May 29, 2025 • 19 mins
Announcing Our $25M Series A | David AI Blog
Litehaus: Revolutionizing Modular Home Construction to Address Europe's Housing Crisis
YC's 2025 Blueprint for Full-Stack AI Domination
#startups, #AI, #YCombinator, #modularhomes, #housingcrisis, #SeriesA, #technology
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:00):
Welcome to Innovation Pulse, your quick no-nonsense update covering the latest in startups and
(00:09):
entrepreneurship news. First, we will cover the latest news.
David AI secures 25 million for audio AI advancements, while Lighthouse raises $1.46 million
to revolutionize construction with modular methods. After this, we'll dive deep into
why combinators 2025 vision for AI agents transforming industries.
(00:35):
David AI is revolutionizing the audio AI landscape by establishing itself as the world's first
audio data research company. Founded less than a year ago, the company has already secured
a $25 million Series A funding round led by Alt Capital and Amplify Partners, with additional
backing from notable investors, including first round capital and why Combinator.
(01:00):
David AI's mission is to seamlessly integrate AI into the real world through voice interfaces,
recognizing that many promising AI applications such as humanoid robots and wearable devices
rely heavily on voice interaction. The startup addresses a critical bottleneck
in the audio AI industry, the scarcity of high quality training data. While AI phone
(01:26):
agents are gaining traction, the development of more complex voice AI systems requires
millions of hours of full duplex, channel separated speech data, far more than the currently
available datasets offer. David AI tackles this challenge by meticulously
building and scaling audio datasets, focusing exclusively on audio to ensure unparalleled
(01:50):
quality and efficacy in model training. This unique approach positions David AI as a key
enabler for the next generation of voice driven AI applications.
T-Bolt and Simi Lone faced significant challenges building their dream home in Portugal, which
inspired them to create Lida House, a startup designed to streamline and innovate the home
(02:15):
building process. Lida House acts like the Uber of construction, connecting landowners
and property developers with professionals such as architects and contractors. The platform
enables users to track costs, manage schedules and monitor building progress in real time,
(02:35):
addressing a fragmented industry plagued with inefficiencies. Lida House focuses on modular
construction, claiming its approach is 30% cheaper, 40% faster and 60% more sustainable
than traditional methods, significantly reducing waste and CO2 emissions. The company distinguishes
(02:56):
itself by integrating innovative construction technology, a sector gaining traction in the
US but underdeveloped in Europe. Recently, Lida House secured a 1,460,000 euro pre-seed
round to expand operations aiming to become Europe's fastest growing construction tech
startup. Investors see potential in Lighthouse's vision to make home building as straightforward
(03:23):
as home buying, offering greater transparency, sustainability and trust in the construction
industry, addressing the pressing housing shortage in Europe. And now, pivot our discussion
towards the main entrepreneurship topic. Today, we're going to explore why Combinator's latest
(03:47):
requests for startups for 2025, and it's fascinating to see how they're doubling down on what
they're calling the Year of AI Agents. These aren't just incremental improvements we're talking
about. YC is essentially mapping out a blueprint for how artificial intelligence can transform
entire industries from the ground up. What makes this particularly compelling is that they're not
(04:10):
just looking for AI tools that help existing businesses work better. They're actively seeking
founders who will use AI to completely reimagine how work gets done across sectors like healthcare,
education, legal services and even personal productivity. Thanks for that excellent introduction,
Donna. This really is an exciting time to be thinking about the intersection of AI and entrepreneurship.
(04:37):
I'm ready to dive deep into what YC is actually looking for this year. Why don't you ask me your
first question? Let's start with this concept of full stack AI companies that YC is promoting.
What exactly does that mean? Full stack AI companies represent a fundamental shift in
how we think about AI implementation. Instead of building AI tools to sell to existing industries,
(05:01):
these companies use AI to become the industry themselves. The classic example YC gives is
legal services. Rather than creating an AI agent to sell to law firms, you'd start your own law firms
staffed with AI agents and directly compete with traditional firms. This approach is particularly
powerful in industries dominated by slow moving incumbents because instead of trying to convince
(05:26):
dinosaurs to change, you're making them extinct by offering superior service at potentially lower
costs. That's a bold approach. Now there's also significant emphasis on design founders this year.
