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XLand-100B: первый в мире большой датасет для контекстного обучения с подкреплением

Хабр, привет! Меня зовут Александр Никулин, я аспирант МФТИ и один из исследователей научной группы «Адаптивные агенты» в Институте AIRI.

Как можно понять из названия, наша группа заинтересована в создании адаптивных агентов, способных обобщаться на новые задачи после обучения. Направление это относительно новое и в литературе именуется как контекстное обучение с подкреплением (далее in-context RL). И мы активно двигаем его вперед! Совсем недавно выпустили две статьи, обе приняты на ICML 2024, а ещё среду на JAX со множеством задач для мета-обучения. Мы обязательно расскажем о них чуть позже (подписывайтесь!), а в этой статье хочется затронуть наш недавний препринт. В нем мы представили и выложили в open-source огромный (по меркам RL) и пока единственный датасет для in-context RL. На сбор траекторий для 40к задач и 130B транзиций потребовалось 50000 GPU-часов. Эту работу мы проделали совместно с коллегами из лаборатории T-Bank AI Research.

Датасетом уже можно пользоваться, так что рассказываем и надеемся на будущий акцепт статьи! Ну а начнем чуть издалека, расскажу, что такое in-context learning, как он появился в RL и почему нам понадобился собственный датасет.

Контекстное и мета-обучение

На самом деле, сказав, что область новая, я чуть чуть схитрил! Конечно же, идея обучения мета‑алгоритмов, то есть алгоритмов, которые сами по себе представляют алгоритмы обучения, появилась относительно давно. В отличие от мультизадачного обучения, мы хотим получить модель, не просто хорошо работающую на всех тренировочных задачах одновременно, а способную максимально эффективно дообучаться на новых за минимальное время. Мета‑обучение существует и в более традиционной области обучения с учителем и в обучении с подкреплением. Для интересующихся: о краткой истории мета‑обучения и основных методах можно узнать подробнее в блогпосте Lilian Weng из Open AI или в недавнем большом обзоре.

Схематическая разница между мультизадачным и мета-обучением. Источник: meta-world.github.io

Однако под новизной я имел в виду способ получения мета‑моделей, набирающий большую популярность в последнее время. Думаю, всем, кто игрался с большими языковыми моделями, например ChatGPT, он знаком, даже если вы не знаете формального названия.

Пример контекстного обучения. Вначале в промпт подаются примеры решения задачи, а дальше модель справляется сама.

Наверное, вы слышали, а может даже пробовали сами, что ChatGPT можно научить новой задаче, просто подав в контекст промпт с некоторым количеством примеров и решений для нее. Для широкого спектра задач это сработает. И это удивительно, ведь никто не учил модель специально решать вашу задачу, она сама разобралась на основе контекста и данных ей примеров как правильно отвечать на новых данных. Данный феномен называется контекстное обучение (in‑context learning или ICL) и по сути своей, является и примером мета‑обучения тоже!

Феномен контекстного обучения был впервые во всей красе продемонстрирован с выходом GPT-3, после чего некоторое время научное сообщество думало, что это свойство исключительно огромных языковых моделей на основе архитектуры трансформер. Однако после было обнаружено, что на него способны и совсем маленькие трансформеры, не трансформеры вовсе, и, в целом, явление это не уникальное для языка, а возникает и в других доменах, например в картиночных генеративных моделях. Долгое время основным ограничением был размер контекста из‑за квадратичности механизма внимания и, как следствие, дороговизны длинных промптов. С появлением миллионных контекстов стало понятно, что контекстное обучение часто гораздо проще и эффективнее более привычного дообучения под конкретную задачу.

Контекстное обучение с подкреплением

Концептуально, контекстное обучение очень хорошо ложится на RL (см. контекстуальный марковский процесс принятия решений). Учитывая, как иногда анекдотически трудно бывает с нуля обучить агента даже на нескольких задачах с помощью обучения с подкреплением, возможность получить агента, способного к быстрой и эффективной адаптации на новых задачах, крайне привлекательна. В конце концов, разве не в этом наша конечная цель — получить аналог базовой (foundation) модели для RL?

Возможный потенциал такого подхода показал Ada от DeepMind, вышедший в прошлом году. Оказалось, что при должном размахе обучения, сложности и разнообразия сред можно получить агента, способного адаптироваться к новым нетривиальным задачам со скоростью равной человеческой, а то и быстрее. Очень советую глянуть видео с презентацией статьи!

Несмотря на успех, Ada обучался с помощью более‑менее традиционного алгоритма из RL, наследуя тем самым все нестабильности обучения и сложности с масштабированием. Можно ли проще?

