QuickLogic Corporation (QUIK) Q1 2015 Earnings Report, Transcript and Summary

Ladies and gentlemen, good afternoon. At this time I’d like to welcome everyone to the QuickLogic Corporation's First Quarter 2015 Earnings Results Conference Call. During the presentation all participants will be in a listen-only mode. A question-and-answer session will follow the Company’s formal remarks. [Operator Instructions] Today's conference call is being recorded. With us today from the Company are Andrew Pease, the President and Chief Executive Officer; Ralph Marimon, Chief Financial Officer; and Brian Faith, Vice President of Worldwide Sales and Marketing. At this time, I’d like to turn the call over to Ralph Marimon, Chief Financial Officer. Please go ahead, sir.

Thank you, and good afternoon. The conference call is being webcast and QuickLogic will be using presentation slides during the call. To access the webcast with slides, go to the Events Section at ir.quicklogic.com. Before we get started, let me take a moment to read our Safe Harbor Statement. During this call we will make statements and refer to presentation slides that are forward-looking. These forward-looking statements and slides involve risks and uncertainties, including but not limited to stated expectations relating to revenue from our new and mature products, statements pertaining to our design activity and our ability to convert new design opportunities into production shipments, market acceptance of our customers' products, our expected results in our financial expectations for revenue, gross margin, operating expenses, profitability and cash. QuickLogic's future results could differ materially from the results described in these forward-looking statements and slides. We refer you to the risk factors listed in our Annual Report on Form 10-K, quarterly reports on Form 10-Q, and prior press releases, for a description of these and other risk factors. QuickLogic assumes no obligation to update any such forward-looking statements. For the first quarter of 2015, total revenue were $6.2 million which was above the midpoint of our guidance range. New product revenue totaled approximately $4.2 million and was above our guidance. This was due to higher than anticipated demand from Samsung for display products and sales of earlier generation new products. Mature product revenue totaled approximately $2 million, which was at the midpoint of our guidance range. Samsung accounted for 39% of total revenue during the first quarter as compared to 49% of total revenue during the fourth quarter. Our non-GAAP gross profit margin for Q1 was 47% and was well above our guidance. The primary reason for the higher than expected gross margin was the product mix, which includes sales of higher margin earlier generation new products. Non-GAAP operating expenses for Q1 totaled $6 million, which was just below the midpoint of our guidance. On a non-GAAP basis, the total for other income, expense and taxes was a charge of $79,000. This resulted in a non-GAAP loss of approximately $3.1 million or $0.06 per share. We ended the quarter with approximately $28.2 million in cash. Our Q1 GAAP net loss was $3.6 million or $0.06 per share. Our GAAP results include stock-based compensation charges of approximately $497,000. Please see today's press release for a detailed reconciliation of our GAAP to non-GAAP results. Now I'll turn it over to Andy who will update you on the status of our strategic efforts.

