Adobe Fuck you, you snakes. Who charges people for canceling a subscription? @Adobe Do better.

🧵0/3 Here's why we are building the AgenC open source AI agent framework entirely in C and how it will revolutionize edge computing and embedded AI.

👇This thread is worth reading. 🧵1/3 Market Impact & Adoption Potential

Shift in Edge Computing and IoT AI: An open-source C AI agent framework will be a game-changer for edge AI deployment. By enabling sophisticated AI models to run on inexpensive, low-power hardware, it will allow AI processing to be pushed out closer to sensors and end-users. This reduces reliance on cloud computation, lowers latency, and improves privacy (since raw data need not leave the device). Industries are already keen on on-device AI – the Edge AI market is booming, projected to grow to $270+ billion by 2032. A lightweight, efficient framework is exactly what's needed to unlock AI use-cases in this space, from smart home appliances to industrial IoT sensors. For example, imagine intelligent monitoring on a microcontroller that can detect anomalies in machinery in real-time, or tiny medical wearables that run neural networks locally. Today, these are often implemented with highly optimized C/C++ inferencing libraries (like TensorFlow Lite Micro, or vendor-specific libraries) because Python frameworks are too heavy. A dedicated C agent framework, especially since it's open-source, will become the standard for these edge scenarios. Analysts predict TinyML (tiny machine learning on microdevices) will explode in the coming years – device installs are expected to rise to over 11 billion by 2027. The AgenC framework will be poised to ride that wave, enabling AI on billions of devices that were previously too resource-constrained for anything beyond trivial logic.

Open-Source Innovation & Industry Collaboration: By being open-source, the AgenC C-based AI framework would benefit from collective innovation. Many organizations in performance-critical industries (automotive, robotics, aerospace, healthcare devices, etc.) have specialized needs that aren't fully met by one-size-fits-all frameworks. With an open project, they could contribute code for optimizations, new hardware backends, or domain-specific features. This collaborative development can dramatically accelerate the project's evolution. History shows that open-source projects often innovate faster and dominate their domains – Linux, for instance, became the ubiquitous OS through community contributions. In the AI domain, the open-source ethos is already seen as crucial for progress. Most people in the tech community believe that OSS fosters a collaborative environment and accelerates AI innovation. By lowering the barrier for anyone (companies, academics, hobbyists) to inspect and improve the code, the framework will quickly gain powerful features and optimizations that a single team can not develop alone. Open availability will also democratize AI deployment know-how. Small startups or research labs can use the framework to run state-of-the-art agents on cheap hardware, driving further creative applications. Essentially, an open-source C AI framework could become a community-driven standard for embedded AI, much like how OpenCV became a standard library for computer vision in C/C++. This broad participation would not only improve the framework rapidly but also increase trust and adoption in enterprise settings (since many eyes have vetted the code, and no single vendor "owns" it).

Advancing AI in Embedded & Constrained Environments: Perhaps the most exciting potential impact is how the framework could expand the frontiers of where AI can be deployed. Today's cutting-edge AI models mostly live in the cloud or on powerful edge devices (like GPUs in cars or phones). A robust C framework will bring advanced AI to far more constrained settings. Think microcontrollers running reinforcement learning for adaptive control, or tiny drones with onboard neural navigation. We're already seeing hints of this – researchers managed to deploy a deep reinforcement learning policy on a microcontroller-powered nano-drone by writing a custom C inference library, something that general frameworks couldn't handle. With a dedicated framework making this easier, we could see a new class of "smart" embedded agents. This could transform products and industries: smart sensors that don't just report data but analyze it on-site, medical implants that adjust therapy in real-time via AI, or spacecraft and autonomous robots that need ultra-reliable, real-time onboard decision making without bulky runtime environments. By optimizing for minimal memory and maximal efficiency, the C framework would empower developers to squeeze AI into devices and scenarios that were previously off-limits. And because it's open-source, educational institutions and hobbyists could also experiment freely, accelerating the spread of AI into every corner of the physical world.

🧵1/19 DeepSeek lied about it's costs.

DeepSeek R1's training did not actually cost only $6 million, that figure was an incomplete and selective representation of the costs. They also have access to around 50,000 Hopper GPUs.

Here's proof.👇 🧵2/19 Officially, the company reported $5.5M in GPU compute for a single training run, but it left out the massive investments in hardware and development that were required to make that run successful.

🧵0/9 Stanford Intro Reinforcement Learning, from generalization to advanced deep RL. Full videos, assignments, and a final project.

Prereqs:
- Programming knowledge.
- Derivatives & matrix vector operations.
- Probability and Stats.
- Foundations of ML.

