Speaker 1: Welcome to the Sentient Code, where intelligence is engineered, autonomy
Speaker 1: is emerging, and a line between human and machine grows thinner.
Speaker 1: Each episode, we decode the algorithms, explore the robotics, and
Speaker 1: examine the ideas shaping the future of artificial minds.
Speaker 2: So I want you to just take a second and
Speaker 2: imagine a machine. Okay, but like not the sleek, indestructible
Speaker 2: kind of android you see in you know, big budget
Speaker 2: sci fi movies.
Speaker 3: Yeah.
Speaker 2: I'm talking about something that is inherently vulnerable.
Speaker 3: Right, something grounded in reality exactly.
Speaker 2: So let's say this machine is navigating a really rough
Speaker 2: environment and it just takes a massive hit, like it
Speaker 2: gets crushed by falling debris, or maybe it completely loses
Speaker 2: a functional limb.
Speaker 3: Which in the normal world of engineering is pretty much
Speaker 3: the end of the story.
Speaker 2: Right. The machine throws a shower of sparks, the motors whine,
Speaker 2: and it just diesoo. But imagine a machine that doesn't
Speaker 2: just break and shut down. Oh wow, Okay, imagine it
Speaker 2: like quitches. It seems to assess what is actually left
Speaker 2: of its shattered body, figures out a completely new way
Speaker 2: to distribute its weight, and then it just it just
Speaker 2: keeps moving forward.
Speaker 3: That is, uh, that's a wild visual.
Speaker 2: Yeah, it looks less like a broken household appliance and
Speaker 2: you know, much more like a wounded animal that's just
Speaker 2: absolutely refusing to give up.
Speaker 3: It's an unsettling image for sure, But I mean it
Speaker 3: cuts to the absolute core of what we're looking at
Speaker 3: today because historically, that specific ability to adapt, to evolve,
Speaker 3: to survive sudden catastrophic physical damage in real time, that
Speaker 3: has belonged exclusively to biology, right to living things exactly,
Speaker 3: for billions of years. Living organisms have refined this capacity
Speaker 3: to persist through severe injury, you know, reorganizing their biological
Speaker 3: functions to keep operating in totally unpredictable environments.
Speaker 2: Right.
Speaker 3: But machines, on the other hand, they've always been inherently brittle.
Speaker 3: They rely on perfect pristine can.
Speaker 2: Up until right now, basically exactly because today we're unpacking
Speaker 2: some genuinely mind blowing research coming out of Northwestern University
Speaker 2: that is actively dissolving that boundary between biology and machinery.
Speaker 3: It's a total paradigm shift, it really is.
Speaker 2: We are looking at the development of dynamic modular robots
Speaker 2: that are capable of evolving and not just in how
Speaker 2: they behave or the software code they run, but in
Speaker 2: their actual physical.
Speaker 3: Form, yeah, the hardware itself.
Speaker 2: Right, So our goal today is to really figure out
Speaker 2: how engineers are stepping away from these rigid, pre programmed
Speaker 2: tools and moving toward machines that can literally thrive in
Speaker 2: unpredictable chaos.
Speaker 3: It's going to be a fun one, oh for sure.
Speaker 2: So whether you are someone who builds drones in your
Speaker 2: garage or you're just intensely curious about the future of automation,
Speaker 2: you are about to experience a major aha moment regarding
Speaker 2: what a machine can actually be.
Speaker 3: I love that, and I think to really grasp how
Speaker 3: a robot survives the kind of catastrophic limb crushing damage
Speaker 3: you just described, we have to we have to rewind a.
Speaker 2: Bit, okay, rewind to wear to look.
Speaker 3: At how it's born, I guess you could say, or
Speaker 3: rather how it's constructed from day one. At the center
Speaker 3: of this Northwestern breakthrough is this concept of modularity.
Speaker 2: Modularity.
Speaker 3: Yeah, so instead of building a robot as a single
Speaker 3: permanent entity, like pouring a solid engine block, these systems
Speaker 3: are made out of smaller, interchangeable.
Speaker 2: Units, and it like highly advanced construction toys.
Speaker 3: Right, It's a great way to think about it.
Speaker 2: Like, you don't have a fixed arm or a fixed
Speaker 2: torso you just have a bin of active building block exactly.
Speaker 3: And each of those modules has its own basic capability.
Speaker 3: So maybe a small motor, some sensors, and these connection.
Speaker 2: Faces they can snap together.
