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Monitor engineer Kevin “KG” Glendinning joins you live from a Roman amphitheater in Pula, Croatia: eight countries in seven days into the Lorde world tour…and he’s got the receipts. You’ll hear how fifteen trips through the SNL stage started with a Carson Daly taping, why the rooms that treat you well are the rooms you remember, and what happens when a 32-year veteran finally plugs in a source expander and realizes the “new guys” were right. That’s the through-line: always be learning, always be open-minded, and never let a get-off-my-lawn attitude about new tech be the reason your phone stops ringing. Then it gets into the real in-ear monitor conversations: recreating a Celestion cab with a 2.6mm armature, the one-ear trick that quietly costs Adam Levine and John Mayer another 25% of volume, and why ear fatigue deserves the same respect a pitcher gives his arm. The road stories land hard from there. Super Bowl XLV in Dallas with snow, the Black Eyed Peas, and a lesson in letting the pros run their own show. Red Rocks (aka “Wet Rocks”) and why a mountain full of shuttle trucks is worth every minute. A locked-up console mid-residency and telling Christina Aguilera the audio will come back, all while genuinely hoping it would. A charter plane struck by lightning over the Amazon, an emergency landing at a decommissioned airfield, and waking up to the news about Taylor Hawkins. Plus the covert phone call that became seven years with Justin Timberlake, and the soft ask years earlier that made it happen. Rehearse enough that nerves turn into muscle memory, thank the people who opened doors for you, ask for the gig you want…and Always Be Performing. 00:00:00 Gig Gab 549 – Monday, August 31st, 2026 August 31st: Eat Outside Day Guest co-host: Kevin Glendinning 00:02:38 Pula, Croatia. 8 countries in 7 days 00:04:36 SNL stage for The Deftones with the Carson Daly show 00:06:20 Making an impression on touring musicians with 00:08:35 Always be learning about the new tech Learning from the “new” guys Neve 5045 Primary Source Expander Waves PSE Plugin Digico Mustard Source Enhancer 00:13:55 Always be open-minded 00:18:57 Mixing ears and the respect of it all 00:21:02 Chris Rabold mixing monitors for REM 00:22:06 Now some REM stories 00:24:23 Helping get Adam Levine & John Mayer through ear fatigue with one ear monitor 00:26:46 OzFest System Engineers and hearing fatigue 00:27:45 Sometimes it just doesn't sound right 00:30:44 Super Bowl in 2011 in Dallas…with snow! And The Black Eyed Peas 00:35:45 Being rehearsed enough to just do the gig (and fix what goes wrong when it goes wrong) 00:36:25 Lorde's large-and-resilient fanbase 00:39:21 Working Red Rocks..”Wet Rocks” 00:44:33 Christina and the reboot “Don't worry…the audio will come back.” Dave's issue with the Mackie DL32S losing input signals 00:49:58 Batteries Matter 00:52:31 Miley Cyrus, Taylor Hawkins, Lightning-stuck aircraft, oh my! 00:56:28 Getting paid to see the world The pros and the cons 00:59:11 The “covert” phone call… and Justin Timberlake Get to know ML who works for ShowCo Ask for the gig you want (and, specifically, ask Anthony Giordano) The Victoria's Secret Awards! Watching Muse with Justin 01:06:11 Have gratitude for everyone who you've worked with 01:08:14 Kevin wants to answer your questions! 01:09:52 Gig Gab 549 Outtro Follow Kevin Glendinning IG: @kev_chitown LinkedIn: Kevin ‘KG' Glendinning Contact Gig Gab! @GigGabPodcast on Instagram feedback@giggabpodcast.com Sign Up for the Gig Gab Mailing List The post Ask for the Gig You Want: Kevin Glendinning on SNL, Super Bowls, and 25 Years on the Road – Gig Gab 549 appeared first on Gig Gab.
Three segments on the Harness Players Podcast this week with a Grand Circuit card at Woodbine Mohawk Park on Saturday Night. Driver Tyler Moore stops in for an interview on Detonator Hanover who is the ML favorite for the William Wellwood Memorial Final. Mikee P. sits down with Edison Hatter for a look at the $5 Pick 3 on Saturday Races 5,7,9 with a 15% Takeout. Ray Cotolo drops by to dissect Race 12 and the Mandatory Payout High 5 with a $200,000 Carryover.
00:00-20:00: ML says the Orange defense could be potentially explosive in 2026. Thanks to CH Insurance and Batavia Downs Gaming. Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.
00:00-20:00: ML says the energy is up with Joe Brady so far in Bills land. Thanks to Ken's Auto Detailing and Marz Motors. Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.
00:00-15:00: How much will Kyle Allen help Josh Allen as the backup? ML breaks it down. Thanks to CH Insurance and Marz Motors. Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.
For the next several weeks, we're sharing exclusive Q&A sessions from The Definitive Veterinary Extraction Protocol, recorded live during the July 2026 course. As a listener of The Vet Dental Show, you have a limited-time opportunity to purchase the complete course for $300 off before its official release. Learn more and enroll here: https://ivdi.org/extract -- Host: Dr. Brett Beckman, DVM, FAVD, DAVDC, DAAPM -- In this episode, Dr. Brett Beckman answers practical questions about extraction workflow, anesthesia considerations, dental instrument maintenance, bur selection, suture materials, extraction site management, flap healing, and preventing postoperative dehiscence. He explains why the decision to extract and suture one quadrant at a time can have important implications for patient safety—particularly when anesthesia monitoring and dental staffing are limited. He also breaks down why bur design matters when creating a groove alongside a canine tooth, which needles and suture sizes he prefers for oral surgery, and how proper flap technique and postoperative protection can help prevent dehiscence. What You'll Learn in This Episode
00:00-15:00: ML wonders if Syracuse has a wide receiver room that is all of a sudden potentially explosive. Thanks to CH Insurance and Marz Motors. Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.
Mary Mallon became known as Typhoid Mary in the early 20th century. She has often been vilified in in modern references, though her story is actually quite complex. Research: "Mary Mallon." Encyclopedia of World Biography Online, vol. 21, Gale, 2001. Gale In Context: Opposing Viewpoints, link.gale.com/apps/doc/K1631007781/GPS?u=mlin_n_melpub&sid=bookmark-GPS&xid=23f34010. Accessed 3 Aug. 2026. Brooks, J. “The sad and tragic life of Typhoid Mary.” CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne vol. 154,6 (1996): 915-6. https://pmc.ncbi.nlm.nih.gov/articles/PMC1487781/ Brooks, Janet. “The Sad and Tragic Life of Typhoid Mary.” Canadian Medical Association Journal. Vol. 154, No. 6. 3/15/1996. Cutter, Laura. “Typhoid Mary/Mary Mallon: An Asymptomatic Carrier of Salmonella typhi.” National Museum of Health and Medicine. 6/18/2020. https://medicalmuseum.health.mil/micrograph/index.cfm/posts/2020/typhoid_mary_mary_mallon_salmonella “Research Starter: Typhoid Mary.” https://www.ebsco.com/research-starters/life-sciences/typhoid-mary Faherty, Anna. “The cook who became a pariah.” Wellcome Collection. 6/29/2017. https://wellcomecollection.org/stories/WsT4Ex8AAHruGfW_ Leavitt, Judith Walzer. “‘Typhoid Mary’ Strikes Back: Bacteriological Theory and Practice in Early Twentieth-Century Public Health.” Isis , Dec., 1992, Vol. 83, No. 4 (Dec., 1992). Via JSTOR. https://www.jstor.org/stable/234261 Leavitt, Judith Walzer. "Typhoid Mary: Captive to the Public Health." Beacon Press. 1997. Mallon, Mary. Letter to Dr. William H. Park. June 1909. Via PBS NOVA. https://www.pbs.org/wgbh/nova/typhoid/letter.html Marineli, Filio et al. “Mary Mallon (1869-1938) and the history of typhoid fever.” Annals of gastroenterology vol. 26,2 (2013): 132-134. https://pmc.ncbi.nlm.nih.gov/articles/PMC3959940/ Mason, W.P. “Typhoid Mary.” Science. Vol. 30, No. 760. 7/23/1909. Via JSTOR. https://www.jstor.org/stable/1635174 Murtagh, Joseh. “David DeKok presents gripping, heartbreaking view into Ithaca’s 1903 typhoid outbreak.” Ithica.com. 4/11/2012. https://www.ithaca.com/visit_ithaca/david-dekok-presents-gripping-heartbreaking-view-into-ithaca-s-1903-typhoid-outbreak/article_943a556c-6b6d-11e0-92b9-001cc4c002e0.html New York Times. “Hospital Epidemic from Typhoid Mary.” 3/28/1915. New York Times. “HOSPITAL EPIDEMIC FROM TYPHOID MARY; Germ Carrier, Cooking Under False Name, Spread Disease in Sloane Institution. CAUGHT HIDING IN QUEENS Blamed for Twenty-five Cases of Fever Among Doctors and Nurses -- Now In Quarantine.” 2/28/1915. https://www.nytimes.com/1915/03/28/archives/hospital-epidemic-from-typhoid-mary-germ-carrier-cooking-under.html?eafs_enabled=false Ogan, ML. “Immunization in a Typhoid Outbreak in the Sloane Hospital for Women.” New York Medical Journal. 3/27/1915. 609-610. Othman, Amani and William W. Darrow. “The Wall, the Ban, and the Objectification of Women.” The International Journal of Social Quality, Winter 2019, Vol. 9, No. 2 (Winter 2019). https://www.jstor.org/stable/10.2307/26948452 Poczai P and Karvalics LZ (2022) The little-known history of cleanliness and the forgotten pioneers of handwashing. Front. Public Health 10:979464. doi: 10.3389/fpubh.2022.979464 Prabhu, Maya. “The tragedy of Typhoid Mary.” Gavi. 6/18/2021. https://www.gavi.org/vaccineswork/tragedy-typhoid-mary Pusey, Allen. “Precedents.” ABA Journal. Vol. 104, No. 3. March 2018. Via JSTOR. https://www.jstor.org/stable/10.2307/26516280 Sawyer, Wilbur. “The Efficiency of Various Anti-Typhoid Vaccines.” Journal of the American Medical Association. Vol. LXV, No. 17. 10/13/2015. Soper, G A. “The Curious Career of Typhoid Mary.” Bulletin of the New York Academy of Medicine vol. 15,10 (1939): 698-712. https://pmc.ncbi.nlm.nih.gov/articles/PMC1911442/ Soper, George A. “The Curious Career of Typhoid Mary.” Read May 10, 1939 before the Section of Historical and Cultural Medicine. Bulletin of the New York Academy of Medicine. Vol. 15, No. 10. October 1939. https://pmc.ncbi.nlm.nih.gov/articles/PMC1911442/ Soper, George A. “Typhoid Mary.” The Military Surgeon. Vol. XLV. No. 1. July 1919. Soper, George. A. “The Work of a Chronic Typhoid Germ Distributor.” Journal of the American Medical Association. Vol. XLVIII. No. 24. 6/15/1907. Teicher, Amir. “Typhoid Mary Was Not a Super-Spreader (and Super-Spreaders Are Not "Typhoid Marys").” American journal of public health vol. 113,12 (2023): 1249-1253. doi:10.2105/AJPH.2023.307434 See omnystudio.com/listener for privacy information.
00:00-15:00: ML says the bullseye is on the back of the Buffalo Sabres this coming season. Thanks to CH Insurance and Batavia Downs Gaming and Western OTB. Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.
