Apple’s Keyframer: A Text-to-Anime AI Using GPT-4
Plus: Stability AI introduced Stable Cascade: A text-to-image model!, and OpenAI disrupted the activities of five state-affiliated threat actors!
Hello Engineering Leaders and AI Enthusiasts!
Welcome to the 211th edition of The AI Edge newsletter. This edition brings you Apple’s Keyframer: A Text-to-Anime AI Using GPT-4
And a huge shoutout to our amazing readers. We appreciate you😊
In today’s edition:
🎥Apple’s Keyframer: A Text-to-Anime AI Using GPT-4
🖼️Stability AI introduced Stable Cascade: A text-to-image model
🛡️OpenAI disrupted the activities of five state-affiliated threat actors
💡 Knowledge Nugget: Economic implications of AGI by
Let’s go!
Apple’s Keyframer: A text-to-anime AI using GPT-4
Apple has developed Keyframer, a prototype generative AI tool that enables users to add motion to 2D images through text descriptions. The LLM-powered Keyframer tool has OpenAI’s GPT-4 as its base model.
Apple’s Keyframer can take SVG files and generate CSS mode to animate images based on the text prompts. Users can upload an image and type in the prompt, for example, “make the stars twinkle,” which will generate the animation of twinkling stars. Among other examples provided in the research paper by Apple, there is one example showcasing how an illustration of Saturn transitions between background colors or shows fading stars in and out.
Keyframer allows users to create multiple animation designs, adjusting color codes, animation duration, and other properties in a separate window.
Keyframe is not publicly available yet and is limited to web-based animations like loading sequences, data visualizations, and animated transitions.
Why does it matter?
Apple’s Keyframer requires no coding experience and automatically converts text-based changes into CSS. The code is fully editable, making it an ideal choice for businesses looking to fine-tune the model for specific tasks. Another key advantage is the description-based approach for text prompts, which is simpler than other AI-generated animations and often requires coding experience.
Stability AI introduced Stable Cascade: A text-to-image model
In the research preview, Stability AI introduced Stable Cascade, a new text-to-image model built upon Würstchen architecture. It leverages a three-stage approach, improving quality, flexibility, fine-tuning, and efficiency. The model is created on a pipeline of three distinct models -Stages A, B, and C. It uses hierarchical compression of images to achieve high-quality output.
Stable Cascade stands out due to its remarkable compression and computational efficiency. The model significantly reduces computational requirements by decoupling text-conditional generation from image decoding while maintaining high-quality image outputs.
Fine-tuning Stage C alone results in a remarkable 16x cost reduction compared to traditional models. Stable Cascade introduces advanced features such as image variations, image-to-image translations, in-painting, and super-resolution, expanding its versatility and utility in various applications
Why does it matter?
Stable Cascade is a breakthrough in text-to-image generation. With its modular architecture and advanced features, it revolutionizes AI-driven art creation. It generates high-quality images with lower computational requirements, opening up new possibilities for image generation and augmentation. It's also free for non-commercial use and encourages developers and researchers to explore its potential. A
OpenAI and Microsoft disrupted the activities of five state-affiliated threat actors
Open AI collaborated with Microsoft to disrupt five state-affiliated malicious actors. Two cyber threat actors were Chine-affiliated, known as Charcoal Typhoon and Salmon Typhoon. One was an Iran-affiliated threat actor called Crimson Sandstorm; another was North Korea-affiliated Emerald Sleet. The last one was a Russia-affiliated threat actor known as Forest Blizzard.
These threat actors used Open AI services to query open-source information, translate, find coding errors, and run basic coding tasks. The action was a part of Microsoft and Open AI’s collaborative efforts towards AI safety. This collaboration aims to monitor and disrupt malicious affiliated actors per an executive order from the US Government on AI.
Why does it matter?
Open AI and Microsoft have limited capabilities in identifying and restricting malicious cybersecurity tasks across their AI models. However, with this initiative, both companies are taking a multi-pronged approach to reduce the impact of malicious state-affiliated actors on their platforms.
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Knowledge Nugget: Economic implications of transitioning from HGI to AGI
In this article,
discusses how the transition from human general intelligence to artificial general intelligence will impact humankind. The article also focuses on the economic impact of task-engaged AIs, the commoditization of the AI value chain, and the role of open-source AI models.Here are several critical aspects of AGI and its economic impact that are discussed:
Task-engaged AIs are expected to have transformative economic impacts when they mature.
The AI value chain is expected to become commoditized everywhere except for proprietary data.
AIs with loop control and dominance will subsume all tasks amenable to those interfaces in those environments.
Open-source AIs will excel in use cases with commoditized knowledge.
AGI development is expected to be monopolistic, commercial, open-access, and affordable.
Proprietary AI models are likely to dominate the market, given the challenges and limitations that open-source models face.
It further highlights the rapid convergence of AGI tech across companies and identifies the dominance of Google, Apple, and OpenAI.
Why does it matter?
Understanding the economic implications of the transition from HGI to AGI is crucial because the impact of AI on the global economy is expected to be significant. Few dominant AI systems are potentially capturing a large portion of the market. Understanding AI dynamics helps mitigate risks from a few firms controlling critical general-purpose technology.
What Else Is Happening❗
📢Amazon develops the BASE TTS text-to-speech model with emergent abilities.
Amazon has developed the largest text-to-speech model, which is named BASE TTS. This model uses 100,000 hours of public domain speech and has shown better adaptability and robustness regarding conversational AI tasks. The BASE-large model can handle various linguistic challenges, such as compound nouns, emotions, foreign words, and syntax. (Link)
🤖Nokia unveils AI assistant for industrial workers
Nokia's AI assistant, "Digital Assistant for Industrial Workers" (DAIW), aims to increase productivity and safety in industrial settings by providing real-time information, guidance, and support. Workers can interact with DAIW through voice commands or text inputs. Nokia plans to deploy DAIW in various industries to help workers perform better. (Link)
🏅Nvidia overtakes Alphabet to become the third most valuable company
Nvidia has become the third most valuable company in the United States, surpassing Alphabet, with a market capitalization of $1.825 trillion. This achievement results from the increasing demand for Nvidia's AI chips, which hold a significant market share of around 80% in the high-end AI chip market. Meanwhile, Microsoft still holds the title of the world's most valuable company, followed by Saudi Aramco. (Link)
🔍 Slack adds AI-based search and summarization to the platform.
Slack has recently added new features powered by AI technology to improve information accessibility and knowledge sharing within the platform. The new search tool uses AI to allow users to ask questions naturally and receive relevant answers from Slack's database. Additionally, it offers a channel summarization feature that automatically generates summaries of discussions, providing transparency and ensuring trust between users. (Link)
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