На самом деле, да. Ведь, если задуматься, в обучении с подкреплением у нас есть траектории взаимодействия агента со средой — суть дискретные последовательности. Да, они состоят из трех модальностей (состояние, действие, награда), но глобально мало чем отличаются от языка с точки зрения трансформера. Можно подавать их в трансформер и предсказывать следующее действие.

Однако так агент не научится максимизировать награду, только имитировать политику в датасете. Можно обучать, обуславливаясь на итоговую суммарную награду в текущей траектории, а во время тестирования промптить наибольшей возможной. Получится Decision Transformer (DT), наверное, самый популярный сейчас метод на основе трансформера в RL.

Визуализация подхода DT. Обратите внимание, что контекст начинается с будущей суммарной наградой. Источник: Lili Chen et al. / arXiv, 2021

Но для контекстного обучения DT подходит плохо, и на самом деле таких способностей у него замечено не было. Во‑первых, разброс суммарной награды может значительно различаться от задачи к задаче, или мы в целом можем заранее его не знать. А во‑вторых, мы не учим трансформер максимизировать награду явно.

Представим, что у нас есть полные истории обучения каких‑то базовых RLных алгоритмов. Награда в них, очевидно, растет с течением обучения. Будем обучать на этом трансформер, подавая траектории как есть, то есть, не меняя порядка и не ломая упорядоченность по награде. Как думаете, что произойдет? А произойдет следующее.

При маленьком размере контекста у нас получится обычный behavioral cloning (BC), так как трансформер будет просто пытаться предсказать действие политики в датасете на основе краткой истории. Однако если мы попробуем расширить контекст достаточно, чтобы вобрать в себя историю улучшения базового алгоритма, например четыре или больше эпизодов, то внезапно трансформер после обучения приобретет in‑context learning свойства! А именно: при тестировании на новой задаче он на основе своего собственного контекста начнет максимизировать награду и решать ранее не виденные задачи (но из схожего с тренировочным распределения). Более того, начнет решать лучше, чем эксперт в данных.

Почему так происходит? У трансформера не остается выбора. Для того, чтобы минимизировать функцию потерь ему придется «дистиллировать» базовый алгоритм, собравший данные. Ключевое здесь, что именно алгоритм улучшения, а не какую‑то одну конкретную усредненную политику. Таким образом, при наличии подходящих данных, у нас получился крайне простой и стабильный метод для обучения мета‑алгоритма обучения с подкреплением, наследующий все открытия для эффективного обучения трансформеров из NLP области. Первым так обучать предложила статья от DeepMind, назвав это Algorithm Distillation (AD). С нее фактически и началась in‑context RL область.

Визуализация подхода AD. В отличие от DT, в контекст подаются состояния, действия и сырые награды в естественном порядке. Источник: Michael Laskin et al. / arXiv, 2022

Любопытно: дальнейший теоретический анализ показал, что обученный таким способом трансформер может реализовывать целые оптимальные RL алгоритмы внутри себя. Причем алгоритмы разнообразные, от простых Thompson Sampling, Lin‑UCB, до многих вариаций TD‑learning, лежащего в основе современных DQN‑подобных алгоритмов. Реализуют ли они их на самом деле, и какие конкретно — вопрос открытый. Теоретический анализ лишь доказывает, что они на это способны. Если вам интересна тема mechanistic interpretability, то вы можете попытать удачу и попробовать декодировать выученные трансформером алгоритмы. Например, недавно так обнаружили, что трансформеры неявно выучивают скрытые модели мира и планируют действия. Так что тема крайне увлекательная!

Проблема контекстного обучения в RL

Только заинтересовавшись in‑context RL, мы быстро поняли что ей не хватает сложного и интересного бенчмарка, а также больших датасетов. Все существующие работы проверяли свои методы на крайне простых средах и были вынуждены каждый раз пересобирать датасеты с нуля, т.к. не существовало стандартизации. У нас, как исследователей, это быстро начало вызывать фрустрацию, ибо в каждой статье среды и датасеты были похожи внешне, но обязательно находились незаметные различия (о которых авторы статей забывали упомянуть), в итоге влияющие на результаты. Мы решили что должны это исправить, и, кажется, у нас получилось!

Преждем чем тратить время и ресурсы на сбор нового датасета, мы, конечно же, посмотрели на все существующие, вдруг их можно приспособить для наших нужд? Оказалось, что из всех нам известных датасетов (особенно крупных) ни один не подходит под требования in‑context RL: не содержит полные истории обучения базовых алгоритмов и не обладает высоким разнообразием задач. Если мы хотим изучать контекстное обучение со всех сторон, например scaling laws по количеству и сложности уникальных задач, а не просто токенов, как в NLP, нам нужен по настоящему разнообразный и большой датасет, содержащий тысячи задач.

