clevernat

Atmospheric Science Student @UWYO || Full Stack Web Developer || Data Scientist.

[Jobs with Aramide @AramideOyekunle]

Remote Job Boards currently serving Remote Jobs!

[Living Tricks @LivingTricks_]

The most difficult in the world.

[Param @ParamSiddh]

Best YouTube Channels To Learn AI in 2026 (No BS)

1. Fundamentals – 3Blue1Brown
2. Deep Learning – Andrej Karpathy
3. AI Research – Yannic Kilcher
4. Practical AI – AssemblyAI
5. LLMs – AI Explained
6. ML Theory – StatQuest
7. Papers Simplified – Two Minute Papers
8. GenAI – Matthew Berman
9. AI Agents – Nicholas Renotte
10. Applied ML – Krish Naik
11. PyTorch – Aladdin Persson
12. Math for ML – Serrano Academy
13. Industry Insights – Lex Fridman
14. Real-world AI – DeepLearningAI

[MJ👑 @iam__Jezreel]

This just gave me goosebumps all over!! Wow!
Too much wisdom🔥

Dr. Myles👏🏽🔥

[Julian Goldie SEO @JulianGoldieSEO]

𝗡𝗼𝘁𝗲𝗯𝗼𝗼𝗸 𝗟𝗠 𝗻𝗼𝘄 𝘁𝘂𝗿𝗻𝘀 𝘆𝗼𝘂𝗿 𝗱𝗼𝗰𝘂𝗺𝗲𝗻𝘁𝘀 𝗶𝗻𝘁𝗼 𝗳𝘂𝗹𝗹 𝗰𝗶𝗻𝗲𝗺𝗮𝘁𝗶𝗰 𝗔𝗜 𝘃𝗶𝗱𝗲𝗼𝘀 𝘄𝗶𝘁𝗵 𝗼𝗻𝗲 𝗰𝗹𝗶𝗰𝗸.

Most people still use it like it's a note-taking app from 2024.

It got 8 big updates in 7 months and almost nobody knows.

It holds 700,000 words at once now.

You give it a question and it goes and finds the sources itself.

From one set of sources it makes a podcast, mind map, and report in one click.

The new videos are real animations, not flat slideshows.

But here is the gap. It does not know you, so it sounds generic.

That is where you wire it into an agent that remembers your voice.

Now every piece sounds like you, not a robot.

Want the setup? DM me.

[Rohit @heyrohitai]

🚨Anthropic just showed a 24-minute workshop on how to actually do prompts for Claude.

Taught by the people who built it.

Free. No registration. No paywall.

I've seen $300 courses that don't cover what they teach in the first 8 minutes.

Watch it and bookmark it now!

[Charly Wargnier @DataChaz]

this guy literally put a full AI engineering curriculum on GitHub and made it 100% FREE 🤯

435 lessons.
20 phases.
320 hours.

The rule that makes this curriculum completely different:

Every algorithm gets implemented from raw math before a single framework gets imported.

You build the backprop.
You build the tokenizer.
You build the attention mechanism.

By the time you use PyTorch, it’s just a shortcut for something you already know how to code from scratch.

It spans four languages:

→ Python for ML pipelines
→ TypeScript for agent tooling
→ Rust for performance-critical components
→ Julia for numerical computation

And the best part?

Every single lesson ships something you can actually use.

You walk away with fully deployable prompts, SKILL. md files, agents, and MCP servers.

The curriculum scales from foundational math all the way up to autonomous agent swarms and production infrastructure.

Free, open-source, and MIT licensed.

repo in 🧵↓

[Julian Goldie SEO @JulianGoldieSEO]

Claude Code is now FREE.

Claude Code is one of the most powerful AI coding tools available — and you can now run it completely free using an open source CLI and a free model called Owl Alpha on OpenRouter.

Connect it to a persistent memory system through Obsidian and your agents remember everything across every session, every conversation, every project. 

You don't have to manage API keys, switch between terminals, or copy and paste between apps anymore — it all lives in one place.

[Elon Musk @elonmusk]

Try Composer 2.5

[Julian Goldie SEO @JulianGoldieSEO]

OpenClaw = the employee.

Hermes = the memory.

Paperclip = the company.

That’s the simplest way to understand the craziest open-source AI agent stack right now.

Most people are still using 1 chatbot.

This setup runs like an AI business.

[Julian Goldie SEO @JulianGoldieSEO]

🔥 INSANE: Free Kimi K2.6 might be the best open-source AI coder right now.

It runs on NVIDIA’s own servers with a free API endpoint.

No subscription.

No credit card.

No complicated setup.

And because it’s OpenAI-compatible, you can plug it into tools like Claude Code, Roo, and Cline fast.

This is one AI coding model I’d actually test ASAP.

[FHILY👑 @Oluwaphilemon1]

How I built an Anime.js-style site with Claude 👇

• Ask Claude to plan a minimal interactive website with smooth motion

• Install Anime.js → "npm i animejs"

• Use Claude to generate timelines, staggered text, and hover animations

• Add smooth SVG, scroll, and cursor interactions with Anime.js

• Keep UI minimal so motion becomes the focus

• Use easing + timing to make animations feel fluid and premium

Save this 🚀

[Charly Wargnier @DataChaz]

🚨 A Google engineer just automated 80% of his job, and he monitors his new AI workforce with a $2 USB-C chip.

