Jing Chang: [Foreign Language] A follow-up question about gross margin. As Mr. Li Tie just mentioned, some [indiscernible] factors on our gross profit margin in the second half of the year, we still maintain the guidance of 20% for the full year guidance. So, is there any potential negative impact we can see and what might that be? Also into plan ’24, our BEV model in the factory we’ll start to put into operation. So because we can see the current BEV models relatively have a very low gross profit margin, so how can we achieve our BEV model to drive higher gross profit margins compared to the industry?
Johnny Tie Li: I’ll take this question. This is Johnny. And as I just mentioned in the early question, the current gross margin has reflected our effort of — from our supply chain team. And we keep improving on the [indiscernible] and to help us to improve our gross margin to the 25% desired gross margin continuously. And for the BEV, we think every time we launch a new product, we will welcome some questions about the margin, and because there are some product offerings in the market, we still want to reinforce our statement that the product gross margin was from the first day, you define a customer and you define your product goal. So, we — what we want to say is that we — overall, we want to keep 35% for the whole company with different product offerings. Yeah. Thank you.
Jing Chang: [Foreign Language] My second question is about autonomous driving. So, we plan to release city NOP — NOA plus — NOA function to 100 cities by the end of this year, which is very aggressive target. Is there any challenge as we can see at present? So, can you share more about our outstanding capabilities in different aspects of our autonomous driving to support us in achieving such a challenging target?
Xiang Li: [Foreign Language] [Interpreted] As we mentioned earlier, we’re still planning to release city NOA and commute NOA batches as opposed to releasing all the cities in one go. And we’re on track to delivering city NOA to 100 cities by the end of this year. In terms of technical capabilities, we think we have advantages in both perception and planning. On the perception side, we have this innovative newer prior network and also traffic end-to-end network to predict traffic lights intentions using this end-to-end model. All of this going to enhance our BEV model, which can perceive or sense the complex road structure information in real-time and understand traffic rules. And also using occupancy network, we’re able to recognize general obstacles on the driver’s front.
On the planning side, we’re using — utilizing imitation learning algorithms, which learns from a lot of human driver behavior and decisions to make sure city NOA can stay safe on track and also follow traffic rules, and, at the same time, drive very similar to human behavior. We have, the biggest autopilot or NOA training testing fleet in China, and also have the most training mileage as well as a significant reserve of cloud — computing power, which we believe will be our absolute competitive advantage.
Operator: Your next question comes from Ming Hsun Lee with Bank of America. Please go ahead.
Ming Hsun Lee: [Foreign Language] So, my first question is regarding your sales channel. So right now you have more than 330 retail stores that cover more than 120 cities. So, in terms of your long-term goal, how many stores and how many cities do you want to cover? Besides that, could you also share what is the successful part of your sales channel management? And also in what area do we want to improve if there’s any?