Сравнение нашего датасета с существующими. Ни один не позволяет изучать контекстное обучение.

Было решено, что нужно собирать самим. Но где взять среду с множеством уникальных и нетривиальных задач, достаточно быструю, чтобы осилить обучения тысяч RLных агентов с нуля? По счастливой случайности, недавно мы выпустили такую среду сами! Назвали ее XLand‑MiniGrid, т.к. она вдохновлена и берет лучшее от XLand от DeepMind и от широко известной в комьюнити минималистичной MiniGrid. Она представляет собой grid‑world с разреженной наградой, некоторым набором целей и правил, способных динамически изменять окружение. Задачи могут генерироваться процедурно в виде бинарных деревьев.

Визуализация окружения в XLand-MiniGrid. Показан краткий пример действия одного правила, преобразующего два конкретных объекта в новый.

Пример одной задачи в XLand-MiniGrid. В корне дерева находится цель, которую нужно достигнуть. Любая другая вершина задает правила, с помощью которых можно получать новые необходимые для цели объекты из уже существующих.

Представьте, что каждый раз, когда вы заходите в Minecraft, дерево крафта рандомизируется, и вас просят добыть какой‑то сложный предмет. Вам предстоит увлекательная задача с помощью экспериментов и хорошей памяти открыть это дерево крафта самостоятельно. Более того, решив одну такую задачу, вы не сможете генерализоваться на новую (ведь новое дерево крафта скрыто от вас), вам придется начинать все сначала, то есть быть адаптивным — выучить сам процесс обучения и эффективного исследования среды.

Благодаря тому, что среда с нуля написана на JAX, она поддерживает GPU и TPU, а, значит, мы можем обучаться на десятках тысяч параллельных сред одновременно, полностью избегая CPU-боттлнека, присущего большинству пайплайнов обучения в RL.

Сбор датасета

Для сбора датасета мы выбрали medium-1m и trivial-1m — наборы задач из заранее сгенерированных в XLand‑MiniGrid. Один самый простой для датасета поменьше, чтобы быстрее итерироваться, и один более сложный, для основного датасета. Мы заранее выбрали суммарно 40к задач различной сложности из этих наборов. В качестве базового алгоритма взяли наиболее известный и стабильный PPO, добавив GRU в качестве модуля памяти. На каждой задаче обучали на множестве сред и GPU параллельно. Во время обучения собирали все логи с первых 32 сред, чтобы не раздувать размер датасета слишком сильно.

К сожалению, первая попытка сбора провалилась. Оказалось, что большая часть задач слишком сложная для базового PPO+RNN даже если обучать на миллиардах транзиций. Награда слишком разреженная и шансы случайно решить минимальны. Пробовали разные способы улучшить исследование среды агентом, но без особого успеха.

В итоге сошлись к сбору в две фазы. Изначально правила и цель скрыты от агента. Мы слегка схитрили и во время первой фазы сделали их открытыми и подавали агенту как дополнительный вход (goal‑conditioning), обучая сразу на множестве различных задач. Такой агент после обучения мог неплохо решать новые задачи в zero‑shot режиме на основе информации о задаче, поданной на вход. Далее, для какой‑то конкретной задачи мы дообучали агента, полностью маскируя всю информацию о правилах и целях. По сути, после предобучения и маскирования мы получали политику, усредненную по всем задачам, что значительно улучшило способности исследования среды у агента и ускорило сходимость на сложных задачах.

Награда в течение обучения усредненная по множеству задач. Как видно, после предобучения агент достигает гораздо лучшего результата в среднем.

Сбор данных занял в сумме две недели. На сбор траекторий для 40к задач и 130B транзиций потребовалось 50 000 GPU‑часов. После сбора мы отфильтровали некоторое количество задач, если агент так и не смог решить их, или во время сбора на них произошел сбой по той или иной причине. Данные хранятся в формате hdf5 с включенной компрессией. Мы немного поигрались с настройками компрессии и размером кэша, сжав датасет в 15 раз и всего в два раза замедлив сэмплирование. Итоговые статистики можно увидеть в таблице ниже:

Остальные подробности и технические детали сбора можно найти в нашей статье

Валидация датасета

Наконец, после сбора надо было удостовериться, что получившийся датасет отвечает всем нужным нам требованиям. Мы смотрели на две вещи.

Во‑первых, мы построили графики обучающих историй, увидев, что траектории естественным образом упорядочены по возрастанию суммарной награды за эпизод, как и должно быть.

