@Machine_Enginee

Connecting with people to expand my ML network.

 Toronto, Ontario
Joined November 2021
  • Tweets4.4K
  • Following736
  • Followers26
Thats a pinned post!
a16z crypto
@a16zcrypto
31 Dec 2025
17 things we're excited about for crypto in 2026... 1. Better, more clever onramps/ offramps for stablecoins 2. Thinking about tokenization of real world assets, and stablecoins, in a more crypto-native way 3. Stablecoins unlock the bank ledger upgrade cycle — and new payment scenarios 4. The internet becomes the bank 5. Wealth management for all 6. From know your customer (KYC) to ‘know your agent’ (KYA) 7. We’ll use AI for substantive research tasks 8. The invisible tax on the open web 9. Privacy will be the most important moat in crypto 10. The (near) future of messaging isn’t just quantum-resistant. It’s decentralized 11. ‘Secrets-as-a-service’ 12. From ‘code is law’ to ‘spec is law’ 13. Prediction markets go bigger, broader, and smarter 14. The rise of staked media 15. Crypto offers a new primitive for use beyond blockchains 16. Trading as a way station, not the last stop, for crypto businesses 17. Unleashing the full potential of blockchains… when legal architecture finally matches technical architecture
1
1,109
Sonny PhD retweeted
Hayato O
@o8_vm
Sep 23
なんとですね！私が作ったRust 製 unix-like OS こと octox がですが、サンフランシスコ大学のコンピュータサイエンスの授業で使用されているようです。AI時代ますます Rust と OSとUnix 的なものが重要になってますね。Rust と Unix-likeなOSを同時にまなべるoctox をどうぞ cs631-s26.cs.usfca.edu/guide…
Hayato O
@o8_vm
20 Sep 2024
全部Rustで作られたUnix-like OSがここにあります！！Rustで思う存分に開発できますよ！CかRust で揉めることはないかと思います！Rust でOS開発したい方、移植、ドライバー開発、ユーザーランド開発歓迎です！！ぜひ起こしください！！！ github.com/o8vm/octox

GitHub - o8vm/octox: Unix-like OS in Rust inspired by xv6-riscv

Unix-like OS in Rust inspired by xv6-riscv. Contribute to o8vm/octox development by creating an account on GitHub.

github.com
10
329
18
1,790
181,569
Sonny PhD retweeted
candy
@shenxiankk
Sep 21
一篇能投顶刊的论文，20分钟就能捅出来？这事儿放现在真不是吹牛逼。 选题、扒文献、洗数据、因果识别、稳健性检验、画表、写正文，一整套流程干下来俩仨月就没了，还得防着referee挑刺、防着期刊反AI，博士生直接被卷到抑郁边缘。 现在斯坦福REAP联手copaper把这套东西给开源了， 23000+个专业Agent技能，横扫经济、政治、社会、心理等8大社科领域，顶尖研究员的方法论全被打包成能直接甩的Skill，从选题到投稿一气呵成全自动。 github.com/brycewang-stanfor…

GitHub - brycewang-stanford/Auto-Empirical-Research-Skills: 🔬 A curated collection of 23,000+...

🔬 A curated collection of 23,000+ agent skills for empirical research across 8 social science disciplines. | 精选 23,000+ AI Agent 技能库，覆盖8大社会科学学科的实证研究。CoPaper.AI 20分钟完成一篇可复现的规范实证论文，并支持用户上传 Skills。--...

github.com
38
248
10
1,151
85,114
Sonny PhD retweeted
GitHubDaily
@GitHub_Daily
Sep 22
耶鲁一位计算机博士生，把自己发论文用的画图脚本全开源了，项目叫 figures4papers。 支持柱状、雷达、折线趋势、三维球体示意、概念等类型图，8 个论文项目各一个文件夹，脚本、数据、成图放在一起，照着改数据就能出自己的图。 他还把这套画图风格整理成了一个 Skill，接进 Cursor、Claude Code 或 Codex，让 Agent 按这套规范帮我们写画图脚本。 GitHub：github.com/ChenLiu-1996/figu… 规范写得挺细，去掉上边和右边的坐标轴线，柱子加黑边，配色固定一套语义，蓝色给自己的方法，绿色系给改进项，红色系给对比基线，默认 300 DPI 导出。 不装也能用，把仓库在 Agent 里打开，提示词里让它照 SKILL.md 和设计原则文件来写就行，README 里给了现成的提示词模板。 前几天分享的 vivid-figures-skill 是让 AI 选图画图，这个更像拿一位常年投顶会的作者的审美当模板，写论文要出图的可以两个都看看。
218
832
16
5,117
299,985
🎓 I’m teaching CIS 6270: Discrete Generative Models at @Penn this fall! It’s a math-first course on modern generative modeling across continuous and discrete spaces, with full derivations, code, worked examples, and current research. Follow along with us this semester! 👇 cis6270.github.io/ We start this semester with core probability, ODEs/SDEs, the continuity and Fokker-Planck equations, and then derive flow matching and score matching through DDPM, DDIM, probability-flow ODEs, along with both single- and multi-objective guidance. 🌊 Then, we rebuild the story in discrete space. 🎲 That means CTMCs and master equations, time reversal, MDLM, D3PM, block diffusion, discrete scores and guidance, followed by discrete flow matching with jump processes and simplex-based flows. 🦘 We also go well beyond the standard material: multi-objective guidance, rectified flows, and a full lecture on modern flow maps, including consistency + shortcut models, categorical/discrete flow maps, Meta Flow Maps, expanding state spaces, and strong stochastic flow maps. 🗺️ We finish by connecting generation to optimal transport, stochastic optimal control, and path-space methods, working from Wasserstein geometry and Sinkhorn through Girsanov, Doob transforms, Schrödinger bridges, and modern continuous and discrete bridge-matching methods. 🌉 Throughout the semester, on the website, we’ll be releasing the lecture slides (you can see how deliberate they are!), project descriptions, exams + full solutions, and accompanying code on HuggingFace! 🤗 Our goal is that someone can start from the foundations and follow the math all the way to the newest papers. 📚 By the end, you should have the tools to turn your own research ideas into papers for the main conferences. Just promise me we won’t be the reason ICLR goes from 60k submissions to 70k! 😅 I’m incredibly grateful to my TAs (also my PhD students), for helping me build and teach all of this: @SophieVincoff @TongChen321 @RosieZ0512! 🥰 We hope you enjoy the material! 🥳

