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Эффективный запуск и инференс LLM на своем сервере с нуля (часть 1)

Привет, Хабр! На связи CEO команды Compressa AI. Недавно обнаружил для себя крутой базовый курс по эффективному запуску и инференсу LLM моделей от легенды AI мира — Andrew NG и его платформы DeepLearning. Он полностью на английском языке в формате видео, поэтому я осмелился адаптировать его под формат Хабра на русском языке. Знания должны быть доступны всем и в удобной форме, так ведь?

Многие команды (включая и Compressa AI) начинали LLM проекты с использования облачных API. Но по мере развития все больше разработчиков хотят использовать open-source LLM, чтобы экономить на токенах, снижать latency, запускать fine-tuning на собственных данных и в целом меньше зависеть от внешних моделей.

Из этого курса вы узнаете детали эффективного обслуживания и дообучения open-source LLM, включая методы обработки множества запросов от нескольких пользователей. Используя несколько таких методов одновременно, вы можете улучшить как задержку (latency), так и пропускную способность (throughput). Например, благодаря применению последних open-source технологий в своем продукте, мы добились увеличения пропускной способности до 70x на 1 GPU в сравнении с дефолтными Hugging Face & PyTorch.

Курс слишком объемный даже для лонгрида, в нем много практического кода, поэтому сегодня начну с первых уроков и выпущу следующие части, если увижу живой интерес. Это адаптация, а не прямой копипаст, поэтому где-то немного расширю курс информацией от себя, а где-то сокращу. Также хочется отметить, что русифицирование терминов вокруг LLM — дело довольно неблагодарное, поэтому часть из них будет на английском.

Что внутри курса?

Детали генерации текста с помощью LLM по одному токену за раз и реализация KV-Caching;
Batching для обработки нескольких входных данных одновременно;
Continuous batching для обработки потока запросов в реальном времени без ожидания формирования полных батчей;
Quantization для уменьшения потребления памяти моделью и снижения требований к железу;
LoRA как эффективный метод fine-tuning без изменения изначальных весов модели;
Объединение нескольких LoRA с continuous batching для одновременного обслуживания десятков дообученных моделей.

От слов к… сути курса

Следуя структуре курса, в первом уроке расскажу и покажу, как итеративно генерировать текст с LLM по одному токену за раз и как этот процесс разделить на две фазы — pre-fill и decode, а также оптимизировать его с помощью KV-caching (кеширования части вычислений).

Загрузка LLM из Hugging Face

Начнем с загрузки LLM из Hugging Face, которая послужит примером модели для инференса (a.k.a. генерации output токенов). В оригинальном курсе используется GPT-2, но в ней плохо поддерживается русский язык, поэтому буду использовать русскоязычный аналог — rugpt3small_based_on_gpt2 на протяжении всего курса.

Давайте теперь импортируем необходимые зависимости (PyTorch, transformers и другие), а затем загрузим нашу LLM и соответствующий токенизатор из Hugging Face.

# Импортируем зависимости
import matplotlib.pyplot as plt
import numpy as np
import time
import torch

# Загружаем LLM и токенизатор
from transformers import AutoModelForCausalLM, AutoTokenizer
model_name = "ai-forever/rugpt3small_based_on_gpt2"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

Если прилетают ошибки, прочитайте их и установите нужные библиотеки с помощью pip install или аналога.

А если хотите глубже посмотреть на архитектуру модели, используйте команду ниже:

print(model)

Здесь стоит напомнить, что GPT-2 и большинство современных LLM — это decoder модели с точки зрения архитектуры. Если изначально модели следовали логике «encoder преобразует input токены в embeddings, а decoder генерирует output токены на основе этих embeddings», то в GPT-2 входные данные сразу преобразуются в embeddings, а затем проходят через серию блоков. Ключевая особенность таких моделей — генерация текста по одному токену за раз, что делает их авторегрессионными. Визуализация на картинке ниже:

Процесс генерации токенов

Ок, теперь когда поговорили про особенности нашей модели и загрузили ее, давайте исследуем сам процесс генерации текста. Возьмем простой промпт:

prompt = "Каждое утро я пью кофе с"

Теперь пропустим этот промпт через токенизатор:

inputs = tokenizer(prompt, return_tensors="pt")

Здесь return_tensors="pt" указывает, что мы хотим получить результаты в формате PyTorch. Он отличается от форматов NumPy или TensorFlow, которые вы тоже можете использовать, но сегодня работаем именно с ним.

