Analyse Podcast

Fresh out of the studio, Dr. Rafael Frankel, Head of Public Policy for Asia Pacific at Meta, joins us to unpack how Meta is stepping up on the fight against scam syndicates in Southeast Asia along with a coalition of partners. He explains why today's syndicates operate with state-like capabilities and forced labor at scale and how AI has become both the scammers' sword and Meta's shield, powering the removal of hundred million scam accounts in 2025. Frankel walks through the disruption-sprint model that took down the million accounts in a single week alongside the FBI, Microsoft and Starlink, and argues that beating scams demands a coalition matched to the criminal supply chain. Closing out, he reminds us that crime is never zero — but through sustained, collective pressure, it can be cut by orders of magnitude.
"I think that people underestimate the criminals that are the drivers of the scams. Mostly what we're talking about at this point is extremely well-financed, highly sophisticated transnational criminal networks that have turnover in the billions, tens of billions, and have the finances, the technological know-how, the sophistication to really be trying to scam people 24/7, 365 days a year. That's a tough adversary to be up against." - Dr Rafael FrankelProfile: Profile: Dr Rafael Frankel, Head of Asia-Pacific Public Policy at Meta
LinkedIn: https://www.linkedin.com/in/rafael-frankel/
Episode Highlights:
[00:00] Quote of the Day by Rafael Frankel from Meta
[02:38] From foreign correspondent to tech policy
[03:39] Career lessons: gut instinct and taking risks
[04:33] Why the Meta APAC policy role, and why now
[07:26] The one thing people misunderstand about scams
[09:13] What changed: industrial scale scam centers
[11:35] AI as Meta's shield, deployed at scale
[13:07] Genesis: the Bangkok 2024 convening
[14:14] First disruption: 59,000 accounts, six warrants
[15:45] June haul: 1.5M accounts, Microsoft, Starlink, 63 arrests
[16:52] Matching the coalition to the criminal supply chain
[18:52] Building trust: results create the feedback loop
[20:05] The Global Signal Exchange and the FIRE program
[22:50] Counter-intuitive lesson: Meta doesn't see everything
[24:13] Asia Pacific as front line of the solution
[26:20] Pulling on the same rope across governments
[27:30] POGO centers and pinpointed police action
[29:02] Is sanctioning a kingpin just theatre?
[30:52] Crime is never zero, but reducible by orders of magnitude
[31:02] The question Rafael wishes people asked: how can I help?
[32:52] What success looks like three years out
[35:08] Closing
Podcast Information: Bernard Leong hosts and produces the show. The proper credits for the intro and end music are "Energetic Sports Drive." G. Thomas Craig mixed and edited the episode in both video and audio format.

