Podcasts about analyzing

1.14.25, Kevin Sheehan analyzes Jayden Daniels historic performance in the win against the Buccaneers.

1.14.25 Hour 1, Kevin Sheehan revisits the Commanders huge win against the Buccaneers in the Wildcard round of the playoffs, Kevin Sheehan analyzes Jayden Daniels historic performance in the win against the Buccaneers, can the Commanders put up points consistently against the Lions?

Jacob and Elohim Monard dive into the significant shifts in voting patterns among the Latino community in the recent U.S. presidential election, highlighting how Trump's appeal has grown, particularly among younger Latino voters. Jacob and Elo discuss the complexities behind these trends, noting that while Trump secured around 40% of the Latino vote, demographic breakdowns reveal nuanced support, especially among Latino men and younger generations. Elo emphasizes that the Latino population is diverse, and their political alignment is influenced by various factors, including migration stories, geographic locations, and generational differences. The conversation further explores how the political dynamics in the U.S. reflect broader trends in Latin America, suggesting that Trump's brand of populism, or "Trumpismo," may find resonance beyond U.S. borders. The episode concludes with reflections on how these evolving narratives will shape both Latino politics and U.S. relations with Latin America moving forward. --Timestamps:(00:03) - Intro(01:34) - Analyzing the Latino Vote in the 2024 Presidential Election(22:03) - The Changing Dynamics of Latino Political Support(28:01) - The Impact of Social Media on Political Awareness Among Young Latinos(44:23) - The Evolving Identity of Hispanics in America(58:33) - The Rise of Trumpismo and Its Implications(01:03:41) - The Political Landscape: A Shift in Focus--Jacob Shapiro Site: jacobshapiro.comJacob Twitter: x.com/JacobShapCI Site: cognitive.investmentsSubscribe to the Newsletter: bit.ly/weekly-sitrep--The Jacob Shapiro Show is produced and edited by Audiographies LLC. More information at audiographies.com --Jacob Shapiro is a speaker, consultant, author, and researcher covering global politics and affairs, economics, markets, technology, history, and culture. He speaks to audiences of all sizes around the world, helps global multinationals make strategic decisions about political risks and opportunities, and works directly with investors to grow and protect their assets in today's volatile global environment. His insights help audiences across industries like finance, agriculture, and energy make sense of the world.Cognitive Investments is an investment advisory firm, founded in 2019 that provides clients with a nuanced array of financial planning, investment advisory and wealth management services. We aim to grow both our clients' material wealth (i.e. their existing financial assets) and their human wealth (i.e. their ability to make good strategic decisions for their business, family, and career).--This podcast uses the following third-party services for analysis: Podtrac - https://analytics.podtrac.com/privacy-policy-gdrp

On this Screaming in the Cloud Replay, Corey is joined by James Governor, co-founder of RedMonk. In this throwback, they discuss how RedMonk is different from traditional analyst firms. You'll also learn how Corey and James met, how James credentialed Corey as a bona fide industry analyst on Twitter, and how anyone can be an analyst in theory. Beyond that, James explains the mindset required to give advice as an analyst, what attracted him to becoming an analyst in the first place, and why RedMonk focuses on the qualitative instead of the quantitative.Show Highlights(0:00) Intro(0:29) The Wiz sponsor read(1:31) What lead James to become an analyst and founding RedMonk(4:36) Why James believes developers are the “ new monarchmakers”(10:06) Recounting the time James credentialed Corey as an analyst on Twitter(12:24) Who and what are analysts?(17:44) The woes of rage-driven development(21:01) The Wiz sponsor read(21:55) Why Corey thinks James is a model Twitter user and advocate(25:23) What makes RedMonk's industry events stick out from everyone else(35:15) Why James habitually changes his name on Twitter(36:45) Where you can find more from JamesAbout James GovernorJames Governor founded RedMonk in 2002 with Stephen O'Grady. They focus on developers as the real key influencers in tech. Understanding that people choose technology because of gut instincts not facts per se. As an ex-journalist, James has managed teams and news agendas in the weekly publication grind. He has also been IBM and MS watcher since 1995.LinksRedMonk: https://redmonk.com/James's Twitter: https://twitter.com/MonkChipsMonktoberfest: https://monktoberfest.com/Monki Gras: https://monkigras.com/Original Episodehttps://www.lastweekinaws.com/podcast/screaming-in-the-cloud/analyzing-analysts-with-james-governor/SponsorThe Wiz: wiz.io/scream

