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4 episodes with Hilary Mason
2 episodes with Hilary Mason
2 episodes with Hilary Mason
2 episodes with Hilary Mason
2 episodes with Hilary Mason
2 episodes with Hilary Mason
3 episodes with Hilary Mason
2 episodes with Hilary Mason
2 episodes with Hilary Mason
Hilary Mason is a world-builder. She's a serial entrepreneur, machine learning expert, and now, as the founder and CEO of Hidden Door, she's creating immersive experiences where fans can interact with their favorite characters from books and movies. The choose-your-own-adventures style games are an amazing blend of AI and human creativity — and Hilary is passionate about both: “If I write a manifesto, this is what it'll be: I don't think the power of generative AI is to create the next amazing novel. I don't think it's gonna create the next amazing movie. I think it is not opinionated, but people are opinionated and people will create those things using these tools.”On this episode of CRAFTED., we discuss what AI is good at and how to create a great marriage of human and machine. And Hilary is not holding back… “Doing data work without a soul or without philosophy is, at best, meaningless and, at worst, harmful.”“I think prompts are gonna go away. We're in a moment of industry-wide product design, chaos…”Listen for a masterclass on building with AI and building with creativity and soul.(02:00) - – This moment in AI: figuring out the right use cases and design patterns (05:00) - – Founding Hidden Door (09:00) - – Why “controllability” is so important (11:00) - – Enabling fans want to play with their favorite characters (13:00) - – Why text-based games are so great (15:00) - – Behind the scenes of how Hidden Door builds for fun (19:00) - – AI has caused a moment of “industry-wide product design chaos” (23:00) - – Industries and use cases where AI will be really good; where it won't (25:00) - – Effective ways to get beyond AI mediocrity (28:00) - – Why Hilary thinks prompts will soon go away (31:00) - – Hilary's liberal arts background: English + Computer Science (33:00) - – Why we need philosophy and soul along with the data Where to find Hidden Door:https://www.hiddendoor.co/Where to find Hilary Mason:LinkedIn: https://www.linkedin.com/in/hilarymason/X: https://x.com/hmason Where to find Dan Blumberg:Website & newsletter: https://www.crafted.fm LinkedIn: https://www.linkedin.com/in/dblums/X: https://x.com/dblumsCRAFTED. is produced by Modern Product Minds, where CRAFTED. host Dan Blumberg and team can help you take a new product from zero to one... and beyond. We specialize in early stage product discovery, growth, and experimentation. Learn more at modernproductminds.com
Welcome to the ongoing mini-series The Orthogonal Bet. Hosted by Samuel Arbesman, a Complexity Scientist, Author, and Scientist in Residence at Lux Capital. In this episode, he speaks with Hilary Mason, co-founder and CEO of Hidden Door, a startup creating a platform for interactive storytelling experiences within works of fiction. Hilary has also worked in machine learning and data science, having built a machine learning R&D company called Fast Forward Labs, which she sold to Cloudera. She was the chief scientist at Bitly and even a computer science professor. Samuel wanted to talk to Hilary not only because of her varied experiences but also because she has thought deeply about how to use AI productively—and far from naively—in games and other applications. She believes that artificial intelligence, including the current crop of generative AI, should be incorporated thoughtfully into software, rather than used without careful examination of its strengths and weaknesses. Additionally, Samuel, who often considers non-traditional research organizations, was eager to get Hilary's thoughts on this space, given her experience building such an organization. Produced by Christopher Gates Music by George Ko & Suno
Hugo speaks with Vincent Warmerdam, a senior data professional and machine learning engineer at :probabl, the exclusive brand operator of scikit-learn. Vincent is known for challenging common assumptions and exploring innovative approaches in data science and machine learning. In this episode, they dive deep into rethinking established methods in data science, machine learning, and AI. We explore Vincent's principled approach to the field, including: The critical importance of exposing yourself to real-world problems before applying ML solutions Framing problems correctly and understanding the data generating process The power of visualization and human intuition in data analysis Questioning whether algorithms truly meet the actual problem at hand The value of simple, interpretable models and when to consider more complex approaches The importance of UI and user experience in data science tools Strategies for preventing algorithmic failures by rethinking evaluation metrics and data quality The potential and limitations of LLMs in the current data science landscape The benefits of open-source collaboration and knowledge sharing in the community Throughout the conversation, Vincent illustrates these principles with vivid, real-world examples from his extensive experience in the field. They also discuss Vincent's thoughts on the future of data science and his call to action for more knowledge sharing in the community through blogging and open dialogue. LINKS The livestream on YouTube (https://youtube.com/live/-CD66CI1pEo?feature=share) Vincent's blog (https://koaning.io/) CalmCode (https://calmcode.io/) scikit-lego (https://koaning.github.io/scikit-lego/) Vincent's book Data Science Fiction (WIP) (https://calmcode.io/book) The Deon Checklist, an ethics checklist for data scientists (https://deon.drivendata.org/) Of oaths and checklists, by DJ Patil, Hilary Mason and Mike Loukides (https://www.oreilly.com/radar/of-oaths-and-checklists/) Vincent's Getting Started with NLP and spaCy Course course on Talk Python (https://training.talkpython.fm/courses/getting-started-with-spacy) Vincent on twitter (https://x.com/fishnets88) :probabl. on twitter (https://x.com/probabl_ai) Vincent's PyData Amsterdam Keynote "Natural Intelligence is All You Need [tm]" (https://www.youtube.com/watch?v=C9p7suS-NGk) Vincent's PyData Amsterdam 2019 talk: The profession of solving (the wrong problem) (https://www.youtube.com/watch?v=kYMfE9u-lMo) Vanishing Gradients on Twitter (https://twitter.com/vanishingdata) Hugo on Twitter (https://twitter.com/hugobowne) Check out and subcribe to our lu.ma calendar (https://lu.ma/calendar/cal-8ImWFDQ3IEIxNWk) for upcoming livestreams!
Hidden Door CEO Hilary Mason joins the show today for a chat about how AI integration can augment human creativity in gaming. Hidden Door uses AI to create incredible worlds based on stories that users can interact with and customize. We'll discuss with Hilary how this is possible and the wider ethics of integrating AI into gaming and creativity for technology companies. Join our host Jon Weigell, for an in-depth conversation with Hilary Mason. Grab HubSpot's free AI-Powered Customer Platform and watch your business grow https://clickhubspot.com/cpt Follow us on social media: TikTok: https://www.tiktok.com/@thehustle.co Instagram: https://www.instagram.com/thehustledaily/ Thank You For Listening to The Hustle Daily Show. Don't forget to hit Subscribe or Follow us on Apple Podcasts so you never miss an episode! If you want this news delivered to your inbox, join millions of others and sign up for The Hustle Daily newsletter, here: https://thehustle.co/email/ Plus! Your engagement matters to us. If you are a fan of the show, be sure to leave us a 5-Star Review on Apple Podcasts https://podcasts.apple.com/us/podcast/the-hustle-daily-show/id1606449047 (and share your favorite episodes with your friends, clients, and colleagues).
Welcome back to another episode!! I know I said that the last episode was going to be our last for a while....that's still true but in light of the recent passing of the legendary actor, Donald Sutherland, we decided to replay Ep. 34, Don't Look Now. Don't Look Now is a 1973 thriller/horror/mystery directed by Nicolas Roeg and stars Julie Christie, Donald Sutherland, Hilary Mason, and Clelia Matania. Synopsis: A married couple grieving the recent death of their young daughter are in Venice when they encounter two elderly sisters, one of whom is psychic and brings a warning from beyond. We recorded this back in May of 2021. Enjoy! RIP Donald Sutherland --- Support this podcast: https://podcasters.spotify.com/pod/show/scarymovieandchillpodcast/support
Horror Hangout | Two Bearded Film Fans Watch The 50 Best Horror Movies Ever!
They walk. They talk. They kill.Dolls is a 1987 American horror film directed by Stuart Gordon, written by Ed Naha, and starring Stephen Lee, Guy Rolfe, Hilary Mason, Ian Patrick Williams, and Bunty Bailey. Its plot follows six people who seek shelter during a storm in the mansion of an elderly puppetmaker and his wife, only to find that the various puppets and dolls in the home contain the imprisoned spirits of criminals.00:00 Intro06:10 Horror News 21:28 What We've Been Watching52:12 Film Review2:03:08 Name Game2:08:40 Film Rating2:13:49 OutroPodcast - https://fanlink.tv/horrorhangoutPatreon - https://www.patreon.com/horrorhangoutFacebook - https://www.facebook.com/horrorhangoutpodcastTwitter - https://twitter.com/horror_hangout_TikTok - https://www.tiktok.com/@horrorhangoutpodcastInstagram - https://www.instagram.com/horrorhangoutpodcast/Website - http://www.hawkandcleaver.comBen - https://twitter.com/ben_erringtonAndy - https://twitter.com/AndyCTWritesJohn - https://www.instagram.com/johncrinanwww.johncrinan.comAudio credit - Taj Eastonhttp://tajeaston.comSupport this show http://supporter.acast.com/thehorrorhangout. Hosted on Acast. See acast.com/privacy for more information.
