Brandon Lang

Enthusiast of all things #ai, #bots, #IoT, #drones. Emerging tech.

[François Chollet @fchollet]

The problem is not so much that we are increasingly relying on algorithms to be our interface with an increasingly information-intensive world. With the rise of the Internet and AI, his trend is inevitable. The issue is control.

[Jenna McLaughlin @JennaMC_Laugh]

Let's just say there are *a lot* of reasons, on purpose or by accident, people might've harvested your personal data back around 2010. https://t.co/juYNJgj9BQ

[Rachel Thomas @math_rachel]

reminder: machine learning can amplify biases https://t.co/PCgLDPHhHp
(algorithm predicted that person cooking is a woman 84% of the time, compared to 67% of people cooking being women in the data set)

[hardmaru @hardmaru]

Ancient neural network diagrams from the 1990s. https://t.co/TVzoILPMlD

[Rudy Agovic @rudyagovic]

Get started with NLP (Part II): overview of an NLP workflow #MachineLearning #DataScience https://t.co/JiMdBgXadv

[Dawn Song @dawnsongtweets]

Extracting secrets from deep learning models:
https://t.co/MbYcBlfjpy Care needs to be taken when training deep learning models on sensitive data. Details in our paper https://t.co/snx30K6ELL

[Jeremy Gardner @Gonzogardner]

Unpopular opinion: one of the big inhibitors to innovation in tech is many programmers’ lack of respect for those who don’t code or know how.

Lack of appreciation for non-technical perspectives and leadership creates a culture of science experiments and solutions to non-problems

[Christian Wolf (🦋🦋🦋) @chriswolfvision]

Computer Science was always a pure field like Mathematics, but with Deep Learning it recently became experimental science. People are studying what neural nets learn from large scale datasets or environments as if they were rats. Excellent paper #iclr2018, https://t.co/duKvS49qxA

[arxiv @arxiv_org]

Contained Neural Style Transfer for Decorated Logo Generation. https://t.co/DGGwiIFuvk