Following the Apostle Paul's instruction to “continue in prayer,” we begin our excursion by studying the prayers of the patriarchs through the Pentateuch. Analyzing how they prayed, what they prayed for, and how they responded when God answered their prayers helps us to understand how God deals with us when we pray. VF-2317 Colossians 4:2 Watch, Listen and Learn 24x7 at PastorMelissaScott.com Pastor Melissa Scott teaches from Faith Center in Glendale. Call 1-800-338-3030 24x7 to leave a message for Pastor Scott. You may make reservations to attend a live service, leave a prayer request or make a commitment. Pastor Scott appreciates messages and reads them often during live broadcasts. Follow @Pastor_Scott on Twitter and visit her official Facebook page @Pastor.M.Scott. Download Pastor Scott's "Understand the Bible" app for iPhone, iPad and iPod at the Apple App Store and for Android devices in the Google Store. Pastor Scott can also be seen 24x7 on Roku and Amazon Fire on the "Understand the Bible?" channel. ©2025 Pastor Melissa Scott, Ph.D., All Rights Reserved

Wondering where the hot spots to invest in 2025 are located I'm sharing which markets I think will be best for our community! Today on The Lady Landlords Podcast, I'm discussing the investing locations ins and outs for 2025. In this episode, you'll learn how to: #1. Analyze the hot market lists. #2. Craft your criteria for a good market. #3. Digest information from real estate gurus. Stay tuned until the end to learn the secret to picking the best locations you won't regret! ===

Asking yourself ‘What am I feeling?' can feel very daunting, but understanding your emotions is a powerful step toward emotional self-awareness. Join me today as we explore how analyzing your emotions can bring you closer to yourself and God.WHAT YOU'LL LEARN:[00:33] How Can We Build a Habit Around Noticing Our Emotions?[05:14] The First Question to Ask Yourself: “What Am I Feeling?”[11:54] The Second Question to Ask Yourself: “Why Does It Make Sense That I'm Feeling This Way?”[13:46] What Keeps You From Asking Yourself These Questions?[15:08] We Are In Control of Our Actions and Habits[15:55] I'd Love to Help You Get to The Next Level in Your Life - Book a Free 15-Minute Call With Me!RESOURCES:Tired of up-and-down feelings stealing your peace, sabotaging your relationships, and filling your mind with self-defeating thoughts? If so, make sure to get my new book, “Emotional Confidence: 3 Simple Steps to Manage Emotions with Science and Scripture”.Want to see what Emotional Confidence is about? Download the first chapter for FREE!Book a Free 15-Minute Call to discuss the next steps on your emotional management journey.Ready to know how to manage emotions for more calm, stronger relationships, and a closer walk with God? Want to implement the concepts discussed in my book "Emotional Confidence"? Then join the Emotional Confidence Club!RELATED EPISODES:All Episodes on EmotionsSend us a text

Nick Kypreos and Justin Bourne are joined by Sportsnet's Garry Galley (7:39) to tour the Canadian teams in the NHL, including rookie Dustin Wolf's solid goaltending with the Calgary Flames, Leon Draisaitl's push for the Hart Trophy this season, the Ottawa Senators' sprint for a wild card spot, a hot Montreal Canadiens club, and managing a bed of relationships in Vancouver. Next, Nick, Justin and Sam McKee chat Cutter Gauthier's fiery return to Philadelphia, Eric Staal's case for a Hockey Hall of Fame bid, and the Senators' arena situation for the future. The views and opinions expressed in this podcast are those of the hosts and guests and do not necessarily reflect the position of Rogers Sports & Media or any affiliates.