What's driving that focus? YC recognizes that as coding tools become more accessible
and AI makes building products easier than ever, great design is going to be the key differentiator.
(05:50):
They're particularly encouraging designers who are worried about AI replacing their jobs to flip
the script and use AI themselves to launch their own companies. Designers already possess the
essential founder skills, strong user empathy, problem solving focus, high quality standards,
and taste. YC points to their biggest successes like Airbnb and Stripe, noting that without
(06:16):
exceptional design, users never would have trusted staying in strangers homes or processing billions
in credit card transactions. The design job of the future, they argue, is actually founder.
Speaking of transforming traditional interactions, what's YC's take on voice AI opportunities?
Voice AI represents a massive opportunity to modernize something that changed in almost a century,
(06:42):
phone calls with businesses. We all know the frustration, long wait times, confusing voice
trees, pressing star and pound keys, all because we desperately want to reach a human agent since
the alternatives have been terrible. But the new voice models and conversational LLMs have reached
a quality threshold where AI bots are now indistinguishable from humans. YC sees this as
(07:09):
similar to riding in an autonomous car for the first time. It just works, and it feels like
experiencing the future. With over a trillion calls happening between businesses and customers
annually, the market opportunity is enormous for startups that can capitalize on these
improved voice AI capabilities. That's impressive scale. How does YC see AI transforming scientific
(07:34):
advancement? YC identifies a significant gap in scientific software tools that haven't evolved
much in decades. Fields like chemistry, biology, materials, science and operations research still
rely on standard methods and PhD level expertise to solve complex problems in drug discovery,
chemical process optimization, metals and mining, or power grid optimization.
(08:00):
What's particularly exciting is that test time compute is now unlocking new types of startups
that can tackle these scientific challenges directly. YC wants to see more startups using
AI to transform how physical things are made, making processes faster and more efficient
across these traditionally slow moving scientific domains.
(08:23):
Let's talk about personal productivity. What's YC's vision for AI personal assistance?
Despite decades of productivity apps, we still struggle with overflowing emails, packed calendars
and endless to-do lists. YC envisions moving from to-do lists to done lists through LLM powered
systems that deeply understand your work patterns, routines, communication history, and personal
(08:49):
preferences. This isn't just another calendar app. They want AI assistance with perfect memory of
your correspondence and projects that can draft emails in your style, auto-schedule meetings
based on your preferences, and handle recurring processes without constant input. Think of it
as having a human personal assistant or chief of staff, but powered by AI that truly understands
(09:15):
how you work and can take meaningful action on your behalf.
Healthcare seems like another major focus area. What specific problems is YC targeting there?
Healthcare represents a massive opportunity. It's over 17% of GDP, about $4 trillion, with estimates
that one third of that spending, over $1 trillion, goes purely to administrative tasks. This waste
(09:40):
exists because health systems aren't interoperable, lack APIs, or require humans to manually transfer
data between systems. The breakthrough is that recent LLMs can now extract data from PDFs and
other systems, organize it, and automatically enter it into different systems through AI agents.
(10:02):
YC sees enormous potential for startups that can automate these administrative healthcare costs,
making the U.S. healthcare system significantly more efficient by solving these interoperability
and workflow issues. Education has always been a challenging sector to disrupt.
How does YC see AI changing that landscape? YC is excited about AI finally making personalized
(10:27):
learning possible, something computer scientists have dreamed about since the 1940s, with ideas like
Vannevar Bush's MIMEX. The latest reasoning capabilities allow AI to break down complex
topics step by step, while multimodal foundation models can present concepts through generated
animations, 3D object manipulation, and voice explanations. They envision having the same
(10:53):
quality of explanation that someone like Grant Sanderson provides with his three blue, brown
YouTube videos, but available for every topic and personalized to each learner's needs.
This could fundamentally change how the world learns, making high quality, interactive tutoring
accessible to everyone, rather than delivering the same generic content to all students.
(11:18):
There's also mention of robotics. What's YC's perspective on that industry?
YC believes robotics is approaching its chat GPT moment, while everyone has known robots are the
future. Previous generations were expensive, brittle, and only worked in controlled conditions.
