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Este audio fue publicado originalmente hace más de dos años, cuando los ciberataques masivos y la fragilidad del mundo digital comenzaban a inquietarnos de verdad. Hoy lo recuperamos, remasterizado y con mejor calidad de sonido, porque su contenido sigue siendo tan actual como inquietante. Vivimos en un mundo hiperconectado, donde todo —desde la luz de nuestra casa hasta el hospital más cercano— depende de sistemas digitales. Pero, ¿qué sucede cuando ese sistema falla? ¿Qué pasa cuando el apagón no es por tormenta, sino por un ataque silencioso e invisible? En esta historia exploramos un escenario cada vez más posible: un corte total, una caída del sistema... y lo que ocurre cuando el mundo entero se queda sin red. Bruce Schneier (traducción Álvaro Robledo) - Haz clic aquí para matarlos a todos, autor BRUCE SCHNEIER (15 de enero de 1963, Nueva York). Apodado «el gurú de la seguridad» digital por The Economist, Bruce Schneier es posiblemente el criptógrafo más reconocido de Estados Unidos. Autor de una decena de libros en materia de seguridad informática, más de doscientas cincuenta mil personas leen sus influyentes Newsletter Crypto-Gram y blog Schneier on Security. Además, ha testificado ante el Congreso de Estados Unidos, ha participado en varios comités gubernamentales y aparece frecuentemente en televisión. Entre las instituciones con las que colabora destacan la Universidad de Harvard e IBM. Más contenido aquí: 📢Nuevo canal informativo en Telegram: https://t.me/historiasparaserleidas 🛑BIO Olga Paraíso: https://instabio.cc/Hleidas Recuerda que para que todo esto siga funcionando hace falta apoyo. Deja un corazoncito en el audio, comenta qué te ha parecido, súbelo a tus redes sociales o incluso aporta tu granito de arena de forma económica pulsado en el botón AZUL apoyar de este mismo podcast. Todo suma. ¡GRACIAS!🚀 ❗️https://www.ivoox.com/support/552842 Escucha el episodio completo en la app de iVoox, o descubre todo el catálogo de iVoox Originals
Recomendados de la semana en iVoox.com Semana del 5 al 11 de julio del 2021
Este audio fue publicado originalmente hace más de dos años, cuando los ciberataques masivos y la fragilidad del mundo digital comenzaban a inquietarnos de verdad. Hoy lo recuperamos, remasterizado y con mejor calidad de sonido, porque su contenido sigue siendo tan actual como inquietante. Vivimos en un mundo hiperconectado, donde todo —desde la luz de nuestra casa hasta el hospital más cercano— depende de sistemas digitales. Pero, ¿qué sucede cuando ese sistema falla? ¿Qué pasa cuando el apagón no es por tormenta, sino por un ataque silencioso e invisible? En esta historia exploramos un escenario cada vez más posible: un corte total, una caída del sistema... y lo que ocurre cuando el mundo entero se queda sin red. Bruce Schneier (traducción Álvaro Robledo) - Haz clic aquí para matarlos a todos, autor BRUCE SCHNEIER (15 de enero de 1963, Nueva York). Apodado «el gurú de la seguridad» digital por The Economist, Bruce Schneier es posiblemente el criptógrafo más reconocido de Estados Unidos. Autor de una decena de libros en materia de seguridad informática, más de doscientas cincuenta mil personas leen sus influyentes Newsletter Crypto-Gram y blog Schneier on Security. Además, ha testificado ante el Congreso de Estados Unidos, ha participado en varios comités gubernamentales y aparece frecuentemente en televisión. Entre las instituciones con las que colabora destacan la Universidad de Harvard e IBM. Más contenido aquí: 📢Nuevo canal informativo en Telegram: https://t.me/historiasparaserleidas 🛑BIO Olga Paraíso: https://instabio.cc/Hleidas Recuerda que para que todo esto siga funcionando hace falta apoyo. Deja un corazoncito en el audio, comenta qué te ha parecido, súbelo a tus redes sociales o incluso aporta tu granito de arena de forma económica pulsado en el botón AZUL apoyar de este mismo podcast. Todo suma. ¡GRACIAS!🚀 ❗️https://www.ivoox.com/support/552842
This week's show is in observance of Yom HaShoah, Holocaust Remembrance Day. Highlights: Rabbi Arthur Schneier, Holocaust survivor, world-renowned human rights activist, and senior rabbi of Manhattan's Park East Synagogue for more than fifty years, shares his wartime memories of the Carpathian town Yasinia (Ukrainian: Ясіня; Hungarian: Körösmező; Czech: Jasiňa; Yiddish: Yasin (יאַסין)). He recalls his grandfather, the town's rabbi, Moyshe Bergmann, and describes his narrow escape from the 1941 Kamenets Podolsk Massacre. We reached Rabbi Schneier at his Manhattan office via Zoom on Feb. 20, 2025. See also Rabbi Arthur Schneier's page at Park East Synagogue: https://parkeastsynagogue.org/about-us/clergy/rabbi-arthur-schneier/ Rebbetzin Yetta Kane is a Holocaust survivor who grew up in Miadziol (Belarusian: Мядзел; Yiddish: Miadl (מיאַדל)), a small town in Belarus. She shares memories of her childhood and her and her family's survival, including hiding from the Nazis in the forests of Belarus in a Partisan camp. Yetta's and her late husband, Rabbi and Cantor David Kane, are authors of the´ memoir How to Survive Anything: The Life Story of David and Yetta Kane. We interviewed her at her home in the Los Angeles area on April 8, 2025. Music: Holocaust songs by various musicians and soloists. Intro instrumental music: DEM HELFANDS TANTS, an instrumental track from the CD Jeff Warschauer: The Singing Waltz Air date: April 23, 2025
Justin invites Dan Schneier from Big Blue Banter to talk about the Giants draft needs and rate some prospects the Giants are looking at!Follow Dan Schneier here:https://www.youtube.com/@bigbluebanter1108twitter.com/DanSchneierNFL00:00 Dan Schneier Joins The Show02:30 What Do The Giants Need To Do14:40 Should The Giants Trade Back19:50 Carter or Hunter29:50 QBs- Shough or Milroe46:05 DLs- Collins or Norman-Lott57:18 Cameron Skattebo sleeper pick at RB01:03:00 RBs-Johnson or JudkinsUse code GIANTS2025 for 10% off your next SeatGeek order*: https://seatgeek.onelink.me/RrnK/GIANTS2025. Sponsored by SeatGeek. *Restrictions apply. Max $20 discountGo to KushyDreams.com and use Promo Code JOMBOY420 for 30% off and enter to win free stuff!Join our Patreon: https://Patreon.com/TalkinGiantsCheck out our Merch: https://shop.jomboymedia.com/collections/talkin-giantsSubscribe to JM Football for our NFL coverage: https://www.youtube.com/@JMFootballSubscribe to the JM Newsletter: http://jomboymedia.com/email#giants #nygiants
Keynote speaker for the upcoming RPR Dickinson banquet
In this episode, we speak with Avi Schneier, an expert in Scrum@Scale. Avi and Dee explore how the Scrum@Scale framework enables organizations to scale agility effectively by improving cross-team collaboration and executive alignment. He also talks about the upcoming Scrum@Scale Assessment, developed in collaboration with Comparative Agility, which helps organizations identify inefficiencies, uncover growth opportunities, and enhance their scaling strategies.
Join Dan Schneier as he breaks down his top 12 tight ends for the 2025 Fantasy Football season! Get expert insights and rankings to help you dominate your fantasy draft and make the best TE selections. Watch FFT on YouTube https://www.youtube.com/fantasyfootballtoday SUBSCRIBE to FFT Express on Apple: https://podcasts.apple.com/us/podcast/fantasy-football-today-express/id1528634304 Follow FFT Express on Spotify: https://open.spotify.com/show/6qyGWfETSBFaciPrtvoWCC?si=6529cbee20634da8 SUBSCRIBE to FFT Dynasty on Apple: https://podcasts.apple.com/us/podcast/fantasy-football-today-dynasty/id1696679179 FOLLOW FFT Dynasty on Spotify: https://open.spotify.com/show/2aHlmMJw1m8FareKybdNfG?si=8487e2f9611b4438&nd=1 SUBSCRIBE to FFT DFS on Apple: https://podcasts.apple.com/us/podcast/fantasy-football-today-dfs/id1579415837 FOLLOW FFT DFS on Spotify: https://open.spotify.com/show/5zU7pBvGK3KPhfb69Q1hNr?si=1c5030a3b1a64be2 Follow our FFT team on Twitter: @FFToday, @AdamAizer, @JameyEisenberg, @daverichard, @heathcummingssr Follow the brand new FFT TikTok account: https://www.tiktok.com/@fftoday Join our Facebook group https://www.facebook.com/groups/FantasyFootballToday/ Sign up for the FFT newsletter https://www.cbssports.com/newsletter You can listen to Fantasy Football Today on your smart speakers! Simply say "Alexa, play the latest episode of the Fantasy Football Today podcast" or "Hey Google, play the latest episode of the Fantasy Football Today podcast." Visit the betting arena on CBSSports.com for all the latest sportsbook reviews and sportsbook promos. To learn more about listener data and our privacy practices visit: https://www.audacyinc.com/privacy-policy Learn more about your ad choices. Visit https://podcastchoices.com/adchoices
Her talk "God, I Really Don't Have Time For This!"
