Don't view generative AI video as just a way to make traditional films more efficiently. Ben Horowitz sees it as a fundamentally new creative medium, much like movies were to theater. It enables entirely new forms of storytelling by making visuals that once required massive budgets accessible to anyone.
Today's dominant AI tools like ChatGPT are perceived as productivity aids, akin to "homework helpers." The next multi-billion dollar opportunity is in creating the go-to AI for fun, creativity, and entertainment—the app people use when they're not working. This untapped market focuses on user expression and play.
Tools like Notebook LM don't just create visuals from a prompt. They analyze a provided corpus of content (videos, text) and synthesize that specific information into custom infographics or slide decks, ensuring deep contextual relevance to your source material.
While generative video gets the hype, producer Tim McLear finds AI's most practical use is automating tedious post-production tasks like data management and metadata logging. This frees up researchers and editors to focus on higher-value creative work, like finding more archival material, rather than being bogged down by manual data entry.
AI can now analyze video ads frame by frame, identifying the most compelling moments and justifying its choices with sophisticated creative principles like color theory and narrative juxtaposition. This allows for deep qualitative analysis of creative effectiveness at scale, surpassing simple A/B testing.
While today's focus is on text-based LLMs, the true, defensible AI battleground will be in complex modalities like video. Generating video requires multiple interacting models and unique architectures, creating far greater potential for differentiation and a wider competitive moat than text-based interfaces, which will become commoditized.
True creative mastery emerges from an unpredictable human process. AI can generate options quickly but bypasses this journey, losing the potential for inexplicable, last-minute genius that defines truly great work. It optimizes for speed at the cost of brilliance.
The real economic value of generative video lies in advertising, not filmmaking. Unlike movies with finite consumption, there is unlimited demand for personalized, diverse ad content. This makes advertising a perfect fit for the technology's scalable content creation capabilities.
As AI-generated content creates a sea of sameness, audiences will seek what machines cannot replicate: genuine emotion and deep, personal narrative. This will drive a creator-led shift toward more meaningful, long-form content that offers a real human connection.
The most creative use of AI isn't a single-shot generation. It's a continuous feedback loop. Designers should treat AI outputs as intermediate "throughputs"—artifacts to be edited in traditional tools and then fed back into the AI model as new inputs. This iterative remixing process is where happy accidents and true innovation occur.
When analyzing video, new generative models can create entirely new images that illustrate a described scene, rather than just pulling a direct screenshot. This allows AI to generate its own 'B-roll' or conceptual art that captures the essence of the source material.