Maintaining Localized Image Variation | ScaleAI LLM Engine | SHOW-1
07/20/23 • 11 min
Welcome to AI Daily! In this episode, we dive into three extraordinary and useful stories. First up, Maintaining Localized Image Variation - the groundbreaking paper that unveils a new way to edit shape variations within text-to-image diffusion models. Next, ScaleAI LLM Engine - ScaleAI has open-sourced a game-changing package for fine-tuning, inference, and training language models. Last but not least, SHOW-1 - the solution to the "slot machine problem" in video generation, where randomness prevails.
Quick Points
1️⃣ Maintaining Localized Image Variations
Discover groundbreaking paper on maintaining localized image variation in text-to-image diffusion models, enabling precise object editing.
A practical and intelligent engineering solution that offers CGI-level control without the labor-intensive process, making it highly useful.
Impressive implementation with a hugging face demo showcasing effective object preservation and image transformations for stunning results.
2️⃣ ScaleAI LLM Engine
ScaleAI revolutionizes language model development by open-sourcing LLM Engine, allowing easy fine-tuning, inference, and training.
Their move showcases commitment to staying at the forefront of AI development and provides practical, useful tools for developers.
The open-source community benefits from ScaleAI's meaningful contribution, offering a powerful project that scales effortlessly with Kubernetes.
3️⃣ SHOW-1
Introducing SHOW-1, a show runner agent that tackles the challenge of creating consistent animated shows using image and video models.
Aiming to solve the "slot machine problem," SHOW-1 combines prompt engineering and consistent frame sets to generate coherent and engaging video content.
Impressive engineering and clean outputs make SHOW-1 stand out, offering videos that resemble popular shows like South Park in appearance and sound. Ambitious and promising for future iterations.
🔗 Episode Links
Maintaining Localized Image Variations
Justin Alvey - Jailbroke Google Nest Mini
Connect With Us:
Follow us on Threads
Subscribe to our Substack
Follow us on Twitter:
This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.aidailypod.com
Welcome to AI Daily! In this episode, we dive into three extraordinary and useful stories. First up, Maintaining Localized Image Variation - the groundbreaking paper that unveils a new way to edit shape variations within text-to-image diffusion models. Next, ScaleAI LLM Engine - ScaleAI has open-sourced a game-changing package for fine-tuning, inference, and training language models. Last but not least, SHOW-1 - the solution to the "slot machine problem" in video generation, where randomness prevails.
Quick Points
1️⃣ Maintaining Localized Image Variations
Discover groundbreaking paper on maintaining localized image variation in text-to-image diffusion models, enabling precise object editing.
A practical and intelligent engineering solution that offers CGI-level control without the labor-intensive process, making it highly useful.
Impressive implementation with a hugging face demo showcasing effective object preservation and image transformations for stunning results.
2️⃣ ScaleAI LLM Engine
ScaleAI revolutionizes language model development by open-sourcing LLM Engine, allowing easy fine-tuning, inference, and training.
Their move showcases commitment to staying at the forefront of AI development and provides practical, useful tools for developers.
The open-source community benefits from ScaleAI's meaningful contribution, offering a powerful project that scales effortlessly with Kubernetes.
3️⃣ SHOW-1
Introducing SHOW-1, a show runner agent that tackles the challenge of creating consistent animated shows using image and video models.
Aiming to solve the "slot machine problem," SHOW-1 combines prompt engineering and consistent frame sets to generate coherent and engaging video content.
Impressive engineering and clean outputs make SHOW-1 stand out, offering videos that resemble popular shows like South Park in appearance and sound. Ambitious and promising for future iterations.
