Category Machine Learning

Training the Machines with Russell Smith

http://traffic.libsyn.com/sedaily/RainforestQA.mp3Podcast: Play in new window | Download Automation is changing the labor market. To automate a task, someone needs to put in the work to describe the task correctly to a computer. For some tasks, the reward for automating a task is tremendous–for example, putting together mobile phones. In China, companies like FOXCONN are investing time and money into programming the instructions for how to assemble your phone. Robots execute

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Model Training with Yufeng Guo

http://traffic.libsyn.com/sedaily/ModelTraining.mp3Podcast: Play in new window | Download Machine learning models can be built by plotting points in space and optimizing a function based off of those points. For example, I can plot every person in the United States in a 3 dimensional space: age, geographic location, and yearly salary. Then I can draw a function that minimizes the distance between my function and each of those data points. Once I

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Sports Deep Learning with Yu-Han Chang and Jeff Su

http://traffic.libsyn.com/sedaily/SportsAnalytics.mp3Podcast: Play in new window | Download A basketball game gives off endless amounts of data. Cameras from all angles capture the players making their way around the court, dribbling, passing, and shooting. With computer vision, a computer can build a well-defined understanding for what a sport looks like. With other machine learning techniques, the computer can make predictions by combining historical data with a game that is going on

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Deep Learning Systems with Milena Marinova

http://traffic.libsyn.com/sedaily/DeepLearningSystems.mp3Podcast: Play in new window | Download The applications that demand deep learning range from self-driving cars to healthcare, but the way that models are developed and trained is similar. A model is trained in the cloud and deployed to a device. The device engages with the real world, gathering more data. That data is sent back to the cloud, where it can improve the model. From the processor level

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Visual Search with Neel Vadoothker

http://traffic.libsyn.com/sedaily/Visual_Search.mp3Podcast: Play in new window | Download If I have a picture of a dog, and I want to search the Internet for pictures that look like that dog, how can I do that? I need to make an algorithm to build an index of all the pictures on the Internet. That index can define the different features of my images. I can find mathematical features in each image that

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Word2Vec with Adrian Colyer

http://traffic.libsyn.com/sedaily/Word2vecAdrianColyer.mp3Podcast: Play in new window | Download Machines understand the world through mathematical representations. In order to train a machine learning model, we need to describe everything in terms of numbers.  Images, words, and sounds are too abstract for a computer. But a series of numbers is a representation that we can all agree on, whether we are a computer or a human. In recent shows, we have explored how

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Artificial Intelligence APIs with Simon Chan

http://traffic.libsyn.com/sedaily/SalesforceEinstein.mp3Podcast: Play in new window | Download Software companies that have been around for a decade have a ton of data. Modern machine learning techniques are able to turn that data into extremely useful models. Salesforce users have been entering petabytes of data into the company’s CRM tool since 1999. With its Einstein suite of products, Salesforce is using that data to build new product features and APIs. Simon Chan

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Healthcare AI with Cosima Gretton

http://traffic.libsyn.com/sedaily/HealthwithCosima.mp3Podcast: Play in new window | Download Automation will make healthcare more efficient and less prone to error. Today, machine learning is already being used to diagnose diabetic retinopathy and improve radiology accuracy. Someday, an AI assistant will assist a doctor in working through a complicated differential diagnosis. Our hospitals look roughly the same today as they did ten years ago, because getting new technology into the hands of doctors

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Lending Machine Learning with Ofer Mendelevitch

http://traffic.libsyn.com/sedaily/Lendup.mp3Podcast: Play in new window | Download Loans give people more financial security. If people know that they can receive a loan, they will be more willing to take intelligent risks. A loan can allow for a short-term investment that pays off enough to justify the interest rate on that loan. For the lender, a loan can be a fantastic return on capital–as long as the lendee does not default.

