ODSC - Open Data Science

MARCH 22, 2023

Be sure to check out his session, “ Improving ML Datasets with Cleanlab, a Standard Framework for Data-Centric AI ,” there! What exactly is data-centric AI? Data-centric AI instead asks how we can systematically engineer better data through algorithms/automation. A common gripe I hear is: “Garbage in, garbage out.

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AssemblyAI

AUGUST 22, 2023

In the interim, it was actually image models like DALL-E 2 and Stable Diffusion that instead took the limelight and gave the world a first look at the power of modern AI models. More recently, a new method called Reinforcement Learning from AI Feedback (RLAIF) sets a new precedent, both from performance and ethical perspectives.

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Towards AI

MAY 10, 2025

Last Updated on May 12, 2025 by Editorial Team Author(s): Luhui Hu Originally published on Towards AI. Image Credit: Meta AI More and more people ask me what world models are, including investors, AI enthusiasts, and AI scientists. ZhiCheng AI World Model: Focused on robotic physical intelligence.

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Towards AI

JANUARY 7, 2025

Author(s): Ehssan Originally published on Towards AI. During this process, they learn language patterns but typically are not capable of following instructions or answering questions. A Quick Look at BERT BERT was introduced by Google in 2018 and has since revolutionized the field of NLP.

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IBM Journey to AI blog

AUGUST 1, 2023

True to their name, generative AI models generate text, images, code , or other responses based on a user’s prompt. Foundation models: The driving force behind generative AI Also known as a transformer, a foundation model is an AI algorithm trained on vast amounts of broad data.

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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. Foundation models underpin generative AI capabilities, from text-generation to music creation to image generation. What is self-supervised learning? Find out in the guide below.

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AWS Machine Learning Blog

AUGUST 16, 2023

Training machine learning (ML) models to interpret this data, however, is bottlenecked by costly and time-consuming human annotation efforts. One way to overcome this challenge is through self-supervised learning (SSL). Jeremy Anderson is a Director & Data Scientist at Travelers on the AI & Automation Accelerator team.

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Google Research AI blog

JANUARY 18, 2023

Over the next several weeks, we will discuss novel developments in research topics ranging from responsible AI to algorithms and computer systems to science, health and robotics. They were followed in 2017 by VQ-VAE, proposed in “ Neural Discrete Representation Learning ”, a vector-quantized variational autoencoder. Let’s get started!

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How to Learn Machine Learning

OCTOBER 10, 2024

Real-Life Examples of Poor Training Data in Machine Learning Amazon’s Hiring Algorithm Disaster In 2018, Amazon made headlines for developing an AI-powered hiring tool to screen job applicants. Microsoft’s Tay Chatbot Misfire Microsoft launched an AI chatbot called Tay on Twitter in 2016. Sounds great, right?

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Explosion

JANUARY 12, 2018

In August 2016, Ines wrote a post on how AI developers could benefit from better tooling and more careful attention to interaction design. Demystifying “AI” by making it easier to use and understand is a big part of that. We think 2018 can be even better – to stay in the loop, follow us on Twitter.

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AWS Machine Learning Blog

AUGUST 7, 2023

AWS ProServe solved this use case through a joint effort between the Generative AI Innovation Center (GAIIC) and the ProServe ML Delivery Team (MLDT). The AWS GAIIC is a group within AWS ProServe that pairs customers with experts to develop generative AI solutions for a wide range of business use cases using proof of concept (PoC) builds.

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Mlearning.ai

JULY 31, 2023

One example is the Pairwise Inner Product (PIP) loss, a metric designed to measure the dissimilarity between embeddings using their unitary invariance (Yin and Shen, 2018). Yin and Shen (2018) accompany their research with a code implementation on GitHub here. Fortunately, there is; use an embedding loss. Equation 2.3.1. and Auli, M.,

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Pickl AI

APRIL 10, 2023

As per the recent report by Nasscom and Zynga, the number of data science jobs in India is set to grow from 2,720 in 2018 to 16,500 by 2025. Top 5 Colleges to Learn Data Science (Online Platforms) 1. The post Best Colleges for Data Science Course Online in India appeared first on Pickl AI.

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Snorkel AI

MAY 25, 2023

Data scientists and researchers train LLMs on enormous amounts of unstructured data through self-supervised learning. The model then predicts the missing words (see “what is self-supervised learning?” From 2018 to the modern day, NLP researchers have engaged in a steady march toward ever-larger models.

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Natural Language Processing Python Machine Learning Machine Learning 52

Snorkel AI

MAY 25, 2023

Data scientists and researchers train LLMs on enormous amounts of unstructured data through self-supervised learning. The model then predicts the missing words (see “what is self-supervised learning?” From 2018 to the modern day, NLP researchers have engaged in a steady march toward ever-larger models.

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Natural Language Processing Python Machine Learning Machine Learning 52

Data Science Blog

MARCH 14, 2023

Dann etwa im Jahr 2018 flachte der Hype um Big Data wieder ab, die Euphorie änderte sich in eine Ernüchterung, zumindest für den deutschen Mittelstand. Von Data Science spricht auf Konferenzen heute kaum noch jemand und wurde hype-technisch komplett durch Machine Learning bzw. Artificial Intelligence (AI) ersetzt.

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IBM Journey to AI blog

JUNE 23, 2023

With the advent of artificial intelligence (AI) , however, companies are now implementing cognitive process automation that enables self-service options for customers and agents self-service and assists in automating many other functions, such as the IT Help Desk and employee HR capabilities.

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DrivenData Labs

FEBRUARY 3, 2025

Xindi Liu ¶ Place: 3rd Prize: $9,000 Hometown: Huaibei City, Anhui Province, China Username: dylanliu Background: Im a freelance programmer (AI related) with 7 years of experience. I love participating in various competitions involving deep learning, especially tasks involving natural language processing or LLMs.

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