CIS 6270: Discrete Generative Models

A math-first course at Penn on continuous and discrete generative models, with derivations, code, worked examples, and current research. Fall 2026 with Pranam Chatterjee.

cis6270.github.io
15
103
5
703
34,306
Sonny PhD retweeted
Ayaan 🐧
@twtayaan
Sep 21
This might be the only free Terraform course you’ll ever need. It takes you from the basics to state, modules, testing and real production workflows. courses.devopsdirective.com/…
11
53
2
364
13,778
Sonny PhD retweeted
Kirk Borne
@KirkDBorne
Sep 14
Introduction to Graph Theory: arxiv.org/abs/2308.04512 (454-page PDF) — edges, vertices, trees, networks, paths, and graphs (and theorems!) ————— #Mathematics #NetworkScience
30
2
121
18,078
Learn Rust by working through 100 short exercises!
GitHub Projects Community
@GithubProjects
Sep 19
Learn Rust by working through 100 short exercises, one at a time. - Start with no Rust knowledge - Build up to writing your own programs - Solutions available for every exercise Explore it here: osp.fyi/100-exercises-to-lea…
32
You don't need to rely entirely on hosted AI APIs anymore thanks to some solid open source options. In this course, @andrewbrown shows how to run open-source LLMs both locally and in the cloud. You’ll learn about model setup, inference options, hardware tradeoffs, and scaling strategies along the way. freecodecamp.org/news/how-to…
6
118
3
856
42,069
Sonny PhD retweeted
Ilir Aliu
@IlirAliu_
Sep 19
A full MIT course on visual autonomous navigation. If you work on robotics, drones, or self-driving systems, this one is worth bookmarking‼️ MIT’s Visual Navigation for Autonomous Vehicles course covers the full perception-to-control stack, not just isolated algorithms. What it focuses on: • 2D and 3D vision for navigation • Visual and visual-inertial odometry for state estimation • Place recognition and SLAM for localization and mapping • Trajectory optimization for motion planning • Learning-based perception in geometric settings All material is available publicly, including slides and notes. 📍vnav.mit.edu/ If you know other solid resources on vision-based autonomy, feel free to share them. —- Weekly robotics and AI insights. Subscribe free: 22astronauts.com
11
313
8
2,111
73,994
Sonny PhD retweeted
ENcenatur@encenatur
Sep 19
Self-organizing memristive networks as physical learning systems nature.com/articles/s42254-0…

Self-organizing memristive networks as physical learning systems

Nature Reviews Physics - Self-organizing memristive networks combine adaptive nanoscale transport, network connectivity and physical plasticity to enable learning directly in hardware. Their...

nature.com
11
79
4,426
JEPA-Anything: Learning Predictive Models across Different Worlds TL;DR: Factorizes JEPA targets into orthogonal predictive subspaces, predicts each factor with a dedicated predictor, and recombines them into a full latent state. The same principle works across vision, biology, control, molecules, physics, and weather. arxiv.org/abs/2609.20800

JEPA-Anything: Learning Predictive Models across Different Worlds

World modeling enables intelligence to anticipate consequences, guide interventions, and learn from interaction. Yet predictive models remain domain-specific: can a common learning principle...

arxiv.org
1
6
95
4,137
Sonny PhD retweeted
Kirk Borne
@KirkDBorne
Sep 18
“Multimodal Deep Learning” arxiv.org/abs/2301.04856 [Download 272-page PDF eBook] —————— #DataScience #AI #ML #MachineLearning #NLProc #ComputerVision #NeuralNetworks
87
424
17,943
Sonny PhD retweeted
NetScience@net_science
Sep 18
Topological Uncertainty and Higher-Order Interactions in Spatial Networks arxiv.org/abs/2609.18439

