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Пятница 24 Марта 20:00 UTC+3 📅
Место: discord.gg/w3voice🗺
Pruvendo: Формальная верификация на примере контракта мульти-подписи (Multisig)
👨🦰 Спикер: Сергей Егоров
Co Founder Pruvendo
План презентации
◽️ Введение в формальную верификацию
◽️ Multisig - история успеха
◽️ Техническое погружение
👥 Ведущие: Ilyar, glazlk
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Pruvendo: Формальная верификация на примере контракта мульти-подписи (Multisig)
Co Founder Pruvendo
План презентации
Чтобы не пропустить его, перейдите по ссылке и нажмите Интересно
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Школьный уровень
* Введение в основы квантовой физики, логики, информатики
* Олимпиады, кружки, STEM-программы
* Проекты вроде Quantum for High Schoolers (IBM, Microsoft Q# programs)
Бакалавриат
* Специализации в физике, информатике, прикладной математике
* Курс по «основам квантовой механики», алгоритмам, линейной алгебре, теории информации
* Некоторые университеты уже предлагают вводные курсы по Quantum Computing
#quantum
Магистратура и аспирантура
* Узкоспециализированные программы: квантовая информация, квантовые технологии, квантовая инженерия
* Междисциплинарные подходы (физика + CS + электроника)
* Совместные программы университетов с индустрией (IBM Q Network, Google Quantum AI Campus Program)
Дополнительное образование
* Онлайн-курсы (edX, Coursera, Qiskit, Braket, QuTiP)
* Bootcamp-программы и стажировки
* Сертификация от крупных вендоров (IBM, Microsoft, Rigetti, D-Wave)
Международные проекты и программы обучения
* IBM Quantum Educators Program – обучение преподавателей и студентов
* Quantum Open Source Foundation (QOSF) – менторские программы
* European Quantum Flagship – поддержка 5000+ исследователей
* NSF Quantum Leap (США) – федеральное финансирование магистерских и PhD программ
* QTOM (Quantum Tech for Optical Materials) – академические консорциумы
Курсы онлайн
* Qiskit Textbook (IBM) Бесплатный интерактивный онлайн-учебник от IBM, охватывает основы квантовых вычислений и работу с библиотекой Qiskit
* Quantum Computing for the Determined (Michael Nielsen) Курс от Майкла Нильсена, акцент на понимание и запоминание основных понятий, глубокий, но доступный
* MIT xPro – Quantum Computing Fundamentals Платный курс от MIT для тех, кто хочет погрузиться в тему на уровне магистратуры, подразумевается знание математики
* QuEra Education Образовательные материалы и практики, связанные с нейтральными атомами и оборудованием компании QuEra
* Q-CTRL Black Opal Платформа для визуального изучения квантовых вычислений, адаптированная под новичков и инженеров
- С помощью курсов и учебников для начинающих oт IBM Quantum (на текущий момент можно использовать до 156 кубитов)
- Кроме IBM Quantum есть и другие платформы которые у каждой различное колличесвое доступных кубитов: Amazon Braket до 256, Microsoft Azure Quantum и qBraid до 1024, Rigetti Quantum Cloud Services 84, Quantinuum 56 и D-Wave Leap 4400
#quantum
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J1: a small Forth CPU Core for FPGAs
This paper describes a 16-bit Forth CPU core, intended for FPGAs. The instruction set closely matches the Forth programming language, simplifying cross-compilation. Because it has higher throughput than comparable CPU cores, it can stream uncompressed video over Ethernet using a simple software loop. The entire system (source Verilog, cross compiler, and TCP/IP networking code) is published under the BSD license. The core is less than 200 lines of Verilog, and operates reliably at 80 MHz in a Xilinx SpartanR -3E FPGA, delivering approximately 100 ANS Forth MIPS.
https://excamera.com/files/j1.pdf
This paper describes a 16-bit Forth CPU core, intended for FPGAs. The instruction set closely matches the Forth programming language, simplifying cross-compilation. Because it has higher throughput than comparable CPU cores, it can stream uncompressed video over Ethernet using a simple software loop. The entire system (source Verilog, cross compiler, and TCP/IP networking code) is published under the BSD license. The core is less than 200 lines of Verilog, and operates reliably at 80 MHz in a Xilinx SpartanR -3E FPGA, delivering approximately 100 ANS Forth MIPS.
https://excamera.com/files/j1.pdf
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Topological Data Analysis over t-SNE or UMAP
🌕 Discuss the advantages of Topological Data Analysis, coupled with self-supervised learning
🌕 Cover different case studies: Internet of Things (IoT), Image analysis, Text analysis
🌕 Highlighting useful open-source libraries to start with TDA
The problem
Have you tried to run a complex supervised machine learning model, only to find unexpected patterns and inconsistencies that make your results unreliable? It's a common problem that can leave even the most experienced data scientists scratching their heads. But fear not! There's a new kid on the block that can help you uncover the hidden structure of your data: topological data analysis (TDA). We'll compare TDA with the popular t-SNE and UMAP packages and show you why TDA is the superhero of data analysis, capable of revealing the unexpected and saving the day.
