Podcasts about dominant

Jacqueline Smith and Ryan Greigg delve into the power of action in achieving success, as inspired by Chris Heller's book "Dominant Thoughts." They discuss the importance of discipline, mindset, and the often overlooked role of energy-generating habits from their 15 Point Plan. Through stories of resilience and persistence, they emphasize the necessity of stepping out of comfort zones and combining intention with tangible effort. Highlighting insights like the law of attraction and the importance of showing up with presence, they invite listeners to rethink personal and professional growth strategies. ---------- Connect with the 15 Point Plan: 15 Point Plan: https://WinMakeGive.com/15-point-plan/ Win Make Give Facebook group: https://www.facebook.com/groups/WinMakeGive Learn more about the co-hosts: Jacqueline Smith: https://www.instagram.com/jacquelinerae_smith/ Ryan Greigg: https://www.instagram.com/ryanparkgreigg/ Book one of our co-hosts for your next event: https://WinMakeGive.com/speakers/ Part of the Win Make Give Podcast Network

“I'd rather do a race than a time trial as my first marathon. I went to New York during my off season last year just to see how it was. I got to feel the atmosphere and I was like: yeah, I want to do this.”My guest for today's episode is Andreas Almgren, who is the newly-minted European 10,000m champion and soon-to-be a first-time marathoner. On November 1st he will run the New York City Marathon for his debut at the distance.He's had a great past 12 months with four European records in that span: the 10K road in Valencia in January at 26:45 (puts him sixth on the world all-time list); the half marathon last October in 58:41 (the first European under 59 minutes); World Championships bronze in Tokyo last September, where he finished 0.25 seconds off gold; and a 5000m European record of 12:44 last outdoor season. He's one of the best in the world right now.Andreas is 31. He grew up in Sweden playing wing-back at AIK, one of the biggest clubs in the Nordics, and only turned to running full-time after recurring injuries ended that path at 18. He won World U20 bronze in the 800m in Eugene in 2014 and looked like Sweden's next great middle-distance runner — then spent four years with stress fractures, a broken navicular, a sacral stress fracture, missing more than he raced. In 2019, sitting on a stationary bike during rehab for that sacral fracture, he watched his friend Kalle Berglund make a world championship 1500m final using double threshold training. He copied it. He has been going up in distance ever since, and every time he steps up, he runs faster. He has been working toward the marathon for a while now.We dive into why he picked New York over Valencia, how his double threshold system has evolved over the last seven years, what it took to stay healthy the past two years, the training he is doing for the marathon right now and much more.____________SUPPORT OUR SPONSORSVELOUS: VELOUS makes recovery footwear designed to help runners bounce back faster between sessions. Their sandals feature Tri-Motion™ Technology: a technical three-density foam system and contoured footbed engineered to cushion impact, support your arches, and help your toes stretch and relax on every step. They keep your feet and legs properly aligned after you put in all of those weekly miles. Run. Recover. Repeat. with VELOUS! ⁠⁠⁠⁠⁠⁠⁠⁠Get 20% off your VELOUS order with code CITIUSMAG20 at checkout including FREE Shipping!⁠⁠⁠⁠⁠⁠⁠⁠OLIPOP: OLIPOP's Citrus Rush packs apple, lemon, lime, and orange juices with 60mg of green tea caffeine for a bold, refreshing blast of flavor ready to fuel your next adventure. If you haven't had tried Olipop yet, grab a can and see what the hype is all about!⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠Head to DrinkOlipop.com and use code CITIUS25 at checkout to get 25% off your orders.⁠⁠

David Jones is joined by Ian Wright, Gary Neville and Jamie Carragher as they discuss Arsenal's dominant 3-0 win over newly promoted Coventry City.•You can watch the Premier League action live on Sky Sports. If you're not already a Sky customer, you can stream Sky Sports on your terms with a NOW membership. Sign up to NOW here: www.nowtv.com/membership/watch-sky-sports?DCMP=ilc_skysports_podcastlink•Listen to every episode of the Sky Sports Premier League Podcast here: www.skysports.com/podcasts/36578/11933957/sky-sports-premier-league-podcast-post-match-analysis-from-super-sunday-mnf-and-more•You can listen to the Sky Sports Premier League Podcast on your smart speaker by asking it to "play Sky Sports Premier League Podcast".•For all the latest Premier League news, head to www.skysports.com/premier-league•For advertising opportunities email: skysportspodcasts@sky.uk

There is one show where insiders share their secrets in this city. One person that they trust and respect. Opinion, reaction and the highest level of informed sports talk in Montreal. Melnick in the Afternoon, with Mitch Melnick.

Sam Short had a historic summer that saw him break numerous barriers and top the podium nearly every time he got in the pool. At the Commonwealth Games in Glasgow, Short swept the 400-800-1500 freestyles and led off Australia's winning 4x200 free relay. Two weeks later, at the Pan Pacific Championships, he swept the same three events, breaking Ian Thorpe's 400 free meet record from 1999 and Grant Hackett's Australian record in the 1500 from 2001.  Today, Short sits down with SwimSwam to reflect on his remarkable consistency throughout the season and dissect his best races. We also speak about Johannes Liebmann's newly minted 14:26 world record in the 1500 and which world record Short would break if he could pick one. 

Ryan ran his mouth and never got to Practice Thirteen — so Sal fixes it. Javon Hargrave returns from P U P and looks like the best lineman on the grass, welcoming a rookie to the N F L one bull rush at a time. Lukas Van Ness wrecks shop coming off a shoulder. Rookie corner Brandon Cisse hasn't left the field since Day Four. Jordan Love threads back-shoulder dimes when the pocket holds — and LaFleur lets the O-line have it when it doesn't. Plus Xavier McKinney's revenge pick, Trey Smack's push wide right, and the play of the day from the second unit. Next stop: Denver. Subscribe, review, and share with the biggest Packers knucklehead you know.

Ryan ran his mouth and never got to Practice Thirteen — so Sal fixes it. Javon Hargrave returns from P U P and looks like the best lineman on the grass, welcoming a rookie to the N F L one bull rush at a time. Lukas Van Ness wrecks shop coming off a shoulder. Rookie corner Brandon Cisse hasn't left the field since Day Four. Jordan Love threads back-shoulder dimes when the pocket holds — and LaFleur lets the O-line have it when it doesn't. Plus Xavier McKinney's revenge pick, Trey Smack's push wide right, and the play of the day from the second unit. Next stop: Denver. Subscribe, review, and share with the biggest Packers knucklehead you know.

Bomani Jones is joined by Charles McDonald to kick off a historical retrospective series looking back at Colin Kaepernick, a decade after his initial protest. In this episode, Bo and Charles refocus the conversation on a frequently forgotten element: just how good of a football player Kaepernick truly was. They trace his trajectory from his breakout college days at Nevada running the pistol offense to being drafted by the San Francisco 49ers.123The duo breaks down Jim Harbaugh's high-stakes mid-season decision to replace Alex Smith with Kaepernick, a move that instantly raised the team's ceiling and altered the strategic landscape of the NFL. They relive the historic, record-setting playoff game against the Green Bay Packers and explore the widespread proliferation of the zone read option across the league. Bo and Charles also analyze the subsequent challenges, front-office tension, coaching changes, and roster downgrades that defined the later years of his career. Ultimately, they evaluate his final seasons under Chip Kelly, his standing as a clear starting-caliber signal-caller, and his lasting legacy as a historically significant figure in modern football history . . . Subscribe to Supercast for Ad-Free Episodes: https://righttime.supercast.com/ Buy 'The Right Time' merch: http://therighttimebomani.com/ Subscribe to The Right Time with Bomani Jones on Spotify, Apple or wherever you get your podcasts and follow the show on Instagram, Twitter, and Tik Tok for all the best moments from the show. Download Full Podcast Here: Spotify: https://open.spotify.com/show/6N7fDvgNz2EPDIOm49aj7M?si=FCb5EzTyTYuIy9-fWs4rQA&nd=1&utm_source=hoobe&utm_medium=social Apple: https://podcasts.apple.com/us/podcast/the-right-time-with-bomani-jones/id982639043?utm_source=hoobe&utm_medium=social Follow The Right Time with Bomani Jones on Social Media: http://lnk.to/therighttime Learn more about your ad choices. Visit megaphone.fm/adchoices

The Arizona Diamondbacks responded to a deflating series loss against the Colorado Rockies by winning their set over the Atlanta Braves. Alex Weiner and Dave Burns break down what stood out, including Brandon Pfaadt's continued dominance. What will Justin Martinez and Jordan Lawlar returning look like, is Nolan Arenado OK and what is the plan for Zac Gallen? 

Australia Bangladesh Daily, 1st Test, Darwin Day 2: The show goes on. Bangladesh winning three sessions in a row in Australia was big news, but now they've gone to make it six, or at leave five and a tie. Australia are not out of this match yet, but a ruthlessly organised and professional performance from the tourists is far beyond what we expected. It's been a genuine thrill to watch this proper style Test match unfold. Bharat Sundaresan joins Geoff. Could you support the show? You can send us a Nerd Pledge or become a member at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠patreon.com/thefinalword⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Maurice Blackburn is Australia's leading social justice law firm. Contact them for help: ⁠mauriceblackburn.com.au⁠ Morie Candles have an extra 5% off any existing promotion: click ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠morie.com.au⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠/discount/TFW5⁠⁠⁠⁠⁠ Stop snoring with 10% off a Zeus device: code TFW2026 at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠zeussleeps.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Get 15% off Step One clothes at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠uk.stepone.life/discount/TFW148⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Get 10% off lovely ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Duncan Fearnley ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠bats and kit with code TFW10 ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Get your big NordVPN discount: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠nordvpn.com/tfw⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ or 10% off BIG Boots UK boots and socks at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠bigboots.co.uk/?ref=thefinalword⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Find more at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠finalwordcricket.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Title track by ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Urthboy⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Learn more about your ad choices. Visit podcastchoices.com/adchoices

Big K Hour 04: Hear from Joe Block following Braxton Ashcraft's dominant complete game! full 1592 Fri, 14 Aug 2026 14:52:10 +0000 6vYSK3MVlAs8eSf5DJ0NhZlicPqdDOWP news The Big K Morning Show news Big K Hour 04: Hear from Joe Block following Braxton Ashcraft's dominant complete game! The Big K Morning Show 2024 © 2021 Audacy, Inc. News https:/

In our latest radio round up, Matt and Oli are joined by Tom Gayle and Matt Yates to talk through all the action on day 4 at the Euros. They discuss the men's 800m final, the women's 800m semi-finals, and much more. Enjoy! Check out https://thesundayplodcast.pages.dev/ for live Euros results.Presented by SportsShoes.com

Will Aerodrome become the definitive onchain spot exchange? This week, we're joined by Dromos Labs CEO, Alexander Cutler, to unpack MetaDEX03, Aerodrome's multi-chain expansion, and the model Alex believes can win across Ethereum and beyond. We discuss MEV capture, tokenized RWAs and FX, LP economics, and why maximum value redistribution could be crypto's strongest competitive moat. Enjoy! TIMESTAMPS: 00:00 Intro 00:45 MetaDEX 3 Upgrade 06:22 Why Arc Is Different 12:49 Aerodrome Takes On Ethereum 21:11 The Case For Full Redistribution 27:39 Capturing MEV For Liquidity Providers 34:11 Tokenized Assets Moving Onchain 39:23 AMMs Vs Prop Liquidity 46:06 What The CLARITY Act Changes 51:11 Why Token Transparency Matters 59:38 Why The Bear Market Misleads FOLLOW THE GUEST › Alex – https://x.com/wagmiAlexander › Dromos – https://x.com/DromosLabs › Aerodrome – https://x.com/AerodromeFi FOLLOW THE SHOW › 0xResearch – https://x.com/0xResearch › Luke – https://x.com/0xMether › Telegram – https://t.me/+UFFz4z3qyrhhMDYx › Blockworks – https://x.com/Blockworks Check out Blockworks Research today! Research, data, governance, tokenomics, and models – all in one place Blockworks Research: https://www.blockworksresearch.com/ Free Daily Newsletter: https://blockworks.co/newsletter EVENTS › Join us at Digital Asset Summit 2026 Asia October 7th & Digital Asset 2026 London November 10-11th https://blockworks.com/events DISCLAIMER Nothing said on 0xResearch is a recommendation to buy or sell securities or tokens. This podcast is for informational purposes only. Any views expressed are opinions, not financial advice. Hosts and guests may hold positions in the companies, funds, or projects discussed.

Willy, Adam and Dmase continue to talk more about college football but they do a recap and talk about how dominant the SEC was at a point in time and more college football talk. Then Ted Nguyen Joins to talk about how the Tennessee Titans did at practice today with the niners and more about Cam Ward. DVD reacts to what Ted had to say about the Titans.

The All Blacks have blitzed the Sharks 54-nil at a soaked Durban to go two wins from two matches on their rugby tour of South Africa. New Zealand ran in eight tries, six of which came in the second half. Former All Black Sir John Kirwan believes the side is making progress in preparing for how to shut down the Springboks in the first test on Sunday week. He told Mike Hosking they're breaking down how the South Africans play and the counters are starting to take shape – a better kicking game, kicking behind them, and trying to break down the closing of the gate defence. Kirwan says they're building in the right direction. LISTEN ABOVE See omnystudio.com/listener for privacy information.