In this episode of Perfectly Good Podcast, hosts Jesse and Sylvan discuss John Hiatt's song 'It All Comes Back Someday' from his album Mystic Pinball. They explore the song's intricate lyrics, musical composition, and the puzzling narrative it presents. Despite some confusion over the verses, the hosts appreciate the song's upbeat chorus and the significance of memories in Hiatt's work. They also reflect on their podcasting journey over the past year and invite listeners to share their thoughts and join future episodes. Support the show here - buymeacoffee.com/setlustingbruce 00:00 Welcome to the Perfectly Good Podcast 01:58 Holiday Season Reflections 02:40 Discussing 'It All Comes Back Someday' 05:21 Analyzing the Lyrics 21:46 Listener Feedback and Ratings 24:14 Wrapping Up and Looking Ahead Learn more about your ad choices. Visit megaphone.fm/adchoices

Rethink Real Estate is back! In this thought-provoking episode of 'Rethink Real Estate,' host Ben Brady reflects on the immediate effects of the Los Angeles wildfires on the local community and real estate market. Amidst the tragedy, Ben explores the robust nature of the Southern California community and its impact on property values and insurance dynamics. This episode not only addresses the current market conditions but also provides a forward-looking analysis of the real estate market for 2025, considering economic indicators like job reports and interest rates. Ben offers insights into the practical aspects of business planning in real estate, emphasizing the importance of recognizing market cycles and maintaining consistent business efforts amidst uncertainties. The discussion also touches on the broader implications of these events on housing markets and insurance, highlighting the resilience required to navigate such challenges. Timestamps & Key Topics: [00:00:00] - Reflecting on the LA wildfires and their impact on real estate [00:01:32] - How community resilience shapes market recovery [00:02:16] - Early predictions for the real estate market in 2025 [00:04:21] - Analyzing economic indicators affecting real estate [00:05:23] - Strategies for business planning in fluctuating markets [00:09:04] - Emphasizing the role of personal strengths in real estate success

Hosts Jim Connelly (@jimmyconnelly), Derek Schooley (@derekschooley), and Ed Trefzger (@EdTrefzger) review games of the weekend and news of the week.They discuss the week's results for the top 20 in the USCHO.com Division I men's ice hockey poll. They highlight the standout performance of Maine, who swept UMass Lowell on the road and solidified their defensive strength; Denver's close wins over Miami, positioning them close to first in the NCHC; and the unexpected struggles of Colorado College and St. Cloud State. The commentary covers key games, impressive individual performances, and the fluctuating standings within conferences. They also delve into the sustainability of Hockey East's dominance in the pairwise rankings and Army's unprecedented 22-goal weekend against Mercyhurst.Times are approximate:00:15 Introduction and hosts00:54 Maine's impressive weekend02:48 Denver's close wins over Miami06:03 Colorado College's struggles07:23 BU's offensive surge09:48 Quinnipiac's winning streak11:49 UConn's rise in Hockey East14:29 BC's unusual stumble17:03 Ohio State's strong season19:09 St. Cloud state's january drop20:11 Cornell's setback against Sacred Heart22:16 Analyzing the PairWise Rankings23:34 Hockey East's NCAA tournament prospects26:16 Arizona State's unexpected performance29:47 Wisconsin's struggles and tournament chances31:12 Augustana's potential as a spoiler33:39 ECAC's historical performance in PairWise37:04 Army's offensive explosion40:46 Wrapup

