Google’s conversation AI tool Bard can now help software developers with programming, including generating code, debugging and code explanation — a new set of skills that were added in response to user demand.

Coding has been one of the top requests Google has received from users, according to a Friday blog post by Google Research product lead Paige Bailey.

Google said Friday it is launching these software development capabilities in more than 20 programming languages including C++, Go, Java, JavaScript, Python and TypeScript. Users can export Python code to Google Colab. Bard can also help with writing functions for Google Sheets. Read More

Today, Amazon CodeWhisperer, a real-time AI coding companion, is generally available and also includes a CodeWhisperer Individual tier that’s free to use for all developers. Originally launched in preview last year, CodeWhisperer keeps developers in the zone and productive, helping them write code quickly and securely and without needing to break their flow by leaving their IDE to research something. Faced with creating code for complex and ever-changing environments, developers can improve their productivity and simplify their work by making use of CodeWhisperer inside their favorite IDEs, including Visual Studio Code, IntelliJ IDEA, and others. CodeWhisperer helps with creating code for routine or time-consuming, undifferentiated tasks, working with unfamiliar APIs or SDKs, making correct and effective use of AWS APIs, and other common coding scenarios such as reading and writing files, image processing, writing unit tests, and lots more.

Using just an email account, you can sign up and, in just a few minutes, become more productive writing code—and you don’t even need to be an AWS customer.  Read More

ChatGDB is a tool designed to superpower your debugging experience with GDB or LLDB, debuggers for compiled languages. Use it to accelerate your debugging workflow by leveraging the power of ChatGPT to assist you while using GDB/LLDB! GitHub Link

#devops

To get both alpaca and llama working on your computer, just run this:

$ npx dalai llama install 7B
$ npx dalai serve

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My GPT-4 coding assistant can now build & deploy brand new web apps!

It initializes my project, builds my app, creates a GitHub repo, and deploys it to Vercel.

All from simply using my voice.

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LangChain is a framework for developing applications powered by language models. We believe that the most powerful and differentiated applications will not only call out to a language model via an api, but will also:

1. Be data-aware: connect a language model to other sources of data
2. Be agentic: Allow a language model to interact with its environment

Twitter has released the code that chooses which tweets show up on your timeline to GitHub and has put out a blog post explaining the decision. It breaks down what the algorithm looks at when determining which tweets to feature in the For You timeline and how it ranks and filters them.

According to Twitter’s blog post, “the recommendation pipeline is made up of three main stages.” First, it gathers “the best Tweets from different recommendation sources,” then it ranks those tweets with “a machine learning model.” Lastly, it filters out tweets from people you’ve blocked, tweets you’ve already seen, or tweets that are not safe for work, before putting them on your timeline. Read More

GitHub Link

Explore how microservices fueled the journey from APIs to containers and paved the way for enhanced API development and software integration.

In recent years, the rise of microservices has drastically changed the way we build and deploy software. The most important aspect of this shift has been the move from traditional API architectures driven by monolithic applications to containerized microservices. This shift not only improved the scalability and flexibility of our systems, but it has also given rise to new ways of software development and deployment approaches. 

In this article, we will explore the path from APIs to containers and examine how microservices have paved the way for enhanced API development and software integration. Read More

GitHub Copilot is evolving to bring chat and voice interfaces, support pull requests, answer questions on docs, and adopt OpenAI’s GPT-4 for a more personalized developer experience

At GitHub, our mission has always been to innovate ahead of the curve and give developers everything they need to be happier and more productive in a world powered by software. When we began experimenting with large language models several years ago, it quickly became clear that generative AI represents the future of software development. We partnered with OpenAI to create GitHub Copilot, the world’s first at-scale generative AI development tool made with OpenAI’s Codex model, a descendent of GPT-3.

GitHub Copilot started a new age of software development as an AI pair programmer that keeps developers in the flow by auto-completing comments and code. And less than two years since its launch, GitHub Copilot is already writing 46% of code and helps developers code up to 55% faster. Read More