Podcasts about mlc

Adam Peacock joins you and Brad Haddin for another episode of Willow Talk, where we address your feedback from the WTC final review. Could we see a potential move up the order for Travis Head? Is Inglis ready for the top side? Steyn vs Rabada - who’s better? Plus, in a special edition of Ask Hadds, we preview the India vs England Test series starting this week and answer your questions: Will England be able to handle Bumrah? Is Shubman Gill up to the leadership task? Will Jacob Bethell make the side, and where do the strengths and weaknesses lie in both teams? We finish with Sundries, Babar Azam is coming to the BBL, the Aussies are scoring runs for fun in the MLC tournament and Maxi has hit another ton! Send your cricket club cap to Producer Joel at the following address: Joel Harrison 50 Goulburn St, Sydney, NSW, 2000 Follow on Apple, Spotify and the LiSTNR app Watch on YouTube Drop us a message on Instagram and TikTok! See omnystudio.com/listener for privacy information.

WATCH THE FULL EPISODE ON OUR YOUTUBE CHANNEL HERE!Finn Caddie joins ACC Head G Lane with an important update on the tension building within ACC HQ ahead of the Super Rugby Final, and what is getting put on the line (00:00)... Then the fellas discuss Foxy's payday at the US Open and perhaps the reasons around him ghosting us (7:00), before getting Shane Van Gisbergen's latest win in NASCAR and the celebration that followed (10:20)... Plus, the French have announced their squad to come out here to face the ABs (21:40), and what the hell is going on at MLC (26:30)? Finally, they get to your feedback in 'Yours Please' (30:45)... Brought to you by Export Ultra!See omnystudio.com/listener for privacy information.

-El Gobierno estafa a los médicos que vuelven de misión en Angola: les da MLC en lugar de dólares. -“La experiencia de una brigada médica es traumatizante”, dice doctora cubana en conferencia en Washington. -FEU conforma grupo "multidisciplinario" para buscar "nuevas" soluciones al tarifazo.

The Maritime Labour Convention – or MLC, 2006 - is a living example of the central role that effective social dialogue plays in shaping labour standards in the maritime sector. This episode of the Future of Work podcast explores why the MLC is a success and what we can learn from it. Guests include Mark Dickinson, the Seafarers' spokesperson, ILO Special Tripartite Committee of the Maritime Labour Convention and Vice Chair of the Seafarers' Section at the International Transport Workers' Federation; Max Johns, the Former Shipowners' spokesperson of the ILO's Special Tripartite Committee of the Maritime Labour Convention; Beatriz Vacotto, Coordinator of the Maritime Unit in the ILO's Application of Standards Branch; and Lu Camoying Valdez, Head of the Human Rights Section at the Permanent Mission of the Philippines to the United Nations and other International Organizations.

In this episode of “How to Get Ahead” by MLC, we discuss how single millennials can reconnect with themselves and find healthy relationships with Special Guest, and Relationship Coach, Syreeta Fields. (4:38) How singles get started meeting the right person (6:01) How to enjoy being single (11:00) Tips and advice to find the right person(15:45) How to connect with Syreeta Follow the Host @tanya_lleigh & @millenniallifecoaches

KarmicX lashes out at the world as he delves back in to drinking on every stream. Pat Dixon is fighting the drama and doesn't want anything to do with it. But is that the right move? FIGHT, PAT! FIGHT! Mersh is mad at Patrick about a clip. Royce makes a sandwich that he pretends he is going to eat over three days. We watch a filthy man make chicken strips and then get in to some hot steak talk. Kevin Brennan and MLC are on life support. ...

Aaron Imholte is back from his vacation, and the tales from the beach in sunny Florida are nothing short of remarkable! As predicted, he is commandeering Keanu's victory and rubbing it in to the haters all while struggling to maintain an audience and earn his goal. Let's go over the latest from our favorite cope-and-seeth king! KarmicX is on fire, and the fake war between Kevin Brennan and Chad Zumock has been put on hold while the MLC podcast retools to find out who should be the future stable of re tools. Richard Leland Neal has other YouTube channels, but they don't always make sense. Let's check out the movie review channel where he reviews McDonald's French fries. Makes sense to me! ...

My interview with Randi starts at 25 mins Stand Up is a daily podcast that I book,host,edit, post and promote new episodes with brilliant guests every day. Please subscribe now for as little as 5$ and gain access to a community of over 700 awesome, curious, kind, funny, brilliant, generous souls Check out StandUpwithPete.com to learn more RANDI WEINGARTEN is president of the 1.8 million-member AFT, which represents teachers; paraprofessionals and school-related personnel; higher education faculty and staff; nurses and other healthcare professionals; local, state and federal government employees; and early childhood educators. The AFT is dedicated to the belief that every person in America deserves the freedom to thrive, fueled by opportunity, justice and a voice in our democracy. This freedom is achieved through an economy that works for all, including the ability to form a union; great public schools and affordable higher education; healthcare as a right; retirement security; the right to vote and civil rights; a vibrant democracy; and safe, welcoming and healthy environments and communities. The AFT and its members advance these principles through community engagement, organizing, collective bargaining and political activism, and especially through members' work—we care, fight, show up and vote. Prior to her election as AFT president in 2008, Weingarten served for 11 years as president of the United Federation of Teachers, AFT Local 2, representing approximately 200,000 educators in the New York City public school system, as well as home child care providers and other workers in health, law and education. Weingarten is the recipient of many commendations; she was included in Washingtonian's 2021 Washington's Most Influential People, City & State New York's 2021 New York City Labor Power 100, and Washington Life's 2018 Power 100 list of prominent leaders, and in 2017 received the Roosevelt Institute's FDR Distinguished Public Service Award. In 2013, the New York Observer named Weingarten one of the most influential New Yorkers of the past 25 years. Weingarten has led the AFT's efforts to strengthen public education for all children and to address the crisis in the teaching profession caused by deep disinvestment and the deprofessionalization of teaching. Through the AFT's Fund Our Future campaign, AFT members and leaders throughout the country are fighting for adequate investment in public education. Parents and many others have joined the AFT's efforts to end the overuse and misuse of standardized tests, and to fix—not close—struggling schools, something Weingarten has advocated since her involvement in the creation of New York City's Chancellor's District, which dramatically improved achievement in what had been some of the city's lowest-performing schools. Weingarten has launched major efforts to place real education reform high on the nation's and her union's agendas. She created the AFT Innovation Fund, a groundbreaking initiative to support sustainable, innovative and collaborative education reform projects developed by members and their local unions. At Weingarten's direction, the AFT developed a model to transform teacher evaluations from a way of simply rating teachers to a tool for continuous improvement and feedback. This model is used to align tenure and due process, so that tenure serves as a guarantee of fairness, not of a job for life. Weingarten led an AFT committee that called for all prospective teachers to meet a high entry standard—as in medicine or law—so that they're prepared from the day they enter the classroom. Weingarten oversaw the development of the AFT's Quality Education Agenda, which advocates for reforms grounded in evidence, equity, scalability and sustainability. She promotes what she calls “solution-driven unionism”—an approach to collective bargaining and collective action that unites the interests of union members and those they serve in the pursuit of solutions that benefit students, schools and communities. Under Weingarten's leadership, the AFT continues to grow and expand its voice as a union of professionals. Nationwide, the AFT is the second-largest union of nurses and other health professionals and the largest higher education union, representing 230,000 higher education faculty, professional staff and graduate employees. Weingarten helped source millions of dollars of personal protective equipment for nurses and health professionals experiencing shortages as they served on the frontlines of the coronavirus pandemic. Weingarten is an advocate for a New Deal for Higher Education, a campaign calling for substantial federal investment in higher education that would prioritize teaching, research and student supports; provide sustainable careers with professional voice for all faculty and staff; allow all students to attend regardless of ability to pay; create academic environments free of racism and other forms of bigotry; and cancel student debt. The AFT provides our members tools and information they can use to manage their federal student loan debt, including having that debt forgiven, while advocating for solutions to the escalating cost of higher education, predatory loan practices, and terrible loan servicing that is holding people back. The AFT and a broad array of parent and community partners across the country have collaborated on events to advance a community- and educator-driven agenda for public school reform. Weingarten spearheaded the development of Share My Lesson, the United States' largest free collection of lesson plans, classroom activities, and teaching strategies and resources created by educators, for educators—all at no cost. The AFT has a long-standing partnership with First Book, which has provided 5 million free and reduced-price books to children. Weingarten and the AFT were asked to lead a partnership to transform McDowell County, W.Va., one of the poorest counties in the United States. The AFT has assembled more than 100 partners not only to improve the quality of education provided to children in the county, but to focus on jobs, transportation, recreation, housing, healthcare and social services. Weingarten believes the rural way of life is worth fighting for, and the AFT's experience in McDowell County informs the work Weingarten is advancing to help rural communities thrive—through education, healthcare and economic opportunities. The AFT supports the strategic establishment of 25,000 community schools where students and families can access tailored health services and social services in one place, and marginalized communities can have access to services and support. Weingarten views this goal as especially vital to help children, families and communities recover from the wide-ranging impacts of the coronavirus pandemic and ensuing recession. When the COVID-19 crisis hit, the AFT worked with scientists and health professionals to develop a blueprint for reopening schools. The AFT continues to advocate for the funding and necessary testing and safety protocols to ensure in-person learning is safe.  During the Trump administration, Weingarten led the AFT's efforts to oppose Trump and Betsy DeVos' fervent attempts to defund and destabilize public education and to stand up to the administration's racist policies and attacks on facts and democracy. In 2012-13, Weingarten served on an education reform commission convened by New York Gov. Andrew Cuomo, which made a series of recommendations to improve teaching and learning. She was appointed to the Equity and Excellence Commission, a federal advisory committee chartered by Congress to examine and make recommendations concerning the disparities in educational opportunities that give rise to the achievement gap. For 10 years, while president of the UFT, Weingarten chaired New York City's Municipal Labor Committee, an umbrella organization for the city's 100-plus public sector unions, including those representing higher education and other public service employees. As chair of the MLC, she coordinated labor negotiations and bargaining for benefits on behalf of the MLC unions' 365,000 members. From 1986 to 1998, Weingarten served as counsel to UFT President Sandra Feldman, taking a lead role in contract negotiations and enforcement, and in lawsuits in which the union fought for adequate school funding and building conditions. A teacher of history at Clara Barton High School in Brooklyn's Crown Heights neighborhood from 1991 to 1997, Weingarten helped her students win several state and national awards debating constitutional issues. Elected as the local union's assistant secretary in 1995 and as treasurer two years later, she became UFT president after Feldman became president of the AFT. Weingarten was elected to her first full term as UFT president in 1998 and was re-elected three times. Weingarten's column “What Matters Most” appears in the New York Times' Sunday Review the third Sunday of each month. You can follow her on Twitter at @rweingarten (Twitter.com/rweingarten) and on Facebook (Facebook.com/randi.weingarten.9). Weingarten holds degrees from Cornell University's School of Industrial and Labor Relations and the Cardozo School of Law. She worked as a lawyer for the Wall Street firm of Stroock & Stroock & Lavan from 1983 to 1986. She is an active member of the Democratic National Committee and numerous professional, civic and philanthropic organizations. Born in 1957 and raised in Rockland County, N.Y., Weingarten now resides in the Inwood neighborhood of New York City. Join us Monday's and Thursday's at 8EST for our Bi-Weekly Happy Hour Hangout!  Pete on Blue Sky Pete on Threads Pete on Tik Tok Pete on YouTube  Pete on Twitter Pete On Instagram Pete Personal FB page Stand Up with Pete FB page All things Jon Carroll  Follow and Support Pete Coe Buy Ava's Art  Hire DJ Monzyk to build your website or help you with Marketing

In this episode of "How to Get Ahead" by MLC, we discuss how millennials scale and succeed in business as entrepreneurs in 2025 with Dr. P. (10:20) How to become more productive and maximize your activity in business. (17:27) How to reconnect to your purpose and separate personal and business to attract clients. (30:09) How to understand and shift your mindset to truly own your business. (45:14) How to connect with Dr. P for Business Coaching, Consulting, and Training. Follow the Host @lorna_tay &  ⁨@millenniallifecoaches⁩  Get to Know Dr. Priscilla "Dr. P." Kucer

This week on the New Music Business podcast, Ari sits down with Danny Ross, a producer and songwriter based in NYC, a columnist at Forbes, and founder of the largest songwriting camp in the world, Anti Social Camp. Danny's Anti Social Camp brings together over 250 songwriters, producers, and artists to collaborate amongst themselves and with major artists every summer in NYC. Past Anti Social Camp attendees have worked with artists including Jacob Collier, Miranda Lambert, Moby, Nile Rodgers, Kimbra, Andy Grammer, JP Saxe, and Rob Thomas. Brands like TikTok, Spotify, YouTube, Amazon, TIDAL, The Recording Academy, Republic Records, DistroKid, and The MLC are also intricately involved in the Anti Social Camp experience.If you are a songwriter or producer who's ever wondered what goes down at songwriting camps or how to get involved, you're going to learn all about that and more in this episode with Danny Ross. https://www.instagram.com/antisocialcamp/ Get $100 your Anti Social Camp Badge by using the code: ARIANTISOCIALVIP at antisocialcamp.comChapters00:00 The Importance of Reputation in the Music Industry03:02 Understanding Songwriting Camps05:48 The Structure and Dynamics of Songwriting Sessions08:47 The Evolution of the Anti Social Camp12:01 Building Community in New York's Music Scene14:54 The Anti Social Camp Experience17:54 Diverse Genres and Collaboration20:54 The Future of Songwriting Camps31:11 Creative Collaborations in Music Production32:26 Success Stories from the Camp33:44 Understanding Major vs. Indie vs. Self-Releasing Artists38:33 The Financial Landscape of Music Production44:53 Navigating Splits and Royalties in Music47:01 The Ethics of Publishing in the Music Industry52:39 Teaching the Next Generation of Music Creators56:40 The Importance of Community in Music Creation59:01 Defining Success in the New Music BusinessEdited and mixed by Ari DavidsMusic by Brassroots DistrictProduced by the team at Ari's TakeOrder the THIRD EDITION of How to Make It in the New Music Business: https://book.aristake.com Hosted on Acast. See acast.com/privacy for more information.