Richard Entrup is unusual in quantum circles: he's not a physicist, and he doesn't pretend to be. He spent decades as a CIO, CTO, CDO, and CISO at organizations including Verizon, Christie's, Disney/ABC, Time Warner, and Tiffany & Company before joining KPMG to lead its Emerging Solutions practice. That background — deep operational experience on the client side — shapes everything about how he thinks about quantum. He's not selling a hardware roadmap; he's thinking about what it actually takes to get a large, complex organization to change its cryptographic infrastructure before a threat materializes.The conversation matters now because the signals are accelerating. NIST has finalized its first post-quantum cryptography standards, executive orders in the US are pushing federal agencies toward PQC migration, and the algorithmic efficiency gains that reduce the qubit threshold for breaking RSA-2048 keep coming. Listeners who work in enterprise technology, cybersecurity, or quantum strategy — or who advise organizations that do — will find Entrup's practitioner perspective a useful counterweight to the more hardware-focused conversations that dominate the field.What We Get IntoWhy Q-Day's exact date is the wrong question — and why the more important issue is how long it will take enterprises to even inventory their cryptographic exposure, let alone remediate itThe scale of the cryptographic migration problem, including why a single laptop may contain hundreds of individual cryptographic components and why upstream/downstream API dependencies make this a supply-chain-wide challenge, not just an internal IT projectWhy "harvest now, decrypt later" creates urgency today, regardless of when fault-tolerant quantum computers arrive — and how compliance and regulatory timelines interact with that threat modelWhat crypto agility actually means in practice — moving from a "set it and forget it" cryptographic posture to a dynamic, continuously monitored framework, including the pressure SSL certificate renewal windows are already creatingHow KPMG built its PQC practice, incubated it within the firm, and handed it off to the cybersecurity advisory team as a core service offeringThe "good quantum" side of the ledger — how KPMG's emerging research function is approaching quantum computing as a source of competitive advantage, not just risk, and what sectors are furthest along in exploring itThe AI-quantum convergence, including Entrup's observation that AI is already being used to read and crack code — and what that means for the urgency of cryptographic modernizationWhy the enterprise quantum opportunity still has a long tail, and how the current moment compares to the early infrastructure phase of the internet — when everyone was talking about TCP/IP and DNS, not Uber or NetflixResources & LinksGuest & OrganizationRichard Entrup — Worth Magazine Profile — Career arc from CIO/CISO roles at major global brands to KPMG's Emerging Solutions practiceKPMG Quantum Dawn (2025) — KPMG's enterprise quantum readiness hub, introducing the Q-PREP framework and PQC implementation services, with Entrup as named leadReports & ResearchKPMG — "The Quantum Threat Is No Longer Theoretical" (2026) — The threat brief discussed in this episode, charting the rapid decline in qubits needed to crack RSA-2048 and urging immediate PQC migrationKPMG — "From Theory to Impact: Real-World Results in Quantum Machine Learning" (2026) — KPMG's joint report with IBM and Kipu Quantum on measurable quantum ML results on real hardwareKPMG — "Prepare Now for Quantum Cyber Risk" — Board Leadership Article (2026) — C-suite and board-level guidance on integrating quantum risk into enterprise oversightarXiv — "Quantum-enhanced satellite image classification" (2026) — The underlying research paper behind the KPMG/IBM/Kipu Quantum ML resultsEcosystem & EventsChicago Quantum Exchange — KPMG Joins CQE (October 2024) — Announcement of KPMG's formal CQE membership, referenced in the episode as part of the firm's ecosystem-building strategyKPMG 2026 Quantum Consortium — The inaugural KPMG Quantum Consortium event (March 2026, Orlando) discussed in the episodeIndependent CoverageQuantum Computing Report — KPMG joins Chicago Quantum Exchange (2024) — Independent coverage of KPMG's CQE partnership and enterprise quantum strategyQuantum Zeitgeist — Kipu Quantum satellite imagery coverage (Feb 2026) — Independent analysis of the KPMG/IBM/Kipu hybrid QML resultsKey Quotes & Insights> "It's not if but when. And it could be five years, could be three years, could be ten years. The fact is organizations are not gonna be ready. And that's the scary part." — Richard Entrup on Q-Day> "This is not just the CISO. This is gonna be the software engineering app dev guys. This is gonna be all your partners, upstream and downstream, who have to also be compliant — because if you change your crypto and they don't, that stuff's gonna break." — On why PQC migration is an enterprise-wide, supply-chain-wide problemInsight: Entrup draws a sharp distinction between the "bad quantum" (cryptographic risk requiring urgent defensive action) and the "good quantum" (competitive opportunity with a longer tail) — and argues that most organizations aren't adequately addressing either.Insight: The analogy to the early internet is deliberate: just as the 1990s were consumed with TCP/IP and DNS rather than the applications those protocols would eventually enable, the current quantum moment is still largely an infrastructure conversation — and that's normal, not a sign of failure.> "AI is expediting all of this. If AI is doing one thing, the use case is reading code and cracking it. That's pretty scary." — On the intersection of AI capability and cryptographic vulnerabilityRelated EpisodesEp. 81 — Quantum LDPC Error Correction with Larry Cohen and Paul Webster — Directly relevant: Cohen and Webster discuss how QLDPC error correction reduces the qubit overhead needed for RSA cryptanalysis, the technical underpinning of the threat timeline Entrup describesEp. 38 — Quantum Machine Learning with Jessic...
Diabetes Dialogue: Therapeutics, Technology, & Real-World Perspectives
Insulin-resistant patients with type 2 diabetes who require high-dose therapy have long lacked a rapid-acting option concentrated enough for compact insulin pumps. New pharmacokinetic data on an ultra-rapid U-500 insulin aspart, alongside additional phase 3 results for a combined once-weekly insulin icodec-semaglutide regimen, both aim to close persistent gaps in insulin delivery for this population. In this episode of Diabetes Dialogue, hosts Diana Isaacs, PharmD, and Natalie Bellini, DNP, reviewed two studies addressing unmet needs in insulin therapy for type 2 diabetes.The investigational agent AT278 is a highly concentrated insulin aspart formulated at 500 units/mL, distinct from existing U-500 regular human insulin, which behaves more like an intermediate-acting product. In a single-center, randomized, double-blind, crossover euglycemic clamp study spanning body mass index from 25 to 38 kg/m², AT278 produced significantly faster absorption and a greater glucose-lowering effect within the first hour versus both standard U-100 insulin aspart and U-500 regular human insulin. The ultra-rapid pharmacokinetic and pharmacodynamic profile held consistent across the BMI range studied.Current U-500 regular insulin requires dosing 30 minutes before meals while simultaneously serving as basal and prandial coverage, complicating use in automated insulin delivery systems and limiting compatibility with smaller-volume pumps. A concentrated, rapid-onset formulation could allow patients with high insulin requirements to use compact pumps and extended-wear infusion sets without the absorption problems tied to large-volume subcutaneous depots. Drawn from an early-phase study, the findings position AT278 as a potential first ultra-rapid option for prandial dosing in this population, though regulatory approval for pump use remains undefined.Separately, the phase 3 COMBINE 4 trial evaluated a fixed combination of once-weekly insulin icodec (Awiqli) and semaglutide, known as IcoSema, against once-daily insulin glargine U-100 in 485 adults with type 2 diabetes and baseline A1C above 8%. Over 40 weeks, IcoSema reduced A1C by 3.32 percentage points versus 2.44 points with glargine, a between-group difference of 0.88 percentage points, while producing a 0.79 kg weight reduction compared with a 3.81 kg gain with glargine. Time in range reached 79.8% with IcoSema versus 64.5% with glargine, consistent with the mechanistic rationale of pairing glucagon-like peptide-1 receptor agonism with basal insulin to limit postprandial excursions.These results build on earlier COMBINE 1 through 3 data, which showed IcoSema achieving noninferior or superior A1C reduction, superior weight outcomes, and lower hypoglycemia rates versus comparators. A single weekly injection combining basal insulin with a GLP-1 receptor agonist could reduce treatment burden and consolidate pharmacy copays, though semaglutide exposure remains capped by concurrent insulin titration, averaging 0.66 mg in COMBINE 4. Whether either agent reaches United States practice, including reported uncertainty around a domestic IcoSema launch, will determine their eventual role in managing insulin-resistant type 2 diabetes.
00:00-15:00: ML wants even more play-action in the Bills' offense. The preseason win over Carolina was a good start for Joe Brady and company. Thanks to CH Insurance and Marz Motors. Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.
00:00-20:00: Brian Higgins previews the Syracuse football season with ML. Thanks to CH Insurance. In your corner. Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.
Key Takeaways & Highlights Mammoth P Relaunch & Product Updates The Return: After stepping away in late 2022 and spending three years working with the Microbial Mass Pro team, Colin bought back and officially relaunched the Mammoth brand. ~70% Price Reduction: Streamlined, scalable manufacturing allowed Colin to drop the price by roughly 70% compared to legacy pricing, making it significantly more accessible for all growers. 3-Year Shelf Life: A subtle reformulation extends the active, non-spore liquid shelf life out to three full years. Application Rate: Continuous weekly applications at 0.6 mL per gallon throughout veg and bloom yield the best results across all substrates (living soil, hydro, coco, and rockwool). Mammoth P vs. Microbial Mass Pro Mammoth P: Uses active (motile), non-spore-forming bacteria selected directly from natural soil samples to liberate phosphorus and trace metals like iron. It is carried in an organic, alfalfa-derived liquid medium. Microbial Mass Pro: Uses dormant Bacillus endospores suspended in a clean, synthetic-like solution. While Bacillus spores require 24–48 hours to germinate once applied, active motile strains start functioning immediately upon contact with the root zone. The Power of Consortia Microbes in nature do not work in isolation. Multi-species consortia offer synergistic functionality (1+1+1+1 = 5, 6, or 7) and greater ecological adaptability across changing pH, moisture levels, and soil micro-pores than single-species products. Addressing Common Grower Myths Brewing into Compost Tea: Discouraged. Tank brewing introduces unpredictable competitive dynamics, risks losing the intended consortia balance, and isn't necessary given the product's concentration and price point. The Triacontanol Myth: Alfalfa meal is used strictly as a carbon and nitrogen source to feed the bacteria, undergoing heavy boiling and filtration to sterilize the media. Independent testing confirmed triacontanol levels were untraceable or present in negligible parts-per-billion amounts—it is not the driver of performance. Pathogen Concerns: Colin debunked rumors regarding human pathogens, explaining strain specificity (the same way safe E. coli strains differ from harmful ones) and highlighting full regulatory approval across international agricultural departments. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
Today we are talking with Vignesh Baskaran, the CTO and co-founder of Hexo Labs, about teaching AI agents to improve themselves. Vignesh has been training neural networks since 2012, back when he was still called a data scientist. Then he became an ML engineer and now an AI engineer, though he says the underlying work has never really changed. It's to figure out how to make a system behave the way you intend it to. He built the litigation search engine that Google itself became a customer of, and now he's chasing something new, agents that rewrite and retrain other agents without a human in the loop. We dig into Sia, the meta-agent at the center of Hexo's research, and why improving an agent means touching both its harness and its actual model weights, not just one or the other. We talk about proxy evals for when you don't have much to ground truth. The Darwin-Gödel machine and why formal verification is too strict a bar for anything commercial. How Hexo's work echoes DeepMind's Alpha lineage from AlphaGo to AlphaEvolve, and the spectrum from clearly verifiable to totally subjective tasks? Why VAE evals are quietly wrecking agent quality across the industry, and a great story about an agent that discovered a customer's own eval file was silently corrupted, something buried in hundreds of thousands of traces that no human would have caught.