Во‑вторых, мы воспроизвели и обучили Algorithm Distillation (AD) и Decision‑Pretrained Transformer (DPT), два наиболее популярных метода для in‑context RL, чтобы продемонстрировать, что обучаясь на наших данных агент на самом деле проявляет способности к контекстному обучению. Выяснили интересное.

Оказалось, что DPT не умеет из коробки работать со средами где не выполняется марковское свойство, что ранее упоминалось лишь вскользь в оригинальной работе. Касательно AD: после обучения он смог решать простые задачи и показывать признаки контекстного обучения на чуть более сложных, однако далеко от идеала. Вероятно, его нужно учить дольше, а может, нужны новые, более эффективные идеи?

Визуализация тестовой награды AD. На простых задачах контекстное обучение быстро улучшает награду (около 50 эпизодов). Однако на более сложных оно либо пока что не наблюдается, либо быстро выходит на плато далеко от оптимальной награды.

Итог

Как видите, работы предстоит еще много! На данный момент датасет уникален в своей нише, как по размеру, так и по своим свойствам. Мы планируем проверить еще много гипотез на его основе и, я уверен, значительно поднять state‑of‑the‑art в in‑context RL области. Надеемся, он окажется полезным и вам, ведь его можно использовать и для многих других областей тоже, например offline RL.

В любом случае, я надеюсь, что помимо самого датасета, неформальное и краткое введение в эту новую область поведало вам что‑то новое и интересное. Оставайтесь на связи и подписывайтесь на каналы AIRI и нашей команды. Обязательно ставьте звездочки датасету и среде на GitHub. Если вас заинтересовала тема или вы в целом интересуетесь RL и научной работой, хотите попробовать себя в этом, то мы всегда рады с вами пообщаться. Пишите мне или руководителю группы Владу Куренкову.

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29 июл. 2024 г.

07.09.23 16:24 CherryTeam

Cherry Team atlyginimų skaičiavimo programa yra labai naudingas įrankis įmonėms, kai reikia efektyviai valdyti ir skaičiuoti darbuotojų atlyginimus. Ši programinė įranga, turinti išsamias funkcijas ir patogią naudotojo sąsają, suteikia daug privalumų, kurie padeda supaprastinti darbo užmokesčio skaičiavimo procesus ir pagerinti finansų valdymą. Štai keletas pagrindinių priežasčių, kodėl Cherry Team atlyginimų skaičiavimo programa yra naudinga įmonėms: Automatizuoti ir tikslūs skaičiavimai: Atlyginimų skaičiavimai rankiniu būdu gali būti klaidingi ir reikalauti daug laiko. Programinė įranga Cherry Team automatizuoja visą atlyginimų skaičiavimo procesą, todėl nebereikia atlikti skaičiavimų rankiniu būdu ir sumažėja klaidų rizika. Tiksliai apskaičiuodama atlyginimus, įskaitant tokius veiksnius, kaip pagrindinis atlyginimas, viršvalandžiai, premijos, išskaitos ir mokesčiai, programa užtikrina tikslius ir be klaidų darbo užmokesčio skaičiavimo rezultatus. Sutaupoma laiko ir išlaidų: Darbo užmokesčio valdymas gali būti daug darbo jėgos reikalaujanti užduotis, reikalaujanti daug laiko ir išteklių. Programa Cherry Team supaprastina ir pagreitina darbo užmokesčio skaičiavimo procesą, nes automatizuoja skaičiavimus, generuoja darbo užmokesčio žiniaraščius ir tvarko išskaičiuojamus mokesčius. Šis automatizavimas padeda įmonėms sutaupyti daug laiko ir pastangų, todėl žmogiškųjų išteklių ir finansų komandos gali sutelkti dėmesį į strategiškai svarbesnę veiklą. Be to, racionalizuodamos darbo užmokesčio operacijas, įmonės gali sumažinti administracines išlaidas, susijusias su rankiniu darbo užmokesčio tvarkymu. Mokesčių ir darbo teisės aktų laikymasis: Įmonėms labai svarbu laikytis mokesčių ir darbo teisės aktų, kad išvengtų baudų ir teisinių problemų. Programinė įranga Cherry Team seka besikeičiančius mokesčių įstatymus ir darbo reglamentus, užtikrindama tikslius skaičiavimus ir teisinių reikalavimų laikymąsi. Programa gali dirbti su sudėtingais mokesčių scenarijais, pavyzdžiui, keliomis mokesčių grupėmis ir įvairių rūšių atskaitymais, todėl užtikrina atitiktį reikalavimams ir kartu sumažina klaidų riziką. Ataskaitų rengimas ir analizė: Programa Cherry Team siūlo patikimas ataskaitų teikimo ir analizės galimybes, suteikiančias įmonėms vertingų įžvalgų apie darbo užmokesčio duomenis. Ji gali generuoti ataskaitas apie įvairius aspektus, pavyzdžiui, darbo užmokesčio paskirstymą, išskaičiuojamus mokesčius ir darbo sąnaudas. Šios ataskaitos leidžia įmonėms analizuoti darbo užmokesčio tendencijas, nustatyti tobulintinas sritis ir priimti pagrįstus finansinius sprendimus. Pasinaudodamos duomenimis pagrįstomis įžvalgomis, įmonės gali optimizuoti savo darbo užmokesčio strategijas ir veiksmingai kontroliuoti išlaidas. Integracija su kitomis sistemomis: Cherry Team programinė įranga dažnai sklandžiai integruojama su kitomis personalo ir apskaitos sistemomis. Tokia integracija leidžia automatiškai perkelti atitinkamus duomenis, pavyzdžiui, informaciją apie darbuotojus ir finansinius įrašus, todėl nebereikia dubliuoti duomenų. Supaprastintas duomenų srautas tarp sistemų padidina bendrą efektyvumą ir sumažina duomenų klaidų ar neatitikimų riziką. Cherry Team atlyginimų apskaičiavimo programa įmonėms teikia didelę naudą - automatiniai ir tikslūs skaičiavimai, laiko ir sąnaudų taupymas, atitiktis mokesčių ir darbo teisės aktų reikalavimams, ataskaitų teikimo ir analizės galimybės bei integracija su kitomis sistemomis. Naudodamos šią programinę įrangą įmonės gali supaprastinti darbo užmokesčio skaičiavimo procesus, užtikrinti tikslumą ir atitiktį reikalavimams, padidinti darbuotojų pasitenkinimą ir gauti vertingų įžvalgų apie savo finansinius duomenis. Programa Cherry Team pasirodo esanti nepakeičiamas įrankis įmonėms, siekiančioms efektyviai ir veiksmingai valdyti darbo užmokestį. https://cherryteam.lt/lt/
08.10.23 01:30 davec8080

