NEWS IN BRIEF: AI/ML FRESH UPDATES

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The Atomic Human: A Terminator Returns

AI expert Neil Lawrence's new book, The Atomic Human, delves into AI myths, including Terminator references. The study challenges techbro arrogance, contrasting biblical creation with AI consciousness.

Eric Evans Honored with DOD Medal

Eric Evans receives DoD Medal for Distinguished Public Service for his leadership at MIT Lincoln Laboratory and Defense Science Board. Evans' impact on national security and defense innovation recognized by U.S. Department of Defense.

Unleashing the Power of NVIDIA AI Workbench

NVIDIA AI Workbench simplifies generative AI development with RAG applications, enabling customized models and seamless collaboration. The free tool streamlines setup and offers ease of collaboration across platforms for data scientists and developers.

Revolutionizing Drug Discovery

AI is transforming drug discovery by helping scientists find cost-efficient molecules with desired properties. MIT's SPARROW algorithm streamlines synthesis planning, optimizing costs and experimental steps for new medicines, agrichemicals, and specialized materials.

Unleashing AI Agent Power

AI Agent Capabilities Engineering Framework introduces a mental model for designing AI agents based on cognitive and behavioral sciences. The framework categorizes capabilities into Perceiving, Thinking, Doing, and Adapting, aiming to equip AI agents for complex tasks with human-like proficiency.

AI silencing angry customers at Softbank

SoftBank is developing AI-powered "emotion-canceling" tech to alter angry customer voices for calmer calls with customer service. The project aims to reduce operator stress, with plans for launch by March 2026, sparking mixed reactions online.

Shadow Modeling Unveils Hidden Objects in 3D Scenes

MIT and Meta researchers develop PlatoNeRF, a computer vision technique using shadows and machine learning to create accurate 3D models of scenes, improving autonomous vehicles and AR/VR efficiency. Combining lidar and AI, PlatoNeRF offers new opportunities for reconstructions and will be presented at the Conference on Computer Vision and Pattern Recognition.

Building k-Means Clustering in JavaScript

Implementing k-means data clustering from scratch using JavaScript led to a simpler, more understandable version. The demo showcases encoding and normalizing data for the k-means algorithm in an engaging way.