EPISODE 1933: In this special KEEN ON show recorded at the DLD conference in Munich, Andrew talks to the Founder & CEO of Hidden Door, Hilary Mason, who peers behind the hidden door of AI, Gaming and StorytellingHilary Mason is the Founder & CEO of Fast Forward Labs, a machine intelligence research company, and the Data Scientist in Residence at Accel Partners. She co-founded HackNY, and she is a member of NYC Resistor.Named as one of the "100 most connected men" by GQ magazine, Andrew Keen is amongst the world's best known broadcasters and commentators. In addition to presenting KEEN ON, he is the host of the long-running How To Fix Democracy show. He is also the author of four prescient books about digital technology: CULT OF THE AMATEUR, DIGITAL VERTIGO, THE INTERNET IS NOT THE ANSWER and HOW TO FIX THE FUTURE. Andrew lives in San Francisco, is married to Cassandra Knight, Google's VP of Litigation & Discovery, and has two grown children.
In this last episode of 2023, Lightspeed Partner and host Michael Mignano takes a look back at the first ten episodes of Generative Now to share a few favorite moments. Episode Chapters(00:00) Introduction (00:41) Connor Zwick on sneaking into early Berkeley courses on AI (04:08) Max Child on being first to a new platform (07:49) Gaurav Misra on how product market fit and a surprise $500k changed their business plan (15:19) Hilary Mason on the nuanced definitions in AI (20:57) Victor Riparbelli on the new paradigm AI can bring into being (23:58) Scott Belsky on his AI “aha” moment Stay in touch: www.lsvp.com X: https://twitter.com/lightspeedvp LinkedIn: https://www.linkedin.com/company/lightspeed-venture-partners/ Instagram: https://www.instagram.com/lightspeedventurepartners/ Subscribe on your favorite podcast app: generativenow.co Email: generativenow@lsvp.com The content here does not constitute tax, legal, business or investment advice or an offer to provide such advice, should not be construed as advocating the purchase or sale of any security or investment or a recommendation of any company, and is not an offer, or solicitation of an offer, for the purchase or sale of any security or investment product. For more details please see lsvp.com/legal.
Today, we're bringing you a special mini episode led by TechCrunch senior reporter and co-host of our sister podcast, Found, Dominic Madori-Davis. During this year's Disrupt, Dom caught up with Hilary Mason from Hidden Door, an AI-driven narrative game engine. Dom and Hilary got into how generative AI is changing online gaming, building a team of creatives, fundraising in the gaming space, and more.Connect with Equity on X and Threads @EquityPods, and keep up with all of TechCrunch's podcasts @TechCrunchPods on TikTok.For episode transcripts and more, head to Equity's Simplecast website.Equity drops at 7 a.m. PT every Monday, Wednesday and Friday, so subscribe to us on Apple Podcasts, Overcast, Spotify and all the casts. TechCrunch also has a great show on crypto, a show that interviews founders and more! Credits: Equity is hosted by Editor in Chief of TechCrunch+ Alex Wilhelm and TechCrunch Senior Reporter Mary Ann Azevedo. We are produced by Theresa Loconsolo with editing by Kell. Bryce Durbin is our Illustrator. We'd also like to thank the audience development team and Henry Pickavet, who manages TechCrunch audio products.
Hilary Mason was on the ground floor of data science research, and now she's bringing that same pioneering spirit to generative AI. For this episode, Host and Partner at Lightspeed, Michael Mignano, talks with Hilary about how to safeguard probabilistic systems and how researchers and founders can form the most effective teams. Episode Chapters (00:00) - Intro (05:18) - A founder's thoughts - NYC vs. Silicon Valley (09:50) - Why Hilary thinks non-linear storytelling was wrong (13:44) - Understanding online traffic through bit.ly (15:57) - The taxonomy of data science (19:06) - Founding Fast Forward Labs - “Hire your nerd best friend” (23:05) - Can academia and startups coexist? (26:50) - Machine learning (ML) vs. Artificial Intelligence (AI) (34:00) - Selling Fast Forward Labs to Cloudera (38:51) - Hidden Door's inception (44:29) - The challenge - and opportunity - of AI hallucinations (48:07) - What is Hidden Door? (52:38) - Building an architecture for unstructured input (57:38) - How can you try Hidden Door? (01:00:45) - Shifting the software engineer mindset (01:04:17) - How will product-building shift with generative AI? (01:07:34) - Is AI hype dangerous? (01:12:36) - Where to learn more about Hidden Door Stay in touch: www.lsvp.com X: https://twitter.com/lightspeedvp LinkedIn: https://www.linkedin.com/company/lightspeed-venture-partners/ Instagram: https://www.instagram.com/lightspeedventurepartners/ Subscribe on your favorite podcast app: generativenow.co Email: generativenow@lsvp.com The content here does not constitute tax, legal, business or investment advice or an offer to provide such advice, should not be construed as advocating the purchase or sale of any security or investment or a recommendation of any company, and is not an offer, or solicitation of an offer, for the purchase or sale of any security or investment product. For more details please see lsvp.com/legal.
This week we're bringing you a conversation with Hilary Mason from Hidden Door, an AI-driven narrative game engine. This mini-episode recorded in person at TechCrunch Disrupt and Dom and Hilary get into how generative AI is changing online gaming, building a team of creatives, and fundraising in the gaming space. Found posts every Friday. Subscribe on Apple, Spotify or wherever you listen to podcasts to be alerted when new episodes drop. Check out the other TechCrunch podcasts: Equity, and Chain Reaction.Connect with us:On TwitterOn InstagramVia email: found@techcrunch.com
EPISODE 1595: In this KEEN ON show, Andrew talks to Hilary Mason, co-founder and CEO of Hidden Door, about how Open Source AI might both democratize Big Tech and empower writers in the creation of role playing games Hilary Mason is the co-founder and CEO of Hidden Door, a role-playing AI platform. She was previously the Founder of Fast Forward Labs, a machine intelligence research company, and the Data Scientist in Residence at Accel as well as the Chief Scientist at bitly. She also co-founded of HackNY, co-host DataGotham, and is a member of NYCResistor. Named as one of the "100 most connected men" by GQ magazine, Andrew Keen is amongst the world's best known broadcasters and commentators. In addition to presenting KEEN ON, he is the host of the long-running How To Fix Democracy show. He is also the author of four prescient books about digital technology: CULT OF THE AMATEUR, DIGITAL VERTIGO, THE INTERNET IS NOT THE ANSWER and HOW TO FIX THE FUTURE. Andrew lives in San Francisco, is married to Cassandra Knight, Google's VP of Litigation & Discovery, and has two grown children. Learn more about your ad choices. Visit megaphone.fm/adchoices
Don't Look Now(1973)This week on MMM Erin and special guest David Joshua Smith do a deep dive review of a classic. grieving over the accidental death of their daughter, Christine (Sharon Williams), John (Donald Sutherland) and Laura Baxter (Julie Christie) head to Venice, Italy, where John's been commissioned to restore a church. There, Laura meets two sisters (Hilary Mason, Clelia Matania) who claim to be in touch with the spirit of the Baxters' daughter. Laura takes them seriously, but John scoffs until he himself catches a glimpse of what looks like Christine running through the streets of Venice.Staring Julie Christie and Donald Sutherland Leave a comment on our social media pages and let us know what you think of this episode or the movie itself. We always love hearing from our listeners!
We're in the countdown to the 2023 INFORMS Business Analytics Conference, in Aurora, CO, April 16-18, and this year's conference is particularly special for the INFORMS community as this was the site of our 2020 meeting … or it was supposed to be, but unfortunately the COVID-19 pandemic had other ideas. Now, here we are three years later and we've come full circle and I think I speak for many in the INFORMS community when I say that I have never been more excited to attend an Analytics Conference. With that in mind, I'm thrilled to be joined by Hilary Mason, the INFORMS Roundtable sponsored keynote speaker and co-founder and CEO of Hidden Door, a game technology studio using machine learning to build the future of immersive entertainment. We're taking this opportunity to get to know Hilary a little bit, talk about her analytics journey, and get a sneak peek at what she'll be presenting at the upcoming conference.
