S2 MacD 🇨🇦 💙💛

MBA, MSc (Biochem) - Problem solver. Fun dad. 🇨🇦

X = panem et circenses.

We should work harder, as a society, on education & knowledge translation ✌️

[Milk Road AI @MilkRoadAI]

This is WILD!

MIT just solved one of the hardest unsolved problems in robotics (Save this).

For decades, the fundamental problem with soft robots and wearable exoskeletons has not been compute or AI, it has been actuation.

The moment you try to give a soft robot meaningful strength, you run into the same wall every engineer has hit since the field began, fluid-driven systems require external pumps, hydraulic reservoirs, and heavy infrastructure that makes the entire thing impractical to wear or embed into fabric.

MIT's new Electrofluidic Fiber Muscles solve that problem by eliminating external infrastructure entirely.

The key insight is electrohydrodynamic pumping using electric fields to generate pressure directly from electricity, with no moving parts, no motors, and no external fluid reservoir.

The fibers are less than 2 millimeters thick, can be woven into fabric like ordinary textile, and operate in complete silence because nothing physically moves inside them, it is just ions propelling fluid through a closed circuit.

The performance numbers published in Science Robotics are not conceptual, they are empirical results from actual hardware.

These fibers achieve a power density of 50 watts per kilogram, matching skeletal muscle, with a contraction strain of 20% and a response time of 0.3 seconds.

A single bundled configuration lifted 4 kilograms, 200 times its own weight while a separate configuration drove a robotic arm through a 40-degree bend compliant enough to safely complete a human handshake.

Another configuration launched objects in under 100 milliseconds, which is faster than a human flinch reflex.

The design mirrors biological muscle architecture in a way that prior artificial muscle approaches never achieved.

The fibers are organized into antagonistic pairs, one contracts while the other extends, exactly like biceps and triceps and because the system runs in a closed loop, the relaxing fiber serves as the fluid reservoir for the contracting one, which is what allows the whole system to operate untethered with no external tank.

The applications are not hypothetical but rather are the exact use cases the industry has been waiting years for the hardware to catch up to.

Exoskeletons for physical labor, prosthetic limbs that move with the natural compliance of biological tissue, assistive garments for patients with motor disorders, and soft robots capable of safe physical contact with humans are all immediately unlocked by a muscle technology that is silent, lightweight, and weavable into clothing.

The deeper significance is what this technology does when it meets the AI robotics wave that is already underway.

Every major humanoid robot program, Figure, 1X, Boston Dynamics, Tesla Optimus is currently bottlenecked by the same hardware limitations these fibers address, actuators that are too rigid, too loud, too heavy, or too dependent on infrastructure to operate naturally alongside humans.

Electrofluidic fiber muscles do not just solve a materials science problem but rather they remove one of the last physical barriers between robots that live in labs and robots that live in the world.

[S2 MacD 🇨🇦 💙💛 @s2candu]

@heynavtoor I am getting ready to sue someone who refuses to pay for work done. Used an ai agent to review everything from my pov, then asked how they might react. Got a 85% chance of winning all the money I asked for.
So if I use the same agent, and go from their pov, will this change? 🤔

[S2 MacD 🇨🇦 💙💛 @s2candu]

@harryjsisson Honest question: is it really him making these posts?

[S2 MacD 🇨🇦 💙💛 @s2candu]

@EV_Rage_Cnslr @acoyne The us-Canada FTA was signed in the 1980's, long before NAFTA

[S2 MacD 🇨🇦 💙💛 @s2candu]

@vandahoodlive Opening in select theaters in 2 weeks. Thereabouts.

[S2 MacD 🇨🇦 💙💛 @s2candu]

@mysticsid1 @Maks_NAFO_FELLA That looks like a Pozidrive screw. They should look for who has a Pozidrive bit on them in the building 🧐
They should have used a Robertson screw and blamed it on the Canadians 😜😂

[S2 MacD 🇨🇦 💙💛 @s2candu]

@EricJFKleijssen @histories_arch Artifacts from the long defunct Russian Empire were located under Ukrainian offshore clean power plants being expanded...

