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Frugality meets Accuracy: Cost-efficient training of GPT NeoX and Pythia models with AWS Trainium

AWS Machine Learning - AI

A generative pre-trained transformer (GPT) uses causal autoregressive updates to make prediction. Training LLMs requires colossal amount of compute time, which costs millions of dollars. Training LLMs requires colossal amount of compute time, which costs millions of dollars. We’ll outline how we cost-effectively (3.2

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Audio Analysis With Machine Learning: Building AI-Fueled Sound Detection App

Altexsoft

Today, we have AI and machine learning to extract insights, inaudible to human beings, from speech, voices, snoring, music, industrial and traffic noise, and other types of acoustic signals. At the same time, keep in mind that neither of those and other audio files can be fed directly to machine learning models.

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Predictive analytics helps Fresenius anticipate dialysis complications

CIO

In September 2021, Fresenius set out to use machine learning and cloud computing to develop a model that could predict IDH 15 to 75 minutes in advance, enabling personalized care of patients with proactive intervention at the point of care. CIO 100, Digital Transformation, Healthcare Industry, Predictive Analytics

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New at Disrupt, the AI Stage

TechCrunch

The AI Stage will feature experts from across the AI landscape , including ethicists, entrepreneurs and investors enmeshed in developments around AI and machine learning technologies. As the tech enters the mainstream, each new day brings a new lawsuit — which the experts on the AI Stage will break down in detail.

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Machine Learning with Python, Jupyter, KSQL and TensorFlow

Confluent

Building a scalable, reliable and performant machine learning (ML) infrastructure is not easy. It takes much more effort than just building an analytic model with Python and your favorite machine learning framework. Impedance mismatch between data scientists, data engineers and production engineers.

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Depressed? This algorithm can tell from the tone of your voice

TechCrunch

Kintsugi is attempting to use technology to build a machine learning model with many more samples than any individual clinician could see in a lifetime. Our neural network model has been trained on tens of thousands of depressed voices. So the first thing they did was build a free voice journaling app, also called Kintsugi.

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Modular secures $100M to build tools to optimize and create AI models

TechCrunch

Compatible with existing cloud environments, machine learning frameworks like Google’s TensorFlow and Meta’s PyTorch and even other AI accelerator engines, Modular’s engine, currently in closed preview, lets developers import trained models and run them up to 7.5 ” Ambitious much?