Believe it or not, the Raspberry Pi came out 11 years ago. In that time, single board computers (SBCs) have gotten unbelievably powerful. During this same decade every major telecom provider started rolling out 5G services. Oh, and by the way, AlexNet, the neural network that completely changed they way we process imagery, landed on the computer vision scene in 2012.

This convolution (ha) of small, powerful computers, fast network access, and practical neural networks created the perfect conditions for edge computing to blossom. We live in the golden age of small, cheap computers capable of running software that didn’t and couldn’t have existed 10 years ago. It’s a great time to be alive! Read More

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