Q4 2023 GSI Technology Inc Earnings Call
Greetings and thank you for standing by your conference will begin momentarily. We thank you for your patience Nasty. Please remain on the line.
[music].
Okay.
Greetings and thank you for standing by welcome to the GSI Technology's fourth quarter and fiscal 2023 results conference call.
At this time all participants are in a listen only mode. Later, we will conduct a question and answer session at that time, we will provide instructions for those interested in entering the queue for the Q&A.
Before we begin today's call. The company has requested that I read the following safe Harbor statement. The matters discussed in this conference call May include forward looking statements regarding future events and the future performance of GSI technology that involve risks and uncertainties that could cause.
Cause actual results to differ materially from those anticipated. These risks and uncertainties are described in the company's Form 10-K filed with the Securities and Exchange Commission. Additionally.
Additionally, I have been asked to advise that this call conference call is being recorded today may 16th 2023 at the request of GSI technology.
Hosting the call today is Lee lean shoe, the company's chairman President and Chief Executive Officer with him are Douglas Shirley Chief Financial Officer, and did you gave us sad Vice president of sales.
I'd now like to turn the conference over to Mr. Hu. Please go ahead.
Good day, everyone and welcome to all physical fourth quarter and full year 2023 financial results, earning call.
The 2000 and Congress with physical year was filled with many positive developments.
Few partnership.
Progress toward achieving our goals.
We also eat pews setback.
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And forcing delays on several phone with Apu.
We learned a lot during the year about the drill support market excuse.
Give me that one can reasonable pursue with our team.
Given our limited resource.
However, we suddenly have met significant size you can leveraging.
Third party resources to help identify users retailer and the OEM.
This resource.
Prove invaluable in helping us identify opportunities for capturing revenue increasing awareness.
What was the Apu something in those capabilities.
We have also sharpened our focus for Gemini one to leverage our resources.
Prioritize near term opportunities.
Such as synthetic aperture radar oversaw.
In South Carolina, where we have a superior solution.
We understand it's a market that no one.
We can support and help with our offering.
Another phone because application for Jim about one victim injuries.
Apu parking has demonstrated enhanced performance.
And we have dedicated more resource.
In parallel tied to the customers.
Have you put into it.
Nevertheless, our solution.
Our data science team has been busy working on the stuff that's caught you.
One eating pork either.
Critical pivot to other players in the space.
We have met all TD mobile with the first.
Looking ahead.
Allomap.
We will build upon the work we have done we are doing today in future Apu versions to address lost you didn't could you model.
All N coordinator.
So language processing.
Victor search engines, our fundamental COO check GBT architecture.
Refunds, you can close the memory for PDP.
March it into your model.
They were subject to transform us to learn beatings or treating for war.
And produce the types.
It's another reason that Victor search you said Oh well.
Yeah, the focus reputation with the Apu.
Additionally, we are improving our search and AI socs platform to support our go to market.
So how does your forces.
We intend to use this tool to be.
But more potential partnership.
Ultimately our parking indeed.
Integration with recently, we recently launched.
With other open source.
Central as associate engine that uses machine learning okaloosa and pick the search engines.
The increasing size and complexity of enterprise it.
The proliferation of AI ml ethical reasons.
So I've been right equals you can discuss your engines.
Encouraged by the positive reception golf ball Apu parking by several key players we are optimistic about January commodities revenue from different market the physical year 2024.
Both of the Gemini one focus applications I just mentioned.
Stop in the phosphate peso, which we have assessed specific revenue goals that we aim to achieve this fiscal year.
Oh, Yeah, I'll pass them competitive stack as a broker progress.
In the past quarter.
Ill pass them competitive that is designed to offer a parallel development of niche y delivery sheath high performance without compromise either.
Almost all Cola focus applications do not require a component.
We have a beta version and use currently.
<unk> on track to release, a production ready version.
A decent year.
