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- Nebraska...fails...again. 
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Weekend Highlights RAMSTEIN

Audio example to accompany the October 2022 Sound On Sound magazine article.

No Melodyne

At Made by Google '22, Google unveiled its latest Pixel lineup with the Pixel 7 and Pixel 7 Pro powered by Google's 2nd-gen mobile chip, the Tensor G2, powering more AI and machine learning features like Super Res Zoom, Photo Unblur, Cinematic Blur. Also announced was Google's first smartwatch, the Google Pixel Watch, with Fitbit's health and fitness expertise, and shared some details on the Pixel Tablet with a charging speaker dock coming in 2023. 
Hosts: <a href="https://twit.tv/people/leo-laporte">Leo Laporte</a> and <a href="https://twit.tv/people/ron-richards">Ron Richards</a> 
Download or subscribe to this show at <a href="https://twit.tv/shows/twit-news">https://twit.tv/shows/twit-news</a>. 
Get episodes ad-free with Club TWiT at <a href="https://twit.tv/clubtwit" rel="payment">https://twit.tv/clubtwit</a>

TWiT News 386: Made by Google 2022

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Ezekiel: Tecnica VIP

In 1977, a mild-mannered aeronautical engineer sideswiped a parked car in Compton, CA. He stopped his car to see the damage, and all of a sudden a man opened his car door, and jumped in the car. He said, "I'm about to save your life." What happened next would torture him for the rest of his life.

Ep 11: I'm About to Save Your Life

The Feynman Series (Part 5) - Think Like A Martian

In November 1986, aged just 20, Mike Tyson became the youngest heavyweight boxing champion of all time. Tyson came from a troubled upbringing in New York and only found a direction in life when he met the legendary trainer, Cus D'Amato. But, after D'Amato's death, Tyson's career was marred by a rape conviction and an ongoing battle with drink and drugs. He talks to the BBC Boxing Correspondent, Mike Costello.



PHOTO: Mike Tyson on the way to his first world heavyweight title (Getty Images) Published on November 19, 2016.

Mike Tyson

There’s a woman who made modern software possible. Here’s her story.

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Grace Hopper: The Life Of A Coding Pioneer

Steven Q-Beatz Kubie
If U Like It
Produced by Steven Q-Beatz Kubie for Steven Kubie Productions LLC

Steven Q-Beatz - If U Like It (Prod. By Steven Q-Beatz)

In this episode of the Data Show, I spoke with Guillaume Chaslot, an ex-YouTube engineer and founder of AlgoTransparency, an organization dedicated to helping the public understand the profound impact algorithms have on our lives. We live in an age when many of our interactions with companies and services are governed by algorithms. At a time when their impact continues to grow, there are many settings where these algorithms are far from transparent. There is growing awareness about the vast amounts of data companies are collecting on their users and customers, and people are starting to demand control over their data. A similar conversation is starting to happen about algorithms—users are wanting more control over what these models optimize for and an understanding of how they work.

I first came across Chaslot through a series of articles about the power and impact of YouTube on politics and society. Many of the articles I read relied on data and analysis supplied by Chaslot. We talked about his work trying to decipher how YouTube’s recommendation system works, filter bubbles, transparency in machine learning, and data privacy.

The Importance of Transparency and User Control in Machine Learning

O'Reilly Media spreads the knowledge of innovators. At O’Reilly, a big part of our business is paying attention to what’s new and interesting in the world of technology. We have a pretty good record at having anticipated some of the big technology developments in recent history. For instance, we launched the first commercial Web site, GNN, in 1993; we organized the meeting at which the term “open source” was first adopted; we were early investors in Blogger, which helped launch the blogging revolution; and more recently, our Web 2.0 conference launched a world-wide meme. We call this predictive sense the “O’Reilly Radar.” And while we’re certainly not always right, we are, at least, good at making interesting guesses.

Our methodology is simple: we draw from the wisdom of the alpha geeks in our midst, paying attention to what’s interesting to them, amplifying these weak signals, and seeing where they fit into the innovation ecology. Add to that the original research conducted by our Research team, and you start to get a good picture of what the technology world is thinking about.

The Importance of Transparency and User Control in Machine Learning

O'Reilly Radar