Podcasts about suhail

The former Loretto Hospital executive charged with stealing millions from the safety-net hospital also used fake COVID-19 testing companies to steal about $300 million from the government, prosecutors alleged in a newly unsealed indictment.Former Loretto COO and CFO Anosh Ahmed is among a group of four who now face charges related to the scheme, prosecutors said.Block Club has reported extensively on Ahmed's troubling conduct at Loretto Hospital, from letting well-connected people access COVID-19 vaccines early — and even bragging he vaccinated Eric Trump — to contracting with companies owned by his business partner, best friend and neighbor, Sameer Suhail.Ahmed and Suhail were charged in July with wire fraud, embezzlement and money laundering, with prosecutors alleging they defrauded the hospital out of $15 million. They fled to Dubai.Separately, Block Club also revealed in 2021 and 2022 that various COVID-19 testing companies were providing questionable and sometimes fake results while appearing to wrongfully seek federal reimbursements worth hundreds of millions of dollars. One of the labs highlighted by Block Club Chicago for problematic work was O'Hare Clinical Lab.Now, those stories have converged, as prosecutors say Ahmed, Mohamed “Siraj” Sirajudeen and Mahmood Sami Khan used O'Hare Clinical Lab, among others, to submit false COVID-19 testing claims to the government. They sought about $900 million in reimbursements, of which they received about $300 million.-- Host - Jon HansenReporter - Kelly Bauer Want to donate to our non-profit newsroom? CLICK HEREWho we areBlock Club Chicago is a 501(c)(3) nonprofit news organization dedicated to delivering reliable, relevant and nonpartisan coverage of Chicago's diverse neighborhoods. We believe all neighborhoods deserve to be covered in a meaningful way.We amplify positive stories, cover development and local school council meetings and serve as watchdogs in neighborhoods often ostracized by traditional news media.Ground-level coverageOur neighborhood-based reporters don't parachute in once to cover a story. They are in the neighborhoods they cover every day building relationships over time with neighbors. We believe this ground-level approach not only builds community but leads to a more accurate portrayal of a neighborhood.Stories that matter to you — every daySince our launch five years ago, we've published more than 25,000 stories from the neighborhoods, covered hundreds of community meetings and send daily and neighborhood newsletters to more than 130,000 Chicagoans. We've built this loyalty by proving to folks we are not only covering their neighborhoods, we are a part of them. Some of us have internalized the national media's narrative of a broken Chicago. We aim to change that by celebrating our neighborhoods and chronicling the resilience of the people who fight every day to make Chicago a better place for all.

Camproot Podcast| Episode 16: Ramadan & the Chance to Revive

Today we dive into the future of omnichannel ecommerce with Sayed Suhail Gaffar, VP of Global Ecommerce at Topps Company. Sayed shares how the iconic collectibles brand expanded globally, modernized its customer experience across channels, and why setting customer expectations, and meeting them, is the ultimate driver of loyalty. Tune in for strategies on balancing retail partnerships, ecommerce growth, and digital innovation in a fast-changing market.

Suhail Shaikh is Chief Investment Officer of Fulcrum Asset Management and is the portfolio manager of Fulcrum's Discretionary Macro and Diversified Absolute Return strategies. In today's incredibly volatile environment of tariff wars and deglobalisation, investors tend to be more sensitive about the level of their absolute returns, than their performance against the benchmark. In this episode, we delve into the philosophy of absolute return investing, we talk about the role of skill versus luck, the use of Nowcasting, learnings from the COVID-19 pandemic and the ever controversial topic of market timing. Enjoy the show! 02:00 Started off working on the intranet and taught myself HTML 02:30 Internship at Goldman Sachs 03:30 A lot of well-known global macro traders made their money during equity market crashes 05:00 If you are constantly looking for the next accident, then 90 per cent of the time you are wrong. It is important to make money while the sun is still shining 10:00 Crisis risk offset and momentum during COVID 13:30 Leaving the model aside 15:00 Using Nowcasting for analysis 18:30 AI has been more useful to us in portfolio construction, risk management, scenario analysis and stress testing. I'm more sceptical about AI being helpful in alpha generation. 22:30 Behavioural finance and Fulcrum paper: ‘Don't Bet the Ranch' 23:30 To determine whether someone is skilled or lucky, look at the number of views they take over time 31:30 Sizing [trades] is a complex topic 33:00 The role of dynamic asset allocation 34:00 “The biggest accidents in asset management happen when, in a draw-down, people don't know whether they are benchmarked or absolute return” 35:00 “Dynamic asset allocation is market timing” 40:00 Global Macro and the Magnificent Seven 42:00 Bitcoin and momentum strategies 44:30 Some clients explicitly prohibit us from investing in Bitcoin The paper "Don't Bet The Ranch: Hit ratios, asymmetry and breadth" can be found at: https://fulcrumasset.com/insights/investment-insights/dont-bet-the-ranch-hit-ratios-asymmetry-and-breadth/

Today's episode is a deep dive into the mind of Suhail Sahrawat,, founder of Garuda SS a label that blurs the lines between workwear, streetwear, and avant-garde with surgical precision and raw creativity. Garuda SS isn't just about clothes; it's about attitude, comfort, and pushing boundaries without taking itself too seriously. We talk design. We talk identity. We talk about building a brand that feels more like an extension of self than a fashion label. Suhail opens up about his creative process, his unfiltered approach to style, and how Garuda SS became an international force with its own unapologetic voice. This isn't your average fashion chat it's a conversation about making art you can wear. Tune in and get inspired.

In this episode of Paisa Vaisa, Anupam Gupta explores the sports business with Suhail Chandhok, CEO of U Mumba and Co-Founder of Elev8 India Sportz. Suhail shares his journey from athlete to entrepreneur and the challenges of managing a sports franchise.

Dive into an electrifying episode of Cyrus Says with Suhail Chandhok – Sports Presenter, Commentator, Entrepreneur & CEO of U Mumba!

In this mouth-watering episode, we sit down with our guest, Mr. Suhail Khan, an avid traveler and passionate foodie whose journeys revolve around tasting and experiencing the local cuisine of every place he visits. From bustling street food stalls to intimate home-cooked meals and Michelin-starred restaurants, Suhail embraces it all. But for him, it's not just about the flavors—it's about the rituals, the culture, and the history that shape every dish.Join us as we dive into fascinating food stories from across the world. We explore the meticulous preparation of Turkish coffee, the slow-cooked Bedouin Zarb in Jordan, and the deep-rooted connections between dishes like Pho and the Vietnam War. We uncover the culinary linkages that span continents—from Uzbek Plov to Indian Biryani, from Samosas to Dumplings. Suhail shares his insights from conversations with locals, unveiling the histories, traditions, and hidden stories behind the meals that define cultures.Get ready for a flavorful journey through Uzbekistan, LatinAmerica, Iran, Jordan, India, Morocco, Portugal, Vietnam, Ethiopia, and beyond. If you love food, travel, and the stories they tell, this episode is a feast for the senses!---------------------------------------------Follow Suhail on Instagram || LinkedIn---------------------------------------------To support our team and donate generously, please click ⁠⁠⁠⁠SUPPORT ⁠⁠⁠⁠.Like our work? Follow, Like & Subscribe to our podcast from wherever you are listening in. We would also love to hear from you, so do write to us at:Email: ⁠⁠⁠⁠misadventuresofasneaker@gmail.com⁠⁠⁠⁠Instagram: ⁠⁠⁠⁠@misadventuresofasneaker⁠⁠⁠⁠Blog: misadventuresofasneaker.substack.com----------------------------------------Show Notes: South America with Sharique: Here---------------------------------------00:00:00 Trailer00:01:53 Episode intro00:04:01 Suhail & early travel stories00:23:43 Food vacation00:26:52 Coffee collection00:29:23 Legendary Ethiopian Coffee00:40:06 Comfort Food & Pho00:48:59 Empanadas in S. America00:50:44 Pastel De nata in Portugal00:53:58 Food Links & Biryanis00:58:00 Iran's Isfahan Beryan01:00:47 Plov in Tashkent01:03:50 Food for the masses01:07:31 Jordan food stories01:09:13 Türkiye food stories01:12:49 Coffee's of the world01:15:00 Uzbekistan food stories01:25:13 Role of yogurt01:27:54 Morocco food stories01:37:13 Fruits of the world01:42:40 Exotic meats01:46:31 Pizzas of the world01:55:04 Community eating practices02:03:09 Street food stories02:07:44 Star restaurants02:09:39 Where next?02:12:08 Toodles

Assad's stunning fall ends a tyrannical 53-year rule in Syria, leaving monstrous crimes against human rights exposed, rocking both Iran and Russia on their heels, and handing the country's future back to its people. Where next for Syria? Will the rebel fighters coalesce into a working government and avoid the factionalism which would jeopardise the Syrian people's hopes? And what does it mean for an international community which had turned its back on the Syrian war? Emma Beals explores an awe-inspiring week in the Middle East with Syria expert and open-source investigator Suhail al-Ghazi.  • No Longer on Twitter? Follow TINAD and Emma Beals on BlueSky.  • Support This Is Not Drill on Patreon to continue by backing us on Patreon. You'll get early, ad-free editions, merchandise and more.  Written and presented by Emma Beals. Audio production by Robin Leeburn. Original theme music by Paul Hartnoll – https://www.orbitalofficial.com. Executive Producer Martin Bojtos. Group Editor Andrew Harrison. This Is Not A Drill is a Podmasters production podmasters.co.uk Learn more about your ad choices. Visit podcastchoices.com/adchoices

• A special crossover with The Bunker's geopolitics partner podcast This Is Not A Drill. Assad's stunning fall ends a tyrannical 53-year rule in Syria, leaving monstrous crimes against human rights exposed, rocking both Iran and Russia on their heels, and handing the country's future back to its people. Where next for Syria? Will the rebel fighters coalesce into a working government and avoid the factionalism which would jeopardise the Syrian people's hopes? And what does it mean for an international community which had turned its back on the Syrian war? This Is Not A Drill regular Emma Beals explores an awe-inspiring week in the Middle East with Syria expert and open-source investigator Suhail al-Ghazi.  • No longer on Twitter? Follow TINAD and Emma Beals on BlueSky.  • Support This Is Not Drill on Patreon to continue by backing us on Patreon. You'll get early, ad-free editions, merchandise and more.  Written and presented by Emma Beals. Audio production by Robin Leeburn. Original theme music by Paul Hartnoll – https://www.orbitalofficial.com. Executive Producer Martin Bojtos. Group Editor Andrew Harrison. This Is Not A Drill is a Podmasters production podmasters.co.uk Learn more about your ad choices. Visit podcastchoices.com/adchoices

Send us a textWriter & Co-Founder of Saltwater Coffee — Suhail's  stories appear in Shenandoah, 3:AM, Passages North, and elsewhere. He has been nominated for Best of the Net, Best Microfiction, and Best Small Fictions twice. In 2022, he made the Wigleaf Top 50 Longlist and Notable in Best American Food Writing.Click below for the full story.https://www.saltwaternyc.comhttps://www.ssmandani.comCheck out the website: www.drinkingonthejob.com for great past episodes. Everyone from Iron Chefs, winemakers, journalist and more.

The Daily Gwei Refuel gives you a recap every week day on everything that happened in the Ethereum and crypto ecosystems over the previous 24 hours - hosted by Anthony Sassano. Timestamps and links to topics discussed: https://daily-gwei-links.vercel.app/recent 00:00 Introductory song 00:45 Ethereum Foundation chat https://x.com/VitalikButerin/status/1849965496151789949 05:57 Light clients in Ethereum https://x.com/VitalikButerin/status/1849942054010552774 12:15 Suhail's tl;dr tweet on Vitalik's blog posts https://x.com/SuhailKakar/status/1850528808631439764 14:24 Gas limit/target chat https://x.com/sassal0x/status/1849324595633066276 https://twitter.com/VitalikButerin/status/1849338545498210652 24:32 Rocket Pool updates https://x.com/drjasper_eth/status/1850689540308316196 https://x.com/drjasper_eth/status/1849206972702228482 27:14 Kraken announces their own L2 https://x.com/inkonchain/status/1849443457883885801 https://x.com/JasonYanowitz/status/1849486268599570487 34:33 USDC transfer volume on Base at all time high https://x.com/peterschroederr/status/1850556872727945285 36:26 Base getting fault proofs on October 30th https://x.com/base/status/1849199337504465335 37:55 Devcon is coming https://x.com/0xj4ksa/status/1849748984602165333 This episode is also available on YouTube: https://youtu.be/-ab3MeZ4cVA Subscribe to the newsletter: https://thedailygwei.substack.com/ Subscribe on YouTube: https://www.youtube.com/channel/UCvCp6vKY5jDr87htKH6hgDA/ Follow Anthony on Twitter: https://twitter.com/sassal0x Follow The Daily Gwei on Twitter: https://twitter.com/thedailygwei Join the Discord Channel: https://discord.gg/4pfUJsENcg DISCLAIMER: All information presented across all of The Daily Gwei's communication channels is strictly for educational purposes and should not be taken as investment advice.

LML: Suhail Rentas : Cómo capitalizar la información de Summit

LML: Suhail Rentas : Cómo calificar para los viajes

Bro. Suhail joins Ken in this edition of "Sunday Morning with Love In Action" to discuss recent persecution of Christians in Pakistan and how to reach out to those of Muslim faith locally.  "Sunday Morning with Love In Action" airs every Sunday at 10:30 a.m. on The Joy FM thanks to a generous donation from Weed Man, who provides quality lawn care services for the greater Dothan area. Please subscribe to the Love In Action Podcast anywhere you listen to podcasts. Thank you and God bless you.

Bro. Suhail joins Ken in this edition of "Sunday Morning with Love In Action" as they talk about some exciting things God is doing in Pakistan. Only 1 percent of the 220 million people in Pakistan are Christian. It is the third largest Islamic country in the world, and over 97 percent of its population is unreached with the Gospel of Jesus Christ. However, the indigenous pastors Love In Action partners with in Pakistan are doing incredible work to spread the Gospel in a very tough country to be a Christian. "Sunday Morning with Love In Action" airs every Sunday at 10:30 a.m. on The Joy FM thanks to a generous donation from Weed Man, who provides quality lawn care service for the greater Dothan area. Please subscribe to the Love In Action Podcast.

Victim Mentality or Victor Mentality? By Shaykh Suhail Mulla.For more information and further updates, please visit us at https://www.icoi.net. Hosted on Acast. See acast.com/privacy for more information.

