Podcasts about recommendation engine

Would AI be a better president than Donald Trump? That's one of many questions raised in this invigorating and topical episode of the podcast Deep Fought. It's actually more of a philosophical discussion than a political one, so sit back and enjoy a discussion of whether utilitarian ideals are appropriate for democratic administration. Plus, we're jingle heavy, with a Mailbag, Science News, Recommendation Engine, and Michael's debut of a brand new seggy. This episode's mistakes include: Pitt pit slander. Furthering the atheist agenda. Misunderstanding an email. Egregious factual inaccuracies. Be wary of hearing damage, then like us on Facebook, follow us on Instagram, rate us on Apple Podcasts and Spotify, and send your questions to deepfought@gmail.com.

Get your own 1 on 1 coach NOW!  https://vidiq.ink/tubetalk1on1In this episode of Tube Talk, Travis and Jen discuss the topic of buying views and subscribers on YouTube. They start by addressing feedback from a listener who was confused about the term '10 of 10' mentioned in a previous episode. Travis explains that '10 of 10' refers to the ranking of a video among the last 10 videos uploaded. They then delve into the dangers and ineffectiveness of buying views and subscribers, emphasizing that it does not lead to an engaged audience or help with monetization goals. They also discuss the practice of buying established channels and the pitfalls associated with it. In this conversation, Travis and Jenn discuss the challenges of being a YouTuber and the importance of hard work and dedication. They emphasize that success on YouTube requires more than just wanting to make money and that there are no shortcuts to building a successful channel. They also discuss the differences between YouTube promotions and Google ads, highlighting the importance of understanding your target audience and utilizing the recommendation engine to grow your channel.This episode was hosted by Travis and Jenn of vidIQ. If you have any questions, please feel free to email support@vidiq.com or email the show theboost@vidiq.com

Wie reif ist ein Unternehmen, was schon vor zehn Jahren Kampagnenmanagement etabliert hat? Auf was muss man achten, um immer noch modern zu sein? Wie baut man eine datengetriebene Organisation aus und ist datengetrieben überhaupt das richtige Wort? Darum geht es in der neuen Folge von MY DATA IS BETTER THAN YOURS, die ihren Fokus auf Strategie und Organisation legt. Zu Gast beim Host Jonas Rashedi ist Oliver Kelz, Head of Data & Analytics bei Congstar, einer hundertprozentigen Tochter der Telekom mit etwa 300 Mitarbeitenden. Sein Ziel: Den Weg zur data driven Company gestalten. Aber ist datengetrieben überhaupt das richtige Wort? Beide Data Nerds stimmen überein: Das getriebene ist so negativ. Wichtig ist es, auf die Daten zu vertrauen und sie an den richtigen Stellen einzusetzen. Oliver nutzt deswegen auch lieber die Vision der data inspired Company. Zur Vision ist ihm auch noch wichtig, dass die verschiedenen Fachabteilungen nicht alle ihr eigenes GenAI-Ding machen, sondern gemeinsam am Big Picture gearbeitet wird. Außerdem geht es in dieser Folge um das Kampagnenmanagement, das früher auf die klassischen Touchpoints ausgelegt war, mittlerweile aber bis zu 10 Touchpoints beinhaltet. Das Ziel ist es, die richtige Nachricht zur richtigen Zeit auf dem richtigen Kanal zu senden. Schließlich geht die Entwicklung stark in Richtung digital und damit auch etwas weiter weg von Briefen. Oliver's Team hat einen guten Blick darauf, was der Kunde tut und was ihn in Zukunft interessieren könnte. Das ist nicht nur ein Recommendation-Engine, sondern das ist stark auf den Lifecycle des Kunden fokussiert. In der Telekommunikationsbranche gelten auch andere Regeln als im eCommerce! Dabei muss immer zwischen Push und Pull entschieden werden. Das Wichtigste ist aber die Konsistenz in der Kommunikation. Für die Entwicklung dieses Kampagnenmanagements war die Personalisierung ein Leuchtturmprojekt, was nun auch weitere Data-Projekte ermöglicht hat. Zum Schluss geht es noch um das Thema Time-to-Market und darum, wie man diese KPI misst, aber auch darum, ob das Kampagnenmanagementtool von Oliver auch als Customer Data Platform gesehen werden könnte. MY DATA IS BETTER THAN YOURS ist ein Projekt von BETTER THAN YOURS, der Marke für richtig gute Podcasts. Zum LinkedIn-Profil von Oliver: https://www.linkedin.com/in/oliver-kelz-0ba69919a/ Zur Webseite von congstar: https://www.congstar.de/ Zu allen wichtigen Links rund um Jonas und den Podcast: https://linktr.ee/jonas.rashedi Zur Podcast Umfrage (Jede Woche wird ein Hoodie verlost!): https://listening.sslsurvey.de/Data-Podcast-Feedback

Build low-latency recommendation engines with Azure Cosmos DB and Azure OpenAI Service. Elevate user experience with vector-based semantic search, going beyond traditional keyword limitations to deliver personalized recommendations in real-time. With pre-trained models stored in Azure Cosmos DB, tailor product predictions based on user interactions and preferences. Explore the power of augmented vector search for optimized results prioritized by relevance. Kirill Gavrylyuk, Azure Cosmos DB General Manager, shows how to build recommendation systems with limitless scalability, leveraging pre-computed vectors and collaborative filtering for next-level, real-time insights.   ► QUICK LINKS: 00:00 - Build a low latency recommendation engine 00:59 - Keyword search 01:46 - Vector-based semantic search 02:39 - Vector search built-in to Cosmos DB 03:56 - Model training 05:18 - Code for product predictions 06:02 - Test code for product prediction 06:39 - Augmented vector search 08:23 - Test code for augmented vector search 09:16 - Wrap up   ► Link References Walk through an example at https://aka.ms/CosmosDBvectorSample  Try out Cosmos DB for MongoDB for free at https://aka.ms/TryC4M   ► Unfamiliar with Microsoft Mechanics?  As Microsoft's official video series for IT, you can watch and share valuable content and demos of current and upcoming tech from the people who build it at Microsoft. • Subscribe to our YouTube: https://www.youtube.com/c/MicrosoftMechanicsSeries • Talk with other IT Pros, join us on the Microsoft Tech Community: https://techcommunity.microsoft.com/t5/microsoft-mechanics-blog/bg-p/MicrosoftMechanicsBlog • Watch or listen from anywhere, subscribe to our podcast: https://microsoftmechanics.libsyn.com/podcast   ► Keep getting this insider knowledge, join us on social: • Follow us on Twitter: https://twitter.com/MSFTMechanics  • Share knowledge on LinkedIn: https://www.linkedin.com/company/microsoft-mechanics/ • Enjoy us on Instagram: https://www.instagram.com/msftmechanics/ • Loosen up with us on TikTok: https://www.tiktok.com/@msftmechanics  

