Podcasts about predictive

Get the full 15 year ad-free archive, including all 2 hour extended interviews with THC+: Subscribe via our website and get the Plus show on your usual podcast apps with a custom RSS feed or at TheHighersideChats.com Subscribe via Patreon if Spotify playback & payment through Paypal are important to you. About Today's Guest: Professor Jiang […] The post Professor Jiang Xueqin | Predictive History, Western Collapse, & The Ivy League Issue appeared first on The Higherside Chats.

In this PT-2 follow up episode to a September 29, 2025, we will objectively explore the details of the Snake Eyes movie and its relationship to the assassination of Charlie Kirk. Despite there being seemingly incredible parallels, many of the important correlations have been ignored in favor of assumed connections like the 9/10 date of the assassination, which was actually 9/19 in the movie, or the 911 in an Erika Kirk music video that was cropped to ignore other numbers. The film features a Charles Kirkland being shot in the neck, taken to the hospital, and later dying during a public event. A strange character is pumping his fist and chanting in front of the camera, a character named Tyler is involved in the conspiracy, and the iconic motifs of the ‘woman in red' and ‘woman in white' are present. There is also the all-seeing eye and lucky number 7. But beyond the real life parallels and other occult imagery, the movie involves a hurricane named Jezebel, which strangely connects to the real Charlie Kirk. Why? Because the leftwing, feminist, anti-child cult website Jezebel published an article two days before Kirk's death about Etsy witches being hired to cast spells against the conservative commentator as an ‘ethical' stance against his opinions.*The is the FREE archive, which includes advertisements. If you want an ad-free experience, you can subscribe below underneath the show description.FREE ARCHIVE (w. ads)SUBSCRIPTION ARCHIVEX / TWITTER FACEBOOKWEBSITEBuyMe-CoffeePaypal: rdgable1991@gmail.comCashApp: $rdgable EMAIL: rdgable@yahoo.com / TSTRadio@protonmail.comBecome a supporter of this podcast: https://www.spreaker.com/podcast/the-secret-teachings--5328407/support.

Luigi Lenguito is the founder and CEO of BforeAI, which recently announced $15 million in Series A funding led by SYN Ventures. In this episode, he joins host Paul John Spaulding to discuss the announcement, including what the funding will be used for, and more. • For more on cybersecurity, visit us at https://cybersecurityventures.com

Stephen's linkshttps://bgbodymindspirit.com/https://www.spreaker.com/podcast/bgcast--5832809https://rumble.com/user/BGcast?e9s=src_v1_sa%2Csrc_v1_sa_mDoors of Perception is available now on Amazon Prime!https://watch.amazon.com/detail?gti=amzn1.dv.gti.8a60e6c7-678d-4502-b335-adfbb30697b8&ref_=atv_lp_share_mv&r=webDoors of Perception official trailerhttps://youtu.be/F-VJ01kMSII?si=Ee6xwtUONA18HNLZIndependent Media Token https://www.independentmediatoken.com/Merchhttps://fknstore.net/Start your microdosing journey with BrainsupremeGet 15% off your order here!!https://brainsupreme.co/FKN15Book a free consultation with Jennifer Halcame Emailjenniferhalcame@gmail.comFacebook pagehttps://www.facebook.com/profile.php?id=61561665957079&mibextid=ZbWKwLWatch The Forbidden Documentary: Occult Louisiana on Tubi: https://link.tubi.tv/pGXW6chxCJbC60 PurplePowerhttps://go.shopc60.com/FORBIDDEN10/or use coupon code knowledge10FKN Link Treehttps://linktr.ee/FKNlinksForbidden Knowledge Network https://forbiddenknowledge.news/ Make a Donation to Forbidden Knowledge News https://www.paypal.me/forbiddenknowledgenehttps://buymeacoffee.com/forbiddenJohnny Larson's artworkhttps://www.patreon.com/JohnnyLarsonSign up on Rokfin!https://rokfin.com/fknplusPodcastshttps://www.spreaker.com/show/forbiddenAvailable on all platforms Support FKN on Spreaker https://spreaker.page.link/KoPgfbEq8kcsR5oj9FKN ON Rumblehttps://rumble.com/c/FKNpGet Cory Hughes books!Lee Harvey Oswald In Black and White https://www.amazon.com/dp/B0FJ2PQJRMA Warning From History Audio bookhttps://buymeacoffee.com/jfkbook/e/392579https://www.buymeacoffee.com/jfkbookhttps://www.amazon.com/Warning-History-Cory-Hughes/dp/B0CL14VQY6/ref=mp_s_a_1_1?crid=72HEFZQA7TAP&keywords=a+warning+from+history+cory+hughes&qid=1698861279&sprefix=a+warning+fro%2Caps%2C121&sr=8-1https://coryhughes.org/YouTube https://youtube.com/@fknclipspBecome Self-Sufficient With A Food Forest!!https://foodforestabundance.com/get-started/?ref=CHRISTOPHERMATHUse coupon code: FORBIDDEN for discountsOur Facebook pageshttps://www.facebook.com/forbiddenknowledgenewsconspiracy/https://www.facebook.com/FKNNetwork/Instagram @forbiddenknowledgenews1@forbiddenknowledgenetworkXhttps://x.com/ForbiddenKnow10?t=uO5AqEtDuHdF9fXYtCUtfw&s=09Email meforbiddenknowledgenews@gmail.comsome music thanks to:https://www.bensound.com/Become a supporter of this podcast: https://www.spreaker.com/podcast/forbidden-knowledge-news--3589233/support.