Yeah I'll pass it worked at mid 65 the Apu.
Awesome.
OCC Bill.
Yeah.
I'm excited to run with that.
We are on track to complete the table Jim.
To put this summer.
The first silicon chip, but isn't located in the year 2023.
And with this solution to market in the second half of 2024.
Gemini two cities that were caused by a significant performance enhancements.
The reduced call consumption nascency.
It's a piece of it.
It kind of the future addressable market for the Apu to larger markets such as Asia application.
<unk>.
Yo Yo N.
The first driver assistance system.
It does.
The last one being the vertical we could go after.
With a strategic partner rather than directly.
Yeah.
Gemini two is appeal with the TSMC 16 nanometer process.
The Triple comes it contains six megabytes of associated memory.
Conducted.
Collected 200 megabyte due to the excellent with a 45 filled up by.
Christa.
Both 15 times the memory bandwidth.
They opened a payroll processor for AI.
It is more than four times the processing power at eight times of memory intensity compared with give me that one.
Cause Gemini Apu, you feel with the beef processing, which allows 41st birthday in a format or application.
Any hurdle advantage versus other payroll processes.
Gemini two is a complete package.
A D D off all controller.
External interface for Pcie Gen four <unk> and Pcie Gen four platform.
This integration solution allows Gemini two to beat us equal affordable age applications, while still providing significant processing capabilities.
In simpler terms given that our true combined with different components together, allowing to be use less expensive devices, whereas steel beam powerful enough to handle demand and pass it.
When they work.
So another way given that data center capability to the H J.
Minda computationally intensive application can be done locally.
For example every does.
Did anybody at all.
Most of the robot and the UAE.
Very cool is that.
Right.
Another advocating for Gemini two could be Iot edge application not critical infrastructure.
Well the process that new crowding of reliable fishing operation.
For example, we inbounds to mitigate failure mode that can lead to significant financial losses or operational disruptions.
Given a combination of a high processing power.
B, we memory with tremendous bandwidth and low cost solution provides a best in class solution for application like fast Victoza.
Or you market to them by the proliferation of big.
Dana.
Before Bob and AQR causes.
Recently, we will win the new patent for Gemini towards the in memory.
Which is the basic building block.
Well I'll give them to perform high processing power.
We are thrilled with where lungs that we are currently in very early stage discussion we set top.
Call service provider.
I'll give them towards foundational architecture.
Could deliver performance advantage.
This year, we have seen the disruptive impact of lost you didn't we models.
Understand and get another human language like Chad TVT, Microsoft Bing and Google.
It was a bumpy Appalachia along with your processing continued to be to.
To be push.
Convenient abundant opportunity into the market for Gemini two.
And future version for the Apu.
We believe that we have immunity scratched the surface of the perpetual of lots of them could you Margo.
Conformity impact they can have across numerous confused.
Lodge, along with your models pension memory, because very large believe memories are very.
Logic memory bandwidth.
So still a GPU solution.
<unk> memory to address the high capacity memory requirement.
As the pool memory bandwidth for adequate amendment.
The limitation is going to get worse or larger liquid your models are progressing.
Given our chip architecture has inherently logic memory bandwidth.
Is the nature of my question to pay the <unk> memory for the next generation Gemini trip towards logic memory Ducommun.
Substantial improvement.
Potentially translate into orders of magnitude better performance.
The result will be.
The provision to compete effectively in a rapidly expanding market.
The industry leading competitors.
Our resource and team.
Brokered loan application, where we have a higher probability of a generally revenue okay, Jimmy that one capabilities.
So we bring gemini towards market.
Your mall peers.
And reports and talking to customers and creating new revenue streams.
We are formulating all of them are for the Apu, which holds tremendous tremendous potential.
With the future of heard US Apu has the capability to cater to a much larger large market and the potential opportunity are quite promising.
In parallel with our board of directors.
Activity.
Putting various options to create shareholder value.
