Pony AI Q1 2025 Earnings Report

Pony AI EPS Results

• Actual EPS: -$0.12
• Consensus EPS: N/A
• Beat/Miss: N/A
• One Year Ago EPS: N/A

Pony AI Revenue Results

• Actual Revenue: N/A
• Expected Revenue: N/A
• Beat/Miss: N/A
• YoY Revenue Growth: N/A

Pony AI Announcement Details

• Quarter: Q1 2025
• Date: 5/20/2025
• Time: Before Market Opens
• Conference Call Date: Tuesday, May 20, 2025
• Conference Call Time: 8:00AM ET

Pony AI (NASDAQ:PONY), through its subsidiaries, engages in the autonomous mobility principally in the People's Republic of China and the United States. The company provides robotruck services, such as transportation services to the logistics platforms. Pony AI Inc. is based in Guangzhou, the People's Republic of China.

Pony AI Q1 2025 Earnings Call Transcript

Presentation

[Operator]

Ladies and gentlemen, thank you for standing by, and welcome to PonyAI Inc. First Quarter twenty twenty five Earnings Conference Call. At this time, all participants are in listen only mode. After the management's prepared remarks, there will be a question and answer session. As a reminder, today's conference call is being recorded and a webcast replay will be available on the company's Investor Relations website at ir.ponyai.com.

[Operator]

I will now turn the call over to your host, George Shao, Head of the Capital Markets and Investor Relations at Pony dot ai. Please go ahead,

[George Shao, Head of Capital Markets & IR at Pony AI]

Thank you, operator, and hello, everyone. We appreciate you joining us today for today's for Pony dot ai's first quarter twenty twenty five earnings call. Earlier today, we issued a press release with our financial and operating results, which is available on our Investor Relations website. Joining with me today are Doctor. James Peng, Chairman of the Board, Co Founder and Chief Executive Officer Doctor.

[George Shao, Head of Capital Markets & IR at Pony AI]

Tianqin Luo, Director, Co Founder and Chief Technology Officer and Doctor. Liu Wang, Chief Financial Officer. They will provide prepared remarks followed by a Q and A session. Before we begin, please refer to the Safe Harbor statement in our earnings release, which applies to this call as we will be making forward looking statements. Please also note that we will discuss non GAAP measures today, which are more thoroughly explained and reconciled to the most comparable measures reported under GAAP in our earnings release available on our Investor Relations website and filings with the SEC.

[George Shao, Head of Capital Markets & IR at Pony AI]

I will now turn the call over to our Chairman, Co Founder and CEO, Doctor. James Peng. Please go ahead.

[Jun Peng, Chairman, Co-Founder & CEO at Pony AI]

Thanks, George. This is James Peng, our Founder and CEO. Twenty twenty five is a year of scaling up for Pony.ai and we embraced it with strong growth momentum. Before we dive into our business development, I would like to highlight four key milestones. Firstly, revenue from our Robotaxi services doubled year over year for the first quarter twenty twenty five with fair charging revenues grew approximately eight folds.

[Jun Peng, Chairman, Co-Founder & CEO at Pony AI]

This is a landmark validating our commercial deployment readiness. Secondly, we launched our seventh generation autonomous driving system in the Shanghai Auto Show. The Gen seven system achieves 70% reduction in bill of materials, basically BOM costs compared with our last generation, the Gen6. This showcased our technological advancement to effectively drive cost efficiency. Thirdly, we have secured the production capability and all the relevant components to grow our fleet to 1,000 vehicles by year end, which will significantly increase our fleet density across our operational network.

[Jun Peng, Chairman, Co-Founder & CEO at Pony AI]

Lastly, we reached strategic partnerships with some key partners such as Tencent and Uber to forge comprehensive ecosystems, both domestically and worldwide. Now, let me walk you through the details of our business progress. In late April, we showcased the Gen7 Robotaxi lineup at the Shanghai Auto Show. Gen7 is a game changing breakthrough in autonomous driving technology. As 100 of the sensors, components and all the add ons are automotive grade, which means that Gen seven will have extended product lifecycle, rock solid reliability and also next level safety.