Links in comments👇 🧵1/9
Full playlist: youtube.com/playlist?list=…

CS234: web.stanford.edu/class/cs234/in…

👇Projects in 2/9 ... 9/9

🚨 Important Notice for Crypto/AI Investors: 🚨

If you see projects claiming "DeepSeek AI Integration," there are serious red flags to consider.

Technical Reality:

DeepSeek-R1 lacks fundamental features needed for - real applications.

- No function calling capability
- Can't interface with external systems
- Limited multi-turn interactions
- No API integration support

Integration Impossibility:

- Without function calling and API support, meaningful integration into other projects is impossible
- Even GPT-3.5 from 2022 has more practical utility for real applications

Market Context:

Projects claiming DeepSeek integration are likely:

- Misrepresenting technical capabilities
- Lacking technical understanding
- Using buzzwords without substance

Bottom Line:

DeepSeek-R1 is a research model showing interesting results on benchmarks, but it cannot be meaningfully "integrated" into applications due to fundamental technical limitations.

Any project claiming otherwise raises serious concerns about their technical credibility and transparency.

Remember:

Real AI integration requires specific technical capabilities that DeepSeek-R1 explicitly acknowledges it doesn't have! Using R1's reasoning outputs as prompts = potentially viable. Claiming full "DeepSeek AI integration" = still misleading if the project needs actual function calling or API integration.

🧵1/3 Operating Systems: Three Easy Pieces is one of the best ways to learn OS concepts.

The book, along with online resources, homework, projects, and video lectures, is completely free.

I've also dropped some playlists to follow the book.

👇Book and resources in comments. 🧵2/3 free online book, in chapter-by-chapter form: pages.cs.wisc.edu/~remzi/OSTEP/

Errata and Book News: pages.cs.wisc.edu/~remzi/OSTEP/c…

👇Lecture videos, homework, projects.

Pain-text linux socket cheatsheet for the C programming language.

👇Repository with the ASCII in comments. Git: github.com/7etsuo/windows… (you'll want to grab socket-cheatsheet.txt)

Raw: raw.githubusercontent.com/7etsuo/windows…

🧵1/n Jerry Cain from Stanford University explains pointers and structs in C, showing a clever way to access struct fields. This series is one of the best resources online for C programming.

Source: Stanford University

👇 Lectures with handouts, assignments, and videos. 🧵2/n Stanford Engineering Everywhere | CS107 - Programming Paradigms:

👇Video Series. see.stanford.edu/Course/CS107

🧵1/2 MIT's Charles Leiserson covers the progression from source code to compilation, machine code, hardware interpretation, and ultimately, execution.

👇Full MIT Performance Engineering of Software Systems Course 👇 🧵2/2
The course programming language is C.

Performance Engineering of Software Systems is an 18-unit class that provides a hands-on, project-based introduction to building scalable and high-performance software systems. Topics include performance analysis, algorithmic techniques for high performance, instruction-level optimizations, caching optimizations, parallel programming, and building scalable systems.

ocw.mit.edu/courses/6-172-…

🧵1/25 Lectures videos for CS 194: Advanced Operating Systems Structures and Implementation (Spring 2013, UC Berkeley).

Lecture 01 - What is an Operating System? 🧵2/25 Lecture 01 - TDD (Test-Driven Design), BDD (Behavior-Driven Design), and all that.

🧵1/n: Ever wanted to build an operating system?

xv6 is a modern re-implementation of Dennis Ritchie's and Ken Thompson's Unix Version 6 (v6) for RISC-V multiprocessors, using ANSI C. Developed by MIT, it is designed to teach fundamental OS concepts.

👇OS, Books and Course👇 🧵2/n

MIT 6.S081 (Introduction to Operating Systems):

xv6-riscv-book:
-

Operating System:
-

👇Full Video Lecture Playlist👇pdos.csail.mit.edu/6.828/2020/ind…
github.com/mit-pdos/xv6-r…
github.com/mit-pdos/xv6-r…

Dr. Randal E. Bryant breaks down C and assembly:

- Arrays vs pointers - what's the difference?
- How multi-dimensional arrays actually work
- Structs and memory alignment

🧵1/n 👇Course book, assignments, and all video lectures. Videos from the book:

Computer Systems: A Programmer's Perspective" provides a detailed look at how computer systems function, focusing on system-level programming in C and x86 assembly.

🧵2/n All lecture material and Videos below 👇

These are the best books you can buy to learn x86-64 assembly.

🧵1/n God tier collection of papers videos exercises and lectures👇 Cheatsheet I wrote for writing x86 Windows shellcode and the Win32 Shellcoder I developed while studying for my OSED Exploit Development certification.