Why is it still important for Jewish people to remain distinct? What is your favorite holiday? Join guest speaker Rabbi David Schneier of Congregation Beth Hallel in Birmingham, Alabama, as he reflects on the interaction between Jew and Gentile in a body of believers united by Yeshua the Messiah. It is imperative to take action and build bridges between these distinct groups to strengthen G-d's kingdom. Shabbat Shalom!Romans 3.1-4; Romans 1.1-4; Romans 1.16; John 10.14-16; Romans 11.1-2; Romans 11.12; Romans 11.18-21; Romans 11.25-26; John 17.20-23Prayer Requests or send an email to info@bethhallel.orgCBH WebsiteDonateYouTube Channel
In this episode, Adrianna is joined by Dan Schneier of Big Blue Banter and CBS Sports. They cover off on all things Giants - the excitement of the win over Seattle, what he's seen from Jalin Hyatt on tape, how the Giants can beat the Bengals and more. They also talk about how they really feel about Coach Daboll and GM Joe Schoen as well as make predictions for the Giants vs Bengals game.
Dan and Nick rack up their first mailbag of the 2024 season and Schneier's thrilled about it because there are no more fun podcasts in lost seasons than these ones! They rip off a slew of questions, trying their best to fit everyone in with the spillover landing on the preview pod (at the end). Discussions of the future for the regime, what they need to see to keep Schoen, Daboll, what's next for the QB and the offensive line and a lot more are answered. They discuss Brian Burns, the future CB1 and a lot more as well. It's a jampacked episode with almost every one of your questions answered. Learn more about your ad choices. Visit podcastchoices.com/adchoices
In this episode of Secure Talk, Justin Beals, founder and CEO of Strike Graph, hosts Bruce Schneier, a renowned security technologist, author, and lecturer at the Harvard Kennedy School. Schneier discusses his book 'A Hacker's Mind,' sharing insights into the psychology of security, societal impacts of cybersecurity, and how businesses can better align security practices with human psychology. He emphasizes the economic incentives behind security design, the concept of decoupling for enhanced security, and addresses the role of public awareness and policy in cybersecurity. Schneier also touches on the pervasive nature of hacking, the importance of building resilient systems, and the integration of computers into every aspect of our lives, highlighting the increasing importance of security by design.
If you want a little snapshot of who's who in Boston's folk music history, look no further than "The Folk Music Portrait Project" featuring photographer Barry Schneier. From legendary performers like Tom Rush to contemporary artists like Lori McKenna, join Morgan tonight as he chats with Schneier about his work photographing famous musicians. Morgan White Fills In On NightSide with Dan ReaAsk Alexa to play WBZ NewsRadio on #iHeartRadio!
Welcome solo and group practice owners! We are Liath Dalton and Evan Dumas, your co-hosts of Group Practice Tech. In our latest episode, we explain what goes into HIPAA security reminders, which are required under the HIPAA Security Rule. We discuss our favorite resources for security reminders; our PCT security reminder memes for group or solo practice; documenting security reminders; why security reminders are more useful than annual training; and using current events to inform your security reminders. Listen here: https://personcenteredtech.com/group/podcast/ For more, visit our website. Resources: Sign up for the OCR's listserv here Sign up for HealthIT Security's newsletter as well, which you can do here (the signup is in a box on the righthand of the screen) Sign up for Bruce Schneier of Schneier on Security's newsletter here PCT Resources: PCT's free digital Security Reminder Posters Sign up for PCT's free Security Reminder Memes Assignable staff training: HIPAA Security Awareness Grab Bag A collection of three short courses helping you maintain your security awareness through better handling of PHI in public, avoiding inappropriate disclosures, and preventing phishing and social engineering attacks. PCT podcast episode: Episode 412: Staff HIPAA Training in Year 2, and Beyond Group Practice Care Premium weekly (live & recorded) direct support & consultation service, Group Practice Office Hours + assignable staff HIPAA Security Awareness: Bring Your Own Device training + access to Device Security Center with step-by-step device-specific tutorials & registration forms for securing and documenting all personally owned & practice-provided devices (for *all* team members at no per-person cost) + assignable staff HIPAA Security Awareness: Remote Workspaces training for all team members + access to Remote Workspace Center with step-by-step tutorials & registration forms for securing and documenting Remote Workspaces (for *all* team members at no per-person cost) + more HIPAA Risk Analysis & Risk Mitigation Planning service for mental health group practices -- care for your practice using our supportive, shame-free risk analysis and mitigation planning service. You'll have your Risk Analysis done within 2 hours, performed by a PCT consultant, using a tool built specifically for mental health group practice, and a mitigation checklist to help you reduce your risks.
Heath Cummings is joined by Dan Schneier to completely re-rank the rookies after a week of training camp. Intro (0:00) Can Malik Nabers overcome his situation in Year 1? (1:46) Does any other pass catcher on the Giants matter in Dynasty? (7:20) How do you envision the Giants running back room working out? (9:00) Re-Ranking 1-4 (11:40) Re-Ranking 5-9 (15:28) Re-Ranking 10-14 (23:47) Re-Ranking 15-16 (30:28) Re-Ranking 17-24 (36:26) Favorite players outside of top 24 (47:43) To learn more about listener data and our privacy practices visit: https://www.audacyinc.com/privacy-policy Learn more about your ad choices. Visit https://podcastchoices.com/adchoices
Heath Cummings is joined by Dan Schneier to completely re-rank the rookies after a week of training camp. Intro (0:00) Can Malik Nabers overcome his situation in Year 1? (1:46) Does any other pass catcher on the Giants matter in Dynasty? (7:20) How do you envision the Giants running back room working out? (9:00) Re-Ranking 1-4 (11:40) Re-Ranking 5-9 (15:28) Re-Ranking 10-14 (23:47) Re-Ranking 15-16 (30:28) Re-Ranking 17-24 (36:26) Favorite players outside of top 24 (47:43) To learn more about listener data and our privacy practices visit: https://www.audacyinc.com/privacy-policy Learn more about your ad choices. Visit https://podcastchoices.com/adchoices
In today's episode, host Tyler Chisholm is joined by Elliott Schneier, COO of Virtual Gurus, to look into the evolving landscape of startup funding, the nuances of remote work, and the strategic growth of tech companies outside traditional hubs. Elliott shares his extensive experience helping founders raise over $750 million in investment capital and discusses the current investor market's shift toward seed and pre-seed funding amidst a cautious venture capital environment. Listeners will gain insights into the operational challenges of scaling businesses, the importance of simplifying user experiences, and the critical need for objective decision-making in entrepreneurship.This episode is sponsored by clearmotive marketing. When it comes to marketing that truly matters to your business, clearmotive is your go-to partner. With a proven track record of more than 15 years, they understand what makes your business tick. Learn more at https://www.clearmotive.ca and discover how clearmotive can help your marketing thrive.We're on social media! Follow us for episodes you might have missed and key insights on Western Canada directly on your feeds.Instagram: https://www.instagram.com/collisionsyycLinkedIn: https://www.linkedin.com/company/collisions-yycYouTube: https://www.youtube.com/@collisionsyycWebsite: https://www.collisionsyyc.comThank you for tuning into Collisions YYC!Remember to subscribe and follow us on Spotify and Apple Podcasts so you never miss an episode.If you loved the episode, please leave us a 5-star review and share the show with your friends! These things really help us reach more potential fans and share everything that's amazing about Western Canada.We sincerely appreciate your support of our local podcast.Host links:Tyler's website: https://www.tylerchisholm.comTyler's LinkedIn: https://www.linkedin.com/in/tylerchisholmGuest links:Elliot Schneier's LinkedIn: https://www.linkedin.com/in/elliotschneier/Virtual Gurus' Website: https://www.thevirtualgurus.comVirtual Gurus' LinkedIn: https://www.linkedin.com/company/your-virtual-gurusVirtual Gurus' Facebook: https://www.facebook.com/yourvirtualgurusVirtual Gurus' Instagram: https://www.instagram.com/virtuals_gurusVirtual Gurus' Twitter: https://www.twitter.com/virtual_gurusCollisions YYC is a Tyler Chisholm original production // Brought to you by clearmotive marketing
CBS Sports' Dan Schneier joins the show to talk about the Giants 2024 Draft class and more! Follow Dan Schneier: https://x.com/DanSchneierNFL 00:00 intro + Dexter Lawrence Softball Event! 05:30 Dan Schneier Joins the Show! 07:45 Thoughts on JJ McCarthy 10:00 Malik Nabers ceiling? 17:22 What stands out about Tyler Nubin 21:45 Thoughts on Shane Bowen's Defense 31:10 Thoughts on Andru Phillips 36:44 OL Worries? 45:20 Theo Johnsons overview 53:22 Tyrone Tracy Jr. Role? This episode was brought to you by SeatGeek Use code GIANTS10 for 10% off tickets on SeatGeek. https://seatgeek.onelink.me/RrnK/GIANTS10 *Up to $25 off Get in on the action with DraftKings Sportsbook and use promo code WORLD when signing up so they know we sent you! Join our Patreon: https://Patreon.com/TalkinGiants Tickets to our tailgates: https://shop.jomboymedia.com/products/talkin-giants-l16-tailgate-series?variant= Check out our Merch: https://shop.jomboymedia.com/collections/talkin-giants Subscribe to JM Football for our NFL coverage: https://www.youtube.com/@JMFootball Subscribe to the JM Newsletter: http://jomboymedia.com/email #giants #nygiants Gambling problem? Call one eight hundred gambler or in West Virginia visit W W W dot one eight hundred gambler dot net. In New York, call eight seven seven eight HOPENY or text HOPENY (four six seven three six nine). In Connecticut, Help is available for problem gambling: call eight eight eight seven eight nine seven seven seven seven, or visit ccpg dot org. Please play responsibly. On behalf of Boot Hill Casino & Resort (in Kansas). Twenty one plus age varies by jurisdiction. Void in Ontario. One No Sweat Bet per new customer. Issued as one Bonus Bet based on amount of initial losing bet. Bonus bets expire one hundred sixty eight hours after issuance See D K N G dot co slash baseball for eligibility, wagering and deposit restrictions, terms, and responsible gaming resources.