Join Matt Biggar, Ph.D., for a lively discussion of his new book, Connected to Place: Regenerating Nature, Community, and Local Economies Through Systems Change, followed by the introduction of Transforming Our Region, a new Member-led Forum at Commonwealth Club World Affairs. This new forum will apply the systems change approach featured in Connected to Place to the Bay Area through expert presentations and interactive activities.  Biggar discusses place-based systems change as a real-world solution to our growing environmental and social challenges. He says at the core of accelerating climate change and biodiversity loss, rising economic inequality, and growing social division lies a deeper crisis of disconnectedness. Dominant economic forces continually push us away from nature, community and each other. Place-based systems offer an alternative model and are gaining traction in places around the world, both urban and rural.  In Connected to Place, Biggar presents a vision that reorients people's daily lives around their neighborhoods, cities and regions. Through place-based living, we can create lasting, regenerative change that addresses our biggest problems while boosting the quality of everyday life.  Most important, Biggar shows us how we can get there with a practical guide to systems change that draws on real-world examples from his research and practice. By reframing our approach to social progress, he outlines the way toward rebuilding connection with nature and local community and revitalizing local and regional economies. Join us as Biggar shares how this is happening and how you can be a part of it here in the Bay Area. About the Speaker Matt Biggar, Ph.D., is a place-based strategy consultant, systems thinker, speaker, writer and university lecturer. He is the principal and founder of Connected to Place, a strategy consulting firm that supports place-based collaboratives, nonprofits, government agencies, and schools with facilitation, strategic planning, and community engagement. Biggar earned his Ph.D. from Stanford University, where his research involved behavioral science, sustainability, transportation and collective impact. He is the author of Connected to Place: Regenerating Nature, Community, and Local Economies through Systems Change (Cornell University Press, 2025) and several published articles in academic journals, the Stanford Social Innovation Review, and other outlets. A Transforming Our Region Member-led Forum program. Forums at the Club are organized and run by volunteer programmers who are members of The Commonwealth Club, and they cover a diverse range of topics. Learn more about our Forums. Organizer: Anne Smith & Matt Biggar  Learn more about your ad choices. Visit megaphone.fm/adchoices

Don't you have someone edit your first speech at your new job...we recap our Greg Oden chat from Thursday...great game to start the NFL season...what was the greatest regular season game you can remember in any sport

slave,A power exchange can be playful, but it can also be a serious practice with rules, rituals, and real follow-through. I, Chastity Queen firmly lay out what devotion looks like when service is the point: preparation, presentation, and consistent obedience. From specific wardrobe tasks to expectations around gifting and tribute, the message is clear: if you want attention, you earn it through action.I also unpack the deeper “why” behind submission. What does it mean to be noticed by a dominant/Me, to make someone else the priority, and to build identity through daily rituals? You'll hear a strong framework for service submission and dominance and submission dynamics, including the idea that boundaries are pushed through discipline and repetition. Chastity and denial show up as core themes, framed as a method of control, focus, and commitment rather than a casual experiment.The episode closes with community and momentum: how to connect, where to share photos, what events are being planned through the Crown and Cage Society, and how listeners can support the show's growth. If you're interested in BDSM mindset, chastity kink culture, and the structure behind long-term power exchange, there's plenty here to think about, whether you're experienced or just learning the language.Subscribe for more, share the episode with someone who's curious, and leave a review to help more listeners find the show. What part of service do you find easiest, and what part challenges you most?Listen and learn,Chastity IS freedom!Chastity QueenTry to connect with your local BDSM community. Fetlife is a great way to see others in similar FLR and chastity lifestyles. You can check out Mine in Fetlife at Chastity-Queen. It's a free to join. Hugs, Chastity Queen Locked In Lust 15% OFF:CHASTITYQUEEN Use Discount Code:CHASTITYQUEEN for 15% OFF ANYTHING at www.lockedinlust.com THRONE WISH LISTBuy Me something anonymously or send Me a note telling Me who you are and I will thank you. Disclaimer: This post contains affiliate links. If you make a purchase, I may receive a commission at no extra cost to you.Support the showSUPPORT ME in 2 ways! XOXO1: https://paypal.me/TiffanyTheQueen?country.x=CA&locale.x=en_USOR2: https://www.buzzsprout.com/1992649/supportCHASTITY IS FREEDOMI LOVE YOU 

Send us Fan MailWe rank the most dominant WNBA team rosters ever by using rings, Finals results, playoff exits, missed playoffs, and regular-season win percentage. We argue through the toughest comparisons, from the Aces' active run to the Lynx and Comets setting the historical standard.• Ranking criteria for dominance: titles, Finals losses, playoff losses, missed playoffs, win percentage• No. 7 case for the 2007 to 2009 Phoenix Mercury and the missed playoffs penalty• No. 6 case for the 2018 to 2020 Seattle Storm and why consistency beats a gap year• No. 5 case for the 2001 to 2003 LA Sparks and valuing deeper playoff runs• No. 4 case for the 2003 to 2008 Detroit Shock and how three rings changes everything• No. 3 case for the 2020 to present Las Vegas Aces and what could move them up• No. 2 case for the 2011 to 2017 Minnesota Lynx with four titles and repeated Finals trips• No. 1 case for the 1997 to 2000 Houston Comets with four straight titles and elite win rates• Future contenders like the Liberty and current Lynx and what they would need to qualifyPlease make sure to hit that like and subscribe button. Comment, tell anyone who's anyone about the show.Support the showhttps://linktr.ee/GetABucketShow for more content!!!

Ken and Lima examine the controversial decision-making in the Guardians' recent loss, specifically focusing on Stephen Vogt's ejection and a questionable bunt. They pivot to Browns training camp to debate whether Deshaun Watson's impressive practice session secures his starting spot over Shedeur Sanders. The segment wraps up with a deep dive into Jared Verse's impact on team culture compared to the high-level stats provided by Myles Garrett. 02:33 - Guardians Loss Breakdown 06:00 - Hotel Bar Game Struggles 13:04 - Vogt Ejection Analysis 21:14 - Watson's Impressive Camp Day 26:37 - Quarterback Competition Debate 34:58 - Jared Verse Leadership Impact

Kevin went on vacation for this episode and left the Chief to edit, so apologies in advance if this sounds like garbage. Please direct all complaints to @cincyle on X, the everything app it's all happening on X.  It's a Grayson & Chief episode of the PostCast. Since the FC is winning, we don't really fight that much -- sorry to disappoint the sickos. FC Cincinnati star goalkeeper and all around good guy Evan Louro joins the show to talk about the FC's massive 3-1 win over Pachuca in the League's Cup. We also break the match down, shout out the stars, and look ahead to Friday's game against Pumas   Timestamps: (21:15) - I picked this number at random so we could have a first segment time stamp and I'm betting we were spitting fire here. (41:13) - Click here to skip ahead to the Evan Louro interview and hear his name actually pronounced correctly (1:12:29) - Pumas talk.   Links:  Looking for an MLS podcast? Check out The World's GAM Visit our friends at Streetside Brewery E&L Roofing has all your Gutter, siding, and roofing needs covered!  Check out The Post at www.thepostcincy.com Music by Jim Trace and the Makers Join the Discord Server and jump into the conversation Follow us on BlueSky, Twitter,  Facebook, Instagram, and YouTube Support us on Patreon https://www.patreon.com/ThePostCincy

Send us Fan MailI rank the most dominant NBA team rosters since 1968, using the 82-game season as the line that keeps the eras comparable. I walk from No. 10 to No. 1 and explain why championships, Finals trips, and repeating matter when we talk about true dominance.  • Why the 1968 cutoff matters for fair NBA dynasty debates  • Honorable Mention• No. 10 Rockets run with back-to-back titles• No. 9 Kobe-led Lakers making three straight Finals• No. 8 Bad Boy Pistons making three straight Finals• No. 7  Heatles superteam and four straight Finals  • No. 6  Bird's Celtics and four straight Finals• No. 5 Spurs winning three rings in five years• No. 4 Shaq and Kobe Lakers three-peat and extra Finals trip  • No. 3 Warriors mix of records, repeats, and Finals volume    • No. 2 Lakers Magic and Kareem's Lakers 12 year dynasty• No. 1 Bulls and the unmatched two three-peats standard  • Listener prompt on who I overlooked and who could rise nextPlease make sure to hit that like and subscribe button. Comment, tell anyone who's anyone about the show. Try and get the ratings up a little bit, you know, just a little bit.  Support the showhttps://linktr.ee/GetABucketShow for more content!!!

We all have a natural strength so built into our wiring that we rarely even notice we are using it. It is the default mode that allows us to swim downstream with the current at our backs, experiencing a sense of pure flow. But because it comes so naturally, we often take it for granted—or assume everyone else sees the world exactly the same way we do.This week, we are kicking off a new four-part series by diving deep into your dominant personality trait. We are exploring what it feels like to be "in the pocket" of your greatest strength, how to recognize when you are operating out of alignment, and why your dominant trait is the ultimate key to building a life you don't need a vacation from.Onward and Inward,Kent & CaananCHAPTERS(00:00) Mind Share: We love short books(02:04) Personality Series Part 5: Going deeper into your personality "stack"(03:05) Understanding your dominant trait: The effortless flow state(06:45) The four positions: Dominant, Auxiliary, Tertiary, and Inferior(09:42) What it feels like to swim downstream with your natural strength(12:58) The "Immature Superhero" trope: Why your strength can work against you(17:17) How introversion and extroversion supercharge your dominant trait(19:23) Mailbag: Is it better to focus on my weaknesses or lean into my strengths?COMMON QUESTIONS ANSWERED IN THIS EPISODE ❓What is a dominant personality trait? Your dominant trait is your core strength and default mode. It is the first personality function to develop in childhood and becomes so natural by adulthood that you often don't even realize you are using it.❓How do I know if I am operating in my dominant trait? When you are using your dominant trait, it feels like "swimming downstream." It is characterized by a sense of flow, ease, and a lack of mental blocks. If everything feels like a struggle, you may be operating out of one of your lesser-developed traits.❓What is a personality "stack"? Your personality stack refers to the hierarchy of your four core cognitive functions: Dominant (your greatest strength), Auxiliary (your supporting strength), Tertiary (a lesser-used trait), and Inferior (your weakest area).❓Can my dominant trait actually work against me? Yes. If you are unaware of your dominant trait, you can become "clumsy" with it—like an immature superhero who doesn't know how to control their powers. You might assume everyone sees the world exactly as you do, which can lead to frustration and miscommunication.❓Should I focus on fixing my weaknesses or leaning into my strengths? You should always lean into your strengths. Rather than trying to force your weaknesses to become strong, focus on making your natural strengths even stronger, and use them to compensate for the areas where you are less naturally gifted.SUPPORT NO VACATION REQUIRED If this episode resonated with you, please leave a review. It is one of the best ways to help more people discover the podcast.✅ Subscribe: Never miss an episode by hitting the follow button✅ Visit Our Website: www.novacationrequired.com✅ Read The Book: www.novacationrequired.com/book✅ Follow Us On Instagram: @novacationrequired✅ Talk To Us: www.novacationrequired.com/contact

The Las Vegas Raiders put the pads on for the first time Monday morning — the fifth practice of training camp — and Fernando Mendoza was still working with the second team. Over the weekend that became a national argument. Mike Florio said the Raiders are "deliberately choosing the lesser guy" by naming Kirk Cousins the starter, and warned it would cost them the locker room. Albert Breer was standing on that same practice field and wrote that Cousins is still clearly the best guy at running Klint Kubiak's offense. Two respected voices, one practice, opposite conclusions. Gully works through both, then makes the case that everyone is arguing about the wrong thing — because what has actually broken for Mendoza in this camp isn't arm talent, it's operation. And the man who built this whole plan isn't the head coach. It's a minority owner named Tom Brady. Plus: Maxx Crosby was dominant on the first day in pads, seven months off a meniscus repair, which puts the Baltimore trade that fell apart back on the table. Eric Stokes is playing like a CB1 and spending practice coaching up the rookies trying to take his job. And the offensive line finally got a real test. Chapters: 0:00 Pads are on — Day 5 at Raiders camp 1:34 Klint Kubiak: "We don't have any turds" 2:04 Florio: the Raiders are starting "the lesser guy" 3:40 Albert Breer's answer from the practice field 5:00 The under-center problem nobody mentions 6:25 What actually happened to Mendoza in pads 7:12 The Jordan Meredith snap detail 8:42 Operation, not arm talent 10:18 Tom Brady's fingerprints are all over this 12:25 Sits all year or plays a lot? Both can't be true 12:54 Carson Palmer, 2003 — the last No. 1 QB to sit 14:10 The tell: watch his under-center reps 15:05 Maxx Crosby was dominant in pads 16:17 Baltimore had two first-rounders on the table 17:49 The snap count nobody will talk about 20:24 Eric Stokes is playing like CB1 21:49 The CB2 job — being honest, we don't know 23:17 Jermod McCoy's knee 25:20 Why the secondary decides this season 27:04 The wide receiver problem 28:48 No No. 1 receiver, and Kubiak may not want one 31:45 The trenches: Linderbaum at the point of attack 33:54 Kubiak adjusted inside the practice 34:32 Tonka Hemingway is emerging 35:43 The whole rebuild in one morning 37:17 What's next: Thursday and Allegiant 39:50 Raider Nation hotline + where to find us Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Kevin, Grayson, and Chief survived a rain-soaked prematch (kinda, not really) to witness The FC's best performance of the season. Bucha's return to the midfield, Brian Ramirez's best match (so far?), and Super Sub Tom Barlow's performances all under the microscope. Chief is held to account for his earliest Evander takes. Then in Part Two it's the launch of the PostCast bookclub! Patreon members will vote on which book we read each month, and at the end of the month the podcast will dedicate a segment to talking about the book. Sometimes soccer related, sometimes not, kinda like the PostCast. And there's some Leagues Cup talk in there too if you're a real freak and into that sort of thing.    Timestamps: (3:11) - San Jose Reactions and Review (1:22:22) - Birth of the PostCast Bookclub (1:28:16) - Leagues Cup Preview and Pachuca Predictions   Links:  Looking for an MLS podcast? Check out The World's GAM Visit our friends at Streetside Brewery E&L Roofing has all your Gutter, siding, and roofing needs covered!  Check out The Post at www.thepostcincy.com Music by Jim Trace and the Makers Join the Discord Server and jump into the conversation Follow us on BlueSky, Twitter,  Facebook, Instagram, and YouTube Support us on Patreon https://www.patreon.com/ThePostCincy