[Jun Peng, Chairman, Co-Founder & CEO at Pony AI]

Its modular architecture also enables rapid deployment across multiple vehicle platforms, starting with three robotaxi models we unveiled in the Shanghai Auto Show. Through our strategic partnership with leading OEMs, including Toyota BAIC, Beijing Auto and the GAC, Guangzhou Auto. Gen seven global taxis will enter mass production and deployment and thereby growing our fleet size to 1,000 vehicles by year end. Most importantly, I want to highlight that such technological advancement and the large scale production and the deployment capabilities have driven a measurable increase in our efficiency, lowering both the capital expenditure and also operational costs. The two key underlying drivers are first on the vehicle economics.

[Jun Peng, Chairman, Co-Founder & CEO at Pony AI]

Our Gen seven Robotaxi total cost per vehicle, this include actually both the vehicle platform and also the ADK, the autonomous driving kits BOM costs. Both have all been reduced, especially with ADK's BOM costs coming down by 70%. The cost down is driven by multiple design optimizations, including 80% reduction in autonomous driving computation and also 68% reduction in the LiDAR costs. These efficiencies demonstrate the power of our system integration as well as scalable production approach positioning us competitively against the industry benchmarks. Second, on operational costs.

[Jun Peng, Chairman, Co-Founder & CEO at Pony AI]

In this front, we have reached a remote assistant to driver ratio of up to 20. This means that one remote assistant can effectively monitor 20 vehicles. In addition, we largely reduced our insurance cost as our commercial insurance premiums stand at approximately half of the typical cost for traditional human operated taxis. The aforementioned operational cost reductions are the results of our proven safety track record and also years of Robotaxi operational experience. Now moving to the operational expansion.

[Jun Peng, Chairman, Co-Founder & CEO at Pony AI]

This is another cornerstone that will empower our quick growth. With strong foundation in place for the future scaling, our total commercialized operational domains across Beijing, Guangzhou, Shenzhen and Shanghai now span over 2,000 square kilometers. This is nearly 20 times larger than the city area of San Francisco. Our vast coverage includes some high value transportation hubs such as central business districts, airports and high speed train stations. Notably, we secured China's First fully driverless commercial robotaxi license in Shenzhen, Nan Shan District in late March this year, unlocking operations in the city's core economic and transportation hubs.

[Jun Peng, Chairman, Co-Founder & CEO at Pony AI]

Regarding the market adoption of our robotaxi service, the number of registered users on our mobile app, this is the Pony Pilot app increased by more than 20% quarter over quarter in the first quarter of this year. We continue to enhance the user experience through innovative operational models, product features and in car infotainment systems. Our user growth trajectory will be further amplified by our new strategic partnership with Tencent, which enables us to integrate our robotaxi services into Tencent's Weixin mobility services and also Tencent Maps. As a result, we can tap into China's billions of user base. As we launch Gen seven robotaxi later this year, we will expand our capability to meet the fastest growing user demand.

[Jun Peng, Chairman, Co-Founder & CEO at Pony AI]

It sets a solid foundation to drive our future fare charging revenues through optimized fleet utilization and enhanced customer experience. With faster pickup time, superior safety and premium comfort. Now, let me share with you our global expansion progress. At Tony AI, our mission has always been since the day we founded has always been autonomous mobility everywhere. Our global footprint now spans across Europe, The Middle East, South Korea, Southeast Asia and the beyond.

[Jun Peng, Chairman, Co-Founder & CEO at Pony AI]

Recently, we have achieved multiple breakthroughs in these areas. First, we have forged strategic alliance with key industry players. We recently partnered with Uber, which will enable users to access our robotaxi service directly through Uber's platform. The partnership is expected to first launch in a key market in The Middle East later this year with the goal of scaling deployments to additional international markets in the future. We are also collaborating with Confidelgro on a joint robotaxi pilot program.