Our momentum in the marketplace has increased significantly during the last three months, and we expect that trend to continue. While its easy to describe our activities into display bridge and smart connectivity markets. The direction and evolutionary path of sensor processing markets are more difficult to articulate. To clarify our position and outlook for these markets, we prepared a special slide presentation for this conference call. As we noted in the press release and Ralph mentioned earlier, you can access the webcast with slides at the event section at ir.quicklogic.com. Please join me now for the presentation. In October 2013, we announced our entry into the sensor processing market with our first silicon platform based on our patent pending Flexible Fusion Engine or FFE. During the 60 months of followed, we built out a complete sensor processing system solution. The cornerstones of this solution include a clear silicon platform roadmap, a growing library of world-class sensor algorithms, a suite of development tools and reference designs, and the assurance of easy system integration provided by our sensor QVL and ecosystem partnerships. Our cornerstone strategy has resonated well with our customers and enabled us to nearly double the number of design engagements during the last three months. More importantly, we’re seeing an increased flow of design wins from these engagements. While we continue to build strength in each of these cornerstones, today we will focus on silicon platforms and our SenseMe algorithm library. To fully appreciate our silicon platform and roadmap strategy, it’s important to understand the advantages of our Customer Specific Standard Product or CSSP business model. This model leverages the core IP advantage of our patent pending ultra-low power reprogrammable logic technology. With this model, we can deploy new silicon platforms by leveraging the flexibility of our reprogrammable technology. This advantage enables us to lower development costs and risks while accelerating our time to market. It also establishes a feedback loop with our customers that helps us refine our silicon platform roadmap. Time to market is critical in these consumer markets. And this model allows us to quickly introduce market specific platform based on our mobile FPGAs. To optimize for power and cost, we hardened [ph] certain aspects of the design over time into what essentially becomes a programmable application specific standard product or a customer specific ASSP. The programmable capabilities of platform allows our customers to tailor it to their specific needs. This entire model is enabled by the fact we have our programmable logic technology. The ArcticLink 3 S1 that we released in October 2013 is a perfect example of this model in action. While certain generic aspects of the S1 platform where implemented in hard logic, virtually everything else was done inside our in-system reprogrammable logic. This allowed us to immediately initiate design activities with targeted customers, and benefit from their feedback as we defined our S2 platform. Through this process, we were able to improve the design, move more functions into hard and logic blocks and increase the amount of programmable logic that customers can use for further hardware customization in our S2 platform. These early engagements also allowed us to move the first design wins in the preproduction approximately one-year after the release with the S1. We have continued to leverage this strategy with our ArcticLink 3 platform. I'll get into more detail on the S3 in a few minutes. Our SenseMe algorithm initiative which is only a year-old is playing out very well. In independent customer tests, applications driven by our proprietary algorithms have set new standard for accuracy and power efficiency. This and the ability to get a complete silicon and algorithm solution from one source has been widely embraced by our customers. Literally every current design that is scheduled to move into production is based on QuickLogic’s SenseMe library. Interestingly, a number of potential customers have expressed a desire to license our SenseMe algorithms ahead of adopting our silicon platforms. These include major participants in the wearable and smartphone markets. In most cases these customers are not at a point in their design cycle that would allow them to easily adopt our silicon platforms. These potential customers have indicated a strong interest in adopting our silicon in future designs. Establishing SenseMe license contract will help us secure commitments for our silicon in those designs. Most algorithms we’ve released so far are considered fundamental. These type of algorithms are commonly used in wearable devices and smartphones today and have enabled us to develop a substantial number of design engagements. A vast majority of our targeted customers want to include a fitness application in their solution and pedometer accuracy has become a very important factor in the selection process. While the pedometer function may seem simple, developing a robust algorithm that delivers accuracy independent of device location, stride, cadence, gender, age and height is a huge accomplishment. As mentioned last quarter, we have applied for a patent protection for this pedometer implementation. In addition to the near-term benefits of our SenseMe library, we’re leveraging these fundamental blocks to deploy more sophisticated algorithms such as our motion compensated heart rate monitor technology that we expect to release early in the second half of the year. This is the first of two line charts I'll show you today. This chart conveys quite a bit of information, so please bear with me as I walk you through it. The power consumption for embedded processor solutions is highly depending on something known as duty cycle. Duty cycle is the percentage of time the processor is turned on to execute instructions. The industry standard terminology for measuring the number of instructions in algorithm requires is MIPS or Millions of Instructions Per Second. The bottom line is the higher the MIPS, the higher the duty cycle requirement, and the more power you will consume. This chart shows MIPS along the horizontal axis. On the vertical axis it shows the corresponding power consumption for our recently announced ArcticLink 3 S2 LP platform and the typical arm M4F processor. Below the horizontal axis are the types of algorithms that are commonly being executed in smartphone and wearable devices today. When using our highly efficient SenseMe algorithms, we can satisfy most of the use cases inside a 0.4 MIPS window, which for our S2 LP platform means an active power consumption of 75 microwatts. A typical M4F solution would more likely have to run at/or above 1 MIPS to satisfy these use cases. While that implies substantially higher power consumption relative to the S2 LP, it is still within the power budget of most smartphone designs. To date the smartphone industry has followed a logical design progression with sensor processing shifting from an ARM core and an application processor to an embedded ARM core and a sensor hub. This was an easy and low-risk decision for designers, because as long as the process -- the MIPS processing requirements and corresponding duty cycle remain low; the power consumption is not terribly disruptive to battery life. However, that is not the case for small wearable devices. Smartphone battery capacity can be as much as 100 times greater than the battery capacity of small wearable devices like fitness bands and smartwatches. This is one of the reasons why our sensor processing system solutions are being so readily embraced by wearable device manufacturers. However, technology standstill for no one and leading smartphone manufacturers are telling us they want to significantly increase the MIPS capabilities of the sensor processing system. As you'll see in the next slide this means they are going to have to take a different design approach. Chart two zooms out to show what we believe will be the evolutionary path for sensor processing in smartphones. To put this in perspective, the previous chart fits into the small area to the left of the 1 MIPS label on the horizontal axis. Smartphone manufacturers seem to be comfortable working with solutions they can operate within the power consumption shown in the green band. This implies that the ARM M4F solutions that are commonly used in smartphone designs today have some headroom. However, due to the evolutionary trends we see in the industry there is not as much headroom as the chart suggests. Below the horizontal axis, you will see icons representing some of the sophisticated next-generation algorithms that smartphones and wearable design manufacturers would like to deploy. Since some of these algorithms require 20 or more MIPS each, the aggregate MIPS requirement is poised to move up significantly and in large steps. As that happens, the power consumption of the M4F solutions moves quickly through the yellow zone and into the red zone. The implication here is we believe there will be an emerging requirement to accommodate substantially higher MIPS at lower power levels than traditional embedded processor solutions can deliver. There are three things we believe will drive the demand for higher MIPS capabilities. First, there will be more data from more sensors to manage fuse and process more frequent data streams, require more MIPS and that means higher power consumption. Second, sophisticated algorithms are needed to drive next-generation applications like those shown across the bottom of the chart. More complex algorithms require more MIPS and with that higher power consumption. Third, design trends suggest we are finally moving towards always-on and always-aware applications. This will require higher duty cycles and as I noted earlier, higher duty cycles drive higher power consumption. As you can see from the line showing a typical embedded M4F processor solution, its power consumption moves into the yellow zone at only 24 MIPS and then into the red zone at 48 MIPS. This means that smartphone OEMs will have to take a different design approach if they want to keep pace with this evolutionary trend. We believe our next-generation sensor processing platform, the ArcticLink S3 is the right solution to support and enable this trend. The S3 remains on schedule for release during mid 2015. As you can see, the S3 is a revolutionary step up from our S1 and S2 platforms. Rather than being MIPS limited like our S1 and S2, it is targeted to deliver nearly 50% more MIPS capability than the typical embedded M4F processor solution. Now let's draw our attention to the middle of the chart, where you can see an inflection of the S3 power consumption at 55 MIPS. I am not going to reveal the unique architecture we have leveraged to keep the S3 power consumption so low at 55 MIPS. But I do want to highlight that typical M4F solution consumes seven times more power than our S3 and enters a smartphone red zone at only 48 MIPS. 55 MIPS is a critical design point for two reasons. First, we believe we can deliver most of the next-generation applications inside the 55 MIPS window and that means our solution is well within the smartphone green zone. As a matter of fact, we stay in the green zone all the way up to 94 MIPS which is more than four times the 23 MIPS, a typical M4F solution can deliver in the green zone. Second, is the fact that wearable device manufacturers would also like to take advantage of high value applications that sophisticated algorithms can deliver, with a targeted power consumption of only 1.65 milliwatts at 55 MIPS. The S3 can do that within what most wearable device manufacturers consider to be tolerable power budget. To put this in perspective, a typical M4F consumes about the same power, but only at 8 MIPS. And there is one more thing I’d like to share with you about the S3 platform. The S3 was intentionally designed to enable manufacturers that are currently embedded ARM solutions to easily port their intellectual property to the S3 platform. That means in addition to having what we believe is the right technical solution; we also present a low-risk migration path for our customers that leverages the economic benefits of integration. During our last conference call, we said that we had initiated ArcticLink S3 discussions with select customers under NDA. These discussions are going very well and we’ve evaluated request from customers that want to be part of our alpha program, which allows first access to this platform. We have had strong interest in this program and we have established full requirements for OEM participation. Members of our S3 alpha program must be top tier OEMs, have a specific and funded project, have executive sponsorship, and have agreed to establish a formal feedback with QuickLogic. We have recently established our first S3 alpha engagement with a top five smartphone company and we’re working to establish an engagement with the second smartphone company this quarter. That brings us to the end of our slide presentation. Now let me take a minute to review our new product activities in Q1 and our outlook for Q2. During Q1, we shipped development quantities of our S2 platform to a total of seven customers to support their design efforts on nine unique products. The three designs we forecasted for production shipments last quarter were delayed due to customer design changes. Including these three, we expect to ship units to support five production designs during Q2. We have received preproduction orders for three of these designs. In smart connectivity and display, we continue to support a variety of designs in North America, Japan, China, and South Korea. These include two new tablets from Samsung, the Tab 3 V and the Tab E7.0. I’d like to turn the call over to Ralph who will provide our Q2 guidance and then I’ll return for my closing remarks and Q&A.

