Dinakar Munagala is building AI for the physical world

A doctor in Southeast Asia had a problem. Certain cancerous cells are hard to spot in retina images, and he had no background in AI. So he built the tool himself. Using AI Studio, the code-free software platform Blaize built, he trained a computer vision model that identifies the cells automatically.

"This is actually pretty transformational," Blaize co-founder and CEO Dinakar Munagala said on the CEO.com Podcast. "Somebody who's not even from an AI background was able to build a solution and deploy it. So that, to me, is a very powerful and democratized version of AI."

That story is the whole company in one anecdote. Blaize makes chips and software for AI outside the data center, which is where nearly all of the industry's money and attention have gone.

"There's the data center part of it, which GPUs and Nvidia are creating massive trillion-dollar valuations," Munagala said. "And then there's outside the data center, everything to do with the real physical world. We're talking about farms, factories, smart cities, education, healthcare, and defense."

Blaize processors go into security cameras, drones, industrial robots, and defense systems. The design premise, set at the founding, is that running AI models in the field at low power and low latency requires a chip built for that job rather than a data center GPU adapted to it.

Munagala spent 12 years at Intel in graphics processor microarchitecture and design, on programs that included the company's first integrated CPU and GPU product family. He studied electrical and computer engineering at Osmania University in India and at Purdue. He left in 2011 to start Blaize with two fellow Intel engineers.

DENSO, the Japanese automotive supplier, tested the technology and then invested. Mercedes-Benz, Magna, and Samsung followed. By the time Blaize went public on the Nasdaq in January 2025, the first AI chip startup to do so that year, it had raised more than $330 million. Chips are expensive. In 2023, the company lost $87.5 million on $3.8 million in revenue.

Munagala divides his week by function. One day for revenue and customers. One for product and innovation. One for his direct reports. One for investors. The company has more than 200 employees across California, North Carolina, India, the United Kingdom, and the United Arab Emirates, and it worked across time zones long before the pandemic forced the question on everyone else.

"We were actually one of the first customers of Zoom," he said. "When Zoom was less than a 10-member company, we adopted Zoom into our workflows."

The public markets have been rough. In second quarter 2026 results reported in August, revenue came in at $12 million for the quarter and $14.7 million for the first half of the year, up 390 percent from a year earlier. Blaize also cut its full-year revenue outlook to between $40 million and $43 million, citing engagements that did not convert into orders and higher memory pricing, and said the revised forecast rests on binding, non-cancellable purchase orders rather than deals still in progress. The prior outlook, reaffirmed as recently as May, had been $130 million, and the stock lost about half its value the day after the report. Against that, the company points to a binding agreement covering 2,000 servers, worth about $70 million at current memory pricing, with roughly $50 million of it expected to be fulfilled in 2027, plus a first purchase order from Europe for several thousand units.

Munagala has seen technology waves take longer than promised. AI itself did.

"It's been around for 30, 40, 50 years," he said. "What is making AI more successful in recent times is computing." He compares what comes next to the PC revolution, a productivity gain that eliminated some jobs and created others, and he does not pretend the technology is risk-free. "As with any technology, any new technology, there's bound to be controversy, and there's bound to be potentially the risk of being utilized negatively," he said. "But then again, what we look at, hey, does the good outweigh the bad? And that's what I keep thinking about as we build our technology, and we just try to focus on the good."

Asked who gave him a chance, Munagala went back to the beginning. "There's a mentor figure who was a chip guru investor. He backed us right when we were in garage mode, and then the rest is history," he said. "Even today, I talk to my first investors quite often, and I am so thankful to all of them that they helped us get here."

00:00:00 Introduction to Blaize and Physical World AI
00:01:24 Why AI Is Gaining Momentum Now
00:03:50 AI's Impact on Jobs and Productivity
00:04:03 Advice for CEOs on Implementing AI
00:06:50 A Day in the Life of Blaize's CEO
00:08:03 Leadership and Managing a Hybrid Workforce
00:10:02 Democratizing AI With No-Code Tools
00:12:31 Downsides and Risks of AI
00:13:50 Reading Habits and Staying Informed
00:15:06 Navigating Tariffs and Economic Uncertainty
00:15:59 Mentors Who Gave Dinakar His Chance

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What<00:03:50.980> advice<00:03:51.365> would<00:03:51.478> you<00:03:51.606> have<00:03:51.863> for<00:03:52.087> other<00:03:52.344> leaders<00:03:52.906> or<00:03:53.067> other<00:03:53.227> CEOs<00:03:54.351> around<00:03:55.555> how<00:03:55.715> to<00:03:55.796> be<00:03:55.956> thinking<00:03:56.438> about<00:03:56.823> AI,<00:03:57.481> how<00:03:57.642> to<00:03:57.802> implement<00:03:58.203> it<00:03:58.268> within<00:03:58.524> their<00:03:58.749> company,<00:03:59.969> and<00:04:00.114> then<00:04:00.290> how<00:04:00.387> to<00:04:00.531> implement<00:04:00.868> it<00:04:00.932> within<00:04:01.253> their<00:04:01.494> products,<00:04:02.072> even<00:04:02.361> their<00:04:02.457> product<00:04:02.923> offerings?

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Because<00:04:03.404> I<00:04:03.501> talk<00:04:03.661> to<00:04:03.758> a<00:04:03.774> lot<00:04:03.998> of<00:04:04.063> CEOs,<00:04:04.544> obviously,<00:04:04.929> through<00:04:05.026> this,<00:04:06.149> and<00:04:06.246> a<00:04:06.374> lot<00:04:06.535> of<00:04:06.631> them<00:04:06.856> use<00:04:06.968> it<00:04:07.112> internally,<00:04:07.915> right,<00:04:08.637> to<00:04:08.782> help<00:04:09.103> kind<00:04:09.264> of<00:04:09.922> automate<00:04:10.307> workflows<00:04:11.752> and<00:04:12.089> things<00:04:12.313> like<00:04:12.490> that.

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But<00:04:13.839> many<00:04:14.176> are<00:04:14.401> like,<00:04:14.594> I<00:04:14.610> don't<00:04:14.754> know<00:04:15.043> how<00:04:15.220> to<00:04:16.489> productize<00:04:17.292> this<00:04:18.015> or<00:04:18.512> put<00:04:18.657> it<00:04:18.753> inside<00:04:19.075> my<00:04:19.235> product,<00:04:20.102> which<00:04:20.215> is<00:04:20.343> kind<00:04:20.504> of<00:04:20.600> this<00:04:20.761> interesting—<00:04:21.724> I'm<00:04:21.965> sure<00:04:22.126> that'll<00:04:22.367> come.

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But<00:04:23.314> how<00:04:23.427> do<00:04:23.555> you<00:04:23.636> think<00:04:23.748> about<00:04:24.037> that?

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I<00:04:24.214> mean,<00:04:24.358> obviously<00:04:24.937> your<00:04:25.097> company<00:04:25.643> literally<00:04:26.061> does<00:04:26.382> this.

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So<00:04:28.936> how<00:04:29.096> would<00:04:29.257> you<00:04:30.156> give<00:04:30.397> that?

