Dataconomy

MARCH 13, 2023

With advances in machine learning, deep learning, and natural language processing, the possibilities of what we can create with AI are limitless. However, the process of creating AI can seem daunting to those who are unfamiliar with the technicalities involved. What is required to build an AI system?

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IBM Journey to AI blog

JULY 6, 2023

These computer science terms are often used interchangeably, but what differences make each a unique technology? To keep up with the pace of consumer expectations, companies are relying more heavily on machine learning algorithms to make things easier. Computer vision is a factor in the development of self-driving cars.

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ODSC - Open Data Science

SEPTEMBER 19, 2023

Then identifying issues that allow fine-tuning of code, optimizing algorithms, and making strategic use of parallel processing. Depending on the position, and company, it can require a strong understanding of natural language processing, computer science, linguistics, and software engineering.

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Snorkel AI

MARCH 1, 2023

Foundation models are large AI models trained on enormous quantities of unlabeled data—usually through self-supervised learning. This process results in generalized models capable of a wide variety of tasks, such as image classification, natural language processing, and question-answering, with remarkable accuracy.

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IBM Journey to AI blog

JULY 6, 2023

Just as humans can learn through experience rather than merely following instructions, machines can learn by applying tools to data analysis. Machine learning works on a known problem with tools and techniques, creating algorithms that let a machine learn from data through experience and with minimal human intervention.

Machine Learning 56

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Becoming Human

MARCH 16, 2023

AI began back in the 1950s as a simple series of “if, then rules” and made its way into healthcare two decades later after more complex algorithms were developed. Since the advent of deep learning in the 2000s, AI applications in healthcare have expanded. A few AI technologies are empowering drug design.

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Pickl AI

APRIL 2, 2024

Data science is the process of extracting the valuable minerals – the insights – that can transform your business. It’s a blend of statistics, computer science, and domain knowledge used to extract knowledge and create solutions from data. Data science for business leaders isn’t about becoming a coding pro.

Data Science 52

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Applied Data Science

MARCH 11, 2022

Then, we will look at three recent research projects that gamified existing algorithms by converting them from single-agent to multi-agent: ?️‍♀️ Our internal agents are playing games until they learn how to cooperate and trick us into believing we are an individual. All the rage was about algorithms for classification.

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Hacker News

MARCH 25, 2022

Transformers made self-supervised learning possible, and AI jumped to warp speed,” said NVIDIA founder and CEO Jensen Huang in his keynote address this week at GTC. Transformers are in many cases replacing convolutional and recurrent neural networks (CNNs and RNNs), the most popular types of deep learning models just five years ago.

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ODSC - Open Data Science

FEBRUARY 14, 2023

The model was fine-tuned to reduce false, harmful, or biased output using a combination of supervised learning in conjunction to what OpenAI calls Reinforcement Learning with Human Feedback (RLHF), where humans rank potential outputs and a reinforcement learning algorithm rewards the model for generating outputs like those that rank highly.

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