Результат токенизации — словарь, содержащий несколько тензоров:

print(inputs)
# {'input_ids': tensor([[ 6207,   900,   647,  7949,   417, 40946,  6715,   281]]), 'attention_mask': tensor([[1, 1, 1, 1, 1, 1, 1, 1]])}

Разберем полученные тензоры:

input_ids: Основной тензор, представляющий числовое отображение нашего текста в токены. Каждое число соответствует определенному токену в словаре модели.
attention_mask: Этот тензор состоит из единиц и имеет ту же длину, что и input_ids.

Концепция attention_mask станет более понятной, когда мы перейдем к batching. Пока достаточно воспринимать его как вспомогательный тензор, который идет вместе с input_ids и определяет, на какие токены внутри входных данных LLM следует обращать внимание при обработке.

После токенизации входных данных мы готовы передать их в модель и проанализировать результат. Как это делается:

# Отключаем вычисление градиентов для экономии памяти при инференсе
with torch.no_grad():
    # Передаем токенизированные входные данные в модель
    outputs = model(**inputs)

# Извлекаем logits — необработанные предсказания модели
logits = outputs.logits
print(logits.shape)
# torch.Size([1, 8, 50264])

Полученный тензор имеет 3 измерения:

1: размер batch (в нашем случае 1, так как мы передали один input);
8: количество токенов в нашем input;
50264: размер словаря модели (количество возможных токенов для output).

Следующий шаг после получения logits от модели — определить, какой токен модель предскажет как наиболее вероятное продолжение последовательности:

# Выбираем logits только для нового токена
last_logits = logits[0, -1, :]
# Находим индекс токена с наибольшей вероятностью быть следующим в последовательности
next_token_id = last_logits.argmax()
print(next_token_id)
# tensor(29258)

Теперь используем токенизатор для декодирования полученного токена обратно в обычный текст:

predicted_token = tokenizer.decode(next_token_id)
print(predicted_token)
# ' молоком'

Если вспомнить исходный промпт «Каждое утро я пью кофе с», можно заметить, что продолжение грамматически корректно и логически осмысленно в контексте данного ввода.

Теперь вместо выбора только наиболее вероятного токена давайте рассмотрим топ-10 наиболее вероятных вариантов продолжения:

top_k = torch.topk(last_logits, k=10)
tokens = [tokenizer.decode(tk) for tk in top_k.indices]
print(tokens)
# [' молоком', ' сахаром', ' лим', ' кори', ' шоколад', ' конья', ' було', ' м', ' пирож', ' утра']

Ставьте лайк, если тоже любите кофе с конья(ком) по утрам :)

При использовании разных стратегий декодирования модель может выбрать какой-то из этих альтернативных токенов. В LLM степень «креативности» при выборе менее вероятных токенов обычно контролируется температурой. Но в это не буду углубляться в рамках текущего урока.

Собственно, после генерации первого токена для продолжения нашей фразы (молоком) можем использовать его для создания нового входного тензора и дальнейшей генерации текста:

next_inputs = {
    # Обновляем input_ids, добавляя новый токен к исходной последовательности
    "input_ids": torch.cat(
        [inputs["input_ids"], next_token_id.reshape((1, 1))],
        dim=1
    ),

# Обновляем attention_mask, добавляя 1 для нового токена

    "attention_mask": torch.cat(
        [inputs["attention_mask"], torch.tensor([[1]])],
        dim=1
    )
}

После добавления нового токена давайте взглянем на обновленный input:

print(next_inputs["input_ids"], next_inputs["input_ids"].shape)
print(next_inputs["attention_mask"], next_inputs["attention_mask"].shape)
# tensor([[ 6207,   900,   647,  7949,   417, 40946,  6715,   281, 29258]]) torch.Size([1, 9])
# tensor([[1, 1, 1, 1, 1, 1, 1, 1, 1]]) torch.Size([1, 9])

Если разобрать результаты:

Видим новые input_ids, включая новый токен (29258) в конце;
Форма тензора изменилась с [1, 8] на [1, 9], отражая добавление нового токена;
Аналогично для attention_mask.