The missing piece has been human level perception and judgment, which rapid improvements in
(11:41):
foundation models are now making possible. Rather than focusing on consumer applications
that dominate science fiction, YC sees the most immediate opportunities in B2B applications.
Industrial use cases like gecko robotics, inspection robots, and farming applications
like bear flag robotics, autonomous tractors. They're particularly interested in funding
(12:07):
people building software tools to help others make robots, recognizing that the infrastructure layer
could be as important as the robots themselves. Let's discuss the broader future of education
beyond just AI tutoring. What's YC's larger vision?
Education is one of the world's largest industries. About 100 million people employed
(12:28):
and 1.5 billion students educated annually. Yet it's remained largely unchanged for decades.
YC sees AI, particularly large language models, as having the potential to reshape teaching,
learning, and outcome measurement entirely. They're seeing early personalized study tools for
(12:49):
students and grading platforms for teachers, but acknowledge we're still very early in
understanding AI's full potential here. The big challenge is the business model.
While over a billion people are engaged in education, budgets are notoriously tight,
and purchasing cycles are incredibly slow. But YC is confident that education simply
(13:12):
cannot continue operating the same way 10 or 20 years from now.
Home security seems like an interesting application area. What opportunity does YC see there?
Consumer home security is a $20 billion annual market, dominated by legacy companies whose
features haven't evolved in decades. Meanwhile, AI is revolutionizing commercial security through
(13:36):
companies like Verkada and Lumana. Doors unlock with facial recognition. Cameras detect suspicious
behavior and send push notifications, and virtual AI guards use loudspeakers to scare away criminals
before crimes happen. Ring was acquired for $1 billion just for making video doorbells and
magnetic door sensors. YC sees enormous potential for the company that uses AI to make people feel
(14:02):
actually safe in their homes, bringing the same AI-powered security capabilities from commercial
buildings into residential settings. There's also focus on internal tools for companies.
Can you explain the internal agent builder concept? YC predicts that soon every company
employee will build their own agents to automate repetitive job tasks, and they want to fund the
(14:25):
infrastructure that enables this. An internal agent builder would be a tool that lets anyone
create agents to handle mundane tasks they dislike doing. This infrastructure needs to access
every piece of software in someone's daily workflow, manage permissions securely,
and send sensitive data safely to the latest LLMs. YC has built and deployed a version
(14:50):
internally, using it to reduce time spent on everything from reviewing term sheets to repetitive
accounting workflows. This frees humans from mundane tasks so they can focus on what humans
uniquely do well, in their case working directly with founders.
I see has an interesting history with AI research. What's their current stance on funding research
(15:12):
labs? Many people don't realize YC was actually open AI's first investor. Open AI began as YC
research, their in-house research lab. YC pioneered the concept of independent AI research labs
and had a front row seat to open AI's entire journey. While open AI is doing incredible work,
(15:36):
YC believes there are many unsolved AI problems and plenty of opportunity for new research labs.
They want to dispel the notion that YC companies must ship products in three months. They're excited
to back deep, open-ended research that may take years to commercialize, just like open AI did.
(15:57):
Their experience shows that when top researchers follow their interests,
it often leads somewhere genuinely interesting and valuable.
Finally, let's talk about some specific AI applications YC is excited about. What about
voice assistance for email? YC wants to meet teams building voice-powered email processing
systems. The vision is using driving time, those 20 minutes commuting each day, to triage emails,
(16:23):
draft replies and delegate scheduling tasks, arriving at work already at inbox zero.
With tools like Vapi, Retell and ChatGPT's advanced voice mode, demonstrating how good
voice agents have become, the use cases extend far beyond just driving. Email could be the perfect
(16:45):
starting place for building comprehensive voice assistance because access to someone's inbox
instantly reveals their friends, plans, writing style and much more personal context that enables
truly useful assistance. And what about personal finance? How does AI fit there? Most humans aren't
rational about finances but life requires constant financial decisions about saving,
(17:10):
investing, debt and taxes that will impact future freedom and opportunities.
Traditional options for financial advice, asking friends, googling, hiring advisors or
consulting banks are filled with bias and don't have complete pictures of individual situations.
