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Reduce ML training costs with Amazon SageMaker HyperPod

AWS Machine Learning - AI

Training a frontier model is highly compute-intensive, requiring a distributed system of hundreds, or thousands, of accelerated instances running for several weeks or months to complete a single job. For example, pre-training the Llama 3 70B model with 15 trillion training tokens took 6.5 During the training of Llama 3.1

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Refer a founder to Startup Battlefield 200 at Disrupt 2023

TechCrunch

Then you’ll want to refer the top early-stage startups in your portfolio/pipeline Rolodex to Startup Battlefield 200 at Disrupt 2023! Refer a founder today. Refer a founder to Startup Battlefield 200 at Disrupt 2023 by Neesha A. Want to make a founder’s day, week, month, and possibly career? That’s huge.

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Efficiently train models with large sequence lengths using Amazon SageMaker model parallel

AWS Machine Learning - AI

Across diverse industries—including healthcare, finance, and marketing—organizations are now engaged in pre-training and fine-tuning these increasingly larger LLMs, which often boast billions of parameters and larger input sequence length. This approach reduces memory pressure and enables efficient training of large models.

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Nigeria’s Decagon raises millions to finance and train software engineers

TechCrunch

That’s what Decagon hopes for by training and connecting engineers to work remotely with both local and international companies. The CEO adds that the company which he refers to as a “tech talent catalyst” is profitable and growing at 500% per annum. “We Canada, the U.K., and Germany. So the issue really is supply.

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Strong Compute raises $7.8M seed round to speed up ML training pipelines

TechCrunch

Strong Compute , a Sydney, Australia-based startup that helps developers remove the bottlenecks in their machine learning training pipelines, today announced that it has raised a $7.8 ” Strong Compute wants to speed up your ML model training. . ” Strong Compute wants to speed up your ML model training.

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Adept, a startup training AI to use existing software and APIs, raises $350M

TechCrunch

The cash injection brings Adept’s total raised to $415 million, which co-founder and CEO David Luan says is being put toward productization, model training and headcount growth. ” Adept, a startup training AI to use existing software and APIs, raises $350M by Kyle Wiggers originally published on TechCrunch

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V7 snaps up $33M to automate training data for computer vision AI models

TechCrunch

It’s only as good as the models and data used to train it, so there is a need for sourcing and ingesting ever-larger data troves. But annotating and manipulating that training data takes a lot of time and money, slowing down the work or overall effectiveness, and maybe both. V7 even lays out how the two services compare.)

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