In this episode of "How to Get Ahead" by Millennial Life Coaches (MLC), Tanya and Austin host special guest and Certified Holistic Coach, Rebecca Visser, as we dive into how to shift your energy and align to your purpose.  Rebecca is an ICF trained coach that helps driven women realign and reconnect, while reducing the overwhelm. We open with Rebecca's “origin story” and what drove her into coaching (1:34). Austin then discusses how he teaches his kids about energy shifting and how it can shape their environment (7:03). We pivot back to the success stories of Rebecca's clients (11:06) and dive a bit deeper into the story behind the Crescent Coaching Brand (14:00). Rebecca then shares details about her upcoming programs and how to best connect with her (20:15)!Connect with the Hosts -@tanya.lleigh@millennial_coach.austin@millennialifecoachesConnect with Rebecca to Reclaim Your Time, Energy, and Purpose -Check out Crescent Coaching website: crescentcoaching.caExplore private 1:1 Coaching Programs – Save 10% when you mention MLC!The Well-Being Routine Reset – Reclaim your time and energy with sustainable habits you can actually keep without feeling guilty. https://crescentcoaching.ca/well-being-routine-reset The Driven by Purpose program – Align your career with what truly fulfills you and make an impact. https://crescentcoaching.ca/driven-by-purpose Book Your Free Breakthrough Call here: https://crescentcoaching.ca/discovery-call Take the 3 Min “How Purposeful Is Your Career?" QuizDiscover what's out of alignment and get personalized insights to move forward: crescentcoaching.ca/career-purpose-quizStay connected for tips, workshops & offers LinkedIn: linkedin.com/in/rebecca-visser Instagram: instagram.com/crescentcoaching Newsletter: crescentcoaching.ca/join-the-newsletterAre you a coach? Visit us today! Millennial Life CoachesCoach Core

Una discusión a fondo de las principales noticias del acontecer diario de Cuba y el mundo, con la conducción de los periodistas Amado Gil y José Luis Ramos | Hoy, en la Tertulia de Las Noticias Como Son: | Los expertos aconsejan deshacerse de la MLC y ahorrar en dólares, sin descartar el peso cubano | La Habana topa los precios de las inversiones constructivas y los privados ponen el grito en el cielo | Carolina Barrero: “No queremos más reuniones escondidas en La Habana” | Invitados: Reinaldo Escobar, escritor y periodista de 14yMedio, La Habana y Dimas Castellanos, escritor, periodista independiente | Comentarios en Audio: Omar Everleny Pérez Villanueva, economista, La Habana y Carolina Barrero, Directora ONG, Ciudadania y Libertad..

Anand Rajaraman is a serial entrepreneur and venture capitalist known for co-founding Junglee, which was acquired by Amazon, and Kosmix, acquired by Walmart. He was Senior Vice President at Walmart Global eCommerce and is a founding partner at Rocketship.vc.Rajaraman is also the co-owner of the San Francisco Unicorns, a Major League Cricket team. Anand has invested early in companies like Facebook and Lyft and focuses on backing high-growth startups globally, but in this episode we will limit our conversation to owning a cricket team and maybe do another episode later to talk about Anand's entrepreneurial & investing success.⭐ Sponsored by Podcast10x - Podcasting agency for VCs - https://podcast10x.comSan Francisco Unicorns website - https://www.sfunicorns.com/Major League Cricket (MLC) website - https://www.majorleaguecricket.com/Anand Rajaraman on LinkedIn - https://www.linkedin.com/in/anandrajaraman/In this episode, we talk about -- Why did he decide to buy a cricket team- The business angle of owning a sports team- Key revenue streams for franchise cricket leagues & teams- Leveraging data & technology in all aspects of team management- The signing of 2 Australian legends: Pat Cummins as a player, & Shane Watson as the coach- The emotional toll of owning a sports team& lots moreTimestamps:(00:00) Introduction to Anand Rajaraman and the podcast episode(03:48) Why Anand decided to buy a cricket team in Major League Cricket (MLC)(05:18) Choosing the San Francisco Unicorns and the reasoning behind the team name(07:23) Parallels between business world and owning a sports team(10:59) Applying data and analytics to team management(13:35) Investment perspective on owning a sports team(18:26) Revenue streams for cricket leagues and teams(22:30) Player acquisition and salary cap details(23:52) Player selection strategy for the team(27:53) Discussion about Pat Cummins joining the team(33:11) Hypothetical scenario of Indian players in MLC(34:17) Emotional aspects of owning a sports team(40:12) Reflections on the 2024 season and reaching the championship match(42:43) Growth of cricket in the USA and impact of the 2023 World Cup(45:23) Long-term vision for team ownership(46:20) How to follow San Francisco Unicorns and Major League CricketFor sponsorship or guest appearance requests, write to prashantchoubey3@gmail.comSubscribe to VC10X on Youtube, Spotify, Apple Podcasts.

Macca and Nevena are joined live on air by Radiothon Edition-Aiv Puglieli, Greens, MLC for North Eastern Metro, for this edition of Radiothon. The post Saturday 10th May, 2025: Radiothon Edition-Aiv Puglieli, Greens, MLC for North Eastern Metro appeared first on Saturday Magazine.

The DabbleVerse is a hilarious community of podcasters but is it also sexist? I'm joined by Keanu C Thompson (stand up comedian & host of KeanuCast), Little Lemmi (host of A Superior Morning Show) and The Quadfather (host of BackYardBoys Podcast) to debate the sexism, talk about if Kevin Brennan's MLC show has been ruined forever and if Aaron Imholte is an unfair victim of the DabbleVerse.FOLLOW THE GUESTS===================Keanu https://x.com/keanuCthompsonLemmi https://x.com/0LittleLemmi0Quad https://x.com/QuadfatherDBecome a supporter of this podcast: https://www.spreaker.com/podcast/it-s-hughezy-hello--3476000/support.