Замеряем скорость

Теперь давайте подумаем, насколько быстро мы можем генерировать токены. Это одна из важнейших метрик, над которой регулярно работает и наша команда при оптимизации LLM.

Начнем с определения функции, которая объединит все, что мы делали в предыдущих ячейках. Она будет принимать один словарь inputs и генерировать следующий токен:

def generate_token(inputs):
    with torch.no_grad():
        outputs = model(**inputs)

    logits = outputs.logits
    last_logits = logits[0, -1, :]
    next_token_id = last_logits.argmax()
    return next_token_id

Теперь, когда у нас есть вспомогательная функция generate_token, попробуем сгенерировать несколько токенов и посмотрим, сколько времени это займет:

generated_tokens = []  # Список для хранения сгенерированных токенов в виде текста
next_inputs = inputs   # Входные данные, которые будут обновляться на каждом шаге
durations_s = []       # Список для хранения длительности каждой итерации в секундах

# Генерация 20 токенов
for _ in range(20):
    # Замер времени перед генерацией токена
    t0 = time.time()
    
    # Генерация следующего токена
    next_token_id = generate_token(next_inputs)
    
    # Запись времени, затраченного на операцию
    durations_s += [time.time() - t0]
    
    # Обновление входных данных для следующей итерации
    next_inputs = {
        "input_ids": torch.cat(
            [next_inputs["input_ids"], next_token_id.reshape((1, 1))],
            dim=1),  # Конкатенация input_ids с новым token_id
        "attention_mask": torch.cat(
            [next_inputs["attention_mask"], torch.tensor([[1]])],
            dim=1)  # Добавление 1 к attention_mask
    }
    
    # Декодирование token_id в текст и добавление в список
    next_token = tokenizer.decode(next_token_id)
    generated_tokens.append(next_token)

# Вывод общего времени генерации
print(f"{sum(durations_s)} s")
# Вывод списка сгенерированных токенов
print(generated_tokens)
# 0.540771484375 s
# [' молоком', '.', ' ', ' И', ' каждый', ' вечер', ' я', ' пью', ' кофе', ' с', ' молоком', '.', ' ', ' И', ' каждый', ' вечер', ' я', ' пью', ' кофе', ' с']

Результат показывает, что генерация 20 токенов заняла около 0.54 секунд. Чтобы детальнее проанализировать динамику этой скорости от токена к токену, смотрим наглядный график:

plt.plot(durations_s)
plt.show()

Замечаем несколько моментов:

Можно предположить, что время генерации каждого токена должно увеличиваться. Это связано с тем, что мы постоянно добавляем новые токены к входным данным, увеличивая размер обрабатываемой последовательности при каждом следующем шаге. Даже на примере всего 20 токенов видим эту тенденцию, хотя график довольно шумный.
Генерация первого токена обычно занимает немного больше времени по ряду причин, но не будем сейчас в это углубляться. После этого время генерации отдельного токена резко падает и начинает постепенно расти. Примерно с 200 миллисекунд до 300+ к концу последовательности.

Этот график показывает, откуда берется значительная часть затрат при инференсе LLM, когда используем такой прямолинейный подход. И сейчас давайте попробуем оптимизировать этот процесс.

Используем кэш для ускорения вычислений

Для трансформеров одной из наиболее ресурсоемких операций является вычисление внимания (attention). Про механизм attention можно написать даже отдельную статью, поэтому постараюсь объяснить кратко и с небольшим упрощением. Attention использует 3 ключевых компонента:

Q (Query — запрос): «Что нужно сейчас?»;
K (Key — ключ): «Ярлыки» для слов во входном тексте;
V (Value — значение): Фактическая информация о словах.

Когда LLM прямолинейно генерирует длинный текст токен за токеном, для каждого нового слова ей приходится «перечитывать» и «обдумывать» весь предыдущий контекст, то есть заново вычислять эти значения для всей последовательности. Это похоже на то, как если бы вы, продолжая длинное предложение, каждый раз перечитывали его с самого начала.

KV-Caching позволяет избежать таких затрат ресурсов и поделить процесс на 2 фазы:

При генерации первого токена (фаза pre-fill) модель вычисляет Q, K и V для всего входного текста.
Для последующих токенов (фаза decode):
- Вычисляются Q, K и V только для нового токена.
- K и V для предыдущих токенов берутся из кэша.
- Новые K и V добавляются в кэш.

