August 18, 2025 • 14 mins
Time to Exit: Are Startups Getting Older?
Sam Altman Co-Founds Merge Labs to Compete with Elon Musk's Neuralink
When Giants Burn Their Own Businesses Down - OpenAI vs Anthropic
#OpenAI, #Anthropic, #Startups, #TechGiants, #SamAltman, #Neuralink, #BusinessCompetition
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.
Startups are staying private longer, with IPO ages reaching 13.5 years in 2024, while
Sam Altman co-found Merge Labs, a brain-to-computer interface startup.
After this, we'll dive deep into OpenAI's bold move to cut AI service prices by 90%,
(00:34):
aiming to revolutionise the advertising market by transforming AI interactions into ad opportunities.
Stay tuned.
The startup landscape is evolving, with companies taking longer to exit or pursue an initial
public offering, resulting in an increase in the median age of startups at the time of
public offering.
(00:55):
The median age was 13.5 years in 2024, reflecting a trend where startups remain private longer
to maintain control and avoid public market scrutiny.
Factors contributing to this include increased availability of private capital, regulatory
pressures and a focus on profitability before going public.
(01:18):
The private market is projected to grow from $13 trillion in 2024 to $20 trillion by 2030,
enabling startups to sustain longer private phases.
For private market investors, this means longer holding periods, a shift towards later stage
investments and a heightened importance of secondary sales for liquidity.
(01:42):
To adapt, investors might consider extending fund life cycles, diversifying across different
stages, leveraging secondary markets and emphasising sustainable growth in their portfolios.
As startups age, investors must remain agile and informed to capitalise on emerging opportunities
and navigate liquidity challenges.
(02:08):
Sam Altman is co-founding a new startup called Merge Labs, focused on developing brain-to-computer
interfaces, a field currently led by Elon Musk's Neuralink.
Merge Labs is in the early stages of fundraising, potentially reaching a valuation of $850
million, with OpenAI's Ventures team as a possible investor.
(02:30):
Although negotiations are ongoing and OpenAI hasn't confirmed participation, the venture
is generating interest due to Altman's involvement and the potential to revolutionise human-tech
interaction.
Merge Labs collaborates with Alex Blania from Tools for Humanity, expanding on Altman's
vision of verifying human identity through digital means.
(02:54):
This positions Merge Labs as a competitor to Neuralink, which is advancing in trials
to help individuals with paralysis control devices using thoughts backed by a $600 million
funding round at a $9 billion valuation.
The concept of merging technology with humans, often referred to as the singularity, is a
(03:17):
shared interest of both Altman and Musk.
Altman previously blogged about this futuristic idea for seeing humans designing their own
tech integrated descendants.
With both leaders having a history of rivalry, Merge Labs emerges as a potential challenger
in this transformative tech space.
(03:40):
And now, pivot our discussion towards the main entrepreneurship topic.
Welcome back to Innovation Pulse.
I'm Donna, and today I've got strategy expert Yakov Lasker with me to unpack one of the
wildest business moves I've seen all year.
(04:00):
Yakov, you've been tracking this OpenAI situation, and honestly, when you first told me about
it, I thought you were making it up.
Right?
So picture this.
You're making decent money selling premium AI services, your competitor swoops in and
steals a third of your market share, and your response is to cut your own prices by 90%
(04:23):
and basically destroy your entire business model.
Most people would call that insane.
But you're telling me this is actually genius?
Not just genius.
It's one of the oldest plays in the tech playbook.
It's called commoditizing your compliments.
And once you see it, you can't unsee it.
Disney does it.
Google does it.
(04:43):
Even your local casino does it.
Okay, hold up.
Disney?
The company that charges me $40 for a turkey sandwich?
Ah, but here's the thing.
They make parking free.
Well, they use to.
The principle is this.
Pick one thing that makes you obscene amounts of money, then make everything else around
it so cheap that your competitors can't survive.
(05:07):
So Disney makes their real money on...
In-park purchases.
Those $40 turkey sandwiches.
So they used to make hotels, parking, even flights cheaper to get more people through
the gates.
More people means more overpriced sandwiches.
That's actually pretty devious.
But wait, what does this have to do with open AI burning down their AI business?
(05:30):
Because open AI realized they were fighting the wrong war.
While everyone's obsessing over who has the best AI model, open AI looked at where the
real money is in tech.
There are basically four kingdoms of profit.
Advertising at $334 billion.
(05:50):
Cloud computing at $193 billion.