Zach and Kevin were joined by Al for a rousing recommendation engine episode! After some hot eclipse talk the fellas recommend a dental thing, a nondental thing and a podcast. We hope you love our recommendations! Some links from the show: Kevin's recommendations SICAT Rapid Guide The Restaurant Club (TRC) The Storyteller: Tales of Life and Music The Joe Rogan Experience Huberman Lab Podcast Zach's recommendations Panavia V5 ("man, that stuff sticks.") Centrix Silversense Lowbackability The Lonely Island and Seth Meyers Podcast Al's recommendations Polydentia Unica anterior matrices X-men '97 The Savage Lovecast (MAGNUM!) Become a member of the Very Clinical Facebook group!  Join the Very Dental Facebook group using the password "Timmerman," Hornbrook," McWethy," "Papa Randy" or "Lipscomb." The Very Dental Podcast network is and will remain free to download. If you'd like to support the shows you love at Very Dental then show a little love to the people that support us! -- Crazy Dental has everything you need from cotton rolls to equipment and everything in between and the best prices you'll find anywhere! If you head over to verydentalpodcast.com/crazy and use coupon code “verydental10” you'll get another 10% off your order! Go save yourself some money and support the show all at the same time! -- The Wonderist Agency is basically a one stop shop for marketing your practice and your brand. From logo redesign to a full service marketing plan, the folks at Wonderist have you covered! Go check them out at verydentalpodcast.com/wonderist! -- Enova Illumination makes the very best in loupes and headlights, including their new ergonomic angled prism loupes! They also distribute loupe mounted cameras and even the amazing line of Zumax microscopes! If you want to help out the podcast while upping your magnification and headlight game, you need to head over to verydentalpodcast.com/enova to see their whole line of products! -- CAD-Ray offers the best service on a wide variety of digital scanners, printers, mills and even  their very own browser based design software, Clinux! CAD-Ray has been a huge supporter of the Very Dental Podcast Network and I can tell you that you'll get no better service on everything digital dentistry than the folks from CAD-Ray. Go check them out at verydentalpodcast.com/CADRay!

Software Delivered AI w/ Brian Stevens of Neural Magic AZ TRT S05 EP08 (223) 2-25-2024  What We Learned This Week Neural Magic Deepsparse software helps B2B Clients incorporate AI into their tech stack Large Language Learning Models of AI can be costly & require massive computing power Their clients now control their AI Model Opensource AI Foundation Models for training AI uses a Recommendation Model         Guest: Brian Stevens Chief Executive Officer of Neural Magic   Brian Stevens is chief executive officer of Neural Magic. A tech veteran with more than 30 years of experience, Brian has a rich history of building/advising high-impact companies and driving disruptions that transform the industry.         In his role at Neural Magic, Brian aims to democratize Generative AI for enterprises and make it more accessible and affordable to all.   In his career, Brian has served in a variety of executive roles at world-renowned companies including VP and CTO of Google Cloud, and CTO and EVP of Worldwide Engineering at Red Hat.   Brian currently serves on the board of directors of Nutanix and Genpact, and is a former member of the board of directors of the American Red Cross, IEEE, OpenStack Foundation, Data Gravity, and Pentaho.   Brian holds a master's degree in computer systems from Rensselaer Polytechnic Institute and a bachelor's degree in computer science from the University of New Hampshire. In his personal life, Brian is an accomplished carpenter and woodworker with a passion for refurbishing old homes.         NEURAL MAGIC   https://neuralmagic.com/     About: Neural Magic is an AI company, born out of the Massachusetts Institute of Technology (MIT), on a mission to help customers innovate with machine learning, without added complexity or cost. While pursuing research at MIT, founders Nir Shavit and Alexander Matveev launched Neural Magic, a software-delivered AI solution, to address their frustration with the constraints of GPUs and existing hardware.   Using Neural Magic's DeepSparse Inference Runtime, customers can easily deploy deep learning models on commodity CPUs with GPU-class performance.   For more information, including all of Neural Magic's offerings, visit https://neuralmagic.com/ or follow @neuralmagic on Twitter, LinkedIn, and YouTube.    Open Source AI for Business-2024 Is the Year to On Ramp   Brian Stevens, CEO of Neural Magic is at the helm of this growing trillion-dollar industry (proper source)   As enterprises prepare for 2024, the growing demand for AI optimization is top of mind.   Neural Magic is fulfilling that need with software-delivered AI. Enterprises use Neural Magic's runtime and open-source sparsification tools for maximum CPU speedups of NLP (including LLMs) and computer vision models.   “It is my goal to democratize AI using optimized CPUs as the onramp to generative AI, making it faster, affordable and agile for enterprises.” – Brian Stevens, CEO, Neural Magic     Neural Magic has created a software architecture for the future of machine learning with an open-source LLM (Large Language Models) approach that enables enterprises to leverage existing commodity hardware (x86 and ARM). The net result demonstrates the power of software and model optimization across different computing platforms to enhance the scalability and efficiency of AI workloads.   Neural Magic was founded in 2017 by MIT professors and research scientists. The company has raised more than $55M from blue chip investors including a recent $35M Series A led by NEA, with participation from Andreessen Horowitz, VMware, Verizon, Amdocs, Comcast, Pillar, and Ridgeline Ventures.   Neural Magic has strategic partnerships with CPU manufacturers like AMD and Intel, cloud providers like AWS and Google Cloud, and software vendors like Red Hat and Ultralytics. These partnerships allow Neural Magic to provide value at all levels of the development lifecycle, from the models themselves down to the silicon.               Notes     Seg 2 AI you've been around since the 1950s and retail businesses have been using AI for years now. Wayfair out of Boston has incorporated AI. They understand the shopper experience.   In its simplest form, AI uses the recommendation model - presents back to you similar things you've been searching for. If you like this, you'll like something similar. This is now a very large part of business revenues, while also helping to better the user experience.   There are large language, AI models, which involve more math in the program and need more computing power. Harder to run this larger AI model.   Businesses need an AI division in their tech stack now. Many large companies have an dedicated AI Lab. This is similar to how they had built out a cloud model in the past. Nowadays though, business understand their models need more integrated.   You train an AI model with company data. Lots of data. Seven data set to start using reference material like Internet sites or Wikipedia. It does cost a lot to change this model.   There are options to build on an existing model open source AI programs. What is used now is called a foundational model, and then you train it on your company product catalog.   Seg 3 Brian‘s background is a computer science degree and software developer. He worked in New England. He's a technologist, solve the problem in use case for tech product manager.   Worked at Redhat through 2001, and the.com crash. Also worked in open source in Linux platforms. Then was at Google cloud, working onsite in Mountain View, California. This was no remote jobs back in 2014. He was there for 5 years and helped with the company going from $50 mil to $10 bil revenue.   Move back to New England. Connected with a professor from MIT, who had started a company on AI software and Brian joined as CEO.   Company is called Neural Magic, and the website is neuralmagic.com. Deepsparse is their software stack which runs deep AI learning model that you deploy on servers.   They fine-tune the model and adapted it to customer stack. This is for businesses to optimize AI for customers. It is similar to an interface with company software. AI language model that is large needs. Lots of infrastructure.   What neural magic does is? It makes the model faster and more efficient.   Seg 4 ChatGPT has changed things with AI. AI interface is similar with API codes with response and language size. Need a model that meets needs with a data set that makes the models run more efficiently on lots of hardware.   Neural magics deep sparse is an inference server and training to deploy in production and could be days to train.   There are 3 challenges with AI for businesses. First is expensive and enterprise does not control things when they use a hosted model or a hosted service like open AI. Second, they have to feed data to the host to train the AI model and there are privacy and security issues. Third you have a lifecycle , which must qualify and test the text stack with each time you update.   Neural Magic allows enterprises to own the AI model. Now they have security, privacy and updates are all handled. This is AI on their own terms and gives them options. Full control and it looks like just another application.   Open source AI machine learning model in the cloud and  can work on servers like Oracle, Amazon - AWS, the Google cloud, or Microsoft Azure. Client has liability with software, and they still need to protect it.   More info go to neural magic.com can learn about the product, the marketing as well as the community.         Seg 1 - Clips from:   Artificial Intelligence (AI) – how the Algorithm Connects Us All - BRT S02 EP43 (90) 10-24-2021   5 Things We Learned This Week: AI is inter-connected with so many technologies & you use AI often on a daily basis AI is a part of almost all industries from Healthcare, Finance to Defense Human in the Loop - humans will always be needed to Interpret the Data, but AI will assist Software Teams must be managed so the product is integrated properly in the bigger picture Moore's Law – Each year computing power grows 2x as fast, but cuts the cost in half     Naru and his team are working on document management, where their AI program will be able to read documents and determine what the info is. Rising Cloud is another project they are building that manages a company cloud usage to improve costs. Moore's Law – Each year computing power grows 2x as fast, but cuts the cost in half Cloud Computing happens in the cloud and internet for your programming vs Edge Computing that happens right on your phone and does not need to go out to the cloud. Bigger the data request or process determines if Cloud or Edge is the best choice. People interact with AI (Artificial Intelligence) daily on their phone, email, internet search and beyond. User Agreements in your phone or websites you use say they can take your search data and use it to enhance your experience. AI Search uses past searches by you, vs what are the popular other searches by other people on the internet. It happens so fast and has the best / popular search options loading before you are even done typing. This is called a Recommendation Engine, just like Netflix or Amazon find shows or products you may like. These recs are similar to what you have watched or bought previously, or in similar genres. The downside is you may not see different options, just more of the same. AI determines what you see daily on the internet, and can create a silo effect. Inventives uses a common solution, called Human in the Loop to review what the AI is doing. Then the searches or recommendations are reviewed to see how accurate they are.       Full Show: HERE           Best of Biotech from AZ Bio & Life Sciences to Jellatech: HERE   Biotech Shows: HERE   AZ Tech Council Shows:  https://brt-show.libsyn.com/size/5/?search=az+tech+council *Includes Best of AZ Tech Council show from 2/12/2023     ‘Best Of' Topic: https://brt-show.libsyn.com/category/Best+of+BRT     Thanks for Listening. Please Subscribe to the BRT Podcast.     AZ Tech Roundtable 2.0 with Matt Battaglia The show where Entrepreneurs, Top Executives, Founders, and Investors come to share insights about the future of business.  AZ TRT 2.0 looks at the new trends in business, & how classic industries are evolving.  Common Topics Discussed: Startups, Founders, Funds & Venture Capital, Business, Entrepreneurship, Biotech, Blockchain / Crypto, Executive Comp, Investing, Stocks, Real Estate + Alternative Investments, and more…    AZ TRT Podcast Home Page: http://aztrtshow.com/ ‘Best Of' AZ TRT Podcast: Click Here Podcast on Google: Click Here Podcast on Spotify: Click Here                    More Info: https://www.economicknight.com/azpodcast/ KFNX Info: https://1100kfnx.com/weekend-featured-shows/     Disclaimer: The views and opinions expressed in this program are those of the Hosts, Guests and Speakers, and do not necessarily reflect the views or positions of any entities they represent (or affiliates, members, managers, employees or partners), or any Station, Podcast Platform, Website or Social Media that this show may air on. All information provided is for educational and entertainment purposes. Nothing said on this program should be considered advice or recommendations in: business, legal, real estate, crypto, tax accounting, investment, etc. Always seek the advice of a professional in all business ventures, including but not limited to: investments, tax, loans, legal, accounting, real estate, crypto, contracts, sales, marketing, other business arrangements, etc.  

