Machine Learning

Welcome to the Machine Learning Hub, your one-stop destination for all things related to machine learning!

Get ready to embark on an exciting journey into the realm of AI and discover how machines can learn and make intelligent decisions. Our blog articles are crafted with simplicity and clarity in mind, making complex machine learning concepts easy to understand for everyone. Whether you’re a beginner or an experienced practitioner, we’ve got you covered with informative and insightful content. Explore the fascinating world of algorithms, models, and data as we delve into supervised and unsupervised learning, reinforcement learning, and more. Discover practical applications in various domains like healthcare, finance, and autonomous vehicles.  From introductory guides to advanced techniques, we’re here to help you demystify machine learning and unlock its potential. Join us on this journey as we unravel the secrets of machine learning and empower you to build intelligent systems that can analyze data, make predictions, and drive innovation.

Let’s shape the future together with the power of machine learning!

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The ethics of advanced AI assistants

Responsibility & Safety Published 19 April 2024 Authors Iason Gabriel and Arianna Manzini Exploring the promise and risks of a future with more capable AI Imagine a future where we interact regularly with a range of advanced artificial intelligence (AI) assistants — and where millions of assistants interact with each other on our behalf. These …

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A New Approach to AI Safety: Layer Enhanced Classification (LEC) | by Sandi Besen | Dec, 2024

LEC surpasses best in class models, like GPT-4o, by combining the efficiency of a ML classifier with the language understanding of an LLM Imagine sitting in a boardroom, discussing the most transformative technology of our time — artificial intelligence — and realizing we’re riding a rocket with no reliable safety belt. The Bletchley Declaration, unveiled …

A New Approach to AI Safety: Layer Enhanced Classification (LEC) | by Sandi Besen | Dec, 2024 Read More »

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Updates to Veo, Imagen and VideoFX, plus introducing Whisk in Google Labs

While video models often “hallucinate” unwanted details — extra fingers or unexpected objects, for example — Veo 2 produces these less frequently, making outputs more realistic. Our commitment to safety and responsible development has guided Veo 2. We have been intentionally measured in growing Veo’s availability, so we can help identify, understand and improve the …

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Introduction to TensorFlow’s Functional API | by Javier Martínez Ojeda | Dec, 2024

Learn what the Functional API is, and how to build complex keras models using it Photo by Hunter Harritt on Unsplash TensorFlow’s Sequential API helps the user to stack layers one on top of another, easily creating linear models, where the input of each layer is always the output of the previous one. But what …

Introduction to TensorFlow’s Functional API | by Javier Martínez Ojeda | Dec, 2024 Read More »

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FACTS Grounding: A new benchmark for evaluating the factuality of large language models

Responsibility & Safety Published 17 December 2024 Authors FACTS team Our comprehensive benchmark and online leaderboard offer a much-needed measure of how accurately LLMs ground their responses in provided source material and avoid hallucinations Large language models (LLMs) are transforming how we access information, yet their grip on factual accuracy remains imperfect. They can “hallucinate” …

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The Essential Guide to R and Python Libraries for Data Visualization | by Sarah Lea | Dec, 2024

Let’s dive into the most important libraries in R and Python to visualise data and create different charts, and what the pros and cons are Being a pro in certain programming languages is the goal of every aspiring data professional. Reaching a certain level in one of the countless languages is a critical milestone for …

The Essential Guide to R and Python Libraries for Data Visualization | by Sarah Lea | Dec, 2024 Read More »

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Google DeepMind at ICLR 2024

Research Published 3 May 2024 Developing next-gen AI agents, exploring new modalities, and pioneering foundational learning Next week, AI researchers from around the globe will converge at the 12th International Conference on Learning Representations (ICLR), set to take place May 7-11 in Vienna, Austria. Raia Hadsell, Vice President of Research at Google DeepMind, will deliver …

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How Have Data Science Interviews Changed Over 4 Years? | by Matt Przybyla | Dec, 2024

An aggregated look on the differences between then & now: 2020 vs 2024 — some big frustrations and positive learnings. Yes this is actually a screenshot of my own LinkedIn [1]. Introduction Application Process Interview Process Summary References This article is intended for data scientists looking for a company change, people considering applying and interviewing …

How Have Data Science Interviews Changed Over 4 Years? | by Matt Przybyla | Dec, 2024 Read More »

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Google DeepMind and Isomorphic Labs introduce AlphaFold 3 AI model

Update November 11, 2024: As of November 2024, we have released AlphaFold 3 model code and weights for academic use to help advance research. Learn more about AlphaFold tools. Original post: Inside every plant, animal and human cell are billions of molecular machines. They’re made up of proteins, DNA and other molecules, but no single …

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Why Retrieval-Augmented Generation Is Still Relevant in the Era of Long-Context Language Models | by Jérôme DIAZ | Dec, 2024

In this article we will explore why 128K tokens (and more) models can’t fully replace using RAG. We’ll start with a brief reminder of the problems that can be solved with RAG, before looking at the improvements in LLMs and their impact on the need to use RAG. Illustration by the author. RAG isn’t really …

Why Retrieval-Augmented Generation Is Still Relevant in the Era of Long-Context Language Models | by Jérôme DIAZ | Dec, 2024 Read More »

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