PodcastsRank #2674
Artwork for Big Tech

Big Tech

TechnologyPodcastsSociety & CultureENcanadaDaily or near-daily
4.5 / 5
Machines Like Us is a technology show about people. We are living in an age of breakthroughs propelled by advances in artificial intelligence. Technologies that were once the realm of science fiction will become our reality: robot best friends, bespoke gene editing, brain implants that make us smarter. Every other Tuesday Taylor Owen sits down with the people shaping this rapidly approaching future. He’ll speak with entrepreneurs building world-changing technologies, lawmakers trying to ensure they’re safe, and journalists and scholars working to understand how they’re transforming our lives.
Top 5.3% by pitch volume (Rank #2674 of 50,000)Data updated Feb 10, 2026

Key Facts

Publishes
Daily or near-daily
Episodes
39
Founded
N/A
Category
Technology
Number of listeners
Private
Hidden on public pages

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Public snapshot
Audience: 4K–8K / month
Canonical: https://podpitch.com/podcasts/big-tech
Cadence: Active monthly
Reply rate: Under 2%

Latest Episodes

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Is China Winning the Technological Arms Race?

Tue Jan 27 2026

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If we don’t build it, China will. That’s the rallying cry of the tech companies and governments racing to develop artificial intelligence as fast as humanly possible. The argument is that whoever reaches AGI first won’t just be dominant technologically, or economically – they’ll be the world’s next super power. But, if I’m being honest, I don’t know if that framing holds up. And part of the reason for that is that we don’t really understand China. Enter Keyu Jin. Jin is a Harvard trained economist who splits her time between London and Beijing, and her book, The New China Playbook, is her attempt to “read China in the original” – to provide a firsthand look at the forces that shaped the country’s unprecedented rise. China’s success is a puzzle. How did one of the poorest nations on the planet become the second richest in less than a century? How did an economy without free markets birth a tech sector that rivals – and in some ways surpasses – Silicon Valley? The answers to these questions aren’t academic. China became a global power without capitalism and without democracy, which means its success has profound implications for both. And as Canada sets out to find its footing in a rapidly changing world order, one thing is abundantly clear: we need to start reckoning with the Chinese playbook.  Mentions: The New China Playbook, by Keyu Jin Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

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If we don’t build it, China will. That’s the rallying cry of the tech companies and governments racing to develop artificial intelligence as fast as humanly possible. The argument is that whoever reaches AGI first won’t just be dominant technologically, or economically – they’ll be the world’s next super power. But, if I’m being honest, I don’t know if that framing holds up. And part of the reason for that is that we don’t really understand China. Enter Keyu Jin. Jin is a Harvard trained economist who splits her time between London and Beijing, and her book, The New China Playbook, is her attempt to “read China in the original” – to provide a firsthand look at the forces that shaped the country’s unprecedented rise. China’s success is a puzzle. How did one of the poorest nations on the planet become the second richest in less than a century? How did an economy without free markets birth a tech sector that rivals – and in some ways surpasses – Silicon Valley? The answers to these questions aren’t academic. China became a global power without capitalism and without democracy, which means its success has profound implications for both. And as Canada sets out to find its footing in a rapidly changing world order, one thing is abundantly clear: we need to start reckoning with the Chinese playbook.  Mentions: The New China Playbook, by Keyu Jin Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Key Metrics

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Pitches sent
64
From PodPitch users
Rank
#2674
Top 5.3% by pitch volume (Rank #2674 of 50,000)
Average rating
4.5
Ratings count may be unavailable
Reviews
2
Written reviews (when available)
Publish cadence
Daily or near-daily
Active monthly
Episode count
39
Data updated
Feb 10, 2026
Social followers
244.4K

Public Snapshot

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Country
Canada
Language
English
Language (ISO)
Release cadence
Daily or near-daily
Latest episode date
Tue Jan 27 2026

Audience & Outreach (Public)

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Audience range
4K–8K / month
Public band
Reply rate band
Under 2%
Public band
Response time band
1–2 days
Public band
Replies received
1–5
Public band

Public ranges are rounded for privacy. Unlock the full report for exact values.

Presence & Signals

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Social followers
244.4K
Contact available
Yes
Masked on public pages
Sponsors detected
Private
Hidden on public pages
Guest format
Private
Hidden on public pages

Social links

No public profiles listed.

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Audience & Growth
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Monthly listeners49,360
Reply rate18.2%
Avg response4.1 days
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Contact preview
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Sponsor signals
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Sponsor mentionsLikely
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How To Pitch Big Tech

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4.5 / 5
RatingsN/A
Written reviews2

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Frequently Asked Questions About Big Tech

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What is Big Tech about?

Machines Like Us is a technology show about people. We are living in an age of breakthroughs propelled by advances in artificial intelligence. Technologies that were once the realm of science fiction will become our reality: robot best friends, bespoke gene editing, brain implants that make us smarter. Every other Tuesday Taylor Owen sits down with the people shaping this rapidly approaching future. He’ll speak with entrepreneurs building world-changing technologies, lawmakers trying to ensure they’re safe, and journalists and scholars working to understand how they’re transforming our lives.

How often does Big Tech publish new episodes?

Daily or near-daily

How many listeners does Big Tech get?

PodPitch shows a public audience band (like "4K–8K / month"). Book a demo to unlock exact audience estimates and how we calculate them.

How can I pitch Big Tech?

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Which podcasts are similar to Big Tech?

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