GPT Engineer: One Prompt to Entire Codebase
Plus: Fine-tune LLMs with limited resources. Combine OpenAI models with your data.
Hello Engineering Leaders and AI Enthusiasts!
Welcome to the 45th edition of The AI Edge newsletter. This edition brings you GPT Engineer and how it’ll take only one prompt to generate the entire codebase.
And a big thanks to all our incredible readers! 😊
In today’s edition:
👩💻 GPT Engineer: One prompt generates the entire codebase
🛠️ Fine-tune full parameters of LLMs with limited resources
📊 Leverage OpenAI models for your data with Microsoft's new feature
🧩 92% of US developers use AI tools at work: GitHub report
Let’s go!
GPT Engineer: One prompt to generate the entire codebase
GPT Engineer can generate an entire codebase based on a text prompt. You specify what you want it to build, it asks for clarification, and then builds it. It:
Generates technical spec
Writes all necessary code
Makes it easy to add your own reasoning steps, modify, and experiment
Is open source (GitHub and Demo)
Lets you finish a coding project in minutes
Why does this matter?
Perhaps this tool is the future of code generation. It could significantly expedite the initial stages of software development, automating the process of generating code structures, modules, and frameworks. It can empower developers to focus on higher-level tasks and potentially foster innovation. Moreover, it can enable businesses to prototype and explore ideas quickly.
Fine-tune full parameters of LLMs with limited resources
Many existing approaches have focused on parameter-efficient fine-tuning, which tunes or adds a small number of parameters. But few have addressed the challenge of tuning the full parameters of LLMs with limited resources.
This research proposes a new optimizer, LOw-Memory Optimization (LOMO), which fuses the gradient computation and the parameter update in one step to reduce memory usage. Integrating LOMO with existing memory-saving techniques can reduce memory usage to 10.8% compared to the standard approach (DeepSpeed solution). Consequently, the approach enables the full parameter fine-tuning of a 65B model on a single machine with 8 RTX 3090, each with 24GB memory.
Why does this matter?
LLMs have revolutionized NLP but demand massive GPU resources for training. LOMO significantly saves GPU memory usage without harming the fine-tuning process. Thus, lowering the threshold for LLMs training can encourage greater participation from researchers and developers, benefiting both academia and businesses.
Leverage OpenAI models for your data with Microsoft's new feature
Microsoft announced Azure OpenAI Service on your data in a public preview. This feature lets you unlock the power of OpenAI models, including ChatGPT and GPT-4, with your own data. It includes data interaction and analysis, offering enhanced accuracy, speed, and insights.
The key use cases include:
1. Simplify document intake, and gain quick access to legal and financial data for better decision-making.
2. Harvest valuable customer insights, monetize data access, and gain deep industry and competitor insights.
3. Transform operations, improve customer experiences, and gain a competitive edge.
Why does this matter?
By leveraging this service, organizations can tap into the power of their data, gaining valuable insights and enhancing strategic choices. This innovative solution is poised to reshape how businesses operate and thrive in the ever-evolving realm of data-driven decision-making.
92% of US developers use AI coding tools at work: GitHub report
Github surveyed 500 developers working at companies with over 1,000 employees in the US. The survey focused on how managers should approach developer productivity, collaboration, and AI coding tools.
The key findings are:
92% of U.S.-based developers already use AI coding tools in and outside work.
Despite industry investments in DevOps, developers still spend much time waiting on builds and tests.
Developers want more collaboration; more than 4/5 of developers expect AI coding tools to make their team more collaborative.
Why does this matter?
It was found that Developers are thrilled by the tremendous benefits that AI brings to the table. 70% say AI coding tools will offer them an advantage at work and cite better code quality, completion time, and resolving incidents as some of the top anticipated benefits.
What Else Is Happening ❗
🤖What if humanity is reborn as a machine? Here’s a manifestation by AI (Link)
💰Voice-generating platform ElevenLabs raises $19M, launches detection tool (Link)
🤝IBM Expands Partnership with Adobe for Generative AI in Supply Chain (Link)
🔍Google's AI can predict cardiovascular events through an eye scan (Link)
🚀Vimeo has announced a trio of AI-powered editing features (Link)
⚙️Researchers have successfully designed a semiconductor chip aided by ChatGPT (Link)
🛠️ Trending Tools
Wise Talk: Voice-activated AI sidekick. Real-time translation for easy global communication.
Mon AI: Track expenses effortlessly with a fun voice interface. Securely saved in iCloud.
Horizon UI: Build AI SaaS Apps & Prompts 10X faster. 100+ components included.
Illusion: No-code generative AI builder. Create unique templates for various needs.
Textcortex AI: Your personal info hub. Retrieve data, improve productivity, and chat seamlessly.
Factiverse: Verify AI-generated text for factual accuracy. Instant credible sources.
Current: Increase team visibility. Share work from various tools. AI-powered summaries.
Typefully: Enhance content with AI, cross-post to LinkedIn, boost productivity.
That's all for now!
Discover new opportunities and insights! By subscribing to The AI Edge, you become part of a select group of readers from Moody’s, Vonage, Voya, WEHI, Cox, INSEAD, and other reputable organizations.
Thanks for reading, and see you tomorrow. 😉