We moeten het nodig weer hebben over dat vermaledijde schoonheidsideaal. Weten we nog dat het - pak ‘m beet - tien jaar geleden was, en dat alles en iedereen wegliep met body positivity? Magazines, reclames, social media, het werd steeds meer en steeds beter. We zagen die verscheidenheid aan lijven en dachten oprecht: the only way is up. Maar heeliedepeelie... anno 2026 is skinny helemaal hartstikke back, vliegen de fillers je om de oren en is Ozempic HOT AND HAPPENING. Onze monden staan open, onze kaken liggen op de grond te liggen en we zitten hier met de vraag: wat is hier gebeurd en komen we er ooit uit? Journalist en schrijver Tatjana Almuli zag dit alles ook met lede ogen aan, beet zich maar weer vast in die hardnekkige schoonheidscultus en het resultaat is haar ijzersterke essay ‘Tot lijf gemaakt’. Hoe komt het dat na die vette jaren (haha) nu de magere jaren (haha) weer de kop op steken? Wanneer was de omslag? Hoe? Waarom? En belangrijker: hoe komen we er definitief weer uit? Definitiever dan een permanente laser-ontharingsbehandeling, zeg maar. Verder in de aflevering: betekent activistisch worden automatisch dat je een risico loopt? En hoe weeg je dat af? Plus, ML en Nyd zijn flink aan het age-shamen, dat ook. Ga voor de shownotes en het transcript naar damnhoney.nl/aflevering-295DAMN, HONEY wordt gemaakt door Marie Lotte Hagen en Nydia van VoorthuizenIn deze aflevering hoor je advertenties voor NordVPN en onszelf: Profiteer NU van de exclusieve NordVPN-deal op nordvpn.com/damnhoney. Probeer zonder risico met de 30 dagen geld-terug-garantie! Steun ons vanaf 1 euro per maand op PetjeAf.com/DamnHoney. Jij krijgt toegang tot onze bonusafleveringen, wij kunnen blijven bestaan. Wat een deal! editwerk: Daniël van de Poppejingles: Lucas de Gier website: Liesbeth Smit DAMN, HONEY is onderdeel van Dag & Nacht Media. Heb je interesse om te adverteren in deze podcast? Neem dan contact op met Dag en Nacht Media via adverteren@dagennacht.nl.See omnystudio.com/listener for privacy information.
In this special DanceSpeak x No Starving Artists crossover episode, we sit down with Moncell Durden for a candid conversation about the International Dance League and some of the bigger questions its inception brings to the dance community. Through Moncell's perspective, we dig into what dancers can consider when new professional opportunities emerge, from sustainability and understanding contracts to asking better questions before signing on the dotted line. This isn't legal advice, but rather an invitation for dancers to think critically, stay curious, and better understand the opportunities in front of them. A thoughtful conversation about IDL that ultimately asks a bigger question: how can dancers become more informed participants in their own careers? Stay tuned and subscribe, as this is the first in a series! Learn more about the No Starving Artists Podcast https://nsadance.com/ Learn more about Moncell https://www.moncelldurden.com/
Hvis man vil finde lyden af en solformørkelse, hvordan vil den så lyde? Vil det være blød pop? Måske en stor strygekvartet? Eller vil det være benhårdt metal, der strømmede ud gennem højtalerne? Det har det danske metalband MØL givet deres bud på. Vi kigger også på solformørkelse gennem kunstens linse, hvor den flere gange er illustreret. Medvirkende: Nicolai Howalt, fotograf og kunstner. Dastan Marouf, musikskribent på GAFFA. Holger Dahl, Kunst- og arkitekturredaktør på Berlingske. Emilie Møllgaard, maskinsnedker lærling. Kim Song Sternkopf; tekstforfatter og forsanger i bandet MØL. Vært: Linnea Albinus Lande. Producer: Anders Skytte Agergaard. Redaktør: Lasse Lauridsen.
See the full Tiemacewe Bozo people group profile here https://joshuaproject.net/people_groups/15476/ML
Ovetta Sampson is a design researcher, AI leader, and founder of Right AI. She previously served as VP of ML and AI Platform Design at Capital One and worked at Google and IDEO. Ovetta brought that experience to the 2026 ITX Product + Design Conference, focusing her keynote on a question that often goes overlooked: what happens when people interact with increasingly powerful machines? To help us answer that question, Ovetta offers a pair of frameworks that center on human engagement risk, responsible AI, and rethinking how product teams design AI products. Building AI responsibly requires more than better models or more sophisticated tools. Product builders must also understand the cognitive, social, cultural, and physical risks that can emerge when humans interact with technology. AI inherits many of the biases embedded in the data used to build it, Ovetta says. So organizations need to rethink how disciplines collaborate; as the lines between traditional product, design, engineering, and security silos blur, responsible AI requires organizations to redesign not only their products, but also the processes used to create them. Here's what else we learned: Human Engagement Risk Belongs in AI Product Design Ovetta's human engagement risk (H-E-R) framework is based on a fundamental premise: technology can harm people when designers fail to account for how humans behave around machines. The H-E-R framework identifies cognitive, social, cultural, physiological, and community risks. These risks become especially important with generative AI, where people can easily attribute human qualities to systems that do not actually possess them. As a result, AI product teams must consider psychological and cognitive outcomes alongside traditional usability concerns. Ovetta cautions: “There are real dangerous risks when we engage with machines and don’t mindfully think about the outcomes that can happen when we don’t protect humans psychologically, cognitively, physically, and physiologically.” AI Strategy Starts With Executive Leadership Responsible AI also requires leadership decisions that extend beyond individual tools or experiments, Ovetta says. Many mid-sized organizations are hesitant to adopt AI because executives are concerned about intellectual property, trust, and data leaks. Meanwhile, employees may already be integrating AI solutions without an overarching organizational strategy. It's a disconnect that creates opportunity for leadership to establish clear priorities before adoption becomes fragmented. AI strategy starts at the top, Ovetta adds, because executives have the authority to establish the conditions under which technology gets developed and used. “Once the C-suite understands the risk to their shareholders, to their products, to their employees, to their customers, it is much easier for me to bring in the implementation of how to mitigate those risks.” Dismantling Silos Is Essential for Effective AI Development AI challenges the traditional handoff model in which designers, engineers, security, legal, compliance, and other teams work separately before passing projects along. Ovetta says AI development requires continuous cross-functional input instead. Her D-C-R framework – draft, critique, revise – organizes teams around development stages, bringing the right expertise into each phase. “Instead of saying, ‘I’m a designer' or ‘I’m a researcher,' or ‘I’m a product manager,' or ‘I'm an engineer,' we say, ‘I’m in the draft mode,'” Ovetta adds. “Each skill set in that move brings what they need to get that draft ready for critiquing, right? And so it’s something that I give to organizations and teams to try to reimagine how they actually do their jobs.” Ovetta Sampson is not arguing for less innovation with AI; instead, she's arguing for a different definition of responsible innovation – one that embeds human consequences, executive accountability, and cross-functional collaboration into the product development process itself. [03:10] Protecting the fragility of humanity. There are a lot of things us humans engage in, especially what I call the cognitive biases, that make engaging with machines and other automated systems that make it risky for us. [05:57] The H-E-R Framework. But what it really is, is there are five dimensions. There’s the cognitive, there’s the social, there’s cultural, there the physiological. And then the overall community risks that when humans engage with machines, that can happen. [10:08] LLMs built on ‘traumatized data sets.’ Generative AI has no moral code. It does not know truth or fact. And accuracy is not in its wheelhouse. In fact, it’s not in this training and it’s in its goals. So why when we type something into chat GPT, we expect truth back? I don’t know. [13:24] Protecting my values as a creator. That’s where I really want to start, because I don’t want to be a part of that. I don’t want to part of designing something that harms people. [14:00] I observed one reoccurring truth. Whatever is happening in the basement of a company starts in the C-suite. So if there is sexism, if there’s homophobia, if there racism, if there is bad culture, if it starts at the C-suite. Because the C-suite is the person who has the ultimate authority about what occurs in every floor of an organization. [18:26] The D-C-R framework — draft, critique, revise. The D-C-R framework is something I created because I was trying to explain to designers and product and engineers how their processes would change when they’re designing for and with AI. Each one of these disciplines should go through that makes the handoffs more like a circular iterative. The post 194 / Ovetta Sampson: Designing AI Products Around Human Needs – Not Just Technology appeared first on ITX Corp..
