Peter Kastelic

42

[Peter Kastelic @5kast]

Joe Rogan Experience #2506 - Michelle Thaller https://t.co/B4LyyGAAY7 via @YouTube

[Peter Kastelic @5kast]

Bob

[Figure @Figure_robot]

Day 2 is Live: Watch humanoid robots Bob, Frank, and Gary running 24/7. This is fully autonomous running Helix-02 https://t.co/dsacH4HOzJ

[vŽIVO.si @vzivo_si]

Botrstvo v športu https://t.co/dwChMeGXV8

[Peter Kastelic @5kast]

https://t.co/qNnwlteRc7

[Peter Kastelic @5kast]

Gledam zanimivo porazdelitev kmetij in vikendic na prodaj v SLO

https://t.co/YkYi3hGAf2

[Peter Kastelic @5kast]

Hahah

[Bo Wang @BoWang87]

We are so over! 😀

[Peter Kastelic @5kast]

Test znova https://t.co/D4i65LAneT

[SpaceX @SpaceX]

Watch Dragon and the Crew-12 astronauts dock with the @Space_Station → https://t.co/RURjWg7R8P https://t.co/1GNBVWhHT7

[Dustin @r0ck3t23]

Elon Musk just dated the death of human language and explained exactly why it has to die.

Musk: “Our brain spends a lot of effort compressing a complex concept into words.”

Language isn’t communication. It’s failed compression. You have a complete thought. You crush it into words. The listener gets fragments and attempts reconstruction. Everything important dies in translation.

We don’t communicate. We approximate and hope it’s close enough.

Musk: “You would be able to communicate very quickly and with far more precision.”

Neuralink doesn’t improve communication. It replaces it. No compression. No loss. Direct cognitive transfer at the speed thoughts occur. Not describing the painting. Transmitting the experience itself.

Musk: “You wouldn’t need to talk.”

Five to ten years until brain interfaces make speech optional. Talking persists for sentiment. For information? Speech becomes primitive compared to direct neural transmission.

Lifetime of memory in one second. Complete schematics transferred instantly. Not summaries. The entire thought structure whole and uncompressed. Not better communication. Actual telepathy at physical information limits.

Musk: “Ideally, we are a symbiosis with artificial intelligence.”

Humans who don’t merge with AI at high bandwidth don’t just fall behind. They become incomprehensible to the intelligence that matters.

We’re already cyborgs with pathetic interfaces. Phones extend cognition through typing at words per minute when bandwidth should be terabytes per second.

Neuralink doesn’t optimize that. It detonates the constraint.

Five to ten years. Not fiction. Deployment window.

From language as default to neural link as standard. From compressing thoughts into inadequate words to transmitting uncompressed cognition. From humans using AI to humans indistinguishable from AI at communication speeds.

The species that survived by evolving language is making it extinct with technology matching how fast we actually think.

The ones who don’t transition won’t just be slow. They’ll operate at such reduced bandwidth they become effectively deaf to everything happening at neural speed around them.

Language served 50,000 years. It has less than a decade before it becomes smoke signals. Functional but hopelessly inadequate for anything that matters.

[Aakash Gupta @aakashgupta]

The scariest number here: 3.61% of CPUs in one large-scale study were found to cause silent data corruptions. Not “a few bad chips.” Nearly 4 out of every 100 processors doing math wrong, silently, with no error log.

Google coined the term “mercurial cores” in 2021 after their production teams kept blaming software for data corruption. They’d debug for weeks, find nothing wrong with the code, swap the machine, problem gone. The actual cause: manufacturing defects at sub-7nm that pass every factory test, then degrade unpredictably months or years after deployment.

Facebook confirmed the same thing independently. Hundreds of affected CPUs across hundreds of thousands of machines. The defect doesn’t crash your system. It just gives you 5 instead of 6 when you multiply 2x3, under specific microarchitectural conditions, with zero indication anything went wrong.

Now think about what this means for AI training. A single corrupted GPU or CPU in a distributed training cluster doesn’t just produce one bad output. It feeds corrupted gradients into a synchronization step that gets averaged across every accelerator in the cluster. One bad chip can silently poison an entire training run. NVIDIA published a whitepaper on exactly this problem. Loss spikes during LLM training that nobody could explain traced back to silent hardware corruption.

The part that keeps infrastructure engineers up at night: traditional defenses don’t work. ECC memory can’t catch this because the corruption happens during computation, not storage. Checksums like CRC heavily use vector operations, which are themselves one of the most vulnerable instruction types. The tools designed to detect corruption are running on the same flawed silicon.

Google’s current detection method? Roughly half human-driven, half automated. And of the machines humans flag as suspicious, only about 50% are actually confirmed mercurial on deeper investigation. We’re debugging trillion-parameter models on hardware where we can’t reliably tell which chips are lying to us.