Enterprise software at $132 billion.
And productivity tools at another $132 billion.
Those are enormous numbers.
So which kingdom did open AI choose?
Advertising.
The monster.
Google makes $207 billion just from ads.
(06:11):
Santa adds another $127 billion.
That's more profit than most countries entire GDP.
Oh!
So when open AI hired that meta executive, what was her name?
Kate something?
Kate Roach, who ran Facebook's Ad Machine for 11 years.
You don't hire the architect of Instagram's ad system to optimize subscription pricing.
(06:32):
You hire them because you're about to summon the advertising monster.
And the monster wants everything else to be free.
Exactly.
Think about it.
Google built Chrome and gave it away for free because every Chrome download funnels people
into their $207 billion advertising empire.
Facebook literally paid Samsung bags of cash to pre-install their app, then subsidized
(06:56):
phones across Africa.
Why?
Because cheaper phones and cheaper internet equals more users equals more ads.
So open AI is making AI inference free to...
To become the default place, people go to think, to search, to create.
They've got 3.6 billion in consumer subscriptions versus only 1.4 billion in API revenue.
(07:20):
They make more money from people paying $20 a month than from enterprises paying millions.
Wait, that seems backwards though.
Shouldn't enterprise customers be worth more?
Not if you're playing the advertising game.
Their eyeballs are worth way more in the long run.
But here's where it gets really interesting.
While open AI was making this strategic pivot, Anthropics was actually winning the infrastructure
(07:45):
war.
How so?
They went from 12% market share to 32% in just 18 months.
They kept prices flat at $75 per million tokens for their top model while open AI was fumbling
around.
And get this.
Anthropics CEO basically admitted they're already profitable on inference.
(08:05):
No way!
I thought everyone was losing money on AI.
That's what makes this so brutal.
Anthropics figured out how to make the AWS of AI actually work.
They dominated coding.
Cursor, Windsurf, all those AI coding tools run on Claude.
They had better reliability, better enterprise features, no drama about their AI making cartoon
(08:28):
characters when it should be running trading desks.
And then open AI just torched it all?
Dropped GPT-5 at $10 per million tokens.
Same performance as Claude's premium offering, but at one-tenth the price.
Every single AI coding tool, cursor, lovable, bolt, devon, they all became open AI launch
(08:50):
partners overnight.
That's got to hurt.
But I'm still confused about something.
If open AI could charge decent margins and still move into advertising, why burn the whole
business down?
Because they're not just competing with Anthropic anymore.
They're declaring war on Google.
On the entire old world of how tech makes money.
(09:11):
Remember, Google and Meta have the same incentive.
They need tokens to be free to protect their advertising empires.
Oh, so this is really about the big picture.
Exactly.
This actually connects to something bigger.
Overwatching these AI companies' paths diverge in real time.
Open AI can afford to let the API business die because they're chasing the $334 billion
(09:37):
advertising kingdom.
But for Anthropic, this is existential.
So what can Anthropic do?
Are they just stuck?
They've got some cards to play.
Their CEO mentioned they could charge real margins for reinforcement learning, interpretability,
fine-tuning.
The advanced stuff enterprises actually need.
(09:57):
Plus their contracts are sticky.
If you know anything about enterprise software, companies aren't as price sensitive when
it comes to reliability and compliance.
But here's what I'm wondering.
Could Anthropic just move up the stack?
Like instead of competing on infrastructure, compete on applications?
That's brilliant.
They're already testing this with Claude Code, which looks suspiciously like cursor.
(10:21):
And their desktop app is making those AI artifacts hostable, putting them in direct
competition with app builders like Lovable and Bolt.
So they could go after those other profit kingdoms.
The productivity tools are enterprise systems?
Right.
There's 132 billion sitting in productivity software that people hate using but can't
(10:42):
live without.
Microsoft Office, Adobe Creative Suite, or the Systems of Record, Salesforce, Oracle,
SAP, the databases that run the world.
This is where it gets wild though, because we're not just talking about two AI companies
having a pricing war.
(11:02):
This is about the entire future of how we interact with computers.
And here's the kicker.
Open AI's move only makes sense if they're absolutely committed to the advertising model.
Because once you start giving away inference for free, you can't really go back.
You've commoditized your own product.
So they've literally burned the boats.
(11:24):
Completely.
But remember when we talked about Disney?
Well, this changes everything about how we think about AI business models.
Because if open AI succeeds, every AI interaction becomes a potential ad placement.
