Podcasts about Gabby

In this week's episode, David and Gabby help a girl trying not to think about her ex on Valentine's Day, a 60 year old wanting to know if she should go for it and sleep with someone on the first date, and a listener who lied about having a partner to get a job! The advice is rolling in so profoundly that the slogan of the podcast is changing to "let us help you"!  To submit a question to David & Gabby email: letmeaskmydadpod@gmail.com Follow Gabby & David:  Let Me Ask My Dad on Instagram: @letmeaskmydadpod Let Me Ask My Dad on TikTok: @letmeaskmydadpod  David Bryan on Instagram: @davidbryanmusic Gabby Bryan on Instagram: @gabbyisbryan Gabby Bryan on TikTok: @gabbyisbryan Let Me Ask My Dad is produced by Lizzie Stewart in partnership with W!zard Radio Learn more about your ad choices. Visit megaphone.fm/adchoices

Gabby Mark was born with a port wine stain birthmark on her face, and for years, she thought it was a curse. As a little girl, she carried the weight of other kids’ fear. They thought they could catch something from her. She learned to shrink herself to make others comfortable. But she chose a different story. During COVID, she connected over Zoom with other young people who shared her birthmark. What once felt isolating became empowering. Together, they realized they weren’t different in a bad way, they were rare in a beautiful way. Now at 21, Gabby walks into a room knowing she was made this way on purpose. Not as something to hide, but as something that sets her apart. She channels her healing through her music trio, The 223, and brings that same confidence and grit to her work as my content creator and intern. I’m blown away by her belief in herself and dedication to what set her soul on fire. She didn’t erase her mark. She became it. ✨See omnystudio.com/listener for privacy information.

This week the honks read listener submitted secrets. Gabby's ex has a friend who writes in about her threesome, being 22, projecting insecurities in relationships, open relationships, Lee's nicknames, coming out and how to navigate it, stealing groceries and being a single mother, a Chinese brother, a mental hospital and so much more! Enjoy!  If you love the show and want to support us, join our growing community on Patreon to see what we're giving for $5 a month! JOIN OUR PATREON https://www.patreon.com/teatime42069 Send your stories to TeaTimeStories42069@gmail.com Tickets to Harper-Rose's Hour Taping on Feb 27th: https://www.eventbrite.com/e/adult-baby-doll-spesh-special-taping-tickets-1982521791045?aff=oddtdtcreator&utm_source=ig&utm_medium=social&utm_content=link_in_bio&fbclid=PAdGRleAP2nvJleHRuA2FlbQIxMQBzcnRjBmFwcF9pZA8xMjQwMjQ1NzQyODc0MTQAAaegzUATREHKWOIp9epGFriR8Eg06DbXfJNAWW9rBibx_Z567ak5RzEXyGEGaA_aem_HV1V-AesBvxSf7go0S710A Watch Gabby Lamb's set here: https://www.youtube.com/watch?v=J7oOYWgK598

Dave & Cody recap Shrinking Season 3, Episode 3 (“D-Day”), an episode built around uncertainty, vulnerability, and people realizing they're not as ready as they thought.They talk through Jimmy's complicated relationship with his dad, Brian and Charlie's early delivery and adoption paperwork scare. They also dig into Sean's awkward reunion with Marisol, Gabby working to rebuild trust with a former client, and why Liz continues to be both overwhelming and strangely essential.The emotional center of the episode, though, belongs to Dr. Paul. As his Parkinson's limits his ability to work, Paul makes the difficult decision to step back from mentoring Alice...forcing him to confront who he is without his profession.Dave and Cody close by unpacking Bon Iver's “Speyside,” why it fits the episode's themes of repair and regret, and why Paul holding the newborn might be one of Harrison Ford's strongest moments of the series.https://linktr.ee/PopCulturePastorPod

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Do you keep getting stuck in the same fights or feeling rejected in your relationship? In this episode of The Wise Effort Show, Dr. Diana Hill shares an evidence-based talk on the science of “wise and fierce” relationships, then follows with a conversation with athlete and entrepreneur Gabby Reece about what helps partnerships last.Diana draws on relationship research and her clinical experience to explain why conflict isn't the main problem—repair is—and on what predicts relationship satisfaction: commitment, appreciation, responsiveness, and sexual satisfaction. She also discusses research on sexual frequency and how motivation matters more than frequency (“getting it on” vs. “getting it over with”).Diana offers a practical exercise to help listeners “put down the broom” of rigid stories: write your story about your partner and their story about you, identify the “negative truth,” then (1) create disconfirming evidence by noticing what contradicts your story about them, and (2) do something that proves their story about you wrong. In the conversation, Gabby describes how respect, emotional honesty, daily connection rituals, and sustaining momentum—along with supporting each partner's individual passions—strengthen her decades-long marriage to Laird, and they discuss reframing intimacy bids and avoiding complacency.Listen and share this episode with someone you want to strengthen a relationship with.Listen and learn:Why repair after disharmony matters more than avoiding conflictThe key relationship ingredients identified across 43 studies: commitment, appreciation, responsiveness, and sexual satisfactionWhat the research suggests about sex frequency and why “getting it on” vs. “getting it over with” changes satisfactionRelated ResourcesGet enhanced show notes for this episodeOrder my book, Wise Effort: How to Focus Your Genius Energy on What Matters Most, and receive special bonus gifts.Want to become more psychologically flexible? Take Diana's "Foundations of ACT" course.Diana's EventsReserve your spot in Diana's Costa Rica retreat in 2026!See Diana at an upcoming eventConnecting With DianaSubscribe for free on Apple Podcasts and Spotify.Leave a 5-star review on Apple so people like you can find the show.Sign up for the free Wise Effort Newsletter.

But we still have THE GRAND PRIZE WINNER NEXT WEEK! Today on the Show, Blake is PISSED but have no fear we are the modern day springer. Lay it on us for all to hear. Then, Gabby messaged us that she needed an Emergency WAR OF THE ROSES on a FRIDAY so we took the case but then she pitched something else entirely. What a MESS. Also, it's the LOVE SHOW today! WE GOT TO AS MUCH VALENTINES DAY STUFF AS WE COULD! We hope you have an amazing weekend! SEND US ALL YOUR ROMANTIC STORIES GOOD AND BAD and we will tackle them back here TUESDAY MORNING! (Monday is Presidents Day)See omnystudio.com/listener for privacy information.

The world of a blissfully detached woman turns upside down when she's forced to adjust to the ordinary life that exists beyond working at an off-the-wall lesbian bar, and its rivalry with the gay club across the street. https://instagram.com/theboxtrapmovie What motivated you to make this film? Inside jokes between me and my friend Gabby, unfortunate life experiences and the uncontrollable urge I felt to make a feature-length film. From the idea to the finished product, how long did it take for you to make this film? The idea was developed in 2023 and I started writing it as a dramedy, which I don't know why I did because I hate dramedies, and I ended up rewriting it a bunch of times throughout that whole year until it became what it did. We shot it in 2024 and it took me around 10 months to edit the whole thing. So, roughly 2 and a half to three years. How would you describe your film in two words!? Chicken wings. What was the biggest obstacle you faced in completing this film? I think I had many obstacles that felt like the end of the world at the time but seem so small when I look back at them now. The main obstacles are typically the same in every set: actors or crew calling out last minute, technical difficulties, unlucky weather and having to stay on schedule through all of it. We were doing an overnight shoot on one of the Box Trap set days, and it was like 5am. The goddamn birds would not shut up outside. It took us way longer to film a super short outside scene that I had dedicated two hours to on the schedule. Among that, almost everything that could've went wrong that day went wrong and we ended up having to plan a reshoot day, which was an extra $5,000 or so over budget. Looking back now, I am thankful that everything went the way it did because it gave us extra time to really focus on the smaller scenes. But at the time, I almost gave myself a stroke and did not sleep the rest of that filming week. —- Subscribe to the podcast: Tweets by wildsoundpod https://www.instagram.com/wildsoundpod/ https://www.facebook.com/wildsoundpod

In this week's episode, Brandon and Gabby talk about the finale of Fallout season 2. They talk about the major reveals in the final episodes, they discuss the answered questions from the season, they explain MBTI for a bit, they talk about why they think certain characters do certain things, and they speculate about what will happen in the 3rd season

What a week we've had here on The Sports Agents, from penis-gate, to Winter Olympics heartbreak and Premier League managers getting sacked.This weekend sees Scotland host the Auld enemy at Murrayfield as they take on England for the Calcutta Cup.Love might not be in the air north of the border, but there were remnants in the studio - as Gabby welcomed her husband and former Scottish winger Kenny Logan onto the show.England's Six Nations title charge, mounting pressure on Scotland head coach Gregor Townsend, and what does Valentine's Day look like in the Logan household?

What a week we've had here on The Sports Agents, from penis-gate, to Winter Olympics heartbreak and Premier League managers getting sacked.This weekend sees Scotland host the Auld enemy at Murrayfield as they take on England for the Calcutta Cup.Love might not be in the air north of the border, but there were remnants in the studio - as Gabby welcomed her husband and former Scottish winger Kenny Logan onto the show.England's Six Nations title charge, mounting pressure on Scotland head coach Gregor Townsend, and what does Valentine's Day look like in the Logan household?

Gabby McCarthy, night one bombshell of the latest Love Island, joins the podcast to dish on her whirlwind experience in the villa and the real-life lessons that followed. From shocking behind-the-scenes truths about filming, producers, and "trauma bonds," to navigating unwanted attention and online backlash, Gabby gets candid on everything. Listen in on her journey of healing, how Love Island reshaped her standards in dating, and the advice she wishes she could give her younger self. Hosted on Acast. See acast.com/privacy for more information.

This podcast features Gabriele Corso and Jeremy Wohlwend, co-founders of Boltz and authors of the Boltz Manifesto, discussing the rapid evolution of structural biology models from AlphaFold to their own open-source suite, Boltz-1 and Boltz-2. The central thesis is that while single-chain protein structure prediction is largely “solved” through evolutionary hints, the next frontier lies in modeling complex interactions (protein-ligand, protein-protein) and generative protein design, which Boltz aims to democratize via open-source foundations and scalable infrastructure.Full Video PodOn YouTube!Timestamps* 00:00 Introduction to Benchmarking and the “Solved” Protein Problem* 06:48 Evolutionary Hints and Co-evolution in Structure Prediction* 10:00 The Importance of Protein Function and Disease States* 15:31 Transitioning from AlphaFold 2 to AlphaFold 3 Capabilities* 19:48 Generative Modeling vs. Regression in Structural Biology* 25:00 The “Bitter Lesson” and Specialized AI Architectures* 29:14 Development Anecdotes: Training Boltz-1 on a Budget* 32:00 Validation Strategies and the Protein Data Bank (PDB)* 37:26 The Mission of Boltz: Democratizing Access and Open Source* 41:43 Building a Self-Sustaining Research Community* 44:40 Boltz-2 Advancements: Affinity Prediction and Design* 51:03 BoltzGen: Merging Structure and Sequence Prediction* 55:18 Large-Scale Wet Lab Validation Results* 01:02:44 Boltz Lab Product Launch: Agents and Infrastructure* 01:13:06 Future Directions: Developpability and the “Virtual Cell”* 01:17:35 Interacting with Skeptical Medicinal ChemistsKey SummaryEvolution of Structure Prediction & Evolutionary Hints* Co-evolutionary Landscapes: The speakers explain that breakthrough progress in single-chain protein prediction relied on decoding evolutionary correlations where mutations in one position necessitate mutations in another to conserve 3D structure.* Structure vs. Folding: They differentiate between structure prediction (getting the final answer) and folding (the kinetic process of reaching that state), noting that the field is still quite poor at modeling the latter.* Physics vs. Statistics: RJ posits that while models use evolutionary statistics to find the right “valley” in the energy landscape, they likely possess a “light understanding” of physics to refine the local minimum.The Shift to Generative Architectures* Generative Modeling: A key leap in AlphaFold 3 and Boltz-1 was moving from regression (predicting one static coordinate) to a generative diffusion approach that samples from a posterior distribution.* Handling Uncertainty: This shift allows models to represent multiple conformational states and avoid the “averaging” effect seen in regression models when the ground truth is ambiguous.* Specialized Architectures: Despite the “bitter lesson” of general-purpose transformers, the speakers argue that equivariant architectures remain vastly superior for biological data due to the inherent 3D geometric constraints of molecules.Boltz-2 and Generative Protein Design* Unified Encoding: Boltz-2 (and BoltzGen) treats structure and sequence prediction as a single task by encoding amino acid identities into the atomic composition of the predicted structure.* Design Specifics: Instead of a sequence, users feed the model blank tokens and a high-level “spec” (e.g., an antibody framework), and the model decodes both the 3D structure and the corresponding amino acids.* Affinity Prediction: While model confidence is a common metric, Boltz-2 focuses on affinity prediction—quantifying exactly how tightly a designed binder will stick to its target.Real-World Validation and Productization* Generalized Validation: To prove the model isn't just “regurgitating” known data, Boltz tested its designs on 9 targets with zero known interactions in the PDB, achieving nanomolar binders for two-thirds of them.* Boltz Lab Infrastructure: The newly launched Boltz Lab platform provides “agents” for protein and small molecule design, optimized to run 10x faster than open-source versions through proprietary GPU kernels.* Human-in-the-Loop: The platform is designed to convert skeptical medicinal chemists by allowing them to run parallel screens and use their intuition to filter model outputs.TranscriptRJ [00:05:35]: But the goal remains to, like, you know, really challenge the models, like, how well do these models generalize? And, you know, we've seen in some of the latest CASP competitions, like, while we've become really, really good at proteins, especially monomeric proteins, you know, other modalities still remain pretty difficult. So it's really essential, you know, in the field that there are, like, these efforts to gather, you know, benchmarks that are challenging. So it keeps us in line, you know, about what the models can do or not.Gabriel [00:06:26]: Yeah, it's interesting you say that, like, in some sense, CASP, you know, at CASP 14, a problem was solved and, like, pretty comprehensively, right? But at the same time, it was really only the beginning. So you can say, like, what was the specific problem you would argue was solved? And then, like, you know, what is remaining, which is probably quite open.RJ [00:06:48]: I think we'll steer away from the term solved, because we have many friends in the community who get pretty upset at that word. And I think, you know, fairly so. But the problem that was, you know, that a lot of progress was made on was the ability to predict the structure of single chain proteins. So proteins can, like, be composed of many chains. And single chain proteins are, you know, just a single sequence of amino acids. And one of the reasons that we've been able to make such progress is also because we take a lot of hints from evolution. So the way the models work is that, you know, they sort of decode a lot of hints. That comes from evolutionary landscapes. So if you have, like, you know, some protein in an animal, and you go find the similar protein across, like, you know, different organisms, you might find different mutations in them. And as it turns out, if you take a lot of the sequences together, and you analyze them, you see that some positions in the sequence tend to evolve at the same time as other positions in the sequence, sort of this, like, correlation between different positions. And it turns out that that is typically a hint that these two positions are close in three dimension. So part of the, you know, part of the breakthrough has been, like, our ability to also decode that very, very effectively. But what it implies also is that in absence of that co-evolutionary landscape, the models don't quite perform as well. And so, you know, I think when that information is available, maybe one could say, you know, the problem is, like, somewhat solved. From the perspective of structure prediction, when it isn't, it's much more challenging. And I think it's also worth also differentiating the, sometimes we confound a little bit, structure prediction and folding. Folding is the more complex process of actually understanding, like, how it goes from, like, this disordered state into, like, a structured, like, state. And that I don't think we've made that much progress on. But the idea of, like, yeah, going straight to the answer, we've become pretty good at.Brandon [00:08:49]: So there's this protein that is, like, just a long chain and it folds up. Yeah. And so we're good at getting from that long chain in whatever form it was originally to the thing. But we don't know how it necessarily gets to that state. And there might be intermediate states that it's in sometimes that we're not aware of.RJ [00:09:10]: That's right. And that relates also to, like, you know, our general ability to model, like, the different, you know, proteins are not static. They move, they take different shapes based on their energy states. And I think we are, also not that good at understanding the different states that the protein can be in and at what frequency, what probability. So I think the two problems are quite related in some ways. Still a lot to solve. But I think it was very surprising at the time, you know, that even with these evolutionary hints that we were able to, you know, to make such dramatic progress.Brandon [00:09:45]: So I want to ask, why does the intermediate states matter? But first, I kind of want to understand, why do we care? What proteins are shaped like?Gabriel [00:09:54]: Yeah, I mean, the proteins are kind of the machines of our body. You know, the way that all the processes that we have in our cells, you know, work is typically through proteins, sometimes other molecules, sort of intermediate interactions. And through that interactions, we have all sorts of cell functions. And so when we try to understand, you know, a lot of biology, how our body works, how disease work. So we often try to boil it down to, okay, what is going right in case of, you know, our normal biological function and what is going wrong in case of the disease state. And we boil it down to kind of, you know, proteins and kind of other molecules and their interaction. And so when we try predicting the structure of proteins, it's critical to, you know, have an understanding of kind of those interactions. It's a bit like seeing the difference between... Having kind of a list of parts that you would put it in a car and seeing kind of the car in its final form, you know, seeing the car really helps you understand what it does. On the other hand, kind of going to your question of, you know, why do we care about, you know, how the protein falls or, you know, how the car is made to some extent is that, you know, sometimes when something goes wrong, you know, there are, you know, cases of, you know, proteins misfolding. In some diseases and so on, if we don't understand this folding process, we don't really know how to intervene.RJ [00:11:30]: There's this nice line in the, I think it's in the Alpha Fold 2 manuscript, where they sort of discuss also like why we even hopeful that we can target the problem in the first place. And then there's this notion that like, well, four proteins that fold. The folding process is almost instantaneous, which is a strong, like, you know, signal that like, yeah, like we should, we might be... able to predict that this very like constrained thing that, that the protein does so quickly. And of course that's not the case for, you know, for, for all proteins. And there's a lot of like really interesting mechanisms in the cells, but yeah, I remember reading that and thought, yeah, that's somewhat of an insightful point.Gabriel [00:12:10]: I think one of the interesting things about the protein folding problem is that it used to be actually studied. And part of the reason why people thought it was impossible, it used to be studied as kind of like a classical example. Of like an MP problem. Uh, like there are so many different, you know, type of, you know, shapes that, you know, this amino acid could take. And so, this grows combinatorially with the size of the sequence. And so there used to be kind of a lot of actually kind of more theoretical computer science thinking about and studying protein folding as an MP problem. And so it was very surprising also from that perspective, kind of seeing. Machine learning so clear, there is some, you know, signal in those sequences, through evolution, but also through kind of other things that, you know, us as humans, we're probably not really able to, uh, to understand, but that is, models I've, I've learned.Brandon [00:13:07]: And so Andrew White, we were talking to him a few weeks ago and he said that he was following the development of this and that there were actually ASICs that were developed just to solve this problem. So, again, that there were. There were many, many, many millions of computational hours spent trying to solve this problem before AlphaFold. And just to be clear, one thing that you mentioned was that there's this kind of co-evolution of mutations and that you see this again and again in different species. So explain why does that give us a good hint that they're close by to each other? Yeah.RJ [00:13:41]: Um, like think of it this way that, you know, if I have, you know, some amino acid that mutates, it's going to impact everything around it. Right. In three dimensions. And so it's almost like the protein through several, probably random mutations and evolution, like, you know, ends up sort of figuring out that this other amino acid needs to change as well for the structure to be conserved. Uh, so this whole principle is that the structure is probably largely conserved, you know, because there's this function associated with it. And so it's really sort of like different positions compensating for, for each other. I see.Brandon [00:14:17]: Those hints in aggregate give us a lot. Yeah. So you can start to look at what kinds of information about what is close to each other, and then you can start to look at what kinds of folds are possible given the structure and then what is the end state.RJ [00:14:30]: And therefore you can make a lot of inferences about what the actual total shape is. Yeah, that's right. It's almost like, you know, you have this big, like three dimensional Valley, you know, where you're sort of trying to find like these like low energy states and there's so much to search through. That's almost overwhelming. But these hints, they sort of maybe put you in. An area of the space that's already like, kind of close to the solution, maybe not quite there yet. And, and there's always this question of like, how much physics are these models learning, you know, versus like, just pure like statistics. And like, I think one of the thing, at least I believe is that once you're in that sort of approximate area of the solution space, then the models have like some understanding, you know, of how to get you to like, you know, the lower energy, uh, low energy state. And so maybe you have some, some light understanding. Of physics, but maybe not quite enough, you know, to know how to like navigate the whole space. Right. Okay.Brandon [00:15:25]: So we need to give it these hints to kind of get into the right Valley and then it finds the, the minimum or something. Yeah.Gabriel [00:15:31]: One interesting explanation about our awful free works that I think it's quite insightful, of course, doesn't cover kind of the entirety of, of what awful does that is, um, they're going to borrow from, uh, Sergio Chinico for MIT. So he sees kind of awful. Then the interesting thing about awful is God. This very peculiar architecture that we have seen, you know, used, and this architecture operates on this, you know, pairwise context between amino acids. And so the idea is that probably the MSA gives you this first hint about what potential amino acids are close to each other. MSA is most multiple sequence alignment. Exactly. Yeah. Exactly. This evolutionary information. Yeah. And, you know, from this evolutionary information about potential contacts, then is almost as if the model is. of running some kind of, you know, diastro algorithm where it's sort of decoding, okay, these have to be closed. Okay. Then if these are closed and this is connected to this, then this has to be somewhat closed. And so you decode this, that becomes basically a pairwise kind of distance matrix. And then from this rough pairwise distance matrix, you decode kind of theBrandon [00:16:42]: actual potential structure. Interesting. So there's kind of two different things going on in the kind of coarse grain and then the fine grain optimizations. Interesting. Yeah. Very cool.Gabriel [00:16:53]: Yeah. You mentioned AlphaFold3. So maybe we have a good time to move on to that. So yeah, AlphaFold2 came out and it was like, I think fairly groundbreaking for this field. Everyone got very excited. A few years later, AlphaFold3 came out and maybe for some more history, like what were the advancements in AlphaFold3? And then I think maybe we'll, after that, we'll talk a bit about the sort of how it connects to Bolt. But anyway. Yeah. So after AlphaFold2 came out, you know, Jeremy and I got into the field and with many others, you know, the clear problem that, you know, was, you know, obvious after that was, okay, now we can do individual chains. Can we do interactions, interaction, different proteins, proteins with small molecules, proteins with other molecules. And so. So why are interactions important? Interactions are important because to some extent that's kind of the way that, you know, these machines, you know, these proteins have a function, you know, the function comes by the way that they interact with other proteins and other molecules. Actually, in the first place, you know, the individual machines are often, as Jeremy was mentioning, not made of a single chain, but they're made of the multiple chains. And then these multiple chains interact with other molecules to give the function to those. And on the other hand, you know, when we try to intervene of these interactions, think about like a disease, think about like a, a biosensor or many other ways we are trying to design the molecules or proteins that interact in a particular way with what we would call a target protein or target. You know, this problem after AlphaVol2, you know, became clear, kind of one of the biggest problems in the field to, to solve many groups, including kind of ours and others, you know, started making some kind of contributions to this problem of trying to model these interactions. And AlphaVol3 was, you know, was a significant advancement on the problem of modeling interactions. And one of the interesting thing that they were able to do while, you know, some of the rest of the field that really tried to try to model different interactions separately, you know, how protein interacts with small molecules, how protein interacts with other proteins, how RNA or DNA have their structure, they put everything together and, you know, train very large models with a lot of advances, including kind of changing kind of systems. Some of the key architectural choices and managed to get a single model that was able to set this new state-of-the-art performance across all of these different kind of modalities, whether that was protein, small molecules is critical to developing kind of new drugs, protein, protein, understanding, you know, interactions of, you know, proteins with RNA and DNAs and so on.Brandon [00:19:39]: Just to satisfy the AI engineers in the audience, what were some of the key architectural and data, data changes that made that possible?Gabriel [00:19:48]: Yeah, so one critical one that was not necessarily just unique to AlphaFold3, but there were actually a few other teams, including ours in the field that proposed this, was moving from, you know, modeling structure prediction as a regression problem. So where there is a single answer and you're trying to shoot for that answer to a generative modeling problem where you have a posterior distribution of possible structures and you're trying to sample this distribution. And this achieves two things. One is it starts to allow us to try to model more dynamic systems. As we said, you know, some of these structures can actually take multiple structures. And so, you know, you can now model that, you know, through kind of modeling the entire distribution. But on the second hand, from more kind of core modeling questions, when you move from a regression problem to a generative modeling problem, you are really tackling the way that you think about uncertainty in the model in a different way. So if you think about, you know, I'm undecided between different answers, what's going to happen in a regression model is that, you know, I'm going to try to make an average of those different kind of answers that I had in mind. When you have a generative model, what you're going to do is, you know, sample all these different answers and then maybe use separate models to analyze those different answers and pick out the best. So that was kind of one of the critical improvement. The other improvement is that they significantly simplified, to some extent, the architecture, especially of the final model that takes kind of those pairwise representations and turns them into an actual structure. And that now looks a lot more like a more traditional transformer than, you know, like a very specialized equivariant architecture that it was in AlphaFold3.Brandon [00:21:41]: So this is a bitter lesson, a little bit.Gabriel [00:21:45]: There is some aspect of a bitter lesson, but the interesting thing is that it's very far from, you know, being like a simple transformer. This field is one of the, I argue, very few fields in applied machine learning where we still have kind of architecture that are very specialized. And, you know, there are many people that have tried to replace these architectures with, you know, simple transformers. And, you know, there is a lot of debate in the field, but I think kind of that most of the consensus is that, you know, the performance... that we get from the specialized architecture is vastly superior than what we get through a single transformer. Another interesting thing that I think on the staying on the modeling machine learning side, which I think it's somewhat counterintuitive seeing some of the other kind of fields and applications is that scaling hasn't really worked kind of the same in this field. Now, you know, models like AlphaFold2 and AlphaFold3 are, you know, still very large models.RJ [00:29:14]: in a place, I think, where we had, you know, some experience working in, you know, with the data and working with this type of models. And I think that put us already in like a good place to, you know, to produce it quickly. And, you know, and I would even say, like, I think we could have done it quicker. The problem was like, for a while, we didn't really have the compute. And so we couldn't really train the model. And actually, we only trained the big model once. That's how much compute we had. We could only train it once. And so like, while the model was training, we were like, finding bugs left and right. A lot of them that I wrote. And like, I remember like, I was like, sort of like, you know, doing like, surgery in the middle, like stopping the run, making the fix, like relaunching. And yeah, we never actually went back to the start. We just like kept training it with like the bug fixes along the way, which was impossible to reproduce now. Yeah, yeah, no, that model is like, has gone through such a curriculum that, you know, learned some weird stuff. But yeah, somehow by miracle, it worked out.Gabriel [00:30:13]: The other funny thing is that the way that we were training, most of that model was through a cluster from the Department of Energy. But that's sort of like a shared cluster that many groups use. And so we were basically training the model for two days, and then it would go back to the queue and stay a week in the queue. Oh, yeah. And so it was pretty painful. And so we actually kind of towards the end with Evan, the CEO of Genesis, and basically, you know, I was telling him a bit about the project and, you know, kind of telling him about this frustration with the compute. And so luckily, you know, he offered to kind of help. And so we, we got the help from Genesis to, you know, finish up the model. Otherwise, it probably would have taken a couple of extra weeks.Brandon [00:30:57]: Yeah, yeah.Brandon [00:31:02]: And then, and then there's some progression from there.Gabriel [00:31:06]: Yeah, so I would say kind of that, both one, but also kind of these other kind of set of models that came around the same time, were kind of approaching were a big leap from, you know, kind of the previous kind of open source models, and, you know, kind of really kind of approaching the level of AlphaVault 3. But I would still say that, you know, even to this day, there are, you know, some... specific instances where AlphaVault 3 works better. I think one common example is antibody antigen prediction, where, you know, AlphaVault 3 still seems to have an edge in many situations. Obviously, these are somewhat different models. They are, you know, you run them, you obtain different results. So it's, it's not always the case that one model is better than the other, but kind of in aggregate, we still, especially at the time.Brandon [00:32:00]: So AlphaVault 3 is, you know, still having a bit of an edge. We should talk about this more when we talk about Boltzgen, but like, how do you know one is, one model is better than the other? Like you, so you, I make a prediction, you make a prediction, like, how do you know?Gabriel [00:32:11]: Yeah, so easily, you know, the, the great thing about kind of structural prediction and, you know, once we're going to go into the design space of designing new small molecule, new proteins, this becomes a lot more complex. But a great thing about structural prediction is that a bit like, you know, CASP was doing, basically the way that you can evaluate them is that, you know, you train... You know, you train a model on a structure that was, you know, released across the field up until a certain time. And, you know, one of the things that we didn't talk about that was really critical in all this development is the PDB, which is the Protein Data Bank. It's this common resources, basically common database where every biologist publishes their structures. And so we can, you know, train on, you know, all the structures that were put in the PDB until a certain date. And then... And then we basically look for recent structures, okay, which structures look pretty different from anything that was published before, because we really want to try to understand generalization.Brandon [00:33:13]: And then on this new structure, we evaluate all these different models. And so you just know when AlphaFold3 was trained, you know, when you're, you intentionally trained to the same date or something like that. Exactly. Right. Yeah.Gabriel [00:33:24]: And so this is kind of the way that you can somewhat easily kind of compare these models, obviously, that assumes that, you know, the training. You've always been very passionate about validation. I remember like DiffDoc, and then there was like DiffDocL and DocGen. You've thought very carefully about this in the past. Like, actually, I think DocGen is like a really funny story that I think, I don't know if you want to talk about that. It's an interesting like... Yeah, I think one of the amazing things about putting things open source is that we get a ton of feedback from the field. And, you know, sometimes we get kind of great feedback of people. Really like... But honestly, most of the times, you know, to be honest, that's also maybe the most useful feedback is, you know, people sharing about where it doesn't work. And so, you know, at the end of the day, it's critical. And this is also something, you know, across other fields of machine learning. It's always critical to set, to do progress in machine learning, set clear benchmarks. And as, you know, you start doing progress of certain benchmarks, then, you know, you need to improve the benchmarks and make them harder and harder. And this is kind of the progression of, you know, how the field operates. And so, you know, the example of DocGen was, you know, we published this initial model called DiffDoc in my first year of PhD, which was sort of like, you know, one of the early models to try to predict kind of interactions between proteins, small molecules, that we bought a year after AlphaFold2 was published. And now, on the one hand, you know, on these benchmarks that we were using at the time, DiffDoc was doing really well, kind of, you know, outperforming kind of some of the traditional physics-based methods. But on the other hand, you know, when we started, you know, kind of giving these tools to kind of many biologists, and one example was that we collaborated with was the group of Nick Polizzi at Harvard. We noticed, started noticing that there was this clear, pattern where four proteins that were very different from the ones that we're trained on, the models was, was struggling. And so, you know, that seemed clear that, you know, this is probably kind of where we should, you know, put our focus on. And so we first developed, you know, with Nick and his group, a new benchmark, and then, you know, went after and said, okay, what can we change? And kind of about the current architecture to improve this pattern and generalization. And this is the same that, you know, we're still doing today, you know, kind of, where does the model not work, you know, and then, you know, once we have that benchmark, you know, let's try to, through everything we, any ideas that we have of the problem.RJ [00:36:15]: And there's a lot of like healthy skepticism in the field, which I think, you know, is, is, is great. And I think, you know, it's very clear that there's a ton of things, the models don't really work well on, but I think one thing that's probably, you know, undeniable is just like the pace of, pace of progress, you know, and how, how much better we're getting, you know, every year. And so I think if you, you know, if you assume, you know, any constant, you know, rate of progress moving forward, I think things are going to look pretty cool at some point in the future.Gabriel [00:36:42]: ChatGPT was only three years ago. Yeah, I mean, it's wild, right?RJ [00:36:45]: Like, yeah, yeah, yeah, it's one of those things. Like, you've been doing this. Being in the field, you don't see it coming, you know? And like, I think, yeah, hopefully we'll, you know, we'll, we'll continue to have as much progress we've had the past few years.Brandon [00:36:55]: So this is maybe an aside, but I'm really curious, you get this great feedback from the, from the community, right? By being open source. My question is partly like, okay, yeah, if you open source and everyone can copy what you did, but it's also maybe balancing priorities, right? Where you, like all my customers are saying. I want this, there's all these problems with the model. Yeah, yeah. But my customers don't care, right? So like, how do you, how do you think about that? Yeah.Gabriel [00:37:26]: So I would say a couple of things. One is, you know, part of our goal with Bolts and, you know, this is also kind of established as kind of the mission of the public benefit company that we started is to democratize the access to these tools. But one of the reasons why we realized that Bolts needed to be a company, it couldn't just be an academic project is that putting a model on GitHub is definitely not enough to get, you know, chemists and biologists, you know, across, you know, both academia, biotech and pharma to use your model to, in their therapeutic programs. And so a lot of what we think about, you know, at Bolts beyond kind of the, just the models is thinking about all the layers. The layers that come on top of the models to get, you know, from, you know, those models to something that can really enable scientists in the industry. And so that goes, you know, into building kind of the right kind of workflows that take in kind of, for example, the data and try to answer kind of directly that those problems that, you know, the chemists and the biologists are asking, and then also kind of building the infrastructure. And so this to say that, you know, even with models fully open. You know, we see a ton of potential for, you know, products in the space and the critical part about a product is that even, you know, for example, with an open source model, you know, running the model is not free, you know, as we were saying, these are pretty expensive model and especially, and maybe we'll get into this, you know, these days we're seeing kind of pretty dramatic inference time scaling of these models where, you know, the more you run them, the better the results are. But there, you know, you see. You start getting into a point that compute and compute costs becomes a critical factor. And so putting a lot of work into building the right kind of infrastructure, building the optimizations and so on really allows us to provide, you know, a much better service potentially to the open source models. That to say, you know, even though, you know, with a product, we can provide a much better service. I do still think, and we will continue to put a lot of our models open source because the critical kind of role. I think of open source. Models is, you know, helping kind of the community progress on the research and, you know, from which we, we all benefit. And so, you know, we'll continue to on the one hand, you know, put some of our kind of base models open source so that the field can, can be on top of it. And, you know, as we discussed earlier, we learn a ton from, you know, the way that the field uses and builds on top of our models, but then, you know, try to build a product that gives the best experience possible to scientists. So that, you know, like a chemist or a biologist doesn't need to, you know, spin off a GPU and, you know, set up, you know, our open source model in a particular way, but can just, you know, a bit like, you know, I, even though I am a computer scientist, machine learning scientist, I don't necessarily, you know, take a open source LLM and try to kind of spin it off. But, you know, I just maybe open a GPT app or a cloud code and just use it as an amazing product. We kind of want to give the same experience. So this front world.Brandon [00:40:40]: I heard a good analogy yesterday that a surgeon doesn't want the hospital to design a scalpel, right?Brandon [00:40:48]: So just buy the scalpel.RJ [00:40:50]: You wouldn't believe like the number of people, even like in my short time, you know, between AlphaFold3 coming out and the end of the PhD, like the number of people that would like reach out just for like us to like run AlphaFold3 for them, you know, or things like that. Just because like, you know, bolts in our case, you know, just because it's like. It's like not that easy, you know, to do that, you know, if you're not a computational person. And I think like part of the goal here is also that, you know, we continue to obviously build the interface with computational folks, but that, you know, the models are also accessible to like a larger, broader audience. And then that comes from like, you know, good interfaces and stuff like that.Gabriel [00:41:27]: I think one like really interesting thing about bolts is that with the release of it, you didn't just release a model, but you created a community. Yeah. Did that community, it grew very quickly. Did that surprise you? And like, what is the evolution of that community and how is that fed into bolts?RJ [00:41:43]: If you look at its growth, it's like very much like when we release a new model, it's like, there's a big, big jump, but yeah, it's, I mean, it's been great. You know, we have a Slack community that has like thousands of people on it. And it's actually like self-sustaining now, which is like the really nice part because, you know, it's, it's almost overwhelming, I think, you know, to be able to like answer everyone's questions and help. It's really difficult, you know. The, the few people that we were, but it ended up that like, you know, people would answer each other's questions and like, sort of like, you know, help one another. And so the Slack, you know, has been like kind of, yeah, self, self-sustaining and that's been, it's been really cool to see.RJ [00:42:21]: And, you know, that's, that's for like the Slack part, but then also obviously on GitHub as well. We've had like a nice, nice community. You know, I think we also aspire to be even more active on it, you know, than we've been in the past six months, which has been like a bit challenging, you know, for us. But. Yeah, the community has been, has been really great and, you know, there's a lot of papers also that have come out with like new evolutions on top of bolts and it's surprised us to some degree because like there's a lot of models out there. And I think like, you know, sort of people converging on that was, was really cool. And, you know, I think it speaks also, I think, to the importance of like, you know, when, when you put code out, like to try to put a lot of emphasis and like making it like as easy to use as possible and something we thought a lot about when we released the code base. You know, it's far from perfect, but, you know.Brandon [00:43:07]: Do you think that that was one of the factors that caused your community to grow is just the focus on easy to use, make it accessible? I think so.RJ [00:43:14]: Yeah. And we've, we've heard it from a few people over the, over the, over the years now. And, you know, and some people still think it should be a lot nicer and they're, and they're right. And they're right. But yeah, I think it was, you know, at the time, maybe a little bit easier than, than other things.Gabriel [00:43:29]: The other thing part, I think led to, to the community and to some extent, I think, you know, like the somewhat the trust in the community. Kind of what we, what we put out is the fact that, you know, it's not really been kind of, you know, one model, but, and maybe we'll talk about it, you know, after Boltz 1, you know, there were maybe another couple of models kind of released, you know, or open source kind of soon after. We kind of continued kind of that open source journey or at least Boltz 2, where we are not only improving kind of structure prediction, but also starting to do affinity predictions, understanding kind of the strength of the interactions between these different models, which is this critical component. critical property that you often want to optimize in discovery programs. And then, you know, more recently also kind of protein design model. And so we've sort of been building this suite of, of models that come together, interact with one another, where, you know, kind of, there is almost an expectation that, you know, we, we take very at heart of, you know, always having kind of, you know, across kind of the entire suite of different tasks, the best or across the best. model out there so that it's sort of like our open source tool can be kind of the go-to model for everybody in the, in the industry. I really want to talk about Boltz 2, but before that, one last question in this direction, was there anything about the community which surprised you? Were there any, like, someone was doing something and you're like, why would you do that? That's crazy. Or that's actually genius. And I never would have thought about that.RJ [00:45:01]: I mean, we've had many contributions. I think like some of the. Interesting ones, like, I mean, we had, you know, this one individual who like wrote like a complex GPU kernel, you know, for part of the architecture on a piece of, the funny thing is like that piece of the architecture had been there since AlphaFold 2, and I don't know why it took Boltz for this, you know, for this person to, you know, to decide to do it, but that was like a really great contribution. We've had a bunch of others, like, you know, people figuring out like ways to, you know, hack the model to do something. They click peptides, like, you know, there's, I don't know if there's any other interesting ones come to mind.Gabriel [00:45:41]: One cool one, and this was, you know, something that initially was proposed as, you know, as a message in the Slack channel by Tim O'Donnell was basically, he was, you know, there are some cases, especially, for example, we discussed, you know, antibody-antigen interactions where the models don't necessarily kind of get the right answer. What he noticed is that, you know, the models were somewhat stuck into predicting kind of the antibodies. And so he basically ran the experiments in this model, you can condition, basically, you can give hints. And so he basically gave, you know, random hints to the model, basically, okay, you should bind to this residue, you should bind to the first residue, or you should bind to the 11th residue, or you should bind to the 21st residue, you know, basically every 10 residues scanning the entire antigen.Brandon [00:46:33]: Residues are the...Gabriel [00:46:34]: The amino acids. The amino acids, yeah. So the first amino acids. The 11 amino acids, and so on. So it's sort of like doing a scan, and then, you know, conditioning the model to predict all of them, and then looking at the confidence of the model in each of those cases and taking the top. And so it's sort of like a very somewhat crude way of doing kind of inference time search. But surprisingly, you know, for antibody-antigen prediction, it actually kind of helped quite a bit. And so there's some, you know, interesting ideas that, you know, obviously, as kind of developing the model, you say kind of, you know, wow. This is why would the model, you know, be so dumb. But, you know, it's very interesting. And that, you know, leads you to also kind of, you know, start thinking about, okay, how do I, can I do this, you know, not with this brute force, but, you know, in a smarter way.RJ [00:47:22]: And so we've also done a lot of work on that direction. And that speaks to, like, the, you know, the power of scoring. We're seeing that a lot. I'm sure we'll talk about it more when we talk about BullsGen. But, you know, our ability to, like, take a structure and determine that that structure is, like... Good. You know, like, somewhat accurate. Whether that's a single chain or, like, an interaction is a really powerful way of improving, you know, the models. Like, sort of like, you know, if you can sample a ton and you assume that, like, you know, if you sample enough, you're likely to have, like, you know, the good structure. Then it really just becomes a ranking problem. And, you know, now we're, you know, part of the inference time scaling that Gabby was talking about is very much that. It's like, you know, the more we sample, the more we, like, you know, the ranking model. The ranking model ends up finding something it really likes. And so I think our ability to get better at ranking, I think, is also what's going to enable sort of the next, you know, next big, big breakthroughs. Interesting.Brandon [00:48:17]: But I guess there's a, my understanding, there's a diffusion model and you generate some stuff and then you, I guess, it's just what you said, right? Then you rank it using a score and then you finally... And so, like, can you talk about those different parts? Yeah.Gabriel [00:48:34]: So, first of all, like, the... One of the critical kind of, you know, beliefs that we had, you know, also when we started working on Boltz 1 was sort of like the structure prediction models are somewhat, you know, our field version of some foundation models, you know, learning about kind of how proteins and other molecules interact. And then we can leverage that learning to do all sorts of other things. And so with Boltz 2, we leverage that learning to do affinity predictions. So understanding kind of, you know, if I give you this protein, this molecule. How tightly is that interaction? For Boltz 1, what we did was taking kind of that kind of foundation models and then fine tune it to predict kind of entire new proteins. And so the way basically that that works is sort of like instead of for the protein that you're designing, instead of fitting in an actual sequence, you fit in a set of blank tokens. And you train the models to, you know, predict both the structure of kind of that protein. The structure also, what the different amino acids of that proteins are. And so basically the way that Boltz 1 operates is that you feed a target protein that you may want to kind of bind to or, you know, another DNA, RNA. And then you feed the high level kind of design specification of, you know, what you want your new protein to be. For example, it could be like an antibody with a particular framework. It could be a peptide. It could be many other things. And that's with natural language or? And that's, you know, basically, you know, prompting. And we have kind of this sort of like spec that you specify. And, you know, you feed kind of this spec to the model. And then the model translates this into, you know, a set of, you know, tokens, a set of conditioning to the model, a set of, you know, blank tokens. And then, you know, basically the codes as part of the diffusion models, the codes. It's a new structure and a new sequence for your protein. And, you know, basically, then we take that. And as Jeremy was saying, we are trying to score it and, you know, how good of a binder it is to that original target.Brandon [00:50:51]: You're using basically Boltz to predict the folding and the affinity to that molecule. So and then that kind of gives you a score? Exactly.Gabriel [00:51:03]: So you use this model to predict the folding. And then you do two things. One is that you predict the structure and with something like Boltz2, and then you basically compare that structure with what the model predicted, what Boltz2 predicted. And this is sort of like in the field called consistency. It's basically you want to make sure that, you know, the structure that you're predicting is actually what you're trying to design. And that gives you a much better confidence that, you know, that's a good design. And so that's the first filtering. And the second filtering that we did as part of kind of the Boltz2 pipeline that was released is that we look at the confidence that the model has in the structure. Now, unfortunately, kind of going to your question of, you know, predicting affinity, unfortunately, confidence is not a very good predictor of affinity. And so one of the things that we've actually done a ton of progress, you know, since we released Boltz2.Brandon [00:52:03]: And kind of we have some new results that we are going to kind of announce soon is kind of, you know, the ability to get much better hit rates when instead of, you know, trying to rely on confidence of the model, we are actually directly trying to predict the affinity of that interaction. Okay. Just backing up a minute. So your diffusion model actually predicts not only the protein sequence, but also the folding of it. Exactly.Gabriel [00:52:32]: And actually, you can... One of the big different things that we did compared to other models in the space, and, you know, there were some papers that had already kind of done this before, but we really scaled it up was, you know, basically somewhat merging kind of the structure prediction and the sequence prediction into almost the same task. And so the way that Boltz2 works is that you are basically the only thing that you're doing is predicting the structure. So the only sort of... Supervision is we give you a supervision on the structure, but because the structure is atomic and, you know, the different amino acids have a different atomic composition, basically from the way that you place the atoms, we also understand not only kind of the structure that you wanted, but also the identity of the amino acid that, you know, the models believed was there. And so we've basically, instead of, you know, having these two supervision signals, you know, one discrete, one continuous. That somewhat, you know, don't interact well together. We sort of like build kind of like an encoding of, you know, sequences in structures that allows us to basically use exactly the same supervision signal that we were using to Boltz2 that, you know, you know, largely similar to what AlphaVol3 proposed, which is very scalable. And we can use that to design new proteins. Oh, interesting.RJ [00:53:58]: Maybe a quick shout out to Hannes Stark on our team who like did all this work. Yeah.Gabriel [00:54:04]: Yeah, that was a really cool idea. I mean, like looking at the paper and there's this is like encoding or you just add a bunch of, I guess, kind of atoms, which can be anything, and then they get sort of rearranged and then basically plopped on top of each other so that and then that encodes what the amino acid is. And there's sort of like a unique way of doing this. It was that was like such a really such a cool, fun idea.RJ [00:54:29]: I think that idea was had existed before. Yeah, there were a couple of papers.Gabriel [00:54:33]: Yeah, I had proposed this and and Hannes really took it to the large scale.Brandon [00:54:39]: In the paper, a lot of the paper for Boltz2Gen is dedicated to actually the validation of the model. In my opinion, all the people we basically talk about feel that this sort of like in the wet lab or whatever the appropriate, you know, sort of like in real world validation is the whole problem or not the whole problem, but a big giant part of the problem. So can you talk a little bit about the highlights? From there, that really because to me, the results are impressive, both from the perspective of the, you know, the model and also just the effort that went into the validation by a large team.Gabriel [00:55:18]: First of all, I think I should start saying is that both when we were at MIT and Thomas Yacolas and Regina Barzillai's lab, as well as at Boltz, you know, we are not a we're not a biolab and, you know, we are not a therapeutic company. And so to some extent, you know, we were first forced to, you know, look outside of, you know, our group, our team to do the experimental validation. One of the things that really, Hannes, in the team pioneer was the idea, OK, can we go not only to, you know, maybe a specific group and, you know, trying to find a specific system and, you know, maybe overfit a bit to that system and trying to validate. But how can we test this model? So. Across a very wide variety of different settings so that, you know, anyone in the field and, you know, printing design is, you know, such a kind of wide task with all sorts of different applications from therapeutic to, you know, biosensors and many others that, you know, so can we get a validation that is kind of goes across many different tasks? And so he basically put together, you know, I think it was something like, you know, 25 different. You know, academic and industry labs that committed to, you know, testing some of the designs from the model and some of this testing is still ongoing and, you know, giving results kind of back to us in exchange for, you know, hopefully getting some, you know, new great sequences for their task. And he was able to, you know, coordinate this, you know, very wide set of, you know, scientists and already in the paper, I think we. Shared results from, I think, eight to 10 different labs kind of showing results from, you know, designing peptides, designing to target, you know, ordered proteins, peptides targeting disordered proteins, which are results, you know, of designing proteins that bind to small molecules, which are results of, you know, designing nanobodies and across a wide variety of different targets. And so that's sort of like. That gave to the paper a lot of, you know, validation to the model, a lot of validation that was kind of wide.Brandon [00:57:39]: And so those would be therapeutics for those animals or are they relevant to humans as well? They're relevant to humans as well.Gabriel [00:57:45]: Obviously, you need to do some work into, quote unquote, humanizing them, making sure that, you know, they have the right characteristics to so they're not toxic to humans and so on.RJ [00:57:57]: There are some approved medicine in the market that are nanobodies. There's a general. General pattern, I think, in like in trying to design things that are smaller, you know, like it's easier to manufacture at the same time, like that comes with like potentially other challenges, like maybe a little bit less selectivity than like if you have something that has like more hands, you know, but the yeah, there's this big desire to, you know, try to design many proteins, nanobodies, small peptides, you know, that just are just great drug modalities.Brandon [00:58:27]: Okay. I think we were left off. We were talking about validation. Validation in the lab. And I was very excited about seeing like all the diverse validations that you've done. Can you go into some more detail about them? Yeah. Specific ones. Yeah.RJ [00:58:43]: The nanobody one. I think we did. What was it? 15 targets. Is that correct? 14. 14 targets. Testing. So we typically the way this works is like we make a lot of designs. All right. On the order of like tens of thousands. And then we like rank them and we pick like the top. And in this case, and was 15 right for each target and then we like measure sort of like the success rates, both like how many targets we were able to get a binder for and then also like more generally, like out of all of the binders that we designed, how many actually proved to be good binders. Some of the other ones I think involved like, yeah, like we had a cool one where there was a small molecule or design a protein that binds to it. That has a lot of like interesting applications, you know, for example. Like Gabri mentioned, like biosensing and things like that, which is pretty cool. We had a disordered protein, I think you mentioned also. And yeah, I think some of those were some of the highlights. Yeah.Gabriel [00:59:44]: So I would say that the way that we structure kind of some of those validations was on the one end, we have validations across a whole set of different problems that, you know, the biologists that we were working with came to us with. So we were trying to. For example, in some of the experiments, design peptides that would target the RACC, which is a target that is involved in metabolism. And we had, you know, a number of other applications where we were trying to design, you know, peptides or other modalities against some other therapeutic relevant targets. We designed some proteins to bind small molecules. And then some of the other testing that we did was really trying to get like a more broader sense. So how does the model work, especially when tested, you know, on somewhat generalization? So one of the things that, you know, we found with the field was that a lot of the validation, especially outside of the validation that was on specific problems, was done on targets that have a lot of, you know, known interactions in the training data. And so it's always a bit hard to understand, you know, how much are these models really just regurgitating kind of what they've seen or trying to imitate. What they've seen in the training data versus, you know, really be able to design new proteins. And so one of the experiments that we did was to take nine targets from the PDB, filtering to things where there is no known interaction in the PDB. So basically the model has never seen kind of this particular protein bound or a similar protein bound to another protein. So there is no way that. The model from its training set can sort of like say, okay, I'm just going to kind of tweak something and just imitate this particular kind of interaction. And so we took those nine proteins. We worked with adaptive CRO and basically tested, you know, 15 mini proteins and 15 nanobodies against each one of them. And the very cool thing that we saw was that on two thirds of those targets, we were able to, from this 15 design, get nanomolar binders, nanomolar, roughly speaking, just a measure of, you know, how strongly kind of the interaction is, roughly speaking, kind of like a nanomolar binder is approximately the kind of binding strength or binding that you need for a therapeutic. Yeah. So maybe switching directions a bit. Bolt's lab was just announced this week or was it last week? Yeah. This is like your. First, I guess, product, if that's if you want to call it that. Can you talk about what Bolt's lab is and yeah, you know, what you hope that people take away from this? Yeah.RJ [01:02:44]: You know, as we mentioned, like I think at the very beginning is the goal with the product has been to, you know, address what the models don't on their own. And there's largely sort of two categories there. I'll split it in three. The first one. It's one thing to predict, you know, a single interaction, for example, like a single structure. It's another to like, you know, very effectively search a space, a design space to produce something of value. What we found, like sort of building on this product is that there's a lot of steps involved, you know, in that there's certainly need to like, you know, accompany the user through, you know, one of those steps, for example, is like, you know, the creation of the target itself. You know, how do we make sure that the model has like a good enough understanding of the target? So we can like design something and there's all sorts of tricks, you know, that you can do to improve like a particular, you know, structure prediction. And so that's sort of like, you know, the first stage. And then there's like this stage of like, you know, designing and searching the space efficiently. You know, for something like BullsGen, for example, like you, you know, you design many things and then you rank them, for example, for small molecule process, a little bit more complicated. We actually need to also make sure that the molecules are synthesizable. And so the way we do that is that, you know, we have a generative model that learns. To use like appropriate building blocks such that, you know, it can design within a space that we know is like synthesizable. And so there's like, you know, this whole pipeline really of different models involved in being able to design a molecule. And so that's been sort of like the first thing we call them agents. We have a protein agent and we have a small molecule design agents. And that's really like at the core of like what powers, you know, the BullsLab platform.Brandon [01:04:22]: So these agents, are they like a language model wrapper or they're just like your models and you're just calling them agents? A lot. Yeah. Because they, they, they sort of perform a function on behalf of.RJ [01:04:33]: They're more of like a, you know, a recipe, if you wish. And I think we use that term sort of because of, you know, sort of the complex pipelining and automation, you know, that goes into like all this plumbing. So that's the first part of the product. The second part is the infrastructure. You know, we need to be able to do this at very large scale for any one, you know, group that's doing a design campaign. Let's say you're designing, you know, I'd say a hundred thousand possible candidates. Right. To find the good one that is, you know, a very large amount of compute, you know, for small molecules, it's on the order of like a few seconds per designs for proteins can be a bit longer. And so, you know, ideally you want to do that in parallel, otherwise it's going to take you weeks. And so, you know, we've put a lot of effort into like, you know, our ability to have a GPU fleet that allows any one user, you know, to be able to do this kind of like large parallel search.Brandon [01:05:23]: So you're amortizing the cost over your users. Exactly. Exactly.RJ [01:05:27]: And, you know, to some degree, like it's whether you. Use 10,000 GPUs for like, you know, a minute is the same cost as using, you know, one GPUs for God knows how long. Right. So you might as well try to parallelize if you can. So, you know, a lot of work has gone, has gone into that, making it very robust, you know, so that we can have like a lot of people on the platform doing that at the same time. And the third one is, is the interface and the interface comes in, in two shapes. One is in form of an API and that's, you know, really suited for companies that want to integrate, you know, these pipelines, these agents.RJ [01:06:01]: So we're already partnering with, you know, a few distributors, you know, that are gonna integrate our API. And then the second part is the user interface. And, you know, we, we've put a lot of thoughts also into that. And this is when I, I mentioned earlier, you know, this idea of like broadening the audience. That's kind of what the, the user interface is about. And we've built a lot of interesting features in it, you know, for example, for collaboration, you know, when you have like potentially multiple medicinal chemists or. We're going through the results and trying to pick out, okay, like what are the molecules that we're going to go and test in the lab? It's powerful for them to be able to, you know, for example, each provide their own ranking and then do consensus building. And so there's a lot of features around launching these large jobs, but also around like collaborating on analyzing the results that we try to solve, you know, with that part of the platform. So Bolt's lab is sort of a combination of these three objectives into like one, you know, sort of cohesive platform. Who is this accessible to? Everyone. You do need to request access today. We're still like, you know, sort of ramping up the usage, but anyone can request access. If you are an academic in particular, we, you know, we provide a fair amount of free credit so you can play with the platform. If you are a startup or biotech, you may also, you know, reach out and we'll typically like actually hop on a call just to like understand what you're trying to do and also provide a lot of free credit to get started. And of course, also with larger companies, we can deploy this platform in a more like secure environment. And so that's like more like customizing. You know, deals that we make, you know, with the partners, you know, and that's sort of the ethos of Bolt. I think this idea of like servicing everyone and not necessarily like going after just, you know, the really large enterprises. And that starts from the open source, but it's also, you know, a key design principle of the product itself.Gabriel [01:07:48]: One thing I was thinking about with regards to infrastructure, like in the LLM space, you know, the cost of a token has gone down by I think a factor of a thousand or so over the last three years, right? Yeah. And is it possible that like essentially you can exploit economies of scale and infrastructure that you can make it cheaper to run these things yourself than for any person to roll their own system? A hundred percent. Yeah.RJ [01:08:08]: I mean, we're already there, you know, like running Bolts on our platform, especially on a large screen is like considerably cheaper than it would probably take anyone to put the open source model out there and run it. And on top of the infrastructure, like one of the things that we've been working on is accelerating the models. So, you know. Our small molecule screening pipeline is 10x faster on Bolts Lab than it is in the open source, you know, and that's also part of like, you know, building a product, you know, of something that scales really well. And we really wanted to get to a point where like, you know, we could keep prices very low in a way that it would be a no-brainer, you know, to use Bolts through our platform.Gabriel [01:08:52]: How do you think about validation of your like agentic systems? Because, you know, as you were saying earlier. Like we're AlphaFold style models are really good at, let's say, monomeric, you know, proteins where you have, you know, co-evolution data. But now suddenly the whole point of this is to design something which doesn't have, you know, co-evolution data, something which is really novel. So now you're basically leaving the domain that you thought was, you know, that you know you are good at. So like, how do you validate that?RJ [01:09:22]: Yeah, I like every complete, but there's obviously, you know, a ton of computational metrics. That we rely on, but those are only take you so far. You really got to go to the lab, you know, and test, you know, okay, with this method A and this method B, how much better are we? You know, how much better is my, my hit rate? How stronger are my binders? Also, it's not just about hit rate. It's also about how good the binders are. And there's really like no way, nowhere around that. I think we're, you know, we've really ramped up the amount of experimental validation that we do so that we like really track progress, you know, as scientifically sound, you know. Yeah. As, as possible out of this, I think.Gabriel [01:10:00]: Yeah, no, I think, you know, one thing that is unique about us and maybe companies like us is that because we're not working on like maybe a couple of therapeutic pipelines where, you know, our validation would be focused on those. We, when we do an experimental validation, we try to test it across tens of targets. And so that on the one end, we can get a much more statistically significant result and, and really allows us to make progress. From the methodological side without being, you know, steered by, you know, overfitting on any one particular system. And of course we choose, you know, w

