OpenAI Brings AI Coding Assistant Codex to iOS and Android
In brief
- OpenAI has integrated its powerful AI coding assistant, Codex, directly into ChatGPT for mobile users.
- This means anyone with the app can now write code in multiple programming languages by simply describing what they want.
- Whether it's debugging or building new features, developers can get real-time assistance right on their phones.
- The move marks a significant expansion of OpenAI's tools, making advanced coding support more accessible than ever.
- Developers who test this feature have praised its speed and accuracy, especially for complex tasks like code generation and debugging.
- This integration could save professionals hours of work and streamline the development process.
- For users already familiar with ChatGPT, accessing Codex is seamless-it works right within the app's interface.
- OpenAI plans to roll out updates with more features and improved performance in the coming months, making it an even stronger tool for developers worldwide.
Terms in this brief
- Codex
- An AI coding assistant developed by OpenAI that helps users write code in multiple programming languages by describing what they want. It provides real-time assistance for tasks like debugging and building new features, making advanced coding support accessible directly within ChatGPT on mobile devices.
Read full story at The Decoder →
More briefs
AI Streamlines Employee Performance Reviews
Companies are using AI to write employee performance reviews. AI systems can pull data from across an organization to draft evaluations. AI can cut review-writing time by 40%. This matters because it can save companies time and money. For example, Boston Consulting Group uses an AI assistant to speed up the review process. Companies will continue to use AI to improve performance reviews.
x.AI Unveils Terminal-Based Coding Tool Grok Build
Elon Musk's AI company, x.AI, has launched Grok Build, a terminal-based coding tool designed to assist developers. This tool marks x.AI's first entry into the coding agent space and aims to compete with existing tools like GitHub Copilot. By integrating AI directly into the command line interface, Grok Build offers suggestions and automates repetitive tasks, potentially saving developers time and effort. The move is significant as it brings advanced AI capabilities to a traditionally manual process, enhancing efficiency for software development. While specific details on its performance and integration with other platforms are limited, Grok Build represents x.AI's strategic push into practical AI applications. Developers can expect more tools from x.AI that focus on streamlining coding workflows in the future.
AI Breakthrough Makes LLMs Faster Without Losing Accuracy
AI researchers have discovered a new way to make large language models (LLMs) run much faster without losing their accuracy. This advancement, unveiled in a recent study, shows that by adjusting the model's internal architecture-specifically the balance between attention layers and MLP layers-they can boost processing speed by up to 47% while keeping performance intact. The key insight is identifying an optimal ratio of MLP-to-attention parameters around 1.0 for LLaMA-style models. This is a significant improvement over existing open-source versions, which often have much higher ratios like 4.8. The researchers tested this approach across different GPU architectures and found consistent gains in efficiency, making it easier to deploy high-performing AI systems in real-time applications. This development could lower the cost of running LLMs while maintaining their accuracy, opening up new possibilities for businesses and developers. Look out for further studies on how these scaling laws can be applied to other types of AI models in the coming months.
Unlocking Private Data for AI Without Sharing
AI researchers have found a way to train large language models using private data without sharing it. This breakthrough is particularly useful in industries like healthcare and finance, where data privacy rules are strict. Instead of moving sensitive information between institutions, the new method lets AI systems learn from distributed datasets while keeping the data secure. The approach uses something called federated learning, which allows multiple institutions to collaborate on improving a shared model without exchanging private information. The study tested this method across healthcare and finance sectors using specific datasets, comparing different fine-tuning techniques. Results showed that the federated approach works almost as well as centralized training but avoids data breaches. This development could make AI systems more effective in real-world applications like medical diagnosis or financial analysis. Future work will focus on scaling up the technique and ensuring it remains efficient enough for widespread use.
AI Helps Recover $400k in Bitcoin After 11 Years
A cryptocurrency holder who lost access to their wallet due to a forgotten password was able to recover 5 Bitcoin, worth nearly $400,000. The user had been trying for over a decade after changing the password while high and forgetting it. Using Claude, an AI, they dumped old computer files, which led to discovering a backup wallet file from 2019 and a bug in the password setup. Claude successfully decrypted the wallet, allowing the Bitcoin to be transferred. This breakthrough highlights how AI can assist in complex tech challenges, offering new hope for data recovery efforts.