For the second quarter of 2015, we’re forecasting total revenue of approximately $5.5 million plus or minus 10%. The $5.5 million in total revenue is expected to be comprised of approximately $3.5 million of new product revenue and $2 million of mature product revenue. New product revenue reflects continued shipments of our display solutions into the tablet segment, shipments of various smart connectivity CSSPs, as well as production shipments of our S2 and other CSSP platforms. As in prior quarters, our actual results may vary significantly due to schedule variations from our customers which are beyond our control. Schedule changes and projected production start dates could push or pull shipments between Q2 and Q3 and impact our actual results significantly. On a non-GAAP basis, we expect gross margin to be approximately 42% plus or minus 3%. The expected sequential decrease in our non-GAAP gross margin is driven by our forecasted product mix. We are currently forecasting non-GAAP operating expenses to be $6 million plus or minus $300,000. Non-GAAP R&D expenses are forecasted to be approximately $3.5 million. The increase in engineering expenses is due to outside service costs related to new chip development and new hires within the engineering organization. Our non-GAAP SG&A expenses are forecast to be approximately $2.5 million. Our other income, expenses and taxes will be a charge of up to $60,000. At the midpoint of our guidance, our non-GAAP loss is expected to be approximately $3.8 million or $0.07 per share. Our stock-based compensation expense during the second quarter is expected to be approximately $420,000. And we expect to end the quarter with approximately $26 million in cash. Before we move to the question-and-answer section of today's call, let me turn the call back over to Andy for his closing remarks.