Great financial advisors are also very expensive. YC sees a unique opportunity for LLMs to provide
(17:36):
personalized finance, investment and tax advice at near zero cost. These systems would use APIs to
access complete financial situations and deliver completely personal, unbiased advice.
This could democratize high quality financial guidance that's currently only available to
wealthy individuals who can afford premium advisory services. This has been fascinating,
(18:00):
Yaakov. Any final thoughts on what makes this year's RFS particularly significant?
What strikes me most about YC's 2025 RFS is how it represents a maturation of AI from
experimental technology to foundational infrastructure for entirely new business models.
These aren't incremental improvements to existing processes, they're blueprints for
(18:24):
rebuilding industries from the ground up. Whether it's full stack AI companies competing directly
with incumbents or AI agents handling everything from scientific research to personal finance,
YC is betting that 2025 will be remembered as the year AI moved from being a tool that
helps existing businesses to being the foundation for entirely new categories of companies.
(18:50):
The entrepreneurs who succeed will be those who see AI not as an add-on feature, but as the core
capability that enables completely new approaches to solving human problems.
We've explored how David AI is advancing audio AI with significant funding and Lighthouse is
(19:13):
innovating the construction industry with modular solutions. Why combinators vision for 2025?
Highlights AI's transformative role across sectors. Pushing for full stack AI companies in
healthcare, education and more. Don't forget to like, subscribe and share this episode with your
(19:35):
friends and colleagues so they can also stay updated on the latest news and gain powerful
insights. Stay tuned for more updates.
Welcome to Innovation Pulse, your quick no-nonsense update covering the latest in startups and
(00:09):
entrepreneurship news. First, we will cover the latest news.
David AI secures 25 million for audio AI advancements, while Lighthouse raises $1.46 million
to revolutionize construction with modular methods. After this, we'll dive deep into
why combinators 2025 vision for AI agents transforming industries.
(00:35):
David AI is revolutionizing the audio AI landscape by establishing itself as the world's first
audio data research company. Founded less than a year ago, the company has already secured
a $25 million Series A funding round led by Alt Capital and Amplify Partners, with additional
backing from notable investors, including first round capital and why Combinator.
(01:00):
David AI's mission is to seamlessly integrate AI into the real world through voice interfaces,
recognizing that many promising AI applications such as humanoid robots and wearable devices
rely heavily on voice interaction. The startup addresses a critical bottleneck
in the audio AI industry, the scarcity of high quality training data. While AI phone
(01:26):
agents are gaining traction, the development of more complex voice AI systems requires
millions of hours of full duplex, channel separated speech data, far more than the currently
available datasets offer. David AI tackles this challenge by meticulously
building and scaling audio datasets, focusing exclusively on audio to ensure unparalleled
(01:50):
quality and efficacy in model training. This unique approach positions David AI as a key
enabler for the next generation of voice driven AI applications.
T-Bolt and Simi Lone faced significant challenges building their dream home in Portugal, which
inspired them to create Lida House, a startup designed to streamline and innovate the home
(02:15):
building process. Lida House acts like the Uber of construction, connecting landowners
and property developers with professionals such as architects and contractors. The platform
enables users to track costs, manage schedules and monitor building progress in real time,
(02:35):
addressing a fragmented industry plagued with inefficiencies. Lida House focuses on modular
construction, claiming its approach is 30% cheaper, 40% faster and 60% more sustainable
than traditional methods, significantly reducing waste and CO2 emissions. The company distinguishes
(02:56):
itself by integrating innovative construction technology, a sector gaining traction in the
US but underdeveloped in Europe. Recently, Lida House secured a 1,460,000 euro pre-seed
round to expand operations aiming to become Europe's fastest growing construction tech
startup. Investors see potential in Lighthouse's vision to make home building as straightforward
(03:23):
as home buying, offering greater transparency, sustainability and trust in the construction
industry, addressing the pressing housing shortage in Europe. And now, pivot our discussion
towards the main entrepreneurship topic. Today, we're going to explore why Combinator's latest
(03:47):
requests for startups for 2025, and it's fascinating to see how they're doubling down on what
they're calling the Year of AI Agents. These aren't just incremental improvements we're talking
about. YC is essentially mapping out a blueprint for how artificial intelligence can transform
entire industries from the ground up. What makes this particularly compelling is that they're not
(04:10):
just looking for AI tools that help existing businesses work better. They're actively seeking
founders who will use AI to completely reimagine how work gets done across sectors like healthcare,
education, legal services and even personal productivity. Thanks for that excellent introduction,
Donna. This really is an exciting time to be thinking about the intersection of AI and entrepreneurship.