Episode 123I spoke with Suhail Doshi about:* Why benchmarks aren't prepared for tomorrow's AI models* How he thinks about artists in a world with advanced AI tools* Building a unified computer vision model that can generate, edit, and understand pixels. Suhail is a software engineer and entrepreneur known for founding Mixpanel, Mighty Computing, and Playground AI (they're hiring!).Reach me at editor@thegradient.pub for feedback, ideas, guest suggestions. Subscribe to The Gradient Podcast:  Apple Podcasts  | Spotify | Pocket Casts | RSSFollow The Gradient on TwitterOutline:* (00:00) Intro* (00:54) Ad read — MLOps conference* (01:30) Suhail is *not* in pivot hell but he *is* all-in on 50% AI-generated music* (03:45) AI and music, similarities to Playground* (07:50) Skill vs. creative capacity in art* (12:43) What we look for in music and art* (15:30) Enabling creative expression* (18:22) Building a unified computer vision model, underinvestment in computer vision* (23:14) Enhancing the aesthetic quality of images: color and contrast, benchmarks vs user desires* (29:05) “Benchmarks are not prepared for how powerful these models will become”* (31:56) Personalized models and personalized benchmarks* (36:39) Engaging users and benchmark development* (39:27) What a foundation model for graphics requires* (45:33) Text-to-image is insufficient* (46:38) DALL-E 2 and Imagen comparisons, FID* (49:40) Compositionality* (50:37) Why Playground focuses on images vs. 3d, video, etc.* (54:11) Open source and Playground's strategy* (57:18) When to stop open-sourcing?* (1:03:38) Suhail's thoughts on AGI discourse* (1:07:56) OutroLinks:* Playground homepage* Suhail on Twitter Get full access to The Gradient at thegradientpub.substack.com/subscribe

Multimodal models are making it possible to create AI art and augment creativity across artistic mediums. This week on No Priors, Sarah and Elad talk with Suhail Doshi, the founder of Playground AI, an image generator and editor. Playground AI has been open-sourcing foundation diffusion models, most recently releasing Playground V2.5.  In this episode, Suhail talks with Sarah and Elad about how the integration of language and vision models enhances the multimodal capabilities, how the Playground team thought about creating a user-friendly interface to make AI-generated content more accessible, and the future of AI-powered image generation and editing. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Suhail Show Notes:  (0:00) Introduction (0:52) Focusing on image generation (3:01) Differentiating from other AI creative tools (5:58) Training a Stable Diffusion model (8:31) Long term vision for Playground AI (15:00) Evolution of AI architecture (17:21) Capabilities of multimodal models (22:30) Parallels between audio AI tools and image-generation

LML: Suhail Rentas: Estrategias para ayudar a tus clientes a obtener resultados

When we say that our top priority is student success, a common refrain in higher education, what does that mean in terms of prioritizing faculty and staff success?  This week's guest, Suhail Johnson of Texas Christian University, says the two are inextricably linked and that student success doesn't happen unless we invest first in employees.  Johnson left her mark on UofL as a leader in residence life and has since shifted her focus to training and supporting faculty and staff, guided by her belief that one cannot be successful without the other.  

In this episode, Nathan sits down with Suhail Doshi, founder of Playground AI. They discuss the current state of AI image generation, how Suhail is building Playground while the technology for vision and image generation is still maturing, thought to image reconstruction, and more. If you need an ecommerce platform, check out our sponsor Shopify: https://shopify.com/cognitive for a $1/month trial period. We're hiring across the board at Turpentine and for Erik's personal team on other projects he's incubating. He's hiring a Chief of Staff, EA, Head of Special Projects, Investment Associate, and more. For a list of JDs, check out: eriktorenberg.com. -- LINKS: - Playground AI: https://playgroundai.com/ SPONSORS: The Brave search API can be used to assemble a data set to train your A I models and help with retrieval augmentation at the time of inference. All while remaining affordable with developer first pricing, integrating the Brave search API into your workflow translates to more ethical data sourcing and more human representative data sets. Try the Brave search API for free for up to 2000 queries per month at https://brave.com/api Shopify is the global commerce platform that helps you sell at every stage of your business. Shopify powers 10% of ALL eCommerce in the US. And Shopify's the global force behind Allbirds, Rothy's, and Brooklinen, and 1,000,000s of other entrepreneurs across 175 countries.From their all-in-one e-commerce platform, to their in-person POS system – wherever and whatever you're selling, Shopify's got you covered. With free Shopify Magic, sell more with less effort by whipping up captivating content that converts – from blog posts to product descriptions using AI. Sign up for $1/month trial period: https://shopify.com/cognitive Omneky is an omnichannel creative generation platform that lets you launch hundreds of thousands of ad iterations that actually work customized across all platforms, with a click of a button. Omneky combines generative AI and real-time advertising data. Mention "Cog Rev" for 10% off www.omneky.com NetSuite has 25 years of providing financial software for all your business needs. More than 36,000 businesses have already upgraded to NetSuite by Oracle, gaining visibility and control over their financials, inventory, HR, eCommerce, and more. If you're looking for an ERP platform ✅ head to NetSuite: http://netsuite.com/cognitive and download your own customized KPI checklist. X/SOCIALS: @labenz (Nathan) @Suhail @CogRev_Podcast TIMESTAMPS: (00:00) Episode Preview (00:44) The current state of AI image generation (08:04) Are we currently at a GPT-2 level for image gen? (15:40) Sponsor - Brave Search API | Shopify (20:46) Shortcomings and use cases for GPT-4V (22:46) Benefits of vision vs language (28:30) Trajectory for what Playground will build next (33:28) Sponsor - NetSuite by Oracle | Omneky (34:48) How will the image generation experience change over time (40:06) Thought to image reconstruction (47:49) What if OpenAI fully focused on image (50:09) Lack of training data in vision and the use of synthetic data (51:30) Multimodal models increasing performance (55:03) Images are information rich but lack the right annotation (57:00) Building Playground while vision technology is maturing (1:03:25) What should the rules for generative AI be? (1:09:19) Parallel to the music industry and streaming for rev share (1:12:21) What are the minimum standards that AI application developers should be expected to uphold? (1:16:48) Wrap

In this episode, Nsikan Essien talks with Hywel Carver and Suhail Patel about developer upskilling and generative AI. Together, they explore the following topics: the software engineer's learning journey, the ways current generative AI technologies could help or hinder it, and what the role of the software engineer becomes with powerful AI technologies. Read a transcript of this interview: https://bit.ly/42dVmTC Subscribe to the Software Architects' Newsletter for your monthly guide to the essential news and experience from industry peers on emerging patterns and technologies: https://www.infoq.com/software-architects-newsletter Upcoming Events: QCon London (April 8-10, 2024) Discover new ideas and insights from senior practitioners driving change and innovation in software development. https://qconlondon.com/ InfoQ Dev Summit Boston (June 24-25, 2024) Actionable insights on today's critical dev priorities. https://devsummit.infoq.com/ QCon San Francisco (November 18-22, 2024) Get practical inspiration and best practices on emerging software trends directly from senior software developers at early adopter companies. https://qconsf.com/ The InfoQ Podcasts: Weekly inspiration to drive innovation and build great teams from senior software leaders. Listen to all our podcasts and read interview transcripts: - The InfoQ Podcast https://www.infoq.com/podcasts/ - Engineering Culture Podcast by InfoQ https://www.infoq.com/podcasts/#engineering_culture Follow InfoQ: - Mastodon: https://techhub.social/@infoq - Twitter: twitter.com/InfoQ - LinkedIn: www.linkedin.com/company/infoq - Facebook: bit.ly/2jmlyG8 - Instagram: @infoqdotcom - Youtube: www.youtube.com/infoq Write for InfoQ: Learn and share the changes and innovations in professional software development. - Join a community of experts. - Increase your visibility. - Grow your career. https://www.infoq.com/write-for-infoq

