01.AI

Zero One Technology (01.AI) is an AI company founded by renowned computer scientist and investor Kai-Fu Lee in May 2023. The company focuses on AI 2.0 technologies and the development of large-scale AI models, aiming to advance natural language processing and large-model technologies.

Yi Series Models

• Yi-1.5 Series

  Yi-1.5 is an upgraded version of the original Yi model, offering enhanced performance, particularly in code generation, mathematical reasoning, complex reasoning, and instruction-following tasks.

  Versions:

  • Yi-1.5-34B: 34 billion parameters, suited for high-complexity tasks.
  • Yi-1.5-9B: 9 billion parameters, suited for medium-complexity tasks.
  • Yi-1.5-6B: 6 billion parameters, suited for lower-complexity tasks.

  Features:

  • Pre-training data: Trained on 500 billion high-quality tokens.
  • Fine-tuning data: Fine-tuned using 3 million diversified samples.
  • Applications: Language understanding, commonsense reasoning, reading comprehension, code generation, and mathematical reasoning.

• Yi-Large

  Yi-Large is a closed-source model with hundreds of billions of parameters. It has excelled in multiple benchmarks, surpassing GPT-4 in some metrics.

  • Parameter size: Hundreds of billions of parameters.
  • Performance: Strong performance in general capabilities, code generation, mathematical reasoning, and instruction-following.
  • Applications: Supports Q&A, document interpretation, PPT creation, and other office-related needs.

• Yi-XLarge MoE

  Yi-XLarge MoE is a larger model currently in training, aiming to achieve or surpass GPT-5-level performance.

  Features:

  • Architecture: Based on the Mixture of Experts (MoE) architecture.
  • Performance: Initial training results show that its metrics already surpass Yi-Large.

Other Models

• Yi-VL (Multimodal Model)

  The Yi-VL series is designed to handle multimodal input, processing both images and related discussions.

  Versions:

  • Yi-VL-34B: 34 billion parameters.
  • Yi-VL-6B: 6 billion parameters.

• Yi-Coder

  Yi-Coder focuses on code generation tasks, with a parameter size of less than 1 billion, but delivers outstanding performance in code-related tasks.

Main Pricing Model

1. API Call Charges

   One of the primary billing methods for Zero One Technology is based on API calls. Fees are usually charged according to the number of API calls or the number of tokens processed.

   • Yi-Large API: The current rate is ¥20 per million tokens (approximately $2.7 USD).
   • Cost Efficiency: In a media interview, Kai-Fu Lee emphasized the significant cost-efficiency advantage of the Yi-Large model's API. For instance, 1 million input tokens cost only $2.5, and 1 million output tokens cost only $12, which is more cost-effective than OpenAI's GPT-4.

Office Applications

1. Meeting Summaries

   Zero One Technology's AI tools can automatically generate meeting summaries, helping users quickly record and organize meeting content.

   Features: Automatically identifies and records key information from meetings, generating structured summaries. Benefits: Improves meeting efficiency and reduces manual note-taking time and errors.

2. Weekly Reports & Writing Assistant

   AI tools can assist users in writing weekly reports and other work documents by providing writing suggestions and auto-generating content.

   Features: Generates weekly reports and work documents based on user-provided keywords and requirements. Benefits: Saves time and improves document quality.

3. Financial Report Interpretation

   The AI tools can quickly interpret financial reports, extracting key data and information.

   Features: Automatically analyzes data from financial reports, generating concise interpretations and summaries. Benefits: Helps users quickly understand complex financial information for better decision-making.

4. PPT Creation

   AI tools can automatically generate PPT outlines and content based on user input.

   Features: Users input the PPT theme, and the AI tool generates an outline and completes the PPT in a short time. Benefits: Significantly reduces PPT creation time and improves work efficiency.

Educational Applications

1. Intelligent Tutoring

   AI technology can be used to provide personalized learning suggestions and guidance to students.

   Features: Generates personalized learning plans and tutoring content based on the student's progress and needs. Benefits: Increases learning efficiency and helps students better grasp knowledge.

2. Automated Homework Grading

   AI tools can automatically grade students' homework, providing detailed feedback and scores.

   Features: Automatically identifies errors in homework and generates detailed feedback reports. Benefits: Reduces teachers' workload and improves grading efficiency and accuracy.

Financial Applications

1. Risk Assessment

   AI technology can be used for financial risk assessment, helping financial institutions identify and manage risks.

   Features: Analyzes large volumes of financial data, generating risk assessment reports and recommendations. Benefits: Improves the accuracy and efficiency of risk management.

2. Investment Analysis

   AI tools assist investors in conducting investment analysis, offering investment suggestions and forecasts.

   Features: Analyzes market data and trends, generating investment recommendations and prediction reports. Benefits: Helps investors make more informed investment decisions.

Other Applications

1. Customer Support

   AI technology can be used for automated customer support, providing instant solutions to customer queries.

   Features: Provides 24/7 customer support through chatbots and automated response systems. Benefits: Improves customer satisfaction and reduces the workload of human support staff.

2. Personalized Shopping Experience

   AI technology can enhance e-commerce platforms by offering personalized shopping suggestions and experiences.

   Features: Generates personalized product recommendations based on users' shopping history and preferences. Benefits: Improves user shopping experience and increases platform sales.

Open-Source Versions

• Yi-1.5 Series

  The Yi-1.5 series is Zero One Technology's open-source model, with various parameter scales for different application scenarios.

  Versions:

  • Yi-1.5-34B: 34 billion parameters, suited for high-complexity tasks.
  • Yi-1.5-9B: 9 billion parameters, suited for medium-complexity tasks.
  • Yi-1.5-6B: 6 billion parameters, suited for lower-complexity tasks.

  Features:

  • Pre-training data: Trained on 500 billion high-quality tokens.
  • Fine-tuning data: Fine-tuned using 3 million diversified samples.
  • Applications: Language understanding, commonsense reasoning, reading comprehension, code generation, and mathematical reasoning.
  • License: Licensed under Apache 2.0, allowing free use, modification, and distribution.

• Yi-VL Series

  The Yi-VL series is an open-source multimodal model that supports joint processing of images and text.

  Versions:

  • Yi-VL-34B: 34 billion parameters.
  • Yi-VL-6B: 6 billion parameters.

  Features: Supports multimodal input, processing both images and related discussions.

• Yi-Coder Series

  The Yi-Coder series specializes in code generation tasks. Despite its smaller parameter size, it excels in code generation tasks.

  Features: Focuses on code generation, with less than 1 billion parameters, but delivers outstanding performance in code-related tasks.

Closed-Source Versions

• Yi-Large

  Yi-Large is Zero One Technology's closed-source model with hundreds of billions of parameters. It excels in multiple benchmarks, surpassing GPT-4 in some metrics.

  • Parameter size: Hundreds of billions of parameters.
  • Performance: Outstanding in general capabilities, code generation, mathematical reasoning, and instruction-following.
  • Applications: Supports Q&A, document interpretation, PPT creation, and other office-related needs.
  • Pricing model: API call charges, ¥20 per million tokens (approximately $2.7 USD).

• Yi-XLarge MoE

  Yi-XLarge MoE is a larger model in training, with the goal of achieving or surpassing GPT-5-level performance.

  Features:

  • Architecture: Based on the Mixture of Experts (MoE) architecture.
  • Performance: Initial training results show that its metrics have already surpassed Yi-Large.