Real-time AI-powered design with Krea CEO Victor Perez | E1850
TLDRThe transcript discusses the revolutionary impact of AI on the creative process, highlighting a new startup called kore.ai that has developed a real-time AI powered creative tool. The tool, which operates in the browser, allows users to transform simple doodles into realistic images and even control them in real-time. The conversation emphasizes the potential of AI to streamline and enhance various creative fields, from filmmaking to journalism, by turning ideas into high-quality, detailed outputs迅速. The startup's success is evident in its growing customer base and the excitement it has generated within the industry.
Takeaways
- 🚀 The startup kore.ai is developing a real-time AI-powered creative toolset that works in the browser, aiming to bridge the gap from concept to finished product efficiently.
- 🎨 The AI tool created by kore.ai allows users to manipulate and generate images in real-time, providing a new dimension for creative prompting and interaction with AI.
- 💡 The technology behind kore.ai's tool uses a version of stable diffusion, a model that can generate images in 40 milliseconds, offering a fast and efficient creative process.
- 🌐 The AI tool went viral on social media, attracting a waiting list of over 200,000 people, showing a high demand for such creative AI solutions.
- 📈 The startup has raised seed funding and is currently focusing on a consumer product, targeting a wide range of creatives including filmmakers, graphic designers, and 3D artists.
- 💻 The tool's infrastructure is built to scale, with the team working on handling thousands of users generating images in real-time, using powerful GPUs like the A100.
- 🎓 The founder of kore.ai, Victor Perez, got into AI after being interested in artistic pursuits and seeing the potential of AI as a new creative medium.
- 🌐 The open-source community has played a significant role in improving stable diffusion, showing the power of collaborative work in advancing AI technologies.
- 🤖 The future of AI in software development includes AI agents taking over tasks that currently require human engineering, significantly increasing efficiency and reducing the need for manual testing.
- 🔍 Testrig, another startup, is streamlining the process of software validation and quality assurance testing by allowing non-technical users to describe how a system should function, and their AI executes those instructions.
Q & A
What is the main goal of the startup kore.ai?
-The main goal of kore.ai is to create a real-time AI-powered creative toolset that works in the browser, allowing users to interactively generate images and art based on simple prompts and visual inputs.
How does the AI model used by kore.ai differ from previous models like DALL-E and Stable Diffusion?
-The AI model used by kore.ai is a version of Stable Diffusion that has been distilled with a new technology called 'consistency', which allows the model to run at incredibly fast speeds, generating images in as little as 40 milliseconds.
What kind of users are currently paying for kore.ai's tool?
-The users who are paying for kore.ai's tool are mainly creatives, including professional film directors, graphic designers, and 3D artists, who use the tool for various creative purposes such as mood boards, typography, and brainstorming.
How does the CEO of kore.ai, Victor Perez, envision the future of AI in creative processes?
-Victor Perez envisions a future where AI becomes an integral part of the creative process, allowing individuals to go from an initial idea or doodle to a finished, high-resolution product with ease and efficiency, potentially running on personal computers or laptops.
What is the current state of AI in the field of software testing?
-AI is starting to play a significant role in software testing by automating the process and allowing non-technical users to describe how a system should function in plain English, which the AI then executes without the need for manual coding or technical details.
How does the startup test trigger address the challenges in software testing?
-Test trigger addresses the challenges in software testing by providing a platform that allows users to describe test cases in normal English, and then the system executes those instructions, emulating exactly how a human would perform the task, increasing test stability and reducing the need for manual testing.
What is the potential impact of AI on the efficiency of software development teams?
-The potential impact of AI on software development teams is significant, as it can automate various tasks, reduce the time and effort required for testing and onboarding new developers, and ultimately increase the overall efficiency and speed of software development processes.
How does the AI in test trigger differ from other AI tools like GitHub Copilot?
-While GitHub Copilot assists developers by providing code suggestions and helping with codebase understanding, test trigger's AI focuses on automating the testing process by executing test cases described in plain English, without the need for manual coding or technical details.
What are some of the challenges that AI in software testing might face in terms of copyright and training data?
-Challenges that AI in software testing might face include issues related to copyright infringement due to the use of copyrighted images in training data, and the need to constantly update and retrain the models to keep up with changes in user interfaces and functionalities.
How does the startup Masterworks differ from traditional art investment?
-Masterworks differs from traditional art investment by providing a platform that allows everyday investors to gain exposure to the Blue Chip art asset class without needing millions of dollars, through the securitization of high-value art pieces and the sale of shares to investors.
What is the significance of the open-source community in the development of AI models like Stable Diffusion?
-The open-source community plays a crucial role in the development of AI models like Stable Diffusion by collaborating on improvements, sharing knowledge, and contributing to the codebase, which accelerates innovation and enhances the capabilities of the models beyond what individual companies or research institutions could achieve alone.