Listening to a podcast? What a great idea! But could you take that idea, patent it, and then charge others for the right to do the same? That's the question at the heart of today's discussion – patent law. It's more interesting than it sounds, maybe! Plus we've got mice, we've got birds, we've got pissing contests, and we've got a Recommendation Engine, so I will accept no complaints about content. This episode's mistakes include: Nick audibly melting into a puddle due to temperature. Nick's computer shutting off mid-record due to temperature. Michael's computer shutting off mid-record due to, I dunno, ghosts? Egregious factual inaccuracies. Strip to your underwear, then like us on Facebook, follow us on Instagram, rate us on Apple Podcasts and Spotify, and send your questions to deepfought@gmail.com.

Now, what seems to be the problem? The answer, it turns out, might well be hundreds of millions of years of viral and bacterial infections. This week we're talking about the history of mankind and civilisation through the lens of disease, which proves out to be more mind-blowing than you might expect. Plus, plenty of our normal nonsense (hats, soap, etc.) and a Recommendation Engine to wrap things up. Enjoy. This episode's mistakes include: Unusual podcast segment order. Dense scientific prose. Reckless hatlessness. Egregious factual inaccuracies. Praise our retrovirus ancestors, then like us on Facebook, follow us on Instagram and Spotify, rate us on Apple Podcasts, and send your questions to deepfought@gmail.com.

Hey! Stop scrolling that endless list of podcasts and just click play on this one! We're talking about a bunch of fun things this ep, from Michael's travels through Vietnam (and its associated gym culture), to a rival Olympics competition where drug use is permitted. Plus, there's a big Recommendation Engine full of great things to hold your attention through these cold winter nights. This episode's mistakes include: A lot of upfront toothpaste chat. Unappreciated Mikey's Horoscopes reference. Couldn't find the clip from an earlier podcast to back up Michael's claim. Egregious factual inaccuracies. Release the leopards, then like us on Facebook, follow us on Instagram and Spotify, rate us on Apple Podcasts, and send your questions to deepfought@gmail.com.  

