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10 things to watch out for with open source gen AI

CIO Business Intelligence

Even if you don’t have the training data or programming chops, you can take your favorite open source model, tweak it, and release it under a new name. According to Stanford’s AI Index Report, released in April, 149 foundation models were released in 2023, two-thirds of them open source.

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Amazon Web Services continues open-source push with code behind SageMaker Neo

CTOvision

Amazon Web Services has decided to release the code behind one of its key machine-learning services as an open-source project, as it continues to push back against critics who find its relationship with open-source software out of balance.

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AI2 and Microsoft use satellite images plus artificial intelligence to monitor the planet

GeekWire

Satlas’ AI modeling software improves satellite image resolution by a factor of four. The Allen Institute for AI, also known as AI2, recently rolled out Satlas , a new software platform for exploring global geospatial data generated from satellite imagery. Training the model was no easy task.

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Open source NLP is fueling a new wave of startups

Venture Beast

A growing number of startups are offering open source language models as a service, competing with heavyweights like OpenAI. Read More.

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Microsoft’s Tutel optimizes AI model training

Venture Beast

Microsoft's Tutel library, now available in open source, optimizes the training of mixture of experts machine learning systems. Read More.

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Creating an artificial intelligence 101

Dataconomy

How to create an artificial intelligence? The creation of artificial intelligence (AI) has long been a dream of scientists, engineers, and innovators. Understanding artificial intelligence Before diving into the process of creating AI, it is important to understand the key concepts and types of AI.

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Gen AI without the risks

CIO Business Intelligence

On top of that, Gen AI, and the large language models (LLMs) that power it, are super-computing workloads that devour electricity.Estimates vary, but Dr. Sajjad Moazeni of the University of Washington calculates that training an LLM with 175 billion+ parameters takes a year’s worth of energy for 1,000 US households. Not at all.

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