Это позволяет избежать повторных вычислений для уже обработанных токенов, значительно ускоряя процесс генерации, особенно для длинных последовательностей.

Итак, ранее уже определяли функцию generate_token, которая принимала на вход только input_ids и attention_mask. Теперь создадим новую функцию generate_token_with_past, которая делает то же самое, но использует и возвращает past_key_values — значения K и V, уже вычисленные для данного входа модели.

def generate_token_with_past(inputs):
    with torch.no_grad():
        outputs = model(**inputs)

    logits = outputs.logits
    last_logits = logits[0, -1, :]
    next_token_id = last_logits.argmax()
    return next_token_id, outputs.past_key_values

Давайте теперь повторим процесс, который делали ранее для измерения времени генерации 20 токенов. Но на этот раз будем использовать KV-caching и передавать только следующий токен в качестве input_ids:

generated_tokens = []
next_inputs = inputs
durations_cached_s = []
for _ in range(20):
    t0 = time.time()
    # Используем новую функцию, которая возвращает past_key_values
    next_token_id, past_key_values = generate_token_with_past(next_inputs)
    durations_cached_s += [time.time() - t0]
    
    next_inputs = {
        # Теперь input_ids содержит только новый токен
        "input_ids": next_token_id.reshape((1, 1)),
        "attention_mask": torch.cat(
            [next_inputs["attention_mask"], torch.tensor([[1]])],
            dim=1),
        # Используем закэшированные past_key_values
        "past_key_values": past_key_values
    }
    
    next_token = tokenizer.decode(next_token_id)
    generated_tokens.append(next_token)

print(f"{sum(durations_cached_s)} s")
print(generated_tokens)
# 0.3520181179046631 s
# [' молоком', '.', ' ', ' И', ' каждый', ' вечер', ' я', ' пью', ' кофе', ' с', ' молоком', '.', ' ', ' И', ' каждый', ' вечер', ' я', ' пью', ' кофе', ' с']

Теперь давайте построим наглядный график, который покажет время генерации токенов с применением KV-caching и без него:

plt.plot(durations_s)
plt.plot(durations_cached_s)
plt.show()

Оранжевая линия, похожая на хоккейную клюшку, показывает новые результаты с применением KV-caching. Как и ожидалось, после генерации первого токена время на генерацию каждого последующего резко падает и остается на низком уровне до самого конца.

Этот подход уже позволил нам сократить общее время генерации токенов на 35%. При этом с дальнейшим увеличением количества токенов или при использовании изначальных длинных промптов разница будет еще больше. Попробуйте поэкспериментировать сами!

KV-caching оптимизация является первым важным шагом в ускорении инференса LLM. И она лежит в основе того, что делают современные библиотеки. Существуют и другие, более сложные техники оптимизации, которые пытаются эффективно использовать кэш как в памяти, так и в вычислениях на уровне CUDA. В нашей готовой сборке Compressa LLM как раз используются лучшие современные подходы, такие как Page Attention, что позволяет ускорить генерацию для 1 запроса в 2-10 раз.

Это завершает первый урок по оптимизации инференса LLM. В следующей части расскажу про batching технику, которая оптимизирует обработку нескольких запросов одновременно и позволяет еще эффективнее «загрузить» наше железо, увеличивая пропускную способность.

Так когда следующая часть?

Я вложил немало сил в адаптацию первой части, поэтому если хотите продолжения — задавайте в комментариях вопросы, делитесь фидбеком, скидывайте ссылку на эту статью друзьям и коллегам,а также сохраняйте ее в закладки. Так я пойму, что стоит продолжать и выпущу урок про batching. Спасибо, что дочитали до конца!

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8 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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09:10 Michal Novotny

The biggest issue with cryptocurrency is that it is unregulated, wh ich is why different people can come up with different fake stories all the time, and it is unfortunate that platforms like Facebook and others only care about the money they make from them through ads. I saw an ad on Facebook for Cointiger and fell into the scam, losing over $30,000. I reported it to Facebook, but they did nothing until I discovered deftrecoup . c o m from a crypto community; they retrieved approximately 95% of the total amount I lost.