Some players dominate because they're bigger. Others dominate because they refuse to be outworked. Aila Courtenay brings both to the floor every time she plays. In this episode of SportsLifeTalk's You Got Next, we sit down with one of the nation's premier Class of 2027 prospects to discuss the journey, mindset, and relentless work ethic that have made her one of the most respected front court players in girls basketball, high school basketball recruiting, and the future of women's basketball. A standout at St. Francis High School in Marietta, Georgia, and a force on the Nike EYBL circuit, Aila has earned a national reputation as an elite rebounder, dominant defender, versatile post player, and one of the most athletic forwards in her class. Whether she's protecting the rim, running the floor in transition, or controlling the paint, she impacts winning in ways that don't always show up on the stat sheet.Throughout the conversation, Aila shares how she fell in love with basketball in fifth grade and how years of hard work transformed her into one of the country's top recruits. While many people focus on scholarship offers and national rankings, she's focused on something much bigger—improving every day and helping her team win.One of the biggest themes of this episode is versatility. Aila explains why she prides herself on doing everything the game requires, from rebounding and defending to handling the ball in transition and making winning plays. She embraces every challenge and believes the best players never stop expanding their game.Listeners also get an inside look at the mindset that separates elite athletes. Aila talks about embracing competition, learning from every matchup, and why playing against the nation's best has accelerated her development. Rather than avoiding pressure, she welcomes it because every game is another opportunity to grow.Away from basketball, fans discover another side of Aila. She shares her love for reading, movies, anime, and spending time with family and friends. She also talks about her passion for academics, why math is her favorite subject, and her plans to study political science in college while continuing her basketball career.Family has played a huge role in Aila's journey. She proudly wears No. 33 in honor of her mother, who inspired her love for basketball and continues to be her biggest supporter. That bond has helped shape the confidence, humility, and leadership she brings both on and off the court.As she looks toward college, Aila says she's searching for more than just a basketball program. She wants coaches she can build genuine relationships with, teammates who feel like family, and a culture where she can compete, grow, and truly enjoy the game she loves.This episode is packed with valuable lessons for athletes, parents, coaches, and basketball fans who love discovering tomorrow's stars before they become household names. Aila's story proves that success is built through discipline, versatility, resilience, and a commitment to continuous improvement.At SportsLifeTalk Media, our mission is to amplify the voices of the athletes, coaches, and leaders shaping the future of girls' and women's basketball. Through You Got Next, we're proud to provide a platform where rising stars like Aila Courtenay can share the stories behind their success while inspiring the next generation.If you enjoy conversations like this, consider supporting our 4 Quarters Program. Your $1 donation helps SportsLifeTalk Media travel to more tournaments, interview more athletes and coaches, and continue telling the stories that deserve to be heard.Subscribe to You Got Next on Spotify and Apple Podcasts so you never miss another inspiring conversation with the next generation of basketball stars. If Aila Courtenay's story inspired you, leave a rating and review, share this episode with a coach, teammate, parent, or basketball fan, and help us continue growing the SportsLifeTalk family.

Welcome to Macro, Micro and Small Cap News with Sharepickers! In today's episode for Friday, 31st July 2026, we review the main market indices, examine the Bank of England's rate decisions alongside Neil Woodford's macroeconomic insights, look at AI security concerns, and highlight 3 promising UK stocks worth researching.

Andy and Randy talk about the Braves lack of offense and still being able to beat the Mets last night.

Jones and Keefe break down all the live play-by-play action from Patriots practice, starting with the early chemistry building between Drake Maye and A.J. Brown after a big completion. The guys react to competitive 1-on-1 drills between Gonzo and Brown. Kyle Williams made a fantastic catch for a touchdown. Plus, a look at running back expectations for the upcoming season and the guys react to the LeBron James "Last Dance" style documentary coming out. Will they tune in?

FAR.AI co-founder and CEO Adam Gleave joins Nathan to discuss FAR.AI's AI Security Leaderboard, the first systematic head-to-head evaluation of the misuse safeguards frontier developers actually ship. The findings expose a major measurement gap: while Claude Fable 5 and GPT-5.6 Sol withstood FAR.AI's suite, Grok 4.5 and Gemini 3.1 Pro yielded hundreds of universal jailbreaks at low cost. Adam explains why many effective attacks look more like social engineering than advanced ML, why “jailbreak tax” should not be relied on for safety, and how FAR.AI scores whether a model is genuinely helping an attacker. The episode's stakes are whether AI developers can measure and harden real deployed defenses before threat actors make routine use of increasingly capable systems. - FAR.AI AI Security Leaderboard: http://leaderboard.far.ai/ - People can e-mail owsa@far.ai if they're interested in the open-weight safety accelerator grantmaking program. For full show notes, links, and references, read the episode page:https://www.cognitiverevolution.ai/is-offense-or-defense-dominant-far-ai-s-adam-gleave-on-the-ai-security-leaderboard/ Sponsor: Claude: Claude by Anthropic is an AI collaborator that understands your workflow and helps you tackle research, writing, coding, and organization with deep context. Get started with Claude and explore Claude Pro at https://claude.ai/tcr CHAPTERS: (00:00) About the Episode (03:22) AI security leaderboard (07:56) Universal jailbreaks explained (16:26) Finding social jailbreaks (Part 1) (16:31) Sponsor: Claude (18:01) Finding social jailbreaks (Part 2) (30:48) Layered safeguard defenses (42:25) Uneven frontier safeguards (51:10) Sharing safety standards (01:00:30) Offense versus defense (01:08:50) Open-weight model safety (01:17:25) Control failure warnings (01:30:05) Coordination and risk (01:39:24) Episode Outro (01:42:52) Outro PRODUCED BY: https://aipodcast.ing SOCIAL LINKS: Website: https://www.cognitiverevolution.ai Twitter (Podcast): https://x.com/cogrev_podcast Twitter (Nathan): https://x.com/labenz LinkedIn: https://linkedin.com/in/nathanlabenz/ Youtube: https://youtube.com/@CognitiveRevolutionPodcast Apple: https://podcasts.apple.com/de/podcast/the-cognitive-revolution-ai-builders-researchers-and/id1669813431 Spotify: https://open.spotify.com/show/6yHyok3M3BjqzR0VB5MSyk

Loyalty can and should be a solid contributor to your monthly sales.  BUT there are steps you must take to optimize it.   --- Is your marketing plan built to WIN? Think so?  Take the audit ... https://business.americasbestrestaurants.com/audit

McMonigle evaluates the New York Yankees' trade deadline strategy, arguing that building a dominant starting rotation is more impactful than marginal offensive upgrades. He reviews Brian Cashman's history with prospects and the potential for a World Series run if they acquire top-tier talent like Tarik Skubal. The discussion shifts to childhood stories about pets and speculation regarding the next manager of the New York Mets. 01:00 - Phone Calls and Banter 02:28 - Yankees Trade Deadline Strategy 10:14 - Pets and Mets Talk

What if your metabolism isn't broken—but responding exactly as your body has been programmed to survive? Welcome to The FutureYou Blueprint™ PNOĒ Metabolic Patterns™ Series, where Debbie Potts explores the five common metabolic patterns revealed through advanced PNOĒ breath analysis. In each episode, you'll learn how stress, nutrition, muscle health, hormones, blood sugar, digestion, sleep, recovery, and lifestyle influence the way your body produces and uses energy. Discover why two people can follow the same diet or exercise plan and experience completely different results—and why identifying your unique metabolic pattern is the first step toward creating a personalized strategy for better health, performance, and longevity. This educational series is designed to help you better understand your metabolism and introduce you to the science behind Debbie's personalized approach through The FutureYou Blueprint™. Learn more or schedule your PNOĒ Metabolism Test:

This is a catch-up version of James O'Brien's Mystery Hour. To join the game, call 0345 60 60 973, Thursdays at 12pm.

Joey and Nick recap the Chicago Cubs 11-2 win over the Detroit Tigers on Tuesday night. A dominant win after falling in the series opener has the guys excited. Cubs On Tap is presented by ontapsportsnet.com

Season 6, Episode 768: Video Version of the interview with Monday Jones, replay to get the video version onto podcast apps. Monday Jones, A Dominant BDSM Shamanatrix, Sex Goddess & Worker, Holistic Somatic Practitioner, Coach, Writer, & the Culture of Sexuality, Sexual Health, & Society. Today on the podcast, you will find an amazing, inspiring, enlightening, and intense discussion with the epic and alternative lifestyle living individual, Monday Jones. We chatted about politics and sex, religion, culture, sex, sexuality, gender, the history of/current environment of sexuality, and sexual health. Connect with Monday Jones: http://www.mondayjones.com/my-links From the Podcast Host Ruan Willow:  Ruan Willow paperbacks always on sale: https://books.ruanwillowauthor.com/booksonsale Book Power Plays: https://books.ruanwillowauthor.com/powerplays Beach House Views: https://books.ruanwillowauthor.com/beachhouseviewsbook One of Ruan's fave brands of adult pleasure toys: Affiliate link Pearl Toys from Kiiroo: Get 10% OFF ENTIRE ORDER (min. purchase $69, no usage limits) with affiliate code RUANWILLOW10 on pleasure sex toys at https://www.kiiroo.com/ https://offers.feeliate.com/to92wTJh Neighborhood Sex Secrets novel: https://books.ruanwillowauthor.com/neighborhoodsexsecrets Discreet cover and title for Neighborhood Secrets: Neighborhood Secrets Novel by Ruan Willow Affiliate link, collect your body's health and sexual health info with a wearable device for men from Firm Ryze coffee use code podna15 to get 15% OFF at (affiliate) https://www.ryzesuperfoods.com/ Tech 15% OFF with affiliate code ruan15 ⁠⁠https://myfirmtech.com/ruanwillow⁠ Copyright 2026 Pink Infinity Publishing. All Rights Reserved. Support the show Newsletters https://subscribepage.io/ruanwillow https://linktr.ee/RuanWillow

Ep 123: In this week's AMA episode, I'm answering some of your most recent fitness questions—from whether you actually need to train your "lower core" differently, to exercises to do if you feel like you're quad-dominant and how and why alignment is so important pre workout + little clues that you might not be as aligned as you think.We also dive into one of my more recent favorite topics - how you can actually  build strength and lose fat when life is busy. (Spoiler: it's less than you think.)Plus... I finally announce my brand new Busy Body program, designed specifically for women who want noticeable results without spending hours in the gym.Busy Body launches July 28th and includes: 5 workouts per week  30–45 minute sessions  Structured body-part split  Alignment drills and warm-up exercises included  Progressive strength-focused programming  Designed for busy women who want maximum results in minimal time If you've been waiting for a realistic program you can actually stick with, this is it.__________________________________________________________________________________________________Apply for Advanced Training and Nutrition with Chelsey & Dr Emily Dow HEREStart your 7 day FREE trial of my new app HERE!Programs:8 Week Summer Prep Planhttps://www.trainerize.me/profile/chelseyrosehealth/?planGUID=d48c6fbf116c4e8fb4d31f94b5376fa3Want to work in person with Chelsey?Join a semi-private class in LA here.Email info@chelseyrosehealth.com to inquire about one on one in person training.Shop the things i'm loving HEREFollow Chelsey on Instagram:@Chelseyrosehealth@StrengthtobuildFollow Chelsey on TikTok Here."Submit a question to the show"

Andy and Randy break down Spain's victory over Argentina in the World Cup final, highlighting the dominance of the Spanish squad and Argentina's controversial behavior. They also discuss Trae Young's failed attempt to rip a Jalen Brunson jersey and the impact of LeBron James on the NBA's scheduling. 01:20 - Michigan AD Warde Manuel 04:45 - Cam Skattebo Backflip Mishap 08:08 - Bourbon Street Versus Broadway 11:41 - World Cup Final Reaction 18:20 - Spain Dominates The Pitch 23:44 - Food Safety And E. Coli 28:44 - Athletes Complaining About Taxes 32:33 - NBA Stars At WWE 36:58 - Gwinnett County Football Stars

Are we staring into the abyss of a hiring chaos or on the brink of a revolution? Join us as we dive deep into the messy truth behind current job boards, AI's role in hiring, and how the market is reshaping the talent game. This is raw, real, and everything you need to understand where work is headed today.  In this episode:  The turbulence in the job board market and declining power of giants like ZipRecruiter and Indeed  How AI could finally end ghosting and improve hiring transparency  The impact of economic slowdown and slow hiring strategies on blue vs. white collar jobs  Why employer distrust is rising and how pricing models fuel the chaos  The future of smaller companies, AI assistants, and the redefinition of HR in a tech-driven world    Timestamps: 00:00 - Introduction: Unpacking the chaos in recruiting tech 02:22 - Fun facts about Chris: Kayaking and hiking adventures 04:40 - The real trouble with job boards: Struggling giants and market share battles 07:12 - Is the market slowdown due to fewer jobs or just hiring shifts? 08:41 - Employer behavior shift: Quantity over quality and ghosting culture 09:56 - AI's potential to eliminate ghosting and streamline the recruitment process 11:11 - How companies like Greenhouse are rethinking candidate experience 12:54 - The fundamental business problems facing job boards today 14:29 - Why secondary job boards are failing to overtake giants 17:50 - Trends in blue collar vs. white collar hiring challenges 19:04 - The nightmare of application processes and resume parsing 22:57 - The future of AI agents for job seekers and hiring automation 26:24 - Will smaller, more AI-driven companies dominate the future? 28:52 - How job seekers are feeling: Fear, hope, and AI optimism 30:33 - The human side of AI: From greeting cards to personalized connections 31:49 - The coming era of smaller teams powered by AI efficiency 33:35 - Creative visions: HR Data Doodles and comedy in Human Resources    Resources & Links:  RecTech Media - Follow Chris Russell for cutting-edge insights  ZIPRecruiter - The struggling giant of job boards  Indeed - Dominant market player and trends insight  Greenhouse - HR tech innovator focusing on candidate experience  Europe's AI & Data Privacy Standards - For regulatory context  YouTube: Human Resources TV Show - Satirical look into HR humor  Connect with Chris Russell:  LinkedIn  Twitter  Stay tuned for more episodes where we challenge the status quo, ignite the future of work, and boldly explore what's next in HR and recruitment. 

