Inside Silicon Valley's Indian AI Boom — Young Turks Reloaded
硅谷的印度 AI 热潮：印度创始人、工程师与投资
本日音频 · material.mp3
正常 1.0 倍速 · 用于 Step 1 Blind Listening 与 Step 5 Final Listening
今日材料
0-5 分钟 · Blind Listening（盲听）
规则： - 关闭字幕（中英都不开）。 - 正常 1.0 倍速。 - 禁止暂停、禁止倒退。 - 听漏一句就跳，绝不追回。
听后回答（口头或笔头）： 1. Who is talking? 2. What are they talking about? 3. What happened / what is the main point?
📝 答题反思
先盲听，再写下针对性题目的答案用 1-2 句话用自己的话回答下面的问题。点「✨ AI 判断」后，AI 会对照当天 transcript 给出参考要点与评分。
5-10 分钟 · Accent Mapping（口音映射）
目标：把「印度英语的声音」映射成你认识的词。
做法：
- 选刚才盲听时最「卡」的 2-3 个位置。
- 单独重放这些 3-5 秒的小片段，逐词听。
- 在 accent_observations.md 里记录：
- What I heard（你听到了什么音）
- Actual phrase（对照后真实原文）
- Error type（P/B/S/V/G/A/K）
提示： - 别急着下结论「他发音错了」，先问「这是不是印度英语里常见的声音对应」。 - 印度英语个体差异极大，同样的音在不同说话者身上可能完全不同。
错误类型标记： - P = Pronunciation 发音（词被读成另一个音） - B = Word boundary 词边界（没听出词与词的边界） - S = Stress/rhythm 重音/节奏 - V = Vowel quality 元音 - G = Grammar 语法 - A = Accent variation 口音变体 - K = Unknown word 生词
10-18 分钟 · Long Chunk（长段跟随）
做法： - 从头开始连续播放，目标连续跟随 连续 8 分钟。 - 中间不暂停（若材料不足目标时长，则一次听完）。 - 只追踪「意思」：谁在讲什么、下一步要做什么。 - 掉线了？Miss it. Drop it. Keep going. - 结束后用 2-3 句英文总结这段讲了什么。
18-25 分钟 · Transcript Check（对照原文）
做法： 打开视频平台自带的英文字幕（或平台自动字幕，标 AUTO_GENERATED）。 只对照以下三种问题： A：单词认识，但声音没听出来。 B：单词认识，但意思反应太慢。 C：真正不知道的表达。 （若平台无字幕，则跳过本步，直接进入复述。）
重点：只解决「没听出来」的问题，不做逐句翻译。
把最难的 3 个片段写进 difficult_segments.md。
25-30 分钟 · Final Retest（复测）
做法： - 关闭 transcript 和字幕。 - 从头完整播放（或播放目标长度），禁止暂停。 - 结束后 30-60 秒英文口头复述： Basically, they were talking about… At first… Then… The main point was… In the end… - 对比这次 vs 第一次盲听：理解率是否提升？掉线是否减少？
📊 每日记录
本日材料（已下载本地音频）
打开本目录 watching_instruction.md，按官方 URL 在 YouTube 合法播放指定片段。
- 视频：Inside Silicon Valley’s Indian AI Boom — Young Turks Reloaded
- 建议播放范围：0:00–12:00（约 12 分钟）
- 播放规则：禁止暂停、禁止倒退、关闭字幕（Step 1）。
Daily Score
- 理解率：____ %
- 明显掉线次数：____
- 最长连续跟随时间：____
- 需要 transcript 才能理解的比例：____ %
- Accent Adaptation Score（1-10）：____
- 今天最明显的口音障碍（1-3 个）：____
Accent Adaptation Score 定义（1-10）： - 10 = 完全适应：第一次听就几乎不需要看 transcript，印度英语不再是障碍。 - 8-9 = 很好：能连续跟随目标时长，偶尔个别词要靠上下文猜。 - 6-7 = 良好：能跟住主线，但每隔一段会掉线一次，需要重听一句。 - 4-5 = 一般：能抓住大意，但频繁掉线，明显依赖 transcript。 - 1-3 = 困难：大部分听不懂，印度英语的发音/节奏造成严重障碍。
本日主题
硅谷的印度 AI 热潮：印度创始人、工程师与投资。
Notes
CNBC-TV18 官方频道。主题：AI / 印度创业者。
Transcript · 英文原文
先盲听再对照。只找 A（没听出）B（反应慢）C（真不会）三类问题。Whisper ASR 为默认，YouTube/火山引擎供对照。
# Day 50 — Whisper (faster-whisper small, int8) 转写
设备 CPU，语言 en，VAD 过滤。ASR 生成，可能含识别错误。
==================================================
A lot of the action in AI is happening in the valley, we're seeing a traffic jam, right?
