Google’s AudioPaLM Can Speak and Listen
Plus: Stable Diffusion's most advanced upgrade, MosaicML's MPT-30B beats GPT-3.
Hello Engineering Leaders and AI Enthusiasts!
Welcome to the 48th edition of The AI Edge newsletter. This edition brings you AudioPaLM, a unified speech-text LLM by Google.
And a huge shoutout to our amazing readers. We appreciate you!😊
In today’s edition:
🤖 Google’s AudioPaLM can speak and listen
💥 SDXL 0.9, the most advanced development in Stabe Diffusion
📈 MosaicML's MPT-30B beats GPT-3
📚 Knowledge Nugget: Emerging architectures for LLM applications
Let’s go!
Google’s AudioPaLM can speak and listen
Google Research presents a large language model that understands and creates spoken language interchangeably. It fuses PaLM-2 and AudioLM into a unified multimodal architecture that can perform tasks such as speech recognition and speech-to-speech translation.
It not only translates but also retains the speaker's identity and tone of voice. Plus, it learns from huge amounts of text data, making it even better at dealing with speech-related tasks.
The model significantly outperforms existing systems for speech translation tasks and can perform zero-shot speech-to-text translation for many languages for which input/target language combinations were not seen in training. And it demonstrates features of audio language models.
Why does this matter?
This model unifies tasks traditionally solved by heterogeneous models into a single architecture and training run. It opens up possibilities for multimodal AI systems and more efficient use of data for training. Moreover, it can significantly advance human communication, education, and collaboration.
SDXL 0.9, the most advanced development in Stabe Diffusion
Stability AI announces SDXL 0.9, the most advanced development in the Stable Diffusion text-to-image suite of models. SDXL 0.9 produces massively improved image and composition detail over its predecessor, Stable Diffusion XL. Here’s an example of a prompt tested on both SDXL beta (left) and 0.9.
The key driver of this advancement in composition for SDXL 0.9 is its significant increase in parameter count over the beta version. SDXL 0.9 is run on two CLIP models, including one of the largest OpenCLIP models trained to date. This beefs up 0.9’s processing power and ability to create realistic imagery with greater depth and a higher resolution of 1024x1024.
Why does this matter?
Despite its ability to be run on a modern consumer GPU, SDXL 0.9 presents a leap in creative use cases for generative AI imagery. The ability to generate hyper-realistic creations and offering advancements for design and industrial use places SDXL 0.9 at the forefront of real-world applications for AI.
MosaicML's MPT-30B beats GPT-3
MPT-30B is a decoder-style transformer pre-trained model, Containing a massive dataset of 1T tokens of English text and code. This model was trained by MosaicML. MosaicML's MPT-30B is the smallest model to beat GPT-3. It is significantly more powerful than MPT-7B and outperforms the original GPT-3.
It is part of the Mosaic Pretrained Transformer (MPT) models family, which uses a modified transformer architecture optimized for efficient training and inference.
MPT-30B possesses special features that set it apart from other LLMs, which include:
- An 8k token context window, which can be further extended via finetuning
- Support for context-length extrapolation via ALiBi
- Efficient inference + training via FlashAttention
Why does this matter?
MPT-30B's extensive training, specialized features, coding abilities, efficiency, and open-source nature makes it a valuable language model for various NLP and coding tasks.
Beneficial for startups and small to medium-sized businesses (SMBs) because it can be deployed on a single GPU, which is a cost-effective and faster option for training and inference. This makes it a practical choice for organizations looking to enhance their NLP applications or improve coding tasks without straining their budget.
Knowledge Nugget: Emerging architectures for LLM applications
This informative post presents a reference architecture for the emerging LLM app stack, showcasing the prevalent systems, tools, and design patterns observed in use by AI startups and advanced technology companies. While this stack is in its early stages and subject to significant changes as the underlying technology progresses, we believe it will be a valuable resource for developers currently engaged with LLMs.
Why does this matter?
The reference architecture will allow developers to focus on implementing LLM functionality rather than spending time on infrastructure decisions.
Additionally, it promotes industry standards and interoperability among LLM applications. It drives innovation and advancement in the field while providing developers with efficient and reliable resources for LLM development.
What Else Is Happening❗
🖨️ Revolutionary “self-aware 3D printers” harness AI to identify and rectify errors! (Link)
💰 AWS introduces a $100M program to fund Gen AI initiatives. (Link)
🤝 MongoDB & Google Cloud's Vertex AI collaborated in light of new ai features. (Link)
📊 Google's AI-powered spreadsheet generator is now available! (Link)
🗣️ YouTube introduces AI-powered dubbing to overcome the language barrier! (Link)
🚗 Toyota Research Institute reveals AI vehicle design tool! (Link)
💻 Inflection launches its own AI model foundation to compete with OpenAI and Google. (Link)
🛠️ Trending Tools
B12 No-Code AI: Automate processes easily- lead generation, idea brainstorming, and drafting.
ChatNode: Train AI ChatBots with your own data, embed them on your website or use internally.
Chatdox: Chat with YouTube videos, save time by asking questions and getting quick answers.
Fix My Code: AI coding assistant for digital accessibility & ADA compliance, producing inclusive code.
Supervised: Create a custom LLM with your own data for precise AI app development.
SiteSpeak AI: Embed ChatGPT chatbot on your website, answering real-time questions about your products.
AI Keyword Suggestions: Discover keywords, generate top-notch website content effortlessly.
Pieces for Developers: Boost coding productivity with AI-infused code snippet manager, streamline workflow.
That's all for now!
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