IBM Journey to AI blog

JULY 6, 2023

Python is the most common programming language used in machine learning. Machine learning and deep learning are both subsets of AI. Deep learning teaches computers to process data the way the human brain does. Deep learning algorithms are neural networks modeled after the human brain.

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IBM Journey to AI blog

AUGUST 11, 2023

MLOps is the next evolution of data analysis and deep learning. Simply put, MLOps uses machine learning to make machine learning more efficient. Generative AI is a type of deep-learning model that takes raw data, processes it and “learns” to generate probable outputs.

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Ofemwire

MARCH 1, 2024

At its core, AI is designed to replicate or even surpass human cognitive functions, employing algorithms and machine learning to interpret complex data, make decisions, and execute tasks with unprecedented speed and accuracy. If you dont get that, let me explain what AI is, like I would do to a fifth grader.

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Pickl AI

APRIL 2, 2024

It explains key concepts, explores applications for business growth, and outlines steps to prepare your organization for data-driven success. Machine Learning: Subset of AI that enables systems to learn from data without being explicitly programmed. Unsupervised Learning: Finding patterns or insights from unlabeled data.

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Pickl AI

JULY 14, 2023

Big Data and Deep Learning (2010s-2020s): The availability of massive amounts of data and increased computational power led to the rise of Big Data analytics. Deep Learning, a subfield of ML, gained attention with the development of deep neural networks.

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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. In xxAI — Beyond Explainable AI Chapter.

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Viso.ai

MARCH 26, 2024

The integration of Artificial Intelligence (AI) technologies within the finance industry has fully transitioned from experimental to indispensable. Initially, AI’s role in finance was limited to basic computational tasks. Real-world applications range from automating loan approvals to processing insurance claims.

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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. In the years to come, AI is expected to become even more powerful.

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The MLOps Blog

JUNE 27, 2023

Learn more The Best Tools, Libraries, Frameworks and Methodologies that ML Teams Actually Use – Things We Learned from 41 ML Startups [ROUNDUP] Key use cases and/or user journeys Identify the main business problems and the data scientist’s needs that you want to solve with ML, and choose a tool that can handle them effectively.

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The MLOps Blog

AUGUST 11, 2023

Many questions regarding building machine learning pipelines and systems have already been answered and come from industry best practices and patterns. But some of these queries are still recurrent and haven’t been explained well. How should the machine learning pipeline operate? Model parallelism What is model parallelism?

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Snorkel AI

MARCH 19, 2024

Google has established itself as a dominant force in the realm of AI, consistently pushing the boundaries of AI research and innovation. These breakthroughs have paved the way for transformative AI applications across various industries, empowering organizations to leverage AI’s potential while navigating ethical considerations.

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Snorkel AI

MARCH 19, 2024

Google has established itself as a dominant force in the realm of AI, consistently pushing the boundaries of AI research and innovation. These breakthroughs have paved the way for transformative AI applications across various industries, empowering organizations to leverage AI’s potential while navigating ethical considerations.

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Marktechpost

JULY 11, 2023

Called AutoGPT, this tool performs human-level tasks and uses the capabilities of GPT-4 to develop an AI agent that can function independently without user interference. GPT 4, which is the latest add-on to OpenAI’s deep learning models, is multimodal in nature. Unlike the previous version, GPT 3.5,

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