William Zahner, Understanding the Role of Language in Math Classrooms ROUNDING UP: SEASON 3 | EPISODE 17 How can educators understand the relationship between language and the mathematical concepts and skills students engage with in their classrooms? And how might educators think about the mathematical demands and the language demands of tasks when planning their instruction?  In this episode, we discuss these questions with Bill Zahner, director of the Center for Research in Mathematics and Science Education at San Diego State University. BIOGRAPHY Bill Zahner is a professor in the mathematics department at San Diego State University and the director of the Center for Research in Mathematics and Science Education. Zahner's research is focused on improving mathematics learning for all students, especially multilingual students who are classified as English Learners and students from historically marginalized communities that are underrepresented in STEM fields. RESOURCES Teaching Math to Multilingual Learners, Grades K–8 by Kathryn B. Chval, Erin Smith, Lina Trigos-Carrillo, and Rachel J. Pinnow National Council of Teachers of Mathematics Mathematics Teacher: Learning and Teaching PK– 12 English Learners Success Forum SDSU-ELSF Video Cases for Professional Development The Math Learning Center materials Bridges in Mathematics curriculum Bridges in Mathematics Teachers Guides [BES login required] TRANSCRIPT Mike Wallus: How can educators understand the way that language interacts with the mathematical concepts and skills their students are learning? And how can educators focus on the mathematics of a task without losing sight of its language demands as their planning for instruction? We'll examine these topics with our guest, Bill Zahner, director of the Center for Research in Mathematics and Science Education at San Diego State University.  Welcome to the podcast, Bill. Thank you for joining us today. Bill Zahner: Oh, thanks. I'm glad to be here. Mike: So, I'd like to start by asking you to address a few ideas that often surface in conversations around multilingual learners and mathematics. The first is the notion that math is universal, and it's detached from language. What, if anything, is wrong with this idea and what impact might an idea like that have on the ways that we try to support multilingual learners? Bill: Yeah, thanks for that. That's a great question because I think we have a common-sense and strongly held idea that math is math no matter where you are and who you are. And of course, the example that's always given is something like 2 plus 2 equals 4, no matter who you are or where you are. And that is true, I guess [in] the sense that 2 plus 2 is 4, unless you're in base 3 or something. But that is not necessarily what mathematics in its fullness is. And when we think about what mathematics broadly is, mathematics is a way of thinking and a way of reasoning and a way of using various tools to make sense of the world or to engage with those tools [in] their own right. And oftentimes, that is deeply embedded with language.  Probably the most straightforward example is anytime I ask someone to justify or explain what they're thinking in mathematics. I'm immediately bringing in language into that case. And we all know the old funny examples where a kid is asked to show their thinking and they draw a diagram of themselves with a thought bubble on a math problem. And that's a really good case where I think a teacher can say, “OK, clearly that was not what I had in mind when I said, ‘Show your thinking.'”  And instead, the demand or the request was for a student to show their reasoning or their thought process, typically in words or in a combination of words and pictures and equations. And so, there's where I see this idea that math is detached from language is something of a myth; that there's actually a lot of [language in] mathematics. And the interesting part of mathematics is often deeply entwined with language. So, that's my first response and thought about that.  And if you look at our Common Core State Standards for Mathematics, especially those standards for mathematical practice, you see all sorts of connections to communication and to language interspersed throughout those standards. So, “create viable arguments,” that's a language practice. And even “attend to precision,” which most of us tend to think of as, “round appropriately.” But when you actually read the standard itself, it's really about mathematical communication and definitions and using those definitions with precision. So again, that's an example, bringing it right back into the school mathematics domain where language and mathematics are somewhat inseparable from my perspective here. Mike: That's really helpful. So, the second idea that I often hear is, “The best way to support multilingual learners is by focusing on facts or procedures,” and that language comes later, for lack of a better way of saying it. And it seems like this is connected to that first notion, but I wanted to ask the question again: What, if anything, is wrong with this idea that a focus on facts or procedures with language coming after the fact? What impact do you suspect that that would have on the way that we support multilingual learners? Bill: So, that's a great question, too, because there's a grain of truth, right? Both of these questions have simultaneously a grain of truth and simultaneously a fundamental problem in them. So, the grain of truth—and an experience that I've heard from many folks who learned mathematics in a second language—was that they felt more competent in mathematics than they did in say, a literature class, where the only activity was engaging with texts or engaging with words because there was a connection to the numbers and to symbols that were familiar. So, on one level, I think that this idea of focusing on facts or procedures comes out of this observation that sometimes an emergent multilingual student feels most comfortable in that context, in that setting.  But then the second part of the answer goes back to this first idea that really what we're trying to teach students in school mathematics now is not simply, or only, how to apply procedures to really big numbers or to know your times tables fast. I think we have a much more ambitious goal when it comes to teaching and learning mathematics. That includes explaining, justifying, modeling, using mathematics to analyze the world and so on. And so, those practices are deeply tied with language and deeply tied with using communication. And so, if we want to develop those, well, the best way to do that is to develop them, to think about, “What are the scaffolds? What are the supports that we need to integrate into our lessons or into our designs to make that possible?”  And so, that might be the takeaway there, is that if you simply look at mathematics as calculations, then this could be true. But I think our vision of mathematics is much broader than that, and that's where I see this potential. Mike: That's really clarifying. I think the way that you unpack that is if you view mathematics as simply a set of procedures or calculations, maybe? But I would agree with you. What we want for students is actually so much more than that.  One of the things that I heard you say when we were preparing for this interview is that at the elementary level, learning mathematics is a deeply social endeavor. Tell us a little bit about what you mean by that, Bill. Bill: Sure. So, mathematics itself, maybe as a premise, is a social activity. It's created by humans as a way of engaging with the world and a way of reasoning. So, the learning of mathematics is also social in the sense that we're giving students an introduction to this way of engaging in the world. Using numbers and quantities and shapes in order to make sense of our environment.  And when I think about learning mathematics, I think that we are not simply downloading knowledge and sticking it into our heads. And in the modern day where artificial intelligence and computers can do almost every calculation that we can imagine—although your AI may do it incorrectly, just as a fair warning [laughs]—but in the modern day, the actual answer is not what we're so focused on. It's actually the process and the reasoning and the modeling and justification of those choices. And so, when I think about learning mathematics as learning to use these language tools, learning to use these ways of communication, how do we learn to communicate? We learn to communicate by engaging with other people, by engaging with the ideas and the minds and the feelings and so on of the folks around us, whether it's the teacher and the student, the student and the student, the whole class and the teacher. That's where I really see the power. And most of us who have learned, I think can attest to the fact that even when we're engaging with a text, really fundamentally we're engaging with something that was created by somebody else. So, fundamentally, even when you're sitting by yourself doing a math word problem or doing calculations, someone has given that to you and you think that that's important enough to do, right?  So, from that stance, I see all of teaching and learning mathematics is social. And maybe one of our goals in mathematics classrooms, beyond memorizing the times tables, is learning to communicate with other people, learning to be participants in this activity with other folks. Mike: One of the things that strikes me about what you were saying, Bill, is there's this kind of virtuous cycle, right? That by engaging with language and having the social aspect of it, you're actually also deepening the opportunity for students to make sense of the math. You're building the scaffolds that help kids communicate their ideas as opposed to removing or stripping out the language. That's the context in some ways that helps them filter and make sense. You could either be in a vicious cycle, which comes from removing the language, or a virtuous cycle. And it seems a little counterintuitive because I think people perceive language as the thing that is holding kids back as opposed to the thing that might actually help them move forward and make sense. Bill: Yeah. And actually that's one of the really interesting pieces that we've looked at in my research and the broader research is this question of, “What makes mathematics linguistically complex?” is a complicated question. And so sometimes we think of things like looking at the word count as a way to say, “If there are fewer words, it's less complex, and if there are more words, it's more complex.” But that's not totally true. And similarly, “If there's no context, it's easier or more accessible, and if there is a context, then it's less accessible.”  And I don't see these as binary choices. I see these as happening on a somewhat complicated terrain where we want to think about, “How do these words or these contexts add to student understanding or potentially impede [it]?” And that's where I think this social aspect of learning mathematics—as you described, it could be a virtuous cycle so that we can use language in order to engage in the process of learning language. Or, the vicious cycle is, you withhold all language and then get frustrated when students can't apply their mathematics. That's maybe the most stereotypical answer: “My kids can do this, but as soon as they get a word problem, they can't do it.” And it's like, “Well, did you give them opportunities to learn how to do this? [laughs] Or is this the first time?” Because that would explain a lot. Mike: Well, it's an interesting question, too, because I think what sits behind that in some ways is the idea that you're kind of going to reach a point, or students might reach a point, where they're “ready” for word problems.  Bill: Right. Mike: And I think what we're really saying is it's actually through engaging with word problems that you build your proficiency, your skillset that actually allows you to become a stronger mathematician. Bill: Mm-hmm. Right. Exactly. And it's a daily practice, right? It's not something that you just hold off to the end of the unit, and then you have the word problems, but it's part of the process of learning. And thinking about how you integrate and support that. That's the key question that I really wrestle with. Not trivial, but I think that's the key and the most important part of this. Mike: Well, I think that's actually a really good segue because I wanted to shift and talk about some of the concrete or productive ways that educators can support multilingual learners. And in preparing for this conversation, one of the things that I've heard you stress is this notion of a consistent context. So, can you just talk a little bit more about what you mean by that and how educators can use that when they're looking at their lessons or when they're writing lessons or looking at the curriculum that they're using? Bill: Absolutely. So, in our past work, we engaged in some cycles of design research with teachers looking at their mathematics curriculum and opportunities to engage multilingual learners in communication and reasoning in the classroom. And one of the surprising things that we found—just by looking at a couple of standard textbooks—was a surprising number of contexts were introduced that are all related to the same concept. So, the concept would be something like rate of change or ratio, and then the contexts, there would be a half dozen of them in the same section of the book. Now, this was, I should say, at a secondary level, so not quite where most of the Bridges work is happening. But I think it's an interesting lesson for us that we took away from this. Actually, at the elementary level, Kathryn Chval has made the same observation.  What we realized was that contexts are not good or bad by themselves. In fact, they can be highly supportive of student reasoning or they can get in the way. And it's how they are used and introduced. And so, the other way we thought about this was: When you introduce a context, you want to make sure that that context is one that you give sufficient time for the students to understand and to engage with; that is relatable, that everyone has access to it; not something that's just completely unrelated to students' experiences. And then you can really leverage that relatable, understandable context for multiple problems and iterations and opportunities to go deeper and deeper.  To give a concrete example of that, when we were looking at this ratio and rate of change, we went all the way back to one of the fundamental contexts that's been studied for a long time, which is motion and speed and distance and time. And that seemed like a really important topic because we know that that starts all the way back in elementary school and continues through college-level physics and beyond. So, it was a rich context. It was also something that was accessible in the sense that we could do things like act out story problems or reenact a race that's described in a story problem. And so, the students themselves had access to the context in a deep way.  And then, last, that context was one that we could come back to again and again, so we could do variations [of] that context on that story. And I think there's lots of examples of materials out there that start off with a core context and build it out. I'm thinking of some of the Bridges materials, even on the counting and the multiplication. I think there's stories of the insects and their legs and wings and counting and multiplying. And that's a really nice example of—it's accessible, you can go find insects almost anywhere you are. Kids like it. [Laughs] They enjoy thinking about insects and other icky, creepy-crawly things. And then you can take that and run with it in lots of different ways, right? Counting, multiplication, division ratio, and so on. Mike: This last bit of our conversation has me thinking about what it might look like to plan a lesson for a class or a group of multilingual learners. And I know that it's important that I think about mathematical demands as well as the language demands of a given task. Can you unpack why it's important to set math and language development learning goals for a task, or a set of tasks, and what are the opportunities that come along with that, if I'm thinking about both of those things during my planning? Bill: Yeah, that's a great question. And I want to mark the shift, right? We've gone from thinking about the demands to thinking about the goals, and where we're going to go next.  And so, when I think about integrating mathematical goals—mathematical learning goals and language learning goals—I often go back to these ideas that we call the practices, or these standards that are about how you engage in mathematics. And then I think about linking those back to the content itself. And so, there's kind of a two-piece element to that. And so, when we're setting our goals and lesson planning, at least here in the great state of California, sometimes we'll have these templates that have, “What standard are you addressing?,” [Laughs] “What language standard are you addressing?,” “What ELD standard are you addressing?,” “What SEL standard are you addressing?” And I've seen sometimes teachers approach that as a checkbox, right? Tick, tick, tick, tick, tick. But I see that as a missed opportunity—if you just look at this like you're plugging things in—because as we started with talking about how learning mathematics is deeply social and integrated with language, that we can integrate the mathematical goals and the language goals in a lesson. And I think really good materials should be suggesting that to the teacher. You shouldn't be doing this yourself every day from scratch. But I think really high-quality materials will say, “Here's the mathematical goal, and here's an associated language goal,” whether it's productive or receptive functions of language. “And here's how the language goal connects the mathematical goal.”  Now, just to get really concrete, if we're talking about an example of reasoning with ratios—so I was going back to that—then it might be generalized, the relationship between distance and time. And that the ratio of distance and time gives you this quantity called speed, and that different combinations of distance and time can lead to the same speed. And so, explain and justify and show using words, pictures, diagrams. So, that would be a language goal, but it's also very much a mathematical goal.  And I guess I see the mathematical content, the practices, and the language really braided together in these goals. And that I think is the ideal, and at least from our work, has been most powerful and productive for students. Mike: This is off script, but I'm going to ask it, and you can pass if you want to.  Bill: Mm-hmm. Mike: I wonder if you could just share a little bit about what the impact of those [kinds] of practices that you described [have been]—have you seen what that impact looks like? Either for an educator who has made the step and is doing that integration or for students who are in a classroom where an educator is purposely thinking about that level of integration? Bill: Yeah, I can talk a little bit about that. In our research, we have tried to measure the effects of some of these efforts. It is a difficult thing to measure because it's not just a simple true-false test question type of thing that you can give a multiple-choice test for.  But one of the ways that we've looked for the impact [of] these types of intentional designs is by looking at patterns of student participation in classroom discussions and seeing who is accessing the floor of the discussion and how. And then looking at other results, like giving an assessment, but deeper than looking at the outcome, the binary correct versus incorrect. Also looking at the quality of the explanation that's provided. So, how [do] you justify an answer? Does the student provide a deeper or a more mathematically complete explanation?  That is an area where I think more investigation is needed, and it's also very hard to vary systematically. So, from a research perspective—you may not want to put this into the final version [laughs]—but from a research perspective, it's very hard to fix and isolate these things because they are integrated. Mike: Yeah. Yeah. Bill: Because language and mathematics are so deeply integrated that trying to fix everything and do this—“What caused this water to taste like water? Was it the hydrogen or the oxygen?”—well, [laughs] you can't really pull those apart, right? The water molecule is hydrogen and oxygen together. Mike: I think that's a lovely analogy for what we were talking about with mathematical goals and language goals. That, I think, is really a helpful way to think about the extent to which they're intertwined with one another. Bill: Yeah, I need to give full credit to Vygotsky, I think, who said that. Mike: You're— Bill: Something. Might be Vygotsky. I'll need to check my notes. Mike: I think you're in good company if you're quoting Vygotsky.  Before we close, I'd love to just ask you a bit about resources. I say this often on the podcast. We have 20 to 25 minutes to dig deeply into an idea, and I know people who are listening often think about, “Where do I go from here?” Are there any particular resources that you would suggest for someone who wanted to continue learning about what it is to support multilingual learners in a math classroom? Bill: Sure. Happy to share that.  So, I think on the individual and collective level—so, say, a group of teachers—there's a beautiful book by Kathryn Chval and her colleagues [Teaching Math to Multilingual Learners, Grades K–8] about supporting multilingual learners and mathematics. And I really see that as a valuable resource. I've used that in reading groups with teachers and used that in book studies, and it's been very productive and powerful for us. Beyond that, of course, I think the NCTM [National Council of Teachers of Mathematics] provides a number of really useful resources. And there are articles, for example, in the [NCTM journal] Mathematics Teacher: Learning and Teaching PK– 12 that could make for a really wonderful study or opportunity to engage more deeply.  And then I would say on a broader perspective, I've worked with organizations like the English Learners Success Forum and others. We've done some case studies and little classroom studies that are accessible on my website [SDSU-ELSF Video Cases for Professional Development], so you can go to that. But there's also from that organization some really valuable insights, if you're looking at adopting new materials or evaluating things, that gives you a principled set of guidelines to follow. And I think that's really helpful for educators because we don't have to do this all on our own. This is not a “reinvent the wheel at every single site” kind of situation. And so, I always encourage people to look for those resources.  And of course, I will say that the MLC materials, the Bridges in Mathematics [curriculum], I think have been really beautifully designed with a lot of these principles right behind them. So, for example, if you look through the Teachers Guides on the Bridges in Mathematics [BES login required], those integrated math and language and practice goals are a part of the design. Mike: Well, I think that's a great place to stop. Thank you so much for joining us, Bill. This has been insightful, and it's really been a pleasure talking with you. Bill: Oh, well, thank you. I appreciate it. Mike: And that's a wrap for Season 3 of Rounding Up. I want to thank all of our guests and the MLC staff who make these podcasts possible, as well as all of our listeners for tuning in. Have a great summer, and we'll be back in September for Season 4.  This podcast is brought to you by The Math Learning Center and the Maier Math Foundation, dedicated to inspiring and enabling all individuals to discover and develop their mathematical confidence and ability. © 2025 The Math Learning Center | www.mathlearningcenter.org  

Linguists at Work! This is a special mini-podcast of the Linguistics Careercast called Linguists at Work. It's a series of 5-minute interviews with career linguists, conducted by grad students in the Georgetown Linguistics program, in which they ask the question: “What’s your job and how did you get it?” Every interview focuses on a job that a linguist not only can do, but adds value to based on the unique skillset we develop as language scientists. Today’s pod features Lexi Slome, who is an associate trial consultant. She earned her Ph.D. in Linguistics from Georgetown University in 2024, where she focused on discourse analysis of courtroom language, including research examining the role of identity construction in telling persuasive opening statement narratives. In her current role as a trial consultant, she uses both her linguistic knowledge and research skills to provide data-driven analysis of juror reactions to complex legal cases through research exercises such as mock trials and focus groups. The interview is conducted by Joana Fehr, a graduate student from Germany in the MLC program at Georgetown University. She has lived and studied in seven countries across Europe, North America, and South America, and brings a global perspective to her work. Lexi Slome on LinkedIn Joana Fehr on LinkedInThe post Mini-pod: Linguists At Work with Lexi Slome first appeared on Linguistics Careercast.

Neil Manthorp is joined by the former England fast bowler Steve Harmison to react to the news that Nat Sciver-Brunt has been appointed the new England Women's captain. They also look back at another round of County Championship action, and debate if Josh Tongue is in pole position to play Test Cricket for England this summer after his 5-fer helped Nottinghamshire beat Sussex to go top of Division One. The former Zimbabwe fast bowler Ed Rainsford looks back at their historic Test win over Bangladesh, and discusses how they are shaping up ahead of facing England next month. They also hear from New Zealand Cricket CEO Scott Weenick after they partnered with MLC, becoming the first ICC full member nation to form a partnership with a franchise competition, and ESPNCricinfo's Assistant Editor Matt Roller discusses reports the IPL schedule could be extended to 94 games from 2028. Hosted on Acast. See acast.com/privacy for more information.

This week in the Niche Cache we celebrate Auckland FC who won the A-League Premiers' Plate in their first season. We chat through all the details from their win over Perth Glory and update the wider themes we see in how the Blue Riders play their footy. There are a few kiwi footballers to discuss from the weekend's footy around the world as well before we check in with Steven Adams in the NBA Playoffs and NBL basketball where Canterbury Rams and Auckland Tuatara lead the league, but youngster Jackson Ball keeps making waves with Hawkes Bay Hawks. Then we roll through a fun weekend for NZ Warriors who had wins in the NRL and NSW Cup vs Newcastle Knights, plus a Jersey Flegg Cup draw vs Knights. The Warriors Under 17 team have made the Harold Matthews Cup grand final for the second season in a row which seems notable. Anzac weekend sparked up thoughts of an NZ Kiwis Anzac Test team and this rolls into the best Kiwi-NRL players from the first stanza of the season. We finish with a net session of New Zealand cricket with notes about MLC buy in, Blackcaps coaching, County Championship and an NZ-A team to tour Bangladesh.Patreon: https://www.patreon.com/elnichecacheNewsletter: https://thenichecache.substack.comHook us up with a brew: https://buymeacoffee.com/thenichecacheSay kia ora: thenichecache@gmail.comwww.theniche-cache.com(00:00) Auckland FC(29:54) Mindfulness(33:46) More Auckland FC(01:06:20) Flying Kiwis(01:11:16) Steven Adams(01:12:54) NBL(01:26:15) NZ Warriors(01:57:38) NZ Kiwis(02:00:58) Cricket

Big moves are brewing in American cricket!New Zealand Cricket makes history, becoming the first national board to invest in an overseas T20 league, teaming up with Major League Cricket for a brand-new franchise in 2027.What could this mean for MLC's future - and for cricket's big moment at the LA Olympics?Plus, we dive into all the latest IPL drama, including Glenn Maxwell getting dropped after Virender Sehwag's suggestion that the Big Show was treating the tournament like a ‘holiday'.

In this episode of the show, Raj, Baldy and Stu look back at week 5 of IPL 2025, which saw Mumbai and RCB make their moves, CSK start looking to next season and New Zealand Cricket invest in Major League Cricket in the USA. We start this week with a check in about RCB. It's been a strange season for them so far - less hyped than previous years, struggles at home, but with a lot of the players in key positions all delivering on what's required. We talk about Virat Kohli's quietly impressive stats, Josh Hazlewood doing the business, Tim David's finishing, Krunal Pandya's key moments and whether it's time to load up on RCB stock before it is too late. From there, we move to Mumbai's charge up the table thanks to Rohit Sharma's return to form, Suryakumar Yadav's consistency, a bag for Trent Boult and a bowling attack that looks so much more complete now that it features Jasprit Bumrah. Then it's time to bounce around a few different topics - from the top 6 teams putting a gap between them and the rest, to left-handed openers like Priyansh Arya and Yashasvi Jaiswal, and the contrasting fortunes of teams like the Delhi Capitals, Sunrisers Hyderabad and Chennai Super Kings. We round out the show with a discussion about New Zealand Cricket's investment in MLC in North America. Is international investment in franchise cricket a glimpse into the future of the game? How will it work in reality? Who could it benefit? Could we ever see something similar in the IPL? We'll be back in your feed again soon with more IPL coverage. If you're enjoying our content then please take the time to give us a like, follow, share or subscribe on all our channels (@toporderpod on Twitter & Facebook, and @thetoporderpodcast on Instagram & YouTube) and a (5-Star!) review at your favourite podcast provider, or tell a friend to download. It really helps others find the show and is the best thing you can do to support us. You can also find all our written content, including our Hall of Fame series, at our website. You can also dip back into our guest episodes - including conversations with Mike Hesson, Shane Bond and Mike Hussey, current players such as Matt Henry, Sophie Devine and Ish Sodhi, coaches Gary Stead, Jeetan Patel and Luke Wright, as well as Barry Richards, Frankie Mackay, Bharat Sundaresan and many more fascinating people from all across the cricketing world. And if you'd like to reach out to us with feedback, questions or guest suggestions, get in touch at thetoporderpodcast@gmail.com. Thanks for listening. 0:00 Intro 0:50 Is it time to invest in RCB & Virat Kohli? 6:35 Mumbai Indians on the charge 10:25 Net Run Rate and the top 6 breaking away 12:45 Can we put a line through CSK and RR? 14:30 Are the Sunrisers also done? 19:25 Do CSK need to look to the future? 22:00 Yashasvi Jaiswal's brilliance 23:35 Is 2025 the year of the specialists? 27:15 Priyansh Arya and the importance of composure 29:55 Why the hesitancy about DC? 36:15 New Zealand Cricket's investment in Major League Cricket Learn more about your ad choices. Visit podcastchoices.com/adchoices

In this episode of How to Get Ahead by Millennial Life Coaches, we sit down with Julie Wieler—marketing agency owner and co-founder of Coach Core—to explore the entrepreneurial path that led her to create not just one, but two powerhouse businesses designed to help others grow. Julie shares how her early days in network marketing sparked a deep dive into digital strategy, ultimately leading to the organic growth of her own agency as others began to notice her results and asked for help. She opens up about the lessons learned in building a business that goes beyond just running ads and posting on social media—diving into what actually matters in marketing: identifying the real problem you solve, finding the right people to serve, and speaking to pain points that motivate action.We also get the inside story of how Coach Core came to life—from late nights wrestling with tech tools to the moment Julie and her co-founder realized the biggest challenge new coaches face isn't passion or purpose—it's the tech. This episode is packed with insights for anyone growing a coaching business, running an agency, or just trying to figure out how to bring their vision to life without burning out.Whether you're a solopreneur struggling with your marketing or a coach sick of duct-taping tech together, this convo is a must-listen.Learn More about Coach Core @ https://www.coachcore.caFollow on Instagram at @CoachCoreCheers to the hosts and special guest - Julie @julieweilerTanya @tanya_lleighAustin @millennial_coach.austinFollow MLC @millenniallifecoachesGet Matched with a Coach! Connect on MLC -https://millenniallifecoaches.com/mlc-members-learn-more/

This week we're starting off with Adam Busch's recent appearance on the Quadfather's BYB Podcast. Quadfather has let reddit convince him that he doesn't like me or Shuli but he's not totally sure why. Quad is so lost he thought Stuttering John's story about the Stevie Tomatoes meet up made sense. Adam Busch had to explain to BYB that WATP isn't a scripted show. Then we watch a show that is recorded in a crowded elevator followed by Tim Dillon on Joe Rogan talking about what he wanted to call his new Netflix special. We get into the falling out between Kevin Brennan and Chad Zumock and no, this is not a re-run. Tookie and Cardiff try their best to make MLC a comedy show. Opie is still complaining about his nephew's wedding and how hectic his schedule has become. He's joined by Ron the Waiter who is the worst Opie cohost of all time. Annie joins us for another round of “2 Minutes with Tom,” a new review, and your voicemails.  Support us, get bonus episodes, and watch live every Saturday and Wednesday: http://bit.ly/watp-patreon https://watp.supercast.tech/ Come to Hackamania May 9-11 in Las Vegas with promo code WATP – https://hackamania.com/ Tickets available Friday morning for Boston - http://watplive.com/  Annie's website – insanneity.com Learn more about your ad choices. Visit megaphone.fm/adchoices

Patrick is back from New York, and has learned so much from his quick jaunt to the east coast. There's a million clips of Aaron Imholte acting like a complete boob in front of his shiny new sign. How long will Steel Toe suffer at the hands of the idle-brained embarrassment pretending like his new "set" or "sign" is an improvement over the previous setup. Tookie and Dat Potato made an appearance on MLC and Chad Zumock is losing his mind about it. When will the 50-year-old wannabe comedian find solace in his own existence without coasting cluelessly around a career cul-de-sac of crime and confusion? ...

Hello and welcome to the The Cricket Slouch, a podcast for fans of all persuasions.We apologise for the long hiatus since the last episode at the conclusion of the BGT and today, we bring you our 3rd anniversary episode where in I am joined by my usual buddies Sandeep,  Ajit and Shounak to talk about a range of topics.Some of these are -1) Consolidation of power among the Big Three in the ICC via the likely proposal of two tier test cricket calendar.2) Saudi entering the game with their Grand Slam model.3) More Associate teams playing multi-nation tournaments now, thus bringing more context to those encounters.4) WPL's success heralding a better future for women's competition and payment.5) MLC looks set to be a fixture on the calendar and thus it could usher in American style professionalism and accountability in the sport. 6) The uptake of data and analysis by most teams now, esp in T20 franchises. 7) Amazon purchasing broadcasting rights (in Australia) to Asia Cup and u-19 tournaments.8) ICC launching a Challenger Trophy. Also ICC creating a task force to look into best supporting Afghan women's cricket. Allowance for using one ball per innings instead of two.As usual, a heartfelt and sincere thank you to all the contributors and listeners, without whom we would never be able to continue doing what we do.

Residents of the Tower Roosevelt area in Yellowstone sound the alarm about a self proclaimed "white redneck" who may potentially be preparing to carry out mass harm against his Yellowstone community.For bonus content join our Patreon!patreon.com/CrimeOfftheGridFor a one time donation:https://www.buymeacoffee.com/cotgFor more information about the podcast, check outhttps://crimeoffthegrid.com/Check out our Merch!!  https://in-wild-places.square.site/s/shopFollow us on Instagram https://www.instagram.com/crimeoffthegridpodcast/ and  (1) FacebookSources:U.S. District CourtDistrict of Wyoming (Sheridan)CRIMINAL DOCKET FOR CASE #: 5:19-mj-00067-MLC-1

Tisha Jones, Assessment as a Shared Journey: Cultivating Partnerships with Families & Caregivers ROUNDING UP: SEASON 3 | EPISODE 16 Families and caregivers play an essential role in students' success in school and in shaping their identities as learners. Therefore, establishing strong partnerships with families and caregivers is crucial for equitable teaching and learning. This episode is designed to help educators explore the importance of collaborating with families and caregivers and learn strategies for shifting to asset-based communication. BIOGRAPHY Tisha Jones is the senior manager of assessment at The Math Learning Center. Previously, Tisha taught math to elementary and middle school students as well as undergraduate and graduate math methods courses at Georgia State University. TRANSCRIPT Mike Wallus: As educators, we know that families and caregivers play an essential role in our students' success at school. With that in mind, what are some of the ways we can establish strong partnerships with caregivers and communicate about students' progress in asset-based ways? We'll explore these questions with MLC's [senior] assessment manager, Tisha Jones, on this episode of Rounding Up.  Welcome back to the podcast, Tisha. I think you are our first guest to appear three times. We're really excited to talk to you about assessment and families and caregivers.  Tisha Jones: I am always happy to talk to you, Mike, and I really love getting to share new ideas with people on your podcast.  Mike: So, we've titled this episode “Assessment as a Shared Journey with Families & Caregivers,” and I feel like that title—especially the words “shared journey”—say a lot about how you hope educators approach this part of their practice.  Tisha: Absolutely.  Mike: So, I want to start by being explicit about how we at The Math Learning Center think about the purpose of assessment because I think a lot of the ideas and the practices and the suggestions that you're about to offer flow out of that way that we think about the purpose.  Tisha: When we think about the purpose of assessment at The Math Learning Center, what sums it up best to me is that all assessment is formative, even if it's summative, which is a belief that you'll find in our Assessment Guide. And what that means is that assessment really is to drive learning. It's for the purpose of learning. So, it's not just to capture, “What did they learn?,” but it's, “What do they need?,” “How can we support kids?,” “How can we build on what they're learning?” over and over and over again. And so, there's no point where we're like, “OK, we've assessed it and now the learning of that is in the past.” We're always trying to build on what they're doing, what they've learned so far.  Mike: You know, I've also heard you talk about the importance of an asset-focused approach to assessment. So, for folks who haven't heard us talk about this in the past, what does that mean, Tisha?  Tisha: So that means starting with finding the things that the kids know how to do and what they understand instead of the alternative, which is looking for what they don't know, looking for the deficits in their thinking. We're looking at, “OK, here's the evidence for all the things that they can do,” and then we're looking to think about, “OK, what are their opportunities for growth?” Mike: That sounds subtle, but it is so profound a shift in thinking about what is happening when we're assessing and what we're seeing from students. How do you think that change in perspective shifts the work of assessing, but also the work of teaching?  Tisha: When I think about approaching assessment from an asset-based perspective—finding the things that kids know how to do, the things that kids understand—one, I am now on a mission to find their brilliance. I am just this brilliance detective. I'm always looking for, “What is that thing that this kid can shine at?” That's one, and a different way of thinking about it just to start with.  And then I think the other thing, too, is, I feel like when you find the things that they're doing, I can think about, “OK, what do I need to know? What can I do for them next to support them in that next step of growth?”  Mike: I think that sounds fairly simple, but there's something very different about thinking about building from something versus, say, looking for what's broken.  Tisha: For sure. And it also helps build relationships, right? If you approach any relationship from a deficit perspective, you're always focusing on the things that are wrong. And so, if we're talking about building stronger relationships with kids, coming from an asset-based perspective helps in that area too.  Mike: That's a great pivot point because if we take this notion that the purpose of assessment is to inform the ways that we support student learning, it really seems like that has a major set of implications for how and what and even why we would communicate with families and caregivers.  So, while I suspect there isn't a script for the type of communication, are there some essential components that you'd want to see in an asset-focused assessment conversation that an educator would have with a family or with their child's caregivers?  Tisha: Well, before thinking about a singular conversation, I want to back it up and think about—over the course of the school year. And I think that when we start the communication, it has to start before that first assessment. It has to start before we've seen a piece of kids' work. We have to start building those relationships with families and caregivers. We need to invite them into this process. We need to give them an opportunity to understand what we think about assessment. How are we approaching it? When we send things home, and they haven't heard of things like “proficiency” or “meeting current expectations”—those are common words that you'll see throughout the Bridges assessment materials—if parents haven't seen that, if families and caregivers haven't heard from you on what that means for you in your classroom at your school, then they have questions. It feels unfamiliar. It feels like, “Wait, what does this mean about how my child is doing in your class?”  And so, we want to start this conversation from the very beginning of the school year and continue it on continuously. And it should be this open invitation for them to participate in this process too, for them to share what they're seeing about their student at home, when they're talking about math or they're hearing how their student is talking about math. We want to know those things because that informs how we approach the instruction in class.  Mike: Let's talk about that because it really strikes me that what you're describing in terms of the meaning of proficiency or the meaning of meeting expectations—that language is likely fairly new to families and caregivers.  And I think the other thing that strikes me is, families and caregivers have their own lived experience with assessment from when they were children, perhaps with other children. And that's generally a mixed bag at best. Folks have this set of ideas about what it means when the teacher contacts them and what assessment means. So, I really hear what you're saying when you're talking about, there's work that educators need to do at the start of the year to set the stage for these conversations.  Let's try to get a little bit specific, though. What are some of the practices that you'd want teachers to consider when they're thinking about their communication?  Tisha: So, I think that starting at the very beginning of the year, most schools do some sort of a curriculum night. I would start by making sure that assessment is a part of that conversation and making sure that you're explaining what assessment means to you. Why are you assessing? What are the different ways that you're assessing? What are some things that [families and caregivers] might see coming home? Are they going to see feedback? Are they going to see scores from assessments? But how were you communicating progress? How do they know how their student is doing? And then also that invitation, right then and there, to be a part of this process, to hear from them, to hear their concerns or their ideas around feedback or the things that they've got questions about.  I would also suggest … really working hard to have that asset-based lens apply to parents and families and caregivers. I know that I have been that parent that was the last one to sign up for the parent teacher conferences, and I'm sending the apologetic email, and I'm begging for a special time slot. So, it didn't mean that I didn't care about my kids. It didn't mean that I didn't care about what they were doing. I was swamped. And so, I think we want to keep finding that asset-based lens for parents and caregivers in the same way that we do for the students.  And then making sure that you're giving them good news, not just bad news. And then making sure when you're sending any communication about how a student is doing, try to be concrete about what you're seeing, right? So, trying to say, “These are the things where I see your child's strengths. These are the strengths that I'm seeing from your student. And these are the areas where we're working on to grow. And this is what we're doing here at school, and this is what you can do to support them at home.” Mike: I was really struck by a piece of what you said, Tisha, when you really made the case for not assuming that the picture that you have in your mind as an educator is clear for families when it comes to assessment. So, really being transparent about how you think about assessment, why you're assessing, and the cadence of when parents or families or caregivers could expect to hear from you and what they could expect as well.  I know for a fact that if my teacher called my family when I was a kid, generally there was a look that came across their face when they answered the phone. And even if it was good news, they didn't think it was good news at the front end of that conversation.  Tisha: I've been there. I had my son's fifth grade teacher call me last year, and I was like, “Oh, what is this?” [laughs] Mike: One of the things that I want to talk about before we finish this conversation is homework. I want to talk a little bit about the purpose of homework. We're having this conversation in the context of Bridges in Mathematics, which is the curriculum that The Math Learning Center publishes. So, while we can't talk about how all folks think about homework, we can talk about the stance that we take when it comes to homework: what its purpose is, how we imagine families and caregivers can engage with their students around it.  Can you talk a little bit about our perspective on homework? How we think about its value, how we think about its purpose? And then we can dig a little bit into what it might look like at home, but let's start with purpose and intent.  Tisha: So, we definitely recognize that there are lots of different ideas about homework, and I think that shows in how we've structured homework through our Bridges units. Most of the time, it's set up so that there's a homework [assignment] that goes with every other session, but it's still optional. So, there's no formal expectation in our curriculum that homework is given on a nightly basis or even on an every-other-night basis. We really have left that up to the schools to determine what is best practice for their population. And I think that is actually what's really the most important thing is, understanding the families and caregivers and the situations that are in your building, and making determinations about homework that makes sense for the students that you're serving. And so, I think we've set homework up in a way that makes it so that it's easy for schools to make those decisions.  Mike: One of the things that I'm thinking about is that—again, I'm going to be autobiographical—when I was a kid, homework went back, it was graded, and it actually counted toward my grade at the end of the semester or the quarter or what have you. And I guess I wonder if a school or a district chose to not go about that, to not have homework necessarily be graded, I wonder if some families and caregivers might wonder, “What's the purpose?” I think we know that there can be a productive and important purpose—even if educators aren't grading homework and adding it to a percentage that is somehow determining students' grades, that it can actually still have purpose. How do you think about the purpose of homework, regardless of whether it's graded or not?  Tisha: So first off, I would just like to advocate not grading homework if I can.  Mike: You certainly can, yeah.  Tisha: [laughs] Mike: Let's talk about that.  Tisha: I think that, one, if we're talking about this idea of putting this score into an average grade or this percentage grade, I think that this is something that has so many different circumstances for kids at home. You have some students who get lots and lots of help. You get some students who do not have help available to them.  Another experience that has been very common when I was teaching was that I would get messages where it was like, “We were doing homework. The kid was in tears, I was in tears. This was just really hard.” And that's just not—I don't ever want that scenario for any student, for any family, for any caregiver, for anybody trying to support a child at home. I used to tell them, “If you are getting to the point where it's that level of frustration, please just stop and send me a message, write it on the homework. Just communicate something that [says,] ‘This was too hard' because that's information now that I can use.”  And so, for me, I think about [how] homework can be an opportunity for students to practice some skills and concepts and things that they've learned at home. It's an opportunity for parents, families, caregivers to see some of the things that the kids are working on at school.  Mike: What do you think is meaningful for homework? And I have kind of two bits to that. What do you think is meaningful for the child? And then, what do you think might be meaningful for the interaction between the child and their family or caregiver? What's the best case for homework? When you imagine a successful or a productive or a meaningful experience with homework at home between child and family and caregiver, what's that look like?  Tisha: Well, one of the things that I've heard families say is, “I don't know how to help my child with blank.” So, then I think it is, “Well, how do we support families and caregivers in knowing what [to] do with homework when we don't know how to tell them what to do?”  So, to me, it's about, how can we restructure the homework experience so that it's not this, “I have to tell you how to do it so you can get the right answer so you can get the grade.” But it's like, “How can I get at more of your thinking? How can I understand then what is happening or what you do know?” So, “We can't get to the answer. OK. So tell me about what you do know, and how can we build from there? How can we build understanding?” And that way it maybe will take some of the pressure off of families and caregivers to help their child get to the right answer.  Mike: What hits me is we've really come full circle with that last statement you made because you could conceivably have a student who really clearly understands a particular problem that might be a piece of homework, [who] might have some ideas that are on the right track, but ultimately perhaps doesn't get to a fully clear answer that is perfect. And you might have a student who at a certain point in time, maybe [for them] the context or the problem itself is profoundly challenging.  And in all of those cases, the question, “Tell me what you do know” or “Tell me what you're thinking” is still an opportunity to draw out the students' ideas and to focus on the assets. Even if the work as you described it is to get them to think about, “What are the questions that are really causing me to feel stuck?” That is a productive move for a family and a caregiver and a student to engage in, to kind of wonder about, “What's going on here that's making me feel stuck?” Because then, as you said, all assessment is formative.  Tisha: Mm-hmm. Mike: That homework that comes back is functioning as a formative assessment, and it allows you to think about your next moves, how you build on what the student knows, or even how you build on the questions that the student is bringing to you.  Tisha: And that's such a great point, too, is there's really more value in them coming back with an incomplete assignment or there's, I don't know, maybe “more value” is not the right way to say it. But there is value in kids coming back with an incomplete assignment or an attempted assignment, but they weren't sure how to get through all the problems—as opposed to a parent who has told their student what to do to get to all of the right answers. And so, now they have all these right answers, but it doesn't really give you a clear picture of what that student actually does understand.  So, I'd much rather have a student attempt the homework and stop because they got too stuck, because now I know that, than having a family [member] or a caregiver—somebody working with that student—feel like if they don't have all of the right answers, then it's a problem.  Mike: I think that's really great guidance, both for teachers as they're trying to set expectations and be transparent with families. But also I think it takes that pressure off of families or caregivers who feel like their work when homework shows up, is to get to a right answer. It just feels like a much more healthy relationship with homework and a much more healthy way to think about the value that it has.  Tisha: Well, in truth, it's a healthier relationship with math overall, right? That math is a process. It's not just—the value is not in just this one right answer or this paper of right answers, but it's really in, “How do we deepen our understanding?,” “How do we help students deepen their understanding and have this more positive relationship with math?” And I think that creating these homework struggles between families and caregivers and the children does not support that end goal of having a more positive relationship with math overall.  Mike: Which is a really important part of what we're looking for in a child's elementary experience.  Tisha: Absolutely.  Mike: I think that's a great place to stop. Tisha Jones, thank you so much for joining us. We would love to have you back at some time. It has been a pleasure talking with you.  Tisha: It's been great talking to you, too, Mike.  Mike: This podcast is brought to you by The Math Learning Center and the Maier Math Foundation, dedicated to inspiring and enabling all individuals to discover and develop their mathematical confidence and ability. © 2025 The Math Learning Center | www.mathlearningcenter.org  

The MLC How to Get Ahead Podcast kicks off with Special Guest and Financial Coach, Brian Rump! Brian breaks down how financial anxiety can affect business and the need for coaching to become confident to create and advance in business (6:03). We further discuss how we originate our money paradigms and money scripts, often founded in the trauma of our youth (12:14). Then Lorna pops in with a quick MLC message (22:20)! Finally, Brian shares his upcoming program detail and how to best connect with him (34:32). Learn more about Special Guest, Brian Rump | ⁠https://brianrump.com/ ⁠Take his quiz at: https://brianrump.com/financialanxietyquiz ⁠Follow the Hosts, Austin Bradley @millennial_coach.austin Tanya Lleigh @tanya_lleigh Learn More about MLC @ ⁠https://millenniallifecoaches.com⁠

What does it take to thrive aboard a luxury superyacht? Step into the world of M/Y Unbridled with veteran Captain Liam Devlin and recruitment expert Joy Weston of Crew Pacific, as they reveal what truly sets elite crew and five-star service apart on the high seas. From high-pressure chef placements to mental health, leadership red flags, MLC compliance, and training for longevity in yachting — this episode offers a rare look into the real dynamics of life and work onboard.

Rusty was sitting around today and thought. "Hmm.. What would happen if I dropped the MLC blog into Google Gemini's Notebook LM and created a podcast?" This is absolutely wild!