[Jun Peng, Chairman, Co-Founder & CEO at Pony AI]

Confidelgro is one of the largest land transport companies headquartered in Singapore and operates in 13 markets covering Europe, China, Australia and others. Second, we are pleased to see the ongoing favorable regulatory and testing programs globally. During the first quarter, we have secured L4 robotaxi testing permit from Luxembourg's Ministry Of Infinity. And we also started road testing in Seoul's Gangan District of South Korea. All these developments collectively demonstrate our platform's adaptability to complex global conditions, while positioning Tony AI for future commercial scaling.

[Jun Peng, Chairman, Co-Founder & CEO at Pony AI]

In summary, I think the mass production and large scale deployment of our Gen seven robotaxis remain a top priority for us. Through continuous technical innovations, we are seeing accelerating production coupled with significant cost reduction. Given the structural efficiency advantages of the Gen seven robotaxis, we have clear line of sight to breakeven and long term profitability. With that, I will now pass it over to our CTO, Doctor. Tianqin Long.

[Jun Peng, Chairman, Co-Founder & CEO at Pony AI]

Thanks, James.

[Tiancheng Lou, Director, Co-founder & CTO at Pony AI]

Hello, everyone.

[Tiancheng Lou, Director, Co-founder & CTO at Pony AI]

This is Tian Chen. So it's a great pleasure to share with you latest advancement and progress in our technology. So when we showcased our Gen seven autonomous driving system during the Shanghai Auto Show in late April, I also shared the progress of our Pony World and hardware system. Pony World, as the industry leading AI powered world foundation model, has built a high fidelity training environment and evaluation system, breaking through the limitation of imitation learning. Each week, Pony will generate test data exceeding 10,000,000,000 kilometers.

[Tiancheng Lou, Director, Co-founder & CTO at Pony AI]

The breadth and the complexity of the data accumulate have far surpassed the data that the human driver can ever collect. This generated world model trains our proprietary virtual driver, a full stack system feature integrated software and hardware, whereas Virtual Driver in turn provides valuable human feedback. It fosters the virtuous cycle of continuous enhancement, accelerating the improvement in safety and reliability of all auto driving technology. The virtual driver has demonstrated our proven L4 autonomous driving capability in the real world, successfully navigating complex urban environment across all Tier one cities in China, operating through rush hour traffic and inclement weather. By the end of first quarter, we have accumulated over 6,000,000 kilometers of drybulk operation, a clear validation of our technology maturity and its readiness for large scale deployment.

[Tiancheng Lou, Director, Co-founder & CTO at Pony AI]

Next, let me elaborate how this advancement drive operational cost optimization across the board. For a mass production perspective, hardware cost reduction remains a fundamental challenge that no automaker can avoid. With respect to our Gen seven robotaxis, our in house developed auto driving domain controller is the world's first to achieve full scenario level four auto driving built on auto grid chips, featuring an extended product life cycle and a mileage lifespan of 600,000 kilometers. Regarding computing platform, we are the first player in the L4 industry to adopt autonomous grade SoC. This advancement has successfully reduced the domain controller size, weight, power consumption and cost each by 50% to 80%.

[Tiancheng Lou, Director, Co-founder & CTO at Pony AI]

Our proprietary wallpony wall has also effectively improved computing efficiency by three times through AI inference optimization, model distillation and other technological innovations, significantly outperformed the broader L4 industry. As a result, we're able to adopt more cost efficient computing power with a total capacity of ten sixteen tons. This cost efficient approach enables us to meaningfully reduce overall cost and reach breakeven as we scale up our fleet in the future. So in terms of LiDAS, we have also made significant improvement to software algorithm to adopt to cost efficient LiDAS. For Gen7 autonomous driving kit, we opt for highly cost efficient semi solid state LiDAR, where the choice may involve many trade offs in individual sensor performance.