AI is reshaping industries at a rapid pace, but as its influence grows, so do the ethical concerns that come with it.   This episode examines how AI is being applied across sectors such as healthcare, finance, and retail, while also exploring the crucial issue of ensuring that these technologies align with human values.   In this conversation, Lois Houston and Nikita Abraham are joined by Hemant Gahankari, Senior Principal OCI Instructor, who emphasizes the importance of fairness, inclusivity, transparency, and accountability in AI systems.   AI for You: https://mylearn.oracle.com/ou/course/ai-for-you/152601/   Oracle University Learning Community: https://education.oracle.com/ou-community   LinkedIn: https://www.linkedin.com/showcase/oracle-university/   X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode.   ---------------------------------------------------- Episode Transcript:   00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:25 Lois: Welcome to the Oracle University Podcast! I'm Lois Houston, Director of Innovation Programs with Oracle University, and with me is Nikita Abraham, Team Lead: Editorial Services. Nikita: Hey everyone! In our last episode, we spoke about how Oracle integrates AI capabilities into its Fusion Applications to enhance business workflows, and we focused on Predictive, Generative, and Agentic AI. Lois: Today, we'll discuss the various applications of AI. This is the final episode in our AI series, and before we close, we'll also touch upon ethical and responsible AI.  01:01 Nikita: Taking us through all of this is Senior Principal OCI Instructor Hemant Gahankari. Hi Hemant! AI is pretty much everywhere today. So, can you explain how it is being used in industries like retail, hospitality, health care, and so on?  Hemant: AI isn't just for sci-fi movies anymore. It's helping doctors spot diseases earlier and even discover new drugs faster. Imagine an AI that can look at an X-ray and say, hey, there is something sketchy here before a human even notices. Wild, right? Banks and fintech companies are all over AI. Fraud detection. AI has got it covered. Those robo advisors managing your investments? That's AI too. Ever noticed how e-commerce companies always seem to know what you want? That's AI studying your habits and nudging you towards that next purchase or binge watch. Factories are getting smarter. AI predicts when machines will fail so they can fix them before everything grinds to a halt. Less downtime, more efficiency. Everyone wins. Farming has gone high tech. Drones and AI analyze crops, optimize water use, and even help with harvesting. Self-driving cars get all the hype, but even your everyday GPS uses AI to dodge traffic jams. And if AI can save me from sitting in bumper-to-bumper traffic, I'm all for it. 02:40 Nikita: Agreed! Thanks for that overview, but let's get into specific scenarios within each industry.  Hemant: Let us take a scenario in the retail industry-- a retail clothing line with dozens of brick-and-mortar stores. Maintaining proper inventory levels in stores and regional warehouses is critical for retailers. In this low-margin business, being out of a popular product is especially challenging during sales and promotions. Managers want to delight shoppers and increase sales but without overbuying. That's where AI steps in. The retailer has multiple information sources, ranging from point-of-sale terminals to warehouse inventory systems. This data can be used to train a forecasting model that can make predictions, such as demand increase due to a holiday or planned marketing promotion, and determine the time required to acquire and distribute the extra inventory. Most ERP-based forecasting systems can produce sophisticated reports. A generative AI report writer goes further, creating custom plain-language summaries of these reports tailored for each store, instructing managers about how to maximize sales of well-stocked items while mitigating possible shortages. 04:11 Lois: Ok. How is AI being used in the hospitality sector, Hemant? Hemant: Let us take an example of a hotel chain that depends on positive ratings on social media and review websites. One common challenge they face is keeping track of online reviews, leading to missed opportunities to engage unhappy customers complaining on social media. Hotel managers don't know what's being said fast enough to address problems in real-time. Here, AI can be used to create a large data set from the tens of thousands of previously published online reviews. A textual language AI system can perform a sentiment analysis across the data to determine a baseline that can be periodically re-evaluated to spot trends. Data scientists could also build a model that correlates these textual messages and their sentiments against specific hotel locations and other factors, such as weather. Generative AI can extract valuable suggestions and insights from both positive and negative comments. 05:27 Nikita: That's great. And what about Financial Services? I know banks use AI quite often to detect fraud. Hemant: Unfortunately, fraud can creep into any part of a bank's retail operations. Fraud can happen with online transactions, from a phone or browser, and offsite ATMs too. Without trust, banks won't have customers or shareholders. Excessive fraud and delays in detecting it can violate financial industry regulations. Fraud detection combines AI technologies, such as computer vision to interpret scanned documents, document verification to authenticate IDs like driver's licenses, and machine learning to analyze patterns. These tools work together to assess the risk of fraud in each transaction within seconds. When the system detects a high risk, it triggers automated responses, such as placing holds on withdrawals or requesting additional identification from customers, to prevent fraudulent activity and protect both the business and its client. 06:42 Nikita: Wow, interesting. And how is AI being used in the health industry, especially when it comes to improving patient care? Hemant: Medical appointments can be frustrating for everyone involved—patients, receptionists, nurses, and physicians. There are many time-consuming steps, including scheduling, checking in, interactions with the doctors, checking out, and follow-ups. AI can fix this problem through electronic health records to analyze lab results, paper forms, scans, and structured data, summarizing insights for doctors with the latest research and patient history. This helps practice reduced costs, boost earnings, and deliver faster, more personalized care. 07:32 Lois: Let's take a look at one more industry. How is manufacturing using AI? Hemant: A factory that makes metal parts and other products use both visual inspections and electronic means to monitor product quality. A part that fails to meet the requirements may be reworked or repurposed, or it may need to be scrapped. The factory seeks to maximize profits and throughput by shipping as much good material as possible, while minimizing waste by detecting and handling defects early. The way AI can help here is with the quality assurance process, which creates X-ray images. This data can be interpreted by computer vision, which can learn to identify cracks and other weak spots, after being trained on a large data set. In addition, problematic or ambiguous data can be highlighted for human inspectors. 08:36 Oracle University's Race to Certification 2025 is your ticket to free training and certification in today's hottest tech. Whether you're starting with Artificial Intelligence, Oracle Cloud Infrastructure, Multicloud, or Oracle Data Platform, this challenge covers it all! Learn more about your chance to win prizes and see your name on the Leaderboard by visiting education.oracle.com/race-to-certification-2025. That's education.oracle.com/race-to-certification-2025. 09:20 Nikita: Welcome back! AI can be used effectively to automate a variety of tasks to improve productivity, efficiency, cost savings. But I'm sure AI has its constraints too, right? Can you talk about what happens if AI isn't able to echo human ethics?  Hemant: AI can fail due to lack of ethics.  AI can spot patterns, not make moral calls. It doesn't feel guilt, understand context, or take responsibility. That is still up to us.  Decisions are only as good as the data behind them. For example, health care AI underdiagnosing women because research data was mostly male. Artificial narrow intelligence tends to automate discrimination at scale. Recruiting AI downgraded resumes just because it had a word "women's" (for example, women's chess club). Who is responsible when AI fails? For example, if a self-driving car hits someone, we cannot blame the car. Then who owns the failure? The programmer? The CEO? Can we really trust corporations or governments having programmed the use of AI not to be evil correctly? So, it's clear that AI needs oversight to function smoothly. 10:48 Lois: So, Hemant, how can we design AI in ways that respect and reflect human values? Hemant: Think of ethics like a tree. It needs all parts working together. Roots represent intent. That is our values and principles. The trunk stands for safeguards, our systems, and structures. And the branches are the outcomes we aim for. If the roots are shallow, the tree falls. If the trunk is weak, damage seeps through. The health of roots and trunk shapes the strength of our ethical outcomes. Fairness means nothing without ethical intent behind it. For example, a bank promotes its loan algorithm as fair. But it uses zip codes in decision-making, effectively penalizing people based on race. That's not fairness. That's harm disguised as data. Inclusivity depends on the intent sustainability. Inclusive design isn't just a check box. It needs a long-term commitment. For example, controllers for gamers with disabilities are only possible because of sustained R&D and intentional design choices. Without investment in inclusion, accessibility is left behind. Transparency depends on the safeguard robustness. Transparency is only useful if the system is secure and resilient. For example, a medical AI may be explainable, but if it is vulnerable to hacking, transparency won't matter. Accountability depends on the safeguard privacy and traceability. You can't hold people accountable if there is no trail to follow. For example, after a fatal self-driving car crash, deleted system logs meant no one could be held responsible. Without auditability, accountability collapses. So remember, outcomes are what we see, but they rely on intent to guide priorities and safeguards to support execution. That's why humans must have a final say. AI has no grasp of ethics, but we do. 13:16 Nikita: So, what you're saying is ethical intent and robust AI safeguards need to go hand in hand if we are to truly leverage AI we can trust. Hemant: When it comes to AI, preventing harm is a must. Take self-driving cars, for example. Keeping pedestrians safe is absolutely critical, which means the technology has to be rock solid and reliable. At the same time, fairness and inclusivity can't be overlooked. If an AI system used for hiring learns from biased past data, say, mostly male candidates being hired, it can end up repeating those biases, shutting out qualified candidates unfairly. Transparency and accountability go hand in hand. Imagine a loan rejection if the AI's decision isn't clear or explainable. It becomes impossible for someone to challenge or understand why they were turned down. And of course, robustness supports fairness too. Loan approval systems need strong security to prevent attacks that could manipulate decisions and undermine trust.  We must build AI that reflects human values and has safeguards. This makes sure that AI is fair, inclusive, transparent, and accountable.  14:44 Lois: Before we wrap, can you talk about why AI can fail? Let's continue with your analogy of the tree. Can you explain how AI failures occur and how we can address them? Hemant: Root elements like do not harm and sustainability are fundamental to ethical AI development. When these roots fail, the consequences can be serious. For example, a clear failure of do not harm is AI-powered surveillance tools misused by authoritarian regimes. This happens because there were no ethical constraints guiding how the technology was deployed. The solution is clear-- implement strong ethical use policies and conduct human rights impact assessment to prevent such misuse. On the sustainability front, training AI models can consume massive amount of energy. This failure occurs because environmental costs are not considered. To fix this, organizations are adopting carbon-aware computing practices to minimize AI's environmental footprint. By addressing these root failures, we can ensure AI is developed and used responsibly with respect for human rights and the planet. An example of a robustness failure can be a chatbot hallucinating nonexistent legal precedence used in court filings. This could be due to training on unverified internet data and no fact-checking layer. This can be fixed by grounding in authoritative databases. An example of a privacy failure can be AI facial recognition database created without user consent. The reason being no consent was taken for data collection. This can be fixed by adopting privacy-preserving techniques. An example of a fairness failure can be generated images of CEOs as white men and nurses as women, minorities. The reason being training on imbalanced internet images reflecting societal stereotypes. And the fix is to use diverse set of images. 17:18 Lois: I think this would be incomplete if we don't talk about inclusivity, transparency, and accountability failures. How can they be addressed, Hemant? Hemant: An example of an inclusivity failure can be a voice assistant not understanding accents. The reason being training data lacked diversity. And the fix is to use inclusive data. An example of a transparency and accountability failure can be teachers could not challenge AI-generated performance scores due to opaque calculations. The reason being no explainability tools are used. The fix being high-impact AI needs human review pathways and explainability built in. 18:04 Lois: Thank you, Hemant, for a fantastic conversation. We got some great insights into responsible and ethical AI. Nikita: Thank you, Hemant! If you're interested in learning more about the topics we discussed today, head over to mylearn.oracle.com and search for the AI for You course. Until next time, this is Nikita Abraham…. Lois: And Lois Houston, signing off! 18:26 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.  

Title: ⏰ Synergy Traders #59: How Predictive Precise Simplicity of Alpha Fibonacci Will Improve Your Trading with Alla Peters-Plocher of FibonacciTradingInstitute.com   Recorded as part of the Synergy Traders #59: "20 Fibonacci & Elliott Wave Trading Strategies" hosted by FXTradersEdge, TradeOutLoud, and TimingResearch.   You can find the full video of this presentation here: https://link.timingresearch.com/ArchiveST59   Bonus info... [AD]

Artificial Intelligence is no longer a futuristic idea—it's here, and it's transforming marketing. In this episode of The Backstory on Marketing and AI, we explore how AI and Marketing intersect to reshape strategy, personalization, and growth.We dive into AI enabled Market Research, showing how businesses can use data-driven insights to predict customer behavior, optimize campaigns, and innovate faster.This discussion breaks down how AI helps marketers personalize experiences, improve ROI, and anticipate market shifts. We cover practical applications such as:Predictive analytics for customer behaviorReal-time market insightsSmarter decision-making with AI toolsCreating stronger customer engagement through personalizationFor companies aiming to stay competitive, adopting AI isn't optional—it's essential. The businesses that leverage AI now will thrive in an increasingly digital future.#AIandMarketing #AIenabledMarketResearch #MarketingTrends #DigitalMarketing #FutureOfAI

In this episode, host Paige West speaks with Matthias Huber, Sr. Director, Solutions Manager, IoT/Embedded & Edge Computing, Supermicro, all about accelerating Edge AI infrastructure for predictive and Generative AI.