Our interview with Matthew Schneier is critically delicious. Matthew—chief restaurant critic for New York Magazine—made his glorious return to to the show nearly 6 years later to the day to expand our palate on buying socks once a quarter, the honor and privilege of having the best job in the world, whether or not there is any redeemable value of TikTok restaurant reviews and if they're actually being encouraged, his own phone eating first, behind every good food critic is a better team of health and wellness professionals keeping their waistline in check, the critic's responsibility to the people, vibes vs. what's on the plate, a return to weirdness, can he even grab a casual bite anymore, a plethora of food and drink trend forecasting, NYC's glorious history of restaurants and their respective scenes, immediate green flags and pet peeves when eating out, chomping on brains and slurping shaft, being engaged to a Greek comedian podcaster, hanging with Ina Garten and Martha Stewart, his last meal on earth, the childhood dream of being a waiter, does he miss anything about working in fashion, the joys of becoming a local, the clothing to homegoods pipeline, the art of managing expectations and much more on Matthew Schneier's interview with The Only Podcast That Matters™. For more Throwing Fits, check us out on Patreon: www.patreon.com/throwingfits.
Bruce Schneier is an internationally renowned security technologist, called a “security guru” by The Economist. He is a public-interest technologist, working at the intersection of security, technology, and people. Schneier was at the first ever RSA Conference in 1991, and he was the first 'exhibitor' in 1994 when he asked Jim Bidzos, Creator of the RSA Conference, if he could sell copies of his book "Applied Cryptography". Bidzos set Schneier up in the hotel lobby where the conference was being held - and the rest is history. Listen to some great RSA Conference memories on this episode of the History of RSA Conference.
May 9 1974 - Bruce Springsteen performed a show that is considered to be a watershed moment in his career. A local photographer, Barry Schneier, had seen Bruce perform a few months earlier and suggested to the promoter that Bruce should open for Bonnie Raitt that night at The Harvard Square Theatre, Cambridge, MA. The promoter agreed and Bruce was booked in to perform at short notice. Also in the audience that night was Jon Landau, a music critic for Rolling Stone and The Real Paper. What Jon witnessed that night, and would write about afterwards, would alter Bruce's life, and indeed his own. Not only was Barry instrumental in putting Bruce on the bill that famous night, but he was there with his camera to capture this important piece of musical history. For more details on Barry's book 'Bruce Springsteen: Rock and Roll Future' - visit barryschneierphotography.com or any other major online store like 'you know who'! Pull up a chair, pour your favourite drink and rewind 50 years. Enjoy. --- Send in a voice message: https://podcasters.spotify.com/pod/show/jeff-matthews4/message
Dan Schneier, host of the Big Blue Banter podcast and senior fantasy editor for CBS Sports, joins Lori to detail why the first week of free agency was a success for both the Giants and the Jets.
Catholic speaker, Patty Schneier, shares her powerful conversion story regarding the Church's teaching on contraception within marriage.
Matthew Schneier is currently the chief restaurant critic at New York magazine and previously reported on fashion and culture at The Cut and the New York Times. Matthew joined us in the studio to talk about the job he took over a little more than six months ago. We discuss putting his own unique stamp on the coverage, what he looks for in both old and new NYC restaurants to review, and how he came to the job in the first place. Matthew is one of our favorite writers around, and it was so great catching up.Also on the show, Aliza and Matt catch up about three things they each are into right now, including: Patita at Spoon & Pork in Los Angeles, the forthcoming cookbook from Los Angeles restaurant Kismet, Kismet: Bright, Fresh, Vegetable-Loving Recipes, clam kalguksu at Hangari Kalguksu in Los Angeles, Mom's Touch Lab in Seoul, Little Fatty in Los Angeles, and come to France this summer with Matt and Marissa Mullen! Do you enjoy This Is TASTE? Drop us a review on Apple, or star us on Spotify. We'd love to hear from you. MORE FROM MATTHEW SCHNEIER:Will Four Twenty Five Kill the Grill [NY Mag]Not-So-Plain Slices [NY Mag]Keith McNally, to Go [NY Mag]The Good Used Book Edition [WITI]
If the internet helped create the era of mass surveillance, then artificial intelligence will bring about an era of mass spying.That's the latest prediction from noted cryptographer and computer security professional Bruce Schneier, who, in December, shared a vision of the near future where artificial intelligence—AI—will be able to comb through reams of surveillance data to answer the types of questions that, previously, only humans could. “Spying is limited by the need for human labor,” Schneier wrote. “AI is about to change that.”As theorized by Schneier, if fed enough conversations, AI tools could spot who first started a rumor online, identify who is planning to attend a political protest (or unionize a workforce), and even who is plotting a crime.But “there's so much more,” Schneier said.“To uncover an organizational structure, look for someone who gives similar instructions to a group of people, then all the people they have relayed those instructions to. To find people's confidants, look at whom they tell secrets to. You can track friendships and alliances as they form and break, in minute detail. In short, you can know everything about what everybody is talking about.”Today, on the Lock and Code podcast with host David Ruiz, we speak with Bruce Schneier about artificial intelligence, Soviet era government surveillance, personal spyware, and why companies will likely leap at the opportunity to use AI on their customers.“Surveillance-based manipulation is the business model [of the internet] and anything that gives a company an advantage, they're going to do.”Tune in today to listen to the full conversation.You can also find us on Apple Podcasts, Spotify, and Google Podcasts, plus whatever preferred podcast platform you use.For all our cybersecurity coverage, visit Malwarebytes Labs at malwarebytes.com/blog.Show notes and credits:Intro Music: “Spellbound” by Kevin MacLeod (incompetech.com)Licensed under Creative Commons: By Attribution 4.0 Licensehttp://creativecommons.org/licenses/by/4.0/Outro Music: “Good God” by Wowa (unminus.com)Listen up—Malwarebytes doesn't just talk cybersecurity, we provide it.Protect yourself from online attacks that threaten your identity, your files, your system, and your financial well-being with our exclusive offer for Malwarebytes Premium for Lock and Code listeners.
Joseph Schneier is CEO of Trusty.care, connecting sales, marketing, and member engagement for 150m Americans that receive insurance through Medicare, Medicaid, or Marketplace plans. The company provides an enterprise SaaS solution to the country's most direct-to-consumer health insurance sector. Joseph says that most insurtech founders do not have personal experience in this space but that it has a disfragmented distribution network and many similar challenges as the private insurance sector. Just as a refresher, Medicare's coverage is 85% for people over the age of 65 and 15% for people living with chronic conditions, Medicaid covers low-income individuals and marketplace plans or Obamacare Plans that primarily focuses on small businesses or people who work for one. These plans comprise a whopping 150m Americans or almost half the country's population, making the US one of the largest socialized, government-connected healthcare systems in the world. Although the government is the payer, most of the underlying plans are in turn managed by private insurers (think Aetna, Humana) and marketed through TV ads. Joseph previously built and exited companies in the education space and is now applying the same lessons to the healthcare space. Mr. Schneier has been at the forefront of innovations in global and domestic education, government, value-based healthcare, and insurance technology for over 20 years. He has built companies and products studying value-based care with complex populations, co-founded and exited two companies, and is a Fellow at Columbia University's MBA Entrepreneurial Program. He continues to focus on care for older Americans and has founded two other companies in this space—Cinematic Health, which trains CNAs, Home Health Aides, and Personal Care Assistants, and BellAge a company working with Area Agencies on Aging on longevity initiatives. Follow the Insurtech Leadership Podcast airing weekly hosted by Joshua R. Hollander. We give you up-close access and personal insights from the leaders of the fastest-growing #insurtechs and most innovative #insurance carriers and brokers.