I was lucky enough to attend a dinner during which Hilary Mason dropped more wisdom about hiring in one course than many people do in a 90-minute talk. In this week's episode, I get to chat with Hilary, learning how she thinks about screening for judgment, identifying the requirements for a role, the value of creating a humane, fun, structured interviewing process, and the importance of valuing a mix of talents and perspectives on the team (hackers and scalable systems builders, optimists and pragmatists, etc).PARTNERThanks to our partner CloudZero — Cloud Cost Intelligence Platform. Control cost and drive better decisions with CloudZero cloud cost intelligence. The CloudZero platform provides visibility into cloud spend without the typical pitfalls of legacy cloud cost management tools, like endless tagging or clunky Kubernetes support. Optimize unit economics, decentralize cost data to engineering, and create a shared language between finance and technical teams. CloudZero helps you organize cloud spending better than anyone else. Join companies like Drift, Rapid7, and SeatGeek by visiting cloudzero.com/ctoconnection to get started.
Sure. GPT-3 and large language models in general can take a prompt and spin out in any of a million human-sounding directions. That's neat, but maybe not exactly what you'd want to turn loose as your guide through a narrative multiverse of AI-boosted creative play and community. "A what?" You say. Exactly. In this episode, we dug into Hilary Mason's latest endeavor, Hidden Door, and how she and her team are working to apply the right level of "human" to AI-driven narrative play. Intrigued? You should be! It's fascinating! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.
Hilary Mason, Co-Founder and CEO of Hidden Door, joins Jon Krohn for a live discussion that explores narrative A.I., emerging ML techniques, and how her OSEMN data science process developed. In this episode you will learn: • How narrative A.I. can assist creativity [5:14] • How to build ML products that have no quantitative error function to optimize [10:31] • How to ensure creative A.I. systems do not output non-sense or explicit content [16:58] • Hilary's OSEMN data science process [21:05] • The emerging ML technique she's most excited about [24:58] • What it takes to be successful as CEO of an early-stage A.I. company [27:20] • What she looks for in engineering hires [32:28] • How she's hopeful A.I. will transform our lives for the better in the decades to come [38:48] Additional materials: www.superdatascience.com/589
This week's guest is Hilary Mason, co-founder of Hidden Door, a startup that uses AI and machine learning to help create and power role-playing games (RPG). Download a FREE copy of our recent NLP Industry Survey Results: https://gradientflow.com/2021nlpsurvey/Subscribe: Apple • Android • Spotify • Stitcher • Google • AntennaPod • RSS.Detailed show notes can be found on The Data Exchange web site.
Hilary Mason, CEO of Hidden Door and data scientist in residence at Accel Partners, talks with World of DaaS host Auren Hoffman. Hilary previously co-founded Fast Forward Labs, which was acquired by Cloudera, and served as the Chief Scientist at bit.ly. Auren and Hilary explore how data science has progressed in the past decade, the role of data science in an organization, and data ethics.World of DaaS is brought to you by SafeGraph. For more episodes, visit safegraph.com/podcasts You can find Auren on Twitter at @auren
Gabe, Joey and Chris talk... Dolls is a 1987 American horror film directed by Stuart Gordon, written by Ed Naha, and starring Stephen Lee, Guy Rolfe, Hilary Mason, Ian Patrick Williams, and Bunty Bailey. Its plot follows six people who seek shelter during a storm in the mansion of an elderly puppetmaker and his wife, only to find that the various puppets and dolls in the home contain the imprisoned spirits of criminals. It was produced by Charles Band and Brian Yuzna, through Band's Empire Pictures.
It's Berktober here at Berkreviews.com, and that means Jonathan (@berkreviews) and Corey (@coreyrstarr) are focusing on horror. This time, the theme of I'll Show you Scary forced Jonathan and Corey to dive into the Rotten Tomatoes top 100 rated horror films for the movies on the list that they've not seen. There are many on the list that both Corey and Jonathan love, but they had to pick some more obscure ones to fulfill the requirements of the show. Will that turn out to be a good thing or a bad thing? In past years, they've not enjoyed some highly loved horror films (listen to their Phantasm and Suspiria episodes), but who knows what they'll find in these selections. As far as the podcast goes, each episode features an in-depth review of the movie for the week. They begin with a spoiler-free review before diving in completely after the needed spoiler warning. However, before getting into the review of the week, Jonathan and Corey discuss what other movies they've seen since the last episode as well as anything else they feel like discussing. To help them decide which of the many films to watch each month they started creating themes for them all. Week 2 - Don't Look Now (1973) Corey picked Don't Look Now (1973) off of the RT list sitting at #28 with a 94% RT score. The film stars Julie Christie, Donald Sutherland, and Hilary Mason and is directed by Nicolas Roeg. While a bit wordy, the synopsis reads "A married couple grieving the recent death of their young daughter are in Venice when they encounter two elderly sisters, one of whom is psychic and brings a warning from beyond." --- Support this podcast: https://anchor.fm/berkreviewscom-moviecasts/support
Hilary Mason is building a new way for kids and families to create stories with AI. It’s called Hidden Door, and in her first interview since founding it, Hilary reveals to Chris and Daniel what the experience will be like for kids. It’s the first Practical AI episode in which some of the questions came from Chris’s 8yo daughter Athena. Hilary also shares her insights into various topics, like how to build data science communities during the COVID-19 Pandemic, reasons why data science goes wrong, and how to build great data-based products. Don’t miss this episode packed with hard-won wisdom!
Hilary Mason is building a new way for kids and families to create stories with AI. It’s called Hidden Door, and in her first interview since founding it, Hilary reveals to Chris and Daniel what the experience will be like for kids. It’s the first Practical AI episode in which some of the questions came from Chris’s 8yo daughter Athena. Hilary also shares her insights into various topics, like how to build data science communities during the COVID-19 Pandemic, reasons why data science goes wrong, and how to build great data-based products. Don’t miss this episode packed with hard-won wisdom!
This Week in Machine Learning & Artificial Intelligence (AI) Podcast
Today we’re joined by Ana Maria Echeverri, Caroline Chavier, Hilary Mason, and Jacqueline Nolis, our guests for the recent Advancing Your Data Science Career During the Pandemic panel. In this conversation, we explore ways that Data Scientists and ML/AI practitioners can continue to advance their careers despite current challenges. Our panelists provide concrete tips, advice, and direction for those just starting out, those affected by layoffs, and those just wanting to move forward in their careers. Topics we cover include: Guerilla Job Hunting Portfolio Building Navigating Hiring Freezes Acing the Technical Interview Presenting the Best Candidate For more information about our guests, or for links to the resources mentioned, visit the show notes page at twimlai.com/talk/380.
This week, it's part one of back-to-back Dolls on Bad Movie Date Night. This week, Nigel and Kaitlyn discuss the 1987 Stuart Gordon film, The Dolls, a fantastically bad movie about killer dolls. In this episode, listen to Nigel and Kaitlyn theorize if this film is a prequel to Toy Story as well as discuss the physics of candles and flashlights. All this and more on this week's episode of Bad Movie Date Night. Next week, tune in to listen to Nigel and Kaitlyn discuss the 2019 movie Dolls. The Dolls (1987) Directed by Stuart GreenWritten by Ed NahaStarring: Ian Patrick Williams, Carolyn Purdy-Gordon, Carrie Lorraine, Guy Rolfe, Hilary Mason, Bunty Bailey, Cassie Stuart, Stephen Lee Don't forget to subscribe in Apple Podcasts or your Podcatcher of choice. Follow us on Facebook and Instagram @JourneyIntoFilm Support us on Patreon at patreon.com/ajourneyintofilm. This has been a production of AJourneyIntoFilm.com
When you think of Cloudera, the billion-dollar software company that's virtually a household name, you probably think of a cloud-based, new technology data warehousing company. Sure, but did you know that Cloudera is currently a challenger in the 2017 Gartner Magic Quadrant for Data Management Analytic Solutions against the likes of Oracle, Teradata, IBM and Microsoft? In this episode, Jon Prial talks to Tom Reilly, Cloudera's CEO, along with Hilary Mason, one of the top data scientists in the world, whose company, Fast Forward Labs, Cloudera recently acquired. Together they discuss machine learning from both an executive and technical perspective. You'll hear about: -- Where the market is heading in terms of machine learning adoption -- The types of challenges companies face with machine learning -- The future of machine learning -- Data curation
This episode features special guest Hilary Mason, Data Scientist in Residence at Accel Partners, co-founder of hackNY.org, and founder of Fast Forward Labs, which is now part of Cloudera. Hilary joins CosmiQ’s Ryan Lewis and Nick Weir as they explore lessons learned and recommendations on executing artificial intelligence (AI) beyond research teams. The discussion explores how machine learning technologies can be applied at an enterprise level for corporations that are looking to move beyond basic prototypes and into real product development that shows results.