The FF Dynasty, Season 9, Episode 90: Casey + @KoalatyStats break down the best dynasty trade targets for Week 4 based on the signature PWOPR Metric (predicted weighted opportunity)— We feature buy-low running backs, sell-high wideouts, and players to stash for long-term upside. We cover dynasty trade strategy around Trey Benson, Cam Skattebo, Quinshon Judkins, Travis Etienne, Ricky Pearsall, George Pickens, and more -- Analytical Models + Predictions powered by @KoalityStats https://koalatystats.substack.com -- • SIGN UP TODAY FOR up to $200 in Prophet Cash BACK -USE CODE: FFD WHEN SIGNING UP AT https://prophetx.onelink.me/E5Yi/FFD or DOWNLOAD THE PROPHETX APP #ProphetX -- ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Fantasy Football Survivor⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ (NEW GAME!) Free ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Patreon⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ + ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Discord⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ 5 Star Contest ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠! ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Twitter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Insta⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠TikTok⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ --

In dieser Folge des Predictive AI Quarterly sprechen wir über die Veröffentlichung von GPT-5 und was sich im Vergleich zu GPT-4 geändert hat. Wir schauen uns an, wie Reasoning jetzt funktioniert und welche Optionen Entwickler*innen bei der Nutzung haben. Außerdem geht's um neue Open-Source-Modelle von OpenAI, die Einführung von TabArena als dynamischem Benchmark für Tabulardaten und spannende Integrationen wie TabPFN in Sourcetable. Im Praxisteil nehmen wir QLoRA unter die Lupe und testen, ob Finetuning mit Quantisierung wirklich so effizient und verlustfrei ist, wie versprochen.   ** Zusammenfassung ** GPT-5 Release: Neues Reasoning-Feature, flexible Steuerung über Parameter und Empfehlungen für die Migration von GPT-4. Open-Source-Modelle von OpenAI: Veröffentlichung von 20B- und 120B-Modellen mit vergleichsweise moderatem Hardwarebedarf. TabArena: Dynamischer Benchmark für tabellarische Daten, der Ensembling und TabPFN bei kleinen Datensätzen hervorhebt. TabPFN in Sourcetable: Integration von Predictive AI direkt in Spreadsheets für nahtlose Nutzung. Praxis-Test QLoRA: Finetuning mit Quantisierung liefert gleiche Qualität wie LoRA, benötigt aber nur halb so viel Speicher.   ** Links ** OpenAI – GPT-5 für Entwickler*innen vorgestellt: https://openai.com/de-DE/index/introducing-gpt-5-for-developers/ OpenAI – API Responses Referenz: https://platform.openai.com/docs/api-reference/responses/create OpenAI – Guide: Reasoning in GPT: https://platform.openai.com/docs/guides/reasoning OpenAI – Modell-Migrationsempfehlungen: https://platform.openai.com/docs/guides/latest-model#migration-guidance Hugging Face – Open-Source GPT 20B: https://huggingface.co/openai/gpt-oss-20b Hugging Face – Open-Source GPT 120B: https://huggingface.co/openai/gpt-oss-120b OpenAI – Ankündigung OSS-Modelle: https://openai.com/de-DE/index/introducing-gpt-oss/ Hugging Face – TabArena Leaderboard: https://huggingface.co/spaces/TabArena/leaderboard arXiv – TabArena Paper: https://arxiv.org/abs/2506.16791 Sourcetable – Homepage / Tool: https://sourcetable.com/ Heise c't – Artikel "Komprimierte KI" (Februar 2025): https://www.heise.de/select/ct/2025/2/2432617330867723674 Heise c't – Artikel "Quantisierung": https://www.heise.de/select/ct/2025/7/2504911435670065158 arXiv – QLoRA Paper (Mai 2023): https://arxiv.org/abs/2305.14314 NeurIPS – QLoRA Veröffentlichung: https://proceedings.neurips.cc/paper_files/paper/2023/hash/1feb87871436031bdc0f2beaa62a049b-Abstract-Conference.html arXiv – Paper zu Quantisierung: https://arxiv.org/abs/2501.13787

This episodes been in the ice box since 2024 (tracked the week before SKY WARS was cancelled) it never saw the airwaves.  There's conversation references that date it.  "Pardon our mess".   We're at the pinnacle of the amateur and professional domestic pyro show competition season here in the United States with Sky Wars this week and Jamie, AJ, and Bo break down the designer competitive landscape across the PRO-AM and PRO divisions and make their winner predictions for this years event.   Support the Sh*t Show!! Contribute -> Patreon  Hang with us -> Discord Buy some Merch, balls, DB25 Cables or leave us a Voicemail (we'll play it on-air)!

Wil talks with Anthony Hamilton of Icon Group Hospitality about building people-first restaurant businesses that last. They riff on digital minimalism (Wil's flip phone!), presence with family, and the hard edges of hospitality—burnout, 24/7 crises, substance abuse—then pivot to how thoughtful leadership, balance, and systems can make the work sustainable. Anthony traces his path from CIA-trained chef to operator/educator to acquiring legacy independent brands and venues, explaining creative deal structures, venue-first catering strategy, and a culture that prizes productivity over performative “grind.” The throughline: lead with hospitality, invest in people, use simple tech well, and protect the soul of beloved neighborhood institutions.Key takeaways Presence beats obsession: Ditching always-on smartphones can reduce noise and make you a better leader, parent, and human. Hospitality is holistic: Mental health, family time, and modeling balance are part of the job, not perks. People > spreadsheets: “Internal customers” (your team) drive guest experience; treat them with autonomy, flexibility, and respect. Productivity > hours: Question 50+ hour weeks; manage to outcomes, not optics. Predictive labor wins: Forecast sales, schedule to targets, and adjust—don't try to “cut” your way out after the fact. Simple tech scales: Use lightweight tools (like scheduling/communications) your staff actually adopts; avoid bells-and-whistles bloat. Legacy brand stewardship: When buying independents, preserve what locals love while modernizing ops; owners are often the brand—honor that story. Creative deals keep doors open: Mix owner financing, profit-sharing, and note-holding to match seller needs and protect cash. Venue-first catering strategy: Securing exclusive/long-term venue leases reliably feeds the catering pipeline. Unreasonable touches pay back: Small, thoughtful gestures (a $60 video game + handwritten note) can lock in lifelong clients. Turnover is expensive: Retention beats replacement—paying an extra $0.50–$1/hour can save thousands in churn costs. Lead by example: Owners will always care most; don't expect staff to out-hustle you—set the standard and the tone.

The FF Dynasty, Season 9, Episode 87: Casey is joined by our Head of Analytics Joseph @KoalatyStats to break down who's Predicted Weighted Opportunity Score is indicative of greater future success. We highlight all of but not limited to (repeats) DK Metcalf/Emeka Egbuka (new additions to the PWOPR list) Kyle Pitts/Ladd McConkey (more buy lows) Brian Thomas Jr./Justin Jefferson/Drake London (are they for real?) Rome Odunze/Troy Franklin/Quentin Johnston -- Analytical Models + Predictions powered by @KoalityStats https://koalatystats.substack.com -- • SIGN UP TODAY FOR up to $200 in Prophet Cash BACK -USE CODE: FFD WHEN SIGNING UP AT https://prophetx.onelink.me/E5Yi/FFD or DOWNLOAD THE PROPHETX APP #ProphetX -- ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Fantasy Football Survivor⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ (NEW GAME!) Free ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Patreon⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ + ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Discord⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ 5 Star Contest ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠! ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Twitter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Insta⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠TikTok⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ --

On this episode of the Cybersecurity Defenders Podcast we speak with Robert Boles, Founder / CEO of BLOKWORX.A veteran of the U.S. Marine Corps, Rob founded BLOKWORX in 2006 to further his passion for creating fast, secure networks. Since 1999 Rob was a core technical contributor and presenter on an Advanced IP Team, delivering bleeding edge WAN and Managed Security services to Small, Mid-level and Fortune 500 businesses around the world. The experience led him back to the same conclusion, regardless of size and resources, every company struggled with the same uncertainty – multiple vendors with infinite solutions, and no real clarity how to make it all “work.” Rob focused BLOKWORX on security, reliability, and positive user experience. He has built a team that leverages their expertise with extensive research and testing, alignment with vendors, partners, and clients, and the experience of 1000's of nodes managed and monitored, all supported by a mature delivery model built on years of operational experience. Rob is an avid outdoorsman and his favorite place to be is in a raft or a kayak with his son Jack.Learn more at blokworx.com.Support our show by sharing your favorite episodes with a friend, subscribe, give us a rating or leave a comment on your podcast platform.This podcast is brought to you by LimaCharlie, maker of the SecOps Cloud Platform, infrastructure for SecOps where everything is built API first. Scale with confidence as your business grows. Start today for free at limacharlie.io.