Josh and Kurt talk about security skills shortage. We start out on the topic of cybersecurity skills and weave our way around a number of human related problems in this space. The world of tech has a lot of weird problems and there's not a lot of movement to fix many of them. Tech is weird and hard, and with the almost complete lack of regulation creates some of these challenges. In the world of security we need a better talent pipeline, but that takes actual efforts, not just complaining on the internet. Show Notes Schneier on security skill shortage British Airways flight smoke The Password Game Tesla accidents Lawn darts
Kennedy School Lecturer in Public Policy Bruce Schneier says Artificial Intelligence has the potential to transform the democratic process in ways that could be good, bad, and potentially mind-boggling. The important thing, he says, will be to use regulation and other tools to make sure that AIs are working for us, and just not for Big Tech companies—a hard lesson we've already learned through our experience with social media. When ChatGPT and other generative AI tools were released to the public late last year, it was as if someone had opened the floodgates on a thousand urgent questions that just weeks before had mostly preoccupied academics, futurists, and science fiction writers. Now those questions are being asked by many of us—teachers, students, parents, politicians, bureaucrats, citizens, businesspeople, and workers. What can it do for us? What will it do to us? Will it take our jobs? How do we use it in a way that's both ethical and legal? And will it help or hurt our already-distressed democracy? Schneier, a public interest technologist, cryptographer, and internationally-known internet security specialist whose newsletter and blog are read by a quarter million people, says that AI's inexorable march into our lives and into our politics is likely to start with small changes, like AI helping write policy and legislation. The future, however, could hold possibilities that we have a hard time wrapping our current minds around—like AI entities creating political parties or autonomously fundraising and generating profits to back political candidates or causes. Overall, like a lot of other things. it's likely to be a mixed bag of the good and the bad.Bruce Schneier is a Lecturer in Public Policy at the Harvard Kennedy School, a faculty affiliate at the Ash Center for Democratic Governance and Innovation at HKS, a fellow at the Berkman-Klein Center for Internet and Society at Harvard University. An internationally renowned security technologist, he has been called a "security guru" by the Economist and is the New York Times best-selling author of 14 books—including A Hacker's Mind—as well as hundreds of articles, essays, and academic papers. His influential newsletter “Crypto-Gram” and blog “Schneier on Security” are read by over 250,000 people. Schneier is a board member of the Electronic Frontier Foundation and AccessNow, and an advisory board member of EPIC and VerifiedVoting.org. He is the Chief of Security Architecture at Inrupt, Inc.Ralph Ranalli of the HKS Office of Public Affairs and Communications is the host, producer, and editor of HKS PolicyCast. A former journalist, public television producer, and entrepreneur, he holds an AB in Political Science from UCLA and an MS in Journalism from Columbia University.PolicyCast is co-produced by Susan Hughes. Design and graphics support is provided by Lydia Rosenberg, Delane Meadows and the OCPA Design Team. Social media promotion and support is provided by Natalie Montaner and the OCPA Digital Team.
It's ESVN Week #50 (!) Emma and Bradley start out by discussing Trey Lance getting traded to Dallas, the continuing fallout from the investigation into Spanish soccer official Luis Rubiales, and discuss some odds for division winners going into the NFL season. Then, Emma talks to Dan Schneier, host of the Big Blue Banter podcast & Senior Fantasy Sports Editor at CBSSports, to give some fantasy advice going into week 1. Follow Dan on Twitter here: https://twitter.com/DanSchneierNFL Check out Big Blue Banter here: https://www.youtube.com/channel/UCJ5JxdXQ6xh48GL8kGQJT0w Follow Emma and Bradley on Twitter: @EmmaVigeland @BradKAlsop Check out Ava Raiza's music here! https://avaraiza.bandcamp.com/
Lori chats with Dan Schneier, host of the Big Blue Banter Podcast and Senior Fantasy Sports Editor for CBS Sports, to discuss the New York Football Giants and some players to look out for in your fantasy football drafts.
What is hacking? We asked Bruce Schneier, New York Times best-selling author of "A Hacker's Mind," which answers the question. For more on hacking, visit Schneier's website, https://schneier.com
"Big Blue Banter" podcast host Dan Schneier joins Lori to discuss what's next for Saquon Barkley and how the Giants look overall with training camp about to open.
What is hacking? We asked Bruce Schneier, New York Times best-selling author of "A Hacker's Mind," which answers the question. In this episode, we talk about flight tickets and how some travelers are creatively saving money. For more on hacking, visit Schneier's website, https://schneier.com
What is hacking? We asked Bruce Schneier, New York Times best-selling author of "A Hacker's Mind," which answers the question. In this episode, we talk about flight tickets and how some travelers are creatively saving money. For more on hacking, visit Schneier's website, https://schneier.com
What is hacking? We asked Bruce Schneier, New York Times best-selling author of "A Hacker's Mind," which answers the question. In this episode, we talk about AirBnB listings and how some property owners are increasing their property's occupancy. For more on hacking, visit Schneier's website, https://schneier.com
00:00 Intro + OTA Expectations 4:20 Welcome Dan Schneier 6:00 Deonte Banks has Dan excited 12:30 Jalin Hyatt 15:55 How will this Giants offense look? 18:50 Concern of the league figuring out the Giants offense? 23:00 Who plays more WR4 or Daniel Bellinger? 24:30 John Michael Schmitz 29:00 Safety rotation + look out for Dane Belton 35:10 Why didn't the Giants get interceptions last year? 39:50 How do we feel about the run defense? 48:30 Wrap up This episode was brought to you by SeatGeek Use code GIANTS for $20 off your first SeatGeek order: https://seatgeek.onelink.me/RrnK/GIANTS Join our Patreon: https://Patreon.com/TalkinGiants Check out our Merch: https://shop.jomboymedia.com/collections/talkin-giants Subscribe to JM Football to see Bobby's Draft Breakdowns: https://www.youtube.com/@JMFootball
What is hacking? We asked Bruce Schneier, New York Times best-selling author of "A Hacker's Mind," which answers the question. In this episode, we talk about AirBnB listings and how some property owners are increasing their property's occupancy. For more on hacking, visit Schneier's website, https://schneier.com
"Big Blue Banter" host Dan Schneier joins Lori to recap the Giants draft.