Microsoft stellt Shopping Guides vor und Google zielt wohl bald nach! Werden damit klassische Onlineshops überflüssig? Darüber diskutieren heute Daniel Höhnke und Tim Schestag in dieser E-Commerce Dudes Podcast Folge. In den News der Woche: - Google Checkout angekündigt - Nosto stellt neue Generative AI Features für Suche und Recommendation Engine vor - Amazon geht gegen Retourenkosten vor

In this bonus episode, Eric and Kostas preview their upcoming conversation with Davor Bonaci of DataStax.

What does it take to design products people love in the world of streaming entertainment? To find out, we're joined by Sarah Lyons, streaming media leader, product executive and former Head of Product at HBO Max in conversation with Sean Rhodes, Executive Creative Director of frog North America. Sarah has worked on products that support a fanbase. The scale of HBO Max's reach is massive–around 95 million subscribers worldwide. Sarah shares her own experience building a career in the rapidly evolving world of streaming entertainment, the new consumer trends and behaviors that are shaping the media landscape and where to look for inspiration on what's next for your product roadmap. Hint: it turns out, children truly are the future.Brought to you by frog, a global creative consultancy. frog is part of Capgemini Invent. (https://www.frog.co)Find episode transcripts and relevant info (https://www.frog.co/designmind/design-mind-frogcast-ep-32-the-future-of-streaming-media)Download the new frog report 'The Regenerative Compass' (https://go.frog.co/the-regenerative-compass)Host/Writer: Elizabeth Wood, Editorial Director, frogResearch & Story Support: Camilla Brown, Senior Copyeditor, frogAudio Production: Richard Canham, Lizard Media (https://www.lizardmedia.co.uk)

In this episode, Troy Hammond speaks with Joel Lieser.  Joel Lieser is the CTO of Trove Money, a child company of Forsyth Barr.   His career has spanned seven states and three countries, where he has held positions from global banks to Silicon Valley technology juggernauts like Netflix, and companies like Nike along with multiple startups along the way.   His passions lie in technology innovation and building teams. In this episode, Joel chats about culture, engineering, the differences between US and NZ, and how he thinks we can help get more people into startups. Joel hones in on his career and how our lives are a culmination of the choices we make against our adjacent possibles It is a really interesting episode and we hope you enjoy watching and or listening as much as we did.  Please join us and subscribe to help us. We want to help New Zealand to support its own when it comes to innovation.   To quote Joel: "Don't let the Tall Poppy Syndrome sidetrack us from supporting Kiwis to change the world."

An appeals court is preparing to hear arguments from Epic, Apple, the State of California and even the US Department of Justice in the ongoing battle between developers and Apple. Hackers gained access to Uber's systems and we're not sure how bad it was yet. And Nvidia is announcing new GPUs today! See omnystudio.com/listener for privacy information.

After a restful July, Al has some things you should check out! From bicycle stuff, to podcasts to a switchblade knife, there's a little something for everyone to check out! Al's local (Michigan) bicycles for sale Facebook group Al's new mountain bike (2020 Trek Fuel EX 5) Hot Money: Porn, Power and Profit podcast Al's new knife Al's new headphones Join the Very Dental Facebook group using the password "Timmerman," Hornbrook" or "McWethy." If you'd like to support the Very Dental Podcast Network then you should support our sponsors!  After the course I took at Cosmedent back in May, I realized that polishing restorations, especially composite restorations is an afterthought for most dentists. Getting a beautiful shine with lasting luster is just too much work, so why bother? But what if you could make your patients happier and make your composite restorations last longer? You need to try Enamelize, the aluminum oxide polishing paste from Cosmedent that will change the way you look at composite polish forever. Check it out at verydentalpodcast.com/enamelize! -- Our friends at Spear Education want Very Dental people to know about a special event they're having this summer! This new opportunity brings the leaders in dental education together to Educate, Elevate, and Empower you! Whether a current member or new to Spear, this event will reignite the spark in your practice. It's a “Whitman's Sampler” of all the amazing educators at Spear Education including Frank Spear, Gregg Kinzer, Jeff Rouse, Darin Dichter, Gary DeWood and Ricardo Mitrani! It's clinical! It's business! But most importantly, it's all Spear! Spear live is happening on the east coast in Boston, MA on August 12th and 13th! Go check it out at verydentalpodcast.com/Spear! -- You know that our friends at Zirc are the organization people. With the Color Method and all the different storage and instrument sterilizations options, they'll keep your processes streamlined and efficient! But they're not JUST the organization people. Every dental office should check out the amazing products that Zirc has to offer for organization, isolation and visualization at verydentalpodcast.com/Zirc! -- Our friends at CAD-Ray want you to know that there has never been a better time to get into intraoral scanning! They sell and support all kinds of digital dentistry products from scanners, to printers and even cloud based software! For instance, the Medit i600 itraoral scanner is priced at just about $13,000! And if you didn't know, CAD-Ray now distributes 3Shape scanners and the amazing Trios 4 wireless just had a $10,000 price cut! It comes in under $25,000. And all these options come with CAD-Ray's unbeatable support! Go check it out at verydentalpodcast.com/cadray! -- If there is one thing that's changed the way I look at teeth the most, it's probably the headlight I use with my loupes. Our friends at Enova make amazing loupes and distribute Zumax dental microscopes, both the best you can buy. But the amazing, weightless and cordless Qubit, Quasar or Quantum headlights (all others are just toys) are the biggest game changer. But be careful…if you try one, you're going to buy one! Why haven't you checked out Enova Illumination yet? You can get a killer deal on all things Enova by using the Very Dental link you'll find at verydentalpodcast.com/Enova! -- Have you been looking at your supply bill lately? Prices are REALLY going up on all the things you use every day in your office. Our friends at Crazy Dental understand and are here to help! Very Dental listeners can get 10% off their orders from Crazy Dental by using coupon code “VERYDENTAL10”! Go check out their amazing catalog and save yourself 10% off of their already amazing prices at verydentalpodcast.com/crazy! -- If you're looking for a one stop dental marketing solution, then look no further than the Wonderist Agency. Wonderist can help you with branding and a killer website. They'll design ad campaigns no matter how you want to get your name out there. But maybe most importantly, they'll show you how your marketing plan is working! They have industry leading analytics that help you understand what works and what doesn't in your area and they'll help you spend your marketing dollar in the wisest way possible! Go check out the Wonderist Agency at verydentalpodcast.com/Wonderist!

Neben der signifikanten Verbesserung der Customer Experience gab es für HSE Home Shopping Europe eine klare wirtschaftliche Vision: der Aufbau einer Cross-Selling-Funktionalität mittels Recommendation Engine. In der Einführung einer Conversational AI Lösung sah HSE den perfekten technologischen Ansatz, um die Vision zum Leben zu erwecken. Realisiert wurde daher ein Phonebot zusammen mit Parloa und MUUUH!