(04:37):
I'm ready to dive deep into what YC is actually looking for this year. Why don't you ask me your
first question? Let's start with this concept of full stack AI companies that YC is promoting.
What exactly does that mean? Full stack AI companies represent a fundamental shift in
how we think about AI implementation. Instead of building AI tools to sell to existing industries,
(05:01):
these companies use AI to become the industry themselves. The classic example YC gives is
legal services. Rather than creating an AI agent to sell to law firms, you'd start your own law firms
staffed with AI agents and directly compete with traditional firms. This approach is particularly
powerful in industries dominated by slow moving incumbents because instead of trying to convince
(05:26):
dinosaurs to change, you're making them extinct by offering superior service at potentially lower
costs. That's a bold approach. Now there's also significant emphasis on design founders this year.
What's driving that focus? YC recognizes that as coding tools become more accessible
and AI makes building products easier than ever, great design is going to be the key differentiator.
(05:50):
They're particularly encouraging designers who are worried about AI replacing their jobs to flip
the script and use AI themselves to launch their own companies. Designers already possess the
essential founder skills, strong user empathy, problem solving focus, high quality standards,
and taste. YC points to their biggest successes like Airbnb and Stripe, noting that without
(06:16):
exceptional design, users never would have trusted staying in strangers homes or processing billions
in credit card transactions. The design job of the future, they argue, is actually founder.
Speaking of transforming traditional interactions, what's YC's take on voice AI opportunities?
Voice AI represents a massive opportunity to modernize something that changed in almost a century,
(06:42):
phone calls with businesses. We all know the frustration, long wait times, confusing voice
trees, pressing star and pound keys, all because we desperately want to reach a human agent since
the alternatives have been terrible. But the new voice models and conversational LLMs have reached
a quality threshold where AI bots are now indistinguishable from humans. YC sees this as
(07:09):
similar to riding in an autonomous car for the first time. It just works, and it feels like
experiencing the future. With over a trillion calls happening between businesses and customers
annually, the market opportunity is enormous for startups that can capitalize on these
improved voice AI capabilities. That's impressive scale. How does YC see AI transforming scientific
(07:34):
advancement? YC identifies a significant gap in scientific software tools that haven't evolved
much in decades. Fields like chemistry, biology, materials, science and operations research still
rely on standard methods and PhD level expertise to solve complex problems in drug discovery,
chemical process optimization, metals and mining, or power grid optimization.
(08:00):
What's particularly exciting is that test time compute is now unlocking new types of startups
that can tackle these scientific challenges directly. YC wants to see more startups using
AI to transform how physical things are made, making processes faster and more efficient
across these traditionally slow moving scientific domains.
(08:23):
Let's talk about personal productivity. What's YC's vision for AI personal assistance?
Despite decades of productivity apps, we still struggle with overflowing emails, packed calendars
and endless to-do lists. YC envisions moving from to-do lists to done lists through LLM powered
systems that deeply understand your work patterns, routines, communication history, and personal
(08:49):
preferences. This isn't just another calendar app. They want AI assistance with perfect memory of
your correspondence and projects that can draft emails in your style, auto-schedule meetings
based on your preferences, and handle recurring processes without constant input. Think of it
as having a human personal assistant or chief of staff, but powered by AI that truly understands
(09:15):
how you work and can take meaningful action on your behalf.
Healthcare seems like another major focus area. What specific problems is YC targeting there?
Healthcare represents a massive opportunity. It's over 17% of GDP, about $4 trillion, with estimates
that one third of that spending, over $1 trillion, goes purely to administrative tasks. This waste
(09:40):
exists because health systems aren't interoperable, lack APIs, or require humans to manually transfer
data between systems. The breakthrough is that recent LLMs can now extract data from PDFs and
other systems, organize it, and automatically enter it into different systems through AI agents.
