Blog

Sep 15, 2015 · post

Pictograph: Unlock Your Images

Have you ever wondered what your photos say about how you look at the world and who you are? Your images won’t say much about what types of things you tend to post unless you routinely tag them.  

Our new toy application, Pictograph, catalogs the objects that make up your Instagram identity. Pictograph analyzes your Instagram photos and creates a visualization, or pictograph, of what you like to photograph. It’s a fun way to play with new deep learning algorithms for image analysis, and it makes some pretty hilarious mistakes.

Here’s the pictograph for our own Grant Custer:

image

Try it out on your Instagram feed!

We built Pictograph as a toy to help us (and you) understand how deep learning works (and doesn’t work) by applying it in context. Deep learning is an important technology, but we’re still at the beginning of seeing its capabilities. Companies like Google and Facebook are using the technique to recognize cats in videos and categorize content, but we know bigger applications are just around the corner. We expect deep learning will affect several industries in the next couple of years: improving medical diagnoses from X-rays and MRIs, streamlining insurance claims adjustment, predicting market conditions in financial services, and many more. 

Given the impact deep learning will have, it’s important to understand how it works and what opportunities it offers. To that end, we are also excited to provide our clients with our Deep Learning for Image Analysis report and advanced prototype. The report and advanced prototype explain the technology in depth, walk through when deep learning is the right option, and demonstrate how to build systems using the technology.

If you’re curious to learn more, join us this Thursday, September 17, at 1:00 ET/10:00 PT for an online discussion between own Hilary Mason and Matt Zeiler, CEO of Clarifai. And stay tuned for more resources throughout the fall!

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Sep 22, 2015 · interview
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Sep 2, 2015 · post

Latest posts

Nov 15, 2022 · newsletter

CFFL November Newsletter

November 2022 Perhaps November conjures thoughts of holiday feasts and festivities, but for us, it’s the perfect time to chew the fat about machine learning! Make room on your plate for a peek behind the scenes into our current research on harnessing synthetic image generation to improve classification tasks. And, as usual, we reflect on our favorite reads of the month. New Research! In the first half of this year, we focused on natural language processing with our Text Style Transfer blog series.
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Nov 14, 2022 · post

Implementing CycleGAN

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Oct 20, 2022 · newsletter

CFFL October Newsletter

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Sep 21, 2022 · newsletter

CFFL September Newsletter

September 2022 Welcome to the September edition of the Cloudera Fast Forward Labs newsletter. This month we’re talking about ethics and we have all kinds of goodies to share including the final installment of our Text Style Transfer series and a couple of offerings from our newest research engineer. Throw in some choice must-reads and an ASR demo, and you’ve got yourself an action-packed newsletter! New Research! Ethical Considerations When Designing an NLG System In the final post of our blog series on Text Style Transfer, we discuss some ethical considerations when working with natural language generation systems, and describe the design of our prototype application: Exploring Intelligent Writing Assistance.
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Sep 8, 2022 · post

Thought experiment: Human-centric machine learning for comic book creation

by Michael Gallaspy · This post has a companion piece: Ethics Sheet for AI-assisted Comic Book Art Generation I want to make a comic book. Actually, I want to make tools for making comic books. See, the problem is, I can’t draw too good. I mean, I’m working on it. Check out these self portraits drawn 6 months apart: Left: “Sad Face”. February 2022. Right: “Eyyyy”. August 2022. But I have a long way to go until my illustrations would be considered professional quality, notwithstanding the time it would take me to develop the many other skills needed for making comic books.
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Aug 18, 2022 · newsletter

CFFL August Newsletter

August 2022 Welcome to the August edition of the Cloudera Fast Forward Labs newsletter. This month we’re thrilled to introduce a new member of the FFL team, share TWO new applied machine learning prototypes we’ve built, and, as always, offer up some intriguing reads. New Research Engineer! If you’re a regular reader of our newsletter, you likely noticed that we’ve been searching for new research engineers to join the Cloudera Fast Forward Labs team.
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Reports

In-depth guides to specific machine learning capabilities

Prototypes

Machine learning prototypes and interactive notebooks
Notebook

ASR with Whisper

Explore the capabilities of OpenAI's Whisper for automatic speech recognition by creating your own voice recordings!
https://colab.research.google.com/github/fastforwardlabs/whisper-openai/blob/master/WhisperDemo.ipynb
Library

NeuralQA

A usable library for question answering on large datasets.
https://neuralqa.fastforwardlabs.com
Notebook

Explain BERT for Question Answering Models

Tensorflow 2.0 notebook to explain and visualize a HuggingFace BERT for Question Answering model.
https://colab.research.google.com/drive/1tTiOgJ7xvy3sjfiFC9OozbjAX1ho8WN9?usp=sharing
Notebooks

NLP for Question Answering

Ongoing posts and code documenting the process of building a question answering model.
https://qa.fastforwardlabs.com

Cloudera Fast Forward Labs

Making the recently possible useful.

Cloudera Fast Forward Labs is an applied machine learning research group. Our mission is to empower enterprise data science practitioners to apply emergent academic research to production machine learning use cases in practical and socially responsible ways, while also driving innovation through the Cloudera ecosystem. Our team brings thoughtful, creative, and diverse perspectives to deeply researched work. In this way, we strive to help organizations make the most of their ML investment as well as educate and inspire the broader machine learning and data science community.

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