(Highlights below) Susan Shu Chang is a principal data scientist at clearco, helping ecommerce founders' by building machine learning-powered investing. In her previous role, she developed the company's very first ML powered website recommender system, deployed to millions of customers, and created a custom OpenAI Gym environment for a reinforcement learning project in production. She is also the founder and developer of Quill Game Studios, selling ~10k copies of the debut game in 6 months. She has given talks at PyCon Canada,Toronto Machine Learning Summit (TMLS), and more. She writes about her career journey and learning on https://www.susanshu.com/ Follow Daliana on Twitter @DalianaLiu for more on data science and this podcast. Highlights (00:00) Intro (00:01:29) from economics to data science (00:07:23) reinforcement learning (RL) (00:20:00) recent reinforcement learning use cases (00:27:28) reinforcement learning for social media's recommender system (01:04:42) common mistakes when productionizing models (01:08:30) principal data scientist's day-to-day (01:14:05) what productivity really means (01:21:04) productivity tips (01:41:48) books and blogs on productivity

Al brings back a "Go Hack Yourself"-esque feature where he gives recommendations of stuff. I know that's a weird description, but it's way better than it sounds. Check it out. Splashtop remote login software Crypto Island podcast PJ Vogt's Substack Elric of Melnibone book/audiobook Early 80's Spotify playlist Redshift Sports Shockstop suspension stem, Redshift Sports Shockstop Seat post Cosmedent felt flexipoints + Enamelize for posterior polishing  Join the Very Dental Facebook group using the password "Timmerman," Hornbrook" or "McWethy." If you'd like to support the Very Dental Podcast Network then you should support our sponsors!  2 days. A bunch of the Spear Education all stars! Literally a Whitman's Sampler of all the greats! (Dr. Frank Spear, Dr. Gary DeWood, Dr. Gregg Kinzer, Dr. Jeff Rouse, Dr. Ricardo Mitrani and Dr. Darin Dichter! Also Adam McWethy! You've heard all of these guys on the podcast and this is a great way to see them all in one huge event! June 16-17 at Spear Education in Scottsdale! August 12-13 in Boston, MA! 14 hours of AMAZING CE! And if you tell them that you heard about it from Very Dental and you'll get $500 off! Go check it out! -- Zirc Dental Products' Color Method will rescue your team from clinical clutter and disorganization and if you use the coupon code “VERYDENTAL” to get 50% off their most popular level of organizational consultation. You'll have a box of all the different trays, tubs, cassettes and other goodies sent ot your office and then have an in depth conversation with one of Zirc's clinical efficiency specialists to help you choose what's best for your office!  So head over to verydentalpodcast.com/zirc and use coupon code “VERYDENTAL” to get 50% off Color Method consultation! -- Cosmedent is known for teaching restorative dentists how to make beautiful front teeth with composite. But let's not forget about gorgeous posterior resins! Would you like to learn to make life-like restorations with firm contacts and ideal occlusion? Dr. Javier Quiros is teaching “Become a Cosmetic Dentist with Posterior Composites this July 14-15th! You'll learn proper posterior layering techniques, material selection, how to get perfect contacts and even how to open the vertical dimension using the dentist's best tool…composite resin! I just got back from a course at the Cosmedent Center for Esthetic Excellence and I can't wait to go back! Their classroom is built for hands on teaching with a small class size. You get to use the best materials and you'll get to know your classmates. It's quite literally the best continuing education experience you can have! All overlooking Michigan Avenue in Chicago at the very best time to visit! Go check it out at verydentalpodcast.com/CEE! -- You won't believe all the changes and advances they're having over at CAD-Ray!  Now you can get the i700 in WIRELESS! Yes, you heard me correctly, all the goodness of the Medit i700 now is now available with no cables! The i700 wireless is available NOW from CAD-Ray and it ships immediately! If you've been waiting for a wireless intraoral scanning solution, your wait is over! Go check out CAD-Ray at verydentalpodcast.com/cadray or cad-ray.com -- Do you have something you use every single day on every single procedure? I do. There isn't anything I do in dentistry that Enova Illumination isn't a huge part of. I've owned a lot of different kinds of loupes. I've had Designs for Vision, Zeiss, Orascoptic…all of them. My favorites are the Enova's Vizix loupes in the Airon frame. Mine are red. RAWR! Along with the amazing, weightless and cordless Qubit, Quasar or Quantum headlights (all others are just toys) you cannot do better. Oh, did I mention the incredible Zumax 2380 operating microscope with built in still and video? Why haven't you checked out Enova Illumination yet? You can get a killer deal on all things Enova by using the Very Dental link you'll find at verydentalpodcast.com/Enova! -- Do you need help with a logo, website design or anything marketing? Our friends at Wonderist can definitely help! Keep your eyes open for the updated Very Dental Podcast website coming soon! It's amazing and it was designed by the pros at the Wonderist Agency! Want more information? Go check them out at verydentalpodcast.com/wonderist! -- Our friends at Crazy Dental have switched things up again! Now you can get 10% off your whole order from Crazy Dental using the coupon code: VERYDENTAL10! That's right…10% off your whole order! Go check out the amazing prices at verydentalpodcast.com/crazy and be sure to use the coupon code: VERYDENTAL10!

Yo, bro, how's it hanging? That question is left dangling until the end of the pod, which first features discussions of moral philosophy, and the slippery slope of adopting a shitty persona as a joke. We also have a long Recommendation Engine™ segment because there's just so much good stuff out there at the moment. So let's just get on with it, eh? This episode's mistakes include: Not addressing the fact that Michael thinks mint and vanilla are weird ice cream flavours. Dearth of Fun Facts™. Overuse of the word 'fact' in this list of mistakes. Egregious factual inaccuracies. Delete your phone number, then like us on Facebook, follow us on Twitter and Instagram, find our tunes on Spotify and SoundCloud, rate us on Apple Podcasts, and send your questions to deepfought@gmail.com.

On this week's episode we deep dive into Netflix's Recommendation Engine and all of the ways streaming services use data science to show recommendations, talk about inflation and which streaming service people are cutting first, and lastly, talk Shrek movie trivia as Shrek 1 and 2 leave Netflix at the end of April. Thanks for listening! This episode is sponsored by Paceline and Honey. Read more about our sponsors here: sassstoriessarcasm.com/sponsors Visit our website: sassstoriessarcasm.com Follow us on Instagram at instagram.com/sassstoriessarcasm and on Facebook at facebook.com/sassstoriessarcasm --- Send in a voice message: https://anchor.fm/sassstoriessarcasm/message