[Tiancheng Lou, Director, Co-founder & CTO at Pony AI]

We have compensated through advanced software algorithms that reduce the noise point by up to 30 times, ultimately resulting in enhanced overall system performance and a six to 8% cost reduction compared with the previous generation. So for sensors more broadly, we have achieved significant performance improvements through upgrading not just the hardware, but also the algorithms. A key component of over cost is related to remote assistance. Unlike remote control, over system features request based remote assistance providing suggestions to autonomous driving vehicles rather than direct interface speed control. Overcome technology allow us to achieve industry leading remote assistance to vehicle ratio of one:twenty compared with one:three for the same period of last year.

[Tiancheng Lou, Director, Co-founder & CTO at Pony AI]

We expect this trend to continue and improve as our technology advances. Our virtual driver enables smarter navigation and our advanced monitoring capability. For instance, in scenario like traffic police gesture recognition, no additional human support is required. Similarly, during passenger pickup and drop off, there's no need to manually confirm passenger status and inspect the vehicle's cabin. This allows us to operate overtax service with a high efficient remote assistance to vehicle ratio significantly reduced operational costs.

[Tiancheng Lou, Director, Co-founder & CTO at Pony AI]

This metric also shows how far we will adapt beyond the industry standards. Moreover, our technical innovations have significantly enhanced the safety of overall passenger fleet, leading to a more favorable interest economics. As James mentioned, our commercial influence premium are approximately 50% of typical cost of traditional equipment operating taxes. This reduction is a result of through accurate assessment by insurer providers who have verified our exceptional loan incident and the claim rates. This continued decrease in insurance cost is a direct outcome of our safety performance and a testament to the reliability of our auto driving system.

[Tiancheng Lou, Director, Co-founder & CTO at Pony AI]

Moving forward, we should have significant room to further solidify, expand our technological leadership and thereby scale up for future commercialization deployment. Before I conclude, I want to recap the tremendous effort we have made over the past few years to prepare for mass production, both on software and hardware front. Our Pony World platform leads the industry in areas such as methodology and the model training. On the hardware side, we have optimized the key component required for lubricant operation, including sensors, LiDAS and domain controllers, not only through traditional cost structure measures, but also through parallel software driven enhancement that significantly boost our overall system performance. This concludes my prepared remarks.

[Tiancheng Lou, Director, Co-founder & CTO at Pony AI]

I will now pass the call over to our CFO, Doctor. Liu Wang, for a closer look at our financial results. Liu, please go ahead.

[Haojun Wang, CFO at Pony AI]

Thank you, Tien Tsin. Hello, everyone. This is Liu. Before reviewing our first quarter financial results, I would like to reiterate that as we enter this pivotal year for scaling up the Gen seven road taxi fleet, we remain fully committed to disciplined investment in mass production and the deployment. We will ensure strong operational momentum while maintaining solid financial resilience or to create long term value to our shareholders.

[Haojun Wang, CFO at Pony AI]

Moving to our financial performance for the first quarter of twenty twenty five. We started this year with a strong note, demonstrating solid execution of our go to market strategy. Revenues totaled at US14 million dollars up 11.6 year over year, mainly driven by rapid growth in Robo Taxi Services. The quarter over quarter volatility was primarily due to the variation in revenue recognition of project based engineering solution services and product sales, a trend consistent with historical pattern. In the first quarter, robotaxis service revenue were US1.7 million dollars growing significantly at 200.3% year over year.

[Haojun Wang, CFO at Pony AI]

This growth was driven by both fair charging and the project based engineering solution services, with fair charging revenues achieving faster growth rate, increasing by roughly 800% year over year. The strong growth rate was attributed to the expansion of our public facing fare charging robotaxi operations in Tier one cities in China, as well as our optimizing operations for diverse user groups. Robotruck services revenue grew by 4.2% year over year to US7.8 million dollars for the first quarter, primarily driven by contributions from new clients. Licensing and application revenues were flattish year over year at US4.5 million dollars We saw increasing orders and the delivery for Autonomous Domain Controller, ADC sales, primarily driven by new robot delivery clients. The total cost of revenue was US11.7 million dollars up 17.9% year over year, in line with revenue trends.