On this episode Byron has a conversation with Hilary Mason, an acclaimed data and research scientist, about the mechanics and philosophy behind designing and building AI. Bonus Episode: A Conversation with Hilary Mason
On this episode Byron has a conversation with Hilary Mason, an acclaimed data and research scientist, about the mechanics and philosophy behind designing and building AI. Bonus Episode: A Conversation with Hilary Mason
On this episode Byron has a conversation with Hilary Mason, an acclaimed data and research scientist, about the mechanics and philosophy behind designing and building AI. Bonus Episode: A Conversation with Hilary Mason
Guests Jerry Kaplan of Stanford University, Oren Etzioni of The Allen Institute for Artificial Intelligence, research fellow Geoffrey Hinton of Google, Hilary Mason of Cloudera, and author Nick Bostrom join host Walter Isaacson and trace the origins of AI, each milestone to date, and reveal how it’s evolving at lightning speed. Stanley Kubrick is no one’s idea of an optimist (in film, anyway). Yet, in his landmark 1968 film “2001: A Space Odyssey,” Kubrick projected a vision into the future that humans still haven’t been able to shake: an intelligent machine, gone rogue, rising up against that who it’d been tasked to serve. The vivid horror shaped the way we view AI, and – to this day – scientists, technologists’, businesses and policymakers still debate this possibility. We may have a long way before we find out the answer, but we’ve come a long way so far just to get here. So will AI rebel against humans? Although many are terrified, a school of thought exists that AI simply wouldn’t have interest in human affairs. Yet, with algorithms and analytics helping diagnose and treat diseases like cancer, humans are very interested in AI’s potential. And, more viscerally still, interested in if AI will automate them out of a job. Humans may make mistakes, but unless we can trust AI to be objective and perfect, so, too, will machines. Plus, without true emotion and real-time intuition, jobs like doctors are more than safe for the foreseeable future. Of chief concern: combatting implicit bias in AI. Technologists are refining algorithms to ensure non-discriminatory objectivity in decision-making. AI may not replace us, but if deployed powerfully and perfectly, AI may be the last invention humans ever need. For more on the podcast go to delltechnologies.com/trailblazers Please let us know what you think of the show by leaving us a rating or review in Apple Podcasts
I caught up with Hilary Mason, GM of Machine Learning at Cloudera and former founder of Fast Forward Labs. We cover how to: - Generate ideas for Machine Learning Research - Hold a good brainstorm - Break into tech as a Data Scientist - Give an engaging and successful tech talk I also asked Hilary about the evolving role of Machine Learning and Data Science, and what she wants to build in the future!
Episode 64 : “Happy new year 2019” -----------------------------AI predictions for 2019 from Yann LeCun, Hilary Mason, Andrew Ng, and Rumman Chowdhury | VentureBeathttps://venturebeat.com/2019/01/02/ai-predictions-for-2019-from-yann-lecun-hilary-mason-andrew-ng-and-rumman-chowdhury/Interview de Yann Le Cun https://anchor.fm/ouiareny/episodes/3-Yann-LeCun-Facebook--Comment-lexcellence-scientifique-Franaise-brille-chez-Facebook-e2pt9p/a-a7tui6-----------------------------In the CloudBigtable Autoscaler: saving money and time using managed storagehttps://labs.spotify.com/2018/12/18/bigtable-autoscaler-saving-money-and-time-using-managed-storage/Will Kubernetes Sink the Hadoop Ship?https://thenewstack.io/will-kubernetes-sink-the-hadoop-ship/-----------------------------DatabaseHas FaunaDB Cracked the Code for Global Transactionality?https://www.datanami.com/2018/12/12/has-faunadb-cracked-the-code-for-global-transactionality/They scaled YouTube — now they’ll shard everyone with PlanetScale (Vitess)https://techcrunch.com/2018/12/13/planetscale/https://vitess.io/-----------------------------OSSLicense Changes for Confluent Platformhttps://www.confluent.io/blog/license-changes-confluent-platformA Developer’s Guide to the Confluent Community Licensehttps://www.confluent.io/blog/developers-guide-confluent-community-licenseOpen source confronts its midlife crisishttp://dtrace.org/blogs/bmc/2018/12/14/open-source-confronts-its-midlife-crisis/We need Sustainable Free and Open Source Communitieshttps://medium.com/sustainable-free-and-open-source-communities/we-need-sustainable-free-and-open-source-communities-edf92723d619-----------------------------DatascienceStandardizing on Keras: Guidance on High-level APIs in TensorFlow 2.0https://medium.com/tensorflow/standardizing-on-keras-guidance-on-high-level-apis-in-tensorflow-2-0-bad2b04c819a-----------------------------Lisez le blog d'Affini-Techhttp://blog.affini-tech.com-------------------------------------------------------------http://www.bigdatahebdo.com https://twitter.com/bigdatahebdoVincent : https://twitter.com/vhe74Alex : https://twitter.com/alexanderDejaCette publication est sponsorisée par Affini-Tech ( http://affini-tech.com https://twitter.com/affinitech )On recrute ! venez cruncher de la data avec nous ! écrivez nous à recrutement@affini-tech.com-----------------------------------------
Episode 64 : “Happy new year 2019” -----------------------------AI predictions for 2019 from Yann LeCun, Hilary Mason, Andrew Ng, and Rumman Chowdhury | VentureBeathttps://venturebeat.com/2019/01/02/ai-predictions-for-2019-from-yann-lecun-hilary-mason-andrew-ng-and-rumman-chowdhury/Interview de Yann Le Cun https://anchor.fm/ouiareny/episodes/3-Yann-LeCun-Facebook--Comment-lexcellence-scientifique-Franaise-brille-chez-Facebook-e2pt9p/a-a7tui6-----------------------------In the CloudBigtable Autoscaler: saving money and time using managed storagehttps://labs.spotify.com/2018/12/18/bigtable-autoscaler-saving-money-and-time-using-managed-storage/Will Kubernetes Sink the Hadoop Ship?https://thenewstack.io/will-kubernetes-sink-the-hadoop-ship/-----------------------------DatabaseHas FaunaDB Cracked the Code for Global Transactionality?https://www.datanami.com/2018/12/12/has-faunadb-cracked-the-code-for-global-transactionality/They scaled YouTube — now they’ll shard everyone with PlanetScale (Vitess)https://techcrunch.com/2018/12/13/planetscale/https://vitess.io/-----------------------------OSSLicense Changes for Confluent Platformhttps://www.confluent.io/blog/license-changes-confluent-platformA Developer’s Guide to the Confluent Community Licensehttps://www.confluent.io/blog/developers-guide-confluent-community-licenseOpen source confronts its midlife crisishttp://dtrace.org/blogs/bmc/2018/12/14/open-source-confronts-its-midlife-crisis/We need Sustainable Free and Open Source Communitieshttps://medium.com/sustainable-free-and-open-source-communities/we-need-sustainable-free-and-open-source-communities-edf92723d619-----------------------------DatascienceStandardizing on Keras: Guidance on High-level APIs in TensorFlow 2.0https://medium.com/tensorflow/standardizing-on-keras-guidance-on-high-level-apis-in-tensorflow-2-0-bad2b04c819a-----------------------------Lisez le blog d'Affini-Techhttp://blog.affini-tech.com-------------------------------------------------------------http://www.bigdatahebdo.com https://twitter.com/bigdatahebdoVincent : https://twitter.com/vhe74Alex : https://twitter.com/alexanderDejaCette publication est sponsorisée par Affini-Tech ( http://affini-tech.com https://twitter.com/affinitech )On recrute ! venez cruncher de la data avec nous ! écrivez nous à recrutement@affini-tech.com-----------------------------------------
This Week in Machine Learning & Artificial Intelligence (AI) Podcast
In this episode of our Strata Data conference series, we’re joined by Justin Norman, Director of Research and Data Science Services at Cloudera Fast Forward Labs. Fast Forward Labs was an Applied AI research firm and consultancy founded by Hilary Mason, who’s TWiML Talk episode remains an all-time fan favorite. My chat with Justin took place on the 1 year anniversary of Fast Forward Labs’ acquisition by Cloudera, so we start with an update on the company before diving into a look at some of recent and upcoming research projects. Specifically, we discuss their recent report on Multi-Task Learning and their upcoming research into Federated Machine Learning for AI at the edge. To learn more about Cloudera and CFFL, visit Cloudera's Machine Learning resource center at cloudera.com/ml. For the complete show notes, visit https://twimlai.com/talk/185.
Welcome back to the PolicyViz Podcast! After a lovely summer break, I'm back with new episodes focusing on data, data visualization, and presentation skills. I'm slowing things down a bit this year and going to an every-other-week format. Still on... The post Episode #133: Hilary Mason appeared first on PolicyViz.