The "Shibarium for this confirmed rug pull is a BEP-20 project not related at all to Shibarium, SHIB, BONE or LEASH. The Plot Thickens. Someone posted the actual transactions!!!! https://bscscan.com/tx/0xa846ea0367c89c3f0bbfcc221cceea4c90d8f56ead2eb479d4cee41c75e02c97 It seems the article is true!!!! And it's also FUD. Let me explain. Check this link: https://bscscan.com/token/0x5a752c9fe3520522ea88f37a41c3ddd97c022c2f So there really is a "Shibarium" token. And somebody did a rug pull with it. CONFIRMED. But the "Shibarium" token for this confirmed rug pull is a BEP-20 project not related at all to Shibarium, SHIB, BONE or LEASH.
24.06.24 04:31 tashandiarisha

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26.06.24 18:46 Jacobethannn098

LEGAL RECOUP FOR CRYPTO THEFT BY ADRIAN LAMO HACKER
26.06.24 18:46 Jacobethannn098

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04.07.24 04:49 ZionNaomi

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13.07.24 21:13 michaelharrell825

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17.07.24 02:26 thompsonrickey

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18.07.24 20:13 austinagastya

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27.08.24 12:50 James889900

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27.08.24 13:06 James889900

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02.09.24 20:24 [email protected]

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06.09.24 01:35 Celinagarcia

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06.09.24 01:44 Celinagarcia

HOW TO RECOVER MONEY LOST IN BITCOIN/USDT TRADING OR TO CRYPTO INVESTMENT !! Hi all, friends and families. I am writing From Alberton Canada. Last year I tried to invest in cryptocurrency trading in 2023, but lost a significant amount of money to scammers. I was cheated of my money, but thank God, I was referred to Hack Recovery Wizard they are among the best bitcoin recovery specialists on the planet. they helped me get every penny I lost to the scammers back to me with their forensic techniques. and I would like to take this opportunity to advise everyone to avoid making cryptocurrency investments online. If you have already lost money on forex, cryptocurrency or Ponzi schemes, please contact [email protected] or WhatsApp: +1 (757) 237–1724 at once they can help you get back the crypto you lost to scammers. BEST WISHES. Celina Garcia.
16.09.24 00:10 marcusaustin

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16.09.24 00:11 marcusaustin

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23.09.24 18:56 matthewshimself

