Seeker;Giver

logic + emotions

[Seeker;Giver @chessman011]

@StatiSense In the current list India is the second last. Why is there a discrepancy?

[Donald B Kipkorir @DonaldBKipkorir]

For Moral Imperatives, SPAIN must beat ARGENTINA in tonight’s World Cup Finals …

Argentina is the only country in the whole world that foreigners came, killed all the natives, then imported Blacks to work on their plantations then killed them all … Argentina has no Indian natives nor blacks …

#FIFAWorldCup

[Piyush Itankar @_streetdogg]

It's ready!!

You are welcome to try it!! -- https://t.co/AfmKt5DUK6

It's been three years (almost) that we are creating content focused on Embedded Systems (software for the most part). The Content Delivery platform always came in the way. Sometimes the features were available but the resources where expensive, sometimes the provider changed the prices on us, some other time we wanted a feature and had no control.

So, in the good old engineering spirit we decided to code one from scratch - on our own!

Happy to say, we are piloting it with the free content and is open to all for access on - https://t.co/AfmKt5DUK6

I should mention, because this is being tested and improved in real-time, things may not be super well behaved (just yet). If you discover a bug, leave a comment here or write to us on [email protected]

So what does this platform have:
-- The courses are in the sidebar.
-- The tree is structured like -- course -- section -- chapters
-- Chapters have Lectures, Quizzes and Challenges.
-- The Lectures have reading and interactive material. Our recorded lectures will appear there.
-- The Quiz tab is to help you revise/recall important points from the lecture.
-- The challenge details activities and experiments that can be run to reinforce the concept.
-- The coding area is the playground. You can write the code there and execute it on the server.
-- At the bottom, we have the notes -- you can take notes in markdown format, save it and also download a copy for later reference.
-- There terminal on the bottom right will show the output and also allows entering linux commands :)

We have been meditating on such a platform for years now and it's finally taking shape.

None of this would have happened without the ~10k of you trusting us!!

Thank you for all the trust and love.

----

If you were looking for structured content on learning Embedded Systems, check this out - https://t.co/Sln2dB7cyb

the new platform is a couple of months away from release and when it is out there, we'll (like all times) welcome the Library members to the exclusive content.

[Math Cafe @Riazi_Cafe_en]

Harvard's lecture notes on "Probability, Statistics, and Linear Algebra"

https://t.co/WPMmOuB0gi

[SzymonOzog @SzymonOzog_]

Saturday reading: "What happens when you run a CUDA kernel" - very cool blogpost on the details about the CPU<->GPU communications required for lauching a kernel

[Dan Kornas @DanKornas]

Machine Learning Pipeline

An in-depth machine learning tutorial introducing readers to a whole machine learning pipeline from scratch by @Harvard

[Ramchand Kumaresan @Mechramc]

I wrote 934 pages on how to build every layer of a large language model from scratch. Many of these concepts were new to me a year back.

Tokenizers, attention, KV cache, MoE, RLHF, quantization, serving. 35 projects. Every chapter has a section where you break the thing you just built.

Everything I use to build TamilLM is in this book. If you have been following the journey and want to understand what is actually happening under the hood, start here. It also ties in to my previous papers as well in the various chapters.

35 copies sold so far.

https://t.co/9hANb7VaLc

Let's go. 🙏

[Ilir Aliu @IlirAliu_]

Peter Corke won the highest honor in robotics.
His entire robotics curriculum is free online.
📌 Has been for 10 years. 👇️

You visit his website and find 200+ free lessons, an open-source toolbox used by researchers worldwide, and a full textbook that runs in Google Colab. Zero install.

He broke his knee before semester started in 2015. Recorded his lectures at home. Put them on YouTube. 70,000 views in one semester.

He never stopped.
→ 200+ free robotics and robotic vision lessons
→ Full Python textbook... runs in Google Colab
→ Open-source Robotics Toolbox for research and teaching
→ Taken by millions of students globally

From kinematics to deep learning. From arm robots to autonomous systems.

