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What’s Next for AI in 2026: From LLM Limits to Image Models
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シニア・ディレクター兼プリンシパル・アナリスト
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AI is entering its next phase — and the economics are getting harder to ignore.
As model performance plateaus and capital spending accelerates toward trillions of dollars, critical questions are emerging:
- Are AI models becoming commodified?
- Can hyperscale data center investments deliver acceptable returns?
- Will business value creation keep pace with infrastructure spending?
- What happens if efficiency gains reduce compute demand?
In this session, we explore:
- How AI model development is shifting — from frontier LLM scaling to miniature and world models
- Why image models may drive the next wave of commercial applications
- The real economics of AI data center buildout — including GPU life, utilization rates, and pricing sensitivity
- Four potential futures for AI adoption
This webinar provides a grounded, data-driven assessment of where AI is headed by 2026 — and what business leaders, investors, and technology strategists should do now to manage risk while positioning for upside.
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オンデマンド・ウェビナー
What’s Next for AI in 2026: From LLM Limits to Image Models
によるものだ：
シニア・ディレクター兼プリンシパル・アナリスト
オンデマンド・ウェビナーを見る
AI is entering its next phase — and the economics are getting harder to ignore.
As model performance plateaus and capital spending accelerates toward trillions of dollars, critical questions are emerging:
- Are AI models becoming commodified?
- Can hyperscale data center investments deliver acceptable returns?
- Will business value creation keep pace with infrastructure spending?
- What happens if efficiency gains reduce compute demand?
In this session, we explore:
- How AI model development is shifting — from frontier LLM scaling to miniature and world models
- Why image models may drive the next wave of commercial applications
- The real economics of AI data center buildout — including GPU life, utilization rates, and pricing sensitivity
- Four potential futures for AI adoption
This webinar provides a grounded, data-driven assessment of where AI is headed by 2026 — and what business leaders, investors, and technology strategists should do now to manage risk while positioning for upside.