🔗 datarefiner.com/feed/why-tda
The problem
Have you tried to run a complex supervised machine learning model, only to find unexpected patterns and inconsistencies that make your results unreliable? It's a common problem that can leave even the most experienced data scientists scratching their heads. But fear not! There's a new kid on the block that can help you uncover the hidden structure of your data: topological data analysis (TDA). We'll compare TDA with the popular t-SNE and UMAP packages and show you why TDA is the superhero of data analysis, capable of revealing the unexpected and saving the day.
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We evaluated the March and June 2023 updates of GPT-3.5 and GPT-4 on math, sensitive questions, code generation, and visual reasoning. Results varied significantly: GPT-4's prime number identification dropped from 97.6% to 2.4%, while GPT-3.5 improved. GPT-4 became less responsive to sensitive questions, and both models showed increased code generation errors. These changes emphasize the need for constant LLM quality monitoring.
🔗 arxiv.org/pdf/2307.09009.pdf
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Code Llama - another step towards AI programmers
Meta has introduced Code Llama today, a model that promises to become a new milestone in the world of programming. It has been created to expedite and simplify the development process for programmers and assist beginners.
🌕 An open and free model, based on the Llama 2 platform.
🌕 Three versions: basic, for Python, and with an emphasis on executing instructions.
🌕 Outperformed other well-known LLMs in tests.
Meta hopes that their new tool will spur innovations in the programming field and provide assistance to the entire developer community.
🔗 github.com/facebookresearch/codellama
Meta has introduced Code Llama today, a model that promises to become a new milestone in the world of programming. It has been created to expedite and simplify the development process for programmers and assist beginners.
Meta hopes that their new tool will spur innovations in the programming field and provide assistance to the entire developer community.
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After speaking to more than 100 game developers, we at Game7, wrote a report about the challenges facing Web3 games, then hosted a 👥 forum to tackle some of the industry's most pressing issues.
📁 2022 Game Dev Report — Read Full Report
🔗 Introducing Web3.Unreal
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Released v0.1.0 of the TonConnect SDK for C# and Unity
https://youtu.be/_m6I370t26Y?feature=shared
C# SDK repository: https://github.com/continuation-team/TonSdk.NET/tree/main/TonSDK.Connect
Unity asset repository: https://github.com/continuation-team/unity-ton-connect
Nuget Package: https://www.nuget.org/packages/TonSdk.Connect/
Unity Asset Package: https://github.com/continuation-team/unity-ton-connect/releases/tag/v0.1.1-alpha (now its available in github repository in topic "Releases", thats cause its takes time to approve asset package in Unity Store)
Support https://t.me/+3yl5C5aFeJRhN2My
https://youtu.be/_m6I370t26Y?feature=shared
C# SDK repository: https://github.com/continuation-team/TonSdk.NET/tree/main/TonSDK.Connect
Unity asset repository: https://github.com/continuation-team/unity-ton-connect
Nuget Package: https://www.nuget.org/packages/TonSdk.Connect/
Unity Asset Package: https://github.com/continuation-team/unity-ton-connect/releases/tag/v0.1.1-alpha (now its available in github repository in topic "Releases", thats cause its takes time to approve asset package in Unity Store)
Support https://t.me/+3yl5C5aFeJRhN2My
YouTube
Unity TonConnect 2.0 Asset #ton #unity
Released v0.1.0 of the TonConnect SDK for C# and Unity
C# SDK repository: https://github.com/continuation-team/TonSdk.NET/tree/main/TonSDK.Connect
Unity asset repository: https://github.com/continuation-team/unity-ton-connect
Nuget Package: https://www…
C# SDK repository: https://github.com/continuation-team/TonSdk.NET/tree/main/TonSDK.Connect
Unity asset repository: https://github.com/continuation-team/unity-ton-connect
Nuget Package: https://www…
Cryptography for developers
Distributed Lab invites you to the free course "Cryptography for developers"
We offer:
🌕 To understand what cryptography is and why modern software development requires such knowledge;
🌕 Understand modern cryptographic algorithms;
🌕 Implement them yourself;
🌕 Get advice from mentors on implementation.
🙋 Speakers and mentors
🌕 Pavel Kravchenko, PhD, Co-founder and CEO
🌕 Oleksandr Kurbatov, Research Department Lead and Business analyst
🌕 Bohdan Skriabin, Leading specialist in cryptography and decentralized systems
🌕 Olena Voloshchuk, PhD, Education Program Coordinator
🗓 Start: October 4, 2023; 18:00 GMT+3.