In this essential episode of the Prolonged Field Care Podcast, Dennis sits down with pediatric intensivist Dr. Sara Bibbens to tackle one of the most challenging and anxiety-inducing scenarios in austere medicine: pediatric burns. From initial trauma assessment using MARCH/ABCDE to nuanced airway decisions in small children, burn resuscitation formulas, fluid management pitfalls, hypothermia prevention, wound care, and safe pain/sedation strategies, this conversation delivers practical, downrange-applicable guidance every combat medic, flight medic, and austere provider needs.Key Takeaways:Stick to MARCH/ABCDE — don't get distracted by dramatic burns; treat life threats first.Pediatric airways swell faster — early intubation considerations (GCS
Aaron Kemp sits at an unusual intersection. He holds a doctorate in cybersecurity, spent years in DoD classified environments running SCI and SAP facilities, and now leads KPMG's quantum research practice — where he's a co-author on a recent hybrid QML paper with Kipu Quantum and IBM. He's also the lead author of KPMG's Q-PREP framework, which pushes enterprises to treat post-quantum cryptography migration as an operational risk problem right now.If you've wondered how quantum actually lands inside a Fortune 200 boardroom — not the hype cycle version, but the "what do you actually tell the CFO" version — this episode maps that territory honestly. It's also useful listening if you're trying to understand the emerging talent gap, why the quiet in enterprise research publications may itself be a signal, and how a firm known for audit and advisory ends up doing multispectral analysis of chestnut trees on IBM quantum processors.What We Get IntoWhy KPMG split quantum into distinct practices — PQC, sensing, optimization, and research — and what that structural choice signals about market timingHow a PBS documentary about the American chestnut tree led to a peer-reviewed quantum ML paper with Kipu Quantum and IBMThe honest case for a 3% accuracy gain over classical ResNet-50 baselines — and why Aaron treats it as a positive-sum signal rather than a victory lapWhy "what makes a good quantum problem" remains the most important question in the field, and how KPMG's client base shapes their answerThe seven-step Q-PREP framework for post-quantum cryptography readiness, and why step one — knowing what you actually have — is the hardest stepHow data-centric thinking (not cryptography-centric thinking) reframes the PQC migration challengeWhy the quiet in enterprise research publications from major financial institutions may itself be a market signalThe talent bottleneck: ~16,500 quantum researchers on the planet against a coming wave of enterprise demandHow AI tooling is compressing quantum research timelines, and what that means for who can enter the fieldWhy the compute stack of the next decade will be heterogeneous — quantum, neuromorphic, thermodynamic, and mechanical computing all coexistingResources & LinksGuest & OrganizationDr. Aaron Kemp — KPMG People Profile — Official bio covering Aaron's DoD/classified cybersecurity background and current role as US Quantum Leader.Papers & ResearcharXiv:2602.18350 — Quantum-enhanced satellite image classification — The peer-reviewed KPMG/Kipu Quantum/IBM paper Aaron co-authored, demonstrating hybrid quantum-classical accuracy gains on IBM processors.From Theory to Impact: Real-World Results in Quantum Machine Learning — KPMG's editorial summary of the satellite imagery research, framed for enterprise readers.From Theory to Impact — Full Technical Report (PDF) — The detailed technical companion walking through the hybrid pipeline step by step.PQC & Enterprise FrameworksQ-PREP: Seven Steps to Post-Quantum Cryptography Readiness (PDF) — KPMG's prescriptive PQC migration framework, with Aaron as lead author.The Quantum Threat Is No Longer Theoretical (PDF) — Aaron's board-level brief on Q-Day urgency.Prepare Now for Quantum Cyber Risk (KPMG Board Leadership Center) — Aaron's article for corporate directors, originally in NACD Directorship Online.Related Coverage & CommentaryKipu Quantum: Quantum-Enhanced AI Deployable in Production — Announcement of the production framework that removes quantum hardware from the inference loop; Aaron quoted as enterprise champion.KPMG's Seven Steps Build Quantum Resilience for Businesses (Quantum Zeitgeist) — Third-party coverage of Q-PREP.A Framework Can Tell You What to Do. It Cannot Tell You What You Have. (Qtonic Substack) — A critical response arguing that advisory frameworks don't solve the underlying cryptographic inventory problem — useful counterpoint reading.Key Quotes & InsightsOn the 3% accuracy gain: "It's a positive game… we did a 12–15 week sprint, and to at least meet classical was our goal when we started. So when we actually did get three percent, it was repeatable. That was, to me, okay — there's something there."On the real PQC problem: "We don't have a cryptographic problem. We have a data problem. None of these organizations know where their data flows."On cybersecurity as a discipline: "Cybersecurity is probably the worst career field ever because perfect cybersecurity has no ROI — because nothing happens."On enterprise timing: Insight: Aaron frames the quiet in financial services quantum research publications as a market signal — organizations may have stopped sharing because they're moving from research toward competitive advantage.On the talent gap: "There's 16,500 quantum researchers on the planet… Fortune 200 will hire 16,000." A single tier of enterprise demand could exhaust the global talent pool.Related EpisodesEpisode 14: A Hybrid NISQ-Classical Solution Architecture with Harry Buhrman — Foundational thinking on hybrid quantum-classical architectures relevant to the Kipu/KPMG/IBM approach.Episode 38: Quantum Machine Learning with Jessica Pointing — A rigorous look at the tradeoffs and open questions in QML that frame Aaron's satellite imagery results.Episode 81: Quantum LDPC error correction with Larry Cohen and Paul Webster — Directly relevant to the compressing resource estimates for breaking RSA that shape PQC urgency.Episode 86: Quantum Advantage Achieved with Dominik Hangleiter — A theorist's careful framing of what advantage claims should and shouldn't mean.Episode 40: Integrating Quantum Computers and Classical Supercomputers with Martin Schultz — Useful context on the heterogeneous compute future Aaron and Sebastian discuss at the end of the episode.Stay in the EcosystemSubscribe on
DNX LIVE REUNION TOUR WHEN????….Maddie and Elle are here to talk the first two episodes of the new idol rom-com “My Bias, My Boss”! While they always love idol shows (bonus points if there's a fake idol group - CHECK), they can't figure out if they can bias Lee Chan due to his high flirt levels LOL.....But, let's be real, this show might have the making for an A+, unserious, kdrama romcom. Chaotic FL? CHECKNon-celebrity ML in a 3-piece suit that she'll choose instead of the famous idol she thinks she loves? CHECK Secondhand embarrassment off the charts? CHECK CHECK CHECK….We hope you enjoy this Through Two, and let us know on our Discord channel if you're watching, too!!….“My Bias, My Boss” is airing on Mondays and Tuesdays this August and can be found on Viki….If you're new to YA GIRL, we're so glad you're here!! I truly hope you enjoy listening to this podcast! …..Also, check out our sister-pod - THE KDROP: A KPop Podcast - if that's your thing. https://www.instagram.com/the.kdrop_kpop_pod/ ….. Before you do anything else, FOLLOW YA GIRL ON INSTAGRAM! For real, please come and say hey to us over the socials! @yagirl_kdrama pod (https://www.instagram.com/yagirl_kdramapod?igsh=OGQ5ZDc2ODk2ZA%3D%3D&utm_source=qr)….And Christina runs an exclusive BTS instagram, so give that a follow! https://www.instagram.com/bts_express_the.kdrop?utm_source=ig_web_button_share_sheet&igsh=ZDNlZDc0MzIxNw== … Finally, jump on YA GIRL's Discord!! It's where all the friends of YA GIRL gather and talk about hot Korean men. You really don't wanna miss it. https://discord.gg/rFmEgTJpJ8
Today, we are taking a deep dive into an intervention that almost every labor and delivery unit in North America has adopted over the last decade: Quantitative Blood Loss, or QBL. ACOG first recommended quantitative blood loss assessment in Committee Opinion Number 794, published in December 2019. This opinion recommended that every birthing facility implement a standardized, quantitative method for measuring cumulative blood loss at all deliveries, replacing visual estimation as the default approach. This built on earlier ACOG efforts, including the 2015 reVITALize initiative, which standardized obstetric data definitions and defined postpartum hemorrhage using cumulative measured blood loss thresholds (≥1,000 mL regardless of delivery route, or blood loss accompanied by signs/symptoms of hypovolemia). We've all weighed sponges, measured calibrated drapes, and run the math. But here's the million-dollar question: Does measuring blood loss accurately, on its own, actually improve outcomes for patients? The answer is YES….and NO at the same time. Listen in for details as we discuss new data (July 2026 in AJOG) on this topic. 1. White A, Burns RN, Pruszynski JE, Ravindra D, Fin KX, Montgomery T, Jestes E, Ambia AM, Anyaehie B, Duryea EL. Establishing Normal Blood Loss Thresholds at the Time of Delivery Based on Quantitative Blood Loss. Am J Obstet Gynecol. 2026 Jul. DOI: 10.1016/j.ajog.2026.07.028. S0002-9378(26)00395-9. YMOB 16849.2. Quantitative Blood Loss in Obstetric Hemorrhage: ACOG COMMITTEE OPINION, Number 794.Obstetrics and Gynecology. 2019. Committee on Obstetric Practice3. Coomarasamy A, Devall AJ, Bell S, et al. Diagnosis and Treatment of Postpartum Haemorrhage: A Race Against Time. Lancet. 2026.
Rajiv Parikh talks with Andrew D'Souza about building Boardy, an AI superconnector that scales warm introductions while protecting its own reputation and the network's goodwill. We dig into why Boardy rejects SaaS norms, how the team trains an autonomous AI to say no, and what it takes to hire imaginative builders for an AI-native company.Boardy.ai: https://www.boardy.ai/• why reputation-weighted introductions beat open messaging• how Boardy works through phone calls, WhatsApp, and email instead of dashboards• using the film Her as a model for shared AI presence• go-to-market lessons from cold start growth and a crafted personality• training Boardy to preserve goodwill and push back on bad asks• combining ML engineers with character design to make the persona feel real• hiring framework focused on imagination, agency, and ambiguous problem solving• monetization paths through Boardy Pro and deeper funnel support beyond intros• managing disagreement when an autonomous AI brings data-backed recommendationsYour next breakthrough might be one introduction away, but most networking platforms confuse access with trust. We sit down with Andrew D'Souza, founder and CEO of Boardy, to unpack what it looks like to build an AI superconnector that behaves less like software and more like a principled relationship driven matchmaker. Boardy operates through live phone calls, WhatsApp, and email, making double opt-in warm introductions across a massive professional network while putting its own reputation on the line.We get specific on product design and go-to-market: why Andrew rejects the usual SaaS playbook, why he thinks the “agentic AI” label misses the point, and how the movie Her helped shape a shared AI that can be deeply present with thousands of people at once. From the cold start grind of getting the first 1,000 users to the craft of an Australian-accented persona, this conversation breaks down what actually creates adoption when the interface is simply a conversation.Then we dig into the hard problem: network goodwill. Andrew explains how Boardy learns to say no without alienating users, how it reasons about mutually beneficial outcomes, and how Boardy Pro pushes beyond introductions into real follow-through like scheduling, prep, and closing the loop. We also talk hiring for imagination over pedigree, treating AI like a teammate in standups, and what a symbiotic future with “a new species” could require from all of us. Subscribe, share this with a builder who cares about real connection, and leave a review so more founders can find the show.Andrew D'Souza: https://www.linkedin.com/in/andrewdsouza/Andrew D'Souza, the Founder and CEO of Boardy, an AI "super-connector" which recently raised its own $8 million seed round through autonomous pitching and even launched its own AI-led venture fund, Boardy Ventures. A serial entrepreneur, Andrew is perhaps best known as the former Co-Founder and CEO of the fintech unicorn Clearco. Before building his own unicorn, he served as the COO and CRO of Top Hat, President of Nymi, and an advisor to major tech players like Wealthsimple and Kik. Born in India before moving to Chicago and eventually the Toronto area, Andrew began his career as a Business Analyst at McKinsey & Company after earning his degree in Systems Design Engineering from the University of Waterloo. #ai #professionalgrowth #networking #entrepreneur #growth #sales #technology #innovatorsmindset #innovator #product #revenue #revenuegrowth #management #founder #entrepreneurship #company #process #processimprovement #value #valuecreationWebsite: https://www.position2.com/podcast/Rajiv Parikh: https://www.linkedin.com/in/rajivparikh/Email us with any feedback for the show: sparkofages.podcast@position2.com
Voice AI sounds simple until you try to deploy it at scale — across airports, accents, languages, and thousands of employees at once. In this episode of ServiceNow Insights, host Bobby Brill sits down with Midam Kim, an ML engineer and linguist at ServiceNow, to unpack what it actually takes to build voice AI as an enterprise product. From the out-of-vocabulary problem (why AI still struggles with names) to why turn-taking in conversation is a linguistic skill most people never think about, Midam breaks down the human science behind the technology. In this episode: - Why voice AI is replacing typing as the default way to interact with enterprise systems - The difference between building for employees (B2B) vs. building for their customers (B2B2C) - Why an airport is one of the hardest possible environments for voice AI — and what ServiceNow does about it - The "out-of-vocabulary" problem: why AI still struggles with names, accents, and rare expressions - Why ServiceNow's secret sauce is hiring linguists, not just engineers - The linguistic framework behind every voice interaction: sounds, words, and turn-taking - Why voice AI is like teaching a kid to speak for the first time Chapters00:00 — Welcome to ServiceNow Insights00:22 — Meet Midam Kim, ML Engineer & Linguist00:35 — Why voice is replacing typing01:48 — What voice AI actually does for employees03:40 — B2B vs. B2B2C: who's really using this?05:11 — Desk employee vs. airport traveler: two different problems06:42 — Building for an ever-changing environment08:53 — Why airports are the hardest use case09:54 — Accents, fluency, and the diversity problem11:20 — "My Name Is. My Name Is. My Name Is." — the OOV problem12:50 — The coffee shop name story13:20 — How ServiceNow trains its models14:59 — The 3 linguistic layers: sounds, words, interaction16:38 — Midam's turn-taking story from Korea18:33 — Why voice agents can't be "that person you avoid"20:16 — "We can make it great" Subscribe for more ServiceNow Insights episodes on AI, voice technology, and enterprise innovation. Related episode: Voice AI Agent Evaluation — how ServiceNow measures whether voice AI meets human expectations. https://youtu.be/x7Ks932T18o For more about voice in AI from Midam Kim - https://youtu.be/3NUf6W_FMWs?is=wGc7BfyhiDp8JlOW #VoiceAI #EnterpriseAI #ServiceNow #ArtificialIntelligence #Linguistics #ConversationalAI #AIProduct #PodcastSee omnystudio.com/listener for privacy information.