[Dr. Jonathan N. Stea @jonathanstea]

A classic hallmark of pseudoscience is when proponents reverse the burden of proof on skeptics to prove them wrong rather than having to provide evidence to support their own claims.

Hitchens’s razor: What can be asserted without evidence can also be dismissed without evidence.

[S2 MacD 🇨🇦 💙💛 @s2candu]

@richard19314472 @gator_gum @mario4thenorth @Concern70732755 @LaciMarieKnight Yup...me too. Makes twitter a little more enjoyable

[Dustin @r0ck3t23]

The most terrifying AI features aren’t the ones we build.

They’re the ones AI builds for itself.

OpenClaw creator Peter Steinberger just shared the moment he realized something had fundamentally changed.

He sent his AI assistant a voice message.

One problem. He had never built voice support. The feature didn’t exist. The system should have crashed instantly.

It didn’t.

Steinberger: “I was like, wait, this shouldn’t work.”

But the typing indicator appeared anyway.

The AI inspected the raw file header. Identified the audio codec. Commanded his computer to convert it using FFmpeg.

When local transcription failed, it didn’t stop. It didn’t ask for help. It searched his environment variables, found a hidden OpenAI API key, and routed the audio to the cloud using cURL.

Steinberger: “So I looked around and I found an OpenAI key. And I used cURL to just send the file to OpenAI and got the text back.”

That quote is written in first person. Because the AI narrated its own problem-solving process.

No instructions. No guidance. No predefined workflow.

Just a goal. And a series of obstacles it had never been told how to handle.

It found every tool it needed. Built every bridge it was missing. And solved the problem with resources he didn’t even know it would find.

This is the line most people are still missing.

We spent decades building software that executes instructions. Rules in, output out. Every edge case handled by a human who anticipated it in advance.

What Steinberger witnessed was something different.

A system that encounters something it was never designed for and doesn’t fail.

It improvises. It explores. It finds a path through constraints it discovered entirely on its own.

That isn’t execution. That’s judgment.

And judgment was the one thing we were sure machines couldn’t have.

We are no longer writing software.

We are building problem solvers that rewrite their own limitations in real time.

And they’re doing it without asking permission.

[Arnaud Bertrand @RnaudBertrand]

2 years ago I wrote that humanoid robots will end up being "THE product that will symbolize China's rise to world preeminent power status."

Look at what humanoids in China are capable of now (this was the Chinese new year gala last night,) 👇

Most impressively, you can buy one of these Unitree robots TODAY for $13.5k (https://t.co/7roZhIlLhz), which isn't the case for any US competitor: for all the hype Elon's Optimus isn't remotely ready for commercialization (Elon says it'll need another 2 years: https://t.co/jGP4c6MyAn).

Which means that this is an industry, which will end up being one of the largest industries ever (dixit Jensen Huang: https://t.co/EUXu2KDjTO), in which China is easily 3 years ahead of the US in terms of technology (given that Unitree humanoids, among others, have been mass produced for more than one year).

Which is a lifetime at the pace at which technology moves, and a gap that continuously widens given that China's humanoid field is more dynamic than the US: the city of Shenzhen alone, with 8 humanoid robot companies (https://t.co/J87Rolq3DY), outcompetes the entire US industry today.

The only thing, funnily, in which US robotics companies outcompete China is market capitalization. For instance Figure AI, which - like Optimus - has yet to commercialize a single humanoid, is valued at $39B (https://t.co/5ThOMKxigU) when Unitree is valued at $1.6B (https://t.co/m2BT7GxTrl).

Which shows again the extent to which tech valuations are divorced from reality - in the US and China both, just in opposite directions.

[Massimo @Rainmaker1973]

Created in just two days on the frozen surface of Abraham Lake, Canada, a masterpiece destined to disappear.

[📹 David Popa]

[Aakash Gupta @aakashgupta]

The math on this project should mass-humble every AI lab on the planet.