Some parts of the media have pronounced MAHA DOA PDA. But maybe they're just FOI? Helena and Theodore discuss. They also tackle the staggering, stunning, Holy Guacamole adoption of GLP-1s by Americans, and the rise – and risks – of compounded weight loss drugs and direct-to-consumer pharma. Finally, a good vibe: a pool full of pickles for a proper purpose!

Republican Opposition: The Intellectual Force of Robert Taft and the Rise of McCarthy GUEST: Nick BunkerSenator Robert Taft, known as "Mr. Conservative," was a dominant intellectual force in the Republican Party, preparing for a potential 1952 presidential run. Moving away from pre-war isolationism, Taft became a staunch "Asia first" advocate, pushing for the defense of Taiwan with the U.S. Navy. This stance created a sharp divide with Dean Acheson, who feared being branded an "imperialist power." While Taft provided the intellectual foundation for Republican policy, Joe McCarthy emerged as the "wild side" of this movement. Driven by pure ambition, McCarthy hijacked the Republican agenda by shifting the focus from domestic "socialism" to communist subversion within the State Department. Meanwhile, Dwight D. Eisenhower, then president of Columbia University, watched from the sidelines with despair. He worried about the "chaos and confusion" in Washington, the demoralization of the military due to budget cuts, and the lack of a clear strategy for Asia. (3)

