Category Greatest Hits

Early Investments with Semil Shah

http://traffic.libsyn.com/sedaily/SemilShah.mp3Podcast: Play in new window | Download An engineer who wants to start a business using investment capital needs to understand the expectations of investors. The market for the business needs to be huge. The team needs to have a differentiated understanding of the market, or a differentiated product. The CEO needs to have the determination to continue operating the company even when it gets very difficult. And the price

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Netflix Serverless-like Platform with Vasanth Asokan

http://traffic.libsyn.com/sedaily/NetflixServerless.mp3Podcast: Play in new window | Download The Netflix API is accessed by developers who build for over 1000 device types: TVs, smartphontes, VR headsets, laptops. If it has a screen, it can probably run Netflix. On each of these different devices, the Netflix experience is different. Different screen sizes mean there is variable space to display the content. When you open up Netflix, you want to efficiently browse through

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Parlaying Failure to Fortune with Paul Martino

http://traffic.libsyn.com/sedaily/PaulMartino.mp3Podcast: Play in new window | Download In 2003, Paul Martino co-founded Tribe.net, one of the earliest social networking sites.  Tribe had significant traction, with hundreds of thousands of users. In the early 2000s, hundreds of thousands of users was enough traffic to pose a company with engineering challenges. Paul had studied computer science, and was able to use his knowledge of high-performance computing to write an efficient graph database,

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Bad Men with Bob Hoffman

http://traffic.libsyn.com/sedaily/BadMen.mp3Podcast: Play in new window | Download In the 1960s, advertising agencies were high-dollar creative producers. A client would come to an ad agency and pay millions of dollars for artistic messaging that would convince a consumer to buy a product. How could you measure the success of these advertising campaigns? Maybe you could see success in the sales data. Maybe people were starting to talk about the product. Ultimately,

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Analyse Asia with Bernard Leong

http://traffic.libsyn.com/sedaily/AnalyseAsia.mp3Podcast: Play in new window | Download In America, the tech companies we focus on are commonly known as FAANG: Facebook, Amazon, Apple, Netflix, Google. We all know what these companies do because they impact our daily lives. In Asia, there are three giant tech companies that have similar scale: Baidu, Alibaba, and Tencent, otherwise known as BAT. Technology within a location is shaped by the pressures of that location.

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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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Serverless Startup with Yan Cui

http://traffic.libsyn.com/sedaily/ServerlessBurningMonk.mp3Podcast: Play in new window | Download After raising $18 million, social networking startup Yubl made a series of costly mistakes. Yubl hired an army of expensive contractors to build out its iOS and Android apps. Drama at the executive level hurt morale for the full-time employees. Most problematic, the company was bleeding cash due to a massive over-investment in cloud services. This was the environment in which Yan Cui

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Quantum Computing with Vijay Pande

http://traffic.libsyn.com/sedaily/VijayPandeQuantum.mp3Podcast: Play in new window | Download Quantum computing is based on the system of quantum mechanics. In quantum computing, we perform operations over qubits instead of bits. A qubit is a vector, which can take on many more values than 0 or 1. The technology used to implement quantum computers is advancing such that it has its own Moore’s Law, but it can also leverage the classical advancements of

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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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Culture Fit with Ammon Bartram

http://traffic.libsyn.com/sedaily/CultureFit.mp3Podcast: Play in new window | Download “Culture fit” is a term that is used to describe engineers that have the right personality for a given company. In the hiring process, “lack of culture fit” is used to turn away engineers who are good enough at coding but just don’t seem right for the company. As today’s guest Ammon Bartram says, “lack of culture fit” usually means “lack of enthusiasm

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Computer Logic with Chris Dixon

http://traffic.libsyn.com/sedaily/ChrisDixon.mp3Podcast: Play in new window | Download The history of computing can be thought of as a series of ideas rather than objects. From Aristotle’s formalization of the syllogism, to Alan Turing’s model for an all-purpose computing machine, to Satoshi Nakamoto’s distributed transaction ledger–these breakthroughs did not come in the form of polished, tangible objects. In fact, the objects which end up changing computing fundamentally are often built from ideas