At first, I was admittedly skeptical about Worldcoin (ref: https://worldcoin.org/blog/worldcoin/this-is-worldcoin-video-explainer-series), particularly around the use of biometric data and the WLD token as a reward mechanism for it. However, after following the project closer, I’ve come to appreciate the broader vision and see the value in the underlying tech behind it. The concept of Proof of Personhood (ref: https://worldcoin.org/blog/worldcoin/proof-of-personhood-what-it-is-why-its-needed) has definitely caught my attention, and does seem like a crucial step towards tackling growing issues like bots, deepfakes, and identity fraud. Sam Altman’s vision is nothing short of ambitious, but I do think he & Alex Blania have the chops to realize it as mainstay in the global economy.
01.10.24 14:54 Sinewclaudia

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02.10.24 22:27 Emily Hunter

Can those who have fallen victim to fraud get their money back? Yes, you might be able to get back what was taken from you if you fell prey to a fraud from an unregulated investing platform or any other scam, but only if you report it to the relevant authorities. With the right plan and supporting documentation, you can get back what you've lost. Most likely, the individuals in control of these unregulated platforms would attempt to convince you that what happened to your money was a sad accident when, in fact, it was a highly skilled heist. You should be aware that there are resources out there to help you if you or someone you know has experienced one of these circumstances. Do a search using (deftrecoup (.) c o m). Do not let the perpetrators of this hoaxes get away with ruining you mentally and financially.
18.10.24 09:34 freidatollerud

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31.10.24 00:13 ytre89

Can those who have fallen victim to fraud get their money back? Yes, you might be able to get back what was taken from you if you fell prey to a fraud from an unregulated investing platform or any other scam, but only if you report it to the relevant authorities. With the right plan and supporting documentation, you can get back what you've lost. Most likely, the individuals in control of these unregulated platforms would attempt to convince you that what happened to your money was a sad accident when, in fact, it was a highly skilled heist. You should be aware that there are resources out there to help you if you or someone you know has experienced one of these circumstances. Do a search using (deftrecoup (.) c o m). Do not let the perpetrators of this hoaxes get away with ruining you mentally and financially.
02.11.24 14:44 diannamendoza732

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12.11.24 00:50 TERESA

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17.11.24 09:31 Vivianlocke223

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19.11.24 03:06 [email protected]

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19.11.24 03:07 [email protected]

My entire existence fell apart when a malevolent hacker recently gained access to my online accounts. I felt violated and extremely uneasy after discovering that the digital platforms I depended on for communication, employment, and finances had been compromised. Regaining control and restoring my digital security was an overwhelming task in the immediate aftermath. To help me navigate the difficult process of recovering my accounts and getting my peace of mind back, TRUST GEEKS HACK EXPERT came into my life as a ray of hope. They immediately put their highly skilled professionals to work, thoroughly examining the vulnerability and methodically preventing unwanted access. They guided me through each stage soothingly, explaining what was occurring and why, so I never felt lost or alone. They communicated with service providers to restore my legitimate access while skillfully navigating the complex labyrinth of account recovery procedures. My digital footprint was cleaned and strengthened against future attacks thanks to their equally amazing ability to remove any remaining evidence of the hacker's presence. However, TRUST GEEKS HACK EXPERT actual worth went beyond its technical aspects. They offered constant emotional support during the ordeal, understanding my fragility and sense of violation. My tense nerves were calmed by their comforting presence and kind comments, which served as a reminder that I wasn't alone in this struggle. With their help, I was able to reestablish my sense of security and control, which enabled me to return my attention to the significant areas of my life that had been upended. Ultimately, TRUST GEEKS HACK EXPERT all-encompassing strategy not only recovered my online accounts but also my general peace of mind, which is a priceless result for which I am incredibly appreciative of their knowledge and kindness. Make the approach and send a message to TRUST GEEKS HACK EXPERT Via Web site <> www://trustgeekshackexpert.com/-- E>mail: Trustgeekshackexpert(At)fastservice..com -- TeleGram,<> Trustgeekshackexpert
21.11.24 04:14 ronaldandre617