We remain fully committed to drive sustained growth in room for innovation in the years ahead.
Thank you for your support and for joining US today, we look forward to updating you on our progress in the coming quarters.
Now I'll turn the call over competing with these operators programs further please.
Please go ahead Didier.
Thank you Lee lean.
Did we have sharpened our focus on a few near term Apu revenue opportunities. In addition, we have strengthened our team with a top data science contractor, whose primary job is to accelerate the development of our plug in solution for the high performance search engine platforms that Lee Lean mentioned, we have also begun work.
With a company that offers custom embedded AI solutions for high speed computing, using Gemini one and Gemini two.
Another critical development to improve our market access for the Apu has been adding distributors. We are pleased to announce that we have added a new distributor for our radiation hard and tolerant SRAM, but also our hardened apu for the European market.
In addition to our partnerships and focus on near term opportunities, we plan to build a platform to enable us to pursue licensing opportunities. This is in the very early stages and we have work to do before we formally approach potential strategic partners.
That said, we have a few preliminary I'm sorry, we have had a few preliminary conversations on determining what is required to integrate Gemini technology into another platform. This would allow us to identify the specific performance benefits for our partners' applications to ensure effective communication of the problem we solve in there.
[noise] system or solution.
We recently download the Gemini one for private companies specializing in SAR satellite technology.
They provide high resolution Earth observation imagery to government and commercial customers for disaster response infrastructure monitoring and national security applications.
The satellites are designed to provide flexible on demand imaging capabilities that customers can access worldwide.
They recently provided the datasets to collect I'm, sorry to conduct comparison benchmarks on the Gemini one and we are commencing the process of running those benchmarks Sars one market. We anticipate that we can generate modest revenue with Gemini one this fiscal year.
GSI was recently awarded a phase one small business innovation research also known as S. P. I R.
S. P. I R is the United States Government program that supports small business R&D projects that could be commercialized for specific government needs.
For this contract we will collaborate with the air and space Force to address the problem of edge computing in space with Gemini one Jim and I, one is already radiation tolerant, making it particularly well suited for space force missions.
This contract is a milestone for GSI technology as it will showcase the apu's capabilities for the military and other government agencies and provide great references for similar applications.
We have submitted other proposals for a direct to phase II project and other Spi our proposals are in the pipeline.
No. We received verbal confirmation just this morning that we have been awarded a research and development contract, which could be worth up to $1 million to $5 million to integrate GSI is next generation Gemini two for air and Space Force mission applications.
This revenue will be recognized as milestones are achieved and a typical timeframe is 18 months to two years.
Once this agreement I'm sorry, once the agreement has been finalized and executed we will issue a press release with full details.
Let me switch now to the customer and product breakdown for the fourth quarter.
In the fourth quarter of fiscal 2023 sales to Nokia were $1 2 million or 21, 8% of net revenues compared to $2 million or 23, 1% of net revenues in the same period, a year ago, and $1 3 million or 20% of net revenues in the prior quarter.
Military defense sales were 44, 2% of fourth quarter shipments compared to 22, 3% of shipments in the comparable period, a year ago, and 26, 2% of shipments in the prior quarter.
Sigma quite sales were 46, 3% of fourth quarter shipments compared to 47, 6% in the fourth quarter of fiscal 2022, and 45, 2% in the prior quarter.
I'd now like to hand, the call over to Doug go ahead, Doug. Thank.
Thank you T D.
I will start with our fourth quarter results summary, followed by a review of the full year fiscal 2023 results.
Just sorry reported a net loss of $4 million or <unk> 16 per diluted share.
Net revenues of $5 4 million for the fourth quarter of fiscal 2023.
Compared to a net loss of $3 million or <unk> per diluted share on net revenues of $8 7 billion for the fourth quarter of fiscal 2022.
And a net loss of four 8 million or 20 cents per diluted share.
Net revenues of $6 4 million for the third quarter of fiscal 2023.