Speaker 3: Right, They have the mechanical ability to connect, detach, and
Speaker 3: communicate with the modules immediately adjacent to them. So the
Speaker 3: structure itself is incredibly floid.
Speaker 2: But I mean people have been tinkering with modular robotics
Speaker 2: for a couple of decades. Right, this isn't brand new.
Speaker 3: Oh, the concept of modularity isn't new. Yeah, But the
Speaker 3: critical pivot here, the thing that changes the entire landscape
Speaker 3: is handing the design process over to an AI driven
Speaker 3: evolutionary algorithm.
Speaker 2: Handing over the design Okay, yeah.
Speaker 3: The final shape of the robot and the way it
Speaker 3: decides to move, they are not mapped out by a
Speaker 3: human sitting at a CAB program. They're discovered through merciless virtual.
Speaker 2: Simulation, discovered rather than engineered. That's literally natural selection on
Speaker 2: fast forward.
Speaker 3: That's exactly what it is.
Speaker 2: But thinking about the mechanics of that simulation for a second.
Speaker 2: If the AI is just sort of throwing random blocks
Speaker 2: together and trying out millions of combinations, aren't the vast
Speaker 2: majority of these virtual robots just immediately flailing, collapsing, and
Speaker 2: falling on their faces the second the simulation starts. Oh.
Speaker 3: Absolutely, the failure rate is astronomical. I figured, yeah, but
Speaker 3: that is exactly the engine driving the innovation. In these
Speaker 3: simulated physics environments. The AI is compressing what would take
Speaker 3: biology millions of years into literally a matter of minutes.
Speaker 2: That is wild.
Speaker 3: It generates thousands of candidate designs. Each one has a
Speaker 3: slightly different arrangement of modules and a slightly different internal
Speaker 3: rhythm for firing its motors. Okay, they're dropped into a
Speaker 3: virtual arena and give it a basic mandate like move
Speaker 3: forward or maintain your balance, And like you said, almost
Speaker 3: all of them fail.
Speaker 2: Incidentally, you just wipe out.
Speaker 3: Yeah, they tip over, they spin in useless circles, or
Speaker 3: they just vibrate aggressively without going anywhere.
Speaker 2: But the AI doesn't just delete them and start over blindly, right, Oh,
Speaker 2: none at all. It acts like a roofless evolutionary judge.
Speaker 2: It looks at the one bizarre assortment of blocks that
Speaker 2: accidentally managed to drag itself half an inch forward before collapsing,
Speaker 2: And it's like, I'm keeping that it saves that specific trait.
Speaker 3: Yes, it takes the traits from the top one percent
Speaker 3: of performers, recombines them, mutates them slightly to introduce new variations,
Speaker 3: and then runs the simulation.
Speaker 2: Again, generation after generation exactly. Yeah.
Speaker 3: System naturally converges on designs that are highly efficient at
Speaker 3: moving through that specific virtual environment, and because human brain
Speaker 3: isn't guiding the esthetics, the end results are completely alien.
Speaker 3: I mean, the AI produces these wildly bizarre, asymmetrical, organic
Speaker 3: looking structures, which.
Speaker 2: Is so interesting because human engineers are just obsessed with symmetry.
Speaker 2: Oh absolutely, we want four equal wheels, two identical legs,
Speaker 2: perfectly balanced geometric shapes. We build things that look clean,
Speaker 2: you know, always, But the AI doesn't care about looking clean.
Speaker 2: It only cares about what survives the harsh math of
Speaker 2: the physics engine.
Speaker 3: And that lack of human bias is crucial here. Because
Speaker 3: these machines are evolved through trial by fire rather than
Speaker 3: being traditionally drafted, the relationship between their hardware and their
Speaker 3: software changes funomously, oh so well. In a standard robot,
Speaker 3: hardware and software are fiercely protected as two completely separate layers.
Speaker 2: Okay, So traditional robotics is basically like a person driving
Speaker 2: a car.
Speaker 3: I like that.
Speaker 2: Yeah, you have a fixed rigid body the car, and
Speaker 2: it's operated by a completely separate, adaptable intelligence the driver.
Speaker 2: You can upgrade the driver's skills without ever changing the
Speaker 2: car's engine.
Speaker 3: That's a perfect analogy for traditional systems.
