Podcast Summary: AdExchanger Talks – "From Hype To Hyperscale In AI"
Date: December 2, 2025
Host: Allison Schiff, Managing Editor, AdExchanger
Guest: Ikjin Ahn (Cuz), CEO & Co-founder of Maloco
Overview
In this episode, Allison Schiff interviews Ikjin Ahn, CEO and co-founder of Maloco, a machine learning-powered digital advertising company, about the journey "from hype to hyperscale" in AI for ad tech. The conversation explores Maloco’s evolution, scaling AI for retail media and commerce, overcoming commoditization in AI, practical use cases, and the future of digital advertising in an AI-driven world. They also address challenges in retail media, creative AI applications, and end on a personal note about corporate responsibility and gratitude for the industry’s collaborative progress.
Key Discussion Points & Insights
Ikjin's Background & Early Lessons from Google/YouTube
[03:13–09:37]
- Ikjin shares his journey from growing up in Korea to becoming a software engineer at Google and YouTube, joining YouTube’s monetization team when it was only five people.
- Scaling challenges at YouTube: Early focus was on solving server outages and scalability ("We even actually took down the server once a week to update the binary." – Ikjin, [04:00]).
- Initiating AI at YouTube: Recognized that monetizing millions of diverse videos required machine learning. He kickstarted YouTube’s first large-scale machine learning project for monetization, moving the whole organization toward AI-driven revenue growth.
- Takeaway: "That experience taught me how critical AI machine learning is for any platform who want to build a sustainable business and who need to monetize and acquire user effectively." – Ikjin, [07:38]
Maloco’s Evolution: From DSP Startup to AI Engine
[09:37–14:01]
- Maloco started without deep ad tech jargon knowledge. Discovered DSPs as an entry point.
- Early pitch decks drew inspiration from Game of Thrones, with themes like "Winter Is Coming," warning of the need for healthy monetization in the open internet.
- Found initial growth in DSPs, but soon expanded to tackle broader monetization problems for commerce media, retail, and streaming.
- "Our goal is always introducing AI to the different parts of our open Internet ecosystem." – Ikjin, [13:47]
Differentiating AI in a "Sea of AI Sameness"
[14:01–18:07]
- Allison highlights the commoditization of AI: “Every single company uses AI... More, more, more, better, better, better: AI, AI, AI." – Allison, [14:29]
- Ikjin responds: Track record and proven hyperscale set Maloco apart. "When someone is asking how your AI is different then I can always say hey, see our cases, see how much scale we can deliver." – Ikjin, [16:45]
- The market’s narrative has shifted: "In 2025, good news is no one is asking why we need AI. Everyone sees, ‘hey, we need AI.' But the question is who has a better AI." – Ikjin, [15:36]
Making It Real: Practical Applications & Success Stories
[18:07–21:33]
- Global scale is key: Maloco enables clients (e.g., gaming companies) to expand campaigns from the US into Middle Eastern and APAC markets with high accuracy and better ROI.
- Notable partnership: Maloco’s work with Wayfair helping them break ad revenue projections by leveraging their first-party data for commerce media.
- Ikjin points to the ad revenue "per GMV" (A2G) gap between Amazon (~7–8%) and other retailers (~1–2%). "Our goal is helping clients to hit 2% very like a consistently within like a 24 months of the project with us. And then we are aiming 3%, 4%... our next frontier will be 5%." – Ikjin, [20:40]
Under the Hood: AI Hyperscale & Infrastructure
[21:33–28:36]
- Host’s summary: Maloco uses an "AI hypercomputer" – 10x faster and cheaper infrastructure to process billions of ad requests per day.
- Ikjin deep dives into the leap from feature engineering to hyperscale deep learning and foundation models, where "we can put all the features and machine learning or AI will figure it out... better than human." – Ikjin, [23:54]
- The challenge: Making these foundation models cost-effective and fast enough for high-frequency ad tech, versus the slow, massive compute required by generic LLMs like ChatGPT.
- AI breakthroughs in creative generation: "Three team members in a week made this automated creative generation. You just put your app store or app link and [the] machine automatically generates the creatives... better than I’ve seen from human creation." – Ikjin, [27:07]
Retail Media Explosion & Its Challenges
Real-World Fragmentation & Operational Headaches
[32:38–39:16]
- Host highlights fragmentation, measurement woes, and the need to onboard “the long tail” of advertisers.
- Ikjin: To succeed, retailers must serve both sophisticated brands and small merchants, requiring high automation and campaign ROI. "In one of our customer example, they onboarded more than 10,000 advertisers with five ad operation team in in three months." – Ikjin, [36:42]
- Many platforms struggle with basic ROI delivery, let alone incrementality. Maloco’s AI is positioned to address these gaps.
Democratizing AI for All Retailers
[39:16–42:29]
- Ikjin notes the advantages even "smaller" retailers have: "each platform have their very loyal user base... Wayfair is great... there are very deep focus over furniture and interior and related verticals." – Ikjin, [39:41]
- Vertical focus and quality of data trumps universal scale for specialized commerce segments.