We are running an end of year survey for our listeners! Please let us know any feedback you have, what episodes resonated with you, and guest requests for 2024! Survey link here!Before language models became all the rage in November 2022, image generation was the hottest space in AI (it was the subject of our first piece on Latent Space!) In our interview with Sharif Shameem from Lexica we talked through the launch of StableDiffusion and the early days of that space. At the time, the toolkit was still pretty rudimentary: Lexica made it easy to search images, you had the AUTOMATIC1111 Web UI to generate locally, some HuggingFace spaces that offered inference, and eventually DALL-E 2 through OpenAI's platform, but not much beyond basic text-to-image workflows.Today's guest, Suhail Doshi, is trying to solve this with Playground AI, an image editor reimagined with AI in mind. Some of the differences compared to traditional text-to-image workflows:* Real-time preview rendering using consistency: as you change your prompt, you can see changes in real-time before doing a final rendering of it.* Style filtering: rather than having to prompt exactly how you'd like an image to look, you can pick from a whole range of filters both from Playground's model as well as Stable Diffusion (like RealVis, Starlight XL, etc). We talk about this at 25:46 in the podcast.* Expand prompt: similar to DALL-E3, Playground will do some prompt tuning for you to get better results in generation. Unlike DALL-E3, you can turn this off at any time if you are a prompting wizard* Image editing: after generation, you have tools like a magic eraser, inpainting pencil, etc. This makes it easier to do a full workflow in Playground rather than switching to another tool like Photoshop.Outside of the product, they have also trained a new model from scratch, Playground v2, which is fully open source and open weights and allows for commercial usage. They benchmarked the model against SDXL across 1,000 prompts and found that humans preferred the Playground generation 70% of the time. They had similar results on PartiPrompts:They also created a new benchmark, MJHQ-30K, for “aesthetic quality”:We introduce a new benchmark, MJHQ-30K, for automatic evaluation of a model's aesthetic quality. The benchmark computes FID on a high-quality dataset to gauge aesthetic quality.We curate the high-quality dataset from Midjourney with 10 common categories, each category with 3K samples. Following common practice, we use aesthetic score and CLIP score to ensure high image quality and high image-text alignment. Furthermore, we take extra care to make the data diverse within each category.Suhail was pretty open with saying that Midjourney is currently the best product for imagine generation out there, and that's why they used it as the base for this benchmark. I think it's worth comparing yourself to maybe the best thing and try to find like a really fair way of doing that. So I think more people should try to do that. I definitely don't think you should be kind of comparing yourself on like some Google model or some old SD, Stable Diffusion model and be like, look, we beat Stable Diffusion 1.5. I think users ultimately want care, how close are you getting to the thing that people mostly agree with? [00:23:47]We also talked a lot about Suhail's founder journey from starting Mixpanel in 2009, then going through YC again with Mighty, and eventually sunsetting that to pivot into Playground. Enjoy!Show Notes* Suhail's Twitter* “Starting my road to learn AI”* Bill Gates book trip* Playground* Playground v2 Announcement* $40M raise announcement* “Running infra dev ops for 24 A100s”* Mixpanel* Mighty* “I decided to stop working on Mighty”* Fast.ai* CivitTimestamps* [00:00:00] Intros* [00:02:59] Being early in ML at Mixpanel* [00:04:16] Pivoting from Mighty to Playground and focusing on generative AI* [00:07:54] How DALL-E 2 inspired Mighty* [00:09:19] Reimagining the graphics editor with AI* [00:17:34] Training the Playground V2 model from scratch to advance generative graphics* [00:21:11] Techniques used to improve Playground V2 like data filtering and model tuning* [00:25:21] Releasing the MJHQ30K benchmark to evaluate generative models* [00:30:35] The limitations of current models for detailed image editing tasks* [00:34:06] Using post-generation user feedback to create better benchmarks* [00:38:28] Concerns over potential misuse of powerful generative models* [00:41:54] Rethinking the graphics editor user experience in the AI era* [00:45:44] Integrating consistency models into Playground using preview rendering* [00:47:23] Interacting with the Stable Diffusion LoRAs community* [00:51:35] Running DevOps on A100s* [00:53:12] Startup ideas?TranscriptAlessio: Hey everyone, welcome to the Latent Space podcast. This is Alessio, partner and CTO-in-Residence at Decibel Partners, and I'm joined by my co-host Swyx, founder of Smol AI. [00:00:15]Swyx: Hey, and today in the studio we have Suhail Doshi, welcome. [00:00:18]Suhail: Yeah, thanks. Thanks for having me. [00:00:20]Swyx: So among many things, you're a CEO and co-founder of Mixpanel, and I think about three years ago you left to start Mighty, and more recently, I think about a year ago, transitioned into Playground, and you've just announced your new round. How do you like to be introduced beyond that? [00:00:34]Suhail: Just founder of Playground is fine, yeah, prior co-founder and CEO of Mixpanel. [00:00:40]Swyx: Yeah, awesome. I'd just like to touch on Mixpanel a little bit, because it's obviously one of the more successful analytics companies we previously had amplitude on, and I'm curious if you had any reflections on the interaction of that amount of data that people would want to use for AI. I don't know if there's still a part of you that stays in touch with that world. [00:00:59]Suhail: Yeah, I mean, the short version is that maybe back in like 2015 or 2016, I don't really remember exactly, because it was a while ago, we had an ML team at Mixpanel, and I think this is when maybe deep learning or something really just started getting kind of exciting, and we were thinking that maybe given that we had such vast amounts of data, perhaps we could predict things. So we built two or three different features, I think we built a feature where we could predict whether users would churn from your product. We made a feature that could predict whether users would convert, we built a feature that could do anomaly detection, like if something occurred in your product, that was just very surprising, maybe a spike in traffic in a particular region, can we tell you that that happened? Because it's really hard to like know everything that's going on with your data, can we tell you something surprising about your data? And we tried all of these various features, most of it boiled down to just like, you know, using logistic regression, and it never quite seemed very groundbreaking in the end. And so I think, you know, we had a four or five person ML team, and I think we never expanded it from there. And I did all these Fast AI courses trying to learn about ML. And that was the- That's the first time you did fast AI. Yeah, that was the first time I did fast AI. Yeah, I think I've done it now three times, maybe. [00:02:12]Swyx: Oh, okay. [00:02:13]Suhail: I didn't know it was the third. No, no, just me reviewing it, it's maybe three times, but yeah. [00:02:16]Swyx: You mentioned prediction, but honestly, like it's also just about the feedback, right? The quality of feedback from users, I think it's useful for anyone building AI applications. [00:02:25]Suhail: Yeah. Yeah, I think I haven't spent a lot of time thinking about Mixpanel because it's been a long time, but sometimes I'm like, oh, I wonder what we could do now. And then I kind of like move on to whatever I'm working on, but things have changed significantly since. [00:02:39]Swyx: And then maybe we'll touch on Mighty a little bit. Mighty was very, very bold. My framing of it was, you will run our browsers for us because everyone has too many tabs open. I have too many tabs open and slowing down your machines that you can do it better for us in a centralized data center. [00:02:51]Suhail: Yeah, we were first trying to make a browser that we would stream from a data center to your computer at extremely low latency, but the real objective wasn't trying to make a browser or anything like that. The real objective was to try to make a new kind of computer. And the thought was just that like, you know, we have these computers in front of us today and we upgrade them or they run out of RAM or they don't have enough RAM or not enough disk or, you know, there's some limitation with our computers, perhaps like data locality is a problem. Why do I need to think about upgrading my computer ever? And so, you know, we just had to kind of observe that like, well, actually it seems like a lot of applications are just now in the browser, you know, it's like how many real desktop applications do we use relative to the number of applications we use in the browser? So it's just this realization that actually like, you know, the browser was effectively becoming more or less our operating system over time. And so then that's why we kind of decided to go, hmm, maybe we can stream the browser. Fortunately, the idea did not work for a couple of different reasons, but the objective is try to make sure new computer. [00:03:50]Swyx: Yeah, very, very bold. [00:03:51]Alessio: Yeah, and I was there at YC Demo Day when you first announced it. It was, I think, the last or one of the last in-person ones, at Pier34 in Mission Bay. How do you think about that now when everybody wants to put some of these models in people's machines and some of them want to stream them in, do you think there's maybe another wave of the same problem before it was like browser apps too slow, now it's like models too slow to run on device? [00:04:16]Suhail: Yeah. I mean, I've obviously pivoted away from Mighty, but a lot of what I somewhat believed at Mighty, maybe why I'm so excited about AI and what's happening, a lot of what Mighty was about was like moving compute somewhere else, right? Right now, applications, they get limited quantities of memory, disk, networking, whatever your home network has, et cetera. You know, what if these applications could somehow, if we could shift compute, and then these applications have vastly more compute than they do today. Right now it's just like client backend services, but you know, what if we could change the shape of how applications could interact with things? And it's changed my thinking. In some ways, AI has like a bit of a continuation of my belief that like perhaps we can really shift compute somewhere else. One of the problems with Mighty was that JavaScript is single-threaded in the browser. And what we learned, you know, the reason why we kind of abandoned Mighty was because I didn't believe we could make a new kind of computer. We could have made some kind of enterprise business, probably it could have made maybe a lot of money, but it wasn't going to be what I hoped it was going to be. And so once I realized that most of a web app is just going to be single-threaded JavaScript, then the only thing you could do largely withstanding changing JavaScript, which is a fool's errand most likely, make a better CPU, right? And there's like three CPU manufacturers, two of which sell, you know, big ones, you know, AMD, Intel, and then of course like Apple made the M1. And it's not like single-threaded CPU core performance, single-core performance was increasing very fast, it's plateauing rapidly. And even these different companies were not doing as good of a job, you know, sort of with the continuation of Moore's law. But what happened in AI was that you got like, if you think of the AI model as like a computer program, like just like a compiled computer program, it is literally built and designed to do massive parallel computations. And so if you could take like the universal approximation theorem to its like kind of logical complete point, you know, you're like, wow, I can get, make computation happen really rapidly and parallel somewhere else, you know, so you end up with these like really amazing models that can like do anything. It just turned out like perhaps the new kind of computer would just simply be shifted, you know, into these like really amazing AI models in reality. Yeah. [00:06:30]Swyx: Like I think Andrej Karpathy has always been, has been making a lot of analogies with the LLMOS. [00:06:34]Suhail: I saw his video and I watched that, you know, maybe two weeks ago or something like that. I was like, oh man, this, I very much resonate with this like idea. [00:06:41]Swyx: Why didn't I see this three years ago? [00:06:43]Suhail: Yeah. I think, I think there still will be, you know, local models and then there'll be these very large models that have to be run in data centers. I think it just depends on kind of like the right tool for the job, like any engineer would probably care about. But I think that, you know, by and large, like if the models continue to kind of keep getting bigger, you're always going to be wondering whether you should use the big thing or the small, you know, the tiny little model. And it might just depend on like, you know, do you need 30 FPS or 60 FPS? Maybe that would be hard to do, you know, over a network. [00:07:13]Swyx: You tackled a much harder problem latency wise than the AI models actually require. Yeah. [00:07:18]Suhail: Yeah. You can do quite well. You can do quite well. You definitely did 30 FPS video streaming, did very crazy things to make that work. So I'm actually quite bullish on the kinds of things you can do with networking. [00:07:30]Swyx: Maybe someday you'll come back to that at some point. But so for those that don't know, you're very transparent on Twitter. Very good to follow you just to learn your insights. And you actually published a postmortem on Mighty that people can read up on and willing to. So there was a bit of an overlap. You started exploring the AI stuff in June 2022, which is when you started saying like, I'm taking fast AI again. Maybe, was there more context around that? [00:07:54]Suhail: Yeah. I think I was kind of like waiting for the team at Mighty to finish up, you know, something. And I was like, okay, well, what can I do? I guess I will make some kind of like address bar predictor in the browser. So we had, you know, we had forked Chrome and Chromium. And I was like, you know, one thing that's kind of lame is that like this browser should be like a lot better at predicting what I might do, where I might want to go. It struck me as really odd that, you know, Chrome had very little AI actually or ML inside this browser. For a company like Google, you'd think there's a lot. Code is actually just very, you know, it's just a bunch of if then statements is more or less the address bar. So it seemed like a pretty big opportunity. And that's also where a lot of people interact with the browser. So, you know, long story short, I was like, hmm, I wonder what I could build here. So I started to take some AI courses and review the material again and get back to figuring it out. But I think that was somewhat serendipitous because right around April was, I think, a very big watershed moment in AI because that's when Dolly 2 came out. And I think that was the first truly big viral moment for generative AI. [00:08:59]Swyx: Because of the avocado chair. [00:09:01]Suhail: Yeah, exactly. [00:09:02]Swyx: It wasn't as big for me as Stable Diffusion. [00:09:04]Suhail: Really? [00:09:05]Swyx: Yeah, I don't know. Dolly was like, all right, that's cool. [00:09:07]Suhail: I don't know. Yeah. [00:09:09]Swyx: I mean, they had some flashy videos, but it didn't really register. [00:09:13]Suhail: That moment of images was just such a viral novel moment. I think it just blew people's mind. Yeah. [00:09:19]Swyx: I mean, it's the first time I encountered Sam Altman because they had this Dolly 2 hackathon and they opened up the OpenAI office for developers to walk in back when it wasn't as much of a security issue as it is today. I see. Maybe take us through the journey to decide to pivot into this and also choosing images. Obviously, you were inspired by Dolly, but there could be any number of AI companies and businesses that you could start and why this one, right? [00:09:45]Suhail: Yeah. So I think at that time, Mighty and OpenAI was not quite as popular as it is all of a sudden now these days, but back then they had a lot more bandwidth to kind of help anybody. And so we had been talking with the team there around trying to see if we could do really fast low latency address bar prediction with GPT-3 and 3.5 and that kind of thing. And so we were sort of figuring out how could we make that low latency. I think that just being able to talk to them and kind of being involved gave me a bird's eye view into a bunch of things that started to happen. Latency first was the Dolly 2 moment, but then stable diffusion came out and that was a big moment for me as well. And I remember just kind of like sitting up one night thinking, I was like, you know, what are the kinds of companies one could build? Like what matters right now? One thing that I observed is that I find a lot of inspiration when I'm working in a field in something and then I can identify a bunch of problems. Like for Mixpanel, I was an intern at a company and I just noticed that they were doing all this data analysis. And so I thought, hmm, I wonder if I could make a product and then maybe they would use it. And in this case, you know, the same thing kind of occurred. It was like, okay, there are a bunch of like infrastructure companies that put a model up and then you can use their API, like Replicate is a really good example of that. There are a bunch of companies that are like helping you with training, model optimization, Mosaic at the time, and probably still, you know, was doing stuff like that. So I just started listing out like every category of everything, of every company that was doing something interesting. I started listing out like weights and biases. I was like, oh man, weights and biases is like this great company. Do I want to compete with that company? I might be really good at competing with that company because of Mixpanel because it's so much of like analysis. But I was like, no, I don't want to do anything related to that. That would, I think that would be too boring now at this point. So I started to list out all these ideas and one thing I observed was that at OpenAI, they had like a playground for GPT-3, right? All it was is just like a text box more or less. And then there were some settings on the right, like temperature and whatever. [00:11:41]Swyx: Top K. [00:11:42]Suhail: Yeah, top K. You know, what's your end stop sequence? I mean, that was like their product before GPT, you know, really difficult to use, but fun if you're like an engineer. And I just noticed that their product kind of was evolving a little bit where the interface kind of was getting a little bit more complex. They had like a way where you could like generate something in the middle of a sentence and all those kinds of things. And I just thought to myself, I was like, everything is just like this text box and you generate something and that's about it. And stable diffusion had kind of come out and it was all like hugging face and code. Nobody was really building any UI. And so I had this kind of thing where I wrote prompt dash like question mark in my notes and I didn't know what was like the product for that at the time. I mean, it seems kind of trite now, but I just like wrote prompt. What's the thing for that? Manager. Prompt manager. Do you organize them? Like, do you like have a UI that can play with them? Yeah. Like a library. What would you make? And so then, of course, then you thought about what would the modalities be given that? How would you build a UI for each kind of modality? And so there are a couple of people working on some pretty cool things. And I basically chose graphics because it seemed like the most obvious place where you could build a really powerful, complex UI. That's not just only typing a box. It would very much evolve beyond that. Like what would be the best thing for something that's visual? Probably something visual. Yeah. I think that just that progression kind of happened and it just seemed like there was a lot of effort going into language, but not a lot of effort going into graphics. And then maybe the very last thing was, I think I was talking to Aditya Ramesh, who was the co-creator of DALL-E 2 and Sam. And I just kind of went to these guys and I was just like, hey, are you going to make like a UI for this thing? Like a true UI? Are you going to go for this? Are you going to make a product? For DALL-E. Yeah. For DALL-E. Yeah. Are you going to do anything here? Because if you are going to do it, just let me know and I will stop and I'll go do something else. But if you're not going to do anything, I'll just do it. And so we had a couple of conversations around what that would look like. And then I think ultimately they decided that they were going to focus on language primarily. And I just felt like it was going to be very underinvested in. Yes. [00:13:46]Swyx: There's that sort of underinvestment from OpenAI, but also it's a different type of customer than you're used to, presumably, you know, and Mixpanel is very good at selling to B2B and developers will figure on you or not. Yeah. Was that not a concern? [00:14:00]Suhail: Well, not so much because I think that, you know, right now I would say graphics is in this very nascent phase. Like most of the customers are just like hobbyists, right? Yeah. Like it's a little bit of like a novel toy as opposed to being this like very high utility thing. But I think ultimately, if you believe that you could make it very high utility, the probably the next customers will end up being B2B. It'll probably not be like a consumer. There will certainly be a variation of this idea that's in consumer. But if your quest is to kind of make like something that surpasses human ability for graphics, like ultimately it will end up being used for business. So I think it's maybe more of a progression. In fact, for me, it's maybe more like Mixpanel started out as SMB and then very much like ended up starting to grow up towards enterprise. So for me, I think it will be a very similar progression. But yeah, I mean, the reason why I was excited about it is because it was a creative tool. I make music and it's AI. It's like something that I know I could stay up till three o'clock in the morning doing. Those are kind of like very simple bars for me. [00:14:56]Alessio: So you mentioned Dolly, Stable Diffusion. You just had Playground V2 come out two days ago. Yeah, two days ago. [00:15:02]Suhail: Two days ago. [00:15:03]Alessio: This is a model you train completely from scratch. So it's not a cheap fine tune on something. You open source everything, including the weights. Why did you decide to do it? I know you supported Stable Diffusion XL in Playground before, right? Yep. What made you want to come up with V2 and maybe some of the interesting, you know, technical research work you've done? [00:15:24]Suhail: Yeah. So I think that we continue to feel like graphics and these foundation models for anything really related to pixels, but also definitely images continues to be very underinvested. It feels a little like graphics is in like this GPT-2 moment, right? Like even GPT-3, even when GPT-3 came out, it was exciting, but it was like, what are you going to use this for? Yeah, we'll do some text classification and some semantic analysis and maybe it'll sometimes like make a summary of something and it'll hallucinate. But no one really had like a very significant like business application for GPT-3. And in images, we're kind of stuck in the same place. We're kind of like, okay, I write this thing in a box and I get some cool piece of artwork and the hands are kind of messed up and sometimes the eyes are a little weird. Maybe I'll use it for a blog post, you know, that kind of thing. The utility feels so limited. And so, you know, and then we, you sort of look at Stable Diffusion and we definitely use that model in our product and our users like it and use it and love it and enjoy it, but it hasn't gone nearly far enough. So we were kind of faced with the choice of, you know, do we wait for progress to occur or do we make that progress happen? So yeah, we kind of embarked on a plan to just decide to go train these things from scratch. And I think the community has given us so much. The community for Stable Diffusion I think is one of the most vibrant communities on the internet. It's like amazing. It feels like, I hope this is what like Homebrew Club felt like when computers like showed up because it's like amazing what that community will do and it moves so fast. I've never seen anything in my life and heard other people's stories around this where an academic research paper comes out and then like two days later, someone has sample code for it. And then two days later, there's a model. And then two days later, it's like in nine products, you know, they're all competing with each other. It's incredible to see like math symbols on an academic paper go to well-designed features in a product. So I think the community has done so much. So I think we wanted to give back to the community kind of on our way. Certainly we would train a better model than what we gave out on Tuesday, but we definitely felt like there needs to be some kind of progress in these open source models. The last kind of milestone was in July when Stable Diffusion Excel came out, but there hasn't been anything really since. Right. [00:17:34]Swyx: And there's Excel Turbo now. [00:17:35]Suhail: Well, Excel Turbo is like this distilled model, right? So it's like lower quality, but fast. You have to decide, you know, what your trade off is there. [00:17:42]Swyx: It's also a consistency model. [00:17:43]Suhail: I don't think it's a consistency model. It's like it's they did like a different thing. Yeah. I think it's like, I don't want to get quoted for this, but it's like something called ad like adversarial or something. [00:17:52]Swyx: That's exactly right. [00:17:53]Suhail: I've read something about that. Maybe it's like closer to GANs or something, but I didn't really read the full paper. But yeah, there hasn't been quite enough progress in terms of, you know, there's no multitask image model. You know, the closest thing would be something called like EmuEdit, but there's no model for that. It's just a paper that's within meta. So we did that and we also gave out pre-trained weights, which is very rare. Usually you just get the aligned model and then you have to like see if you can do anything with it. So we actually gave out, there's like a 256 pixel pre-trained stage and a 512. And we did that for academic research because we come across people all the time in academia, they have access to like one A100 or eight at best. And so if we can give them kind of like a 512 pre-trained model, our hope is that there'll be interesting novel research that occurs from that. [00:18:38]Swyx: What research do you want to happen? [00:18:39]Suhail: I would love to see more research around things that users care about tend to be things like character consistency. [00:18:45]Swyx: Between frames? [00:18:46]Suhail: More like if you have like a face. Yeah, yeah. Basically between frames, but more just like, you know, you have your face and it's in one image and then you want it to be like in another. And users are very particular and sensitive to faces changing because we know we're trained on faces as humans. Not seeing a lot of innovation, enough innovation around multitask editing. You know, there are two things like instruct pics to pics and then the EmuEdit paper that are maybe very interesting, but we certainly are not pushing the fold on that in that regard. All kinds of things like around that rotation, you know, being able to keep coherence across images, style transfer is still very limited. Just even reasoning around images, you know, what's going on in an image, that kind of thing. Things are still very, very underpowered, very nascent. So therefore the utility is very, very limited. [00:19:32]Alessio: On the 1K Prompt Benchmark, you are 2.5x prefer to Stable Diffusion XL. How do you get there? Is it better images in the training corpus? Can you maybe talk through the improvements in the model? [00:19:44]Suhail: I think they're still very early on in the recipe, but I think it's a lot of like little things and you know, every now and then there are some big important things like certainly your data quality is really, really important. So we spend a lot of time thinking about that. But I would say it's a lot of things that you kind of clean up along the way as you train your model. Everything from captions to the data that you align with after pre-train to how you're picking your data sets, how you filter your data sets. I feel like there's a lot of work in AI that doesn't really feel like AI. It just really feels like just data set filtering and systems engineering and just like, you know, and the recipe is all there, but it's like a lot of extra work to do that. I think we plan to do a Playground V 2.1, maybe either by the end of the year or early next year. And we're just like watching what the community does with the model. And then we're just going to take a lot of the things that they're unhappy about and just like fix them. You know, so for example, like maybe the eyes of people in an image don't feel right. They feel like they're a little misshapen or they're kind of blurry feeling. That's something that we already know we want to fix. So I think in that case, it's going to be about data quality. Or maybe you want to improve the kind of the dynamic range of color. You know, we want to make sure that that's like got a good range in any image. So what technique can we use there? There's different things like offset noise, pyramid noise, terminal zero, SNR, like there are all these various interesting things that you can do. So I think it's like a lot of just like tricks. Some are tricks, some are data, and some is just like cleaning. [00:21:11]Swyx: Specifically for faces, it's very common to use a pipeline rather than just train the base model more. Do you have a strong belief either way on like, oh, they should be separated out to different stages for like improving the eyes, improving the face or enhance or whatever? Or do you think like it can all be done in one model? [00:21:28]Suhail: I think we will make a unified model. Yeah, I think it will. I think we'll certainly in the end, ultimately make a unified model. There's not enough research about this. Maybe there is something out there that we haven't read. There are some bottlenecks, like for example, in the VAE, like the VAEs are ultimately like compressing these things. And so you don't know. And then you might have like a big informational information bottleneck. So maybe you would use a pixel based model, perhaps. I think we've talked to people, everyone from like Rombach to various people, Rombach trained stable diffusion. I think there's like a big question around the architecture of these things. It's still kind of unknown, right? Like we've got transformers and we've got like a GPT architecture model, but then there's this like weird thing that's also seemingly working with diffusion. And so, you know, are we going to use vision transformers? Are we going to move to pixel based models? Is there a different kind of architecture? We don't really, I don't think there have been enough experiments. Still? Oh my God. [00:22:21]Swyx: Yeah. [00:22:22]Suhail: That's surprising. I think it's very computationally expensive to do a pipeline model where you're like fixing the eyes and you're fixing the mouth and you're fixing the hands. [00:22:29]Swyx: That's what everyone does as far as I understand. [00:22:31]Suhail: I'm not exactly sure what you mean, but if you mean like you get an image and then you will like make another model specifically to fix a face, that's fairly computationally expensive. And I think it's like not probably not the right way. Yeah. And it doesn't generalize very well. Now you have to pick all these different