⏲ Frequency: 1 time a week, every Wednesday.
⏩ ⏲ Duration of the course: 2-3 months.
💻 Format: online.
💬 Language: Ukrainian
📌 Requirements for students: basic programming skills, programming language - of your choice.
🎉 Result: exam 🎓 certification 🆔 internship offer for the best students of the course 👥 .
🖋 Registration: https://forms.gle/tnPizw1Cwf5KkhCZ7
Distributed Lab invites you to the free course "Cryptography for developers"
We offer:
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🚩2023 MetaTrust Web3 Security CTF
🔗 ctf.metatrust.io
🖋 Registration will end in 3 hours Sep 14 10:00:00pm GMT+8
📄 Competition will end in 15 hours Sep 15 10:00:00am GMT+8
#CTF
#CTF
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TinyML and Efficient Deep Learning Computing
6.5940 • Fall 2023 • MIT
🔗 efficientml.ai
Large generative models (e.g., large language models, diffusion models) have shown remarkable performance, but they require a massive amount of computational resources. To make them more accessible, it is crucial to improve their efficiency.
This course will introduce efficient AI computing techniques that enable powerful deep learning applications on resource-constrained devices. Topics include model compression, pruning, quantization, neural architecture search, distributed training, data/model parallelism, gradient compression, and on-device fine-tuning. It also introduces application-specific acceleration techniques for large language models, diffusion models, video recognition, and point cloud. This course will also cover topics about quantum machine learning. Students will get hands-on experience deploying large language models (e.g., LLaMA 2) on a laptop.
🖼 The slides and lab assignments from the last semester are available for access here.
🙋 Speakers and mentors
🌕 Instructor: Song Han, Associate Professor, MIT EECS
🌕 TA: Ji Lin, PhD Student, MIT EECS
🌕 TA: Han Cai, PhD Student, MIT EECS
💻 Format: online — lecture recordings are available at YouTube.
⏲ Frequency: Live Streaming — Lectures are live streamed at live.efficientml.ai every Tuesday/Thursday 3:35-5:00pm Eastern Time.
💬 Discussion: Discord
🎓 Homework submission: Canvas
💳 Resources: MIT HAN Lab, HAN Lab Github, TinyML, MCUNet, OFA, SmoothQuant
6.5940 • Fall 2023 • MIT
Large generative models (e.g., large language models, diffusion models) have shown remarkable performance, but they require a massive amount of computational resources. To make them more accessible, it is crucial to improve their efficiency.
This course will introduce efficient AI computing techniques that enable powerful deep learning applications on resource-constrained devices. Topics include model compression, pruning, quantization, neural architecture search, distributed training, data/model parallelism, gradient compression, and on-device fine-tuning. It also introduces application-specific acceleration techniques for large language models, diffusion models, video recognition, and point cloud. This course will also cover topics about quantum machine learning. Students will get hands-on experience deploying large language models (e.g., LLaMA 2) on a laptop.
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TON Blockchain course 🎓
This course will be dedicated to developing on The Open Network (TON) blockchain.
The TON blockchain was launched by the founders of Telegram, Nikolai and Pavel Durov, and later transferred to the open TON community that has been supporting and improving it since then. The Open Network allows processing of millions of transactions per second. The TON ecosystem includes blockchain, payment platform, TON Proxy, file storage, and other decentralized services.
The course was designed to be as close to reality as possible so that participants can work on their own projects on the TON blockchain, or get a job at existing startups and funds.
This course includes
🌕 46 lessons
🌕 9 hours 6minutes of video
🌕 55 quizzes
🔗 stepik.org/course/176754/promo#toc
This course will be dedicated to developing on The Open Network (TON) blockchain.
The TON blockchain was launched by the founders of Telegram, Nikolai and Pavel Durov, and later transferred to the open TON community that has been supporting and improving it since then. The Open Network allows processing of millions of transactions per second. The TON ecosystem includes blockchain, payment platform, TON Proxy, file storage, and other decentralized services.
The course was designed to be as close to reality as possible so that participants can work on their own projects on the TON blockchain, or get a job at existing startups and funds.
This course includes
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Tokenization: Overview and Financial Stability Implications
Tokenization is a new and rapidly growing financial innovation in crypto asset markets, and we discuss potential benefits and financial stability implications. Tokenization refers to the process of constructing digital representations (crypto tokens) for non-crypto assets (reference assets). As we discuss below, tokenizations create interconnections between the digital asset ecosystem and the traditional financial system. At sufficient scale, tokenized assets could transmit volatility from crypto asset markets to the markets for the crypto token's reference assets.
1. Tokenization Design: Tokenization connects reference assets with crypto tokens. Both small ventures and big financial firms are behind these projects.
2. Market Size of Tokenization: By May 2023, the market value of tokenized assets on public blockchains is estimated at $2.15 billion.
