Analyse Podcast

Fresh out of the studio, this marks the 11th year of the e-Conomy SEA report with Nitin Gajria, Managing Director, Southeast Asia & South Asia Frontier Markets, Google; Florian Hoppe, Partner at Bain & Company; and Cassie Wu, Director of Investments, Asia Pacific (excluding China and India), Temasek. Generative AI reached 240 million users, or 60% of the working population, in three years — a milestone the Internet took ten years to hit. Yet per capita token usage is one-tenth of the US, with the gap almost entirely in enterprises outside Singapore and Malaysia. The panel shows AI-assisted shopping journeys lifting average order value by 75%, sets four tests for durable AI companies in Southeast Asia, and argues the region's diversity is its moat as Southeast Asia enters its AI decade.
"62% of users in Southeast Asia feel more positively about AI this year than they did last year ... We're stepping into the AI decade for Southeast Asia. And we're just at the ground floor of that. So it's going to be fascinating to watch how the technology arc plays out."" - Nitin Gajria"In Southeast Asia, I think we should use our diversity to our advantage. Our diversity is a feature, not a bug. You know, in our survey we say 70% of local usage is in local languages, that's just one reflection of that. Different culture, different cultural context, consumer preferences, user behaviors, also enterprise behaviors. And if you actually are able to build deep embedded local partnerships to have those contacts and to build tailored products for those verticals and users, I think that's important." - Cassie Wu"We've consistently seen a picture of double-digit growth in the mid to high teens, even in countries and markets where wouldn't have expected this. E-commerce is up 17 to 18% if I quote correctly. Digital media and the whole kind of digital ad space up above 20%. Digital financial services in many pockets, like lending, is up above 20% as well." - Florian HoppeProfiles:Nitin Gajria, Managing Director, Southeast Asia & South Asia Frontier Markets, Google
Florian Hoppe, Partner at Bain & Company
Cassie Wu, Director, Southeast Asia at Temasek
e-Conomy SEA Report 2026: https://economysea.withgoogle.com/
Episode Highlights:[00:00] Quotes of the Day [01:46] Introducing the e-Conomy SEA 2026 panel[05:10] Was Southeast Asia the most AI-curious region?[07:28] 17% growth and the path to US$1 trillion[08:24] AI integrations lift e-commerce conversions by 10%[10:08] How generative AI transforms the marketplace seller workflow[12:16] Tokenomics: Southeast Asia at one-tenth of US usage[15:42] AI makes purchase journeys richer, not shorter[18:10] AI reshuffles the cards for digital platforms[19:14] Broader investor participation in the AI economy[22:13] Two AI cohorts emerge across Southeast Asia[24:11] Sector performance and the digital economy's resilience[26:41] Who owns the customer when AI starts the journey?[27:22] Trust but verify: AI, search and Reddit[30:12] Digital advertising grows 20%+ and diversifies[32:26] Who is accountable when an agent buys wrongly?[33:13] AI applications take 80% of private funding[34:00] Four tests for a durable AI company[37:18] How Southeast Asian firms outcompete global AI providers[41:56] Is power the binding constraint on compute?[45:09] Pragmatic optimism defines Southeast Asian AI users[48:46] Beyond data centres: semiconductors and advanced packaging[50:40] Indicators to watch for next year's report[52:32] The ground floor of Southeast Asia's AI decade[53:21] Late-stage liquidity and IPO pipelines[54:19] 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, Rui Ma, founder of TechBuzz China, returns to examine China's AI ecosystem on its own terms rather than as a horse race with Silicon Valley. She maps the atlas of China's AI labs by strategy, from DeepSeek's "cost curve rebels"; to the big-tech war over office agents, and explains why cheap intelligence comes from brutal domestic competition rather than an export plan. Rui Ma unpack why robotics enjoys a homegrown market that pure AI lacks, why robot hardware and software must co-evolve, and how China prices insurance for brain-computer interfaces before the devices ship. Last but not least, she shows how Chinese municipalities now act as startup service providers, raising the floor for everyone while letting markets pick the winners.