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Search Engine Land with Danny Sullivan

http://traffic.libsyn.com/sedaily/SearchEngineLand.mp3Podcast: Play in new window | Download Search engines run our lives. The path we take to information is dictated by Google, Facebook, Amazon, and other forms of search. Search engines feel objective and truthful, but are built through ongoing experimentation and subjective decision making. That’s what has kept Danny Sullivan writing about search engines for twenty years. The content Google prioritizes, the ads that we see, the way that

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Google Early Days with John Looney

http://traffic.libsyn.com/sedaily/googleearlydays_edited.mp3Podcast: Play in new window | Download John Looney spent more than 10 years at Google. He started with infrastructure, and was part of the team that migrated Google File System to Colossus, the successor to GFS. Imagine migrating every piece of data on Google from one distributed file system to another. In this episode, John sheds light on the engineering culture that has made Google so successful. He has

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Off-Grid Social Network with Andre Staltz

http://traffic.libsyn.com/sedaily/Scuttlebutt.mp3Podcast: Play in new window | Download Social networks like Facebook and Twitter facilitate interactions between individuals. Every message I send to you on Facebook goes through Facebook’s servers before reaching you. This is known as the client-server model. Since the early days of the internet, engineers have always envisioned a peer-to-peer model, where I could communicate to you directly, without a company brokering that relationship. Andre Staltz works on

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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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CRISPR with Geoff Ralston

http://traffic.libsyn.com/sedaily/crispr_edited.mp3Podcast: Play in new window | Download CRISPR is a technique for altering the human genome. It might be the most powerful tool for biological modification that we have ever discovered. In this episode, we explore CRISPR: how it works, why it exists in the natural world, and the implications for being able to modify DNA so easily. Geoff Ralston is a partner at Y-Combinator. He wrote an article entitled

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Zencastr with Josh Nielsen

http://traffic.libsyn.com/sedaily/ZencastrEngineering.mp3Podcast: Play in new window | Download There are certain experiences when a product solves a problem so thoroughly and elegantly that it lifts a weight off of your shoulders that you didn’t even know was there. Dropbox did this with file storage. Slack did this with group collaboration. Zencastr does this for recording podcasts. Before I used Zencastr to record my podcasts, like most podcasters, I used a Skype

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Data Intensive Applications with Martin Kleppmann

http://traffic.libsyn.com/sedaily/dataintensive_edited_fixed.mp3Podcast: Play in new window | Download A new programmer learns to build applications using data structures like a queue, a cache, or a database. Modern cloud applications are built using more sophisticated tools like Redis, Kafka, or Amazon S3. These tools do multiple things well, and often have overlapping functionality. Application architecture becomes less straightforward. The applications we are building today are data-intensive rather than compute-intensive. Netflix needs to

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Robot Assistant with Abhishek Singh

http://traffic.libsyn.com/sedaily/RobotAssistant.mp3Podcast: Play in new window | Download We view our iPhones as inanimate objects. But when we see robots such as the Boston Dynamics machines that move with a motion that seems like an animal, the robot comes alive. We feel more sympathy and connection towards it. Today’s episode is about the distinction between inanimate machines and machines that seem alive. Peeqo is a robot assistant similar to Amazon Echo

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Facebook Open Source with Tom Occhino

http://traffic.libsyn.com/sedaily/fb_oss_edited_fixed.mp3Podcast: Play in new window | Download Facebook’s open source projects include React, GraphQL, and Cassandra. These projects are key pieces of infrastructure used by thousands of developers–including engineers at Facebook itself. These projects are able to gain traction because Facebook takes time to decouple the projects from their internal infrastructure and clean up the code before releasing them into the wild. Facebook has high standards for what they are

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