Thank you again for joining us today. I hope you found our special slide presentation informative and work the extra time it took to present. The markets we are addressing with our sensor processing system solutions are rapidly evolving, but their evolutionary path is clear. OEMs will need to use more robust processing solutions. The traditional embedded MCU processor solutions that have taken the market to this point consume too much power to support the evolutionary trajectory. We believe we have the best solution and roadmap in a market today to enable this trajectory. Operator, we’d now like to open-up the call for questions.

Certainly. [Operator Instructions] Our first question comes from the line of Krishna Shankar from ROTH Capital. Your question please.

Yes. Andy and Ralph, congratulations on the design win momentum and some of the technology achievements with the sensor platform. You mentioned that, I guess, you have several design wins moving into production this quarter, can you -- last quarter I think you had mentioned a couple of design wins, one with a smartglass customer in Japan and another with Foxconn. Can you talk about the nature of the design wins moving into production this quarter in terms of wearables, smartphones, and just give us a little more color on the design wins moving into production?

Sure. I’ll let Brian handle that.

Hi, Krishna. Yes, so the wearables is the big market for us right now as Andy was alluding to for the S2 with the power consumption savings, and those are the ones that we are referring to for the Q2 designs moving to production.

Okay. And would you -- are some of these smart bluff, can you just talk about the types of wearables that are going into production?

I can say that they’re going to be wrist-worn for these new ones beyond the Telepathy, Google glass type product that we had talked about previously. And I think I’ll leave it at that. As we get permission from the customers to acknowledge who is actually using us in production devices, we’ll make sure that we can communicate that out to you. But for now I’ll just say that they’re wrist-worn.

Okay. And then, through the course of this year would you expect more traction in terms of revenues from wearables versus smartphones for your sensor hub product line?

I’d say in the near-term the traction is certainly going to be in the wearable side, again due to the power consumption advantages that Andy was referring to. He also mentioned that the S3 was specifically architected to address some of the growing needs from the smartphone area, both from a compute and a power point of view. So, we do see some traction in gaining there as we get out to more customers and lockdown who will actually be part of the Alpha program. And then through the rest of the year we do see the S2 as being a very good platform still for wearable side. I expect more momentum in that area.

