AI Podcast: Margot Gerritsen’s Got Binders Full of Women in Data Science — and She’s Serious

This week’s AI Podcast guest is a renaissance woman with a special passion for data science.

Margot Gerritsen is senior associate dean for educational affairs and professor of energy resources engineering at Stanford University. She’s the co-founder and co-director of the organization Women in Data Science (WiDS). And she’s the host of the WiDS podcast.

Gerritsen spoke to AI Podcast host Noah Kravitz about WiDS, the projects she’s overseeing at Stanford, and what she’s excited about in the current era of data science: the democratization of data.

Gerritsen sees today’s vast quantities of data, open source code and computational power as a “perfect storm” for groundbreaking analytical work.

Key Points From This Episode:

  • The idea for WiDS was born during a conversation at Stanford’s Coupa Cafe, in which Gerritsen lamented the lack of female speakers at technology conferences and was inspired to take action.
  • WiDS hosted its major technical conference at Stanford earlier this month. Conference sessions are available to watch for free. This event is traditionally followed by a series of over 150 regional events across the world through the month of March.

Tweetables:

“We wanted to create binders of women in data science so that we could help promote them, and that’s a very serious thing because we want to make sure that these women who are making outstanding contributions are being seen, and listened to.” — Margot Gerritsen [3:23]

“You know, when you can use your data skills and your modeling and simulation skills to come up with better policies — that’s the golden spot. That’s the best place to be.” — Margot Gerritsen [30:50]

You Might Also Like

AI4Good: Canadian Lab Empowers Women in Computer Science

Doina Precup, an associate professor at McGill University and research team lead at AI startup DeepMind, speaks about the AI4Good Lab she co-founded to give women more access to machine learning training.

Entrepreneur Brings GPUs to Fashion

Pinar Yanardag, a postdoctoral research associate at MIT Media Lab, talks about her innovative project at the MIT Media Lab that’s producing a host of AI-inspired creations, including AI fashion.

Pod Squad: Descript Uses AI to Make Managing Podcasts Quicker, Easier

Serial entrepreneur Andrew Mason is making podcast editing easier and more collaborative with his company, Descript Podcast Studio, which uses AI, natural language processing and automatic speech synthesis.

Tune in to the AI Podcast

Get the AI Podcast through iTunes, Google Podcasts, Google Play, Castbox, DoggCatcher, Overcast, PlayerFM, Pocket Casts, Podbay, PodBean, PodCruncher, PodKicker, Soundcloud, Spotify, Stitcher and TuneIn. If your favorite isn’t listed here, drop us a note.

Tune in to the Apple Podcast Tune in to the Google Podcast Tune in to the Spotify Podcast

Make the AI Podcast Better

Have a few minutes to spare? Fill out this listener survey. Your answers will help us make a better podcast.

The post AI Podcast: Margot Gerritsen’s Got Binders Full of Women in Data Science — and She’s Serious appeared first on The Official NVIDIA Blog.

Keeping an Eye on AI: Building Ethical Technology at Salesforce

Kathy Baxter, the architect of the ethical AI practice at Salesforce, is helping her team and clients create more responsible technology. To do so, she supports employee education, the inclusion of safeguards in Salesforce technology, and collaboration with other companies to improve ethical AI across industries.

Baxter spoke with AI Podcast host Noah Kravitz about her role at the company, a position she helped create as the need for AI ethicists became apparent.

She’s helped construct practices such as release readiness planning, in which teams brainstorm any potential unintended negative consequences, along with ways to mitigate them.

In the future, Baxter predicts more global policies that will help companies define ethical AI and guide them in creating responsible technology.

Kathy Baxter, architect of ethical AI at Salesforce.

Key Points From This Episode:

  • There are several ways to correct bias in AI. This includes making edits to the training data or editing the model itself (for example, not using race or gender as a factor).
  • Einstein is Salesforce’s AI platform. The company implements in-app guidance through a feature called Einstein Discovery. One of its functions is to alert users when they might be using sensitive variables such as age, race or gender. Administrators can also select the variables they don’t want to include in their model, to avoid accidental bias.