Speaker 2: But these evolved robots, they seem more like an elite athlete. Okay,
Speaker 2: keep gun, like with a gymnast or a sprinter. Their
Speaker 2: muscle memory, their nervous system reflexes, and their literal bone
Speaker 2: structure are completely inseparable from the way they move.
Speaker 3: That athlete analogy captures the exact shift we're seeing. In
Speaker 3: traditional engineering. You build a generic robotic arm, and then
Speaker 3: you write a software program to tell that specific arm
Speaker 3: how to swing. But with these Northwestern robots, the behavioral
Speaker 3: strategy is deeply embedded in the physical form.
Speaker 2: Itself, embedded in the form.
Speaker 3: Yeah, the exact placement of those building block modules, the
Speaker 3: asymmetrical shape they form, the rhythm of their movement, it's
Speaker 3: all part of a single coevolved solution. Wow. The robot
Speaker 3: embodies movement as a property of its structure. Its physical
Speaker 3: shape is the literal reason it walks the way it does.
Speaker 3: The brain and the body they grew up together in
Speaker 3: the simulation.
Speaker 2: If the body and the brain are that tightly woven together,
Speaker 2: then what happens when half of that integration gets smashed
Speaker 2: by a falling rock?
Speaker 3: Right the catastrophe?
Speaker 2: Yeah, this brings us back to that wounded animal concept
Speaker 2: from the start. Let's look at how conventional robots handle
Speaker 2: catastrophe first, because normally, damage to a highly engineered system
Speaker 2: is fatal.
Speaker 3: Totally fatal. In a conventional robot, the control code relies
Speaker 3: on rigid mathematical models, specifically something called inverse kinematics. The
Speaker 3: central computer is constantly running equations that assume the physical
Speaker 3: body matches the original blueprints perfectly. It calculates that joint
Speaker 3: A is exactly twenty centimeters away from joint B.
Speaker 2: So if a heavy piece of debris falls and cleanly
Speaker 2: snaps off one of the robot's four legs, the computer
Speaker 2: just panics.
Speaker 3: Oh, it completely freaks out.
Speaker 2: Because the code is still trying to send movement commands
Speaker 2: to a motor that literally doesn't exist anymore. And the
Speaker 2: matrix math just returns an endless string of errors.
Speaker 3: Exactly, the robot freezes or crashes because its mental map
Speaker 3: of its body no longer matches physical reality.
Speaker 2: But the Northwestern robots operate under a totally different paradigm.
Speaker 3: Completely different because their control isn't centralized into one rigid
Speaker 3: mathematical model. Damage doesn't cause a systemic crash. So what
Speaker 3: does it do when a module is forcibly removed or
Speaker 3: an entire appendage becomes non functional? The robot doesn't throw
Speaker 3: an air code and shut down. It reinterprets its own
Speaker 3: physical form on the fly.
Speaker 2: See the idea of a machine reinterpreting its own body
Speaker 2: feels so incredibly sci fi. It does, But there is
Speaker 2: a specific example from the research that illustrates us perfectly.
Speaker 3: Oh the four legged one.
Speaker 2: Yes, so they had this physical robot evolved in the
Speaker 2: simulation to walk on four somewhat awkward appendages. It's moving
Speaker 2: across the floor and the researcher is intentional remove one
Speaker 2: of the appendages, s rip it right off. Yeah. Now,
Speaker 2: a normal machine would tip over and helplessly spin its
Speaker 2: remaining wheels, but this robot, it momentarily stumbles and then
Speaker 2: smoothly shifts its internal rhythm to adopt a three point gate.
Speaker 3: It's incredible to watch.
Speaker 2: And then when they damaged it even further, literally destroying
Speaker 2: its ability to walk upright at all, it didn't give up.
Speaker 2: It simply started exploiting whatever degrees of freedom were left
Speaker 2: in its surviving modules to drag itself.
Speaker 3: Forward across the floor, just refusing to quit.
Speaker 2: It accepted its new mangled condition instantly. But okay, I
Speaker 2: have to push back on the mechanics of this a
Speaker 2: little bit. Is the robot actually pausing recognizing it lost
Speaker 2: a leg and calculating a massive new physics equation for
Speaker 2: how to balance on three points? Or is it more
Speaker 2: like a dog that steps on a thorn, hurts its paw,
Speaker 2: and instantly just knows how to hobble without doing any
Speaker 2: conscious math.
Speaker 3: It operates much much closer to the dog. Really, Yeah,
Speaker 3: it is absolutely not freezing in place to run complex
Speaker 3: kinematic equations or recalculate a new center of gravity from scratch.
