DrivenData Labs

JULY 19, 2023

How can we use data and AI to help combat the effects of climate change? In recent years, advances in computing and data science have powered new capabilities for computer programs to learn patterns from vast amounts of examples and apply those learnings automatically and at scale. Let's take a look!

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Mlearning.ai

DECEMBER 21, 2023

However, when it comes to using LLMs in real scenarios, we still grapple with the knowledge limitations and hallucinations of the LLMs. The Curse of the LLMs 30th November, 2022 will be remembered as the watershed moment in artificial intelligence. aside, people realised that there are two major limitations of Large Language Models.

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Dataconomy

APRIL 4, 2023

Artificial intelligence (AI) is a broad term that encompasses the ability of computers and machines to perform tasks that normally require human intelligence, such as reasoning, learning, decision-making, and problem-solving. When given enough data, the model may draw certain inferences and make predictions.

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Dataconomy

APRIL 4, 2023

Artificial intelligence (AI) is a broad term that encompasses the ability of computers and machines to perform tasks that normally require human intelligence, such as reasoning, learning, decision-making, and problem-solving. When given enough data, the model may draw certain inferences and make predictions.

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K-nearest Neighbors Decision Trees AI AI 91

Dataconomy

MAY 11, 2023

It is the second iteration of PaLM, which was launched in April 2022. The model is able to learn the relationships between words and phrases, and it can use this knowledge to perform a variety of tasks. Google I/O brings a fresh LLM to the AI race. Meet Bard AI’s new engine, PaLM 2. How does PaLM 2 work? What is Google PaLM 2?

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Dataconomy

JULY 18, 2023

By removing all ethical boundaries and limitations, WormGPT becomes a potent weapon in the hands of unscrupulous individuals, enabling them to create phishing emails, propagate malware, and generate abusive content with ease. For those seeking unrestricted AI capabilities without limitations, it provides an enticing allure.

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PyImageSearch

JULY 3, 2023

In this blog post, we will dive deeper into the Netflix movies and series recommendation systems ( Figure 1 ). Whenever you watch something on Netflix, the system collects various kinds of data, which is then consumed by these algorithms to update recommendations on your profile home page the very next day.

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Mlearning.ai

JULY 20, 2023

In the intricate world of machine learning algorithms, probability serves as the foundational pillar. In this three-part blog series, we delve into the basics of probability and conditional probability, using the engaging context of cycling and supplemented by dynamic Python simulations. Which route should the cyclist take?

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Heartbeat

FEBRUARY 28, 2023

The past few years have witnessed exponential growth in medical image analysis using deep learning. In this article we will look into medical image segmentation and see how deep learning can be helpful in these cases. This can be further classified as supervised and unsupervised learning. What is Semi-supervised Learning (SSL)?

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Flipboard

MARCH 23, 2023

ChatGPT, or something built on ChatGPT, or something that’s like ChatGPT, has been in the news almost constantly since ChatGPT was opened to the public in November 2022. What is it, how does it work, what can it do, and what are the risks of using it? A quick scan of the web will show you lots of things that ChatGPT can do. GPT-2, 3, 3.5,

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Dataconomy

FEBRUARY 22, 2023

We’ve got you covered whether you’re motivated by a desire to learn more or a want to save money on subscription costs. Facts: To learn how people in the United States, the United Kingdom, and Japan feel about digital productivity tools, Microsoft recently conducted a poll with 2,700 employees and 1,800 company decision-makers.

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Mlearning.ai

MARCH 2, 2023

This blog post promises to be easier to understand than the underlying research paper, especially for readers not that familiar with the field. Preliminaries: Transformers and Unsupervised Transfer Learning II.1 2 Unsupervised Transfer Learning: Feature-based vs. Fine-tuning Approach III. Training Data III.4 1 Impact V.2

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Deep Learning Deep Learning Machine Learning Machine Learning 52

AWS Machine Learning Blog

FEBRUARY 28, 2023

In today’s highly competitive market, performing data analytics using machine learning (ML) models has become a necessity for organizations. It enables them to unlock the value of their data, identify trends, patterns, and predictions, and differentiate themselves from their competitors.

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AWS Machine Learning Blog

MARCH 21, 2023

The tool makes it easy to access geospatial data sources, run purpose-built processing operations, apply pre-trained ML models, and use built-in visualization tools faster and at scale. Learn more about NDVI calculations here ). The following diagram illustrates this architecture.

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Google Research AI blog

JANUARY 24, 2023

Shortcut learning: Age impacts correct medical diagnosis. In computer vision, we studied the robustness of new vision transformer models and developed new negative data augmentation techniques to improve their robustness. Another key part of our ML work involves developing techniques to build models that are more inclusive.

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AWS Machine Learning Blog

FEBRUARY 24, 2023

Amazon SageMaker multi-model endpoints (MMEs) provide a scalable and cost-effective way to deploy a large number of machine learning (ML) models. In November 2022, MMEs added support for GPU s, which allows you to run multiple models on a single GPU device and scale GPU instances behind a single endpoint.

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