The Verge56%

This motor could be the future of e-bikes 60%

By Thomas Ricker0%

6/30/2026, 10:30:04 AM

BS Summary: This article contains 13 faulty reasoning types, including Halo Effect, Appeal to Emotion, and Hasty Generalization, with Confirmation Bias as the most egregious example at 19.2% saturation with 148 hits. Analysis detected 891 faulty-reasoning hits from 770 analyzed words, generating a BS Score of 56.1% and a BS Rank of 60% (8,812 of 21,887 articles). This article is worse (more manipulative) than 59.70% of the article peer group.

Imagine an e-bike motor that lets you select your preferred pedaling cadence and then automatically adjusts the gears to keep your legs spinning at that exact speed, no matter how steep the hill gets  all without a fragile derailleur or heavy multi-speed cassette to maintain. 
Prefer manual control? 
No problem, you can have as many gears as you like in whatever ratio makes you feel most connected to the terrain. 
That’s the e-bike motor announced last week at the big Eurobike trade show in Frankfurt, by not just one company, but two. 
Pictured above is the MG Concept. 
It’s a Motor Gearbox Unit, or MGU, from Avinox, the DJI spinoff that’s upending the electric mountain bike (eMBT) industry. 
Avinox burst onto the scene two years ago with the launch of its impressive M1 drive system that packed unprecedented power inside a mid-drive motor that’s smaller, lighter, and cheaper than anything provided by competitors like Bosch or Specialized  and Avinox just launched the upgraded M2-series two months ago. 
The MG Concept takes things a step further by combining an electric motor with an automatic gearing system inside a single, compact housing that lets bike makers do away with derailleurs and cassettes. 
Avinox wasn’t alone, either. 
The MG concept debuted alongside the very similar X-series MGUs also announced last week by newcomer Gobao. 
These next-generation motors could fundamentally alter how standard e-bikes are built, despite both getting their start in cutting-edge electric mountain bikes that can easily cost $10,000 or more. 
Like Formula 1, eMTBs are a tech proving ground for manufacturers whose customers are willing to pay top dollar for a measurable performance advantage. 
Advances in eMTBs eventually trickle down to the rest of the bicycle market, as we’ve recently seen with the new Amflow TL “eSUV” built around a traditional Avinox M2 motor, derailleur, and cassette. 
Existing MGUs, like those made by Pinion, already integrate the gearbox inside the motor housing, but they still rely on a finite number of fixed, discrete gear ratios. 
The innovation behind both Avinox’s MG Concept and Gobao’s X-series motors is an integrated eCVT (Electronic Continuously Variable Transmission) that adds a layer of computerized precision to eliminate the stepped nature of mechanical shifting. 
Both of these new motor gearbox units with integrated eCVTs feature infinite gear ratios that adjust continuously and seamlessly, meaning there are no fixed steps between gears (unless you want them). 
You can define as many virtual gears as you like with your preferred gear ratios. 
The system constantly evaluates your speed, pedal pressure, and the terrain in real time. 
The motors also feature an auto mode that keeps your legs pedaling at a constant cadence, delivering a ride similar to the “stepless” shifting experience I enjoyed in 2023, when I first reviewed a bike fitted with Enviolo’s mechanical CVT. 
E-bikes built around these new motor gearboxes should benefit from a more durable transmission that requires far less maintenance, gears that can quickly shift under heavy load or at a standstill, and improved handling by moving the transmission mass from the rear wheel to the bike’s center. 
The Avinox MG was developed in partnership with Canyon, Commencal, Forbidden, and Mondraker, who all had prototype eMTBs on display at Eurobike  three with chains, and one with a belt drive. 
Gobao used a self-branded e-bike at the show to demonstrate pre-production prototypes of its motor. 
First ride reports found both MGUs to be very impressive, and better and quieter than existing Pinion MGUs. 
And while targeting electric mountain bikes for now, if this new breed of MGUs prove reliable and affordable, expect the motors to migrate to commuter, cargo, and family e-bikes over the next few years. 
Gobao says it’ll begin mass production of the X1 (120Nm of torque / 1200W max power) and X1P (150Nm / 1500W) in February 2027, according to Bikebiz, and is targeting eMTBs and categories spanning “urban, trekking, cargo, and SUVs.” 
