josip budimcic

Tweeting is like sending out cool telegrams to your friends once a week. - Tom Hanks

[Physics In History @PhysInHistory]

Matter → Molecule → Atom → Nucleus → Proton/Neutron → Quarks.

📷 by Beth Sherwin

[4nzn @paoloanzn]

say hello to free-code

claude code source code fully recompiled, telemetry stripped, security guardrails prompts stripped, all working experimental features enabled

including ultraplan mode - a new async agentic planning mode where claude starts a multi-agent research session in the browser lasting between 10 and 30 minutes

since i know there are gonna be DMCA strikes on this i've uploaded it on the blockchain on IPFS

[Miss Sentient @0xsachi]

Some of the best open source repos to try this weekend:

1. Paperclip : https://t.co/3L6aDGr48u

2. Mirofish : https://t.co/RsbxfrLRbr

3. Hermes: https://t.co/i4N7XmVqhO

4. Openclaw: https://t.co/lZ2li1B8uw

[Bilawal Sidhu @bilawalsidhu]

You can try it out here: https://t.co/JOkNBGduKD

[Ben Burtenshaw @ben_burtenshaw]

You can finetune AI models with Unsloth + Hugging Face, and right now it’s free!

We're giving away GPU credits on HF Jobs + Unsloth.

Train a 1.2B model like @liquidai LFM2.5-1.2B with one command. Ship it to your phone, laptop, or API.

No infra. No setup. Just prompt your coding agent and go.

[Jordan Golson @jlgolson]

I spent a day inside the Transamerica Pyramid with Jony Ive, Marc Newson, and the interior of Ferrari's first electric car: The Luce. It isn't just a new Ferrari. It's Ive's argument that the entire car industry copied the wrong part of the iPhone.

[Lior Alexander @LiorOnAI]

You can now run 70B LLMs on a 4GB GPU.

AirLLM just made massive models usable on low-memory hardware.

𝗪𝗵𝗮𝘁 𝗷𝘂𝘀𝘁 𝗵𝗮𝗽𝗽𝗲𝗻𝗲𝗱
AirLLM released memory-optimized inference for large language models.

It runs 70B models on 4GB VRAM.
It can even run 405B Llama 3.1 on 8GB VRAM.

𝗛𝗼𝘄 𝗶𝘁 𝘄𝗼𝗿𝗸𝘀
AirLLM loads models one layer at a time.

Instead of loading everything:
→ Load a layer
→ Run computation
→ Free memory
→ Load the next layer

This keeps GPU memory usage extremely low.

𝗞𝗲𝘆 𝗱𝗲𝘁𝗮𝗶𝗹𝘀
• No quantization required by default
• Optional 4-bit or 8-bit weight compression
• Same API as Hugging Face Transformers
• Supports CPU and GPU inference
• Works on Linux and macOS Apple Silicon

𝗪𝗵𝗮𝘁 𝘆𝗼𝘂 𝗰𝗮𝗻 𝗱𝗼
• Run Llama, Qwen, Mistral, Mixtral locally
• Test large models without cloud GPUs
• Prototype agents on cheap hardware

[TonyVT SkarredGhost @SkarredGhost]

This is an ambitious project: an opensource mid-range AR/VR headset with in-house eye/mouth tracking, inside-out tracking, and controller/glove-based inside-out full body tracking. More on it on Reddit: https://t.co/1Tno7symyq

#VirtualReality #VR

[Dhairya @dkare1009]

Stop wasting hours trying to learn AI. 📘📚

I have already done it for you.