[Haojun Wang, CFO at Pony AI]

Our gross profit reached US2.3 million dollars resulting a gross margin of 16.6%, down from 21% in the same period last year. This decrease was mainly due to the change in revenue mix on increased ADC sale for new robot delivery clients in the first quarter. That being said, we are actively working on initiatives to reduce gross margin variability for the coming quarters. Total operating expense were million dollars an increase of 56.3% year over year. Excluding share based compensation expenses, non GAAP operating expenses were US49.3 million dollars up 35% year over year.

[Haojun Wang, CFO at Pony AI]

The increase was primarily due to investment in the mass production for Gen seven and one time expenses associated with share awards settled upon the completion of IPO. Additionally, we increased employee expenses in the first quarter to strengthen our R and D capacity for concurrently developing three Gen seven vehicle models. Reflecting the investment preparing for our upcoming production of Gen seven, net loss was US37.9 million dollars compared to US20.8 million dollars in the first quarter of twenty twenty four. Non GAAP net loss was US28.4 million dollars compared to US25.7 million dollars in the first quarter of twenty twenty four. Turning to our balance sheet.

[Haojun Wang, CFO at Pony AI]

Our combined cash and cash equivalents, restricted cash, short term investments and long term debt instruments for wealth management was US738.5 million dollars as of 03/31/2025, compared to US825.8 million dollars at the end of twenty twenty four. The cash outflow was primarily driven by our Gen seven R and D effort and the supply chain preparation, in which the procurement of some key components kicked off ahead of the mass production. With the imminent scaling up and the commercial deployment, we believe our current cash reserve is sufficient for our future growth and we'll continue to explore more opportunities to ensure sustained support. Looking ahead, we are thrilled to embark on a chapter in our journey towards mass production and deployment, aiming at scalable commercialization. With our core technological advancements as the foundation, we will continue making disciplined investments to strengthen mass production capability and drive long term cost and operational efficiencies.

[Haojun Wang, CFO at Pony AI]

Our robust go to market strategy will also allow us gradually reduce financial volatility and build a more predictable path to growth. I will now turn the call over to the operator to begin our Q and A session. Thank you.

[Operator]

Thank you. We will now begin the question and answer

[Operator]

session.

[Operator]

For the benefit of all participants on today's call, please limit yourself to two questions. And if you have any follow-up questions, you may reenter the question queue. If you ask your questions in Chinese, please repeat them in English. Today's first question comes from Ming Sun Li with BMA. Please go ahead.

[Ming Hsun Lee, Managing Director - Head of Greater China Auto research at Bank of America]

Thank you, James, Tien Tsin and Leo. Congrats for the first quarter results and also your launch of Gen seven robotaxi product. So I have one question. As you mentioned 2025 as a year of scaling up, How should we address your progress throughout this year? Is there any color or pipeline for 2026?

[Jun Peng, Chairman, Co-Founder & CEO at Pony AI]

I'll take this question. This is James. We actually have a very clear pipeline for the Gen seven robotaxi mass production. This will as I mentioned, this remains to be our main focus for this year. We expect Gen seven will enter mass production for the second quarter and thereby bringing the total number of our fleet size up to 1,000 vehicles by year end.

[Jun Peng, Chairman, Co-Founder & CEO at Pony AI]

In addition, the large scale deployment will ramp up gradually throughout the second half of the year. We are especially working on the following three areas to ensure a quick ramp up. First, we are closely working very closely with OEM partners such as Toyota, GAC and BAIC for the mass production across the component sourcing pre installment and the final assembly, thereby ensuring that each robotaxi meets the highest industrial standards of quality and safety. Second thing we're working on is our agile and flexible approach to sourcing the key components allows us to rapidly adapt to the changing demand, ensuring our stable supply chains and supporting the efficient execution of our mass production plants. Lastly, our years of collaborations with the central and local governments have established a proven track record of our superior safety level and operational capability.

