Podcasts about predictive

Mike Noble, founder of Noble Predicitve Insights, breaks down latest survey on Arizona's primary election.

Jonathan Whistman is The Sales Boss - the architect behind human powered organizations where identity, belief, and culture drive extraordinary performance. He helped Tommy Mello scale A1 Garage Door to a half-billion dollar exit, with technicians going from $200-300k producers to $900k average - and top performers reaching $3 million.Andy Elliott had so much success running his team on Jonathan's system that he invested $2 million and partnered with Jonathan to co-create the Performance Machine - combining The Sales Boss methodology with ElliottHire's training and activation systems.Jonathan's superpower comes from an unusual place: growing up inside a religious cult. That experience taught him how to read human behavior with precision - and how identity, belief, and culture shape everything people do. Now he applies those insights to help leaders build organizations where humans perform at their highest level.In this episode, he walks through the Think | Feel | Act framework, explains Sacred Rhythms, and reveals why most companies are like a high school band when they could be Carnegie Hall. He also shares the Talent Reveal Interview - a group hiring method that lets you find your first $100k producer in 30 days.TIMESTAMPS:0:00 Introduction and opening hook3:08 The saddest thing about hiring7:14 Predictive hiring and the Reggie Blueprint12:59 Jonathan's cult backstory19:07 Think | Feel | Act explained28:41 Sacred Rhythms in action31:41 Inside Andy Elliott's sales meeting40:03 How the software platform works51:08 The Talent Reveal Interview55:55 Final question and closing

Tell us what you think of the show! The energy landscape has entered a volatile era of climate disruption. Regions once considered safe now face the devastating reality of escalating wildfires and extreme weather. In this episode, we sit down with Don McPhail, VP of Market Development at eSmart Systems, to discuss why traditional, asset-focused mitigation is no longer enough for utilities across the United States.We explore the critical shift to community-first resilience models, where protecting life-sustaining infrastructure takes priority over mere compliance. How exactly are digitization and AI-powered digital twins transforming grid safety? What does it mean to use high-resolution imagery to identify minute defects like upside-down cotter pins in a way that creates quantifiable value? Don provides a roadmap for utility leaders ready to trade siloed data practices for predictive insights that save time, money, and lives.Want to make a suggestion for This Week in Cleantech? Nominate the stories that caught your eye each week by emailing Paul.Gerke@clarionevents.com

In this episode of The Clinical Research Coach, host Leanne Woehlke sits down with Alen Hadzic, Founder and CEO of CT Scan, to explore how data, digital advertising, and AI are reshaping the way patients are enrolled into clinical trials.Coming from a background in consulting, marketing strategy, and lead generation, Alen brings a fresh lens to one of the industry's most persistent challenges—patient recruitment and enrollment. Rather than relying on traditional recruitment models, his company has developed a methodology called Predictive Enrollment Engineering, designed to calculate and optimize cost-per-enrollment using real-world advertising data.Alen shares how CT Scan's patent-pending AI platform, Dyno AI, analyzes millions of dollars in digital advertising performance across dozens of clinical research projects to model enrollment funnels—from ad engagement and qualification to phone contact, eligibility, and final enrollment.During the conversation, Leanne and Alen discuss:Why traditional patient recruitment models often fail to deliver resultsThe hidden friction points that cause patients to drop out of the enrollment funnelHow digital advertising can be used to measure and optimize patient interestThe importance of rapid follow-up and human engagement in improving response ratesHow CT Scan achieves a 65% phone answer rate through immediate outreach and optimized workflowsWhy focusing on cost per enrollment—not cost per lead—changes the entire recruitment strategyAlen also shares his unconventional journey into the clinical trials industry—from early exposure to research through his physician father to a career in consulting and entrepreneurship that ultimately led him to rethink how clinical trials approach patient enrollment.If clinical trial recruitment has ever felt unpredictable, inefficient, or frustrating, this episode offers a data-driven perspective on how AI, marketing science, and operational discipline could transform enrollment into a measurable and predictable process.Tune in to learn how predictive modeling and digital marketing principles may help bring new optimism to clinical trial enrollment.Alen Hadzic is a healthcare technology entrepreneur focused on bringing predictability and operational rigor to clinical trial enrollment. He is the Founder and CEO of CT SCAN™, a company developing systems to remove uncertainty from patient recruitment by engineering enrollment as a measurable process rather than a marketing outcome. His work centers on Predictive Enrollment Engineering™, a methodology that models each stage of the patient journey, from initial awareness through screening and enrollment, using probability-based performance metrics. The company's patent-pending enrollment technology, DYNO Ai™, analyzes operational and advertising data to forecast cost-per-enrollment and reduce study timelines.Hadzic holds a graduate degree from Columbia University and completed a Master's in Innovation and Entrepreneurship at Vlerick Business School, a top-ranked European program in the field. His background combines business strategy, systems thinking, and applied analytics in clinical research operations.Outside of his professional work, he is an active musician who records and performs his own material, playing guitar, drums, and vocals. He approaches both technology and music with a similar philosophy: structured systems can create reliable outcomes, but creativity determines how far those outcomes can be pushed.

Predictive Markets Are Problematic... by Nick Espinosa, Chief Security Fanatic

In this episode, Amir Syed, President of BRSi, shares insights on revenue cycle management, the impact of AI in healthcare, and strategies for healthcare leaders to stay ahead in the evolving landscape. Discover practical tips on process improvement, predictive analytics, and how to leverage technology effectively.AI is accelerating claim denials and revenue cycle challenges. Healthcare providers must focus on process optimization before investing in AI. Predictive analytics can prevent denials by identifying problem areas early.Resources: - ⁠BRSi Website ⁠- ⁠Aamir Syed LinkedIn⁠

March 4, 2026: Your daily rundown of health and wellness news, in under 5 minutes. Today's top stories: Quest Diagnostics unveils AI chatbot in MyQuest portal analyzing five years of lab data powered by Google's Gemini models Subco launches independent supplement certification program anonymously purchasing retail supplements and verifying ingredients in independent labs Eight Sleep raises funding at $1.5B valuation, shifting from reactive sleep optimization to predictive AI agent and pursuing FDA clearance for sleep apnea detection More from Fitt: Fitt Insider breaks down the convergence of fitness, wellness, and healthcare — and what it means for business, culture, and capital. Subscribe to our newsletter → insider.fitt.co/subscribe Work with our recruiting firm → https://talent.fitt.co/ Follow us on Instagram → https://www.instagram.com/fittinsider/ Follow us on LinkedIn → linkedin.com/company/fittinsider Reach out → insider@fitt.co

A new poll shows how gubernatorial candidates are faring as midterms approach. Mike Noble, CEO of Noble Predictive Insights, breaks down the numbers.

The AI Advantage: Why Your Business Can't Afford to Wait

Van and Rachel welcome Indiana University associate professor Hussein Banai, who gives his insight on the joint strikes against Iran. Then they switch gears to discuss Michael B. Jordan's Oscar odds and Jonathan Majors's next project. Then Jeff and Nicole Friday join to celebrate 30 years of the American Black Film Festival. (0:00) Intro (09:23) Hussein Banai on the conflict in Iran (41:53) Predictive history (1:02:20) NAACP Image Awards (1:09:27) Oscar speculation (1:23:36) Jonathan Majors and Ben Shapiro (1:36:34) Jeff and Nicole Friday join the show (2:05:42) Magic City Monday and the NBA Hosts: Van Lathan and Rachel Lindsay Guests: Hussein Banai, Jeff Friday, and Nicole Friday Producers: Donnie Beacham Jr. and Jade Whaley Social Producer: Bernard Moore Learn more about your ad choices. Visit podcastchoices.com/adchoices

Businesses are pouring millions into generative AI—chatbots, copilots, “agents”—while quietly ignoring the other half of the AI stack that's been delivering measurable value for decades. Predictive AI doesn't write poetry. It predicts who's going to churn, which transaction is fraud, and which customer is worth contacting. It calculates probabilities and helps you act on them at scale. Not glamorous. Just effective.In this conversation, Eric Siegel—author of The AI Playbook and founder of Machine Learning Week—makes a subversive claim: most organizations should be investing at least as much in predictive AI as generative AI. The problem isn't the math. It's the gap between tech and business. Companies celebrate models as value. But the model isn't the value. Acting on predictions is.Related Links:Join the People Managing People CommunitySubscribe to the newsletter to get our latest articles and podcastsCheck out this episode's sponsor: DeelConnect with Eric:LinkedInGooder AICheck out Eric's book: The AI PlaybookSupport the show

On today's episode, Joe, Prez and Bryan Power discuss the BIGGEST matchups on today's betting card, predictive market betting, parlay of the day and more!00:00 INTRODUCTION00:47 WEEKEND RECAP01:54 BIG GAME MONDAY: NHL + 2 CBB GAMES02:12 NHL: COLORADO AT LA KINGS03:15 CBB: IOWA ST AT ARIZONA05:50 CBB: DUKE AT NC STATE12:44 PARLAY OF THE DAY14:29 PREDICTIVE MARKETS: BITCOIN | MARCH MADNESS27:09 CBB RUNDOWN29:21 NHL RUNDOWN31:13 NBA RUNDOWN

The Carton Show opens with one of the wildest discussions you'll ever hear — millions of dollars wagered on global events through predictive gambling markets… and when the outcome happens, bettors STILL don't get paid!