🔗 Episode Links
Maintaining Localized Image Variations
Justin Alvey - Jailbroke Google Nest Mini
Connect With Us:
Follow us on Threads
Subscribe to our Substack
Follow us on Twitter:
This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.aidailypod.com
Previous Episode
Meta's Llama 2 | Neural Video Editing | FlashAttention-2
Today on AI Daily, we have three-big stories for you. First, Meta's Llama 2 takes the spotlight, revolutionizing open-source models with its commercial availability. Next, we discuss Neural Video Editing which offers a game-changing solution for seamless frame-by-frame editing in videos. And lastly, FlashAttention-2 delivers lightning-fast GPU efficiency and supercharging performance.
Key Points
1️⃣ Meta’s Llama 2
Llama 2, Meta's new addition to the llama open source model, is now commercially available and free for commercial use.
Llama 2 is highly capable, comparable to GP 3.5, and is expected to dominate the open source model landscape.
The release of Llama 2 creates a significant shift for AI developers, allowing them to run and fine-tune models without additional costs or safety measures from OpenAI.
2️⃣ Neural Video Editing
Neural video editing allows users to edit a single frame in a video and apply the edit to the entire video, making it accessible and powerful for beginners and those with limited resources.
This technology combines optical flow, control nets, and segment anything to enable interactive and real-time editing of videos.
Adobe and the University of British Columbia collaborated on the development of this interactive neural video editing, which is expected to be integrated into Adobe products soon.
3️⃣ FlashAttention-2
FlashAttention-2 is a highly efficient GPU usage technique that is twice as fast as the original FlashAttention, providing a significant boost in performance and cost-effectiveness.
The improved FlashAttention enables longer context windows for video and language models and paves the way for future hardware developments.
This advancement is crucial for maximizing GPU capabilities and brings us closer to unlocking the full potential of current and upcoming hardware.
🔗 Episode Links
Latent Space Episode: Datasets 101
Connect With Us:
Follow us on Threads
Subscribe to our Substack
Follow us on Twitter:
This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.aidailypod.com
Next Episode
3D LLM | VIMA | FreeWilly1&2
Welcome to another fascinating episode of AIDaily, where your hosts, Farb, Ethan, and Conner, delve into the latest in the world of AI. In this episode, we cover 3D LLM, a cutting-edge blend of large language models and 3D understanding, heralding a future where AI could navigate full spatial rooms in homes and robotics. We also discuss VIMA, a groundbreaking demonstration of how large language models and robot arms can synergistically work together, suggesting a transformative path for robotics with multimodal prompts. Lastly, we explore the implications of StabilityAI's recent launch of FreeWilly1 and FreeWilly2, open-source AI models trained on GPT-4 output.
Quick Points:
1️⃣ 3D LLM
A revolutionary mix of large language models and 3D understanding, enabling AI to navigate full spatial rooms effectively.
Potentially instrumental for smart homes, robotics, and other applications requiring spatial understanding.
Combines 3D point cloud data with 2D vision models for effective 3D scene interpretation.
2️⃣ VIMA
A groundbreaking demonstration of robot arms working with large language models, expanding their capabilities.
Uses multimodal prompts (text, images, video frames) to mimic movements and tasks.
The model's potential real-world application is yet to be tested against various edge cases.
3️⃣ FreeWilly1 & FreeWilly2
Open-source AI models launched by StabilityAI, trained on GPT-4 output.
Demonstrates the capability of the Orca framework in producing efficient AI models.
The models are primarily available for research purposes, showing improvements over their predecessor, Llama.
🔗 Episode Links:
OpenAI Closes AI Detection Tool
Connect With Us:
Follow us on Threads
Subscribe to our Substack
Follow us on Twitter:
This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.aidailypod.com
If you like this episode you’ll love
Episode Comments
Generate a badge
Get a badge for your website that links back to this episode
<a href="https://goodpods.com/podcasts/ai-daily-275807/maintaining-localized-image-variation-scaleai-llm-engine-show-1-33523505"> <img src="https://storage.googleapis.com/goodpods-images-bucket/badges/generic-badge-1.svg" alt="listen to maintaining localized image variation | scaleai llm engine | show-1 on goodpods" style="width: 225px" /> </a>
Copy