Welcome to the Newcomer Investor Channel, where we uncover the story behind great businesses and make investing accessible and fun for everyone! In this episode, I am joined by AJ Button for a conversation on China. Links: Newcomer Investor on X:⁠⁠ ⁠⁠https://twitter.com/NewcomerInvest⁠⁠⁠⁠ Newcomer Investor Email: ⁠⁠iamthenewcomerinvestor@gmail.com AJ Button on X: https://x.com/AJButton2 Get a 15% discount on my FAVOURITE Financial Research tool: https://finchat.io/?via=anthony Episode Highlights: (0:00) - Introducing AJ Button (2:10) - Is China investable? Analyzing the risks and benefits. (16:00) - Alibaba (27:00) - PDD Holdings (34:40) - Postal Savings Bank of China (41:43) - Why AJ purchased more Brookfield Corporation Please note, this conversation was recorded on January 12th 2025. As a result, any references to specific future dates/events in the episode may refer to a time that has already passed. And remember that nothing here is financial advice!

Welcome to the EmpowerHer Business Accelerator podcast! Join host Philippa Channer as she shares insights and strategies to help you grow and thrive in your business. In this episode, Philippa dives into the power of data and its pivotal role in business success. Learn how to measure progress, identify trends, and make data-driven decisions. Philippa outlines five critical steps to transform raw data into actionable insights for your business growth. Timestamps: (00:00) Welcome to the EmpowerHer Business Accelerator Podcast! (01:00) Why Data Matters for Business Success (02:00) Step 1: Setting Measurable Goals (03:00) Step 2: Tracking Key Metrics (04:00) Step 3: Analyzing the Data (05:00) Step 4: Making Data-Driven Adjustments (05:45) Step 5: Testing and Iterating (06:00) Outro and Preview of Next Episode Special Announcements and Links: Free 30-Hour EmpowerHer Discovery Session: https://channerconsultingllc.hbportal.co/schedule/660da85649ef86002d1790d3 Subscribe for regular content on developing a solid marketing plan, marketing strategy, and marketing tips. Connect with us: LinkedIn: https://www.linkedin.com/company/channer-consulting-llc Facebook: https://www.facebook.com/channerconsulting/ Instagram: https://www.instagram.com/channerconsulting/ Email: info@channer-consulting.com