Description:  Hosts Roz and Dr. Sanchez-Fueyo are joined by Justin Barr to discuss the key articles of the March issue of the American Journal of Transplantation. Justin Barr practices abdominal transplant and advanced hepatobiliary surgery at Ochsner Medical Center [03:13] Implementation of a physician assistant-led recovery model for heart transplantation: Clinical outcomes and programmatic benefits at a high-volume center [13:54] A 100-year simulation of the National Kidney Registry's voucher program [25:32] Risk of deficient mismatch repair colorectal cancer and precursors after kidney transplantation: A nationwide study [35:09] Predictive value of torque teno virus viral load for BK polyomavirus DNAemia depends on BK polyomavirus–specific humoral immunity in kidney transplant recipients [42:50] Suppression of cardiac allograft vasculopathy by a macrophage efferocytosis receptor

For the Good of the Public brings you news and weekly conversations at the intersection of faith and civic life. Monday through Thursday, The Morning Five starts your day off with scripture and prayer, as we also catch up on the news together. Throughout the year, we air limited series on Fridays to dive deeper into conversations with civic leaders, thinkers, and public servants reimagining public life for the good of the public. Today's host was Michael Wear, Founder, President and CEO of the Center for Christianity and Public Life.  Thanks for listening to The Morning Five! Please subscribe to and rate The Morning Five on your favorite podcast platform. Learn more about the work of the Center for Christianity and Public Life at www.ccpubliclife.org. Today's scripture: Matthew 11:2-11 (ESV) News sources:  https://apnews.com/live/donald-trump-news-updates-2-25-2026#0000019c-95c4-d3e7-a5fe-b5f62faa0000  https://www.nytimes.com/2026/02/25/world/europe/pope-africa-visit.html  https://www.npr.org/2026/02/24/nx-s1-5724999/house-rejects-aviation-safety-bill-rotor-act  https://www.wsj.com/business/media/kalshi-fines-former-gubernatorial-candidate-mrbeast-employee-on-prediction-wagers-208b6b5a?mod=hp_lead_pos11  https://www.pbs.org/newshour/nation/a-400000-payout-after-maduros-capture-put-prediction-markets-in-the-spotlight-heres-how-they-work  Join the conversation and follow us at: Instagram: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@michaelwear⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, @ccpubliclife Twitter: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@MichaelRWear⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, @ccpubliclife and check out ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@tsfnetwork⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Music by: King Sis #politics #faith #prayer #scripture #IranTalks #PresidentTrump #PopeLeo #Africa #Congress #Aviation #MrBeast #PredictionMarkets Learn more about your ad choices. Visit megaphone.fm/adchoices

The integration of Artificial Intelligence (AI) into post-injury rehabilitation is transforming recovery paradigms by enabling personalized, adaptive, and efficient rehabilitation pathways tailored to individual patient needs. This podcast reviews the current advances in AI applications that facilitate assessment, monitoring, and optimization of rehabilitation programs following injuries. Through machine learning algorithms, wearable sensors, and predictive analytics, AI enhances the precision of therapy plans, tracks patient progress in real-time, and predicts recovery trajectories. The discussion includes the benefits of AI-driven rehabilitation, including improved functional outcomes, reduced recovery times, and increased patient engagement. It also addresses challenges such as data privacy, algorithmic bias, and integration with clinical workflows.  1. Transforming recovery paradigms Traditional post‑injury rehab relies on periodic in‑person assessments, therapist intuition, and standardized protocols that only partially account for individual variability. AI is shifting this model toward: Continuous, data‑driven care: Instead of snapshots in clinic, rehab can be informed by near real‑time streams of kinematic, physiological, and behavioral data from wearables, smart devices, and robot interfaces. Dynamic adaptation: Therapy intensity, task difficulty, and exercise selection can be automatically adjusted based on ongoing performance, fatigue, and recovery trends, rather than fixed schedules. Precision rehabilitation: Algorithms can identify which patients are likely to respond to specific interventions (e.g., constraint‑induced movement therapy vs robotics) and tailor plans accordingly. This moves rehabilitation from a "one‑size‑fits‑many" paradigm toward precision, context‑aware therapy, analogous to precision oncology but focused on function and participation. 2. Assessment, monitoring, and optimization AI for assessment Sensor‑based movement analysis: Machine learning models process accelerometer, IMU, EMG, and pressure data to quantify gait symmetry, joint kinematics, balance, and fine motor control with higher resolution than visual observation alone. Automated scoring: AI can approximate or support standardized scales (e.g., Fugl‑Meyer, Berg Balance Scale) by mapping sensor features or video-derived pose estimates to clinical scores, reducing inter‑rater variability and saving clinician time. Continuous monitoring Home and community tracking: Wearable and ambient sensors enable monitoring of daily steps, walking speed, arm use, posture, and adherence to exercises outside the clinic, feeding rich longitudinal datasets into AI models. Real‑time alerts: Algorithms can detect abnormal patterns—such as increased fall risk, reduced limb use, or signs of over‑exertion—and flag the clinician or adjust digital therapy content automatically. Optimization and decision support Predictive models: Using historical data, AI can forecast functional gains, plateau points, or risk of complications (e.g., falls, readmission), supporting individualized goal‑setting and resource allocation. Reinforcement learning and "digital twins": Emerging work in neurorehabilitation treats rehab as a sequential decision problem, using model‑based reinforcement learning and patient "digital twins" to recommend optimal timing, dosing, and progression of interventions over weeks to months.​ 3. Technologies: ML, wearables, analytics Machine learning algorithms: Supervised ML classifies movement quality (normal vs compensatory), detects exercise type from sensor streams, and estimates clinical scores. Unsupervised learning clusters patients into phenotypes (e.g., gait patterns after stroke), revealing subgroups that respond differently to certain therapies. Reinforcement learning and contextual bandits explore which therapy adjustments yield the best long‑term functional outcomes for a given individual.​ Wearable sensors and robotics: Inertial sensors, EMG, pressure insoles, and exoskeleton sensors capture high‑frequency movement and muscle activity data during training. Robotic devices (upper‑limb exoskeletons, gait trainers) coupled with AI can modulate assistance, resistance, or task difficulty in real time based on performance and predicted fatigue. Predictive and prescriptive analytics: Predictive analytics estimate trajectories (e.g., time to independent walking, expected upper‑limb function) to inform shared decisions with patients and families. Prescriptive analytics recommend therapy intensity, modality mix, and scheduling to maximize functional gains under resource constraints. 4. Benefits: outcomes, efficiency, engagement Improved functional outcomes: Studies report better motor recovery, gait quality, and ADL performance when AI‑assisted training is used—especially when robotics and intelligent feedback are involved. Reduced recovery time and resource use: More precise dosing and earlier identification of non‑responders can reduce ineffective sessions, shorten time to key milestones, and support safe earlier discharge with robust remote follow‑up. Increased adherence and engagement: AI‑driven digital rehab platforms use gamification, adaptive difficulty, and personalized feedback to keep patients engaged in home programs, improving adherence compared to static paper instructions. Support for clinicians: Instead of replacing therapists, AI can offload repetitive measurement tasks, highlight concerning trends, and offer data‑driven suggestions, allowing clinicians to focus on relational, motivational, and complex decision‑making aspects of care. 5. Challenges and ethical considerations Data privacy and security: Rehab AI often relies on continuous collection of sensitive motion, physiological, and sometimes audio/video data, raising questions about consent, storage, secondary use, and breach risk. Approaches like federated learning and on‑device processing are being explored to reduce centralization of identifiable data while still enabling model training. Algorithmic bias and fairness: If training data under‑represent older adults, women, certain racial/ethnic groups, or people with severe disability, AI models may misestimate performance or risk for those groups, potentially widening disparities in rehab access and outcomes. Ongoing auditing, diverse datasets, and participatory design with patients and clinicians are needed to ensure equitable performance. Integration with clinical workflows: Many AI tools are developed in research settings and are not yet seamlessly integrated into EHRs, scheduling systems, or therapist documentation workflows. Poorly integrated tools risk adding documentation burden or "alert fatigue," reducing adoption. Successful implementations co‑design interfaces with frontline therapists and physicians. Regulation, liability, and trust: It remains unclear in many jurisdictions how to regulate adaptive rehab algorithms (as medical devices, clinical decision support, or wellness tools) and who is liable when AI‑informed plans cause harm.​ Transparent, explainable models and clear communication to patients about the role of AI are critical for maintaining trust. 6. Case studies and emerging trends Remote and hybrid digital rehabilitation: AI‑driven platforms providing home‑based stroke, orthopedic, or Parkinson's rehab with clinician dashboards are improving adherence and extending care beyond brick‑and‑mortar clinics. Collaborative AI for precision neurorehabilitation: Frameworks combining patient‑clinician goal setting, digital twins, and reinforcement learning exemplify "collaborative AI" that augments rather than replaces therapists.​ Multimodal personalization: Integration of movement data, EMG, heart rate, sleep, and self‑reported pain/fatigue is enabling more nuanced adaptation to daily fluctuations in capacity. Conversational AI for education and coaching: Early work is assessing tools like ChatGPT as low‑risk supports for exercise education and motivation, though they are not yet precise enough to replace professional plan design AI is moving rehab toward patient‑centered, continuously adapting, and data‑rich care, but realizing this promise depends on addressing privacy, bias, workflow, and regulatory challenges in partnership with clinicians and patients.