Hey y'all, today I'm sitting down with Timothy Frie and honestly, I could talk about his brain all day. He's a neuro-nutritionist, researcher and writer who takes the big stuff - grief, trauma, burnout, stress - and shows us how it all connects to the way we eat. We get into why our bodies do what they do around food, how the brain makes patterns we don't even realise, and what it actually takes to create real, lasting change. This conversation is one of those that sticks with you.Highlights:(08:31) Predictive maps: why our brains link food to stress(16:13) The power of safety in healing our body(24:23) Nutrition isn't diet rules, it's cell-level survival(32:12) Supplements as support when life feels too much(40:58) Food freedom starts with trusting your own bodyFind out more:Website's HERE and HEREInstagramThreadsBrain Fried NewsletterQualia Mind - click hereCoupon Code: SHOCKANDYALL (15% off any purchase)Visit Nicole's on demand fitness platform for live weekly classes and a recorded library of yoga, strength training, guided audio meditations and mobility (Kinstretch) classes, as well: https://www.sweatandstillness.comGrab Nicole's bestselling children's book and enter your email for A FREE GIFT: https://www.yolkedbook.comFind Nicole on Instagram:https://www.instagram.com/nicolesciacca/Tik Tok: https://www.tiktok.com/@thenicolesciaccaFacebook: https://www.facebook.com/nicolesciaccayoga/Youtube:https://www.youtube.com/channel/UC1X8PPWCQa2werd4unex1eAPractice yoga with Nicole in person in Santa Monica, CA at Aviator Nation Ride. Get the App to book in: https://apps.apple.com/us/app/aviator-nation-ride/id1610561929Book a discovery call or virtual assessment with Nicole here: https://www.calendly.com/nicolesciaccaThis Podcast is proudly produced by Wavemakers Audio

Dr. Judy Morgan discusses with Dr. Terry Fossum the potential of using dogs as a better predictive model for drug approval compared to mice. Dr. Fossum highlights the inefficiencies and high costs of current drug development, noting that in 2022, the U.S. spent $100.8 billion on prescription drugs, and globally, $1.3 trillion. She emphasizes the need for more efficient and cost-effective methods, citing that 50% of healthcare dollars go to 5% of the population, largely due to chronic diseases. Listen in as Dr. Fossum shares her research showing promise with using dogs that have naturally occurring disease as a more predictive model for human disease. Fascinating! OFFER: - Free surveys for common ailments. Drfossums.com/surveys One time use Coupon Code: drjudy30% The surveys are designed to be taken over time to see your dog's progression. So, you can take a survey today, then take it in 60 days to see how your dog is progressing. This is super helpful for slow progressing disease where it is hard to identify changes that take time to develop. Website: https://drfossums.com/ instagram.com/drfossumspetcare/ facebook.com/drfossumspetcare https://www.facebook.com/drfossums linkedin.com/company/84275603 https://www.facebook.com/thecuttingedgevet/ https://www.instagram.com/thecuttingedgevet/ https://www.youtube.com/@TheCuttingEdgeVet/ Additional Links: Senior Dog's Book for pet owners Dr. Fossum's Pet Care Logo Terry Teaching Surgery https://drive.google.com/file/d/1IJDQdDS1PnKXkBRJvq5A4D7xTAAPj8hf/view?usp=sharing B-roll: https://drive.google.com/file/d/1E3qIyJhrGXojo-c-LeoMhur3F5b4qlY_/view?usp=sharing https://drive.google.com/file/d/1rZujljB_4CGl4gtGFSnG1c5DeiyDC1M-/view?usp=sharing Calculators/Surveys track results over time https://thecuttingedgevet.com/cbd-oil-dosage-calculator/ https://thecuttingedgevet.com/canine-cognitive-dysfunction-survey/ https://thecuttingedgevet.com/canine-cardiac-disease-assessment/ https://thecuttingedgevet.com/chronic-kidney-disease-risk-assessment/ https://thecuttingedgevet.com/cbd-mobility-survey/ https://thecuttingedgevet.com/cbd-calm-survey/ https://thecuttingedgevet.com/dog-dental-health-assessment/ https://thecuttingedgevet.com/osteoarthritis-risk-assessment/ https://thecuttingedgevet.com/senior-dog-general-wellness-assessment/ PRODUCT SPOTLIGHT #1 Are you interested in even more helpful content from Dr Judy? Check out Dr Judy's private Patreon community to receive exclusive perks such as live Q & A opportunities with Dr Judy herself, exclusive recipes, merchandise discounts, guest interviews, educational presentations, Black Friday and Cyber Monday early access and more. Be in the know and help Dr Judy as she continues her mission to empower and educate pet parents like you so you can advocate for a happier, healthier life for your pet. Go to patreon.com/DrJudyMorgan to sign up now. PRODUCT SPOTLIGHT #2Could your pet benefit from PEA? Pulmitoyl ethanolamide, also known as PEA is a naturally occurring fatty acid compound found in plants and animals. PEA may help support healthy, inflammatory and immune balance, comfort and well being. We found it helpful for cats, dogs and equines. Podcast listeners can take advantage of 15% off of any size of Dr Judy's PEA with the code PODCAST64 Get your Dr Judy's PEA today at NaturallyHealthyPets.com and 15% off using the code PODCAST64

Welcome to a fascinating exploration of the hidden legal battles shaping tomorrow's technology. Predictive algorithms have become the crystal balls of modern business, forecasting everything from home prices to healthcare costs, but they're also becoming the center of high-stakes courtroom dramas worth hundreds of millions of dollars.Across the globe, from Texas courtrooms to China's Supreme People's Court, judges and juries are answering a profound question: who owns the right to predict the future? The House Canary v. Amrock case resulted in a staggering $600 million verdict over real estate valuation algorithms, while Alibaba secured a 30 million RMB judgment against a company that allegedly scraped its predictive marketing tools. Even industrial applications aren't immune, with companies like Shen Group successfully protecting predictive design software for machinery components.What makes these cases particularly compelling is how they're redefining intellectual property law. Courts are now recognizing that AI model weights, the mathematical parameters tuned during training, qualify as protectable trade secrets. Data pipelines, prediction engines, and algorithmic structures have all received similar protection. The real drama often unfolds when employees change companies, raising thorny questions about what constitutes general expertise versus proprietary knowledge that belongs to the former employer.Healthcare prediction presents especially valuable territory, with ongoing battles between companies like Qruis and Epic Systems, or Milliman and Gradient AI, demonstrating how patient data forecasting creates immensely valuable intellectual property. Whether it's forecasting home values on Zillow or optimizing Medicare billing, these predictive tools aren't just convenient features, they're corporate crown jewels worth protecting at almost any cost.Ready to dive deeper into the invisible rules governing innovation? Subscribe now and join us as we continue to decode the legal frameworks shaping our technological future. The algorithms may predict tomorrow, but who gets to own those predictions? That's what we're exploring on Intangiblia.Get the book!Send us a textSupport the show

This is a story with a lad in it called Aladdin.   Support the show and get extra episodes www.patreon.com/worldaroundewe 

At the Society of Hematologic Oncology 2025 Annual Meeting, CancerNetwork® spoke with a variety of experts about notable clinical developments and trial results across the hematologic oncology landscape. Throughout the meeting, clinicians and researchers discussed the latest data and initiatives in myelofibrosis, multiple myeloma, lymphoma, and other types of blood cancer. Francesca Palandri, MD, PhD, an adjunct professor in the Department of Medical and Surgical Sciences at the University of Bologna in Bologna, Italy, shared insights from a session focused on exploring predictive markers for the efficacy of ruxolitinib (Jakafi) among patients with myelofibrosis.1 Noting variance in response rates as well as possibilities of disease progression or treatment discontinuation associated with ruxolitinib, Palandri emphasized the importance of assessing predictors of response to better orient clinical decision-making strategies regarding the agent's use. She also highlighted how factors such as cytopenic phenotype, higher peripheral blast counts, and higher burden of disease may impact response rates and survival among patients. Additionally, Sundar Jagannath, MD, a professor of Medicine specializing in hematology and medical oncology at the Icahn School of Medicine at Mount Sinai and The Tisch Cancer Institute, spoke about his presentation on potentially defining a cure in the management of multiple myeloma.2 He described the importance of “chang[ing] the dialogue” in multiple myeloma to give hope to patients and encourage physicians to engage in patient care more optimally. By defining a cure in multiple myeloma, Jagannath stated, it may be possible to offer more finite durations of treatment and stop therapy with the confidence that patients will not relapse. Finally, Adam J. Olszewski, MD, an associate professor of medicine at The Warren Alpert Medical School of Brown University, discussed his work on the phase 3 SUNMO trial (NCT05171647).3 Findings from this presentation showed that mosunetuzumab-axgb (Lunsumio) plus polatuzumab vedotin-piiq (Polivy; M-Pola) reduced the risk of progression or death by 59% vs rituximab (Rituxan) with gemcitabine and oxaliplatin (R-GemOx) in relapsed/refractory large B-cell lymphoma (LBCL). Olszewski also outlined next steps for refining treatment strategies in this patient population. References Palandri F. Predictive markers for ruxolitinib in MF. Presented at the Society of Hematologic Oncology 2025 Annual Meeting; September 3-6, 2025; Houston, TX. Jagannath S. Is it time to say “CURE” in multiple myeloma? Presented at the Society of Hematologic Oncology 2025 Annual Meeting; September 3-6, 2025; Houston, TX. Westin J, Zhang H, Kim W, et al. Mosunetuzumab plus polatuzumab vedotin is superior R-GemOx in transplant-ineligible patients with R/R LBCL: primary results of the phase III SUNMO trial. Presented at the Society of Hematologic Oncology 2025 Annual Meeting; September 3-6, 2025; Houston, TX. Abstract ABCL-1492.

Game B's theosophical utopia vs. Dark Enlightenment's technocracy, esoteric roots, surveillance tech, fantasy delusions, and resisting AI-driven control During our podcast break, enjoy this replay of Courtenay's appearance on Out Of This World with host Jamie Hanshaw from June 2025. Key topics: Dialectic of Game B (decentralized, theosophical utopia) vs. Dark Enlightenment (authoritarian technocracy), both pushing a technological singularity/noosphere. Game B details: 2011 Stanton meetings (Jim Rutt, Jordan Hall, Brett Weinstein), transpolitical movement, civium projects, collective intelligence, and UN/climate narrative ties. Dark Enlightenment: Curtis Yarvin (Mencius Moldbug), Nick Land's accelerationism, Peter Thiel's network states, and technocracy roots (e.g., Elon Musk's grandfather). Esoteric influences: Theosophy, Gnosticism, neoplatonism, occult symbolism (e.g., Saturn, X logo), and subversion of Christianity (Jordan Hall, liturgy for communitarianism). Cultural impact: Predictive programming (e.g., Mickey 17, Dollhouse), surveillance tech (internet of nanobio things, Palantir), and fantasy delusions shaping technocratic agendas. Courtenay's insights: Decoding technocrat lingo, resisting utopian traps, and preserving free will against AI-driven control. Follow and Connect with Jamie Hanshaw:

The FF Dynasty, Season 9, Episode 82: Casey and Joseph @KoalatyStats dive into his Predictive Weighted Opportunity Score (PWOPR, pronounced Pee Whopper) to find Dynasty trade targets before they explode in value. -Seriously if you can produce a metric with a better R^2 score than our guy Joseph please leave a comment below we'd love to hear from you • SIGN UP TODAY FOR up to $200 in Prophet Cash BACK -- USE CODE: FFD WHEN SIGNING UP AT https://prophetx.onelink.me/E5Yi/FFD or DOWNLOAD THE PROPHETX APP #ProphetX ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Fantasy Football Survivor⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ (NEW GAME!) Free ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Patreon⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ + ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Discord⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ 5 Star Contest ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠! ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Twitter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Insta⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠TikTok⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ --

In this episode of the En Factor, we are joined by serial entrepreneur Xavier Serrano, who is now the founder and CEO of Marqi Medical. After spending over two decades in the insurance world, Xavier transitioned out of his previous venture to revolutionize preventive healthcare with Marqi. Using resources like artificial intelligence, advanced testing and diagnostics, and personalized coaching, Xavier and his team have developed a personalized predictive healthcare platform that works to identify and prevent significant illnesses and diseases before they truly become significant.  In this conversation, Xavier and Dr. Rebecca White take a deep dive into a variety of topics including Xavier's journey from insurance to starting his own holistic healthcare platform, navigating and managing the many relationships and moving parts involved in leading Marqi Medical, and the importance of prioritizing your own personal health as an entrepreneur. Tune in as you won't want to miss a second of Xavier's incredible journey, insights and advice! Key Words - Healthcare Innovation, Technology Entrepreneurship

In this episode of The Responsive Lab, we go deeper into the real, raw questions nonprofit leaders are asking about artificial intelligence. Things like strategy and governance to privacy, personalization, and predictive modeling. Join Virtuous' Chief AI Officer, Nathan Chappell, alongside co-hosts Carly Berna and Scott Holthaus as they unpack: What AI really means for nonprofit teams How predictive and generative AI work together to drive giving Why most AI initiatives fail and how to beat the odds Ethical and environmental concerns (and how to respond to them) How Virtuous is building the future of fundraising through AI Nathan brings years of experience in machine learning, innovation, and responsible AI use in philanthropy. This session is a roadmap for nonprofit teams looking to move from AI curiosity to AI clarity. Watch the webinar that prompted this conversation here: 5 Essentials for AI Success: What Today's Fundraising Teams Need to Know (and Do) to Thrive Learn more about Virtuous at virtuous.org/learnmore and download your free Nonprofit CRM Checklist at virtuous.org/crmchecklist

A cautionary tale about a life-threatening reaction to the double flu/Covid booster; Are migraines predictive of heart attacks? Where does all our recycling go? (The answer will shock you!); Ultra-processed foods damage male reproductive health.

Artificial intelligence is radically transforming the military—an institution grappling with an eligibility crisis at home. According to the Department of Defense, a mere 23% of Americans aged 17 to 24 qualify for military force without needing a waiver, meaning that 77% are currently ineligible due to factors like obesity, drug use, and mental or physical health issues. This stark reality intensifies the urgency for smarter, data-driven solutions: AI-driven analytics that can refine recruiting strategies, predict readiness, and help optimize both talent acquisition and human capital management.But how exactly can AI help the U.S. military win the “war for talent” while also modernizing its massive infrastructure? What lessons can private industry learn from the defense sector's adoption of AI-driven workforce strategies?In this episode of DisruptED, host Ron Stefanski sits down with Tyler Zagurski, Vice President of Talent at r4 Technologies and a retired U.S. Marine Corps colonel with 31 years of service. Together, they explore how artificial intelligence is being leveraged to transform both the workforce and the military force of the future. Their conversation spans from deeply personal origin stories to the broader technological and organizational revolutions happening today.Key Discussion Points:The shrinking pool of military-eligible talent: Fewer than one in four young Americans qualify to serve, making AI tools essential in identifying, attracting, and retaining candidates.AI-powered logistics and sustainment: Predictive analytics are being used to forecast asset readiness, prevent costly breakdowns, and optimize supply chains across global military operations.Human-centered decision intelligence: AI is not replacing military leaders but equipping them with better insights to retain talent, deploy personnel effectively, and maintain mission readiness.Tyler Zagurski is the Vice President of Talent at r4 Technologies, where he applies AI-driven solutions to defense and national security challenges. Before entering private industry, Zagurski served 31 years in the U.S. Marine Corps as an infantry officer, commanding units in combat and spearheading service-level transformation initiatives such as Talent Management 2030. A graduate of the U.S. Army War College, he has deep expertise in workforce modernization, logistics, and education strategy, making him a leading voice at the intersection of AI and military readiness.

In the late 2010s, a group of sheriffs out of Pasco County, Florida, believed they could predict crime. The Sheriff's Department there had piloted a program called “Intelligence-Led Policing” and the program would allegedly analyze disparate points of data to identify would-be criminals.But in reality, the program didn't so much predict crime, as it did make criminals out of everyday people, including children. High schoolers' grades were fed into the Florida program, along with their attendance records and their history with “office discipline.” And after the “Intelligence-Led Policing” service analyzed the data, it instructed law enforcement officers on who they should pay visit to, who they should check in on, and who they should pester.As reported by The Tampa Bay Times in 2020:“They swarm homes in the middle of the night, waking families and embarrassing people in front of their neighbors. They write tickets for missing mailbox numbers and overgrown grass, saddling residents with court dates and fines. They come again and again, making arrests for any reason they can.One former deputy described the directive like this: ‘Make their lives miserable until they move or sue.'”Predictive policing can sound like science fiction, but it is neither scientific nor is it confined to fiction.Police and sheriff's departments across the US have used these systems to plug broad varieties of data into algorithmic models to try and predict not just who may be a criminal, but where crime may take place. Historical crime data, traffic information, and even weather patterns are sometimes offered up to tech platforms to suggest where, when, and how forcefully police units should be deployed.And when the police go to those areas, they often find and document minor infractions that, when reported, reinforce the algorithmic analysis that an area is crime-ridden, even if those crimes are, as the Tampa Bay Times investigation found, a teenager smoking a cigarette, or stray trash bags outside a home.Today, on the Lock and Code podcast with host David Ruiz, we speak with Emily Galvin-Almanza, cofounder of Partners for Justice and author of the upcoming book “The Price of Mercy,” about predictive policing, its impact on communities, and the dangerous outcomes that might arise when police offload their decision-making to data.“ I am worried about anything that a data broker can sell, they can sell to a police department, who can then feed that into an algorithmic or AI predictive policing system, who can then use that system—based on the purchases of people in ‘Neighborhood A'—to decide whether to hyper-police ‘Neighborhood A.'”Tune in today.You can also find us on Apple Podcasts, Spotify, and whatever preferred podcast platform you use.For all our cybersecurity coverage, visit Malwarebytes Labs at malwarebytes.com/blog.Show notes and credits:Intro Music: “Spellbound” by Kevin MacLeod (incompetech.com)Licensed under Creative Commons: By Attribution 4.0 Licensehttp://creativecommons.org/licenses/by/4.0/Outro Music: “Good God” by Wowa...

Vanese McNeill, co-producer of the Magical Egypt series, returns to the show. In this episode, we explore the hows and possible whys of spirit involvement in history, from the super-elite level down to the everyday. And also across to some of the sillier claims about AI floating in the air like so many plasma entities. And all of this was inspired by a post Vanese wrote on the Magical Egypt substack about ontozoology back in June. So that's where we begin, and this is where we go after: 1. The Ontozoology Framework What invisible beings actually exist in the ecosystem Moving beyond Christian binary (demons vs. angels) to animist complexity The difference between malevolent, benevolent, and simply non-human agendas 2. Catherine Austin Fitts & Demonic Capital The exact quote about interdimensional intelligences controlling capital Why this is being discussed now by credible people The problem with oversimplifying complex entities as "Satan" 3. Conscious vs. Unconscious Elite Collaboration How much is deliberate ritual worship vs. unconscious possession The decline of magical literacy among modern elites Why materialist worldviews make people more vulnerable to influence 4. Historical Magic & Modern Mind Control Ancient Egyptian spirit relationships as information exchange How modern "operations" are rituals without the practitioners knowing it Predictive programming as contemporary magic 5. The AI & Slop Demon Problem Why "The Architect" and similar AIs aren't sentient but are dangerous How AI creates mental conditions ripe for spiritual colonisation The difference between AI hosting demons vs. AI making minds available for possession 6. UFOs, Aliens, and Interdimensional Beings The reframing of UFO phenomena as spiritual rather than extraterrestrial Catherine's invitation to meet "aliens in human bodies" Distinguishing between visiting organisms and native invisible ecology

"You don't get paid for the hour. You get paid for the value you bring to the hour." – Jim Rohn Check Out These Highlights: In the midst of all the chaos, how do you stand out from the crowd and become the only logical choice in your field of expertise? In this episode, my guest will share proven principles that, when applied, have empowered people to monetize their life's mission and create a lasting legacy for their family. So I ask you, “Are you ready to break free from your limiting beliefs, so you can design your destiny and monetize your expertise like never before?” About Joel Bauer: Joel has trained some of the world's top income-producing speakers, presenters, and online marketers to monetize their life experience, both online and offline. For decades, Joel's principles have set the bar for speaking, teaching, and closing at the highest level. By applying Joel's strategies, you can break free from limitations, design your destiny, and monetize your expertise like never before. How to Get in Touch with Joel Bauer: Website:   https://joelbauer.com/ Email:  support@joelbauer.com Gift - 5Moves2Authority on Instagram:  https://www.instagram.com/joelbauermentor/  direct message the phrase, “5Moves”  Stalk me online! LinkTree: https://linktr.ee/conniewhitman   Subscribe to the Changing the Sales Game Podcast on your favorite podcast streaming service or YouTube. New episodes are posted every week - listen as Connie delves into new sales and business topics, or addresses problems you may have in your business.

We made it to Episode 6 - the final in our 15 Architectural Decisions series and saved some of the best for last - Predictive and Proactive support (Pure1) combined with our Evergreen architecture and non-disruptive everything. In this episode, JD, Andrew and I dive into Pure Storage's foundational principles that ensure continuous operation and future-proof your storage. We explore the concept of "Non-Disruptive Everything," a core tenet that allows for seamless upgrades and expansions without any downtime. This ties directly into the innovative Evergreen Storage Model, which redefines the ownership experience by eliminating forklift upgrades and enabling independent evolution of performance, capacity, and features over a decade-long array lifecycle. We also discuss how Pure's proactive and predictive support, powered by Pure1, plays a critical role in maintaining this non-disruptive environment. Pure1's advanced analytics, anomaly detection, and data protection assessments provide unparalleled visibility and ensure that potential issues are identified and addressed before they impact operations. This integrated approach, from architecture to support, highlights how Pure Storage consistently delivers a cloud-like experience on-premises, setting a new standard for reliability and longevity in the storage industry. Thanks for watching our series. Series Overview: Pure Storage's foundational approach to product engineering is guided by 15 architectural decisions that were established at the company's inception and have shaped both the technical and user experience across its product lines. These architectural choices were not made arbitrarily—they stem from a deliberate focus on simplicity, efficiency, and scalability, ensuring Pure could deliver storage solutions that break away from legacy complexity and enable continuous innovation without compromise. This series will guide viewers through all of the 15 principles, helping you understand why certain choices were made, how they impact your operations, and how they compare to other industry features and products. Join Pure Report podcast hosts Rob Ludeman, Andrew Miller, and J.D Wallace for this fun technical retrospective on Pure Storage.

What if the clean energy transition is built on one of the dirtiest secrets in industry—rare earth metals? They power EVs, AI, and defense systems, yet most are processed overseas with toxic, outdated methods. In this episode, Nicholas Myers, CEO of Phoenix Tailings, shares how his company is transforming mining waste into a clean, domestic source of critical materials. From backyard prototypes to pioneering world-first predictive complexation, Nick shares the grit, innovation, and vision it takes to scale deep tech in one of the world's most entrenched industries—and why zero-waste, zero-emission metals are vital for both energy security and the environment. Tune in to hear how backyard experiments grew into a global metals revolution.--- Hey Climate Tech enthusiasts! Check out Leaders on a Mission, where I interview climate tech leaders shaking up the industry and bringing us the next wave of sustainable solutions. Join me for a deep dive into the future of green innovation—exploring the highs, lows, and everything in between of pioneering new technologies.Tune in on…YouTube: https://www.youtube.com/@leadersonamissionNet0Spotify: https://open.spotify.com/show/7o41ubdkzChAzD9C53xH82Apple Podcasts: https://podcasts.apple.com/us/podcast/leaders-on-a-mission/id1532211726…to listen to the latest episodes!Timestamps:00:58 – Nick's unconventional journey04:17 – Backyard experiments begin07:22 – Tackling mining waste11:23 – Predictive complexation breakthrough13:40 – AI in metallurgy17:04 – US-China supply chain exposure19:15 – Scaling defense capacity22:56 – Financing beyond VC25:05 – Rare earths in production28:27 – Lessons from fundraising31:43 – The three-year IPO vision33:35 – Building high-performance teams38:31 – Values that drive Phoenix TailingsUseful links: Phoenix Tailings website: https://phoenixtailings.com/Phoenix Tailings LinkedIn: https://www.linkedin.com/company/phoenixtailings/Nicholas Myers  LinkedIn: https://www.linkedin.com/in/nicholaswilliammyers/Leaders on a Mission website: https://cs-partners.net/podcasts/Simon Leich's LinkedIn: https://www.linkedin.com/in/executive-talent-headhunter-agtech-foodtech-agrifoodtech-agritech/

September 2024 Chris Bygraves blasted onto Unexplained Inc. from down under for the very first time for an epic encounter. This time to close out August the chat doesn't go nearly as long but it is just as epic. The episode title touches on a lot of what gets discussed but here are some additional points.- Phantom Phil's recent reading material and how it connects to the Orion Wars.- Spiritual stereotyping and professional ethics.- Judgment and shaming within truth seeking and spirituality- Events concerning Earth's conflicts reflecting what's going on in other parts of the galaxy.- Predictive programming from 1984....ie: The Dark Crystal & DreamscapePlus much much more....Connect with Unexplained Inc. here:https://www.unexplainedinc.com/Watch the episode, like and subscribe on Rumble...here:https://rumble.com/user/Unexplainedinc

Today we cover more of John Coleman's forgotten predictive text from the 90s as well as films that accidentally predicted where we are in culture, and more secrets of Klaus and the popes. https://www.eventbrite.com/e/athens-jerusalem-orthodox-art-philosophy-life-tickets-1598008298839?aff=oddtdtcreator Send Superchats at any time here: https://streamlabs.com/jaydyer/tip Join this channel to get access to perks: https://www.youtube.com/channel/UCnt7Iy8GlmdPwy_Tzyx93bA/join PRE-Order New Book Available in Sept here: https://jaysanalysis.com/product/esoteric-hollywood-3-sex-cults-apocalypse-in-films/ Get started with Bitcoin here: https://www.swanbitcoin.com/jaydyer/ The New Philosophy Course is here: https://marketplace.autonomyagora.com/philosophy101 Set up recurring Choq subscription with the discount code JAY44LIFE for 44% off now https://choq.com Lore coffee is here: https://www.patristicfaith.com/coffee/ Subscribe to my site here: https://jaysanalysis.com/membership-account/membership-levels/ Follow me on R0kfin here: https://rokfin.com/jaydyer Music by Amid the Ruins 1453 https://www.youtube.com/@amidtheruinsOVERHAUL Join this channel to get access to perks: https://www.youtube.com/channel/UCnt7Iy8GlmdPwy_Tzyx93bA/join Join this channel to get access to perks: https://www.youtube.com/channel/UCnt7Iy8GlmdPwy_Tzyx93bA/join #comedy #religion #podacstBecome a supporter of this podcast: https://www.spreaker.com/podcast/jay-sanalysis--1423846/support.

Darshan H. Brahmbhatt, Podcast Editor of JACC: Advances, discusses a recently published original research paper on Evaluating the Performance and Potential Bias of Predictive Models for Detection of Transthyretin Cardiac Amyloidosis.

Tony Shipley, a seasoned entrepreneur and founder of Queen City Angels, joins Jeff Bloomfield to share his journey from a Tennessee farm to building one of America's fastest-growing tech companies and mentoring over 125 startups. Tony reveals the timeless lessons from his upbringing, the importance of intellectual curiosity and critical thinking in entrepreneurship, and why being coachable is the most underrated trait for founders. This episode is a roadmap for anyone seeking to build a meaningful business while leaving a lasting legacy. This isn't just a conversation about startups—it's a masterclass on building something that matters. Whether you're a founder, executive, or aspiring leader, Tony's wisdom will challenge how you think about success, decision-making, and leadership. If you've ever wondered how to turn ideas into impact—or how to avoid the mistakes that sink early-stage companies—this episode is a must-hear. Entrepreneurship is simple, not easy: Businesses succeed when they focus on customer problems, not just clever ideas. Coachability trumps confidence: Founders who “know it all” rarely get funded or scale successfully. Fail fast, learn faster: Quick iteration saves time, money, and credibility. Every founder is first selling themselves, not just their product. Networking is a superpower: Mentors and advisors are everywhere if you're willing to ask. Intellectual curiosity and critical thinking are the twin engines of progress. Predictive programming drives unconscious decision-making—be aware of yours. Fractional expertise beats lone hero syndrome—hire where you lack skills. Legacy is built on people and memories, not exits or net worth. Ideas aren't fragile—if you're afraid to share them, they're not strong enough. 00:00 – Opening & Tony's $1B startup impact 03:45 – Growing up on a Tennessee farm: lessons for life and business 12:30 – The stages of entrepreneurship (idea → MVP → scale) 20:30 – Networking and the power of asking the right questions 23:30 – Fear, pride, and the failure coin in entrepreneurship 28:40 – Intellectual curiosity and critical thinking as superpowers 31:00 – Predictive programming and founder patterns 35:30 – Building a lasting personal and professional legacy Why You Should Listen Top 10 Takeaways Chapter Markings 39:35 – Resources and how to get started in entrepreneurship

Wasabi Technologies (a Boston-based cloud storage company with over $530M in funding, a decade of hypergrowth, 450+ team members, and multiple exabytes of storage deployed) sets high standards for its finance and analytics teams.  Both teams are under pressure to deliver fast, accurate, and actionable insights. Marcos Bento, Director Business Intelligence at Wasabi Technologies and David Suter, Director, Financial Planning And Analysis at Wasabi Technologies join us for a special two-parter. They delve deep into how their teams work together, across functions to turn raw data into real-time financial intelligence. In this episode:  Building and gaining trust between BI and FP&A  Getting from “10% out” to within a couple percentage points for forecasting  KPIs such as dollars per terabyte  BI and FP&A as investigative reporters  Predictive analytics: forecast in the 6 or 12 months working with sales  The manifesto for AI at Wasabi 

Join me for a podcast summary looking at Ai in orthodonticsand its clinical application. A growing topic in orthodontics, and one of themost featured topics at this years AAO. This summary is based on 3 lectures fromthis year's summer meeting by Juan Francisco Gonzalez & Jean Marc Retrouvey,Tarek ElShebiny , Jonas Bianchi and Lucia Cevidanes. We will look whatAi is, the way it works and its clinical application, as well as a criticalview on this young field.  What is Ai: 1.       Technology that enables computers and machinesto simulate human intelligence, perform 1 task very well, e.g. voice command, Youtuberecommendations2.       Predictive modelling, makes calculations,  convert information into numbers or categoriesand recognise patterns  Levels of Ai: Machine learning, Neural Networks and Deep Learning1.       Machine learninga.       The ability for a machine to learn from data andpast experience to identify patterns and make predictions  2.       Neural Networks  a.       Specific model which relies on interconnectednodes, which perform a mathematical calculation of associations , patterns, andprobabilities 3.       Deep learninga.       Is a complex version of neural networks Virtual patient·     CBCT segment + STL file – segmentation of theteeth and roots, with labelling of different stuctureso  Can print model, visualise ideal vector andcalculate ideal vectoro  However clinician still required to establish biomechanics ·     CBCT integration for aligner cases, Unpublishedthesis Khalid Alotaibi:o  Treatment planning confidence increased 50%, leastchange was treatment planning modification  Diagnostic data:·     Ai cephalometric tracingo  46% of 24 landmarks 2.0mm withino  4 different programmes  Iortho, Webceph, Orthodc, cephxo  All landmarks had good overall agreement butvariation in identification  ·     Facial Analysis·     Automated 3D facial asymmetry analysis usingmachine learning  Adel 2025o  Study – 7 landmarks o  Identified manually and with deep learning o  5 accurate, 2 significant difference but notclinically relevant Diagnostic accuracy of photos·     Clinical photos assessment by Ai, and comparedto clinical examination·     Sensitivity 72%, specificity 54% Vaughan & Ahmed2025  Growth prediction·     Poor agreement age 9  Comparison between direct, virtual and AI bonding·     DIBs – uses Ai for bonding·     Compare Ai Vs user modified indirect bonding Vsdirect bonding (gold standard), 0.5mm significant ·     Incisors accurate·     Premolars and lower laterals inaccurate  Monitoring Previous podcast exploring the accuracy of remote monitoringo   with Ferlito 2022 80%repeatability from 2 scans 44.7% repeatability and reproducibility  Bracket removal from scan and retainer fitTarek Assessment of virtual bracket removal by artificialintelligence and thermoplastic retainer fit AJODO 2024o  Retainers for both – clinically acceptable    FDA approval of Ai in dentistry·     FDA - Software of Medical Diagnosis § 4  dental:·     Dental Monitoring·     Ray Co ·     X-Nav technologies·     Densply Sirona    What's next·     More data learning to train AI model·     Robotics customising appliances per patient    

In this episode of the Engineering Influence Podcast, we're joined by Eileen Canady, CMO of BST Global, to discuss the groundbreaking findings from the 2025 Global AEC AI & Data Insights Report. From AI adoption trends to workforce transformation, we explore how engineering firms are embracing AI, overcoming challenges, and reshaping the future of the industry.  

This is a clip from The After Dark Show with Don Rogers! Get access to the full episode and all thier content on all podcast platforms or click the link belowFull episode here! https://www.spreaker.com/episode/s2-e39-aurora-diamondheart-bg-cast-rick-morty-predictive-programing-disclosure--67401951Get access to every episode of The After Dark Show with Don Rogers https://www.spreaker.com/podcast/the-after-dark-show-with-don-rogers--6191691Forbidden Knowledge Network https://forbiddenknowledge.news/Become a supporter of this podcast: https://www.spreaker.com/podcast/forbidden-knowledge-news--3589233/support.

The future of Disease Care medicine is described as Predictive, Preventive, Personalized, Participatory, and Precision.  But as we first started to discuss on last week's show, Dr. Prather says all of those elements are already available in Structure-Function Health Care.  In this episode, we talk about:—How two patients diagnosed with the same Cancer can have different underlying causes for the same Disease. —The importance of getting to the root cause of an issue in Structure-Function Health Care, while Disease Care focuses on symptoms. —Why Dr. Prather actually cautions his patients against doing parasite cleanses or a Liver flush on their own.  And the gentle approach he utilizes instead. —The critical aspect of patient participation for Structure-Function Care to work, as the doctor and patient have to "work together."—How patients who understand their health condition actually report less pain and discomfort.  And why Dr. Prather always makes sure a patient receives a copy their lab tests with his own notes showing the numbers they are trying to achieve.—The features of Homeopathic Medicine that were actually copied by the pharmaceutical industry and even "led the way" in many of changes made by pharmaceutical companies. —Why both the diagnostics and treatments in Dr. Prather's office all focus on precision to target exactly what the patient needs.  And why the "normal" ranges listed on lab tests are not the "ideal" ranges you actually need for good health. —How Dr. Prather describes Disease Care like a football team's offense, while Structure-Function Care is a team's defense.  And how "defense wins championships".—Why using Structure-Function Health Care as primary care can improve outcomes by 85% and can also solve America's National debt.—The number one thing Dr. Prather would change in how medicine is practiced today. http://www.TheVoiceOfHealthRadio.com

In this episode of the TestGuild DevOps Toolchain Podcast, host Joe Colantonio sits down with Jennifer Rahmani, Co-founder and COO of Thoras.ai, a company redefining how infrastructure scales with AI-driven predictive technology. Drawing from her years as a DevOps engineer in the defense tech sector, Jennifer shares how she and her twin sister turned real-world frustrations into a reliability-first platform that eliminates the guesswork from scaling. We discuss how Thoras.ai integrates with Kubernetes to predict workload demand minutes—or even hours—in advance, allowing teams to maintain high availability without overspending. Jennifer explains why they use the right AI for the right use case, how their predictive autoscaling works in multi-cloud and hybrid environments, and how it helps SREs avoid downtime during unpredictable events like Black Friday or major product launches. Whether you're dealing with noisy data, high cloud bills, or sleepless nights worrying about reliability, this episode delivers practical insights for making smarter scaling decisions.

Demetrios chats with Arpita Vats about how LLMs are shaking up recommender systems. Instead of relying on hand-crafted features and rigid user clusters, LLMs can read between the lines—spotting patterns in user behavior and content like a human would. They cover the perks (less manual setup, smarter insights) and the pain points (latency, high costs), plus how mixing models might be the sweet spot. From timing content perfectly to knowing when traditional methods still win, this episode pulls back the curtain on the future of recommendations.// BioArpita Vats is a passionate and accomplished researcher in the field of Artificial Intelligence, with a focus on Natural Language Processing, Recommender Systems, and Multimodal AI. With a strong academic foundation and hands-on experience at leading tech companies such as LinkedIn, Meta, and Staples, Arpita has contributed to cutting-edge projects spanning large language models (LLMs), privacy-aware AI, and video content understanding.She has published impactful research at premier venues and actively serves as a reviewer for top-tier conferences like CVPR, ICLR, and KDD. Arpita's work bridges academic innovation with industry-scale deployment, making her a sought-after collaborator in the AI research community.Currently, she is engaged in exploring the alignment and safety of language models, developing robust metrics like the Alignment Quality Index (AQI), and optimizing model behavior across diverse input domains. Her dedication to advancing ethical and scalable AI reflects both in her academic pursuits and professional contributions.// Related Links#recommendersystems #LLMs #linkedin ~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreMLOps Swag/Merch: [https://shop.mlops.community/]Connect with Demetrios on LinkedIn: /dpbrinkmConnect with Arpita on LinkedIn: /arpita-v-0a14a422/Timestamps:[00:00] Smarter Content Recommendations[05:19] LLMs: Next-Gen Recommendations[09:37] Judging LLM Suggestions[11:38] Old vs New Recommenders[14:11] Why LLMs Get Stuck[16:52] When Old Models Win[22:39] After-Booking Rec Magic[23:26] One LLM to Rule Models[29:14] Personalization That Evolves[32:39] SIM Beats Transformers in QA[35:35] Agents Writing Research Papers[37:12] Big-Company Agent Failures[41:47] LinkedIn Posts Fade Faster[46:04] Clustering Shifts Social Feeds[47:01] Vanishing Posts, Replay Mode

NOLA Con Review Wildkat Open House and Match Announcement Mutant Rabbits WWESPN Review of The Accountant 2 The Champ Suge Whyte and a single call from Multiple Dave's more ......... live channel {Every Sunday Night ∙ 8-10P CT} https://nrr.mixlr.com/ all past shows available at Spotify: https://tinyurl.com/4bwkzfw7 Apple Podcasts​: https://goo.gl/SvRBJB SoundCloud​: https://soundcloud.com/not-real-radio Or Your Podcast App Store: https://www.zazzle.com/store/not_real_store

The future of Disease Care medicine is described as Predictive, Preventive, Personalized, Participatory, and Precision.  But Dr. Prather says all of those elements are already available in the Structure-Function Health Care that he practices.  In this episode, find out:—The FDA distinction between Disease Care Medicine and Structure-Function Health Care.—Why Dr. Prather says that "Structure-Function has always had the 5 P's" which are "integral" to this philosophy of care.—How Structure-Function Health Care is best known for its preventative benefits, but should also be better known for its necessity after a disease has already developed. —How the functional lab tests at Holistic Integration can "pick up on problems way before they come", which can then be prevented.—Why Dr. Prather cautions against drastic action because of genetic tests that show a tendency of a patient to develop a disease in the future. —The amazing story of a patient during the AIDS crisis who developed all the symptoms of AIDS after receiving what turned out to be a false HIV-positive test, but the symptoms disappeared after the second (and correct) negative test came back. —How Dr. Prather encouragingly says that "everything can be changed, everything can be helped, and everything can be prevented".  And why his experience with patients causes him to conclude that "having the right attitude makes all the difference in the world". —The importance of keeping the body structurally-aligned, as well as functionally-aligned, for the prevention of future issues.  And how Dr. Prather sees that 90% of people no longer fit the "normal" pattern of structural alignment due to changes that he never witnessed at the start of his career 40 years ago.—The reason Dr. Prather says anti-Cholesterol statin drugs have done "more harm than good".  And why using Cholesterol drugs as a preventative for future Cardiovascular Disease has failed. —Why Dr. Prather says that his three foundational lab tests (The Prather Profile Bloodwork, a Hair Analysis, and a stool kit) are usually all he needs to get a patient healthy before the need for "fancy" testing. http://www.TheVoiceOfHealthRadio.com

Recorded live at the Ascend Conference in Salt Lake City, this episode of ShiftShapers features John Troutman, Vice President of Business Development at Mind Club America. Host David A. Saltzman and John discuss the “mutual mystification” surrounding mental health solutions—and how employers and advisors can start cutting through the noise with real access, real engagement, and real outcomes.From personal burnout to a professional mission, John shares how his experience as a former pastor helped shape his drive to help a million people get the mental health support they need. The conversation unpacks access issues, poor utilization reporting, stigma, and the vital importance of employer-led engagement.

How do we move from reactive recruiting to predictive talent acquisition? In an era where performance metrics drive every business decision, recruitment often remains stubbornly intuition-based, especially when evaluating soft skills like empathy, communication, and critical thinking. What if AI could help us predict performance before a candidate even starts? And what happens when we connect hiring decisions to actual performance outcomes, creating a feedback loop that makes recruiters smarter over time? Can technology help us understand which risks are worth taking, and which gut feelings we should trust?  My guests this week are Veronique Lacasse, Senior Manager at Bell Canada, and Stephane Rivard, Co-founder and CEO of HiringBranch. In our conversation, Veronique and Stephane walk us through Bell's integrated approach to talent acquisition, which utilizes AI assessment data on soft skills to create a predictive, performance-driven hiring system that is still very much driven by human recruiters. In the interview, we discuss: Soft skills and business performance Measuring soft skills with AI driven assessments Challenges in high-volume hiring Building a feedback loop in recruiting, onboarding, and training Showing recruiters the performance outcomes of their decisions The candidate experience Why human recruiters aren't being replaced What does the future look like? Recruiting Future helps Talent Acquisition teams drive measurable impact by developing their strategic capability in Foresight, Influence, Talent, and Technology. If you're interested in finding out how your TA function measures up in these four critical areas, I've created the free FITT for the Future Assessment. It'll give you personalised insights to help you build strategic clarity and drive greater impact immediately. Just head to mattalder.me/podcast to complete the assessment; it takes less than 5 minutes. Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.

The Grizzlies announced that they will play their first ever regular season game in Europe, as they will face the Orlando Magic in Berlin and London as part of the NBA's Europe Games. This decision means that the Grizzlies will not host a nationally televised MLK Day game, which breaks from the longstanding tradition since the team moved to Memphis.On this episode, Keith goes over that decision (0:50), and then he speaks with former NBA front office worker Owen Phillips about the most (and least) predictive stats from summer league, the new rule change about heaves, and some other general NBA topics (7:45).You can sign up for Owen's newsletter at theF5.substack.comJoin the listener slack and get a bonus episode at Patreon.com/FastbreakBreakfastUse promo code FBBF and get up to $1000 in bonus cash at Underdog Fantasy: play.underdogfantasy.com/p-fastbreak-breakfastCheck out the NBA and Grizzlies merchandise at teepublic.com/stores/fastbreak-breakfastGet $20 off your first purchase at SeatGeek with promo code: FASTBREAKBREAK

What if your infrastructure could predict demand before it happens? In this episode, Nilo Rahmani, CEO and co-founder of Thoras AI, breaks down how predictive scaling is transforming the Kubernetes landscape. With over a decade of experience in site reliability engineering, Nilo shares why the observability market is slower to adopt AI—and why that might finally be changing. If you're navigating the pressures of DevOps or building AI tools for technical teams, this conversation is a must-listen.Key TakeawaysAI adoption in reliability engineering isn't about replacing humans—it's about reducing fire drills and enabling better decision-making.Predictive scaling using ML can dramatically cut cloud costs and reduce latency—without compromising reliability.DevOps teams remain cautious with AI due to the high stakes of downtime and the need for human-in-the-loop decision-making.The best tools won't just optimize infrastructure—they'll increase engineer confidence and operational readiness.Nilo's founder journey started with a thesis and became unstoppable once she “couldn't unsee the better way.”Timestamped Highlights[01:02] What Thoras AI actually does—and how it tackles the double challenge of utilization and cost[03:12] Why reliability engineering is a high-stakes, thankless job and how AI can change that[08:54] Can AI fully handle outages at 2 a.m.? Why human-in-the-loop still matters[13:22] The low-hanging fruit: where ML delivers value fast in infrastructure planning[17:56] Increasing confidence, not replacing engineers—rethinking developer experience with AI[24:38] Nilo's founder story: from SRE to CEO, driven by a problem too obvious to ignoreQuote of the Episode“I couldn't unsee that there's a better way. Using machine learning to make decisions in reliability engineering is the obvious next step.”Resources MentionedThoras AI: thoras.aiConnect with Nilo on LinkedIn: linkedin.com/in/nilo-devopsCall to ActionEnjoyed this episode? Share it with someone who lives on-call or is building for DevOps teams. Subscribe on your favorite platform and leave a review—it helps more tech professionals discover the show.

In this episode, I dive into a real, timely conversation with Scott Brighton, CEO of Bonterra — a social good software company helping nonprofits raise and give more through data-driven innovation. We talk candidly about what AI and data can actually do for nonprofit leaders looking to grow their impact, especially when resources are tight.If you've ever felt overwhelmed by the idea of “using data” or confused about what AI can realistically do for your small-but-mighty team, this one's for you.We talk about the why and the how — and Scott shares some real-world tools, examples, and strategies that can help organizations like yours scale smarter (not harder). This is about doing more of what works, with less burnout.

In this episode of Breaking Math, Autumn explores the complex world of AI ethics, focusing on its implications in education, the accuracy of AI systems, the biases inherent in algorithms, and the challenges of data privacy. The discussion emphasizes the importance of ethical considerations in mathematics and computer science, advocating for transparency and accountability in AI systems. Autumn also highlights the role of mathematicians in addressing these ethical dilemmas and the need for society to engage critically with AI technologies.Takeaways AI systems can misinterpret student behavior, leading to false accusations. Bias in AI reflects historical prejudices encoded in data. Predictive analytics can help identify at-risk students but may alter their outcomes. Anonymization of data is often ineffective in protecting privacy. Differential privacy offers a way to share data while safeguarding individual identities. Ethics should be a core component of algorithm design. The impact of biased algorithms can accumulate over time. Mathematicians must understand both technical and human aspects of AI. Society must question the values embedded in AI systems. Small changes in initial conditions can lead to vastly different outcomes.Chapters 00:00 Introduction to AI Ethics 02:14 The Accuracy and Implications of AI in Education 04:14 Bias in AI and Its Consequences 05:45 Data Privacy Challenges in AI 06:37 Mathematical Solutions for Ethical AI 08:04 The Role of Mathematicians in AI Ethics 09:42 The Future of AI and Ethical ConsiderationsSubscribe to Breaking Math wherever you get your podcasts.Become a patron of Breaking Math for as little as a buck a monthFollow Breaking Math on Twitter, Instagram, LinkedIn, Website, YouTube, TikTokFollow Autumn on Twitter and InstagramBecome a guest hereemail: breakingmathpodcast@gmail.com