Fresh out of the studio, Jing Yang, Asia Bureau Chief at The Information, joins us to explore how China is building frontier AI under chip constraints, state capital, and open source ambition. Jing breaks down her scoop on DeepSeek's $7.4 billion round at a $50 billion valuation, unpacking a deal structure in which the founder wrote two-fifths of the check and outside investors got no voting rights. She explains why Chinese AI valuations trail US labs, why seven to eight language model players refuse to consolidate, and why DeepSeek chose Huawei chips before Huawei knew about it. Last but not least, Jing shares the indicators she is watching from now to 2027.
"This is one of the things that really surprised me when I was working on this story: DeepSeek had spent a lot of time last year retrofitting their models and software with Huawei chips. I think a lot of people assumed it's because the government ordered DeepSeek to work with Huawei to embrace the domestic ecosystem, but it's actually the opposite. It was DeepSeek that voluntarily started using Huawei, experimenting with the Huawei chips, and Huawei actually only found out after. Then they started sending people to DeepSeek to help..." - Jing Yang, Asia Bureau Chief, The InformationEpisode Highlights:[00:00] Quote of the Day by Jing Yang from The Information
[01:30] What changed since September: the ByteDance mystery resolved
[03:00] Why China's AI must be read on its own terms
[04:10] Breaking the story of DeepSeek on their 7.4B fundraise
[05:40] How the valuation went from $10 to $50 billion
[08:30] The lab that became famous for rejecting scaling laws
[10:15] Unpacking the DeepSeek deal structure: four types of investors
[12:40] Five-year lock-up and no secondary market trading
[14:20] Reverse due diligence: DeepSeek vetting its own investors
[16:40] Balancing open source, AGI research and IPO pressure
[17:45] The irony: inclusive vision, exclusive deal structure
[20:35] How Anthropic's Mythos preview changed Liang's mind[21:30] Why Chinese AI valuations look tiny next to US labs
[23:00] Why Chinese founders go consumer when they go global
[26:45] "The worst of customers" — price sensitivity and zero loyalty
[27:45] The compute constraint that caps every Chinese lab
[28:40] New labs in China: weaker infrastructure, harder exit
[30:30] Can China leapfrog on hardware the way it did on models?
[32:50] Stricter compliance, not political muscle
[34:30] Founder power when your company becomes strategic
[36:40] Junyang Lin's new lab and the scarcity premium
[38:00] Open source influence versus sustainable commercial models
[39:30] Zhipu versus MiniMax: how sentiment diverged after IPO
[42:30] What is the right mental map for China's AI ecosystem?
[43:20] The consolidation that still hasn't happened
[45:00] Seven to eight serious players and nobody giving up
[46:40] The one thing Jing wishes people would ask
[47:20] Nobody ordered DeepSeek to use Huawei chips
[50:00] Indicators to watch from now to 2027
[55:30] Closing

Profile: Jing Yang, Asia Bureau Chief from The Information
The Information Profile: https://www.theinformation.com/u/JingYang
LinkedIn: https://www.linkedin.com/in/jing-yang-33548123/
X: https://x.com/jingyanghk
Podcast Information: Bernard Leong hosts and produces the show. The proper credits for the intro and end music are "Energetic Sports Drive." G. Thomas Craig mixed and edited the episode in both video and audio format.

Fresh out of the studio, Aneesh Raman, Chief Economic Opportunity Officer at LinkedIn and co-author of Open to Work: How to Get Ahead in the Age of AI, joins us to dismantle the flattened narrative that AI is simply taking jobs. His counter-thesis: work is changing, not ending — and we never truly left the industrial age, only traded the factory floor for the office floor. Aneesh walks through his three-bucket framework for auditing your week, the move from the career ladder to the career wall, and why the org chart is giving way to the work chart. He closes by reframing the current AI moment as a battle of belief, urging leaders and workers to move from anxiety to agency and bet on themselves.
"We are in a battle of belief right now more than anything else. So stories matter a lot to humans. It's not just the tools we create, it's the stories we tell that have allowed us to become everything we've become. But whether it leads to better or worse... depends on the story we tell now. If we tell ourselves a story that it's going to lead to worse, it's more likely going to lead to worse. Because we have to unwind a lot of what the industrial age has told us to think about ourselves. A lot of industrial age work was about deficit management. I don't have the degree yet, I need to get it. I don't have the job title yet, I need to get it. We all started from a place of what we don't have, that we needed to get, in order to feel of value and succeed. This world..." - Aneesh RamanEpisode Highlights:
[00:00] Quote of the Day by Aneesh Raman
[01:55] Aneesh's origin story
[04:00] The labour market: least efficient, transparent, dynamic market ever built
[05:45] Career advice: worry about what you can control
[07:19] Open to Work and the misaligned labour market
[09:00] We never left the industrial age
[10:36] Jobs are tasks, not titles — the software engineer example
[11:50] The three buckets: automated, augmented, uniquely human
[13:34] Gen Z: highest AI confidence, entrepreneurial by survival
[15:49] The real gap: mid- and late-career professionals
[16:13] Using the tool while rejecting the fatalism
[18:06] Auditing your week: list twelve tasks, sort three buckets
[20:22] Is there a cognitive ceiling? Bucket two for everyone
[21:00] Human capability is a fraction; it's human with AI
[23:34] Why the org chart emerged from the industrial age
[25:30] Work-chart principles: capabilities, not categories
[26:30] Managers as coaches and the rise of the super IC
[27:37] Asia Pacific: a responsible AI-era workforce strategy
[31:00] Anxiety to agency: we are in a battle of belief
[32:10] Bet on yourself: from deficit management to asset inventory
[34:07] How long is the window? Five years of experimentation
[36:04] The question no one asks: what's possible?
[36:23] The innovation explosion and the Lost Einsteins
[38:02] Fifty years to outdo the last five hundred
[38:17] What this all means for LinkedIn
[40:30] Recommendations