Like number of founders were moving here.
AI is going to play an incredible role there to rethink what the market model for pharma would look like.
Each event has 100-point checklists and for 10,000 events we have a million points to continuously monitor.
It's humanly impossible to do it at scale worldwide and that's why we have agents to continuously look at it.
When you want to get into vertical domain specific, I think that's where the expertise will come into play.
So, can you be qualified or not?
We'll probably be the last ones on the list if that happens, right?
If you're building applications horizontally, then I think very quickly you have to find out what is your niche.
In the last one year, I would say we've probably done like eight or nine deals on the AI space.
The key which we had invested in a few months ago got acquired by Palo Alto Networks.
Great validation of the fact that founders from India can build world-class technology.
There's three trillion dollars of liquidity.
That capital is going to get redeployed again.
You need to first establish trust and credibility.
If you get that right, I think you can constantly change or improve your input.
What does the story look like for India in 2026?
Indian founders have started to get a lot more ambitious, a lot more audacious.
That flywheel has started turning and I think that's been the most exciting thing to watch.
You know, going to courts, solving cases is very different in India than anywhere else.
Is there an entrepreneur today who is kind of the North Star?
It will have to be Elon.
I would say you're still playing the game and you know, we're not at the end of it.
Like we say, you know, picture abhi baki hai.
Welcome to this edition of Voices from the Valley,
a part of the Young Turks programming for 24 years of focusing on startups and entrepreneurship.
I'm Shirin Ban. We're in Palo Alto, right outside the Palo Alto city hall
and we're here to have a conversation about, guess what, all things AI
and all things startups and entrepreneurs.
Now, an interesting trend that we're starting to see is not just Indian founders
looking at moving to the valley to be closer to the customer,
but it's also Indian funds who are looking at setting up shop here in the valley,
in the Bay area to be closer to their customers and their portfolio companies.
We will talk about what that means as far as capital allocation is concerned
and the kinds of bets that that is likely to see these funds make.
We're also going to talk about Indian founders who have one foot in the valley
and half a foot perhaps still in India as they make their bets in the world of AI.
I have a very interesting set of people here with me to talk about all of that.
Krishna Mera at Elevation. Krishna, thanks so much for joining us.
Great to be here.
Also with us, Supreet Deshpande, the co-founder of Sintio Lab, Deepakanshna of Adopt,
AI and Abhishek Humbad, the founder of Good Error, who's been on Young Turks
many, many years ago. Abhishek, it's great to have you back.
But Krishna, let's get started. You know, this trend of funds looking at the valley
to get in on the AI wave, how significant is this move?
I mean, I think it's pretty significant.
And the reason is because all the founders are here.
A lot of the action in AI is happening in the valley.
But we also find that founders even from India, the moment they have an idea
and, you know, 50K in funding, they got a plane and land in SF.
And they're living in a hostel. They're hustling hard and, you know, landing customers.
And I think when we see that trend, we have to be here to support them.
Obviously, on an ongoing basis as they continue to grow and scale,
a lot of the customers are, you know, coming from the U.S.
CIOs who are customers, you know, they're all based in the U.S.
So I think you want to support that entire journey.
But we also want to catch them young and early when they're, you know,
first here in the U.S.
You know, but let's talk about the investment thesis now at Elevation.
200 odd companies later.
What is it?
A dozen plus unicorns later.
Ten odd IPOs later.
How does the investment thesis now change for Elevation,
given the fact that you're all in now on this AI wave?
Absolutely.
So, I mean, obviously, focusing on India consumer and fintech
and, you know, the India macro is still a big part of our business.
So not giving up on that.
We're not giving up on it.
But we are finding a lot more AI-pilled solutions there.
So a lot of the companies we are backing now are a lot more AI-pilled
or using AI in their operations.
Right?
And then there's this third, a third of our fund,
which is going to be deployed in Enterprise AI.
And the focus of that is B2B companies which are building
both India for India as well as India for the world.
A large portion of that is India for the world.
And that's why, you know, having a presence here
is so much more valuable.
The thing we find on that thesis is that Indian founders
have started to get a lot more ambitious, a lot more audacious.
We recently had a company called Porti,
which we had invested in a few months ago,
got acquired by Palo Alto Networks.
Great validation of the fact that founders from India
can build world-class technology and kind of, you know,
get acquired by the best in the world, so to say.
But I think we want to see a lot more of it
and we are seeing a lot more of it.
We're excited about that.
So before I get to the founders,
a quick question from you in terms of the kind of capital
that you intend to deploy here in this area.
And, you know, is this likely to be a big year?
You just talked about Palo Alto Networks and Porti.
We've just seen SpaceX and Cursor.
You know, the assumption is that this is going
to be a big year for M&A, not just IPOs.
