Did you know that the .png format was created out of spite? Or that .jpeg just discards like half of the colours in your image because you won't notice?
To celebrate last week's launch, I published a chapter on image compression.
https://t.co/IwwPF9l1LK
Quantum needs an EDA stack. Here's who's building it. 👀
I'm speaking at DAC, The Chips to Systems Conference in July in a focused session "From Bit to Qubit: EDA Meets Quantum" with Duncan Huffman (Classiq), Izhar Medalsy (Quantum Elements), Jonathon Riddell PhD (Kothar Computing), and Chris Mueth (Keysight Technologies).
Thanks to Moshe Zalcberg from Veriest for moderating, and looping me in to help organize this topic for a newer track at DAC.
We hit a lot of this at ISIG recently. This is the next level.
Quick context for anyone wondering why EDA (Electronic Design Automation) is the invisible plumbing of the chip industry. The tools that turn "I want a chip that does X" into something a fab can actually build. Synopsys Inc, Cadence, Siemens - they're the reason modern semiconductors exist.
None of that fully exists for quantum yet. Quantum compilers, layout for qubit arrays, verification, hardware digital twins are being built right now, and a lot of it doesn't look like classical EDA because a qubit isn't a transistor. New methods of simulation, using all sorts of chips (CPU, GPU, TPU and eventually QPU) and AI will unlock scalability and is a huge opportunity in the space.
Monday, July 27, 3:30pm PDT, Seaside RM 7. Come say hi!
this guy vibe coded an infinite pixel art canvas using Claude Code
anyone can hop on and draw whatever they want
416 million individual pixels drawn on it so far which is crazy
In October 2025, @nvidia published a whitepaper about connecting GPUs to quantum processors.
Less than 6 months later, 12 quantum hardware companies had already integrated it!
At GTC 2026, Jensen didn't mention quantum on the main stage.
But here's what shipped from NVIDIA:
cudaq-realtime — a library that lets an FPGA call a function on a GPU and get the result back in 2.92 microseconds.
Why that number matters more than many announcements you've seen this year:
Can LLMs be PROVABLE computers?
Percepta showed that a transformer can BE a computer. Compiled weights, deterministic execution, 30k tokens/sec.
But nobody asked the obvious follow-up: how do you know it computed correctly?
So I built the verification layer. A STARK that proves it 👇
The robotics algorithm library every engineer should know! 📚
PythonRobotics is an open-source collection of Python code and textbook for robotics algorithms, created by Atsushi Sakai.
It has 27.2k stars on GitHub and 7k forks, so it's a no brainer to bookmark it! 🔖
The project covers everything from localization (EKF, particle filters, histogram filters) to SLAM (FastSLAM, ICP matching), path planning (A*, RRT*, Dijkstra, D*, potential fields, state lattice), path tracking (Stanley, LQR, MPC), arm navigation, aerial navigation, and even bipedal planning.
What makes this special? It's designed to be easy to read and understand, with minimal dependencies and practical, widely-used algorithms.
Each algorithm comes with visual animations, mathematical explanations, and working code.
The documentation is essentially a full textbook on robotics algorithms, available free online.
Requirements are simple: Python 3.13+, NumPy, SciPy, Matplotlib, and cvxpy.
That's it.
This a learning resource with 2,201 commits, contributions from 138 developers, and active maintenance. The animations alone (stored in a separate repo) are worth studying.
If you're learning robotics, building autonomous systems, or teaching algorithms, this is the resource. It's MIT licensed, so you can use it freely in research or commercial projects.
Here's the link: https://t.co/7ZK5xP6ljh
P.S. This is what good open-source looks like: educational, practical, well-documented, and community-driven. Bookmark it. 🔖
Thanks for this @Atsushi_twi! 🦾
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"Vinod's style is he asks you to draw a 2030 picture of your company and walk that back from first principles all the way from today.
He expects you to do that flawlessly where he can challenge any assumption or any part of the vision and he asks you very technical questions. He truly backs people that have these very large visions and the ability to defend it alone.
Through this question, he gets to know a lot of things and then he just backs fully. He really gets in your corner if it's the right fit. They've been incredible partners. They've opened so many doors for us."
Pim gives an inside look on what it's like pitching to Vinod and General Intuition's partnership with Khosla Ventures.
@PimDeWitte@vkhosla@khoslaventures
What new mathematics 🧮 will we invent? 🔬
Just as calculus emerged to empower the Industrial Revolution, what new mathematics will arise for the AI revolution? I believe it will be the mathematics that enables us to TRUST. 🤝 💙 🤲
#AI#AISafety#FormalVerification
I like this direction a lot. As we get code writing increasingly automated we’ll want to move to higher level representations of code.
a lot of UX to invent here
Microsoft just killed the GPU mafia! 🤯
They've open-sourced bitnet.cpp, a blazing-fast 1-bit LLM inference framework optimized for CPUs.
This is a major step forward for running large models locally, without expensive GPUs or cloud costs.
Demo app + repo + paper in 🧵 ↓
✨ New in LeRobot ✨
We now officially support LIBERO, one of the largest open benchmark for Vision-Language-Action (VLA) policies with 130+ tasks 🤯
Why this matters:
🧩 Unified benchmark: evaluate any VLA policy under a common setup.
🛠️ Easy integration: just install lerobot, and you’re ready to run LIBERO tasks.
📊 Baseline condition: LIBERO is now the default benchmark for adding new VLAs to LeRobot.
🔗 Dataset: https://t.co/ekUHOP2SKs
📚 Docs: https://t.co/n2WxEQCTYo
This is a huge step toward building the go-to evaluation hub for VLAs.
Let’s make robot learning as open and reproducible as NLP & CV. 💪
👉 Try it out today, share your runs, and let’s push forward the frontier of embodied AI together!