AWS Machine Learning Blog

JANUARY 13, 2023

This dataset comprises a multi-center critical care database collected from over 200 hospitals, which makes it ideal to test our FL experiments. We used the eICU Collaborative Research Database , a multi-center intensive care unit (ICU) database, comprising 200,859 patient unit encounters for 139,367 unique patients.

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AWS Machine Learning Blog

MAY 2, 2023

There are a few limitations of using off-the-shelf pre-trained LLMs: They’re usually trained offline, making the model agnostic to the latest information (for example, a chatbot trained from 2011–2018 has no information about COVID-19). For each record in the knowledge database, we generate an embedding vector using the GPT-J embedding model.

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Mlearning.ai

JANUARY 17, 2024

Traditional AI can recognize, classify, and cluster, but not generate the data it is trained on. The foundations for today’s generative language applications were elaborated in the 1990s ( Hochreiter , Schmidhuber ), and the whole field took off around 2018 ( Radford , Devlin , et al.). Let’s play the comparison game.

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Google Research AI blog

FEBRUARY 28, 2023

For example, supporting equitable student persistence in computing research through our Computer Science Research Mentorship Program , where Googlers have mentored over one thousand students since 2018 — 86% of whom identify as part of a historically marginalized group. sequence protein database with annotations. MGnify proteins A 2.4B-sequence

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O'Reilly Media

NOVEMBER 28, 2023

If we asked whether their companies were using databases or web servers, no doubt 100% of the respondents would have said “yes.” And there are tools for archiving and indexing prompts for reuse, vector databases for retrieving documents that an AI can use to answer a question, and much more. We expect others to follow.

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Explosion

MAY 17, 2023

For instance, you could extract a few noisy metrics, such as a general “positivity” sentiment score that you track in a dashboard, while you also produce more nuanced clustering of the posts which are reviewed periodically in more detail. So you do have to work around things, and use things like vector databases or other tricks.

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ODSC - Open Data Science

JULY 11, 2023

For HPC, it’s possible to use a cluster of powerful workstations or servers, each with multiple processors and large amounts of memory. Edwards J, 7 things to know about AI in the data center, CIO December 20, 2018 8. This will always be a work in progress. ChatGPT: The most advanced AI chatbot in 2022, on [link] 7. On [link] 9.

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Hacker News

JANUARY 9, 2024

And in a similar vein, we can expect LLMs to be useful in making connections to external databases, functions, etc. but with things like clustering). We’ve had ExternalEvaluate for evaluating Python code since 2018. But in Version 14.0 we’ve actually added one function— DigitSum —that was suggested to us by LLMs.

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Flipboard

NOVEMBER 24, 2023

The SnapLogic Intelligent Integration Platform (IIP) enables organizations to realize enterprise-wide automation by connecting their entire ecosystem of applications, databases, big data, machines and devices, APIs, and more with pre-built, intelligent connectors called Snaps.

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Tableau

DECEMBER 1, 2021

Chris had earned an undergraduate computer science degree from Simon Fraser University and had worked as a database-oriented software engineer. In 2004, Tableau got both an initial series A of venture funding and Tableau’s first EOM contract with the database company Hyperion—that’s when I was hired. Let’s take a look at each. .

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Tableau

DECEMBER 1, 2021

Chris had earned an undergraduate computer science degree from Simon Fraser University and had worked as a database-oriented software engineer. In 2004, Tableau got both an initial series A of venture funding and Tableau’s first OEM contract with the database company Hyperion—that’s when I was hired. Let’s take a look at each. .

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Flipboard

APRIL 13, 2023

Second, customers want integration into applications to be seamless, without having to manage huge clusters of infrastructure or incur large costs. In 2018, we announced Inferentia, the first purpose-built chip for inference. In this role, Swami oversees all AWS Database, Analytics, and AI & Machine Learning services.

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