Machine Learning Archives - Software Engineering Daily

For several years, we have had the ability to create artificially generated text articles. More recently, audio and video synthesis have been feasible for artificial intelligence. Rosebud is a company that creates animated virtual characters that can speak. Users can generate real or fictional presenters easily with Rosebud. Dzmitry Pletnikau is an engineer with Rosebud and joins the show to talk about the technology and engineering behind the company.

Sponsorship inquiries: [email protected]

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Originally published November 7, 2018

An instruction set defines a low level programming language for moving information throughout a computer. In the early 1970’s, the prevalent instruction set language used a large vocabulary of different instructions. One justification for a large instruction set was that it would give a programmer more freedom to express the logic of their programs.

Many of these instructions were rarely used. Think of your favorite programming language (or your favorite human language). What percentage of words in the vocabulary do you need to communicate effectively? We sometimes call these language features “syntactic sugar”. They add expressivity to a language, but may not improve functionality or efficiency.

These extra language features can have a cost.

Dave Patterson and John Hennessy created the RISC architecture: Reduced Instruction Set Compiler architecture. RISC proposed reducing the size of the instruction set so that the important instructions could be optimized for. Programs would become more efficient, easier to analyze, and easier to debug.

Dave Patterson’s first paper on RISC was rejected. He continued to research the architecture and advocate for it. Eventually RISC became widely accepted, and Dave won a Turing Award together with John Hennessy.

Dave joins the show to talk about his work on RISC and his continued work in computer science research to the present. He is involved in the Berkeley RISELab and works at Google on the Tensor Processing Unit.

Machine learning is an ocean of new scientific breakthroughs and applications that will change our lives. It was inspiring to hear Dave talk about the changing nature of computing, from cloud computing to security to hardware design.

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Deep learning uses neural networks to identify patterns. Neural networks allow us to sequence “layers” of computing, with each layer using learning algorithms such as unsupervised learning, supervised learning, and reinforcement learning. Deep learning has taken off in the last few years, but it has been around for much longer.

Adam Gibson founded Skymind, the company behind Deeplearning4j. Deeplearning4j is a distributed deep learning library for Scala and Java. It integrates with Hadoop and Spark, and is specifically designed to run in business environments on distributed GPUs and CPUs. Adam joins the show today to discuss the history and future of deep learning.

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Interest in autonomous vehicles dates back to the 1920s. It wasn’t until the 1980s that the first truly autonomous vehicle prototypes began to appear. The first DARPA Grand Challenge took place in 2004 offering competitors $1 million dollars to complete a 150-mile course through the Mojave desert. The prize was not claimed.

Since then, rapid progress has begun in autonomous driving fueled by advances in sensor technology, software, and the hardware which runs it. Infrastructure has become a serious consideration for autonomous vehicle companies. In this episode, I speak with Vinoj Kumar, VP of Infrastructure at Cruise, the San Francisco company building an all-electric self-driving rideshare and delivery service. They’re tackling the infinite longtail scenarios of city driving and helping Walmart with self-driving grocery delivery.

Sponsorship inquiries: [email protected]

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Companies can have a negative impact on the environment by outputting excess carbon. Many companies want to reduce their net carbon impact to zero, which can be done by investing in forests. Pachama is a marketplace for forest investments. Pachama uses satellites, imaging, machine learning, and other techniques to determine how much carbon is being absorbed by different forests. Diego Saez-Gil is a founder of Pachama, and joins the show to talk through how Pachama works and the long-term goals of the company.

Sponsorship inquiries: [email protected]

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