[Jun Peng, Chairman, Co-Founder & CEO at Pony AI]

This enhance our credibility and positions us to secure the required licenses, paving the way for commercial deployment of our Gen seven robotaxis. With aforementioned three things that we are working on, we will focus on reinforcing these critical foundations to realize robust growth momentum of our fleet size, ensuring a scalable and sustainable expansion. As for year 2026, I think our scale up will be even more accelerated. We will produce more autonomous driving vehicles and then deploy them in China and also the international markets. With this, back to the operator.

[Operator]

Thank you. And our next question today comes from Ting Song at Goldman Sachs. Please go ahead.

[Ting Song, Global Investment Research Associate at Goldman Sachs]

Thank you. Congratulations on the results. I have two questions. And the first one is, while you emphasized China First strategy last quarter, we have now seen some progress on global market this time. So could you elaborate more on your evolving global strategy?

[Ting Song, Global Investment Research Associate at Goldman Sachs]

And to what extent does the China market remain a core focus on at this stage? Thank you.

[Jun Peng, Chairman, Co-Founder & CEO at Pony AI]

Sure. This is James again. I think I'll take this one. As I mentioned in my prepared remarks, PolyAI's mission has always been autonomous mobility everywhere. While we currently prioritize the China market, given its relatively mature regulatory environment, we believe our established ecosystem, technological advancement and the scaled operation in China have empowered us to enter new markets with proven capabilities, experiences and proven business models.

[Jun Peng, Chairman, Co-Founder & CEO at Pony AI]

At this stage, we are aiming for markets with strong mobility demand, advanced infrastructure and welcoming regulations. While the commercialization of these international markets is still at the early stage, we relentlessly work hand in hand with our global partners to showcase the technology readiness, move forward local commercial driverless regulations, build momentum for public acceptance and generate revenues along the course. This approach actually mirrors our achievements that we have already established in the Tier one cities in China over the recent years, which we believe our successful track record in China will also help foster greater confidence for these new markets. Recently, we have formed strategic partnerships with key global players. One of them is Uber, with plans to launch our Robo Taxi service on their platform starting in a key market in The Middle East this year and expanding to other international markets.

[Jun Peng, Chairman, Co-Founder & CEO at Pony AI]

Another partner is Comfort Aero, one of Singapore's largest transport companies operating across 13 countries, including Europe, China and Australia. We also continue to make regulatory and testing progress globally, having secured L4 robotaxi testing permit from Luxembourg and also initiated road testing in Seoul's Gangnam District in South Korea. These successes have provided us with valuable experience as we explore future opportunities beyond the China market. With this, back to the operator.

[Operator]

Thank

[Ting Song, Global Investment Research Associate at Goldman Sachs]

my second question

[Operator]

please proceed.

[Ting Song, Global Investment Research Associate at Goldman Sachs]

Okay.

[Ting Song, Global Investment Research Associate at Goldman Sachs]

My second question is, you delivered very impressive revenue growth in Global Tax What factors are driving the high this quarter? And do you believe this is sustainable in the upcoming quarters? Thank you.

[Haojun Wang, CFO at Pony AI]

Yes, this is Liu, and I'll take this question. So the revenue growth in Robotaxis segment was driven by both fare charging and the project based engineering solution services. With fare charging revenues achieving at a much faster growth rate, increasing by roughly 800% year over year. The strong growth rate was attributed to the expansion of our public facing fare charging and robotaxi operations in Tier one cities in China. We also optimized our operations to cater to diverse user group such as interactive rewards features.