Speaker 3: It doesn't have to do that heavy computational lifting because
Speaker 3: of the way it was born in that simulated environment.
Speaker 3: The evolution part, right, Remember those millions of spectacular failures
Speaker 3: we talked about during its evolution.
Speaker 2: All those generations of flailing and collapsing, exactly.
Speaker 3: Those failures actually mapped out an incredibly vast landscape of possibilities.
Speaker 3: This robot does not possess one single rigid correct way
Speaker 3: to function. Oh interesting, because it evolved through endless variations.
Speaker 3: It exists within a massive space of possible behaviors. So
Speaker 3: when it takes catastrophic damage, that physical trauma simply forces
Speaker 3: the system out of its current behavioral state and into
Speaker 3: a different region of that pre mapp space.
Speaker 2: Okay, wait, so it's less like a computer trying to
Speaker 2: recalculate a blocked route on a GPS and more like
Speaker 2: dropping a marble into an uneven bowl when the shape
Speaker 2: of the bowl changes when it loses a leg, the
Speaker 2: marble just naturally rolls down into whatever the next stable
Speaker 2: valley is.
Speaker 3: That is a brilliant way to put it.
Speaker 2: It just falls into a new behavioral rhythm that basically says, okay,
Speaker 2: we are a three legged entity now, and we already
Speaker 2: roughly know how this shape interacts with gravity.
Speaker 3: Yes, because the control is highly distributed, it doesn't even
Speaker 3: need perfect information about what just happened to its body.
Speaker 3: It doesn't no, it just needs enough remaining mechanical structure
Speaker 3: to keep pushing forward. Resilience isn't some extra subroutine they
Speaker 3: programmed in for emergencies.
Speaker 2: It's built in.
Speaker 3: Resilience is an emergent property of having a sufficiently rich,
Speaker 3: deeply evolved repertoire of movement strategies.
Speaker 2: That is wild, but I mean watching a strange asymmetric
Speaker 2: robot drag itself across the laboratory floor is a fascinating
Speaker 2: parlor trick. But the reason we are really dissecting this
Speaker 2: today is what happens when you take this technology outside.
Speaker 2: This concept of emergent resilience is going to completely revolutionize
Speaker 2: how we operate rate in the most extreme vital industries
Speaker 2: on Earth and off it for that matter.
Speaker 3: Oh, without a doubt, the most immediate and profound impact
Speaker 3: will be in environments where human intervention is either too
Speaker 3: dangerous or physically impossible, like where the deep ocean floor,
Speaker 3: for one, or navigating the unstable, shifting rubble of an
Speaker 3: earthquake zone. And of course, extraterrestrial exploration.
Speaker 2: Space exploration is the ultimate use case for this, isn't
Speaker 2: it Absolutely You send a multi billion dollar rover to
Speaker 2: the surface of Mars. The environment is brutal. If a
Speaker 2: sharp rock tears off a vital wheel, or a Martian
Speaker 2: sandstorm jams a primary joint, the mission is effectively over.
Speaker 3: You just out of luck.
Speaker 2: Right. You cannot dispatch a technician with a wrench to
Speaker 2: go fix it, and the time delay in communications means
Speaker 2: engineers on Earth can't joys stick it out of trouble
Speaker 2: in real time. The machine just has to endure on
Speaker 2: its own.
Speaker 3: And a rover built on these Northwestern principles wouldn't need
Speaker 3: a rescue mission.
Speaker 2: It would just adapt exactly.
Speaker 3: It would adapt its gate, reconfigure its remaining functional modules,
Speaker 3: and just continue you gathering data despite the degradation. It
Speaker 3: fundamentally changes the risk calculus of deep space exploration when
Speaker 3: your hardware can dynamically heal its own behavioral strategies.
Speaker 2: But it's not just the dramatic stuff like Mars or
Speaker 2: deep ocean trenches. Right. Think about the everyday technology that
Speaker 2: runs our world and how incredibly frustrating it is.
Speaker 3: Oh, I know where you're going with this.
Speaker 2: If a single millimeter of silicon brace inside a modern smartphone,
Speaker 2: the entire device totally bricks itself. It becomes an incredibly
Speaker 2: expensive paperweight over one tiny failure.
Speaker 3: It's infuriating.