Your coding assistant suggests libraries based on sponsorships.
Your writing assistant promotes certain products.
(11:46):
Your search results get influenced by who paid the most.
That's actually kind of terrifying when you put it that way.
It's the exact same playbook that turned the internet into an advertising machine.
And now open AI is betting they can do it to artificial intelligence.
So what should we be watching for?
How do we know if this strategy is working?
(12:06):
Keep an eye on open AI's hiring.
More advertising executives means they're doubling down.
Watch their consumer product launches.
If they start integrating shopping or sponsored content, that's your signal.
And for Anthropik, watch whether they can successfully move up the stack into higher
margin applications.
But here's my big takeaway.
(12:27):
This isn't really about AI at all, is it?
It's about recognizing which game you're actually playing.
Exactly.
Most companies think they're competing on product features, but the real competition
is about business models.
Everyone AI looked at their situation and realized they weren't in the AI inference
business.
They were in the human attention business.
(12:49):
So next time you're wondering why a company is making what seems like a destructive decision,
ask yourself, what's the real product they're selling?
Because I guarantee you, it's probably not what you think.
And remember, in tech, the company willing to commoditize the thing everyone else thinks
is valuable, that's usually the company that wins.
(13:09):
That's innovation pulse for today.
Thanks for helping us decode this wild business chess match, Yakov.
Always fun to peek behind the curtain with you, Donna.
Until next time, keep questioning the obvious.
That's it for today's podcast.
We explored the extended timeline for startups going public and Sam Altman's venture into
(13:32):
brain-to-computer interfaces.
Alongside OpenAI's bold move to slash AI service prices to pivot towards the advertising
market.
Don't forget to like, subscribe, and share this episode with your friends and colleagues
so they can also stay updated on the latest news and gain powerful insights.
(13:53):
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.
Startups are staying private longer, with IPO ages reaching 13.5 years in 2024, while
Sam Altman co-found Merge Labs, a brain-to-computer interface startup.
After this, we'll dive deep into OpenAI's bold move to cut AI service prices by 90%,
(00:34):
aiming to revolutionise the advertising market by transforming AI interactions into ad opportunities.
Stay tuned.
The startup landscape is evolving, with companies taking longer to exit or pursue an initial
public offering, resulting in an increase in the median age of startups at the time of
public offering.
(00:55):
The median age was 13.5 years in 2024, reflecting a trend where startups remain private longer
to maintain control and avoid public market scrutiny.
Factors contributing to this include increased availability of private capital, regulatory
pressures and a focus on profitability before going public.
(01:18):
The private market is projected to grow from $13 trillion in 2024 to $20 trillion by 2030,
enabling startups to sustain longer private phases.
For private market investors, this means longer holding periods, a shift towards later stage
investments and a heightened importance of secondary sales for liquidity.
(01:42):
To adapt, investors might consider extending fund life cycles, diversifying across different
stages, leveraging secondary markets and emphasising sustainable growth in their portfolios.
As startups age, investors must remain agile and informed to capitalise on emerging opportunities
and navigate liquidity challenges.
(02:08):
Sam Altman is co-founding a new startup called Merge Labs, focused on developing brain-to-computer
interfaces, a field currently led by Elon Musk's Neuralink.
Merge Labs is in the early stages of fundraising, potentially reaching a valuation of $850
million, with OpenAI's Ventures team as a possible investor.
(02:30):
Although negotiations are ongoing and OpenAI hasn't confirmed participation, the venture
is generating interest due to Altman's involvement and the potential to revolutionise human-tech
interaction.
Merge Labs collaborates with Alex Blania from Tools for Humanity, expanding on Altman's
vision of verifying human identity through digital means.
(02:54):
This positions Merge Labs as a competitor to Neuralink, which is advancing in trials
to help individuals with paralysis control devices using thoughts backed by a $600 million
funding round at a $9 billion valuation.
The concept of merging technology with humans, often referred to as the singularity, is a
(03:17):
shared interest of both Altman and Musk.
Altman previously blogged about this futuristic idea for seeing humans designing their own
tech integrated descendants.
With both leaders having a history of rivalry, Merge Labs emerges as a potential challenger
in this transformative tech space.
(03:40):
And now, pivot our discussion towards the main entrepreneurship topic.
Welcome back to Innovation Pulse.
I'm Donna, and today I've got strategy expert Yakov Lasker with me to unpack one of the
wildest business moves I've seen all year.
(04:00):
Yakov, you've been tracking this OpenAI situation, and honestly, when you first told me about
it, I thought you were making it up.