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What<00:04:31.377> advice<00:04:31.682> would<00:04:31.826> you<00:04:31.907> have<00:04:32.164> for<00:04:32.324> other<00:04:32.485> CEOs?

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So<00:04:33.770> I<00:04:33.850> guess<00:04:34.235> adopting<00:04:35.456> AI<00:04:36.002> is<00:04:36.885> already<00:04:37.126> happening<00:04:37.528> in<00:04:37.608> almost<00:04:37.881> every<00:04:38.090> company,<00:04:38.443> right?

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Thanks<00:04:38.909> to<00:04:39.166> Microsoft<00:04:39.696> Copilot,<00:04:40.290> et<00:04:40.419> cetera,<00:04:40.820> it<00:04:40.933> is<00:04:41.077> integrated<00:04:41.703> into<00:04:41.944> your<00:04:42.685> into<00:04:42.830> your<00:04:42.992> computer,<00:04:43.492> into<00:04:43.637> your<00:04:43.734> software,<00:04:44.379> right?

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So,<00:04:45.428> how<00:04:45.525> much<00:04:45.815> you<00:04:46.380> use<00:04:46.638> it,<00:04:46.880> et<00:04:46.961> cetera,<00:04:47.364> is<00:04:47.751> of<00:04:48.090> course<00:04:48.397> case<00:04:48.639> by<00:04:48.736> case.

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Things<00:04:50.685> which<00:04:50.846> are<00:04:50.927> obvious,<00:04:51.556> if<00:04:51.895> you<00:04:52.040> have<00:04:52.202> a<00:04:52.315> Zoom<00:04:52.782> video<00:04:53.089> call<00:04:53.412> now,<00:04:54.460> there<00:04:55.509> are<00:04:55.606> note-takers,<00:04:56.235> et<00:04:56.332> cetera,<00:04:57.300> right?

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Instead<00:04:57.848> of<00:04:57.945> actually<00:04:58.268> having<00:04:58.526> a<00:04:58.832> meeting<00:04:59.397> scribe,<00:04:59.865> our<00:04:59.930> company<00:05:00.203> actually<00:05:00.606> practices<00:05:01.153> it<00:05:01.314> throughout,<00:05:02.296> right?

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Almost<00:05:03.279> every<00:05:03.424> meeting,<00:05:03.971> there's<00:05:04.953> a<00:05:04.969> report<00:05:05.340> generated<00:05:05.903> and<00:05:06.080> with<00:05:06.241> action<00:05:06.563> items<00:05:07.030> and<00:05:07.127> so<00:05:07.272> on<00:05:07.449> and<00:05:07.530> so<00:05:07.691> forth.

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So,<00:05:08.834> it<00:05:09.220> is<00:05:09.397> a<00:05:09.430> productivity<00:05:10.096> gain.

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We're<00:05:11.373> also<00:05:11.614> dabbling<00:05:12.094> with<00:05:12.319> it<00:05:13.233> at<00:05:13.377> other<00:05:13.601> places,<00:05:14.739> like<00:05:15.605> they<00:05:15.926> call<00:05:16.407> this<00:05:16.823> wipe<00:05:17.144> coding<00:05:17.721> or<00:05:17.945> automatic<00:05:18.346> code<00:05:18.571> generation,<00:05:19.212> right?

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Having<00:05:20.574> AI<00:05:20.831> generate<00:05:21.232> certain<00:05:21.696> code,<00:05:21.969> et<00:05:22.049> cetera.

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And<00:05:24.518> the<00:05:24.662> core<00:05:24.903> of<00:05:25.143> our<00:05:25.303> innovation<00:05:25.704> though<00:05:25.816> in<00:05:25.944> the<00:05:26.041> chip<00:05:26.265> design<00:05:26.602> part<00:05:26.778> of<00:05:26.922> it,<00:05:27.724> thus<00:05:27.964> far<00:05:28.285> we've<00:05:28.461> not<00:05:28.910> used<00:05:29.311> AI<00:05:29.487> directly,<00:05:30.529> but<00:05:30.754> that's<00:05:30.930> something<00:05:31.250> it's<00:05:31.411> in<00:05:31.812> exploratory<00:05:32.709> stages.

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We<00:05:34.216> do<00:05:34.360> have<00:05:34.601> to<00:05:35.338> wait<00:05:35.563> for<00:05:35.739> the<00:05:35.979> chip<00:05:36.156> design<00:05:36.621> tools,<00:05:37.021> the<00:05:37.101> EDA<00:05:37.406> companies<00:05:37.823> to<00:05:37.967> adopt<00:05:38.304> it,<00:05:39.009> right?

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And<00:05:39.266> make<00:05:39.506> it<00:05:40.131> widely<00:05:40.388> available<00:05:40.788> for<00:05:41.125> somebody<00:05:41.494> like<00:05:41.750> us<00:05:42.055> to<00:05:42.440> go<00:05:42.569> and<00:05:42.661> do<00:05:42.771> it.

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Coming<00:05:44.933> to<00:05:45.013> advice,<00:05:45.416> I<00:05:45.480> guess<00:05:45.674> I<00:05:45.803> think,<00:05:46.930> you<00:05:47.027> know,<00:05:47.107> I<00:05:47.188> can<00:05:48.009> say<00:05:48.315> this,<00:05:48.622> that<00:05:49.926> the<00:05:50.071> low-hanging<00:05:50.554> fruit<00:05:50.877> for<00:05:51.038> us<00:05:51.682> is<00:05:52.407> cost<00:05:52.649> savings<00:05:53.293> across<00:05:53.872> wherever,<00:05:54.740> you<00:05:54.820> know,<00:05:54.917> using<00:05:55.382> AI<00:05:56.427> in,<00:05:57.230> you<00:05:57.262> know,<00:05:57.551> potentially<00:05:58.033> you<00:05:58.194> could<00:05:58.788> save<00:05:59.560> costs<00:05:59.897> up<00:06:00.058> to<00:06:00.234> 20-30%,<00:06:01.407> right?

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Depending<00:06:01.809> on<00:06:01.969> the<00:06:02.050> size<00:06:02.323> of<00:06:02.467> your<00:06:02.708> company<00:06:03.190> and<00:06:03.351> the<00:06:03.480> nature<00:06:03.657> of<00:06:03.754> the<00:06:03.835> work.

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So<00:06:04.948> that's<00:06:05.432> where<00:06:05.594> I<00:06:05.610> see<00:06:05.836> the<00:06:05.916> low-hanging<00:06:06.320> fruit<00:06:06.659> immediately<00:06:07.207> happening.

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Everything<00:06:08.531> about<00:06:08.757> documentation,<00:06:10.048> et<00:06:10.112> cetera,<00:06:10.387> et<00:06:10.451> cetera,<00:06:10.855> right?

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All<00:06:11.178> of<00:06:11.339> these,<00:06:12.506> is<00:06:12.682> the<00:06:12.779> natural<00:06:13.163> thing.

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And,<00:06:15.552> you<00:06:15.632> know,<00:06:16.289> I<00:06:16.369> think<00:06:16.530> people<00:06:16.770> do<00:06:16.914> need<00:06:17.091> to<00:06:17.171> get—<00:06:18.918> so<00:06:19.030> right<00:06:19.239> now<00:06:19.319> all<00:06:19.399> of<00:06:19.559> the<00:06:19.656> AI<00:06:19.736> is<00:06:19.896> happening<00:06:21.162> on<00:06:22.044> generic<00:06:22.477> and<00:06:22.653> cloud.