Welcome back to the PolicyViz Podcast! After a lovely summer break, I'm back with new episodes focusing on data, data visualization, and presentation skills. I'm slowing things down a bit this year and going to an every-other-week format. Still on... The post Episode #133: Hilary Mason appeared first on PolicyViz.
Hugo speaks with Eric Colson, Chief Algorithms Officer at Stitch Fix, an online personal styling service reinventing the shopping experience by delivering one-to-one personalization to their clients through the combination of data science and human judgment. Eric is responsible for the creation of dozens of algorithms at Stitch Fix that are pervasive to nearly every function of the company, from merchandise, inventory, and marketing to forecasting and demand, operations, and the styling recommender system. Join for all of this and more. Links from the show FROM THE INTERVIEW Stitch Fix Algorithm Tour Warehouse Maps, Movie Recommendation, Structural Biology Advice for Data Scientists on where to work More Human Humans: how our work-life can be improved by ceding tasks to machines. Learning from Textual Feedback (natural Language processing) Deep Style: Teaching machines about style from images Hybrid Designs You Can’t Make this stuff up … or can you? The Blissful Ignorance of the Narrative Fallacy FROM THE SEGMENTS Blog Post of the Week (with Emily Robinson) Doing Good Data Science by Mike Loukides, Hilary Mason and DJ Patil Original music and sounds by The Sticks.
In this episode of the ARCHITECHT Show, Hilary Mason -- now GM of machine learning at Cloudera, and formerly founder of Fast Forward Labs, chief scientist at Bitly and more -- discusses a breadth of topics related to artificial intelligence, including what's exciting today in enterprise AI and machine learning, and how to discern the wheat from the chaff in AI research. Mason also goes into depth on the topic of data ethics, explaining why we're at a day of reckoning and how companies and data scientists can go about getting their ethics in order.
The most important thing is to have an AI-enable infrastructure. It sounds very boring, but that was the learning that I got from the bank as well. It’s actually very easy for us to build the model, but what took a long time was to have the AI infrastructure that enables us to do so. Per: The most important thing is to have an AI-enable infrastructure. It sounds very boring, but that was the learning that I got from the bank as well. It’s actually very easy for us to build the model, but what took a long time was to have the AI infrastructure that enables us to do so. Ginette: I’m Ginette. Curtis: And I’m Curtis. Ginette: And you are listening to Data Crunch. Curtis: A podcast about how data and prediction shape our world. Ginette: A Vault Analytics production. Ginette: Before we get into this episode, let’s bring you behind the scenes at Data Crunch. We’re going to show you what we’ve learned about your tastes so far. According to the podcast analytics, which are still rudimentary and can only tell us so much, you really liked our last episode with DataOps. You also enjoyed the "No PhD Necessary" episode, the "How Artificial Intelligence Might Change Your World" episode. Almost all of you have loved the history of data science series. In fact, the third one in the series is our most popular episode in terms of how much of the show you listen to. But in terms of sheer listening numbers, the Hilary Mason episode, titled "The Complex World of Data Scientists and Black-Box Algorithms," tops our charts, with the Ran Levi episode, titled "Deep Learning—A Powerful Tool with a Name that Means Nothing," coming in second place. What this seems to tell us is you like interesting data history, you like interesting projections into the future, and you like learning practical ways you can be successful with data projects. But since the podcast analytics are still rudimentary, we want to hear if our conclusions are correct. So if you want to steer our future seasons, let us know what you want to hear more about by filling out a short survey. Just go to datacrunchpodcast.com/survey, and we would love to hear from you! Today we talk to the cofounder and CEO of a Danish company that employs machine learning to gather insights on what content on your website leads people to take action. If you’re looking into building a company using artificial intelligence or machine learning, this episode will be of particular interest to you because he talks about the impetus for his idea, some tools he used to build his product, some challenges, how he hired his team, when he uses or discards algorithms, and how he packages his product. And you can even try a free version of his product, which he mentions at the end of the show. Per Damgaard Husted: My name is Per Damgaard Husted. I'm the founder and CEO of Canecto. Canecto is a new way of doing web analytics based on machine learning, and the reason we do machine learning is because we want to understand the intention of the users so that we can predict how they are interacting on the website. We focus a lot on how content influences people to make decisions on a website, so it sort of compliments the user journey that you have and the UX and the SEO, but we focus on the content. Curtis: So how did Per come up with this idea of extracting insights from users’ interaction with content? Per: The background was that actually I needed this tool. I was a manager in one of the big Danish banks, and I was in charge of the online banking elements, and I got a lot of traffic, or we got a lot of traffic statistics about what's going on, but I didn't really know anything about that users’ intent. I wanted to make our website better. I wanted to understand what motivates them. I wanted to understand what content we produced. We produced a lot of content in the bank, and we had no tools that could explain how the users’ interaction with the content drove them to take specific a...
Hilary Mason talks about the past, present, and future of data science with Hugo. Hilary is the VP of Research at Cloudera Fast Forward, a machine intelligence research company, and the data scientist in residence at Accel. If you want to hear about where data science has come from, where it is now, and the direction it's heading, you've come to the right place. Along the way, we'll delve into the ethics of machine learning, the challenges of AI, automation and the roles of humanity and empathy in data science.
Today’s topic is machine learning and I’m talking to one of the brightest minds in the field, Hilary Mason. She’s the founder of Fast Forward Labs, a machine intelligence research company. She also advises startups through Accel, a prominent venture capital firm. If you’re interested in artificial intelligence and machine learning, I’m pretty sure you’ll love this episode.
In this episode of the ARCHITECHT Show, data scientist extraordinaire Hilary Mason covers a wide range of topics, including her path from Bitly to Cloudera—where she's now VP of research after the company acquired her applied research firm, Fast Forward Labs. Among other topics, Mason also discusses the state of AI readiness and adoption within large enterprises; the importance of getting "big data" pieces in place before jumping into AI; and who will actually do AI inside the companies that adopt it.
Hilary Mason is a huge name in the data science space, and she has an extensive understanding of what's happening in this space. Today, she answers these questions for us: What are the backgrounds of your typical data scientists? What are key differences between software engineering and data science that most companies get wrong? How should you measure the effectiveness of your work or your team's work as a data scientist for the best results? What is a good approach for creating a successful data product? How can we peak behind the curtain of black-box deep learning algorithms? Below is a partial transcript. For the full interview, listen to the podcast episode by selecting the Play button above or by selecting this link, or you can also listen to the podcast through Apple Podcasts, Google Play, Stitcher, and Overcast. Curtis: Today we hear from one of the biggest thinkers in the data science space, someone who DJ Patil endorses on LinkedIn for data science skills. She worked at bit.ly, the url shortener, and is a data scientist in residence at venture capital firm Accel Partners, a firm that helped fund some companies you may know, like Facebook, Slack, Etsy, Venmo, Vox Media, Lynda.com, Cloudera, Trifacta—and you get the picture. Ginette: The partner of this VC firm said that Accel wouldn’t have brought on just any data scientist. This position was specifically created because this particular data scientist might be able to join their team. Curtis: But beyond her position as data in residence with Accel, she founded a company that’s doing very interesting research, and today, she shares with us some of her experiences and perspective on where AI is headed. Ginette: I’m Ginette. Curtis: And I’m Curtis. Ginette: And you are listening to Data Crunch. Curtis: A podcast about how data and prediction shape our world. Ginette: A Vault Analytics production. Hilary: I'm Hilary Mason, and I'm the founder and CEO of Fast Forward Labs (Please note that Hilary is now the VP of Research at Cloudera). In addition to that, I'm a data science in residence for Accel Partners. And I've been working in what we now call data science, or even now call AI, for about twenty years at this point. Started my career in academic machine learning and decided startups were more fun and have been doing that for about 10, 12 years depending on how you count now, and it's a lot of fun! Ginette: Something I’d like to note here is there’s been a very recent change: Hilary’s company, Fast Forward Labs, and Cloudera recently joined forces, and Hilary’s new position is Vice President of Research at Cloudera. Now, one thing that Hilary talks to is where the data scientists she works with come from, which is a great example of the different paths people take to get into this field. Hilary I am a computer scientist, and I have studied computer science. It's funny because now at Fast Forward, our team only has only two computer scientists on it, and one of them is our general counsel, and one is me, and I'm running the business, so most of the people doing data science here come from very different backgrounds. We have a bunch of physicists, mathematicians, a neuroscientist, a person who does brilliant machine learning design who was an English major, and so data science is one of those fields where one of the things I really love about it is that people come to it from so many different backgrounds, but mine happens to be computer science. The people on our team at Fast Forward typically have a PhD in a quantitative field, such as physics, neuroscience, electrical engineering, and then have, through that, learned sufficient programming skill. One of the jokes I make about my team is that we're essentially a halfway house for wayward academics in the sense that we can absorb people and teach them to be good software engineers, help them understand the difference between theoretical machine learning an...
