1.5: A Creator's First 30 Days – AI, From Hype to Utility — LiliDi Bl…
Follow one creator's journey over 30 days, navigating the evolving landscape of AI image and video generation and understanding what '1.5' realistically means…
By lilidi editorial
1.5: A Creator's First 30 Days – AI, From Hype to Utility Thirty days. That's how long I gave myself to move past the initial buzz surrounding AI image and video generation and truly integrate it into my creative process. The promise of "1.5" versions, referring to incremental but significant updates in AI models, particularly in diffusion models, was often met with a mix of excitement and skepticism within creator communities. My goal was simple: filter out the noise and find practical applications, especially with new platforms like lilidi.ai emerging. This isn't about showcasing viral magic tricks; it's about documenting a month of learning, frustration, and eventual integration. Week 1: The Initial Dive and Reality Check My first week was dedicated to exploration. I wasn't entirely new to AI tools, but the pace of development, especially around what constitutes a "1.5" jump in
capability, meant constant re learning. I started by generating static images, focusing on specific styles and compositions that usually take me hours of manual work. The Allure of "V1.5" Capabilities Many discussions around "1.5" versions centered on improved coherence, better understanding of complex prompts, and enhanced detail. For me, this translated to a desire for less "AI weirdness" – fewer distorted limbs, more believable textures, and a better grasp of artistic nuances. I began with basic prompts: "A lone cyberpunk samurai walking through a rainy neon city, cinematic lighting," and then iterated. What I found was a significant reduction in the need for extensive negative prompting compared to earlier versions I'd used. Faces were more consistent, hands (a notorious AI challenge) were improving, and the overall scene composition felt more intentional. Early Frustrations and
Learning the Language Despite improvements, the initial days were challenging. AI still possesses its own unique "language." My usual art direction terms didn't always translate directly. I spent hours tweaking prompts, adding weights to specific keywords (e.g., (cinematic lighting:1.3) ), and experimenting with different aspect ratios. It was less about generating a perfect image on the first try and more about understanding the model's sensitivities. By the end of week one, I had a collection of decent static images, but the workflow still felt clunky. I questioned whether the time saved in rendering was being eaten up by prompt engineering. Week 2: Experimenting with Control and Iteration The second week marked a shift from pure generation to more controlled creation. This is where features often associated with the "1.5" iterations truly began to shine, particularly in terms of
consistency and control over generated outputs. Image to Image and Inpainting One of the most powerful aspects I discovered was image to image generation. Instead of starting from scratch, I could feed the AI a rough sketch or a photograph and guide it towards my desired output. This was a game changer for maintaining consistent character designs or specific environmental elements across multiple images. For example, I had a character concept sketch for a personal project. I fed it into lilidi.ai and used a refined prompt. The ability to iterate on this initial image, changing lighting, expressions, or apparel while retaining the core identity, significantly accelerated my conceptualization phase. Inpainting – the ability to modify specific areas of an image – also proved invaluable for correcting minor flaws or adding details I hadn't considered in the initial prompt. The Subtle Art of
Prompt Blending I also delved into prompt blending, where you combine the characteristics of multiple prompts. For instance, [photorealistic::abstract painting:0.7] allowed me to create images that had a photographic base but with an overlaid painterly aesthetic. This level of granular control was a clear indicator of how "1.5" models were moving beyond simple text to image and into more sophisticated artistic control. My focus this week was less on speed and more on precision. I started to see AI not as a replacement, but as an incredibly powerful assistant for creative exploration. Week 3: Venturing into Video and Beyond Static With a solid grasp of image generation, week three was dedicated to the more complex world of AI video. This is where the hype around "1.5" capabilities often reached its peak, promising seamless animations and dynamic scenes from text. AI Video: Expectations
vs. Reality My initial attempts at AI video were a dose of reality. While impressive progress has been made, particularly in short, stylized clips, generating long form, narrative driven video with consistent characters and camera movements from text alone is still a significant challenge. The "1.5" improvements in consistency were more apparent in maintaining object coherence within short clips rather than entire story arcs. I focused on generating short looping backgrounds for presentations, stylized transitions for video edits, and abstract motion graphics. For example, I successfully created a 5 second animated loop of "glowing bioluminescent plants in a mystical forest, gently swaying" that I could use as an overlay. The quality was production ready for specific applications, but not for complex character animation. The Importance of Compositing and Post Production What I learned
quickly was that AI generated video, for a creator like me, is often a starting point, not a finished product. It requires compositing, editing, and often traditional animation techniques to achieve professional results. Lilidi.ai's output could provide excellent base footage, which I then brought into my video editor for further refinement, sound design, and color grading. This hybridized workflow felt genuinely productive. Week 4: Integration and Workflow Optimization The final week was about integrating AI into my existing creative pipelines. This meant less experimentation and more focused application. AI as a "Co Creator" I started viewing the AI as a co creator or a highly skilled intern. Instead of spending hours conceptualizing character poses or environment lighting, I could generate dozens of variations in minutes. This rapid prototyping significantly reduced the initial
ideation phase of projects. For a recent client project requiring a series of abstract digital art pieces, I used AI to generate stylistic elements and textures, which I then refined in Photoshop. The initial output from lilidi.ai provided a strong foundation, allowing me to focus on the artistic direction and finer details rather than getting bogged down in repetitive tasks. The Future of "1.5" and Beyond My 30 day journey reinforced that "1.5" iterations represent crucial steps forward, offering better fidelity, more control, and expanded capabilities. However, they don't erase the need for human creativity, skill, or critical thinking. Instead, they elevate what's possible, allowing creators to explore ideas faster and push artistic boundaries further. The key takeaway is that learning to effectively "talk" to these models, understanding their strengths and limitations, and
integrating them intelligently into an existing workflow is paramount. The creator who embraces this partnership will be the one who truly benefits from the rapid evolution of AI. FAQ Q: What does "1.5" actually refer to in AI text to image/video models? A: "1.5" is a shorthand often used by developers and communities to denote an incremental but notable update to an existing AI model, particularly diffusion models. These updates typically bring improvements in image quality, coherence, prompt understanding, detail generation, and sometimes new features like enhanced inpainting or control mechanisms, without being a complete architectural overhaul of a "2.0" version. Q: Is AI image and video generation fully automated now with these updates? A: No, far from it for professional use. While AI tools like those on lilidi.ai can generate impressive raw output, particularly with "1.5"
improvements, they still require significant human input, iteration, prompt engineering, and often post processing (editing, compositing, color grading) to achieve polished, production ready results that meet specific creative visions. Q: How can a traditional artist or designer best integrate these AI tools into their workflow? A: For traditional artists, AI tools are best utilized as powerful conceptualization, ideation, and assistance tools. They can rapidly generate variations of compositions, lighting, character poses, or visual styles. Instead of replacing traditional skills, AI can free up time for artists to focus on higher level artistic direction, refinement, and injecting their unique creative voice into the final output. Think of it as a creative assistant that handles the initial heavy lifting or generates unexpected inspiration.