Okay. And then given what you had now in terms of preproduction wins, would you anticipate entering a seasonally stronger second half of this year? Would you anticipate the material pickup in revenues from new products in the second half of this year based on what you have sort of in confirmed designs moving to production today?

Yes, Krishna obviously we don’t give guidance out for the whole year. But I think it’s fair to say that we do believe we should see increased traction on the S2 side of things as we move forward in the central processing market. We’re starting from a very low base and we obviously hope that that will grow throughout the year.

Thank you.

Thank you. [Operator Instructions] Our next question comes from the line of Gary Mobley from Benchmark. Your question please.

Hi, guys. Thanks for taking my question. I’m assuming since the S2 is garnering most design win traction in wearables, most of the competing solutions you’ve gone up against or going up against would include M0 based and M4 based discreet ASSPs, and then as well multi-chip integrated sensors within MCU. Could you talk about how you won out over those alternative solutions? And then, for the S3 I’m assuming that it will be more so targeted at the smartphone market in which case the apps processors would integrate or handle some of that sensor processing need. And do you find it difficult to compete now against ARMs big little architecture which presumably is more efficient to allow those smaller A53 cores to handle the minute processing task in the sensor -- the sensors coming in, and I guess I’ll just stop there and let you answer the question.

Yes, so that’s a lot of questions. I’ll take the first part of it and throw the competing part of the smartphone over to Brian. But the people that we are competing with and how we win is, we’ve been very careful to say if you listen to the prepared text is, we believe that we’ve got a sensor processing system. And what that means is that, we not only offer the silicon, but the algorithms themselves so we could deliver the complete solution to the customer, and frankly that’s one of the things that set us apart. Recall I said, that every design that we have now that’s moving into production is using our algorithms and when you look at most of the other competing solutions out there, they’re really more of a hardware solution rather than a complete sensor processing solution.

So, this is Brian, I’ll take the second question there. As we look forward I think that for smartphones, first of all this is more than a billion unit market. If you look at what IHSI supply saying for sensor processing processors distributed between the different categories that you referred to. I think what we’re going to see in the future is, more use cases that are driving more processing requirements, and even in a big little architecture, if you’re still doing that processing in software, you’re still going to be architecture limited in consuming the types of power that we showed in our graph. And that’s why we’re really excited about this architecture that we have, because we think it’s an architecture advantage. It’s not just the process noted advantage that a lot of the application processor companies have. And that’s going to have staying power and that’s how we’re going to be I think viable in this market from a power consumption point of view.

Yes, and I think just to sum up what Brian said, I think those big little architectures that you hear from the AP guys, think of that little core MCU cores being the same MCU core that we described in our presentation, because fundamentally they’re using the same intellectual property.

Okay. I appreciate the fact that you guys are in a position to license your algorithms, in fact I’m happy to see it. Is there any licensing revenue from those algorithms embedded in your Q2 revenue expectations, and to what extent can you drive revenue from licensing the algorithms? And that’s it from me. Thanks.

Yes, well Gary we have not yet implemented the model and where we are in that model is we are taking into consideration many of the different things that get involved with developing an IP licensing model. I would put a high probability that we will go in that direction as long as it has strategic advantage and it can bring up return, shareholder value to our company. But so for right now we have not actively engaged or signed a deal with anybody in particular, but as we said in the prepared remarks there are many, many people that are interested in licensing our library.

Okay, all right. Thank you guys.

Thank you. Our next question comes from the line of Rick Neaton from Rivershore Investment. Your question please.

Thank you. Hello, Andy. And my first question is, how are you seeing the wearable market develop this year or grow this year from its kind of infant stage right now? Do you see more of a third, fourth quarter inflection like a consumer electronics product timeline here? Is that what you’re seeing from your customers right now?

I’ll take that question. This is, Brian.

Hi, Brian.

I think what we’ve seen is that, the typical phenomenon where a lot of the OEMs were somewhat waiting to see what Apple would actually come out with, with their product determining how they’re going to position against that and then bring their products to market to that plan. So, right now we’re seeing I’d say a flurry of activity with people now and now that the watch is out, people are looking at battery life, they’re using at use cases, they’re figuring out what they need to do in their product and moving forward. So I do expect it will be second half where we start to see a lot of people coming out with their version of the watch taking into account what they’ve learned from the Apple launch.

