Computer vision

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A better method for planning complex visual tasks

Aeronautical and astronautical engineering, ai, AI (Artificial Intelligence), Algorithms, Artificial Intelligence, Computer science and technology, Computer vision, Laboratory for Information and Decision Systems (LIDS), Machine Learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Research, Robotics, School of Engineering

MIT researchers have developed a generative artificial intelligence-driven approach for planning long-term visual tasks, like robot navigation, that is about twice as effective as some existing techniques.Their method uses a specialized vision-language model to perceive the scenario in an image and simulate actions needed to reach a goal. Then a second model translates those simulations […]

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Improving AI models’ ability to explain their predictions

ai, AI (Artificial Intelligence), Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, data, Electrical engineering and computer science (EECS), Human-computer interaction, Machine Learning, MIT Schwarzman College of Computing, Research, School of Engineering

In high-stakes settings like medical diagnostics, users often want to know what led a computer vision model to make a certain prediction, so they can determine whether to trust its output.Concept bottleneck modeling is one method that enables artificial intelligence systems to explain their decision-making process. These methods force a deep-learning model to use a

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A Coding Guide to Build a Scalable End-to-End Machine Learning Data Pipeline Using Daft for High-Performance Structured and Image Data Processing

ai, AI (Artificial Intelligence), Artificial Intelligence, Computer vision, Editors Pick, Machine Learning, Staff, Technology, Tutorials

In this tutorial, we explore how we use Daft as a high-performance, Python-native data engine to build an end-to-end analytical pipeline. We start by loading a real-world MNIST dataset, then progressively transform it using UDFs, feature engineering, aggregations, joins, and lazy execution. Also, we demonstrate how to seamlessly combine structured data processing, numerical computation, and

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Physical Intelligence Team Unveils MEM for Robots: A Multi-Scale Memory System Giving Gemma 3-4B VLAs 15-Minute Context for Complex Tasks

agentic ai, ai, AI (Artificial Intelligence), Artificial Intelligence, Computer vision, Editors Pick, Language Model, New Releases, Robotics, Technology, Vision Language Model

Current end-to-end robotic policies, specifically Vision-Language-Action (VLA) models, typically operate on a single observation or a very short history. This ‘lack of memory’ makes long-horizon tasks, such as cleaning a kitchen or following a complex recipe, computationally intractable or prone to failure. To address this, researchers from Physical Intelligence, Stanford, UC Berkeley, and MIT have

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[Tutorial] Building a Visual Document Retrieval Pipeline with ColPali and Late Interaction Scoring

ai, AI (Artificial Intelligence), Artificial Intelligence, Computer vision, Editors Pick, Staff, Technology

In this tutorial, we build an end-to-end visual document retrieval pipeline using ColPali. We focus on making the setup robust by resolving common dependency conflicts and ensuring the environment stays stable. We render PDF pages as images, embed them using ColPali’s multi-vector representations, and rely on late-interaction scoring to retrieve the most relevant pages for

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Meta Plans to Add Facial Recognition Technology to Its Smart Glasses

ai, AI (Artificial Intelligence), Artificial Intelligence, Be My Eyes (Accessibly Inc), Computer vision, Computers and the Internet, EssilorLuxottica SA, Face, Facebook Inc, Facial Recognition Software, Federal Trade Commission, Instagram Inc, Meta Platforms Inc, Privacy, Social media, Surveillance of Citizens by Government, Wearable Computing, Zuckerberg, Mark E

In an internal memo last year, Meta said the political tumult in the United States would distract critics from the feature’s release.

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