Voice AI sounds simple until you try to deploy it at scale — across airports, accents, languages, and thousands of employees at once. In this episode of ServiceNow Insights, host Bobby Brill sits down with Midam Kim, an ML engineer and linguist at ServiceNow, to unpack what it actually takes to build voice AI as an enterprise product. From the out-of-vocabulary problem (why AI still struggles with names) to why turn-taking in conversation is a linguistic skill most people never think about, Midam breaks down the human science behind the technology. In this episode: - Why voice AI is replacing typing as the default way to interact with enterprise systems - The difference between building for employees (B2B) vs. building for their customers (B2B2C) - Why an airport is one of the hardest possible environments for voice AI — and what ServiceNow does about it - The "out-of-vocabulary" problem: why AI still struggles with names, accents, and rare expressions - Why ServiceNow's secret sauce is hiring linguists, not just engineers - The linguistic framework behind every voice interaction: sounds, words, and turn-taking - Why voice AI is like teaching a kid to speak for the first time Chapters00:00 — Welcome to ServiceNow Insights00:22 — Meet Midam Kim, ML Engineer & Linguist00:35 — Why voice is replacing typing01:48 — What voice AI actually does for employees03:40 — B2B vs. B2B2C: who's really using this?05:11 — Desk employee vs. airport traveler: two different problems06:42 — Building for an ever-changing environment08:53 — Why airports are the hardest use case09:54 — Accents, fluency, and the diversity problem11:20 — "My Name Is. My Name Is. My Name Is." — the OOV problem12:50 — The coffee shop name story13:20 — How ServiceNow trains its models14:59 — The 3 linguistic layers: sounds, words, interaction16:38 — Midam's turn-taking story from Korea18:33 — Why voice agents can't be "that person you avoid"20:16 — "We can make it great" Subscribe for more ServiceNow Insights episodes on AI, voice technology, and enterprise innovation. Related episode: Voice AI Agent Evaluation — how ServiceNow measures whether voice AI meets human expectations. https://youtu.be/x7Ks932T18o For more about voice in AI from Midam Kim - https://youtu.be/3NUf6W_FMWs?is=wGc7BfyhiDp8JlOW #VoiceAI #EnterpriseAI #ServiceNow #ArtificialIntelligence #Linguistics #ConversationalAI #AIProduct #PodcastSee omnystudio.com/listener for privacy information.
Most apple cider vinegar on supermarket shelves is dead. Pasteurized. Filtered. Stripped of the mother, the enzymes, and the polyphenols that made vinegar a medical remedy for over 2,000 years — sold back to you at a 33-fold markup for what's essentially acidified water. In this episode, we make genuine raw, unpasteurized apple cider vinegar from scratch — for about 30 cents a batch. You'll learn the two-stage fermentation process, how to avoid mold and spoilage, and why homemade ACV is more biologically active than anything you can buy. ⏱ Cost breakdown: $10 vs $0.30 11:00 — Safety rules you must follow
Smart. Key. The core of a performance. While, on paper, it may not look like Kotaro Nishiyama will be key to any 2D music project he's a part of, the truth is, the groups he's a part of, without him, would sound completely unbalanced.Yes, Kotaro Nishiyama has a hidden power that he brings to his performances, and that has both made him essential for the 2D groups he's a part of and also, in his solo career, led to me labeling as a smart singer.Music suggestions:- ZOOL "4ROAR"- ZOOL "Stronger and Stronger"- QUELL "What do you see"- Kotaro Nishiyama "Time Machine"Thanks to M L for inspiring this series of episodes!
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
The ingredient people complain about the most is the single one that'll make the biggest difference in your skin — and no, it's not a retinoid or a fancy peptide. It's your sunscreen.This week we're getting into why SPF is the highest-leverage thing you can do for your skin (prevention is cheaper and easier than reversal), the difference between UVB and the UVA rays nobody talks about, chemical vs. mineral without the fear-mongering, what those "sunscreen in your bloodstream" studies actually found, and the new filter the FDA finally approved in June — what it is, and when you'll actually see it on shelves.No demonizing, no overclaiming. Just the nuance, from a friend who did the research so you don't have to.
Extrémna vlna horúčav ukázala reálny stav slovenských nemocníc. Kým pacienti mali v izbách vysoké teploty a nosili si vlastné ventilátory, minister Kamil Šaško vyhlásil, že klimatizácie nemajú prednosť pred obstaraním napríklad CT prístrojov. Mlčaniu štátu sa však mnohí ľudia nedokázali prizerať, a preto prevzali iniciatívu do vlastných rúk. Informovali sme o tom, že malá rodinná firma počas víkendu na vlastné náklady oblepila špeciálnymi fóliami celé oddelenie ružinovskej nemocnice, kde pacienti mali na izbách viac ako 42 stupňov Celzia, či o tom, že tri aktivistky sa rozhodli vyzbierať 380-tisíc eur na klimatizácie pre viaceré nemocnice.Po vlne kritiky ale aj solidarity pre nemocnice sa včera minister zdravotníctva za svoj výrok ospravedlnil a sľúbil nemocniciam 250 klimatizácií. Prečo by klimatizácia v nemocnici nemala byť nadštandardom a čo odhaľuje iniciatíva občanov, ktorí sa rozhodli nemocniciam pomôcť? Na podcaste spolupracovali Sophia Štefániková a Adam Obšitník.
What does it actually take to keep your body healthy through rehearsals, performances, flights, hotels, and the demands of life on the road? Athletic trainer Adam Quigley has supported artists and tours including Post Malone, Lorde, Tyla, Karol G, the Jabbawockeez, 5 Seconds of Summer, plus broadway tours like MJ the Musical and Moulin Rouge, helping performers care for their bodies through the unique physical demands of touring. In this conversation, Adam shares practical strategies for staying healthy on the road while challenging dancers to think of themselves as athletes. We discuss how to build a warm-up that supports the demands of dance, what to pack on tour, navigating time zone changes and travel fatigue, fueling your body while traveling, and why recovery deserves just as much attention as performance. Adam also shares his philosophy of care, explains why movement is medicine, and offers practical advice for preventing small issues from becoming bigger ones. The conversation also explores the physical and mental comedown after tour - something many dancers experience but rarely discuss, despite how important it can be for long-term health and performance. Whether you're touring internationally, teaching on weekends, traveling for work, or simply want to build a longer, healthier dance career, this episode is packed with practical tools to help you take better care of your body. Follow Galit: Instagram - https://www.instagram.com/gogalit Website - https://www.gogalit.com/ Fit From Home - https://galit-s-school-0397.thinkific.com/courses/fit-from-home Connect with Adam Quigley on Instagram - www.instagram.com/adamquigley Explore Adam's company website - https://blvperformancetherapy.com/ Listen to DanceSpeak on Spotify and Apple Podcasts.
00:00-25:00: ML says it may be the year for the Bills to just air it out on offense and see what happens. Thanks to CH Insurance and Batavia Downs Gaming. Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.
Третий выпуск подкаста об образовании. На этот раз — про ШАД, Школу Анализа Данных Яндекса: бесплатную двухлетнюю программу, куда, по словам самих выпускников, поступить сложнее, чем её закончить. Разбираемся, чем ШАД отличается от вуза и курсов, как устроен отбор и почему компания вкладывается в образование, за которое не берёт денег. Гости: Анжелика Пуминова, куратор ШАДа в Новосибирске, организатор совместной магистерской программы ПМОБД на ММФ НГУ. Наталья Баданина, методист академических программ ML-направления Яндекс ШАД. В выпуске: Что такое ШАД на самом деле: не вуз, не курсы и не совсем магистратура Кто идёт в ШАД: студенты, разработчики, учёные — и один из выпускников этого года старше 60 лет Нагрузка 30+ часов в неделю: как совмещают ШАД с работой, вузом и личной жизнью Как устроен отбор: анкета, тестирование, творческий экзамен и собеседование — и почему порог такой высокий при бесплатном обучении Из чего состоит программа: ML, инфраструктура больших моделей и классические алгоритмы Новое направление для учёных: как в ШАДе учат применять ИИ в естественно-научных исследованиях Как программа не устаревает: гибкие занятия и обратная связь от студентов после каждого курса Первый опыт студенческих поездок на конференции ICML и ICLR ИИ внутри самого ШАДа: эксперимент с проверкой домашних заданий, где решение остаётся за человеком Зачем Яндексу бесплатно готовить специалистов — и куда потом идут выпускники Учиться можно и без поступления: открытые материалы ШАДа и открытые интенсивы Гитхаб ШАДа Оставайтесь на связи Пишите нам: info@linkmeup.ru Канал в телеграме: t.me/linkmeup_podcast Канал на youtube: youtube.com/c/linkmeup-podcast Подкаст доступен в iTunes, Google Подкастах, Яндекс Музыке, Castbox Сообщество в вк: vk.com/linkmeup Группа в фб: www.facebook.com/linkmeup.sdsm Добавить RSS в подкаст-плеер. Пообщаться в общем чате в тг: https://t.me/linkmeup_chat Поддержите проект:
Третий выпуск подкаста об образовании. На этот раз — про ШАД, Школу Анализа Данных Яндекса: бесплатную двухлетнюю программу, куда, по словам самих выпускников, поступить сложнее, чем её закончить. Разбираемся, чем ШАД отличается от вуза и курсов, как устроен отбор и почему компания вкладывается в образование, за которое не берёт денег. Гости: Анжелика Пуминова, куратор ШАДа в Новосибирске, организатор совместной магистерской программы ПМОБД на ММФ НГУ. Наталья Баданина, методист академических программ ML-направления Яндекс ШАД. В выпуске: Что такое ШАД на самом деле: не вуз, не курсы и не совсем магистратура Кто идёт в ШАД: студенты, разработчики, учёные — и один из выпускников этого года старше 60 лет Нагрузка 30+ часов в неделю: как совмещают ШАД с работой, вузом и личной жизнью Как устроен отбор: анкета, тестирование, творческий экзамен и собеседование — и почему порог такой высокий при бесплатном обучении Из чего состоит программа: ML, инфраструктура больших моделей и классические алгоритмы Новое направление для учёных: как в ШАДе учат применять ИИ в естественно-научных исследованиях Как программа не устаревает: гибкие занятия и обратная связь от студентов после каждого курса Первый опыт студенческих поездок на конференции ICML и ICLR ИИ внутри самого ШАДа: эксперимент с проверкой домашних заданий, где решение остаётся за человеком Зачем Яндексу бесплатно готовить специалистов — и куда потом идут выпускники Учиться можно и без поступления: открытые материалы ШАДа и открытые интенсивы Гитхаб ШАДа Оставайтесь на связи Пишите нам: info@linkmeup.ru Канал в телеграме: t.me/linkmeup_podcast Канал на youtube: youtube.com/c/linkmeup-podcast Подкаст доступен в iTunes, Google Подкастах, Яндекс Музыке, Castbox Сообщество в вк: vk.com/linkmeup Группа в фб: www.facebook.com/linkmeup.sdsm Добавить RSS в подкаст-плеер. Пообщаться в общем чате в тг: https://t.me/linkmeup_chat Поддержите проект:
00:00-15:00: ML likes the Orange's QB depth compared to last year. Thanks to CH Insurance and Batavia Downs Gaming. Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.