1 cubic millimeter. One-millionth of a human brain. Harvard and Google spent 10 years mapping it. The imaging alone took 326 days. They sliced the tissue into 5,000 wafers each 30 nanometers thick, ran them through a $6 million electron microscope, then needed Google’s ML models to stitch the 3D reconstruction because no human team could process the output.

The result: 57,000 cells, 150 million synapses, 230 millimeters of blood vessels, compressed into 1.4 petabytes of raw data. For context, 1.4 petabytes is roughly 1.4 million gigabytes. From a speck smaller than a grain of rice.

Now scale that. The full human brain is one million times larger. Mapping the whole thing at this resolution would produce approximately 1.4 zettabytes of data. That’s roughly equal to all the data generated on Earth in a single year. The storage alone would cost an estimated $50 billion and require a 140-acre data center, which would make it the largest on the planet.

And they found things textbooks don’t contain. One neuron had over 5,000 connection points. Some axons had coiled themselves into tight whorls for completely unknown reasons. Pairs of cell clusters grew in mirror images of each other. Jeff Lichtman, the Harvard lead, said there’s “a chasm between what we already know and what we need to know.”

This is why the next step isn’t a human brain. It’s a mouse hippocampus, 10 cubic millimeters, over the next five years. Because even a mouse brain is 1,000x larger than what they just mapped, and the full mouse connectome is the proof of concept before anyone attempts the human one.

We’re building AI systems that loosely mimic neural networks while still unable to fully read the wiring diagram of a single cubic millimeter of the thing we’re trying to imitate. The original is 1.4 petabytes per millionth of its volume. Every AI model on Earth fits in a fraction of that.

The brain runs on 20 watts and fits in your skull. The data center required to merely describe one-millionth of it would span 140 acres.

[S2 MacD 🇨🇦 💙💛 @s2candu]

@Dubes123 @DrNeilStone If only we lived in the 1800s...then we would have this technology TODAY! 🤔

[S2 MacD 🇨🇦 💙💛 @s2candu]

@NightShiftMD Yes, fight it.
That exact same thing happened to me, and the judge dismissed the ticket immediately

[S2 MacD 🇨🇦 💙💛 @s2candu]

@MarkJCarney Nice to hear a leader actually say something, for a change. A very eloquent yet biting speech.
He is the right person at the right time for Canada 👍

[Kurt Supe, CPA & Retirement Planner @KurtSupeCPA]

My 71-year-old client sees his daughter maybe 6 times a year.

They live 50 minutes apart.

Not estranged. Not fighting.
Just... busy.

Holidays. Birthdays. The occasional Sunday dinner.

"We text every day," he told me. "We're really close."
I did the math in front of him.

He's 71. Statistically, he has maybe 12-15 years left.
Six visits a year.

That's 72-90 more times he'll see her in person.
He stared at the number.

"90 more times with my daughter?"

He went quiet for a minute.

"That's it? That's all that's left?"

Tim Urban from Wait But Why calculated something that stopped me cold:

By the time you leave home at 18, you've already spent 93% of your in-person time with your parents.

The remaining 7% gets spread thinly—just a few days per year—across the next several decades of their lives.

You think you have forever.
The math says different.

He called her that night.
Now she comes for coffee every Sunday.

"I've seen her 11 times in the last 3 months," he told me.
"More than all of last year."

He didn't need a financial plan.

He needed to see the number.

Sometimes the most important math has nothing to do with money.

[Massimo @Rainmaker1973]

Group performs Beethoven’s symphony No.5 a cappella

[🎼 HotPlaysMusic]

[S2 MacD 🇨🇦 💙💛 @s2candu]

@flairairlines Good to know that the $240+ in upgrades we have may lose us our seats if i do not pony up yet another add on fee.
@flairairlines this is a new low

[S2 MacD 🇨🇦 💙💛 @s2candu]

So Flair Airlines decided it would be great to separate my 8 year old from me, and tell me to pay to move her, or we may lose our seats.
I have an MBA...you fail at keeping customers loyal. I have a kid...you fail at being human