Tweetables:

“We have to understand that everything that we build and bring into society has an impact,” — Kathy Baxter [2:29]

“One of the magical things about AI is that we can become aware of biases that we might not have known even existed in our business processes in the first place.” — Kathy Baxter [10:18]

You Might Also Like

How Federated Learning Can Help Keep Data Private

Walter De Brouwer, CEO of Doc.ai — a company building a medical research platform that addresses the issue of data privacy with federated learning — talks about the complications of putting data to work in industries such as healthcare.

Good News About Fake News: AI Can Now Help Detect False Information

If only there was a way to filter the fake news from the real. Thanks to Vagelis Papalexakis, a professor of computer science at the University of California, Riverside, there is. He discusses his algorithm that can detect fake news with 75 percent accuracy.

Teaching Families to Embrace AI

Tara Chklovski is CEO and founder of Iridescent, a nonprofit that provides access to hands-on learning opportunities to prepare underrepresented children and adults for the future of work. She talks about Iridescent, the UN’s AI for Good Global Summit and the AI World Championship — part of the AI Family Challenge.

Tune In to the AI Podcast

Get the AI Podcast through iTunesGoogle PodcastsGoogle PlayCastbox, DoggCatcher, OvercastPlayerFM, Pocket Casts, PodbayPodBean, PodCruncher, PodKicker, SoundcloudSpotifyStitcher and TuneIn.

Listen on Apple Podcast Listen on Google Podcast Listen on Spotify Podcast

Make Our Podcast Better

Have a few minutes to spare? Fill out this short listener survey. Your answers will help us make a better podcast.

The post Keeping an Eye on AI: Building Ethical Technology at Salesforce appeared first on The Official NVIDIA Blog.

An AI for Detail: Nanotronics Brings Deep Learning to Precision Manufacturing

Matthew Putman, this week’s guest on the AI Podcast, knows that the devil is in the details. That’s why he’s the co-founder and CEO of Nanotronics, a Brooklyn-based company providing precision manufacturing enhanced by AI, automation and 3D imaging.

He sat down with AI Podcast host Noah Kravitz to discuss how running deep learning networks in real-time on factory floors produces the best possible products, and how Nanotronics models and equipment are finding success in fields ranging from the semiconductor industry to genome sequencing.

SUBHEAD: Key Points From This Episode:

Nanotronics develops universal AI models that can be customized depending on individual customers’ processes and deployments.

The AI models that Nanotronics deploys at a customer site can be communicated directly from the GPU to the machine, without the cloud, to ensure security and speed.

When the new Nanotronics factory is finished (pictured, above), they’ll use their own deep learning models to ensure precision manufacturing as they construct their equipment.

Tweetables:

  • “It’s a great advantage to our customers to actually have a smaller footprint because we have a computationally driven system, rather than a system that requires a lot of very expensive large hardware” — Matthew Putman [7:14]
  • “We can adjust actual controls in real time to make corrective actions for any type of anomalies that occur. It’s not so important to us what the absolute value is on each of the stations, it’s that by the end, the product has the most reproducibility and highest quality possible” Matthew Putman [8:47]

You Might Also Like

No More Trying Taxes: Intuit Uses AI for Smarter Finances

As tax season looms closer, listen to Intuit Senior Vice President and Chief Data Officer Ashok Srivastava as he explains how the personal finance giant utilizes AI to help customers.

UC Berkeley’s Pieter Abbeel on How Deep Learning Will Help Robots Learn

Pieter Abbeel, director of the Berkeley Robot Learning Lab and cofounder of deep learning and robotics company Covariant AI, discusses how AI is the key to producing more efficient and natural robots.

Astronomers Turn to AI as New Telescopes Come Online

As our view of the skies improves, astronomers are accumulating more data than they can process. Brant Robertson, visiting professor at the Institute for Advanced Study in Princeton, explains how AI can transform data into discoveries.

Tune in to the AI Podcast

Get the AI Podcast through iTunesGoogle PodcastsGoogle PlayCastbox, DoggCatcher, OvercastPlayerFM, Pocket Casts, PodbayPodBean, PodCruncher, PodKicker, SoundcloudSpotifyStitcher and TuneIn.