Welcome back to Intellicast! On today's episode, Brian is joined by Gabby Blados to discuss the latest news from around the market research industry. Before jumping into the news, Brian and Gabby trade notes on the Super Bowl. (Not the game, as they both agree it was a bit of a snoozer) They talk about their favorite commercials, the ones they were less impressed with, and Bad Bunny's performance. Then they jump into the latest news, starting with the news that Anita Watkins has been named the new CEO of the Insights Association. Both are excited with the experience Anita is going to bring to the role. Additionally, Gabby and Brian touch on: The acquisition of Rare Patient Voice by Konova The launch of Knowledge Navigator by MRII and UGA Sago Health's rebrand to Trivoca Health The launch of the GDQ Feedback Loop In the final segment, Brian and Gabby talk about the announcement that Rep Data acquired the in-survey data quality provider, ReDem. Brian and Gabby are both excited to see how the ReDem tool set will be integrated into the Research Defender platform. Thanks for tuning in! We've just launched our new whitepaper, The Fraud Detection Reality Check. Get your copy and find out why relying on a single fraud detection tool is a mistake. Download here: https://content.emi-rs.com/fraud-detection-report   Did you miss one of our webinars or want to get some of our whitepapers and reports?  You can find it all on our Resources page on our website here:  https://emi-rs.com/resources/  Learn more about your ad choices. Visit megaphone.fm/adchoices

Good Vibe Tribe: Gabby Is Running Boston Marathon For Special Olympics! full 257 Wed, 11 Feb 2026 13:04:42 +0000 2kkd2xL9kPYN1Grx6zSB8bVpQc7zM5WP latest,wwbx,society & culture Karson & Kennedy latest,wwbx,society & culture Good Vibe Tribe: Gabby Is Running Boston Marathon For Special Olympics! Karson & Kennedy are honest and open about the most intimate details of their personal lives. The show is fast paced and will have you laughing until it hurts one minute and then wiping tears away from your eyes the next. Some of K&K’s most popular features are Can’t Beat Kennedy, What Did Barrett Say, and The Dirty on the 30! 2024 © 2021 Audacy, Inc. Society & Culture False https://player.amperw

Have you ever dated someone, or are currently married to a person whose relationship with money looks very different from yours? Maybe they like to spend and you're more of a saver? Or, you're self-employed and want to know the best strategy for saving for retirement? Then give this week's special episode a listen. In celebration of five years of Uncorked with Funny Wine Girl, I'm hosting several live, on-line opportunities for you to ask questions of "experts." This week's episode was recorded live on Jan. 28 with Emily Hickox of Budget Through Life, who shared her expertise in financial literacy with question askers Oliver Ord and Tina Gallagher who will be answering questions on my next Ask the Expert on Feb. 18 at 7PM, ET. Tina is a self-published romance author who is ready to answer your questions about writing, self-publishing, marketing, book signings and much more.If you would like to learn about Emily's financial coaching services, email Emily at budgetthroughlife.com.Thank you to my podcast sponsors Reinvented Threads with Gabby Lynn and Healthy Lifestyle Management with Lisa Rigau. Gabby is busy at work making beautiful, spring-inspired ecofriendly handmade hats, bags and monster dolls. Follow Reinvented Threads on Facebook and Instagram to stay up to date on Gabby's latest creations and you can shop online on ReinventedThreads.com. Lisa of Healthy Lifestyle Management offers a variety of health coaching services including her upcoming 8-week mindfulness-based stress reduction course beginning in March. Enroll before Feb. 18 to save $50. Register here. If you would like to support this podcast through sponsorship, email Jeannine.Luby@gmail.com for a list of affordable sponsorship packages. Remember that you can also show support by sharing an episode of this podcast with a friend, foe, or anyone you know, or by rating the podcast or writing a review. Follow Funny Wine Girl Jeannine on Facebook and Instagram to stay in the know and get some laughs. Click here.

For this episode, Gabby sits down with author and speaker Catherine Gray for an honest, curious conversation about the habits that shape our lives — and the tiny patterns that quietly run the show.Best known for her writing on behaviour change and sobriety, Catherine joins us to explore the ideas behind her book Little Addictions, unpacking how small compulsions — from scrolling and sugar to work and worry — can subtly steer our choices, moods, and identities. Together, we look at why humans cling to rituals, what it really takes to shift ingrained habits, and how self-awareness can open the door to something more intentional.This episode marks a reflective pause in the journey: a chance to examine the everyday dependencies we often overlook, and to ask what freedom might look like — not in dramatic transformations, but in small, meaningful changes.A thoughtful Midpoint conversation about awareness, agency, and the stories we tell ourselves about control.More than 40 percent of respondents who began drinking before age 15 were classified with alcohol dependence at some time in their lives, the researchers found: https://www.niaaa.nih.gov/news-events/news-releases/age-drinking-onset-predicts-future-alcohol-abuse-and-dependence Hosted on Acast. See acast.com/privacy for more information.

Gabby era uma garota criativa e querida por todos, e sempre teve o sonho de ter seu próprio vlog de viagem e viver na estrada em uma van. Quando ela começou a namorar Brian ele logo embarcou na ideia, e juntos os dois tornaram esse sonho realidade. Mas o que ninguém sabia era o quanto Brian era abusivo no relacionamento, e quando Gabby desapareceu sem deixar vestígios a internet inteira foi tomada por teorias e especulações sobre o que poderia ter acontecido.Apoie nosso podcast: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.1001crimes.com.br⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Mande suas histórias: 1001medinhos@gmail.comFale com a gente: 1001crimes@gmail.comConfira nosso canal! ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠youtube.com/1001crimes

In this week's episode, David and Gabby help a wife wanting to bring spice back to the bedroom and a band member wanting to know how to deal with nerves before going on stage. They also get probably their best submission yet so you're going to have to listen to the full episode to find out what situation has Gabby and David's jaws on the FLOOR! To submit a question to David & Gabby email: letmeaskmydadpod@gmail.com Follow Gabby & David:  Let Me Ask My Dad on Instagram: @letmeaskmydadpod Let Me Ask My Dad on TikTok: @letmeaskmydadpod  David Bryan on Instagram: @davidbryanmusic Gabby Bryan on Instagram: @gabbyisbryan Gabby Bryan on TikTok: @gabbyisbryan Let Me Ask My Dad is produced by Lizzie Stewart in partnership with W!zard Radio Learn more about your ad choices. Visit megaphone.fm/adchoices

Two years into Albuquerque's DWI dismissal scandal, the fallout is still unfolding. Chris and Gabby sit down with KRQE Investigates reporter Ann Pierret to break down her latest reporting, revealing how many accused drunk drivers reoffended after getting a free pass due to their arresting officers losing credibility in court. The KRQE Investigates team also brings listeners up to speed on where the federal investigation stands now, including shocking new court admissions from a former APD Lieutenant who described targeting drunk drivers and exploiting them for cash. When will officers face prison time? How deep can this scheme go?  They got a free pass due to the DWI scandal. Then, they got in trouble again. Watch: APD officer admits to setting up a drunk driver  Comprehensive KRQE Investigates team coverage of the DWI dismissal scandal  Thanks for listening. If you've got an idea, send it to us at chris.mckee@krqe.com or gabrielle.burkhart@krqe.com. Give us a follow on social media at @ChrisMcKeeTV and @gburkNM. Watch or listen to our prior podcasts online at KRQE.com/insiders and our KRQE YouTube channel, or on broadcast TV every Wednesday at 10:35 p.m. MST on Fox New Mexico. 

Gabby Osio Vanden and Jack Weisman join the show after winning Sundance's Grand Jury Prize to unpack the ten-year road behind Nuisance Bear, a polar bear's journey through two connected worlds: tourist-heavy Churchill, Manitoba, and the Inuit community of Arviat, where the stakes are far more complex and far less welcoming. The film becomes a meditation on coexistence, control, and who gets labeled a “nuisance” in a shared landscape.We dig into craft and access: finding the right position for the camera so the story can reveal itself, structuring the feature in two halves, and how a dialogue-free short film born partly out of COVID constraints became the proof of concept that unlocked TIFF, The New Yorker, and eventually A24. They also talk candidly about what the audience never sees: rough living conditions, long hours waiting, the specific agony of “the best thing happened, and we missed it,” and the slow but important work of earning trust, where listening comes before filming.They share influences that shaped them, including Miyazaki's sense of nature and modernity, Gus Van Sant's bravery with form, and John Cassavetes' belief in the energy of a set. The conversation closes on what it meant to experience Sundance as both a career peak and a personal milestone, getting engaged and then married during the festival. Advice to filmmakers: be tenacious when you know you need to tell a story, protect trust like it is part of the craft, and do not turn on each other when the pressure spikes.What Movies Are You Watching?This episode is brought to you by BeastGrip. When you're filming on your phone and need something solid, modular, and built for real productions - including 28 Years Later and Left Handed Girl - BeastGrip's rigs, lenses, and accessories are designed to hold up without slowing you down. If you're ready to level up your mobile workflow, visit BeastGrip.com and use coupon code PASTPRESENTFEATURE for 10 % off.  Revival Hub is your guide to specialty screenings in Los Angeles - classics on 35mm, director Q&As, rare restorations, and indie gems you won't find on streaming. We connect moviegoers with over 200 venues across LA, from the major revival houses to the 20-seat microcinemas and more.Visit revivalhub.com to see what's playing this week.  Acclaimed documentary ROADS OF FIRE is now available on Amazon, iTunes, and Fandango at home. Directed by Nathaniel Lezra, the film won best documentary at the 2025 Santa Barbara International Film Festival. The film examines the migrant crisis here in the States all the way down to Venezuela, and Academy Award nominee Diane Lane calls it "a must-see journey of human dignity." Roads of Fire - now on Amazon, iTunes, Fandango. Introducing the Past Present Feature Film Festival, a new showcase celebrating cinematic storytelling across time. From bold proof of concept shorts to stand out new films lighting up the circuit, to overlooked features that deserve another look. Sponsored by the Past Present Feature podcast and Leica Camera. Submit now at filmfreeway.com/PastPresentFeatureSupport the show Listen to all episodes on Spotify, Apple Podcasts, and more, as well as at www.pastpresentfeature.com. Like, subscribe, and follow us on our socials @pastpresentfeature The Past Present Feature Film Festival - Nov. 20-22, 2026 in Hollywood, CA - Submit at filmfreeway.com/PastPresentFeature