Gross margin was 55, 9% in the fourth quarter of fiscal 2023.
We're at 58, 6% from the prior year period and.
At 57, 5% in the preceding third quarter.
The decrease in gross margin in the fourth quarter of 2023.
It was primarily due to the effect of lower revenue.
On the fixed costs in our cost of goods sold.
Total operating expenses in the fourth quarter of fiscal 2023 or $6 9 billion.
$8 1 million in the fourth quarter of fiscal 2022.
They've put $5 billion in the prior quarter.
Research and development expenses were $5 million compared to $6 5 billion in the prior year period, and $5 5 million from the prior quarter.
Selling general and administrative expenses were $1 9 billion in the quarter ended March 31, 2023, compared to $1 5 billion in the prior year quarter of $3 million in the previous quarter.
Fourth quarter fiscal 2023 operating loss was $3 9 billion.
<unk> operating loss of $2 9 million in the prior year period.
The operating loss of 4 million from the prior quarter.
Fourth quarter fiscal 2023 net loss included interest and other income of $101000 the tax provision of $191000.
$47000 in interest and other expense.
And a tax provision of 21000 for the same period a year ago.
In the preceding third quarter net loss included interest and other income.
$61000 and a tax provision of $84000.
Total fourth quarter pretax stock based compensation expense was $515000 compared to $714000 in the comparable quarter a year ago.
$654000 in the prior quarter.
For the fiscal year ended March 31 2023.
The company reported a net loss of 16 million or <unk> 65 per diluted share.
Net revenues of $29 7 million compared to a net loss of $16 4 million or <unk> 67 per diluted share.
Net revenues of $33 4 million in the fiscal year ended March 31 2022.
Gross margin for fiscal 2023 was 59, 6%.
Compared to 55, 5% from the prior year.
The increase in gross margin was primarily due to product mix.
Total operating expenses were $33 5 million in fiscal 2023, compared to 34 9 million for fiscal 'twenty to 'twenty two.
Research and development expenses were 23 6 million.
We had a 24 7 million for the purpose of the year.
Selling general and administrative expenses were $9 9 million compared to two <unk> compared to $10 2 million in fiscal 2022.
The decline in research and development expenses was primarily due to the cost reduction measures announced by the company in November 2022.
The operating loss for fiscal 2023 was $15 8 million compared to an operating loss of $16 4 million in the prior year.
For fiscal 2023 net loss included interest and other income of $202000.
The tax provision of $372000.
Compared to $60000 interest and other expense.
And a tax benefit of $45000 a year ago.
At March 31 2023.
The company had $30 6 million in cash cash equivalents and short term investments with no long term in the restaurants.
Compared to $44 billion in cash cash equivalents.
And short term investments of $3 3 million and long term investments at March 31 2022.
Working capital was $34 7 million as of March 31, 2023 versus $45 8 million at March 31, 2022 with.
With no debt.
Stockholders' equity as of March 31, 2023 was 51 4 million.
Third to $64 5 million as of the fiscal year ended March 31 2022.
Operator at this point, we will open the call for Q&A.
Thank you.
And if you would like to register for a question. Please press. The one followed by the four on your telephone keypad right now you'll hear us retail prompt to acknowledge your request.
Your question has been answered and you would like to withdraw your registration. Please press the one followed by the three.
And one moment please for the first question.
Yes.
Yeah.
And the first question comes from the line of Raj.
Rajiv Gill with Needham. Please proceed with your question.
Hi, This is Nick Doyle on for Rajeev.
Two questions on Gemini two.
Are all the costs related to the tape out and then the chassis volume production contemplated in your current outlook.
Could you expand on what kind of applications, you're seeing traction with that Gemini Smith.
Specifically anything in Adas, and then using the large language models.
Yes.
Yes in terms of R&D spending yes.
Most of them were spending today is on the Gemini two.