🧵2/n raw.githubusercontent.com/7etsuo/win32-s…

Unix Network Programming, Volume 1: The Sockets Networking API, 3rd Edition, is god-tier for learning C socket programming. It covers TCP/IP, UDP, SCTP, raw sockets, and IPC under System V and BSD UNIX.

I've added a thread with some goated resources.
🧵0/n 🧵1/n
Here are some free online computer networking courses that complement the book.

1) CS 144 Introduction to Computer Networking - Stanford University, Fall 2013



2) Computer Networking: A Top-Down Approach


3) Computer Communication Networks, Rensselaer Polytechnic Institute - Fall 2001




4) Audio/Video Recordings and Podcasts of Professor Raj Jain's Lectures - Washington University in St. Louis



5) Computer Networks, Tanenbaum, Wetherall Computer Networks 5e - Video Lectures


6) CSEP 561 - PMP Network Systems, Fall 2013 - University of Washington



7) CSEP 561 – Network Systems, Autumn 2008 - University of Washington



8) Computer Networks - IIT Kharagpur


9) Introduction to Data Communications 2013, Steven Gordon - Thammasat University, Thailand


10) Introduction to Complex Networks - RIT


11) Structural Analysis and Visualization of Networks


12) Data Communication - IIT Kharagpur


13) Error Correcting Codes - IISC Bangalore


14) Information Theory and Coding - IIT Bombay


15) Complex Network : Theory and Application - IIT Kharagpur


16) Advanced 3G and 4G Wireless Mobile Communications - IIT Kanpur


17) Broadband Networks: Concepts and Technology - IIT Bombay


18) Coding Theory - IIT Madras


19) Digital Communication - IIT Bombay


20) Digital Voice & Picture Communication - IIT Kharagpur


21) Wireless Ad Hoc and Sensor Networks - IIT Kharagpur


22) Internetworking with TCP/IP by Prof. Dr. Christoph Meinel - HPI


23) CS798: Mathematical Foundations of Computer Networking - University of Waterloo
scs.stanford.edu/10au-cs144/
youtube.com/playlist?list=…
youtube.com/playlist?list=…
ecse.rpi.edu/Homepages/kous…
ecse.rpi.edu/Homepages/kous…
ecse.rpi.edu/Homepages/kous…
cse.wustl.edu/~jain/videos.h…
youtube.com/user/ProfRajJa…
media.pearsoncmg.com/ph/streaming/e…
courses.cs.washington.edu/courses/csep56…
courses.cs.washington.edu/courses/csep56…
courses.cs.washington.edu/courses/csep56…
courses.cs.washington.edu/courses/csep56…
nptel.ac.in/courses/106105…
youtube.com/playlist?list=…
youtube.com/playlist?list=…
leonidzhukov.net/hse/2015/netwo…
nptel.ac.in/courses/106105…
nptel.ac.in/courses/117108…
nptel.ac.in/courses/117101…
nptel.ac.in/courses/106105…
nptel.ac.in/courses/117104…
nptel.ac.in/courses/117101…
nptel.ac.in/courses/117106…
nptel.ac.in/courses/117101…
nptel.ac.in/courses/117105…
nptel.ac.in/courses/106105…
youtube.com/playlist?list=…
youtube.com/playlist?list=…

Prof. John Guttag from MIT outlines standard algorithms in computer science you should be familiar with, including brute force, divide-and-conquer, and advanced methods such as successive approximation and Newton-Raphson.

🧵1/3 🧵2/3
Source:
youtube.com/playlist?list=…

10/10 Book recomendations for C systems programming.

Book 1:

The Linux Programming Interface (TLPI) by Michael Kerrisk is goated for learning Linux systems programming in C. The book has over 200 example programs.

🧵1/5
Key topics:

- Efficient file I/O
- Signals, clocks, and timers
- Process creation and execution
- Secure programming
- POSIX threads for multithreading
- Shared libraries
- Interprocess communication
- Network programming with sockets
🧵2/5

Computer Systems: A Programmer's Perspective" provides a detailed look at how computer systems function, focusing on system-level programming in C and x86 assembly.

This is a large thread covering the book materials, including 17 video lectures that will be added over time. Required Reading:

CMU Systems Programming book:
The C Programming Language by Kernighan and Ritchie: amazon.com/Computer-Syste…
amazon.com/Programming-La…

Professor Jerry Cain from Stanford University covers C programming, emphasizing pointers and structs. He demonstrates an unconventional method to access struct fields. I highly recommend this entire 29-video series for anyone interested in C. Full Series: Stanford University - C programming