IBM Journey to AI blog

AUGUST 11, 2023

Today, 35% of companies report using AI in their business, which includes ML, and an additional 42% reported they are exploring AI, according to the IBM Global AI Adoption Index 2022. Generative AI is a type of deep-learning model that takes raw data, processes it and “learns” to generate probable outputs.

Data Science 188

Data Science DevOps Machine Learning Data Scientist 188

Heartbeat

SEPTEMBER 13, 2023

Source: ResearchGate Explainability refers to the ability to understand and evaluate the decisions and reasoning underlying the predictions from AI models (Castillo, 2021). For instance, human experts bring domain knowledge and expertise that can complement AI systems. Explaining Explanations in AI || SSRN Onose, E.

Explainability 52

Explainability Machine Learning Deep Learning Explainable AI 52

DataRobot Blog

JUNE 23, 2022

Replacing these with a more accurate (and rational) AI/ML model in an existing system or process is generally straightforward, because there is a context and environment in which the new model can succeed. DATAROBOT AI CLOUD. Too often the new model fails the “so what” test. using an AI model.

AI 59

AI AI Data Science AI Modeling 59

NVIDIA

DECEMBER 13, 2023

Financial institutions, including banks, were fined nearly $5 billion for AML, breaching sanctions as well as failures in KYC systems in 2022, according to the Financial Times. The output of this can be used for models like XGBoost, GNNs or techniques for clustering, offering better results when deployed for inference.

Explainability 95

Explainability Neural Network Computer Vision Generative AI 95

DataRobot Blog

MARCH 15, 2022

In addition, as more decisions are guided by machine learning, there’s the prerequisite to monitor, assess, and explain AI model performance against the constant of changing data (volumes fluctuate, casemix varies, clinical system configuration changes, and so on). Build a modern workforce equipped to deliver change.

Explainability 52

Explainability AI AI Explainable AI 52

Heartbeat

FEBRUARY 2, 2024

Despite its significance, a thorough analysis uncovers inherent biases within COCO-VQA that have the potential to influence the learning trajectory of AI models. Researchers and developers leverage the VizWiz dataset to advance the development of AI models that enhance the accessibility of visual information. Salewski, L.,

Computer Vision 52

Computer Vision Natural Language Processing Artificial Intelligence Artificial Intelligence 52

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. The concept of Explainable AI revolves around developing models that offer inference results and a form of explanation detailing the process behind the prediction.

ML 52

ML Machine Learning Data Ingestion Deep Learning 52

AI Impacts

DECEMBER 22, 2022

Quick clarifications First, to fend off misunderstanding— I take ‘slowing down dangerous AI’ to include any of: reducing the speed at which AI progress is made in general, e.g. as would occur if general funding for AI declined.

AI 130

AI AI AI Research AI Researcher 130

Pickl AI

MARCH 31, 2024

Generative AI Process: From Data to Creation Generative AI isn’t magic, but it can feel like it when a machine starts churning out realistic images or composing coherent text. The process behind this impressive feat involves several key steps: Data Acquisition The foundation of any generative AI model is a massive amount of data.

Generative AI 52

Generative AI Deep Learning AI AI 52

IBM Journey to AI blog

FEBRUARY 9, 2024

2022 was the year that generative artificial intelligence (AI) exploded into the public consciousness, and 2023 was the year it began to take root in the business world. iii] “AI models haven’t had that kind of data before. Those models will just have a better understanding of everything.”

AI 316

AI AI Artificial Intelligence Artificial Intelligence 316