Robbie Deckard is a professional middle-distance triathlete and triathlon coach, and the founder of Freaky Fast Aero Accessories. In this episode, Robbie and Mikael dig into the real differences between American and European training methods, using lactate and VLaMax to optimise training and performance, and how age-group triathletes can apply lab-grade thinking to swim, bike and run training without actually going into a lab. HIGHLIGHTS AND KEY TOPICS: The real difference between FTP-centric American coaching and the German/Benelux style built around VLaMax, VO2max and physiological profiling. The evolution of VLaMax based training: from Alois Mader's 1970s model through Jan Olbrecht to current day coaches like Dan Lorang. Robbie's case for still doing dedicated VO2max work, including a case study that took an amateur cyclist's VO2max from 74 to 87 mL/kg/min over 58 weeks of block periodisation. Why building maximal aerobic power early is more valuable long-term than chasing threshold gains, and how that shapes the "durability" that separates junior and U23 cyclists from senior professional cyclists. How Robbie profiles athletes using LT1, LT2 and 5-minute power (or 500 yd swim time, or mile run time), and what typical percentage utilisation looks like for age-groupers versus elites. How he prescribes endurance, threshold and VO2max sessions in practice, including cues (power, pace, RPE), lactate targets, and why exact wattage precision on threshold work matters less than people think. Practical advice for age-groupers: open-water swim skills and ankle-band drills, running road races for pacing and durability, and hill running for strength and economy. Improving aerodynamics on a budget: reduce frontal area first, then refine airflow, and how to measure progress without a wind tunnel using Golden Cheetah or a simple speed sensor. SHOWNOTES, LINKS, RESOURCES AND RELATED EPISODES: Follow Robbie Deckard and Freaky Fast Aero Accessories on his website, blog, Instagram, and Freaky Fast Aero Accessories' Instagram. The shownotes for today's episode can be found here. The full podcast episode archives (including category filters) can be found here. A Scientific Approach to Improve Physiological Capacity of an Elite Cyclist - Rønnestad & Hansen 2018 FTP, VO2max and VLaMax with Sebastian Weber | EP#169 VLaMax, Polarised training, Fatigue and Complexity with Mark Burnley, PhD | EP#331 Training talk with Sebastian Zeller | EP#259 Training structure, periodisation and the science of winning with Jan Olbrecht, PhD | EP#198 Training, testing, metabolism and physiology with Björn Kafka | EP#286 Kolie Moore – Overrated and Underrated Factors for Cycling Performance The Science of Winning: Planning, Periodizing and Optimizing Swim Training - book by Jan Olbrecht The Triathlete's Training Bible - book by Joe Friel Software mentioned: Aerotune, Golden Cheetah, INSCYD, Sentiero SPONSORS: Precision Fuel & Hydration produce our favourite gels, sports drinks, and electrolyte and carbohydrate products here at That Triathlon Show and Scientific Triathlon. Use the free Fuel & Hydration Planner to get a personalised plan for your carbohydrate, sodium and fluid intake in your next event, and get 15% off your first 2026 order by using the code TTS2026 at checkout. Rouvy is hands down the most complete indoor cycling platform for triathletes. Among their thousands of beautiful bike courses from all around the world, all filmed in stunning quality, they have over 75 IRONMAN and IRONMAN 70.3 race courses plus 20+ Challenge Family courses, so you can pre-ride your race from home. Real gradients, real visuals, and real feel! Head to rouvy.com and use the code TTS to get your first month free on top of a 7-day free trial. Effortless Swimming produce the best swim goggles for triathletes and open water swimmers. Their NanoClear anti-fog lenses give you clear, fog-free vision that lasts and doesn't wear off. Don't let foggy or leaky goggles ruin another swim. Go to shop.effortlessswimming.com and use the code TTS15 to get 15% off your goggles, and get a free two-month Effortless Swimming course membership. ZenAI is the next frontier of podcasting. It lets you turn your ideas into a podcast without any knowledge of audio editing, video, or production. You do the talking, and the AI handles the production, editing, clipping, and the rest, and you can direct your AI producer in plain English. You can even record from your phone, so no expensive studio gear is needed to sound great. ZenAI is a new product from Zencastr, a platform I've been a paying customer of for over nine years here at That Triathlon Show. ZenAI is currently in invite-only beta. Join the waitlist today here.LEARN MORE ABOUT SCIENTIFIC TRIATHLON: The Scientific Triathlon website is the home of That Triathlon Show and everything else that we doContact us through our contact form or email me directly (note - email/contact form messages get responded to much more quickly than Instagram DMs)Subscribe to our NewsletterFollow us on InstagramLearn more about our coaching, training plans, and training camps. We have something to offer for everybody from beginners to professionals.HOW CAN I SUPPORT THAT TRIATHLON SHOW (FOR FREE)? I really appreciate you reading this and considering helping the show! If you love the show and want to support it to help ensure it sticks around, there are a few very simple things you can do, at no cost other than a minute of your time. Subscribe to the podcast in your podcast app to automatically get all new episodes as they are released.Tell your friends, internet and social media friends, acquaintances and triathlon frenemies about the podcast. Word of mouth is the best way to grow the podcast by far!Rate and review the podcast (ideally five stars of course!) in your podcast app of choice (Spotify and Apple Podcasts are the biggest and most important ones).Share episodes online and on social media. Share your favourite episodes in your Instagram stories, start a discussion about interesting episodes on forums, reference them in your blog or Substack. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
00:00-15:00: ML says it's time for Dalton Kincaid to finally break out and the Bills need big stuff from the tight end room overall in 2026. Thanks to CH Insurance and Batavia Downs Gaming. Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.
Dive into the evolving role of AI in design and collaboration as Danny Wu, Head of AI Products at Canva, shares insights on how the platform is transforming creative workflows, democratizing design, and leveraging large language models and diffusion techniques.In this episode:How Canva redefined abstraction layers in design, moving from pixel edits to object-based workflowsThe evolution of AI at Canva: from traditional ML to transformers and large language modelsThe impact of ChatGPT integration on Canva's user experience and business growthAgentic AI: Canva's approach to AI that acts as a collaborative partner in designChallenges and misconceptions about AI generative models in creative industriesFuture plans: video content tools and more AI-powered featuresTimestamps:00:00 - Introduction to Canva's innovation in abstraction layers01:12 - Danny Wu's background and journey at Canva02:46 - Transition from software engineer to Head of AI Products04:25 - How diffusion and large language models accelerate Canva's AI capabilities06:50 - The dominance of transformer models in Canva's AI strategy08:51 - Shift from pixel to object, then conceptual design with AI09:19 - Limitations of chat-based creativity vs direct manipulation11:01 - The future of design involving AI-generated, editable content13:30 - Launch of Canva AI and the platform's new architecture15:22 - Use cases and limitations of AI in visual and video content17:05 - Canva's diverse user base and how AI personalization fits different needs18:48 - Challenges of AI aesthetics and user customizations20:32 - Amazing AI features like Magic Layers for editable image designs22:16 - Comparing models: diffusion, open source, and proprietary tech27:36 - Exploring agentic AI: Canva's vision of AI as a collaborative partner30:37 - How ChatGPT and similar tools boost Canva's reach and usability34:26 - Personalizing AI output for users and reducing generated “cookie-cutter” content37:38 - Managing AI's creative style and avoiding homogenization42:39 - Canva's feature development process and testing workflows46:36 - Surprising use cases, like self-grading quizzes in education48:59 - Overlap and differentiation between Canva and other design tools like Figma50:54 - Future video tools and content creation enhancements at Canva
Disclaimer: This article is for educational purposes only and is not a substitute for individualized medical advice. Talk to your own physician before making decisions about cancer screening, testing, or treatment.TL;DR* A healthy 58-year-old gets a routine full-body scan, finds a “cancer” that would never have hurt him, and ends up with permanent incontinence from unnecessary treatment. This is more common than most people realize.* Dr. H. Gilbert Welch, a Dartmouth-trained cancer epidemiologist, spent 30 years documenting overdiagnosis — the discovery of cancers that meet the technical definition but would never have caused harm. His estimate: roughly 60% of PSA-detected prostate cancers and 25% of mammography-detected breast cancers fall into this category.* The “5-year survival rate” you hear cited as proof screening saves lives is often distorted by lead-time bias — finding a cancer earlier can make survival numbers look better without adding a single day to anyone's life.* Not all screening is suspect. Colonoscopy, low-dose CT for high-risk smokers, and cervical cancer screening (Pap/HPV) have strong randomized-trial evidence behind them.* The piece conventional screening misses: metabolic health. A 2026 Nature Communications study using machine learning on UK biobank data linked insulin resistance to increased risk across at least 12 cancer types — independent of body weight — and standard checkups rarely test for it.* Want a personalized look at your own metabolic terrain? Book a Metabolic Audit Call — link in show notes, spots limited weekly.The Test That Didn't Save His LifePicture a 58-year-old man. Healthy weight, active, doesn't smoke, feels completely fine. He goes in for a routine total-body scan — the kind now available at imaging centers with no doctor's referral required. Two hours later, a radiologist flags a small spot on his prostate.Six months, two biopsies, and one surgery later, he has a diagnosis: permanent incontinence. And the cancer itself? “Clinically insignificant.” It almost certainly would never have caused him harm. He would have lived out a full life and died of something else entirely, never knowing it was there.The test didn't save his life. It changed it — for the worse.This scenario happens thousands of times a year, and it's exactly what Dr. H. Gilbert Welch — a general internist, cancer epidemiologist, and senior researcher at Brigham and Women's Hospital — spent his career warning about. His book, Should I Be Tested for Cancer?, makes a case that runs against decades of public health messaging: more testing is not automatically better testing, and early detection does not automatically mean lives saved.This article unpacks what Welch got right, where his argument leaves a gap, and what a more complete, proactive approach to cancer risk actually looks like.The Cancer Reservoir: Why Finding More Doesn't Mean Saving MoreFor decades, the operating assumption in medicine has been simple: catch cancer early, save the life. No asterisk, no nuance.Welch's research complicates that. His central idea is the cancer reservoir — the observation that most people carry small clusters of abnormal cells somewhere in their bodies right now. In the prostate, thyroid, breast, or lung. Under a microscope, these cells look like cancer. But many of them will never grow, never spread, and never threaten a life. A person could carry one for thirty years and die at 87 of heart disease, never knowing it existed.The problem is that increasingly sensitive tools — full-body scans, PSA tests, low-dose CT — are very good at finding these dormant clusters. And once something is found and labeled “cancer,” the medical system is built to treat it.Welch's numbers, drawn from randomized trial data, are striking: approximately 60% of PSA-detected prostate cancers are overdiagnosed, meaning they meet the technical definition of cancer but would never have caused symptoms or death. For mammography-detected breast cancers, the estimate is around 25% — meaning roughly one in four women treated for a screen-detected breast cancer may never have needed that treatment: the chemotherapy, the radiation, the surgery, the fear, the financial cost.This isn't an anti-medicine argument. It's a call for a conversation that rarely happens: here's the case for this test, and here's the case against it — here's what we might find that helps you, and here's what we might find that sets off a chain reaction you'll spend years managing. For most patients, that conversation never occurs.The 5-Year Survival Stat Is Misleading YouFive-year survival rates for cancer are often cited as evidence that screening works — and they sound like exactly that. But Welch shows why the number can be deceptive, and it comes down to lead-time bias.Here's the mechanism. Imagine a woman whose cancer will kill her at 65, regardless of when it's found. If screening catches it at 62, she lives three years with the diagnosis before dying at 65 — a five-year survival rate under five years. But if that same cancer isn't found until symptoms appear at 64, she lives one year with the diagnosis and dies at 65 — a five-year survival rate of zero.Same woman. Same cancer. Same date of death. But the version of her found earlier through screening appears, statistically, to have “survived longer.” Screening didn't add a single day to her life — it just moved up the start date of her diagnosis. It's the equivalent of claiming a win in a race because someone moved your starting line 200 meters ahead of everyone else's: you didn't run faster, you just started earlier. The finish line never moved.Now layer in overdiagnosis. If 1,000 people are diagnosed with cancers that would never have hurt them, and all 1,000 are alive five years later — which they would have been regardless — the survival statistics look dramatically better without a single life actually being saved. Welch's research shows that 5-year survival rates can climb while actual cancer death rates stay flat. More survivors on paper. Same number of people dying.None of this means medicine isn't making genuine progress in some cancers — colon cancer being a clear example, discussed below. It