(10:02):
YC sees enormous potential for startups that can automate these administrative healthcare costs,
making the U.S. healthcare system significantly more efficient by solving these interoperability
and workflow issues. Education has always been a challenging sector to disrupt.
How does YC see AI changing that landscape? YC is excited about AI finally making personalized
(10:27):
learning possible, something computer scientists have dreamed about since the 1940s, with ideas like
Vannevar Bush's MIMEX. The latest reasoning capabilities allow AI to break down complex
topics step by step, while multimodal foundation models can present concepts through generated
animations, 3D object manipulation, and voice explanations. They envision having the same
(10:53):
quality of explanation that someone like Grant Sanderson provides with his three blue, brown
YouTube videos, but available for every topic and personalized to each learner's needs.
This could fundamentally change how the world learns, making high quality, interactive tutoring
accessible to everyone, rather than delivering the same generic content to all students.
(11:18):
There's also mention of robotics. What's YC's perspective on that industry?
YC believes robotics is approaching its chat GPT moment, while everyone has known robots are the
future. Previous generations were expensive, brittle, and only worked in controlled conditions.
The missing piece has been human level perception and judgment, which rapid improvements in
(11:41):
foundation models are now making possible. Rather than focusing on consumer applications
that dominate science fiction, YC sees the most immediate opportunities in B2B applications.
Industrial use cases like gecko robotics, inspection robots, and farming applications
like bear flag robotics, autonomous tractors. They're particularly interested in funding
(12:07):
people building software tools to help others make robots, recognizing that the infrastructure layer
could be as important as the robots themselves. Let's discuss the broader future of education
beyond just AI tutoring. What's YC's larger vision?
Education is one of the world's largest industries. About 100 million people employed
(12:28):
and 1.5 billion students educated annually. Yet it's remained largely unchanged for decades.
YC sees AI, particularly large language models, as having the potential to reshape teaching,
learning, and outcome measurement entirely. They're seeing early personalized study tools for
(12:49):
students and grading platforms for teachers, but acknowledge we're still very early in
understanding AI's full potential here. The big challenge is the business model.
While over a billion people are engaged in education, budgets are notoriously tight,
and purchasing cycles are incredibly slow. But YC is confident that education simply
(13:12):
cannot continue operating the same way 10 or 20 years from now.
Home security seems like an interesting application area. What opportunity does YC see there?
Consumer home security is a $20 billion annual market, dominated by legacy companies whose
features haven't evolved in decades. Meanwhile, AI is revolutionizing commercial security through
(13:36):
companies like Verkada and Lumana. Doors unlock with facial recognition. Cameras detect suspicious
behavior and send push notifications, and virtual AI guards use loudspeakers to scare away criminals
before crimes happen. Ring was acquired for $1 billion just for making video doorbells and
magnetic door sensors. YC sees enormous potential for the company that uses AI to make people feel
(14:02):
actually safe in their homes, bringing the same AI-powered security capabilities from commercial
buildings into residential settings. There's also focus on internal tools for companies.
Can you explain the internal agent builder concept? YC predicts that soon every company
employee will build their own agents to automate repetitive job tasks, and they want to fund the
(14:25):
infrastructure that enables this. An internal agent builder would be a tool that lets anyone
create agents to handle mundane tasks they dislike doing. This infrastructure needs to access
every piece of software in someone's daily workflow, manage permissions securely,
and send sensitive data safely to the latest LLMs. YC has built and deployed a version
(14:50):
internally, using it to reduce time spent on everything from reviewing term sheets to repetitive
accounting workflows. This frees humans from mundane tasks so they can focus on what humans
uniquely do well, in their case working directly with founders.
I see has an interesting history with AI research. What's their current stance on funding research
(15:12):
labs? Many people don't realize YC was actually open AI's first investor. Open AI began as YC
research, their in-house research lab. YC pioneered the concept of independent AI research labs
and had a front row seat to open AI's entire journey. While open AI is doing incredible work,
(15:36):
YC believes there are many unsolved AI problems and plenty of opportunity for new research labs.
They want to dispel the notion that YC companies must ship products in three months. They're excited
to back deep, open-ended research that may take years to commercialize, just like open AI did.