  

Make Our Podcast Better

Have a few minutes to spare? Fill out this short listener survey. Your answers will help us make a better podcast.

The post An AI for Detail: Nanotronics Brings Deep Learning to Precision Manufacturing appeared first on The Official NVIDIA Blog.

NVIDIA’s Neda Cvijetic Explains the Science Behind Self-Driving Cars

What John Madden was to pro football, Neda Cvijetic is to autonomous vehicles. No one’s better at explaining the action, in real time, than Cvijetic.

Cvijetic, senior manager of autonomous vehicles at NVIDIA, drives our NVIDIA DRIVE Labs series of videos and blogs breaking down the science behind autonomous vehicles.

A Serbian-American electrical engineer, Cvijetic seems destined for this role. She literally grew up in the shadow of Nikola Tesla. His statue in Belgrade stood across the street from her childhood home.

On this week’s AI Podcast, Cvijetic spoke to host Rick Merritt about what’s driving autonomous vehicles. She also shared her perspective on how both broad initiatives and day-to-day actions can promote diversity in AI.

 Key Points From This Episode:

  • Autonomous vehicles use three key techniques: perception, localization, and control and planning.
  • Each self-driving car runs on dozens of deep neural networks, which are each trained on thousands of hours of real-world driving data and on NVIDIA DRIVE Constellation, which provides extensive testing in virtual reality before the car even hits the road.
  • Autonomous vehicles drive safely because diversity and redundancy are designed into their systems. Multiple cameras with overlapping fields of view, radar, and more provide a wealth of perception data for the highest level of accuracy.

Tweetables:

“I want every driver out there to feel that they understand AI, to understand how AI works in self-driving cars, and feel empowered by that understanding” — Neda Cvijetic [1:56]

“The NVIDIA DRIVE simulator seeks to create some of these corner cases that might take years to actually observe” — Neda Cvijetic [10:36]

You Might Also Like

Deep Learning 101: Will Ramey, NVIDIA Senior Manager for GPU Computing

If you’ve ever wanted a guided tour through the history of AI, this is the episode for you. NVIDIA’s Will Ramey covers the big bang of AI and the concepts that are now defining the industry.

How AI Turns Kiddie Cars Into Fast and Frugal Autonomous Racers

Take brains, a few hundred bones and a pink Barbie jeep. What have you got? For inventive hackers, a new sport filled with f-words — fast, furious, frugal. Founder of the Power Racing Series Jim Burke talks about why he’s bringing autonomous vehicles to a racing event built on the backs of $500 kiddie cars.

AutoX’s Professor X on the State of Automotive Autonomy

Jianxiong Xiao, CEO of startup AutoX, is speeding towards fully autonomous vehicles, as defined by the National Highway Traffic Administration. Ranging from level 0, or no automation, to level 5, full autonomy, Xiao is pursuing level 4 — a car that can perform all driving functions under certain conditions.

 

Tune in to the AI Podcast

Get the AI Podcast through iTunesGoogle PodcastsGoogle PlayCastbox, DoggCatcher, OvercastPlayerFM, Pocket Casts, PodbayPodBean, PodCruncher, PodKicker, SoundcloudSpotifyStitcher and TuneIn.

  

Make Our Podcast Better

Have a few minutes to spare? Fill out this short listener survey. Your answers will help us make a better podcast.

The post NVIDIA’s Neda Cvijetic Explains the Science Behind Self-Driving Cars appeared first on The Official NVIDIA Blog.

AI’s Mild Ride: RoadBotics Puts AI on Pothole Patrol

National Pothole Day is Jan. 15. Its timing is no accident.

All over the Northern hemisphere, potholes are at their suspension-wrecking, spine-shaking worst this month.

Thanks to AI, one startup is working all year long to alleviate this menace. Benjamin Schmidt, president and co-founder of RoadBotics, is using the tech to pave the way to better roads.

His startup is identifying areas at risk of potholes, so city governments can improve roads before damage worsens.

