🧠 What if your car's AI chip worked like a human brain? Honda is teaming up with U.S. startup Mythic to co-develop a "neuromorphic SoC"—a chip inspired by how our brains think. Said to rival NVIDIA's GPUs in power efficiency, this technology could redefine autonomous driving.
Why Honda Is Betting on Brain-Inspired Chips
On February 4, 2026, Honda Motor Co. announced an investment in Mythic, a Texas-based AI semiconductor startup, along with plans for Honda R&D Co., Ltd. to co-develop next-generation automotive system-on-chips (SoCs) with the company.
The timing reflects an urgency within Honda's strategy. The automotive world is rapidly shifting toward SDVs—software-defined vehicles—cars whose capabilities are defined by software and can continuously evolve through updates even after purchase. To power this vision, Honda needs SoCs with an order-of-magnitude leap in computing performance. Everything from autonomous driving and advanced driver-assistance systems (ADAS) to powertrain control and comfort features will be managed by a single, centralized electronic control unit (ECU).
But there's a fundamental problem: boosting AI computing power nearly always means consuming proportionally more energy. For a vehicle—especially an EV with limited battery capacity—that's a critical tradeoff. Honda recognized that solving this "performance vs. power consumption" dilemma requires looking beyond conventional digital computing. Their answer: neuromorphic technology.
What Exactly Is a Neuromorphic SoC?
"Neuromorphic" literally means "shaped like a nerve." It refers to semiconductor technology inspired by how the human brain processes information.
Standard computers operate on what's called von Neumann architecture, where the processor (CPU) and memory are physically separate. Every computation requires shuttling data back and forth between them—a process that creates delays and guzzles power. This well-known limitation is called the "von Neumann bottleneck."
The human brain works entirely differently. Neurons and synapses store and process information simultaneously, all in one integrated system. Our brains run on roughly 20 watts—less than a household light bulb—yet they handle pattern recognition, prediction, and decision-making far more elegantly than any supercomputer.
A neuromorphic SoC attempts to replicate this brain-like integration in silicon. By combining computation and memory in the same place, it drastically reduces the data transfer overhead that plagues conventional chips—and the enormous power consumption that comes with it.
Mythic's Secret Weapon: Analog Compute-in-Memory
Mythic was founded in 2012 as a spinoff from the University of Michigan and is headquartered in Austin, Texas and Redwood City, California. The company has raised approximately $172 million from prominent venture capital firms including Lux Capital and DCVC.
At the heart of Mythic's technology is "analog CiM" (Compute-in-Memory). While conventional AI chips process information as digital signals (ones and zeros), Mythic performs calculations directly inside flash memory cells using analog signals. Memory elements act as tunable resistors: inputs arrive as voltages, and outputs emerge as electrical currents. This means multiply-and-accumulate operations—the mathematical backbone of AI—happen right where the data is stored.
The advantage is straightforward: since data doesn't need to travel between memory and processor, the power consumed by data movement drops dramatically. Mythic's M1076 Analog Matrix Processor (AMP) reportedly delivers up to 25 TOPS (25 trillion operations per second) at just 3–4 watts of power.
For perspective, high-performance GPUs typically consume tens to hundreds of watts. Some observers have noted that Mythic's chips offer a compelling advantage over NVIDIA GPUs in terms of performance per watt—a metric that matters enormously in vehicles.
Honda's Two-Pronged Semiconductor Strategy
To fully appreciate the Mythic partnership, you need to see it alongside Honda's other major chip collaboration. In January 2025 at CES, Honda announced a partnership with Renesas Electronics to develop an SoC targeting 2,000 TOPS of AI performance at 20 TOPS/W power efficiency, built on TSMC's cutting-edge 3nm process. That chip, combining Renesas's 5th-generation R-Car X5 SoC with Honda's custom AI accelerator via chiplet technology, is destined for the "Honda 0 (Zero) Series" EVs launching in the late 2020s. It represents the leading edge of digital computing.
The Mythic partnership, by contrast, looks further ahead. It's Honda's hedge against the eventual limits of digital scaling—a bet on analog-based neuromorphic computing as a fundamentally different approach that could deliver the next breakthrough. In essence, Honda is running a dual strategy: Renesas for near-term digital dominance, Mythic for longer-term neuromorphic innovation.