Right?
So picture this.
You're making decent money selling premium AI services, your competitor swoops in and
steals a third of your market share, and your response is to cut your own prices by 90%
(04:23):
and basically destroy your entire business model.
Most people would call that insane.
But you're telling me this is actually genius?
Not just genius.
It's one of the oldest plays in the tech playbook.
It's called commoditizing your compliments.
And once you see it, you can't unsee it.
Disney does it.
Google does it.
(04:43):
Even your local casino does it.
Okay, hold up.
Disney?
The company that charges me $40 for a turkey sandwich?
Ah, but here's the thing.
They make parking free.
Well, they use to.
The principle is this.
Pick one thing that makes you obscene amounts of money, then make everything else around
it so cheap that your competitors can't survive.
(05:07):
So Disney makes their real money on...
In-park purchases.
Those $40 turkey sandwiches.
So they used to make hotels, parking, even flights cheaper to get more people through
the gates.
More people means more overpriced sandwiches.
That's actually pretty devious.
But wait, what does this have to do with open AI burning down their AI business?
(05:30):
Because open AI realized they were fighting the wrong war.
While everyone's obsessing over who has the best AI model, open AI looked at where the
real money is in tech.
There are basically four kingdoms of profit.
Advertising at $334 billion.
(05:50):
Cloud computing at $193 billion.
Enterprise software at $132 billion.
And productivity tools at another $132 billion.
Those are enormous numbers.
So which kingdom did open AI choose?
Advertising.
The monster.
Google makes $207 billion just from ads.
(06:11):
Santa adds another $127 billion.
That's more profit than most countries entire GDP.
Oh!
So when open AI hired that meta executive, what was her name?
Kate something?
Kate Roach, who ran Facebook's Ad Machine for 11 years.
You don't hire the architect of Instagram's ad system to optimize subscription pricing.
(06:32):
You hire them because you're about to summon the advertising monster.
And the monster wants everything else to be free.
Exactly.
Think about it.
Google built Chrome and gave it away for free because every Chrome download funnels people
into their $207 billion advertising empire.
Facebook literally paid Samsung bags of cash to pre-install their app, then subsidized
(06:56):
phones across Africa.
Why?
Because cheaper phones and cheaper internet equals more users equals more ads.
So open AI is making AI inference free to...
To become the default place, people go to think, to search, to create.
They've got 3.6 billion in consumer subscriptions versus only 1.4 billion in API revenue.
(07:20):
They make more money from people paying $20 a month than from enterprises paying millions.
Wait, that seems backwards though.
Shouldn't enterprise customers be worth more?
Not if you're playing the advertising game.
Their eyeballs are worth way more in the long run.
But here's where it gets really interesting.
While open AI was making this strategic pivot, Anthropics was actually winning the infrastructure
(07:45):
war.
How so?
They went from 12% market share to 32% in just 18 months.
They kept prices flat at $75 per million tokens for their top model while open AI was fumbling
around.
And get this.
Anthropics CEO basically admitted they're already profitable on inference.
(08:05):
No way!
I thought everyone was losing money on AI.
That's what makes this so brutal.
Anthropics figured out how to make the AWS of AI actually work.
They dominated coding.
Cursor, Windsurf, all those AI coding tools run on Claude.
They had better reliability, better enterprise features, no drama about their AI making cartoon
(08:28):
characters when it should be running trading desks.
And then open AI just torched it all?
Dropped GPT-5 at $10 per million tokens.
Same performance as Claude's premium offering, but at one-tenth the price.
Every single AI coding tool, cursor, lovable, bolt, devon, they all became open AI launch
(08:50):
partners overnight.
That's got to hurt.
But I'm still confused about something.
If open AI could charge decent margins and still move into advertising, why burn the whole
business down?
Because they're not just competing with Anthropic anymore.
They're declaring war on Google.
On the entire old world of how tech makes money.
(09:11):
Remember, Google and Meta have the same incentive.
They need tokens to be free to protect their advertising empires.
Oh, so this is really about the big picture.
Exactly.
This actually connects to something bigger.
Overwatching these AI companies' paths diverge in real time.
Open AI can afford to let the API business die because they're chasing the $334 billion
(09:37):
advertising kingdom.
But for Anthropic, this is existential.
So what can Anthropic do?
Are they just stuck?
They've got some cards to play.
Their CEO mentioned they could charge real margins for reinforcement learning, interpretability,
fine-tuning.
