RECENT UPDATES: Podsheets is our open source set of tools for managing podcasts and podcast businesses New version of Software Daily, our app and ad-free subscription service Software Daily is looking for help with Android engineering, QA, machine learning, and more FindCollabs Hackathon has ended–winners will probably be announced by the time this episode airs; we will be announcing our next hackathon in a few weeks, so stay tuned Drishti is a company focused on improving manufacturing workflow...
Apr 17, 2019•52 min
RECENT UPDATES: Podsheets is our open source set of tools for managing podcasts and podcast businesses New version of Software Daily, our app and ad-free subscription service Software Daily is looking for help with Android engineering, QA, machine learning, and more FindCollabs Hackathon has ended–winners will probably be announced by the time this episode airs; we will be announcing our next hackathon in a few weeks, so stay tuned Until Google DeepMind came into the field, protein structure pre...
Apr 15, 2019•54 min
RECENT UPDATES: FindCollabs $5000 Hackathon Ends Saturday April 15th, 2019 New version of Software Daily, our app and ad-free subscription service Software Daily is looking for help with Android engineering, QA, machine learning, and more Data sets can be modeled in a row-wise, relational format. When two data sets share a common field, those data sets can be combined in a procedure called a join. A join combines the data of two data sets into one data set that is often bigger than the initial t...
Apr 10, 2019•59 min
The demand for electricity is based on the consumption of the electrical grid at a given time. The supply of electricity is based on how much energy is being produced or stored on the grid at a given time. Because these sources of supply and demand fluctuate rapidly but predictably, energy markets present profit opportunities for traders. Minh Dang and Corey Noone are engineers with Advanced Microgrid Solutions, a company that builds software to help traders capture better opportunities in the e...
Mar 11, 2019•43 min
Zoox is a full-stack self-driving car company. Zoox engineers work on everything a self-driving car company needs, from the physical car itself to the algorithms running on the car to the ride hailing system which the company plans to use to drive around riders. Since starting in 2014, Zoox has grown to over 500 employees. Ethan Dreyfuss is a software infrastructure engineer at Zoox. He joins the show to discuss scaling an engineering team for self-driving. Machine learning was a big part of our...
Feb 20, 2019•1 hr 3 min
DoorDash is a food delivery company where users find restaurants to order from. When a user opens the DoorDash app, the user can search for types of food or specific restaurants from the search bar or they can scroll through the feed section and look at recommendations that the app gives them within their local geographic area. Recommendations is a classic computer science problem. Much like sorting, or mapping, or scheduling, we will probably never “solve” recommendations. We will adapt our rec...
Feb 19, 2019•50 min
Artificial intelligence is reshaping every aspect of our lives, from transportation to agriculture to dating. Someday, we may even create a superintelligence–a computer system that is demonstrably smarter than humans. But there is widespread disagreement on how soon we could build a superintelligence. There is not even a broad consensus on how we can define the term “intelligence”. Information technology is improving so rapidly we are losing the ability to forecast the near future. Even the most...
Jan 31, 2019•57 min
When TensorFlow came out of Google, the machine learning community converged around it. TensorFlow is a framework for building machine learning models, but the lifecycle of a machine learning model has a scope that is bigger than just creating a model. Machine learning developers also need to have a testing and deployment process for continuous delivery of models. The continuous delivery process for machine learning models is like the continuous delivery process for microservices, but can be mor...
Jan 25, 2019•56 min
Robots are making their way into every area of our lives. Security robots roll around industrial parks at night, monitoring the area for intruders. Amazon robots tirelessly move packages around in warehouses, reducing the time and cost of logistics. Self-driving cars have become a ubiquitous presence in cities like San Francisco. For a hacker in a dorm room, or a researcher in a small lab, how do you get started with robotics? There are drones and other small options like AWS DeepRacer–but what ...
Jan 16, 2019•45 min
Originally posted on 13 September 2017. 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 to train machine learning models to understand images and video. Today, we explore words. Y...
Dec 28, 2018•55 min
Originally posted on 28 July 2017. 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 find itself in. The computer needs to perceive its surro...
Dec 27, 2018•52 min
Originally posted on May 12, 2015. 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 space of poker is different than that of Go. It has 10^160 different situations–which is more than the number of a...
Nov 21, 2018•45 min
The volume of data in the world is always increasing. The costs of storing that data is always decreasing. And the means for processing that data is always evolving. Sensors, cameras, and other small computers gather large quantities of data from the physical world around us. User analytics tools gather information about how we are interacting with the Internet. Logging servers collect terabytes of records about how our systems are performing. From the popularity of MapReduce, to the rise of ope...
Nov 16, 2018•1 hr 5 min
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...
Nov 07, 2018•51 min
Google Search allows humans to find and access information across the web. A human enters an unstructured query into the search box, the search engine provides several links as a result, and the human clicks on one of those links. That link brings up a web page, which is a set of unstructured data. Humans can read and understand news articles, videos, and Wikipedia pages. Google Search solves the problem of organizing and distributing all of the unstructured data across the web, for humans to co...
Oct 31, 2018•50 min
David Cancel has started five companies, most recently Drift. Drift is a conversational marketing and sales platform. David has a depth of engineering skills and a breadth of business experience that make him an amazing source of knowledge. In today’s episode, David discusses topics ranging from the technical details of making a machine learning-driven sales platform to the battle scars from his early career, when he spent a lot of time building products that people did not want. He has found su...