We've been running a bit of an Agent Cloud series surveying all the top inference/compute/cloud providers, from Databricks to Daytona to Railway and, even further back, E2B, but we're excited to conclude this series returning to Modal, which has just raised a monster $355M Series C.The cloud was built for developers. But agents are now changing that.The old infra stack was designed for a human who could read docs, reason through YAML, and understand dashboards to figure out what they need when something broke. While this was painful for developers, it worked since they could fill in missing context in their heads.However, agents don't have that luxury. Now in this new era of agents, everything has to be tighter.They need a place to write code, run it, inspect the output, change the environment, debug failures, and try again. Fast iteration and feedback loops with all the necessary context are crucial for agents to operate properly. Furthermore, sandboxes are a clear representation of this shift as agents can easily spin up isolated environments. This programmatic infra even extends to research:Two years ago, we were one of the first to cover Modal with CEO Erik Bernhardsson and Alessio designed our favorite LS thumbnail of all time:At the time, Modal was just a teeny little company with a $17M Series A.Today, fresh off their $355M Series C, Modal is one of the clearest examples of the agent cloud future being built in real time: a cloud platform moving past traditional web app assumptions toward the workloads AI actually creates such as elastic inference, sandboxes, GPU burst, post-training, background agents, and infrastructure that agents themselves can operate.In this episode, Modal CTO Akshat Bubna joins swyx and Vibhu to unpack why AI applications don't fit traditional cloud assumptions, why Kubernetes was never designed for bursty compute-heavy workloads, and why Modal is now shifting from developer experience to agent experience.We go deep on Modal's AI infra stack: serverless functions, decorator-based infrastructure, elastic inference for custom models, GPU snapshotting, DeFlash, speculative decoding, Auto Endpoints, sandboxes, persistent storage, networked containers, private IPv6, RDMA, multi-node training, and Modal's capacity pool across 17 cloud providers. Akshat also explains why RL rollouts can require 100,000 sandboxes, why production agents need hard guardrails, why observability may matter more than reading code, and why AI has made infrastructure exciting again.We discuss:* Why Kubernetes wasn't built for bursty AI workloads* How Modal started as a better runtime before becoming an AI cloud* Why Modal added GPUs before ChatGPT* The shift from developer experience to agent experience* Why observability matters when agents are writing the code* Elastic inference for custom models across audio, video, robotics, and comp bio* GPU snapshotting, cold starts, and why inference workloads are so bursty* Why RL rollouts can require 100,000 sandboxes* DeFlash, speculative decoding, and frontier-level inference performance* Auto Endpoints and making optimized inference easier to deploy* What Modal adds beyond vLLM, SGLang, and raw GPU rental* Modal's 17-cloud capacity pool and supercloud strategy* Networked sandboxes, sidecars, private IPv6, and RDMA* Serverless multi-node training for post-training and research workloads* Auto-research, model-guided sweeps, and agents launching GPU experiments* Compute strategy, capacity planning, and batch tiers* Why production agents need specialized sandboxes and hard guardrails* Modal's take on managed agents, CI, Gitpod/Ona, Python, TypeScript, and Modal BenchAkshat Bubna* LinkedIn: https://www.linkedin.com/in/akshat-bubna-188885103* X: https://x.com/akshat_bModal* Website: https://modal.comTimestamps00:00:00 Introduction00:00:39 Modal's origin and why Kubernetes wasn't enough00:04:32 Developer Experience → Agent Experience00:06:21 Modal's AI cloud primitives00:09:14 Sandboxes, agent loops, and proto-Cognition00:12:12 Elastic inference, GPU snapshotting, and 100,000 sandboxes00:15:24 DeFlash, speculative decoding, and Auto Endpoints00:19:59 Production-grade inference beyond raw GPUs00:22:00 Background agents, Ramp Inspect, and the agent lifecycle00:24:08 Modal's 17-cloud supercloud strategy00:26:40 Networked sandboxes, private IPv6, and RDMA00:32:48 Multi-node training, post-training, and auto research00:37:36 Compute strategy, capacity planning, and batch tiers00:40:55 Open models, real-time AI, and production agent infra00:43:06 Hard guardrails, managed agents, and specialized sandboxes00:46:06 Why AI made infrastructure exciting again00:48:30 Model APIs, differentiated products, and agentic video00:51:50 CI, coding-agent infra, SDKs, and Modal Bench00:57:28 Closing ThoughtsTranscriptIntroduction: Modal, Series C, and the Art PartySwyx [00:00:00]: We're here with Akshat, CTO of Modal, together with Vibhu. Congrats on your Series C.Akshat [00:00:10]: Thank you.Swyx [00:00:11]: Your party yesterday was amazing.Akshat [00:00:15]: Yeah.Swyx [00:00:15]: From all the photos and all the swag.Akshat [00:00:17]: We had a bunch of art installations, which was fun, seeing, like, our products on pedestals next to, like, Rodin.Swyx [00:00:25]: Very nice. Very nice. When you started, it was not the GPU inference company. Maybe it was in your mind. Take us back to the origin story.Modal's Origin: A New Runtime Beyond KubernetesAkshat [00:00:39]: I first met Eric, who's the CEO, through an investor. Back then Eric was already thinking about building, a new runtime, and he got there thinking through why are workflow orchestration products so hard to use. It's because you have to run them on Kubernetes. Kubernetes is hard to manage. It's not built for burstiness and, custom images,Swyx [00:01:03]: YeahAkshat [00:01:03]: It has a terrible developer experience.Swyx [00:01:05]: And I'll, I'll interjectAkshat [00:01:06]: YeahSwyx [00:01:07]: For listeners, who are new, we interviewed Eric two years ago, and there's a bit more of the story there from Spotify and all those things.Swyx [00:01:14]: And I came across Eric through Data Council because he did that talk on the serverless container stack that you guys did, which was like, that was my first like, “Okay, I need to take Modal very seriously” moment.Akshat [00:01:26]: Yeah.Swyx [00:01:26]: But it was still very unclear, like, do I need all this for just my data pipelines?Akshat [00:01:33]: Yeah. initially what we were thinking about was if we build a better runtime, it's a very useful primitive in itself. It's There's a lot of things that, get solved by serverless functions, like you can do, ETL stuff, you can do job queues, you can do all this, like, bursty processing, which it turns out every company had needs for. but then we also were thinking about this as like, this is a primitive that we can build a whole collection of products on, which are very verticalized. So perhaps data engineering would've been the first one, but we were thinking about inference. Back then it was more classical inference, like computer vision stuff and running XGBoosts and whatnot. But we added GPUs to the product a year before ChatGPT came out.From Serverless Containers to GPU WorkloadsSwyx [00:02:19]: Nice.Akshat [00:02:19]: We just didn't think it would be that big of a deal.Swyx [00:02:22]: Yeah, just like add A100.Vibhu [00:02:23]: Was there any, like, early key problem that really sparked off why you built it?Akshat [00:02:28]: Yeah. Primarily it's just, none of the tooling that was out there was built for, one, a really great developer experience, and also there's a general trend of, a lot of the workloads that we were seeing were very. I wish there was a better word for it, but compute-heavy. Like, they need, one, like, need a lot more resources, so you need to burst up and down a lot, versus like Kubernetes designed for, like, slow scaling and, more for, like, web server use cases. And also there's just a lot more specialization in, like, what kinds of environments these workloads run in. Like, we had sometimes they need accelerators, sometimes they need different kinds of images, and this is just like a consistent thing that we saw across a lot of companies. That would be the next step.Software-Defined Infrastructure and Decorator-Based DXSwyx [00:03:13]: Yeah. Yeah. Be nice. I don't know how much this factored into the early story, but I wrote a post when I was at Temporal about infrastructure, software-defined infrastructure or something like that.Akshat [00:03:22]: Yeah, the self-provisioningSwyx [00:03:23]: Self-provisioning.Akshat [00:03:24]: Yeah.Swyx [00:03:24]: Yeah. I can't even remember my own post.Swyx [00:03:26]: And then you put me on the landing page.Akshat [00:03:28]: Yeah. We really like, the term and so we stole it.Swyx [00:03:32]: Because you had the insight that everything can just be in decorators co-located with the code, right?Akshat [00:03:37]: Yeah.Swyx [00:03:37]: Was that a big part of the originalAkshat [00:03:39]: YesSwyx [00:03:39]: Story or it was just like a DX layer?Akshat [00:03:41]: That was, really important because we really didn't want people to spend, so much time, writing YAML, and it seemed like you could really condense the surface area of what you're doing, put it in code so you can operate on it just like you operate on other code, and like build stuff that's more expressive and dynamic. and so yeah, that was always a very important part.Swyx [00:04:04]: Then the pushback is this is a DSL.Akshat [00:04:07]: Yeah.Swyx [00:04:07]: It's you're closed source. I am locked into Modal.Akshat [00:04:11]: Yeah. We never really got pushback for that because the nice thing about Modal is you can bring whatever code you have, and sure, the DSL is at the configuration layer for, what hardware you're using, how you're scaling things up, but you still own the code.Akshat [00:04:27]: And that's, that's been an important, part of our story, even as we do inference now.Swyx [00:04:32]: Yeah.Vibhu [00:04:32]: How much of do you think still stays the same today? Like if you were to build something today, DevX very important, but I feel like, a lot of this has been changed with just hook it up to an agent, have Claude Code, have Codex implement a tool. there's very agent native primitives that are different than if I'm doing this myself, right?Developer Experience → Agent ExperienceAkshat [00:04:54]: We've changed our SDK team to think about agent experience instead of, developer experience and we think that the same benefits that apply for DX also apply for AX, which is why would you have an agent read through hundreds of Kubernetes files and like write YAML that's not even typed when it can make a couple of changes in a decorator and it gets this self-provisioning runtime of, being able to see its changes live in action? yeah, it just seems from the customers we talk to, they find Modal is much faster for agents to use versus operating on a different substrate.Swyx [00:05:34]: Yeah, because like you, again, you co-locate the infrastructure requirements to the code that runs it.Akshat [00:05:38]: Yeah.Swyx [00:05:38]: Well, the negative thesis now is that nobody's looking at their code anymore, so there's no point.Akshat [00:05:44]: Yeah, people aren't looking at code. one thing we still see is really important is observability.Swyx [00:05:51]: Yeah.Akshat [00:05:51]: Like how good is your dashboard? And of course, like we have, we push a lot of it to the CLI so the agents can do their own investigation, but you still need humans to go interpret what's going on and, make judgment calls and whatnot. and that's I feel like, Maybe more important now than looking at the code itself.Swyx [00:06:11]: Yes, because like, you can try to treat the code as a black box and then use, see the observable action that comes out of it, and then just prompt a change.What Modal Is For: AI Cloud PrimitivesAkshat [00:06:21]: Yeah.Swyx [00:06:22]: So I think it takes a bit of restraint to not specialize, to say, “I want to ship a new primitive,” and then just be general purpose.Swyx [00:06:31]: People ask you, “What are you for?” You're like, “ I don't know. We can do this, we can do that.”Vibhu [00:06:36]: Well, I'd be curious to see, like, okay, if we were to ask you, like, what is Modal for even at a high level? There's a lot you guys do, sandboxes, GPUs, everything. How do you answer?Akshat [00:06:46]: Modal is a cloud platform that's built for, where we've built the primitives from scratch for AI applications. and right now it covers, inference, training, batch processing, and sandbox workloads.Akshat [00:07:00]: But we're building a lot moreSwyx [00:07:02]: I noticed you didn't say web server, so there is still a role for, like, the always-on large-scale Kubernetes type things.Akshat [00:07:09]: Yeah, absolutely. We're, we're not trying to compete with the renders of the world, because yeah, we think the differentiator for us is the, are the workloads that need specialized compute, need to scale up and down a lot. yeah, they're, they're, they're just shaped differently.Working Alongside Frontier StartupsVibhu [00:07:26]: I think you're building a lot of it alongside the startups, right? They're innovating quite a bit, even in your, like, latest blog post. Like, even in the series C, the customers that you mention here, the cognitions, technical ones, ramps and whatnot, they're, they're innovating with you, right? And that's not something AWS is doing directly with.Akshat [00:07:45]: Yeah, absolutely. I think, this is again classic. We're a small team. We can move really fast. our engineers are working with our customers and figuring it out. Yeah.Swyx [00:07:54]: So my first week at Cognition, I walked in, there was someone wearing a Modal shirt. I was like, “What are you doing here?” They're like, “Yeah, I just. I am embedded inside of Cog.”Akshat [00:08:05]: Yeah, I think that was Peyton. We sent him overSwyx [00:08:07]: Yeah.Akshat [00:08:07]: Because, the latency of communication was too high otherwise.Swyx [00:08:12]: Yeah, distributed node, you have to - you have to place one and collocate.Vibhu [00:08:16]: Yeah.Swyx [00:08:16]: So I had a, I had direct personal experience, right? So I worked on smol developer three years ago. it was inspired by Claude 1. I think you onboarded me at some point, like, just before, and I was like, “Oh, like, I need some bursty compute. Like, I was just gonna try using Modal.” And it was a, it was a pretty pleasant experience. apparently, I showed up in the board meeting, like the analytics.smol developer, Sandboxes, and Proto-CognitionAkshat [00:08:39]: Yeah, you blew up on Hacker News and,Swyx [00:08:41]: YeahAkshat [00:08:41]: We got a big traffic spike. I. I think the way you used smol developer was Modal functions for running stuff, which was. Like, the, that was a good use case. but then, yeah.Swyx [00:08:53]: Yeah. That - So to me, that was proto-cognition.Akshat [00:08:55]: Right.Swyx [00:08:56]: If only I had, like, stuck to it.Swyx [00:08:58]: Like, that was like, if - did you say draw the tech treeAkshat [00:09:00]: AbsolutelySwyx [00:09:00]: You're just like, “Yeah, like, probably this will happen.”Akshat [00:09:02]: Yeah. Like, he was so close. You were just rebuilding upon usSwyx [00:09:04]: I just didn't realize.Akshat [00:09:05]: But the funny story there is at the same time, we were talking to a bunch of customers who needed something like sandboxing.Swyx [00:09:14]: Yeah.Akshat [00:09:14]: This is like twenty-three.Swyx [00:09:15]: Yeah.Akshat [00:09:16]: So we builtSwyx [00:09:17]: You introduced a new API right after that.Akshat [00:09:18]: Yeah.Swyx [00:09:19]: Yes.Akshat [00:09:19]: Like, we built sandboxes in May of twenty-three before anyone was even knew this was gonna be a thing. And the first example we published was, we took smol developerSwyx [00:09:28]: Smol developerAkshat [00:09:28]: And put it in a loop, so the agent can iterate on itself.Swyx [00:09:33]: Loops are hot these days.Vibhu [00:09:34]: It's the looper.Akshat [00:09:34]: Yeah.Vibhu [00:09:35]: Loops in. When was this, twenty-three?Akshat [00:09:38]: Yeah.Vibhu [00:09:39]: A small check.Akshat [00:09:39]: Yeah.Swyx [00:09:39]: It's like twenty-three. so the. the, those for listeners, like, the problem was the models are not built for any of this, right?Swyx [00:09:46]: Like, you're just trying to like. They're not post-training to understand, like, looping and, like, self-correction and tool calling was there, but, like, also not that great.Akshat [00:09:55]: Yeah.Akshat [00:09:55]: I don't remember if you used tool calling in this one, but yeah, the models would just diverge after like ten iterations and not produce anything meaningful.Swyx [00:10:03]: Yeah. But like, then. So okay, like now talking to myself three years ago, the answerVibhu [00:10:08]: Of course they will get betterSwyx [00:10:09]: Collect all the failures, build benchmark, and then collect all the, examples, build the RL environmentAkshat [00:10:15]: RightSwyx [00:10:15]: Sell it for like ten billion dollars to Meta.Swyx [00:10:17]: And then also train a model and then sell that for sixty billion dollars to Elon. And this isAkshat [00:10:23]: Yeah, of courseSwyx [00:10:23]: The funny machine. Like, it's like, it's about the hardware.Akshat [00:10:28]: It's hard to have that inherent conviction that the stuff will get that much better.Swyx [00:10:33]: In retrospect, it's so f*****g obvious.Akshat [00:10:36]: Fair enough.Swyx [00:10:37]: Like, what else were we doing back then? I don't know. anyway. Yeah. So this. That was the start of your sandboxing journey, right? I feel like it didn't blow up until, like, last year.Akshat [00:10:49]: Yeah.Swyx [00:10:50]: So there was like a couple years of quietness.Akshat [00:10:52]: Exactly, yeah. We wereVibhu [00:10:53]: I think very underrated product value. Like, my experience with Modal, Charles, before he had joined Modal, met this guy at a hackathon, and he really insisted we wanted to run some small model, not hosted anywhere, and he's like, “ there's this cool company, Modal. They'll like spin up a GPU sandbox, we can throw it on there. They'll take a Hugging Face link.” And like there's so much value just right there, right? Like instant hosting, spin it up, spin it down. It'll stay cold, but we run the demo a few days later, it'll come back up and like all this stuff in retrospect, like it's still what we needed like today.Akshat [00:11:27]: Yeah, it's still needed today. workload shapes have changed a lot as, we run stuff for people with really massive production scale and, there it's it's not about scaling from zero to one, but it's how do we scale really elastically, from like thousand to fifteen hundred GPUs very quickly in a given region. It's the same shape problem.Elastic Inference, GPU Autoscaling, and Custom ModelsVibhu [00:11:50]: Okay. So you look at, say, Cursor Composer, right?Akshat [00:11:53]: Yeah.Vibhu [00:11:53]: They had a. “We'll do RL on a model every couple hours.” you guys have a whole version of RL inference gym and whatnot.Vibhu [00:12:01]: When you look at workloads like that, you're doing train runs where you need to scale up, scale down every hour thousands of GPUs, right? That's the example for we do need it, right?Akshat [00:12:12]: Yeah. Well, so I'll, I'll take a step back and, maybe talk about like how people use Modal today. because our biggest use case is, elastic inference. And the thing we first found product market fit, with was inference for custom models. So we stayed away from the LLM space, and we were serving companies like Suno for audio, Runway for video, robotics, comp bio companies that train their own model elsewhere. But Modal is the best black box that for deployment, scaling to however many GPUs you need as your traffic pattern changes. And we saw all of them like have a very unpredict- predict- predictable, traffic pattern. it's like diurnal. It's Some days, like the company will do a launch and, they'll need like, way more. And it's not just one model that they deploy. They-- all these companies deploy, lots of different models in different regions, and so the autoscaling problem becomes even harder because then you have to scale within a certain region, and those cycles are offset. So different times you scale up in different regions.Akshat [00:13:20]: So that's like our sortVibhu [00:13:22]: And thatAkshat [00:13:22]: YeahVibhu [00:13:22]: That in and of itself is a huge category. There's a bunch of inference providers which, provide this fireworks, does this as a service together, whatnot, Base10. that's carved into its own niche for language models, at least right now.Akshat [00:13:36]: Yeah. the thing that we have specialized in is the autoscaling aspect.Vibhu [00:13:41]: Yeah.Akshat [00:13:41]: Because we found that it's not universally true that everyone else can autoscale, and we've gone deeper into it on the tech side by, we've incorporated GPU snapshotting into the product so we can take the GPU state, like your torch.compile model, snapshot it, and the next cold start is way faster. And so going back to your question, it's That's why you need a lot of burstiness for inference. But then people also do a lot of demand training, like for RL stuff, your rollouts are bursty, as you said. People also do a lot of batch jobs. So we'll see, a lot of companies, before they have a training run, they'll need thousands of GPUs to run encoding or something like that. And I think those things are much more bursty than. I agree that agents are not that bursty. sandboxes are, except when you're doing RL. RL is justRL, Batch Jobs, and 