On today's episode, Joe, Prez and Bryan Power discuss the upcoming college basketball schedule and its massive implications, predictive market betting and more!00:00 INTRODUCTION00:11 USA WINS GOLD & PREZ IS NOT HAPPY06:26 PREZ DOESN'T UNDERSTAND TACO BELL11:08 DIFFERENCE BETWEEN SWEATER AND JERSEY13:00 NBA PREVIEW: SPURS VS PISTONS18:17 CBB PREVIEW: HOUSTON AT KANSAS27:06 PARLAY OF THE DAY28:34 PREDICTIVE MARKETS: SOCCER + BITCOIN43:28 TODAY'S BEST BETS45:41 NBA + CBB EXTRA GAMES47:58 NHL FUTURE BETS

News of the Bogus: 0:43 – Before We Blame AI For Suicide, We Should Admit How Little We Know About Suicide https://www.techdirt.com/2026/02/19/before-we-blame-ai-for-suicide-we-should-admit-how-little-we-know-about-suicide/ Prediction of suicidal behavior in high risk psychiatric patients using an assessment of acute suicidal state: The suicide crisis inventory https://pubmed.ncbi.nlm.nih.gov/27712028/ Predictive validity and symptom configuration of proposed diagnostic criteria for the Suicide Crisis Syndrome: A replication study https://www.sciencedirect.com/science/article/abs/pii/S0022395622005702 7:12 – Trump said tariffs would reduce the trade deficit. It hit a record high in 2025. https://reason.com/2026/02/19/trump-said-tariffs-would-reduce-the-trade-deficit-instead-it-hit-a-record-high-in-2025/ 11:14 – NSA and IETF, part 5: One battle after another. #pqcrypto #hybrids #nsa #ietf #lastcall https://blog.cr.yp.to/20260219-obaa.html 20:45 – Biggest Bogon Emitter: California Tesla Takes Corrective Action to Avoid DMV Suspension – California DMV https://www.dmv.ca.gov/portal/news-and-media/tesla-takes-corrective-action-to-avoid-dmv-suspension/ Now We Know Why Tesla Killed Autopilot https://insideevs.com/news/787656/tesla-autopilot-california-dmv-marketing/ 25:50 – Idiot Extraordinaire: Democrats Democrats revive a once-taboo idea: Capping grocery prices https://www.yahoo.com/news/articles/democrats-revive-once-taboo-idea-145715732.html This Week’s Quote: “Despite the disastrous history of price controls, politicians never manage to resist tampering with prices—that’s not a flattering observation of their learning abilities.” —Walter E. Williams 🔊Pᴏᴅᴄᴀꜱᴛ: https://podcast.bogosity.tv/💬Dɪꜱᴄᴏʀᴅ: https://discord.bogosity.tv/▶️YᴏᴜTᴜʙᴇ: https://www.youtube.com/shanedk▶️Oᴅʏsᴇᴇ: https://odysee.com/%24/invite/@shanedk:4▶️Rᴜᴍʙʟᴇ https://rumble.com/c/shanedk💰Dᴏɴᴀᴛᴇ ᴏʀ ꜱᴜʙꜱᴄʀɪʙᴇ: https://donate.bogosity.tv

Fertility care is undergoing a significant shift as new diagnostic technologies offer deeper insight into reproductive health. OTO Fertility focuses on predicting the likelihood of IVF success before treatment begins, giving couples clarity at a stage where uncertainty has traditionally dominated the process. The system uses a wearable device that captures physiological signals and converts them into predictive metrics, offering a noninvasive method for understanding fertility readiness.The challenge addressed by this technology is substantial. IVF remains expensive, time‑consuming, and emotionally demanding, yet the success rate for a single transfer remains low. Many couples undergo multiple cycles without clear guidance on their likelihood of success. By providing predictive insight before treatment, the system aims to reduce unnecessary cycles, lower financial burden, and support more informed decision‑making.Physiological Monitoring and Predictive ModelingThe OTO Fertility device performs medical‑grade ECG and EEG measurements, capturing data from multiple physiological systems. These include cardiac activity, central and autonomic nervous system responses, hormonal regulation patterns, and energy supply indicators. Dozens of body signals are synthesized into a set of metrics that correlate with fertility outcomes. These metrics are then combined into a single index that reflects the couple's overall fertility readiness.Both partners participate in the process, allowing the system to evaluate male and female factors independently and together. This dual‑side approach supports a more complete understanding of fertility challenges, including those that may not be detected through traditional testing. The system also supports natural conception by identifying physiological patterns that can be optimized without clinical intervention.Personalized Guidance Through AIOnce the fertility index is generated, the system provides personalized recommendations designed to improve physiological readiness. These recommendations are based on lifestyle factors that influence fertility, including activity levels, rest, recovery, nutrition, sleep, and stress management. The guidance is tailored to each individual and delivered through the accompanying application, creating a structured pathway for improvement.The use of AI allows the system to adapt recommendations as new data is collected. Daily measurements support continuous monitoring, enabling couples to track progress and understand how their bodies respond to changes. This dynamic approach contrasts with traditional fertility diagnostics, which often rely on static snapshots taken at a single point in time.Broader Fertility Insights and Lifecycle SupportThe technology also provides insight into previously unexplained fertility challenges. A significant portion of infertility cases fall into the unexplained category, where standard tests show no clear cause. By analyzing physiological patterns across multiple systems, the device offers a new layer of understanding that can help clarify these cases.The system extends beyond conception, offering support during pregnancy and postpartum. This continuity allows couples to remain engaged with their physiological health throughout the entire fertility journey. The solution is delivered in partnership with treating physicians and virtual clinics, integrating seamlessly into existing care pathways.ConclusionOTO Fertility introduces a predictive diagnostic system designed to improve IVF outcomes and support natural conception through physiological monitoring and AI‑driven guidance. By providing insight into fertility readiness, offering personalized recommendations, and addressing both partners' health, the system creates a more informed and supportive pathway for couples seeking to build their families. As fertility challenges continue to rise globally, technologies that deliver clarity, personalization, and noninvasive insight are becoming essential components of modern reproductive care.Interview by Don Baine, The Gadget Professor.Sponsored by: Get $5 to protect your credit card information online with Privacy. Amazon Prime gives you more than just free shipping. Get free music, TV shows, movies, videogames and more. Secure your connection and unlock a faster, safer internet by signing up for PureVPN today.

Fertility care is undergoing a significant shift as new diagnostic technologies offer deeper insight into reproductive health. OTO Fertility focuses on predicting the likelihood of IVF success before treatment begins, giving couples clarity at a stage where uncertainty has traditionally dominated the process. The system uses a wearable device that captures physiological signals and converts them into predictive metrics, offering a noninvasive method for understanding fertility readiness.The challenge addressed by this technology is substantial. IVF remains expensive, time‑consuming, and emotionally demanding, yet the success rate for a single transfer remains low. Many couples undergo multiple cycles without clear guidance on their likelihood of success. By providing predictive insight before treatment, the system aims to reduce unnecessary cycles, lower financial burden, and support more informed decision‑making.Physiological Monitoring and Predictive ModelingThe OTO Fertility device performs medical‑grade ECG and EEG measurements, capturing data from multiple physiological systems. These include cardiac activity, central and autonomic nervous system responses, hormonal regulation patterns, and energy supply indicators. Dozens of body signals are synthesized into a set of metrics that correlate with fertility outcomes. These metrics are then combined into a single index that reflects the couple's overall fertility readiness.Both partners participate in the process, allowing the system to evaluate male and female factors independently and together. This dual‑side approach supports a more complete understanding of fertility challenges, including those that may not be detected through traditional testing. The system also supports natural conception by identifying physiological patterns that can be optimized without clinical intervention.Personalized Guidance Through AIOnce the fertility index is generated, the system provides personalized recommendations designed to improve physiological readiness. These recommendations are based on lifestyle factors that influence fertility, including activity levels, rest, recovery, nutrition, sleep, and stress management. The guidance is tailored to each individual and delivered through the accompanying application, creating a structured pathway for improvement.The use of AI allows the system to adapt recommendations as new data is collected. Daily measurements support continuous monitoring, enabling couples to track progress and understand how their bodies respond to changes. This dynamic approach contrasts with traditional fertility diagnostics, which often rely on static snapshots taken at a single point in time.Broader Fertility Insights and Lifecycle SupportThe technology also provides insight into previously unexplained fertility challenges. A significant portion of infertility cases fall into the unexplained category, where standard tests show no clear cause. By analyzing physiological patterns across multiple systems, the device offers a new layer of understanding that can help clarify these cases.The system extends beyond conception, offering support during pregnancy and postpartum. This continuity allows couples to remain engaged with their physiological health throughout the entire fertility journey. The solution is delivered in partnership with treating physicians and virtual clinics, integrating seamlessly into existing care pathways.ConclusionOTO Fertility introduces a predictive diagnostic system designed to improve IVF outcomes and support natural conception through physiological monitoring and AI‑driven guidance. By providing insight into fertility readiness, offering personalized recommendations, and addressing both partners' health, the system creates a more informed and supportive pathway for couples seeking to build their families. As fertility challenges continue to rise globally, technologies that deliver clarity, personalization, and noninvasive insight are becoming essential components of modern reproductive care.Interview by Don Baine, The Gadget Professor.Sponsored by: Get $5 to protect your credit card information online with Privacy. Amazon Prime gives you more than just free shipping. Get free music, TV shows, movies, videogames and more. Secure your connection and unlock a faster, safer internet by signing up for PureVPN today.