What is hacking? We asked Bruce Schneier, New York Times best-selling author of "A Hacker's Mind," which answers the question. In this episode, we talk about travel expenses, and the practice of being strategic about credit card points and miles in order to save on plane tickets. For more on hacking, visit Schneier's website, https://schneier.com
What is hacking? We asked Bruce Schneier, New York Times best-selling author of "A Hacker's Mind," which answers the question. In this episode, we cover a common practice among Netflix users: password sharing, which gained popularity for allowing friends and family members to access a wider variety of content without having to pay for additional accounts. For more on hacking, visit Schneier's website, https://schneier.com
On the latest #CybersecurityByDesign conversation, we've got our minds set on… hacking. Bruce Schneier, author of the recently published *A Hacker's Mind: How the Powerful Bend Society's Rules and How to Bend Them Back Again,* chats with Sam Rehman, EPAM's Chief Information Security Officer and SVP, about the hacking mindset and what it means for security in the age of generative AI. Schneier gets the conversation rolling by defining a hacker as “Someone who finds a bug or vulnerability, a loophole in a set of rules, and exploits it to their advantage.” He talks about hacking not just computers but tax systems, hockey, tax codes, and Formula 1 racing. Rehman mentions that he appreciated a couple of Schneider's examples and Schneier replies: “There are a couple? There are dozens of examples! Examples are what makes the book fun!” (Reader: The book is fun indeed.) Schneier notes that “hacking isn't necessarily good nor bad,” which might surprise some who live outside the perimeter of the cybersecurity world. “Hacking is how systems evolve. If I figure a clever way to use a system, to subvert a system that no one thought of before, there are benefits as well as costs.” The guys then get into the inevitable topic of 2023: The costs and benefits of hacking in the context of AI. “I think it's gonna be a big arms race in AI and security,” says Schneier, adding that in the near term, AI will benefit the defender. “The attacker is already attacking at computer speeds. Being able to defend at computer speeds will be an enormous benefit.” While he's generally optimistic that AI will be good for the good guys, Schneier says “The transition period will be very chaotic.” This chaos will come from the idea of AI has a hacker. He points to the idea of accountants—human ones—poring through tax code looking for loopholes to exploit: “That feels like something that you can train an AI to do,” he says. “And what happens when AI finds vulnerabilities in tax codes or financial regulations or other sets of laws? How will that work? How fast will they be? How clever will they be? Will they find things that are just so complicated that humans would never have found them?” Schneier says that AI will increase the speed, scale, sophistication, and scope of hacking and wonders if these differences in degree will make a difference in kind. Then he answers: “The advances in AI in the past six months have been enormous. The next six months will be even bigger. Conversations we have today aren't going to be true in six months.” What won't change, however, is the hacker's essential mind, which Reman admits has always been part of him: “I have always looked at everything as: ‘What else can I do with this?'” “That's totally the hacker mindset,” replies Schneier. “I don't think you can train that. I think that is something you either are or are not.” Host: Macy Donaway Engineer: Kyp Pilalas Producer: Ken Gordon
Happy Monday! In a pre-taped conversation, Sam speaks with Bruce Schneier, lecturer in Public Policy at the Harvard Kennedy School, to discuss his recent book A Hacker's Mind: How the Powerful Bend Society's Rules, and How to Bend them Back. First Emma, runs through updates on the leaking of classified documents about the Russian invasion of Ukraine, the potential reinstatement of Rep. Justin Jones to the Tennessee Statehouse, the revelations about Harlan Crow's interests (beyond buying politicians), Rutgers' faculty strike, and Israel's expansive bombings over Ramadan, before parsing through the recent overturning (and overturning of said overturning?) of the multi-decade precedent of the FDA's approval of the abortion pill Mifepristone. Next, Bruce Schneier dives right into the concept of hacking as a way to subvert the intent of a system while following its rules, something not inherently negative or criminal, as he walks Sam through myriad examples of non-digital hacking, from the first filibuster to the rules of F1 and cricket, and how those in power of the system responded. Sam and Schneier then turn more particularly to the role that power plays in this equation, with hacks against those with power getting codified out while hacks by the powerful are often accepted, walking through the politics of tax loopholes and financial “hacks” in comparison to the technological hacking of financial institutions and corporations. Wrapping up, they explore how to push back on this power imbalance, the role Artificial Intelligence, in particular, can play in helping the public scope out and regulate the hacks of the elites, and why keeping AI privatized is antithetical to its ability to level the playing field. And in the Fun Half, Emma and Bradley discuss Clarence Thomas's Nazi-curious friend Harlan Crow and his breathless flop sweating defenders (Jonah Goldberg, David French, Ben Shapiro and...Glenn Greenwald), Jon Stewart taking on a Defense Department ghoul on C-SPAN, Nancy Mace surprisingly siding with AOC on not following freak Texas Judge Kacsmaryk's abortion court order, the tragic uncoupling of Elon Musk and Matt Taibbi, plus your calls & IM's! Check out Bruce's book here: https://www.schneier.com/books/a-hackers-mind/ Become a member at JoinTheMajorityReport.com: https://fans.fm/majority/join Subscribe to the ESVN YouTube channel here: https://www.youtube.com/esvnshow Subscribe to the AMQuickie newsletter here: https://am-quickie.ghost.io/ Join the Majority Report Discord! http://majoritydiscord.com/ Get all your MR merch at our store: https://shop.majorityreportradio.com/ Get the free Majority Report App!: http://majority.fm/app Check out today's sponsors: Sunset Lake CBD: sunsetlakecbd is a majority employee owned farm in Vermont, producing 100% pesticide free CBD products. Starting today, all CBD products will be 30% off with coupon code “420”. Orders over $150 will get one FREE 20-count jar of gummies-Sour bears, good vibe gummies, or sleep gummies! 5% of all proceeds will be donated to the Last Prisoner Project-and The Majority Report will match those donations! Also, use code Leftisbest and get 20% off when you shop at http://www.sunsetlakecbd.com. ZipRecruiter: Some things in life we like to pick out for ourselves - so we know we've got the one that's best for us - like cuts of steak or mattresses. What if you could do the same for hiring - choose your ideal candidate before they even apply? See for yourself! Just go to this exclusive web address, https://www.ziprecruiter.com/majority to try ZipRecruiter for free! Follow the Majority Report crew on Twitter: @SamSeder @EmmaVigeland @MattBinder @MattLech @BF1nn @BradKAlsop Check out Matt's show, Left Reckoning, on Youtube, and subscribe on Patreon! https://www.patreon.com/leftreckoning Subscribe to Discourse Blog, a newsletter and website for progressive essays and related fun partly run by AM Quickie writer Jack Crosbie. https://discourseblog.com/ Check out Ava Raiza's music here! https://avaraiza.bandcamp.com/ The Majority Report with Sam Seder - https://majorityreportradio.com/
What is hacking? We asked Bruce Schneier, New York Times best-selling author of "A Hacker's Mind," which answers the question. In this episode, we cover an "ingenious hack," according to The Daily Mail, that "helps callers bypass the endless automated questions now used by most major firms' helplines and get straight through to a human being." For more on hacking, visit Schneier's website, https://schneier.com
Links from the show:* A Hacker's Mind: How the Powerful Bend Society's Rules, and How to Bend Them Back* Visit Bruce's site* Follow Bruce on Twitter* Follow Ryan on Twitter* Support the showAbout my guest:Bruce Schneier is an internationally renowned security technologist, called a “security guru” by The Economist. He is the author of over one dozen books—including his latest, We Have Root—as well as hundreds of articles, essays, and academic papers. His influential newsletter “Crypto-Gram” and his blog “Schneier on Security” are read by over 250,000 people. He has testified before Congress, is a frequent guest on television and radio, has served on several government committees, and is regularly quoted in the press. Schneier is a fellow at the Berkman Klein Center for Internet & Society at Harvard University; a Lecturer in Public Policy at the Harvard Kennedy School; a board member of the Electronic Frontier Foundation and AccessNow; and an Advisory Board Member of the Electronic Privacy Information Center and VerifiedVoting.org. He is the Chief of Security Architecture at Inrupt, Inc. Get full access to Dispatches from the War Room at dispatchesfromthewarroom.substack.com/subscribe
Matthew Coller gets together with Dan Schneier of the Big Blue Banter podcast to talk about how Daniel Jones' playing style has changed vastly over season under Brain Daboll, how the matchups in the trenches will probably determine this game and whether Saquon Barkley is as dangerous now as he was earlier in the season. Learn more about your ad choices. Visit megaphone.fm/adchoicesSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
Matthew Coller gets together with Dan Schneier of the Big Blue Banter podcast to talk about how Daniel Jones' playing style has changed vastly over season under Brain Daboll, how the matchups in the trenches will probably determine this game and whether Saquon Barkley is as dangerous now as he was earlier in the season. Learn more about your ad choices. Visit podcastchoices.com/adchoices