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So<00:06:23.102> people,<00:06:23.503> of<00:06:23.647> course,<00:06:23.888> don't<00:06:24.048> want<00:06:24.224> to<00:06:24.304> share<00:06:24.625> their<00:06:24.785> data<00:06:25.170> there.

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So<00:06:26.452> that's<00:06:27.029> one<00:06:27.190> of<00:06:27.334> the<00:06:27.510> roadblocks.

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So,<00:06:29.995> but<00:06:30.219> a<00:06:30.235> way<00:06:30.396> to<00:06:30.540> solve<00:06:30.861> it,<00:06:31.261> and<00:06:31.358> companies<00:06:31.822> are<00:06:32.400> going<00:06:32.704> at<00:06:32.864> it<00:06:33.041> in<00:06:33.121> terms<00:06:33.506> of<00:06:33.826> on-prem<00:06:34.307> clouds<00:06:34.948> and<00:06:35.109> how<00:06:35.590> you<00:06:35.686> can<00:06:35.830> actually<00:06:36.968> help<00:06:37.930> end<00:06:38.090> customers<00:06:38.731> keep<00:06:38.972> their<00:06:39.068> data,<00:06:39.773> but<00:06:39.918> also<00:06:40.399> use<00:06:41.040> AI.

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I<00:06:42.258> think<00:06:42.483> as<00:06:42.723> that<00:06:42.883> happens<00:06:43.284> more<00:06:43.460> and<00:06:43.508> more,<00:06:44.166> there'll<00:06:44.503> be<00:06:44.583> more<00:06:44.824> adoption,<00:06:45.751> I<00:06:45.771> think.

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Yeah,<00:06:46.830> yeah,<00:06:46.990> I<00:06:47.151> think,<00:06:47.456> I<00:06:47.472> think<00:06:47.632> that<00:06:47.793> makes<00:06:48.017> sense.

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I<00:06:48.740> think,<00:06:48.900> I<00:06:49.060> think,<00:06:49.317> I<00:06:49.462> think<00:06:49.622> you're<00:06:49.702> right<00:06:49.959> there.

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How<00:06:50.922> do<00:06:51.067> you<00:06:51.163> think<00:06:51.468> about—<00:06:51.708> well,<00:06:51.949> well,<00:06:52.190> first<00:06:52.527> give<00:06:52.607> me<00:06:52.752> a<00:06:52.768> sense<00:06:53.073> for<00:06:53.169> like<00:06:53.410> what<00:06:53.506> a<00:06:53.570> typical<00:06:54.051> day<00:06:54.196> looks<00:06:54.372> like<00:06:54.613> for<00:06:54.693> you<00:06:55.239> as<00:06:55.335> CEO<00:06:55.720> of<00:06:55.881> Blaze.

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So<00:06:57.101> yeah,<00:06:57.422> um,<00:06:57.743> it's<00:06:57.903> a<00:06:57.967> pretty<00:06:58.160> interesting<00:06:58.689> thing.

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I<00:06:58.882> mean,<00:06:59.075> I'm<00:06:59.251> just<00:06:59.412> coming<00:06:59.668> off,<00:06:59.973> uh,<00:07:00.310> a<00:07:00.391> couple<00:07:00.631> of,<00:07:01.177> uh,<00:07:01.434> board<00:07:01.674> meetings<00:07:02.156> followed<00:07:02.477> by<00:07:02.814> a<00:07:03.022> couple<00:07:03.263> of<00:07:03.520> other<00:07:03.745> meetings.

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But<00:07:04.162> a<00:07:04.258> typical<00:07:04.579> day<00:07:04.788> is,<00:07:05.109> uh,<00:07:05.365> more<00:07:05.510> like<00:07:05.751> a,<00:07:06.954> uh,<00:07:07.195> I,<00:07:07.291> I,<00:07:07.516> I<00:07:07.612> try<00:07:07.837> to<00:07:08.254> actually<00:07:08.960> divide<00:07:09.297> my<00:07:09.458> week<00:07:09.843> into<00:07:10.806> a<00:07:10.918> day<00:07:11.383> I<00:07:11.560> spend<00:07:12.009> on<00:07:12.971> everything<00:07:14.014> related<00:07:14.511> to<00:07:15.778> revenue<00:07:16.340> and<00:07:16.500> customers,<00:07:17.864> then<00:07:18.265> a<00:07:18.601> day<00:07:18.682> related<00:07:19.259> to<00:07:19.564> product,<00:07:20.189> right?

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Product<00:07:20.703> and<00:07:20.847> tech<00:07:21.088> and<00:07:21.232> innovation.

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And<00:07:23.237> a<00:07:23.574> day<00:07:23.799> related<00:07:24.841> to<00:07:25.018> talking<00:07:26.445> to<00:07:26.606> all<00:07:26.702> my<00:07:27.263> team<00:07:27.424> members,<00:07:27.969> right?

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My<00:07:28.306> direct<00:07:28.546> reports,<00:07:29.268> et<00:07:29.349> cetera.

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And<00:07:31.033> then<00:07:31.658> a<00:07:31.739> day<00:07:32.460> specifically<00:07:33.760> to<00:07:33.904> everything<00:07:34.401> investors<00:07:34.899> and<00:07:35.043> outbound.

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So,<00:07:36.390> I<00:07:36.487> try<00:07:36.647> to<00:07:36.888> keep<00:07:37.529> them<00:07:37.690> that<00:07:37.850> way.

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Largely.

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Of<00:07:38.973> course,<00:07:39.134> things<00:07:39.374> do<00:07:39.535> get,<00:07:39.840> uh,<00:07:40.642> uh,<00:07:41.605> you<00:07:41.717> know,<00:07:42.103> disturbed<00:07:42.440> if<00:07:42.568> something<00:07:43.065> else<00:07:43.226> comes<00:07:43.451> up.

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Hey,<00:07:43.788> this<00:07:43.932> has<00:07:44.093> to<00:07:44.173> happen<00:07:45.296> on<00:07:45.409> a<00:07:45.457> certain<00:07:45.778> day,<00:07:45.874> we<00:07:45.954> prioritize.

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But<00:07:47.944> by<00:07:48.057> and<00:07:48.185> large,<00:07:48.682> trying<00:07:48.939> to<00:07:49.148> keep<00:07:49.389> it<00:07:49.742> such<00:07:50.047> a<00:07:50.111> way<00:07:50.448> so<00:07:50.624> that,<00:07:50.929> uh,<00:07:51.170> I<00:07:51.250> do<00:07:51.475> get<00:07:51.892> quality<00:07:52.374> time,<00:07:53.080> uh,<00:07:53.417> with<00:07:53.722> all<00:07:54.059> aspects<00:07:54.524> of<00:07:54.781> the<00:07:54.941> business.

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I<00:07:55.744> would<00:07:55.840> say,<00:07:56.851> uh,<00:07:57.092> that's<00:07:57.429> how<00:07:57.493> I<00:07:57.525> approach<00:07:57.846> it.

