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Llama 2: A Deep Dive into the Open-Source Challenger to ChatGPT

Unite.AI

Technical Deep Dive of Llama 2 For training the Llama 2 model; like its predecessors, it uses an auto-regressive transformer architecture , pre-trained on an extensive corpus of self-supervised data. For those interested in experiencing this, a live demo is available at Llama2.ai.

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Prioritizing employee well-being: An innovative approach with generative AI and Amazon SageMaker Canvas

AWS Machine Learning Blog

In a single visual interface, you can complete each step of a data preparation workflow: data selection, cleansing, exploration, visualization, and processing. Custom Spark commands can also expand the over 300 built-in data transformations. Complete the following steps: Choose Prepare and analyze data.

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16 Companies Leading the Way in AI and Data Science

ODSC - Open Data Science

We couldn’t be more excited to announce our first group of partners for ODSC East 2023’s AI Expo and Demo Hall. These organizations are shaping the future of the AI and data science industries with their innovative products and services. These tools are designed to help companies derive insights from big data.

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MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

Can you see the complete model lineage with data/models/experiments used downstream? It enables data scientists to log, compare, and visualize experiments, track code, hyperparameters, metrics, and outputs. Is it accessible from your language/framework/infrastructure, framework, or infrastructure? Can you render audio/video?

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Using Snowflake Connector in Snorkel Flow

Snorkel AI

Data science and machine learning teams use Snorkel Flow’s programmatic labeling to intelligently capture knowledge from various sources—such as previously labeled data (even when imperfect), heuristics from subject matter experts, business logic, and even the latest foundation models —and then scale this knowledge to label large quantities of data.

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Using Snowflake Connector in Snorkel Flow

Snorkel AI

Data science and machine learning teams use Snorkel Flow’s programmatic labeling to intelligently capture knowledge from various sources—such as previously labeled data (even when imperfect), heuristics from subject matter experts, business logic, and even the latest foundation models —and then scale this knowledge to label large quantities of data.

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Synthetic Data: A Model Training Solution

Viso.ai

Organizations can easily source data to promote the development, deployment, and scaling of their computer vision applications. Get a demo. Viso Suite is the End-to-End, No-Code Computer Vision Platform – Learn more What is Synthetic Data? 1: Variational Auto-Encoder. Technique No.1: