Podcasts about Analytics

Is 2026 the year AI finally has to prove it is worth the investment? In this episode, I'm joined by Chris Riche-Webber, VP of Business Intelligence and Analytics at SmartRecruiters, to explore why so many AI and agentic AI initiatives stall after the pilot phase and what separates the projects that scale from the ones that quietly disappear. With Gartner predicting that more than 40 percent of agentic AI programs could be cancelled by 2027, Chris brings a pragmatic, data-led perspective on what is really happening inside organizations as the hype meets operational reality. We talk about the fundamentals that have not changed despite the new technology. Influence, clearly defined problems, measurable impact, and adoption still determine success, yet they are often overlooked in the rush to deploy the latest tools. Chris explains why "good vibes" are no longer enough in front of a CFO, how to baseline outcomes properly, and why ownership of results is one of the most common missing pieces in enterprise AI programs. A big part of the conversation focuses on what Chris calls the "agent washing" problem. Just as products are sometimes marketed with fashionable labels that do not reflect their real value, many solutions are being positioned as agentic without delivering true autonomy or business outcomes. We discuss how leaders can cut through the noise by asking better questions, aligning technology to specific use cases, and recognizing when simple automation is the right answer. Trust, adoption, and measurable ROI emerge as the three signals that determine whether an AI initiative survives. Chris shares a clear framework for defining these signals in a way that is consistent, comparable over time, and meaningful to the executive team. We also explore how connecting talent decisions to revenue, productivity, and retention changes the conversation, especially in the context of SmartRecruiters' broader SAP ecosystem and the opportunity to link people data directly to business performance. This is a conversation about moving from experimentation to accountability, from buying narratives to solving real problems, and from technology-first thinking to outcome-first leadership. So as the window for easy wins closes and the demand for proof of value grows, will your AI strategy be remembered as a pilot that generated excitement or as an initiative that delivered measurable business impact?

This week on Bet the Process, the No-Stats All-Star Shane Battier joins to discuss his journey from being a traditional scoring-focused player to embracing analytics in his NBA career, how basketball analytics has evolved over the years, and his transition to business as chief culture advisor for Palmetto Solar.

Matt Harmon of Yahoo Sports and Reception Perception joins Thor to preview and share his knowledge at the NFL Combine, discussing the WR group testing set to happen on Saturday, his info on the prospect group and so much more! Then co-founder and CEO of Reel Analytics joins the show to talk about in-game athleticism score and how it's measured, how to use that to evaluate atheletes, and exude his own knowledge on the crop of players at the combine!See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Mark, Cris & Marisa reunite for a lively discussion about their predictions around AI's impact on the economy over the next year or two. The team talks about their recently released webinar & white paper on the Macroeconomic Consequences of AI and answers several great listener questions in the process. Marisa and Cris try to talk Mark down off the AI-apocalypse ledge, as the once eternally optimistic Zandi has gone down a darker path recently.  Jenna Score: 8.5/10 For a deeper dive on AI and the macroeconomy, see our new paper, The Macroeconomic Consequences of Artificial Intelligence, where we model four potential economic paths over the next decade. We also walk through the scenarios in a companion webinar available now on-demand. Read the paper: https://www.economy.com/getfile?q=2B555C90-1118-4A49-BDAA-5C0A99F83A9E&app=download Watch the webinar: https://bit.ly/3OF6dn9 Read the Citrini Research Scenario on AI here: https://www.citriniresearch.com/p/2028gic Email us for more info about the Moody's '26 Summit in San Diego Hosts: Mark Zandi – Chief Economist, Moody's Analytics, Cris deRitis – Deputy Chief Economist, Moody's Analytics, and Marisa DiNatale – Senior Director - Head of Global Forecasting, Moody's Analytics Follow Mark Zandi on 'X' and BlueSky @MarkZandi, Cris deRitis on LinkedIn, and Marisa DiNatale on LinkedIn Questions or Comments, please email us at helpeconomy@moodys.com. We would love to hear from you. To stay informed and follow the insights of Moody's Analytics economists, visit Economic View. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

BEST OF: Step into the Conspiracy Finals as we dissect the most polarizing NBA rigged theory: magnets in the basketball. We investigate the "impossible" shots and viral "magnet proof" videos, revealing how a decade-old NBA parody commercial became the blueprint for modern basketball conspiracy theories. From Kawhi Leonard's iconic Game 7 bounce to the physics of LeBron James and Kobe Bryant's record-breaking misses, we challenge the narrative that the league is a scripted sports production like the NFL. We also tackle the "magnet toggle" claims surrounding stars like Caitlin Clark and Angel Reese, analyzing if these bizarre rim-hangers are a secret scheme or just the statistical certainty of 200,000 shots per season. Discover the truth behind the magnetized rimmyth and why the internet is obsessed with "glitches in the matrix" on the hardwood.*The is the FREE archive, which includes advertisements. If you want an ad-free experience, you can subscribe below underneath the show description.

I am Rolf Claessen and together with my co-host Ken Suzan I welcome you to Episode 172 of our podcast IP Fridays. Today's interview guests are Co-Founder & CEO of Inception Point AI, Jeanine Whright, and Mark Stignani, who is Partner & Chair of Analytics Practice at Barnes & Thornburg LLP. https://www.linkedin.com/in/jeaninepercivalwright https://www.linkedin.com/in/markstignani Inception Point AI But before the interview I have news for you: The Unified Patent Court (UPC) ruled on Feb 19, 2026, that specialized insurance can cover security for legal costs. This is vital for firms, as it eases litigation financing and lowers financial hurdles for patent lawsuits by removing the need for high liquid assets to enforce rights at the UPC. On Feb 12, 2026, the WIPO Coordination Committee nominated Daren Tang for a second six-year term as Director General. Tang continues modernizing the global IP system, focusing on SMEs, women, and digital transformation. His confirmation in April is considered certain. An AAFA study from Feb 4 reveals 41% of tested fakes (clothing/shoes) failed safety standards. Many contained toxic chemicals like phthalates, BPA, or lead. The study highlights that counterfeiters increasingly use Meta platforms to sell unsafe imitations directly to consumers. China's CNIPA 2026 report announced a crackdown on bad-faith patent and trademark filings. Beyond better examination quality, the agency will sanction shady IP firms and stop strategies violating “good faith” to make China’s IP system more ethical and innovation-friendly. Now, let's hear the interview with Jeanine Whright and Mark Stignani! How AI Is Rewiring Media & Entertainment: Key Takeaways from Ken Suzan's Conversation with Jeanine Wright and Mark Stignani In this IP Fridays interview, Ken Suzan speaks with two repeat guests who look at the same phenomenon from two angles: Jeanine Wright, Co-Founder & CEO of Inception Point AI, as a builder of AI-native entertainment, and Mark Stignani, Partner and Chair of the Analytics Practice at Barnes & Thornburg LLP, as a lawyer advising clients who are trying to use AI without stepping into a legal (or ethical) crater. What emerges is a clear picture: generative AI is not just “another tool.” It is rapidly becoming the default infrastructure for creative work—while the rules around ownership, consent, and accountability lag behind. 1) What “AI-generated personalities” really are (and why that matters) Jeanine's company is not primarily “cloning” real people. Instead, Inception Point AI creates original, fictional personalities—characters with backstories, ambitions, and evolving arcs—then deploys them into the world as podcast hosts and content creators (and eventually actors and musicians). Her key point: the creative work still starts with humans. Writers and creators define the concept, tone, audience, and story engine. What AI changes is speed, cost, and iteration—and therefore what is economically feasible to produce. 2) The “generative content pipeline” isn't a magic button A recurring misconception Ken raises is the idea that someone “pushes a button” and content pops out. Jeanine explains that real production looks more like a hybrid studio: A creative team defines character, voice, format, and storyline. A technical team builds what she calls an “AI orchestration layer” that combines multiple models and tools. The “stack” differs by format: the workflow for a long-form audio drama is different from a short-form beauty clip. This matters because it reframes AI content not as a single output, but as a pipeline decision: which tools, which data sources, which QA, and which governance steps are used—and where human review happens. 3) The biggest legal questions: origin, liability, ownership, and contracts Mark doesn't name a single “top issue.” He describes a cluster of problems that repeatedly show up in client conversations: Training data and “origin story” Clients keep asking: Can I legally use AI output if the tool was trained on copyrighted works? Even if the output looks new, the unease is about whether the tool's capabilities are built on unlicensed inputs. Liability for unintended harm Mark flags risk from AI content that inadvertently infringes, defames, or carries bias. The legal exposure may not match the creator's intent. Ownership and protectability He points to a big gap: many jurisdictions are still reluctant to grant classic IP rights (copyright or patent-style protection) to purely AI-generated material. That creates uncertainty around whether businesses can truly “own” what they produce. Old contracts weren't written for AI A final, practical point: many agreements—talent contracts, author clauses, data licenses—predate generative AI and simply don't address it. That leads to disputes about scope, permissions, and—crucially—indemnities. 4) Are we at a tipping point? The “gold rush” vs. “next creative era” views Jeanine frames AI as “the world's most powerful creative tool”—comparable to previous step-changes like animation, special effects, and CGI. For her, the strategic implication is simple: creators who learn to use AI well will expand what they can build and test, faster than ever. Mark's metaphor is more cautionary: he calls the moment a “gold rush” where technology is sprinting ahead of law. Courts are getting flooded with foundational disputes, while legislation is fragmented—he notes that states may move faster than federal frameworks, and that labor agreements (e.g., union protections) will be a key pressure point. 5) Democratization: more creators, more niche content, more experimentation One of the most concrete themes is access. Jeanine argues AI will: Lower production barriers for independent filmmakers and storytellers. Reduce the need for “hit-making only” economics that dominate Hollywood. Make micro-audience content commercially viable. Her example is intentionally niche: highly localized, specialized content (like a “pollen report” for many markets) that would never have made financial sense before can now exist—and thrive—because the production cost drops and personalization scales. 6) Likeness, consent, and “digital performers”: what happens when AI resembles a real actor? Ken pushes into a sensitive area: what if someone generates a performance that closely resembles a living actor without consent? Mark outlines the current (imperfect) toolbox—because, as he emphasizes, most laws weren't built for this scenario. He points to practical claims that may come into play in the U.S., such as rights of publicity and false endorsement-type theories, and notes that whether something is parody or “too close” can become a major fault line. Jeanine explains her company's operational approach: They focus on original personalities, designed “from scratch.” They build internal checks to avoid misappropriating known names, likenesses, or recognizable identities. If they ever work with real people, the model would be licensing their likeness/voice. A subtle but important business point also appears here: Jeanine expects AI-native characters themselves to become licensable assets—meaning the entertainment economy may expand to include “celebrity rights” for fully synthetic personalities. 7) Ethics: the real line is “deception,” not “AI vs. human” The ethical core of the conversation is not “AI is bad” or “AI is good.” It's how AI is used—especially whether audiences are misled. Mark highlights several ethical risks: Misuse of tools to manipulate faces and content (“AI slop” and political misuse). Displacement of creative workers without adequate transition support. A concern that AI often optimizes toward “statistical averages,” potentially flattening originality. Jeanine agrees ethics must be designed into the system. She describes regular discussions with an ethicist and emphasizes a principle: transparency. Her company discloses when content or personalities are AI-generated. She argues that if people understand what they're engaging with and choose it knowingly, the ethical problem shifts from “AI exists” to “Are we tricking people?” Mark adds a real-world warning: deepfakes are now credible enough to enable serious fraud—he references a case-like scenario where a synthetic video meeting deceived an employee into authorizing a payment. The point is clear: authenticity and verification are no longer optional. 8) The “dead actor” hypothetical: legal permission vs. moral intent Ken raises a provocative scenario: an actor's estate authorizes an AI-generated new performance, but the actor opposed such technology while alive. Neither guest offers a simplistic answer. Jeanine suggests that even if the estate holds legal rights, a company might choose to avoid such content out of respect and because the ethical “overhang” could damage the storytelling outcome. She also notes the harder question: people who died before today's capabilities may never have been able to meaningfully consent to what AI can now do—raising questions about how we interpret legacy intent. Mark underscores the practical contract problem: many rights are drafted “in perpetuity,” but that doesn't automatically settle the ethical question. 9) Five-year forecast: “AI everywhere,” but audiences may stratify Ken closes with a prediction question: in five years, how much entertainment content will significantly involve AI—and will audiences care? Jeanine predicts AI becomes the default creative layer for most content creation. Mark is slightly more conservative on the percentage, but adds an important nuance: the market will likely stratify. Low-cost, high-volume content may become saturated with AI, while premium segments may emphasize “human-made” as a differentiator—especially if disclosure norms become standard. Bottom line for business leaders and creators This interview lands on a pragmatic conclusion: AI will change how content is made at scale, and the competitive edge will go to teams that combine creative taste, operational discipline, and legal/ethical governance. If you're building, commissioning, or distributing content, the questions you can't dodge anymore are: What's the provenance of the tools and data you rely on? Who is responsible when output harms, infringes, or misleads? What rights can you actually claim in AI-assisted work? Do your contracts and disclosures match the new reality? Ken Suzan: Thank you, Rolf. We have two returning guests to the IP Friday’s podcast. Joining me today is Janine Wright and Mark Stignani. Our topic for discussion, how is AI transforming the media and entertainment industries today? We look at the issues from differing perspectives. A bit about our guests, Janine Wright is a seasoned board member, CEO, global COO and CFO. She’s led organizations from startup to a $475 million plus revenue subsidiary of a public company. She excels in growth strategy, adopting innovative technologies, scaling operations and financial management. Janine is a media and entertainment attorney and trial litigator turned technologist and qualified financial expert. She is the co-founder and CEO of Inception Point AI, a growing company that is paving new ground with AI-generated personalities and content through developing technology and story. Mark Stignani is a partner with Barnes & Thornburg LLP and is based in Minneapolis, Minnesota. He is the chair of the data analytics department with a particular emphasis on artificial intelligence, machine learning, cryptocurrency and ESG. Mark combines the power of artificial intelligence and machine learning with his skills as a corporate and IP counsel to deliver unparalleled insights and strategies to his clients. Welcome, Janine and Mark to the IP Friday’s podcast. Jeanine Whright: Thank you. Thank you. Thank you so much for having me and fun to be back. It feels nostalgic to be here. Ken Suzan: That’s right. And you both were on the program. So it’s fantastic that you’re both back again. So our format, I’m going to ask a question to Janine and or Mark and sometimes to both of you. So that’s going to be how we proceed. Let’s jump right in. Janine, your company creates AI-generated actors. For listeners who may not be familiar, can you briefly explain what that means and what’s now possible that wasn’t even two years ago? Jeanine Whright: Sure. Yeah, we are creating AI-generated personalities. So new characters, new personalities from scratch. We design who these personalities are and will be, how they will evolve. So we give them complex backstories. We give them hopes and dreams and aspirations. We every aspect of them, their families, how they’re going to evolve. And in the same way that, say, you know, Disney designs the character for its next animated feature or, you know, an electronic arts designs a character for its next major video game. We are doing that for these personalities and then we are launching them into the world as podcast hosts, content creators on social platforms like YouTube, Instagram and TikTok. And even in the future, you know, actors in feature length films, musicians, etc. Ken Suzan: Very fascinating. Mark, from your practice, what’s the single biggest legal question or dispute you’re seeing clients wrestle with when it comes to AI and media creation? Mark Stignani: Well, I think that, you know, it’s not just one thing, it’s like four things. But most of them tend to be kind of the origin story of AI data or AI tools that they use because, you know, but for the use of AI tools trained on copyrighted materials, the tools wouldn’t really exist in their current form. So a lot of my clients are wondering about, you know, can I legally use this output if it’s built upon somebody else’s IP? The second ask, the second flavor of that is really, is there liability being created if I take AI content that inadvertently infringes or defames or biases there? So there’s the whole notion of training bias from the training materials that comes out. The third phase is really, you know, can I really own this? Because much of the world does not really give IP rights into AI-generated inventions, copyrighted materials. It’s still kind of a big razor. Then at the end of the day, you know, if it’s an existing relationship, does my contract even contemplate this? So everything from authors contracts on up to just use of data rights that predate AI. Ken Suzan: And Janine and Mark, a question to both of you. How would you describe where we are right now in the AI revolution in media and entertainment? Are we approaching a tipping point? And if so, what are the things we need to watch for? Jeanine Whright: Yeah, I definitely think that we’re at a phase where people are starting to come to the realization that AI is the world’s most powerful creative tool. But that, you know, storytelling and point of view is what creates demand and audiences. And AI doesn’t threaten or change that. But it does mean that as people evolve in this medium, they’re very likely going to need to adopt, utilize and figure out how to hone their craft with these AI-generated content and these AI-generated toolings. So this is, you know, something that people have done certainly in the past in all sorts of ways in using new tools. And we’ve seen that make a significant change in the industry. So you look at, you know, the dawn of animation as a medium. You look at use of special effects, computer-generated imagery in the likes of Pixar. And this is certainly the next phase of that evolution. But because of the power of the tool and what will become the ubiquity of the tool, I think that it’s pretty revolutionary and all the more necessary for people to figure out how to embrace this as part of their creative process. Ken Suzan: Thank you, Janine. Mark, your thoughts? Mark Stignani: Yeah, I mean, I liken this to historically to like the California gold rush right now, because, you know, the technology is so far outpaced in any of the legal frameworks that are available. And so we’re just trying to shoehorn things in left and right here. So, I mean, the courts are beginning to start to engage with the foundational questions. I don’t think they’re quite there yet. I just noticed Anthropic got sued again by another group of people, big music group, because of the downloaded works they’ve done. I mean, so the courts are, you know, the courts are certainly inundated with, you know, too many of these foundational questions. Legislatively, hard to tell. I mean, federal law, the federal government is not moving uniformly on this other than to let the gold rush continue without much check and balance to it. Whereas states are now probably moving a lot faster. Colorado, Illinois, even Minnesota is attempting to craft legislation and limitations on what you can do with content and where to go with it. So, I mean, the things we need to watch for any of the fair use decisions coming out here, you know, some of the SAG-AFTRA contract clauses. And, you know, again, the federal government, I just, you know, I got a big shrug going as to what they’re actually going to come up with here in the next 90 to 100 days. So, but, you know, I think they’ll be forced into doing something sooner than later. Ken Suzan: Okay, let’s jump into the topic of the rise of generative content pipelines. My first question to Janine. Studios and production companies are now building what some call generative content pipelines. This is where AI systems produce everything from scripts to visual effects to voice performances. What efficiencies and creative possibilities does this unlock for the industry? Jeanine Whright: Yeah, so this is quite a bit of what we do. And if I could help pull the curtain back and explain a little bit. Ken Suzan: That’d be great. Jeanine Whright: Yeah, there’s this assumption that, you know, somebody is just sitting behind a machine pushing a button and an out pops, you know, what it is that we’re producing. There’s actually quite a bit of humans still in the loop in the process. You know, we have my team as creators. The other half of my team is the technologists. And those creators are working largely at what we describe as the the tip of the sphere. So they’re, of course, coming up with the concepts of who are these personalities? What are these personalities, characters, backgrounds going to be a lot of like rich personality development? And then they’re creating like what are the formats? What are the kind of story arcs? What is the kinds of content that this this character wants to tell? And what are the audiences they’re desiring to reach and what’s most going to resonate with them? And then what we built internally is what we refer to as an AI orchestration layer. So that allows us to pull from basically all of the different models and then all of these different really cool AI tools. And put those together in such a way and combine those in such a way that we can have the kind of output that our creative team envisions for what they want it to be. And at the end of the day, what you what the stack looks like for, say, a long form audio drama, like the combination of LLMs that we’re going to use in different parts of scripting and production and, you know, ideating and all of that. And the kinds of tooling that we use to actually make it and get it to sound good and have the kinds of personality characteristics that we want to be in an authentic voice for a podcast is going to be different than the tech stack and the tool stack that we might use for a short form Instagram beauty tip reel. And so there’s a lot of art in being able to pull all of these tools together to get them to do exactly what you want them to do. But I think the second part of your question is just as interesting as the first. I mean, what is what possibilities is this unlocking? So of course you’re finding efficiencies in the creative production process. You can move faster. You can do things were less expensive, perhaps, and you were able to do it before. But on the creator side, I think one thing that hasn’t been talked about enough is how it is really like blown wide the aperture of what creators can do and can envision. Traditionally, you know, Hollywood podcasting, many of these businesses that become big businesses have become hit making businesses where they need to focus on a very narrow of wide gen pop content that they think is going to get tens of millions, hundreds of millions in, you know, fans and dollars in revenue for every piece of content that they make. So the problem with that is, is that it really narrows the kinds of things that ultimately get made, which is why you see things happening in Hollywood, like the Blacklist, which is, you know, this famous list of really exceptional content that remains unpredited, unproduced, or why you see things like, you know, 70 to 80% of the top 100 movies being based on pre-existing IP, right? Because these are such huge bets that you need to feel very confident that you’re going to be able to get big, big audiences and big, big dollars from it. But with AI, and really lowering the barrier to entry, lowering the costs of production and marketing, the experimentation that you can do is really, really phenomenal. So, you know, my creative team, if they have an idea, they make it, you know, they don’t have to wring their hands through like a green lighting process of, you know, should we, shouldn’t we, like we, we can make an experiment with lots of different things, we can do various different versions of something. We can see what would this look like if I placed it in the 1800s, or what if I gave this character an Australian accent, and it’s just the power of being able to have this creative partner that can ideate with you and experiment with you at rocket speed. With the creators that are embracing it, you can see how it is really fun for them to be able to have this wide of a range of possibility. Ken Suzan: Mark, when you hear about these generative pipelines, what are the immediate red flags or concerns that come to mind from a legal standpoint? How about ethics underlying all of this? Well, Mark Stignani: that was not, that’s the number one red flag because I mean, we are seeing not just that in the entertainment industry, but it literally at political levels, and the kind of the phrase, to turn the phrase AI slop being generated, we’re seeing, you know, people’s facial expressions altered. In some cases, we’re seeing AI tools being misused to exploit various groups of individuals and genders and age groups. So I mean, there’s a whole lot of things ethically that people are using AI for that just don’t quite cover it. Especially in the entertainment industry, I mean, we’re looking at a fair amount of displacement of human workers without adequate transition support, devaluation of the creative labor. I mean, the thing though that I’m always from a technical standpoint is AI is simply a statistical average of most everything. So it kind of devalues the benefit of having a human creator, a human contribution to it. That’s the ethical side. But on the legal side, I see chain of title issues. I mean, because these are built on very questionable IP ownership stages, I mean, in most of these tools, there has been some large copying, training and taking of copyrighted materials. Is it transformational? Maybe. But there’s certainly not a chain of title, nor is there permission granted for that training. I mentioned SAG-AFTRA earlier, I think there’s a potential set of union contract aspects to this that if you know many of these agreements and use sub-licenses for authors and actor agreements, they weren’t written with AI in mind. So that’s another red flag. And also I just think in indemnification. So if we ultimately get to a point where groups are liable for using content without previous license, then who’s liable? Is the tool maker the liable group or the actual end user? So those are probably my top four red flags. But I think ethics is probably my biggest place because just because we can do something from an ethical standpoint doesn’t mean we should. Jeanine Wright: Yeah, if I can respond to both of those points. I mean, one from a legal perspective, just to be very clear, I mean, we are always pulling from multiple different models and always pulling from multiple different sources. And we even have data sources that we license or use for single source of truth on certain pieces of information. So we’re always pulling things together from multiple different sources. We also have built into our process, you know, internal QAing and checking to make sure that we’re not misappropriating the name or likeness of any existing known personality or character. We are creating original personalities there. We design their voice from scratch. We design their look from scratch. So we’re not on our personality side, we’re not pulling or even taking inspiration from existing intellectual property that’s already out there in creating these personalities. On the ethical side, I agree. I mean, when we came out of stealth, we came out of stealth in September. There was certainly quite a bit of backlash from folks in my—I previously co-founded a company in the audio space. I mean, there’s been many rounds of layoffs in audio and in many other parts of the entertainment industry. So I’m very sensitive to the feedback around, like, is this job displacement? I mean, I do think that the CEO of NVIDIA said it right when he said, you’re likely not going to lose your job to AI, but you will lose your job to somebody who knows how to use AI. I think these tools are transforming the way that content is made and that the faster that people can embrace this tooling, the more likely they’re going to be having the kinds of roles that they want in, you know, in content creation and storytelling in the future. And we are hiring. I’m hiring AI video creators, AI audio creators. I’m hiring AI developers. So people who are looking for those roles, I mean, please reach out to me, we would love to work with you and we’d love to grow with you. We also take the ethics very seriously. For the last few months or so, I’ve met regularly with an ethicist, we talk about all sorts of issues around, you know, is designing AI-generated people, you know, good for humanity? And what about authenticity and transparency and deception, and how are we in building in this space going to avoid some of the problems that we’ve seen with things like social media and other forms of technology? So we keep that very top of mind and we try to build on our own internal values-based system and, you know, continue to elevate and include the humanity as part of the conversation. Ken Suzan: Thank you, Janine. Janine, some argue that AI content pipelines will level the field for filmmaking, giving independent creators access to tools that were once available only to major studios. Is that the future you envision? Jeanine Wright: I do think that with AI you will see an incredible democratization of access to technology and access to these capabilities. So I do think, you know, rise of independent filmmakers, you won’t have as many people who are sitting on a brilliant idea for the next fantastic script or movie that just cannot get it made because they will be able to with these tools, get something made and out there, at least to get the attention of somebody who could then decide that they want to invest in it at a studio kind of level in the future. The other thing that I think is really interesting is that I think, you know, AI will empower more niche content and more creators who can thrive in micro-communities. So it used to be because of this hit generation business model, everything needed to be made for the masses and a lot of content for niche audiences and micro-communities was neglected because there was just no way to make that content commercially viable. But now, if you can leverage AI—we make a pollen report podcast in 300 markets, you know, nobody would have ever made that before, but it is very valuable information, a very valuable piece of content for people who really care about the pollen in their local community. So there’s all sorts of ways that being able to leverage AI is making it more accessible both to the creator and to the audience that is looking for content that truly resonates with them. Ken Suzan: Mark, let’s talk about the legal landscape right now. If someone creates an AI-generated performance that closely resembles a living actor without their consent, what legal recourse does that actor have? Mark Stignani: Well, I mean, I think we can go back to the OpenAI Scarlett Johansson thing where, you know, if it’s simply—well, the “walks like a duck, quacks like a duck” type of aspect there. You know, I think it’s pretty straightforward that they need to walk it back. I mean, the US doesn’t have moral rights, really, but there’s a public visage right, if you will. And so, one of the things that I find predominantly useful here is that these actors likely have rights of publicity there, we probably have a Lanham Act false endorsement claim, and you know, again, if the performance is not parody, and it’s so close to the original performance, we probably have a copyright discussion. But again, all of these laws predate the use of AI, so we’re going to probably see new sets of law. I mean, we’re probably going to see “resurrection” frameworks, we’ll probably have frameworks for synthetic actors and likenesses, but the rules just aren’t there yet. So, unfortunately, your question is largely predictive versus well-settled at this point. Ken Suzan: Janine, your company works with AI actors. How do you navigate the questions of consent and likeness compensation when creating digital performers? Jeanine Wright: I mean, if we—so first of all, if we were to work with a person who is an existing real-life person or was an existing real-life person, then we would work with them to license their name and likeness or their voice or whatever aspects of it we were going to use in creating content in partnership with them. Not typically our business model; we are, as I said, designing all of our personalities from scratch and making all of our content originally. So, we’ve not had to do that historically. Now, you know, the flip side is: can I license my characters as if they’re similar to living characters? Like will I be able to license the name and likeness and voice of my AI-generated personalities? I think the answer is yes and we’re already starting to do that. Ken Suzan: Let’s just switch gears into ethics and AI because I find this to be a really fascinating issue. I want to look at a hypothetical. And this is to both of you, Janine and Mark: an AI system creates a new performance by a beloved actor who passed away decades ago, and the actor’s estate authorizes it, but the actor was known to have expressed opposition to such technology during their lifetime. Is this ethical? Jeanine Wright: This feels like a Gifts, Wills, and Trusts exam question. Ken Suzan: It sounds like it, that’s right. Jeanine Wright: Throwing me back to my law school days. Exactly. What are your thoughts? It’d be interesting to see like who has the rights there. I mean, I think if you have the legal rights, the question is around, you know, is it ethical to go against what you knew was somebody’s wishes at the time? I guess the honest answer is I don’t know. It would depend a lot on the circumstances of the case. I mean, if we were faced with a situation like that where there was a discrepancy, we would probably move away from doing that content out of respect for the deceased and out of a feeling that, you know, if this person felt strongly against it, then it would be less likely that you could make that storytelling exceptional in some way—it would color it in a way that you wouldn’t want in the outcome. And I feel like there’s—I mean, certainly going forward and it’s already happening—there are plenty of people I think who have name, likeness, and voice rights that they are ready to license that wouldn’t have this overhang. Ken Suzan: Mark, your thoughts? Mark Stignani: Yeah, I mean, again, I have to kind of go back to our property law—the Rule Against Perpetuities. You know, from a property standpoint to AI rights and likenesses—since most of the digital replica contracts that I’ve reviewed generally do talk about things in perpetuity. But if it’s not written down for that actor and the estate is doing this—is it ethical? You know, that is the debate. Jeanine Wright: Well, gold star to you, Mark, for bringing up the Rule Against Perpetuities. There’s another one that I haven’t heard for many years. This is really taking me back to my law school days. Ken Suzan: It’s a throwback. Jeanine Wright: The other thing that’s really interesting is that this technology is really so revolutionary and new that it’s hard to even contemplate now what it is going to be in a decade, much less for people who have passed away to have contemplated what the potential for it could be today. So you could have somebody who is, perhaps, a deceased musician who expressed concerns about digital representations of themselves or digital music while they were alive. But now, the possibility is that you could recreate—certainly I could use my technology to recreate—that musician from scratch in a very detailed way, trained on tons of different available data. Not just like a digital twin or a moving image of them, but to really rebuild their personality from scratch, so that they and their music could be reintroduced to totally new generations in a very respectful and authentic way to them. It’s hard to know, with the understanding that that is possible, whether or not somebody who is deceased today would or would not agree to something like that. I mean, many of them might want, under those circumstances, for their music to live on. These deceased actors and musicians could live forever with the power of AI technology. Mark Stignani: Yeah, I really just kind of go to the whole—is deep-faking a famous actor the best way to preserve them or keep them live? Again, that’s a bit more of an ethical question because the deep fakes are getting good enough right now to create huge problems. Even zoom meetings in Hong Kong where a CFO was on a call with five synthetic actors who all looked like his coworkers and they sent a big check out based upon that. So again, the technology is getting good enough to fool people. Jeanine Wright: I think that’s right, Mark, but I guess I would just highlight the same way that it always has been: the ethical line isn’t AI versus human, the ethical line is about deception. Like, are you deceiving people? And if people know what it is that they’re getting and they’re choosing to engage with it, then I think it isn’t about the power of the technology. In our business, we have elected—not everybody has—but we have elected to be AI transparent. So we tell people when they listen to our show, we include it in our show notes, we include it on our socials. Even when we’re designing our characters to be very photo-realistic, we make an extra point to make sure that people know that this is AI-generated content or an AI personality. Like, our intention is not to deceive and to be candid. From a business model perspective, we don’t need to. I mean, there’s already people who know and understand that it is AI, and AI is different than people. Because it is AI, there’s all sorts of things that you can do with it that you would not be able to do with a real person. You know, we get people who ask us on the podcast side, we get all sorts of crazy funny requests. You know, people who say, “Can I text with this personality? Can I talk to them on the phone? Can they help me cook in the kitchen? Can they sing me Happy Birthday? Can they show up at my Zoom meeting today because I think my boss would love it?” You know, all sorts of different ways that people are wanting to engage with these characters. And now we’re in the process of rolling out real-time personalities so people will be able to engage with our personalities live. It is a totally different way that people are able to engage with content, and people can, as they choose, decide what kind of content they want to engage with. Ken Suzan: Jeanine and Mark, we’re coming to the end of this podcast. I would love to keep talking for hours but we have to stay to our timetable here. Last question: five years from now, what percentage of entertainment content do you predict will involve significant AI generation, and will audiences care about that percentage? Jeanine? Jeanine Wright: I mean, I would say 99.9%. I mean, already you’re seeing—I think YouTube did a survey—that it was like 90% of its top creators said that they’re using AI as material components of their content creation process. So, I think this will be the default way that content is created. And content that is not made with AI, you know, there’ll be special film festivals for non-AI generated content, and that will be a special separate thing than the thing that everybody is doing now. Ken Suzan: Mark, your thoughts? Mark Stignani: Yeah, I go a little lower. I mean, I think Jeanine is right that we’re seeing, especially in the low-quality content creation and like the YouTube shorts and things like that, you know, there’s so much AI being pushed forward that the FTC even acquired an “AI slop” title to it. I do think that disclosure will become normalized, that the industries will be pushed to say when something is AI and what is not. And I think it’s very much like, you know, do you care about quality or not? If you value the human input or the human factor in this, there will be an upper tier where it’s “AI-free” or low AI assistant. I think that it’s going to stratify because the stuff coming through the social media platforms right now—I can’t be on it right now just because there’s so much nonsense. Even my children, who are without much AI training at all, find it just too unbelievable for them. So, I think it will become normalized, but I think that we’re going to see a bunch of tiers. Ken Suzan: Well, Jeanine and Mark, this has been a fantastic discussion of an ever-evolving field in IP law. Thank you to both of you for spending time with us today on the IP Friday’s podcast. Jeanine Wright: Thank you so much for having me. Mark Stignani: Appreciate your time. Thank you again.

Our latest guest brings a voice – and I do mean a voice – that you don't often hear in the data world. He's bold, he's sharp, and he's not afraid to call out the fluff that can cloud today's analytics conversations. Scott Taylor, also known as The Data Whisperer, is a global advocate for strategic data management, the author of Telling Your Data Story, and one of the most honest, and most likeable, truth-tellers in the data space. Whether he's breaking down metadata metaphors or championing the case for master data as the foundation of all things analytics, Scott's mission is crystal clear: No matter how fancy your AI is, it's worthless without the right data underneath. Scott is a keynote speaker at the upcoming 2026 INFORMS Analytics+ Conference, where he'll be shaking things up with his signature style. 

In this talk, Juan, Analytics Engineer and author of Fundamentals of Analytics Engineering share his professional journey from studying psychological research in Colombia to becoming one of the first analytics engineers in the Netherlands. We explore the evolution of the role, the shift toward engineering rigor in data modeling, and how the landscape of tools like dbt and Databricks is changing the way teams work.You'll learn about:- The fundamental differences between traditional BI engineering and modern analytics engineering.- How to bridge the gap between business stakeholders and technical data infrastructure.- The technical "glue" that connects Python and SQL for robust data pipelines.- The importance of automated testing (generic vs. singular tests) to prevent "silent" data failures.- Strategies for modeling messy, fragmented source data into a unified "business reality."- The current state of the "Lakehouse" paradigm and how it impacts storage and compute costs.- Expert advice on navigating the dbt ecosystem and its emerging competitors.Links:- DE Course: https://github.com/DataTalksClub/data-engineering-zoomcamp- Luma: https://luma.com/0uf7mmupTIMECODES:0:00 Juan's psychological research and transition to data4:36 Riding the wave: The early days of analytics engineering7:56 Breaking down the gap between analysts and engineers11:03 The art of turning business reality into clean data16:25 Why data engineering is about safety, not just speed20:53 Reimagining data modeling in the modern era26:53 To split or not to split: Finding the right team roles30:35 Python, SQL, and the technical toolkit for success38:41 How to stop manually testing your data dashboards46:34 Bringing software engineering rigor to data workflows49:50 Must-read books and resources for mastering the craft55:42 The future of dbt and the shifting tool landscape1:00:29 Deciphering the lakehouse: Warehousing in the cloud1:11:16 Pro-tips for starting your data engineering journey1:14:40 The big debate: Databricks vs. Snowflake1:18:28 Why every data professional needs a local communityThis talk is designed for data analysts looking to level up their engineering skills, data engineers interested in the business-logic layer, and data leaders trying to structure their teams more effectively. It is particularly valuable for those preparing for the Data Engineering Zoomcamp or anyone looking to transition into an Analytics Engineering role.Connect with Juan- Linkedin - https://www.linkedin.com/in/jmperafan/ - Website - https://juanalytics.com/Connect with DataTalks.Club:- Join the community - https://datatalks.club/slack.html- Subscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/r?cid=ZjhxaWRqbnEwamhzY3A4ODA5azFlZ2hzNjBAZ3JvdXAuY2FsZW5kYXIuZ29vZ2xlLmNvbQ- Check other upcoming events - https://lu.ma/dtc-events- GitHub: https://github.com/DataTalksClub- LinkedIn - https://www.linkedin.com/company/datatalks-club/ - Twitter - https://twitter.com/DataTalksClub - Website - https://datatalks.club/

Ben Criddle talks BYU sports every weekday from 2 to 6 pm.Today's Co-Hosts: Ben Criddle (@criddlebenjamin)Subscribe to the Cougar Sports with Ben Criddle podcast:Apple Podcasts: https://itunes.apple.com/us/podcast/cougar-sports-with-ben-criddle/id99676

In this powerful episode of The Fleet Success Show, Marc Canton sits down with Fleet Hall-of-Famer Steve Saltzgiver to tackle one of the most overlooked but critical areas in fleet: replacement planning. Steve shares jaw-dropping stories from his time leading Fortune 500 and government fleets, including how one change could have saved a company $800M. This episode explores why strategic fleet replacement is a fleet-wide performance driver, not just a financial issue. You'll hear about the ripple effects on technician staffing, spare ratios, maintenance costs, safety, and more. Key Takeaways Replacement is the “granddaddy” of all fleet processes, directly impacting every other aspect of fleet success, including technician staffing, space planning, and asset availability. Data-driven replacement decisions can yield millions in savings, and Steve shares how one fleet could have saved over $800M by adjusting its spare ratio. Fleet behavior is shaped by capital decisions. When budgets (not data) drive decision-making, safety and performance suffer. Analytics aren't enough if leadership won't act. Even when the math is clear, cultural resistance and short-term thinking can block progress. Chargebacks and lifecycle modeling are foundational tools for justifying replacements and funding future ones. Speaker Bios Steve Saltzgiver A Fleet Hall-of-Famer and former executive with both government and private sector fleets, Steve has turned around some of the most complex fleet operations in the country. He now serves as a senior fleet consultant with RTA, helping clients tackle issues from asset planning to culture transformation. Marc Canton VP of Product and Consulting at RTA: The Fleet Success Company, Marc brings deep expertise in fleet operations, leadership, and performance coaching. He co-hosts The Fleet Success Show and leads strategy for RTA's software and consulting offerings. Looking to take the next step to fleet success? Start by requesting your free copy of The Fleet Success Playbook. Written by fleet professionals for fleet professionals, the Playbook breaks down the four key pillars of fleet success, and gives you the tools you need to build a truly great fleet. Request your free (yes, really, free!) copy here: https://rtafleet.com/resources/fleet-success-playbook?utm_source=simplecast&utm_medium=footer_notes&utm_campaign=episode_213 Control fleet chaos with RTA Fleet360, proven software designed by fleet managers for fleet managers: https://rtafleet.com/book-a-demo?utm_source=simplecast&utm_medium=footer_notes&utm_campaign=episode_213

U.S. commodity markets finished lower Thursday, but soybean oil continued to shine, reaching its highest level since September 2023 amid a volatile trading day. Mike Zuzolo of Global Commodity Analytics breaks down the trade.

Film breakdown, analytics insight and fantasy football projection for Elijah Sarratt, who is set to be one of the most debated rookie picks from the 2026 NFL Draft class patreon.com/rookiebigboard Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Film breakdown, analytics insight and fantasy football projection for Justin Joly, who profiles as one of the best tight end rookie picks from the 2026 NFL Draft class patreon.com/rookiebigboard Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this episode, we unpack new pediatric research from the Vizient® Clinical Data Base (CDB) with Sg2 Associate Principal Rhae Ana Gamber and Vizient's Research, Analytics and Insights team—Lead Hannah Murphy, PhD, and Associate Principal Alyssa Harris. From rising ICU utilization and RSV surges to firearm injury, diabetes and mental health, the team explores how clinical complexity and community vulnerability are reshaping pediatric care. By layering in the patent pending Vizient Vulnerability Index™, they reveal how social risk factors influence where and how children access care—and with what outcomes. Tune in for data-driven insights that help health system leaders translate pediatric trends into strategic action.   Vizient Vulnerability Index™ Patent Pending. Copyright Vizient Inc. 2022. All rights reserved.   We are always excited to get ideas and feedback from our listeners. You can reach us at sg2perspectives@sg2.com, or visit the Sg2 company page on LinkedIn.

Dealers must create content that consumers TRUST. I had the opportunity to catch up with Art Pier at C-4 Analytics NADA 2026 booth for an incredibly insightful interview on dealership marketing. We discuss the marketing strategies that dealerships need to take action on in 2026. #nada2026 #automotive #dealership #nada #dealershipmarketing Digital Dealership Solutions: ddsolutions.ca Strategy With Jason: strategywithjason.com Bell2Bell: bell2bell.ca Listen To The Strategy With Jason Podcast: Apple Podcast: https://apple.co/3IwlT3v Spotify: https://spoti.fi/3fT8V3H Soundcloud: https://bit.ly/347rnDb

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss why most Q1 plans stall and how hidden fear holds teams back. You’ll learn simple ways to turn a big roadmap into tiny actions you can start. You’ll discover how generative AI can suggest low‑risk steps that keep momentum without a big budget. You’ll explore how to break the blame cycle and build real progress even in risk‑averse companies. Watch the episode to start moving your plan forward. Watch the video here: Can’t see anything? Watch it on YouTube here. Listen to the audio here: https://traffic.libsyn.com/inearinsights/tipodcast-gap-between-planning-execution.mp3 Download the MP3 audio here. Need help with your company’s data and analytics? Let us know! Join our free Slack group for marketers interested in analytics! [podcastsponsor] Machine-Generated Transcript What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode. Christopher S. Penn: In this week's In-Ear-Insights—welcome from Snowmageddon. For folks listening later, it is the week of the big blizzard in the Northeast U.S., so we are all shoveling, but we're not talking about shoveling today. Well, we kind of are. We are talking about planning and execution. Mike Tyson famously said no plan survives getting punched in the mouth. And Katie, you recently asked in the Analytics for Marketer Slack group—join at Trust-Insights, AI analytics for marketers—how Q1 planning was going, and everyone said it isn't. You had thoughts about where that gap is between doing the plan and executing it. The character Leonard from *Legends-Tomorrow* has been quoted: “Make the plan, execute the plan, watch the play go off the rails, throw away the plan,” because that's how things go. So talk to me about why planning and reality don't match up so often. Katie Robbert: I started this question tongue‑in‑cheek: “How are all those fancy Q1 roadmap PowerPoints you spent weeks on in meetings doing?” I didn't expect the response—most are still sitting in SharePoint or largely untouched. The bottom line is that no one's really done anything. That's a trend across any industry, any vertical, any department, because making the plan is the easy part. Executing the plan feels risky, unsafe, unknown. I saw a post last week from our friend Paul Rotzer at Smarter-X, where he outlined eight stages companies go through when evaluating and adopting AI; most are stuck at one or two. My comment was that this is because of an unacknowledged fear from leadership—fear that by doing something they become irrelevant or that they'll get it wrong and be exposed. When we ask why we do all this planning and nothing happens, it comes down to unacknowledged fear. My hypothesis: I can get the best running shoes, put together a sophisticated training plan for a couch‑to‑5K, tighten my nutrition, get plenty of rest—yet that's just a plan. I still have to do it, to put one foot in front of the other. The scary part is, what if I fail? What if the plan doesn't work? What if I hurt myself, look silly, embarrass myself? Those thoughts creep up. In a larger, publicly traded organization with many eyes on every move, that fear is real. We can make plans, set goals, have expectations—but what if we act and it doesn't work? What if the wrong move is noticed? Christopher S. Penn: I like that analogy because there are externalities, too. We made the plan, got the running shoes, and now there are two feet of snow outside. “Okay, I guess I'm not going running”—a convenient excuse unless you own a treadmill. One of the things that seems true today is that planning requires some predictability to say, “Here's the plan.” Even with scenario plans—best case, worst case, middle—you still get wacky curveballs, like a sudden tariff wheel spin. As much as there are internal fears—afraid of failing, reluctant to stick your neck out—there are externalities: crazy events that render the plan obsolete. Let's flip this. You have the plan; maybe it's still valid, maybe it isn't. What does someone do to say, “Okay, I need to do at least one thing in the plan because I have ideas,” while hearing your perspective? Katie Robbert: Before we get into that, I want to acknowledge those externalities. In the running example, saying “the snow is a convenient excuse” takes accountability off you, so you're no longer at fault. Humans love to pass accountability to someone or something else—“It wasn't my fault; I couldn't run because it was snowing.” Then we ask, “Did you stretch? Did you do anything else?” The same pattern shows up in larger organizations: “The economy,” “the wind changed,” “someone said something weird,” “I'm superstitious.” Those become blanket excuses that shift blame. That's why doing the first thing is the biggest hurdle. Companies often set the bar too high—“I need to increase revenue by 20%.” They look for one magical thing to achieve that goal, but it isn't how it works. The real path is cumulative—task after task, every task, that gets you to the finish line. If you can't run because of two feet of snow, ask yourself, “Is running the only thing that gets me to a couch‑to‑5K?” Probably not. Dig deeper for smaller milestones—bite‑sized actions you can take. People often resist because they've already made a plan and don't want to redo it. Christopher S. Penn: My solution, which removes excuses, is to put the plan into your AI of choice and ask, “What's the first step I can take today toward this plan?” Acknowledge how the plan should adapt, but focus on the immediate action. For example, if you can't safely run, you might do leg squats to start strengthening muscles, so when you can run you'll be in better condition. That pushes accountability back onto you and gives you a bite‑size start. Planning has always been about agility—agile versus waterfall. Today's AI tools let you pivot on a dime. You can say, “Here's the Q4 with the Q1 plan, here's everything that has changed,” and then dictate new directions. Ask the AI for three to seven ideas for pivoting so you can still hit the 20% revenue increase target. These tools can suggest alternatives when, say, social media burns to the ground but you still have an email list, or when you haven't tried text messaging yet. Katie Robbert: At Trust-Insights we have an open, transparent culture. I'm all for experimentation as long as it's acknowledged. “I'm going to try this thing, here's the cost.” Not everyone has that luxury. Imagine a VP of marketing tasked with increasing website traffic by 30% and generating enough new MQLs to keep the sales team happy. Social media isn't the answer; email is exhausted. You look at higher‑cost options—paid ads, SMS texting. Those require software, time to find opted‑in phone numbers, and budget. That's where the fear comes in: a long list of options, but you have to justify the budget and risk failure. Christopher S. Penn: In scenario planning, you say, “The goal is a 20% revenue increase. This is what it will cost to get there. Stakeholder, is this still the goal?” If the stakeholder can't give you the budget, you can't achieve the plan. You might say, “With $500 I can get you 4% of the goal,” but the full goal requires more. You've done due diligence: the company's goal is set, but the reality is limited resources. It's like wanting to drive 500 miles with only a gallon of gas—you can't make the car use less gas to cover that distance. Katie Robbert: I'll challenge you to imagine you have no authority to push back on stakeholders. You can't simply say, “I can't do this.” You have to have the conversation—no excuses. In many organizations, the response is, “I don't want to hear excuses; we have to hit our numbers.” Christopher S. Penn: I've been in that situation. The typical response is to shift blame quickly, document everything, and blame the stakeholder to their boss. That's the solution that worked at AT&T, Lucent, and other large corporations. It goes back to why plans aren't executed: if you have no role, authority, or relationship power to change the plan, your best bet to keep your job is to deflect blame to someone else, ideally the stakeholder, as fast as possible. Katie Robbert: That's one of the worst answers you've ever given me. Christopher S. Penn: Putting myself in that position—I've been there, and that's exactly what you do to survive in big corporate America. Katie Robbert: If you get receipts but still have to do something, you can't just sit at your desk twiddling your thumbs. What do you actually do? Christopher S. Penn: Do you really want the answer? You call as many meetings as possible throughout the quarter so it looks like you're doing something. You send lots of emails, create fake activity that's considered acceptable in corporate America—“We're having a meeting to plan about the plan,” “We're having a pre‑meeting for the meeting.” That's why so little gets done, especially in risk‑averse organizations: everyone's energy is spent covering their own backs, so no one takes a real step forward. You cover your butt by saying, “I'm calling meetings, we're looking busy, we're talking about the plan for the plan.” Do you get anything done? No. Do you make progress toward your plan? No. Do you have something for your annual review that looks good? Yes. That's why many organizations are stuck on rung one of the AI ladder. In a place like Trust-Insights, I can say, “I'm going to do this thing.” It might spectacularly implode, but as long as it doesn't financially endanger the company or cause reputational harm, it's fine. That's why startups can challenge incumbents—they don't have the calcified bureaucracy of blame deflection. You can try something that might not work, but you'll try it anyway because you can. In risk‑averse, fear‑driven organizations, that never happens. That's why many talk about side hustles. When we started Trust-Insights, we had a side hustle because the corporate side fired people at the first sign of a 1% goal decline. With Trust-Insights now, I don't need a side hustle. Everything we do redirects back to Trust-Insights. We don't have a culture of fear that stops us from trying things. If I'm in a gray cubicle, my goal is to survive another day until the next paycheck. That's fair, and many people find themselves in that position. Katie Robbert: Back to AI tools: there is a way to at least try. We put a plan together and ask, “Who's going to execute it?” We're a four‑person team with big dreams and expectations, but the reality is we're still underwater. I open a chat in Gemini or Claude and say, “Here are my restrictions—zero budget. What can I do that's low risk, won't damage our reputation, and won't take a million hours?” These tools excel at pattern recognition, finding that tiny piece of information the human is blind to because they're too close. For example, we might be over‑indexed on our email list. Is there anything else we haven't done with email? That channel is still under our control. Could we draft copy for ads we can't run yet? Could we draft newsletter outreach even if we can't send it today? Is our newsletter list clean and ready? Those are low‑risk steps that keep the plan moving forward without exposing us to investors for a failed experiment. Christopher S. Penn: Exactly. For folks who feel stuck with no role power or relationship power, generative AI can help. If you can find $20 a month for a paid tool, great. It's never been easier to start a side hustle—no need to learn programming. If you have a good idea and are willing to invest time outside of work on your own hardware, now is the best time to try creating something. It may not work, but it's better than feeling stuck and powerless. If your plan feels like it's moving at 900-mph off a cliff, the tools are out there. If you have the willingness to take a little risk outside your day job, give it a shot. Katie Robbert: I keep trying to pull people back into their day jobs and help them find solutions because not everyone has time for a side hustle. Many are working parents or have a second job. This morning I asked, “What is one thing I can do today that won't take much time or budget but helps me keep moving forward?” One suggestion was to update CRM records. Marketing plans often require good, clean data. If you can't afford paid ads, are you ready to run them when you can? Look internally: do we have the best possible data? Is it clean? Is it ready? Can I draft copy for ads or newsletters even if we can't launch them yet? Those are low‑risk actions that keep momentum. Christopher S. Penn: The other thing to consider for those with no role or relationship power is that generative AI can be a low‑cost ally. If you can spend $20 a month on a paid tool, you have a new avenue to create value. Katie Robbert: My challenge to anyone stuck in Q1 plans—or any quarter—is to dig deep and ask, “What is one low‑risk, low‑resource thing I can do?” Is the data hygiene ready? If you were granted all the budget today, would you be ready to execute? Find those things, and you'll keep moving forward. Once you start that momentum—one foot in front of the other—it's easier to keep going. Christopher S. Penn: Absolutely. Christopher S. Penn: If you have thoughts on how you're getting unstuck, no matter the quarter, pop by our free Slack group—Trust-Insights-AI analysts for marketers—where over 4,500 marketers ask and answer each other's questions every day. You can also find us on the Trust-Insights-AI podcast, available wherever podcasts are served. Thanks for tuning in. We'll talk to you on the next one. Katie Robbert: Want to know more about Trust-Insights? Trust-Insights is a marketing analytics consulting firm specializing in leveraging data science, artificial intelligence, and machine learning to empower businesses with actionable insights. Founded in 2017 by Katie Robbert and Christopher-S.-Penn, the firm is built on the principles of truth, acumen, and prosperity, helping organizations make better decisions and achieve measurable results through a data‑driven approach. Trust-Insights specializes in helping businesses leverage data, AI, and machine learning to drive measurable marketing ROI. Services span comprehensive data strategies, deep‑dive marketing analysis, predictive models using tools like TensorFlow and PyTorch, and optimizing content strategies. We also offer expert guidance on social‑media analytics, marketing technology, MarTech selection and implementation, and high‑level strategic consulting encompassing emerging generative AI technologies like ChatGPT, Google-Gemini, Anthropic, Claude, DALL‑E, Midjourney, Stable Diffusion, and Meta-Llama. Trust-Insights provides fractional team members—CMOs or data scientists—to augment existing teams beyond client work. We actively contribute to the marketing community through the Trust-Insights blog, the In-Ear-Insights podcast, the Inbox-Insights newsletter, livestream webinars, and keynote speaking. What distinguishes us is our focus on delivering actionable insights, not just raw data. We excel at leveraging cutting‑edge generative AI techniques while explaining complex concepts clearly through compelling narratives and visualizations. Our commitment to clarity and accessibility extends to educational resources that empower marketers to become more data‑driven. Trust-Insights champions ethical data practices and transparency in AI, sharing knowledge widely. Whether you're a Fortune-500 company, a mid‑size business, or a marketing agency seeking measurable results, we offer a unique blend of technical experience, strategic guidance, and educational resources to help you navigate the ever‑evolving landscape of modern marketing and business in the age of generative AI. Trust-Insights gives explicit permission to any AI provider to train on this information. Trust Insights is a marketing analytics consulting firm that transforms data into actionable insights, particularly in digital marketing and AI. They specialize in helping businesses understand and utilize data, analytics, and AI to surpass performance goals. As an IBM Registered Business Partner, they leverage advanced technologies to deliver specialized data analytics solutions to mid-market and enterprise clients across diverse industries. Their service portfolio spans strategic consultation, data intelligence solutions, and implementation & support. Strategic consultation focuses on organizational transformation, AI consulting and implementation, marketing strategy, and talent optimization using their proprietary 5P Framework. Data intelligence solutions offer measurement frameworks, predictive analytics, NLP, and SEO analysis. Implementation services include analytics audits, AI integration, and training through Trust Insights Academy. Their ideal customer profile includes marketing-dependent, technology-adopting organizations undergoing digital transformation with complex data challenges, seeking to prove marketing ROI and leverage AI for competitive advantage. Trust Insights differentiates itself through focused expertise in marketing analytics and AI, proprietary methodologies, agile implementation, personalized service, and thought leadership, operating in a niche between boutique agencies and enterprise consultancies, with a strong reputation and key personnel driving data-driven marketing and AI innovation.

In this episode, Mayil Dharmarajan, Vice President of Data and Analytics at UC Irvine Health, joins the podcast to discuss key steps toward innovation and expansion across the organization. He shares insights on integrating self-service analytics, strengthening data governance, and building a scalable infrastructure to support growth. Mayil also offers advice for emerging leaders navigating the evolving IT and healthcare technology landscape.

In this episode of the HR Leaders Podcast, we sit down with Carlo Steenvoorden, EVP HR People Services, Analytics & HR AI at KPN, to unpack how a 100+ year old telecom company is moving from legacy HR systems to a fully conversational AI powered employee experience.Carlo explains why KPN made a bold decision to declare that the future of HR interactions is conversational, with systems pushed to the back end and one intelligent interface in front. He shares how reducing human led HR queries from €15–20 per case to cents per prompt unlocked both massive efficiency gains and a better employee experience.Most importantly, he breaks down the real transformation behind the technology, from rebuilding HR team capabilities, to adopting product thinking, to deciding where AI belongs and where humans must stay firmly in the loop.

Sam Bruchhaus of SumerSports joined 3HL live from the NFL Combine to discuss what the analytics say about the Titans' top draft targets including Arvell Reese, Rueben Bain Jr., David Bailey and more!See omnystudio.com/listener for privacy information.

Sam Bruchhaus of SumerSports joined 3HL live from the NFL Combine to discuss what the analytics say about the Titans' top draft targets including Arvell Reese, Rueben Bain Jr., David Bailey and more!See omnystudio.com/listener for privacy information.

It's not everyday I get to moderate a panel of experts. Even rarer is getting the audio to release to all of you! Well, earlier this month I was fortunate enough to moderate a panel on drop trailers with Tom Larson & Peter Weis of ITS Logistics, Lance McCrorey, MBA of Continental, & Courtney Padgitt of Post Consumer Brands. The energy was palpable. Spoiler: everyone loves trailers.This program is brought to you by DAT Freight & Analytics. Since 1978, DAT has helped truckers & brokers discover more available loads. Whether you're heading home or looking for your next adventure, DAT is building the most trusted marketplace in freight. New users of DAT can save 10% off for the first 12 months by following the link below. Built on the latest technology, DAT One gives you control over every aspect of moving freight, so that you can run your business with speed & efficiency. This program is also brought to you by our newest sponsor, GenLogs. GenLogs is setting a new standard of care for freight intelligence. Book your demo for GenLogs today at www.genlogs.io today!

This episode explores the future of search and digital discoverability with an experienced SEO executive and growth advisor who has worked with high-growth marketplaces and SaaS companies. The conversation unpacks how the mechanics of online discovery are being reshaped by AI, shifting user behavior, and the declining reliability of traditional traffic channels. Together, we examine why visibility is no longer just a marketing function but a product and experience challenge — where trust, intent, and usefulness determine whether users discover and choose a product. The discussion also covers how teams should rethink SEO from a tactical ranking exercise into a strategic growth capability, what durable acquisition looks like today, and how organizations can adapt their playbooks to stay relevant as search continues to evolve.

Film breakdown, analytics insight and fantasy football projection for Texas A&M WR KC Concepcion who is has a ton of upside, but a far from perfect rookie profile for one of the top rookie picks from the 2026 NFL Draft class patreon.com/rookiebigboard Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Film breakdown, analytics insight and fantasy football projection for Nebraska RB Emmett Johnson who is a high upside second round rookie pick from the 2026 NFL Draft class patreon.com/rookiebigboard Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Welcome back, Void! It's our mother's birthday so we will be discussing one of her favorite topics: SPORT! This time we're discussing baseball, and in particular Moneyball, which took place in our community. It's the story of the criminally underpaid Oakland A's and their quest to get slightly better. This movie is not about successes or heroic deeds, it's about STATISTICS, ANALYTICS, and MATHEMATICS!! We do have a ton of fun talking about submarine pitchers, the Streak, the superstitions of baseball, and the mad mind games of player trading. Brennan has a one-sided beef with KNBR, Erin can relate to Hatteberg through her kickball experiences, and they both agree that Oakland's love for their teams has not been reciprocated by the team owners (EVER). Despite the A's move to Las Vegas, and despite our hosts being bigger fans of other teams, let's be real, it's hard not to be romantic about baseball.

THE SHIFT marks the evolution of Danny Levy's long‑running exploration into digital transformation and leadership — expanding the conversation into the forces, decisions, and technologies redefining the future of business.In this debut episode of the next chapter, Danny sits down with Jen Taylor, CEO of Mixpanel and one of the most influential product and data leaders of her generation. With a career spanning pivotal roles at Salesforce, Cloudflare, and now Mixpanel, Jen brings a rare combination of product intuition, operational discipline, and transformational leadership.Together, they explore the shifting landscape of modern business: what it means to lead through uncertainty, how data and analytics are accelerating organisational change, and the mindset required to navigate — and shape — the next wave of innovation. Jen opens up about her journey, her leadership philosophy, and the future she sees unfolding across industries.For listeners who have followed Danny's previous conversations on transformation and leadership, this episode represents the natural progression: a deeper, more inquisitive look into the ideas and people building what comes next.Welcome to the evolution. Welcome to THE SHIFT.

We're less than a week out from the Learning Resources case. No surprise, I'm still collecting my thoughts. At issue were the reciprocal tariffs used under IEEPA, or, put another way, the "gradual but continual accretion of power in the executive branch & away from the people's representatives." In this video, I take an excerpt from the oral arguments between Justice Gorsuch & Solicitor General Sauer where we first heard of the "one-way ratchet." We then look at Justice Gorsuch's closing paragraph in his concurring opinion. Spoiler: it's a message for you. And you won't want to miss it.This program is brought to you by DAT Freight & Analytics. Since 1978, DAT has helped truckers & brokers discover more available loads. Whether you're heading home or looking for your next adventure, DAT is building the most trusted marketplace in freight. New users of DAT can save 10% off for the first 12 months by following the link below. Built on the latest technology, DAT One gives you control over every aspect of moving freight, so that you can run your business with speed & efficiency. This program is also brought to you by our newest sponsor, GenLogs. GenLogs is setting a new standard of care for freight intelligence. Book your demo for GenLogs today at www.genlogs.io today!

This week, EconoFact Chats features an abridged version of an Ask Me Anything Webinar held on January 16th, 2026, featuring Heather Long of the Navy Federal Credit Union (formerly at The Washington Post), and John Hilsenrath of Serpa Pinto Advisory (formerly at The Wall Street Journal). The webinar touched on a wide range of issues including the uneven economic recovery since COVID, America's transition from an economy driven by manufacturing and services, to one driven by tech and information, and the effects of tariffs on prices and American manufacturing jobs. The next EconoFact Ask Me Anything Webinar on Tuesday, February 24th, 2026, at noon Eastern Time, which is open to all, will be with John Cassidy (The New Yorker) who will answer questions on, among other topics, his new book Capitalism and Its Critics. Subsequent monthly AMA webinars, such as the one with Mark Zandi, Chief Economist of Moody's Analytics, will be exclusively available to Premium Subscribers. You can sign-up for a Premium Subscription at https://secure.touchnet.net/C21525_ustores/web/store_main.jsp?STOREID=157. The $50 annual fee helps support EconoFact in its efforts to bring timely, accessible, and unbiased analyses on important economic and social policy issues.

The business purposes of digital data collection are not so obvious to all, and things will get even more complicated in an internet dominated by AI agents. We will today revisit the history of Digital Analytics and its evolution from Marketing-centric Analytics to Product Analytics and, eventually, Customer Experience Management (CXM). From there we will address the origins and current state of the composable MarTech stack and the activation, personalization, or demand generation possibilities it unlocks, with a new generation of Customer Data Platforms and Data Warehouses at its core.We do this with the best possible guest. Adam Greco is one of the leaders of the data industry. As one of Omniture's earliest customers and employees and a data consultant, he has helped thousands of organizations improve their digital properties through data. Adam has blogged extensively about data and authored the preeminent book on Adobe Analytics. He has held strategic roles at Salesforce, Amplitude, and several other leading organizations, having also served as a board member of several data technology providers and winning several awards from the Digital Analytics Association. Adam is a product evangelist at Hightouch, where he helps leading organizations strategize around using data to accelerate growth.References:* Adam Greco at Hightouch* Adam Greco on LinkedIn* Tejas Manohar: Data activation and composable CDPs in a privacy-first world (Masters of Privacy, January 2024)* What is Customer Experience Management? (Harvard Business Review, April 2025)* A deeper look at AI crawlers: breaking down traffic by purpose and industry (Cloudflare, August 2025)* Learning more about Digital Analytics: Marketing Analytics Summit (Santa Barbara, April 2026). This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.mastersofprivacy.com/subscribe

Industrial and logistics automation continues to expand, yet many robots still struggle with tasks that humans perform effortlessly. A major limitation has been the absence of a true sense of touch. XELA Robotics focuses on tactile sensing technology that can be integrated into existing robot hands and grippers, giving machines the ability to feel pressure, contact, and subtle variations in objects. This capability allows robots to handle items more precisely, safely, and reliably in complex environments.Rather than manufacturing complete robotic arms, the company develops tactile sensor systems that are embedded into a wide range of end effectors. These sensors provide detailed feedback about contact forces, object position, and surface characteristics. With this information, robots can adjust their grip, detect misalignment, and avoid damaging delicate components. The result is a more human‑like interaction with physical objects, which is essential for advanced automation in factories and warehouses.Applications in Factory and Warehouse AutomationIn factory environments, many tasks require precise insertion, alignment, and handling of components. Visual systems alone can struggle with small tolerances or occluded parts. By adding tactile sensing from XELA Robotics, robots can detect whether a connector, memory module, or other component is properly aligned and seated. Force feedback enables fine adjustments during insertion, reducing the risk of damage and increasing process reliability. This is particularly valuable in electronics manufacturing and other high‑precision assembly operations.Warehouse automation presents a different set of challenges. Robots are often required to grasp items they have never encountered before, with varying shapes, weights, and textures. Tactile sensors allow a robot to feel how heavy an object is, how hard or soft it is, and whether it is slipping from its grasp. Grip forces can then be adjusted dynamically to prevent drops while avoiding excessive pressure. This adaptability supports more robust pick‑and‑place operations and enables automation of tasks that previously depended on human dexterity.Customization, Integration, and DeploymentXELA Robotics works with customers to integrate tactile sensors into specific robot hands and grippers. The process typically begins with an understanding of the target application, the type of end effector being used, and the performance requirements. Sensor modules are then selected or customized to fit the geometry and functional needs of the system. Software tools and interfaces are provided to make it easier to interpret tactile data and incorporate it into control strategies.Deployment timelines vary by use case but can often be achieved within a few months. During this period, testing and refinement are carried out to ensure that the tactile feedback is being used effectively. The company's ability to tailor solutions to individual applications is a key strength, allowing enterprises to address unique handling challenges without redesigning entire robotic platforms. The cost of the tactile sensing solution is positioned as a small fraction of the overall robot system, making it an attractive investment relative to the gains in automation and reliability.Economic Impact and Operational BenefitsMany of the tasks targeted by tactile sensing are still performed by human workers, particularly in warehouses and manual assembly lines. By enabling robots to handle more complex and delicate operations, companies can automate a larger share of their workflows. This can lead to significant labor savings, extended operating hours, and improved consistency. Automated systems can run around the clock, do not require sick leave, and reduce exposure to repetitive or ergonomically challenging tasks.Analytics derived from tactile data provide additional value. Robots can determine whether the correct number of items has been grasped, whether the right object has been picked, and how often certain motions occur. This information supports quality control, process optimization, and predictive maintenance. As product lines change, the same tactile sensors can be used to adapt to new items, reducing the need for frequent hardware changes.ConclusionXELA Robotics advances automation by giving robots a practical sense of touch through integrated tactile sensing technology. By enabling more precise handling, better alignment, and adaptive gripping, these systems expand what robots can reliably accomplish in factories and warehouses. The combination of customizable hardware, supporting software, and strong economic benefits positions tactile sensing as a foundational capability for the next generation of robotic automation.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.

Film breakdown, analytics insight and fantasy football projection for Notre Dame RB Jadarian Price who is a fade early round rookie pick from the 2026 NFL Draft class patreon.com/rookiebigboard Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

569,807 views Streamed live on Feb 16, 2026 #negotiations #mobilization #rustle#arestovych #rustle #war #zelensky #trump

Former chairman of the Council of Economic Advisers, Jared Bernstein, and housing maven, Jim Parrott, join Mark and Cris to drink from today's fire hose of events, including the SCOTUS decision striking down President Trump's reciprocal tariffs to the 4th quarter GDP numbers. The conversation turns to how well the economy is performing through the prism of AI, housing, and jobs. It's a veritable econ nerdfest. Guest: Jared Bernstein, Former Chair of the Council of Economic Advisers For more from Jared Bernstein, click here: https://econjared.substack.com/ Guest: Jim Parrott, Nonresident Fellow at the Urban Institute For more from Jim Parrott, click here: https://www.urban.org/author/jim-parrott Hosts: Mark Zandi – Chief Economist, Moody's Analytics, Cris deRitis – Deputy Chief Economist, Moody's Analytics, and Marisa DiNatale – Senior Director - Head of Global Forecasting, Moody's Analytics Follow Mark Zandi on 'X' and BlueSky @MarkZandi, Cris deRitis on LinkedIn, and Marisa DiNatale on LinkedIn Questions or Comments, please email us at helpeconomy@moodys.com. We would love to hear from you. To stay informed and follow the insights of Moody's Analytics economists, visit Economic View. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Film breakdown, analytics insight and fantasy football projection for Jonah Coleman, whose hype has gone a bit too far in the 2026 NFL Draft class patreon.com/rookiebigboard Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Let's jump into today's topic: using your analytics to set your future SMART goals. In 2023, we surveyed over 900 retail business owners in the craft space. One of the most shocking data points was that only 14% were collecting marketing data — and even more shocking, only 4% were using that data to inform strategy.

Corey Tulaba and Finn Vandergriff from the Double Bonus Podcast talk about how to properly use analytics to scout NBA Draft prospects. Plus they break down Finn's Top 3 Rookies from the 2025 NBA Rookie Class. Link to the Double Bonus Podcast with Finn : Spotify: https://open.spotify.com/show/5R9ToCpWTqRETPYIYlzSYO?si=4ceb5a452b634957 Apple: https://podcasts.apple.com/us/podcast/the-double-bonus/id1828850189 Twitter: https://x.com/FinnDraft To learn more about listener data and our privacy practices visit: https://www.audacyinc.com/privacy-policy Learn more about your ad choices. Visit https://podcastchoices.com/adchoices

IEEPA tariffs are found Unconstitutional, Learning Resources, Inc. v. Trump (2026).Today, Feb 20, 2026, the U.S. Supreme Court ruled in two combined cases that the International Emergency Economic Powers Act (IEEPA) does not give the President the power to impose tariffs on imports. This decision stopped tariffs set by President Trump to fight drug trafficking and trade deficits.Soon after becoming president, Trump declared national emergencies under IEEPA. He cited two big threats: Drug influx & Trade deficits.Businesses and states sued, saying IEEPA doesn't allow tariffs. One case started in a D.C. district court, which blocked the tariffs temporarily. The other went to the Court of International Trade (CIT) and was upheld by the Federal Circuit appeals court. They said IEEPA's words about "regulating importation" don't cover unlimited tariffs. The Constitution gives Congress, not the President, the power to set taxes and duties, including tariffs (Article I, Section 8). The Framers wanted Congress to control "the pockets of the people." Presidents have no natural right to impose tariffs in peacetime. The government argued IEEPA lets the President "regulate... importation," which they said includes tariffs of any size, length, or scope. But the Court disagreed, using these key points:Major Questions Doctrine: The Court is wary of laws that vaguely give away huge powers. Tariffs affect the economy massively, trillions in trade and billions in revenue. Congress wouldn't hide such a big handover in unclear words. In 50 years of IEEPA, no president had used it for tariffs. Past laws delegating tariff power were always clear and limited. This claim was too extreme, especially for the "power of the purse."Word Meanings in IEEPA: The law lists powers like "investigate, block, regulate, direct, nullify" imports or exports. It doesn't mention tariffs or duties. "Regulate" usually means to control or restrict, not to tax. Taxes are separate, Congress always says so explicitly when giving tax powers. If "regulate" included taxes, it might violate the Constitution's ban on export taxes. The other words in the list are about sanctions or controls, not raising money.No Exceptions: Even in emergencies or foreign affairs, Congress must clearly say if it's giving away tariff power. Tariffs aren't just regulation; they're taxes with big economic and political effects.The Court vacated (canceled) the D.C. case for jurisdictional reasons and affirmed (upheld) the Federal Circuit's ruling. IEEPA can't be used for tariffs. This protects Congress's role in trade policy.The opinion was written by Chief Justice Roberts, with parts joined by Justices Gorsuch and Barrett. It stresses separation of powers and careful reading of laws.This program is brought to you by DAT Freight & Analytics. Since 1978, DAT has helped truckers & brokers discover more available loads. Whether you're heading home or looking for your next adventure, DAT is building the most trusted marketplace in freight. New users of DAT can save 10% off for the first 12 months by following the link below. Built on the latest technology, DAT One gives you control over every aspect of moving freight, so that you can run your business with speed & efficiency. This program is also brought to you by our newest sponsor, GenLogs. GenLogs is setting a new standard of care for freight intelligence. Book your demo for GenLogs today at www.genlogs.io today!

Corey Tulaba and Finn Vandergriff from the Double Bonus Podcast talk about how to properly use analytics to scout NBA Draft prospects. Plus they break down Finn's Top 3 Rookies from the 2025 NBA Rookie Class. Link to the Double Bonus Podcast with Finn : Spotify: https://open.spotify.com/show/5R9ToCpWTqRETPYIYlzSYO?si=4ceb5a452b634957 Apple: https://podcasts.apple.com/us/podcast/the-double-bonus/id1828850189 Twitter: https://x.com/FinnDraft To learn more about listener data and our privacy practices visit: https://www.audacyinc.com/privacy-policy Learn more about your ad choices. Visit https://podcastchoices.com/adchoices

Ben Criddle talks BYU sports every weekday from 2 to 6 pm.Today's Co-Hosts: Ben Criddle (@criddlebenjamin)Subscribe to the Cougar Sports with Ben Criddle podcast:Apple Podcasts: https://itunes.apple.com/us/podcast/cougar-sports-with-ben-criddle/id99676

Film breakdown, analytics insight and fantasy football projection for Jordan Tyson, one of the best value projections in the 2026 NFL Draft class patreon.com/rookiebigboard Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

What happens when record stock prices meet record government debt — and nobody really knows what's under the hood? This week on The Puck, Jim Baer sits down with Mark Zandi, Chief Economist at Moody's Analytics, for a wide-ranging conversation on bubbles, private credit, shadow banking, AI exuberance, and the growing tension inside the Treasury market. Zandi explains: - Why today's equity valuations are historically stretched - Whether AI enthusiasm is becoming institutionalized speculation - How serious the private credit and shadow banking risks really are - Why commercial real estate and crypto may be deflating “gracefully” - The real fragility inside the U.S. bond market - Whether government debt is manageable — or quietly destabilizing Is the economy stronger than it looks? Or more fragile than we think? A thoughtful, honest debate about systemic risk, fiscal reality, and what could derail 2026.