Avinox is offering fewer specifics, committing to a launch sometime in 2027. 
Its production MG motor is expected to produce about the same max torque and power as Gobao, and be “easily adapted to eMTB, eTrekking, eSUV, eGravel and other bike models.” 
I personally can not wait. 
I’m so done with snapping and bending derailleurs on rocks and urban bike racks and digging mud and grit out of cassette cogs. 
It’s time for a simplified drivetrain for people who need to climb hills or carry a heavy load, even if it’s only to bring the kids to school up a paved road instead of a double-black trail. 
Article reasoning-pattern comparisonThis article: 19.2%Thomas Ricker: 4.6%The Verge: 3.6%Confirmation Bias19.2%This article: 0.0%Thomas Ricker: 2.1%The Verge: 1.3%Anchoring Bias0.0%This article: 0.0%Thomas Ricker: 2.6%The Verge: 3.8%Availability Heuristic0.0%This article: 0.0%Thomas Ricker: 1.5%The Verge: 1.3%Representativeness Heuristic0.0%This article: 0.0%Thomas Ricker: 0.4%The Verge: 0.7%Hindsight Bias0.0%This article: 0.0%Thomas Ricker: 5.4%The Verge: 1.7%Overconfidence Bias0.0%This article: 10.8%Thomas Ricker: 4.5%The Verge: 6.2%Framing Effect10.8%This article: 0.0%Thomas Ricker: 0.6%The Verge: 0.9%Loss Aversion0.0%This article: 0.0%Thomas Ricker: 0.6%The Verge: 0.5%Status Quo Bias0.0%This article: 0.0%Thomas Ricker: 0.4%The Verge: 0.4%Sunk Cost Effect0.0%This article: 9.1%Thomas Ricker: 8.4%The Verge: 4.0%Optimism Bias9.1%This article: 0.0%Thomas Ricker: 1.5%The Verge: 2.4%Pessimism Bias0.0%This article: 3.0%Thomas Ricker: 4.3%The Verge: 9.7%Negativity Bias3.0%This article: 8.8%Thomas Ricker: 1.0%The Verge: 1.5%Self-Serving Bias8.8%This article: 0.0%Thomas Ricker: 0.6%The Verge: 0.8%Fundamental Attribution Error0.0%This article: 0.0%Thomas Ricker: 0.0%The Verge: 0.2%Actor-Observer Bias0.0%This article: 0.0%Thomas Ricker: 0.0%The Verge: 0.6%In-Group Bias0.0%This article: 0.0%Thomas Ricker: 0.4%The Verge: 0.4%Out-Group Homogeneity Bias0.0%This article: 17.7%Thomas Ricker: 4.7%The Verge: 2.8%Halo Effect17.7%This article: 0.0%Thomas Ricker: 0.6%The Verge: 0.2%Horn Effect0.0%This article: 0.0%Thomas Ricker: 0.0%The Verge: 0.0%Dunning-Kruger Effect0.0%This article: 0.0%Thomas Ricker: 1.5%The Verge: 1.8%Recency Bias0.0%This article: 0.0%Thomas Ricker: 0.0%The Verge: 0.4%Primacy Effect0.0%This article: 0.0%Thomas Ricker: 0.2%The Verge: 0.1%Blind-Spot Bias0.0%This article: 0.0%Thomas Ricker: 0.6%The Verge: 1.1%Ad Hominem0.0%This article: 0.0%Thomas Ricker: 0.0%The Verge: 0.3%Straw Man0.0%This article: 2.3%Thomas Ricker: 2.8%The Verge: 4.0%Appeal to Authority2.3%This article: 0.0%Thomas Ricker: 1.2%The Verge: 1.6%False Dilemma0.0%This article: 0.0%Thomas Ricker: 0.6%The Verge: 1.2%Slippery Slope0.0%This article: 0.0%Thomas Ricker: 0.2%The Verge: 0.2%Circular Reasoning0.0%This article: 10.9%Thomas Ricker: 6.7%The Verge: 6.8%Hasty Generalization10.9%This article: 0.0%Thomas Ricker: 0.0%The Verge: 0.2%Red Herring0.0%This article: 3.4%Thomas Ricker: 1.2%The Verge: 0.7%Bandwagon3.4%This article: 12.6%Thomas Ricker: 2.5%The Verge: 4.2%Appeal to Emotion12.6%This article: 0.0%Thomas Ricker: 0.5%The Verge: 1.1%Begging the Question0.0%This article: 0.0%Thomas Ricker: 1.1%The Verge: 2.3%Post Hoc (False Cause)0.0%This article: 0.0%Thomas Ricker: 0.0%The Verge: 0.2%Tu Quoque0.0%This article: 0.0%Thomas Ricker: 0.9%The Verge: 0.8%Burden of Proof0.0%This article: 0.0%Thomas Ricker: 0.3%The Verge: 0.3%Appeal to Nature0.0%This article: 0.0%Thomas Ricker: 0.9%The Verge: 0.3%Composition/Division0.0%This article: 4.3%Thomas Ricker: 3.8%The Verge: 3.6%Anecdotal4.3%This article: 0.0%Thomas Ricker: 0.0%The Verge: 0.1%No True Scotsman0.0%This article: 0.0%Thomas Ricker: 1.7%The Verge: 2.2%Ambiguity (Equivocation)0.0%This article: 0.0%Thomas Ricker: 0.0%The Verge: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Thomas Ricker: 0.0%The Verge: 0.1%Middle Ground0.0%This article: 0.0%Thomas Ricker: 0.0%The Verge: 0.1%Personal Incredulity0.0%This article: 0.0%Thomas Ricker: 0.6%The Verge: 0.2%Special Pleading0.0%This article: 0.0%Thomas Ricker: 0.0%The Verge: 0.2%Genetic Fallacy0.0%This article: 0.0%Thomas Ricker: 1.6%The Verge: 2.6%Unattributed Quote0.0%This article: 0.0%Thomas Ricker: 0.4%The Verge: 1.4%Quote-first Misdirection0.0%This article: 8.8%Thomas Ricker: 6.7%The Verge: 10.8%Biased Writer Voice8.8%This article: 4.8%Thomas Ricker: 1.9%The Verge: 1.1%Indoctrination4.8%This article: 0.0%Thomas Ricker: 0.0%The Verge: 1.6%Politically Left Leaning Bias0.0%This article: 0.0%Thomas Ricker: 0.3%The Verge: 0.1%Politically Right Leaning Bias0.0%This article: 0.0%Thomas Ricker: 6.3%The Verge: 4.2%Attempt to Sell a Product or S…0.0%