This Week in Machine Learning & Artificial Intelligence (AI) Podcast
This week's guest is Kathryn Hume. Kathryn is the President of Fast Forward Labs, which is an independent machine intelligence research company that helps organizations accelerate their data science and machine intelligence capabilities. If Fast Forward Labs sounds familiar, that's because we had their founder, Hilary Mason on a few months ago. We’ll link to that in the show notes. My discussion with Kathryn focused on AI adoption within the enterprise. She shared several really interesting examples of the kinds of things she’s seeing enterprises do with machine learning and AI, and we discussed a few of the various challenges enterprises face and some of the lessons her company has learned in helping them. I really enjoyed our conversation and I know you will too! You can find the notes for todays show here: https://twimlai.com/talk/20
This Week in Machine Learning & Artificial Intelligence (AI) Podcast
My guest this time is Hilary Mason. Hilary was one of the first “famous” data scientists. I remember hearing her speak back in 2011 at the Strange Loop conference in St. Louis. At the time she was Chief Scientist for bit.ly. Nowadays she’s running Fast Forward Labs, which helps organizations accelerate their data science and machine intelligence capabilities through a variety of research and consulting offerings. Hilary presented at the O'Reilly AI conference on “practical AI product development” and she shares a lot of wisdom on that topic in our discussion. The show notes can be found at twimlai.com/talk/11.
The O'Reilly Radar Podcast: Thinking critically about AI, modeling language, and overcoming hurdles.This week, I sit down with Hilary Mason, who is a data scientist in residence at Accel Partners and founder and CEO of Fast Forward Labs. We chat about current research projects at Fast Forward Labs, adoption hurdles companies face with emerging technologies, and the AI technology ecosystem—what's most intriguing for the short term and what will have the biggest long-term impact.Here are some highlights: Missing wisdom There are a few things missing [from the AI conversation]. I think we tend to focus on the hype and eventual potential without thinking critically about how we get there and what can go wrong along the way. We have a very optimistic conversation, which is something I appreciate. I'm an optimist, and I'm very excited about all of this stuff, but we don't really have a lot of critical work being done in things like how do we debug these systems, what are the consequences when they go wrong, how do we maintain them over time, and operationalize and monitor their quality and success, and what do we do when these systems infiltrate pieces of our lives where automation may have highly negative consequences. By that, I mean things like medicine or criminal justice. I think there's a big conversation that is happening, but the wisdom still is missing. We haven't gotten there yet. Making the impossible possible I'm particularly intrigued at the moment by being able to model language. That's something where I think we can't yet imagine the ultimate applications of these things, but it starts to make things that previously would have seemed impossible possible, things like automated novel writing, poetry, things that we would like to argue are purely human creative enterprises. It starts to make them seem like something we may one day be able to automate, which I'm personally very excited about. The impact question is a really good one, and I think it is not one technology that will have that impact. It's the same reason we're starting to see all these different AI products pop up. It's the ensemble of all of the techniques that are falling under this umbrella together that is going to have that kind of impact and enable applications like the Google Photos app, which is my favorite AI product, or self-driving cars or things like Amazon's Alexa, but actually smarter. That's a collection of different techniques. Making sentences and languages computable We've done a project in automated summarization that I'm very excited about—that is applying neural networks to text, where you can put in a single article and it will extract; this is extractive summarization. It extracts sentences from that article that, combined together, contain the same information in the article as a whole. We also have another formulation of the problem, which is multi-document summarization, where we apply this to Amazon product reviews. You can put in 5,000 reviews, and it will tell you these reviews tend to cluster in these 10 ways, and for each cluster, here's the summary of that cluster review. It gives you the capability to read or understand thousands of documents very quickly. ... I think we're going to see a ton of really interesting things built on the techniques that underlie that. It's not just summarization, but it's making sentences and languages computable. Adoption hurdles I think the biggest adoption hurdle [for emerging technologies]—there are two that I'll say. The one is that sometimes these technologies get used because they're cool, not because they're useful. If you build something that's not useful, people don't want to use it. That can be a struggle. The second thing is that people are generally resistant to change. When you're in an organization and you're trying to advocate for the use of a new technology to make the organization more efficient, you will likely run into friction. In those situations, it's a matter of time and making the people who are most resistant look good.
The O'Reilly Radar Podcast: Thinking critically about AI, modeling language, and overcoming hurdles.This week, I sit down with Hilary Mason, who is a data scientist in residence at Accel Partners and founder and CEO of Fast Forward Labs. We chat about current research projects at Fast Forward Labs, adoption hurdles companies face with emerging technologies, and the AI technology ecosystem—what's most intriguing for the short term and what will have the biggest long-term impact.Here are some highlights: Missing wisdom There are a few things missing [from the AI conversation]. I think we tend to focus on the hype and eventual potential without thinking critically about how we get there and what can go wrong along the way. We have a very optimistic conversation, which is something I appreciate. I'm an optimist, and I'm very excited about all of this stuff, but we don't really have a lot of critical work being done in things like how do we debug these systems, what are the consequences when they go wrong, how do we maintain them over time, and operationalize and monitor their quality and success, and what do we do when these systems infiltrate pieces of our lives where automation may have highly negative consequences. By that, I mean things like medicine or criminal justice. I think there's a big conversation that is happening, but the wisdom still is missing. We haven't gotten there yet. Making the impossible possible I'm particularly intrigued at the moment by being able to model language. That's something where I think we can't yet imagine the ultimate applications of these things, but it starts to make things that previously would have seemed impossible possible, things like automated novel writing, poetry, things that we would like to argue are purely human creative enterprises. It starts to make them seem like something we may one day be able to automate, which I'm personally very excited about. The impact question is a really good one, and I think it is not one technology that will have that impact. It's the same reason we're starting to see all these different AI products pop up. It's the ensemble of all of the techniques that are falling under this umbrella together that is going to have that kind of impact and enable applications like the Google Photos app, which is my favorite AI product, or self-driving cars or things like Amazon's Alexa, but actually smarter. That's a collection of different techniques. Making sentences and languages computable We've done a project in automated summarization that I'm very excited about—that is applying neural networks to text, where you can put in a single article and it will extract; this is extractive summarization. It extracts sentences from that article that, combined together, contain the same information in the article as a whole. We also have another formulation of the problem, which is multi-document summarization, where we apply this to Amazon product reviews. You can put in 5,000 reviews, and it will tell you these reviews tend to cluster in these 10 ways, and for each cluster, here's the summary of that cluster review. It gives you the capability to read or understand thousands of documents very quickly. ... I think we're going to see a ton of really interesting things built on the techniques that underlie that. It's not just summarization, but it's making sentences and languages computable. Adoption hurdles I think the biggest adoption hurdle [for emerging technologies]—there are two that I'll say. The one is that sometimes these technologies get used because they're cool, not because they're useful. If you build something that's not useful, people don't want to use it. That can be a struggle. The second thing is that people are generally resistant to change. When you're in an organization and you're trying to advocate for the use of a new technology to make the organization more efficient, you will likely run into friction. In those situations, it's a matter of time and making the people who are most resistant look good.