Do your customers see a huge demand for, power efficiency right away or is they more focused on getting accurate data from the sensors in the wearable devices?

I think that’s a great question, and I think that the answer to that is, two parts. First, on the accuracy. I think that because pedometer apps have been out there for so long that people are becoming keenly aware of the inaccuracy of many solutions. So, we are seeing now with our customers that accuracy is absolutely key, and so is power efficiency and I’m not sure I could rank one above the other, because both of those what turns out to be must haves. And by the way, when they talk about accuracy, what they mean by that is the number of steps that is recorded are equal to the actual number of steps you’ve walked more over that you do not record false steps, as that’s been the case with some of the solutions when you’re eating, a lot of that motion when you’re putting food in your mouth gets recorded as steps.

Okay. And in terms of some of these global macro headwinds, are you seeing any delays in product development because of currency or economic issues in some of the locations that your customers are?

No, well we don’t see that at all. I would just eco what Brian said. We’ve had lots of activity, but since we’ve started really going after this in earnest at the end of last year as we talked about in last call, but we definitely see an increase now that the Apple watch is out. There definitely are people that wanted to understand what they were competing against, and this was really much like with the introduction of the iPhone and also the tablet.

So you see the wearables then leading to -- leading demand for better always and always wear smartphones rather than the smartphones pulling the wearables along behind them, is that how you see things? In other words the wearables -- the demand for wearables are going to create the demand or the need for a more efficient and more robust smartphone that has all these sensor capabilities on it?

I think it’s actually going to depend on the use case. If you’re talking about indoor navigation and pedestrian, I’d reckon that you’re probably going to want to be doing that with a larger display like your phone. So those types of use cases are going to drive more innovation in the smartphone area. On the wearables, the fact that you would probably want to be not just doing steps 24 hours a day, but analyzing your sleep patterns, recommending things that can maybe make you a more healthy person, measuring your heart rate for example, those are going to drive innovations in the watch side. So, we see these things somewhat different, but at the end of the day they all boil down to more MIPS at less power to enable those use cases.

Okay. And one last question, is the S3 oriented only towards android operating systems or is it compatible with others?

Well, I’ll take that. So, the S3 from a technology point of view is agnostic to any operating system. But I can tell you that we are focused on android and RTOSs, because that’s where most of the market is. So, from a focus point of view in our company we are absolutely focused on android and RTOSs.

Okay. Thank you, guys. Excellent presentation.

Thank you.

Thank you. Our next question comes from the line of Robert West from Oak Grove Associates. Your question please.

Thank you for taking the call, Andy.

My pleasure, Bob.

I wanted to begin with going back to the FFE engine; it’s in the ArcticLink 3 S2 LP?

Right.

Will that FFE engine also be in the ArcticLink 4 S3?

Yes, the FFE as we have stated in the presentation is really at the heart of our corner stone strategy. So, virtually every silicon platform that we come out with that’s on our roadmap will contain an FFE.

Let me just expand a little bit on that, Bob.

Okay.

The FFE architecture is the same as we go from generation to generation. What we will do is, we’ll pick elements of the FFE that we should harden to optimize for power, for size, for cost and we’ll get that advantage moving on from generation to generation. But the ultimate architecture itself at a high level remains consistent, because that’s really the only way that we can enable customers the assurance that they can move their IP from generation to generation without ripping up their code.

Okay. Well, as we talk about the partitioning of algorithm functions between hardware gates and software, and also the ArcticLink 3 S2 LP, there is going to -- I presume there is going to have to be a revision of the algorithms for the ArcticLink 3 S2 LP to ship, because some of the code has been moved to hard logic. Can you give us an update on that and when this new LP product will be production ready?

I’ll take that, Bob. So the difference between the S2 and the S2 LP from the FFE point of view is actually the same, in fact it will run the same bit stream as of the S2. So there is no software migration issue between those two. What we did for the S2 LP to achieve the really low power is we worked quite a bit in the inner workings of clocks and working with our foundry partner to make sure that we could optimize the whole chip for power consumption. So again, there’s no software change required at all to use that.

Okay. That’s good. I’m glad to understand that. So, basically it is essentially no change in the two -- the logic of the two products?