In this episode of How To Get Ahead, hosted by Millennial Life Coaches, Tanya and Austin have a lively discussion with special guest and founder of "Coaching with Grace", Jennifer Henriquez! During the show, Jennifer talks about her coaching journey and some of the lessons learned in order to help better serve clients (7:09). We also have a special message from Marketing & Sales Coach, Hailey Rowe (14:34)! The team then discusses the need for boundaries and prioritizing "to-do's" to best serve all parties involved (21:26). And finally, Jennifer sets the story straight about the beautiful people of New York and Austin comments on his true feelings about NY Hotdogs, eat at your own risk! (25:50). Special Guest, Coach Jennifer Henriquez | @Coaching_withGrace https://www.coachingwgrace.com/Learn more about Jennifer in the MLC Coaches Directory!Follow the Hosts: Austin Bradley @millennial_coach.austin Tanya Lleigh @tanya_lleigh Learn More about MLC @ https://millenniallifecoaches.com

In this episode, Tanya tells us “What's in that cup” (2:00)while Lorna breaks down the Day 1 blueprint for new coaches (6:59). Also, Sailynn chimes in with a quick side note about MLC (9:00). Then the team discusses the magic behind “Coach Core”, a must for new coaches (17:58) and Lorna demystifies social media and provides tips on how to make it work for you (28:01)!Become an official member of the Millennial Life Coaches community and access resources, coaches, and content! Join MLC here @ https://millenniallifecoaches.comLearn More about Coach Core @ https://www.coachcore.caCoaches Spotlight:Tanya @tanya_lleigh | Lorna – Social Media Coach, @lorna_tayInstagram.com/lorna_tayLorna @lorna_tay | Monique – Meditation & Yogi Practitioner, @the.freespirit.yogiInstagram.com/ the.freespirit.yogiAustin @millennial_coach.Austin | Bianca – ICF Certified, Health & Wellness Coach @bianca.topham.coachBiancatopham.com

I met Matt Ross-Sprang thanks to Mark Rubel. Mark was an amazing knowledge and super generous chap who sadly died not so long ago. RIP to that legend. I'll never forget that trip to visit some of America's most amazing studios. We toured most of the iconic rooms in Memphis which is the city where Matt Ross-Sprang has always resided. We went to Sun where Elvis, Johnny Cash, Howlin' Wolf all recorded and then on to Sam Philips recording service which Matt helped restore to its former glory. What a place! Just full of history and so beautiful both aesthetically and sonically. Matt has had quite the journey. He started interning at Sun Studios as a teen and now he has been awarded the key to the city of Memphis!  Somewhere in the middle of this wild ride is what we spend of our time chatting about in this pod. From humble beginnings to mixing Elvis, getting those Grammy's and the key to the city of Memphis, Matt has seen and heard an awful lot of good stuff! ________________________   Music for this episode comes courtesy of Indy500 check it here: https://indy500.bandcamp.com/    ________________________   This episode is sponsored by the MLC or The Mechanical Licensing Collective. They're a nonprofit organization that's revolutionizing how creators get paid their mechanical streaming royalties from platforms like Spotify and Apple Music in the U.S. Every month, The MLC collects the streaming data and royalties from those platforms, matches the money to the creator who has earned it, and then pays out the royalties due. With over $2.5 billion in royalties distributed and more than 50,000 Members worldwide, The MLC is already making a huge impact. And the best part? Membership is completely free! Don't leave money on the table — visit TheMLC.com today to sign up!        

In the latest MLC episode, Austin talks about balance and necessary shifts to take massive action (10:01). Tanya talks about positive intention and finding balance (17:08). Also, Austin asks about buffaloes and storms (19:01). And finally Lorna discusses how AI will influence the coaches' industry (25:05)!Become an official member of the Millennial Life Coaches community and access resources, coaches, and content! Join MLC here: https://millenniallifecoaches.comLearn More about Coach Core @ https://www.coachcore.caCoaches Spotlight:Tanya @tanya_lleigh | Sailynn - The "Fun" Business Coach, @sailynndoyle passionpurposeposture.comLorna @lorna_tay | Hailey - Marketing & Business Coach, @hailey_rowehttps://haileyrowe.com/Austin @millennial_coach.Austin | Nicole - Women's Marketing & Business Coach, @_nicolaaayhttps://www.nicoleconcepcion.co/virtual-vision-board-workshop

What's more romantic than an hour of offensive jokes & arguments? Well, you're in luck! On today's show Rob Saul (host of The Rob Saul Show) joins me, Ekul Pineapple (host of Pint Dabble Pint) & Dave Sarra (co-host of MLC) to talk about the fallout from the Atlantic City MLC meet up, the controversy around Shuli Egar's former staff members & Stuttering John's endless feuding with people.All set to a romantic soundtrack.FOLLOW THE GUESTS===================Rob Saul https://x.com/RobSaulCastEkul Pineapple https://x.com/EkulPineappleDave Sarra https://x.com/DaveXHALEBecome a supporter of this podcast: https://www.spreaker.com/podcast/it-s-hughezy-hello--3476000/support.

In late 2024, Upper House member Jeremy Buckingham addressed the NSW state parliament with a shocking possibility—one of Australia's most prolific serial killers may have never been identified.There are up to 72 unsolved cases of missing and murdered persons along the NSW North Coast, spanning from 1977 to 2024. In today's episode of Australian True Crime, guest host and criminologist Dr. Xanthé Mallett speaks with Jeremy Buckingham to discuss the disturbing possibility that these cases are connected—and why police haven't acted sooner.Do you have information regarding any of the cases discussed on this podcast? Please report it on the Crime Stoppers website or by calling 1800 333 000.Click here to subscribe to ATC Plus on Apple Podcasts and access all ATC episodes early and ad-free, as well as exclusive bonus episodes. Got a True Crime question you want answered on the podcast? Send us a question by recording a voice message here.For Support: Lifeline  on 13 11 1413 YARN on 13 92 76 (24/7 crisis support phone line for Aboriginal and Torres Strait Islander peoples)1800RESPECT: 1800 737 732CREDITS:Guest Host: Dr. Xanthé MallettGuest: The Hon. Jeremy Buckingham, MLCExecutive Producer/Editor: Matthew TankardThis episode contains extra content from Channel 9.GET IN TOUCH:https://www.australiantruecrimethepodcast.com/Follow the show on Instagram @australiantruecrimepodcast and Facebook Send us a question to have played on the show by recording a voice message here.Email the show at AusTrueCrimePodcast@gmail.com  Become a subscriber to Australian True Crime Plus here: https://plus.acast.com/s/australiantruecrime. Hosted on Acast. See acast.com/privacy for more information.

This week Ari sits down with Marc Caruso, the CEO and co-founder of Angry Mob Music, an independent music publisher based in LA. Aside from being an advocate for independent artists in the publishing world, Marc is a composer, producer, and Emmy-nominated music editor himself. He is also the President of the LA chapter of the Association of Independent Music Publishers (AIMP), a member of the Academy of Television Arts & Sciences, a member of The Recording Academy, and a member of The Motion Picture Editors Guild.In this episode, Marc describes the evolving landscape of music publishing, particularly in the context of our streaming economy. He breaks down essential terms, like ‘music publishing' itself, ‘copyright', and ‘royalties', before diving into the deeper complexities of the publishing world. Marc is incredibly transparent about how the money gets made at his publishing company—giving detailed accounts of how much sync licenses pay these days and what royalties look like for microsyncs on platforms like YouTube and TikTok. Rounding out a more global view, Marc and Ari discuss Universal's deal with Spotify, the MLC's failed lawsuit against Spotify and what all this means for independent publishers and independent songwriters. https://www.instagram.com/angrymobmusic/ Chapters00:00 The Shift from Sales to Streaming Economy04:07 Understanding Music Publishing12:50 The Role of Angry Mob Music16:55 Revenue Streams in Music Publishing21:30 The Importance of Sync Licensing22:00 Sync Fees and Their Variability29:44 Sync in Film and Advertising34:34 Micro Sync and Social Media Platforms39:41 Navigating Music Licensing for Creators45:24 The Complexities of Music Rights on Social Media49:11 The Role of Music Publishers and Advocacy57:02 Inequities in the Music Industry01:10:30 Empowering Independent Artists and PublishersEdited and mixed by Ari DavidsMusic by Brassroots DistrictProduced by the team at Ari's TakeOrder the THIRD EDITION of How to Make It in the New Music Business: https://book.aristake.com Hosted on Acast. See acast.com/privacy for more information.

Aaman and Nate break down the 2025 MLC retentions and conduct a mock draft ahead of Thursday's MLC domestic draft. Willow CEO Todd Myers joins Nate to discuss how Willow Sports is hoping to create new cricket fans in North America. 

Hoy en la Tertulia de LNCS: -Heridas de muerte, las tiendas en MLC desmienten el discurso oficial sobre su prolongación. -Rusia envía a Cuba un barco sancionado por EEUU cargado de petróleo. -Más que “captar divisas”, habría que generarlas. Un artículo del economista Orlando Freire Santana.

This is part of a longer conversation I had with Prof. James Danell about the imperative need for scholars who know German to do Lutheran history.You can support the Confessional Language Scholarship at MLC to encourage this endeavor here.Support the show Confessional Languages Scholarship Youtube ( even more behind-the-scenes videos available for certain patron tiers) Facebook Website Interview Request Form email: thelutheranhistorypodcast@gmail.com About the Host Benjamin Phelps is a 2014 graduate from Martin Luther College with a Bachelor of Arts with a German emphasis. From there went on to graduate from Wisconsin Lutheran Seminary in 2018. Ben loves all things history and enjoys traveling. A descendant of over a dozen Lutheran pastors, Ben has an interest in his family roots, especially 19th-century Lutheranism, and has written several papers and journal articles on the topic. His 2018 thesis on Wyneken won the John Harrison Ness award and the Abdel Ross Wentz prize. He is also the recipient of two awards of commendation from the Concordia Historical Institute. Ben is currently a doctoral student in historical theology through Concordia Seminary's reduced residency program in St. Louis.

Comedian Sean Donnelly (Conan, Tonight Show) joins, talk potential TicTok ban, his podcast about the suburbs w/ Dan St. Germain, people protesting drinking & driving laws from the 80's and other nonsense we enjoy. fun times!  follow Sean on IG at @seanytime

Kevin Brennan is a comedian from the 90s that your dad probably loved, but lately he's just been yelling at dead Friends and relying on YouTube viewers to pay for his bike tires. Kevin hung up his comedy coat years ago, but now he's letting Chad Zumock plan his comeback in Atlantic City! Chad takes to MLC for a big announcement about the show, and it's all falling apart at the seams in real time. WinBY2 goes live to let everyone know that this event was not on as of yesterday, and he still doesn't understand what's going on because of the lack of communication. But everyone is pumped for this disaster and NLO has all the angles as the once mighty Kevin Brennan prepares to "sell tickets" for the first time in two years! ...

Legendary skateboarder Tony Hawk teams up with skateboarder/MMA fighter/broadcaster/author/annoying personality Jason Ellis. They get a wide array of guests but on this episode they have the freestyle skateboarding GOAT Rodney Mullen and the most versatile and creative young skateboarder, Andy Anderson. So of course they talk about - Jason Ellis. Doug from Good Times Great Movies joins us to discuss Jason Ellis riding bareback on his horse. Caleb Hammer has another dummy on his show who thinks she's going to be rich. Tom Myers and Ray DeVito battle on MLC to decide who's a slightly less pathetic comic. Pat Dixon joins the show to discuss Stuttering John's final episode, an episode that Pat was a part of. We also discuss the big controversy of the week, the fact that Pat made it sound like anyone who uses Supertip gets private information from donors that they can use to dox them. Cardiff and Maribeth also joins the show for another round of Who Said It?, a review, and your voicemails.  Doug's podcast - https://www.youtube.com/@GoodTimesGreatMovies Pat Dixon's channel - https://rumble.com/user/PatDixon Cardiff's channel - http://dabbleverse.tv/ Maribeth's OnlyFans - https://onlyfans.com/maribethrosie  Support us, get bonus episodes, and watch live every Saturday and Wednesday: http://bit.ly/watp-patreon https://watp.supercast.tech/ Come to Hackamania May 9-11 in Las Vegas with promo code WATP – https://hackamania.com/ Learn more about your ad choices. Visit megaphone.fm/adchoices

