младший научный сотрудник AIRI. Наша группа занимается исследованием и разработкой новых методов оценивания неопределенности для языковых моделей. Этим летом мы опубликовали две статьи на ACL 2023 . Про одну из них я уже рассказывал в одном из предыдущих текстов — там мы описали новый гибридный метод оценивания неопределенности для задачи выборочной классификации текстов. Другая же статья про то, как мы адаптировали современные методы оценивания неопределенности на основе скрытого представления модели для задачи генерации текста, а так же показали их высокое качество и скорость работы для задачи обнаружения примеров вне обучающего распределения. Ниже я хотел бы подробнее рассказать об используемых методах и результатах, которые мы получили.<a href="https://habr.com/ru/companies/airi/articles/787340/" rel="nofollow noopener noreferrer" translate="no" target="_blank">https://habr.com/ru/companies/airi/articles/787340/</a><a href="https://zhub.link/tags/uncertainty_estimation" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#uncertainty_estimation</a> <a href="https://zhub.link/tags/natural_language_processing" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#natural_language_processing</a> <a href="https://zhub.link/tags/machine_translation" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#machine_translation</a> <a href="https://zhub.link/tags/question_answering" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#question_answering</a> <a href="https://zhub.link/tags/summarization" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#summarization</a> <a href="https://zhub.link/tags/seq2seq" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#seq2seq</a>

Félicien BretonCory Doctorow <a href="https://mamot.fr/@pluralistic" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@pluralistic</a> "on how a poisoned <a href="https://mstdn.social/tags/ML" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#ML</a> system could be abused in ways that evade detection": <a href="https://pluralistic.net/2022/10/21/let-me-summarize/#i-read-the-abstract" rel="nofollow noopener noreferrer" target="_blank">https://pluralistic.net/2022/10/21/let-me-summarize/#i-read-the-abstract</a> <a href="https://mstdn.social/tags/LLM" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#LLM</a> <a href="https://mstdn.social/tags/seq2seq" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#seq2seq</a> <a href="https://mstdn.social/tags/metaBackdoor" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#metaBackdoor</a> <a href="https://mstdn.social/tags/machineLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#machineLearning</a> <a href="https://mstdn.social/tags/ai" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#ai</a> <a href="https://mstdn.social/tags/backdoors" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#backdoors</a> <a href="https://mstdn.social/tags/modelSpinning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#modelSpinning</a> <a href="https://mstdn.social/tags/dataGovernance" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#dataGovernance</a> <a href="https://chirp.social/@dataGovernance" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@dataGovernance</a> <a href="https://mstdn.social/tags/AIEthics" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#AIEthics</a> <a href="https://mstdn.social/tags/ethicalAI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#ethicalAI</a> <a href="https://mstdn.social/tags/retrieval" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#retrieval</a> <a href="https://mstdn.social/tags/dataMining" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#dataMining</a> <a href="https://mstdn.social/tags/dataDon" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#dataDon</a> <a href="https://mstdn.social/tags/infoSec" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#infoSec</a>

n0bodyCan anyone recommend an online survey course on Neural Networks in Python? I'm especially interested in learning about applied <a href="https://hachyderm.io/tags/NLP" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#NLP</a>, <a href="https://hachyderm.io/tags/RNN" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#RNN</a>, <a href="https://hachyderm.io/tags/CNN" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#CNN</a>, <a href="https://hachyderm.io/tags/Seq2Seq" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#Seq2Seq</a>, <a href="https://hachyderm.io/tags/BERT" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#BERT</a>, and <a href="https://hachyderm.io/tags/GPT" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#GPT</a>. Thanks!

Dave HowcroftThis is not to say, however, that I think these models are useless. I think the interesting question is how to integrate these models into systems that express a particular meaning, a la data-to-text <a href="https://mastodon.social/tags/NaturalLanguageGeneration" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#NaturalLanguageGeneration</a>. Whether this involves <a href="https://mastodon.social/tags/PromptEngineering" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#PromptEngineering</a>, integrating them into the decoder for <a href="https://mastodon.social/tags/seq2seq" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#seq2seq</a> models, or some other more clever application remains to be seen. I am looking forward to seeing how <a href="https://mastodon.social/tags/LLM" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#LLM</a>/s get used for <a href="https://mastodon.social/tags/NLG" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#NLG</a> going forward.

Dave HowcroftAround 2015 and 2016 we saw sequence-to-sequence (<a href="https://mastodon.social/tags/seq2seq" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#seq2seq</a>) models applied to data-to-text <a href="https://mastodon.social/tags/NLG" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#NLG</a> for the first time. These models were trained end-to-end and were very exciting because it raised the prospect of reducing the amount of hand-crafted <a href="https://mastodon.social/tags/GrammarEngineering" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#GrammarEngineering</a> one would have to do to create a <a href="https://mastodon.social/tags/NaturalLanguageGeneration" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#NaturalLanguageGeneration</a> system.

Aurélien Grosdidier ✅Direct speech-to-speech <a href="https://mastodon.social/tags/translation" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#translation</a> with a sequence-to-sequence model | <a href="https://mastodon.social/tags/google" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#google</a> <a href="https://mastodon.social/tags/machinelearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#machinelearning</a> <a href="https://mastodon.social/tags/nlp" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#NLP</a> <a href="https://mastodon.social/tags/seq2seq" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#seq2seq</a> <a href="https://mastodon.social/tags/speech" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#speech</a> <a href="https://mastodon.social/tags/translatotron" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#translatotron</a> <a href="https://arxiv.org/abs/1904.06037" rel="nofollow noopener noreferrer" target="_blank">https://arxiv.org/abs/1904.06037</a>

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