💬 Chat with your code using RAG!

🦾Plus: 🤖26 AI Reports from Famous Brands

Hey folks! Let’s get into Big Data and AI craziness…

In today's edition:

  • 🔍Monitoring Your ML Models in Production

  • 📦Amazon S3 is files, but not a filesystem

  • 🐍How to Handle Imbalanced Data for ML in Python

    📊The Categorization of Clustering Algorithms in Machine Learning

  • 💻Databricks Asset bundles for Machine Learning

  • 🎉OpenAI announces new board members

  • 📚 Access Anthropic’s free prompt library

  • 🤖 6 AI Tools and Data Tools

  • 🖼️ A.I. Generated Image of the Day

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Machine learning model monitoring refers to tracking and understanding your production models’ performance from a science and operation point of view. In other words, it’s the tracking of a Machine learning model during production so that you can fix any potential issues that may negatively impact your business.

Transform your interaction with GitHub repositories through a natural language interface. In this studio we are building a "Chat with your code" RAG application that simplifies code queries, making coding more intuitive and productive.

The idea that Amazon S3 is really an 'Amazon Cloud Filesystem' is a bit of a fiction - it isn't a file system and it can't stand in for one. S3 implements a completely different arrangement and its primitives are only partly compatible with the Unix file API.

Imagine a scenario where we have a three-class problem. We make our initial analyses, calculate accuracy, and get 93%. Then, we go deeper and see that 80% of the data belongs to one class. Is that a good sign?

Clustering is one of the core branches of unsupervised learning in ML. The first (and sometimes the only) clustering algorithm folks learn is KMeans. Yet, it is important to note that KMeans is not a universal solution to all clustering problems.

In this guide, I will discuss Databricks Asset Bundles for Machine Learning and how they enable individuals to efficiently construct an end-to-end machine learning life cycle with continuous integration and continuous delivery (CI/CD) capabilities.

This dataset contains more than 650,000 English books (~ 61 billion words) presumed to be in the public domain in the US which were digitised by the Internet Archive and catalogued as part of the Open Library project. The dataset was compiled by Sebastian Majstorovic.

🤖 AI News:

ChatGPT's Consumption: ChatGPT consumes over half a million kWh of electricity each day, an amount staggering enough to service about 200 million requests. Comparative Consumption: ChatGPT's daily power usage is nearly equal to 180,000 U.S. households, each using about 29 kWh.

Water Consumption: A ChatGPT conversation uses about 50 cl of water.

OpenAI just announced the addition of several board members and the reinstatement of CEO Sam Altman to his board seat, with the company looking to move past the turmoil of its November crisis.

Last month, Washington and Chicago researchers developed ArtPrompt. It bypasses the safety measures of LLMs with ASCII art. It tricks AI models into advising on prohibited topics such as bomb-making and counterfeiting money by bypassing content restrictions.

ArtPrompt operates through word masking and cloaked prompt generation, where sensitive words are replaced with ASCII art to evade detection.

When it comes to hiring in AI, there are three main camps:

Employers (BULLISH)⅔ recruiters hope AI will make it faster / easier to source candidates.

Candidates (BEARISH)71% of Americans oppose AI making the final hiring calls, and only 28% favor AI screening applications at all.

Everyone else (CONCERNED)—The media always calls out AI for bias, and NYC recently passed a law demanding companies pass bias audits and disclose when they use AI in hiring processes.

A Bloomberg report had ChatGPT-3.5 pick “the most qualified candidate” for various roles in thousands of trials, and the results revealed consistent biases towards certain demographics.

Biased against black men in financial analyst roles. Biased against white men in HR roles. Biased against black women in software engineering roles.

Uncover the newest developments in AI for 2024. Delve into discussions on emerging AI trends and the societal implications of generative AI.

Here’s a list of suggested prompts for Claude across various topics.

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👨‍💻 Data Tools, Libraries 

Hatchet (GitHub Repo)

By replacing difficult-to-manage legacy queues and pub/subsystems, Hatchet allows developers to design durable workloads that recover from failure and solve for problems like concurrency, fairness, and rate limiting.

Rolldown (GitHub Repo)

Rolldown is a fast bundler for JavaScript with a Rollup-compatible API and plugin interface.

React Geiger (GitHub Repo)

React Geiger runs in the background and alerts developers to excessively slow React component rerenders.

A.I. Generated Image of the Day

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