Outlines
🚀 Introduction to AI-Powered Creative Tools
The paragraph discusses the emergence of AI-powered creative tools that are revolutionizing the way creatives work. It highlights the transition from initial ideas and doodles to finished products, facilitated by AI. The conversation involves a startup called kore.ai, which has developed a real-time AI-powered creative tool set that operates in the browser. The tool went viral and has attracted a waiting list of over 200,000 people. The startup's aim is to streamline the creative process by providing a platform where users can generate images and ideas quickly and efficiently.
🎨 Real-Time AI Creative Tool Demonstration
This paragraph provides a detailed demonstration of kore.ai's real-time AI creative tool. It explains how the tool works by using an image-to-image technique, allowing users to manipulate and generate images based on simple prompts. The tool's innovative aspect lies in its ability to respond to visual prompts in real time, giving users full control over the final image. The backend of the tool uses a version of stable diffusion, which can generate a single image in 40 milliseconds. The conversation also touches on the potential of these tools in various creative fields, including journalism and documentary making.
💡 The Future of AI in Creative Industries
The discussion in this paragraph focuses on the future potential of AI in the creative industry. It emphasizes the efficiency and quality improvements that AI is expected to bring to various sectors, including graphic design, web page creation, and illustration. The conversation also explores the possibility of AI tools becoming accessible on personal computers and laptops, predicting that in a few months, these tools could be running on devices like M1 and M2 chips. The potential applications of AI in journalism and the creation of illustrative content are also discussed, highlighting the transformative impact of AI on creative processes.
🌐 Open Source AI Models and Collaboration
This paragraph delves into the open-source nature of AI models like stable diffusion and the collaborative efforts of the global community in improving these models. It discusses the power of open-source projects, where individuals from around the world contribute to enhance the technology. The conversation also touches on the importance of weights in neural networks and how sharing these weights allows for rapid advancements in AI capabilities. The potential legal and ethical considerations surrounding the use of copyrighted images in training data are also briefly mentioned.
🤖 AI's Impact on Software Development and Testing
The paragraph discusses the impact of AI on software development and quality assurance (QA) testing. It introduces Test Rigor, a startup that aims to streamline the software validation process by enabling non-technical users to perform test automation. The conversation highlights the limitations of current test automation methods and how Test Rigor's approach allows for more efficient and cost-effective testing. The potential of AI to completely replace human engineers in certain aspects of software development and testing is also explored, emphasizing the shift towards AI agents that can execute tasks based on plain English instructions.
Mindmap
Keywords
💡AI powered creative tools
💡Real-time AI
💡Stable Diffusion
💡Image to image
💡Creatives
💡Infrastructure
💡GPU clustering
💡Open source
💡Weights in AI
💡Copyright and AI
Highlights
AI powered creative tools are increasingly popular in the market, with platforms like Canva, Open AI, Adobe, Mid Journey, and Stable Fusion Runway offering innovative ways for creatives to produce interesting outputs faster and better.
A new startup, kore.ai, is developing a real-time AI powered creative toolset that operates in the browser, offering a unique interactive experience for users.
The AI model can transform simple shapes into realistic images based on prompts, and allows users to control and refine the generated images in real-time.
Kore.ai's technology enables users to visually prompt the AI model, adding a new dimension to the creative process and making it more interactive.
The backend of kore.ai's tool utilizes a version of Stable Diffusion, a powerful image model that can generate high-quality images in milliseconds.
Kore.ai's tool can be used by a wide range of creative professionals, from filmmakers to graphic designers and 3D artists, to brainstorm and produce high-quality visual content.
The startup has attracted a large number of users, with a waiting list of over 200,000 people, showing the high demand for such technology.
Kore.ai's tool has the potential to revolutionize the creative process by allowing users to go from a simple doodle to a finished product with the help of AI.
The company has raised funds and is focusing on a consumer product, aiming to make the technology accessible to a wide audience.
The AI model can be run on powerful GPUs like the A100, making it possible to generate images at high speeds.
Kore.ai's technology could potentially be integrated into various industries, such as journalism, where it could help create illustrative content quickly and efficiently.
The startup scene in Barcelona is vibrant, with many talented individuals and entrepreneurs, despite some challenges in the local economy and legal system.
AI is expected to play a significant role in the future of software development and testing, potentially replacing humans in certain tasks and increasing efficiency.
Test Rigor is a startup that aims to streamline the software validation process by allowing non-technical users to perform quality assurance testing through natural language instructions.
AI has the potential to significantly reduce the time and cost associated with software testing, making it a more efficient and accessible process for companies of all sizes.
The future of AI in software testing may involve AI agents that can automatically execute tests and provide suggestions for improvements, further revolutionizing the field.