Being a parent is great until your toddler figures out how to use your devices. One afternoon, I left my phone unattended for just a few minutes rookie mistake of the century. I thought I’d take a quick break, but little did I know that my curious little genius was about to embark on a digital adventure. By the time I came back, I was greeted by two shocking revelations: my toddler had somehow managed to buy a $5 dinosaur toy online and, even more alarmingly, had locked me out of my cryptocurrency wallet holding a hefty $75,000. Yes, you heard that right a dinosaur toy was the least of my worries! At first, I laughed it off. I mean, what toddler doesn’t have a penchant for expensive toys? But then reality set in. I stared at my phone in disbelief, desperately trying to guess whatever random string of gibberish my toddler had typed as a new password. Was it “dinosaur”? Or perhaps “sippy cup”? I felt like I was in a bizarre game of Password Gone Wrong. Every attempt led to failure, and soon the laughter faded, replaced by sheer panic. I was in way over my head, and my heart raced as the countdown of time ticked away. That’s when I decided to take action and turned to Digital Tech Guard Recovery, hoping they could solve the mystery that was my toddler’s handiwork. I explained my predicament, half-expecting them to chuckle at my misfortune, but they were incredibly professional and empathetic. Their confidence put me at ease, and I knew I was in good hands. Contact With WhatsApp: +1 (443) 859 - 2886 Email digital tech guard . com Telegram: digital tech guard recovery . com website link :: https : // digital tech guard . com Their team took on the challenge like pros, employing their advanced techniques to unlock my wallet with a level of skill I can only describe as magical. As I paced around, anxiously waiting for updates, I imagined my toddler inadvertently locking away my life savings forever. But lo and behold, it didn’t take long for Digital Tech Guard Recovery to work their magic. Not only did they recover the $75,000, but they also gave me invaluable tips on securing my wallet better like not leaving it accessible to tiny fingers! Who knew parenting could lead to such dramatic situations? Crisis averted, and I learned my lesson: always keep my devices out of reach of little explorers. If you ever find yourself in a similar predicament whether it’s tech-savvy toddlers or other digital disasters don’t hesitate to reach out to Digital Tech Guard Recovery. They saved my funds and my sanity, proving that no challenge is too great, even when it involves a toddler’s mischievous fingers!
21.11.24 08:02 Emily Hunter

If I hadn't found a review online and filed a complaint via email to support@deftrecoup. com , the people behind this unregulated scheme would have gotten away with leaving me in financial ruins. It was truly the most difficult period of my life.
22.11.24 04:41 [email protected]

I never could have imagined the nightmare of losing access to my digital wallet. All of my cryptocurrency holdings were abruptly imprisoned, inaccessible, and appeared to be lost forever following a catastrophic hardware breakdown. Years of meticulous investment and careful saving were reduced to nothing more than strings of code that I could no longer control, and I could feel the dread and sorrow that swept through me at that very instant. Thankfully, during my worst moment, I came into (TRUST GEEKS HACK EXPERT), a professional service devoted to recovering lost or inaccessible digital data. With optimism, I went out to their team of skilled technologists, laying bare the full nature of my issue. What followed was a laborious, multi-step process that required an almost surgical level of digital forensics and Bitcoin skill. In order to create a thorough profile of my wallet's contents and activities, the (TRUST GEEKS HACK EXPERT) team first thoroughly examined the transaction history and metadata connected to it. Next, they implemented a series of advanced recovery techniques, using cutting-edge software tools to bypass the access barriers that had left me locked out. The entire process was shrouded in secrecy and discretion, with the (TRUST GEEKS HACK EXPERT) team working tirelessly to protect the confidentiality of my sensitive financial information. After what felt like an eternity of nervous anticipation, the day finally arrived when I received the triumphant notification – my wallet had been successfully restored, and all of my precious digital assets had been returned to my control. The sense of relief was indescribable, as I could finally breathe easy knowing that the fruits of my financial discipline had been safeguarded. While the experience of losing access to my wallet was undoubtedly traumatic, (TRUST GEEKS HACK EXPERT) intervention allowed me to emerge from the ordeal with my cryptocurrency holdings intact, and a renewed appreciation for the importance of proactive digital asset management. You can contact Them through EMAIL: [email protected] - TELEGRAM: TRUSTGEEKSHACKEXPERT
22.11.24 15:26 cliftonhandyman

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22.11.24 23:43 teresaborja

all thanks to Tech Cyber Force Recovery expert assistance. As a novice in cryptocurrency, I had been carefully accumulating a modest amount of Bitcoin, meticulously safeguarding my digital wallet and private keys. However, as the adage goes, the best-laid plans can often go awry, and that's precisely what happened to me. Due to a series of technical mishaps and human errors, I found myself locked out of my Bitcoin wallet, unable to access the fruits of my digital labors. Panic set in as I frantically searched for a solution, scouring the internet for any glimmer of hope. That's when I stumbled upon the Tech Cyber Force Recovery team, a group of seasoned cryptocurrency specialists who had built a reputation for their ability to recover lost or inaccessible digital assets. Skeptical at first, I reached out, desperate for a miracle. To my utter amazement, the Tech Cyber Force Recovery experts quickly assessed my situation and devised a meticulous plan of attack. Through their deep technical knowledge, unwavering determination, and a keen eye for detail, they were able to navigate the complex labyrinth of blockchain technology, ultimately recovering my entire Bitcoin portfolio. What had once seemed like a hopeless endeavor was now a reality, and I found myself once again in possession of my digital wealth, all thanks to the incredible efforts of the Tech Cyber Force Recovery team. This experience has not only restored my faith in the cryptocurrency ecosystem. Still, it has also instilled in me a profound appreciation for the critical role that expert recovery services can play in safeguarding one's digital assets. ENAIL < Tech cybers force recovery @ cyber services. com > WEBSITE < ht tps : // tech cyber force recovery. info > TEXT < +1. 561. 726. 3697 >
24.11.24 02:21 [email protected]