Profile: Aneesh Raman, Chief Economic Opportunity Officer, LinkedIn and Co-Author of "Open to Work"
LinkedIn: https://www.linkedin.com/in/aneeshraman/
Open To Work: https://www.linkedin.com/opentowork/
Podcast Information: Bernard Leong hosts and produces the show. The proper credits for the intro and end music are "Energetic Sports Drive." G. Thomas Craig mixed and edited the episode in both video and audio format.
Here are the links to watch or listen to our podcast.
Analyse Podcast Main Site: https://analysepodcast.com

Fresh out of the studio, Benedict Evans, independent technology analyst and author of AI Eats the World, returns to explore whether the AI model layer is becoming commodity infrastructure. Benedict argues there is no winner-takes-all effect in models yet, drawing parallels to telecoms, cloud, chips and the fiber bubble to ask where durable value actually accrues when everyone runs similar infrastructure on similar tokens. He unpacks why the chatbot remains a poor interface, introduces the "blank screen" and "jagged frontier" problems that keep software companies alive, and explains why large language models inherently give you "the average." Closing the conversation, Benedict reflects on the indicators that would show AI has truly eaten the world — and why the answer is better products, not better models."When you automate away work, you can always see the jobs that are going away because they're right there. And you don't know what the new jobs are going to be. Human needs are infinite. How many people are earning a living from making podcasts now? Imagine predicting that 10 years ago. There's a stage in the evolution of the market where like if you're still arguing about that, you're an idiot. But there's a stage at the beginning where you might have opinions about some of these questions, you're probably not even asking the right questions. That, I think, is where we are with this stuff today." — Benedict EvansEpisode Highlights: [00:00] Quote of the Day by Benedict Evans from AI Eats the World[01:16] The public market test: what are investors buying?[04:21] How far up the stack can models go?[05:30] Models can't build all the apps themselves[06:00] The thesis: models as commodity infrastructure[07:52] "All the value went up the stack"[08:24] Chips and Rock's Law: down to three players[11:23] The 1999 reseller story: one-time sales[13:28] The S-curve framing of technology[16:38] You're probably not asking the right questions on AI[18:02] "If this works, we're competing with a Mac"[20:25] Incumbents make it a feature[22:14] Big tech "killing startups" is overstated[24:39] Cowork as the new spreadsheet[26:01] The blank-screen and jagged-frontier problems[29:00] The hard part isn't writing the code[31:25] "What a good answer would probably look like"[33:38] The job displacement debate[37:38] Jevons paradox and the lump-of-labour fallacy[40:30] LLMs inherently give you the average[42:36] Why you really hire McKinsey[45:33] Punk versus prog rock: outside the training data[49:00] Automating ever-higher human functions[49:55] Why this is unanswerable: no theory of scaling[51:30] Indicators that AI has eaten the world[54:53] The solution isn't a better model[56:39] Where to find Benedict Evans
Profile: Benedict Evans, Independent Technology Analyst
LinkedIn: https://www.linkedin.com/in/benedictevans/Website: https://www.ben-evans.com/newsletter
Podcast Information: Bernard Leong hosts and produces the show. The proper credits for the intro and end music are "Energetic Sports Drive." G. Thomas Craig mixed and edited the episode in both video and audio format.
Here are the links to watch or listen to our podcast.