things. [00:22:45]Swyx: Yeah. You're just kind of glomming things on together. Yeah. Like when I look at AI artists, like that's what they do. [00:22:50]Suhail: Ah, yeah, yeah, yeah. They'll do things like, you know, I think a lot of ARs will do control net tiling to do kind of generative upscaling of all these different pieces of the image. Yeah. And I think these are all just like, they're all hacks ultimately in the end. I mean, it just to me, it's like, let's go back to where we were just three years, four years ago with where deep learning was at and where language was that, you know, it's the same thing. It's like we were like, okay, well, I'll just train these very narrow models to try to do these things and kind of ensemble them or pipeline them to try to get to a best in class result. And here we are with like where the models are gigantic and like very capable of solving huge amounts of tasks when given like lots of great data. [00:23:28]Alessio: You also released a new benchmark called MJHQ30K for automatic evaluation of a model's aesthetic quality. I have one question. The data set that you use for the benchmark is from Midjourney. Yes. You have 10 categories. How do you think about the Playground model, Midjourney, like, are you competitors? [00:23:47]Suhail: There are a lot of people, a lot of people in research, they like to compare themselves to something they know they can beat, right? Maybe this is the best reason why it can be helpful to not be a researcher also sometimes like I'm not trained as a researcher, I don't have a PhD in anything AI related, for example. But I think if you care about products and you care about your users, then the most important thing that you want to figure out is like everyone has to acknowledge that Midjourney is very good. They are the best at this thing. I'm happy to admit that. I have no problem admitting that. Just easy. It's very visual to tell. So I think it's incumbent on us to try to compare ourselves to the thing that's best, even if we lose, even if we're not the best. At some point, if we are able to surpass Midjourney, then we only have ourselves to compare ourselves to. But on First Blush, I think it's worth comparing yourself to maybe the best thing and try to find like a really fair way of doing that. So I think more people should try to do that. I definitely don't think you should be kind of comparing yourself on like some Google model or some old SD, Stable Diffusion model and be like, look, we beat Stable Diffusion 1.5. I think users ultimately want care, how close are you getting to the thing that people mostly agree with? So we put out that benchmark for no other reason to say like, this seems like a worthy thing for us to at least try, for people to try to get to. And then if we surpass it, great, we'll come up with another one. [00:25:06]Alessio: Yeah, no, that's awesome. And you killed Stable Diffusion Excel and everything. In the benchmark chart, it says Playground V2 1024 pixel dash aesthetic. Do you have kind of like, yeah, style fine tunes or like what's the dash aesthetic for? [00:25:21]Suhail: We debated this, maybe we named it wrong or something, but we were like, how do we help people realize the model that's aligned versus the models that weren't? Because we gave out pre-trained models, we didn't want people to like use those. So that's why they're called base. And then the aesthetic model, yeah, we wanted people to pick up the thing that makes things pretty. Who wouldn't want the thing that's aesthetic? But if there's a better name, we're definitely open to feedback. No, no, that's cool. [00:25:46]Alessio: I was using the product. You also have the style filter and you have all these different styles. And it seems like the styles are tied to the model. So there's some like SDXL styles, there's some Playground V2 styles. Can you maybe give listeners an overview of how that works? Because in language, there's not this idea of like style, right? Versus like in vision model, there is, and you cannot get certain styles in different [00:26:11]Suhail: models. [00:26:12]Alessio: So how do styles emerge and how do you categorize them and find them? [00:26:15]Suhail: Yeah, I mean, it's so fun having a community where people are just trying a model. Like it's only been two days for Playground V2. And we actually don't know what the model's capable of and not capable of. You know, we certainly see problems with it. But we have yet to see what emergent behavior is. I mean, we've just sort of discovered that it takes about like a week before you start to see like new things. I think like a lot of that style kind of emerges after that week, where you start to see, you know, there's some styles that are very like well known to us, like maybe like pixel art is a well known style. Photorealism is like another one that's like well known to us. But there are some styles that cannot be easily named. You know, it's not as simple as like, okay, that's an anime style. It's very visual. And in the end, you end up making up the name for what that style represents. And so the community kind of shapes itself around these different things. And so if anyone that's into stable diffusion and into building anything with graphics and stuff with these models, you know, you might have heard of like Proto Vision or Dream Shaper, some of these weird names, but they're just invented by these authors. But they have a sort of je ne sais quoi that, you know, appeals to users. [00:27:26]Swyx: Because it like roughly embeds to what you what you want. [00:27:29]Suhail: I guess so. I mean, it's like, you know, there's one of my favorite ones that's fine tuned. It's not made by us. It's called like Starlight XL. It's just this beautiful model. It's got really great color contrast and visual elements. And the users love it. I love it. And it's so hard. I think that's like a very big open question with graphics that I'm not totally sure how we'll solve. I don't know. It's, it's like an evolving situation too, because styles get boring, right? They get fatigued. Like it's like listening to the same style of pop song. I try to relate to graphics a little bit like with music, because I think it gives you a little bit of a different shape to things. Like it's not as if we just have pop music, rap music and country music, like all of these, like the EDM genre alone has like sub genres. And I think that's very true in graphics and painting and art and anything that we're doing. There's just these sub genres, even if we can't quite always name them. But I think they are emergent from the community, which is why we're so always happy to work with the community. [00:28:26]Swyx: That is a struggle. You know, coming back to this, like B2B versus B2C thing, B2C, you're going to have a huge amount of diversity and then it's going to reduce as you get towards more sort of B2B type use cases. I'm making this up here. So like you might be optimizing for a thing that you may eventually not need. [00:28:42]Suhail: Yeah, possibly. Yeah, possibly. I think like a simple thing with startups is that I worry sometimes by trying to be overly ambitious and like really scrutinizing like what something is in its most nascent phase that you miss the most ambitious thing you could have done. Like just having like very basic curiosity with something very small can like kind of lead you to something amazing. Like Einstein definitely did that. And then he like, you know, he basically won all the prizes and got everything he wanted and then basically did like kind of didn't really. He can dismiss quantum and then just kind of was still searching, you know, for the unifying theory. And he like had this quest. I think that happens a lot with like Nobel Prize people. I think there's like a term for it that I forget. I actually wanted to go after a toy almost intentionally so long as that I could see, I could imagine that it would lead to something very, very large later. Like I said, it's very hobbyist, but you need to start somewhere. You need to start with something that has a big gravitational pull, even if these hobbyists aren't likely to be the people that, you know, have a way to monetize it or whatever, even if they're, but they're doing it for fun. So there's something, something there that I think is really important. But I agree with you that, you know, in time we will absolutely focus on more utilitarian things like things that are more related to editing feats that are much harder. And so I think like a very simple use case is just, you know, I'm not a graphics designer. It seems like very simple that like you, if we could give you the ability to do really complex graphics without skill, wouldn't you want that? You know, like my wife the other day was set, you know, said, I wish Playground was better. When are you guys going to have a feature where like we could make my son, his name's Devin, smile when he was not smiling in the picture for the holiday card. Right. You know, just being able to highlight his, his mouth and just say like, make him smile. Like why can't we do that with like high fidelity and coherence, little things like that, all the way to putting you in completely different scenarios. [00:30:35]Swyx: Is that true? Can we not do that in painting? [00:30:37]Suhail: You can do in painting, but the quality is just so bad. Yeah. It's just really terrible quality. You know, it's like you'll do it five times and it'll still like kind of look like crooked or just artifact. Part of it's like, you know, the lips on the face, there's such little information there. So small that the models really struggle with it. Yeah. [00:30:55]Swyx: Make the picture smaller and you don't see it. That's my trick. I don't know. [00:30:59]Suhail: Yeah. Yeah. That's true. Or, you know, you could take that region and make it really big and then like say it's a mouth and then like shrink it. It feels like you're wrestling with it more than it's doing something that kind of surprises you. [00:31:12]Swyx: Yeah. It feels like you are very much the internal tastemaker, like you carry in your head this vision for what a good art model should look like. Do you find it hard to like communicate it to like your team and other people? Just because it's obviously it's hard to put into words like we just said. [00:31:26]Suhail: Yeah. It's very hard to explain. Images have such high bitrate compared to just words and we don't have enough words to describe these things. It's not terribly difficult. I think everyone on the team, if they don't have good kind of like judgment taste or like an eye for some of these things, they're like steadily building it because they have no choice. Right. So in that realm, I don't worry too much, actually. Like everyone is kind of like learning to get the eye is what I would call it. But I also have, you know, my own narrow taste. Like I don't represent the whole population either. [00:31:59]Swyx: When you benchmark models, you know, like this benchmark we're talking about, we use FID. Yeah. Input distance. OK. That's one measure. But like it doesn't capture anything you just said about smiles. [00:32:08]Suhail: Yeah. FID is generally a bad metric. It's good up to a point and then it kind of like is irrelevant. Yeah. [00:32:14]Swyx: And then so are there any other metrics that you like apart from vibes? I'm always looking for alternatives to vibes because vibes don't scale, you know. [00:32:22]Suhail: You know, it might be fun to kind of talk about this because it's actually kind of fresh. So up till now, we haven't needed to do a ton of like benchmarking because we hadn't trained our own model and now we have. So now what? What does that mean? How do we evaluate it? And, you know, we're kind of like living with the last 48, 72 hours of going, did the way that we benchmark actually succeed? [00:32:43]Swyx: Did it deliver? [00:32:44]Suhail: Right. You know, like I think Gemini just came out. They just put out a bunch of benchmarks. But all these benchmarks are just an approximation of how you think it's going to end up with real world performance. And I think that's like very fascinating to me. So if you fake that benchmark, you'll still end up in a really bad scenario at the end of the day. And so, you know, one of the benchmarks we did was we kind of curated like a thousand prompts. And I think that's kind of what we published in our blog post, you know, of all these tasks that we a lot of some of them are curated by our team where we know the models all suck at it. Like my favorite prompt that no model is really capable of is a horse riding an astronaut, the inverse one. And it's really, really hard to do. [00:33:22]Swyx: Not in data. [00:33:23]Suhail: You know, another one is like a giraffe underneath a microwave. How does that work? Right. There's so many of these little funny ones. We do. We have prompts that are just like misspellings of things. Yeah. We'll figure out if the models will figure it out. [00:33:36]Swyx: They should embed to the same space. [00:33:39]Suhail: Yeah. And just like all these very interesting weirdo things. And so we have so many of these and then we kind of like evaluate whether the models are any good at it. And the reality is that they're all bad at it. And so then you're just picking the most aesthetic image. We're still at the beginning of building like the best benchmark we can that aligns most with just user happiness, I think, because we're not we're not like putting these in papers and trying to like win, you know, I don't know, awards at ICCV or something if they have awards. You could. [00:34:05]Swyx: That's absolutely a valid strategy. [00:34:06]Suhail: Yeah, you could. But I don't think it could correlate necessarily with the impact we want to have on humanity. I think we're still evolving whatever our benchmarks are. So the first benchmark was just like very difficult tasks that we know the models are bad at. Can we come up with a thousand of these, whether they're hand rated and some of them are generated? And then can we ask the users, like, how do we do? And then we wanted to use a benchmark like party prompts. We mostly did that so people in academia could measure their models against ours versus others. But yeah, I mean, fit is pretty bad. And I think in terms of vibes, it's like you put out the model and then you try to see like what users make. And I think my sense is that we're going to take all the things that we notice that the users kind of were failing at and try to find like new ways to measure that, whether that's like a smile or, you know, color contrast or lighting. One benefit of Playground is that we have users making millions of images every single day. And so we can just ask them for like a post generation feedback. Yeah, we can just ask them. We can just say, like, how good was the lighting here? How was the subject? How was the background? [00:35:06]Swyx: Like a proper form of like, it's just like you make it, you come to our site, you make [00:35:10]Suhail: an image and then we say, and then maybe randomly you just say, hey, you know, like, how was the color and contrast of this image? And you say it was not very good, just tell us. So I think I think we can get like tens of thousands of these evaluations every single day to truly measure real world performance as opposed to just like benchmark performance. I would like to publish hopefully next year. I think we will try to publish a benchmark that anyone could use, that we evaluate ourselves on and that other people can, that we think does a good job of approximating real world performance because we've tried it and done it and noticed that it did. Yeah. I think we will do that. [00:35:45]Swyx: I personally have a few like categories that I consider special. You know, you know, you have like animals, art, fashion, food. There are some categories which I consider like a different tier of image. Top among them is text in images. How do you think about that? So one of the big wow moments for me, something I've been looking out for the entire year is just the progress of text and images. Like, can you write in an image? Yeah. And Ideogram came out recently, which had decent but not perfect text and images. Dolly3 had improved some and all they said in their paper was that they just included more text in the data set and it just worked. I was like, that's just lazy. But anyway, do you care about that? Because I don't see any of that in like your sample. Yeah, yeah. [00:36:27]Suhail: The V2 model was mostly focused on image quality versus like the feature of text synthesis. [00:36:33]Swyx: Well, as a business user, I care a lot about that. [00:36:35]Suhail: Yeah. Yeah. I'm very excited about text synthesis. And yeah, I think Ideogram has done a good job of maybe the best job. Dolly has like a hit rate. Yes. You know, like sometimes it's Egyptian letters. Yeah. I'm very excited about text synthesis. You know, I don't have much to say on it just yet. You know, you don't want just text effects. I think where this has to go is it has to be like you could like write little tiny pieces of text like on like a milk carton. That's maybe not even the focal point of a scene. I think that's like a very hard task that, you know, if you could do something like that, then there's a lot of other possibilities. Well, you don't have to zero shot it. [00:37:09]Swyx: You can just be like here and focus on this. [00:37:12]Suhail: Sure. Yeah, yeah. Definitely. Yeah. [00:37:16]Swyx: Yeah. So I think text synthesis would be very exciting. I'll also flag that Max Wolf, MiniMaxxier, which you must have come across his work. He's done a lot of stuff about using like logo masks that then map onto food and vegetables. And it looks like text, which can be pretty fun. [00:37:29]Suhail: That's the wonderful thing about like the open source community is that you get things like control net and then you see all these people do these just amazing things with control net. And then you wonder, I think from our point of view, we sort of go that that's really wonderful. But how do we end up with like a unified model that can do that? What are the bottlenecks? What are the issues? The community ultimately has very limited resources. And so they need these kinds of like workaround research ideas to get there. But yeah. [00:37:55]Swyx: Are techniques like control net portable to your architecture? [00:37:58]Suhail: Definitely. Yeah. We kept the Playground V2 exactly the same as SDXL. Not because not out of laziness, but just because we knew that the community already had tools. You know, all you have to do is maybe change a string in your code and then, you know, retrain a control net for it. So it was very intentional to do that. We didn't want to fragment the community with different architectures. Yeah. [00:38:16]Swyx: So basically, I'm going to go over three more categories. One is UIs, like app UIs, like mock UIs. Third is not safe for work, and then copyrighted stuff. I don't know if you care to comment on any of those. [00:38:28]Suhail: I think the NSFW kind of like safety stuff is really important. I kind of think that one of the biggest risks kind of going into maybe the U.S. election year will probably be very interrelated with like graphics, audio, video. I think it's going to be very hard to explain, you know, to a family relative who's not kind of in our world. And our world is like sometimes very, you know, we think it's very big, but it's very tiny compared to the rest of the world. Some people like there's still lots of humanity who have no idea what chat GPT is. And I think it's going to be very hard to explain, you know, to your uncle, aunt, whoever, you know, hey, I saw President Biden say this thing on a video, you know, I can't believe, you know, he said that. I think that's going to be a very troubling thing going into the world next year, the year after. [00:39:12]Swyx: That's more like a risk thing, like deepfakes, faking, political faking. But there's a lot of studies on how for most businesses, you don't want to train on not safe for work images, except that it makes you really good at bodies. [00:39:24]Suhail: Personally, we filter out NSFW type of images in our data set so that it's, you know, so our safety filter stuff doesn't have to work as hard. [00:39:32]Swyx: But you've heard this argument that not safe for work images are very good at human anatomy, which you do want to be good at. [00:39:38]Suhail: It's not like necessarily a bad thing to train on that data. It's more about like how you go and use it. That's why I was kind of talking about safety, you know, in part, because there are very terrible things that can happen in the world. If you have an extremely powerful graphics model, you know, suddenly like you can kind of imagine, you know, now if you can like generate nudes and then there's like you could do very character consistent things with faces, like what does that lead to? Yeah. And so I tend to think more what occurs after that, right? Even if you train on, let's say, you know, new data, if it does something to kind of help, there's nothing wrong with the human anatomy, it's very valid for a model to learn that. But then it's kind of like, how does that get used? And, you know, I won't bring up all of the very, very unsavory, terrible things that we see on a daily basis on the site, but I think it's more about what occurs. And so we, you know, we just recently did like a big sprint on safety. It's very difficult with graphics and art, right? Because there is tasteful art that has nudity, right? They're all over in museums, like, you know, there's very valid situations for that. And then there's the things that are the gray line of that, you know, what I might not find tasteful, someone might be like, that is completely tasteful, right? And then there are things that are way over the line. And then there are things that maybe you or, you know, maybe I would be okay with, but society isn't, you know? So where does that kind of end up on the spectrum of things? I think it's really hard with art. Sometimes even if you have like things that are not nude, if a child goes to your site, scrolls down some images, you know, classrooms of kids, you know, using our product, it's a really difficult problem. And it stretches mostly culture, society, politics, everything. [00:41:14]Alessio: Another favorite topic of our listeners is UX and AI. And I think you're probably one of the best all-inclusive editors for these things. So you don't just have the prompt, images come out, you pray, and now you do it again. First, you let people pick a seed so they can kind of have semi-repeatable generation. You also have, yeah, you can pick how many images and then you leave all of them in the canvas. And then you have kind of like this box, the generation box, and you can even cross between them and outpaint. There's all these things. How did you get here? You know, most people are kind of like, give me text, I give you image. You know, you're like, these are all the tools for you. [00:41:54]Suhail: Even though we were trying to make a graphics foundation model, I think we think that we're also trying to like re-imagine like what a graphics editor might look like given the change in technology. So, you know, I don't think we're trying to build Photoshop, but it's the only thing that we could say that people are largely familiar with. Oh, okay, there's Photoshop. What would Photoshop compare itself to pre-computer? I don't know, right? It's like, or kind of like a canvas, but you know, there's these menu options and you can use your mouse. What's a mouse? So I think that we're trying to re-imagine what a graphics editor might look like, not just for the fun of it, but because we kind of have no choice. Like there's this idea in image generation where you can generate images. That's like a super weird thing. What is that in Photoshop, right? You have to wait right now for the time being, but the wait is worth it often for a lot of people because they can't make that with their own skills. So I think it goes back to, you know, how we started the company, which was kind of looking at GPT-3's Playground, that the reason why we're named Playground is a homage to that actually. And, you know, it's like, shouldn't these products be more visual? These prompt boxes are like a terminal window, right? We're kind of at this weird point where it's just like MS-DOS. I remember my mom using MS-DOS and I memorized the keywords, like DIR, LS, all those things, right? It feels a little like we're there, right? Prompt engineering, parentheses to say beautiful or whatever, waits the word token more in the model or whatever. That's like super strange. I think a large portion of humanity would agree that that's not user-friendly, right? So how do we think about the products to be more user-friendly? Well, sure, you know, sure, it would be nice if I wanted to get rid of, like, the headphones on my head, you know, it'd be nice to mask it and then say, you know, can you remove the headphones? You know, if I want to grow, expand the image, you know, how can we make that feel easier without typing lots of words and being really confused? I don't even think we've nailed the UI UX yet. Part of that is because we're still experimenting. And part of that is because the model and the technology is going to get better. And whatever felt like the right UX six months ago is going to feel very broken now. So that's a little bit of how we got there is kind of saying, does everything have to be like a prompt in a box? Or can we do things that make it very intuitive for users? [00:44:03]Alessio: How do you decide what to give access to? So you have things like an expand prompt, which Dally 3 just does. It doesn't let you decide whether you should or not. [00:44:13]Swyx: As in, like, rewrites your prompts for you. [00:44:15]Suhail: Yeah, for that feature, I think once we get it to be cheaper, we'll probably just give it up. We'll probably just give it away. But we also decided something that might be a little bit different. We noticed that most of image generation is just, like, kind of casual. You know, it's in WhatsApp. It's, you know, it's in a Discord bot somewhere with Majorny. It's in ChatGPT. One of the differentiators I think we provide is at the expense of just lots of users necessarily. Mainstream consumers is that we provide as much, like, power and tweakability and configurability as possible. So the only reason why it's a toggle, because we know that users might want to use it and might not want to use it. There's some really powerful power user hobbyists that know what they're doing. And then there's a lot of people that just want something that looks cool, but they don't know how to prompt. And so I think a lot of Playground is more about going after that core user base that, like, knows, has a little bit more savviness and how to use these tools. You know, the average Dell user is probably not going to use ControlNet. They probably don't even know what that is. And so I think that, like, as the models get more powerful, as there's more tooling, hopefully you'll imagine a new sort of AI-first graphics editor that's just as, like, powerful and configurable as Photoshop. And you might have to master a new kind of tool. [00:45:28]Swyx: There's so many things I could go bounce off of. One, you mentioned about waiting. We have to kind of somewhat address the elephant in the room. Consistency models have been blowing up the past month. How do you think about integrating that? Obviously, there's a lot of other companies also trying to beat you to that space as well. [00:45:44]Suhail: I think we were the first company to integrate it. Ah, OK. [00:45:47]Swyx: Yeah. I didn't see your demo. [00:45:49]Suhail: Oops. Yeah, yeah. Well, we integrated it in a different way. OK. There are, like, 10 companies right now that have kind of tried to do, like, interactive editing, where you can, like, draw on the left side and then you get an image on the right side. We decided to kind of, like, wait and see whether there's, like, true utility on that. We have a different feature that's, like, unique in our product that is called preview rendering. And so you go to the product and you say, you know, we're like, what is the most common use case? The most common use case is you write a prompt and then you get an image. But what's the most annoying thing about that? The most annoying thing is, like, it feels like a slot machine, right? You're like, OK, I'm going to put it in and maybe I'll get something cool. So we did something that seemed a lot simpler, but a lot more relevant to how users already use these products, which is preview rendering. You toggle it on and it will show you a render of the image. And then graphics tools already have this. Like, if you use Cinema 4D or After Effects or something, it's called viewport rendering. And so we try to take something that exists in the real world that has familiarity and say, OK, you're going to get a rough sense of an early preview of this thing. And then when you're ready to generate, we're going to try to be as coherent about that image that you saw. That way, you're not spending so much time just like pulling down the slot machine lever. I think we were the first company to actually ship a quick LCM thing. Yeah, we were very excited about it. So we shipped it very quick. Yeah. [00:47:03]Swyx: Well, the demos I've been seeing, it's not like a preview necessarily. They're almost using it to animate their generations. Like, because you can kind of move shapes. [00:47:11]Suhail: Yeah, yeah, they're like doing it. They're animating it. But they're sort of showing, like, if I move a moon, you know, can I? [00:47:17]Swyx: I don't know. To me, it unlocks video in a way. [00:47:20]Suhail: Yeah. But the video models are already so much better than that. Yeah. [00:47:23]Swyx: There's another one, which I think is general ecosystem of Loras, right? Civit is obviously the most popular repository of Loras. How do you think about interacting with that ecosystem? [00:47:34]Suhail: The guy that did Lora, not the guy that invented Loras, but the person that brought Loras to Stable Diffusion actually works with us on some projects. His name is Simu. Shout out to Simu. And I think Loras are wonderful. Obviously, fine tuning all these Dreambooth models and such, it's just so heavy. And it's obvious in our conversation around styles and vibes, it's very hard to evaluate the artistry of these things. Loras give people this wonderful opportunity to create sub-genres of art. And I think they're amazing. Any graphics tool, any kind of thing that's expressing art has to provide some level of customization to its user base that goes beyond just typing Greg Rakowski in a prompt. We have to give more than that. It's not like users want to type these real artist names. It's that they don't know how else to get an image that looks interesting. They truly want originality and uniqueness. And I think Loras provide that. And they provide it in a very nice, scalable way. I hope that we find something even better than Loras in the long term, because there are still weaknesses to Loras, but I think they do a good job for now. Yeah. [00:48:39]Swyx: And so you would never compete with Civit? You would just kind of let people import? [00:48:43]Suhail: Civit's a site where all these things get kind of hosted by the community, right? And so, yeah, we'll often pull down some of the best things there. I think when we have a significantly better model, we will certainly build something that gets closer to that. Again, I go back to saying just I still think this is very nascent. Things are very underpowered, right? Loras are not easy to train. They're easy for an engineer. It sure would be nicer if I could just pick five or six reference images, right? And they might even be five or six different reference images that are not... They're just very different. They communicate a style, but they're actually like... It's like a mood board, right? And you have to be kind of an engineer almost to train these Loras or go to some site and be technically savvy, at least. It seems like it'd be much better if I could say, I love this style. Here are five images and you tell the model, like, this is what I want. And the model gives you something that's very aligned with what your style is, what you're talking about. And it's a style you couldn't even communicate, right? There's n