Free. No login.
[https://t.co/6qFLkCFKLo]

——-

Weekly robotics and AI insights.
Subscribe free: https://t.co/9Nm01QUcw3

[Brian Roemmele @BrianRoemmele]

The Well Just Dropped: 15 Terabytes of Pure Physics Gold Is Now Open Source

The scientific AI world just got a massive upgrade.Polymathic AI, in collaboration with the Flatiron Institute and researchers from Princeton, Cambridge, NYU, Berkeley, Los Alamos, and more, has released The Well: a staggering 15TB collection of high-fidelity physics simulations.

This isn’t toy data.

These are real, expensive-to-run simulations across 16 different physical domains, including turbulent fluid dynamics, supernova explosions, magneto-hydrodynamic cosmic flows, acoustic scattering, and active biological matter.

Until now, reproducing this level of data required weeks on national supercomputers and grant money most teams will never see. The Well changes everything. It’s purpose-built for training PDE surrogate models the AI systems that can replace slow, costly physics solvers with a single fast neural network forward pass.

Everything is fully open source, easy to load with PyTorch, and ready to drop straight into your training pipeline. Researchers and builders can now train on world-class physics data without the insane compute barriers that used to stand in the way.

This is more than just another dataset drop. It’s a serious accelerator for scientific machine learning.The future of physics-informed AI just got a whole lot more accessible.Get it here:
https://t.co/mIW0xA6RAs

[MIT CSAIL @MIT_CSAIL]

A free guide that answers key reinforcement learning questions: https://t.co/CY91nDnOkb

v/@arjunkocher & @sheriyuo

[Cyber City Circuits @MakeAugusta]

Short answer: It only takes commitment, a little bit of money, and a lot of free time.

Long answer: Over the next six months, read this book. All the way through. Get a physical copy on eBay if you need to. Take notes. Actually learn what it is trying to teach you. It can be hard. This is the best book to learn from. Edition doesn't matter. This is fundamental to everything that comes next. Spend the following three months reading the book over and over again.

Consume the book. Really take in what it means to be an electron in a current flow. Imagine it. Spend entire weekends with your pen, a notebook, and this book, and do that over and over again for nine months of your life. Trust the process. Six months of learning. Three months reviewing. It is not a race. I can give you a one-on-one test in six months if you want. Take the time to do it correctly. Learn it.

Now, nine months in, come back to this post and I'll give you further instructions. Don't really worry about anything else other than putting the knowledge held in the book, inside your head. Try as hard as you can. Commit to it and then do it. You will learn more than a four-year degree. You can come back to this post with questions, but the book will serve you well. Lets use #TeachYourselfElectricity to come back to this thread of posts. Just be easier to keep track of. See you in nine months.

https://t.co/YuBH0B7kJj

[Cyber City Circuits @MakeAugusta]

I'm pretty sure the average person could go from zero knowledge to a graduate EE-level of knowledge very quickly. If you want to get into board design, this book is the place to start learning the fundamentals. Learn this book. This time next year, you can be totally up to speed.

[André Rieu @superrieu]

Die ersten 30 Minuten 👇 Vorlesungsgesprächs zu Einsteins Relativitätstheorie sind didaktisch wirklich brillant und man kann sie nur jedem empfehlen, der die Allgemeine Relativitätstheorie eher intuitiv verstehen will. 1/10

[Praveen Kumar Verma @Alacritic_Super]

Want to learn Robot Learning for free?

🤗 Hugging Face Robotics Course is one of the best modern courses covering robotics, AI, and machine learning from classical robotics to foundation models and embodied AI. It's hands-on and built around LeRobot, Hugging Face's open-source robotics framework.