Analyse Podcast Main Site: https://analysepodcast.com
Analyse Podcast Spotify: https://open.spotify.com/show/1kkRwzRZa4JCICr2vm0vGl
Analyse Podcast Apple Podcasts: https://podcasts.apple.com/us/podcast/analyse-asia-with-bernard-leong/id914868245
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Fresh out of the studio, Eyck Freymann, Hoover fellow at Stanford and author of Defending Taiwan: A Strategy to Prevent War with China, joins us to explore why the Taiwan question will be decided by economics and coercion, not by invasion. Eyck unpacks the Thucydides Trap as a warning, not a prophecy, traces how Xi Jinping's Belt and Road statecraft shapes his approach to Taiwan, and contrasts a kinetic invasion with the "quarantine" scenario he fears most. He reframes 2027 as a capability milestone, recasts TSMC as a "silicon magnet" binding America to Taiwan, and flags Taiwan's 2028 election as the real flashpoint. Last but not least, Eyck argues the real task is to deter the crisis, not the war.
"For Beijing, I hope they will say: the United States actually does have a strategy to use every element of its national power to preserve peace and stability without provoking us, and we should not assume the United States is incapable of an effective response. In Taiwan, I think the lesson is: the United States trusts the people of Taiwan to choose the best future for themselves, and ultimately Taiwan's fate is up to the people of Taiwan to choose. That is the heart of what the American One China policy is about and must be about. The people of Taiwan must choose, and the United States will respect their choices. That is a profound insight that doesn't get said often enough." - Eyck FreymannEpisode Highlights:
[00:00] Quote of the Day by Eyck Freymann from the Hoover Institution at Stanford
[01:18] Eyck's origin story
[04:02] When Taiwan deterrence pulled the threads together
[06:33] Why the CCP embraces the Thucydides Trap
[07:36] Belt and Road as decentralized statecraft
[10:18] How Belt and Road consolidated Xi's power
[11:39] Xi's legacy project: why Taiwan comes next
[12:17] What gets lost without untranslated Chinese sources
[14:12] China's unexplained nuclear breakout
[16:23] Applied history: lessons from three mentors
[19:50] Reframing the timeline: 2027 vs 2049
[22:49] Declassifying the Davidson window
[24:27] Is 2049 bound by Xi's resolution?
[27:34] Cross-strait history and the counterintuitive lesson
[29:28] Two scenarios: kinetic invasion vs customs quarantine
[34:00] The TSMC financial-shock trigger
[36:48] Strategic ambiguity vs structured ambiguity
[42:39] The one thing few understand: it's all economic
[44:39] The right and wrong asks of Southeast Asian neutrals
[47:17] The silicon shield paradox and chip onshoring
[50:19] Why the CHIPS Act won't replace Hsinchu
[53:49] The January 2028 Taiwan election as a flashpoint
[55:24] Meta-question: the neglected domestic politics of Taiwan
[58:07] What success looks like for the book
[60:14] Closing

Profile: Eyck Freymann, author of "Defending Taiwan" and Hoover Fellow
LinkedIn: https://www.linkedin.com/in/eyck-freymann/Personal Site: https://www.eyckfreymann.com/
Podcast Information: Bernard Leong hosts and produces the show. The proper credits for the intro and end music are "Energetic Sports Drive." G. Thomas Craig mixed and edited the episode in both video and audio format. /
Here are the links to watch or listen to our podcast.
Analyse Podcast Main Site: https://analysepodcast.com
Analyse Podcast Spotify: https://open.spotify.com/show/1kkRwzRZa4JCICr2vm0vGl
Analyse Podcast Apple Podcasts: https://podcasts.apple.com/us/podcast/analyse-asia-with-bernard-leong/id914868245
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