does mean that 5-year survival statistics, on their own, are not proof that a screening program is saving lives.Where the Evidence for Screening Is Actually StrongIt would be a mistake to leave this discussion thinking all screening is suspect. Welch himself is careful to draw a distinction, and there are tests with solid, randomized-trial evidence behind them.Colonoscopy for colorectal cancer is arguably the strongest case for screening that exists. It's unique because it doesn't just detect cancer — it can prevent it, by removing precancerous polyps before they ever become malignant. Colon cancer incidence and mortality have both dropped measurably in populations with high screening rates. If you're 45 or older, or have a family history, this is worth a serious conversation with your doctor.Low-dose CT for lung cancer, in high-risk individuals specifically, showed a 15–20% reduction in lung cancer deaths in the National Lung Screening Trial — but only among heavy smokers (roughly a pack a day for 20+ years). The risk-benefit math works because the baseline risk in that population is high.Cervical cancer screening — Pap smears and HPV testing — is a genuine public health success story. Rates have dropped dramatically since routine screening began, because cervical cancer has a long, slow, detectable precancerous stage that can be caught before it turns invasive.The common thread: these screenings either catch a long, slow precancerous process, or they target a population where the risk is already high enough that the math clearly favors testing. That's the question worth bringing to your doctor: given my specific risk factors, does the math on this test work in my favor?By contrast, the evidence is much weaker for consumer-marketed total-body scans, full-body MRI as a general “optimization” tool, universal PSA screening in all men over 50, and mammography in average-risk women in their 40s. These aren't mandates — they're conversations, and informed consent means understanding both sides before deciding.The Harms Nobody Talks AboutHealthcare marketing tends to present testing as one-sided: test early, catch it early, save your life. Welch's research catalogs the costs that rarely make it into that pitch.False positives. A mammogram flags a shadow. It isn't cancer — but you don't know that yet. Six weeks of follow-up imaging, maybe a biopsy, and the stress hormones flooding your body during that stretch are a real physiological cost, even when the final answer is “you're fine.”Unnecessary treatment. When a cancer that would never have caused harm is treated anyway — with surgery, radiation, or chemotherapy — the harm is real and the benefit is zero.The cancer label itself. Research shows that being labeled a cancer patient, even for a cancer that's never actively treated, changes a person's psychology, relationships, insurability, and life trajectory. Welch identifies this as a form of harm medicine rarely accounts for.Radiation exposure. Repeated CT scans carry cumulative radiation risk. A full-body scan can expose a person to the radiation equivalent of hundreds of chest X-rays — a real risk added to the body in pursuit of a cancer that may never develop.Welch's central reframe: the question isn't “should I get tested,” it's “given my risk factors, my age, my family history, and my values, does the math on this specific test work in my favor?” That's informed consent — and most people never get that conversation.The Missing Piece: Your Metabolism Is an Early Warning SystemWelch's work is thorough on what not to do. Where it leaves a gap is the proactive question: if blanket screening of healthy people isn't the answer, what is?The answer lies in the years — sometimes decades — before a tumor ever forms. Cancer doesn't appear overnight. The cellular environment that allows it to take root and grow develops gradually, and it leaves metabolic fingerprints long before any scan could detect a tumor.The clearest evidence for this comes from a 2026 study published in Nature Communications, which used machine learning on a massive UK database and linked insulin resistance to a significantly increased risk of at least 12 types of cancer. Pancreatic cancer risk was elevated by roughly 29%, colon cancer by 18%, and breast cancer by 13% — and critically, this risk showed up independent of body weight. A person at a healthy weight can still be carrying the metabolic dysfunction that drives cancer risk, and a standard annual physical would miss it entirely, because most doctors check fasting glucose, not fasting insulin. By the time glucose is elevated, insulin regulation has often been off for years.Layer in chronic inflammation (measured by hs-CRP), elevated ferritin, low vitamin D, rising homocysteine, and a poor triglyceride-to-HDL ratio, and what emerges is a picture of a metabolic environment that is increasingly hospitable to cancer. Think of it as soil: a healthy garden doesn't grow weeds easily, but depleted, imbalanced soil invites them. Cancer is the weed. Metabolic dysfunction is the depleted soil. The strategy, then, is to work on the soil rather than wait to spot the weed.What to Actually Do About ItPath A: Testing to ask your provider forThese tests build a real metabolic picture — the kind that shows soil quality before any weed appears.* Fasting insulin + HOMA-IR — not just fasting glucose. This is likely the single most important test most doctors aren't ordering.* Hemoglobin A1c — your 3-month blood sugar average.* hs-CRP — a high-sensitivity marker of systemic inflammation.* Full lipid panel, including TG/HDL ratio — a ratio above 3 is a strong metabolic red flag.* Ferritin — elevated levels are increasingly linked to inflammatory cancer environments.* Vitamin D (25-OH) — low levels are associated with higher cancer risk across multiple types; optimal is 60–80 ng/mL, not just “in range.”* Homocysteine — a methylation marker that, when elevated, signals oxidative stress.* LDH (Lactate Dehydrogenase) — rises when cells are under metabolic stress.For a deeper look, consider a comprehensive nutrient and organic acids panel (NutrEval), a gut microbiome panel (GI-MAP) — the gut-cancer connection is real — and a full hormone panel including cortisol, estrogen, testosterone, and SHBG.Path B: Lifestyle changes to start today* Eat in this order: protein and fat first, vegetables second, starches last. This alone can meaningfully blunt post-meal blood sugar spikes.* Cut refined sugars and seed oils — the two most direct dietary drivers of insulin resistance and inflammation.* Move daily. At minimum, 150 minutes of moderate activity per week, resistance training twice a week, and even a 10-minute walk after meals to improve glucose metabolism.* Prioritize sleep. Poor sleep disrupts glucose metabolism after a single bad night. Seven to nine hours is non-negotiable for metabolic health.* Manage stress. Chronic cortisol elevation drives insulin resistance — this is biochemistry, not soft advice.You don't need to do all of this at once. Pick one test to ask for at your next appointment, and one lifestyle change to start this week.Summary & Next StepDr. Welch's research makes an uncomfortable but important case: early detection is not automatically synonymous with lives saved, the 5-year survival statistic can be misleading, and testing healthy people carries real costs — false positives, unnecessary treatment, radiation exposure, and the psychological weight of a cancer label. At the same time, some screenings — colonoscopy, cervical cancer screening, low-dose CT for high-risk smokers — have strong evidence behind them and are worth pursuing for the right person.What's missing from that picture is a proactive strategy, and that's where metabolic health comes in. Insulin resistance, chronic inflammation, and blood sugar dysregulation show up years before cancer does, and unlike a full-body scan, they're both measurable and fixable.If you want a clear picture of where your own metabolic terrain stands — and what your highest-leverage next steps are — book a Metabolic Audit Call. It's a complementary 45-minute session where we review your current labs, symptoms, health history, and goals together. Spots are limited each week; the link is in the show notes.References* Welch, H.G. Should I Be Tested for Cancer? Maybe Not and Here's Why. University of California Press.* National Lung Screening Trial Research Team. Reduced lung-cancer mortality with low-dose computed tomographic screening.* Nature Communications (2026). Machine learning analysis of UK biobank data linking insulin resistance to increased risk across 12 cancer types, independent of body weight.* Thrive 120 Podcast, Episode 126: “Should I Be Tested for Cancer? What Dr. Welch Got Right — And What He Missed,” This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit tripleplaydoc.substack.com/subscribe
00:00-25:00: Pinstripe People Crossover. Yanks' 2nd Half Preview. Sal and ML break it down. Thanks to CH Insurance and Marz Motors. Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.
Imagine a dark warehouse. Racks and racks of devices with wires, tubes, and electronics sticking out. The next AI data center? No. This is Lila Sciences‘ dream for the future of science. A dark warehouse full of AI-guided robotics and lab equipment, cranking out new experiments 24/7, building toward a scientific superintelligence.Their automated lab is almost hypnotizing to watch. They have floating plates zipping around on Wall-E-esque tracks, used vision-language models to control Windows 95 boxes, and created the world's largest collection of voided warranties. In the process they've built a massive library of scientific reasoning tokens. Over 10 trillion of them, all experimentally validated.No warranties were voided in the making of this videoTo say Lila is ambitious is an understatement. Their goal is a scientific superintelligence wired directly into the wet lab. They are all in on the bitter lesson, and the thesis follows from it: a lab is an infinite token generator. Produce data at scale, and the synergies give you a general reasoner that can tackle any scientific problem. They are committing hard. Biology, chemistry, drug discovery, and materials science, all at the same time. Time will tell if it works, but it is an exciting hypothesis.In our latest episode we sat down with Lila's very own Andy Beam (CTO) and Rafa Gómez-Bombarelli (CSO, physical sciences) and went on a journey through the possibilities of AI-run science, almost as wide-ranging as Lila's goals.Did we mention they do both materials science and biology? In the same AI science factory? Same time, same lab, same AI. Finally a guest who can settle a long-running debate we've had amongst ourselves: is biology or materials science harder?Watch to find out!We discuss:* The internet is spent, science is next. Why Lila thinks the scientific method is the last untapped internet-scale dataset, and why they treat RL as a data generation mechanism with nature as the verifier.* The lab as a data center. Instruments as nodes on a graph, a magnetically levitating “PCI bus” transport layer between them, orchestration as a slurm queue. Andy is not short on analogies.* Why Lila insists it is not an automation company. They optimize for flexibility and generalizability over raw throughput, which means humans stay below the API line wherever automating does not pay.* Your experiment has a runtime. We put Escalante Bio's question to Andy: if science is the token generator, what is the runtime of your data collection? His answer, in short, is that you cannot make the ribosome go faster. Why Lila bets on fast round-over-round iteration rather than big noisy multiplexed screens, and how Rafa's team rebuilt a gas sorption measurement to run roughly 2,500x faster.* What is actually in 10 trillion scientific tokens. Not sequences. Experimentally verified reasoning traces, a kind of data that Andy argues exists on the internet in quantities that round to zero.* Breadth as a path to depth. Small molecule chemistry priors transferring to metal organic frameworks for carbon capture, and the claim that the general model beats domain-specific models sample for sample.* If you have the data, what do you need the model for? Sri Kosuri's koan about the ML-for-drug-discovery business model, and Andy's answer: the coding model got better because it also read Shakespeare and carnitas recipes.* The serendipity they want to automate. Emily Whitehead survived the first pediatric CAR-T cure only because the doctor treating her happened to know, from pediatric arthritis, which antibody would blunt her IL-6 response. Roll that dice again and you probably lose her. Breadth is how you stop depending on luck.* Move 37 for catalysts. Model suggestions for platinum-group-free electrocatalysts that went from boring, to what a 40-paper expert called stupid, to the best performers they have made.* Six months to in vivo CAR-T data in non-human primates, and the zero-FTE virtual startup commercial model that fell out of it. For context on why that number is startling, AbbVie paid $2.1B for Capstan on the strength of preclinical in vivo CAR-T data.* You cannot have scientific superintelligence if you are just a good test taker. Ken Stanley, who wrote Why Greatness Cannot Be Planned, runs open-endedness at Lila. RL at scale gives you a ruthlessly Vulcan problem solver. Machine creativity is a different thing, and it is the part nobody has solved.* The chain of thought is an unreliable narrator. The model reasons in latent space and only emits tokens. Sometimes it skips the experiment entirely and is still right. So how much do you trust the reasoning versus the verifier?* Reward hacking when the rollout is physical. Chains of thought that collapse into repetition, and a model that got annoyed and swore at the scientist who kept asking it to redo a plate map. What happens when a pathological loop has a wet lab inside it?* The bittersweet lesson. Rafa's inversion of the bitter lesson: in AI, scaling is a roadmap. In materials, scaling is a filter, because only the things that scale end up mattering.* Not your typical Flagship company. Why a famously single-asset biotech incubator spun out a platform bet, and Andy's line that if Lila called itself a biopharma it would have a top-three GPU cluster.* Bottlenecks they would remove by fiat. Sim-to-real for physics-based simulation, and the fact that RL training runs at roughly 5% mean FLOP utilization.Watch on YouTube: This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.latent.space/subscribe
00:00-30:00: Sal and ML break down the Yanks' sweep of the Nats, chat Jazz gonna Jazz, ASG and Derby with break and more. Plus, Ben Rice rocks. Pinstripe People crossover. Thanks to CH Insurance and Marz Motors. Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.
