🤩💥 'What's New in AI' Recap

Recap collections help you navigate specific topics and fill the gaps if you missed something

What’s New in AI – our deep dives into the latest updates in AI research and technology. Here we discuss in-depth the recent research papers or technology frameworks that are worth your attention. Our goal is to keep you up to date with new developments in AI in a way that complements the concepts we are debating in other editions of our newsletter.

💥  What’s New in AI: Uber Ludwig 0.3

Functionally, Ludwig is a framework for simplifying the processes of selecting, training and evaluating machine learning models for a given scenario. Think about configuring rather than coding machine learning models. Ludwig provides a set of model architectures that can be combined together to create an end-to-end model optimized for a specific set of requirements. Conceptually, Ludwig was designed based on a series of principles: No coding required. Generality. Flexibility. Extensibility. Understandability.

One of the greatest things about Ludwig 0.3 is that it incorporates contributors outside Uber. Notably, Stanford University has been very active in modernizing the Ludwig stack. The new version of Ludwig incorporates new features, widely used in machine learning applications, via a consistent no-code interface: Hyperparameter Optimization, Integration with Weights and Biases, Code-Free Transformers, TensorFlow 2 Backend, New Data Source Integration, and Other Capabilities

💥  What’s New in AI: On the Measure of Intelligence is One of the Most Groundbreaking Papers in the Recent Years of Deep Learning

Every once in a while, you encounter a research paper that is so simple yet so profound and brilliant that you wish you would have written it yourself. That’s how I felt when I read François Chollet’s On the Measure of Intelligence. The paper resonated with me not only because it confronts some of the key philosophical and technical challenges about artificial intelligence (AI) systems that I have spent time thinking about, but also because it does so in such an elegant way that it is hard to argue with. Mr. Chollet’s thesis is remarkably simple: for AI systems to reach their potential, we need quantitative and actionable methods that measure intelligence in a way that shows similarities with human cognition ->read the full article about this fascinating paper

💥 What’s New in AI: Dagli is a New, Open Source, Java-Based Framework that Powers ML at LinkedIn

Java is one of the most popular programming languages in the world with millions of developers and a rich community. However, the support for machine learning stacks for Java Virtual Machine (JVM) languages has paled in comparison to that of Python’s. LinkedIn recently open-sourced Dagli, a new framework for simplifying the implementation of machine learning models in JVM-based languages

💥 What’s New in AI: The AI Behind DeepMind’s Agent57 Which Outperformed Humans in 57 Atari Games 

DeepMind truly believes that Reinforcement learning holds the key to the most advanced forms of artificial intelligence (AI) so it is not a surprise that they focused on those methods when they tried to solve the Atari57 challenge. The first attempt to tackle Atari57 was the Deep Q-network agent (DQN) and subsequently variations of it. Despite the notable advancements, most DRL agents failed to generalize knowledge of diverse tasks.

💥 What’s New in AI:  Pro-ML is the Architecture Powering Machine Learning at LinkedIn 

The core of LinkedIn’s machine learning infrastructure is a proprietary system called Pro-ML. Conceptually, Pro-ML controls the entire lifecycle of machine learning models, from training to monitoring. The original goal of the Pro-ML initiative at LinkedIn was to double the effectiveness of machine learning engineers while providing an open infrastructure to foment the adoption of machine learning technologies within the company. To achieve that, Pro-ML focused on providing a robust infrastructure that will enable a key set of stages in the lifecycle of machine learning solutions ->become Premium to read this Edge and stay up-to-date with the most relevant developments in the ML world

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