Schmidt spoke with AI Podcast host Noah Kravitz about how RoadBotics is working with over 160 governments across the world to collect and analyze video data to improve preventative maintenance.

 Key Points From This Episode:

  • Using smartphones placed against car windshields, RoadBotics collects and analyzes video data to assign each road a score, which local governments can use to inform infrastructure decisions.
  • RoadBotics protects privacy by blurring people, cars and other sensitive data so only roads are analyzed.
  • Early this year, RoadBotics will be release an app so anyone can use smartphones to collect data and submit to their neural network to help improve analysis.

Tweetables:

“The sooner you can detect [surface distresses], the sooner you can put a cheaper intervention in now that really just saves the life of the road.” — Benjamin Schmidt [5:00]

“RoadBotics was founded at exactly the right moment with the right tech, the right hardware. So we’re now in this sweet spot where we can actually deploy a solution” — Benjamin Schmidt [6:46]

You Might Also Like

How Deep Learning Will Reshape Our Cities

Lynn Richards, president and CEO of the Congress for New Urbanism, and Charles Marohn, president and co-founder of Strong Towns, weigh in on the benefits of using AI to design cities, and simulating designs in VR prior to construction.

How AI Will Revolutionize Driving

Danny Shapiro, senior director of automotive at NVIDIA, explains the capabilities necessary for autonomous driving, from object detection to AI to high performance computing.

Where Is Deep Learning Going Next?

Bryan Catanzaro, head of applied deep learning research at NVIDIA, explains his journey in AI from UC Berkeley, to Baidu, to NVIDIA. He’s striving for AI that works so seamlessly that users don’t even notice it, and he explains how GPUs are helping to make that happen.

Featured image credit: Santeri Viinamäki, some rights reserved.

The post AI’s Mild Ride: RoadBotics Puts AI on Pothole Patrol appeared first on The Official NVIDIA Blog.

Saved by the Spell: Serkan Piantino’s Company Makes AI for Everyone

Spell, founded by Serkan Piantino, is making machine learning as easy as ABC.

Piantino, CEO of the New York-based startup and former director of engineering for Facebook AI Research, explained to AI Podcast host Noah Kravitz how he’s bringing compute power to those that don’t have easy access to GPU clusters.

Spell provides access to hardware as well as a software interface that accelerates execution. Piantino reported that a wide variety of industries has shown interest in Spell, from healthcare to retail, as well as researchers and academia.

Key Points From This Episode

  • Spell’s basic tool is a command line, which has users type “spell run” before code that they previously would’ve run locally. Spell will then snapshot the code, find any necessary data and move that computation onto relevant hardware in the cloud.
  • Spell’s platform provides a collaborative workspace in which clients within an organization can work together on their Jupyter Notebooks and Labs.
  • Users can choose what type of GPU they require for their machine learning experiment, and Spell will run it on the corresponding hardware in the cloud.

Tweetables

“You know there’s some upfront cost to running an experiment, but if you get that cost down low enough, it disappears mentally” — Serkan Piantino [11:52]

“Providing access to hardware and making things easier — giving everybody the same sort of beautiful compute cluster that giant research organizations work on — was a really powerful idea” — Serkan Piantino [18:36]

You Might Also Like

NVIDIA Chief Scientist Bill Dally on How GPUs Ignited AI, and Where His Team’s Headed Next

Deep learning icon and NVIDIA Chief Scientist Bill Dally reflects on his career in AI and offers insight into the AI revolution made possible by GPU-driven deep learning. He shares his predictions on where AI is going next: more powerful algorithms for inference, and neutral networks that can train on less data.

Speed Reader: Evolution AI Accelerates Data Processing with AI

Across industries, employees spend valuable time processing mountains of paperwork. Evolution AI, a U.K. startup and NVIDIA Inception member, has developed an AI platform that extracts and understands information rapidly. Evolution AI Chief Scientist Martin Goodson explains the variety of problems that the company can solve.

Striking a Chord: Anthem Helps Patients Navigate Healthcare with Ease

Health insurance company Anthem helps patients personalize and better understand their healthcare information through AI. Rajeev Ronanki, senior vice president and chief digital officer at Anthem, explains how the company gives users the opportunity to schedule video consultations and book doctor’s appointments virtually.