Moore’s Law gave us more transistors. It also gave us transistors we can’t fully verify.

[Everyday Astronaut @Erdayastronaut]

@SpaceflightNow @FAANews Holy crap... I don't think any rocket should be overflying that much populated area until it's flown a few hundred times without a RUD on ascent. I would not trust Starship for a while. All it takes is one Flight 6 or 7 incident to have heavy debris falling over populated areas.

[Peter Kastelic @5kast]

https://t.co/dVsiWPvLQZ

[Peter Kastelic @5kast]

Uf to bo napeto

[Ryan Caton @dpoddolphinpro]

It's a big day for SLS, Artemis, and the future of humanity. For the first time since 1972, a rocket which will take humans to the moon is headed to the launch pad → https://t.co/l8IHImfLIB

Big props to @thenasaman for not only running cameras & commentating on the livestream, but also for recording a BREAKINGspace video as well!

[Peter Kastelic @5kast]

How to delete 15 years of your company’s work in one easy move:

S1: Pay Google for email for 15 years.

S2: Accidentally get moved to “Google Workspace Essentials” (the plan without… email).

Step 3: Watch 15 years of emails disappear forever.

No warnings.
All gone @Google

[Peter Kastelic @5kast]

Lol

[NYPrepper @nyprepper1]

⚠️⚠️⚠️⚠️⚠️⚠️⚠️⚠️⚠️PAPA JOHN'S PIZZA NEAR THE PENTAGON SPIKING 1,250% TONIGHT!! JUST FOR COMPARISON THE NIGHT WE ATTACKED VENEZUELA IT SPIKED 700%!! SOMETHING BIG IS ABOUT TO HAPPEN!!

[Peter Kastelic @5kast]

Kako se reče temu folku z letnimi gumami zdaj na cesti?

[Peter Kastelic @5kast]

@Zoom down, @Vimeo down, @Restreamio down…..

Cloud down…..

[Night Sky Now @NightSkyNow]

If you collapse an underwater bubble with a sound wave, light is produced, and nobody knows why.

[Peter Kastelic @5kast]

Tega nisem vedel

[Bart @Feniks_projects]

"nobody knows why" ... is ... not entirely correct. We don't know the fine deep-deep-layerd details, but have some pretty good idea's whats happening here. Allow me:

When you collapse an underwater bubble with a sound wave and it produces light, you’re talking about something called sonoluminescence - often nicknamed “a star in a jar.”
🌐https://t.co/zwIdmw29dC

The basic idea is this: you take a tiny gas bubble in water and drive it with powerful sound waves, usually ultrasound. The sound field makes the bubble expand and then collapse very violently. In the final instant of that collapse, the bubble emits a tiny flash of light that lasts only picoseconds to nanoseconds. We can observe and measure these flashes, and even make them occur regularly - one flash for each cycle of the sound wave in the single-bubble version of the experiment.
🌐https://t.co/WIdXmGTQrW

What makes this so intriguing is that the exact mechanism behind the light is still not completely agreed upon. We do know a few things reasonably well. As the bubble collapses, the gas inside is compressed extremely rapidly. That compression can drive the temperature and pressure inside the bubble to enormous values - calculations and models often suggest tens of thousands of kelvin, which is in the same ballpark as the surface of the Sun. Under such conditions, several different light-producing processes become possible. The gas might become hot and ionized enough to behave like a glowing plasma, emitting something like thermal radiation. Charges that are suddenly accelerated could emit light through processes similar to bremsstrahlung. Atoms and molecules could be excited in the chaos and then emit photons as they relax back down.

Experiments reveal a few striking features. The light pulses are incredibly short and can be astonishingly regular. The spectrum - the distribution of colors - sometimes looks roughly like that of a very hot “blackbody” radiator, but not perfectly so. Changing the gas inside the bubble or the liquid around it affects the brightness and the spectrum in ways that suggest both high-temperature plasma effects and specific chemical or molecular processes are involved.

So it’s not quite right to say “nobody knows why”; it’s closer to: we have several plausible explanations, but none of them nails every single detail in a way that convinces everyone. Researchers still argue about the precise temperature and pressure at the very moment of collapse, about whether the emission is primarily thermal glow from a hot plasma, discrete emission from excited molecules and radicals, or a mixture with shock-wave and non-equilibrium effects layered in. There’s also ongoing debate about how much purely classical fluid dynamics can explain and where you need to bring in more subtle or quantum-level considerations.

In other words, we understand the broad strokes quite well: a violently collapsing bubble compresses gas to extreme conditions, and that extreme state emits light. The mystery lives in the finer details - exactly what that extreme state looks like and precisely how it turns its energy into those tiny, beautiful flashes.