In dieser Podcast-Folge zu Gast: Christian Hagemeyer, Geschäftsführer econda GmbH, https://www.econda.de/ Mit ihm sprechen wir über Personalisierung, Web und Usability Analytics, datengetriebene Geschäftsmodelle und Recommendation Engine. Wir stellen ihm die Fragen: Wofür braucht man das – MUSS man das machen und was habe ich davon bzw. was sind die Vorteile für die Verbraucher von datengetriebenem Marketing. Außerdem schauen wir uns die Voraussetzung für digitale, datengetriebene Geschäftsmodelle an, und das sind valide Daten. Voraussetzungen hierfür wiederum sind DSGVO konforme Technologien, Prozesse und Consent Management. Ausgewertet werden können beispielsweise Web- und Appdaten, CRM-Daten, Produktdaten, die über die verschiedenen Kanäle gesammelt werden können: Website, Webshop, E-Mail Marketing, Re-Targeting. Besucht auch unsere Facebook Gruppe und Facebook Fanpage. Wir freuen uns auf den Austausch mit Euch! Noch mehr Folgen findet ihr hier: https://www.online-erfolgreicher.de/podcast-marketing-masterminds/

NEWS An overview of how YouTube's video recommendation works The warehouse storing the history of analog electronic music no one knows about GUEST Byta.com founder and CEO Marc Brown Also check out HowWeListen.org My guest this week is Marc Brown, founder and CEO of Byta.com, a site that enables sending and receiving digital audio in a clean, simple and secure way. Marc has an extensive music business background and considerable digital audio knowledge which has helped him deliver unique insights to audiences from Tallinn to Toronto. He got his start at Murderecords, Canada's premier artist owned label, during the mid 90s.  After working in A&R at the legendary London indie Creation Records, then at Alan McGee's Poptones, Marc started his own boutique UK radio promotion company off the back of his success with The Hives. For over 10 years Marc worked with an impressive list of indie rock luminaries including Wilco, Bloc Party, Conor Oberst/Bright Eyes, Spoon and Refused as well as legends such as Tom Waits, Yoko Ono, Booker T and Mavis Staples. During the interview, we spoke about why radio might still be important to an artist, the downside of sending files via email, the challenges of getting music to industry execs and radio, and much more. On the intro I'll take a look at YouTube's video recommendation engine, and the fantastic analog electronic music museum that no one knows about. var podscribeEmbedVars = { epGuid: 'https://bobbyoinnercircle.com/?p=2984', rssUrl: 'https://bobbyoinnercircle.com/feed/podcast/', backgroundColor: 'white', font: undefined, fontColor: undefined, speakerFontColor: undefined, height: '600px', showEditButton: false, showSpeakers: true, showTimestamps: true };

Stop what you're doing and look at me! I'm a podcast and I deserve to be listened to! In this ep, we wend our way through some more Recommendation Engine, which leads to a discussion of Matt Damon, which leads into a discussion of cancel culture. And then we cap it all off with a terrific Science News, which you can read here. This episode's mistakes include: Omitting several interesting topics in service of our next episode. Wearing our Mattfleck love on our chest. Buckwild declaration at the very end by Michael. Egregious factual inaccuracies. Stare at the ocean, then like us on Facebook, follow us on Twitter and Instagram, find our tunes on SoundCloud, rate us on Apple Podcasts, and send your questions to deepfought@gmail.com.

Good afternoon, and thank you all for coming. We hope you're ready for some commentary, because it's time for a patented Deep Dive™ into Nick's comedy series Good Grief. We're walking through some of the writing process, the creative decisions and challenges, and how it feels to see your words translated into a visual medium. Be aware that we do spoil some character and comedy beats, but it's pretty clearly signposted, and there's still plenty more to enjoy if you want to skip to other chapters for now – including vaxx chat and a Recommendation Engine. This episode's mistakes include: Forgetting many other interesting Good Grief development nuggets. More Skype lag shenanigans. Sigh.  You cannot kill abstract emotional concepts like 'dread'. Egregious factual inaccuracies. Splash out on some Prosecco, then like us on Facebook, follow us on Twitter and Instagram, find our tunes on SoundCloud, rate us on Apple Podcasts, and send your questions to deepfought@gmail.com.

(1) A crop of US startups are promising “instant delivery” in under 30 minutes (0:53). (2) Vaccine certificate programs are being rolled out (8:38). (3) TikTok's AI recommendation engine is now for sale (13:37). Read this 3 Shifts Edition: https://6pag.es/jpjdbm. Sign up to receive free summaries of our deeply researched briefs: 6Pages.com. 

Recommendation systems have changed how we choose what we want. But are they choosing what we want? | Subscribe to our weekly newsletter here.

On today's show, we have Rae Shanahan from Businesssolver here to discuss a report that they've done, titled MyChoice Recommendation Engine Benefits Insights Report.A mouthful, but Rae will break that down for us and explain what it all means. This is the third time that they've done this report, so it should actually be really interesting. We'll get into discussing employee benefits as well as their findings.And of course, here's a link to the report. 

Andreas und Kai sprechen über modernes Dashboarding und wie Ansätze aus alltäglichen Anwendungen wie Netflix und Co. uns dabei helfen! In dieser Folge lernt ihr: • Welche Dashboardtypen es gibt • Was eine einfache und intuitive Navigation in Dashboards ausmacht • Warum Kacheln in keinem Guided Dashboard fehlen dürfen • Wie Storytelling mit dem Ebenenkonzept für Dashboards funktioniert • Warum Netflix und Co. als Inspiration für Business Dashboards so wichtig ist

Recommendation engines are quite popular in the consumer space, but they are even more effective and essential in the enterprise space. Robin Purohit, Co-founder and CEO of Peritus.ai (https://peritus.ai/) compares them with Grammarly that we all use in our work life to help write better, Peritus.ai recommendation engine does the same for DevOps engineers and Developers with technical content. “Millions of tech workers around the world are all trying to master the latest technology and do their job better, we are trying to provide them insights and how they can either support a customer or develop a new product faster by giving recommendations in the moment that they're doing their work,” said Purohit.

№29 Chip Reaves, Bigger BrainsMy guest for today's episode is Chip Reaves, IT veteran and President for almost 10 years of Bigger Brains. Bigger Brains' vast library of high-quality video-based courses on a variety of corporate training issues has received awards every year since at least 2015. And with Brain Bot, a chatbot that periodically quizzes you about past courses taken, it adds spaced repetition into the mix to multiply the value of the content.In my conversation with such a fountain of wisdom we talk about:The highlights and perils of producing corporate training contend during a pandemic, and whether or not you've been committing “eLearning malpractice”?What it takes to adapt: From classroom to online, from recorded to live, from Microsoft to Google, from lectures to microlearning, and much more..The challenge of adapting to young mindsets, and the enormous rewards that await you. Or as a millennial learning with Chip says: “Old people want to be paid with money, young people want to be paid with time.”Chips's adventures in microlearning, and how, despite the seemingly small number of variables at play, there is still a lot of room for creativity and rigorous experimentation~

When something goes wrong, tech teams don't have the luxury of logging a support ticket. When I heard about Peritus, an AI recommendation for technical support, I felt compelled to find out more. Robin Purohit is the co-founder and CEO of Peritus.ai, a Bay area startup that is tackling technical support for developers and engineers. He was previously a senior executive at BMC and HP Software, where he led multi-billion dollar business units for IT management, application delivery, and security. AI chatbots for customer support are getting significant attention and investment in industries ranging from retail to financial services to employee help desks. However, an important area neglected is support for engineers and developers who are driving IT innovation. These technical users have little patience for pre-wired chatbots without industry context and view opening a support ticket as the last resort. Instead, they look for insights from trusted experts on Community Forums, such as Stack Overflow or vendor-sponsored communities. When done well, community forums can create both user loyalty and deflect costly support cases. Peritus, an AI recommendation engine for support automation, recently announced the results of its first IT Industry Forum Benchmark that examined over 12 million posts and responses on over 50 leading IT industry forums for vendors and open source technologies such as Cisco, MongoDB, and Kubernetes. The benchmark study zeroed in on four key metrics: The number of posts that were resolved How quickly the average length to resolve each post was resolved. Whether posts were resolved by the first response, How many experts answered the bulk of the questions.