The O’Reilly Bots Podcast: Hilary Mason, Jimi Smoot, and Roger Chen on what AI means now.Something remarkable is happening in the world of artificial intelligence. At the O’Reilly AI Conference in New York, people weren’t just talking about AI as a far-off dream; they were talking about AI as something that exists in real products today. In this episode of the O’Reilly Bots podcast, I talk with three artificial-intelligence practitioners about the real practice of AI: Hilary Mason, Jimi Smoot, and Roger Chen. Hilary Mason, founder and CEO of Fast Forward Labs, a startup that conducts research on machine intelligence, says that today’s AI “gives us a capability that would have seemed like magic even five years ago, and yet that capability is not nearly as interesting as the fact that the app is actually useful.” We also talk about the potential of AI-generated content, and some products that provide a glimpse of what a new AI-written world might look like. My second conversation is with Jimi Smoot, founder and CEO of Vesper, a hybrid AI and human assistant that helps executives with tasks like scheduling and travel arrangements. AI that augments human functions is likely to be a facet of the next economy. Smoot says that “early in the process with a new user, having a human touch is critical to developing trust.” Finally, Roger Chen, co-chair of the O’Reilly AI Conference, talks about what the term AI really means, the origins of the AI Conference, and how companies can implement AI now. “I think a lot of these interfaces that we call AI and bots are just going to be known as seamless, great experiences and interfaces,” he says. O’Reilly’s upcoming Bot Day on October 19, 2016, in San Francisco, will provide more insight on AI for bots. Other links: Google’s "Deep Dream" paper, illustrating how a neural network can be used to turn an ordinary photograph into a dream-like composite Composing classical music using neural networks Video highlights from the O’Reilly AI Conference Brief, from Fast Forward Labs, a summarization engine that uses AI to extract the most interesting sentences from long passages of text
The O’Reilly Bots Podcast: Hilary Mason, Jimi Smoot, and Roger Chen on what AI means now.Something remarkable is happening in the world of artificial intelligence. At the O’Reilly AI Conference in New York, people weren’t just talking about AI as a far-off dream; they were talking about AI as something that exists in real products today. In this episode of the O’Reilly Bots podcast, I talk with three artificial-intelligence practitioners about the real practice of AI: Hilary Mason, Jimi Smoot, and Roger Chen. Hilary Mason, founder and CEO of Fast Forward Labs, a startup that conducts research on machine intelligence, says that today’s AI “gives us a capability that would have seemed like magic even five years ago, and yet that capability is not nearly as interesting as the fact that the app is actually useful.” We also talk about the potential of AI-generated content, and some products that provide a glimpse of what a new AI-written world might look like. My second conversation is with Jimi Smoot, founder and CEO of Vesper, a hybrid AI and human assistant that helps executives with tasks like scheduling and travel arrangements. AI that augments human functions is likely to be a facet of the next economy. Smoot says that “early in the process with a new user, having a human touch is critical to developing trust.” Finally, Roger Chen, co-chair of the O’Reilly AI Conference, talks about what the term AI really means, the origins of the AI Conference, and how companies can implement AI now. “I think a lot of these interfaces that we call AI and bots are just going to be known as seamless, great experiences and interfaces,” he says. O’Reilly’s upcoming Bot Day on October 19, 2016, in San Francisco, will provide more insight on AI for bots. Other links: Google’s "Deep Dream" paper, illustrating how a neural network can be used to turn an ordinary photograph into a dream-like composite Composing classical music using neural networks Video highlights from the O’Reilly AI Conference Brief, from Fast Forward Labs, a summarization engine that uses AI to extract the most interesting sentences from long passages of text
Hilary Mason, founder at Fast Forward Labs and Data Scientist in Residence at Accel Partners, debunks some of the myths around startups being "data-driven." In addition, she tackles some complex but critical topics and translates them for the rest of us. This episodes includes... 1) A clear definition of what data science actually is (and should be) 2) Hard truth about how much a startup should actually value its data 3) The evolution of the field of data science, who should use it, and where it's going and why Follow Hilary @hmason and visit fastforwardlabs.com to learn more. And let me know what you think of the show -- tweet me (Jay Acunzo) @jayacunzo. You can also subscribe to receive every episode plus weekly insights and resources about gaining startup traction: goo.gl/4eP9Ch
Ben Orenstein and Hilary Mason, Data Scientist in Residence at Accel Partners, talk about Data Science, Bitly and Cheeseburgers. rt.ly search engine OkCupid Blog hackNY DataGotham NYC Resister Hilary Mason's Personal Website Hilary Mason on Twitter
Digital Preservation 2013 Speaker: Hillary Mason chief scientist at bitly, co-founder of HackNY, creator of dataists, and member of NYCResistor, opened Digital Preservation 2013 with her keynote talk on the delicacies of data. Hilary Mason is the chief scientist at bitly, a company that studies attention on the internet in realtime, doing a mix of research, exploration, and engineering. Mason co-founded HackNY, a non-profit that helps talented engineering students find their way into the startup community of creative technologists in New York City. She is also an advisor to a few organizations, including knod.es, collective, and DataKind, as well as a mentor to Betaspring, the Providence, Rhode Island-based startup accelerator, and TechStars New York. She’s a member of Mayor Bloomberg’s Technology and Innovation Advisory Council, which has been a fascinating way to learn how government and industry can work together. For more information visit http://www.digitalpreservation.gov/multimedia/videos/hillary-mason.html&loclr=itb
In this week's podcast, Ben Orenstein is joined by Chad Fowler, author, speaker, and CTO of 6wunderkinder. Ben and Chad discuss Chad's recent move to Berlin and 6wunderkinder, what a CTO does, getting back to coding, the early Ruby community, who Chad wants to hire, predicting success of new hires, and what makes a truly good developer, favorite interview questions, how Chad's interviewing process has changed over time, how age and experience can change your perspective, how Chad built a great team, and what he might write about in the future. They also discuss Chad's new tattoo, his regrets, meditation, therapy, gaining control over your mind, and much, much more. Wunderlist David A. Black Rich Kilmer Dave Thomas Hilary Mason, Speaking: Entertain, Don’t Teach Befunge Ook! a programming language designed for orangutans LivingSocial Gains Wealth Of Ruby on Rails Expertise With InfoEther Acquisition Ben Scofield Evan Pheonix The Passionate Programmer: Creating a Remarkable Career in Software Development My Job Went to India: 52 Ways to Save Your Job Martin Fowler Clojure Scala Amy Cuddy: Your body language shapes who you are (Power Posing) Railsberry Power Posing! Follow @thoughtbot, @r00k, and @chadfowler on twitter.
Audio File: Download MP3Transcript: Interview with Hilary Mason Lucy Sanders: Hi, this is Lucy Sanders. I'm the CEO for the National Center for Women in Information Technology, or NCWIT. Today, we're continuing with our series of wonderful interviews with women who have founded technology companies. We really love this interview series and are very excited about the person we're talking to today. With me is Larry Nelson from W3W3.com. Hi, Larry. Larry Nelson: Hi. Boy, I'm really happy to be here. This is a wonderful series. It's extremely popular on our W3W3.com website. In fact, we archive all the interviews so you can go back and listen to them also. Lucy: Also, listeners you can find this interview on the NCWIT website as well. Today, we're interviewing a very special person, Hilary Mason, who is the chief scientist at Bitly. We'll have to have Hilary explain it more precisely than I will, of course. But Bitly is primarily a URL shortening service, a bookmarking service. It really provides a fun and easy way to save and share and discover links from the web, by using links that they call bit marks. Reducing that URLs pretty important. Those things can get pretty beefy. You can't really share them very easily when you have only so many bytes that you can send along. This is pretty important to services like Twitter, for example, and others. Hilary's got a great job at Bitly. She's the chief scientist and her work crosses peer research, math and the development of product focused systems. Another thing we know about Hilary. She loves New York. Absolutely loves New York. Loves everything about New York, entrepreneurship, I'm sure she's going to tell us about that. She also gave one of my very favorite TED talks of all time, Replacing Yourself with a Very Small Shell Script, which I listened to several times. Hillary, welcome. Hilary Mason: Thank you so much. Lucy: Tell us a little bit about what's going on at Bitly. Hilary: You gave a great overview of what Bitly is. But it's a fantastic example of something that is extremely simple that becomes quite interesting at a large scale. At Bitly, we see the links that people are sharing across all their different social networks. These are things like Twitter, Facebook, Tumblr, WordPress, Live Journal. Even strange places like YouTube or inside a virtual world like Habbo Hotel. Then we analyze the data in aggregate that comes from that social behavior. The kind of work that my team does is looking at human behavior through our social data. We work on things like building a search engine to try and find the most popular links about any topic you might be interested in. We also work on content recommendations. Some other really fun applications that are only possible because of the data set that comes from that very simple mechanism of shortening and sharing a link. Larry: Wow. Lucy: That's pretty interesting. All the social networking and sharing that's going on, we just redeveloped our website so we could more easily share our resources and also shorten our URLs. Very timely for us. Hilary, tell us a little bit about how you first got into technology and as you look out across the landscape today, which technologies do you find particularly interesting? Hilary: The question about how I first got interested in technology was actually when I was a little girl. I was fascinated by computers. I taught myself to write code from reading the back of magazines when I was still in elementary school. I remember my first program. It was the Absolutely Wonderful 10 Print Hilary is Great 20 Go to 10 Run. [laughter] Hilary: I thought it was amazing because it was an infinite loop and my teacher had no idea how to turn it off, who was even funnier. Lucy: I know, infinite loops are pretty funny anyway. Larry: Yes. [laughter] Hilary: Yes, so I've always been fascinated by it and I always knew that it was what I wanted to study. Then I went off and majored in computer science. As to what technologies I think are exciting right now, they're so many different ways to think about that. On the human side, I think