article thumbnail

6 trends framing the state of AI and ML

O'Reilly on Data

We use it as a data source for our annual platform analysis , and we’re using it as the basis for this report, where we take a close look at the most-used and most-searched topics in machine learning (ML) and artificial intelligence (AI) on O’Reilly [1]. What’s driving this growth? disproportionately involve Python.

article thumbnail

ChatGPT, the rise of generative AI

CIO Business Intelligence

A transformer is a type of AI deep learning model that was first introduced by Google in a research paper in 2017. It’s hard to achieve a deep, experiential understanding of new technology without experimentation. They should respond to innovations in an agile way: starting small and learning by doing.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Is Google Cloud Platform Ready to Run Your Data Analytics Pipeline?

Sanjeev Mohan

Fast forward to early 2017. I saw the winds change and the inquiry requests shifted towards advanced analytics involving machine learning (ML) questions. Then in the middle of 2017, a realization set in that we were one year away from GDPR and needed to focus on data governance.

article thumbnail

Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

To find optimal values of two parameters experimentally, the obvious strategy would be to experiment with and update them in separate, sequential stages. Our experimentation platform supports this kind of grouped-experiments analysis, which allows us to see rough summaries of our designed experiments without much work.

article thumbnail

Themes and Conferences per Pacoid, Episode 9

Domino Data Lab

I’ve been out themespotting and this month’s article features several emerging threads adjacent to the interpretability of machine learning models. Machine learning model interpretability. Other good related papers include: “ Towards A Rigorous Science of Interpretable Machine Learning ”. 2018-06-21).

article thumbnail

Themes and Conferences per Pacoid, Episode 6

Domino Data Lab

Spoiler alert: a research field called curiosity-driven learning is emerging at the nexis of experimental cognitive psychology and industry use cases for machine learning, particularly in gaming AI. Ensure a culture that supports a steady process of learning and experimentation. This is not that.

article thumbnail

Themes and Conferences per Pacoid, Episode 11

Domino Data Lab

Doesn’t this seem like a worthy goal for machine learning—to make the machines learn to work more effectively? For more background about program synthesis, check out “ Program Synthesis Explained ” by James Bornholt from 2015, as well as the more recent “ Program Synthesis in 2017-18 ” by Alex Polozov from 2018.

Metadata 105