Oct 30, 2018•54 min
Google Brain is an engineering team focused on deep learning research and applications. One growing area of interest within Google Brain is that of generative models. A generative model uses neural networks and a large data set to create new data similar to the ones that the network has seen before. One approach to making use of generative models is GANs: generative adversarial networks. GANs can use a generative model (which creates new examples) together with a discriminator model (which can c...
Oct 11, 2018•1 hr 1 min
Stock traders have access to high volumes of information to help them make decisions on whether to buy an asset. A trader who is considering buying a share of Google stock can find charts, reports, and statistical tools to help with their decision. There are a variety of machine learning products to help a technical investor create models of how a stock price might change in the future. Real estate investors do not have access to the same data and tooling. Most people who invest in apartment bui...
Sep 11, 2018•51 min
Self-driving transportation will be widely deployed at some point in the future. How far off is that future? There are widely varying estimations: maybe you will summon a self-driving Uber in a New York within 5 years, or maybe it will take 20 years to work out all of the challenges in legal and engineering. Between now and the self-driving future, there will be a long span of time where cars are semi-autonomous. Maybe your car is allowed to drive itself in certain areas of the city. Maybe your ...
Aug 31, 2018•58 min
Stitch Fix is a company that recommends packages of clothing based on a set of preferences that the user defines and updates over time. Stitch Fix’s software platform includes the website, data engineering infrastructure, and warehouse software. Stitch Fix has over 5000 employees, including a large team of engineers. Cathy Polinsky is the CTO of Stitch Fix. In today’s show Cathy describes how the infrastructure has changed as the company has grown–including the process of moving the platform fro...
Aug 23, 2018•51 min
DoorDash is a last mile logistics company that connects customers with their favorite national and local businesses. When a customer orders from a restaurant, DoorDash needs to identify the ideal driver for picking up the order from the restaurant and dropping it off with the customer. This process of matching an order to a driver takes in many different factors. Let’s say I order spaghetti from an Italian restaurant. How long does the spaghetti take to prepare? How much traffic is there in diff...
Aug 16, 2018•51 min
In the smartphone market there are two dominant operating systems: one closed source (iPhone) and one open source (Android). The market for self-driving cars could play out the same way, with a company like Tesla becoming the closed source iPhone of cars, and a company like Comma.ai developing the open source Android of self-driving cars. George Hotz is the CEO of Comma.ai. Comma makes hardware devices that allow users with “normal” cars to be augmented with advanced cruise control and lane assi...
Aug 08, 2018•57 min
“Bots” are becoming increasingly relevant to our everyday interactions with technology. A bot sometimes mediates the interactions of two people. Examples of bots include automated reply systems, intelligent chat bots, classification systems, and prediction machines. These systems are often powered by machine learning systems that are black boxes to the user. Today’s guest Rob May argues that these systems should be auditable and accountable, and that using a blockchain-based identity system for ...
Jul 19, 2018•47 min
Machine learning models allow our applications to perform highly accurate inferences. A model can be used to classify a picture as a cat, or to predict what movie I might want to watch. But before a machine learning model can be used to make these inferences, the model must be trained and deployed. In the training process, a machine learning model consumes a data set and learns from it. The training process can consume significant resources. After the training process is over, you have a trained...
Jul 13, 2018•54 min
When a patient comes into the hospital with stroke symptoms, the hospital will give that patient a CAT scan, a 3-dimensional imaging of the patient’s brain. The CAT scan needs to be examined by a radiologist, and the radiologist will decide whether to refer the patient to an interventionist–a surgeon who can perform an operation to lower the risk of long-term damage to the patient’s brain function. After getting the CAT scan, the patient might wait for hours before a radiologist has a chance to ...
Jul 05, 2018•57 min
Evolutionary algorithms can generate surprising, effective solutions to our problems. Evolutionary algorithms are often let loose within a simulated environment. The algorithm is given a function to optimize for, and the engineers expect that algorithm to evolve a solution that optimizes for the objective function given the constraints of the simulated environment. But sometimes these results are not exactly what we are looking for. For example, imagine an evolutionary algorithm that tries to ev...
Jun 15, 2018•51 min
Moore’s Law states that the number of transistors in a dense integrated circuit double about every two years. Moore’s Law is less like a “law” and more like an observation or a prediction. Moore’s Law is ending. We can no longer fit an increasing amount of transistors in the same amount of space with a highly predictable rate. Dennard scaling is also coming to an end. Dennard scaling is the observation that as transistors get smaller, the power density stays constant. These changes in hardware t...
Jun 07, 2018•56 min
Applications of artificial intelligence are permeating our everyday lives. We notice it in small ways–improvements to speech recognition; better quality products being recommended to us; cheaper goods and services that have dropped in price because of more intelligent production. But what can we quantitatively say about the rate at which artificial intelligence is improving? How fast are models advancing? Do the different fields in artificial intelligence all advance together, or are they improv...
Jun 04, 2018•58 min
A sample of the human voice is a rich piece of unstructured data. Voice recordings can be turned into visualizations called spectrograms. Machine learning models can be trained to identify features of these spectrograms. Using this kind of analytic strategy, breakthroughs in voice analysis are happening at an amazing pace. Rita Singh researches voice at Carnegie Mellon University. Her work studies the high volume of latent data that is available in the human voice. As she explains, just a small ...
May 21, 2018•57 min
Data Skeptic is a podcast about machine learning, data science, and how software affects our lives. The first guest on today’s episode is Kyle Polich, the host of Data Skeptic . Kyle is one of the best explainers of machine learning concepts I have met, and for this episode, he presented some material that is perfect for this audience: machine learning for software engineers. Second Spectrum is a company that analyzes data from professional sports, turning that data into visualizations, reports,...
May 19, 2018•1 hr 10 min