3. Examples of Tokenized Assets: These tokens can represent agricultural goods, gold, real estate, and financial securities.
4. Potential Benefits: Tokenization can offer better market access, faster transactions, and improved liquidity.
Tokenization is a significant and rapidly growing innovation in the crypto asset realm. It offers a range of benefits, such as enhanced market access, swift transaction execution, and improved liquidity. However, there are also inherent risks associated with intertwining crypto assets with the traditional financial system. Specifically, these risks include potential volatility transmission from the crypto market to traditional markets, regulatory challenges, and the possibility of systemic vulnerabilities if large-scale tokenized assets were to face abrupt devaluations or liquidity crises. Such complexities could impact overall financial stability.
DOI: https://doi.org/10.17016/FEDS.2023.060
#token #enomics
Tokenization is a new and rapidly growing financial innovation in crypto asset markets, and we discuss potential benefits and financial stability implications. Tokenization refers to the process of constructing digital representations (crypto tokens) for non-crypto assets (reference assets). As we discuss below, tokenizations create interconnections between the digital asset ecosystem and the traditional financial system. At sufficient scale, tokenized assets could transmit volatility from crypto asset markets to the markets for the crypto token's reference assets.
1. Tokenization Design: Tokenization connects reference assets with crypto tokens. Both small ventures and big financial firms are behind these projects.
2. Market Size of Tokenization: By May 2023, the market value of tokenized assets on public blockchains is estimated at $2.15 billion.
3. Examples of Tokenized Assets: These tokens can represent agricultural goods, gold, real estate, and financial securities.
4. Potential Benefits: Tokenization can offer better market access, faster transactions, and improved liquidity.
Tokenization is a significant and rapidly growing innovation in the crypto asset realm. It offers a range of benefits, such as enhanced market access, swift transaction execution, and improved liquidity. However, there are also inherent risks associated with intertwining crypto assets with the traditional financial system. Specifically, these risks include potential volatility transmission from the crypto market to traditional markets, regulatory challenges, and the possibility of systemic vulnerabilities if large-scale tokenized assets were to face abrupt devaluations or liquidity crises. Such complexities could impact overall financial stability.
DOI: https://doi.org/10.17016/FEDS.2023.060
#token #enomics
www.federalreserve.gov
Tokenization: Overview and Financial Stability Implications
The Federal Reserve Board of Governors in Washington DC.
MixBytes Farm открывает набор на курс «Аудитор смарт-контрактов»
Подойдёт всем, кто хочет работать с низкоуровневым кодом и эффективными алгоритмами, разбираться в логике DeFi или освоить новую профессию.
🗓 Старт обучения: 30.10.23
🎓 Прием заявок и проверка тестов: до 27.10.23 (включительно)
🥇 Стоимость: бесплатно
👒 Условие поступления: входное тестирование
⏲ Длительность: 1.5 месяца
Программа:
🌕 Ethereum architecture;
🌕 Solidity low-level patterns;
🌕 Solidity high-level patterns;
🌕 DeFi protocols code review;
🌕 DeFi typical vulnerabilities;
🌕 DeFi hacks;
🌕 CTF (capture the flag);
🌕 Test audit.
*лекции размещены в записи, поэтому ты сможешь проходить теорию в удобное время дня.
После успешного завершения обучения выдается сертификат в виде SBT (soulbound token). Он не только позволит участвовать в закрытых аудит-контестах по поиску уязвимостей в составе команды Stronghold, которая образовалась из выпускников MixBytes Farm, но и станет опорой при поиске работы аудитором смарт-контрактов.
🖋 Зарегистрироваться и пройти входной тест 👈
🙋 Для связи @kudryaviyartemiy
Подойдёт всем, кто хочет работать с низкоуровневым кодом и эффективными алгоритмами, разбираться в логике DeFi или освоить новую профессию.
Программа:
*лекции размещены в записи, поэтому ты сможешь проходить теорию в удобное время дня.
После успешного завершения обучения выдается сертификат в виде SBT (soulbound token). Он не только позволит участвовать в закрытых аудит-контестах по поиску уязвимостей в составе команды Stronghold, которая образовалась из выпускников MixBytes Farm, но и станет опорой при поиске работы аудитором смарт-контрактов.
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Your mission: Improve the open-source bot solution for liquidations from the EVAA team, using existing protocols.
🗓 Important dates:
Development phase: from November 27 to December 14
Robot competition: from December 15 to December 21
Evaluation and awarding of winners: from December 22 to December 30
🎁 There are valuable prizes
🎓 All information is in hackathon documentation of the hackathon
📷 How Liquidations Work on DeFi? B.Protocol explained part 1
@evaabuidl
Development phase: from November 27 to December 14
Robot competition: from December 15 to December 21
Evaluation and awarding of winners: from December 22 to December 30
@evaabuidl
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