Yeah, we have the hardware team here in Sunnyvale and software team in Israel, and there will be a taped out.
In the first half of fiscal 2024.
Gemini two it'll run probably about two and a half million dollars.
Other than that.
R&D expenses should be similar.
What we've seen in the most recent quarter.
And regarding the applications you cut out when you're talking to Kevin I want our Gemini two.
Gemini two three.
So Gemini too so Gemini two.
As we discussed in the in the conversation before it's something we want to address but we most likely will use a partner to do that and as far as the lawyers language models.
As we discussed we certainly feel that the Gemini technology.
The advantage and the technology is certainly will be applicable there and so whether it's a.
Start with Gemini two or if it's also.
Customized with the Gemini three is to be determined.
Okay that makes sense and then just a quick one did you guys.
Did you say if there is a timeline is there a timeline for the Rad hard roadmap for the product you mentioned in the EU.
The Rad hard in Rad tolerant as Frans are available today.
We have done some testing its boy, it's been at least a year and a half we did the testing.
On the Apu Gemini one specifically came back very favorable but it was the beam was a little bit off that data was limited in the test we could do so we are actually going to do the full complement of radiation testing in the second half of this year. So we have all the data requirements for the folks that.
We'll be setting it into space. So so officially the Apu will be Rad tolerant sometime by the end of this year.
Makes sense. Thank you.
Yeah.
And the second the next question comes from the line of Jeff Bernstein with TD Cowen. Please proceed with your quiet.
Hi, guys just a couple of questions for me just wanted to make sure I heard right.
You you brought on a consultant that's helping target applications for Gemini one is that right.
They're they're specifically helping us.
Right the interfaces for some of the fast fix our search platforms that are out there.
Gotcha.
And then.
You said.
There is a custom embedded AI solutions supplier and that guys can now integrate Jim and I wanted to some high performance compute solutions for clients is that well.
Am I getting that right.
Partially so it's not limited to Gemini one is Jim and I won an Gemini two.
They and they have a multitude of different potential applications ranging from Saar to satellite applications to marine search and rescue Theres a lot of different applications that theyre looking at it for some of the cases there'll be able to use.
Essentially our leader boards, but in many cases, they will be developing their own ultra small boards for some of these applications that our.
Our boards are considered a little too big for for those applications. So so it's it's a multitude of different applications and it will be for both Gemini one in Gemini two.
Gotcha, Okay, and then as far as the large language model kind of applications I think theres two potentially correct me if I'm wrong.
One is just to run queries as opposed to do training and just run queries.
These large matrices.
<unk> quickly and at low power and I guess, the other one has to do with making training more efficient.
But by being able to.
Not we do matrices over and over again as you do new learning as it is that right and and which are we talking about here today, having some oh, yes.
Got it.
It's all primarily pocket will feed through the third squishy influenced pop okay. We are not yet.
We are not on the training path, okay, but.
You can do first efficiently you can tell the 'twenty.
Okay Mike.
Like a week, we can do to yellow shop training or single shots.
Could you mean.
You don't need to spend the time.
In the dataset.
You have a first.
First liquidity come in we don't recognize we can store into a memory chip.
And the second time that similar hasn't come in that you can recognize a right of way there is a very different beast.
No training, okay at the traditional trade and you get the wrong the whole model hope it does it all over again, that's very very time consuming. So if you can do zero shop, and you have a capability to do that then you can say, but thats fairly positive come indefinitely.
That's great. Thank you.
Yeah.
Okay.
And the next question comes from the line of Orin Hirschman.
With a I G H investment partners. Please proceed with your question.
I have got you.
Good though.
One of the things that the Gemini architecture.
In memory processing architecture is very good at which really wasn't a tremendous interest.
When you first introduced Gemini was this natural language processing and oldest son, the whole world has changed and you've got things like at GPT and other similar.
Types of NLP situations, where it's actually exactly fits in to what you do best.
So I guess.