Join award-winning journalist Redi Tlhabi and a selection of guests, from leaders to policy-makers and climate activists, as they unpack what COP28 means for South Africa and the continent. In partnership with Investec Focus Radio, this four-part podcast series brings you the latest developments on the ground from the UN climate summit in Dubai. In this episode, hear from: • H.E Shamma bint Suhail bin Faris Al Mazrouei, Youth Climate Champion and Minister of State for Youth Affairs in UAE • Ellyanne Wanjiku, Chlystun Githae, 13-year-old Climate Activist • Kumi Naidoo, Human Rights and Climate Justice Activist Investec Focus Radio SA

Is implementing generative AI different from implementing other tools? Should CIOs build or buy, and how should they choose their AI partners? IIn this episode, Yadin sits down with Suhail Nimji, VP/Head of Business Development, Corporate Development, and Partnerships at Jasper, to discuss what he is seeing and hearing in the market. They dive into the change management differences with AI, as well as the questions CIOs should ask as they build AI partnerships.---------Key Quotes:“This is a journey, not a sort of, hey, we've implemented this thing and let's go. And so when I talk to CIOs about the landscape, it's more so who can you partner with on this journey? And I think that's the most important thing to think about. Because it will be iterative.”“The CIO's job is to be thinking about the next frontier constantly while having one eye on the present and one eye on the future. And to think that this is like a net new sort of revelation for them would be remiss. Their entire job with their leadership is to think about, how are we implementing the best technology for our customers, for our employees? How do we give the best experience? Generative is just another sort of like, oh, look, there's another tool that we should go evaluate.”---------Timestamps:(01:15) What is the current conversation about generative AI? (02:30) What is different about the AI conversation now? (07:34) Is upskilling and reskilling a big part of the conversation?(09:32) AI creates workflow change, more than a technical one (12:22) Deciding who to partner with(15:05) Trust in AI partnerships (16:20) Questions tech leaders should ask as they choose AI partners (21:44) Data security and privacy (24:38) Is this different than other tools? (27:27) Build versus buy (29:14) Are there unique hurtles when rolling out AI solutions?(30:47) Change management (33:54) Suhail's advice for CIOs--------Links:Suhail Nimji on LinkedInCIO Exchange on XYadin Porter de León on X[Subscribe to the Podcast] On Apple PodcastFor more podcasts, video and in-depth research go to https://www.vmware.com/cio

The government says it wants to protect local small businesses, which were facing competition from online cheaper retailers. We get the latest from our correspondent in Jakarta. Also in the programme, we talk to the energy minister of the United Arab Emirates, Suhail al-Mazrouei, about the role of the OPEC+, fuel prices and the rumours about the UAE mulling a departure from the oil producers cartel. And South Africans in the province of Gauteng are seeing water supply cuts as part of a "water shifting" scheme, the latest stopgap to one of the many infrastructure issues the country faces.

Suhail star is usually seen above the UAE skies towards the end of August. Mohammad Baker Rihan from Sharjah Academy For Astronomy, Space Sciences and Technology joins us to discuss how the weather is expected to change during this particular period. Listen to #Pulse95Radio in the UAE by tuning in on your radio (95.00 FM) or online on our website: www.pulse95radio.com ************************ Follow us on Social. www.facebook.com/pulse95radio www.twitter.com/pulse95radio www.instagram.com/pulse95radio www.youtube.com/pulse95radio

Bro. Suhail, Love In Action's pastor from Pakistan, joins Ken once again on "Sunday Morning with Love In Action" on The Joy FM. In this episode they talk about how disciples are being made in Pakistan, and how acts of compassion opens the door to sharing the Gospel of Jesus Christ with unreached people groups.   "Sunday Morning with Love In Action" airs every Sunday at 10:30 a.m. on The Joy FM 94.3/96.1/101.7, on the Alabama Joy FM app, and livestream at https://alabama.thejoyfm.com We thank Weed Man for their generous donation to make “Sunday Morning with Love In Action” possible.

In today's edition of “Sunday Morning with Love In Action” on The Joy FM, Bro. Suhail, Love In Action's pastor from Pakistan, joins Ken to talk about the exciting things God is doing in Pakistan and ways you can help.   "Sunday Morning with Love In Action" airs every Sunday at 10:30 a.m. on The Joy FM 94.3/96.1/101.7, on the Alabama Joy FM app, and livestream at https://alabama.thejoyfm.com   We thank Weed Man for their generous donation to make “Sunday Morning with Love In Action” possible.