Speaker 2: Now and apply that fragility to industry. Could this modular
Speaker 2: adaptive approach mean the end of the factory out of
Speaker 2: order sign? That's the dream, because imagine a multi million
Speaker 2: dollar automotive assembly line right now. If one tiny gear
Speaker 2: strips on one robotic arm, the entire line might have
Speaker 2: to shut down for hours while a human replaces the part,
Speaker 2: costing millions exactly. But with this technology, the robot recognizes
Speaker 2: the stripped gear, reconfigures its movement path to avoid using
Speaker 2: that specific joint, and just keeps working at say, eighty
Speaker 2: percent capacity until the shift is over.
Speaker 3: You've just described a really profound industrial engineering concept known
Speaker 3: as graceful degradation.
Speaker 2: Graceful degradation I like the sound of that.
Speaker 3: It's crucial. Modern infrastructure is deeply, entirely dependent on automation.
Speaker 3: Yet most of those systems demand perfectly sterile, highly controlled
Speaker 3: environments to function. They fail abruptly, one.
Speaker 2: Thing goes wrong and boom, the whole system halts right.
Speaker 3: But graceful degradation means introducing systems that tolerate wear and
Speaker 3: tear physical damage and the messy variability of the real world.
Speaker 3: Without needing constant maintenance, they don't break, They just slowly
Speaker 3: degrade in performance while maintaining their core emission.
Speaker 2: It totally changes the economics of automation. Think about global
Speaker 2: logistics networks, massive construction sites, mining operations. They would all
Speaker 2: benefit immensely from robotic labor that just stubbornly finds a
Speaker 2: way to get the job done. Even as the machinery
Speaker 2: it's self slowly wears down over years of use.
Speaker 3: It dramatically expands where robotics can be reliably deployed. But
Speaker 3: I will say bringing this into the industrial sphere forces
Speaker 3: a rather uncomfortable realization for the people who actually build
Speaker 3: these things. Uncomfortable because if machines are now evolving themselves
Speaker 3: in simulations, determining their own physical forms and figuring out
Speaker 3: their own survival strategies, we have to really rethink what
Speaker 3: it actually means to be an engineer.
Speaker 2: Well, yeah, because the human didn't build that three legged,
Speaker 2: hobbling robot. The human just set up the digital sandbox it.
Speaker 3: Grew up in exactly. It is a massive philosophical shift.
Speaker 3: Humans are stepping away from being traditional designers and becoming
Speaker 3: what we call meta designers.
Speaker 2: Meta designers. Okay, break that down for me.
Speaker 3: Historically, an engineer dictates the exact, granular solution. They decide
Speaker 3: the torque of the motor, the length of the lever,
Speaker 3: the exact placement of every single screw, very top down right.
Speaker 3: But a meta designer doesn't dictate any of that. They
Speaker 3: shape the environment. They define the physical rules of the simulation.
Speaker 3: They set the ultimate goal like moving from point A
Speaker 3: to point B, and then they step back and let
Speaker 3: the AI discover the solution within those parameters.
Speaker 2: But this totally blurs the lines of authorship, doesn't it?
Speaker 3: Oh completely?
Speaker 2: If the algorithm runs for three days and spits out
Speaker 2: a brilliant, highly capable, completely bizarre design that no human
Speaker 2: brain would have ever dreamed up, ye, who actually gets
Speaker 2: to say they invented the robot? The great question does
Speaker 2: the credit go to the human who set the gravity
Speaker 2: parameters or the algorithm that did the heavy lifting of
Speaker 2: discovering the form?
Speaker 3: Authorship becomes completely diffuse. The final robot isn't invented in
Speaker 3: the conventional historical sense of an inventor sitting at a
Speaker 3: drafting table. The researchers themselves describe the robot as being
Speaker 3: found within a space of possibilities. The human guided the
Speaker 3: search party, but no one explicitly imagined the final product beforehand.
Speaker 2: That is so poetic.
Speaker 3: It feels much closer to discovering a new species of
Speaker 3: animal in the wild than it does to building a
Speaker 3: grandfeather clock.
Speaker 2: Okay, wait, we need a reality check here. Sure, simulating
Speaker 2: millions of generations of evolution in a pristine digital environment
Speaker 2: sounds incredible, But a virtual robot doesn't have to deal
Speaker 2: with real gravity. Sure it doesn't have to deal with
Speaker 2: a sudden gust of wind pushing it over, or a
Speaker 2: change in humidity that totally alters the friction of its
Speaker 2: rubber footpads. How much of this simulated evolution actually survives
Speaker 2: when you try to build it out of physical metal
Speaker 2: and plastic.
