NVIDIA

MARCH 1, 2024

Developers of trustworthy AI understand that no model is perfect, and take steps to help customers and the general public understand how the technology was built, its intended use cases and its limitations.

AI 133

AI AI Algorithm Artificial Intelligence 133

Marktechpost

MAY 8, 2024

Among the main advancements in AI, seven areas stand out for their potential to revolutionize different sectors: neuromorphic computing, quantum computing for AI, Explainable AI (XAI), AI-augmented design and Creativity, Autonomous Vehicles and Robotics, AI in Cybersecurity and AI for Environmental Sustainability.

Artificial Intelligence 130

Artificial Intelligence Artificial Intelligence Robotics Machine Learning 130

IBM Journey to AI blog

JULY 6, 2023

Machine learning engineers can specialize in natural language processing and computer vision, become software engineers focused on machine learning and more. to learn more) In other words, you get the ability to operationalize data science models on any cloud while instilling trust in AI outcomes.

Data Science 175

Data Science Machine Learning Big Data Data Mining 175

NVIDIA

DECEMBER 13, 2023

AI-driven applications using deep learning with graph neural networks (GNNs), natural language processing (NLP) and computer vision can improve identity verification for know-your customer (KYC) and anti-money laundering (AML) requirements, leading to improved regulatory compliance and reduced costs.

Explainability 112

Explainability Neural Network Computer Vision Generative AI 112

Heartbeat

FEBRUARY 2, 2024

Visual Question Answering (VQA) stands at the intersection of computer vision and natural language processing, posing a unique and complex challenge for artificial intelligence. is a significant benchmark dataset in computer vision and natural language processing. or Visual Question Answering version 2.0,

Computer Vision 52

Computer Vision Natural Language Processing Artificial Intelligence Artificial Intelligence 52

Viso.ai

MAY 10, 2024

The example image below is from a model that was built to identify and segment people within images. Person detection with a computer vision model Step 2: Create a Dataset for Model Training & Testing Before we can train a machine learning model, we need to have data on which to train.

Machine Learning 52

Machine Learning Computer Vision Neural Network Convolutional Neural Networks 52

Viso.ai

JULY 9, 2024

provides the leading end-to-end Computer Vision Platform Viso Suite. Global organizations like IKEA and DHL use it to build, deploy, and scale all computer vision applications in one place, with automated infrastructure. When the model learns those patterns and their distribution, it allows to generate new data.

Generative AI 52

Generative AI Neural Network Convolutional Neural Networks AI 52

How to Learn Machine Learning

JANUARY 21, 2023

This market growth can be attributed to factors such as increasing demand for AI-based solutions in healthcare, retail, and automotive industries, as well as rising investments from tech giants such as Google , Microsoft , and IBM. This has helped to drive innovation in the industry.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Robotics Natural Language Processing 52

Snorkel AI

MARCH 19, 2024

In an ideal world, every company could easily and securely leverage its own proprietary data sets and assets in the cloud to train its own industry/sector/category-specific AI models. There are multiple approaches to responsibly provide a model with access to proprietary data, but pointing a model at raw data isn’t enough.

Data Scientist 52

Data Scientist LLM Chatbots AI 52

Snorkel AI

MARCH 19, 2024

In an ideal world, every company could easily and securely leverage its own proprietary data sets and assets in the cloud to train its own industry/sector/category-specific AI models. There are multiple approaches to responsibly provide a model with access to proprietary data, but pointing a model at raw data isn’t enough.

Data Scientist 52

Data Scientist Chatbots AI AI 52

DataRobot Blog

DECEMBER 20, 2022

Datarobot enables users to easily combine multiple datasets into a single training dataset for AI modeling. The great thing about DataRobot Explainable AI is that it spans the entire platform. You can understand the data and model’s behavior at any time. Predicting the Real Estate Asset’s Price Using DataRobot.

Explainability 59

Explainability Automation Machine Learning Data Scientist 59

The MLOps Blog

JUNE 27, 2023

Auto-annotation tools such as Meta’s Segment Anything Model and other AI-assisted labeling techniques. MLOps workflows for computer vision and ML teams Use-case-centric annotations. It provides various tools for monitoring model performance, detecting drift, and identifying issues with data quality.

Machine Learning 134

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The MLOps Blog

AUGUST 11, 2023

OpenAI, on the other hand, has been at the forefront of advancements in generative AI models, such as GPT-3, which heavily rely on embeddings. Embeddings are utilized in computer vision tasks, NLP tasks, and statistics. This innovative creation has the sole purpose of enhancing the training process of massive AI models.

ML 52

ML Machine Learning Data Ingestion Deep Learning 52

Pickl AI

APRIL 2, 2024

Use it for sentiment analysis, topic modeling, and building chatbots. Computer Vision: Analyze visual data like images and videos to automate tasks, identify objects and patterns, and improve product development. Explainable AI (XAI): As AI models become more complex, there’s a growing need for interpretability.

Data Science 52

Data Science Data Scientist Machine Learning Big Data 52

IBM Journey to AI blog

FEBRUARY 9, 2024

The incoming generation of interdisciplinary models, comprising proprietary models like OpenAI’s GPT-4V or Google’s Gemini, as well as open source models like LLaVa, Adept or Qwen-VL, can move freely between natural language processing (NLP) and computer vision tasks.

AI 298

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