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AI Meets Language in Autonomous Vehicles 🚘
PLUS: Generative Art with Coding, New AI Capabilities for Document Processing
Today’s top AI Highlights:
LINGO-1's Language-Powered Driving Intelligence
Google's Document AI Workbench Transforms Documents
Art and Code Converge using Spellburst
From Meta Prompt to Maximum Accuracy
& so much more!
Read time: 3 mins
Latest Developments 🌍
Autonomously Driving into the Future 🚘
Wayve has introduced LINGO-1, an open-loop driving commentator, harnessing natural language in autonomous driving to enhance the interpretability and training of driving models. They are taking inspiration from LLMs and combining language with vision and action data to create VLAMs.
LINGO-1 is trained using a dataset that includes image, language, and action data from expert drivers. Expert drivers provide commentary while driving, similar to how driving instructors teach by explaining their actions.
It performs visual Q&A related to perception, counterfactuals, planning, reasoning, and attention, and can describe driving actions and reasoning for autonomous driving.
It achieves around 60% accuracy compared to human-level performance and is continually improving its accuracy through further enhancements.
Get More from Your Documents 🔖
Document AI Workbench, Google’s document processing powerhouse, introduces powerful generative AI capabilities, enhancing document structuring and customization.
Users can now extract structured data from complex documents without model training, significantly reducing processing time.
The Summarizer offers customizable document summaries for up to 250 pages, providing flexibility and efficiency.
Auto-labeling with generative AI enables users to prepare datasets and enhance document quality effortlessly.
Self-Optimizing Language Models 🛠️
Google DeepMind has discovered that LLMs can optimize their own prompts, improving their accuracy in real-world applications. They introduce Optimization by PROmpting (OPRO), that involves using LLMs as optimizers by describing optimization tasks in natural language rather than formal mathematical terms.
OPRO is highly adaptable and can be guided to solve a wide range of problems by modifying problem descriptions or adding specific instructions.
OPRO begins with a "meta-prompt" that includes task descriptions, examples, placeholders for instructions, and solutions. The LLM generates candidate solutions based on this meta-prompt.
LLMs, when used with OPRO, can generate effective solutions on small-scale optimization problems, consistently outperforming traditional algorithms, and optimize LLM prompts to maximize accuracy.
Generative Art Meets Coding ✍️
Researchers at Stanford University have introduced Spellburst, a creative-coding environment powered by LLM, addressing challenges faced by generative artists in translating their artistic visions into code.
Spellburst, powered by GPT-4, offers artists fine-grained control, allowing them to adjust textures, colors, and patterns with dynamic sliders and modification notes.
The tool allows artists to combine elements from different iterations, enabling experimentation with various visual elements.
Artists can easily transition between prompt-based exploration and code editing by clicking on the generated image.
Tools of the Trade ⚒️
Fireworks AI: Fast, affordable, and customizable generative AI platform for LLM inference, with low latency, and support for fine-tuned models, all accessible through simple APIs.
Onnix AI: AI copilot for bankers, offering personalized services for preparing slide decks, excel analysis, and querying data sources quickly.
Munch: AI-powered video repurposing platform that automatically extracts engaging clips from long-form videos, with video editing and caption generation.
Spoke.ai: AI-driven summarization tools to get actionable and contextual summaries for various teams, AI-digests of Slack channels, along with data privacy.
Morph: All-in-one data studio with AI-powered real-time collaboration that simplifies data tasks, eliminates file exchanges, and offers robust API support for developers.
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Hot Takes 🔥
it’s tiring being america and being responsible for 90% of the innovation that happens at all. if some American company doesn’t do it nobody will ~ roon
the fact that i didn't learn about testing during my entire computer science degree is insane ~ Kevin Naughton Jr.
Meme of the Day 🤡
That’s all for today!
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