the way that I can carry a computer in my pocket that's more powerful than that computer I had when I was in elementary school is amazing. I'm excited to see how our devices interact with the real world in the next few years through projects like Google Glass and other sorts of augmented reality things, things people have been trying to build for decades. Only now has the tide caught up to the idea that people have. I'm also really excited about data technologies and the way that we can use data. We have data available, we have compute capacity available. We can use it to make our lives better and more interesting. As a throwaway side project, I went and got all the menu data for all of the restaurants that are not fast‑food restaurants in Manhattan and was able to find...If you want Thai food, you should go to the area around Hell's Kitchen because it has the highest density of high‑quality Thai restaurants in the city. That's something I could do in a day that never would've been possible even a couple years ago. Larry: Wow. Lucy: Things are changing really quickly. Larry: Very quickly. I must say, just a couple days ago, a colleague of mine sent me an email. The link was so long, it was incredible and I get these long links from him frequently. I'm going to make sure I send him your website. [laughs] Hilary: Definitely should. I think email is still the biggest social network. Larry: Yes. Now, let me ask this, Hilary. It's two parts, all related. Why are you an entrepreneur and what is it about entrepreneurism that makes you tick? Hilary: I've always had mixed feelings about the word "entrepreneur" because it's so overloaded in our culture and it's become really trendy in a way that I'm not sure is healthy. The way that I like to describe the work that I do is that I tend to find problems and then try to make things that solve those problems. Sometime those things might be hacks, like the one I just described to you. At one point, we also built a door knob that you could text to unlock a door. That was very clearly a hack to solve a problem. It was not a company, it was not a product. Sometimes they're products, sometimes they're companies, sometimes they're non‑profits, like HackNY, which is an organization I co‑founded a couple years ago. The way I like to think about it is more engineering the right thing to solve the problem. Not so much about starting a business just for the sake of being an entrepreneur. Lucy: That's pretty interesting. Larry: It is. Lucy: What is it about that problem solving that you really like? Can you expand a bit more on that? Hilary: Sure. It's very much my philosophy about how we should build and develop technology. I really think it should give us super powers. The ability to do something we really couldn't do before. We're extremely lucky to live at a moment in time, when if you're willing to put in the time and energy, it is actually possible to build things that have not existed before, that actually do make people's lives a bit more interesting. Lucy: That's a great answer. I have to think a lot about your answer around entrepreneur being too overloaded. Larry: Yes, me, too. Lucy: That's a fascinating point of view. So far along your career path, who would you say influenced you? Who would your role models be, or your mentors? Hilary: That's a really wonderful question. I've had a few. One of them is definitely my mother, who, in her retirement years, went and became a ski instructor. Because it was something she really wanted to do. Now she's kicking ass with people much younger than her and having a great time. But really, I realized a couple years ago that the idea of entrepreneurship has always been in my family. I think it's also tied to the traits of stubbornness and impatience that tend to run in our family as well. But several people in my family who I admire, including my dad, have started their own businesses. Generally doing something that was not entirely normal. So, creating a solution to something that had never quite existed before. I've also really been inspired by certain authors. People who write things that just change the way you think about the world. In computer science, I've been reading the work of Richard Hamming, who was a mathematician who worked on the Manhattan Project and taught at West Point for many years. He has a wonderful book called On Science and Engineering that has quotes like, "In science, if you know what you're doing, you should stop. In engineering, if you don't know what you're doing, you should stop." Most of us live in the middle of that. I'd highly recommend it to any scientist and engineer. Lucy: I need to get out and read it because I love quotes like that. Larry: Boy, yeah, me, too. Lucy: I think that's really interesting. Larry: You've done so many different things. I want to congratulate you for that. But let me just ask you this... What is the toughest thing that you've ever had to do in your career? Hilary: Wow. Thank you. I really feel like I'm just getting started so it's really a pleasure to hear something like that. I think the toughest thing I ever had to do, and this may be an artifact of my own failings and weaknesses, is that it took me a long time to realize that, to succeed at anything, you really need other people to want you to succeed. And you need their help. The hardest thing, for me, was to learn how to get other people excited about the things I'm excited about and to work with them, hopefully helping them at the same time, to build things together in a community. Lucy: That's a hard lesson for, I think, a lot of people. That kind of a lesson, they don't teach that in school. Larry: Nope. Hilary: Not at all. Especially for somebody who grew up very nerdy and very independent, it's a hard thing to realize that you really do need other people to accomplish what you want to accomplish. Lucy: That leads directly to being able to communicate about, to be able to enlist people to be passionate about it in some external way, right? Hilary: Absolutely. Lucy: So that people can really sign on. When I worked at Bell Labs we had, obviously, hundreds and hundreds of engineers who had to excite other engineers about their approaches. Many of us had to learn that the hard way. That's a great lesson to learn for anybody, entrepreneur or not, I think. I you were sitting here, though, with a young person and giving them advice about entrepreneurship, given our prior conversation about the word itself... But given that we'll call it that for now. If you were giving a young person advice, what would you tell them? Hilary: Funny. I was invited to speak to a bunch of college students from NYU on Saturday. I spent quite a long time thinking about the answer to this question. I actually do have one for you. My answer to that is just to have adventures and to say yes when you're not sure about something. You're going to learn something fascinating along the way. Larry: That's really good. I like that. Hilary: Also, if you keep that spirit of adventure with you, even if the thing you're doing is a total failure, you'll have had a great time. It doesn't matter. Lucy: This is important for technologists, especially, because technology's on the edge. Like Hilary and others, who are inventing new things. That whole invention process is really an adventure. You can't invent something you already know what the end is. Larry: [laughs] Yes. Lucy: That's a pretty important observation. Larry: There's a real good question here that's good for any entrepreneur. They ought to take a look at it. That is, how do you, Hilary, bring balance into your personal and your professional lives? Hilary: Another good question. It's one that, I think, we tend to set up personal life and work life as if they're diametrically opposed and they're two things that should have a wall between them. I don't really look at it that way. I try and make sure I enjoy what I'm doing in my professional life. I try to make sure that it doesn't overwhelm what I'm doing in my personal life. But, in general, a lot of the things that I do are on that line of both. Where, for example, I'm taking a trip to San Francisco this week. I'm giving three talks. That's definitely professional. I'm also meeting up with friends. It's going to be a great time. I think it is a challenge. But it's one that, as long as you're happy, it's OK. Lucy: That blended answer, we get that a lot. One of our most popular answers and also an answer that says, "What balance?" Larry: [laughs] Yeah. Lucy: Totally imbalanced. You've already achieved a lot. You mentioned you were just starting out. You mentioned your love of adventure and always keeping that adventuresome attitude. What can you say about your next big adventure? Hilary: That's really a good question and one that I try to think about quite a lot. There are a couple of things I'm pretty excited about that I don't think have really caught on in the community, which means it might be an opportunity. Or it might be a terrible idea. I'd like to pursue those things. In general, themes around how technology can help us be better people. Lucy: That's interesting. That's one of the themes today, in fact, as the beginning of computer science education week. Some of the themes around technology to serve the world, technology to make people better, those are great things. Larry: Yes, absolutely. I love it. Lucy: Well, thank you so much, Hilary. It's been a pleasure talking to you. Have fun on your trip to San Francisco. Hilary: It's been great speaking with both of you, too. Lucy: I just want to remind listeners that they can find this interview at w3w.com and ncwit.org. Larry: All right. Lucy: All right, thank you. Larry: Thanks Hilary. Hilary: Thank you. Lucy: Have a safe trip and have fun. [music] Series: Entrepreneurial HeroesInterviewee: Hilary MasonInterview Summary: Hilary Mason, Chief Scientist at bitly, describes problem solving and the development of technology as a super power - "the ability to do something we really couldn't do before." She goes on to say "we're extremely lucky to live at a moment in time, when if you're willing to put in the time and energy, it is actually possible to build things that have not existed before, that actually do make people's lives a bit more interesting. Release Date: February 1, 2013Interview Subject: Hilary MasonInterviewer(s): Lucy Sanders, Larry NelsonDuration: 13:57
Bringing Art and Technology Together - Inspire. Create. Evolve.
batt_001_hilary.mp3 batt_001_hilary.oggHilary Mason lives in New York City where she is the Chief Scientist at bitly. She is trying to bring into popularity the field of Data Science. We also discuss her involvement with HackNY, NYCResistor, and her app to find the Median Hamburger in the West Village. Mentioned in this podcast: Read about Hilary's Burger App Watch a Video of Hilary's talk at Urban ReThink Read updates from Hilary's team on the Bitly Blog 4th of July Recipes on Bitly Inspiration: Jer Thorp, Data Artist in Residence at the NYTimes Jake Porway of DataKind littleBits (on CNN) MakerBot Adafruit Industries FamiLAB The Lean Startup Music: Soldiers of Speccy, Intermission by PILL Follow us: Hilary Mason @hmason Bootstrapping Green @peregrineneel Ryan Price @liberatr
Hilary Mason of bit.ly talks about her work and how she got started with computers.
Hilary Mason is Senior Manager for West Sussex Youth Service AND the first ever uk-based statutory youth worker blogging. Agree, disagree, like, don't like...? Feel free to leave a comment at http://mediasnackers.com/2008/05/mediasnackers-podcast109/
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