No change there. Customer can drop it into an existing PCB if they wanted to use that.

Great. Okay. That certainly simplifies you go to market.

It does. Absolutely.

Yes. And Bob, moving to the S3 it’s important to know that algorithms that the customers use and/or develop for the S2 can be easily ported to the S3. So, there’s not as Brian said in the earlier answer, we wanted to make sure that we had this forward compatibility and backward compatibility of the algorithm so that customers could migrate from one platform to the other.

Okay. One more question in that area. Clearly non-standard hardware has historically been a choke point for many mobile OEMs. How do they view the FFE engine? Is that an impediment in your sales and closing area?

So, Bob let me talk about two different buckets of customers.

Okay.

There’s a bucket that actually want a sensor processing solution and from us they’re going to use a device plus our algorithms, and so they don’t actually every get into the FFE architecture. They’re just buying a solution that counts steps and does context and gestures and at very little power, and that’s more or less a catalogue solution. If you go to customers that actually have their own IP, their own algorithms then obviously their preference as you point out would be to just compile that straight into the architecture and not make any changes. And the fact that we now have the working complier available; we’ve actually addressed that concern. So, now a customer could take standard C which is their typical language of preference throw it into our complier and that will compile it down into the instruction set that we use for the FFE. So now they’re getting to take advantage of the proprietary hardware without making their code proprietary. And we anticipate that tool will also be in conjunction with the S3, so that again they have that forward migration in the future.

So that really, the C complier really mitigates any concern about non-centered hardware?

Yes.

Right. Well think of it this way. If the customer has their algorithm they’re going to have to compile their algorithm using the C-code into go into a basic ARM, MCU anyway. And what we’ve done is we’ve made that transparent. That same process that they would use to compile it down to run on an ARM core would be the same thing that they do to run it all the way down to our FFE.

Okay. Now, one other question there I had. I didn’t understand the discussion of the PDR. While the PDR algorithm, Pedestrian Dead Reckoning algorithm when it comes out from QuickLogic will it be able to operate on the ArcticLink 3 S2 LP or will it require more MIPS?

Yes, we have not -- we didn’t really address PDR in this conference call other than I think that in that S3 slide we did say that PDR is one of those more complex algorithms. I would not expect that PDR would be able to run in an S2 all by itself, but it definitely will run in an S3.

Okay. All right. Well, Andy would you do me a favor of repeating again what you said about the point, the time that we’ll see the next generation ArcticLink 4 S3 be announced. Is that mid summer or would you go through that again?

We said we’ve been consistent, we said mid 2015. So we have always said that we would be sampling customers by midyear and we’re still tacking towards that.

Okay. One other question and I’ll close this all from. Would you expect the ArcticLink 4 S3 to be far enough along that you could have some production late in the year from that product?

We believe that the customer base that we’re targeting with the S3 and the types of design cycles that are associated with those customers and their designs would make a 2015 revenue event highly, highly unlikely.

Okay. So at what point in 2016 would that become more likely?

I would say first half of the year.

Okay. Well, very good. Well, thank you Andy and Brian, and I really appreciate the update and I thought the slide presentation was excellent, and the material increase in engagements was encouraging. So, congratulations on the quarter.

Thank you.

Thank you. End of Q&A

Thank you. This does conclude the question-and-answer session of today's program. I’d like to hand the program back to you Andy Pease for any further remarks.

Thank you. During the next few months we’ll be participating in the following industry events. First at SID Display Week Wearable-Flexible Conference that will be held June 4, at the San Jose Convention Center in San Jose. Our CTO, Dr. Timothy Saxe will be presenting -- participating in a panel discussion on power, The Elephant in the Room. That’s the title of the panel discussion. Secondly, we’ll be part of the Design Automation Conference to be held on June 8, at the Moscone Center in San Francisco. Dr. Saxe will be presenting a paper entitled, Design Challenges for Sensor Hubs in Smartphones and Wearable Devices. And then finally we’ll be part of the Sensor Expo and Conference that will be held from the 9 to 12 of June at the Long Beach Convention Center and details will be included in our upcoming media alerts. I want to thank you all for your continued support, and I look forward to reporting our strategic progress in our next earnings call which is scheduled for Wednesday, July 29, 2015. Thank you.