About RamDr. Ram Sriharsha held engineering, product management, and VP roles at the likes of Yahoo, Databricks, and Splunk. At Yahoo, he was both a principal software engineer and then research scientist; at Databricks, he was the product and engineering lead for the unified analytics platform for genomics; and, in his three years at Splunk, he played multiple roles including Sr Principal Scientist, VP Engineering and Distinguished Engineer.Links Referenced: Pinecone: https://www.pinecone.io/ XKCD comic: https://www.explainxkcd.com/wiki/index.php/1425:_Tasks TranscriptAnnouncer: Hello, and welcome to Screaming in the Cloud with your host, Chief Cloud Economist at The Duckbill Group, Corey Quinn. This weekly show features conversations with people doing interesting work in the world of cloud, thoughtful commentary on the state of the technical world, and ridiculous titles for which Corey refuses to apologize. This is Screaming in the Cloud.Corey: This episode is sponsored in part by our friends at Chronosphere. Tired of observability costs going up every year without getting additional value? Or being locked into a vendor due to proprietary data collection, querying, and visualization? Modern-day, containerized environments require a new kind of observability technology that accounts for the massive increase in scale and attendant cost of data. With Chronosphere, choose where and how your data is routed and stored, query it easily, and get better context and control. 100% open-source compatibility means that no matter what your setup is, they can help. Learn how Chronosphere provides complete and real-time insight into ECS, EKS, and your microservices, wherever they may be at snark.cloud/chronosphere that's snark.cloud/chronosphere.Corey: This episode is brought to you in part by our friends at Veeam. Do you care about backups? Of course you don't. Nobody cares about backups. Stop lying to yourselves! You care about restores, usually right after you didn't care enough about backups. If you're tired of the vulnerabilities, costs, and slow recoveries when using snapshots to restore your data, assuming you even have them at all living in AWS-land, there is an alternative for you. Check out Veeam, that's V-E-E-A-M for secure, zero-fuss AWS backup that won't leave you high and dry when it's time to restore. Stop taking chances with your data. Talk to Veeam. My thanks to them for sponsoring this ridiculous podcast.Corey: Welcome to Screaming in the Cloud. I'm Corey Quinn. Today's promoted guest episode is brought to us by our friends at Pinecone and they have given their VP of Engineering and R&D over to suffer my various sling and arrows, Ram Sriharsha. Ram, thank you for joining me.Ram: Corey, great to be here. Thanks for having me.Corey: So, I was immediately intrigued when I wound up seeing your website, pinecone.io because it says right at the top—at least as of this recording—in bold text, “The Vector Database.” And if there's one thing that I love, it is using things that are not designed to be databases as databases, or inappropriately referring to things—be they JSON files or senior engineers—as databases as well. What is a vector database?Ram: That's a great question. And we do use this term correctly, I think. You can think of customers of Pinecone as having all the data management problems that they have with traditional databases; the main difference is twofold. One is there is a new data type, which is vectors. Vectors, you can think of them as arrays of floats, floating point numbers, and there is a new pattern of use cases, which is search.And what you're trying to do in vector search is you're looking for the nearest, the closest vectors to a given query. So, these two things fundamentally put a lot of stress on traditional databases. So, it's not like you can take a traditional database and make it into a vector database. That is why we coined this term vector database and we are building a new type of vector database. But fundamentally, it has all the database challenges on a new type of data and a new query pattern.Corey: Can you give me an example of what, I guess, an idealized use case would be of what the data set might look like and what sort of problem you would have in a vector database would solve?Ram: A very great question. So, one interesting thing is there's many, many use cases. I'll just pick the most natural one which is text search. So, if you're familiar with the Elastic or any other traditional text search engines, you have pieces of text, you index them, and the indexing that you do is traditionally an inverted index, and then you search over this text. And what this sort of search engine does is it matches for keywords.So, if it finds a keyword match between your query and your corpus, it's going to retrieve the relevant documents. And this is what we call text search, right, or keyword search. You can do something similar with technologies like Pinecone, but what you do here is instead of searching our text, you're searching our vectors. Now, where do these vectors come from? They come from taking deep-learning models, running your text through them, and these generate these things called vector embeddings.And now, you're taking a query as well, running them to deep-learning models, generating these query embeddings, and looking for the closest record embeddings in your corpus that are similar to the query embeddings. This notion of proximity in this space of vectors tells you something about semantic similarity between the query and the text. So suddenly, you're going beyond keyword search into semantic similarity. An example is if you had a whole lot of text data, and maybe you were looking for ‘soda,' and you were doing keyword search. Keyword search will only match on variations of soda. It will never match ‘Coca-Cola' because Coca-Cola and soda have nothing to do with each other.Corey: Or Pepsi, or pop, as they say in the American Midwest.Ram: Exactly.Corey: Yeah.Ram: Exactly. However, semantic search engines can actually match the two because they're matching for intent, right? If they find in this piece of text, enough intent to suggest that soda and Coca-Cola or Pepsi or pop are related to each other, they will actually match those and score them higher. And you're very likely to retrieve those sort of candidates that traditional search engines simply cannot. So, this is a canonical example, what's called semantic search, and it's known to be done better by these other vector search engines. There are also other examples in say, image search. Just if you're looking for near duplicate images, you can't even do this today without a technology like vector search.Corey: What is the, I guess, translation or conversion process of existing dataset into something that a vector database could use? Because you mentioned it was an array of floats was the natural vector datatype. I don't think I've ever seen even the most arcane markdown implementation that expected people to wind up writing in arrays of floats. What does that look like? How do you wind up, I guess, internalizing or ingesting existing bodies of text for your example use case?Ram: Yeah, this is a very great question. This used to be a very hard problem and what has happened over the last several years in deep-learning literature, as well as in deep-learning as a field itself, is that there have been these large, publicly trained models, examples will be OpenAI, examples will be the models that are available in Hugging Face like Cohere, and a large number of these companies have come forward with very well trained models through which you can pass pieces of text and get these vectors. So, you no longer have to actually train these sort of models, you don't have to really have the expertise to deeply figured out how to take pieces of text and build these embedding models. What you can do is just take a stock model, if you're familiar with OpenAI, you can just go to OpenAIs homepage and pick a model that works for you, Hugging Face models, and so on. There's a lot of literature to help you do this.Sophisticated customers can also do something called fine-tuning, which is built on top of these models to fine-tune for their use cases. The technology is out there already, there's a lot of documentation available. Even Pinecone's website has plenty of documentation to do this. Customers of Pinecone do this [unintelligible 00:07:45], which is they take piece of text, run them through either these pre-trained models or through fine-tuned models, get the series of floats which represent them, vector embeddings, and then send it to us. So, that's the workflow. The workflow is basically a machine-learning pipeline that either takes a pre-trained model, passes them through these pieces of text or images or what have you, or actually has a fine-tuning step in it.Corey: Is that ingest process something that not only benefits from but also requires the use of a GPU or something similar to that to wind up doing the in-depth, very specific type of expensive math for data ingestion?Ram: Yes, very often these run on GPUs. Sometimes, depending on budget, you may have compressed models or smaller models that run on CPUs, but most often they do run on GPUs, most often, we actually find people make just API calls to services that do this for them. So, very often, people are actually not deploying these GPU models themselves, they are maybe making a call to Hugging Face's service, or to OpenAI's service, and so on. And by the way, these companies also democratized this quite a bit. It was much, much harder to do this before they came around.Corey: Oh, yeah. I mean, I'm reminded of the old XKCD comic from years ago, which was, “Okay, I want to give you a picture. And I want you to tell me it was taken within the boundaries of a national park.” Like, “Sure. Easy enough. Geolocation information is attached. It'll take me two hours.” “Cool. And I also want you to tell me if it's a picture of a bird.” “Okay, that'll take five years and a research team.”And sure enough, now we can basically do that. The future is now and it's kind of wild to see that unfolding in a human perceivable timespan on these things. But I guess my question now is, so that is what a vector database does? What does Pinecone specifically do? It turns out that as much as I wish it were otherwise, not a lot of companies are founded on, “Well, we have this really neat technology, so we're just going to be here, well, in a foundational sense to wind up ensuring the uptake of that technology.” No, no, there's usually a monetization model in there somewhere. Where does Pinecone start, where does it stop, and how does it differentiate itself from typical vector databases? If such a thing could be said to exist yet.Ram: Such a thing doesn't exist yet. We were the first vector database, so in a sense, building this infrastructure, scaling it, and making it easy for people to operate it in a SaaS fashion is our primary core product offering. On top of that, this very recently started also enabling people who have who actually have raw text to not just be able to get value from these vector search engines and so on, but also be able to take advantage of traditional what we call keyword search or sparse retrieval and do a combined search better, in Pinecone. So, there's value-add on top of this that we do, but I would say the core of it is building a SaaS managed platform that allows people to actually easily store as data, scale it, query it in a way that's very hands off and doesn't require a lot of tuning or operational burden on their side. This is, like, our core value proposition.Corey: Got it. There's something to be said for making something accessible when previously it had only really been available to people who completed the Hello World tutorial—which generally resembled a doctorate at Berkeley or Waterloo or somewhere else—and turn it into something that's fundamentally, click the button. Where on that, I guess, a spectrum of evolution do you find that Pinecone is today?Ram: Yeah. So, you know, prior to Pinecone, we didn't really have this notion of a vector database. For several years, we've had libraries that are really good that you can pre-train on your embeddings, generate this thing called an index, and then you can search over that index. There is still a lot of work to be done even to deploy that and scale it and operate it in production and so on. Even that was not being, kind of, offered as a managed service before.What Pinecone does which is novel, is you no longer have to have this pre-training be done by somebody, you no longer have to worry about when to retrain your indexes, what to do when you have new data, what to do when there is deletions, updates, and the usual data management operations. You can just think of this is, like, a database that you just throw your data in. It does all the right things for you, you just worry about querying. This has never existed before, right? This is—it's not even like we are trying to make the operational part of something easier. It is that we are offering something that hasn't existed before, at the same time, making it operationally simple.So, we're solving two problems, which is we building a better database that hasn't existed before. So, if you really had this sort of data management problems and you wanted to build an index that was fresh that you didn't have to super manually tune for your own use