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How<00:07:58.488> do<00:07:58.536> you<00:07:58.697> think<00:07:58.873> about<00:07:59.178> leadership<00:08:00.061> and<00:08:01.200> motivating<00:08:01.762> your<00:08:01.907> employees<00:08:02.484> in<00:08:02.565> this?

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And<00:08:03.206> where<00:08:03.367> have<00:08:03.511> you<00:08:03.672> landed<00:08:03.945> on<00:08:04.073> this<00:08:04.234> whole<00:08:04.892> everybody<00:08:05.277> in<00:08:05.357> the<00:08:05.517> office,<00:08:06.095> to<00:08:06.256> work<00:08:06.480> from<00:08:06.721> home,<00:08:07.299> to<00:08:07.459> hybrid<00:08:08.085> and<00:08:08.165> all<00:08:08.342> that<00:08:08.502> type<00:08:08.743> of<00:08:08.807> stuff,<00:08:09.224> and<00:08:09.770> just<00:08:10.251> overall<00:08:10.524> managing<00:08:11.053> a<00:08:11.134> culture?

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Sure.

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We<00:08:14.118> have<00:08:14.263> always,<00:08:14.905> actually<00:08:15.306> even<00:08:15.546> pre-COVID,<00:08:16.926> the<00:08:17.392> team,<00:08:18.371> we<00:08:18.515> are<00:08:18.547> a<00:08:18.611> global<00:08:19.173> company.

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We<00:08:19.735> have<00:08:19.959> teams<00:08:20.360> in<00:08:21.420> India,<00:08:22.126> in<00:08:22.286> UK,<00:08:23.345> different<00:08:23.746> parts<00:08:24.067> of<00:08:24.163> the<00:08:24.292> US,<00:08:24.549> 3<00:08:24.709> different<00:08:25.030> places<00:08:25.431> in<00:08:25.495> the<00:08:25.576> US.

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So,<00:08:27.341> we<00:08:27.581> are<00:08:27.983> quite<00:08:28.303> a<00:08:29.186> hybrid<00:08:29.908> company<00:08:30.245> in<00:08:30.325> a<00:08:30.390> way.

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We<00:08:31.449> do<00:08:31.593> have<00:08:31.770> offices,<00:08:32.812> but<00:08:34.000> realized<00:08:34.401> that<00:08:34.898> people<00:08:35.155> have<00:08:35.299> to<00:08:35.443> work<00:08:35.764> at<00:08:36.326> different<00:08:36.582> time<00:08:36.823> zones,<00:08:37.208> right?

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A<00:08:37.866> lot<00:08:38.042> of<00:08:38.187> development<00:08:38.764> in<00:08:38.909> India<00:08:39.935> and<00:08:41.074> the<00:08:41.235> architects<00:08:41.780> are<00:08:41.940> here<00:08:42.133> in<00:08:42.261> the<00:08:42.342> US.

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So,<00:08:44.748> a<00:08:45.069> lot<00:08:45.245> of<00:08:46.368> meetings<00:08:46.753> that<00:08:46.914> happen<00:08:47.491> late<00:08:47.732> nights,<00:08:48.133> early<00:08:48.373> mornings,<00:08:49.079> around<00:08:49.512> the<00:08:49.641> clock.

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So,<00:08:51.582> we've<00:08:51.903> been<00:08:52.288> quite<00:08:52.946> hybrid<00:08:53.587> even<00:08:53.908> before.

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We<00:08:54.550> were<00:08:54.694> actually<00:08:54.951> one<00:08:55.095> of<00:08:55.256> the,<00:08:56.539> I<00:08:56.555> would<00:08:56.812> say,<00:08:57.020> the<00:08:57.100> first<00:08:57.758> customers<00:08:58.336> of<00:08:58.480> Zoom<00:08:59.668> when<00:08:59.781> Zoom<00:09:00.006> was<00:09:00.873> less<00:09:01.034> than<00:09:01.146> a<00:09:01.210> 10-member<00:09:01.612> company,<00:09:02.014> we<00:09:02.158> adopted<00:09:02.560> Zoom<00:09:02.817> into<00:09:03.283> our<00:09:03.379> workflows.

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So,<00:09:05.789> we've<00:09:06.174> kept<00:09:06.351> it<00:09:06.431> that<00:09:06.978> way.

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That's<00:09:08.520> why<00:09:08.616> when<00:09:08.841> COVID<00:09:09.082> actually<00:09:09.387> happened,<00:09:10.287> we<00:09:10.367> were<00:09:10.512> efficient.

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We<00:09:11.331> already<00:09:11.636> knew<00:09:12.134> how<00:09:12.696> things<00:09:12.937> would<00:09:13.098> work<00:09:13.805> and<00:09:14.624> we<00:09:14.705> just<00:09:15.588> were<00:09:16.006> prepared<00:09:16.311> for<00:09:16.472> it.

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That<00:09:17.596> said,<00:09:19.026> some<00:09:19.203> of<00:09:19.347> the<00:09:20.327> activity<00:09:20.809> does<00:09:21.050> involve<00:09:22.094> whiteboarding<00:09:23.315> solutions<00:09:24.086> and<00:09:24.247> going<00:09:24.440> into<00:09:24.648> the<00:09:24.729> office<00:09:25.066> and<00:09:25.452> discussing.

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So,<00:09:26.175> that<00:09:26.496> also<00:09:27.298> is<00:09:27.458> there.

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So,<00:09:28.597> we<00:09:28.917> just<00:09:29.078> make<00:09:29.318> it<00:09:29.864> happen<00:09:30.361> depending<00:09:30.762> on<00:09:31.724> the<00:09:31.884> kind<00:09:32.205> of<00:09:33.087> interaction<00:09:33.632> meeting,<00:09:34.530> what<00:09:34.691> is<00:09:34.835> needed,<00:09:35.653> whether<00:09:35.958> it's<00:09:36.134> a<00:09:36.198> virtual<00:09:36.519> or<00:09:36.615> physical.

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And<00:09:37.481> then<00:09:38.444> cross-border,<00:09:38.877> as<00:09:38.957> I<00:09:39.021> said,<00:09:39.245> there's<00:09:39.743> quite<00:09:39.887> a<00:09:39.919> bit<00:09:40.063> of<00:09:40.208> travel<00:09:41.090> within<00:09:41.410> the<00:09:41.571> company,<00:09:41.908> people<00:09:42.613> visiting<00:09:43.014> different<00:09:43.271> sites<00:09:43.592> as<00:09:43.752> needed<00:09:44.859> to<00:09:44.955> solve,<00:09:45.917> let's<00:09:46.719> say,<00:09:46.799> technical<00:09:47.184> issues,<00:09:48.162> actually<00:09:48.403> the<00:09:48.483> physical<00:09:48.868> hardware,<00:09:49.205> bringing<00:09:49.509> up<00:09:49.686> boards<00:09:50.472> and<00:09:51.306> so<00:09:51.514> on<00:09:51.546> and<00:09:51.674> so<00:09:51.835> forth.

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So,<00:09:53.135> it's<00:09:53.359> a<00:09:53.391> mixture<00:09:54.081> of<00:09:54.242> all<00:09:54.322> of<00:09:54.418> that.