Sounded like from one of the prior comments on the last question that you're actually having code and drivers written to be able to optimize the use of Gemini one and certainly Gemini two is this application because I would think that one of the simple applications, where you could sell a lot of boards.
Simply on the acceleration, where everybody is having difficulty using gpus because they're not this is not where GPU signs on the AI side in terms of the MLP in order to accelerate something like chat GT GPT.
Yeah.
What's the question.
Yes.
What question.
The question is isn't that is in fact is that a priority in terms of what you're working on to be able to introduce your own acceleration board to do it with partners.
Or is it in fact.
Great application it sounds like certainly so far in the call that it's a great application.
For the Gemini Apu.
Okay.
I think I discussed this on on Oh My statement.
The biggest challenge for the larger language Yamato up a pool from first of all you would need a very larger memory.
The second one you did a very a.
High bandwidth memory.
Most of our proved very difficult thing to achieve okay I finger today at the market in the market because nobody has a dissolution of the <unk>.
<unk>.
Okay. So just as I mentioned, we do have.
Oh really.
Very exciting the discussion with.
Larger costco reasonable it either and to see how we can help them all with Gemini.
Foundational Alcatel.
You can see.
How we can help us to move this thing forward. Okay. We already have a very very good memory.
Okay.
That's why I mentioned that you match them and I say, we are 15 times memory bandwidth.
After today's state of the art CPU, okay, or payroll processes, Okay, and that's all you headwind architecture. Okay. So so if you if we can add this one to the high memory capacity.
Ben Yes, the duty of the evolution low body in the market chemical VI, okay. So.
Now we are very excited that we tried to call out as a gift.
These are the very nature, we have and see where we can go from here.
It is there.
Any idea when you will.
The coding to the interface to be able to demo the type of acceleration gains that were talking about with something like a chat GPT or something like that so customers can actually see some type of benchmarking, even with Gemini one and maybe a simulation until Gemini two is rather you Wendell.
Code be ready, but that's what you mentioned youre working on.
Yes, yes, yes.
You know the Oakland they have parking okay. So basically you can you can yeah, you could put your software to parking to the to the amended amendment shouldn't but shouldn't you can.
Now you can utilize our existing model and then through the parking so right now we are working on it okay.
Give me one study and the Gemini two.
Carlo.
At least.
You can extrapolate from the hallway or those are walking a nice profit into the future.
Any ideas when we might see some benchmark in coming months.
Oh Hell of a thing maybe a quarter or two we will have something to tell us do you feel you've got.
Okay, and just a related question, but even more futuristic there's talk of doing something similar to let's say and there are a number of projects and in fact, even you've had a early project with movie I mean.
We need to to be able to show off what you can do in terms of the visuals as well.
And I guess my question is.
Taking that same natural language processing and doing it on a visit level.
Is it beyond belief in terms of the computationally intensive but also well suited for what you guys do.
Is anybody talking about doing anything like that you know obviously you did that early demo. So there's a lot of people but.
Obviously, that's even a step beyond what almost with people have dreamed up today, but.
But the.
You can't do that using current architecture, so any any thoughts on that from a futuristic perspective will that need a gemini three or can that you've been doing in the Gemini two and then one last follow up question.
So you're asking a widow well we want to do in the future generation.
No no no no no specifically, there's a more important part for me is just in terms of incredible you know visual search capabilities. The almost like NLP search capabilities on visuals you did that impressive early demo with movie and you know there's been some others experimental projects when people all of the world.
Starting with new experimental projects on massive amount massive amount of visual data.
Any more thoughts as to.
To be very suitable or uniquely suitable for what you do versus just a new winter just gpus for that matter any other interesting projects like that movie project and I know, it's a bit futuristic, but if anybody has done more in terms of that massive.
Type of visual search comparative visual search user.
Using NLP for visual search using Gemini yes.
Look at <unk> with.
With all just I mentioned that we saw.
With all the.
We are we are.