In this episode, Daniel Metcalf and Mike Stromsoe discuss the challenges and opportunities faced by independent insurance agencies as they scale. They emphasize the importance of visibility in understanding progress, the current landscape of AI in the industry, and the need for predictive analysis to drive future growth. The discussion also highlights the significance of leadership, structure, and technology in overcoming fragmentation and achieving sustainable growth.Key takeaways:You're not behind, you just can't see it.Visibility is crucial for understanding agency progress.83% of agencies have used AI, but only 10% see ROI.Clarity of vision is essential for agency growth.Revenue growth without system growth feels like falling behind.Leadership must evolve as agencies scale.Fragmentation can hinder agency efficiency and growth.Predictive analysis can help agencies plan for the future.Technology should complement human efforts, not replace them.Agencies need to identify and address workflow gaps. Chapters:00:00 Unlocking Potential in Insurance Agencies03:11 Visibility: The Key to Progress05:51 AI in Insurance: The Current Landscape08:51 Predictive Analysis: Looking Ahead12:03 Overcoming Fragmentation in Growth15:12 Leadership and Structure in Scaling Agencies17:59 The Role of Technology in Agency Growth21:01 Final Thoughts and Future Opportunities

Most health insurance brokers rely on reactive cost-containment strategies. They wait for a catastrophic claim to hit and then scramble to manage it through cheaper drug sourcing or traditional case management. But looking in the rearview mirror won't solve the reality of 20% stop-loss increases. To win in a brutal renewal market, brokers must shift from managing claims after the fact to avoiding them entirely.My guest, Ryan Chapman, VP of Sales at HealthCare Strategies, joins me to share the predictive care playbook. We discuss how AI algorithms can identify emerging health risks, like missed screenings and trending A1C levels, years before a member ever reaches the hospital. We break down how to position predictive intervention to self-funded employers, the strategy behind running low-risk pilot programs, and why stop-loss carriers are actively rewarding this proactive approach. This is the blueprint for delivering long-term savings and proving your value before you ever win the Agent of Record.▶▶ Sign Up For Your Free Discovery Callcompletegameu.com/agaCONNECT WITH ANDY NEARY

For the Good of the Public brings you news and weekly conversations at the intersection of faith and civic life. Monday through Thursday, The Morning Five starts your day off with scripture and prayer, as we also catch up on the news together. Throughout the year, we air limited series on Fridays to dive deeper into conversations with civic leaders, thinkers, and public servants reimagining public life for the good of the public. Today's host was Michael Wear, Founder, President and CEO of the Center for Christianity and Public Life.  Thanks for listening to The Morning Five! Please subscribe to and rate The Morning Five on your favorite podcast platform. Learn more about the work of the Center for Christianity and Public Life at www.ccpubliclife.org. Today's scripture: Matthew 7:7-11 News sources:  https://www.washingtonpost.com/world/2026/02/18/russia-ukraine-geneva-negotiations-impasse/  https://theconversation.com/air-pollution-may-directly-contribute-to-alzheimers-disease-new-study-275873  https://www.deseret.com/utah/2026/02/17/governor-cox-vows-legal-battle-over-prediction-markets/  https://www.nytimes.com/2026/02/18/technology/meta-65-million-election-ai.html  https://thehill.com/policy/technology/5742396-ai-regulation-midterm-ads/  https://ai-law-center.orrick.com/us-ai-law-tracker-see-all-states/  Join the conversation and follow us at: Instagram: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@michaelwear⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, @ccpubliclife Twitter: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@MichaelRWear⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, @ccpubliclife and check out ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@tsfnetwork⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Music by: King Sis #politics #faith #prayer #scripture #Russia #Ukraine #airpollution #Alzheimers #predictionmarkets #SpencerCox #BenSasse #AI #Meta #midterms Learn more about your ad choices. Visit megaphone.fm/adchoices

February 17th, 2026 EP: 081 AI or Oracle? The Rise of Predictive Personal Intelligence Can artificial intelligence move beyond algorithms and statistics to predict your future? In this one-off special, we explore whether AI could evolve into a modern-day Tech Oracle—capable of foreseeing personal destinies—or whether its insights remain bound to probabilities and pattern recognition. From predictive policing and life forecasting to eerie AI “coincidences,” we push past data science and into the uncanny, asking where technology ends… and the unknown begins.

AI is moving faster than most service businesses can keep up with. Voice agents. Text automation. Follow-up systems. AI sales emails. Predictive messaging. But here's the real question: How do you use AI to convert more leads without losing the human touch? In this episode of Service Business Mastery, Tersh Blissett and Joshua Crouch sit down with Ryan Fenn, CEO at CHIIRP, to break down what's actually working in AI-driven lead conversion right now. They dive into: Why speed to lead still wins (and why seconds matter) How one word in your follow-up could be killing 90 percent of your conversions Why most contractors misuse AI for sales emails How to "download your brain" into systems using AI Why tools are becoming commodities and experience is becoming king How AI agents are replacing static drip campaigns If you're a service business owner trying to figure out how to adopt AI without sounding robotic, this episode will give you clarity, strategy, and practical application. What You Will Learn in This Episode • Why speed to lead still dramatically impacts booking rates • The difference between static drip campaigns and dynamic AI follow-up • How AI can analyze hundreds of millions of messages to improve conversion • Why empathy in messaging increases response rates • How to use AI as an editor instead of a ghostwriter • How to turn 20 years of experience into systems and training using AI • Why the future of software is outcome-based, not tool-based • How to evaluate tech partners based on deployment experience, not features • Why humans will still matter even if AI becomes indistinguishable Timestamps 00:00 The AI arms race and what's changed 03:00 Why speed to lead still dominates 08:00 The future of AI in sales and follow-up 12:20 Why humans will still matter in the age of AI 21:20 Download your brain using AI 22:11 How to use AI to write better sales emails 27:24 Why experience matters more than software features 33:02 The single word that could be killing your sales 36:00 Is there such thing as responding too fast? 40:57 AI agents replacing static drip campaigns 49:00 What contractors should stop doing immediately Follow the Host and Guest Tersh Blissett: https://www.linkedin.com/in/tershblissett/ Josh Crouch: https://www.linkedin.com/in/josh-crouch/ Ryan Fenn: https://www.linkedin.com/in/ryan-fenn-76568b165/ CHIIRP: https://www.linkedin.com/company/chiirp/  Connect with Us • LinkedIn - https://www.linkedin.com/company/service-business-mastery • TikTok - https://www.tiktok.com/@servicebusinessmastery • Facebook Group - https://www.facebook.com/groups/servicebusinessmasterypodcast • Instagram - https://www.instagram.com/servicebusinessmasterypodcast  

Your team is sitting on closed loans… and doesn't even know it.In this episode, Josh Friend (CEO & Founder of Insellerate) explains how Aithena listens to 100% of your calls, surfaces the moments that win or lose deals, and predicts who's likely to close in the next 60 days—so your loan officers stop chasing dead ends and start closing more loans.If you lead mortgage sales, lending ops, call centers, or revenue teams, this is the AI episode that cuts through the hype—because it's not a shiny tool. It's real work getting done: call reviews, coaching, prioritization, and smarter follow-up.Automates call reviews by jumping straight to the critical moment (objection, missed step, buying signal)Gives managers 10 coachable moments in 20 minutes instead of wasting 20 minutes on one full callApplies a deal likelihood score so reps know who to call today vs. who to nurtureDetects borrower intent using patterns learned from 1M+ conversationsHelps reps stay confident and effective by prioritizing higher-probability borrowers firstTurns scattered conversations into a repeatable, coachable system that scalesWhen call volume spikes and rates shift, most teams can't tell the difference between:“Not ready”and“Ready to close—just not with you yet.”Aithena helps you find the borrowers who are most likely to act soon—before they close somewhere else.FAQ'sWhat is Aithena?Aithena is an AI platform from Insellerate that reviews calls, scores conversations, and delivers coaching + lead prioritization based on borrower intent.How does Aithena help close more loans?It identifies high-intent borrowers, surfaces objections and missed moments, improves coaching speed, and focuses reps on the leads most likely to close soon.Who should use Aithena?Mortgage and lending organizations, call centers, and revenue teams that want better call performance, faster coaching, and smarter follow-up.Email Josh: josh@insellerate.com0:00 Welcome + Josh Friend returns0:40 Why most AI projects fail ROI2:10 Aithena: AI call reviews + coaching moments4:00 100% call coverage and better insights5:20 Predictive lead scoring + borrower intent9:00 Sales confidence and performance11:10 Vibe coding + building faster with AI19:20 Events + how to connect21:30 Wrap-up###Michael Hammond, Founder of NexLevel Advisors, is the leading fractional CMO in mortgage and mortgage technology, specializing in AI-powered growth strategy and audience development.