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Yeah.

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And<00:09:56.489> you've<00:09:56.601> talked<00:09:56.890> a<00:09:56.906> lot<00:09:57.082> about<00:09:57.484> democratizing<00:09:58.655> AI<00:10:00.035> and<00:10:00.116> making<00:10:00.437> it<00:10:00.517> accessible<00:10:01.159> to<00:10:01.303> everyone.

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What<00:10:03.037> does<00:10:03.149> that<00:10:03.309> look<00:10:03.486> like?

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What<00:10:03.887> exactly<00:10:04.272> does<00:10:04.433> that<00:10:04.609> mean?

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One<00:10:05.973> of<00:10:06.118> the<00:10:06.294> way<00:10:06.519> to<00:10:06.615> look<00:10:06.776> at<00:10:07.402> AI<00:10:07.899> is<00:10:08.605> it's<00:10:09.905> a<00:10:09.970> super<00:10:10.387> powerful<00:10:11.109> innovation<00:10:12.377> and<00:10:12.794> it<00:10:12.955> can<00:10:13.195> be<00:10:14.174> impacting<00:10:15.201> everybody,<00:10:15.667> every<00:10:16.549> business,<00:10:16.886> every<00:10:18.074> person.

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By<00:10:20.755> making<00:10:21.220> the<00:10:21.525> tools<00:10:21.943> and<00:10:22.039> the<00:10:22.168> compute<00:10:22.569> power<00:10:23.693> and<00:10:24.030> the<00:10:24.110> technology<00:10:24.592> so<00:10:24.977> easy<00:10:25.234> to<00:10:25.378> use<00:10:25.635> and<00:10:25.715> deploy<00:10:27.000> that<00:10:27.417> somebody<00:10:27.883> who's<00:10:28.220> not<00:10:28.669> a<00:10:28.766> data<00:10:28.942> scientist<00:10:29.873> can<00:10:30.034> actually<00:10:31.093> deploy<00:10:31.559> AI,<00:10:32.217> I<00:10:32.297> think<00:10:32.699> that<00:10:32.940> is<00:10:33.084> how<00:10:33.646> simplified<00:10:34.240> it<00:10:34.368> should<00:10:34.465> become,<00:10:34.866> just<00:10:35.091> like<00:10:35.893> your<00:10:36.937> personal<00:10:37.194> computing<00:10:37.531> history,<00:10:37.932> right?

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Imagine<00:10:39.441> a<00:10:39.522> doctor<00:10:39.987> who—<00:10:40.244> and<00:10:40.292> this<00:10:40.501> is<00:10:40.645> a<00:10:40.661> real<00:10:40.870> example<00:10:41.287> at<00:10:41.432> Blaze—<00:10:42.251> a<00:10:42.491> doctor<00:10:44.081> in<00:10:44.418> Southeast<00:10:44.964> Asia<00:10:46.183> was<00:10:46.408> looking<00:10:46.729> at<00:10:46.825> retina<00:10:47.306> images.

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And<00:10:49.456> it's<00:10:49.793> hard<00:10:50.130> to<00:10:50.595> actually<00:10:50.916> identify<00:10:51.477> a<00:10:51.542> certain<00:10:52.520> kind<00:10:52.905> of<00:10:54.108> cancerous<00:10:54.638> cells.

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Applying<00:10:56.194> AI<00:10:56.595> tools<00:10:57.638> and<00:10:58.520> our<00:10:59.017> AI<00:10:59.194> studio,<00:10:59.659> we've<00:11:00.221> developed<00:11:00.525> a<00:11:00.622> code-free<00:11:01.183> platform<00:11:01.584> called<00:11:01.745> Studio.

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So<00:11:03.590> we<00:11:04.312> have<00:11:04.472> our<00:11:04.616> chips<00:11:04.873> and<00:11:04.953> we<00:11:05.049> have<00:11:05.130> our<00:11:05.274> software.

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The<00:11:05.900> software<00:11:06.253> is<00:11:06.381> intended<00:11:06.782> to<00:11:06.862> make<00:11:07.055> the<00:11:07.135> life<00:11:07.504> of<00:11:09.124> people,<00:11:09.766> different<00:11:10.007> practitioners,<00:11:10.729> easy<00:11:11.033> to<00:11:11.065> adopt<00:11:11.386> AI.

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Using<00:11:12.901> Asophie<00:11:13.306> tools,<00:11:14.375> he<00:11:14.682> could<00:11:14.909> actually<00:11:15.395> identify<00:11:16.933> these<00:11:17.062> cells<00:11:18.325> automatically<00:11:18.876> using<00:11:20.025> computer<00:11:20.349> vision<00:11:20.592> AI.

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This<00:11:22.954> is<00:11:23.261> actually<00:11:23.665> pretty<00:11:24.313> transformational.

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Somebody<00:11:25.445> who's<00:11:25.607> not<00:11:25.785> even<00:11:25.930> from<00:11:26.399> the<00:11:26.561> AI<00:11:26.820> background<00:11:27.532> was<00:11:27.694> able<00:11:27.952> to<00:11:28.599> build<00:11:28.777> a<00:11:28.842> solution<00:11:29.473> and<00:11:29.892> deploy<00:11:31.242> it.

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That<00:11:31.901> to<00:11:31.998> me<00:11:32.287> is<00:11:32.544> very<00:11:32.785> powerful<00:11:33.171> and<00:11:33.267> democratized<00:11:34.553> version<00:11:35.051> of<00:11:35.196> AI.

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I<00:11:36.787> think<00:11:36.964> countries,<00:11:37.687> I<00:11:38.233> forget<00:11:38.490> which<00:11:38.651> one<00:11:38.796> was<00:11:38.894> it,<00:11:38.975> Norway<00:11:39.286> or<00:11:39.384> somewhere,<00:11:40.347> they<00:11:40.428> have<00:11:40.543> this<00:11:40.689> concept<00:11:40.951> of<00:11:41.032> a<00:11:41.049> citizen<00:11:41.293> data<00:11:41.424> scientist.

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Meaning<00:11:43.523> that<00:11:44.390> anybody<00:11:44.791> who's<00:11:45.755> doing<00:11:45.931> any<00:11:46.092> walk<00:11:46.269> of<00:11:46.413> life<00:11:46.734> should<00:11:46.975> be<00:11:47.939> being<00:11:48.163> able<00:11:48.340> to<00:11:48.501> build<00:11:48.677> an<00:11:48.806> AI<00:11:49.400> solution.

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And<00:11:51.311> that's<00:11:51.551> underway,<00:11:51.873> right?

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Initially,<00:11:52.419> it<00:11:52.499> started<00:11:53.478> in<00:11:54.281> all<00:11:55.148> the<00:11:55.405> deep<00:11:55.646> data<00:11:55.807> center,<00:11:56.128> Google,<00:11:56.369> Facebook,<00:11:56.770> et<00:11:56.850> cetera,<00:11:57.171> where<00:11:57.717> they<00:11:57.798> have<00:11:58.055> all<00:11:58.135> the<00:11:58.215> expertise.