Speaker 3: That is the single greatest bottleneck in the field right now.
Speaker 3: It is known as crossing the reality gap.
Speaker 2: The reality gap.
Speaker 3: Yeah, the transition from a perfect virtual simulation to the dirty,
Speaker 3: unforgiving physical world is incredibly difficult. In a physics engine,
Speaker 3: you can calculate friction, but it is an idealized version
Speaker 3: of friction, and.
Speaker 2: A virtual motor never overheats. And melts its own wiring.
Speaker 3: Exactly that real world materials have complex constraints. Metals bend
Speaker 3: and fitt over time, plastic snap under unexpected torsion. Energy
Speaker 3: efficiency is a massive hurdle.
Speaker 2: Because a physical robot has to carry its own battery right.
Speaker 3: And power drain is highly unpredictable when a machine is
Speaker 3: improvising new ways to walk. Ensuring that an intricate asymmetrical
Speaker 3: design that evolved in the digital utopia remains viable when
Speaker 3: it is constructed from physical atoms it is a massive
Speaker 3: ongoing engineering challenge.
Speaker 2: But even with that reality gap, even acknowledging the friction
Speaker 2: and the battery issues, the broader trajectory of this technology
Speaker 2: is undeniable, isn't it.
Speaker 3: It really is. We are watching the entire field of
Speaker 3: robotics move fundamentally away from rigid, pre defined tools.
Speaker 2: Right by combining modular, interchangeable hardware with evolutionary AI, we
Speaker 2: are staring at a future where machines are no longer
Speaker 2: static objects. They are active participants in a continuous, open
Speaker 2: ended process of physical change.
Speaker 3: And in that future, a robot's identity isn't defined solely
Speaker 3: by how it looked when it rolled off the embly
Speaker 3: line on day one, it will be defined by its
Speaker 3: capacity to transform on day one hundred. Well, physical damage
Speaker 3: no longer marks the end of its usefulness. Damage just
Speaker 3: becomes another piece of environmental data. It's just another condition
Speaker 3: to adapt to another puzzle for the distributed network of
Speaker 3: modules to solve.
Speaker 2: Function is no longer tied to one perfect symmetrical shape.
Speaker 2: It is distributed across countless possible forms. And that means
Speaker 2: our basic definition of machine intelligence has to evolve as well,
Speaker 2: doesn't it. Absolutely, intelligence isn't just a supercomputer calculating a
Speaker 2: massive math problem in a sterile room anymore. In this context,
Speaker 2: intelligence is defined by the physical ability to persist through
Speaker 2: violent change.
Speaker 3: It points toward an entirely new class of machines systems
Speaker 3: that carry within them a principle that we previously thought
Speaker 3: was the exclusive domain of biological life. The survival instinct exactly,
Speaker 3: the sheer, stubborn capacity to just keep going even when
Speaker 3: the form that began the journey is completely destroyed.
Speaker 2: Completely rewrites our relationship with the synthetic world. And before
Speaker 2: we wrap this up, I want to leave you with
Speaker 2: one final provocative thought to mull over on your own.
Speaker 3: Well, let's hear it.
Speaker 2: So, throughout this discussion, we focused on a single robot,
Speaker 2: a loan machine, taking damage, reinterpreting its own broken body,
Speaker 2: and figuring out a new way to drag itself out
Speaker 2: of a collapsed building. But think about where communication technology
Speaker 2: is heading. What happens when these evolving adaptive machines are
Speaker 2: networked together. Oh wow, Imagine a scenario where one crushed robot,
Speaker 2: trapped under debris, spends ten minutes evolving a highly specific,
Speaker 2: bizarre muscle memory to worm its way out. What if
Speaker 2: it could instantly transmit that newly evolved survival strategy to.
Speaker 3: A cloud network a shared consciousness.
Speaker 2: Exactly, could an entire swarm of hundreds of other robots
Speaker 2: waiting outside instantly download that strategy, artificially, inheriting an evolutionary
Speaker 2: survival trait in a matter of seconds.
Speaker 3: That's terrifying and amazing.
Speaker 2: Imagine a single machine that doesn't just surve its own catastrophe,
Speaker 2: but permanently and instantly immunizes every other machine in the
Speaker 2: world against it. Take a moment and let that sci
Speaker 2: fi reality sink in