770 words analyzed.

Speakers

1speaker5.1%attributed speech731writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 8 words • 0.0% coverageWriter's voice • 46 words • 0.0% coverageWriter's voice • 3 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageWriter's voice • 20 words • 0.0% coverageWriter's voice • 50 words • 0.0% coverageWriter's voice • 33 words • 0.0% coverageWriter's voice • 4 words • 0.0% coverageWriter's voice • 17 words • 0.0% coverageWriter's voice • 28 words • 0.0% coverageWriter's voice • 24 words • 0.0% coverageWriter's voice • 33 words • 0.0% coverageWriter's voice • 28 words • 0.0% coverageWriter's voice • 34 words • 0.0% coverageWriter's voice • 31 words • 0.0% coverageWriter's voice • 15 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 40 words • 100.0% coverageWriter's voice • 47 words • 0.0% coverageWriter's voice • 32 words • 0.0% coverageWriter's voice • 15 words • 0.0% coverageWriter's voice • 18 words • 0.0% coverageWriter's voice • 34 words • 0.0% coverageGobao • 39 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverageWriter's voice • 30 words • 0.0% coverageWriter's voice • 5 words • 100.0% coverageWriter's voice • 23 words • 100.0% coverageWriter's voice • 37 words • 100.0% coverage
Selected voice

Gobao

0%flagged-word coverage
39 attributed words100% of attributed speech71% writer coverage
0%5.0%10.0%Biased Writer Voice-9.3 ptsWriter: 9.3%Gobao: 0.0%0.0%Indoctrination-5.1 ptsWriter: 5.1%Gobao: 0.0%0.0%

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

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Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.