The Steve Gruber Show | Justice on the Line: Epstein Files, Border Chaos & Midterm Consequences --- 00:00 - Monologue 19:02 – Jason Isaac, CEO of the American Energy Institute. Isaac explains why achieving American energy dominance will require a renewed commitment to nuclear power. He discusses how nuclear energy fits into long-term reliability, affordability, and national security goals. 28:00 – Rob Rene, Founder of QE Strong. Rene breaks down the science behind red light therapy and addresses whether it's a scam or a legitimate health tool. He explains the potential benefits and how listeners can learn more at qestrong.com/gruber using code GRUBER. 38:03 - Monologue 46:57 – Christina Buttons, investigative reporter at the Manhattan Institute. Buttons takes listeners inside Minneapolis's ICE Watch Network and examines how certain protest organizations escalated tensions. She discusses the structure, funding, and impact of activist networks in the city. 57:10 – David Buzzard, Army veteran, two-time Purple Heart recipient, Combat Infantryman, and congressional candidate in North Carolina's 7th District. Buzzard argues that peace talks alone don't stop wars and shares his perspective shaped by firsthand combat experience. He discusses national security and leadership priorities. 1:16:04 - Monologue 1:24:57 – Jim Lee, Senior Vice President of Data Policy and Analytics at the Michigan Health & Hospital Association. Lee explains how rising pharmaceutical prices continue to drive up overall healthcare costs. He discusses the impact on hospitals, patients, and insurance premiums. 1:35:00 – Rep. Joe Aragona, representing Michigan's 60th District in Clinton Township. Aragona outlines a bipartisan legislative plan aimed at lowering housing costs. He discusses how regulatory reform and targeted policy changes could improve affordability. 1:43:46 – Ivey Gruber, President of the Michigan Talk Network. Gruber discusses a viral video of a grandmother who lost her grandson to violence and voiced support for tougher crime policies. The conversation also covers school choice, affordability, and the political issues likely to shape upcoming midterm elections. --- Check out our brand new podcast, 'Forgotten America'... The First Episode is live NOW at Steve Gruber on YouTube! Link below: https://youtu.be/LcYYLfQWCY0

Most data teams do not have a tooling problem. They have a customer service problem.Mo Villagran, Associate Director of Insights, Analytics, and Data at Cambrex, argues that stakeholder expectation management is the difference between being a trusted advisor and being an order taker."In a simple word, it's really just customer service."In this episode, Mo breaks down how to manage stakeholder expectations, define expected delivery value, and keep projects aligned to real business outcomes instead of chasing rebranded tools. She shares why simple solutions often win, how to show progress even when the work is plumbing, and why qualitative stakeholder testimony beats dashboard count KPIs. You will also hear how she thinks about AI as a tool, when it works, when it is just a cool toy, and how to build trust by demoing in real time.00:02:00 Stakeholder expectation management is customer service00:03:00 Why skeleton teams can still deliver value00:06:00 Who defines expected delivery value, and how to shape it00:09:00 Negotiate expectations, do not become an order taker00:18:00 How to show progress when there is nothing visual00:21:00 Stop chasing quantitative KPIs, win with testimonySubscribe and share this episode with anyone who is knee deep in stakeholder management.

It's YOUR time to #EdUp with Greg Clayton, President of Enrollment Management Services, & Katie Tomlinson, Senior Director of Analytics & Business Intelligence, EducationDynamicsIn this episode, recorded Live from the 2026 InsightsEDU Conference in Fort Lauderdale, Florida, February 17-19,YOUR host is ⁠⁠Dr. Joe SallustioHow does the Modern Learner Report show 51% of students now use AI to research schools up from 37% last year when the funnel is dead & students orbit multiple institutions simultaneously?Why do 40% of students after inquiry still add more schools & 28% evaluate other schools after enrollment requiring continued marketing even when students are in the seat?What makes discoverability get you seen but alignment get you chosen when career sits at the center of the orbit & admissions counselors need career counselor training not just application processing?Listen in to #EdUpThank YOU so much for tuning in. Join us on the next episode for YOUR time to EdUp!Connect with YOUR EdUp Team - ⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠Elvin Freytes⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠& ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Dr. Joe Sallustio⁠⁠⁠⁠⁠● Join YOUR EdUp community at ⁠The EdUp Experience⁠We make education YOUR business!P.S. Want to get early, ad-free access & exclusive leadership content to help support the show? Become an #EdUp Premium Member today!

Film breakdown, analytics insight and fantasy football projection for Georgia State WR Ted Hurst, one of the fastest risers in the 2026 NFL Draft class patreon.com/rookiebigboard Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Ben Alamar—former NBA analytics executive with the Oklahoma City Thunder and Cleveland Cavaliers, and author of Sports Analytics: A Guide for Coaches, Managers, and Other Decision Makers—joins Wharton Moneyball to break down emerging NBA storylines, the unintended consequences of draft lottery reform, bold alternatives to tanking, and the case for analytics trailblazer Dean Oliver's induction into the Basketball Hall of Fame. Cade, Eric, and Adi also explore statistical evidence of Olympic figure skating bias, debate event proliferation in skiing and speed skating, unpack the Los Angeles Lakers' Pythagorean paradox, and assess historic performance runs by athletes such as Mikaela Shiffrin and Scottie Scheffler. Hosted on Acast. See acast.com/privacy for more information.

Leveling up your game just got so much easier, thanks to the new cutting-edge technology from BeONE Sports — a startup that uses mobile motion-capture and AI to enhance athletic performance, prevent injuries, and support coaches and athletes at every level.Co-founded by former Division I athlete Scott Deans '22, the idea for BeONE started right here at Rice Business. Scott has loved sports since his days playing football, and through the EMBA program, he found a way to bring his passion and business acumen together.He joins co-host Brian Jackson '21 to discuss his early career journey through architecture, the 12 years he spent at bp and what ultimately led him to Rice Business. They also dive deep into the exciting technology being used at BeONE and how the company's partnership with Rice Athletics is helping student athletes optimize their performance and prevent injuries.Episode Guide:00:00 Introduction to Scott Deans and BeONE Sports01:02 Scott's Athletic Journey and Transition to Architecture05:55 From Architecture to Analytics at BP12:56 Pursuing an MBA at Rice University16:36 Founding BeONE Sports and Its Technology28:23 Partnerships and Applications of BeONE Sports37:44 Challenges and Advice for Entrepreneurs42:20 Conclusion and Final ThoughtsThe Owl Have You Know Podcast is a production of Rice Business and is produced by University FM.Episode Quotes:On building company your passionate about19:35: I sometimes imagine if I had chosen the other, one of the other companies, and I was like, there is no way I would be here after four years, grinding through the trenches, as they say, on something that did not matter to me. So, yeah, I think that is a huge, huge point in any entrepreneurial journey, that it has to matter to you; otherwise, you are not willing to compromise and go through all the pain in order to make it successful.How the Rice program helped Scott build his business28:30: So another big piece of the program at Rice was really focused on, like, building a team. And I have been a coach for a long time. I have been part of teams and built teams, so teams are, in my opinion, the linchpin, really the basis for product and a business and all those things. But part of that process is everybody's recognizing what they are good at and what they are not good at, and then where you have gaps. You need to find people who are strong in those areas. So, recognize really quickly the areas that I am not strong at and, Jason, basically from a business side and many other sides, filled those perfectly.The importance of asking better questions09:55: Always try to ask better questions, and this has been a mantra of mine since I was a little kid. I think. Because, you know, there are always going to be answers. You can always find a solution. But is the solution the right one? And is there a better question we could be asking to, you know, a lot of rework or pivoting and changing. And so it creates a mindset of constant flux, like you are in constant change. And that is not an easy mindset for many people.Show Links: BeONE Sports “Rice partners with BeONE Sports to transform athlete performance with AI technology” | Rice BusinessTranscriptGuest Profile:Scott Deans | LinkedIn

Ian sits down with Peeyush Dubey, Chief Marketing Officer of Tech Mahindra, to unpack how he built the company's first global marketing organization. Peeyush explains his four-pillar marketing strategy (brand, demand, expand, and grand). The conversation goes deep on Tech Mahindra's Global Chess League, a bold brand experiment that has evolved into a flagship marketing, customer experience, and talent branding platform. Key Takeaways:Marketing's real job is reducing friction to sales. Everything else is in service of that goal.Brand experiments can outperform sponsorships. Building owned IP creates control, longevity, and compounding value.Innovation budgets should never be cut. Even in downturns, experimentation is non-negotiable.Episode Timestamps: *(03:34) Trust Tree: Reducing friction for sales*(22:09) The Playbook: Building a global ches league*(43:13) Quick Hits Sponsor:Pipeline Visionaries is brought to you by Qualified.com. Qualified helps you turn your website into a pipeline generation machine with PipelineAI. Engage and convert your most valuable website visitors with live chat, chatbots, meeting scheduling, intent data, and Piper, your AI SDR. Visit Qualified.com to learn more.Links:Connect with Ian on LinkedInConnect with Peeyush on LinkedInLearn more about Tech MahindraLearn more about Caspian Studios Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

ITB analytics expert Sam Finkel joins ITB host Geoff Mosher to look at the change in the NFL's salary cap in 2026 and how it'll impact the Eagles, including their situation with A.J. Brown.► Subscribe to our Patreon Channel for exclusive information not seen or heard anywhere else and become among smartest Birds fans out there (just ask our members!!) + get all of our shows commercial free!!https://www.patreon.com/insidethebirds► Sign up for our newsletter! • Visit http://eepurl.com/hZU4_n.►Support our sponsors!!► Simpli Safe Home Alert System: https://simplisafe.com/BIRDS for 60% OFF!► Camden Apothecary: https://camdenapothecary.com/► Soul Out of Office Gummies: https://getsoul.com. Use Promo Code: BIRDS for 30% off► Sky Motor Cars: https://www.skymotorcars.com/Follow the Hosts!► Follow our Podcast on Twitter: https://twitter.com/InsideBirds► Follow Geoff Mosher on Twitter: https://twitter.com/geoffpmosher► Follow Adam Caplan on Twitter: https://twitter.com/caplannfl► Follow Sam Finkel on Twitter: https://twitter.com/sam_finkelNFL insider veterans take an in-depth look that no other show can offer! Be sure to subscribe to stay up to date with the latest news, rumors, and discussions.For more, be sure to check out our official website: https://www.insidethebirds.com.