100,000 SandboxesVibhu [00:14:28]: Or commerceAkshat [00:14:28]: Insanely bursty.Vibhu [00:14:29]: Yeah.Akshat [00:14:30]: Yeah. Like when you're doing, rollouts, you sometimes need a hundred thousand sandboxes in your sandboxes.Vibhu [00:14:37]: Yeah. I'm curious if you've seen early sparks of continual learning. There are some people, like our friends, ngram, recently announced thisAkshat [00:14:45]: YeahVibhu [00:14:45]: They're, they're trying to do training. That also seems like a different workload, right? If you're doing training twenty-four/seven per se, there's a very weird dynamic of how you're using GPUs between people and whatnot, but seems like something you guys would work for.Akshat [00:15:00]: As you said, we're, we're fortunate to work with a number of, customers at the frontier and grab some of our customers. and they are taking the primitives we have, and trying to use them in very interesting ways, like continual learning. It's possible as the stuff gets better, some of that will be part of, our offering as well if, more people need it. but we're, we're just waiting to seeVibhu [00:15:23]: YeahAkshat [00:15:23]: How it shakes out.Vibhu [00:15:24]: Is there a primitive that you added after sandboxing that was the next step in the story?LLM Inference, DeFlash, and Speculative DecodingAkshat [00:15:32]: I guess we've been going much deeper into LLM inferenceVibhu [00:15:35]: YeahAkshat [00:15:35]: Because we realized that some of the advantages we have with like autoscaling, again, especially in different regions and whatnot, are, not present elsewhere. and the place where we had a gap was we weren't, working on the model layer itself. Like we were a black box. And, we realized that, we can get to frontier-level model performance, with, by having great people who work on this. And, we've been open sourcing a lot of our work, in terms of, Recently, we, shared our work on DeFlash, which is a block-based, speculator, and we've open sourced, all of it. So, you can - By using open source DeFlash, you can get the same performance as you would with one of the proprietary providers. And the next thing we're thinking about hereVibhu [00:16:23]: I thought this wasAkshat [00:16:24]: YeahVibhu [00:16:24]: An interesting blog post as well, right? Like, I think in here you make a claim that. Not a claim, just that how effective speculative deco-decoding really just get to.Akshat [00:16:33]: Yeah.Vibhu [00:16:33]: Anything you wanna point out from this around, what people should know?Akshat [00:16:39]: Yeah, absolutely. the high-level summary is, it would help to describe what speculative decoding is.Vibhu [00:16:44]: Yes.Akshat [00:16:44]: I will, yes.Vibhu [00:16:45]: I think, likeAkshat [00:16:46]: YeahVibhu [00:16:46]: So we've covered like Eagle and all thisAkshat [00:16:47]: YeahVibhu [00:16:47]: Like Hydra and all those things, but it was like two years ago.Akshat [00:16:51]: Yeah.Vibhu [00:16:51]: I think it doesn't hurt, right?Akshat [00:16:52]: Yeah. Speculative decoding is you have a smaller model, called a draft model, predict tokens ahead of the bigger model, and then you have the bigger model, verify all of this, all the tokens are predicted. And the reason it's faster is if you're predicting, one token at once, you're bound by memory bandwidth. But if you can batch the verification of, the draft model, then you're much more efficient using compute, and it's faster, and as long as your draft model is producing a lot of tokens that can get accepted, which is called the accept length, you can get a speed up that's, multiple times of, the original model speed. and well, that's what we highlight here. It's Like people talk a lot about we made these kernels faster and whatnot, but improving kernel will only give you like few percentage points of improvement, and, increasing accept length, literally is a multiplicative decreaseVibhu [00:17:47]: Like two to four X.Akshat [00:17:48]: Yeah, exactly.Vibhu [00:17:48]: Without much head-on performance.Akshat [00:17:50]: Yeah. I think it may - you are running a second model, right? So it may be something more expensive in the compute,Vibhu [00:17:57]: I meant quality performanceAkshat [00:17:58]: Probably not by muchVibhu [00:17:58]: But yeah. I thinkAkshat [00:17:59]: So there's no drop in quality performanceVibhu [00:18:01]: YeahAkshat [00:18:01]: Because you're always. You're never accepting a token that the big modelVibhu [00:18:04]: It's strictly betterAkshat [00:18:05]: YeahVibhu [00:18:05]: Or it's same.Akshat [00:18:06]: Exactly.Vibhu [00:18:07]: Right. Yeah.Akshat [00:18:08]: And so we've been working a bunch on DeFlash, which is a block-based speculator. so it's instead of predicting, one token at a time, it's predicting a block. And we've been open sourcing our work with it. The next thing for us here is for helping people train speculators and custom models. it's it's something that traditionally is very forward-deployed engineering driven, support deployed, engineer driven, like you work with customers and help them do that. And our vision for. This is why we launched Auto Endpoints, is we want to make frontier-level performance available to everyone. And so, we mentioned this in the announcement, we teased it. The next thing we're, we're launching is, as you run an auto endpoint, we shadow trafficAuto Endpoints and Frontier-Level PerformanceVibhu [00:18:54]: Do you want to explain what auto endpoints are?Akshat [00:18:57]: Yeah.Vibhu [00:18:57]: I lovely, yeah.Akshat [00:18:58]: Yeah. So, this is, I guess, going back to your Modal is you touch the code, but, sometimes people don't wanna touch the code, and they wanna get started with an endpoint that works and has all the great performance and, scalability that Modal has. So we've made that easier with, a way to create an endpoint from our UI, from the CLI, that has all of our optimizations that we talked about, like the DeFlash stuff already baked in, and there's full transparency. So we give you the code, you can go run it yourself, and if you want, you can eject out into the full Modal experience, which we see as people get sophisticated, they do wanna tweak the models, they wanna, fine-tune stuff. You can still do all of that. It's it's not a black box. And yeah, the next thing, as we teased later in the post, is how do we give you value even beyond this in terms of having your draft models evolve as your data distribution evolves, again, without having to talk to a person and, yeah.Vibhu [00:19:59]: I guess just to understand it directly, you have the GPUs, you have an endpoint that's compatible, you serve open model. If someone was to do this themselves, what's the delta that you guys provide? So you do a lot of open source great work on effective inference. how does it compare to, say, I take the same model, 5.2 FP8, take shelf inference engine, vLLM, SGLang, get compute of similar capacity, similar cost. What's the delta that plugging into something this, like this offers outside of the benefit of, scaling?Production Inference Beyond Raw GPUsAkshat [00:20:34]: It's interesting because we've taken the approach of open sourcing our contributions and upstreaming them. we work closely with the SGLang team. We want the improvements that our team, comes up with to be, there in open source for others to use, even outside of Modal. The benefit to us is we have a team that has significant expertise in terms of if you do have something that is not there, our team can help you get that performance, first. the other thing is with these endpoints, we are way more elastic, as you said, than, anyone else, and you have true scaling to zero. you have true, burstiness, and in practice, that matters a lot more to people than just finding, the GPU and, running Modal code on something.Vibhu [00:21:20]: Yeah. And I will say it's not that straightforward to just. like what I said is easier said than done, right?Akshat [00:21:26]: Yeah.Vibhu [00:21:27]: It's I think still for the average person, still hard to just gut check using different. There's, there's quite a bit of combinations you can make there. the trade-offs aren't really known at face value.Akshat [00:21:40]: Yeah. it's it's not just that. I think it's it's that running production-grade inference is a hard infer problem.Vibhu [00:21:49]: YeahAkshat [00:21:49]: Even if you subtract out the autoscalingVibhu [00:21:50]: YeahAkshat [00:21:51]: Is controlling things like tail latency and, making sure every, request is delivered at least once and whatnot.The Model and Agent LifecycleVibhu [00:22:00]: There's a lot of innovation that you can do here. I think, it's very interesting that you're starting to encroach on, like as you become a full cloud, you're starting to encroach on other people's turf.Vibhu [00:22:09]: What will you not do?Akshat [00:22:13]: Well, we wanna follow our users and, make sure they get like a platform that has everything that works well together. so right now we're focused on the model lifecycle and the agent, lifecycle. so both like going from data prep to training to inference, and then also if I want to deploy a background agent, let's say, sandbox, do persistent storage, a whole bunch of other stuff.Vibhu [00:22:38]: We talked to Cole, who did, OpenInspect. Yeah.Akshat [00:22:42]: Yeah.Vibhu [00:22:42]: And RealInspect also is on Modal.Akshat [00:22:44]: Yeah. So Ramp Inspect was a great example of a background agent that was really successful because they, were able to use some of the primitives like snapshotting and fast scaling to just have something that feels really reactive and works well.Ramp Inspect and Background AgentsVibhu [00:23:02]: Yeah. That's the new CTO of, Ramp right there.Akshat [00:23:05]: Yeah, Rahul.Vibhu [00:23:08]: It was really fun. yeah, okay, I think, all very bullish. Like, one of my reflections was also I did not originally. So when I met you guysThe Inference Inflection: CPU, GPU, and Co-LocationVibhu [00:23:19]: You weren't that much in the GPU game, and now you're all about, inference. And one of the points that I hinged on for Jensen's keynote at GTC this year was, what we're calling like the inference inflection, right? That let's say in AI workloads or machine learning workloads, it used to be like, let's call it eight to one GPU to CPU, and now it's more like one to one, which is like a interesting. Like, - because of how much agents are blocked or call out to this, to CPU heavy stuff the actual, like, limiting factor, like, swings back and forth from GPU to CPU a lot more than it used to be all GPU and then occasional CPU.Akshat [00:24:01]: Yeah.Vibhu [00:24:02]: GPU, CPU. And now it's like just constantly, and you just have to locate everything.Seventeen Clouds and the Supercloud StrategyAkshat [00:24:08]: Yeah. And that's one of the things that, again, we see as, something appealing about Modal, which is we've built this capacity pool that spans, 17 cloud providers, so we're, we're very good at Running on various kinds of cloud capacity across the worldSwyx [00:24:24]: You don't have your own data centers?Akshat [00:24:25]: We don't have our own data centers. We just run across a lot of neo cloudsSwyx [00:24:29]: Yeah. AreAkshat [00:24:30]: Metal providers.Swyx [00:24:30]: Yeah. Question mark.Swyx [00:24:31]: Yeah. You're, you're running the math, and you're like, “What's the cutover point where you're like.”Akshat [00:24:36]: Yeah, it's a good question. part of it is we see our differentiator in the software layer, and, being capital light and focusing on the software helps us move really fast. so far it's worked out well because there are so many other people building data centers that we're able to work effectively with them, and again, focus on what makes us, special.Swyx [00:24:55]: Yeah.Swyx [00:24:56]: 17 gets you into, like, the local providers sometimes. LikeAkshat [00:25:00]: The,Swyx [00:25:01]: Which was the most interesting one?Akshat [00:25:02]: There are a lot more neo clouds than you expect, and they all have various degrees of, various levels of reliability. And, that's why it's something we've invested a lot of time in, is building our own reliability layer on top. so if the GPU falls off the bus or something happens, we user workloads are not affected, and that lets us use a lot more capacity than,Swyx [00:25:30]: YeahAkshat [00:25:30]: You as a user would be able to.Swyx [00:25:32]: It's a useful thing to have because like now everyone knows, like, what layer you are and, like, you optimize for being the super cloud of all clouds.Akshat [00:25:41]: Yeah. That's, that's, that's the idea. and so I guess when you mentioned colocation, that's, that's another interesting thing where, one thing we've seen is people come to us when they want, very specifically located, CPUs or GPUs, like they wantSwyx [00:25:57]: Oh, they pin it in likeAkshat [00:25:58]: YeahSwyx [00:25:58]: EU?Akshat [00:25:59]: Exactly. Or EU, US.Swyx [00:26:01]: Right. Data resiliencyAkshat [00:26:02]: AustraliaSwyx [00:26:02]: Locality thing or performance or what?Akshat [00:26:04]: It's either data locality or latency, yeah.Swyx [00:26:07]: Yeah.Akshat [00:26:07]: Like, you want your. They're running sandboxes and model. They want them to be right next to aSwyx [00:26:10]: Yeah, it's easy thenAkshat [00:26:11]: YeahSwyx [00:26:12]: To. That is important in all those things. and so, like, you've accidentally, I don't know if it's accident, but, like, you've built the perfect primitive for agents to express themselves. And then, like, it's almost very funny how every extra development just involves more file system, just involves more CPU.Akshat [00:26:30]: Yeah.Swyx [00:26:31]: Just like the things that you already have. I don't know much about, if there's any, like, networking usages that are interesting, but you've also done some good work on networking.Networking, Sidecars, Private IPv6, and SandboxesAkshat [00:26:40]: Yeah, that's exactly right. Like, we're just taking compute storage and networking and building stuff on that layer, for, again, the stuff people need.Swyx [00:26:49]: YeahAkshat [00:26:50]: We see a few interesting networking things coming up. one is people want networked sandboxes. so we haveSwyx [00:26:57]: For like a Docker cluster type thing.Akshat [00:26:59]: Yeah.Swyx [00:26:59]: Sorry, Docker Swarm. Oh, f**k. What is it called?Akshat [00:27:02]: Compose.Swyx [00:27:03]: Compose type thing.Akshat [00:27:04]: Yeah. So if you want Docker Compose, our sandboxes now support, this thing called sidecars. So you can. A sandbox is a pod of containers, and you can run multiple containers in, a sandbox. also useful because, going back to networking, people want a lot of control over, outbound networking from a sandbox.Swyx [00:27:23]: Yeah.Akshat [00:27:23]: Like, they might wanna run a middle proxy for, like, maybe logging stuff for RL or, controlling how egress can happen to a domain, injecting credentials. and yeah. So we've, we've had to build a lot of that stuff ourselves.Swyx [00:27:38]: Yeah.Akshat [00:27:39]: But then also sometimes people want, sandboxes spanning multiple nodes to talk to each other, which is an emerging thing we're seeing. We have support for that for a different reason, and yeah, we'll see if that becomes stable.Swyx [00:27:52]: Like, just an open socket. It's a. This is directly like mTLS.Akshat [00:27:56]: We do support that, which is you can, expose a tunnel inside a sandbox.Swyx [00:28:01]: Yeah.Akshat [00:28:01]: And then you can either expose it to public internet or it can be, you can add like a HTTP, auth layer above it. But we have this thing called I6PN, which we haven't talked about, which is this, like, overlay network using IPv6 addresses. so if Modal containers, within the same workspace, when this is enabled, can address each other using this private IPv6 address, and no one else can.Akshat [00:28:28]: So it's like private networking, for containers. We built it because we needed it as a primitive for our distributed training product. so we have this other feature, which is you can add a decorator to a function, and you get a cluster of GPUs. and they have RDMA networking. so you can run a distributed training job, that's truly serverless. and we did the overlay network for that. But then we've seen that people are using it for other reasons, and, I'm intrigued to yeah, what would people do with it.Swyx [00:28:59]: Build primitives and let people figure it out, right?Akshat [00:29:01]: Yeah, exactly.Swyx [00:29:02]: You put out a pretty interestingAkshat [00:29:03]: They're like, they read the docs webpage. Let me use thatSwyx [00:29:06]: YeahAkshat [00:29:06]: Something they never intended to work. This is literally not even in our docs page. People somehow found it, and they're using it.RDMA, Memory Movement, and Distributed TrainingSwyx [00:29:12]: Huh.Swyx [00:29:14]: The way you portrayed it with, like, RDMA versus TCP, like, very well laid out, but just the transfer speed change at scale for RL, like yeah, you have it, you have it built in. I'm sure someone found it. It's found it to be a lot more efficient before you made a thing out of it, right?Akshat [00:29:32]: Yeah. And not to split hairs, I guess the overlay network is the TCP overlay network.Akshat [00:29:39]: The reason we have that is you need that to do the key exchange for RDMA before you set up the RDMA network on top of that. but then people found the TCP part.Swyx [00:29:48]: Can I tell you, this is like a big aha moment for me becauseAkshat [00:29:51]: YeahSwyx [00:29:51]: So I review 2,200 submissions for the World's Fair.Akshat [00:29:56]: Yeah.Swyx [00:29:57]: And then I got this from John OsterhoutAkshat [00:29:58]: HuhSwyx [00:29:59]: Who I don't know if. Do John Osterhout by name?Akshat [00:30:01]: The name sounds familiar.Swyx [00:30:02]: He published a. He's a well-known professor, published a lot of interesting software design books, and this is the talk he chose to submit, is on RDMA at Inference. And I'm like, you wouldn't think that this guy, who is like operating systems guy, would care about RDMA.Akshat [00:30:20]: I, it makes sense to me because I,Swyx [00:30:24]: This is the cloud, right? YeahAkshat [00:30:25]: Like, the way you move around your KV cache and how efficiently you can do it, how efficiently you move, your weights from your training GPUs to your inference GPUs in RL is there's a lot of degrees of freedom, and it is a systems problemSwyx [00:30:41]: YeahAkshat [00:30:41]: Moving memory aroundSwyx [00:30:42]: YeahAkshat [00:30:43]: Scheduling.Swyx [00:30:44]: This shows you how primitive my understanding of networking stuff is.Swyx [00:30:46]: Is this like the domain of WireGuard as well?Akshat [00:30:50]: Not quite.Swyx [00:30:51]: It's adjacent?Swyx [00:30:53]: Explain everything.Akshat [00:30:54]: Sure.Swyx [00:30:56]: How do we move memory around GPUs?Akshat [00:30:58]: Well, so sorry. Yeah, that is memory. Sorry, I was talking more, and maybe I was talking like five minutes back, about the private IPv6, addressing that you've set up.Swyx [00:31:09]: Yeah.Akshat [00:31:09]: Is it like it's a VPN?Swyx [00:31:10]: Yeah, it is like a VPN, and yeah, WireGuard is, yeah, you're right. It is,Akshat [00:31:16]: Right. Yeah, you already moved on to new topicsSwyx [00:31:17]: A similarAkshat [00:31:18]: OkaySwyx [00:31:19]: In the same space, WireGuard is, encrypted and this is,Akshat [00:31:23]: And you don't need encryption.Swyx [00:31:23]: Yeah.Akshat [00:31:24]: Yeah.Swyx [00:31:24]: This is not encrypted. that's the main difference. This is TCP and we have eBPF programs that will reject or allow the TCP connection based on whether you're allowed to do it.Akshat [00:31:35]: Used to involve a full sidecar, but now you have eBPF in the Linux kernel.Swyx [00:31:39]: Yeah.Akshat [00:31:40]: Yeah. I don't know if this is a natural follow-on to the topic of like my skepticism on distributed training is that while, like, people spend a lot of money on, like, cables to hook up GPUs, and even that is not, like, fast enough, and that's the bottleneck, is your networking fast enough?Swyx [00:31:59]: Yeah. So I guess you're talking about fully distributed training like, Dialog or something which is like cross data centerAkshat [00:32:06]: That would be, yes.Swyx [00:32:07]: That's the extreme.Akshat [00:32:08]: Yeah.Swyx [00:32:08]: You're in the middle, and then other people would have like the Mellanox cables up in, like, their actual data center.Akshat [00:32:14]: When you run multi-node training on Modal, RDMA, I think Mellanox, is, or InfiniBand is like a, is all seen as RDMA. but it's a way to bypass the TCP networking stack and, transfer, stuff much faster, between one node, to the other. And we have I think like 3 terabit per second, internal networkingSwyx [00:32:40]: OkayAkshat [00:32:40]: Which is the standard that's needed.Swyx [00:32:42]: Okay. So I misunderstood whatAkshat [00:32:43]: 50Swyx [00:32:43]: What part of the stack you wereAkshat [00:32:44]: 50 gigs overSwyx [00:32:45]: YeahAkshat [00:32:45]: If you wentSwyx [00:32:45]: YeahAkshat [00:32:46]: RDMA.Swyx [00:32:46]: Okay.Swyx [00:32:48]: Yeah. I, very impressive work.Multi-Node Training, Post-Training, and Auto ResearchSwyx [00:32:52]: So effectively you're extending like the model philosophy to the training cluster, like, yeah.Akshat [00:32:59]: Yeah. And we're, we're not going for like large scale training runs. the thing that we've built multi-node training for is, we see a lot of, smaller scale post-training. like, people are post-training like medium sized fund models, so they can, get higher quality on inference. this is a perfect fit, for something like that.Swyx [00:33:21]: Yeah. That is my impression of how a lot of these labs explore branches in post-training and then eventually merge whatever they find in.Akshat [00:33:31]: Yeah. The other use case we've seen for multi-node training is even if you have a big cluster, your researchers are still doing small runsSwyx [00:33:38]: YesAkshat [00:33:39]: Having elasticity thereSwyx [00:33:40]: Right, sureAkshat [00:33:40]: Matters a lot more.Swyx [00:33:41]: Yeah. the, like, this is like the current limiting factor for auto research, which is like you need to give your model some GPUs in order for it to completely run.Akshat [00:33:51]: We have a blog post on auto resource and model is,Swyx [00:33:55]: YeahAkshat [00:33:56]: Yeah, like, turns out to be pretty good substrate for that.Swyx [00:33:59]: So my impression is auto research means many things, likeAkshat [00:34:01]: YeahSwyx [00:34:01]: Anything that Andrej coins. Right now it's still science fair, right? Like not like, I don't know how many people are doing this.Akshat [00:34:08]: We're having a golf.Swyx [00:34:08]: Yeah.Akshat [00:34:09]: I thought the same thing.Swyx [00:34:11]: Yeah, you would know.Akshat [00:34:12]: We, like, our internal both training and inference teams use this the general shape of this quite a bit. like we have this one internal repo called auto inference, which essentially we've automated our own forward-deployed engineering efforts using, this harness, which is, the agent will just spin up a sweep of different things. It'll even run like, NVIDIA inside profiler and it'll like tweak configs and it'll arrive the right thing. it'll change your GPUs both from H200 to B200, and works really well.Swyx [00:34:47]: Nice.Akshat [00:34:47]: So yeah.Swyx [00:34:48]: By the way, I enjoy that your forward-deployed engineering is so technical that you have to do these things.Swyx [00:34:52]: It's very different from forward-deployed engineering from other people.Akshat [00:34:54]: Yeah. For our forward-deployed engineering team is, essentially they're like applied inference researchers or applied training researchers.Swyx [00:35:02]: Someone told me like they have to be able to build, but they also have to be able to sell. do they have to sell or are they like they're good, they're just like post-sale type of thing?Akshat [00:35:09]: It does, being able to talk to a customer and engage effectively with themSwyx [00:35:13]: YeahAkshat [00:35:13]: Matters a lot.Swyx [00:35:14]: They want the same thing.Akshat [00:35:15]: Yeah.Swyx [00:35:15]: ?Akshat [00:35:15]: But it's it's not really a sales, thing. We pair them with-- We have solution architects as well that are more on the sales side.Swyx [00:35:23]: Okay. Let's spend a bit more time on auto research. This is a big focus for for this year. Where does this go? like, have people explored enough? Like, there's all these beautiful charts of like improve and then level off a bit and then you find the next thing. Is this one abstraction up from normal training? Is that how we think about it, or do you think about it differently? Like model level training versus high, like driven hyperparameter search.Auto Inference and Modal BenchAkshat [00:35:51]: Yeah, like,Swyx [00:35:51]: Someone, some people call it like neural architecture search or whatever, right? Like.Akshat [00:35:54]: Yeah, - So the stuff I've seen people do with it is nowhere on the architecture level. It's pretty much tweaking parameters, but it's it's a hyperparameter sweep that's guided by some model intuition, so it's like much more efficient than, whatever other, sweep you would have.Swyx [00:36:12]: Yeah, it's just, it's just a question of where you want to spend your compute?Akshat [00:36:16]: Right.Swyx [00:36:16]: ‘Cause yeah, you can just throw infinite amounts of money on this and somehow you'll bang out Shakespeare?Akshat [00:36:22]: Yeah, infinite monkey.Swyx [00:36:24]: Yeah, so like the very good for model. and I think it's also very important that agents can spin up other agents, can spin up their infrastructure. Like very good for you. how good is our LLMs at generating model code? Like the benefit of existing LLMs is that you are in the data.Akshat [00:36:42]: Yeah. They're, they're surprisingly good. I think like pre Cloud 4 they were not, and then now they're able to shot, stuff out of the box. But we're playing around with releasing like a Modal Bench for like the harderSwyx [00:36:55]: YeahAkshat [00:36:55]: Things, that the LLMs cannot do yet and maybeSwyx [00:36:59]: What's an example of that?Akshat [00:37:01]: I think the things that- Sometimes agents struggle with, without right guidance and a skill is, how to, use the rest of our observability. Like how to. Something is failing, like how do you look at the logs and then update the right thing? It's reasoning about that. But they're able to shot, likeSwyx [00:37:23]: Yeah. You can just add a skill to it?Compute Strategy and Capacity PlanningAkshat [00:37:26]: Yeah. So we have a Modal skill now that. Which is why we built this Modal Bench. It's to find things like that, so we can address them in our tool.Swyx [00:37:35]: Tune a skill. Yeah.Akshat [00:37:36]: Yeah.Swyx [00:37:36]: No. it's it's good. are you facing any shortages? like we talk a lot about GPU shortages, but also CPU, also memory.Swyx [00:37:44]: Yeah.Akshat [00:37:45]: We have had a lot of growth, which means that, there's - we've had to be much better aboutSwyx [00:37:53]: PlanningAkshat [00:37:54]: Proactive capacity planning.Swyx [00:37:55]: Yeah.Akshat [00:37:55]: So we have,Swyx [00:37:57]: Which by the way, like it's like a MBA's like dreamAkshat [00:38:00]: YesSwyx [00:38:00]: Is like just planning this stuff. I think last time you and I talked about something maybe about this.Akshat [00:38:03]: Yeah. we have a really competent team of people that we call, The role is called compute strategy. so yeah, if anyone listening here or wants to work on thatSwyx [00:38:13]: Compute strategy?Akshat [00:38:13]: Yeah.Swyx [00:38:14]: I think,Akshat [00:38:14]: I feel like,Swyx [00:38:15]: I think the normies call it FP&A or something.Akshat [00:38:18]: Well, it's more It's it's not FP&A. It's it's There's a lot of interesting financial questions of like what is the blend between one year and three-year reservations? how do we forecast our own capacity? how do we. especially since our capacity is very fungible across different GPU types and different regions, like you have to model a lot of it. and you also have to have an opinion on how the supply chain is gonna evolve, and then you have to like, take bets,Swyx [00:38:49]: YeahAkshat [00:38:49]: Based on that.Swyx [00:38:50]: Tokenomics.Akshat [00:38:50]: Yeah.Swyx [00:38:51]: This is like probably a not a real point, but, I was trying to think about like what other industries. I was trying to think about like, we cannot be first to like these kinds of problems.Akshat [00:38:59]: Yeah.Swyx [00:39:00]: And what other industries have had this? And I was like, airlines with fuel and like they have to hedge their fuel and like, I think for a long time Southwest because they made like a hero fuel bet, they like were like super low cost becauseAkshat [00:39:12]: OhSwyx [00:39:12]: Compared to everyone else.Akshat [00:39:14]: Yeah. I hadn't thought about that.Vibhu [00:39:16]: We're at a fun time too?Akshat [00:39:18]: Yeah. It's. A lot of the compute business in general, for us is also about being very good about capacity management. That is how you have great unit, economics. but also over time it's how you can unlock more value for customers. Like, one of the things we're building now is like a way for customers to get, If they don't care about latency, like get much cheaper pricing and they'll get results back in like next 24 hours or something, like a batch tier essentially.Batch Tiers and Latency-Insensitive WorkloadsSwyx [00:39:47]: Yeah.Akshat [00:39:47]: And those are levers we have because we control the whole stack and scheduling and whatnot to give people a sufficientSwyx [00:39:53]: Yeah. I feel like they're not as popular. Like those, like the Frontier Labs have all those APIs. They're not as popular as they should be.Akshat [00:40:00]: The demand that we see for something like that is not for LLMs. although sometimes people wanna run evals andSwyx [00:40:08]: OkayAkshat [00:40:08]: Synthetic data prep and there it makes sense.Swyx [00:40:10]: Okay.Akshat [00:40:11]: But it's from a lot of LLM companies, like people who are doing computational bio, like they have to run really big batch jobs and they don't care about when they get it back.Swyx [00:40:22]: Yeah. And like they have a reasonable. It's it's also like a cousin to the stopping problem of like, will this finish in time?Akshat [00:40:30]: Yeah. You can bound it.Swyx [00:40:33]: Yeah.Akshat [00:40:33]: Like you can give peopleSwyx [00:40:34]: YeahAkshat [00:40:34]: SLAs on it.Swyx [00:40:35]: Yeah. I think what's, what's interesting is like the next phase of model.Swyx [00:40:38]: Like what, do people expect from you, now that you're established and you're like well-known compute player among all these leading companies. You had an inference launch week, and we talked a little bit about the launches. like what else? Like what else should people know?What Modal Builds NextAkshat [00:40:55]: We are building primitives that make our users' lives much easier. So, I think for example, with LLM inference, thousands more companies are gonna post-train their own models and, deploy open source models for inference. so we're thinking a lot about what is the best product shape for that. And, that involves everything from our training gym to, then, endpoints that get frontier-level performance. again, but I haven't talked to anyone. It looks somewhat different on other verticals. Like, we're also seeing a lot of real-time, audio-video stuff in there, which is why like, we're working on things like regional routing, with fallbacks. So you can get GPUs that are as close to users as possible. so you get like low latency for video streaming and whatnot. And then on the agent side, it's,Akshat [00:41:52]: We're still working very closely with our customers because stuff is changing so fast in terms of what they need. And, I think beyond sandboxes and persistent file systems, there's a lot of other things people will need from this agent stack as they build production agents. So yeah, we're thinking about those other things that fit in there.Swyx [00:42:13]: I want to ask what the other things are.Akshat [00:42:15]: Yeah. I probably should share right now.Swyx [00:42:17]: I think-- I think, okay, so, I do think a lot about the principal components of cloud, and you do talk about compute storage networking.Akshat [00:42:25]: Yeah.Swyx [00:42:25]: Because so far for me, it's fine. so far for the. the first couple generations of cloud, it's fine. What's different, qualitatively different about agents that you need some new permission level? Like a lot of people, okay, and I'll just kinda spew tokens at you until it like hopefully sparks something.Akshat [00:42:43]: Yeah.Swyx [00:42:44]: Like the new level now is whatever Claude Code does, which is dangerously scope permissions or like allow list by command or like whatever, right? And sometimes they're like, “Well, okay, we have like this adaptive thinking mode where like, just trust me, bro. I will make the calls for you.” Is that it? like mediated permissions.Hard Guardrails vs. LLM-Mediated PermissionsVibhu [00:43:03]: Now you're looping it with a goal and letting it roll.Akshat [00:43:06]: Yeah, I'm, I'm skeptical of LLM media permission for stuff that is at the sandbox level because you do want hard boundaries.Swyx [00:43:16]: Yeah.Akshat [00:43:16]: Otherwise, someone can exfiltrate stuff.Swyx [00:43:20]: But likeAkshat [00:43:20]: YeahSwyx [00:43:20]: Maybe that's old school thinking. Maybe we're the dinosaurs.Swyx [00:43:23]: Maybe the AI OS or the LLM OS is really the kernel is a goddamn LLM.Swyx [00:43:30]: Like it makes you feel uncomfortable.Akshat [00:43:31]: Yeah, I'm, I'm toldSwyx [00:43:32]: But that's what trusting the LLM is. Like imagine a spherical cow perfect LLM.Akshat [00:43:36]: Right.Swyx [00:43:37]: That it.Akshat [00:43:39]: Maybe.Swyx [00:43:41]: I wanna test the boundaries, right?Akshat [00:43:42]: Yeah.Swyx [00:43:42]: Like, and I don't believe that, but I wanna see where I'm wrong ‘cause that's, that's the consensus.Akshat [00:43:49]: Yeah. I think you always need hard guardrails when you want, And you can pair those with softer guardrails, right? And that's gonna be a lot of mediated.Managed Agents and Specialized SandboxesSwyx [00:44:00]: There. I'll also get you a end with a couple of your commentary on like the ecosystem outside of Modal. Manage agents. Everyone has one. Gemini, OpenAI, Claude, very useful for you, but also like it is their way of starting to edge into your space.Akshat [00:44:17]: Yeah.Swyx [00:44:17]: What's going on?Akshat [00:44:19]: Yeah, we're, very excited to partner with Anthropic and some of the other foundation labs, will not name who we're also working with. the way we see it is the manage agent thing is a great place to start if you're starting out building an agent and, But then when you get to, building something more production grade, like you're a company that's like Ramp that's building their own, Ramp also runs their accounting agent on us, so their external-facing agent. You need a lot more control over, your compute primitive on things like, what sort - how do you persist different files that the agent has access to, and how do you snapshot and restore? How do you control the networking? maybe you want GPUs. When you get to that point, you kinda want, a specialized sandbox provider, that gives you those things, and that's the role that we are trying to play.Swyx [00:45:15]: YeahAkshat [00:45:16]: We don't really have an opinion on the harness, whether it runs - it's a cloud-managed agent, and you hook it up to Model Sandbox, or you run the harness in Model Sandbox. We'll see where people converge with that.Swyx [00:45:26]: Yeah. Do you any opinions on like the meta harnesses, or just another layer on top of these things?Akshat [00:45:31]: You mean like the OpenPipeSwyx [00:45:33]: OpenPipe is one. I think Vercel had one, which I can't remember the name of right now. Fredshot had one. and then, to me, most recently was Data Databricks that had Omnigen. All these are meta harness. Like it's kinda pseudo agent cloud type things.Akshat [00:45:50]: I personally have not played around with them.Swyx [00:45:53]: Yeah.Akshat [00:45:53]: Build agents with them.Swyx [00:45:54]: Everything's bullish Modal, as long as it consumes more infra.Akshat [00:45:57]: That's why we're focusing on the infra layer. It's somewhere where our, relative competence is and, also it's a hard problem to solve.Swyx [00:46:06]: Yeah. I will say like just generally reflecting on that, I don't know if - if there's other topics on Modal, but like just generally reflecting as an infra person, not as intense as you, but in that field, this has like been the most exciting time in infra. Like it was boring for a while, and you couldn't really get people excited about data infrastructure. Like Eric would get on Data Console, everyone just watched the video and like say, “Look at how many sandboxes I can spin up,” and no one gave a crap.Why Infrastructure Became Exciting AgainAkshat [00:46:39]: Yeah.Swyx [00:46:40]: And like now everyone gives a crap.Akshat [00:46:42]: That's true. It is a very exciting time, and I think a lot of that's driven by just the amount of scale all of this stuff needs.Swyx [00:46:50]: I think the, like a lot of your initiatives or a lot of your like product directions make sense in retrospect, which is like the best kind, but I wouldn't necessarily have thought about it myself, which.Akshat [00:47:00]: We need the predictions.Swyx [00:47:02]: I think there's a lot that you just don't even see, right? Like you have the batch, you have the voice, you have the multimodal, but what else?Akshat [00:47:10]: What else is coming up for usSwyx [00:47:11]: Yeah. Where do you see things going?Akshat [00:47:13]: Yeah. I, in generalBiotech, Robotics, and Non-LLM AI WorkloadsAkshat [00:47:15]: It's it's clear that there's there's a huge shift happening. I think one thing that's not as obvious to people because LLM inference gets talked about so much and is also we work a lot of companies that are, doing things like drug discovery and computational bio, like the Chai Discoveries of the world. Big things are probably gonna happen there. we work a lot of robotics companies that are putting robots in like active deployments and getting good results out of them.Swyx [00:47:45]: Is there Air Gap Modal? Is there a version that is like prem air gapped whatever?Akshat [00:47:50]: No. We,Swyx [00:47:51]: You should cloud only.Akshat [00:47:51]: Yeah.Swyx [00:47:52]: Yeah. Okay. But yeah, so what you're saying is like because you're focused on primitives and they're good primitives, you find use cases in all these kinds of things.Akshat [00:48:01]: Yeah.Swyx [00:48:01]: Probably diversifies you a little bit away from LMS all the time.Akshat [00:48:05]: Yeah, absolutely. We're, we'- our goal isn't to only serve the LLM inference market.Swyx [00:48:10]: There are a lot just on the website, the audio,Akshat [00:48:12]: Yeah. We said both onSwyx [00:48:14]: Computational bio images. Yeah, there's a lot here. There's QTA TTS, customizing. Oh, Chatterbox. there was customizing Whisper.Akshat [00:48:24]: Okay. Yeah.Swyx [00:48:25]: This screen reminds me of a fallen competitor, which Replicate.Model APIs vs. Differentiated AI ProductsSwyx [00:48:31]: What's your postmortem on what happened?Akshat [00:48:34]: This is one thing we've stayed away from is providing an API for models because I think providing model APIs is some of it ends up serving like a really hobbyist market, which is much less sticky.Swyx [00:48:50]: Yeah.Akshat [00:48:50]: And we've always wanted to build for companies that are building products and need more flexibility that's not just an API.Swyx [00:48:57]: Which you can build an API for a model and this is clearly what it is. But you - but what you're saying, you can wrap it into a more fully functioning back end that you run.Akshat [00:49:06]: Yeah. So all of our examples, it's not that spin up this model, here's an API token, use it. They're all code.Swyx [00:49:13]: Okay.Akshat [00:49:13]: And so the point is that this is just an example.Swyx [00:49:16]: Starter code.Akshat [00:49:17]: Yeah. But you can tweak it however you want.Swyx [00:49:20]: Yeah.Akshat [00:49:21]: And if you're like a company building a product, like, computational bio whatnot, yeah.Swyx [00:49:26]: I guess I'm trying to tease out for listenersAkshat [00:49:28]: YeahSwyx [00:49:28]: When does it stop becoming, oh, you're just an API call and you're just a wrapper on API to becoming what you call a product, right?Swyx [00:49:36]: Like, what is that layer? Like what-- Like, more lines of code, but like beyond that, what is the substance that people add that qualifies it to be something more?Akshat [00:49:46]: I think there's a little bit of like a selection effect of like a lot of the companies who do wanna get deeper into that level are probably building something that's more differentiated. And, I think, an example is like - with LLM inference, originally we, worked with companies that were building their own post-training frameworks or they were, - Ramp early in the day was training their own tokenizer and like swapping out the tokenizer in Llama and whatnot. I'm not saying that's, that successful, in that case. But a better example is like, let's say Suno. because Suno, does not use Modal for training.Swyx [00:50:26]: Mikey on the pod. Yeah.Akshat [00:50:27]: But they use Modal for all their inference and that's because they have like a custom-- They have completely custom model architecture and that means that they have to be at the code level and tweak things that are not, just an API.Swyx [00:50:41]: It's interesting as well, like we had, Ethan, most recently on the xAI Groq team make a prediction that like the next tier in video gen is not a better video model, it's a better model or agent that orchestrates video models.Video Agents and Production WorkflowsAkshat [00:50:56]: Oh, interesting.Vibhu [00:50:56]: Language model backbone that can use toolsAkshat [00:50:58]: RightVibhu [00:50:59]: And write code.Akshat [00:51:00]: Like, yes, I can make my second video or my second video from Groq, but I want my minute video.Akshat [00:51:06]: And I'm not going there through normal video gen.Swyx [00:51:10]: Yeah, that's interesting. I - So we have GPU sandboxes and recently have seen a few companies doing agents that do video manipulation or,Akshat [00:51:22]: Yeah. Give it FFmpeg and just do it.Swyx [00:51:23]: Run FFmpeg. But likeAkshat [00:51:25]: That's not enough.Swyx [00:51:25]: Yeah.Akshat [00:51:26]: You need to give it Adobe.Swyx [00:51:27]: Yeah, I hadn't put it together with like it would be a video production thing. in my mind these things were going more towards editingAkshat [00:51:36]: Yeah.Vibhu [00:51:36]: Well, shout out Mantis.Akshat [00:51:37]: I think about this a lot.Swyx [00:51:38]: .Akshat [00:51:41]: Yeah. Sorry.Vibhu [00:51:41]: Luma. Luma Agent is a version of this for video production, but it's a off.Swyx [00:51:46]: I was gonna get your quick takes, on some other stuff that happensGitpod/Ona, CI, and Runtime SandboxesSwyx [00:51:50]: In recent news and just-just see if you have anything interesting. Gitpod, very li