I never could have imagined the nightmare of losing access to my digital wallet. All of my cryptocurrency holdings were abruptly imprisoned, inaccessible, and appeared to be lost forever following a catastrophic hardware breakdown. Years of meticulous investment and careful saving were reduced to nothing more than strings of code that I could no longer control, and I could feel the dread and sorrow that swept through me at that very instant. Thankfully, during my worst moment, I came into (TRUST GEEKS HACK EXPERT), a professional service devoted to recovering lost or inaccessible digital data. With optimism, I went out to their team of skilled technologists, laying bare the full nature of my issue. What followed was a laborious, multi-step process that required an almost surgical level of digital forensics and Bitcoin skill. In order to create a thorough profile of my wallet's contents and activities, the (TRUST GEEKS HACK EXPERT) team first thoroughly examined the transaction history and metadata connected to it. Next, they implemented a series of advanced recovery techniques, using cutting-edge software tools to bypass the access barriers that had left me locked out. The entire process was shrouded in secrecy and discretion, with the (TRUST GEEKS HACK EXPERT) team working tirelessly to protect the confidentiality of my sensitive financial information. After what felt like an eternity of nervous anticipation, the day finally arrived when I received the triumphant notification – my wallet had been successfully restored, and all of my precious digital assets had been returned to my control. The sense of relief was indescribable, as I could finally breathe easy knowing that the fruits of my financial discipline had been safeguarded. While the experience of losing access to my wallet was undoubtedly traumatic, (TRUST GEEKS HACK EXPERT) intervention allowed me to emerge from the ordeal with my cryptocurrency holdings intact, and a renewed appreciation for the importance of proactive digital asset management. You can contact Them through EMAIL: [email protected] - TELEGRAM: TRUSTGEEKSHACKEXPERT
25.11.24 02:19 briankennedy

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25.11.24 02:20 briankennedy

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26.11.24 21:59 [email protected]

In a world brimming with enticing investment opportunities, it is crucial to tread carefully. The rise of digital currencies has attracted many eager investors, but along with this excitement lurk deceitful characters ready to exploit the unsuspecting. I learned this lesson the hard way, and I want to share my story in the hopes that it can save someone from making the same mistakes I did. It all began innocently enough when I came across an engaging individual on Facebook. Lured in by promises of high returns in the cryptocurrency market, I felt the electric thrill of potential wealth coursing through me. Initial investments returned some profits, and that exhilarating taste of success fueled my ambition. Encouraged by a meager withdrawal, I decided to commit even more funds. This was the moment I let my guard down, blinded by greed. As time went on, the red flags started to multiply. The moment I tried to withdraw my earnings, a cascade of unreasonable fees appeared like a thick mist, obscuring the truth. “Just a little more,” they said, “Just until the next phase.” I watched my hard-earned money slip through my fingers as I scraped together every last cent to pay those relentless fees. My trust had become my downfall. In the end, I lost not just a significant amount of cash, but my peace of mind about $1.1 million vanished into the abyss of false promises and hollow guarantees. But despair birthed hope. After a cascade of letdowns, I enlisted the help of KAY-NINE CYBER SERVICES, a team that specializes in reclaiming lost funds from scams. Amazingly, they worked tirelessly to piece together what had been ripped away, providing me with honest guidance when I felt utterly defeated. Their expertise in navigating the treacherous waters of crypto recovery was a lifeline I desperately needed. To anyone reading this, please let my story serve as a warning. High returns often come wrapped in the guise of deception. Protect your investments, scrutinize every opportunity, and trust your instincts. Remember, the allure of quick riches can lead you straight to heartbreak, but with cautious determination and support, it is possible to begin healing from such devastating loss. Stay informed, stay vigilant, and may you choose your investment paths wisely. Email: kaynine @ cyberservices . com
26.11.24 23:12 rickrobinson8

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26.11.24 23:12 rickrobinson8

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00:39 [email protected]

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