Anthropic’s New AI Can Control Your Computer!

Anthropic's New Models and Computer Use Feature

Introduction to New Models

• Anthropic has released two new models, including Claude 3.5 Sonet, which is an upgrade over their previous best model, Claude 3 Opus.

• The new Claude 3.5 Sonet is reported to be better at coding tasks, reinforcing its reputation as a leading AI coder in the industry.

Performance Benchmarks

• The upgraded Claude 3.5 Sonet shows significant improvements across various benchmarks compared to its predecessor.

• Notably, it excels in graduate-level reasoning (increased from 59% to 65%) and math problem-solving (from 71% to 78%), although Gemini 1.5 Pro still leads with an impressive score of 86.2%.

• The model also demonstrates enhanced performance in agentic coding (49% vs. previous version's 33%) and tool use metrics.

Introduction of Computer Use Feature

• A groundbreaking feature called "computer use" allows users to command Claude to control their computer directly through prompts.

• This feature enables tasks like filling out forms by gathering data from various sources on the user's computer automatically.

Demonstration of Computer Use

• In a fictional demo, Claude successfully fills out a vendor request form by searching for necessary information across different applications on the computer.

• The demonstration highlights how Claude can automate tedious tasks without user intervention, showcasing its potential for efficiency.

Future Implications and Considerations

• This innovative interface suggests a future where traditional computer interfaces may become obsolete as users interact with AI more naturally.

Understanding AI's Interaction with Computers

Importance of Sensitive Data Management

• Emphasizes the need to prevent AI models from accessing sensitive information, such as account logins, to mitigate risks of information theft.

• Suggests limiting internet access to a predefined list of domains to reduce exposure to malicious content.

• Recommends human confirmation for decisions that could lead to significant real-world consequences.

Functionality of AI in Computer Use

• Describes how AI interprets user commands by analyzing screenshots and mapping coordinates on the screen for mouse movements and clicks.

• Notes that the coordinate system used by some projects may not function effectively, impacting overall performance.

• Introduces a simple API schema for interacting with desktop GUI applications, including various mouse actions and screenshot capabilities.

Future Prospects of AI Integration

• Mentions potential future testing of computer use functionality with Claude and invites viewer feedback for further exploration.

• Highlights Claude's ability to emulate human interaction with computers through cursor movement and keyboard input based on user commands.

Challenges in Current Systems

• Discusses the limitations of existing operating systems designed primarily for human users rather than AI interactions.

• Argues that current technology lacks advanced operating systems tailored specifically for large language models (LLMs).

The Need for Enhanced Interaction Capabilities

• Stresses that without APIs available for all software, there is a necessity for AIs to interact similarly to humans using traditional interfaces like mice and keyboards.

• Points out that achieving comprehensive task execution by agents requires them to engage directly with personal accounts and computer systems.

Competitive Landscape in Technology

• Observes that companies like Google and Apple hold significant advantages due to their deep integration into everyday technology usage across devices.

Research Insights on Multimodality

• Explains how research into multimodal capabilities has facilitated the development of computer use functionalities within AI systems.

Limitations in Pixel Counting Techniques

• Details challenges faced when training Claude on pixel counting necessary for accurate cursor movements during software interactions.

• Concludes that without precise pixel counting abilities, the model struggles with executing mouse commands effectively.

Coding with Claude: A Demonstration of AI-Assisted Development

Introduction to AI Coding Assistance

• Alex, a lead developer relations at Anthropic, introduces a coding task using the AI model Claude to demonstrate its capabilities in coding and debugging.

Creating a Personal Homepage

• The demonstration begins with Claude navigating to "claw" within Chrome and prompting another instance of Claude to create a personal homepage themed around "9s."

• After receiving the generated code, Alex decides to download it for local modifications in VS Code.

Setting Up the Local Environment

• Claude successfully opens the downloaded file in VS Code after saving it from Chrome.

• When attempting to start a local server, an error occurs due to Python not being installed; however, Claude quickly identifies this and switches to Python 3 which is available.

Debugging Process

• With the server running, they check the website but notice an error indicated in the terminal output.

• Claude uses the find-and-replace tool in VS Code to locate and remove the problematic line of code before saving and rerunning the website.

Final Review of Changes

• After fixing the error, they review the website again where both issues—the missing file icon and terminal error—are resolved successfully.

Exploring Practical Applications of AI

Planning Activities with AI Assistance

• Puja, a researcher at Anthropic, shares her experience using Claude for planning logistics for a friend's visit involving tourist activities like hiking.

Utilizing Google Maps and Calendar Integration

• Claude searches for sunrise times and calculates distances using Google Maps while also creating calendar invites with relevant details for easy scheduling.

Limitations Observed During Demonstration

Unexpected Behavior from AI Model