What you will learn:
🤖 Classical Robotics
🧠 Robot Learning
📦 LeRobot Framework
🎮 Reinforcement Learning (RL)
🎭 Imitation Learning
🖥️ Vision-Language-Action (VLA) Models
📷 Robot Perception
🦾 Manipulation
🚶 Locomotion
📊 Robotics Datasets
🌍 Embodied AI
⚡ Foundation Models for Robotics
🔬 Real Robot Deployment

Robotics Course: https://t.co/FtNbY2pQTX

[Youssef Hosni @YoussefHosni951]

Most engineers don't fail at CUDA because it's hard.

They fail because they read the right books in the wrong order.

CUDA has a reputation for breaking people. The usual advice, "just read PMPP", drops a beginner straight into the deepest book in the field and then wonders why they quit by chapter 4.

The book isn't the problem. The sequence is. After going through the whole shelf, here's the order that actually compounds: each book earns the next one:

1️⃣ 𝐂𝐔𝐃𝐀 𝐛𝐲 𝐄𝐱𝐚𝐦𝐩𝐥𝐞 (Sanders & Kandrot): Don't learn kernels yet. Learn to feel the GPU. This builds the intuition that every later book assumes you already have.

2️⃣ 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠 𝐌𝐚𝐬𝐬𝐢𝐯𝐞𝐥𝐲 𝐏𝐚𝐫𝐚𝐥𝐥𝐞𝐥 𝐏𝐫𝐨𝐜𝐞𝐬𝐬𝐨𝐫𝐬 (Hwu, Kirk, El Hajj): The foundation. This is where the mental model gets built: threads, blocks, parallel patterns. Now it lands, because Book 1 gave you something to attach it to.

3️⃣ 𝐏𝐫𝐨𝐟𝐞𝐬𝐬𝐢𝐨𝐧𝐚𝐥 𝐂𝐔𝐃𝐀 𝐂 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠 (Cheng, Grossman, McKercher): The architecture book. Memory hierarchy, streams, and the why behind every performance cliff you're about to hit.

4️⃣ 𝐆𝐏𝐔 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠 𝐰𝐢𝐭𝐡 𝐂++ 𝐚𝐧𝐝 𝐂𝐔𝐃𝐀 (Motta): The modern workflow. Nsight profiling, the full dev loop, packaging kernels into libraries you can call from Python.

5️⃣ 𝐓𝐡𝐞 𝐂𝐔𝐃𝐀 𝐇𝐚𝐧𝐝𝐛𝐨𝐨𝐤 (Wilt): The reference you grow into. You don't read this cover to cover. You reach for it when "works on my machine" stops being enough.

6️⃣ 𝐂𝐔𝐃𝐀 𝐟𝐨𝐫 𝐃𝐞𝐞𝐩 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 (Arledge): The payoff. Where kernels stop being an exercise and start accelerating the models you actually ship.

The pattern across all six: intuition before theory, theory before architecture, architecture before application.

Most people quit at the wrong book. Almost nobody quits in the wrong order, because nobody told them that order was the thing.

[Palden Bhutia @paldenbhutiaa]

https://t.co/zXGy2Vyuax

[Seeker;Giver @chessman011]

@shaanchopra @DanQayyum @HelleLyngSvends @TanushreePande You can tell us here. Who was Gauri Lankesh?

[Manish @drmanishtn]

@vineetJindal19 @HelleLyngSvends Dear @HelleLyngSvends , do not get intimidated by these sycophantic people. They are habitual liars and you’ve hit the right spot that’s why the right wingist are coming after you. Do not get intimidated by these bastards.They are good for nothing who want to earn by engaging you

[Abhijit Shingate @abshingate]

Let me ask you this because you are advocate. What is the job of a journalist? And because someone is voted 3 times, should that person feel more accountable towards people or arrogant? As a advocate, whats your purpose of interrogations in the court? Shouldn't you just take everything on face value?

[Seeker;Giver @chessman011]

@Amara__Don Bhai tu hi karle join as you have already "left studies".