Why Power Efficiency Is Life or Death for Autonomous Driving
Consider what happens inside a Level 3+ autonomous vehicle. Multiple cameras, LiDAR sensors, and millimeter-wave radar generate enormous volumes of data every second. The AI must perform object detection, path prediction, and driving decisions in real time. Current ADAS chips deliver hundreds of TOPS but frequently consume over 100 watts.
For an EV, that's power directly subtracted from driving range. If the AI system continuously draws 100 watts, it meaningfully reduces how far the car can travel on a single charge. Heat is another problem—high temperatures degrade semiconductor reliability and may require additional cooling systems, adding cost and weight.
A neuromorphic SoC achieving equivalent performance at a fraction of the power could fundamentally change this equation. It would allow sophisticated autonomous driving features without significantly compromising range—a genuine game-changer for the EV era.
The Global Neuromorphic Race
Honda and Mythic aren't operating in a vacuum. A global competition in neuromorphic technology is intensifying. Intel's "Loihi" series pursues real-time processing through spiking neural networks. IBM's "TrueNorth" famously simulated one million neurons on a single chip. BrainChip's "Akida" targets ultra-low-power edge AI. In Europe, the Fraunhofer Institute is advancing next-generation neuromorphic chips using ferroelectric transistors.
What makes Honda's involvement distinctive is that it's an automaker directly participating in chip development—not a semiconductor company or tech giant. By embedding automotive requirements (vibration resistance, temperature extremes, safety certifications) into chip design from the very beginning, Honda can ensure that the resulting technology is purpose-built for vehicles rather than adapted from other applications.
The Road Ahead: Cars as Rolling AI Platforms
The Honda-Mythic partnership is more than a procurement story. It's an attempt to replicate the human brain's architecture in silicon and deploy it in one of the most demanding environments imaginable—a moving vehicle.
By securing the present with Renesas and investing in the future with Mythic, Honda is charting a path for how traditional automakers can remain competitive in the AI era. As cars transform from simple transportation into rolling AI platforms, brain-inspired chips may fundamentally reinvent what a vehicle's "brain" can do.
In Japan, Honda's bold move into neuromorphic semiconductor development is generating significant attention. How is your country approaching the challenge of energy-efficient AI for autonomous driving? Are your domestic automakers getting involved in chip development? We'd love to hear your perspective.
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Reactions in Japan
Compute-in-memory as a concept has been around for ages, but the key is whether it can be mass-produced with automotive-grade reliability. If Mythic has that capability, this gets interesting.
Honda's really going all-in. Partnering with Renesas while also investing in Mythic—that's a two-front semiconductor war. Hope they have the management resources for this.
As an EV owner, this is urgent. Range already tanks in winter from the heater—if autonomous driving eats another 100W, I'd cry. Low-power chips are genuinely needed.
Brain-mimicking chips sound sci-fi, but what's the real-world performance? Analog computing always has precision issues. How well can autonomous driving models run at INT8?
In automotive, without AEC-Q100 or ISO 26262 certification you're dead in the water. Whether Mythic can upgrade from edge-device chips to pass automotive certifications is the first real hurdle.
Honestly, Honda stepping into semiconductor design is a major industry impact. Toyota leans software-side with Woven, Honda goes hardware. They're differentiating nicely.
Didn't Mythic have financial trouble rumors at one point? Something about being acquired by FuriosaAI? Hope Honda's investment means they've properly stabilized.
Neuromorphic is gaining attention in aerospace too—radiation-resistant and low-power, ideal for satellites. Honda's trajectory from ASIMO to jets to space to brain chips is genuinely romantic.
Skeptical whether neuromorphic actually works for autonomous driving. CNN and Transformer inference is optimized for GPUs—porting to CiM isn't as simple as it sounds.
A chip that mimics the brain—that's kinda cool, right? 😂 I always associated Honda with F1, didn't know they invested in cutting-edge R&D like this.
Investment amount undisclosed—that's notable. Mythic's total funding is $172M, and Honda's influence depends on equity stake. If it's a minority stake, it may be more of a hedge than commitment.