Absolutely.
So two things playing out, right?
One, if you look at the public markets,
there's three trillion dollars of liquidity
which is going to hit, you know, firms, investors,
you know, companies which have invested
in, you know, these new IPOs of open-air,
anthropic, and SpaceX.
That's going to go back to the system.
That capital is going to get redeployed again,
both in the form of M&A.
Google is one of the biggest investors
in all these companies, right?
Yes.
As well as in, you know, the startup line where, you know,
VCs are going to have new liquidity.
For about seven or eight years, we've been kind of suffering
from this lack of liquidity in the valley, so to say.
And suddenly we have three trillion dollars worth of it.
So one is that thesis playing out.
The second part of the thesis is also incumbents
which, you know, find themselves on kind of the back foot now
and want to make themselves AI-pilled.
They came out with these first set of solutions
and, you know, an example is Salesforce
which launched Agent Force with a lot of fanfare,
great adoption, but still wants to do a lot more in AI
and they just bought Fin for 3.6 billion dollars,
you know, yesterday.
And, you know, a year ago, Fin was running ads,
you know, calling Salesforce not so nice things, right?
So the whole idea is incumbents who have cash flow,
who have revenues also want to actually go play
the early stage game now.
And we should start seeing a lot more acquisitions,
both for buying the business, buying the technology,
as well as buying the talent that can build the technology
in their company.
Yes, you know, we're likely to see a lot more of that happen.
But let's talk to the founders now.
Nansu Preet, I want to start by asking you
tell us a little bit about the problem that you're hoping
to solve in an AI world.
And of course, the focus for you is FOWER.
Yeah, absolutely.
So yeah, so at Cynthia Labs, what we do is we completely kind of
imagine what pharma go-to-market model looks like.
Over the last two decades, it's predominantly been human-led,
right? And in some sense, now technology can unlock things
that weren't possible.
So one example is, can you have an AI engaged with physicians
who are the end customers for pharma
and have that expert sort of on 24-7?
Now, of course, a lot of things around that come with
compliance, regulations, what the FDA thinks about it.
But I think that also makes it very interesting.
So it's a massive space, you know, often unknown.
Yeah, because the focus has always been on what can AI do
to drug discovery, what can AI do in terms of breakthroughs
for, you know, mega complex problems, health care problems.
But you're actually addressing the other side of the spectrum.
Absolutely.
And I think that's a good point because, you know,
oftentimes when we talk about pharma and AI happening,
we talk about drug discovery, which is extremely upstream.
But if you think about spend, right?
You do a map of where all the spend happens.
A large part of it is commercial.
And today, almost half of that, I think it's close to 300 billion
plus in spend.
A significant portion of that is just services, right?
Like the accentures, deloids, years of the world.
And what's happened is over the last two decades,
because of either call it lack of technology or just
how the process where there were too many processes that
were added on, right?
And it sort of layered on.
And I think now it's an incredible time to just
completely rethink that go-to-market model.
And a bunch of other interesting elements to that, right?
So if you think about GLP once of the world,
now you're talking about a drug class where your customer base
is pretty much every physician.
Yes.
So if your go-to-market model cannot be,
I'll have a thousand reps, right?
Because the economic model on that will never make sense.
So I think AI is going to play an incredible role there
to rethink what that go-to-market model for pharma
would look like.
Okay.
So you're based, of course, here in the valley,
but you do have a foot in India as well.
Yeah.
So we, in fact, have a couple of engineers,
and we are kind of growing that team a lot.
A lot of that is sort of either our IC network
where there were engineers building there.
But the way we are seeing is, in fact,
a lot of our kind of actual product build
and even for deployed engineers,
we have dedicated folks in India that are helping us build.
So yeah.
So in fact, we recently got five of them here.
They're spending some time with us.
Okay.
We have a nice apartment here in the Bay Area
that kind of hosts our folks from India that come here.
No, I think we are really excited about that model.
So Deepak, let's talk a little bit about what you're trying to do,
the problem that you're addressing at Adopt AI.
I mean, you know, that kind of captures everything
that everybody's talking about here on the adoption front.
But what exactly are you hoping to do?
Yeah, it's an interesting name we came up with.
We saw the domain and we got it.
I'm surprised it wasn't taken.
Yeah, we saw it and then the moment it was available,
we rushed and got to that domain.
But just like Sukrit talked about reimagining
and then go-to-market workflows,
we do that on the back office side.
We do that on the back office and then side of things.
There we are reimagining tax accounting,
account recon, book closing workflows.
Essentially, you know, this is a very hot space now.
After coding and legal accounting and taxes
become a very hot space.
And then we have agents that, autonomous agents
that can connect to legacy systems,
which is finances full of these legacy systems with no APIs,
spreadsheets, PDFs, all of these documents,
and then recreate general edges, trial balances,
close books and go-file taxes, right?
