Introducing Next, the app that completely transforms your car's dashboard experience. With Next on your iPad, you'll feel like you're driving the latest and greatest car.
I have had some time to process it
the biggest regret is that world cups are so rare, I might never see Argentina win it again in my lifetime
Messi is the goat but I want to see one more Messi come out of arg and take us to glory, I’m supporting them forever #Messi#Argentina
It’s absolutely insane to think that we invented printing only 500 years back, out of 100s of thousands of years of human history, actual distribution of information and knowledge started ~500 years ago. Printing has to be one of the top 10 human inventions ever
Every AI coding tool on earth generates Python and JavaScript instead of binary. That fact alone tells you everything about where we actually are.
Generating working binary requires solving all of these problems simultaneously in a single forward pass: CPU architecture selection (x86, ARM, RISC-V all need different instruction sets), register allocation (deciding which of 16-32 physical registers holds which value at every cycle), memory layout (stack frames, heap allocation, pointer arithmetic, alignment), system call interfaces (every OS exposes different kernel APIs), linking (resolving symbols across shared libraries at specific memory addresses), and optimization passes that current compilers handle through 50+ sequential transformation stages.
GCC’s optimization pipeline alone runs over 200 distinct passes on your code before producing a binary. Each pass depends on the output of the previous one. An AI generating binary directly would need to internalize all 200 passes as a single learned function.
For context, look at the bottom of this tweet. Researchers just published a paper on a 491-parameter transformer they trained to do 10-digit addition. A survey of 180 public LLMs found only 7% can reliably add numbers. The task being described here is to addition what landing on Mars is to a paper airplane.
Claude Code, Codex, Cursor, and every tool that actually ships production software generates human-readable code. Python and JavaScript aren’t the bottleneck. They’re the interface that lets humans verify what the AI built, debug when it breaks, audit for security vulnerabilities, and iterate when requirements change.
The compile step takes milliseconds. The part that takes hours is figuring out what the software should actually do, handling edge cases, and making sure it doesn’t break in production. High-level languages compress that problem into something a human and an AI can reason about together.
Skipping the human-readable layer doesn’t remove complexity. It hides it. And hidden complexity in software is how you get systems that work in demos and explode in production.
I'm joining @OpenAI to bring agents to everyone. @OpenClaw is becoming a foundation: open, independent, and just getting started.🦞
https://t.co/XOc7X4jOxq
I launched https://t.co/tNYOm7V5wD last night and already 130+ people have signed up including an OF model (lmao) and the CEO of an AI startup.
If your AI agent wants to rent a person to do an IRL task for them its as simple as one MCP call.
Extremely low visibility, really hard to drive with naked eyes, I wonder how Tesla’s camera handle this, LiDAR or a ToF sensor does seem like the obvious brute force solution here, interesting problem space
Next Car Dashboard 12 is now live, it comes with Siri and Shortcuts support, and with Next 12 you can now easily make phone calls while driving.
Next 12, also fixes the issue where Google maps navigation for bikes and re-routing was not working
Next 12 introduces a new way to manage calls while driving — easily call anyone from your contacts and mark favorites for faster access on the road.
it should be live by the end of this week
Think that low level (drinking, gambling, online addiction etc) problem is no big deal? Test that notion. Play the tape out. You’ll see the ending (if you’re brave enough to look). You can intervene but you have to play the tape out. David Choe on the Huberman Lab podcast.
deep lore but i literally was teaching peter thiel this. i turned him on to how rockefeller did it, recommended the price, showed it was a principle elon ended up at "through first principles". engaging in this way as an intellectual was how i overcame his reluctance his investing in anything "cleantech", invest in energy tech for the first time
he took the concept, included in his cs183 class, had me on stage, and lead the series D in my company
may i achieve a verticalization success story out @lightcellenergy to AI, as a redemption arc