Predictive, generative, agentic. These might be fairly new words, yet they already resonate and are immediately recognisable. Artificial Intelligence is turning the media landscape on its head, from powerful prediction planning tools to cutting-edge creative tech and innovative solutions to buy and optimise ad campaigns. AI is fundamentally reshaping the industry. A good example is Values Media, an independent media agency based in France, which recently completed a full TV campaign buying via agentic AI. We're only scratching the surface, but the implications are huge and profound. In this episode, we talked to Emmanuel Crego, Values Media Group Managing Director to talk about his perspectives and what the future potentially holds for the media industry. 

On today's episode, Joe, Prez and Bryan Power discuss the upcoming college basketball schedule and its massive implications, predictive market betting and more!00:00 INTRODUCTION00:31 WEEKEND RECAP06:03 HUGE CBB WEEK STARTS TONIGHT WITH HOUSTON VS IOWA STATE09:24 OLYMPIC HOCKEY PICKS17:13 PREDICTIVE MARKETS: NHL-CBB-NBA-BITCOIN29:40 PARLAY OF THE DAY36:00 TODAY'S BEST BETS38:43 CBB RUNDOWN: HOUSTON AT IOWA STATE40:30 MAILBAG! VIEWER QUESTIONS

 For one week in university, his dreams stopped feeling symbolic.They became precise. Predictive. Details appeared before reality caught up—conversations, locations, moments that unfolded exactly as he'd already seen them. It was unsettling, but still easy to rationalize.Until one dream went further.Sleep dropped him into a familiar bar and slowed time to a crawl. He watched a bullet spin toward him, felt the heat, the impact, the certainty of dying. When he woke up, the fear didn't fade. It lingered—enough to change his plans. So he stayed home.His friends didn't. Hours later, his roommate returned shaken with news that transformed the dream from coincidence into warning. After that, the dreams stopped—almost as if they'd said everything they needed to say.#RealGhostStoriesOnline #Premonition #PredictiveDreams #ParanormalPodcast #TrueStory #DreamWarning #DéjàVu #Unexplained #Intuition #CloseCall Love real ghost stories? Want even more?Become a supporter and unlock exclusive extras, ad-free episodes, and advanced access:

Did you know that there are predictable patterns of behavior that drive the success and failure of relationships? The Bible and the social sciences provide clear pathways to relational success, but the world system clouds them with chaos and confusion. We see the fallout in the trail of broken relationships, the ghosting phenomenon, the attachment crisis, and the tragic stats on anxiety and depression in the youngest generations. Join Dr. Lisa Dunne for today's show as we talk about the secrets of relational success, from friendship to marriage. With a few simple and strategic changes, you can activate patterns of predictive behavior that will strengthen your interpersonal relationships. K to 12 Rescue Mission: https://www.academicrescuemission.com Christian Community College: https://www.veritascc.us CVCU degree programs: https://www.cvcu.us Book Dr. Lisa to speak: https://www.DrLisaDunne.com @DrLisaDunne

Enterprise IT is drowning in repeat incidents, slow triage, and reactive firefighting—burning teams out while costs rise and service quality slips. In this episode, Sandy and Umesh Shiknis of Publicis Sapient explore how Sapient Sustain uses AI-driven automation, predictive insights, and self-healing workflows to break the cycle, turning IT operations from constant crisis mode into a resilient, proactive engine that sustains the business. They also discuss how Publicis Sapient is leveraging AI to address challenges in the healthcare sector. They put an importance on modernizing legacy systems while also emphasizing the concept of agentic AI.Check out more about Sapient Sustain here: https://www.publicissapient.com/sapient-ai/sustainIn this episode, they talk about:Publicis Sapient focuses on human-centered digital transformation in healthcareAI can accelerate product development and modernize legacy systemsIt's easy to confuse automation with simple elements of machine learning, which are progressively more deterministicOrganizations must establish guardrails for AI implementation because of how powerful agentic AI can beSapient Sustain helps healthcare companies manage and stabilize their applicationsThe end-user experience is crucial in technology deploymentAI can significantly reduce technical debt in healthcare organizationsHealthcare leaders should look at the boring stuff and focus on practical AI applicationsEducate your workforce to embrace the future instead of fearing itA Little About Umesh:Umesh Shiknis is Executive Vice President and Global Chief Growth Officer at Publicis Sapient, a human-centered, product-led digital business transformation firm. He leads global growth and go-to-market strategy, scaling new buying centers, accelerating client impact, and driving transformational revenue across industries. Previously, Umesh held senior leadership roles at Capgemini, Infosys, and ISG. His current focus is on taking the Publicis Sapient AI product suite—Sapient Slingshot, Bodhi, and Sapient Sustain—to market, turning AI innovation into measurable, enterprise-wide outcomes.

Prediction markets are exploding in popularity—but most people still don't understand how they actually work. In today's episode, we break down the surge in predictive markets, what they are, how they function, and the big questions traders are asking: Are prediction markets legal? How do they differ from traditional markets? And what risks do they carry for you as a participant? We'll cut through the hype and explain the mechanics behind event-based trading, how pricing reflects probability, and why regulators are paying closer attention. Whether you're looking at political prediction markets, economic-event contracts, or blockchain-based platforms, you need to understand the structure before you risk capital. I'll also answer several viewer questions—including a (slightly delayed!) response to Ed in San Jose about my recent Tesla trade and what was going through my mind during that position. If you're curious about alternative markets and evolving financial structures, this episode is a must-listen. Listen now:

HEADLINE: The Predictive Brain and Auditory Hallucinations. GUEST: Professor Andy Clark. SUMMARY: Clark explains how brains predict reality, using "White Christmas" auditory hallucination experiments and a deer-spotting anecdote to illustrate that expectation strongly shapes perception. 1917

On today's episode, Joe, Prez and Bryan Power discuss Super Bowl bad beats and bad bets, predictive market betting, NBA, college basketball and more!00:00 INTRODUCTION00:44 SUPER BOWL RECAP | BAD BEATS & BETS02:01 PREZ LEARNS THE NAME OF A BAD BUNNY SONG04:56 MAKING MONEY IN THE PREDICTIVE MARKETS06:21 NEW ENGLAND'S COACHING14:16 PREZ SHOUTS OUT MUSICIANS19:45 BE CAREFUL BETTING THE NBA MOVING FORWARD22:55 PARLAY OF THE DAY30:05 TODAY'S BEST BETS33:29 NBA RUNDOWN35:36 CBB RUNDOWN

In the rapidly evolving landscape of data science, the need for efficient and effective predictive modeling is more critical than ever. As organizations strive to leverage data for informed decision-making, the traditional methods of creating predictive models often prove to be cumbersome and time-consuming. However, the advent of autonomous data science agents, such as ELAI, is revolutionizing this process by automating predictive model creation and democratizing access to predictive analytics.The Challenge of Traditional Predictive ModelingHistorically, the creation of predictive models has been a labor-intensive endeavor, often requiring extensive manual effort. Organizations typically face significant roadblocks in data readiness, including issues related to data integration, cleaning, and enrichment. The process can take anywhere from six to nine months to develop a single predictive model, which is a considerable investment of time and resources. This lengthy timeline not only hinders the agility of businesses but also limits their ability to respond to market changes and customer needs effectively.Introducing ELAI: The Autonomous Data Science AgentELAI, described by its CEO Antonio Sciuto, is an autonomous data science agent designed to streamline the end-to-end workflow of predictive modeling. By combining a robust reasoning engine with machine learning capabilities, ELAI can automate the tasks associated with data integration, cleaning, enrichment, model deployment, backtesting, and maintenance. This innovative approach significantly reduces the time required to create predictive models, allowing organizations to transition from a six-to-nine-month timeline to just a few hours.ELAI's architecture is built to handle complex data environments. It can automatically integrate existing customer data with over 650 social and economic indicators, enriching the dataset and enhancing the predictive capabilities of the model. For instance, in the case of a company like QNX, which provides infotainment systems in vehicles, ELAI can analyze customer data to identify the best products for cross-selling, thereby optimizing sales strategies and improving customer satisfaction.Democratizing Predictive AIOne of the most significant contributions of ELAI is its potential to democratize predictive AI across various business functions. Traditionally, predictive modeling has been confined to specialized teams within organizations, limiting its accessibility. However, by automating the intricate processes involved in model creation, ELAI enables a broader range of stakeholders to engage with predictive analytics.Predictive models can now be applied to diverse areas such as human resources, where organizations can assess employee attrition risks and development needs; supply chain management, which benefits from enhanced forecasting and predictive maintenance; and customer relationship management, where businesses can optimize their offerings based on customer behavior and preferences. This democratization of predictive AI empowers organizations to make data-driven decisions across all functions, enhancing overall operational efficiency.The Future of Predictive ModelingAs the demand for data-driven insights continues to grow, the automation of predictive model creation represents a significant advancement in the field of data science. By reducing the time and complexity associated with traditional methods, autonomous agents like ELAI are enabling organizations to harness the power of predictive analytics more effectively. The implications of this shift are profound, as businesses can now respond rapidly to changing market dynamics and customer needs, ultimately leading to improved outcomes and competitive advantages.ConclusionIn conclusion, automating predictive model creation is not just a technological innovation; it is a transformative approach that redefines how organizations leverage data. By streamlining the modeling process and making predictive analytics accessible to a wider audience, tools like ELAI are paving the way for a future where data-driven decision-making is the norm, rather than the exception. As we embrace this new era of data science, the potential for enhanced insights and improved business performance is limitless.Interview by Scott Ertz of F5 Live: Refreshing Technology.Sponsored by: Get $5 to protect your credit card information online with Privacy. Amazon Prime gives you more than just free shipping. Get free music, TV shows, movies, videogames and more. Secure your connection and unlock a faster, safer internet by signing up for PureVPN today.

In the rapidly evolving landscape of data science, the need for efficient and effective predictive modeling is more critical than ever. As organizations strive to leverage data for informed decision-making, the traditional methods of creating predictive models often prove to be cumbersome and time-consuming. However, the advent of autonomous data science agents, such as ELAI, is revolutionizing this process by automating predictive model creation and democratizing access to predictive analytics.The Challenge of Traditional Predictive ModelingHistorically, the creation of predictive models has been a labor-intensive endeavor, often requiring extensive manual effort. Organizations typically face significant roadblocks in data readiness, including issues related to data integration, cleaning, and enrichment. The process can take anywhere from six to nine months to develop a single predictive model, which is a considerable investment of time and resources. This lengthy timeline not only hinders the agility of businesses but also limits their ability to respond to market changes and customer needs effectively.Introducing ELAI: The Autonomous Data Science AgentELAI, described by its CEO Antonio Sciuto, is an autonomous data science agent designed to streamline the end-to-end workflow of predictive modeling. By combining a robust reasoning engine with machine learning capabilities, ELAI can automate the tasks associated with data integration, cleaning, enrichment, model deployment, backtesting, and maintenance. This innovative approach significantly reduces the time required to create predictive models, allowing organizations to transition from a six-to-nine-month timeline to just a few hours.ELAI's architecture is built to handle complex data environments. It can automatically integrate existing customer data with over 650 social and economic indicators, enriching the dataset and enhancing the predictive capabilities of the model. For instance, in the case of a company like QNX, which provides infotainment systems in vehicles, ELAI can analyze customer data to identify the best products for cross-selling, thereby optimizing sales strategies and improving customer satisfaction.Democratizing Predictive AIOne of the most significant contributions of ELAI is its potential to democratize predictive AI across various business functions. Traditionally, predictive modeling has been confined to specialized teams within organizations, limiting its accessibility. However, by automating the intricate processes involved in model creation, ELAI enables a broader range of stakeholders to engage with predictive analytics.Predictive models can now be applied to diverse areas such as human resources, where organizations can assess employee attrition risks and development needs; supply chain management, which benefits from enhanced forecasting and predictive maintenance; and customer relationship management, where businesses can optimize their offerings based on customer behavior and preferences. This democratization of predictive AI empowers organizations to make data-driven decisions across all functions, enhancing overall operational efficiency.The Future of Predictive ModelingAs the demand for data-driven insights continues to grow, the automation of predictive model creation represents a significant advancement in the field of data science. By reducing the time and complexity associated with traditional methods, autonomous agents like ELAI are enabling organizations to harness the power of predictive analytics more effectively. The implications of this shift are profound, as businesses can now respond rapidly to changing market dynamics and customer needs, ultimately leading to improved outcomes and competitive advantages.ConclusionIn conclusion, automating predictive model creation is not just a technological innovation; it is a transformative approach that redefines how organizations leverage data. By streamlining the modeling process and making predictive analytics accessible to a wider audience, tools like ELAI are paving the way for a future where data-driven decision-making is the norm, rather than the exception. As we embrace this new era of data science, the potential for enhanced insights and improved business performance is limitless.Interview by Scott Ertz of F5 Live: Refreshing Technology.Sponsored by: Get $5 to protect your credit card information online with Privacy. Amazon Prime gives you more than just free shipping. Get free music, TV shows, movies, videogames and more. Secure your connection and unlock a faster, safer internet by signing up for PureVPN today.

Guest IntroductionRick Griffin is the founder and CEO of the Neuro Leadership Academy, an organization dedicated to demystifying neuroscience and making it actionable for everyday life, leadership, and healing. With a master's degree in education, Rick is known for translating complex brain science into engaging, usable concepts.Before launching Neuro Leadership Academy, he spent decades as the executive director of a trauma-informed therapeutic residential program for teens, witnessing firsthand how past struggles shape present behavior. This experience ignited his passion to understand the brain's role in trauma and resilience.Rick is a renowned speaker and developer of programs used by schools, businesses, and community organizations, including the Certified Trauma-Informed Specialist micro-credential. He now focuses on writing, teaching, and designing training that applies neuroscience to leadership, learning, relationship-building, and culture, helping people move from being trauma-informed to what he calls "neuro-informed."Summary / Key Takeaways:In this enlightening conversation, Rick Griffin explains the core concept of the brain as a prediction machine. Our experiences aren't direct recordings of reality, but constructions created by our brain based on sensory input and past experiences. Its primary job is to keep us safe by asking: "Is this a threat, or is this a resource?"Key Insights:Prediction Over Perception: We don't just react to the world; our brain constantly predicts what will happen next based on past patterns to conserve energy and ensure survival.The Threat Bias: The brain's default setting leans toward predicting potential threats (e.g., "Is that something that will eat me?"). This is the root of the stress/trauma response.From Trauma-Informed to Neuro-Informed: Understanding behavior shifts from "What happened to you?" to "How is your brain preparing you for what's happening right now?" This removes blame and focuses on the brain's protective, biological function.Healing Through Prediction: Recovery—from trauma or concussion—involves helping the brain make new, safer predictions. By intentionally introducing safe, positive sensory experiences (sights, smells, sounds, connection), we can create predictions that update the brain's model of the world.Agency & The "Sensory Buffet": With 11 million sensory inputs processed every second, we have immense power to influence our state. We can "stamp" resilience into simple cues (a mint, a coin, a song) and use them to ground ourselves or others.Application to Concussion Recovery: Symptoms like brain fog, fatigue, and anxiety are not signs of a "broken" brain, but of a brain in protection mode, reallocating energy to heal. Recognizing this allows for self-compassion and intentional practices (like rest and calibrated sensory input) to support the healing process.Resources Mentioned by Rick:Book: How Emotions Are Made: The Secret Life of the Brain by Dr. Lisa Feldman Barrett. This book was Rick's gateway into understanding the predictive brain.Website: Neuro-LA.com (Home of the NeuroLeadership Academy)Newsletter/Substack: Neuro Notes – Weekly articles on neuro-informed practices. Subscribe at: https://rickgriffin894.substack.comLinkedIn: linkedin.com/in/rick-griffin-nlaEmail: Rick@neuro-LA.com (He welcomes engagement and questions)Services: Rick offers keynote speaking, virtual and in-person training, workshops, and consulting for organizations. He also has a series of eBooks available. Contact him via email or his website for more information.Bethany Lewis & The Concussion Coach:Free Guide: "5 Best Ways to Support Your Loved One Dealing with a Concussion" - Download at www.theconcussioncoach.comConcussion Coaching Program: For personalized mentorship in recovery. Sign up for a free consultation HERE 

“Predictive coding offers a powerful lens for understanding psychosis…”Dr. Marta Garrido is a professor at the Melbourne School of Psychological Sciences, where she leads the Cognitive Neuroscience and Computational Psychiatry Laboratory and directs the Cognitive Neuroscience Hub. She is also a research program lead at the Graeme Clark Institute. With a background in engineering physics from the University of Lisbon and a PhD in neuroscience from University College London under the mentorship of Professor Karl Friston, Marta has become a leading figure in understanding how the brain processes predictions and surprise. Her research spans mismatch negativity, predictive coding theory, dynamic causal modeling, and the development of cutting-edge neuroimaging technologies, including Australia's first optically pumped MEG system.In this episode, Peter and Marta explore the elegant framework of predictive coding and its implications for understanding psychiatric conditions like psychosis. They discuss how the brain generates predictions about sensory input and how disruptions in these mechanisms may contribute to symptoms of mental illness. Marta shares her journey from engineering to neuroscience, her transformative PhD experience, and the challenges of building a new MEG system from the ground up. The conversation covers fascinating topics including mismatch negativity as a prediction error signal, subcortical shortcuts for processing threatening stimuli, the phenomenon of blindsight, and the critical importance of mentorship in academic careers. Marta also offers candid reflections on being a woman in neuroscience and her vision for the future of computational psychiatry.We hope you enjoy this episode!Chapters:00:00 - Introduction to Dr. Marta Guerrero04:46 - Journey from Engineering to Neuroscience10:39 - Understanding Predictive Coding and Bayesian Inference18:34 - Implications of Predictive Coding in Schizophrenia27:08 - Advancements in Brain Imaging Techniques36:31 - Exploring Blindsight and Subcortical Shortcuts44:14 - Reverse Engineering the Brain: Challenges and Ambitions51:23 - The Journey of Developing Optically Pumped Magnetometers01:00:29 - Promoting Women in Neuroscience and Leadership ChallengesWorks mentioned:15:59 - Randeniya et al. (2018). Sensory prediction errors in the continuum of psychosis. https://doi.org/10.1016/j.schres.2017.04.01918:36 - Goodwin et al. (2026). Predictive processing accounts of psychosis: Bottom-up or top-down disruptions. https://doi.org/10.1038/s44220-025-00558-526:02 - Larsen et al. (2019). 22q11.2 deletion syndrome: intact prediction but reduced adaptation. https://doi.org/10.1016/j.nicl.2019.10172129:40 - Garvert et al. (2014). Subcortical amygdala pathways enable rapid face processing. https://doi.org/10.1016/j.neuroimage.2014.07.04729:40 - McFadyen et al. (2017). A rapid subcortical amygdala route for faces. https://doi.org/10.1523/JNEUROSCI.3525-16.2017Episode producers:Karthik Sama, Xuqian Michelle Li

Unlock real ROI with predictive AI in this episode of Future Tech featuring Pecan AI CEO Zohar Bronfman. While GenAI dominates headlines, Zohar breaks down how predictive models are quietly transforming decision-making and operations across industries. From data democratization to actionable use cases, this episode is a must-listen for leaders ready to use AI to solve real business problems — not just chase trends.