He copied a Chinese student who wired the thumb-sized chip to Claude Code in 15 minutes.

A blue LED simply blinks when agents work and goes dark when waiting.

Now, the engineer just decides whether to let it work.

Out of the box, it's packing:
> 27 agents
> 64 skills
> 1,282 security tests

You simply stop chatting and start managing.

Fun story: Commenters laughed that a toaster has more compute.

He ignored everyone and added one line at the bottom: the LED knows before you do.

I also added the ace article by @noisyb0y1 that explains this in way more detail

[Andrew Brown @andrewbrown]

I finished creating the Claude Code Essentials, Codex Essentials and Gemini CLI Essentials certification courses. In less than 20 hours you can master them all.

Those who keep all their path opens succeed in tech.

[Victor M @victormustar]

GLM-5.1 > Claude Code (Opus 4.6)?

I'm tripping or CC has become very bad but built a Three.js racing game to eval and it's extremely impressive. Thoughts:

- One-shot car physics with real drift mechanics (this is hard)

- My fav part: Awesome at self iterating (with no vision!) created 20+ Bun.WebView debugging tools to drive the car programmatically and read game state. Proved a winding bug with vector math without ever seeing the screen

- 531-line racing AI in a single write: 4 personalities, curvature map, racing lines, tactical drifting. Built telemetry tools to compare player vs AI speed curves and data-tuned parameters

- All assets from scratch: 3D models, procedural textures, sky shader, engine sounds, spatial AI audio!

- Can do hard math: proved road normals pointed DOWN via vector cross products, computed track curvature normalized by arc length to tune AI cornering speed

You are going to hear about this model a lot in the next months - open source let's go 🚀🚀

[Jahir Sheikh @jahirsheikh8]

🧠 AI/ML Skills - Difficulty Breakdown 🤖🔥

• 🧾 Python basics -> 🟢 Easy
• 📦 NumPy/Pandas -> 🟢 Easy
• 🔁 Data cleaning -> 🟢 Easy
• 🧠 Basic models -> 🟡 Easy–Medium

• ⚙️ Regression/classification -> 🟡 Easy–Medium
• 🔄 Feature engineering -> 🟡 Easy–Medium
• 🧩 Model evaluation -> 🟡 Easy–Medium
• 🎯 Sklearn usage -> 🟡 Easy–Medium

• ⚔️ Neural networks -> 🟠 Medium
• 🔍 Backpropagation -> 🟠 Medium
• 🧠 Hyperparameter tuning -> 🟠 Medium
• 📡 Model deployment -> 🟠 Medium

• 🧬 Transformers -> 🔴 Hard
• ⚖️ Distributed training -> 🔴 Hard
• 🔒 ML system design -> 🔴 Hard

• 🧠 Debugging models -> 🟣 Very Hard
• ⚙️ Building production AI -> ☠️ Extreme

accuracy ≠ understanding 😭

Feel free to add 👇

[Piyush @piyush784066]

Best YouTube Channels To Learn in 2026

1. Cybersecurity – John Hammond
2. Artificial Intelligence – Andrej Karpathy
3. AI Research Breakdown – Yannic Kilcher
4. Web Development – The Net Ninja
5. Python Programming – Corey Schafer
6. DevOps – TechWorld with Nana
7. Cloud Computing – AWS re:Invent
8. Data Analytics – Luke Barousse
9. System Design – Gaurav Sen
10. Databases – Hussein Nasser
11. Low-Level Programming – The Cherno
12. Linux – Learn Linux TV
13. Networking – David Bombal
14. Math for ML – 3Blue1Brown

[NASA @NASA]

Coming up next, our @NASAArtemis astronauts and @NASAAdmin answer questions from social media. Stay tuned: https://t.co/do2p0Gvxdu

[smrati tiwari @smratitiwa86867]

Anthropic just introduced the Claude Architect Certification — and it’s not easy.

60 questions.
5 competency areas.
One sitting. No breaks. No external help.

Here’s a simple roadmap to prepare:

Week 1 — Foundations
• Claude API
• Model Context Protocol (MCP)
• Claude Code
• Claude 101

Week 2 — Build
• Claude Code
• Agent SDK
• Anthropic API
• MCP

Week 3 — Understand the Exam
• Exam scenarios
• Competency areas
• Required skills

Week 4 — Practice Systems
• Multi-tool agent with escalation
• Team workflow setup
• Data extraction pipeline
• Multi-agent research system

Week 5 — Test Yourself
Practice exam → Target 850+

Week 6 — Final Attempt
One attempt. Be ready.

A few notes:

• Early access is limited to partners
• Prep time varies (2–10 weeks depending on skill level)

If you’re eligible, register here:
https://t.co/YK3O6KCxwm

This isn’t just a certification.

It’s a signal of how seriously you build with AI.

[Teejay Communication Hub @jayteeofnaija]

Listen for full gist