The center the architectural advantage of Gemini architecture, we look at the one one workload.
We can be a if we have enough memory, we will be 10 times faster than any solution exists today okay.
So that that doesn't why we say hey, we have this inherited and.
The vantage idea, but.
The senior so we don't have enough memory for that.
So if we can combine all the future road map. So we can if we can put enough memory into it.
That's why you are looking for you know, although imagines performed much better than existing solutions.
So on that note a closing question just in terms of the.
What nanometer geometry.
It's being used for.
For Gemini, one Gemini too and what you're thinking for Gemini three.
And obviously that will affect what you just discussed in terms of the ability to attack in memory.
And and that's just if you can kind of tell us tell us more about that and then just one follow up and that's it for me. Thank you so much.
Yeah today, we give me that one is a 28 nanometer.
And the Gemini pool is the 15 known either.
And if we look at the future okay.
Today, it's a fail about GPU is the 40 nanometer.
If we look at the future and then we.
We do find Amit and then we have the <unk> memory.
Because that's the only way you can get the high capacity memory, we said reasonable families is a three D memory.
So if we put in the three D memory with a final meter.
Will it be all of them are going to do better.
Yeah.
So this is the velo up question, but with understanding that in terms of Gemini three knowing the Gemini two is going to be the platform coming up here shortly.
A key platform in terms of your ability to accelerate.
L T.
Again, not not not visual stuff forget about that futuristic question here today.
Terms of accelerating NLP applications, and and chat GTT et cetera.
Gemini two got enough in it so that your competitive slash even superior on that type of application too.
Leading edge GPU optimized GPU like Uh huh.
With that ill GPU have you passed that with Gemini two and the question is can you leapfrog it even further.
That's my last question. Thank you.
They are proofing.
And then when your capacity of <unk> memory bandwidth, Okay. We have a wellington so Eva any waterlow can fit into our chip.
Well it would be the best solution out there.
Many many cases like that.
Okay, even the charge EBITDA it doesn't have to be a humongous dataset.
Okay. So it can be a smaller dealers and but they're not a completely into the all.
All chip.
We will be well.
Number one in the market.
Okay, great. Thank you so much.
And as a reminder to register for a question and first one followed by the four on your telephone keypad. The next question is from the line of Luke Boyne Private Investor. Please proceed with your question.
Hi.
It'll be back.
Well.
It's very exciting.
And development.
Great to hear all the comprehensive lay out there just for you really.
Yeah kind of minor clarifications and and.
Going a little bit broader with the you have a near term potential I'm wondering if you're Amazon web services server offering is capable of fielding.
Yes, they like.
So just a broader range of companies.
Potential end use cases that could more or less played around with your service without having to go through them in more complex processes.
Embedding in the or.
The other integration processes just.
Plug and play and see what you can do for their application, especially thinking about Vectra search.
But also rich data like was mentioned.
First maybe for dense registration.
Things like that I'm wondering how you're seeing the potential to expand.
Amazon Web services or similar offering out there there are other clouds.
And especially how that would relate to an earlier rollout of Gemini two from your own facility around servers all of those clouds.
So we've we've started as we've discussed in the past we started the integration with with the open search.
And so that's ongoing.
It's really and we have already set up our own servers for that we have some here in our Sunnyvale facility seminar Israeli facility and then we also have somewhat of an offsite facility that's directly across the street from AWS Western is directly connected so we have that in place.
With the Gemini one you know over time, obviously, we would migrate dosage Gemini two so those are in place and we do have some saar.
Demos that people can run off those remotely and it's not set up yet to be able to do you know load. Your own data is the data is that sets that are already in there, which you can run and so we're not at the point, yet where you can enter your own data at least got larger datasets. So.
But that is certainly the direction, we're going we're just not quite there yet.
Do you have a timeline on when you'd be able to rollout. This interactive features.
Taxes.
Ah we're shooting for this year.