Tune in to the AI Podcast

Get the AI Podcast through iTunesGoogle PodcastsGoogle PlayCastbox, DoggCatcher, OvercastPlayerFM, Pocket Casts, PodbayPodBean, PodCruncher, PodKicker, SoundcloudSpotifyStitcher and TuneIn.

  

Make Our Podcast Better

Have a few minutes to spare? Fill out this short listener survey. Your answers will help us make a better podcast.

The post Saved by the Spell: Serkan Piantino’s Company Makes AI for Everyone appeared first on The Official NVIDIA Blog.

Playing Pod: Our Top 5 AI Podcast Episodes of 2019

If it’s worth doing, it’s worth doing with AI.

2019 was the year deep-learning driven AI made the leap from the rarefied world of elite computer scientists and the world’s biggest web companies to the rest of us.

Everyone from startups to hobbyists to researchers are picking up powerful GPUs and putting this new kind of computing to work. And they’re doing amazing things.

And with NVIDIA’s AI Podcast, now in its third year, we’re bringing the people behind these wonders to more listeners than ever, with the podcast reaching more than 650,000 downloads in 2019.

Here are the episodes that were listener favorites in 2019.

A Man, a GAN, and a 1080 Ti: How Jason Antic Created ‘De-Oldify’

You don’t need to be an academic or to work for a big company to get into deep learning. You can just be a guy with a NVIDIA GeForce 1080 Ti and a generative adversarial network. Jason Antic, who describes himself as “a software guy,” began digging deep into GANs. Next thing you know, he’s created an increasingly popular tool that colors old black-and-white shots. Interested in digging into AI for yourself? Listen and get inspired.

Sort Circuit: How GPUs Helped One Man Conquer His Lego Pile

At some point in life, every man faces the same great challenge: sorting out his children’s Lego pile. Thanks to GPU-driven deep learning, Francisco “Paco” Garcia is one of the few men who can say they’ve conquered it. Here’s how.

UC Berkeley’s Pieter Abbeel on How Deep Learning Will Help Robots Learn

Robots can do amazing things. Compare even the most advanced robots to a three-year-old, however, and they can come up short. UC Berkeley Professor Pieter Abbeel has pioneered the idea that deep learning could be the key to bridging that gap: creating robots that can learn how to move through the world more fluidly and naturally. We caught up with Abbeel, who is director of the Berkeley Robot Learning Lab and cofounder of Covariant AI, a Bay Area company developing AI software that makes it easy to teach robots new and complex skills, at GTC 2019.

How the Breakthrough Listen Harnessed AI in the Search for Aliens

UC Berkeley’s Gerry Zhang talks about his work using deep learning to analyze signals from space for signs of intelligent extraterrestrial civilizations. And while we haven’t found aliens, yet, the doctoral student has already made some extraordinary discoveries.

How AI Helps GOAT Keep Sneakerheads a Step Ahead

GOAT Group helps sneaker enthusiasts get their hands on authentic Air Jordans, Yeezys and a variety of old-school kicks with the help of AI. Michael Hall, director of data at GOAT Group, explains how in a conversation with AI Podcast host and raging sneakerhead Noah Kravitz.

Tune in to the AI Podcast

We’re available through iTunesGoogle Play MusicGoogle PodcastsCastboxCastro, DoggCatcher, OvercastPodbayPocket Casts, PodCruncher, PodKicker, SpotifyStitcher and Soundcloud. If your favorite isn’t listed here, drop us a note.

  The AI Podcast SpotifyThe AI Podcast Google Podcasts The AI Podcast Apple Podcasts

Make the AI Podcast Better

Have a few minutes to spare? Fill out this listener survey. Your answers will help us make a better podcast.

The post Playing Pod: Our Top 5 AI Podcast Episodes of 2019 appeared first on The Official NVIDIA Blog.

Pod Squad: Descript Uses AI to Make Managing Podcasts Quicker, Easier

You can’t have an AI podcast and not interview someone using AI to make podcasts better.