Topological Uncertainty and Higher-Order Interactions in Spatial Networks

Environmental systems are characterized by complex spatial interactions that cannot be fully described through pairwise relationships or local uncertainty measures. We propose a unified framework...

arxiv.org
7
1
30
1,659
Sonny PhD retweeted
Ebokify
@ebokify
Sep 17
🦀 RUST Firmware Engineering The Complete Developer's Guide to Build Safe, Bare-Metal Systems for Microcontrollers, IoT Devices, and Real-Time Applications With Full Source Code By Erik Volkmann 📖 Get the book: amzn.to/4xzHeT5 ⚡ Stop fighting undefined behavior. Start building firmware designed to be safe, reliable, and fast. A single dangling pointer, buffer overflow, or data race can turn embedded development into weeks of debugging—or worse, a field failure. Rust brings memory and concurrency safety to firmware development while preserving the performance and hardware control embedded systems require. This hands-on guide provides a roadmap from embedded C/C++ development to confident embedded Rust engineering. 🚀 What You’ll Learn: • 🦀 Master "no_std" Rust and bare-metal programming • 🧠 Understand registers, memory-mapped I/O, and "embedded-hal" • 🔌 Work with UART, SPI, I²C, ADC, PWM, and DMA • ⚙️ Build firmware for STM32F4, nRF52840, RP2040, and ESP32-C3 • 🔄 Use Embassy async/await without an RTOS, heap, or busy-waiting • ⏱️ Build hard real-time systems with RTIC • 🛡️ Design robust error handling and panic strategies • 📡 Implement on-device logging with "defmt" • 🧪 Test embedded code without physical hardware using mocks and "embedded-hal-mock" • 🔬 Explore model checking with Kani • 🔋 Optimize firmware for battery-powered IoT devices • 📲 Build and deploy DFU/OTA firmware update systems 🏗️ From Bare Metal to Production: Across 18 chapters and three full capstone projects, you'll move beyond simple microcontroller experiments and learn how to engineer firmware for real-world constraints. The book combines Rust's safety guarantees with direct hardware control, real-time performance, testing, debugging, power optimization, and production deployment. 🎯 Perfect for embedded C/C++ developers, firmware engineers, IoT developers, microcontroller programmers, and engineers ready to bring Rust into serious embedded systems. 🔥 Write safer firmware. Control the hardware. Ship with confidence. #Rust #RustLang #EmbeddedRust #Firmware #EmbeddedSystems #BareMetal #Microcontrollers #IoT #RTOS #RealTimeSystems #SystemsProgramming #TechBooks
2
113
1
724
18,634
Model-based Bootstrap for Offline Policy Evaluation in Tabular Reinforcement Learning ift.tt/W7Zaxe6

Model-based Bootstrap for Offline Policy Evaluation in Tabular...

Offline policy evaluation (OPE) is crucial in high-stakes reinforcement learning applications, where new policies must be assessed reliably before deployment. In such settings, point estimates...

arxiv.org
2
7
919
Null importance: Disentangling relevance for interpretable machine learning ift.tt/as5C9VN

Null importance: Disentangling relevance for interpretable machine learning

Feature importance is central to interpretable machine learning, but the term "importance" encompasses several fundamentally different notions of relevance. We develop a unified perspective based...

arxiv.org
1
1
15
1,162
Robust Multi-Task Learning for Principal Component Analysis ift.tt/FxzRUTY

Robust Multi-Task Learning for Principal Component Analysis

Principal component analysis (PCA) is a fundamental tool for learning low-dimensional structure from high-dimensional data. When data are collected from multiple sources, the underlying task...

arxiv.org
4
20
1,275
The current AI panic is an artifact of our current poor understanding of AI, but better days are coming: arxiv.org/abs/2510.12269

Tensor Logic: The Language of AI

Progress in AI is hindered by the lack of a programming language with all the requisite features. Libraries like PyTorch and TensorFlow provide automatic differentiation and efficient GPU...

arxiv.org
11
44
2
349
19,264
Sonny PhD retweeted
Math Cafe
@Riazi_Cafe_en
Sep 18
Steven Skiena's "Analysis of Algorithms" Lecture Videos: youtube.com/playlist?list=PL… Course Website: www3.cs.stonybrook.edu/~skie…
2
49
408
11,671
Sonny PhD retweeted
PrismML
@PrismML
Sep 17
Today, we’re announcing Ternary Bonsai 2 27B. Based on Qwen3.8 27B, Bonsai 2 27B is 9x smaller than its full-precision counterpart while retaining 98.2% of its aggregate benchmark performance. Two months after the first Bonsai 27B release, the biggest change is quality. The footprint remains 5.9 GB, but the gap to full precision has narrowed materially, with particularly strong gains in agentic coding, multimodal reasoning, and long-horizon tool use. Ternary Bonsai 2 27B is available today under Apache 2.0.
642
1,567
774
15,534
5,395,182
Load more