Japanese companies still depend on foreign chips for the important stuff. Renesas exists but can't beat NVIDIA in GPUs. At least I hope they can mount a comeback on this new front.
Honda R&D's in-house AI model design expertise is the real strength here. Not just buying and mounting chips—being able to optimize both model and hardware together is a huge advantage.
25 TOPS at 3 watts is impressive if true, but can it scale to the hundreds or thousands of TOPS needed for autonomous driving? Solve it by parallelizing chips?
I've been reading neuromorphic papers in my lab, never expected a Japanese automaker to jump into implementation. Different approach from Intel's Loihi—the comparison will be fascinating.
Don't understand the technical stuff, but if autonomous driving uses less electricity, I'm all for it. When taxis go self-driving, electricity costs become a business expense—energy savings directly help.
I drive my kids around daily—if autonomous driving is safe and doesn't drain the battery, I'd want it someday. But how many years until news like this becomes an actual car?
Honda investing in a startup to absorb technology—that's a reference case even for SMEs like mine. Big companies abandoning the not-invented-here mentality for open innovation is the right call.
Korean semiconductor engineer here. CiM is a hot topic in next-gen memory, but guaranteeing automotive quality with analog is a serious technical challenge. Samsung and SK Hynix are researching this area too, so the Japan-Korea tech race will be worth watching.
As a Michigan alum, it's moving to see Mythic come this far. A project that started on campus in 2012 now partnering with Honda. Honestly though, I'm anxious about the lack of a visible roadmap to actual automotive deployment.
I work on autonomous driving software at an Indian IT firm. Low-power chips are especially crucial in India's hot climate. Less heat means less AC load, giving EVs a double range benefit.
From the German auto industry perspective, Honda's move is intriguing. VW and BMW basically leave chips to suppliers. An OEM getting directly into chip design is closer to the Tesla approach.
In China, autonomous driving chip companies like Horizon Robotics and Black Sesame are growing fast. Neuromorphic is interesting but GPU-based approaches are more mature today. Honda seems to be investing long-term, but can they keep up with China's speed?
I'm a BrainChip shareholder in the UK. Akida is also a strong neuromorphic contender. If Honda chose Mythic for its analog CiM uniqueness, it might coexist with BrainChip's digital approach rather than compete directly.
I teach electronics at a Brazilian university. For developing nations, low-power chips are key to EV adoption in areas with poor electrical infrastructure. If Honda's tech eventually brings costs down, emerging markets benefit too.
I run an EV startup in Poland. EU CO2 regulations keep tightening—if in-car AI power consumption affects range, then energy-efficient chips directly impact regulatory competitiveness.
From Vietnam's motorcycle culture. Honda is king of bikes in Southeast Asia. If this tech eventually applies to two-wheeler safety systems, it could be hugely significant for our accident-prone region.
Former Tesla FSD team member here. Tesla started custom chip in-house development years ago. Honda is finally moving the same direction. That said, Tesla hasn't gone neuromorphic, so it is a differentiation point.
Autonomous taxi trials are progressing in the UAE. In desert heat, chip thermal output is a serious problem. Low-power, low-heat chips have strong demand in the Middle East market.
Former Volvo Cars in Sweden. This is tech Volvo—with its safety DNA—would find interesting, but Honda got there first. The Nordic auto industry is starting to watch neuromorphic closely too.
Former Renault engineer. European automakers tend to rely on local suppliers like STMicro and NXP, but in neuromorphic, the Japan-US alliance seems ahead. The EU Chips Act should increase investment in this field.
I work on manufacturing processes at TSMC in Taiwan. Neuromorphic chips rely on analog characteristics, so they need different fab approaches than cutting-edge node shrinking. It's fascinating that even 40nm can be competitive here.
Nigerian tech journalist here. Power supply is unreliable across much of Africa, so low-power tech directly enables adoption of all AI devices, not just EVs. If Honda's technology eventually becomes affordable, it could transform African mobility.
I work at an autonomous trucking company in Australia. In long-haul, power consumption differences translate to massive cost gaps. If neuromorphic extends to commercial vehicles, it could transform the entire logistics industry.