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But<00:11:59.757> if<00:11:59.885> you<00:12:00.222> look<00:12:00.383> at<00:12:00.768> outside<00:12:01.748> the<00:12:01.828> data<00:12:02.069> center<00:12:02.374> in<00:12:02.470> the<00:12:02.551> physical<00:12:02.936> world,<00:12:04.076> there's<00:12:04.542> a<00:12:04.638> genuine<00:12:05.120> massive<00:12:05.746> opportunity<00:12:06.308> for<00:12:06.485> AI,<00:12:07.047> but<00:12:07.191> also<00:12:07.673> a<00:12:07.834> knowledge<00:12:08.090> gap.

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So<00:12:09.696> a<00:12:09.776> company<00:12:10.162> that<00:12:10.338> gets<00:12:10.579> it<00:12:10.724> right<00:12:11.366> and<00:12:11.687> addresses<00:12:12.826> the<00:12:12.970> hardware<00:12:13.467> plus<00:12:13.660> software,<00:12:14.847> the<00:12:14.911> act<00:12:15.135> of<00:12:15.232> actually<00:12:15.536> making<00:12:16.178> AI<00:12:16.659> easily<00:12:16.916> deployable<00:12:18.263> is<00:12:18.584> onto<00:12:18.760> something<00:12:19.145> huge.

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And<00:12:21.150> that's<00:12:21.567> where<00:12:21.728> we<00:12:21.872> are<00:12:21.904> focused,<00:12:22.690> right?

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To<00:12:23.011> having<00:12:24.358> the<00:12:24.759> ideal<00:12:25.096> mix<00:12:25.321> of<00:12:25.401> hardware<00:12:25.642> and<00:12:25.738> software,<00:12:26.379> making<00:12:26.700> it<00:12:26.845> like<00:12:26.957> a<00:12:27.005> Macintosh<00:12:27.502> experience<00:12:28.048> so<00:12:28.224> that<00:12:28.385> you<00:12:28.529> can<00:12:28.625> deploy<00:12:28.882> solutions.

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We've<00:12:29.972> talked<00:12:30.213> a<00:12:30.229> lot<00:12:30.325> about<00:12:30.486> the<00:12:30.630> upsides<00:12:31.111> of<00:12:31.256> AI.

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What<00:12:31.929> are<00:12:32.090> some<00:12:32.250> of<00:12:32.314> the<00:12:32.459> downsides<00:12:33.020> you<00:12:33.116> see?

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As<00:12:34.384> with<00:12:35.346> any<00:12:35.603> technology,<00:12:36.084> any<00:12:36.244> new<00:12:36.709> technology,<00:12:37.207> there's<00:12:38.394> bound<00:12:38.570> to<00:12:38.714> be<00:12:41.000> controversy.

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There's<00:12:41.741> bound<00:12:41.902> to<00:12:41.998> be<00:12:43.046> potentially<00:12:43.690> the<00:12:43.771> risk<00:12:44.077> of<00:12:44.657> being<00:12:45.366> utilized<00:12:45.865> negatively.

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Imagine<00:12:47.622> a<00:12:47.863> world<00:12:48.121> where<00:12:49.313> AI<00:12:49.716> algorithms<00:12:50.282> are<00:12:51.106> being<00:12:51.413> used<00:12:51.671> to<00:12:53.368> mimic<00:12:54.660> these<00:12:54.757> spam<00:12:55.210> callers,<00:12:55.565> et<00:12:55.694> cetera,<00:12:56.341> and<00:12:57.310> try<00:12:57.488> to<00:12:57.649> get<00:12:57.892> people's<00:12:58.938> information,<00:12:59.518> et<00:12:59.598> cetera,<00:13:00.065> for<00:13:00.371> all<00:13:00.709> bad<00:13:00.951> kinds<00:13:01.128> of<00:13:01.257> things.

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Those<00:13:01.756> are<00:13:01.837> some<00:13:01.981> of<00:13:02.159> the<00:13:02.239> things<00:13:02.481> that<00:13:02.706> are<00:13:03.012> happening.

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They<00:13:05.421> could<00:13:05.577> also<00:13:05.854> be<00:13:06.456> national<00:13:06.777> security-related<00:13:08.222> items.

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They<00:13:09.860> do<00:13:10.021> say<00:13:10.310> that<00:13:10.567> the<00:13:11.626> next<00:13:11.803> generation<00:13:12.815> battles<00:13:13.280> will<00:13:13.377> not<00:13:13.537> be<00:13:13.762> physical<00:13:14.099> fights,<00:13:14.485> but<00:13:14.645> more<00:13:14.806> about<00:13:16.042> cyber-based<00:13:17.215> and<00:13:18.017> complex<00:13:18.435> AI<00:13:18.676> algorithms-based.

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So,<00:13:20.747> all<00:13:20.828> kinds<00:13:21.068> of<00:13:21.566> those<00:13:21.887> things<00:13:22.433> are<00:13:22.867> the<00:13:22.947> negative<00:13:23.333> ramifications<00:13:24.441> of<00:13:24.601> any<00:13:25.420> technology.

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But<00:13:26.641> then<00:13:26.785> again,<00:13:28.230> we<00:13:28.375> look<00:13:28.551> at,<00:13:28.728> hey,<00:13:29.354> does<00:13:29.531> the<00:13:29.659> good<00:13:29.916> outweigh<00:13:30.173> the<00:13:30.318> bad?

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And<00:13:31.506> that's<00:13:31.988> what<00:13:32.309> I<00:13:32.389> keep<00:13:32.566> thinking<00:13:32.887> about<00:13:33.208> as<00:13:33.850> we<00:13:34.479> we<00:13:34.576> build<00:13:34.754> our<00:13:34.883> technology<00:13:35.384> and<00:13:36.031> we<00:13:36.112> just<00:13:36.257> try<00:13:36.419> to<00:13:36.499> focus<00:13:36.839> on<00:13:36.920> the<00:13:37.001> good.

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Yeah.

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And<00:13:39.005> focusing<00:13:39.425> on<00:13:39.506> the<00:13:39.587> good,<00:13:39.813> I<00:13:39.829> imagine,<00:13:40.379> can<00:13:40.557> be<00:13:41.268> exhilarating,<00:13:42.076> right?

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And<00:13:42.496> thinking<00:13:42.803> about<00:13:42.981> all<00:13:43.143> of<00:13:43.224> the<00:13:43.304> various<00:13:43.789> things<00:13:43.935> that<00:13:44.000> it<00:13:44.032> can<00:13:44.213> do.

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What<00:13:45.016> do<00:13:45.098> you<00:13:45.328> read<00:13:45.836> and<00:13:45.984> what<00:13:46.164> reading<00:13:46.410> recommendations<00:13:47.132> would<00:13:47.230> you<00:13:47.312> have<00:13:47.542> for<00:13:47.706> us?

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I've,<00:13:51.303> you<00:13:51.400> know,<00:13:51.786> nowadays<00:13:52.269> a<00:13:52.430> lot<00:13:52.591> of<00:13:52.688> my<00:13:53.010> reading<00:13:53.316> happens<00:13:53.799> on,<00:13:54.942> you<00:13:55.039> know,<00:13:55.167> short,<00:13:56.391> short<00:13:57.518> things<00:13:57.824> like<00:13:58.307> articles<00:13:58.710> written,<00:13:59.273> written<00:13:59.515> on<00:13:59.774> LinkedIn<00:14:00.983> and<00:14:01.080> Medium<00:14:01.734> and<00:14:01.881> so<00:14:02.044> on<00:14:02.077> and<00:14:02.158> so<00:14:02.306> forth.