If you find yourself stuck in a cycle of attracting the wrong partners or repeating the same painful relationship dynamics, this episode serves as a spiritual guide to breaking those patterns for good. Gabrielle Bernstein reveals that our relationship struggles aren't coincidences, but rather "spiritual assignments" that mirror our internal core wounds and beliefs. Drawing on the profound self-healing practices of Internal Family Systems (IFS) therapy, Gabrielle teaches you how to transform your greatest triggers into opportunities for growth, how to energetically shift a connection by "taking care of your side of the street," and how to raise your self-worth by learning to truly see yourself first. This episode is a deep dive into becoming an energetic match for the love you deserve while maintaining the clarity and boundaries needed for a miraculous life.Try Gabrielle's FREE guided meditation to heal relationships https://gabbybernstein.com/relationship/Read Gabrielle's #1 NYT Bestselling books: Self Help: This Is Your Chance to Change Your Life. http://bit.ly/4j1asmA Join Gabby for the Trust the Universe 21-day Challenge and learn how to co-create your dream life with the Universe http://bit.ly/4eTlKZxIf you feel you need additional support, please consult this list of safety, recovery, and mental health resources.Disclaimer: This podcast is intended to educate, inspire, and support you on your personal journey towards inner peace. I am not a psychologist or a medical doctor and do not offer any professional health or medical advice. If you are suffering from any psychological or medical conditions, please seek help from a qualified health professional.Sponsors:Use my code GABBY to save 20% at tonetoday.comGet 60% off your first order, plus free shipping, when you head to smalls.com/gabbyGet 15% off OneSkin with the code DEARGABBY at oneskin.co/DEARGABBY #oneskinpodProduced by Dear MediaSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

This week we discuss the demands of a home chef with a family that doesn't appreciate them (Gabby's close to striking). We get into a food moral dilemma and conclude with a discussion on feminism and the next generation of boys.  We always love to hear from you, so feel free to fire us over an email on hello@makinganeffortpodcast.com AND - Don't forget - if you fancy some bonus episodes, weekly episode commentary, community chat and BTS content, we'd love you to consider supporting us at www.patreon.com/makinganeffortpodcast

Miracles can happen on Christmas Eve.Based on a post by auguy86, in 2 parts. Listen to the ► Podcast at My First Time.“I; I don’t want to just be a charity case,” Ken replied. “If you do this, Gabrielle;”“It will only be because I want to. Promise,” Gabby replied, finishing his thought. “Now, your first lesson in kissing: making the move. I’m a young, attractive woman who has been making eye contact with you all night and finding every excuse in the book to touch you. You may not realize it, but when a woman does that, it means she’s ready for you to make the move. Try it on me, just like I did.”Mimicking Ken, Gabby closed her eyes, waiting for the moment that Ken would kiss her once more. He leaned in as she had done, trying to take his time and not rush anything. As he was about to kiss her, he remembered that agonizing wait when he could sense her almost on top of him. Pausing mere centimeters from her lips, he allowed the tension to build up for a few moments. Soon, a huge smile began to form on Gabby’s lips; she was enjoying this, and he hadn’t even touched her yet! Ken collected his courage and finally met her lips with his, moving them ever so slightly as he kissed her. He only had his instincts to guide him, but she didn’t seem to mind one bit.“Umm; that was very nice,” Gabby whispered as they parted. “Good job in mimicking my technique. Let’s try one more. This time, lick your lips just a bit before you kiss me, and try to let our mouths fit together like a puzzle. You can take my lower lip between yours, or I can take your lip between mine. Tilting your head to the side a bit is also a natural position. The possibilities are almost endless. When you’re ready, don’t be afraid to put your tongue in my mouth. In the future, you’ll want to be careful about doing this too soon, but for our purposes tonight, go right ahead.”Ken did as she instructed, and found that the increased moisture to be quite pleasant. It allowed each of their lips to slide along the other’s with little effort. All too soon, he felt Gabby take his lower lip in hers, sucking lightly and even nibbling for an instant. After she did this a second time, Ken took the hint and reciprocated in kind, eliciting a contented murmur from Gabby. As their kissing became more passionate, he could no longer resist the urge to taste this gorgeous woman. Still tentative, he pressed his tongue against the crease of her lips, which parted to allow him entry. Though he didn’t know what to do once he was in, he soon found himself enthralled in Gabby’s passions. Her tongue danced with his, exploring his mouth in a slow, methodical fashion. This gave him the perfect gauge to judge his own efforts by. After nearly twenty minutes of making out, they finally separated, their faces flushed from the experience.“Holy shit.” Ken sighed.“You, my friend, are one quick study. The next girl that kisses you may well get addicted and refuse to let you go,” Gabby agreed with a playful grin. Leaning back on the sofa, she reached down and unbuttoned the top button of her jeans, asking, “You ready to learn something else?”In spite of his hardening cock, Ken couldn’t help but feel like he was doing something he shouldn’t. “Look, you seriously don’t have to;”“I want to,” she said with confidence. “Ken, you are such a sweet, special guy, and I want to show you that. I want to prove to you how lucky a girl I would be to have a guy like you.”Would be? What’s that supposed to mean?“I’ve never made love to a virgin, Ken,” she continued. “But I know what I love in bed, and I think I can help you get quite good at this. You don’t have to do anything you don’t want to, but if you’ll allow me, I’d love nothing more than to take your virginity tonight.”Ken was torn. This woman certainly drove him crazy, but part of him worried this was all an elaborate setup. Women never came on to him like this, let alone one this beautiful! Then again, she hadn’t balked in the slightest in kissing him. Hell, she had even encouraged him to French kiss her. In spite of the fact that he had every reason to be distrusting after Jacqueline’s message, he recognized that she had shown him nothing but kindness and patience. He didn’t believe in destiny or fate, but if there was a moment in which he was supposed to lose his virginity, this had to be it.“Okay; I want to,” he whispered.“I’m glad,” she replied with a warm smile.Fumbling with his belt, he said, “I guess I’d better;”“There’s plenty of time, Ken,” Gabby reassured him. “If we do this, I want to do it right. I want to show you the proper way to take a girl around the world. That starts with what we were doing earlier, only this time, you can start removing my clothes in the process.”As Ken leaned in and resumed their kissing, Gabby guided his hands lower and slipped them underneath her sweater. He spent a few moments enjoying the warm sensation of skin-to-skin contact before tugging her sweater up. They separated for a moment so that Gabby could finish peeling her top off, revealing a simple, black silk bra. As they continued making out, Ken reached behind her, trying to decipher the key to unhooking the ever-hated bra.“Want some advice?” Gabby asked with a slight giggle.“Sure,” Ken signed, beginning to get frustrated.“Feel for the crease, then slip one finger under and one finger over. Squeeze together and rub your fingers until it unhooks.”Concentrating, Ken did as she instructed. The clasp itself was easy to find, and her descriptions were spot on. To his surprise, it only took one unsuccessful attempt before he managed to snap the garment open.“Impressive,” Gabby marveled.“Thanks, but that was all you. I’d be lost without your instructions.”“You’re a natural student; you take direction well. Ready for the next lesson?”“Oh yeah,” Ken said with anticipation.“Your kissing skills have grown by leaps and bounds in just a few minutes. Now you should remember that you don’t have to kiss just my lips. My cheeks, my neck, my shoulders; my entire body is your playground. Few things turn a woman on more than a man whose only desire is to worship every inch of her form.”With that, Gabby shrugged her shoulders and slipped her bra off, revealing her ample D-cup tits to Ken. He was utterly speechless at the sight he now beheld. They were not only large, but quite perky as well. Her tiny pink nipples, already hard from their making out, were the perfect accent to Gabby’s most notable assets. As he drank her in, he felt her guide his hand towards her, reaching him out to touch her tit. It barely fit into his hand, yet it was so soft and warm that it felt like it just belonged there. Taking a deep breath, Ken now reached in with both of his hands, squeezing her tits together and exploring every inch of their surface. Remembering her words from a moment ago, he leaned in once more and began to kiss his way from her lips down to her chest.“Yes; just like that.” she cooed.Arriving at the valley of her bosom, he made his way to one side, kissing her tit while also stimulating her nipple with his finger.“That’s so good, Ken; ooh, you can suck on them too,” she whispered with encouragement.Ken’s heart leapt at her suggestion, and he moved to take one of her tiny nipples in his mouth. He sucked with eagerness at first, but Gabby soon coaxed him to go slower.“Careful there; be gentle.”“Sorry.”“Quite alright, they’re just a bit sensitive,” she said with a sweet giggle.Ken spent quite some time lapping at her tits, alternating sides every so often. At first, Gabby advised him on when to change so as not to over stimulate one side or the other. Soon, though, Ken was moving back and forth all on his own, driving her wild with lust in the process. After several minutes of this, she lifted his head up, a wicked grin on her face.“Ready for the big reveal?” she asked, lowering the zipper of her jeans.“Uh; uh huh.”Lifting her hips up, Gabby slipped her jeans over her curvy ass and down her long legs before kicking them off with her boots. She then turned to recline back on the sofa, spreading her legs a tiny bit. The smoldering come hither look she gave Ken was enough to bring any man to his knees.“Come on, Ken; you’ve got a Christmas present to open.”Ken’s mouth went dry as he stared at her black thong panties, mesmerized in disbelief by what was about to happen. With trembling hands, he slipped his fingers into her waistband and slid the silky garment off, revealing Gabby’s shaven pussy at last. In that moment, Ken had completely forgotten that he was still wearing all his clothes.“I just love the way you’re looking at me,” Gabby breathed, breaking his trance. “It’s like you won the lottery or something.”“I; think I did.”“So sweet. Now then, time to learn how to really make a woman happy. Most women are at least willing to engage in oral sex, but you always need to give at least as much as you receive. It’s only polite. And there’s no better way to make a woman want to suck your cock; than to eat her pussy without prompting. With that said.”Gabby now spread her legs wide for him, beckoning him to explore her delectable womanhood. Following a trail she laid with her fingers, Ken began to kiss his way up her leg and inner thigh. After repeating the action on her other leg, he arrived at her soaked pussy, breathing in the musky aroma seeping from within her.“Spread my lips, Ken,” Gabby whispered.Using a gentle touch, he did as she asked, gazing deep into her slick tunnel. He soon leaned forward, touching his tongue to the folds of her labia. She tasted different than he had expected, perhaps a bit salty, but nothing unpleasant in Ken’s mind. He continued to taste and tease her lips for a few moments, and she began to squirm and writhe under him in pleasure.“Oh, yes; that’s just right, Ken; you can move a little higher, too. See that little bump there? That’s my clit. She’s sensitive, but if you pay enough attention to her; something good is bound to happen.”He tilted his head upwards a bit, running his tongue along her lips as he arrived at her clit. Flicking the nub a couple of times, he was surprised at just how strong Gabby’s reaction was. Ken liked that. She was having the time of her life, and it was all because of him. Feeling a twinge of confidence, he redoubled his efforts and began lapping at her clit again and again, never giving her a chance to rest.“Yes; yes, that’s fucking incredible!” she cried out.As Gabby’s hips began to buck, Ken looped his arms around her thighs on instinct, helping her to remain still. He continued his worshipping of her womanhood, savoring every drop of her juices as she squirmed and squealed in delight. Soon, he began to sense that her thrashing was reaching a crescendo and an ultimate plateau. He received almost immediate verbal confirmation of this.“Holy shit; Fuck that’s awesome! Oh, Ken don’t stop; don’t; stop; please don’t stop don’t stop don’t stop; ah!”Ken knew in an academic sense that women could achieve powerful orgasms. Still, he had never actually seen it happen, let alone experienced it by his hand, or rather his tongue. Yet lying beneath him was the most beautiful woman he had ever met in his life, and she was becoming even more beautiful by the second as her body erupted in ecstasy. The look of pleasure on her face as her eyes fluttered closed was awe-inspiring. A few final licks to her pussy, and she gently pushed his face away from her crotch.“That’s quite enough; but oh so wonderful.” she sighed. “You’re a natural, Ken.”“Thanks. That’s; got to be the hottest thing I’ve ever seen in my life. Seeing you lose control like that, it was surreal.”“So sweet,” she said, sitting up straight on the sofa. “For all your supposed awkwardness, you sure know how to pay a girl a compliment.” She leaned forward, planting a long, slow kiss on his lips. As they parted, she whispered, “Ready for your due reward?”With a slight gasp, he replied, “Oh, hell yes.”Gabby stood from the sofa, smiling the entire time. Reaching behind the armrest of the sofa, she pulled out a dark blue sleeping bag and began to spread it out on the thick rug in front of the fire.“It’s a tradition,” she explained, seeing the look of confusion on Ken’s face. “When I was a little girl, I swore I’d catch Santa in the act by sleeping next to the tree. He’d never be able to sneak past me. Well, my parents told me to go for it, but that it wouldn’t work; he’s too good. Sure enough, he had come and gone the next morning. He even left a note next to my pillow that said, ‘Nice try, Gabby. Merry Christmas.’ Ever since then, I’ve slept by the tree every Christmas Eve.”“Love it,” Ken grinned.By now, she had finished spreading the sleeping bag out on the floor and affixed a couple of pillows at the head for them. As it was designed for one person, she had opened it completely and laid it out flat, making it large enough for two to lie on. Seeing what she was doing, Ken grabbed a large throw blanket from the sofa to cover up with.“Why, thank you,” she said. “But don’t you think you’re a bit overdressed?”“Huh?” Ken had been so entranced with Gabby’s naked body that he’d forgotten that he was still wearing his clothes. “Oh, uh, I guess so.”“Can I help with that?” she asked with a mischievous grin.“Sure.”Gabby sauntered over to him, wrapping him in a warm hug as they stood next to the fireplace. After kissing his lips, she moved to his cheek and neck, just as he had done to her before. As she began to drive him crazy, she slipped her fingers into his tee shirt and pulled it off of him, exposing his bare chest to her. Now with a new playground to explore, Gabby continued from where she left off. She first lingered around his neck and shoulders, then down his chest before finally reaching his stomach. As she knelt before him, she unbuckled his belt and slid his jeans and boxers down to his ankles, freeing his rock hard cock at last.Ken was not large my most standards, being only about five inches in length at full staff, but to Gabby he was perfect. She had no hesitation as she began to lightly stroke his length in her hand, and soon began to take him in her mouth bit-by-bit. Ken was in blissful agony; not only was he receiving is first blowjob, but he also had to keep from exploding too soon, all while concentrating on standing still. She sucked him for a few seconds more before releasing him.“If you get close, let me know, okay? I want this inside my pussy, too.”Ken could only nod in reply. She soon resumed her pleasuring of his member, sucking him with gleeful determination. He had been so good to her tonight; she only wanted to reward his efforts. Slowing her pace, she gazed up at him with her smoldering eyes, her pretty face framed by her long blonde hair. As Ken began to lose himself in her beauty, he also felt a familiar bubbling up in the pit of his stomach. Though he panicked for a moment, he soon had the presence of mind to tap Gabby on the forehead.“I think you’d better slow down,” he stammered.Releasing his cock from her mouth with a pop, Gabby grinned and replied, “Good. Because I think it’s time for me to take your virginity.”After switching off the gas logs, she stretched out on the open sleeping bag and held part of the blanket up, beckoning Ken to slide in with her. He did so with eagerness, though was still nervous as hell; he had no idea what he was doing! Sensing his doubts, Gabby spoke with soft confidence and reassurance.“Let’s go you on top to start. That way you can control it so you don’t go off too soon. Honestly, though, don’t worry about stamina. You’ve already lasted through one of my blowjobs, which is no small feat, if I do say so myself. You ready?”“Um, yeah; I think so. But do we need any; protection? I don’t have a condom or anything.”With a warm smile, she replied, “Don’t ever change, Ken. Sweet, humble, and considerate, that’s what you are. I don’t have any diseases per my last doctor’s visit two months ago, and I know you’re a virgin so I don’t think there’s any concern.”“That’s good. But; what if you get pregnant? I’m not sure I’d be able to pull out in time.”“Well,” she paused, her smile becoming more bittersweet. “It’s a long story, but trust me when I say that there’s no risk of me becoming pregnant. We’re clear to let loose with this, as long as you’re comfortable with that, of course.”“I am. I just; wanted to be sure.”“Thank you, Ken. Now, if you please, my pussy is aching for your cock, and you’d best make her happy.”Positioning his pelvic region between her legs, Ken attempted to push into her, but his slick cock merely grazed the surface before slipping up to her belly. Gabby just smiled and reached down, taking a gentle grip on his cock with her hand and guiding him to the entrance of her pussy. Feeling a bit of give, he followed his instincts and penetrated her at long last, his virginity melting away in the process. She was divine, far tighter than Ken had ever imagined in his wildest dreams and fantasies.“Oh Ken; that’s just where you belong,” she cooed in satisfaction.“Holy fuck; so tight.” he could only reply.Ken began to thrust in and out of her, keeping his tempo moderate at the start to get a feel for how sensitive he was. The sensations of making love to this goddess were only enhanced by the look of sheer enjoyment in Gabby’s eyes. He prayed that he would be able to last and enjoy it all, even if only for a few minutes. As he continued thrusting into her, Gabby began to get a mischievous look in her eyes.“You’re thinking something,” Ken observed.“Uh huh. Wanna learn a trick that’ll drive any girl nuts?”“Sure.”“Come up on your knees and keep your torso straight up. Try to get to where you can keep yourself inside me without having to balance on your arms.”“Like this?” he asked, relaxing back on his folded knees.“Exactly. You can also stretch my leg out against your chest to help you balance.”“Very nice,” he said as he followed her instructions.&ld

Miracles can happen on Christmas Eve.Based on a post by auguy86, in 2 parts. Listen to the ► Podcast at My First Time.“I; I don’t want to just be a charity case,” Ken replied. “If you do this, Gabrielle;”“It will only be because I want to. Promise,” Gabby replied, finishing his thought. “Now, your first lesson in kissing: making the move. I’m a young, attractive woman who has been making eye contact with you all night and finding every excuse in the book to touch you. You may not realize it, but when a woman does that, it means she’s ready for you to make the move. Try it on me, just like I did.”Mimicking Ken, Gabby closed her eyes, waiting for the moment that Ken would kiss her once more. He leaned in as she had done, trying to take his time and not rush anything. As he was about to kiss her, he remembered that agonizing wait when he could sense her almost on top of him. Pausing mere centimeters from her lips, he allowed the tension to build up for a few moments. Soon, a huge smile began to form on Gabby’s lips; she was enjoying this, and he hadn’t even touched her yet! Ken collected his courage and finally met her lips with his, moving them ever so slightly as he kissed her. He only had his instincts to guide him, but she didn’t seem to mind one bit.“Umm; that was very nice,” Gabby whispered as they parted. “Good job in mimicking my technique. Let’s try one more. This time, lick your lips just a bit before you kiss me, and try to let our mouths fit together like a puzzle. You can take my lower lip between yours, or I can take your lip between mine. Tilting your head to the side a bit is also a natural position. The possibilities are almost endless. When you’re ready, don’t be afraid to put your tongue in my mouth. In the future, you’ll want to be careful about doing this too soon, but for our purposes tonight, go right ahead.”Ken did as she instructed, and found that the increased moisture to be quite pleasant. It allowed each of their lips to slide along the other’s with little effort. All too soon, he felt Gabby take his lower lip in hers, sucking lightly and even nibbling for an instant. After she did this a second time, Ken took the hint and reciprocated in kind, eliciting a contented murmur from Gabby. As their kissing became more passionate, he could no longer resist the urge to taste this gorgeous woman. Still tentative, he pressed his tongue against the crease of her lips, which parted to allow him entry. Though he didn’t know what to do once he was in, he soon found himself enthralled in Gabby’s passions. Her tongue danced with his, exploring his mouth in a slow, methodical fashion. This gave him the perfect gauge to judge his own efforts by. After nearly twenty minutes of making out, they finally separated, their faces flushed from the experience.“Holy shit.” Ken sighed.“You, my friend, are one quick study. The next girl that kisses you may well get addicted and refuse to let you go,” Gabby agreed with a playful grin. Leaning back on the sofa, she reached down and unbuttoned the top button of her jeans, asking, “You ready to learn something else?”In spite of his hardening cock, Ken couldn’t help but feel like he was doing something he shouldn’t. “Look, you seriously don’t have to;”“I want to,” she said with confidence. “Ken, you are such a sweet, special guy, and I want to show you that. I want to prove to you how lucky a girl I would be to have a guy like you.”Would be? What’s that supposed to mean?“I’ve never made love to a virgin, Ken,” she continued. “But I know what I love in bed, and I think I can help you get quite good at this. You don’t have to do anything you don’t want to, but if you’ll allow me, I’d love nothing more than to take your virginity tonight.”Ken was torn. This woman certainly drove him crazy, but part of him worried this was all an elaborate setup. Women never came on to him like this, let alone one this beautiful! Then again, she hadn’t balked in the slightest in kissing him. Hell, she had even encouraged him to French kiss her. In spite of the fact that he had every reason to be distrusting after Jacqueline’s message, he recognized that she had shown him nothing but kindness and patience. He didn’t believe in destiny or fate, but if there was a moment in which he was supposed to lose his virginity, this had to be it.“Okay; I want to,” he whispered.“I’m glad,” she replied with a warm smile.Fumbling with his belt, he said, “I guess I’d better;”“There’s plenty of time, Ken,” Gabby reassured him. “If we do this, I want to do it right. I want to show you the proper way to take a girl around the world. That starts with what we were doing earlier, only this time, you can start removing my clothes in the process.”As Ken leaned in and resumed their kissing, Gabby guided his hands lower and slipped them underneath her sweater. He spent a few moments enjoying the warm sensation of skin-to-skin contact before tugging her sweater up. They separated for a moment so that Gabby could finish peeling her top off, revealing a simple, black silk bra. As they continued making out, Ken reached behind her, trying to decipher the key to unhooking the ever-hated bra.“Want some advice?” Gabby asked with a slight giggle.“Sure,” Ken signed, beginning to get frustrated.“Feel for the crease, then slip one finger under and one finger over. Squeeze together and rub your fingers until it unhooks.”Concentrating, Ken did as she instructed. The clasp itself was easy to find, and her descriptions were spot on. To his surprise, it only took one unsuccessful attempt before he managed to snap the garment open.“Impressive,” Gabby marveled.“Thanks, but that was all you. I’d be lost without your instructions.”“You’re a natural student; you take direction well. Ready for the next lesson?”“Oh yeah,” Ken said with anticipation.“Your kissing skills have grown by leaps and bounds in just a few minutes. Now you should remember that you don’t have to kiss just my lips. My cheeks, my neck, my shoulders; my entire body is your playground. Few things turn a woman on more than a man whose only desire is to worship every inch of her form.”With that, Gabby shrugged her shoulders and slipped her bra off, revealing her ample D-cup tits to Ken. He was utterly speechless at the sight he now beheld. They were not only large, but quite perky as well. Her tiny pink nipples, already hard from their making out, were the perfect accent to Gabby’s most notable assets. As he drank her in, he felt her guide his hand towards her, reaching him out to touch her tit. It barely fit into his hand, yet it was so soft and warm that it felt like it just belonged there. Taking a deep breath, Ken now reached in with both of his hands, squeezing her tits together and exploring every inch of their surface. Remembering her words from a moment ago, he leaned in once more and began to kiss his way from her lips down to her chest.“Yes; just like that.” she cooed.Arriving at the valley of her bosom, he made his way to one side, kissing her tit while also stimulating her nipple with his finger.“That’s so good, Ken; ooh, you can suck on them too,” she whispered with encouragement.Ken’s heart leapt at her suggestion, and he moved to take one of her tiny nipples in his mouth. He sucked with eagerness at first, but Gabby soon coaxed him to go slower.“Careful there; be gentle.”“Sorry.”“Quite alright, they’re just a bit sensitive,” she said with a sweet giggle.Ken spent quite some time lapping at her tits, alternating sides every so often. At first, Gabby advised him on when to change so as not to over stimulate one side or the other. Soon, though, Ken was moving back and forth all on his own, driving her wild with lust in the process. After several minutes of this, she lifted his head up, a wicked grin on her face.“Ready for the big reveal?” she asked, lowering the zipper of her jeans.“Uh; uh huh.”Lifting her hips up, Gabby slipped her jeans over her curvy ass and down her long legs before kicking them off with her boots. She then turned to recline back on the sofa, spreading her legs a tiny bit. The smoldering come hither look she gave Ken was enough to bring any man to his knees.“Come on, Ken; you’ve got a Christmas present to open.”Ken’s mouth went dry as he stared at her black thong panties, mesmerized in disbelief by what was about to happen. With trembling hands, he slipped his fingers into her waistband and slid the silky garment off, revealing Gabby’s shaven pussy at last. In that moment, Ken had completely forgotten that he was still wearing all his clothes.“I just love the way you’re looking at me,” Gabby breathed, breaking his trance. “It’s like you won the lottery or something.”“I; think I did.”“So sweet. Now then, time to learn how to really make a woman happy. Most women are at least willing to engage in oral sex, but you always need to give at least as much as you receive. It’s only polite. And there’s no better way to make a woman want to suck your cock; than to eat her pussy without prompting. With that said.”Gabby now spread her legs wide for him, beckoning him to explore her delectable womanhood. Following a trail she laid with her fingers, Ken began to kiss his way up her leg and inner thigh. After repeating the action on her other leg, he arrived at her soaked pussy, breathing in the musky aroma seeping from within her.“Spread my lips, Ken,” Gabby whispered.Using a gentle touch, he did as she asked, gazing deep into her slick tunnel. He soon leaned forward, touching his tongue to the folds of her labia. She tasted different than he had expected, perhaps a bit salty, but nothing unpleasant in Ken’s mind. He continued to taste and tease her lips for a few moments, and she began to squirm and writhe under him in pleasure.“Oh, yes; that’s just right, Ken; you can move a little higher, too. See that little bump there? That’s my clit. She’s sensitive, but if you pay enough attention to her; something good is bound to happen.”He tilted his head upwards a bit, running his tongue along her lips as he arrived at her clit. Flicking the nub a couple of times, he was surprised at just how strong Gabby’s reaction was. Ken liked that. She was having the time of her life, and it was all because of him. Feeling a twinge of confidence, he redoubled his efforts and began lapping at her clit again and again, never giving her a chance to rest.“Yes; yes, that’s fucking incredible!” she cried out.As Gabby’s hips began to buck, Ken looped his arms around her thighs on instinct, helping her to remain still. He continued his worshipping of her womanhood, savoring every drop of her juices as she squirmed and squealed in delight. Soon, he began to sense that her thrashing was reaching a crescendo and an ultimate plateau. He received almost immediate verbal confirmation of this.“Holy shit; Fuck that’s awesome! Oh, Ken don’t stop; don’t; stop; please don’t stop don’t stop don’t stop; ah!”Ken knew in an academic sense that women could achieve powerful orgasms. Still, he had never actually seen it happen, let alone experienced it by his hand, or rather his tongue. Yet lying beneath him was the most beautiful woman he had ever met in his life, and she was becoming even more beautiful by the second as her body erupted in ecstasy. The look of pleasure on her face as her eyes fluttered closed was awe-inspiring. A few final licks to her pussy, and she gently pushed his face away from her crotch.“That’s quite enough; but oh so wonderful.” she sighed. “You’re a natural, Ken.”“Thanks. That’s; got to be the hottest thing I’ve ever seen in my life. Seeing you lose control like that, it was surreal.”“So sweet,” she said, sitting up straight on the sofa. “For all your supposed awkwardness, you sure know how to pay a girl a compliment.” She leaned forward, planting a long, slow kiss on his lips. As they parted, she whispered, “Ready for your due reward?”With a slight gasp, he replied, “Oh, hell yes.”Gabby stood from the sofa, smiling the entire time. Reaching behind the armrest of the sofa, she pulled out a dark blue sleeping bag and began to spread it out on the thick rug in front of the fire.“It’s a tradition,” she explained, seeing the look of confusion on Ken’s face. “When I was a little girl, I swore I’d catch Santa in the act by sleeping next to the tree. He’d never be able to sneak past me. Well, my parents told me to go for it, but that it wouldn’t work; he’s too good. Sure enough, he had come and gone the next morning. He even left a note next to my pillow that said, ‘Nice try, Gabby. Merry Christmas.’ Ever since then, I’ve slept by the tree every Christmas Eve.”“Love it,” Ken grinned.By now, she had finished spreading the sleeping bag out on the floor and affixed a couple of pillows at the head for them. As it was designed for one person, she had opened it completely and laid it out flat, making it large enough for two to lie on. Seeing what she was doing, Ken grabbed a large throw blanket from the sofa to cover up with.“Why, thank you,” she said. “But don’t you think you’re a bit overdressed?”“Huh?” Ken had been so entranced with Gabby’s naked body that he’d forgotten that he was still wearing his clothes. “Oh, uh, I guess so.”“Can I help with that?” she asked with a mischievous grin.“Sure.”Gabby sauntered over to him, wrapping him in a warm hug as they stood next to the fireplace. After kissing his lips, she moved to his cheek and neck, just as he had done to her before. As she began to drive him crazy, she slipped her fingers into his tee shirt and pulled it off of him, exposing his bare chest to her. Now with a new playground to explore, Gabby continued from where she left off. She first lingered around his neck and shoulders, then down his chest before finally reaching his stomach. As she knelt before him, she unbuckled his belt and slid his jeans and boxers down to his ankles, freeing his rock hard cock at last.Ken was not large my most standards, being only about five inches in length at full staff, but to Gabby he was perfect. She had no hesitation as she began to lightly stroke his length in her hand, and soon began to take him in her mouth bit-by-bit. Ken was in blissful agony; not only was he receiving is first blowjob, but he also had to keep from exploding too soon, all while concentrating on standing still. She sucked him for a few seconds more before releasing him.“If you get close, let me know, okay? I want this inside my pussy, too.”Ken could only nod in reply. She soon resumed her pleasuring of his member, sucking him with gleeful determination. He had been so good to her tonight; she only wanted to reward his efforts. Slowing her pace, she gazed up at him with her smoldering eyes, her pretty face framed by her long blonde hair. As Ken began to lose himself in her beauty, he also felt a familiar bubbling up in the pit of his stomach. Though he panicked for a moment, he soon had the presence of mind to tap Gabby on the forehead.“I think you’d better slow down,” he stammered.Releasing his cock from her mouth with a pop, Gabby grinned and replied, “Good. Because I think it’s time for me to take your virginity.”After switching off the gas logs, she stretched out on the open sleeping bag and held part of the blanket up, beckoning Ken to slide in with her. He did so with eagerness, though was still nervous as hell; he had no idea what he was doing! Sensing his doubts, Gabby spoke with soft confidence and reassurance.“Let’s go you on top to start. That way you can control it so you don’t go off too soon. Honestly, though, don’t worry about stamina. You’ve already lasted through one of my blowjobs, which is no small feat, if I do say so myself. You ready?”“Um, yeah; I think so. But do we need any; protection? I don’t have a condom or anything.”With a warm smile, she replied, “Don’t ever change, Ken. Sweet, humble, and considerate, that’s what you are. I don’t have any diseases per my last doctor’s visit two months ago, and I know you’re a virgin so I don’t think there’s any concern.”“That’s good. But; what if you get pregnant? I’m not sure I’d be able to pull out in time.”“Well,” she paused, her smile becoming more bittersweet. “It’s a long story, but trust me when I say that there’s no risk of me becoming pregnant. We’re clear to let loose with this, as long as you’re comfortable with that, of course.”“I am. I just; wanted to be sure.”“Thank you, Ken. Now, if you please, my pussy is aching for your cock, and you’d best make her happy.”Positioning his pelvic region between her legs, Ken attempted to push into her, but his slick cock merely grazed the surface before slipping up to her belly. Gabby just smiled and reached down, taking a gentle grip on his cock with her hand and guiding him to the entrance of her pussy. Feeling a bit of give, he followed his instincts and penetrated her at long last, his virginity melting away in the process. She was divine, far tighter than Ken had ever imagined in his wildest dreams and fantasies.“Oh Ken; that’s just where you belong,” she cooed in satisfaction.“Holy fuck; so tight.” he could only reply.Ken began to thrust in and out of her, keeping his tempo moderate at the start to get a feel for how sensitive he was. The sensations of making love to this goddess were only enhanced by the look of sheer enjoyment in Gabby’s eyes. He prayed that he would be able to last and enjoy it all, even if only for a few minutes. As he continued thrusting into her, Gabby began to get a mischievous look in her eyes.“You’re thinking something,” Ken observed.“Uh huh. Wanna learn a trick that’ll drive any girl nuts?”“Sure.”“Come up on your knees and keep your torso straight up. Try to get to where you can keep yourself inside me without having to balance on your arms.”“Like this?” he asked, relaxing back on his folded knees.“Exactly. You can also stretch my leg out against your chest to help you balance.”“Very nice,” he said as he followed her instructions.&ld

Miracles can happen on Christmas Eve.Based on a post by auguy86, in 2 parts. Listen to the ► Podcast at My First Time.“I; I don’t want to just be a charity case,” Ken replied. “If you do this, Gabrielle;”“It will only be because I want to. Promise,” Gabby replied, finishing his thought. “Now, your first lesson in kissing: making the move. I’m a young, attractive woman who has been making eye contact with you all night and finding every excuse in the book to touch you. You may not realize it, but when a woman does that, it means she’s ready for you to make the move. Try it on me, just like I did.”Mimicking Ken, Gabby closed her eyes, waiting for the moment that Ken would kiss her once more. He leaned in as she had done, trying to take his time and not rush anything. As he was about to kiss her, he remembered that agonizing wait when he could sense her almost on top of him. Pausing mere centimeters from her lips, he allowed the tension to build up for a few moments. Soon, a huge smile began to form on Gabby’s lips; she was enjoying this, and he hadn’t even touched her yet! Ken collected his courage and finally met her lips with his, moving them ever so slightly as he kissed her. He only had his instincts to guide him, but she didn’t seem to mind one bit.“Umm; that was very nice,” Gabby whispered as they parted. “Good job in mimicking my technique. Let’s try one more. This time, lick your lips just a bit before you kiss me, and try to let our mouths fit together like a puzzle. You can take my lower lip between yours, or I can take your lip between mine. Tilting your head to the side a bit is also a natural position. The possibilities are almost endless. When you’re ready, don’t be afraid to put your tongue in my mouth. In the future, you’ll want to be careful about doing this too soon, but for our purposes tonight, go right ahead.”Ken did as she instructed, and found that the increased moisture to be quite pleasant. It allowed each of their lips to slide along the other’s with little effort. All too soon, he felt Gabby take his lower lip in hers, sucking lightly and even nibbling for an instant. After she did this a second time, Ken took the hint and reciprocated in kind, eliciting a contented murmur from Gabby. As their kissing became more passionate, he could no longer resist the urge to taste this gorgeous woman. Still tentative, he pressed his tongue against the crease of her lips, which parted to allow him entry. Though he didn’t know what to do once he was in, he soon found himself enthralled in Gabby’s passions. Her tongue danced with his, exploring his mouth in a slow, methodical fashion. This gave him the perfect gauge to judge his own efforts by. After nearly twenty minutes of making out, they finally separated, their faces flushed from the experience.“Holy shit.” Ken sighed.“You, my friend, are one quick study. The next girl that kisses you may well get addicted and refuse to let you go,” Gabby agreed with a playful grin. Leaning back on the sofa, she reached down and unbuttoned the top button of her jeans, asking, “You ready to learn something else?”In spite of his hardening cock, Ken couldn’t help but feel like he was doing something he shouldn’t. “Look, you seriously don’t have to;”“I want to,” she said with confidence. “Ken, you are such a sweet, special guy, and I want to show you that. I want to prove to you how lucky a girl I would be to have a guy like you.”Would be? What’s that supposed to mean?“I’ve never made love to a virgin, Ken,” she continued. “But I know what I love in bed, and I think I can help you get quite good at this. You don’t have to do anything you don’t want to, but if you’ll allow me, I’d love nothing more than to take your virginity tonight.”Ken was torn. This woman certainly drove him crazy, but part of him worried this was all an elaborate setup. Women never came on to him like this, let alone one this beautiful! Then again, she hadn’t balked in the slightest in kissing him. Hell, she had even encouraged him to French kiss her. In spite of the fact that he had every reason to be distrusting after Jacqueline’s message, he recognized that she had shown him nothing but kindness and patience. He didn’t believe in destiny or fate, but if there was a moment in which he was supposed to lose his virginity, this had to be it.“Okay; I want to,” he whispered.“I’m glad,” she replied with a warm smile.Fumbling with his belt, he said, “I guess I’d better;”“There’s plenty of time, Ken,” Gabby reassured him. “If we do this, I want to do it right. I want to show you the proper way to take a girl around the world. That starts with what we were doing earlier, only this time, you can start removing my clothes in the process.”As Ken leaned in and resumed their kissing, Gabby guided his hands lower and slipped them underneath her sweater. He spent a few moments enjoying the warm sensation of skin-to-skin contact before tugging her sweater up. They separated for a moment so that Gabby could finish peeling her top off, revealing a simple, black silk bra. As they continued making out, Ken reached behind her, trying to decipher the key to unhooking the ever-hated bra.“Want some advice?” Gabby asked with a slight giggle.“Sure,” Ken signed, beginning to get frustrated.“Feel for the crease, then slip one finger under and one finger over. Squeeze together and rub your fingers until it unhooks.”Concentrating, Ken did as she instructed. The clasp itself was easy to find, and her descriptions were spot on. To his surprise, it only took one unsuccessful attempt before he managed to snap the garment open.“Impressive,” Gabby marveled.“Thanks, but that was all you. I’d be lost without your instructions.”“You’re a natural student; you take direction well. Ready for the next lesson?”“Oh yeah,” Ken said with anticipation.“Your kissing skills have grown by leaps and bounds in just a few minutes. Now you should remember that you don’t have to kiss just my lips. My cheeks, my neck, my shoulders; my entire body is your playground. Few things turn a woman on more than a man whose only desire is to worship every inch of her form.”With that, Gabby shrugged her shoulders and slipped her bra off, revealing her ample D-cup tits to Ken. He was utterly speechless at the sight he now beheld. They were not only large, but quite perky as well. Her tiny pink nipples, already hard from their making out, were the perfect accent to Gabby’s most notable assets. As he drank her in, he felt her guide his hand towards her, reaching him out to touch her tit. It barely fit into his hand, yet it was so soft and warm that it felt like it just belonged there. Taking a deep breath, Ken now reached in with both of his hands, squeezing her tits together and exploring every inch of their surface. Remembering her words from a moment ago, he leaned in once more and began to kiss his way from her lips down to her chest.“Yes; just like that.” she cooed.Arriving at the valley of her bosom, he made his way to one side, kissing her tit while also stimulating her nipple with his finger.“That’s so good, Ken; ooh, you can suck on them too,” she whispered with encouragement.Ken’s heart leapt at her suggestion, and he moved to take one of her tiny nipples in his mouth. He sucked with eagerness at first, but Gabby soon coaxed him to go slower.“Careful there; be gentle.”“Sorry.”“Quite alright, they’re just a bit sensitive,” she said with a sweet giggle.Ken spent quite some time lapping at her tits, alternating sides every so often. At first, Gabby advised him on when to change so as not to over stimulate one side or the other. Soon, though, Ken was moving back and forth all on his own, driving her wild with lust in the process. After several minutes of this, she lifted his head up, a wicked grin on her face.“Ready for the big reveal?” she asked, lowering the zipper of her jeans.“Uh; uh huh.”Lifting her hips up, Gabby slipped her jeans over her curvy ass and down her long legs before kicking them off with her boots. She then turned to recline back on the sofa, spreading her legs a tiny bit. The smoldering come hither look she gave Ken was enough to bring any man to his knees.“Come on, Ken; you’ve got a Christmas present to open.”Ken’s mouth went dry as he stared at her black thong panties, mesmerized in disbelief by what was about to happen. With trembling hands, he slipped his fingers into her waistband and slid the silky garment off, revealing Gabby’s shaven pussy at last. In that moment, Ken had completely forgotten that he was still wearing all his clothes.“I just love the way you’re looking at me,” Gabby breathed, breaking his trance. “It’s like you won the lottery or something.”“I; think I did.”“So sweet. Now then, time to learn how to really make a woman happy. Most women are at least willing to engage in oral sex, but you always need to give at least as much as you receive. It’s only polite. And there’s no better way to make a woman want to suck your cock; than to eat her pussy without prompting. With that said.”Gabby now spread her legs wide for him, beckoning him to explore her delectable womanhood. Following a trail she laid with her fingers, Ken began to kiss his way up her leg and inner thigh. After repeating the action on her other leg, he arrived at her soaked pussy, breathing in the musky aroma seeping from within her.“Spread my lips, Ken,” Gabby whispered.Using a gentle touch, he did as she asked, gazing deep into her slick tunnel. He soon leaned forward, touching his tongue to the folds of her labia. She tasted different than he had expected, perhaps a bit salty, but nothing unpleasant in Ken’s mind. He continued to taste and tease her lips for a few moments, and she began to squirm and writhe under him in pleasure.“Oh, yes; that’s just right, Ken; you can move a little higher, too. See that little bump there? That’s my clit. She’s sensitive, but if you pay enough attention to her; something good is bound to happen.”He tilted his head upwards a bit, running his tongue along her lips as he arrived at her clit. Flicking the nub a couple of times, he was surprised at just how strong Gabby’s reaction was. Ken liked that. She was having the time of her life, and it was all because of him. Feeling a twinge of confidence, he redoubled his efforts and began lapping at her clit again and again, never giving her a chance to rest.“Yes; yes, that’s fucking incredible!” she cried out.As Gabby’s hips began to buck, Ken looped his arms around her thighs on instinct, helping her to remain still. He continued his worshipping of her womanhood, savoring every drop of her juices as she squirmed and squealed in delight. Soon, he began to sense that her thrashing was reaching a crescendo and an ultimate plateau. He received almost immediate verbal confirmation of this.“Holy shit; Fuck that’s awesome! Oh, Ken don’t stop; don’t; stop; please don’t stop don’t stop don’t stop; ah!”Ken knew in an academic sense that women could achieve powerful orgasms. Still, he had never actually seen it happen, let alone experienced it by his hand, or rather his tongue. Yet lying beneath him was the most beautiful woman he had ever met in his life, and she was becoming even more beautiful by the second as her body erupted in ecstasy. The look of pleasure on her face as her eyes fluttered closed was awe-inspiring. A few final licks to her pussy, and she gently pushed his face away from her crotch.“That’s quite enough; but oh so wonderful.” she sighed. “You’re a natural, Ken.”“Thanks. That’s; got to be the hottest thing I’ve ever seen in my life. Seeing you lose control like that, it was surreal.”“So sweet,” she said, sitting up straight on the sofa. “For all your supposed awkwardness, you sure know how to pay a girl a compliment.” She leaned forward, planting a long, slow kiss on his lips. As they parted, she whispered, “Ready for your due reward?”With a slight gasp, he replied, “Oh, hell yes.”Gabby stood from the sofa, smiling the entire time. Reaching behind the armrest of the sofa, she pulled out a dark blue sleeping bag and began to spread it out on the thick rug in front of the fire.“It’s a tradition,” she explained, seeing the look of confusion on Ken’s face. “When I was a little girl, I swore I’d catch Santa in the act by sleeping next to the tree. He’d never be able to sneak past me. Well, my parents told me to go for it, but that it wouldn’t work; he’s too good. Sure enough, he had come and gone the next morning. He even left a note next to my pillow that said, ‘Nice try, Gabby. Merry Christmas.’ Ever since then, I’ve slept by the tree every Christmas Eve.”“Love it,” Ken grinned.By now, she had finished spreading the sleeping bag out on the floor and affixed a couple of pillows at the head for them. As it was designed for one person, she had opened it completely and laid it out flat, making it large enough for two to lie on. Seeing what she was doing, Ken grabbed a large throw blanket from the sofa to cover up with.“Why, thank you,” she said. “But don’t you think you’re a bit overdressed?”“Huh?” Ken had been so entranced with Gabby’s naked body that he’d forgotten that he was still wearing his clothes. “Oh, uh, I guess so.”“Can I help with that?” she asked with a mischievous grin.“Sure.”Gabby sauntered over to him, wrapping him in a warm hug as they stood next to the fireplace. After kissing his lips, she moved to his cheek and neck, just as he had done to her before. As she began to drive him crazy, she slipped her fingers into his tee shirt and pulled it off of him, exposing his bare chest to her. Now with a new playground to explore, Gabby continued from where she left off. She first lingered around his neck and shoulders, then down his chest before finally reaching his stomach. As she knelt before him, she unbuckled his belt and slid his jeans and boxers down to his ankles, freeing his rock hard cock at last.Ken was not large my most standards, being only about five inches in length at full staff, but to Gabby he was perfect. She had no hesitation as she began to lightly stroke his length in her hand, and soon began to take him in her mouth bit-by-bit. Ken was in blissful agony; not only was he receiving is first blowjob, but he also had to keep from exploding too soon, all while concentrating on standing still. She sucked him for a few seconds more before releasing him.“If you get close, let me know, okay? I want this inside my pussy, too.”Ken could only nod in reply. She soon resumed her pleasuring of his member, sucking him with gleeful determination. He had been so good to her tonight; she only wanted to reward his efforts. Slowing her pace, she gazed up at him with her smoldering eyes, her pretty face framed by her long blonde hair. As Ken began to lose himself in her beauty, he also felt a familiar bubbling up in the pit of his stomach. Though he panicked for a moment, he soon had the presence of mind to tap Gabby on the forehead.“I think you’d better slow down,” he stammered.Releasing his cock from her mouth with a pop, Gabby grinned and replied, “Good. Because I think it’s time for me to take your virginity.”After switching off the gas logs, she stretched out on the open sleeping bag and held part of the blanket up, beckoning Ken to slide in with her. He did so with eagerness, though was still nervous as hell; he had no idea what he was doing! Sensing his doubts, Gabby spoke with soft confidence and reassurance.“Let’s go you on top to start. That way you can control it so you don’t go off too soon. Honestly, though, don’t worry about stamina. You’ve already lasted through one of my blowjobs, which is no small feat, if I do say so myself. You ready?”“Um, yeah; I think so. But do we need any; protection? I don’t have a condom or anything.”With a warm smile, she replied, “Don’t ever change, Ken. Sweet, humble, and considerate, that’s what you are. I don’t have any diseases per my last doctor’s visit two months ago, and I know you’re a virgin so I don’t think there’s any concern.”“That’s good. But; what if you get pregnant? I’m not sure I’d be able to pull out in time.”“Well,” she paused, her smile becoming more bittersweet. “It’s a long story, but trust me when I say that there’s no risk of me becoming pregnant. We’re clear to let loose with this, as long as you’re comfortable with that, of course.”“I am. I just; wanted to be sure.”“Thank you, Ken. Now, if you please, my pussy is aching for your cock, and you’d best make her happy.”Positioning his pelvic region between her legs, Ken attempted to push into her, but his slick cock merely grazed the surface before slipping up to her belly. Gabby just smiled and reached down, taking a gentle grip on his cock with her hand and guiding him to the entrance of her pussy. Feeling a bit of give, he followed his instincts and penetrated her at long last, his virginity melting away in the process. She was divine, far tighter than Ken had ever imagined in his wildest dreams and fantasies.“Oh Ken; that’s just where you belong,” she cooed in satisfaction.“Holy fuck; so tight.” he could only reply.Ken began to thrust in and out of her, keeping his tempo moderate at the start to get a feel for how sensitive he was. The sensations of making love to this goddess were only enhanced by the look of sheer enjoyment in Gabby’s eyes. He prayed that he would be able to last and enjoy it all, even if only for a few minutes. As he continued thrusting into her, Gabby began to get a mischievous look in her eyes.“You’re thinking something,” Ken observed.“Uh huh. Wanna learn a trick that’ll drive any girl nuts?”“Sure.”“Come up on your knees and keep your torso straight up. Try to get to where you can keep yourself inside me without having to balance on your arms.”“Like this?” he asked, relaxing back on his folded knees.“Exactly. You can also stretch my leg out against your chest to help you balance.”“Very nice,” he said as he followed her instructions.&ld

Gabby Sylvester discusses her running journey on the podcast. She is a Goofy, Dopey runner, yes those are compliments. Check out her story. And she is trying something new, being a race director at the Shamrock Run 5K register here:https://runsignup.com/Race/OH/Canfield/ShamrockRun5k1MileFor coaching email Bruce at Justarunner65@gmail.comMcIntoshruncoaching.com

Arsenal go 9 points clear at the top of the table with a comfortable 3-0 win over Sunderland at The Emirates!Join Coach, Gabby and Mitch as they discuss how the match happened, what the road ahead looks like and of course some tactical nuances that were on display today. Tap In!

Hey everybody, happy Friday! Today, join the Reillys and Gabby as we talk all about the rebrand of the Mickey and the Mouse Podcast.We're so grateful for your support, both in the past and as we step into this new chapter, and we can't wait for what's ahead. Tune in as we share our thoughts on the new name and look, discuss Disney news, and do a deep dive into Bridgerton! Happy listening!

Welcome to The AZREIA Show!

This week, Brandon and Gabby talk about the first half of the newest Marvel series. They talk about how the perceived what kind of show it would be before it came out, they talk about how so far they're really liking it, they discuss the questions they still have about the characters, what the show could mean for what's going on in the greater MCU, and the set their ecpectations for the remainder of the series

As a new season of the YWP Podcast begins, Gabby returns to the Kruger National Park under very different circumstances.Recent floods have left parts of Kruger damaged, roads washed away, and access limited and this is a powerful reminder that even places we see as timeless are shaped by nature's force. In this opening episode, Gabby reflects on what it means to move through wild spaces on nature's terms, drawing from a chaotic teenage camping trip to Pafuri and contrasting it with the reality of returning to a park in recovery.This episode explores resilience, uncertainty, and the uncomfortable questions around conservation, access, privilege, and patience. It asks what it really means to love a place when it is wounded and whether we, as visitors, are willing to slow down and listen.Visit our online store to get your birding related merchandise at great prices https://www.thebirdinglife.com/online-storeIntro and outro music by Tony ZA https://soundcloud.com/tonyofficialzaLinks from show:

In this episode of The Real Life English with Gabby podcast, you'll learn 18 real-life phrasal verbs, idioms, and slang expressions that Americans to talk about starting over, leaving the past behind, and turning life around.Through a powerful story and clear examples, you'll hear natural English in context and learn how to use expressions like light a fire under someone, to be self-made, to be driven and more! This episode is perfect for English learners who want to sound more natural, fluent, and confident.You'll hear these expressions used naturally in context and then broken down clearly, so you can start using them confidently in your own conversations. Don't forget to download the episode study guide! It includes:All 18 vocabulary words with clear definitionsExample sentencesThe full story from the episodePractice activities to help you remember and actually use the languageTo get the Study Guide, click >> HERE

The Winter Olympics are here! What sport are we all going to pretend to be an expert at? Curling maybe? Today Gabby and Mark are joined by one of Great Britain's biggest medal hopes, freestyle skier Kirsty Muir.She started skiing at 3 years old on the dry slopes of Scotland - imagine the carpet burn doing flips on that surface! Her nan can't even watch when she does the huge tricks. This year she's already won gold at the X Games and her third World Cup title. So can she win gold in Italy?Plus, we catch you up on the best bits from The Sports Agents this week, from Carlos Alcaraz's historic victory in Australia, to Gabby being pranked by Roger Federer at Wimbledon, and a big look at the Super Bowl this weekend.