Happy holidays! We'll be sharing snippets from Latent Space LIVE! through the break bringing you the best of 2024! We want to express our deepest appreciation to event sponsors AWS, Daylight Computer, Thoth.ai, StrongCompute, Notable Capital, and most of all all our LS supporters who helped fund the gorgeous venue and A/V production!For NeurIPS last year we did our standard conference podcast coverage interviewing selected papers (that we have now also done for ICLR and ICML), however we felt that we could be doing more to help AI Engineers 1) get more industry-relevant content, and 2) recap 2024 year in review from experts. As a result, we organized the first Latent Space LIVE!, our first in person miniconference, at NeurIPS 2024 in Vancouver. Today, we're proud to share Loubna's highly anticipated talk (slides here)!Synthetic DataWe called out the Synthetic Data debate at last year's NeurIPS, and no surprise that 2024 was dominated by the rise of synthetic data everywhere:* Apple's Rephrasing the Web, Microsoft's Phi 2-4 and Orca/AgentInstruct, Tencent's Billion Persona dataset, DCLM, and HuggingFace's FineWeb-Edu, and Loubna's own Cosmopedia extended the ideas of synthetic textbook and agent generation to improve raw web scrape dataset quality* This year we also talked to the IDEFICS/OBELICS team at HuggingFace who released WebSight this year, the first work on code-vs-images synthetic data.* We called Llama 3.1 the Synthetic Data Model for its extensive use (and documentation!) of synthetic data in its pipeline, as well as its permissive license. * Nemotron CC and Nemotron-4-340B also made a big splash this year for how they used 20k items of human data to synthesize over 98% of the data used for SFT/PFT.* Cohere introduced Multilingual Arbitrage: Optimizing Data Pools to Accelerate Multilingual Progress observing gains of up to 56.5% improvement in win rates comparing multiple teachers vs the single best teacher model* In post training, AI2's Tülu3 (discussed by Luca in our Open Models talk) and Loubna's Smol Talk were also notable open releases this year.This comes in the face of a lot of scrutiny and criticism, with Scale AI as one of the leading voices publishing AI models collapse when trained on recursively generated data in Nature magazine bringing mainstream concerns to the potential downsides of poor quality syndata:Part of the concerns we highlighted last year on low-background tokens are coming to bear: ChatGPT contaminated data is spiking in every possible metric:But perhaps, if Sakana's AI Scientist pans out this year, we will have mostly-AI AI researchers publishing AI research anyway so do we really care as long as the ideas can be verified to be correct?Smol ModelsMeta surprised many folks this year by not just aggressively updating Llama 3 and adding multimodality, but also adding a new series of “small” 1B and 3B “on device” models this year, even working on quantized numerics collaborations with Qualcomm, Mediatek, and Arm. It is near unbelievable that a 1B model today can qualitatively match a 13B model of last year:and the minimum size to hit a given MMLU bar has come down roughly 10x in the last year. We have been tracking this proxied by Lmsys Elo and inference price:The key reads this year are:* MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases* Apple Intelligence Foundation Language Models* Hymba: A Hybrid-head Architecture for Small Language Models* Loubna's SmolLM and SmolLM2: a family of state-of-the-art small models with 135M, 360M, and 1.7B parameters on the pareto efficiency frontier.* and Moondream, which we already covered in the 2024 in Vision talkFull Talk on YouTubeplease like and subscribe!Timestamps* [00:00:05] Loubna Intro* [00:00:33] The Rise of Synthetic Data Everywhere* [00:02:57] Model Collapse* [00:05:14] Phi, FineWeb, Cosmopedia - Synthetic Textbooks* [00:12:36] DCLM, Nemotron-CC* [00:13:28] Post Training - AI2 Tulu, Smol Talk, Cohere Multilingual Arbitrage* [00:16:17] Smol Models* [00:18:24] On Device Models* [00:22:45] Smol Vision Models* [00:25:14] What's NextTranscript2024 in Synthetic Data and Smol Models[00:00:00] ​[00:00:05] Loubna Intro[00:00:05] Speaker: ​I'm very happy to be here. Thank you for the invitation. So I'm going to be talking about synthetic data in 2024. And then I'm going to be talking about small on device models. So I think the most interesting thing about synthetic data this year is that like now we have it everywhere in the large language models pipeline.[00:00:33] The Rise of Synthetic Data Everywhere[00:00:33] Speaker: I think initially, synthetic data was mainly used just for post training, because naturally that's the part where we needed human annotators. And then after that, we realized that we don't really have good benchmarks to [00:01:00] measure if models follow instructions well, if they are creative enough, or if they are chatty enough, so we also started using LLMs as judges.[00:01:08] Speaker: Thank you. And I think this year and towards the end of last year, we also went to the pre training parts and we started generating synthetic data for pre training to kind of replace some parts of the web. And the motivation behind that is that you have a lot of control over synthetic data. You can control your prompt and basically also the kind of data that you generate.[00:01:28] Speaker: So instead of just trying to filter the web, you could try to get the LLM to generate what you think the best web pages could look like and then train your models on that. So this is how we went from not having synthetic data at all in the LLM pipeline to having it everywhere. And so the cool thing is like today you can train an LLM with like an entirely synthetic pipeline.[00:01:49] Speaker: For example, you can use our Cosmopedia datasets and you can train a 1B model on like 150 billion tokens that are 100 percent synthetic. And those are also of good quality. And then you can [00:02:00] instruction tune the model on a synthetic SFT dataset. You can also do DPO on a synthetic dataset. And then to evaluate if the model is good, you can use.[00:02:07] Speaker: A benchmark that uses LLMs as a judge, for example, MTBench or AlpacaEvil. So I think this is like a really mind blowing because like just a few years ago, we wouldn't think this is possible. And I think there's a lot of concerns about model collapse, and I'm going to talk about that later. But we'll see that like, if we use synthetic data properly and we curate it carefully, that shouldn't happen.[00:02:29] Speaker: And the reason synthetic data is very popular right now is that we have really strong models, both open and closed. It is really cheap and fast to use compared to human annotations, which cost a lot and take a lot of time. And also for open models right now, we have some really good inference frameworks.[00:02:47] Speaker: So if you have enough GPUs, it's really easy to spawn these GPUs and generate like a lot of synthetic data. Some examples are VLM, TGI, and TensorRT.[00:02:57] Model Collapse[00:02:57] Speaker: Now let's talk about the elephant in the room, model [00:03:00] collapse. Is this the end? If you look at the media and all of like, for example, some papers in nature, it's really scary because there's a lot of synthetic data out there in the web.[00:03:09] Speaker: And naturally we train on the web. So we're going to be training a lot of synthetic data. And if model collapse is going to happen, we should really try to take that seriously. And the other issue is that, as I said, we think, a lot of people think the web is polluted because there's a lot of synthetic data.[00:03:24] Speaker: And for example, when we're building fine web datasets here at Guillerm and Hinek, we're interested in like, how much synthetic data is there in the web? So there isn't really a method to properly measure the amount of synthetic data or to save a webpage synthetic or not. But one thing we can do is to try to look for like proxy words, for example, expressions like as a large language model or words like delve that we know are actually generated by chat GPT.[00:03:49] Speaker: We could try to measure the amount of these words in our data system and compare them to the previous years. For example, here, we measured like a, these words ratio in different dumps of common crawl. [00:04:00] And we can see that like the ratio really increased after chat GPT's release. So if we were to say that synthetic data amount didn't change, you would expect this ratio to stay constant, which is not the case.[00:04:11] Speaker: So there's a lot of synthetic data probably on the web, but does this really make models worse? So what we did is we trained different models on these different dumps. And we then computed their performance on popular, like, NLP benchmarks, and then we computed the aggregated score. And surprisingly, you can see that the latest DOMs are actually even better than the DOMs that are before.[00:04:31] Speaker: So if there's some synthetic data there, at least it did not make the model's worse. Yeah, which is really encouraging. So personally, I wouldn't say the web is positive with Synthetic Data. Maybe it's even making it more rich. And the issue with like model collapse is that, for example, those studies, they were done at like a small scale, and you would ask the model to complete, for example, a Wikipedia paragraph, and then you would train it on these new generations, and you would do that every day.[00:04:56] Speaker: iteratively. I think if you do that approach, it's normal to [00:05:00] observe this kind of behavior because the quality is going to be worse because the model is already small. And then if you train it just on its generations, you shouldn't expect it to become better. But what we're really doing here is that we take a model that is very large and we try to distill its knowledge into a model that is smaller.[00:05:14] Phi, FineWeb, Cosmopedia - Synthetic Textbooks[00:05:14] Speaker: And in this way, you can expect to get like a better performance for your small model. And using synthetic data for pre-training has become really popular. After the textbooks are all you need papers where Microsoft basically trained a series of small models on textbooks that were using a large LLM.[00:05:32] Speaker: And then they found that these models were actually better than models that are much larger. So this was really interesting. It was like first of its time, but it was also met with a lot of skepticism, which is a good thing in research. It pushes you to question things because the dataset that they trained on was not public, so people were not really sure if these models are really good or maybe there's just some data contamination.[00:05:55] Speaker: So it was really hard to check if you just have the weights of the models. [00:06:00] And as Hugging Face, because we like open source, we tried to reproduce what they did. So this is our Cosmopedia dataset. We basically tried to follow a similar approach to what they documented in the paper. And we created a synthetic dataset of textbooks and blog posts and stories that had almost 30 billion tokens.[00:06:16] Speaker: And we tried to train some models on that. And we found that like the key ingredient to getting a good data set that is synthetic is trying as much as possible to keep it diverse. Because if you just throw the same prompts as your model, like generate like a textbook about linear algebra, and even if you change the temperature, the textbooks are going to look alike.[00:06:35] Speaker: So there's no way you could scale to like millions of samples. And the way you do that is by creating prompts that have some seeds that make them diverse. In our case, the prompt, we would ask the model to generate a textbook, but make it related to an extract from a webpage. And also we try to frame it within, to stay within topic.[00:06:55] Speaker: For example, here, we put like an extract about cardiovascular bioimaging, [00:07:00] and then we ask the model to generate a textbook related to medicine that is also related to this webpage. And this is a really nice approach because there's so many webpages out there. So you can. Be sure that your generation is not going to be diverse when you change the seed example.[00:07:16] Speaker: One thing that's challenging with this is that you want the seed samples to be related to your topics. So we use like a search tool to try to go all of fine web datasets. And then we also do a lot of experiments with the type of generations we want the model to generate. For example, we ask it for textbooks for middle school students or textbook for college.[00:07:40] Speaker: And we found that like some generation styles help on some specific benchmarks, while others help on other benchmarks. For example, college textbooks are really good for MMLU, while middle school textbooks are good for benchmarks like OpenBookQA and Pico. This is like a sample from like our search tool.[00:07:56] Speaker: For example, you have a top category, which is a topic, and then you have some [00:08:00] subtopics, and then you have the topic hits, which are basically the web pages in fine web does belong to these topics. And here you can see the comparison between Cosmopedia. We had two versions V1 and V2 in blue and red, and you can see the comparison to fine web, and as you can see throughout the training training on Cosmopedia was consistently better.[00:08:20] Speaker: So we managed to get a data set that was actually good to train these models on. It's of course so much smaller than FineWeb, it's only 30 billion tokens, but that's the scale that Microsoft data sets was, so we kind of managed to reproduce a bit what they did. And the data set is public, so everyone can go there, check if everything is all right.[00:08:38] Speaker: And now this is a recent paper from NVIDIA, Neumatron CC. They took things a bit further, and they generated not a few billion tokens, but 1. 9 trillion tokens, which is huge. And we can see later how they did that. It's more of, like, rephrasing the web. So we can see today that there's, like, some really huge synthetic datasets out there, and they're public, so, [00:09:00] like, you can try to filter them even further if you want to get, like, more high quality corpses.[00:09:04] Speaker: So for this, rephrasing the web this approach was suggested in this paper by Pratyush, where basically in this paper, they take some samples from C4 datasets, and then they use an LLM to rewrite these samples into a better format. For example, they ask an LLM to rewrite the sample into a Wikipedia passage or into a Q& A page.[00:09:25] Speaker: And the interesting thing in this approach is that you can use a model that is Small because it doesn't, rewriting doesn't require knowledge. It's just rewriting a page into a different style. So the model doesn't need to have like knowledge that is like extensive of what is rewriting compared to just asking a model to generate a new textbook and not giving it like ground truth.[00:09:45] Speaker: So here they rewrite some samples from C4 into Q& A, into Wikipedia, and they find that doing this works better than training just on C4. And so what they did in Nemo Trans CC is a similar approach. [00:10:00] They rewrite some pages from Common Crawl for two reasons. One is to, like improve Pages that are low quality, so they rewrite them into, for example, Wikipedia page, so they look better.[00:10:11] Speaker: And another reason is to create more diverse datasets. So they have a dataset that they already heavily filtered, and then they take these pages that are already high quality, and they ask the model to rewrite them in Question and Answer format. into like open ended questions or like multi choice questions.[00:10:27] Speaker: So this way they can reuse the same page multiple times without fearing like having multiple duplicates, because it's the same information, but it's going to be written differently. So I think that's also a really interesting approach for like generating synthetic data just by rephrasing the pages that you already have.[00:10:44] Speaker: There's also this approach called Prox where they try to start from a web page and then they generate a program which finds how to write that page to make it better and less noisy. For example, here you can see that there's some leftover metadata in the web page and you don't necessarily want to keep that for training [00:11:00] your model.[00:11:00] Speaker: So So they train a model that can generate programs that can like normalize and remove lines that are extra. So I think this approach is also interesting, but it's maybe less scalable than the approaches that I presented before. So that was it for like rephrasing and generating new textbooks.[00:11:17] Speaker: Another approach that I think is really good and becoming really popular for using synthetic data for pre training is basically building a better classifiers. For filtering the web for example, here we release the data sets called fine web edu. And the way we built it is by taking Llama3 and asking it to rate the educational content of web pages from zero to five.[00:11:39] Speaker: So for example, if a page is like a really good textbook that could be useful in a school setting, it would get a really high score. And if a page is just like an advertisement or promotional material, it would get a lower score. And then after that, we take these synthetic annotations and we train a classifier on them.[00:11:57] Speaker: It's a classifier like a BERT model. [00:12:00] And then we run this classifier on all of FineWeb, which is a 15 trillion tokens dataset. And then we only keep the pages that have like a score that's higher than 3. So for example, in our case, we went from 15 trillion tokens to 3. to just 1. 