With one list. Zero confusion. And no fluff

📹 Videos:

1. LLM Introduction: https://t.co/Qja4lkPWlY

2. LLMs from Scratch: https://t.co/DAtGeO5if3

3. Agentic AI Overview (Stanford): https://t.co/APcq2oulIY

4. Building and Evaluating Agents: https://t.co/UeCQBskKUS

5. Building Effective Agents: https://t.co/B2tpQHaVoz

6. Building Agents with MCP: https://t.co/CwVBIVUjd0

7. Building an Agent from Scratch: https://t.co/u2jhiZy6UV

8. Philo Agents: https://t.co/lFMIus5CpQ

🗂️ Repos

1. GenAI Agents: https://t.co/yoTno6RBAb

2. Microsoft's AI Agents for Beginners: https://t.co/EGGYhcMq7b

3. Prompt Engineering Guide: https://t.co/fSCoEaFtNf

4. Hands-On Large Language Models: https://t.co/TvpkfJN2sR

5. AI Agents for Beginners: https://t.co/EGGYhcMq7b

6. GenAI Agentshttps://lnkd.in/dEt72MEy

7. Made with ML: https://t.co/cCWWXKh2wW

8. Hands-On AI Engineering:https://t.co/fiLwjmXR8B

9. Awesome Generative AI Guide: https://t.co/MEhtfRlhiu

10. Designing Machine Learning Systems: https://t.co/l21VO4rRBK

11. Machine Learning for Beginners from Microsoft: https://t.co/d3EPcDJWmz

12. LLM Course: https://t.co/xXxETt90eS

🗺️ Guides

1. Google's Agent Whitepaper: https://t.co/rVDu4EyPB5

2. Google's Agent Companion: https://t.co/IWjvSpSE2q

3. Building Effective Agents by Anthropic: https://t.co/0wK5pe5DD6.

4. Claude Code Best Agentic Coding practices: https://t.co/fu7GHgvnAi

5. OpenAI's Practical Guide to Building Agents: https://t.co/sXpo72PxpI

📚Books:

1. Understanding Deep Learning: https://t.co/YRV9Kz78Gy

2. Building an LLM from Scratch: https://t.co/naslph9aCF

3. The LLM Engineering Handbook: https://t.co/BwmUJ6OgHe

4. AI Agents: The Definitive Guide - Nicole Koenigstein: https://t.co/ZIDeOOamnz

5. Building Applications with AI Agents - Michael Albada: https://t.co/409SxePxhA

6. AI Agents with MCP - Kyle Stratis: https://t.co/3k9lFG3ByM

7. AI Engineering: https://t.co/tHfgc3wNKQ

📜 Papers

1. ReAct: https://t.co/8yV9k9RjOK

2. Generative Agents: https://t.co/PpaAbCvWmj.

3. Toolformer: https://t.co/mSfjjT6urU

4. Chain-of-Thought Prompting: https://t.co/uGktDnFBOb.

🧑🏫 Courses:

1. HuggingFace's Agent Course: https://t.co/4MLjHKcWSI

2. MCP with Anthropic: https://t.co/EnUWTrvaK4

3. Building Vector Databases with Pinecone: https://t.co/AmQzrCVweX

4. Vector Databases from Embeddings to Apps: https://t.co/HZbr4UBlw2

5. Agent Memory: https://t.co/TxvrpeBMFj

Repost for your network ♻️

[josip budimcic @budoliki]

@carlvellotti Antigravity

[Carl Vellotti 🥞 @carlvellotti]

Google's Cursor competitor: FREE!
My course for you to learn: FREE!
My holiday gift to you 🎁

[⚠️ Comment "Antigravity" & I'll send you the link]

Antigravity is Google's answer to Cursor.
It's an AI tool that works directly on your device.
Not just for developers!
For ANYONE who works with text.

It's 100% free right now.
Access to Gemini 3 Pro.
Even Claude Opus 4.5 (!)
Use Nano Banana Pro right in the chat.
No subscription. No trial. No credit card.

This won't last forever.

I've been teaching Cursor to PMs for months.
But Cursor costs $20/month.
Antigravity removes that barrier completely.

So I rebuilt the entire course for AG.

It's an Antigravity course taught IN Antigravity.
So everything you do is directly applicable!
The AI IN the tool is your teacher.

