Forwarded from Buidl Radio
The new episode about Ethereum MPC Ceremony is out! Ignacio Hagopian created go-kzg-ceremony-client for MPC Ceremony for generating Trusted Setup for KZG Commitment. We discuss Protodanksharding, Security aspects of MPC Ceremony. Listen to our new episode and participate in Ceremony until 13 Mar.
https://www.youtube.com/watch?v=r78cYgaT9I0
Audio version:
https://anchor.fm/buidlradio/episodes/Ethereum-KZG-Ceremony-with-Ignacio-Hagopian-go-kzg-ceremony-client--Buidl-Radio-5-e1vl8r3
https://www.youtube.com/watch?v=r78cYgaT9I0
Audio version:
https://anchor.fm/buidlradio/episodes/Ethereum-KZG-Ceremony-with-Ignacio-Hagopian-go-kzg-ceremony-client--Buidl-Radio-5-e1vl8r3
YouTube
Ethereum KZG Ceremony with Ignacio Hagopian (go-kzg-ceremony-client) | Buidl Radio #5
In the new episode, we discuss MPC Ceremony for generating Trusted Setup for Kate Polinomial Commitment in Ethereum. Our guest is Ignacio Hagopian, go-kzg-ceremony-client developer. If want to know more about MCP Ceremony, Protodanksharding just checkout…
Forwarded from Ever Incubator
DeVote — the first voting application providing true anonymity and verifiability of results
Project presentation, application demo and AMA session
⚪️ What product does DeVote offer?
⚪️ What is under the hood?
⚪️ What are the roadmap and fundraising plans?
📅 10 March |17:00 UTC
🗺 Place: discord.gg/w3voice
👥 Speakers: Eugene Morozov, Alexander Zvezdin
👨🦰 Host: Ben Bateman
To make sure you don't miss it, go to the link and click Interesting🔔
Project presentation, application demo and AMA session
To make sure you don't miss it, go to the link and click Interesting
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Sumanth: Statistics is essential for Data Science and the best way you can learn is by Visualizing concepts
"Seeing Theory" will teach you everything from Statistics to Probability and much more with interactive visuals!
Check this out:
- seeing-theory.brown.edu
- github.com/seeingtheory/Seeing-Theory
#SeeingTheory
"Seeing Theory" will teach you everything from Statistics to Probability and much more with interactive visuals!
Check this out:
- seeing-theory.brown.edu
- github.com/seeingtheory/Seeing-Theory
#SeeingTheory
MOOC: Zero Knowledge Proofs
🔗 zk-learning.org
📼 youtube.com/watch?v=uchjTIlPzFo&list=PLS01nW3Rtgor_yJmQsGBZAg5XM4TSGpPs
#ZeroKnowledge #Course
#ZeroKnowledge #Course
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This ZKP / Web3 Hackathon
🔗 zk-hacking.org
The hackathon is designed to have 4 tracks:
- zk-Applications track: any developer can build and showcase innovative applications using ZKP in diverse domains.
- zkBridge track: building a secure, universal foundation for multichain interoperability using ZKP through decentralized community collaboration.
- zk-Circuits track: optimizing and improving commonly used circuits through decentralized community collaboration.
- zk-Benchmarks track: building a unified framework for benchmarking ZKPs, with standardized interfaces for integrating different components, ZKP frameworks, and workloads, enabling anyone to contribute to advance the understanding and improvement in ZKP performance in practice.
TIMELINE
🗓 March 1 — Begin ZKP Hackathon; Participant Sign up Open
🗓 March 12 — Team/Track Sign Up
🗓 April 4 — Mid-hackathon Progress Check-in
🗓 April 21 — Submission 1st round Deadline
🗓 April 25 — Announcement of final demo participants
🗓 May 2 — Submission demos, Winner announcement & Closing event
#Hackathon #ZeroKnowledge
The hackathon is designed to have 4 tracks:
- zk-Applications track: any developer can build and showcase innovative applications using ZKP in diverse domains.
- zkBridge track: building a secure, universal foundation for multichain interoperability using ZKP through decentralized community collaboration.
- zk-Circuits track: optimizing and improving commonly used circuits through decentralized community collaboration.
- zk-Benchmarks track: building a unified framework for benchmarking ZKPs, with standardized interfaces for integrating different components, ZKP frameworks, and workloads, enabling anyone to contribute to advance the understanding and improvement in ZKP performance in practice.
TIMELINE
#Hackathon #ZeroKnowledge
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Forwarded from Ever Incubator
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
Чтобы не пропустить его, перейдите по ссылке и нажмите Интересно🔔
Место: discord.gg/w3voice
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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