So that's the space you're operating in.
Okay, so let me ask you and then I'll ask Sukrit this as well.
I think the big question that everyone's grappling with
is that, you know, will all of you be able
to do what you're currently doing?
It's a matter of time before Claude and Open Air
decide to come in your direction
and try and eat your breakfast, lunch and dinner.
Now, what is the mode in a market like today
when you're up against that kind of capability
and that kind of capital?
Yeah, absolutely.
So there's this narrative in the market
that, you know, everyone can get glorified, right?
Yes.
# Day 50 — YouTube 自动生成字幕（AUTO_GENERATED）
覆盖训练段 000–12 分钟。已去滚动字幕重叠。ASR 生成可能含识别错误。
==================================================
>> A lot of the action in AI is happening in the valley. We are seeing [music] a traffic jam, right? Like number of founders were moving here. AI is going to play an incredible role there to rethink what go-to-market model for pharma would look like. >> Each event has a 100-point checklist, and for 10,000 events, we have a million points to continuously monitor. Humanly impossible to do it at scale worldwide, and that's where we have agents to continuously continuously >> they look at it. >> When
you want to get into vertical domain specific, I think that's where the expertise will will come into play. >> [music] >> [music] >> So, can you be cloudified or not? >> We'll probably be the last ones on the list if that happens, right? >> If you're building applications horizontally, then I think very quickly you have to find out what is your niche. >> Over the last 1 year, I would say we've probably done like eight or nine deals on the AI space. >> Port key, which
we'd invested in a [music] few months ago, got acquired by Palo Alto Networks. Great validation of the fact that founders from India can build world-class technology. >> [music] >> [music] >> There's $3 trillion of liquidity. That capital is going to get redeployed again. again. >> You need to first establish trust and credibility. If you get that right, I think you can constantly change or improve your influence. improve your influence. >> What does the story look like for India in 2026? in 2026? >> Indian founders have
started to get a lot more ambitious, a lot more audacious. [music] audacious. [music] That flywheel has started turning, and I think that's been the most exciting thing to watch. thing to watch. >> You know, going to courts, solving cases is very different in India than it is, you know, anywhere else. >> Is there an entrepreneur today who is kind of the North Star? >> It will have to be Elon. >> I would say you're still playing the game. I mean, you know, we're not yet at
the end of it. Like we say, you know, picture abhi baaki hai. >> [music] >> Hello, and welcome to this edition of Voices the Valley, a part of the Young Turks programming for 24 years of focusing on startups and entrepreneurship. I'm Shirin Banu in Palo Alto, right outside the Palo Alto City Hall, and we're here to have a conversation about, guess what? All things AI and all things startups and entrepreneurs. Now, entrepreneurs. Now, an interesting trend that we're starting to see is not just Indian founders
looking at moving to the Valley to be closer to the customer, but it's funds who are looking at setting up shop here in the Valley, in the Bay Area to be closer to their customers and their portfolio companies. We will talk about what that means as far as capital allocation is concerned and the kinds of bets that that is likely to see these funds make. We're also going to talk about Indian founders who have one foot in the Valley and half a foot perhaps still in
the India as they make their bets in the world of AI. I have a very interesting set of people here with me to talk about all of that. Krishna Mera at Elevation. Krishna, thanks so much for joining us. Also with us Supreet Deshpande, the co-founder of Cintio Lab, Deepak Anchana of Adopt AI, and Abhishek Kumar, the founder of Goodera, who's been on Young Turks many, many years ago. Abhishek, it's great to have you back, but Krishna, let's get started. You know, this trend of funds looking
at the Valley to get in on the AI wave, how significant is this move? >> I mean, I think it's pretty significant, and the reason is because all the founders are here. A lot of the action in AI is happening in the Valley, but we also find that founders even from India, the moment they have an idea >> Yeah. >> Yeah. >> and, you know, 50K in funding, they get on a plane and land in SF. And they're living in a hostel, they're hustling hard, and,
you know, landing customers. And I think when we see that trend, we have to be here to support them. Obviously, on an ongoing basis as they continue to grow and scale, A lot of the customers you know coming from the US CIOs who are customers, you know, they're all based in the US. So I think we want to support that entire journey, but we also want to catch them young and early when they are you know first here in the US. in the US. >> You
know, but let's talk about the investment pieces now at Elevation. 200 odd companies later, what is it a dozen plus unicorns later, plus unicorns later, 10 odd IPOs later, how does the investment pieces now change for Elevation given the fact that you're all in now on this AI wave? >> Absolutely. So >> Absolutely. So I mean obviously I mean obviously focusing on India consumer and fintech and you know the India macro is still big part of our thesis. >> So not giving up on that. >>
giving up on it, but we are finding a lot more AI built solutions there. So a lot of the companies we are backing now are a lot more AI built or using AI in their operations, right? And then there's this third a third of our fund which is going to be deployed in enterprise AI and the focus of that is B2B companies which are building both India for India as well as India for the world. A large portion of that is India for the world and
that's why you know having a presence here is so much more valuable. Um the thing we find on that thesis is that Indian founders have started to get a lot more ambitious, a lot more ambitious. ambitious. We recently had a company called Portkey which we'd invested in a few months ago got acquired by Palo Alto Networks. Great validation of the fact that founders from India can build world-class technology and kind of you know get acquired by the best in the world so to say. Uh but