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My<00:14:04.326> wife<00:14:04.566> also<00:14:06.010> tells<00:14:06.250> me<00:14:06.331> about<00:14:06.571> these<00:14:07.149> AI<00:14:07.518> abridged<00:14:09.218> kind<00:14:11.062> of<00:14:11.223> books.

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An<00:14:11.864> entire<00:14:12.105> book<00:14:12.265> gets<00:14:12.490> summarized<00:14:12.923> into<00:14:13.067> like<00:14:13.228> 15<00:14:13.500> minutes<00:14:13.805> or<00:14:13.869> 10<00:14:14.030> minutes<00:14:14.735> while<00:14:14.912> you're<00:14:15.072> on<00:14:15.136> the<00:14:15.233> treadmill.

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I've<00:14:16.115> yet<00:14:16.275> to<00:14:16.580> take<00:14:16.740> to<00:14:16.836> that.

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But<00:14:18.200> yeah,<00:14:18.585> I<00:14:18.825> think<00:14:19.499> some<00:14:19.884> of<00:14:19.964> those,<00:14:20.349> right,<00:14:20.846> and<00:14:20.991> podcasts,<00:14:21.664> et<00:14:21.745> cetera,<00:14:22.274> are<00:14:22.354> actually<00:14:23.012> quite<00:14:23.397> helpful.

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You<00:14:24.680> get<00:14:25.418> what<00:14:25.738> the<00:14:25.819> person<00:14:26.139> is<00:14:26.171> saying,<00:14:26.460> the<00:14:26.524> emotion<00:14:26.941> of<00:14:27.166> it<00:14:27.583> more<00:14:28.048> so<00:14:28.289> by<00:14:28.385> hearing<00:14:28.722> it.

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So<00:14:29.764> some<00:14:29.973> of<00:14:30.069> those<00:14:30.374> are<00:14:30.550> interesting.

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It's<00:14:31.826> just<00:14:32.052> a<00:14:32.068> mixed<00:14:32.343> bag.

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And<00:14:33.426> of<00:14:33.523> course,<00:14:33.749> reading.

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I<00:14:34.266> like<00:14:34.734> the<00:14:36.253> MIT<00:14:36.916> Tech<00:14:37.498> Review.

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That's<00:14:38.920> pretty<00:14:39.081> interesting.

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They<00:14:40.148> talk<00:14:40.374> about<00:14:40.520> new<00:14:40.697> trends,<00:14:41.036> et<00:14:41.117> cetera,<00:14:41.682> and<00:14:43.928> mixture<00:14:44.202> of<00:14:44.348> different<00:14:44.671> articles<00:14:45.462> here<00:14:45.575> and<00:14:45.656> there,<00:14:45.817> I<00:14:45.882> guess.

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How<00:14:47.239> are<00:14:48.289> you<00:14:48.386> feeling<00:14:48.693> about<00:14:48.870> this<00:14:49.096> year?

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We've<00:14:50.624> had<00:14:50.737> a<00:14:50.865> lot<00:14:51.026> of<00:14:51.123> kind<00:14:51.348> of<00:14:52.796> economic<00:14:53.519> maybe,<00:14:54.034> I<00:14:54.131> don't<00:14:54.983> know<00:14:55.144> if<00:14:55.369> turmoil<00:14:55.852> is<00:14:55.932> the<00:14:55.964> right<00:14:56.173> word,<00:14:56.334> but<00:14:58.162> just<00:14:59.045> kind<00:14:59.205> of<00:14:59.285> confusion,<00:15:00.071> let's<00:15:00.392> say,<00:15:01.675> with<00:15:01.788> tariffs<00:15:02.333> and<00:15:02.413> things<00:15:02.654> of<00:15:02.718> that<00:15:02.878> nature.

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And<00:15:03.841> it<00:15:04.114> does<00:15:04.338> seem<00:15:04.482> like<00:15:04.643> maybe<00:15:04.964> things<00:15:05.204> might<00:15:05.461> be<00:15:05.541> calming<00:15:05.846> down.

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How<00:15:06.151> are<00:15:06.247> you<00:15:06.407> thinking<00:15:06.664> about<00:15:06.889> the<00:15:06.921> rest<00:15:07.033> of<00:15:07.145> the<00:15:07.290> year<00:15:07.466> from<00:15:07.643> an<00:15:07.771> economic<00:15:08.252> perspective?

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We,<00:15:09.648> of<00:15:09.792> course,<00:15:10.049> are<00:15:10.177> paying<00:15:10.418> very<00:15:10.674> close<00:15:10.915> attention<00:15:11.316> to<00:15:11.380> everything<00:15:11.717> that's<00:15:11.941> happening<00:15:12.278> because<00:15:13.064> our<00:15:13.161> customers<00:15:13.578> are<00:15:13.642> global<00:15:14.428> and<00:15:14.989> our<00:15:15.503> supply<00:15:15.871> chain<00:15:16.064> is<00:15:16.192> also<00:15:16.433> global.

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Our<00:15:18.614> chips<00:15:18.855> are<00:15:18.919> manufactured<00:15:19.481> here<00:15:20.138> on<00:15:20.283> US<00:15:20.459> soil.

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And<00:15:22.544> then,<00:15:22.929> so<00:15:23.427> we<00:15:23.651> pay<00:15:23.828> very<00:15:24.149> close<00:15:24.389> attention<00:15:24.870> to<00:15:25.914> everything<00:15:26.155> that's<00:15:26.395> going<00:15:26.620> on.

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We<00:15:26.861> have<00:15:27.022> an<00:15:27.102> outside<00:15:27.905> law<00:15:28.001> firm<00:15:28.306> and<00:15:28.403> inside<00:15:28.869> counsel,<00:15:29.206> everybody<00:15:29.527> advising<00:15:29.993> us<00:15:31.036> on<00:15:31.133> the<00:15:31.293> ramifications.

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And<00:15:32.964> we're<00:15:33.140> in<00:15:33.285> constant<00:15:33.702> touch<00:15:33.943> with<00:15:34.168> our<00:15:34.248> customers<00:15:34.730> because<00:15:36.095> as<00:15:36.256> we<00:15:36.288> supply,<00:15:37.621> if<00:15:37.781> there<00:15:38.022> are<00:15:38.118> ramifications<00:15:38.921> in<00:15:39.066> terms<00:15:39.323> of<00:15:39.467> tariffs,<00:15:39.869> et<00:15:39.949> cetera,<00:15:40.367> how<00:15:40.527> do<00:15:40.608> we<00:15:41.651> make<00:15:41.796> sure<00:15:42.037> the<00:15:42.133> customer<00:15:42.695> gets<00:15:43.000> their<00:15:43.321> product<00:15:43.659> on<00:15:43.819> time<00:15:44.221> and<00:15:44.703> within<00:15:45.329> what<00:15:45.505> they<00:15:45.586> expected<00:15:46.068> and<00:15:46.148> so<00:15:46.389> on?