Small teams with smart AI can solve problems no one imagined before. In this episode, I spoke with Zhen Lu, CEO of Runpod, about the rapidly evolving AI landscape and the future of software development. Zhen Lu shared how Runpod is empowering engineers to train AI models tailored to specific business needs, improve efficiency, and reduce waste. We also discussed his founder journey, the power of co-founder alignment, global innovation outside traditional tech hubs, and the importance of human accountability in AI-driven organizations. Here are the highlights: ● Runpod builds AI developer infrastructure. The platform supports tailored AI workloads, enabling businesses to efficiently train models specific to their needs. ● AI is changing how software is built. Engineers are challenged to rethink software design, not just accelerate existing processes, creating new opportunities for innovation. ● Efficiency and sustainability matter. Fine-tuning smaller, focused models reduces resource waste, energy consumption, and operational costs compared to massive off-the-shelf models. ● Co-founder alignment drives success. Implicit trust, complementary skills, and low ego between Zhen and his co-founder have accelerated decision-making and execution. ● Global networks and bootstrapping foster innovation. Scarcity encourages creativity, and building strong relationships outside Silicon Valley has enabled Runpod to grow and support AI developers worldwide. About the guest: Zhen Lu and co-founder Pardeep Singh started by running crypto mining rigs out of their New Jersey basements. When Ethereum's "The Merge" threatened to make that obsolete, they pivoted, converting the rigs into AI servers. As corporate developers at Comcast building ML projects, they saw firsthand that the GPU developer experience was, in Zhen's words, "just hot garbage." That insight became Runpod. Launched in early 2022, Runpod offers fast, developer-friendly GPU infrastructure: clean APIs, CLI tools, serverless options, and easy configuration. Rather than the traditional VC route, they debuted on Reddit with "Hey Reddit, give us your worst" — and got "please take my money" in return. They went on to earn validation from Hugging Face co-founder Julien Chaumond and a seed round led by Dell Technologies Capital, hitting $120M ARR, 10 billion serverless requests, and serves ~900,000 developers across 31 global regions. Connect with Zhen Lu: LinkedIn: https://www.linkedin.com/in/zeen/ Website: https://www.runpod.io/ Connect with Allison: Feedspot has named Disruptive CEO Nation as one of the Top 25 CEO Podcasts on the web. LinkedIn: https://www.linkedin.com/in/allisonsummerschicago/ Website: https://www.disruptiveceonation.com/ #CEO #leadership #startup #founder #business #businesspodcast Learn more about your ad choices. Visit megaphone.fm/adchoices
Small teams with smart AI can solve problems no one imagined before. In this episode, I spoke with Zhen Lu, CEO of Runpod, about the rapidly evolving AI landscape and the future of software development. Zhen Lu shared how Runpod is empowering engineers to train AI models tailored to specific business needs, improve efficiency, and reduce waste. We also discussed his founder journey, the power of co-founder alignment, global innovation outside traditional tech hubs, and the importance of human accountability in AI-driven organizations. Here are the highlights: ● Runpod builds AI developer infrastructure. The platform supports tailored AI workloads, enabling businesses to efficiently train models specific to their needs. ● AI is changing how software is built. Engineers are challenged to rethink software design, not just accelerate existing processes, creating new opportunities for innovation. ● Efficiency and sustainability matter. Fine-tuning smaller, focused models reduces resource waste, energy consumption, and operational costs compared to massive off-the-shelf models. ● Co-founder alignment drives success. Implicit trust, complementary skills, and low ego between Zhen and his co-founder have accelerated decision-making and execution. ● Global networks and bootstrapping foster innovation. Scarcity encourages creativity, and building strong relationships outside Silicon Valley has enabled Runpod to grow and support AI developers worldwide. About the guest: Zhen Lu and co-founder Pardeep Singh started by running crypto mining rigs out of their New Jersey basements. When Ethereum's "The Merge" threatened to make that obsolete, they pivoted, converting the rigs into AI servers. As corporate developers at Comcast building ML projects, they saw firsthand that the GPU developer experience was, in Zhen's words, "just hot garbage." That insight became Runpod. Launched in early 2022, Runpod offers fast, developer-friendly GPU infrastructure: clean APIs, CLI tools, serverless options, and easy configuration. Rather than the traditional VC route, they debuted on Reddit with "Hey Reddit, give us your worst" — and got "please take my money" in return. They went on to earn validation from Hugging Face co-founder Julien Chaumond and a seed round led by Dell Technologies Capital, hitting $120M ARR, 10 billion serverless requests, and serves ~900,000 developers across 31 global regions. Connect with Zhen Lu: LinkedIn: https://www.linkedin.com/in/zeen/ Website: https://www.runpod.io/ Connect with Allison: Feedspot has named Disruptive CEO Nation as one of the Top 25 CEO Podcasts on the web. LinkedIn: https://www.linkedin.com/in/allisonsummerschicago/ Website: https://www.disruptiveceonation.com/ #CEO #leadership #startup #founder #business #businesspodcast Learn more about your ad choices. Visit megaphone.fm/adchoices
How do you build the career you actually want—inside an industry that was not exactly built for you—without softening who you are to fit inside it? Chee Smalls has spent fifteen years answering that question. She is Senior Director of Product Development at Coach, a style voice, and a content creator. She is also a Harlem girl who has never—not once, not in a single meeting, not in a single boardroom—code-switched a day of her career.That refusal is the whole conversation.In this episode, we get into how she got into fashion without the resume the industry usually demands, and how curiosity became her actual professional currency. We talk about the moments when she could have softened her voice to fit a room and didn't, and what that cost her at first, and what it eventually earned her. Her personal philosophy on luxury and why she refuses to follow trends—including the very sharp question she asks about whether the algorithm is quietly killing our individuality. The features she was insecure about for years and what changed when she stopped shrinking from them. Her marriage as a real partnership—the "we take turns climbing" model she and her husband built, where one goes head-down while the other holds it together, then they switch. And how she is thinking about ambition, identity, and the life she is building on her own terms.She closes the episode with an "I am" affirmation you'll want to write down: "I am beauty. I am woman. I am ambition. I am God's favored and blessed. I am me."This is also the first episode with our new behind-the-scenes intro. We shot Chee arriving at the door, the two of us mixing a rosé lemonade in my kitchen, and the moment before we settled onto the couch. The full recipe is below, make it while you listen: Meanwhile, She Rosé LemonadeMakes 4 cocktails (about 5 oz each)Ingredients1 bottle (750 mL) chilled rosé (The Beach Ros√©)1/2 cup (4 oz) freshly squeezed lemon juice2 oz Grand Marnier1 1/2 oz simple syrup1 oz agave nectarIce Optional GarnishesLemon wheelsFresh mintEdible rose petals (if you're feeling fancy)Frozen raspberries or strawberries InstructionsIn a pitcher, combine the lemon juice, Grand Marnier, simple syrup, and agave. Stir until fully combinedPour in the chilled rose and stir gently so you don't lose too much of its freshness.Taste.Want it brighter? Add another splash of lemon.Want it softer? Add another ½ oz simple syrup.Fill glasses with ice and pour over.Garnish with a lemon wheel and mint.
00:00-15:00: ML recaps another blown chance for Team USA men's soccer. Thanks to CH Insurance and Marz Motors. Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.
One of Detroit's most notorious crimes inspires a murder mystery set Up North. Author Bryan Gruley joins ML and Marc […]
Seth Woolcock and Andrew Erickson break down their favorite early NFL Week 1 bets, including spreads, totals, moneyline underdogs, and where they believe sportsbooks have already made mistakes. The duo discusses why the Cowboys could continue their dominance over the Giants, whether the Steelers are being undervalued against Atlanta, why several Week 1 unders stand out, and which underdogs offer intriguing value before kickoff. If you're betting NFL futures, building your Week 1 card, or simply looking for the sharpest early betting angles, this episode has you covered. Timestamps: (May be off due to ads) Intro - 0:00:00 Dallas Cowboys -1.5 vs. New York Giants - 0:04:04 Pittsburgh Steelers -2.5 vs. Atlanta Falcons - 0:06:43 Tennessee Titans -2.5 vs. New York Jets - 0:10:43 BettingPros App - 0:12:38 New York Jets vs. Tennessee Titans Under 39.5 - 0:13:12 San Francisco 49ers vs. Los Angeles Rams Under 49.5 -0:15:44 Baltimore Ravens vs. Indianapolis Colts Under 49.5 - 0:18:58 Hard Rock Bet - 0:22:02 Houston Texans (-104) ML vs. Buffalo Bills - 0:24:15 Miami Dolphins ML (+176) vs. Las Vegas Raiders - 0:28:03 Minnesota Vikings ML (+100) vs. Green Bay Packers - 0:30:54 Helpful Links: Hard Rock Bet - Sign up for Hard Rock Bet and make a $5 bet and you'll get $150 in bonus bets if you win. Head over to Hard Rock Bet, sign up and make your first deposit today. Payable in bonus bet(s). Not a cash offer. Offered by the Seminole Tribe of Florida in FL. Offered by Seminole Hard Rock Digital, LLC, in all other states. Must be 21+ and physically present in AZ, CO, FL, IL, IN, NJ, OH, TN or VA to play. Terms and conditions apply. Concerned about gambling? In FL, call 1-888-ADMIT-IT. In IN, if you or someone you know has a gambling problem and wants help, call 1-800-9-WITH-IT. GAMBLING PROBLEM? CALL 1-800-GAMBLER (AZ, CO, IL, NJ, OH, TN, VA) BettingPros App - Make winning bets with advice and picks from top sports betting experts. The BettingPros app puts consensus and expert-driven sports betting advice at your fingertips to help you pinpoint the best odds and make winning bets. Download it today on the App Store or Google Play. BettingPros Discord - Looking to up your game in sports betting? Join our exclusive sports betting Discord community at bettingpros.com/chat! Not only can you connect with expert handicappers who provide free picks for NBA, NFL, MLB, NHL, player props, live betting, and more, but now you can also participate in our weekly community picks. Cast your vote, see how your picks stack up against the experts, and track your success! BettingPros Pick Tracker – Want to track all of your wagers in one place? Check out the BettingPros Pick Tracker. It syncs up with your sportsbooks to tally which picks hit, and which miss AND gives you a live look at what the public is doing so you can use real-time tracking to determine which plays to make, and which to fade: bettingpros.com/pick-trackingSee omnystudio.com/listener for privacy information.
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