That’s why we reached out to serial entrepreneur Andrew Mason to talk to him about what he’s doing now. His company, Descript Podcast Studio, uses AI, natural language processing and automatic speech synthesis to make podcast editing easier and more collaborative.

Mason, Descript’s CEO and perhaps best known as Groupon’s founder, spoke with AI Podcast host Noah Kravitz about his company and the newest beta service it offers, called Overdub.

 

Key Points From This Episode

  • Descript works like a collaborative word processor. Users record audio, which Descript converts to text. They can then edit and rearrange text, and the program will change the audio.
  • Overdub, created in collaboration with Descript’s AI research division, eliminates the need to re-record audio. Type in new text, and Overdub creates audio in the user’s voice.
  • Descript 3.0 launched in November, adding new features such as a detector that can identify and remove vocalized pauses like “um” and “uh” as well as silence.

Tweetables

“We’re trying to use AI to automate the technical heavy lifting components of learning to use editors — as opposed to automating the craft — and we leave space for the user to display and refine their craft” — Andrew Mason [07:10]

“What’s really unique to us is a kind of tonal or prosodic connecting of the dots, where we’ll analyze the audio before and after whatever you’re splicing in with Overdub, and make sure that it sounds continuous in a natural transition” — Andrew Mason [10:30]

You Might Also Like

The Next Hans Zimmer? How AI May Create Music for Video Games, Exercise Routines

Imagine Wolfgang Amadeus Mozart as an algorithm or the next Hans Zimmer as a computer. Pierre Barreau and his startup, Aiva Technologies, are using deep learning to compose music. Their algorithm can create a theme in four minutes flat.

How Deep Learning Can Translate American Sign Language

Rochester Institute of Technology computer engineering major Syed Ahmed, a research assistant at the National Technical Institute for the Deaf, uses AI to translate between American sign language and English. Ahmed trained his algorithm on 1,700 sign language videos.

Tune in to the AI Podcast

Get the AI Podcast through iTunesGoogle PodcastsGoogle PlayCastbox, DoggCatcher, OvercastPlayerFM, Pocket Casts, PodbayPodBean, PodCruncher, PodKicker, SoundcloudSpotifyStitcher and TuneIn.

  

Make Our Podcast Better

Have a few minutes to spare? Fill out this short listener survey. Your answers will help us make a better podcast.

The post Pod Squad: Descript Uses AI to Make Managing Podcasts Quicker, Easier appeared first on The Official NVIDIA Blog.

Speaking the Same Language: How Oracle’s Conversational AI Serves Customers

At Oracle, customer service chatbots use conversational AI to respond to consumers with more speed and complexity.

Suhas Uliyar, vice president for product management for digital assistance and AI at Oracle, stopped by to talk to AI Podcast host Noah Kravitz about how the newest wave of conversational AI can keep up with the nuances of human conversation.

Many chatbots frustrate consumers because of their static nature. Asking a question or using the wrong keyword confuses the bot and prompts it to start over or make the wrong selection.

Uliyar says that Oracle’s digital assistant uses a sequence-to-sequence algorithm to understand the intricacies of human speech, and react to unexpected responses.

Their chatbots can “switch the context, keep the memory, give you the response and then you can carry on with the conversation that you had. That makes it natural, because we as humans fire off on different tangents at any given moment.”

Key Points From This Episode:

  • The contextual questions that often occur in normal conversation stump single-intent systems, but the most recent iteration is capable of answering simple questions quickly and remembering customers.
  • The next stage in conversational AI, Uliyar believes, will allow bots to learn about users in order to give them recommendations or take action for them.
  • Learn more about Oracle’s digital assistant for enterprise applications and visit Uliyar’s Twitter.

Tweetable

“If machine learning is the rocket that’s going to take us to the next level, then data is the rocket fuel.” — Suhas Uliyar [15:59]

You Might Also Like

Charter Boosts Customer Service with AI

Jared Ritter, the senior director of wireless engineering at Charter Communications, describes their innovative approach to data collection on customer feedback. Rather than retroactively accessing the data to fix problems, Charter uses AI to evaluate data constantly to predict issues and address them as early as possible.