cases, that simply couldn't have been done before. But at the same time, we are doing all of this in a cloud-native fashion; it's easy for you to just operate and not worry about.Corey: You've said that this hasn't really been done before, but this does sound like it is more than passingly familiar specifically to the idea of nearest neighbor search, which has been around since the '70s in a bunch of different ways. So, how is it different? And let me of course, ask my follow-up to that right now: why is this even an interesting problem to start exploring?Ram: This is a great question. First of all, nearest neighbor search is one of the oldest forms of machine learning. It's been known for decades. There's a lot of literature out there, there are a lot of great libraries as I mentioned in the passing before. All of these problems have primarily focused on static corpuses. So basically, you have a set of some amount of data, you want to create an index out of it, and you want to query it.A lot of literature has focused on this problem. Even there, once you go from small number of dimensions to large number of dimensions, things become computationally far more challenging. So, traditional nearest neighbor search actually doesn't scale very well. What do I mean by large number of dimensions? Today, deep-learning models that produce image representations typically operate in 2048 dimensions of photos [unintelligible 00:13:38] dimensions. Some of the OpenAI models are even 10,000 dimensional and above. So, these are very, very large dimensions.Most of the literature prior to maybe even less than ten years back has focused on less than ten dimensions. So, it's like a scale apart in dealing with small dimensional data versus large dimensional data. But even as of a couple of years back, there hasn't been enough, if any, focus on what happens when your data rapidly evolves. For example, what happens when people add new data? What happens if people delete some data? What happens if your vectors get updated? These aren't just theoretical problems; they happen all the time. Customers of ours face this all the time.In fact, the classic example is in recommendation systems where user preferences change all the time, right, and you want to adapt to that, which means your user vectors change constantly. When even these sort of things change constantly, you want your index to reflect it because you want your queries to catch on to the most recent data. [unintelligible 00:14:33] have to reflect the recency of your data. This is a solved problem for traditional databases. Relational databases are great at solving this problem. A lot of work has been done for decades to solve this problem really well.This is a fundamentally hard problem for vector databases and that's one of the core focus areas [unintelligible 00:14:48] painful. Another problem that is hard for these sort of databases is simple things like filtering. For example, you have a corpus of say product images and you want to only look at images that maybe are for the Fall shopping line, right? Seems like a very natural query. Again, databases have known and solved this problem for many, many years.The moment you do nearest neighbor search with these sort of constraints, it's a hard problem. So, it's just the fact that nearest neighbor search and lots of research in this area has simply not focused on what happens to that, so those are of techniques when combined with data management challenges, filtering, and all the traditional challenges of a database. So, when you start doing that you enter a very novel area to begin with.Corey: This episode is sponsored in part by our friends at Redis, the company behind the incredibly popular open-source database. If you're tired of managing open-source Redis on your own, or if you are looking to go beyond just caching and unlocking your data's full potential, these folks have you covered. Redis Enterprise is the go-to managed Redis service that allows you to reimagine how your geo-distributed applications process, deliver and store data. To learn more from the experts in Redis how to be real-time, right now, from anywhere, visit snark.cloud/redis. That's snark dot cloud slash R-E-D-I-S.Corey: So, where's this space going, I guess is sort of the dangerous but inevitable question I have to ask. Because whenever you talk to someone who is involved in a very early stage of what is potentially a transformative idea, it's almost indistinguishable from someone who is whatever the polite term for being wrapped around their own axle is, in a technological sense. It's almost a form of reverse Schneier's Law of anyone can create an encryption algorithm that they themselves cannot break. So, the possibility that this may come back to bite us in the future if it turns out that this is not potentially the revelation that you see it as, where do you see the future of this going?Ram: Really great question. The way I think about it is, and the reason why I keep going back to databases and these sort of ideas is, we have a really great way to deal with structured data and structured queries, right? This is the evolution of the last maybe 40, 50 years is to come up with relational databases, come up with SQL engines, come up with scalable ways of running structured queries on large amounts of data. What I feel like this sort of technology does is it takes it to the next level, which is you can actually ask unstructured questions on unstructured data, right? So, even the couple of examples we just talked about, doing near duplicate detection of images, that's a very unstructured question. What does it even mean to say that two images are nearly duplicate of each other? I couldn't even phrase it as kind of a concrete thing. I certainly cannot write a SQL statement for it, but I cannot even phrase it properly.With these sort of technologies, with the vector embeddings, with deep learning and so on, you can actually mathematically phrase it, right? The mathematical phrasing is very simple once you have the right representation that understands your image as a vector. Two images are nearly duplicate if they are close enough in the space of vectors. Suddenly you've taken a problem that was even hard to express, let alone compute, made it precise to express, precise to compute. This is going to happen not just for images, not just for semantic search, it's going to happen for all sorts of unstructured data, whether it's time series, where it's anomaly detection, whether it's security analytics, and so on.I actually think that fundamentally, a lot of fields are going to get disrupted by this sort of way of thinking about things. We are just scratching the surface here with semantic search, in my opinion.Corey: What is I guess your barometer for success? I mean, if I could take a very cynical point of view on this, it's, “Oh, well, whenever there's a managed vector database offering from AWS.” They'll probably call it Amazon Basics Vector or something like that. Well, that is a—it used to be a snarky observation that, “Oh, we're not competing, we're just validating their market.” Lately, with some of their competitive database offerings, there's a lot more truth to that than I suspect AWS would like.Their offerings are nowhere near as robust as what they pretend to be competing against. How far away do you think we are from the larger cloud providers starting to say, “Ah, we got the sense there was money in here, so we're launching an entire service around this?”Ram: Yeah. I mean, this is a—first of all, this is a great question. There's always something that's constantly, things that any innovator or disrupter has to be thinking about, especially these days. I would say that having a multi-year head, start in the use cases, in thinking about how this system should even look, what sort of use cases should it [unintelligible 00:19:34], what the operating points for the [unintelligible 00:19:37] database even look like, and how to build something that's cloud-native and scalable, is very hard to replicate. Meaning if you look at what we have already done and kind of tried to base the architecture of that, you're probably already a couple of years behind us in terms of just where we are at, right, not just in the architecture, but also in the use cases in where this is evolving forward.That said, I think it is, for all of these companies—and I would put—for example, Snowflake is a great example of this, which is Snowflake needn't have existed if Redshift had done a phenomenal job of being cloud-native, right, and kind of done that before Snowflake did it. In hindsight, it seems like it's obvious, but when Snowflake did this, it wasn't obvious that that's where everything was headed. And Snowflake built something that's very technologically innovative, in a sense that it's even now hard to replicate. Plus, it takes a long time to replicate something like that. I think that's where we are at.If Pinecone does its job really well and if we simply execute efficiently, it's very hard to replicate that. So, I'm not super worried about cloud providers, to be honest, in this space, I'm more worried about our execution.Corey: If it helps anything, I'm not very deep into your specific area of the world, obviously, but I am optimistic when I hear people say things like that. Whenever I find folks who are relatively early along in their technological journey being very concerned about oh, the large cloud provider is going to come crashing in, it feels on some level like their perspective is that they have one weird trick, and they were able to crack that, but they have no defensive mode because once someone else figures out the trick, well, okay, now we're done. The idea of sustained and lasting innovation in a space, I think, is the more defensible position to take, with the counterargument, of course, that that's a lot harder to find.Ram: Absolutely. And I think for technologies like this, that's the only solution, which is, if you really want to avoid being disrupted by cloud providers, I think that's the way to go.Corey: I want to talk a little bit about your own background. Before you wound up as the VP of R&D over at Pinecone, you were in a bunch of similar… I guess, similar styled roles—if we'll call it that—at Yahoo, Databricks, and Splunk. I'm curious as to what your experience in those companies wound up impressing on you that made you say, “Ah, that's great and all, but you know what's next? That's right, vector databases.” And off, you went to Pinecone. What did you see?Ram: So, first of all, in was some way or the other, I have been involved in machine learning and systems and the intersection of these two for maybe the last decade-and-a-half. So, it's always been something, like, in the in between the two and that's been personally exciting to me. So, I'm kind of very excited by trying to think about new type of databases, new type of data platforms that really leverages machine learning and data. This has been personally exciting to me. I obviously learned very different things from different companies.I would say that Yahoo was just the learning in cloud to begin with because prior to joining Yahoo, I wasn't familiar with Silicon Valley cloud companies at that scale and Yahoo is a big company and there's a lot to learn from there. It was also my first introduction to Hadoop, Spark, and even machine learning where I really got into machine learning at scale, in online advertising and areas like that, which was a massive scale. And I got into that in Yahoo, and it was personally exciting to me because there's very few opportunities where you can work on machine learning at that scale, right?Databricks was very exciting to me because it was an earlier-stage company than I had been at before. Extremely well run and I learned a lot from