I think we want to see a lot more of it and we are seeing a lot more of it and we're excited about that. excited about that. >> So before I get to the founders, a quick question from you in terms of the kind of capital that you intend to deploy here in this area. And you know is this likely to be a big year? You just talked about Palo Alto Networks and Portkey. We've just seen SpaceX and Kasa, you know, the assumption is that this
is going to be a big year for M&A, not just IPOs. >> Absolutely. So, two things playing out, right? One, if you look at the public markets, there's $3 trillion of liquidity which is going to hit, you know, funds, investors, you know, companies which have invested in, you know, these these new IPOs of Open AI and Anthropic and SpaceX. That's going to go back to the system. That capital is going to get redeployed again, again, both in the form of M&A. Google is one of the
biggest investors in all these companies, right? >> As well as in, you know, the startup land where, you know, VCs are going to have new liquidity. For about seven or eight years, we've been kind of suffering from this lack of liquidity in the valley, so to say, and suddenly we have $3 trillion worth of it. So, one is that thesis playing out. This second part of the thesis is also incumbents which, which, you know, find themselves on kind of the back foot now and want to
make themselves AI built. They They They came out with these first set of solutions. You know, an example is Salesforce which launched Agent Force with a lot of fanfare, great adoption, but still wants to do a lot more in AI and they just bought Fin for $3.6 billion yesterday. And, you know, a year ago, Fin was running ads, you know, calling Salesforce not so nice things, right? So, So, the the whole idea is incumbents who have cash flow, who have revenues also want to actually go
play the the early stage game now and we should start seeing a lot more acquisitions both for buying the business, buying the technology, as well as buying the talent that can build that technology in their company. company. >> Yes, you know, we're we're likely to see a lot more of that happen, but let's talk to the founders. Now, Supreet, I want I'm going by asking you. Tell us a little bit about the problem that you're hoping to solve in an AI world. And of course, the
focus for you is pharma. >> Yeah, absolutely. So yeah, so at Cintio Labs, what we do is we completely kind of reimagine what pharma go-to-market model looks like. Over the last two decades, it's predominantly been human-led, right? And in some sense, now technology can unlock things that weren't possible. So one example is can you have an AI engage with physicians who are the end customers for pharma and have that expert sort of on 24/7. Now of course, a lot of things around that come with compliance,
regulations, what the FDA thinks about it. But I think that also makes it very interesting. So it's a massive space, you know, often unknown. So I think >> the focus has always been on what can AI do to drug discovery, what can AI do in terms of breakthroughs for, you know, mega complex problems, health care problems. But you're actually addressing the other side of the spectrum. >> Absolutely. And I think I think that's a great point because you know, often times when you talk about pharma
and AI happening, we talk about drug discovery, which is extremely upstream. But if you think about spend, right? You do a map of where all the spend happens, a large part of it is commercial. And today, almost half of that, I think it's close to 300 billion plus in spend. A significant portion of that is just services, right? Like the Accentures, Deloittes of the world. And what's happened is over the last two decades, because of either call it lack of technology or just how the process
is, where they were too many processes that were added on. >> Right. >> Right. >> Right. And it's sort of layered on. And and I think now it's it's an incredible time to just completely rethink that go-to-market model. go-to-market model. And a bunch of other interesting elements to that, right? So if you think about GLP-1s of the world. >> Yeah. >> Yeah. >> Now you're talking about a drug class where your customer base is pretty much every physician. every physician. >> Yes. >> Yes. >> So
your your go-to-market model cannot be I'll have a thousand reps, right? Because the economic model on that will never make sense. never make sense. So I think AI is going to play an incredible role there to rethink what that go-to-market model for pharma would look like. look like. >> Okay. So, your base of course here in in the valley, but you do have a footprint in India as well. >> Yeah, so we we in fact have a couple of juniors and we are kind of growing
that team a lot. team a lot. A lot of that is sort of either our YC network where there were engineers building there. But, But, you know, the way we are seeing is in fact a lot of our kind of actual product built and even deployed engineers. We have dedicated folks in India that are helping us build. So, yeah, in fact, we recently got five five of them here. They're spending some time with us. >> Okay. >> Okay. >> We have a a nice apartment here
in in the Bay Area that kind of hosts our folks from India that come here. No, I think we are really excited about that, Maddy. that, Maddy. >> So, so Deepak, let's talk a little bit about what you're trying to do, the problem that you're addressing at Adapt AI. I mean, you know, it kind of captures everything that everybody's talking about here on the adoption front, but what exactly are you hoping to do? to do? >> Yeah, it's an interesting name we came up with. We
saw the domain and we got it. But, essentially it. But, essentially >> it wasn't [laughter] taken. >> Yeah, we we we saw it and then the moment it was available, we rushed and got it. We own that domain. But, just like Sukrit talked about reimagining entire go-to-market reimagining entire go-to-market workflows, we do that on the back office side. We do that on the back office finance side of things. There we are reimagining tax, accounting, account recon, book closing workflows. Essentially, you know, this is a very
hot space now. After coding and legal, accounting and taxes become a very hot space. And we have agents that autonomous agents that can connect to legacy systems, which is finance is full of these legacy systems with no APIs. Spreadsheets, PDFs, all of these documents, and then recreate general ledgers, trial balances, close books, and go file taxes, right? So, that's the that's the space we are operating in. >> Okay, so let me let me ask you and then I'll ask Sukrit I'll ask Sukrit this as well.