Joe Giglio and Hugh Douglas react to Zack Wheeler's 14-strikeout masterpiece against the Reds following his exclusion from the MLB All-Star Game. They debate whether Jesús Luzardo should offer his spot to Wheeler and admit they ranked the pitcher too low on the station's Top 11 list. Zack Wheeler himself calls the selection rules "BS" in post-game comments regarding his availability. 01:23 - Intro and Wheeler Performance 06:52 - All-Star Snub Debate 13:24 - Wheeler Blasts Selection Rules 20:49 - Caller Slams Top 11

-CBS Sports did a great list that we addressed earlier, starting with Notre Dame in the 1920s…but seeing Florida as the top team of the 2000s,Alabama the top team of the 2010s, and Georgia the tops of the 2020s shows how the B1G still has a long ways to go to get that kind ofdominance-Also---Nebraska was honorable mention in both the 70s and 80s---showing just how incredible that run of time was in the programAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Why your dominant hand seems better at almost everything Hand Dominance Is Driven by Practice, Not Birth Contact the Show: coolstuffdailypodcast@gmail.com Learn more about your ad choices. Visit megaphone.fm/adchoices

ESPN FC is up to react to another exciting day in the World Cup. France took care of Sweden. Kylian Mbappe just keeps scoring, and he is one goal behind Lionel Messi for the Golden Boot of the World Cup. Erling Haaland scored late to help Norway advance. They are set up for a date with Brazil. Do they have a chance? We also recap the Mexico vs Ecuador match before closing out with some predictions. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Welcome back to SANDCAST: Beach Volleyball with Tri Bourne and Travis Mewhirter, and welcome back to the Gstaad Elite, the greatest place on Earth. We're recapping an action-packed opening day in Gstaad, where: Trevor Crabb and Chase Budinger delivered an enormous day one, qualifying with a win over Adrian Heidrich and Yves Haussener and then handling Taylor Crabb and Andy Benesh with ease Tina Graudina continues thriving here in Gstaad, making the main draw with young Liv Ebere USA Volleyball's women so-so day, with three teams punching their main draw tickets and four bowing out Switzerland's young guns, Luc Fluckiger and Andrin Kolb upsetting the Grimalt cousins before ALMOST taking David Ahman and Jonatan Hellvig to three And more! SHOOTS! We have a NEW BOOK! Pre-order your copy of Volleyball for Dummies today at Barnes and Noble! Get 25 PERCENT off and FREE SHIPPING on all Mikasa products with our code, SANDCAST and play with the ball. played with the best in the game. Head to Mikasa's website and get your bag of balls today! Get 10 PERCENT OFF VBTV using our discount code, SANDCAST10 Want to get better at beach volleyball? Use our discount code, SANDCAST, and get 10 percent off all Better at Beach products!  Want SANDCAST merch? We got you covered. Check it out here! Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

--{ "Dominant Minority and Passive Majority vs Sentient Minority"}-- Detaching from the mainstream and the alternative - The choices we make - Casualties in a long war - Alan Greenspan - Anna Paulina Luna and interdimensional beings - Political routines, promises and "Something for Nothing" - Free flu shots - Differing scripts for each age group - John Edwards speech - MANDATORY Health Care - "Preventative" and "Mental Health" Care - Psychological evaluations - Cradle to Grave - (Permanent) Income Tax - "Temporary" War Tax of Britain - Loopholes for elite - Lawyers-Liars - The "New Freedom" - Good Reasons and Real Reasons - Schmucks - National DNA databases - Criminal, medical blood samples - Information collection, Law enforcement - Predictability for "safety" - Airport biometric scanning - Cashless society, system of punishment and reward - "Total Quality Management" - Problem of elite AND vast majority of population (Land of the Dead) - Democracy to force minority to conform - Governance, Government - Good slaves. Groups and organizations - Conformity, sameness, gregariousness - Intolerance of individualism - Animating force of Spirit. Creatures of instinct (earth bound) - Compassion is a survival mechanism - Global government; Scientific dictatorship under "Benevolence" - Mindset of passive compliance, content to be happy slaves - Mind Control for the Masses. Article: "Judge Wants Everyone in U.K. on DNA Database" by James Orr, Sept. 5, 2007 Guardian Unlimited)

Shohei Ohtani and rookie catcher Dalton Rushing couldn't seem to get on the same page early in Wednesday's start... and it led to one of the most frustrating innings of Shohei's season. Then everything changed. In this week's 'This Week in Shohei Ohtani News', we break down the miscommunication between Ohtani and Rushing, Shohei's postgame comments explaining exactly what happened, and how he responded by striking out the side and dominating the rest of the game. We also discuss: ⚾ Shohei averaging 100 MPH for the first time in his MLB career ⚾ The fastest pitch of his career (101.7 MPH) ⚾ Another dominant start (6 IP, 2 ER, 8 K) ⚾ Six home runs in his last 12 games ⚾ Becoming a father of two and his first comments after welcoming his son ⚾ Why Shohei continues to prove he's the most incredible player baseball has ever seen. If you enjoyed the episode, don't forget to like, subscribe, and leave a comment! Did the Shohei Ohtani frustration with Dalton Rushing surprise you? #ShoheiOhtani #Dodgers #MLB #Baseball #ThisWeekInShoheiOhtaniNews #DaltonRushing #大谷翔平 Timestamps: 0:00 Intro 0:16 Ohtani vs Rushing Frustration 3:15 Performance vs Twins 5:20 Rushing Struggles 7:42 Shohei Pushing Through Pain 9:35 Postgame Comments 10:54 Shohei Offense 13:38 New Dad x2 15:08 Outro Learn more about your ad choices. Visit megaphone.fm/adchoices