YouTube seems like a promising platform for people who want to put out their content and monetize it. I don’t see why not. There’s a multitude of YouTubers who are making more than enough through their content. Whenever someone reaches thousands of views, their video gains the potential of being monetized. Today’s Marketing Speak guest, Evan Carmichael, has over 2 million subscribers and over 300 million views. Gary Vaynerchuck called him the DJ who inspires people, and Ed Mylett called him the modern-day Napoleon Hill. At 19, he built and then sold a biotech software company. At 22, he was a venture capitalist and raised $500k to $15M. He now runs a YouTube channel for entrepreneurs, has written four books, and speaks globally. Tune in as we talk about the smart, data-driven decisions you can make when you understand how YouTube works. The show notes, including the transcript and checklist to this episode, are at marketingspeak.com/265.

Sorry for the wee delay, but Nick has been a little under the weather this week and started slacking off. It's a nice and fun ramble today with an earth-shattering scientific pronouncement, a Weird News™, a Science News™, and even a Recommendation Engine™ to cap things off. This episode's mistakes include: Aggressive energy. Not being able to edit out all the coughing. Literally just spent a minute trying to remember the phrase 'writer's block', which is pretty on the nose. Egregious factual inaccuracies. Pair your brown foods, then like us on Facebook, follow us on Twitter and Instagram, find our tunes on SoundCloud, rate us on Apple Podcasts, and send your questions to deepfought@gmail.com.

Hey everyone, hope you're all keeping happy and healthy. This week is a light and easy one in which we practice simple dinner time conversation with the help of some prompts, with a nice second course of Science News and some Recommendation Engine for dessert. Grab a spoon. This episode's mistakes include: Rushed episode notes lending a generic feel. Buxton references. The um... horse... got.... loose I dunno look I've got a dinner to get to. Egregious factual inaccuracies. Gather around the kitchen table, then like us on Facebook, follow us on Twitter and Instagram, find our tunes on SoundCloud, rate us on Apple Podcasts, and send your questions to deepfought@gmail.com.

Quando si parla di motori di raccomandazione o “recommendation engine”, ci vengono in mente un sacco di nomi importanti.► I consigli di Amazon,► I video correlati di YouTube,► I “Consigliati per te” di Netflix.Parliamo di multinazionali (multimiliardarie) che investono budget inimmaginabili per i motori di raccomandazione.E il loro obiettivo è principalmente uno: migliorare così tanto l'esperienza degli utenti, che quest'ultimi non troveranno motivo per andare da altre parti.Perché in un momento storico dove il mondo scoppia di prodotti e l'indecisione regna sovrana, ‘qualcosa' che ti guida nelle decisioni è la soluzione migliore che ti possa capitare.Ora, facendo questo ragionamento sembra che solo i colossi con un parco prodotti enorme si possano permettere di installare un motore di raccomandazione...Ma la realtà è molto diversa…Al momento ci sono tantissime aziende (anche in Italia) che vendono prodotti che potrebbero installare un sistema di raccomandazione (e trarne lo stesso vantaggio di Amazon).Soprattutto se in questo momento i clienti si infastidiscono perché di fronte ad un parco prodotti abbastanza grande comunque non sanno scegliere…Scopri se puoi installare un sistema di Intelligenza Artificiale con la puntata #6 del podcast!***P.S. Vuoi scoprire come implementare un sistema di Recommendation Engine alla tua azienda?► Telefona al numero verde 800-270-021.► Scrivi un'email a info@bluetensor.ai.► Visita il sito www.bluetensor.aiA presto!

Adam Singolda (Taboola) on the state of the industry, working from home and ongoing communication AND attitude.

We've come to the end of 2019. Python 2 has just a handful of days before it goes unsupported. And I've met up with Dan Bader from RealPython.com to look back at the year of Python articles on his website. We dive into the details behind 10 of his most important articles from the past year. Links from the show Dan Bader: @dbader_org The 10 Articles on RealPython.com #1: How to Run Your Python Scripts #2: 13 Project Ideas for Intermediate Python Developers #3: 3 Ways of Storing and Accessing Lots of Images #4: Speed Up Your Python Program With Concurrency #5: Build a Recommendation Engine #6: Your Guide to the Python Print Function #7: How to Write Beautiful Python Code With PEP 8 #8: How to Use Python Lambda Functions #9: How to Stand Out in a Python Interview #10: Inheritance and Composition: A Python OOP Guide Sponsors Linode Brilliant Talk Python Training

When we press play on a YouTube video, we set in motion an algorithm that taps all available data to find the next video that keeps us glued to the screen. Because of its advertising-based business model, YouTube’s top priority is not to help us learn to play the accordion, tie a bow tie, heal an injury, or see a new city — it’s to keep us staring at the screen for as long as possible, regardless of the content. This episode’s guest, AI expert Guillaume Chaslot, helped write YouTube’s recommendation engine and explains how those priorities spin up outrage, conspiracy theories and extremism. After leaving YouTube, Guillaume’s mission became shedding light on those hidden patterns on his website, AlgoTransparency.org, which tracks and publicizes YouTube recommendations for controversial content channels. Through his work, he encourages YouTube to take responsibility for the videos it promotes and aims to give viewers more control.

Kevin Roose and Brian Stelter discuss Roose's newest story, "The Making of a YouTube Radical." Roose, a tech columnist at The New York Times, says YouTube's algorithm is "designed to create personalized rabbit holes," sometimes with dangerous consequences. Roose talks about how YouTube evolved into a "behavioral modification AI wrapped in the skin of a video website." And he discusses the positive and negative "garbage fire" reactions to his investigation.

Dom Bettinelli, Fr. Andrew Kinstetter, and Thomas Sanjurjo discuss the trap of the recommendation algorithms many sites employ that discourage curiosity and then talk about the evolution of gaming in light of the Game Boy's 30th anniversary. The post The Recommendation Engine Problem and The Evolution of Gaming appeared first on StarQuest Media.

