Artificial Intelligence | News, analysis, features, how-tos, and videos
Llama 2 Chat can generate and explain Python code quite well, right out of the box. Code Llama’s fine-tuned models offer even better capabilities for code generation.
Amazon CodeWhisperer, Google Bard, and GitHub Copilot X plod through our AI pair programming challenge. Each tool has its strengths, and none of them are perfect.
Add-on to Jupyter Notebooks enables a literate Python development style that gives you high-quality documentation, tests, continuous integration, and packaging for free.
Snowpark for Python gives data scientists a nice way to do DataFrame-style programming against the Snowflake data warehouse, including the ability to set up full-blown machine learning pipelines to run on a recurrent schedule.
Databricks Lakehouse Platform combines cost-effective data storage with machine learning and data analytics, and it's available on AWS, Azure, and GCP. Could it be an affordable alternative for your data warehouse needs?
Nvidia’s VMware-optimized AI software stack offers a strong alternative to doing machine learning in the AWS, Azure, and Google clouds. Nvidia LaunchPad lets you try it out for free.
Amazon Textract, Azure Form Recognizer, and Google Document AI can parse your unstructured documents and produce structured information for all kinds of digital transformation use cases.
The Copilot technical preview doesn’t always generate good, correct, or even running code, but it’s still somewhat useful. Future versions could be real time-savers.
Vertex AI greatly improves the integration of Google Cloud’s AI/ML platform and AutoML services, combining a new unified API with very good modeling capabilities.
Dataiku’s end-to-end machine learning platform combines visual tools, notebooks, and code to address the needs of data scientists, data engineers, business analysts, and AI consumers.
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