I I the the big question that that everyone's grappling with is that, you know, will all of you be able to do what you're currently doing? It's a matter of time before Claude and Open AI decide to come in your direction and try and eat your breakfast, lunch, and dinner. Now, what is the moat in a market like today when you're up against that kind of capability and that kind of capital? capital? >> Yeah, absolutely. So, there's this narrative in the market that, you know, everyone
can get Claudified, right? So, there's this fear, but uh let me tell
# Day 50 — 火山引擎 录音文件识别（volc.seedasr.auc）
豆包大模型 ASR，异步接口。可能含识别错误，仅供听力对照。
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A lot of the action in AI is happening in the valley, we're seeing a traffic jam, right?
Like number of founders were moving here.
AI is gonna play an incredible role there to rethink what go to market model for pharma would look like.
Each event has 100 point checklist and for 10,000 events, we have a million points to continuously monitor humanly.
Impossible to do it at scale worldwide.
And that's where we have agents to continuously look at it.
When you want to get into vertical domain specific, I think that's where the expertise will, will come into play.
So can you be qualified or not?
We'll probably be the last ones on the list if that happens, right?
If you're building applications horizontally, then I think very quickly you have to find out what is your niche.
In the last one year, I would say we've probably done like eight or nine deals on the AI space.
Portkey, which we had invested in a few months ago, got acquired by Palo Alto Networks, great validation of the fact that founders from India can build world class technology.
There's $3 trillion of liquidity.
That capital is going to get redeployed again.
You need to first establish trust and credibility.
If you get that right, I think you can constantly change or improve your infrastructure.
What does the story look like for India in 2026?
Indian founders have started to get a lot more ambitious, a lot more audacious.
That flywheel has started turning, and I think that's been the most exciting thing to watch.
You know, going to courts, solving cases is very different in India than it is, you know, anywhere else.
Is there an entrepreneur today who is kind of the North Star?
It will have to be Elon, I would say.
You're still playing the game.
I mean, you know, we're not the at the end of it like we say, you know, picture of a buck.
Yeah.
Hello and welcome to this edition of voices from the valley, a part of the Young Turks programming for 24 years of focusing on startups and entrepreneurship.
I'm Shirin Ban.
We're in Palo Alto, right outside the Palo Alto City Hall.
And we're here to have a conversation about, guess what?
All things AI and all things startups and entrepreneurs.
Now, an interesting trend that we're starting to see is not just Indian founders looking at moving to the valley to be closer to the customer, but it's also Indian Funds were looking at setting up shop here in the valley.
In the Bay Area to be closer to their customers and their portfolio companies.
Uh, we will talk about what that means as far as capital allocation is concerned and the kinds of bets that that is likely to see these funds make.
We're also going to talk about Indian founders who have one foot in the valley and half a foot perhaps still in India as they make their bets in the world of AI.
I have a very interesting set of people here with me to talk about all of that.
Krishna Mehra at Elevation.
Krishna, thanks so much for joining us.
Also with us, Supreet Deshpande, the co founder of Cynthio Lab, Deepakantana of Adopt AI and Abhishek Humber, the founder of Goodera who's been on Young Turks many, many years ago.
Abhishek, it's great to have you back.
But Krishna, let's get started.
You know, this trend of funds looking at the valley to get in on the AI wave, how significant is this move?
I mean, I think it's pretty significant and the reason is because all the founders are here.