- "If you want to know... what kind of style people like most in the US about like a living room decoration. I think Wayfair has probably, I mean one of the best data." – Ikjin, [41:50]
The Future: Chatbots, AI-Driven Shopping, and Ad Tech Disruption
Chatbots & the Evolving Purchase Funnel
[42:29–46:13]
- Maloco has clients experimenting with removing their homepage in favor of AI chat agents. Prototypes are now quick to build and advanced chatbots can drive commerce within specific verticals or platforms.
- Integration challenge: Making sponsored search, on-site, and chatbot-driven ad experiences seamless and effective.
Personal Experience & Broader Adoption
[46:13–48:50]
- Ikjin shares personal use of chatbots for purchasing (e.g., buying luggage tailored to airline regulations) – useful for complex, criteria-intensive product searches.
- Host admits to not using chatbots for commerce yet, but uses generative AI for editing and productivity.
Lighter Moments & Cultural Touchstones
Meaning Behind "Maloco"
[32:38–33:57]
- The name Maloco stands for “machine learning company” (M L C, with an ‘O’ for pronunciation) but amusingly, it also means “milk” in Russian.
Food, Ramen, and Costco
[48:50–50:58]
- Allison and Ikjin bond over Costco (Kirkland seltzer, jeans), Buldak ramen, and the organic marketing loops forming through TikTok influencer culture.
- "They are the first form of ChatGPT in some sense." (On Costco offering curated, unexpected shopping experiences) – Ikjin, [49:37]
Social Impact: Maloco Love Initiative
[50:58–55:42]
- Maloco Love, launched in 2021, supports global communities through donations, volunteering, and local school initiatives. Originated with laptop donations during the pandemic.
- "This is almost ritual... giving back to society. And actually that has brought a lot of positive energy... reminding what our mission is." – Ikjin, [54:16]
Closing Reflections: Gratitude & The Collaborative Ecosystem
[55:42–57:48]
- Allison asks what Ikjin is thankful for in the industry.
- Ikjin praises the growing spirit of collaboration, diversity, and the shift away from zero-sum thinking:
"Over time I think we see more collaborations... technology can make the industry way more effective and create more value. Now we can design the win win situation rather than like a zero sum game." – Ikjin, [56:27]
- Expresses optimism about ad tech’s diversity and AI’s power to keep creating net new value.
Notable Quotes & Timestamps
-
On Scaling AI:
"That experience taught me how critical AI machine learning is for any platform who want to build a sustainable business and who need to monetize and acquire user effectively."
— Ikjin, [07:38] -
On Differentiation in AI:
"In 2025 good news is no one is asking why we need AI. Everyone see ‘hey, we need AI.’ But the question is who has a better AI."
— Ikjin, [15:36] -
On Democratizing Ad Tech:
"Each platform can focus on their unique value and can have actually very unique data... That’s kind of a world we want to support. And with AI, I think that can become possible."
— Ikjin, [41:14] -
On Retail Media Scaling:
"...onboarded more than 10,000 advertisers with five ad operation team in in three months. And this is just a different scale of operations... what AI can provide as efficiency."
— Ikjin, [36:42] -
On Social Responsibility:
"You can do it now and it become ritual. And actually that has brought a lot of positive energy... and that kind of changed me in some way and changed our team in deep way."
— Ikjin, [54:44] -
On Industry Optimism:
"...players are realizing their potential and then the technology, especially AI is making really possible by creating more values. Right. So that's something I'm hopeful again for the next two and five years."
— Ikjin, [57:04]
Segment Timeline
| Timestamp | Segment Description | |------------|------------------------------------------------------| | 00:12–02:17| Introductions, guest welcome | | 03:13–09:37| Google/YouTube background, lessons on scaling & AI | | 09:37–14:01| Maloco’s founding, niche to hyperscale pivot | | 14:01–18:07| AI commoditization, standing out in the market | | 18:07–21:33| Real-world client examples (global scaling, Wayfair) | | 21:33–28:36| AI hyperscaler/architecture & future innovations | | 32:38–33:57| Maloco’s name origin, anecdotal banter | | 34:44–39:16| Retail media operational challenges & automation | | 39:16–42:29| Democratizing AI for various vertical retailers | | 42:29–46:13| Chatbots, AI assistants, the new commerce funnel | | 46:13–48:50| Personal use of chatbots in commerce | | 48:50–50:58| Ramen, Costco, influencer feedback loops | | 50:58–55:42| Maloco Love social impact initiative | | 55:42–57:48| Gratitude for industry collaboration, closing remarks|
Tone and Style
The conversation is fast, candid, and often light-hearted, balancing concrete technical insights with story-driven, sometimes playful anecdotes. It’s both accessible for newcomers and insightful for ad tech insiders, with technical depth on AI’s transformation of advertising—plus plenty of human moments about Costco, ramen, and real-world impact.
For anyone seeking a real-world map of how AI is upending—and operationalizing—ad tech, and how thoughtful leadership can make scaling feel both practical and personal, this episode is a must-listen.