"The [Chinese] government's not looking to build a multi-trillion dollar AI behemoth. The government is like, 'What is the best outcome for my society?'The best outcome is that the best technology survives. I don't want it to go bankrupt, right, and die too early. But the best technology survives and it is deployed at scale using my own whatever self-sufficient tech stack. It is not subject to foreign interference and it is also increasingly cheaper, right ..." - Rui Ma, Creator of Tech Buzz ChinaProfile: Rui Ma, Creator of Tech Buzz China
Substack: https://techbuzzchina.substack.com/
LinkedIn: https://www.linkedin.com/in/ruima/
Episode Highlights: [00:00] Quote of the Day by Rui Ma from TechBuzz China[00:45] Introduction: Rui Ma from Tech Buzz China [01:50] When intelligence becomes too cheap to meter[04:50] TechBuzz China pivots from e-commerce to AI and robotics[08:15] The biggest change since 2023: Chinese tech confidence[08:55] Independent labs versus big-tech labs in China[09:45] Distribution, cloud, and core business: why everyone builds models[11:05] Mapping China's AI labs by strategy, not benchmarks[12:05] DeepSeek as the "cost curve rebels"[12:45] Z AI, Moonshot and MiniMax: three distinct bets[14:35] The office agent war for China's enterprise software[18:15] The outdated Western belief about Chinese AI[20:25] Censorship and data fears versus real workflows[21:45] Brutal competition or deliberate export strategy?[25:05] Collapsing margins: where does the profit pool go?[27:05] Beijing optimises for society, not an AI behemoth[27:55] Why "China exporting tokens" is overblown[29:15] Investment decoupled, supply chains still entangled[31:05] China measures AI progress at the system level[35:05] Chinese investors want pilots; US investors want breakthroughs[39:55] Huawei's supercluster: cluster-to-cluster, not chip-to-chip[41:55] Embodied AI and China's ageing population[44:15] Brain-computer interfaces with insurance priced in advance[46:15] China's AI legislation is more advanced than assumed[47:25] What proves robots can cross the chasm?[50:05] AGVs and cleaning robots are effectively solved[51:15] The bottleneck: robot body, brain or data?[52:05] Why hardware and software must co-evolve[53:15] Why China may hold the robotics advantage[54:45] Chinese municipalities as startup service providers[56:45] Governments that drag decision-makers into meetings[58:05] Infrastructure building as a public service[59:15] Raising the floor, not king-making[60:25] Rui Ma's recommendation: homeschooling with AI and agents
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, Jon Russell from Asia Tech Review and executive director at Ellerton & Co., returns to trace how Chinese AI crossed from technological challenger into a commercial industry and a geopolitical export model. He unpacks the first public earnings from Z.ai and MiniMax, where revenue growth above 300% still cannot explain the valuations, and why cutthroat domestic competition makes international expansion existential for Chinese labs. Bernard and Jon examine the hidden on-premises market, the sovereignty stacks forming in Europe and Asia, why the copying narrative around distillation collapses under scrutiny, and China's remaining bottleneck in lithography. Jon closes on what he calls the dome: an AI ecosystem now self-sufficient from technology through to capital.
"The really impressive thing isn't just that China's building its own tech stack. It's that—it's so integrated. Companies are going public, they're raising money. It's entirely self-sufficient from the technology to the financing side too, right? So I think that's the really crazy bit for me. It's not like they have to build these companies and at some point they have to go public in America, right? They can do this all now in China and Hong Kong. But that's the ultimate thing, right? Capital is what these companies need, and if they can also get that from China too, then that completes the system. So it's almost like a dome has now got on top, right? Everything's in there." - Jon RussellProfile: Jon Russell from Asia Tech Review and executive director at Ellerton & Co
LinkedIn: https://www.linkedin.com/in/jmarussell/
Newsletter: https://www.asiatechreview.com/
Episode Highlights:
[00:00] Quote of the Day by Jon Russell
[01:30] Introduction: Jon Russell
[04:00] Chinese CEOs step onto the stage themselves
[06:30] Has China AI crossed from challenger to industry?