In this episode of the Award-winning PRS Journal Club Podcast, 2023 Resident Ambassadors to the PRS Editorial Board – Rami Kantar, Yoshi Toyoda, and Ronnie Shammas- and special guest Suhail Mithani, MD, discuss the following articles from the July 2023 issue: “Creating a Policy for Coverage of Lymphatic Surgery: Addressing a Critical Unmet Need” Johnson, Otenti, Bates, et al. Read the article for FREE: https://bit.ly/LymphaticSurgeryPolicy Special guest Suhail Mithani, MD, is an Associate Professor of Plastic and Orthopedic Surgery at Duke University. He completed his residency training at Johns Hopkins followed by a hand fellowship at Duke. He currently specializes in all aspects of hand surgery and is an expert in reconstruction of the traumatic injury extremity.  READ the articles discussed in this podcast as well as free related content from the archives: https://bit.ly/JCJuly23Collection

In this episode of the Award-winning PRS Journal Club Podcast, 2023 Resident Ambassadors to the PRS Editorial Board – Rami Kantar, Yoshi Toyoda, and Ronnie Shammas- and special guest Suhail Mithani, MD, discuss the following articles from the July 2023 issue: “Functional Outcomes of Cubital Tunnel Release in Patients with Negative Electrodiagnostic Studies” by Townsend, Katt, Tawfik, et al. Read the article for FREE: https://bit.ly/FxnalCubitalTunnel Special guest Suhail Mithani, MD, is an Associate Professor of Plastic and Orthopedic Surgery at Duke University. He completed his residency training at Johns Hopkins followed by a hand fellowship at Duke. He currently specializes in all aspects of hand surgery and is an expert in reconstruction of the traumatic injury extremity.  READ the articles discussed in this podcast as well as free related content from the archives: https://bit.ly/JCJuly23Collection

In this episode of Frankly Speaking, we speak to Taliban leader and Head of the Political office in Doha, Suhail Shaheen, and ask him how the Taliban government really functions, if women and girls will ever be allowed to attend school, and how they've dealt with challenges to their authority from neighboring countries.

In this episode of the Award-winning PRS Journal Club Podcast, 2023 Resident Ambassadors to the PRS Editorial Board – Rami Kantar, Yoshi Toyoda, and Ronnie Shammas- and special guest Suhail Mithani, MD, discuss the following articles from the July 2023 issue: “Impact of Adding Carpal Tunnel Release or Trigger Finger Release to Carpometacarpal Arthroplasty on Postoperative Complications” by Trinh, Luan, Tawfik, et al. Read the article for FREE: https://bit.ly/AddingCarpalTunnel Special guest Suhail Mithani, MD, is an Associate Professor of Plastic and Orthopedic Surgery at Duke University. He completed his residency training at Johns Hopkins followed by a hand fellowship at Duke. He currently specializes in all aspects of hand surgery and is an expert in reconstruction of the traumatic injury extremity.  READ the articles discussed in this podcast as well as free related content from the archives: https://bit.ly/JCJuly23Collection

In this episode of Pop Wrap, Snayhil is joined by Ravina Sharma, Harshita Gaur & Suhail Nayyar as they share their journey of becoming an actor. They share their memories of what it was like to find their first acting jobs, the crazy audition experiences they got along the way, and what's in store from them, going forward. Tune in!  Follow Snayhil on Instagram : https://instagram.com/snayhil Follow Ravina on Instagram : https://www.instagram.com/ravinasharma_  Follow Suhail on Instagram : https://www.instagram.com/suhailnayyar/  Follow Harshita on Instagram : https://www.instagram.com/harshita1210/  Listen to Pop Wrap, Has It Aged Well? and Just A Filmy Game Show on the IVM Pop feed which is available across platforms. Spotify | Apple Podcasts | JioSaavn | Gaana | Amazon MusicSee omnystudio.com/listener for privacy information.

It seems you can't switch on your TV or pick up your phone these days without being assailed by headlines lamenting the crisis in our NHS. Whether it's nurses going on strike, long wait times for operations, ambulances queuing outside hospitals, or stories of a social care system on the verge of collapse…. There is undoubtedly a crisis in our health and care sector, but are we getting the whole picture, and are we hearing enough about what's being done by the people in charge to try and put things right? A new podcast series from Newcross Healthcare called Voices of Care has launched intending to do precisely that, giving leaders and experts from NHS Trusts, Health Boards, and care associations a chance to share their thoughts on the challenges facing the sector and explain how they are striving to give the workforce…whether its nurses, carers, doctors or administrators….the tools and the support they need to deliver high-quality care. Suhail Mirza has 20 years of experience as a Provider, Writer, and Speaker. He is the author of the LaingBuisson UK Healthcare Workforce Report, a wellness speaker and coach supporting the NHS workforce, and a Non-Executive Director on the Board of Newcross Healthcare  Learn more about your ad choices. Visit megaphone.fm/adchoices

00:00 Intro 00:30: Image technology breakthroughs 00:45 The Cognitive Revolution 03:10 Intro to Suhail 03:43 Sponsor 07:04 Suhail's path to AI 12:57 Suhail's vision for Playground 17:58 Suhail's cancellation on Twitter 19:06 AI artists are artists 20:25 Non-AI artists feel threatened by AI 26:47 Suhail on defensibility at AI companies 30:30 Playground's product roadmap 33:01 Suhail on good design 35:55 Latent space 44:04 Building Playground with lessons learned from Mighty 53:55 Monitoring led to 2x improvement in the product 55:53 How people use Playground 1:03:48 AI is having it's mobile moment 01:15:12 Finding, investing and building durable AI companies 01:22:06 Suhail's kid's best friends may be AI characters   01:23:20 AI religion 01:24:16 Conclusion   RECOMMENDED PODCAST: The HR industry is at a crossroads. What will it take to construct the next generation of incredible businesses – and where can people leaders have the most business impact? Hosts Nolan Church and Kelli Dragovich have been through it all, the highs and the lows – IPOs, layoffs, executive turnover, board meetings, culture changes, and more. With a lineup of industry vets and experts, Nolan and Kelli break down the nitty-gritty details, trade offs, and dynamics of constructing high performing companies. Through unfiltered conversations that can only happen between seasoned practitioners, Kelli and Nolan dive deep into the kind of leadership-level strategy that often happens behind closed doors. Check out the first episode with the architect of Netflix's culture deck Patty McCord. https://link.chtbl.com/hrheretics Thank you Omneky for sponsoring The Cognitive Revolution. Omneky is an omnichannel creative generation platform that lets you launch hundreds of thousands of ad iterations that actually work, customized across all platforms, with a click of a button. Omneky combines generative AI and real time advertising data, to generate personalized experiences at scale.   Twitter: @CogRev_Podcast @eriktorenberg (Erik) @suhail (Suhail) @labenz (Nathan)   Websites: playgroundai.com mixpanel.com  waymark.com 

Today I'm speaking with Suhail Kakar, a Developer Advocate Engineer at Livepeer. You have likely already come across Suhail's work either on Twitter, through his blog, or through his newsletter. Suhail is a content machine, regularly producing Tweets, illustrations, and articles that explain Web3 and empower devs to build the next generation of dapps. During our discussion, Suhail talks about his background and his work at Livepeer, his perspectives on dapps and the Web3 stack, and then we talk about his enthusiasm for different projects, such as Lens Protocol and, of course, The Graph. Show NotesThe GRTiQ Podcast takes listeners inside The Graph (GRT) by interviewing members of The Graph's community and ecosystem.  Please help support this project and build the community by subscribing and leaving a review.Twitter: GRT_iQwww.GRTiQ.com

SPF Podcast Episode 4: twitter haters already, FTX, more confident founders raise more venture capital, Klout was a rocketship, our origin stories, raising at too high valuations, @Suhail founder of Mighty pivots Description: Discussing weekly tech news w/ second time venture founders. No investors. @julien (Breather, Practice) @kevingibbon (Shyp, Airhouse) @berman66 (Nanit, Vowel) @JoeFernandez (Klout, Joymode, newco)

Suhail Rentas – Porqué y cómo invito a la oportunidad.

The number of retail grocery retailers across India in 2022 amounted to about 13 million. Grocery retail account for about 65% of India's overall retailers.And the most common problems faced by these retailers on a financial front up until a few years back were - Accepting digital payments such as UPI or CardsEasy & Quick access to loans for expanding business or in the form of working capital for buying new stock.In 2018, BharatPe was started to cater to these problems faced by every day retailers in India. Since then the company has grown to enable 10 million merchants in 400+ cities, processing US$ 20 bn of annualized TPV in payments.During the peak of Covid, they also joined hands with ICICI Lombard to launch Coronavirus insurance cover for shopkeepers. To enable hands-free checking of transactions they also launched Speaker. To know how digital payments turned out as a big break for them, we've got BharatPe founder Shashvat Nakrani  & CEO Suhail Sameer on our guest seats this time.In this episode we discuss-How they've scaled BharatPe over the past 4 years?Does the age gap between them affect the decision-making at the top level?What do they keep in mind while building or scaling any new product?And much moreNotes - 01:35 - Expectations with BharatPe's current scale03:17 - Joining a Rocket Ship as a CEO05:10 - Changes in culture and customer offerings in the last 2 years12:19 - Very less attachment to a particular role amongst founders & CEOs16:30 - Dealing and coming out the challenging times at BharatPe18:17 - Zoho Sponsored – Prashant Ganti on Where do founders struggle with Payroll and how can they fix it?19:33 - Helping the team innovate faster and plan Go-To-Market strategy25:37 - Strengths & Weakness of Shashvat29:33 - Strengths & Weakness of Suhail31:03 - Handling the firing decisions35:17 - What are the things they bond over? 36:38 - Processes v/s Hustle in 0 to 1 and 1 to 10 journey40:49 - Secret recipe behind success at 0 to 1 on a product-level44:02 - Idea behind building distribution network47:33 - Suhail's top priorities while joining BharatPe49:29 - Biases and things Suhail had to unlearn55:21 - Listening to Younger v/s Older Team members while decision making 58:39 - Next Chapter of BharatPe01:01:00 - What is being IPO-ready? 01:07:39 - Things which they could have explored outside of Fintech?