The advanced stuff enterprises actually need.
(09:57):
Plus their contracts are sticky.
If you know anything about enterprise software, companies aren't as price sensitive when
it comes to reliability and compliance.
But here's what I'm wondering.
Could Anthropic just move up the stack?
Like instead of competing on infrastructure, compete on applications?
That's brilliant.
They're already testing this with Claude Code, which looks suspiciously like cursor.
(10:21):
And their desktop app is making those AI artifacts hostable, putting them in direct
competition with app builders like Lovable and Bolt.
So they could go after those other profit kingdoms.
The productivity tools are enterprise systems?
Right.
There's 132 billion sitting in productivity software that people hate using but can't
(10:42):
live without.
Microsoft Office, Adobe Creative Suite, or the Systems of Record, Salesforce, Oracle,
SAP, the databases that run the world.
This is where it gets wild though, because we're not just talking about two AI companies
having a pricing war.
(11:02):
This is about the entire future of how we interact with computers.
And here's the kicker.
Open AI's move only makes sense if they're absolutely committed to the advertising model.
Because once you start giving away inference for free, you can't really go back.
You've commoditized your own product.
So they've literally burned the boats.
(11:24):
Completely.
But remember when we talked about Disney?
Well, this changes everything about how we think about AI business models.
Because if open AI succeeds, every AI interaction becomes a potential ad placement.
Your coding assistant suggests libraries based on sponsorships.
Your writing assistant promotes certain products.
(11:46):
Your search results get influenced by who paid the most.
That's actually kind of terrifying when you put it that way.
It's the exact same playbook that turned the internet into an advertising machine.
And now open AI is betting they can do it to artificial intelligence.
So what should we be watching for?
How do we know if this strategy is working?
(12:06):
Keep an eye on open AI's hiring.
More advertising executives means they're doubling down.
Watch their consumer product launches.
If they start integrating shopping or sponsored content, that's your signal.
And for Anthropik, watch whether they can successfully move up the stack into higher
margin applications.
But here's my big takeaway.
(12:27):
This isn't really about AI at all, is it?
It's about recognizing which game you're actually playing.
Exactly.
Most companies think they're competing on product features, but the real competition
is about business models.
Everyone AI looked at their situation and realized they weren't in the AI inference
business.
They were in the human attention business.
(12:49):
So next time you're wondering why a company is making what seems like a destructive decision,
ask yourself, what's the real product they're selling?
Because I guarantee you, it's probably not what you think.
And remember, in tech, the company willing to commoditize the thing everyone else thinks
is valuable, that's usually the company that wins.
(13:09):
That's innovation pulse for today.
Thanks for helping us decode this wild business chess match, Yakov.
Always fun to peek behind the curtain with you, Donna.
Until next time, keep questioning the obvious.
That's it for today's podcast.
We explored the extended timeline for startups going public and Sam Altman's venture into
(13:32):
brain-to-computer interfaces.
Alongside OpenAI's bold move to slash AI service prices to pivot towards the advertising
market.
Don't forget to like, subscribe, and share this episode with your friends and colleagues
so they can also stay updated on the latest news and gain powerful insights.
(13:53):
Stay tuned for more updates.
Popular Podcasts
Stuff You Should Know
If you've ever wanted to know about champagne, satanism, the Stonewall Uprising, chaos theory, LSD, El Nino, true crime and Rosa Parks, then look no further. Josh and Chuck have you covered.
My Favorite Murder with Karen Kilgariff and Georgia Hardstark
My Favorite Murder is a true crime comedy podcast hosted by Karen Kilgariff and Georgia Hardstark. Each week, Karen and Georgia share compelling true crimes and hometown stories from friends and listeners. Since MFM launched in January of 2016, Karen and Georgia have shared their lifelong interest in true crime and have covered stories of infamous serial killers like the Night Stalker, mysterious cold cases, captivating cults, incredible survivor stories and important events from history like the Tulsa race massacre of 1921. My Favorite Murder is part of the Exactly Right podcast network that provides a platform for bold, creative voices to bring to life provocative, entertaining and relatable stories for audiences everywhere. The Exactly Right roster of podcasts covers a variety of topics including historic true crime, comedic interviews and news, science, pop culture and more. Podcasts on the network include Buried Bones with Kate Winkler Dawson and Paul Holes, That's Messed Up: An SVU Podcast, This Podcast Will Kill You, Bananas and more.
The Joe Rogan Experience
The official podcast of comedian Joe Rogan.