Using Deep Learning to Improve the Hands-Free, Voice Experience

What would the future of intelligent devices look like if we could bounce from using Amazon’s Alexa to order a new book to Google Assistant to schedule our next appointment, all in one conversation? Xuchen Yao, the founder of AI startup KITT.AI, discusses the toolkit that his company has created to achieve a “hands-free” experience.

AI-Based Virtualitics Demystifies Data Science with VR

Aakash Indurkha, head of machine learning projects at AI-based analytics platform Virtualitics, explains how the company is bringing creativity to data science using immersive visualization. Their software bridges the gap created by a lack of formal training to help inexperienced users identify anomalies on their own, and gives experts the technology to demonstrate their complex calculations.

Make Our Podcast Better

Have a few minutes to spare? Fill out this short listener survey. Your answers will help us make a better podcast.

The post Speaking the Same Language: How Oracle’s Conversational AI Serves Customers appeared first on The Official NVIDIA Blog.

AI4Good: Canadian Lab Empowers Women in Computer Science

Doina Precup is applying Romanian wisdom to the gender gap in the fields of AI and computer science.

The associate professor at McGill University and research team lead at AI startup DeepMind spoke with AI Podcast host Noah Kravitz about her personal experiences, along with the AI4Good Lab she co-founded to give women more access to machine learning training.

Growing up in Romania, Precup attended a high school that specialized in computer science and a technical university. She didn’t experience gender disparity in these learning environments.

“If anything, programming was considered a very good job for women, because you did not need to be working in the fields,” she explained.\

It made the gap in Canadian universities and companies even more noticeable. At McGill, Precup saw that female students were hesitant to speak up or pursue graduate studies.

Together with Angelique Mannella, CEO of AM Consulting and an Amazon employee, Precup was inspired to start the AI4Good Lab in 2017.

Key Points From This Episode:

  • Aimed at improving women’s access to advanced AI and machine learning, the AI4Good Lab brings together 30 women from across Canada every spring for a seven-week workshop
  • Workshop participants take classes, hear from speakers, visit companies and work in small groups to create projects.
  • This year’s projects ranged from identifying fake news to using a caf ’s food supplies efficiently to helping people manage chronic pain.
  • To hear Precup’s best sci-fi book recommendations, listen to the podcast for her guide to the genre.
  • Visit the AI4Good Lab website or Twitter to learn more about participants’ projects and to apply to next year’s workshop. And visit Precup’s Google Scholar page to see her most recent publications.

Tweetables:

“Emphasizing the creativity and the fun in computer science and algorithms is really important, for everybody” — Doina Precup [04:30]

“I also noticed that people were sometimes afraid to speak up in classes, even if they were really good at based on their exams and their assignments and their projects” — Doina Precup [05:43]

You Might Also Like

UC Berkeley’s Pieter Abbeel on How Deep Learning Will Help Robots Learn

Robots can do amazing things. Compare even the most advanced robots to a three-year-old, however, and they can come up short. UC Berkeley Professor Pieter Abbeel has pioneered the idea that deep learning could be the key to bridging that gap: creating robots that can learn how to move through the world more fluidly and naturally.

Teaching Families to Embrace AI

Tara Chklovski is CEO and founder of Iridescent, a nonprofit that provides access to hands-on learning opportunities to prepare underrepresented children and adults for the future of work. We spoke with her about the UN’s AI for Good Global Summit last May in Geneva and the AI World Championship, part of the AI Family Challenge, also in May in Silicon Valley.

Good News About Fake News: AI Can Now Help Detect False Information

With “fake news” embedding itself into, well, our news, it’s become more important than ever to distinguish between content that is fake or authentic. That’s why Vagelis Papalexakis, a professor of computer science at the University of California, Riverside, developed an algorithm that detects fake news with 75 percent accuracy.

Make Our Podcast Better

Have a few minutes to spare? Fill out this short listener survey. Your answers will help us make a better podcast.

 

The post AI4Good: Canadian Lab Empowers Women in Computer Science appeared first on The Official NVIDIA Blog.