In this episode of The Lectern, host Ethan Hsieh sits down with philosopher and cognitive scientist Mark Miller to explore the science of predictive processing and its implications for happiness, meaning, and wellbeing. They unpack how the brain is not a passive receiver of reality, but an active prediction engine—constantly generating its best guesses about the world and updating them through experience. From belief formation and perception to resilience, virtue, play, and mindfulness, the conversation bridges cutting-edge cognitive science with ancient contemplative wisdom. Together, Ethan and Mark discuss how understanding the predictive nature of the mind can transform how we relate to uncertainty, cultivate agency, and develop a deeper, more participatory sense of happiness—both individually and collectively. This episode also introduces Mark Miller's upcoming course, Generations of Joy, which explores these ideas through neuroscience, philosophy, and contemplative practice. Sign up for the course: https://lectern.johnvervaeke.com/courses/generations-of-joy   00:00 Welcome back to The Lectern 02:30 Mark Miller's background and research focus 06:00 Predictive processing and cognitive science 09:00 Belief, perception, and meaning-making 10:18 "You're not seeing the world—you're seeing your best guess about the world." 13:00 Course overview and key themes 27:00 Honesty, virtue, and transformation 39:30 Practical applications and course dynamics 41:30 Real-world implications of science 43:00 Emptiness, neuroscience, and insight 43:30 The frame problem in cognitive science 45:30 Optimism vs. pessimism: locking onto the world 46:30 Training the mind to discern 47:30 The interpretive nature of reality 52:00 The role of play in cognitive development 56:00 Managing uncertainty through play 01:12:30 Mindfulness and emerging evidence 01:22:00 The Transformational Neuroscience course   Mark Miller is a philosopher and cognitive scientist whose work bridges philosophy, neuroscience, and contemplative science. His research explores how the predictive brain shapes happiness, wellbeing, and meaning in a technologically saturated world. He is a Senior Research Fellow at Monash University's Centre for Consciousness and Contemplative Studies (Australia), cross-affiliated with the Psychology Department at the University of Toronto (Canada), and a visiting researcher at Hokkaido University's Centre for Human Nature, Artificial Intelligence, and Neuroscience (Japan). Website: https://www.markdmiller.live/   Ethan Hsieh is a facilitator, educator, and philosophical practitioner working at the intersection of performance, cognition, and transformative pedagogy. He is the creator of TIAMAT, a three-tier developmental framework integrating cognitive science, dialogical philosophy, and embodied practice. Through immersive learning environments and collaborative inquiry, Ethan helps individuals cultivate virtuosity as a way of life—emphasizing participatory sense-making, metacognitive mapping, and shared agency. His work with the 5toMidnight collective focuses on building deliberately developmental communities grounded in relational ontology and lived philosophical transformation.

NEW 2026 PODCAST SCHEDULEGuest Episodes every MondayAstrology Episodes with Vanessa every ThursdayWatch this episode on Youtube: https://youtu.be/jUVWEnvI5lAReady to work with astrology in a grounded, practical way?Book your 2026 Astrology Session or Package here: https://vanessasoul.com/AstrologyEpisode 139: Astrology Is a Cheat Code for Conscious Entrepreneurs with Vanessa Soul Astrology doesn't have to be confusing, overwhelming, or something you “believe in” to be useful.In this episode of the Power and Purpose Podcast, Vanessa Soul shares why astrology is officially becoming a regular part of the show and how to use it as a functional, real-world tool for navigating life, business, relationships, and major decisions with more clarity and confidence.This conversation sets the foundation for the Thursday astrology episodes, so whether you're astrology-curious or already familiar with the language, you'll walk away with enough context to actually apply what you hear without feeling overloaded or intimidated.Astrology is not about labels or identity alone. It's about understanding the energetic weather so you can prepare, respond intentionally, and stop feeling blindsided by change.What You'll Learn in This Episode• Why astrology works best as a practical, functional tool• The difference between identity astrology and usable astrology• How to use astrology without studying charts or memorizing meanings• Why knowing your Sun, Rising, and Moon really matters• How transits impact your emotions, decisions, and business timing• Why astrology is like checking the weather, not predicting fate• When astrology helps you prepare instead of react• How to integrate astrology with intuition and modern toolsTimestamps00:00 – Welcome and why attention matters01:00 – The new 2026 podcast schedule explained02:35 – Why astrology is returning to the podcast03:30 – What functional astrology actually is05:10 – Identity astrology vs practical application06:30 – Who these astrology episodes are for09:30 – Using astrology in business, career, and daily life11:00 – Timing awareness and common astrology “do nots”13:00 – Astrology styles, house systems, and philosophy15:20 – Understanding the Big Three: Sun, Rising, Moon17:00 – The Rising sign, identity, and the first house18:15 – The Moon, emotions, and fulfillment19:10 – Why houses matter more than memorization22:30 – Using astrology updates without full chart readings26:20 – Astrology as energetic weather forecasting28:30 – Predictive astrology vs thematic astrology31:30 – Building trust instead of dependency with astrology33:00 – Closing thoughts and what's coming next

Gamble on anything & everything.

Rheumatoid arthritis is often seen as “just” joint pain, but Mayo Clinic rheumatologist Dr. John Davis and University of Colorado researcher Dr. Kevin Deane reveal a far more complex and promising story. In this episode of Tomorrow's Cure, host and journalist Cathy Wurzer explores how autoimmune disease can quietly develop for years before the first swollen joint, and how new blood tests, gut microbiome insights, and the exposome, our lifetime of environmental exposures such as cigarette smoke and wildfire haze, are helping clinicians see risk much earlier. The conversation dives into emerging tools that use artificial intelligence to sift through genetics, autoantibodies, microbiome data, and real-world exposures to predict who is most likely to develop rheumatoid arthritis and who will respond to specific treatments. Hear how prevention trials, lessons from type 1 diabetes, and more virtual models of care could change what it means to live with, or even avoid, rheumatoid arthritis in the future. How to listen and stay connected: Subscribe to Tomorrow's Cure on your favorite podcast app and follow the show so you never miss an episode. Get the latest health information from Mayo Clinic's experts—subscribe to Mayo Clinic's newsletter for free today: https://mayocl.in/3EcNPNc Connect with Mayo Clinic: Like Mayo Clinic on Facebook: https://www.facebook.com/mayoclinic/ Follow Mayo Clinic on Instagram: https://www.instagram.com/mayoclinic/ Follow Mayo Clinic on X (formerly Twitter): https://x.com/MayoClinic Follow Mayo Clinic on Threads: https://www.threads.net/@mayoclinic