(15:57):
Their experience shows that when top researchers follow their interests,
it often leads somewhere genuinely interesting and valuable.
Finally, let's talk about some specific AI applications YC is excited about. What about
voice assistance for email? YC wants to meet teams building voice-powered email processing
systems. The vision is using driving time, those 20 minutes commuting each day, to triage emails,
(16:23):
draft replies and delegate scheduling tasks, arriving at work already at inbox zero.
With tools like Vapi, Retell and ChatGPT's advanced voice mode, demonstrating how good
voice agents have become, the use cases extend far beyond just driving. Email could be the perfect
(16:45):
starting place for building comprehensive voice assistance because access to someone's inbox
instantly reveals their friends, plans, writing style and much more personal context that enables
truly useful assistance. And what about personal finance? How does AI fit there? Most humans aren't
rational about finances but life requires constant financial decisions about saving,
(17:10):
investing, debt and taxes that will impact future freedom and opportunities.
Traditional options for financial advice, asking friends, googling, hiring advisors or
consulting banks are filled with bias and don't have complete pictures of individual situations.
Great financial advisors are also very expensive. YC sees a unique opportunity for LLMs to provide
(17:36):
personalized finance, investment and tax advice at near zero cost. These systems would use APIs to
access complete financial situations and deliver completely personal, unbiased advice.
This could democratize high quality financial guidance that's currently only available to
wealthy individuals who can afford premium advisory services. This has been fascinating,
(18:00):
Yaakov. Any final thoughts on what makes this year's RFS particularly significant?
What strikes me most about YC's 2025 RFS is how it represents a maturation of AI from
experimental technology to foundational infrastructure for entirely new business models.
These aren't incremental improvements to existing processes, they're blueprints for
(18:24):
rebuilding industries from the ground up. Whether it's full stack AI companies competing directly
with incumbents or AI agents handling everything from scientific research to personal finance,
YC is betting that 2025 will be remembered as the year AI moved from being a tool that
helps existing businesses to being the foundation for entirely new categories of companies.
(18:50):
The entrepreneurs who succeed will be those who see AI not as an add-on feature, but as the core
capability that enables completely new approaches to solving human problems.
We've explored how David AI is advancing audio AI with significant funding and Lighthouse is
(19:13):
innovating the construction industry with modular solutions. Why combinators vision for 2025?
Highlights AI's transformative role across sectors. Pushing for full stack AI companies in
healthcare, education and more. Don't forget to like, subscribe and share this episode with your
(19:35):
friends and colleagues so they can also stay updated on the latest news and gain powerful
insights. Stay tuned for more updates.
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I’m Jay Shetty host of On Purpose the worlds #1 Mental Health podcast and I’m so grateful you found us. I started this podcast 5 years ago to invite you into conversations and workshops that are designed to help make you happier, healthier and more healed. I believe that when you (yes you) feel seen, heard and understood you’re able to deal with relationship struggles, work challenges and life’s ups and downs with more ease and grace. I interview experts, celebrities, thought leaders and athletes so that we can grow our mindset, build better habits and uncover a side of them we’ve never seen before. New episodes every Monday and Friday. Your support means the world to me and I don’t take it for granted — click the follow button and leave a review to help us spread the love with On Purpose. I can’t wait for you to listen to your first or 500th episode!
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Does hearing about a true crime case always leave you scouring the internet for the truth behind the story? Dive into your next mystery with Crime Junkie. Every Monday, join your host Ashley Flowers as she unravels all the details of infamous and underreported true crime cases with her best friend Brit Prawat. From cold cases to missing persons and heroes in our community who seek justice, Crime Junkie is your destination for theories and stories you won’t hear anywhere else. Whether you're a seasoned true crime enthusiast or new to the genre, you'll find yourself on the edge of your seat awaiting a new episode every Monday. If you can never get enough true crime... Congratulations, you’ve found your people. Follow to join a community of Crime Junkies! Crime Junkie is presented by audiochuck Media Company.
Ridiculous History
History is beautiful, brutal and, often, ridiculous. Join Ben Bowlin and Noel Brown as they dive into some of the weirdest stories from across the span of human civilization in Ridiculous History, a podcast by iHeartRadio.