The End of Buying Robots – It's Time to Download Their Brains

The Arrival of the $20,000 Humanoid, and the Shift to Intelligent Logistics

The Logistics Industry in a Critical Dilemma

“The needs are growing exponentially, but the costs must keep falling.” This is how Dongshin Son, Head of Smart Logistics Robotics at LG CNS, summed up the reality of today’s logistics industry. The explosive growth of e-commerce, normalization of dawn deliveries, and constant wage hikes have created a triple bind—making logistics automation not an option but a condition for survival.

But the limitations of traditional automation technologies have also become apparent. “Over time, performance degrades, and continuous maintenance and management are required—something both implementers and operators have overlooked,” Son points out. While functions like storage, picking, and sorting have been mostly automated, tasks in diverse physical environments—such as unloading, inspection, and loading—still rely heavily on manual labor.

The Rise of 4th Generation Robots: Humanoids with Brains

To overcome these challenges, the 4th generation humanoid robots have emerged. According to Son, the key difference between conventional AMRs (autonomous mobile robots) and these next-gen robots lies in whether they “have a brain.”

“With the emergence of 4th generation robots, we’re entering an era where machines can understand human language and operate in human environments,” he says. This represents a new level of automation that extends beyond logistics into actual factory operations.

Son categorizes AI’s evolution into four stages: Traditional AI → Generative AI → Agent AI → Physical AI. Physical AI is a transformative technology that “thinks and acts autonomously,” recognizing its environment and carrying out tasks with minimal instruction.

Hardware Price Disruption Is Changing the Game

What Son finds most striking is the sharp decline in humanoid robot costs. “Since Tesla announced its $20,000 humanoid, Chinese companies have started listing prices below that threshold,” he observes.

Take China’s Unitree robot: while its hardware—vision sensors, voice recognition, joint controllers, batteries—is relatively basic, its core lies in its intelligent brain system. By contrast, Tesla and other U.S. firms are developing strong actuators to give these robots powerful “muscles.”

This price disruption carries two key implications:

Humanoid robots are now within reach for small and mid-sized logistics centers and even individual businesses.

The battleground has shifted from hardware to the acquisition and deployment of “robotic brains.”

LG CNS and the Measurable Impact of Intelligence

LG CNS’s smart logistics centers show how intelligence translates into results. Metrics improved across the board:

■ Total travel distance decreased by 22%

■ Picking accuracy rose from ~89% to 98.7%

■ Loading time reduced by 42%

■ Packaging time dropped by 43% (from 1.4 min to 0.8 min)

■ Employee turnover declined significantly

Son highlights optimization algorithms as the core of intelligent logistics. “We reduce costs and deploy resources efficiently by applying optimization engines,” he explains. LG CNS’s AI system integrates computer vision, speech recognition, and reinforcement learning to simultaneously process thousands of variables.

He adds that “mixed palletizing delivers greater business value.” Robots must be able to stack boxes like Tetris in real-time, faster than humans. However, traditional suction systems are limited, requiring advanced gripper technologies. Still, he frankly acknowledges that the industry hasn’t yet reached the point where robots can “think like humans” when deciding how to stack.

Korea’s Opportunity and Challenge

Son offered a blunt assessment of Korea’s position: “Korea hasn’t fully demonstrated its AI capabilities,” and “in robotics, the U.S. and China are ahead with massive investments—it’ll be hard for us to catch up.”

In particular, China has developed “data factories” to systematically collect massive datasets for robot training, rapidly advancing in both hardware and software.

Yet he is not entirely pessimistic. “China’s robotic brains aren’t yet that advanced,” he says, leaving room for Korea to compete in software and algorithm development. Hardware is another relative strength. He sees potential in Korea developing solutions tailored for its market—particularly for small and mid-sized logistics centers where large-scale infrastructure may not apply.

The ChatGPT of Robots Is Coming

Perhaps Son’s most revolutionary prediction: “Robot brains that can be downloaded like ChatGPT are coming.”

Rather than developing algorithms from scratch, success will hinge on how well and where you deploy affordable, pre-trained brains.
“The winners,” Son declares, “will be those who know how to source the right brains and deploy robots effectively.”

Complementary technologies like digital twins (3D simulations of logistics centers) and teleoperation (remote control of robots) are also emerging as vital components of this new robotic era.

Strategic Responses by Industry Sector

Logistics companies must go beyond simple automation and prepare to adopt physical AI-based robots. Investment should focus less on hardware and more on intelligent software and algorithms. Like China, firms must build structured data systems for robot learning.

E-commerce and retail companies should pursue phased adoption strategies. Solutions must be scalable for both large and small centers. Hybrid models—where complex tasks are handled via teleoperation—should also be explored.

Technology vendors should focus on developing “robot brain platforms” that can be downloaded like ChatGPT. Tailored solutions for SMEs and individual operators, plus specialized grippers that overcome the limits of suction-based systems, will be essential.

The Beginning of the Intelligence Revolution

The arrival of 4th generation robots is a watershed moment for logistics. With humanoid robots now priced around $20,000, the democratization of logistics automation has begun.

From this point forward, the competitive edge will not lie in hardware, but in brains—not in systems, but in cognition—not in automation, but in intelligence.

As Son puts it:

“Those who can secure the right brains at the right price, deploy them efficiently, and use them well—those are the ones who will win.”

The window of opportunity is open—but it won’t remain so forever.

📌 Five Core Technologies for Intelligent Logistics

1.AI-Based Optimization Engines

Real-time processing of thousands of variables using computer vision, speech recognition, and reinforcement learning

2. Mixed Palletizing

Real-time Tetris-style box stacking capability

3. Advanced Gripper Technology

Overcomes suction method limitations for diverse cargo types

4. Digital Twins & Teleoperation

3D modeling and remote control to overcome current automation limits

5. IoT-Based Real-Time Monitoring

Feedback optimization through comprehensive data collection and analysis