5 trillion tokens. Those are really highly educational.[00:12:16] Speaker: And as you can see here, a fine web EDU outperforms all the other public web datasets by a larger margin on a couple of benchmarks here, I show the aggregated score and you can see that this approach is really effective for filtering web datasets to get like better corpuses for training your LLMs.[00:12:36] DCLM, Nemotron-CC[00:12:36] Speaker: Others also try to do this approach. There's, for example, the DCLM datasets where they also train the classifier, but not to detect educational content. Instead, they trained it on OpenHermes dataset, which is a dataset for instruction tuning. And also they explain like IAM5 subreddits, and then they also get really high quality dataset which is like very information dense and can help [00:13:00] you train some really good LLMs.[00:13:01] Speaker: And then Nemotron Common Crawl, they also did this approach, but instead of using one classifier, they used an ensemble of classifiers. So they used, for example, the DCLM classifier, and also classifiers like the ones we used in FineWebEducational, and then they combined these two. Scores into a, with an ensemble method to only retain the best high quality pages, and they get a data set that works even better than the ones we develop.[00:13:25] Speaker: So that was it for like synthetic data for pre-training.[00:13:28] Post Training - AI2 Tulu, Smol Talk, Cohere Multilingual Arbitrage[00:13:28] Speaker: Now we can go back to post training. I think there's a lot of interesting post training data sets out there. One that was released recently, the agent instructs by Microsoft where they basically try to target some specific skills. And improve the performance of models on them.[00:13:43] Speaker: For example, here, you can see code, brain teasers, open domain QA, and they managed to get a dataset that outperforms that's when fine tuning Mistral 7b on it, it outperforms the original instruct model that was released by Mistral. And as I said, to get good synthetic data, you really [00:14:00] have to have a framework to make sure that your data is diverse.[00:14:03] Speaker: So for example, for them, they always. And then they see the generations on either source code or raw text documents, and then they rewrite them to make sure they're easier to generate instructions from, and then they use that for their like instruction data generation. There's also the Tool3SFT mixture, which was released recently by Allen AI.[00:14:23] Speaker: It's also really good quality and it covers a wide range of tasks. And the way they make sure that this dataset is diverse is by using personas from the persona hub datasets. Which is basically a data set of like I think over a million personas. And for example, in the tool mixture to generate like a new code snippet, they would give like the model persona, for example, a machine learning researcher interested in neural networks, and then ask it to generate like a coding problem.[00:14:49] Speaker: This way you make sure that your data set is really diverse, and then you can further filter the data sets, for example, using the reward models. We also released a dataset called Smalltalk, [00:15:00] and we also tried to cover the wide range of tasks, and as you can see here, for example, when fine tuning Mistral 7b on the dataset, we also outperformed the original Mistral instructs on a number of benchmarks, notably on mathematics and instruction following with ifevil.[00:15:18] Speaker: Another paper that's really interesting I wanted to mention is this one called Multilingual Data Arbitrage by Cohere. And basically they want to generate a data set for post training that is multilingual. And they have a really interesting problem. It's the fact that there isn't like one model that's really good at all the languages they wanted.[00:15:36] Speaker: So what they do is that like they use not just one teacher model, but multiple teachers. And then they have a router which basically sends the prompts they have to all these models. And then they get the completions and they have a reward model that traces all these generations and only keeps the best one.[00:15:52] Speaker: And this is like arbitrage and finance. So well, I think what's interesting in this, it shows that like synthetic data, it doesn't have to come from a single model. [00:16:00] And because we have so many good models now, you could like pull these models together and get like a dataset that's really high quality and that's diverse and that's covers all your needs.[00:16:12] Speaker: I was supposed to put a meme there, but. Yeah, so that was it for like a synthetic data.[00:16:17] Smol Models[00:16:17] Speaker: Now we can go to see what's happening in the small models field in 2024. I don't know if you know, but like now we have some really good small models. For example, Lama 3. 2 1B is. It matches Lama 2. 13b from, that was released last year on the LMSYS arena, which is basically the default go to leaderboard for evaluating models using human evaluation.[00:16:39] Speaker: And as you can see here, the scores of the models are really close. So I think we've made like hugely forward in terms of small models. Of course, that's one, just one data point, but there's more. For example, if you look at this chart from the Quint 2. 5 blog post, it shows that today we have some really good models that are only like 3 billion parameters [00:17:00] and 4 billion that score really high on MMLU.[00:17:03] Speaker: Which is a really popular benchmark for evaluating models. And you can see here that the red, the blue dots have more than 65 on MMLU. And the grey ones have less. And for example, Llama33b had less. So now we have a 3b model that outperforms a 33b model that was released earlier. So I think now people are starting to realize that like, we shouldn't just scale and scale models, but we should try to make them more efficient.[00:17:33] Speaker: I don't know if you knew, but you can also chat with a 3B plus model on your iPhone. For example, here, this is an app called PocketPal, where you can go and select a model from Hugging Face. It has a large choice. For example, here we loaded the 5. 3. 5, which is 3. 8 billion parameters on this iPhone. And we can chat with this and you can see that even the latency is also acceptable.[00:17:57] Speaker: For example, here, I asked it to give me a joke about [00:18:00] NeurIPS. So let's see what it has to say.[00:18:06] Speaker: Okay, why did the neural network attend NeurIPS? Because it heard there would be a lot of layers and fun and it wanted to train its sense of humor. So not very funny, but at least it can run on device. Yeah, so I think now we have good small models, but we also have like good frameworks and tools to use these small models.[00:18:24] On Device Models[00:18:24] Speaker: So I think we're really close to having like really on edge and on device models that are really good. And I think for a while we've had this narrative. But just training larger models is better. Of course, this is supported by science scaling laws. As you can see here, for example, when we scale the model size, the loss is lower and obviously you get a better model.[00:18:46] Speaker: But and we can see this, for example, in the GPT family of models, how we went from just a hundred million parameters to more than a trillion. parameters. And of course, we all observed the performance improvement when using the latest model. But [00:19:00] one thing that we shouldn't forget is that when we scale the model, we also scale the inference costs and time.[00:19:05] Speaker: And so the largest models were are going to cost so much more. So I think now instead of just building larger models, we should be focusing on building more efficient models. It's no longer a race for the largest models since these models are really expensive to run and they require like a really good infrastructure to do that and they cannot run on, for example, consumer hardware.[00:19:27] Speaker: And when you try to build more efficient models that match larger models, that's when you can really unlock some really interesting on device use cases. And I think a trend that we're noticing now is the trend of training smaller models longer. For example, if you compare how much, how long LLAMA was trained compared to LLAMA3, there is a huge increase in the pre training length.[00:19:50] Speaker: LLAMA was trained on 1 trillion tokens, but LLAMA3 8b was trained on 15 trillion tokens. So Meta managed to get a model that's the same size, but But it performs so much [00:20:00] better by choosing to like spend the sacrifice during training, because as we know, training is a one time cost, but inference is something that's ongoing.[00:20:08] Speaker: If we want to see what are like the small models reads in 2024, I think this mobile LLM paper by Meta is interesting. They try to study different models that are like have the less than 1 billion parameters and find which architecture makes most sense for these models. For example, they find that depth is more important than width.[00:20:29] Speaker: So it's more important to have models that have like more layers than just one. making them more wide. They also find that GQA helps, that tying the embedding helps. So I think it's a nice study overall for models that are just a few hundred million parameters. There's also the Apple intelligence tech report, which is interesting.[00:20:48] Speaker: So for Apple intelligence, they had two models, one that was like on server and another model that was on device. It had 3 billion parameters. And I think the interesting part is that they trained this model using [00:21:00] pruning. And then distillation. And for example, they have this table where they show that, like, using pruning and distillation works much better than training from scratch.[00:21:08] Speaker: And they also have some interesting insights about, like, how they specialize their models on specific tasks, like, for example, summarization and rewriting. There's also this paper by NVIDIA that was released recently. I think you've already had a talk about, like, hybrid models that was all interesting.[00:21:23] Speaker: And this model, they used, like, a hybrid architecture between state space models and transformers. And they managed to train a 1B model that's really performant without needing to train it on a lot of tokens. And regarding our work, we just recently released SmallM2, so it's a series of three models, which are the best in class in each model size.[00:21:46] Speaker: For example, our 1. 7b model outperforms Lama 1b and also Qt 2. 5. And how we managed to train this model is the following. That's where you spent a lot of time trying to curate the pre training datasets. We did a lot of [00:22:00] ablations, trying to find which datasets are good and also how to mix them. We also created some new math and code datasets that we're releasing soon.[00:22:08] Speaker: But you basically really spent a lot of time trying to find what's the best mixture that you can train these models on. And then we spent some time trying to like we also trained these models for very long. For example, small M1 was trained only on 1 trillion tokens, but this model is trained on 11 trillion tokens.[00:22:24] Speaker: And we saw that the performance kept improving. The models didn't really plateau mid training, which I think is really interesting. It shows that you can train such small models for very long and keep getting performance gains. What's interesting about SmallLM2 is that it's fully open. We also released, like the pre training code base, the fine tuning code, the datasets, and also evaluation in this repository.[00:22:45] Smol Vision Models[00:22:45] Speaker: Also there's, like, really interesting small models for text, but also for vision. For example, here you can see SmallVLM, which is a 2B model that's really efficient. It doesn't consume a lot of RAM, and it also has a good performance. There's also Moondream 0. [00:23:00] 5b, which was released recently. It's like the smallest visual language model.[00:23:04] Speaker: And as you can see, there isn't like a big trade off compared to Moondream 2b. So now I showed you that we have some really good small models. We also have the tools to use them, but why should you consider using small models and when? I think, like, small models are really interesting because of the on device feature.[00:23:23] Speaker: Because these models are small and they can run fast, you can basically run them on your laptop, but also on your mobile phone. And this means that your dataset stays locally. You don't have to send your queries to third parties. And this really enhances privacy. That was, for example, one of the big selling points for Apple Intelligence.[00:23:42] Speaker: Also, right now, we really have a lot of work to do. So many frameworks to do on device inference. For example, there's MLX, MLC, Llama, CPP, Transformers, JS. So we have a lot of options and each of them have like great features. So you have so many options for doing that. Small models are also really powerful if you choose to specialize them.[00:24:00][00:24:00] Speaker: For example, here there's a startup called Numind, which took small LM and then they fine tuned it on text extraction datasets. And they managed to get a model that's not very far from models that are much larger. So I think text extraction is like one use case where small models can be really performant and it makes sense to use them instead of just using larger models.[00:24:19] Speaker: You can also chat with these models in browser. For example, here, you can go there, you can load the model, you can even turn off your internet and just start chatting with the model locally. Speaking of text extraction, if you don't want to fine tune the models, there's a really good method of structure generation.[00:24:36] Speaker: We can basically force the models to follow a JSON schema that you defined. For example, here, we try to force the model to follow a schema for extracting key information from GitHub issues. So you can input free text, which is a complaint about a GitHub repository, something not working. And then you can run it there and the model can extract anything that is relevant for your GitHub issue creation.[00:24:58] Speaker: For example, the [00:25:00] priority, for example, here, priority is high, the type of the issue bug, and then a title and the estimation of how long this will take to fix. And you can just like do this in the browser, you can transform your text into a GitHub issue that's properly formatted.[00:25:14] What's Next[00:25:14] Speaker: So what's next for synthetic data and small models?[00:25:18] Speaker: I think that domain specific synthetic data is going to be, it's already important, it's going to be even more important. For example, generating synthetic data for math. I think this really would help improve the reasoning of a lot of models. And a lot of people are doing it, for example, Quint 2. 12 math, everyone's trying to reproduce a one.[00:25:37] Speaker: And so I think for synthetic data, trying to specialize it on some domains is going to be really important. And then for small models, I think specializing them through fine tuning, it's also going to be really important because I think a lot of companies are just trying to use these large models because they are better.[00:25:53] Speaker: But on some tasks, I think you can already get decent performance with small models. So you don't need to Pay like a [00:26:00] cost that's much larger just to make your model better at your task by a few percent. And this is not just for text. And I think it also applies for other modalities like vision and audio.[00:26:11] Speaker: And I think you should also watch out for on device frameworks and applications. For example, like the app I showed, or lama, all these frameworks are becoming really popular and I'm pretty sure that we're gonna get like more of them in 2025. And users really like that. Maybe for other, I should also say hot take.[00:26:28] Speaker: I think that like in AI, we just started like with fine tuning, for example, trying to make BERT work on some specific use cases, and really struggling to do that. And then we had some models that are much larger. So we just switched to like prompt engineering to get the models And I think we're going back to fine tuning where we realize these models are really costly.[00:26:47] Speaker: It's better to use just a small model or try to specialize it. So I think it's a little bit of a cycle and we're going to start to see like more fine tuning and less of just like a prompt engineering the models. So that was my talk. Thank you for following. And if you have [00:27:00] any questions, we can take them now. 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Stuttering John was on the Opie and Jim show back in 2015 with Dave Attell. John takes over the interview and boy is he desperate for a job! Wow! Jenny Jingles joins us on this special episode where we travel back in time to discover how out of his league John is with Jim Norton and Dave Atell. Then we watch Rob Saul defend himself for applauding his ex-wife's child dying. Spoiler - it wasn't his fault. We also check out Cardiff on MLC this past weekend where KB once again does something he used to rail against and promised he'd never do. Cardiff was fantastic! Support us, get bonus episodes, and watch live every Saturday and Wednesday: http://bit.ly/watp-patreon https://watp.supercast.tech/ Learn more about your ad choices. Visit megaphone.fm/adchoices