[07:00] Private AI valuations beyond anything ever seen
[09:15] Z.ai revenue growth above 300%
[10:30] Valuations conventional ratios cannot justify
[11:00] Moonshot postpones its IPO, waiting for Anthropic
[13:15] Cloud is marketing, on-premises is the real market
[16:00] Why most AI revenue stays out of public view
[17:45] Segmenting China AI companies from BAT to Upstarts
[19:45] First time the world cares about a Chinese model release
[21:15] The belief about Chinese AI the Bay Area gets wrong
[23:45] Qwen's problem: huge adoption, tiny revenue
[25:15] Chinese models undercutting US margins tenfold
[26:00] Not the dotcom bubble — the railway bubble
[29:30] Distillation, old books, and the irony of the copying claim
[33:30] AI as the next iteration of One Belt One Road
[35:30] Why Anthropic prioritises Japan, Korea and Australia
[35:45] The shift to ChatGPT Enterprise across the region
[37:00] Switching to Qwen and DeepSeek at one-tenth the cost
[38:15] Distribution is the real piece
[42:45] The surprise: enterprises run both Claude and ChatGPT
[45:30] Where is China's real bottleneck in the AI stack?
[47:15] China is not a monolithic organisation
[48:30] Lithography and ASML remain the hardest component
[50:45] The dome closes over the Chinese AI ecosystem
[51:00] The bigger prize: default infrastructure for the Global South
[53:00] Belt and Road, Central Asian rail, and long-horizon returns
[55:45] Most of the world cannot afford frontier models
[57:00] 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, Ang Li, CEO and co-founder of Simular and previously a research scientist at Google DeepMind, joins us to explore why computer use is the last mile to AGI. Ang traces his path from studying catastrophic forgetting and continual learning at DeepMind to founding a company on a single conviction: models break in production because the data distribution never stops moving, and the only place to close that loop is the real world. He explains why the chatbot metaphor misleads enterprise buyers, why the right unit of measurement is tokens per task rather than price per token, and how the power law of practice should make an agent cheaper every time it repeats the same work. He separates capability from reliability through pass@k and pass^k, argues that deterministic work belongs in code rather than in a model, and makes the case that frontier labs exist to sell tokens while Simular exists to remove them. Last but not least, Ang shares his test for AGI — one you feel rather than see — and what it will take to bring autonomous work down to the cost of water.
"So when I go to the gym, [doing] the same workout everyday, as I do this more and more, more reps, more sets, I don't even need to think. It's called muscle memory. I just do the same in a standard way, my consumption or my tokens in my brain dramatically drops. And there's a term describing this behavior in human cognition called 'the Power Law of Practice'. So that's the whole idea. Do we see power law practice in AI agents? We don't have that yet."Profile: Ang Li, CEO and co-founder of Simular AI
X: https://x.com/angli_ai
LinkedIn: https://www.linkedin.com/in/angli-ai/
Simular AI: https://simular.ai
Episode Highlights:
[00:00] Quote of the Day by Ang Li from Simular
[01:09] Why AGI arrives through the mouse and keyboard
[02:27] Legacy systems with no APIs block automation
[03:45] Computer use is the last mile
[04:05] One device, a hundred agents in the cloud
[05:51] The gap between research and production
[07:45] The day Covid became a dominant search keyword
[08:13] Continual learning over evolving distributions
[09:21] Catastrophic forgetting remains unsolved
[10:11] Why the learning loop requires a product
[11:04] Why AGI must be built commercially, not academically
[12:23] Chat versus work: two different problems
[13:40] Every company needs a repeatable playbook
[15:10] Tokens per task beats price per token
[16:13] Same task 100 times, 100 times the tokens
[16:34] The gym analogy and the power law of practice
[18:18] Where the scaling frame breaks for computer use