Databricks, just the team, the culture, the focus on innovation, and the focus on product thinking. I joined Databricks as a product manager. I hadn't played the product manager hat before that, so it was very much a learning experience for me and I think I learned from some of the best in that area. And even at Pinecone, I carry that forward, which is think about how my learnings at Databricks informs how we should be thinking about products at Pinecone, and so on. So, I think I learned—if I had to pick one company I learned a lot from, I would say, it's Databricks. The most [unintelligible 00:23:50].Corey: I would also like to point out, normally when people say, “Oh, the one company I've learned the most from,” and they pick one of them out of their history, it's invariably the most recent one, but you left there in 2018—Ram: Yeah.Corey: —then went to go spend the next three years over at Splunk, where you were a Senior Principal, Scientist, a Senior Director and Head of Machine-Learning, and then you decided, okay, that's enough hard work. You're going to do something easier and be the VP of Engineering, which is just wild at a company of that scale.Ram: Yeah. At Splunk, I learned a lot about management. I think managing large teams, managing multiple different teams, while working on very different areas is something I learned at Splunk. You know, I was at this point in my career when I was right around trying to start my own company. Basically, I was at a point where I'd taken enough learnings and I really wanted to do something myself.That's when Edo and I—you know, the CEO of Pinecone—and I started talking. And we had worked together for many years, and we started working together at Yahoo. We kept in touch with each other. And we started talking about the sort of problems that I was excited about working on and then I came to realize what he was working on and what Pinecone was doing. And we thought it was a very good fit for the two of us to work together.So, that is kind of how it happened. It sort of happened by chance, as many things do in Silicon Valley, where a lot of things just happen by network and chance. That's what happened in my case. I was just thinking of starting my own company at the time when just a chance encounter with Edo led me to Pinecone.Corey: It feels from my admittedly uninformed perspective, that a lot of what you're doing right now in the vector database area, it feels on some level, like it follows the trajectory of machine learning, in that for a long time, the only people really excited about it were either sci-fi authors or folks who had trouble explaining it to someone without a degree in higher math. And then it turned into—a couple of big stories from the mid-2010s stick out at me when we've been people were trying to sell this to me in a variety of different ways. One of them was, “Oh, yeah, if you're a giant credit card processing company and trying to detect fraud with this kind of transaction volume—” it's, yeah, there are maybe three companies in the world that fall into that exact category. The other was WeWork where they did a lot of computer vision work. And they used this to determine that at certain times of day there was congestion in certain parts of the buildings and that this was best addressed by hiring a second barista. Which distilled down to, “Wait a minute, you're telling me that you spent how much money on machine-learning and advanced analyses and data scientists and the rest have figured out that people like to drink coffee in the morning?” Like, that is a little on the ridiculous side.Now, I think that it is past the time for skepticism around machine learning when you can go to a website and type in a description of something and it paints a picture of the thing you just described. Or you can show it a picture and it describes what is in that picture fairly accurately. At this point, the only people who are skeptics, from my position on this, seem to be holding out for some sort of either next-generation miracle or are just being bloody-minded. Do you think that there's a tipping point for vector search where it's going to become blindingly obvious to, if not the mass market, at least more run-of-the-mill, more prosaic level of engineer that haven't specialized in this?Ram: Yeah. It's already, frankly, started happening. So, two years back, I wouldn't have suspected this fast of an adoption for this new of technology from this varied number of use cases. I just wouldn't have suspected it because I, you know, I still thought, it's going to take some time for this field to mature and, kind of, everybody to really start taking advantage of this. This has happened much faster than even I assumed.So, to some extent, it's already happening. A lot of it is because the barrier to entry is quite low right now, right? So, it's very easy and cost-effective for people to create these embeddings. There is a lot of documentation out there, things are getting easier and easier, day by day. Some of it is by Pinecone itself, by a lot of work we do. Some of it is by, like, companies that I mentioned before who are building better and better models, making it easier and easier for people to take these machine-learning models and use them without having to even fine-tune anything.And as technologies like Pinecone really mature and dramatically become cost-effective, the barrier to entry is very low. So, what we tend to see people do, it's not so much about confidence in this new technology; it is connecting something simple that I need this sort of value out of, and find the least critical path or the simplest way to get going on this sort of technology. And as long as it can make that barrier to entry very small and make this cost-effective and easy for people to explore, this is going to start exploding. And that's what we are seeing. And a lot of Pinecone's focus has been on ease-of-use, in simplicity in connecting the zero-to-one journey for precisely this reason. Because not only do we strongly believe in the value of this technology, it's becoming more and more obvious to the broader community as well. The remaining work to be done is just the ease of use and making things cost-effective. And cost-effectiveness is also what the focus on a lot. Like, this technology can be even more cost-effective than it is today.Corey: I think that it is one of those never-mistaken ideas to wind up making something more accessible to folks than keeping it in a relatively rarefied environment. We take a look throughout the history of computing in general and cloud in particular, were formerly very hard things have largely been reduced down to click the button. Yes, yes, and then get yelled at because you haven't done infrastructure-as-code, but click the button is still possible. I feel like this is on that trendline based upon what you're saying.Ram: Absolutely. And the more we can do here, both Pinecone and the broader community, I think the better, the faster the adoption of this sort of technology is going to be.Corey: I really want to thank you for spending so much time talking me through what it is you folks are working on. If people want to learn more, where's the best place for them to go to find you?Ram: Pinecone.io. Our website has a ton of information about Pinecone, as well as a lot of standard documentation. We have a free tier as well where you can play around with small data sets, really get a feel for vector search. It's completely free. And you can reach me at Ram at Pinecone. I'm always happy to answer any questions. Once again, thanks so much for having me.Corey: Of course. I will put links to all of that in the show notes. This promoted guest episode is brought to us by our friends at Pinecone. Ram Sriharsha is their VP of Engineering and R&D. And I'm Cloud Economist Corey Quinn. If you've enjoyed this podcast, please leave a five-star review on your podcast platform of choice, whereas if you've hated this podcast, please leave a five-star review on your podcast platform of choice along with an angry, insulting comment that I will never read because the search on your podcast platform is broken because it's not using a vector database.Corey: If your AWS bill keeps rising and your blood pressure is doing the same, then you need The Duckbill Group. We help companies fix their AWS bill by making it smaller and less horrifying. The Duckbill Group works for you, not AWS. We tailor recommendations to your business and we get to the point. Visit duckbillgroup.com to get started.Announcer: This has been a HumblePod production. Stay humble.
Elisabeth Egan, an editor at the Book Review, curates our Group Text column — a monthly choice of a book that she feels is particularly well suited to book clubs and their discussions. On this week's podcast, she talks about her latest pick: “Jackie & Me,” by Louis Bayard, which imagines the friendship between Jacqueline Bouvier and Lem Billings, a close friend of the Kennedys.“This is rooted in reality,” Egan says, “but Bayard runs with it and imagines conversations between Lem and Jackie, and just shows this, on one hand, fabulous life of parties and museums and fun they had together, but also sets up this ticking clock where you come to understand what Jackie really has at stake, and has to lose by committing to this life with the Kennedys.”Matthew Schneier visits the podcast to discuss Paula Byrne's new biography, “The Adventures of Miss Barbara Pym.” Pym, a British writer, began publishing novels in the 1950s.“She published six novels in pretty quick succession, and they're great,” Schneier says of the first decade or so of her career. “Very clever, very witty, she was often compared to Jane Austen — which was a writer that she loved and appreciated, but also a kind of very easy comparison, whereas Pym's ironies can be a little bit darker than some of Austen's. And there's a sense in her work that she is spotlighting characters who are not the Emma Woodhouses, who are beautiful and rich and effervescent. They're what she ended up calling ‘excellent women,' which is the title of I think her best starter novel. These women who are well brought up and very proper, a little bit pious, but can also be a little dowdy, a little dreary, a little bit easier to overlook.”Also on this week's episode, Alexandra Alter talks about the filmmaker Werner Herzog and his first novel, “The Twilight World”; and Jennifer Szalai and Molly Young talk about books they've recently reviewed. John Williams is the host.Here are the books discussed by The Times's critics this week:“The Facemaker” by Lindsey Fitzharris“Meet Me by the Fountain” by Alexandra Lange
Bobby and Justin are joined by Dan Schneier of the Big Blue Banter podcast to talk all about the Giants draft class, Dan's thoughts on most of the picks, what he likes/dislikes about it, and more! This episode was presented by SeatGeek Go to https://getroman.com/WORLD today, and if you're prescribed, get $15 off your first month of ED treatment. Get in on the action with DraftKings Sportsbook and use promo code JOMBOY when signing up so they know we sent you! https://dkng.co/jomboy If you or someone you know has a gambling problem, crisis counseling and referral services can be accessed by calling 1-800-GAMBLER (1-800-426-2537) (IL/IN/MI/NJ/PA/WV/WY), 1-800-NEXTSTEP (AZ), 1-800-522-4700 (CO/NH), 888-789-7777/ visit http://ccpg.org/chat (CT), 1-800-BETS OFF (IA), 1-877-770-STOP(7867) (LA), 877-8-HOPENY/text HOPENY (467369) (NY), visit OPGR.org (OR), call/text TN REDLINE 1-800-889-9789 (TN), or 1-888-532-3500 (VA). 21+ (18+ NH/WY). Physically present in AZ/CO/CT/IL/IN/IA/LA/MI/NH/NJ/NY/OR/ PA/TN/VA/WV/WY only. Min. $5 deposit required. Eligibility restrictions apply. See https://draftkings.com/sportsbook for details.
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