Joe Moore: Great. Thank you. Can you talk about how you’re thinking about spending your OpEx at this point close to your revenue? I understand revenues were a temporary low point, just how are you thinking about that sort of the balance between the importance of the revenue pipeline versus that sort of near-term cash burn?
Fermi Wang: So, Joe, I think, well — I think you’ll notice that we are definitely trying to control expense, you can see that our Q2 OpEx came below the guidance and that’s the direction we’re going to continue to look at, where we can cut and where we can save, but however, we still want to continue to invest on our strategic directions, namely CV3 architecture, as well as for the auto and IoT — our IoT auto, and ARR (ph), but those are the three big pieces of the investment area. But things before we align, we need to look at whether we have a resource to support it. So while we continue to managing carefully by expense, we do not want to sacrifice our strategic directions.
Joe Moore: Great. Thank you. And then in terms of the video processing market that you talked about, we’ve obviously recognized that there was going to be a replacement cycle from video processing to computer vision, but do you think you’re losing share in this segment, this sort of legacy markets that aren’t moving to CV, is that part of why the numbers are challenged here.
Fermi Wang: I think what I said in the consumer IP can, majority of the product today is really focused on low end and cost competitive solutions and that’s where we don’t spend a lot of money to invest. As you know, our investment strategy is always focused on the areas where we can continue to demand higher AI performance. And for the consumer IoT side that we have a focus on low-end SoC roadmap definitely hurt us. I think that’s where we have the biggest risk in terms of losing market share.
Joe Moore: Great. Thank you.
Operator: Thank you. One moment for our next question. And our next question comes from the line of Matt Ramsay from TD Cowen. Your question, please.
Matt Ramsay: Thank you. Good afternoon, guys. Forgive me for this question, Fermi, but — maybe I read a little bit too much into sort of the tone of your earnings release and some of your commentary, and with all that — I mean, Joe asked the question just now about your investments and how you’re going to focus on and what I’m trying to get at is maybe one step — maybe one level abstraction above that is like the focus of the company like changed a lot now. I mean it seems like there’s maybe a de-emphasis of your camera business and now a shift toward investments in hardware and probably more software to support inference inclusive of some data center application. So I guess should we be taking some of the tone here over the last tonight and maybe last quarter’s call, as well as a big shift in direction of where you and your team are focused.
And I guess the second part of the question is, has there been a change at all in the focus of the company on the automotive end market? Changes in expectation of revenue, timing of revenue, investment, et cetera., like I said, maybe you can, if I’m reading things that aren’t there certainly tell me, but I think it’s an important question to address.
Fermi Wang: Right. First of all, I think we continue to committed to the IoT market. I think that this is, when you say camera, I think you meant IoT market. I think that’s one area we need to continue to focus and continue to provide solution. After we think that we have a differentiated technology, as well as a big customer base, we need to continue and we will continue to provide solutions to our customers. So I think that is one area I will never say we take our eyes off the ball. And given that, I think we want to continue to invest on auto, but when you see change in auto strategy, one thing that I would say, what’s happening in the last six months is, we believe that the China market will give us earlier and shorter-term revenue and then the other market.
We definitely more focus our resources to the Chinese market for the CV72 and CV3, and I think that’s an area we believe is — can give us faster to the revenue, but that doesn’t mean we don’t focus on our USA, Europe, or other markets that we can get our CV3 design, but obviously, those design will take longer time to go to revenue. So I think it’s really a focus on the short-term revenue versus our longer-term opportunities. But I will say for LLM (ph), one thing is it’s become very clear even our current market like even security camera, when we talk to our professional security camera customers, they all start thinking about how and what impact their business, how to use LLM (ph) to integrate multiple cameras into the services for the service they provide to their customers.
And also that automotive guys also start thinking bigger, bigger transformer model, which kept the performance getting higher and leverage, while we investment in AI model. So I rethink that although that LLM (ph) start with, on the server side, which is definitely an interesting area for us, but just in the last three months, when we started talking to our existing customers, it became very clear that LLM (ph) is also on the roadmap for all our existing customer. So LLM (Ph) became a roadmap for us is not just an opportunity we can choose to invest on that. I hope this clarifies your question.
Matt Ramsay: No. Thank you, Fermi, for all the color there. I appreciate it. I guess as my follow-up question you mentioned there’s going to be different phases of your new investment around inference and LLM, have you guys thought about sizing some of those investment areas, I mean, how — what number of people or number of dollars that you’re shifting internal resources? And then, if it goes well, like, what kind of the magnitude of investment are you guys considering given where the P&L is right now? Thanks.
Fermi Wang: Right now, so for the current phase, we talk about we only carve-out a team that we using our current resources, which is under our payroll already to do that, but obviously, when we start ramping up, we probably need to duplicate a similar size of team to support the LLM. So we’re talking about anywhere from 60 to 80 people total to support or limit engagement for the customer like our goal is not going to hold the possible customer that we said last time, we need to prove the concept, and with several customers that really want to have a second source for LLM on the server side. Also several customer in our current customer base that can use LLM for their roadmap, So I think with the size and limit to the scope and we think that we can fund this activity with our P&Ls.
Matt Ramsay: Got it. I’ll jump back in the queue. Thank you very much.