[20:46] Why AGI will not be a single model
[21:43] The 72.6% peak versus repeated-run reliability
[22:32] Hiring analogy: the interview versus daily work
[25:22] Replaying trajectories to drive token cost down
[26:17] The idea almost nobody in the industry discusses
[29:01] Democratising autonomous computers to the cost of water
[30:26] SMBs, not enterprises, are the real market
[32:59] Why healthcare and insurance came inbound
[34:06] Launching Sai on Windows virtual machines
[34:38] Simulang and the unity of opposites
[35:52] Frontier labs sell tokens; Simular removes them
[38:01] The hidden cost of self-hosting open models
[39:23] Why CPU and memory matter more than GPU
[41:10] You only have two hands: the physical constraint
[42:48] The AGI test you feel rather than see
[44:19] Why humanoids take longer than software
[45:23] The motivation: doing your work from the forest
[47:03] What Great Look Likes for Simular AI
[48:34] 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, recorded in Singapore, Steve Clayton, Senior Vice President and Chief Communications Officer at Cisco, joins us to discuss what it takes for AI to scale inside enterprises globally. Steve argues that narrative belongs at the top of the AI pyramid, not the bottom — in an era when models generate more material than any organisation can absorb, the story a company can credibly tell becomes the scarce asset, not the technology itself. He explains why the truth lies in the field rather than at global headquarters, how regional dynamics reshape where a story lands, and walks through Cisco's advances in silicon and quantum computing networking. Showing a real customer deployment, he argues, is what earns permission to talk about security and trust at all. Last but not least, he shares what great look like for Cisco to build their story in the age of AI.
"Take your phone and switch it into airplane mode and see how much you can do on your phone. Very little. You can use the calculator, but you can't use an AI model. You can't surf the web, you can't send messages. And people get excited about GPUs and data centers and models and applications and devices. But sitting at the center of all of that is the network. And that's what Cisco is all about. So that's our job, is to help people understand the value of the network and to realize that AI, as exciting as it is, it simply doesn't happen without the network." - Steve Clayton, SVP & Chief Communications Officer, CiscoProfile: Steve Clayton, SVP & Chief Communications Officer, Cisco
LinkedIn: https://www.linkedin.com/in/stevecla/
Friday Note Newsletter: https://www.linkedin.com/newsletters/the-friday-thing-7412856034161229824/
Episode Highlights:
[00:00] Quote of the Day by Steve Clayton from Cisco
[00:30] Introduction: Steve Clayton from Cisco
[02:13] Why storytelling began around the campfire
[02:55] Telling stories about impact, not technology
[03:43] Why the AI debate over-indexes on models
[04:51] The airplane mode test for AI dependence
[06:17] Steve inverts the pyramid, narrative on top
[07:04] Communicating without leading with the technology
[07:49] Breaking through by doing the opposite
[08:37] Why "content" has become a bad word
[09:59] Audience-first: meeting policymakers where they are
[11:10] The trap of filling the pipeline
[11:34] Attention, not creativity, is the scarce resource
[12:15] Curation and judgment against AI slop
[12:51] We are not entitled to people's attention
[13:26] Silicon One, the Cisco business nobody expects
[14:26] Cisco's universal quantum switch at room temperature
[14:57] Balancing ambition against credibility
[16:08] Show the possible, do not just describe it
[16:35] Earning permission to talk security and trust
[17:18] The truth lies in the field
[18:16] McLaren F1 and Networking Academy stories
[19:12] The question Steve wishes people would ask
[20:56] The Friday Thing: human first draft, AI editor
[21:26] Humans create the novel ideas, AI supports
[22:07] What Cisco should mean to business and to family
[23:21] 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.