About MartinMartin Casado is a general partner at the venture capital firm Andreessen Horowitz where he focuses on enterprise investing. He was previously the cofounder and chief technology officer at Nicira, which was acquired by VMware for $1.26 billion in 2012. While at VMware, Martin was a fellow, and served as senior vice president and general manager of the Networking and Security Business Unit, which he scaled to a $600 million run-rate business by the time he left VMware in 2016.Martin started his career at Lawrence Livermore National Laboratory where he worked on large-scale simulations for the Department of Defense before moving over to work with the intelligence community on networking and cybersecurity. These experiences inspired his work at Stanford where he created the software-defined networking (SDN) movement, leading to a new paradigm of network virtualization. While at Stanford he also cofounded Illuminics Systems, an IP analytics company, which was acquired by Quova Inc. in 2006.For his work, Martin was awarded both the ACM Grace Murray Hopper award and the NEC C&C award, and he's an inductee of the Lawrence Livermore Lab's Entrepreneur's Hall of Fame. He holds both a PhD and Masters degree in Computer Science from Stanford University.Martin serves on the board of ActionIQ, Ambient.ai, Astranis, dbt Labs, Fivetran, Imply, Isovalent, Kong, Material Security, Netlify, Orbit, Pindrop Security, Preset, RapidAPI, Rasa, Tackle, Tecton, and Yubico.Links: Yet Another Infra Group Discord Server: https://discord.gg/f3xnJzwbeQ “The Cost of Cloud, a Trillion Dollar Paradox” - https://a16z.com/2021/05/27/cost-of-cloud-paradox-market-cap-cloud-lifecycle-scale-growth-repatriation-optimization/ 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 Honeycomb. When production is running slow, it's hard to know where problems originate. Is it your application code, users, or the underlying systems? I've got five bucks on DNS, personally. Why scroll through endless dashboards while dealing with alert floods, going from tool to tool to tool that you employ, guessing at which puzzle pieces matter? Context switching and tool sprawl are slowly killing both your team and your business. You should care more about one of those than the other; which one is up to you. Drop the separate pillars and enter a world of getting one unified understanding of the one thing driving your business: production. With Honeycomb, you guess less and know more. Try it for free at honeycomb.io/screaminginthecloud. Observability: it's more than just hipster monitoring.Corey: This episode is sponsored in part by our friends at Sysdig. Sysdig secures your cloud from source to run. They believe, as do I, that DevOps and security are inextricably linked. If you wanna learn more about how they view this, check out their blog, it's definitely worth the read. To learn more about how they are absolutely getting it right from where I sit, visit Sysdig.com and tell them that I sent you. That's S Y S D I G.com. And my thanks to them for their continued support of this ridiculous nonsense.Corey: Welcome to Screaming in the Cloud. I'm Corey Quinn. I'm joined today by someone who has taken a slightly different approach to being—well, we'll call it cloud skepticism here. Martin Casado is a general partner at Andreessen Horowitz and has been on my radar starting a while back, based upon a piece that he wrote focusing on the costs of cloud and how repatriation is going to grow. You wrote that in conjunction with your colleague, Sarah Wang. Martin, thank you so much for joining me. What got you onto that path?Martin: So, I want to be very clear, just to start with is, I think cloud is the biggest innovation that we've seen in infrastructure, probably ever. It's a core part of the industry. I think it's very important, I think every company's going to be using cloud, so I'm very pro-cloud. I just think the nature of how you use clouds is shifting. And that was the focus.Corey: When you first put out your article in conjunction with your colleague as well, like, I saw it and I have to say that this was the first time I'd really come across any of your work previously. And I have my own biases that I started from, so my opening position on reading it was this is just some jerk who's trying to say something controversial and edgy to get attention. That's my frickin job. Excuse me, sir. And who is this clown?So, I started digging, and what I found really changed my perspective because as mentioned at the start of the show, you are a general partner at Andreessen Horowitz, which means you are a VC. You are definitionally almost the archetype of a VC in that sense. And to me, being a venture capitalist means the most interesting thing about you is that you write a large check consisting of someone else's money. And that's never been particularly interesting.Martin: [laugh].Corey: You kind of cut against that grain and that narrative. You have a master's and a PhD in computer science from Stanford; you started your career at one of the national labs—Laurence Livermore, if memory serves—you wound up starting a business, Nicira, if I'm pronouncing that correctly—Martin: Yeah, yeah, yeah.Corey: That you then sold to VMware in 2012, back at a time when that was a noble outcome, rather than a state of failure because VMware is not exactly what it once was. You ran a $600 million a year business while you were there. Basically, the list of boards that you're on is lengthy enough and notable enough that it sounds almost like you're professionally bored, so I don't—Martin: [laugh].Corey: So, looking at this, it's okay, this is someone who actually knows what he is talking about, not just, “Well, I talked to three people in pitch meetings and I now think I know what is going on in this broader industry.” You pay attention, and you're connected, disturbingly well, to what's going on, to the point where if you see something, it is almost certainly rooted in something that is happening. And it's a big enough market that I don't think any one person can keep their finger on the pulse of everything. So, that's when I started really digging into it, paying attention, and more or less took a lot of what you wrote as there are some theses in here that I want to prove or disprove. And I spent a fair bit of time basically threatening, swindling, and bribing people with infinite cups of coffee in order to start figuring out what is going on.And I am begrudgingly left with no better conclusion than you have a series of points in here that are very challenging to disprove. So, where do you stand today, now that, I guess, the whole rise and fall of the hype around your article on cloud repatriation—which yes, yes, we'll put a link to it in the show notes if people want to go there—but you've talked about this in a lot of different contexts. Having had the conversations that you've had, and I'm sure some very salty arguments with people who have a certain vested interest in you being wrong, do you wind up continuing to stand by the baseline positions that you've laid out, or have they evolved into something more nuanced?Martin: So yeah, I definitely want to point out, so this was work done with Sarah Wang was also at Andreessen Horowitz; she's also a GP. She actually did the majority of the analysis and she's way smarter than I am. [laugh]. And so, I'm just very—feel very lucky to work with her on this. And I want to make sure she gets due credit on this.So, let's talk about the furor. So like, I actually thought that this was kind of interesting and it started a good discussion, but instead, like, [laugh] the amount of, like, response pieces and, like, angry emails I got, and [laugh] like, I mean it just—and I kind of thought to myself, like, “Why are people so upset?” I think there's three reasons. I'm going to go through them very quickly because they're interesting.So, the first one is, like, you're right, like, I'm a VC. I think people see a VC and they're like, oh, lack of credibility, lack of accountability, [laugh], you know, doesn't know what they're doing, broad pattern matcher. And, like, I will say, like, I did not necessarily write this as a VC; I wrote this as somebody that's, like, listen, my PhD is an infrastructure; my company was an infrastructure. It's all data center stuff. I had a $600 million a year data center business that sold infrastructure into data centers. I've worked with all of the above. Like, I've worked with Amazon, I've—Corey: So, you sold three Cisco switches?Martin: [laugh]. That's right.Corey: I remember those days. Those were awesome, but not inexpensive.Martin: [laugh]. That's right. Yeah, so like, you know, I had 15 years. It's kind of a culmination of that experience. So, that was one; I just think that people see VC and they have a reaction.The second one is, I think people still have the first cloud wars fresh in their memories and so they just don't know how to think outside of that. So, a lot of the rebuttals were first cloud war rebuttals. Like, “Well, but internal IT is slow and you can't have the expertise.” But like, they just don't apply to the new world, right? Like, listen, if you're Cloudflare, to say that you can't run, like, a large operation is just silly. If you went to Cloudflare and you're like, “Listen, you can't run your own infrastructure,” like, they'd take out your sucker and pat you on the head. [laugh].Corey: And not for nothing, if you try to run what they're doing on other cloud providers from a pure bandwidth perspective, you don't have a company anymore, regardless of how well funded you are. It's a never-full money pit that just sucks all of the money. And I've talked to a number of very early idea stage companies that aren't really founded yet about trying to do things like CDN-style work or streaming video, and a lot of those questions start off with well, we did some back-of-the-envelope math around AWS data transfer pricing, and if our numbers are right, when we scale, we'll be spending $65,000 on data transfer every minute. What did we get wrong?And it's like, “Oh, yeah, you realize that one thing is per hour not per minute, so slight difference there. But no, you're basically correct. Don't do it.” And yeah, no one pays retail price at that volume, but they're not going to give you a 99.999% discount on these things, so come up with a better plan. Cloudflare's business will not work on AWS, full stop.Martin: Yep, yep. So, I legitimately know, basically, household name public companies that are software companies that anybody listening to this knows the name of these companies, who have product lines who have 0% margins because they're [laugh] basically, like, for every dollar they make, they pay a dollar to Amazon. Like, this is a very real thing, right? And if you go to these companies, these are software infrastructure companies; they've got very talented teams, they know how to build, like, infrastructure. To tell them that like, “Well, you know, you can't build your own infrastructure,” or something is, I mean, it's like telling, like, an expert in the business, they can't do what they do; this is what they do. So, I just think that part of the furor, part of the uproar, was like, I just think people were stuck in this cloud war 1.0 mindset.I think the third thing is, listen, we've got an oligopoly, and they employ a bunch of people, and they've convinced a bunch of people they're right, and it's always hard to change that. And I also think there's just a knee-jerk reaction to these big macro shifts. And it was the same thing we did to software-defined networking. You know, like, my grad school work was trying to change networking to go from hardware to software. I remember giving a talk at Cisco, and I was, like, this kind of like a naive grad student, and they literally yelled at me out of the room. They're like, it'll never work.Corey: They tried to burn you as a witch, as I recall.Martin: [laugh]. And so, your specific question is, like, have our views evolved? But the first one is, I think that this macro downturn really kind of makes the problem more acute. And so, I think the problem is very, very real. And so, I think the question is, “Okay, so what happens?”So, let's say if you're building a new software company, and you have a choice of using, like, one of the Big Three public clouds, but it impacts your margins so much that it depresses your share price, what do you do? And I think that we thought a lot more about what the answers there are. And the ones that I think that we're seeing is, some actually are; companies are building their own infrastructure. Like, very famously MosaicML is building their own infrastructure. Fly.io, -building their own infrastructure.Mighty—you know, Suhail's company—building his own infrastructure. Cloudflare has their own infrastructure. So, I think if you're an infrastructure provider, a very reasonable thing to do is to build your own infrastructure. If you're not a core infrastructure provider, you're not; you can still use somebody's infrastructure that's built at a better cost point.So, for example, if I'm looking at a CDN tier, I'm going to use Fly.io, right? I mean, it's like, it's way cheaper, the multi-region is way better, and so, like, I do think that we're seeing, like, almost verticalized clouds getting built out that address this price point and, like, these new use cases. And I think this is going to start happening more and more now. And we're going to see basically almost the delamination of the cloud into these verticalized clouds.Corey: I think there's also a question of scale, where if you're starting out in the evening tonight, to—I want to build, I don't know Excel as a service or something. Great. You're pretty silly if you're not going to start off with a cloud provider, just because you can get instant access to resources, and if your product catches on, you scale out without having to ever go back and build it as quote-unquote “Enterprise grade,” as opposed to having building it on cheap servers or Raspberry Pis or something floating around. By the time that costs hit a certain point—and what that point is going to depend on your stage of company and lifecycle—you're remiss if you don't at least do an analysis on is this the path we want to continue on for the service that we're offering?And to be clear, the answer to this is almost entirely going to be bounded by the context of your business. I don't believe that companies as a general rule, make ill-reasoned decisions. I think that when we see a decision a company makes, by and large, there's context or constraints that we don't see that inform that. I know, it's fun to dunk on some of the large companies' seemingly inscrutable decisions, but I will say, having had the privilege to talk to an awful lot of execs in an awful lot of places—particularly on this show—I don't find myself encountering a whole lot of people in those roles who I come away with thinking that they're a few fries short of a Happy Meal. They generally are very well reasoned in why they do what they do. It's just a question of where we think the future is going on some level.Martin: Yep. So, I think that's absolutely right. So, to be a little bit more clear on what I think is happening with the cloud, which is I think every company that gets created in tech is going to use the cloud for something, right? They'll use it for development, the website, test, et cetera. And many will have everything in the cloud, right?So, the cloud is here to stay, it's going to continue to grow, it's a very important piece of the ecosystem, it's very important piece of IT. I'm very, very pro cloud; there's a lot of value. But the one area that's under pressure is if your product is SaaS if your product is selling Software as a Service, so then your product is basically infrastructure, now you've got a product cost model that includes the infrastructure itself, right? And if you reduce that, that's going to increase your margin. And so, every company that's doing that should ask the question, like, A, is the Big Three the right one for me?Maybe a verticalized cloud—like for example, whatever Fly or Mosaic or whatever is better because the cost is better. And I know how to, you know, write software and run these things, so I'll use that. They'll make that decision or maybe they'll build their own infrastructure. And I think we're going to see that decision happening more and more, exactly because now software is being offered as a service and they can do that. And I just want to make the point, just because I think it's so important, that the clouds did exactly this to the hardware providers. So, I just want to tell a quick story, just because for me, it's just so interesting. So—Corey: No, please, I was only really paying attention to this market from 2016 or so. There was a lot of the early days that I was using as a customer, but I wasn't paying attention to the overall industry trends. Please, storytime. This is how I learned things. I hang out with smart people and I come away a little bit smarter than when I started.Martin: [laugh]. This is, like, literally my fa—this is why this is one of my favorite topics is what I'm about to tell you, which is, so the clouds have always had this argument, right? The big clouds, three clouds, they're like, “Listen, why would you build your own cloud? Because, like, you don't have the expertise, and it's hard and you don't have economies of scale.” Right?And the answer is you wouldn't unless it impacts your share price, right? If it impacts your share price, then of course you would because it makes economic sense. So, the clouds had that exact same dilemma in 2005, right? So, in 2005, Google and Amazon and Microsoft, they looked at their COGS, they looked like, “Okay, I'm offering a cloud. If I look at the COGS, who am I paying?”And it turns out, there was a bunch of hardware providers that had 30% margins or 70% margins. They're like, “Why am I paying Cisco these big margins? Why am I paying Dell these big margins?” Right? So, they had the exact same dilemma.And all of the arguments that they use now applied then, right? So, the exact same arguments, for example, “AWS, you know nothing about hardware. Why would you build hardware? You don't have the expertise. These guys sell to everybody in the world, you don't have the economies of scale.”So, all of the same arguments applied to them. And yet… and yes because it was part of COGS] that it impacted the share price, they can make the economic argument to actually build hardware teams and build chips. And so, they verticalized, right? And so, it just turns out if the infrastructure becomes parts of COGS, it makes sense to optimize that infrastructure. And I would say, the Big Three's foray into OEMs and hardware is a much, much, much bigger leap than an infrastructure company foraying into building their own infrastructure.Corey: There's a certain startup cost inherent to all these things. And the small version of that we had in every company that we started in a pre-cloud era: renting virtual computers from vendors was a thing, but it was still fraught and challenging and things that we use, then, like, GoGrid no longer exist, for good reason. But the alternative was, “Great, I'm going to start building and seeing if this thing has any traction.” Well, you need to go lease a rack somewhere and buy servers from Dell, and they're going to do the fast expedited option, which means only six short weeks until they show up in the data center and then gets sent away because they weren't expecting to receive them. And you wind up with this entire universe of hell between cross-connects and all the rest.And that's before you can ever get anything in front of customers or users to see what happens. Now, it's a swipe of a credit card away and your evening's experiments round up to 25 cents. That was significant. Having to make these significant tens of thousands of dollars of investment just to launch is no longer true. And I feel like that was a great equalizer in some respects.Martin: Yeah, I think that—Corey: And that cost has been borne by the astonishing level of investment that the cloud providers themselves have made. And that basically means that we don't have to. But it does come at a cost.Martin: I think it's also worth pointing out that it's much easier to stand up your own infrastructure now than it has been in the past, too. And so, I think that there's a gradient here, right? So, if you're building a SaaS app, [laugh] you would be crazy not to use the cloud, you just be absolutely insane, right? Like, what do you know about core infrastructure? You know, what do you know about building a back-end? Like, what do you know about operating these things? Go focus on your SaaS app.Corey: The calluses I used to have from crimping my own Ethernet patch cables in data centers have faded by now. I don't want them to come back. Yeah, we used to know how to do these things. Now, most people in most companies do not have that baseline of experience, for excellent reasons. And I wouldn't wish that on the current generation of engineers, except for the ones I dislike.Martin: However, that is if you're building an application. Almost all of my investments are people that are building infrastructure. [laugh]. They're already doing these hardcore backend things; that's what they do: they sell infrastructure. Would you think, like, someone, like, at Databricks doesn't understand how to run infr—of course it does. I mean, like, or Snowflake or whatever, right?And so, this is a gradient. On the extreme app end, you shouldn't be thinking about infrastructure; just use the cloud. Somewhere in the middle, maybe you start on the cloud, maybe you don't. As you get closer to being a cloud service, of course you're going to build your own infrastructure.Like, for example—listen, I mean, I've been mentioning Fly; I just think it's a great example. I mean, Fly is a next-generation CDN, that you can run compute on, where they build their own infrastructure—it's a great developer experience—and they would just be silly. Like, they couldn't even make the cost model work if they did it on the cloud. So clearly, there's a gradient here, and I just think that you would be remiss and probably negligent if you're selling software not to have this conversation, or at least do the analysis.Corey: This episode is sponsored in part by our friend EnterpriseDB. EnterpriseDB has been powering enterprise applications with PostgreSQL for 15 years. And now EnterpriseDB has you covered wherever you deploy PostgreSQL on-premises, private cloud, and they just announced a fully-managed service on AWS and Azure called BigAnimal, all one word. Don't leave managing your database to your cloud vendor because they're too busy launching another half-dozen managed databases to focus on any one of them that they didn't build themselves. Instead, work with the experts over at EnterpriseDB. They can save you time and money, they can even help you migrate legacy applications—including Oracle—to the cloud. To learn more, try BigAnimal for free. Go to biganimal.com/snark, and tell them Corey sent you.Corey: I think there's also a philosophical shift, where a lot of the customers that I talk to about their AWS bills want to believe something that is often not true. And what they want to believe is that their AWS bill is a function of how many customers they have.Martin: Oh yeah.Corey: In practice, it is much more closely correlated with how many engineers they've hired. And it sounds like a joke, except that it's not. The challenge that you have when you choose to build in a data center is that you have bounds around your growth because there are capacity concerns. You are going to run out of power, cooling, and space to wind up having additional servers installed. In cloud, you have an unbounded growth problem.S3 is infinite storage, and the reason I'm comfortable saying that is that they can add hard drives faster than you can fill them. For all effective purposes, it is infinite amounts of storage. There is no forcing function that forces you to get rid of things. You spin up an instance, the natural state of it in a data center as a virtual machine or a virtual instance, is that it's going to stop working two to three years left on maintain when a raccoon hauls it off into the woods to make a nest or whatever the hell raccoons do. In cloud, you will retire before that instance does is it gets migrated to different underlying hosts, continuing to cost you however many cents per hour every hour until the earth crashes into the sun, or Amazon goes bankrupt.That is the trade-off you're making. There is no forcing function. And it's only money, which is a weird thing to say, but the failure mode of turning something off mistakenly that takes things down, well that's disastrous to your brand and your company. Just leaving it up, well, it's only money. It's never a top-of-mind priority, so it continues to build and continues to build and continues to build until you're really forced to reckon with a much larger problem.It is a form of technical debt, where you've kicked the can down the road until you can no longer kick that can. Then your options are either go ahead and fix it or go back and talk to you folks, and it's time for more money.Martin: Yeah. Or talk to you. [laugh].Corey: There is that.Martin: No seriously, I think everybody should, honestly. I think this is a board-level concern for every compa—I sit on a lot of boards; I see this. And this has organically become a board-level concern. I think it should become a conscious board-level concern of, you know, cloud costs, impact COGS. Any software company has it; it always becomes an issue, and so it should be treated as a first-class problem.And if you're not thinking through your options—and I think by the way, your company is a great option—but if you're not thinking to the options, then you're almost fiduciarily negligent. I think the vast, vast majority of people and vast majority of companies are going to stay on the cloud and just do some basic cost controls and some just basic hygiene and they're fine and, like, this doesn't touch them. But there are a set of companies, particularly those that sell infrastructure, where they may have to get more aggressive. And that ecosystem is now very vibrant, and there's a lot of shifts in it, and I think it's the most exciting place [laugh] in all of IT, like, personally in the industry.Corey: One question I have for you is where do you draw the line around infrastructure companies. I tend to have an evolving view of it myself, where things that are hard and difficult do not become harder with time. It used to require a deep-level engineer with a week to kill to wind up compiling and building a web server. Now, it is evolved and evolved and evolved; it is check a box on a webpage somewhere and you're serving a static website. Managed databases, I used to think, were something that were higher up the stack and not infrastructure. Today, I'd call them pretty clearly infrastructure.Things seem to be continually, I guess, a slipping beneath the waves to borrow an iceberg analogy. And it's only the stuff that you can see that is interesting and differentiated, on some level. I don't know where the industry is going at all, but I continue to think of infrastructure companies as being increasingly broad.Martin: Yeah, yeah, yeah. This is my favorite question. [laugh]. I'm so glad you asked. [laugh].Corey: This was not planned to be clear.Martin: No, no, no. Listen, I am such an infrastructure maximalist. And I've changed my opinion on this so much in the last three years. So, it used to be the case—and infrastructure has a long history of, like, calling the end of infrastructure. Like, every decade has been the end of infrastructure. It's like, you build the primitives and then everything else becomes an app problem, you know?Like, you build a cloud, and then we're done, you know? You build the PC and then we're done. And so, they are even very famous talks where people talk about the end of systems when we've be built everything right then. And I've totally changed my view. So, here's my current view.My current view is, infrastructure is the only, really, differentiation in systems, in all IT, in all software. It's just infrastructure. And the app layer is very important for the business, but the app layer always sits on infrastructure. And the differentiations in app is provided by the infrastructure. And so, the start of value is basically infrastructure.And the design space is so huge, so huge, right? I mean, we've moved from, like, PCs to cloud to data. Now, the cloud is decoupling and moving to the CDN tier. I mean, like, the front-end developers are building stuff in the browser. Like, there's just so much stuff to do that I think the value is always going to accrue to infrastructure.So, in my view, anybody that's improving the app accuracy or performance or correctness with technology is an infrastructure company, right? And the more of that you do, [laugh] the more infrastructure you are. And I think, you know, in 30 years, you and I are going to be old, and we're going to go back on this podcast. We're going to talk and there's going to be a whole bunch of infrastructure companies that are being created that have accrued a lot of value. I'm going to say one more thing, which is so—okay, this is a sneak preview for the people listening to this that nobody else has heard before.So Sarah, and I are back at it again, and—the brilliant Sarah, who did the first piece—and we're doing another study. And the study is if you look at public companies and you look at ones that are app companies versus infrastructure companies, where does the value accrue? And there's way, way more app companies; there's a ton of app companies, but it turns out that infrastructure companies have higher multiples and accrue more value. And that's actually a counter-narrative because people think that the business is the apps, but it just turns out that's where the differentiation is. So, I'm just an infra maximalist. I think you could be an infra person your entire career and it's the place to be. [laugh].Corey: And this is the real value that I see of looking at AWS bills. And our narrative is oh, we come in and we fix the horrifying AWS bill. And the naive pass is, “Oh, you cut the bill and make it lower?” Not always. Our primary focus has been on understanding it because you get a phone-number-looking bill from AWS. Great, you look at it, what's driving the cost? Storage.Okay, great. That doesn't mean anything to the company. They want to know what teams are doing this. What's it going to cost for them to add another thousand monthly active users? What is the increase in cost? How do they wind up identifying their bottlenecks? How do they track and assign portions of their COGS to different aspects of their service? How do they trace the flow of capital for their organization as they're serving their customers?And understanding the bill and knowing what to optimize and what not to becomes increasingly strategic business concern.Martin: Yeah.Corey: That's the fun part. That's the stuff I don't see that software has a good way of answering, just because there's no way to use an API to gain that kind of business context. When I started this place, I thought I was going to be building software. It turns out, there's so many conversations that have to happen as a part of this that cannot be replicated by software. I mean, honestly, my biggest competitor for all this stuff is Microsoft Excel because people want to try and do it themselves internally. And sometimes they do a great job, sometimes they don't, but it's understanding their drivers behind their cost. And I think that is what was often getting lost because the cloud obscures an awful lot of that.Martin: Yeah. I think even just summarize this whole thing pretty quickly, which is, like, I do think that organically, like, cloud cost has become a board-level issue. And I think that the shift that founders and execs should make is to just, like, treat it like a first-class problem upfront. So, what does that mean? Minimally, it means understanding how these things break down—A, to your point—B, there's a number of tools that actually help with onboarding of this stuff. Like, Vantage is one that I'm a fan of; it just provides some visibility.And then the third one is if you're selling Software as a Service, that's your core product or software, and particularly it's a infrastructure, if you don't actually do the analysis on, like, how this impacts your share price for different cloud costs, if you don't do that analysis, I would say your fiduciarily negligent, just because the impact would be so high, especially in this market. And so, I think, listen, these three things are pretty straightforward and I think anybody listening to this should consider them if you're running a company, or you're an executive company.Corey: Let's be clear, this is also the kind of problem that when you're sitting there trying to come up with an idea for a business that you can put on slide decks and then present to people like you, these sounds like the paradise of problems to have. Like, “Wow, we're successful and our business is so complex and scaled out that we don't know where exactly a lot of these cost drivers are coming from.” It's, “Yeah, that sounds amazing.” Like, I remember those early days, back when all I was able to do and spend time on and energy on was just down to the idea of, ohh, I'm getting business cards. That's awesome. That means I've made it as a business person.Spoiler: it did not. Having an aggressive Twitter presence, that's what made me as a business person. But then there's this next step and this next step and this next step and this next step, and eventually, you look around and realize just how overwrought everything you've built is and how untangling it just becomes a bit of a challenge and a hell of a mess. Now, the good part is at that point of success, you can bring people in, like, a CFO and a finance team who can do some deep-level analysis to help identify what COGS is—or in some cases, have some founders, explain what COGS is to you—and understand those structures and how you think about that. But it always feels like it's a trailing problem, not an early problem that people focus on.Martin: I'll tell you the reason. The reason is because this is a very new phenomenon that it's part of COGS. It's literally five years new. And so, we're just catching up. Even now, this discussion isn't what it was when we first wrote the post.Like, now people are pretty educated on, like, “Oh yeah, like, this is really an issue. Oh, yeah. It contributes to COGS. Oh, yeah. Like, our stock price gets hit.” Like, it's so funny to watch, like, the industry mature in real-time. And I think, like, going forward, it's just going to be obvious that this is a board-level issue; it's going to be obvious this is, like, a first-class consideration. But I agree with you. It's like, listen, like, the industry wasn't ready for it because we didn't have public companies. A lot of public companies, like, this is a real issue. I mean really we're talking about the last five, seven years.Corey: It really is neat, just in real time watching how you come up with something that sounds borderline heretical, and in a relatively short period of time, becomes accepted as a large-scale problem, and now it's now it is fallen off of the hype train into, “Yeah, this is something to be aware of.” And people's attention spans have already jumped to the next level and next generation of problem. It feels like this used to take way longer for these cycles, and now everything is so rapid that I almost worry that between the time we're recording this and the time that it publishes in a few weeks, what is going to have happened that makes this conversation irrelevant? I didn't used to have to think like that. Now, I do.Martin: Yeah, yeah, yeah, for sure. Well, just a couple of things. I want to talk about, like, one of the reasons that accelerated this, and then when I think is going forward. So, one of the reasons this was accelerated was just the macro downturn. Like, when we wrote the post, you could make the argument that nobody cares about margins because it's all about growth, right?And so, like—and even then, it still saved a bunch of money, but like, a lot of people were like, “Listen, the only thing that matters is growth.” Now, that's absolutely not the case if you look at public market valuations. I mean, people really care about free cash flow, they really care about profitability, and they really care about margins. And so, it's just really forced the issue. And it also, like, you know, made kind of what we were saying very, very clear.I would say, you know, as far as shifts that are going, I think one of the biggest shifts is for every back-end developer, there's, like, a hundred front-end developers. It's just crazy. And those front-end developers—Corey: A third of a DevOps engineer.Martin: [laugh]. True. I think those front-end developers are getting, like, better tools to build complete apps, right? Like, totally complete apps, right? Like they've got great JavaScript frameworks that coming out all the time.And so, you could argue that actually a secular technology change—which is that developers are now rebuilding apps as kind of front-end applications—is going to pull compute away from the clouds anyways, right? Like if instead of, like, the app being some back-end thing running in AWS, but instead is a front-end thing, you know, running in a browser at the CDN tier, while you're still using the Big Three clouds, it's being used in a very different way. And we may have to think about it again differently. Now, this, again, is a five-year going forward problem, but I do feel like there are big shifts that are even changing the way that we currently think about cloud now. And we'll see.Corey: And if those providers don't keep up and start matching those paradigms, there's going to be an intermediary shim layer of companies that wind up converting their resources and infrastructure into things that suit this new dynamic, and effectively, they're going to become the next version of, I don't know, Level 3, one of those big underlying infrastructure companies that most people have never heard of or have to think about because they're not doing anything that's perceived as interesting.Martin: Yeah, I agree. And I honestly think this is why Cloudflare and Cloudflare work is very interesting. This is why Fly is very interesting. It's a set of companies that are, like, “Hey, listen, like, workloads are moving to the front-end and, you know, you need compute closer to the user and multi-region is really important, et cetera.” So, even as we speak, we're seeing kind of shifts to the way the cloud is moving, which is just exciting. This is why it's, like, listen, infrastructure is everything. And, like, you and I like if we live to be 200, we can do [laugh] a great infrastructure work every year.Corey: I'm terrified, on some level, that I'll still be doing the exact same type of thing in 20 years.Martin: [laugh].Corey: I like solving different problems as we go. I really want to thank you for spending so much time talking to me today. If people want to learn more about what you're up to, slash beg you for other people's money or whatnot, where's the best place for them to find you?Martin: You know, we've got this amazing infrastructure Discord channel. [laugh].Corey: Really? I did not know that.Martin: I love it. It's, like, the best. Yeah, my favorite thing to do is drink coffee and talk about infrastructure. And like, I posted this on Twitter and we've got, like, 600 people. And it's just the best thing. So, that's honestly the best way to have these discussions. Maybe can you put, like, the link in, like, the show notes?Corey: Oh, absolutely. It is already there in the show notes. Check the show notes. Feel free to join the infrastructure Discord. I will be there waiting for you.Martin: Yeah, yeah, yeah. That'll be fantastic.Corey: Thank you so much for being so generous with your time. I appreciate it.Martin: This was great. Likewise, Corey. You're always a class act and I really appreciate that about you.Corey: I do my best. Martin Casado, general partner at Andreessen Horowitz. I'm Cloud Economist Corey Quinn, and this is Screaming in the Cloud. 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 comment telling me that I got it completely wrong and what check you wrote makes you the most interesting.Announcer: The content here is for informational purposes only and should not be taken as legal, business, tax, or investment advice, or be used to evaluate any investment or security and is not directed at any investors or potential investors in any a16z fund. For more details, please see a16z.com/disclosures.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.