Click to Subscribe: https://bit.ly/Youtube-Subscribe-SoapDirt Days of our Lives spoilers for Feb 09-13, 2026 expect a flurry of drama and unexpected twists. Phillip Kiriakis (John-Paul Lavoisier) has Gabi Hernandez (currently Cherie Jimenez) in for a surprise, while Kate Roberts (Lauren Koslow) is moving forward with her plans. Major developments occur when Rafe Hernandez (Galen Gering) and Eli grant (Lamon Archey) uncover new information in Alamania, and Vivian Alamain (Louise Sorel) seems to be playing a deceptive game with Dimitri von Leuschner DiMera (Peter Porte) and Gwen Rizczech (Emily O'Brien). Meanwhile, Liam Fraser (Adam Leadbeater) is regretful about Theo Carver's (Tyler Joseph Andrews) kidnapping situation. DOOL spoilers indicate Gabi finds comfort with Rafe and Arianna "Ari" Grace Horton (Marissa Reyes) after being confronted with Stefan DiMera's (Brandon Barash) death. In a surprising turn of events, Sophia Choi (Rachel Boyd) and Holly Jonas (Ashley Puzemis) decide to keep the peace at Bayview, which could potentially be a part of Sophia's escape plan. Meanwhile, Brady Black (Eric Martsolf) leans on Tate Black (currently Leo Howard) to reach out to Rachel Black (Alice Halsey), who has been sentenced to an indefinite stay at Bayview.  Spoilers for Days of our Lives suggest that as the DiMera clan prepares to bury Stefano DiMera (Joseph Mascolo), Chad DiMera (Billy Flynn) encourages EJ DiMera (Dan Feuerriegel) and Kristen DiMera (Stacy Haiduk) to set aside their differences. However, family tensions rise when Chanel Dupree (Raven Bowens) warns Johnny DiMera (Carson Boatman) against letting Stefano's death make him vulnerable to EJ.  More Days of our Lives spoilers divulge that Stephanie Johnson (Abigail Klein) and Alex Kiriakis (Robert Scott Wilson) make an unexpected decision about their wedding, while Brady and Sarah Horton (Linsey Godfrey) decide to start dating despite the potential issues with Xander Cook (Paul Telfer). Gabby and Philip take off for a romantic getaway in Miami, while Steve Johnson (Stephen Nichols) and Kayla Brady (Mary Beth Evans) celebrate their wedding anniversary. Lastly, Ari receives a kiss from Liam, which Gabby is likely to dislike. You are listening to Belynda from Soap Dirt. The most listened to soap opera podcaster. Visit our Days of our Lives section of Soap Dirt: https://soapdirt.com/category/days-of-our-lives/ Listen to our Podcasts: https://soapdirt.podbean.com/ Check out our always up-to-date Days of our Lives Spoilers page at: https://soapdirt.com/days-of-our-lives-spoilers/ Check Out our Social Media... Twitter: https://twitter.com/SoapDirtTV Facebook: https://www.facebook.com/SoapDirt Pinterest: https://www.pinterest.com/soapdirt/ TikTok: https://www.tiktok.com/@soapdirt Instagram: https://www.instagram.com/soapdirt/

Former professional volleyball player, model, and lifelong athlete Gabrielle Reece joins the show for a grounded, powerful conversation about what it actually means to think—and live—like an athlete.We talk about pursuing excellence without perfection, why being “selfish” with your energy can make you better for everyone around you, and how mental strength is built just as deliberately as physical strength. Gabby shares what truly drives her, how she uses fear as a compass instead of a stop sign, and the importance of telling yourself better stories—especially as you move through different seasons of life.We also get practical: her real life gratitude practice, exercise snacking for busy days, the one movement almost everyone can do in 10 minutes for maximum benefit, her current training split, and non stimulant ways she supports energy and focus (including an honest take on nicotine). Gabby opens up about being wired for hypervigilance, shedding old identities, navigating conflict in marriage and parenting, and why internal strength matters more than external toughness.This episode is about aging with power, feeling good through perimenopause, building better boundaries with yourself, and surrounding yourself with people who raise your standard. If you want to train your body, sharpen your mindset, and live with more intention—this one will stay with you.This episode is brought to you by:Go to CLEARSTEM.com/WELL and use code WELL at checkout to get 15% off your first order.If you want clearer insight into your health, go to ForHers.com and schedule your labs todayVisit Piquelife.com/well to get 20% off.Go to paleovalley.com/well or use code well at checkout for 15% off your first purchase. Go to fatty15.com/WELL and use code WELL at checkout for an additional 15% off their Starter Kit.Save 20% on your first order at https://justthrivehealth.com/WELL. This episode may contain paid endorsements and advertisements for products and services. Individuals on the show may have a direct, or indirect financial interest in products, or services referred to in this episode.Produced by Dear MediaSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Sean Ross Sapp & Gabby LaSpisa take your superchats and humperchats on The Hump, February 4, 2026: Follow Gabby here! https://x.com/GabLaSpisaGrab your EXCLUSIVE NordVPN Deal by going to http://nordvpn.com/fightful to get a Huge Discount off your NordVPN Plan + a Bonus Gift!  It's completely risk free with Nord's 30 day money-back guarantee! ➼ https://nordvpn.com/fightful Try it risk-free now with a 30-day money-back guarantee! If you want to bet on Wrestling, or any other sport, check out our new partner where we get ALL of our odds! https://mybookie.website/joinwithFIGH... and use the promo code FIGHTFUL. Deposit $100, get $50. Go in with $200, and they'll make it $100! Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

No Gluten Gabby joins me today! Sharing her Celiac journey, her experience with Celiac Cruise, her learning curve and her travels! She is a great follow and gluten free friend to learn from! Podcast Rundown: Gabby's Edition Favorite Bite: Funfetti Cake from Pillsbury (literally available everywhere!)Favorite Brand: GloryLand Noodles https://www.instagram.com/glorylandfood/Favorite IG account: https://www.instagram.com/celiacsarahexplores/Follow Gabby on IG: https://www.instagram.com/noglutengabby/ AND https://www.instagram.com/glutenfreeeatsmichigan/Learn more about The Celiac Cruise here: https://celiaccruise.com/

In this week's episode, David and Gabby come to you virtually to help a woman who may or may not be getting catfished navigate meeting up for the first time, a guy whose girl left him for his best friend, and a listener wanting to know how in the world do you ask out a shy guy! They also give you an itinerary for the perfect day out in New York City so if you've got upcoming travel planes,  you're gonna wanna take some notes!  To submit a question to David & Gabby email: letmeaskmydadpod@gmail.com Follow Gabby & David:  Let Me Ask My Dad on Instagram: @letmeaskmydadpod Let Me Ask My Dad on TikTok: @letmeaskmydadpod  David Bryan on Instagram: @davidbryanmusic Gabby Bryan on Instagram: @gabbyisbryan Gabby Bryan on TikTok: @gabbyisbryan Let Me Ask My Dad is produced by Lizzie Stewart in partnership with W!zard Radio Learn more about your ad choices. Visit megaphone.fm/adchoices

What really happens after someone is arrested for a serious crime? Chris and Gabby sit down with Bernalillo County District Court Judge Cindy Leos for a rare, behind-the-bench look at what goes on inside Albuquerque courtrooms. Judge Leos breaks down how the justice system works, what accountability and rehabilitation can look like in practice, and challenges the idea that harsh punishment is stopping youth crime. She also explains how diversion programs like Young Adult Court can be life-changing for some. Who qualifies for the extra help? What's actually working to change criminal behavior? Thanks for listening. If you've got an idea, send it to us at chris.mckee@krqe.com or gabrielle.burkhart@krqe.com. Give us a follow on social media at @ChrisMcKeeTV and @gburkNM. Watch or listen to our prior podcasts online at KRQE.com/insiders and our KRQE YouTube channel, or on broadcast TV every Wednesday at 10:35 p.m. MST on Fox New Mexico. 

If you've been stuck in “not good enough,” “not healed enough,” or “not doing it right,” this episode is for you. In this inspiring re-air from a 2022 Dear Gabby Q&A, Gabrielle Bernstein shares how to break free from the "freeze mode" of perfectionism and self-judgment by embracing the small, meaningful steps that build genuine momentum. Through live coaching sessions with listeners, Gabrielle provides actionable guidance on navigating personal growth without spiraling into unrealistic expectations, teaching you how to stop ruminating on what "should" be happening so you can finally clear the way for creative flow and miraclesTry Gabrielle's FREE magnetic energy meditation to supercharge your attracting powers http://bit.ly/40gOfueRead Gabrielle's #1 NYT Bestselling books: Self Help: This Is Your Chance to Change Your Life. http://bit.ly/4j1asmA and May Cause Miracles: A 40-Day Guidebook of Subtle Shifts for Radical Change and Unlimited Happiness. https://bit.ly/4akBh3JIf you feel you need additional support, please consult this list of safety, recovery, and mental health resources.Disclaimer: This podcast is intended to educate, inspire, and support you on your personal journey towards inner peace. I am not a psychologist or a medical doctor and do not offer any professional health or medical advice. If you are suffering from any psychological or medical conditions, please seek help from a qualified health professional.For a limited time only, go to drinkag1.com/GABBY to get a FREE AG1 Flavor Sampler and AGZ Sampler to try all the flavors, plus FREE Vitamin D3+K2 and AG1 Welcome Kit with your first AG1 subscription order!Sign up and get 10% off at betterhelp.com/DEARGABBYShop my favorite bras and underwear at SKIMS.comProduced by Dear MediaSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In Part 2 of our real-time salon build docuseries, we return to Corte in Washington, D.C., now fully built and officially open. Gabby and Franky, two first-time salon owners in Washington, D.C., reflect on the months between construction and opening day, sharing hard-earned lessons on patience, budgeting, design compromises, team building, and what it actually feels like to step into ownership.This episode goes beyond the build to discuss comfort, workflow, client experience, and what it takes to step into ownership intentionally.

Anniversaries are fragile things—like soufflés, or secrets kept by Steve and Takoda.Adelia and Brandi return to Happy's Place for a full spoiler breakdown of Season 2, Episode 9—an episode built on careful planning, emotional intention, and one secret that threatens to flip the table before dessert.As Bobbie tries to orchestrate the perfect anniversary dinner for herself and Emmett, the pressure is on—romance, timing, vibes, all of it. Meanwhile, Steve and Takoda are sitting on a secret that cannot get out to Isabella and Gabby without completely derailing Bobbie's big night. Naturally, this only makes everything worse.✨ We unpack:- Bobbie's high-stakes attempt at the perfect anniversary- Emmett's role in the evening and what it reveals about him & their relationship- Steve & Takoda's increasingly doomed secret-keeping mission- Isabella and Gabby hovering dangerously close to the truth- How tension, comedy, and heart collide in this episode

In this episode of the Spirit and Soul podcast, Tiffany welcomes her chiropractor, Dr. Gabrielle Pajero, who shares her journey into chiropractic care and the importance of nervous system regulation. They discuss how emotional health impacts physical well-being, the role of chiropractic in promoting overall wellness, and personal stories that highlight the healing process. The conversation emphasizes the need for self-care, balance, and the understanding that healing comes from within. Follow Dr. Gabby at Pojero Family Chiropractic on Instagram @pojerofamilychiropractic Takeaways Chiropractic is not just about treating pain but promoting overall wellness. The nervous system plays a crucial role in how we experience life. Emotional stress can manifest as physical ailments in the body. Self-care is essential for maintaining health and balance. Healing comes from within; chiropractors facilitate this process. Understanding the connection between mind and body is vital for health. Women often carry stress in their bodies, particularly in the heart area. Regular chiropractic care can help maintain wellness and prevent illness. It's important to listen to your body and recognize when it needs care. Finding joy and balance in life is crucial for overall health. Chapters 00:00 Introduction to Chiropractic and Personal Journey 05:50 The Importance of Nervous System Regulation 13:00 Understanding the Mind-Body Connection 19:53 The Role of Chiropractic in Wellness 22:48 Stress and Its Impact on Physical Health 24:36 The Importance of the Sacrum and Atlas 26:58 Healing from Within: A Chiropractic Perspective 29:22 Emotional Release Through Chiropractic Adjustments 31:35 Chiropractic Miracles: Healing Beyond Expectations 37:44 The Role of Environment in Health 42:20 Self-Care for Caregivers: The Need for Balance

Welcome to season nine of Intellicast! On today's season premiere (and very special episode), Brian is joined by Gabby Blados, Matthew Alexander, and Jason Inderhees to celebrate a major milestone for the show; its 300th episode! The team takes some time in the first half of this episode to take a step back to reflect on the conversations, people, and moments that have shaped Intellicast over the years. Kicking things off, the group reflects on how Intellicast started and how far it's come. What began as a loose, informal podcast quickly evolved into a regular space for honest industry dialogue — sometimes polished, sometimes chaotic, but always real. From early technical hiccups to live recordings that didn't quite go as planned, the team laughs through the growing pains that came with finding their rhythm. The conversation naturally turns to the people who've made the podcast what it is. Over 80 guests have joined Intellicast over the last 8 season, including researchers, clients, partners, and industry voices who were willing to speak candidly, challenge assumptions, and occasionally disagree. The group reflects on recurring guests and familiar names that listeners have come to recognize, as well as first-time appearances that sparked memorable discussions. Brian, Gabby, Matthew, and Jason also share some of their favorite moments from past episodes, from COVID-era conversations recorded in the middle of uncertainty, to debates that ran long because no one wanted to wrap them up, to the occasional episode that earned an explicit tag. These moments weren't scripted or planned, but they helped define the personality of the show and made it feel less like a production and more like a conversation. Another theme that surfaces throughout the episode is how Intellicast became a place for the industry to talk honestly about what wasn't working. Long before data quality became a headline issue, the podcast was already digging into fraud, feasibility challenges, client pressure, and unrealistic expectations. Those conversations didn't always have neat conclusions, but they reflected what people were actually dealing with day to day. The group also acknowledges how the podcast has evolved alongside the industry. As new voices joined the conversation and new challenges emerged (AI, synthetic data, tighter budgets, shifting client expectation), Intellicast adapted without losing its core identity. The format changed, contributors rotated in and out, but the focus stayed the same: curiosity, skepticism, and real discussion over rehearsed talking points. It wouldn't be Intellicast without discussing some of the latest headlines. The team discusses a few of the recent headlines from around market research including: New partnership between Qualtrics and ROI Rocket PureSpectrum's new partnership with TA Associates New roles for Michael Polster and Vignesh Krishnan IRB's new healthcare professional panel. Thanks to everyone who has been with us on this ride! We've just launched our new whitepaper, The Fraud Detection Reality Check. Get you copy and find out why relying on a single fraud detection tool is a mistake. Download here: https://content.emi-rs.com/fraud-detection-report Did you miss one of our webinars or want to get some of our whitepapers and reports? You can find it all on our Resources page on our website here: https://emi-rs.com/resources/ Learn more about your ad choices. Visit megaphone.fm/adchoices

#914. You may think you know how American Idol works… but Gabby Barrett explains how the audition process actually goes.This week on Off The Vine, Gabby takes us behind the scenes of Idol in a way you've probably never heard before — from how she was really discovered, to what happens before you ever stand in front of the judges, to competing on the show while falling for her now-husband.After Idol, we get into the song no label wanted… before it changed her life forever and suddenly everyone started calling. We also talk about what tour life looks like with three kids, how she writes heartbreak songs from a happy marriage, and how a John Mayer quote shaped why she never reveals who her songs are about.AND yes — there's an embarrassingly honest confession you won't see coming.Trust us, this is one of the good ones ;) (get it?).If you're LOVING this podcast, please follow and leave a rating and review below! PLUS, FOLLOW OUR PODCAST INSTAGRAM HERE!Thank you to our Sponsors! Check out these deals!Covergirl: Go the distance with COVERGIRL's new Eye Enhancer Wrap Tubing Mascara for a lash extension effect. Shop at your nearest retailer now. Only from Easy, Breezy, Beautiful COVERGIRL.comFigs: Check out the limited-edition Team USA collection, and get 15 percent off your first order at Wearfigs.com with code FIGSRX.Tonal: Right now, Tonal.com is offering $200 off your Tonal purchase with promo code VINE.Momentous: Right now, Momentous is offering up to 35% off your first order with promo code VINE when you head to livemomentous.com.Pura: For a limited time, get a free Pura Plus home diffuser when you subscribe to your favorite fragrances for 12 months. Grab your free diffuser at Pura.com.Progressive: Visit Progressive.com to see if you could save on car insurance! Booking.com: Head over to booking.com and start your listing today. Get Seen. Get Booked on Booking.com!EPISODE HIGHLIGHTS: (4:28) – Gabby breaks down the real American Idol audition process — what happens long before you ever see the judges!(7:05) – Falling for her now-husband while competing on Idol (and why she had to chase him).(32:15) – The song no label wanted… until everyone wanted it!(49:15) – An unexpectedly humbling (and hilarious) confession you won't see coming.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Why does patience feel so hard—especially when you're doing all the “right” things? In this special re-air from a 2022 Dear Gabby Q&A, Gabrielle Bernstein explores one of the most misunderstood spiritual principles: patience as the natural result of faith, not something you force. Responding to listener questions about manifestation and feeling stuck, Gabrielle reframes patience as an energetic state that emerges when fear transforms into trust. Through live coaching, she offers practical guidance on surrendering to divine timing while navigating financial pressure, worthiness, and entrepreneurship. This episode is a powerful reminder that manifestation doesn't respond to hustle—it responds to grounded belief, alignment, and faith. When trust is strong, patience becomes effortless.Try Gabrielle's FREE magnetic energy meditation to supercharge your attracting powers http://bit.ly/40gOfueRead Gabrielle's #1 NYT Bestselling book: The Universe Has Your Back: Transform Fear Into Faith. http://bit.ly/45T1sfcIf you feel you need additional support, please consult this list of safety, recovery, and mental health resources.Disclaimer: This podcast is intended to educate, inspire, and support you on your personal journey towards inner peace. I am not a psychologist or a medical doctor and do not offer any professional health or medical advice. If you are suffering from any psychological or medical conditions, please seek help from a qualified health professional.Sponsors:Visit tonetoday.com and use my code GABBY for 20% off your first order.Visit yourreformer.com to shop their New Year sale on now to save.Get 20% off your first order and free shipping by using checkout code GABBY at naturessunshine.comFor a limited time, save 40% off your first month at ritual.com/DEARGABBYShop my favorite bras and underwear at SKIMS.comProduced by Dear MediaSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.