What you'll learn:
→ Write PRDs with AI assistance
→ Analyze CSV data and survey results
→ Create strategy documents
→ Build reusable templates and workflows

But here's what most people don't realize:

This isn't just for PM work.

The real reason I wanted to get this out today...

On-device AI assistants are useful for LIFE:
🔹 Want to reorganize your files?
🔹 Rename hundreds of photos?
🔹 Clean up your Downloads folder?
🔹 Convert documents between formats?
🔹 Troubleshoot why something isn't working?

Just open the files and ask.
Talk to it like a person.

I spend all day in these tools now.
I've never been so productive.
Or had so much fun.

AI in a browser is like wearing a straightjacket.
This is a terrible day for a launch.
But I genuinely want to free you!

You've been meaning to learn this stuff.
You've got the time.
The course is free.
The tool is free.
No excuses!

This is my gift to you.
Happy Holidays 🌲

👉 Repost + comment "Antigravity" & I'll send you the link

[Shubham Saboo @Saboo_Shubham_]

My biggest highlight of 2025 at Google

Kaggle 5-day AI Agent Intensive Course

> 1.5 million AI Agent Builders
> 2 million views on AI agent whitepapers
> 3.3 million views on the course notebooks
> 11,000 capstone agent project submission

Now it's 100% free for all.

[Python Developer @PythonDvz]

Most Data Scientists structure their projects wrong.
Use this clean, production-ready layout👇

1️⃣ config/ – config files
Separate params from code (local.yaml, prod.yaml)

2️⃣ data/ – full data lifecycle
raw → preprocessed → features → predictions

3️⃣ entrypoint/ – main scripts
https://t.co/msVSpFUsGI (pipeline)
https://t.co/ClDVrYTRBT (batch/real-time)

4️⃣ notebooks/ – exploration only
EDA, analysis — never production logic

5️⃣ src/ – core ML code
feature engineering, training, inference (modular + testable)

6️⃣ tests/ – automated checks
prevent silent failures

7️⃣ docker + env files – reproducibility
same setup on any machine/CI

8️⃣ pinned dependencies – stability
exact versions → consistent results

Picture Credits : Timur Bikmukhametov

[Your Tech Girl @yourtechgirl24]

Secret AI tools that 99% never use.

1. https://t.co/aKyMpR70iL – 3D photos
2. https://t.co/jQRAJFmIZX – AI models
3. https://t.co/rAsT50z3FZ – Video editor
4. https://t.co/wOgiO0MDHe – Vector graphics
5. https://t.co/eyL2KFvwB9 – Product photos
6. https://t.co/qiBvFeja1T – Voice generator
7. https://t.co/0ODzRTp4Ky – Computer memory
8. https://t.co/d8QSqMU8gR – Code testing
9. https://t.co/yDyHSiABhZ – 3D assets
10. https://t.co/tCQypE9cNJ – Music creator
11. https://t.co/5nCTdQraSd – Video maker
12. https://t.co/23ISuoWTBZ – 3D design
13. https://t.co/r7L2qHdCz5 – Image creator
14. https://t.co/AhQFgzdkfP – Music generator

[AI at Meta @AIatMeta]

Introducing SAM 3D, the newest addition to the SAM collection, bringing common sense 3D understanding of everyday images. SAM 3D includes two models:

🛋️ SAM 3D Objects for object and scene reconstruction

🧑‍🤝‍🧑 SAM 3D Body for human pose and shape estimation

Both models achieve state-of-the-art performance transforming static 2D images into vivid, accurate reconstructions.

🔗 Learn more: https://t.co/yXcvts8Ogc

[NZ ☄️ @CodeByNZ]

This is all you need to build a million dollar company in 2025.

[josip budimcic @budoliki]

@Ai_Vaidehi ML

[josip budimcic @budoliki]

@samruddhi_mokal BUILD