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Self-Driving Deep Learning with Lex Fridman

http://traffic.libsyn.com/sedaily/SelfDrivingDeepLearning.mp3Podcast: Play in new window | Download Self-driving cars are here. Fully autonomous systems like Waymo are being piloted in less complex circumstances. Human-in-the-loop systems like Tesla Autopilot navigate drivers when it is safe to do so, and lets the human take control in ambiguous circumstances. Computers are great at memorization, but not yet great at reasoning. We cannot enumerate to a computer every single circumstance that a car might

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Distributed Deep Learning with Will Constable

http://traffic.libsyn.com/sedaily/Distributeddeeplearning.mp3Podcast: Play in new window | Download Deep learning allows engineers to build models that can make decisions based on training data. These models improve over time using stochastic gradient descent. When a model gets big enough, the training must be broken up across multiple machines. Two strategies for doing this are “model parallelism” which divides the model across machines and “data parallelism” which divides the data across multiple copies

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Video Object Segmentation with the DAVIS Challenge Team

http://traffic.libsyn.com/sedaily/objectsegmentation.mp3Podcast: Play in new window | Download Video object segmentation allows computer vision to identify objects as they move through space in a video. The DAVIS challenge is a contest among machine learning researchers working off of a shared dataset of annotated videos. The organizers of the DAVIS challenge join the show today to explain how video object segmentation models are trained and how different competitors take part in the

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Poker Artificial Intelligence with Noam Brown

http://traffic.libsyn.com/sedaily/Libratus.mp3Podcast: Play in new window | Download Humans have now been defeated by computers at heads up no-limit holdem poker. Some people thought this wouldn’t be possible. Sure, we can teach a computer to beat a human at Go or Chess. Those games have a smaller decision space. There is no hidden information. There is no bluffing. Poker must be different! It is too human to be automated. The game

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Convolutional Neural Networks with Matt Zeiler

http://traffic.libsyn.com/sedaily/ClarifaiCNNs.mp3Podcast: Play in new window | Download Convolutional neural networks are a machine learning tool that uses layers of convolution and pooling to process and classify inputs. CNNs are useful for identifying objects in images and video. In this episode, we focus on the application of convolutional neural networks to image and video recognition and classification. Matt Zeiler is the CEO of Clarifai, an API for image and video recognition.

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Google Brain Music Generation with Doug Eck

http://traffic.libsyn.com/sedaily/GoogleBrain.mp3Podcast: Play in new window | Download Most popular music today uses a computer as the central instrument. A single musician is often selecting the instruments, programming the drum loops, composing the melodies, and mixing the track to get the right overall atmosphere. With so much work to do on each song, popular musicians need to simplify–the result is that pop music today consists of simple melodies without much chord

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Hedge Fund Artificial Intelligence with Xander Dunn

http://traffic.libsyn.com/sedaily/numerai_edited.mp3Podcast: Play in new window | Download A hedge fund is a collection of investors that make bets on the future. The “hedge” refers to the fact that the investors often try to diversify their strategies so that the direction of their bets are less correlated, and they can be successful in a variety of future scenarios. Engineering-focused hedge funds have used what might be called “machine learning” for a

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Multiagent Systems with Peter Stone

http://traffic.libsyn.com/sedaily/multiagent-systems_edited_1.mp3Podcast: Play in new window | Download Multiagent systems involve the interaction of autonomous agents that may be acting independently or in collaboration with each other. Examples of these systems include financial markets, robot soccer matches, and automated warehouses. Today’s guest Peter Stone is a professor of computer science who specializies in multiagent systems and robotics. In this episode, we discuss some of the canonical problems of multiagent systems, which

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Biological Machine Learning with Jason Knight

http://traffic.libsyn.com/sedaily/biodeeplearing_edited.mp3Podcast: Play in new window | Download Biology research is complex. The sample size of a biological data set is often too small to make confident judgments about the biological system being studied. During Jason Knight’s PhD research, the RNA sequence data that he was studying was not significant enough to make strong conclusions about the gene regulatory networks he was trying to understand. After working in academia, and then

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Stripe Machine Learning with Michael Manapat

http://traffic.libsyn.com/sedaily/stripeantifraud_edited.mp3Podcast: Play in new window | Download Every company that deals with payments deals with fraud. The question is not whether fraud will occur on your system, but rather how much of it you can detect and prevent. If a payments company flags too many transactions as fraudulent, then real transactions might accidentally get flagged as well. But if you don’t reject enough of the fraudulent transactions, you might not

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Artificial Intelligence Implications with Rumman Chowdhury

http://traffic.libsyn.com/sedaily/aiwithrumman_edited_1.mp3Podcast: Play in new window | Download Machine learning has improved both in tools and accessibility. Frameworks like TensorFlow create the right abstractions for developers to work efficiently. Educational programs like Metis and Insight Data Science provide a place for developers to learn these tools. As a result, artificial intelligence is becoming easier to develop and more widespread. Rumman Chowdhury works on artificial intelligence at Accenture. Before her current role,

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