Iaaaago Jorge convida Raphael Barreto e Lucas Brandão para discutir sobre neutropenia febril, em 5 clinicagens:1. Neutropenia febril é emergência oncológica2. Como escolher o antibiótico?3. Quando escalonar o antibiótico?4. Quando suspender o antibiótico?5. Quando prescrever filgrastim?Referências:1. Klastersky J, de Naurois J, Rolston K, et al. Management of febrile neutropaenia: ESMO Clinical Practice Guidelines. Ann Oncol. 2016;27(suppl 5):v111-v118. doi:10.1093/annonc/mdw3252. Taplitz RA, Kennedy EB, Bow EJ, et al. Outpatient Management of Fever and Neutropenia in Adults Treated for Malignancy: American Society of Clinical Oncology and Infectious Diseases Society of America Clinical Practice Guideline Update. J Clin Oncol. 2018;36(14):1443-1453. doi:10.1200/JCO.2017.77.62113. Zhang H, Wu Y, Lin Z, et al. Naproxen for the treatment of neoplastic fever: A PRISMA-compliant systematic review and meta-analysis. Medicine (Baltimore). 2019;98(22):e15840. doi:10.1097/MD.00000000000158404. Zheng B, Huang Z, Huang Y, Hong L, Li J, Wu J. Predictive value of monocytes and lymphocytes for short-term neutrophil changes in chemotherapy-induced severe neutropenia in solid tumors. Support Care Cancer. 2020;28(3):1289-1294. doi:10.1007/s00520-019-04946-35. Douglas C, Morse JD, Anderson BJ. Mucositis Pain and Its Temporal Relationship to White Cell Count. Paediatr Anaesth. 2025;35(4):302-309. doi:10.1111/pan.150636. Vassallo M, Michelangeli C, Fabre R, et al. Procalcitonin and C-Reactive Protein/Procalcitonin Ratio as Markers of Infection in Patients With Solid Tumors. Front Med (Lausanne). 2021;8:627967. Published 2021 Mar 12. doi:10.3389/fmed.2021.6279677. Smith TJ, Bohlke K, Lyman GH, et al. Recommendations for the Use of WBC Growth Factors: American Society of Clinical Oncology Clinical Practice Guideline Update. J Clin Oncol. 2015;33(28):3199-3212. doi:10.1200/JCO.2015.62.34888. Heil G, Hoelzer D, Sanz MA, et al. A randomized, double-blind, placebo-controlled, phase III study of filgrastim in remission induction and consolidation therapy for adults with de novo acute myeloid leukemia. The International Acute Myeloid Leukemia Study Group. Blood. 1997;90(12):4710-4718.9. Weiss JM, Csoszi T, Maglakelidze M, et al. Myelopreservation with the CDK4/6 inhibitor trilaciclib in patients with small-cell lung cancer receiving first-line chemotherapy: a phase Ib/randomized phase II trial. Ann Oncol. 2019;30(10):1613-1621. doi:10.1093/annonc/mdz27810. Bodey GP, Buckley M, Sathe YS, Freireich EJ. Quantitative relationships between circulating leukocytes and infection in patients with acute leukemia. Ann Intern Med. 1966;64(2):328-340. doi:10.7326/0003-4819-64-2-32811. Nucci M, Arrais-Rodrigues C, Bergamasco MD, et al. Management of febrile neutropenia: consensus of the Brazilian Association of Hematology, Blood Transfusion and Cell Therapy - ABHH. Hematol Transfus Cell Ther. 2024;46 Suppl 6(Suppl 6):S346-S361. doi:10.1016/j.htct.2024.11.11912. Guarana M, Nucci M, Nouér SA. Shock and Early Death in Hematologic Patients with Febrile Neutropenia. Antimicrob Agents Chemother. 2019;63(11):e01250-19. Published 2019 Oct 22. doi:10.1128/AAC.01250-1913. Rosa RG, Goldani LZ. Cohort study of the impact of time to antibiotic administration on mortality in patients with febrile neutropenia. Antimicrob Agents Chemother. 2014;58(7):3799-3803. doi:10.1128/AAC.02561-1414. Averbuch D, Orasch C, Cordonnier C, et al. European guidelines for empirical antibacterial therapy for febrile neutropenic patients in the era of growing resistance: summary of the 2011 4th European Conference on Infections in Leukemia. Haematologica. 2013;98(12):1826-1835. doi:10.3324/haematol.2013.09102515. Beyar-Katz O, Dickstein Y, Borok S, Vidal L, Leibovici L, Paul M. Empirical antibiotics targeting gram-positive bacteria for the treatment of febrile neutropenic patients with cancer. Cochrane Database Syst Rev. 2017;6(6):CD003914. Published 2017 Jun 3. doi:10.1002/14651858.CD003914.pub416. Puerta-Alcalde P, Cardozo C, Suárez-Lledó M, et al. Current time-to-positivity of blood cultures in febrile neutropenia: a tool to be used in stewardship de-escalation strategies. Clin Microbiol Infect. 2019;25(4):447-453. doi:10.1016/j.cmi.2018.07.02617. Ljungman P, Alain S, Chemaly RF, et al. Recommendations from the 10th European Conference on Infections in Leukaemia for the management of cytomegalovirus in patients after allogeneic haematopoietic cell transplantation and other T-cell-engaging therapies. Lancet Infect Dis. 2025;25(8):e451-e462. doi:10.1016/S1473-3099(25)00069-618. Maertens J, Lodewyck T, Donnelly JP, et al. Empiric vs Preemptive Antifungal Strategy in High-Risk Neutropenic Patients on Fluconazole Prophylaxis: A Randomized Trial of the European Organization for Research and Treatment of Cancer. Clin Infect Dis. 2023;76(4):674-682. doi:10.1093/cid/ciac62319. Aguilar-Guisado M, Espigado I, Martín-Peña A, et al. Optimisation of empirical antimicrobial therapy in patients with haematological malignancies and febrile neutropenia (How Long study): an open-label, randomised, controlled phase 4 trial. Lancet Haematol. 2017;4(12):e573-e583. doi:10.1016/S2352-3026(17)30211-9

Voicemail: 951-292-4377;  Predictive market platforms;  Hard 16 vs. Ace in blackjack;  Las Vegas buffets;  What's better in casinos now vs. forty years ago;  Trip reports:  Aruba;  Black Hawk;  Hard Rock Casino Tejon

Noble Predictive Insights has released its power rankings of Arizona and national politicians. Mike Noble, CEO of Noble Predictive Insights, talks about the poll and the shocking places some politicians got.

In this stream I am joined by professor Jiang of the YouTube channel Predictive History to discuss his game theory in light of Orthodox prophecy and tradition concerning the direction of the world. Make sure to leave a comment and let me know what you think. God Bless

Deep Dive in DDH is a three-part limited series where experts in the field of DDH have been invited to discuss the controversies in the management of hip dysplasia. Episode 1 was published in August and discussed management of DDH in infants under 6 months of age. In Episode 2, we are joined by Eduardo Novais at Nemour Children's Health in Jacksonville and Salil Upasani of Rady Children's Hospital and discuss the controversies in the management of developmental hip dislocations in the operating room including the process to decide between closed and open reduction, the use of concomitant osteotomies, adjunctive imaging, and casting protocols. Hosted by Will Morris (Scottish Rite for Children). Music by A. A. Aalto. Referenced Publications: Novais EN, Hill MK, Carry PM, Heyn PC. Is Age or Surgical Approach Associated With Osteonecrosis in Patients With Developmental Dysplasia of the Hip? A Meta-analysis. Clin Orthop Relat Res. 2016 May;474(5):1166-77. doi: 10.1007/s11999-015-4590-5. PMID: 26472583; PMCID: PMC4814411. Schmaranzer F, Justo P, Kallini JR, Ferrer MG, Miller P, Bixby SD, Novais EN. Hip Morphology on Post-Reduction MRI Predicts Residual Dysplasia 10 Years After Open or Closed Reduction. J Bone Joint Surg Am. 2024 Jan 17;106(2):110-119. doi: 10.2106/JBJS.23.00333. Epub 2023 Nov 22. PMID: 37992184; PMCID: PMC12205695. Morris WZ, Chilakapati S, Hinds SA, Herring JA, Kim HKW. The Clinical Significance of Infolded Limbus on Postreduction Arthrogram in Developmental Dysplasia of the Hip. J Pediatr Orthop. 2022 Apr 1;42(4):e309-e314. doi: 10.1097/BPO.0000000000002070. PMID: 35132011. Morris WZ, Hinds S, Worrall H, Jo CH, Kim HKW. Secondary Surgery and Residual Dysplasia Following Late Closed or Open Reduction of Developmental Dysplasia of the Hip. J Bone Joint Surg Am. 2021 Feb 3;103(3):235-242. doi: 10.2106/JBJS.20.00562. PMID: 33252590. Gans I, Sankar WN. The medial dye pool revisited: correlation between arthrography and MRI In closed reductions for DDH. J Pediatr Orthop. 2014 Dec;34(8):787-90. doi: 10.1097/BPO.0000000000000187. PMID: 24787303. Novais EN, Hollnagel KF, Bixby SD, Ferrer MG, Williams DN, Kim YJ, Schmaranzer F. Predictive value of post-reduction gadolinium-enhanced magnetic resonance imaging in detecting avascular necrosis after closed and open reduction for developmental dysplasia: A minimum 5-year follow-up study. J Child Orthop. 2025 Jul 6;19(4):329-338. doi: 10.1177/18632521251350524. PMID: 40630930; PMCID: PMC12230044. Paez C, Badrinath R, Holt J, Bomar JD, Mubarak SJ, Upasani VV, Wenger DR. Ligamentum Teres Transfer During Medial Open Reduction in Patients with Developmental Dysplasia of the Hip. Iowa Orthop J. 2021;41(1):47-53. PMID: 34552403; PMCID: PMC8259203.

As 2025 closed, small business remained resilient with job growth showing very little variation throughout the year, while hourly wage growth finished close to inflation, according to Paychex Small Business Employment Watch. Manufacturing didn't fare well last year and is in contraction, according to the Purchasing Manager's Index. Some industries such as computer and electronic products have seen expansion, but eyes are on what impact tariffs will continue to have. Gene Marks offers insights on these topics, as well as details on a lawsuit in NYC on predictive scheduling that cost Starbucks $39 million to settle. Businesses need to be aware of similar laws in their states.  Additional Resources Meet Paychex: https://bit.ly/3VtM6bs On-demand webinar on top regulatory issues: https://bit.ly/2026-top-regs-webinar Top Regulatory Issues of 2026 article: https://bit.ly/top-regs-2026 No Tax on Tips and OT webinar registration: https://bit.ly/no-tax-on-tips-ot No Tax on Tips article: https://bit.ly/no-tax-tips-ot DISCLAIMER: The information presented in this podcast, and that is further provided by the presenter, should not be considered legal or accounting advice, and should not substitute for legal, accounting, or other professional advice in which the facts and circumstances may warrant. We encourage you to consult legal counsel as it pertains to your own unique situation(s) and/or with any specific legal questions you may have.

Most people think goal failure is a mindset issue, but the real constraint is often physiological. This episode reframes why we don't rise to our goals, we return to the baseline our nervous system has been conditioned to expect. I break down how predictive physiology, stress exposure, and environmental consistency shape metabolism, hormones, and behavior over time. Topics discussed: - Physiological baselines explained- Predictive nervous system- Stress conditioning patterns- Homeostasis versus optimization- Familiar stress responses- Environment over intensity