Mlearning.ai

JUNE 8, 2023

Like traditional database index, vector index organizes the vectors into a data structure and makes it possible to navigate through the vectors and find the ones that are closest in terms of semantic similarity. Clustering  — we can cluster our sentences, useful for topic modeling. Reduced price. lower price.

Machine Learning 52

Machine Learning Machine Learning Clustering Database 52

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.

AWS 81

AWS Analytics Analytics Machine Learning 81

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.

Algorithm 86

Algorithm Machine Learning Machine Learning Natural Language Processing 86

AWS Machine Learning Blog

SEPTEMBER 11, 2024

The following figure illustrates the idea of a large cluster of GPUs being used for learning, followed by a smaller number for inference. In 2018, other forms of PBAs became available, and by 2020, PBAs were being widely used for parallel problems, such as training of NN. For these three training approaches, the role of PBAs varies.

AWS 92

AWS ML ML Clustering 92

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.

AI 98

AI AI Deep Learning Deep Learning 98

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.

AI 135

AI AI Data Analysis Data Analysis 135

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.

Supervised Learning 135

Supervised Learning Natural Language Processing Clustering Machine Learning 135

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

ML 72

ML ML Deep Learning Deep Learning 72

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.

Python 181

Python Algorithm Machine Learning Machine Learning 181

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.

Data Lakes 40

Data Lakes AI AI Cloud Computing 40

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.

Database 158

Database AWS ETL SQL 158

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. .

Tableau 145

Tableau ML ML Database 145

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. .

Tableau 98

Tableau ML ML Database 98

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.

AWS 182

AWS AI AI ML 182