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So<00:15:47.529> it's<00:15:48.235> basically<00:15:48.878> paying<00:15:49.440> close<00:15:49.681> attention<00:15:50.163> and<00:15:51.271> being<00:15:51.447> nimble<00:15:51.768> enough<00:15:52.009> to<00:15:52.314> act.

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When<00:15:53.374> you—<00:15:53.695> like,<00:15:54.016> we<00:15:54.273> think<00:15:54.498> a<00:15:54.514> lot<00:15:54.675> about<00:15:54.980> at<00:15:55.140> CEO.com,<00:15:55.943> the<00:15:56.088> chances<00:15:56.569> one<00:15:56.810> gives<00:15:57.453> is<00:15:57.613> just<00:15:57.806> as<00:15:57.886> important<00:15:58.271> as<00:15:58.416> the<00:15:58.512> chances<00:15:58.978> one<00:15:59.155> takes.

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Yeah.

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When<00:16:00.760> you<00:16:00.921> hear<00:16:01.146> that,<00:16:01.386> who<00:16:01.563> gave<00:16:01.868> you<00:16:01.964> a<00:16:02.045> chance<00:16:02.526> to<00:16:02.607> get<00:16:02.832> you<00:16:02.928> to<00:16:03.008> where<00:16:03.233> you<00:16:03.329> are<00:16:03.474> today?

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I<00:16:05.095> would<00:16:05.240> say<00:16:05.497> early<00:16:05.882> on,<00:16:06.797> some<00:16:07.006> of<00:16:07.103> the<00:16:07.359> investors<00:16:08.532> and<00:16:08.885> a<00:16:09.110> mentor<00:16:09.431> figure<00:16:09.736> who<00:16:10.234> backed<00:16:10.474> me,<00:16:11.743> you<00:16:11.839> know,<00:16:11.920> my<00:16:12.787> godparents<00:16:13.284> who<00:16:13.365> backed<00:16:13.686> me.

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There's<00:16:14.649> a<00:16:14.665> mentor<00:16:15.211> figure<00:16:15.516> who<00:16:16.480> was<00:16:16.656> a<00:16:16.737> chip<00:16:17.042> guru<00:16:17.475> investor<00:16:18.182> He<00:16:18.342> backed<00:16:18.663> us,<00:16:19.609> you<00:16:19.706> know,<00:16:19.786> right<00:16:20.026> when<00:16:20.171> we<00:16:20.267> were<00:16:20.331> in<00:16:20.427> garage<00:16:20.893> mode,<00:16:21.855> and<00:16:22.593> then<00:16:22.754> the<00:16:22.850> rest<00:16:23.074> is<00:16:23.219> history.

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So,<00:16:23.780> we've<00:16:24.101> definitely<00:16:24.598> beneficiaries.

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And<00:16:26.058> along<00:16:26.283> the<00:16:26.427> way,<00:16:27.229> automotive<00:16:27.646> company<00:16:28.128> Denso,<00:16:28.850> right,<00:16:29.636> they<00:16:30.133> tested<00:16:30.518> our<00:16:30.678> technology<00:16:31.176> and<00:16:31.320> then<00:16:31.416> they<00:16:31.577> invested.

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And<00:16:33.486> so,<00:16:33.646> we've<00:16:34.127> definitely<00:16:34.545> been<00:16:34.705> beneficiaries<00:16:35.491> of,<00:16:36.774> you<00:16:36.806> know,<00:16:36.951> people<00:16:37.352> rooting<00:16:37.657> for<00:16:37.817> us.

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And<00:16:38.475> I<00:16:38.699> immensely<00:16:39.421> value<00:16:39.919> all<00:16:40.015> of<00:16:40.159> the<00:16:40.239> support<00:16:41.603> all<00:16:41.763> over<00:16:42.325> the<00:16:42.469> years<00:16:42.806> that<00:16:43.031> we've<00:16:43.159> received.

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Even<00:16:44.892> till<00:16:45.052> this<00:16:45.196> today,<00:16:45.918> I'm,<00:16:46.737> you<00:16:46.817> know,<00:16:46.881> I<00:16:46.977> talk<00:16:47.154> to<00:16:47.218> my<00:16:47.442> first<00:16:47.763> investors<00:16:48.405> and<00:16:49.030> Uh,<00:16:49.530> they,<00:16:49.860> and<00:16:50.710> you<00:16:50.850> know,<00:16:51.190> of<00:16:51.370> course,<00:16:51.490> uh,<00:16:52.310> quite<00:16:52.490> often<00:16:52.790> in<00:16:52.970> there<00:16:53.190> and,<00:16:53.830> uh,<00:16:53.850> so<00:16:53.910> thankful<00:16:54.190> to<00:16:54.350> all<00:16:54.490> of<00:16:54.550> them<00:16:54.930> that,<00:16:55.410> uh,<00:16:55.730> they<00:16:55.790> helped<00:16:55.910> us<00:16:56.110> get<00:16:56.270> here.

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That's<00:16:57.870> incredible.

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Well,<00:16:58.571> Dinkar,<00:16:58.710> thank<00:16:58.930> you<00:16:59.010> so<00:16:59.190> much<00:16:59.310> for<00:16:59.430> coming<00:16:59.650> on.

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Uh,<00:17:00.490> what<00:17:00.650> an<00:17:00.830> honor<00:17:00.950> to<00:17:01.050> have<00:17:01.230> you.

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Congratulations<00:17:02.010> on<00:17:02.210> everything<00:17:02.470> you've<00:17:02.690> done.

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I<00:17:03.590> mean,<00:17:03.850> Blaze<00:17:04.290> has<00:17:04.890> had<00:17:05.390> $330<00:17:06.050> million<00:17:06.330> in<00:17:06.910> funding.

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You<00:17:07.570> were<00:17:07.710> recognized<00:17:08.070> as<00:17:08.330> the<00:17:08.450> Innovator<00:17:08.750> of<00:17:08.890> the<00:17:09.050> Year<00:17:09.610> locally<00:17:10.390> there<00:17:10.650> in<00:17:10.770> Sacramento.

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I<00:17:11.510> mean,<00:17:11.511> it's<00:17:11.650> just,<00:17:11.950> just<00:17:12.170> unbelievable<00:17:12.890> what<00:17:13.270> you're<00:17:13.450> doing,<00:17:13.810> and<00:17:14.050> we<00:17:14.190> kind<00:17:14.430> of<00:17:14.490> scratched<00:17:14.670> the<00:17:14.910> surface<00:17:15.050> here.

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I<00:17:15.450> hope<00:17:15.550> you'll<00:17:15.710> come<00:17:15.870> back<00:17:16.070> and<00:17:16.210> we'll,<00:17:16.450> we'll,<00:17:16.570> we'll<00:17:16.770> talk<00:17:16.930> more,<00:17:17.710> but<00:17:17.830> thank<00:17:18.010> you<00:17:18.070> so<00:17:18.230> much<00:17:18.350> for<00:17:18.490> coming<00:17:18.610> on.

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Really<00:17:18.650> appreciate<00:17:18.670> it.

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Thank<00:17:20.113> you,<00:17:20.194> Clint.

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Thanks<00:17:21.318> so<00:17:21.398> much.