Some of the some of the examples you brought up is going to be you know we're going to get some help from this data science contractor that we have on board now so it's something we're trying to roll out a second half of this year.
Excellent.
Alright, that's all I have pipeline flooded I appreciate you all.
Thanks Luke.
And the next question is a follow up from the line of Jeff Bernstein with TD count.
Hi, Yeah, just wanted to see if you could give us an up to.
On the Alta.
So our application and what's going on there.
Yeah. So as you recall, we did the debt.
The POC with them and it was a very.
Broad POC.
It could be used for different.
The vehicles are vessels it could be used it a lot of multitude of of heights from 100 meters to you know much much higher obviously into space.
And so the initial program.
Program. They were looking at for it for US was just a just a single.
Laptop I guess you could call it that and are you know they had already been using a GPU and so they're using the GPU still for that program. Its theres a fallen program that they're looking at us for now and so we're going through that process with them. So it it'll be it won't be another POC, because we've already done one but it'll be.
I had kind of a bit of a different project than what we were working on with them, but it will still be under Saar and it'll still be the same algorithm so should be a simple integration.
Okay and then.
Just wondering about.
Waiting to hopefully get some space.
Evidence.
On the Rad hard SRAM and I'm wondering if you guys have any visibility now on when that launch might happen or is it something that we scrubbed.
No it's not.
Apparently scrubbed, who we are.
Follow up.
Yeah.
Yeah, I get your frustration because I'm with you on this one.
So it's not it's not scrubbed there were multiple programs that they are when I say they there was a few as we talked.
Defense contractors, we're using it there have been a couple of the programs that have been scrubbed, but the large ones. We're looking at or have not been scrubbed theres certainly still out there. It's just they've just been pushing out the launch dates and we're just not getting a good.
Feel for exactly when the next launch is gonna be originally they we know they were delayed because they couldnt get some critical components in and now it's just a matter of you know.
Getting them to actually do it. So the answer is we're still optimistic about it. It's just the timing is elusive for us when it's actually going to happen.
And so can the European distributor to kind of do anything.
The Rad hard piece or are they are stuck with just doing rad tolerant until you get that states provenance.
Current approach in Europe .
Oh, no there definitely are going to be going out for everything. So so the folks that we've already said parts to that we're looking to get heritage. It's really just a heritage part and the heritage just base as a signal to the world that says you parse had been having launched into space and they work and so it's really it's an additional check mark.
In a box for a lot of these folks, but it doesn't change the fact that our parts are already internally qualified to work up there. So we know they will work based off of the.
That said the testing that we have done so this European distributor is gonna be finding additional opportunities.
<unk> for Us I mean, the the folks that we were looking to do the the heritage for the for the short term launches those were those were U S based companies.
We have shipped some rad tolerant and at least one rad hard to a European customer, but they were not the ones, we anticipated to get us the initial heritage.
Okay.
Alright.
Right and then any update on some of the scientific applications as you know Weizmann Institute come back for more boards or any.
Analogous type customers in pharma.
Pharma and Med Tech biotech.
Overseas et cetera.
Universities, yes, so weird, where candidly not spending a lot of time on that market the the.
Revenue opportunities for the other markets. We've discussed today are larger we do have two universities that you think yeah. Yeah. There are two different applications for two different universities theyre looking at them for genomics and so they will be running.
There'll be essentially doing the algorithms and doing the right up but personally we are not spending much effort ourselves we've already done a plug ins specifically for the bio via 10 tomorrow and so it just doesn't make sense for us based off of our limited resources to spend more time developing more algorithms for more.
Platform.
The revenue volumes, there just arent as great as they are in other markets we're addressing.
Makes sense makes sense. Thanks.
There are no further questions at this time I will now turn the presentation back to the hosts.
Thank you all for joining US we look forward to speaking with you again, when we do pull off.
For all fiscal first quarter physical 2024 results.
No.
Yeah.
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