Uh, a lot of the action in AI is happening in the valley, but we also find that founders, even from India, the moment they have an idea.
Yeah.
And, you know, 50 k in funding, they get on a plane and land in SF and they're living in a hostel.
They're hustling hard and, you know, landing customers.
And I think when we see that trend, we have to be here to support them, obviously, on an ongoing basis as they continue to grow and scale.
A lot of the customers are, you know, coming from the US.
Uh, CIOs who are customers, you know, they're all based in the US.
So I think we want to support that entire journey, but we also want to catch them young and early when they're, you know, first here in the US.
You know, but let's talk about the investment pieces now.
At Elevation, 200 odd companies later, what is it, a dozen plus unicorns later, uh, 10 odd ipos later.
How does the investment pieces now change, uh, for elevation, given the fact that you're all in now on this AI wave?
Absolutely.
So, um, I mean, obviously focusing on India consumer and fintech and you know the India macro is still big part of our.
So not giving up on that.
We're not giving up on it, but we are finding a lot more AI built solutions there.
So a lot of the companies we are backing now are a lot more AI failed or using AI in their operations, right?
And then there's this third, a third of our fund, which is going to be deployed in enterprise AI.
And the focus of that is b to B companies, which are building, uh, both India for India as well as India for the world.
A large portion of that is India for the world.
And that's why, you know, having a presence here is so, so much more valuable.
Um, the thing we find on that thesis is that Indian founders have started to get a lot more ambitious, a lot more audacious.
Um, we recently had a company called Port Key, which we had invested in a few months ago, got acquired by Palo Alto Networks.
Great validation of the fact that founders from India can build world class technology and kind of, you know, get acquired by the best in the world, so to say.
Uh, but I think we want to see a lot more of it and we are seeing a lot more of it and very excited about that.
So before I get to the founders, a quick, uh, uh, question from you in terms of the kind of capital that you intend to deploy here in this area.
Uh, and, you know, is this likely to be a big year?
You just talked about follow all to Netflix and port key.
We've just seen Spacex and cursor.
Uh, you know, the, the Assumption is that this is going to be a big year for M&A, not just ipos.
Absolutely.
So two things playing out, right?
One, if you look at, uh, the public markets, there's $3 trillion of, uh, liquidity which is going to hit, uh, you know, firms, investors, uh, you know, companies which have invested in, you know, these, these new ipos of Open Anthropic and Spacex, that's going to go back to the system.
That capital is going to get redeployed again, both in the form of M&A.
Google is one of the biggest investors in all these companies, right, as well as in, you know, the startup land where, you know, vcs are going to have new liquidity.
For about seven or eight years, we've been kind of suffering from this lack of liquidity in the valley, so to say, and suddenly we have $3 trillion worth of it.
So one is that thesis playing out.
The second part of the thesis is also incumbents, which, you know, find themselves on kind of the back foot now and want to make themselves AI build.
They, they, they came out with these first set of solutions.
Um, you know, an example is Salesforce, which launched Agent Force with a lot of fanfare, great adoption, but still wants to do a lot more in AI and they just bought Finn, uh, for $3.6 billion.
Uh, you know, yesterday and, you know, a year ago, uh, Finn was running ads, uh, you know, calling Salesforce not so nice things, right?
So the, the whole idea is incumbents who have cash flow, who have revenues also want to actually go play the, the early stage game now and we should start seeing a lot more acquisitions, both for buying the business.
Buying the technology as well as buying the talent that can build that technology in their company.
Yes.
Uh, you know, we're, we're likely to see a lot more of that happen.
But let's talk to the founders.
Nansupreet, I want to start by asking you, tell us a little bit about the problem that you're hoping to solve, uh, in an AI world and of course, the focus for you is pharma.
Yeah, no, absolutely.
So yeah, so at Cynthia Labs, what we do is we completely kind of imagine what pharma go to market model looks like over the last two decades, it's predominantly been human LED, right?
And in some sense now technology can unlock things that weren't possible.
So one example is can you have an AI engage with physicians who are the end customers for pharma and have that expert sort of on 24 7.
Now of course, a lot of things around that come with compliance regulations, what the FDA thinks about it, but I think that also makes it very interesting.
So it's a massive space, you know, often unknown.
Yeah.
Because the focus has always been on what can AI do to drug discovery?
What can AI do in terms of breakthroughs for, you know, mega complex problems, healthcare problems, but you're actually addressing the other side of the spectrum.
Absolutely.
And I think, I think that's a good point because, you know, oftentimes when we talk about pharma and AI happening, we talk about drug discovery, which is extremely upstream.
But if you think about spend, right, you do a map of where all the spend happens, a large part of it is commercial.
And today, almost half of that, I think it's close to 300000000000+ in spend, a significant portion of that is just services, right?
Like the Accenture, Deloitte.
Yes.
Of the world.
And what's happened is over the last two decades, because of either, call it lack of technology or just how the processes where there were too many processes that were added on.
Right, right.
And it's sort of layered on.
And, and I think now it's, it's an incredible time to just completely rethink that go to market model and bunch of other interesting ailments to that, right?
So if you think about GLP ones of the world.
Yeah.
Now you're talking about a drug class where your customer base is pretty much every physician.
Yes.
So your go to market model cannot be I'll have 1,000 reps, right, because the economic model on that will never make sense.
So I think yeah is gonna play an incredible role there to rethink what that go to market model for pharma would look like.
Okay, so you're based of course here in in the valley, but you do have a foot in India as well.
Yeah, so we, we in fact have a couple of juniors and we are kind of growing that team a lot.
A lot of that is sort of either our YC network where there were engineers building there.
Uh, but uh, you know, the way we are seeing is, uh, in fact a lot of our kind of actual product build and even for deployed engineers, we have dedicated folks in India that are helping us build.
Um, so yeah, so in fact, we recently got 5, 5 of them here.
They're spending some time with us.
Okay.
We, we have a, a nice apartment here in, in the Bay Area that kind of hosts our folks from India that come here.
Um, no, I think we are really excited about that.
Modi.
So.
So Deepak, let's talk a little bit about what you're trying to do, the problem that you're addressing at Adopt AI.
I mean, you know, that kind of captures everything that everybody's talking about here on the adoption front.
But what exactly are you hoping to do?
Yeah, it's an interesting name we came up with.
We saw the domain and we got it.
But I'm surprised it wasn't taken.
Yeah, we, we, we saw it and then the moment it was available, we rushed and got that domain.
But just like Sukrit talked about reimagining entire go to market workflows, we do that on the back office side.
We do that on the back office finance side of things.
There, we are reimagining tax accounting, account recon, book closing workflows.
Essentially, you know this is a very hot space now after coding and legal accounting and taxes become a very hot space.
And we have agents that autonomous agents that can connect to legacy systems, which is finance is full of these legacy systems with no APIs, spreadsheets, uh, pdfs, all of these documents and then recreate general ledgers, trial balances, close books and go file taxes, right? So, uh, that's the, that's.
The space we're operating in.
Okay.
So let me, let me ask you and then I'll ask supreeth, uh, this as well.
I think the, the big question that, that everyone's grappling with is that, you know, will all of you be able to do what you're currently doing?
It's a matter of time before Claude and Open AI decide to come in your direction, uh, and try and eat your breakfast, lunch and dinner.
Now, what is the mode in a market like today when you're up against that kind of capability and that kind of capital.
Yeah, absolutely.
So there's this narrative in the market that, you know, everyone can get clarified, right? So there's this fear.
Vocabulary · 本日最多 5 个重点
Vocabulary — Day 50
每天最多 5 个最值得训练的项。优先：技术英语 / 工作表达 / 连读后难识别的表达。 本日音频已下载（无官方 transcript），请先盲听再复述，必要时对照官方字幕。 所有读音说明依据印度英语实际听感（个体差异大，仅供参考）。
1. boom
Expression: boom Meaning: 热潮 / 繁荣 Original sentence: India’s AI boom. Natural pronunciation note (Indian English): boom /buːm/，印度英语元音饱满。 My own simple paraphrase: 快速发展期。 Example: There’s an AI boom in Silicon Valley.
2. founder
Expression: founder Meaning: 创始人 Original sentence: Indian founders in Silicon Valley. Natural pronunciation note (Indian English): founder 重音在 foun /ˈfaʊn.dər/。 My own simple paraphrase: 创立公司的人。 Example: The founder shared his journey.
3. venture capital / VC
Expression: venture capital / VC Meaning: 风险投资 Original sentence: VC funding for AI startups. Natural pronunciation note (Indian English): venture 重音在 ven /ˈven.tʃər/。 My own simple paraphrase: 投给初创企业的钱。 Example: VC money is flooding into AI.
4. engineer / talent
Expression: engineer / talent Meaning: 工程师 / 人才 Original sentence: Indian AI talent. Natural pronunciation note (Indian English): engineer 重音在 neer /ˌen.dʒɪˈnɪr/。 My own simple paraphrase: 技术人才。 Example: Indian engineers lead many AI teams.
5. ecosystem
Expression: ecosystem Meaning: 生态系统 Original sentence: the startup ecosystem. Natural pronunciation note (Indian English): ecosystem 重音在 sys /ˈiː.koʊ.sɪs.təm/。 My own simple paraphrase: 相互支持的体系。 Example: The ecosystem supports new founders.
⚠️ 以上表达依据标题/主题推断。听完后请对照实际对白，删改不准确项。