[Haojun Wang, CFO at Pony AI]

I would also like to take this opportunity to explain our Robotaxis revenue structure. Our revenue are currently generated from two main streams. The first stream consists of engineering solution services, which are recognized upon the achievement of project milestones. Hence, this is project based and could fluctuate among quarters. The second stream is recurring revenue, primarily from our virtual driver operations, such as our Robo Taxi fare charging services.

[Haojun Wang, CFO at Pony AI]

While the project based revenues currently make a larger portion in our total Robo Taxi revenue. We believe the nonrecurring revenues we are generating from partners such as ride hailing platforms, OEMs and other parties are very critical to enhance and advance our recurring revenue stream. These collaborations also further paved the way for a robust long term monetization model. As a result, we anticipate some natural volatility in revenues from quarter to quarter in this segment. That being said, we will gradually reduce financial fluctuations and are very confident to deliver strong growth trajectory in the long term.

[Haojun Wang, CFO at Pony AI]

I'll get back to the operator.

[Operator]

Thank you. And our next question comes from Bin Wong with Deutsche Bank. Please go ahead.

[Ben Wang, Director at Deutsche Bank]

Thank you for taking my question. My small polar technology perspective, you mentioned that in the ADK pricing were declined dramatic. Did you need to upgrade your software to fulfill this ADK cost reduction? In particular, what's the improvements you're doing for computing power? You also mentioned that you actually were declined 48% of the cost for computing power.

[Ben Wang, Director at Deutsche Bank]

Thank you.

[Tiancheng Lou, Director, Co-founder & CTO at Pony AI]

Thank you. I will take this question. So this is Tianqiang. So before I answer your question, I would like to say that we believe in the field of our front driving technology, Pony AI is poised to represent China's leading company in embracing the deep seek moment. So by optimizing our pointing word and enhancing engineering capabilities, so we have designed a cost effective hardware and software system.

[Tiancheng Lou, Director, Co-founder & CTO at Pony AI]

This enables us to significantly improve inference performance while reducing associated cost, even with auto grade SoC and the lower precision LiDAR sensors. So for instance, the network had effectively improved computing power efficiency by three times through AI input optimization, auto distillation and other innovations, significantly outperformed the broader LFO industry. As a result, we're able to adopt more cost efficient computing power with a total capacity of ten sixteen TOPs compared with industry peers typically ranging from 2,000 to 5,000 TOPs. In terms of the inference computing, it has implemented numerous optimizations, such as optimizing operators in AI models, creating computational parallelism and improving model memory efficiency to enhance inference performance. So all these efforts help us to improve cost efficiency without give up performance, proving that we're able to realize the cost effective and the scale L4 driver based outbound driving.

[Tiancheng Lou, Director, Co-founder & CTO at Pony AI]

Thank you. I will get back to the operator.

[Operator]

Thank you. And our next question today comes from Chuyang Yi with Haitai Securities. Please go ahead.

[Analyst]

Thank you for taking my question. So congrats on your expansion in global taxi services. So we noticed that the Ministry of Industry and Information Technology of China has recently issued some regulatory requirements regarding driver assist. So I just wonder that could this potentially have an impact on Konya Eye? Thank you.

[Tiancheng Lou, Director, Co-founder & CTO at Pony AI]

Yes, this is Tian Chen. Will take this one. So a lot I think a lot of people mistakenly equate L2, driver assist with L4, autonomous driving. Recently, the Ministry of Industry and Information Technology, MIIT, issued a notice clearly state that L2 is not equal to L4. The key requirement from MIIT include: first, the manufacturers or solution providers must avoid using misleading terms such as autonomous driving, intelligent driving, brand promoting L2 driver assist system.

