2024年AI现状报告-2024年10月版（英）
AI智能总结State of AI Report 2024
Key Dimensions
The State of AI Report 2024, produced by Nathan Benaich and the Air Street Capital team, focuses on several key dimensions:
- Research: Technology breakthroughs and their capabilities.
- Industry: Commercial applications and business impact.
- Politics: Regulation, economic implications, and geopolitical dynamics.
- Safety: Identifying and mitigating risks posed by advanced AI systems.
- Predictions: Projections for the next 12 months and a 2023 performance review.
Definitions
- Artificial Intelligence (AI): A broad discipline aimed at creating intelligent machines.
- Artificial General Intelligence (AGI): Future machines that could match and exceed human cognitive abilities.
- AI Agent: An AI system that can take actions in an environment.
- AI Safety: A field focused on mitigating risks posed by future AI.
- Computer Vision (CV): A program's ability to analyze and understand images and videos.
- Deep Learning (DL): An AI approach inspired by brain neurons, using many layers to recognize complex patterns.
- Diffusion: An algorithm that generates new, high-quality outputs by iteratively denoising corrupted signals.
- Generative AI: AI systems capable of generating new content based on prompts.
- Graphics Processing Unit (GPU): A semiconductor for parallel calculations, originally used for rendering graphics.
- Large Language Model (LLM): A model trained on vast textual data to predict the next word.
- Machine Learning (ML): A subset of AI using statistical techniques to learn from data.
- Model: An ML algorithm trained on data to make predictions.
- Natural Language Processing (NLP): A program's ability to understand human language.
- Prompt: User input used to instruct an LLM.
- Reinforcement Learning (RL): An area of ML where software agents learn through trial and error.
- Self-Supervised Learning (SSL): Unsupervised learning where data is modified to create artificial labels.
- Transformer: A model architecture used in state-of-the-art ML research, focusing on attention layers.
Research
- Frontier Lab Performance: Converging, with OpenAI maintaining a leading edge post-launch of o1.
- Foundation Models: Demonstrating capability beyond language, breaking into fields like mathematics, biology, genomics, and neuroscience.
- Chinese (V)LLMs: Rising despite US sanctions.
Industry
- NVIDIA: Remains the most powerful company in the AI ecosystem, reaching $3T in market value.
- Regulation: Regulators probing the concentration of power within Generative AI (GenAI).
- Revenue: Established GenAI companies generating billions in revenue, with startups gaining traction in video and audio generation.
- Pricing and Sustainability: Long-term questions around pricing and sustainability unresolved.
Politics
- Global Governance: Efforts stalled, with national and regional regulation advancing.
- Compute Requirements: Big Tech companies facing real-world physical constraints on scaling and emissions targets.
- AI Effects: Potential impacts on elections, employment, and other areas not yet realized at scale.
Safety
- Bike Shift: From safety to acceleration, as companies focus on enterprise sales and usage.
- Government Action: Governments building capacity around AI safety, identifying critical infrastructure vulnerabilities.
- Attacks: Concerns over sophisticated, long-term attacks, with jailbreaking fixes failing.
Executive Summary
- 2023 Predictions Review:
- Hollywood Visual Effects: Correctly predicted that generative AI would be used for visual effects.
- Media Company Investigation: Not yet, but expected soon.
- Self-Improving AI Agents: Not achieved, though still in development.
This summary captures the key points and data from the State of AI Report 2024, providing a comprehensive overview of the current landscape and future trends in AI.