A decision has been made and the Cleveland Browns Deshaun Watson has been suspended 11 games for the 2022 NFL season. In this episode of The  Fantasy Football Top 5 in the re.Intro Podcast, Suhail will break down the impact on the Cleveland Browns offense including Nick Chubb, Kareem Hunt, Amari Cooper and Deshaun Watson. Where should you begin drafting these guys in your 2022 fantasy football drafts? Are any of them must have players now?#2022fantasyfootball  #fantasyfootball  #fantasyfootballadvice  #fantasyfootball2022  #fantasyfootballnews  #nflnews  #nfl  #nflfootball  #fantasysportsIntro to re.Intro

A reading that Theresa describes as "refreshing" because of how incredible the personalities and love shown through on this unique reading between husband and wife, Suhail and Paul. Both of their departed mothers had met together in the afterlife over a bond so strong they wouldn't leave each others side the whole time! A must listen to hear how their moms want to experience the good old days all over again with their children. Our GDPR privacy policy was updated on August 8, 2022. Visit acast.com/privacy for more information.

Top 5:1.      Running Backs2.      Wide Receivers3.      Quarterbacks4.      Tight Ends5.      SleepersThe 2022 Fantasy Football Season is getting close, but it's never too early to start looking at 2022 Fantasy Football rankings! In this episode of The Fantasy Football Top 5 podcast Suhail will give fantasy football advice and break down a few players that are a sure bet to finish top 5 at each position Who will be the top 5 must have players at quarterback, wide receiver, running back and tight end? You need to be sure to have these guys marked during your fantasy football draft! Be sure to hit that Like button and let us know how you have your fantasy football rankings right now! Leave a comment down below for the next topic you would like me to discuss#2022fantasyfootball #fantasyfootball #fantasyfootballadvice #fantasyfootball2022 #fantasyfootballnews #nflnews #nfl #nflfootball #fantasysports Check Out Our Audio Podcast: Link to iTunes: https://podcasts.apple.com/podcast/id1622859294 Link To Spotify: https://open.spotify.com/show/0vwgoqYomoW6EqG1NWuM1J?si=d2c7bbb498234a92Intro to re.Intro

Palestinian writer Suhail Matar speaks to managing editor Emily Everett about his story “Granada,” translated by Amika Fendi. The story appears in The Common's new spring issue, in a special portfolio of Arabic fiction from Palestine. Suhail talks about the inspiration and process behind the story, which explores the complex ways in which Palestinians connect when they meet and interact abroad. Suhail also discusses the difficulties of translation, the history and modern realities of Palestinians living within Israel's current borders, and his PhD work exploring how the brain processes and reacts to language. Suhail Matar was born in Haifa in 1987, where he also grew up. He is finishing a PhD in neurocognitive sciences at New York University. The story “Granada” belongs to his short story collection North of Andalusia, West of the Homeland, which was jointly awarded the Al Qattan Foundation's 2012 Young Writer of the Year Award. Read Suhail's story in The Common at thecommononline.org/granada. Learn more about Suhail at suhailmatar.com or follow him on Twitter at @SuhailMatar_. The Common is a print and online literary magazine publishing stories, essays, and poems that deepen our collective sense of place. On our podcast and in our pages, The Common features established and emerging writers from around the world. Read more and subscribe to the magazine at thecommononline.org, and follow us on Twitter @CommonMag. Emily Everett is managing editor of the magazine and host of the podcast. Her debut novel is forthcoming from Putnam Books. Her stories appear in the Kenyon Review, Electric Literature, Tin House Online, and Mississippi Review. She is a 2022 Massachusetts Cultural Council Fellow. Say hello on Twitter @Public_Emily. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/new-books-network

Welcome to another episode of The Action and Ambition Podcast! Joining us today is Dr. Suhail, an entrepreneur, healthcare investor, and philanthropist whose mission is to provide cost-effective, quality healthcare training programs in areas that are underserved and in need of quality care. Dr. Suhail is the CEO of Metropolitan Behavioral Associates (MBA) of Chicago, a Psychiatric Group of highly qualified psychiatry physicians with 30+ years of experience. The physicians are committed to providing quality care to all of the Chicago metropolitan communities. Tune in to learn more!

Join us for discussion on the intersection between Muslim Dating and Porn. FOLLOW US: ►INSTAGRAM: http://bit.ly/PM_INSTA ►FACEBOOK: http://bit.ly/PM_FACEB ►ITUNES: http://bit.ly/PM_ITUNES

Hiiii, we are Shri & Suhail and we have a podcast called re.Intro. it's a podcast were we share stories and talk about different subject related to society, culture, mainstream and we will bring in guest to share and talk about each sides of the argument. We say everything we know about that subject and they correct us or we correct eachother and or share each's opinionsJoin in, listen to the podcast you might laugh and learn something

As the international community watches in shock as the Taliban takes control of Afghanistan at lightening speed and people frantically try escape the country, we take a look at what this means for the country and their political future. First, Taliban Spokesperson Suhail Shaheen joins Christiane Amanpour to answer questions about what will happen to the Afghan people now they're in control. Then former Afghan lawmaker Fawzia Koofi speaks from the ground about the fear spreading amongst ordinary citizens and the reality that awaits women and girls. While former Defense Secretary Chuck Hagel says he supports the decision to withdraw, he explains that the White House underestimated the Afghan government's weakness. And British MP Tom Tugendhat, an Afghan veteran, argues the sudden withdrawal throws fuel on the fire of Afghanistan's 40-year war. To learn more about how CNN protects listener privacy, visit cnn.com/privacy