2008 gründet Adam Singolda das Content Discovery-Startup Taboola, zieht ein paar Monate danach nach New York – und peilt mit 800 Mitarbeitern an weltweit 14 Standorten eine Milliarde Dollar Umsatz für dieses Jahr an. Im aktuellen Podcast verrät er, wie sich die Branche um Werbung am Artikelende verändert, dass Facebook der größte Konkurrent ist und warum er einen IPO zumindest aktuell ausschließt. Alle Themen vom Podcast mit Taboola-Gründer Adam Singolda im Überblick: So entstand bei Adam Singolda nach sieben Jahren beim Militär die Idee zur Recommendation Engine von Taboola (ab 3:10) Die ersten Umsätze hat Taboola 2012, fünf Jahre nach der Gründung, generiert (4:30) Das Geschäftsmodell von Taboola: So verdient das Unternehmen Geld (ab 5:05) 2012 hatte Taboola noch rund 20 Mitarbeiter, heute sind es insgesamt 800 und das Unternehmen peilt die Umsatz-Milliarde an (ab 6:20) Plant Adam Singolda einen IPO? (ab 7:05) Wie stellt Taboola die Qualität der empfohlenen Artikel und Produkte sicher? (ab 8:50) Welchen Preis pro Klick müssen Advertiser Taboola im Schnitt zahlen? (ab 10:40) Diese deutschen Publisher nutzen Taboola und deshalb sind solche Deals meistens exklusiv (11:20) Ligatus, Plista, Outbrain: So schätzt Adam Singolda die Konkurrenz auf dem deutschen Markt ein (ab 12:30) Deshalb ist Deutschland ein für Taboola sehr wichtiger Markt (ab 13:50) Facebook ist laut Singolda der größte Konkurrent – und der Grund, warum Taboola Tools für Publisher und Redaktionen entwickelt (ab 14:15) Warum kauft Taboola Firmen für bis zu dreistellige Millionenbeträge auf? (ab 16:00) Welche Rolle spielt Google Adsense laut Adam Singolda im Recommendation-Game? (ab 19:00) Diese Publisher hält der Taboola-Gründer für besonderes innovativ (ab 21:00) Publisher, die sich nicht ganz gezielt mit Traffic-Quellen außerhalb von Search, Facebook & Co. beschäftigen, riskieren laut Singolda ihre Zukunft (ab 22:30) Gibt es ein Erfolgsrezept, das Adam Singolda beim Aufbau einer Milliarden-Company geholfen hat? (ab 23:30) Woran liegt es, dass beide Global Player im Recommendation-Bereich – Taboola und Outbrain – aus Israel kommen? (ab 25:15) Wie geht Taboola gegen „Fake News“ vor? (ab 27:00) Arbitrage mit Content Recommendations: Geht Taboola gegen Clickbait-Publisher vor? (ab 29:40) Muss ein Publisher eine gewisse Traffic-Größe erreichen, damit eine Implementierung von Taboola Sinn macht? (ab 32:45) Was ist dran an immer wieder aufkommenden Gerüchten von Fusionen zwischen Taboola, Outbrain und anderen Marktteilnehmern? (ab 34:00) Das sind nach Umsatz die wichtigsten Märkte für Taboola (ab 35:35) Von wem lässt sich Adam Singolda als Gründer inspirieren? (ab 38:30)

Spruce up your decor as the Gaming Hut reveals the secrets of room description. Ken does the bulk of the replying in an eliptonic Ask Ken and Robin, as RogerBW seeks a disentanglement of convex and concave hollow earth theories. Once again we rev up the Recommendation Engine, tipping you to a movie, two books, […]

Summary:As you know, we’ve been trying to cover from every angle, the innovations that ecommerce sites in general, and Amazon.com specifically, brought to the world. That is why I was thrilled to get to speak with Greg Linden, who was one of the Amazon engineers who was responsible for a lot of the personalization and data-driven innovations at Amazon, especially the recommendation engine. Greg explains in great detail the technological challenges involved, but also gives us a conceptual and almost philosophical background to the ways that harnessing data and deploying personalized systems can improve commerce.If you want to read any of the blog posts Greg has done about his early Amazon days, go here. See acast.com/privacy for privacy and opt-out information.

A pithy remark from LEGO Batman inspires our latest excursion into the Gaming Hut, as we ponder the question of narratively acceptable character demises. In the Tradecraft Hut we look at bone music, 50s era contraband pop music recordings etched against the will of Soviet authorities onto old medical X-rays. The Recommendation Engine spits out […]

In the Gaming Hut we consider the dividing line between fun character customization and tiresome homework, and whether it’s moving lately. Still in a Draculanean mood, Ken enters the Book Hut for a vantage on the career of Bram Stoker. We rev up the Recommendation Engine for its sophomore run to talk about a movie, […]

Our multi-episode arc about the underwater dead who sell life and buy dreams comes to a conclusion in the Gaming Hut as we break out specific scenario ideas for our riffed setting. In a new segment called Recommendation Engine we tell you what’s catching our fancy in the worlds of books, TV, movies, and food. […]

Voce del Glossario a cura di Roberto Basile RECOMMENDATION ENGINE I Recommender systems o i recommendation engines costituiscono una specifica forma di analisi e di filtraggio dell’informazione. Sono infatti tecniche che forniscono una presentazione di elementi informativi (film, musica, libri, immagini, pagine Web) che potrebbero essere di interesse per l’utente. Tipicamente un sistema di raccomandazioni compara un profilo dell’utente con diverse voci di riferimento e cerca prevedere quali saranno gli altri elementi aventi caratteristiche simili che interesseranno l’utente. Queste caratteristiche derivano spesso da voci informative basate sull’utente stesso (approccio basato sui contenuti) oppure sull’ambiente sociale dell’utente (approccio basato sul filtro collaborativo) Quando viene costruito il profilo utente viene fatta una distinzione tra le informazioni implicite e di informazioni esplicite di una collezione di dati. Esempi di informazioni esplicite possono essere: - Chiedere all’utente di valutare una particolare voce. - Chiedere l’utente di ordinare una collezione di voci dalla preferita meno preferita - Presentare due voci all’utente e chiedergli di scegliere la migliore - Chiedere all’utente di creare una lista di voci in base alle sue preferenze Esempi di informazioni implicite possono essere: - Osservare le voci che un utente visualizza nel negozio on-line - Analizzare il rapporto tra le diverse voci ed i vari utenti - Analizzare le registrazioni delle voci riferite ai prodotti che gli utenti acquistano on-line - Analizzare la rete sociale degli utenti e scoprire eventuali elementi simili (graditi e sgraditi). Tutto questo lo avviene attraverso particolari algoritmi che riescono a prevedere il comportamento dell’utente attraverso determinate tecniche.

A company has developed a recommendation engine that uses AI to anticipate what users want even before they have a chance to ask.