[Tiancheng Lou, Director, Co-founder & CTO at Pony AI]

Second, manufacturer solution provider are required to clear define the capabilities and safety measures of driver assist system. Terms like zero takeover or hands off must not be used and the responsibility of the driver for continuous monitoring must be emphasized. So we believe this is a clear beneficial for PonyAI as it helps foster a comprehensive and a clear understanding of distinctions between L2 and L4 for the public. That's also the reason why we consistently emphasize that L2 and L4 L2 and L4 are fundamentally different in value add to the customer. Being more specifically, only L4 can truly fulfill users' need in the situation where they are looking for relaxation or even wish to take a nap while autonomous driving system is on.

[Tiancheng Lou, Director, Co-founder & CTO at Pony AI]

So I would like to go into more detail about the technological difference between L2 and L4 systems. So L2 system widely use imitation learning. The AI drivers learn by copying human behavior from real world driving data. The limitation of imitation learning is that AI driver cannot understand the reasoning behind the driving behavior. So as a result, it is not safe enough to handle ever changing traffic scenarios.

[Tiancheng Lou, Director, Co-founder & CTO at Pony AI]

For L4 system, we use the reinforcement learning and our generative pony word. So on the pony word, our virtual driver teach itself through a large amount of generative data. This allows our pony our virtual driver to understand why by analyzing the outcome of every action, teaches them to make smarter decisions in different scenarios and eventually surpass the safety of human driver. So over time, the over Virtual Driver trained under PonyWare developed advanced skills needed for complex tasks, such as multi navigating urban areas, handling unpredictable traffic scenarios, or safely operating for five hundred thousand hours without any human intervention. More importantly, the key competitive edge difference is significant between the two approaches.

[Tiancheng Lou, Director, Co-founder & CTO at Pony AI]

So imitation learning requires large amount of data, while reinforcement learning relies heavily on AI model capabilities. This underlying distinction creates a considerable barrier, making it challenging to transit from one to another. It basically requires company to start over and build the whole team of exercise, which means it cannot be simply accelerated through prior experience. Yes, thank you. I will go back to the operator.

[Operator]

Thank you. And our next question comes from Xiaoyu Lei with Jefferies. Please go ahead.

[Xiaoyi Lei, Analyst at Jefferies]

Hi, thanks for taking my question. My question is regarding The U. S.-China tariff issue, which appears to be easing at the moment. But I'm still wondering, will it have still have any potential negative impact on the operations? How many materials are you sourced from the overseas market?

[Haojun Wang, CFO at Pony AI]

Thank you. And this is Liu. I'll take this question. We believe the potential impact from the tariffs issue will be very minimal to our operation. First, the majority of our supply chain is domestically sourced.

[Haojun Wang, CFO at Pony AI]

Second, over the past few quarters, we have enhanced our supply chain resilience in response to the evolving geopolitical landscape. This includes diversifying suppliers and also increasing inventories when necessary. As a result, we are well prepared to manage this risk. In addition, I would like to highlight that our Gen seven mass production plan has also been reflected with these assumptions and also uncertainties. Therefore, we are confident that our full year target of deploying a 1,000 unit fleet size is on track and will not be affected by the changing trade environment.

[Haojun Wang, CFO at Pony AI]

I will now get back to the operator.

[Operator]

Thank you. This concludes our question and answer session. I'd like to turn the conference back over to management for closing remarks.

[George Shao, Head of Capital Markets & IR at Pony AI]

Thank you once again for joining us today. If you have any further questions, please feel free to contact our IR team. We look forward to speaking with you in the next quarter.

[Operator]

Thank you. This concludes today's conference call. We thank you all for attending today's presentation. You may now disconnect your lines and have a wonderful day.

Participants

Executives

• George Shao, Head of Capital Markets & IR
• Jun Peng, Chairman, Co-Founder & CEO
• Tiancheng Lou, Director, Co-founder & CTO
• Haojun Wang, CFO

Analysts

• Ming Hsun Lee, Managing Director - Head of Greater China Auto research at Bank of America
• Ting Song, Global Investment Research Associate at Goldman Sachs
• Ben Wang, Director at Deutsche Bank
• Analyst
• Xiaoyi Lei, Analyst at Jefferies