Alan Baratz: Yes. So, the starting point for the work with Zapata is really in the life sciences area and identification of new molecules in a variety of different life sciences areas. But that’s really just the initial target. But that having been said, really what that means is that the initial model building and training is not large language model, but more in the area of kind of molecular data, if you like. And in some sense, I think that from there, we’ll likely launch into other corporate applications. There’s nothing that we can see right now that would prevent using this technology for training large language models as well, But the initial go-to-market focus is on corporate machine learning and generative AI. As far as accelerating the timeline, look, how do I want to say this, there’s been experimental work done on investigating how quantum systems might be applied to improving machine learning.
But this has all been basic research and experimental investigation. And in fact, if we put D-Wave aside for a minute and we talk about using quantum computers to generate better samples, because they’re generating them from a quantum distribution rather than a classical distribution, on the current non-D-Wave gate model systems, it can take days to weeks to generate the samples that GPUs can create in seconds. So, it’s always been thought of as very early days in research experimentation. However, with our system, leveraging the Advantage2 processor and frankly, the basic work that we did on the supremacy efforts, we are now able to generate those samples in seconds as well. And that’s really what’s allowing us to make this commercial today.
And with Zapata, we expect to have products to market in a timeframe measured in months, not years.
Richard Shannon: Okay. Very interesting. Thanks for that detail, Alan. My last question here is maybe kind of following up on a prior question as well and it’s really a topic you brought up and discussed at the analyst event a few months ago. And recognize that this is probably too short of a timeframe to expect any change, but always interested in seeing some improvement in the sales cycle. I know that’s a big focus for you. Since the analyst event, have you seen any kind of green shoots or experiences that have helped you or even started to see any real world progress in terms of shortening sales cycles either at the beginning or the end of the process to getting to production revenues?
Alan Baratz: Yeah. So, two things. First of all, and I think I might have mentioned this even at the Analyst Day meeting, but our sales cycles, over the course of the last few years, has shortened. When we started down this path a couple of years ago, we were looking at 12-plus month sales cycles to kind of get the initial engagement in place with the customer, I think the professional services proof of concept engagement. We’re now able to do that fairly regularly on a four to six months’ timeframe. The verticalization strategy, which we only just initiated at the beginning of this year, we think we’ll shorten that a bit further, but we really think it will shorten the back end, which is the transition from proof of concept to production.
But it’s still a little early because we did only launch that at the beginning of this year. That having been said, we have started demand gen and lead gen against the verticalization strategy and we’re already seeing really good results from that with a number of large Global 2000 companies that had not previously been customers expressing interest in what we’re doing.
Richard Shannon: Okay. That sounds like we could see as an expansion of the customer funnel here in terms of the customer count that you’re giving us in the not too distant future. Is that a fair expectation, Alan?
Alan Baratz: I think so.
Richard Shannon: Okay. Excellent. Last quick question here, just on the financial guidance for the year, the EBIT loss here, you haven’t given us any thought process either on revenues or the OpEx and related items to help us kind of put those together here. Anyway you kind of help us think about what kind of revenue growth you’re expecting for this year? You’ve been fairly tight on OpEx here. I don’t know if you’re expecting to open the funnel up at all as you trying to drive faster growth. But just any general expectations you can help us in your thought process for the year that would be great. That’s all for me.
Alan Baratz: John, do you want to take that?
John Markovich: Richard, I can give you some guidance on the operating expenses. So, the area that we will invest in this year in OpEx is go-to-market. And we’re focused on a relatively significant increase in go-to-market investment from last year. And we anticipate that our year-over-year G&A will actually be down between 2024 and 2023, principally due to a lot of the non-recurring costs associated with the going public process last year and R&D being relatively flat to slightly up on a year-over-year basis. Does that answer your question, Richard?
Richard Shannon: Perfect. Thank you, guys.
John Markovich: You’re welcome.
Richard Shannon: This only answers part of the OpEx question. I mean, the essence of the question is really about revenue growth. I’m assuming since you didn’t put it in the press release, you’re probably not prepared to talk about that. So, if you have any thoughts there, that’s kind of what I was looking for, John.
John Markovich: You’re correct. We have not provided revenue guidance.
Richard Shannon: Okay. That’s all for me, guys. Thank you.
Operator: Thank you. Our next question comes from Quinn Bolton with Needham & Company. Please go ahead.