Due to overwhelming demand (>15x applications:slots), we are closing CFPs for AI Engineer Summit NYC today. Last call! Thanks, we'll be reaching out to all shortly!The world's top AI blogger and friend of every pod, Simon Willison, dropped a monster 2024 recap: Things we learned about LLMs in 2024. Brian of the excellent TechMeme Ride Home pinged us for a connection and a special crossover episode, our first in 2025. The target audience for this podcast is a tech-literate, but non-technical one. You can see Simon's notes for AI Engineers in his World's Fair Keynote.Timestamp* 00:00 Introduction and Guest Welcome* 01:06 State of AI in 2025* 01:43 Advancements in AI Models* 03:59 Cost Efficiency in AI* 06:16 Challenges and Competition in AI* 17:15 AI Agents and Their Limitations* 26:12 Multimodal AI and Future Prospects* 35:29 Exploring Video Avatar Companies* 36:24 AI Influencers and Their Future* 37:12 Simplifying Content Creation with AI* 38:30 The Importance of Credibility in AI* 41:36 The Future of LLM User Interfaces* 48:58 Local LLMs: A Growing Interest* 01:07:22 AI Wearables: The Next Big Thing* 01:10:16 Wrapping Up and Final ThoughtsTranscript[00:00:00] Introduction and Guest Welcome[00:00:00] Brian: Welcome to the first bonus episode of the Tech Meme Write Home for the year 2025. I'm your host as always, Brian McCullough. Listeners to the pod over the last year know that I have made a habit of quoting from Simon Willison when new stuff happens in AI from his blog. Simon has been, become a go to for many folks in terms of, you know, Analyzing things, criticizing things in the AI space.[00:00:33] Brian: I've wanted to talk to you for a long time, Simon. So thank you for coming on the show. No, it's a privilege to be here. And the person that made this connection happen is our friend Swyx, who has been on the show back, even going back to the, the Twitter Spaces days but also an AI guru in, in their own right Swyx, thanks for coming on the show also.[00:00:54] swyx (2): Thanks. I'm happy to be on and have been a regular listener, so just happy to [00:01:00] contribute as well.[00:01:00] Brian: And a good friend of the pod, as they say. Alright, let's go right into it.[00:01:06] State of AI in 2025[00:01:06] Brian: Simon, I'm going to do the most unfair, broad question first, so let's get it out of the way. The year 2025. Broadly, what is the state of AI as we begin this year?[00:01:20] Brian: Whatever you want to say, I don't want to lead the witness.[00:01:22] Simon: Wow. So many things, right? I mean, the big thing is everything's got really good and fast and cheap. Like, that was the trend throughout all of 2024. The good models got so much cheaper, they got so much faster, they got multimodal, right? The image stuff isn't even a surprise anymore.[00:01:39] Simon: They're growing video, all of that kind of stuff. So that's all really exciting.[00:01:43] Advancements in AI Models[00:01:43] Simon: At the same time, they didn't get massively better than GPT 4, which was a bit of a surprise. So that's sort of one of the open questions is, are we going to see huge, but I kind of feel like that's a bit of a distraction because GPT 4, but way cheaper, much larger context lengths, and it [00:02:00] can do multimodal.[00:02:01] Simon: is better, right? That's a better model, even if it's not.[00:02:05] Brian: What people were expecting or hoping, maybe not expecting is not the right word, but hoping that we would see another step change, right? Right. From like GPT 2 to 3 to 4, we were expecting or hoping that maybe we were going to see the next evolution in that sort of, yeah.[00:02:21] Brian: We[00:02:21] Simon: did see that, but not in the way we expected. We thought the model was just going to get smarter, and instead we got. Massive drops in, drops in price. We got all of these new capabilities. You can talk to the things now, right? They can do simulated audio input, all of that kind of stuff. And so it's kind of, it's interesting to me that the models improved in all of these ways we weren't necessarily expecting.[00:02:43] Simon: I didn't know it would be able to do an impersonation of Santa Claus, like a, you know, Talked to it through my phone and show it what I was seeing by the end of 2024. But yeah, we didn't get that GPT 5 step. And that's one of the big open questions is, is that actually just around the corner and we'll have a bunch of GPT 5 class models drop in the [00:03:00] next few months?[00:03:00] Simon: Or is there a limit?[00:03:03] Brian: If you were a betting man and wanted to put money on it, do you expect to see a phase change, step change in 2025?[00:03:11] Simon: I don't particularly for that, like, the models, but smarter. I think all of the trends we're seeing right now are going to keep on going, especially the inference time compute, right?[00:03:21] Simon: The trick that O1 and O3 are doing, which means that you can solve harder problems, but they cost more and it churns away for longer. I think that's going to happen because that's already proven to work. I don't know. I don't know. Maybe there will be a step change to a GPT 5 level, but honestly, I'd be completely happy if we got what we've got right now.[00:03:41] Simon: But cheaper and faster and more capabilities and longer contexts and so forth. That would be thrilling to me.[00:03:46] Brian: Digging into what you've just said one of the things that, by the way, I hope to link in the show notes to Simon's year end post about what, what things we learned about LLMs in 2024. Look for that in the show notes.[00:03:59] Cost Efficiency in AI[00:03:59] Brian: One of the things that you [00:04:00] did say that you alluded to even right there was that in the last year, you felt like the GPT 4 barrier was broken, like IE. Other models, even open source ones are now regularly matching sort of the state of the art.[00:04:13] Simon: Well, it's interesting, right? So the GPT 4 barrier was a year ago, the best available model was OpenAI's GPT 4 and nobody else had even come close to it.[00:04:22] Simon: And they'd been at the, in the lead for like nine months, right? That thing came out in what, February, March of, of 2023. And for the rest of 2023, nobody else came close. And so at the start of last year, like a year ago, the big question was, Why has nobody beaten them yet? Like, what do they know that the rest of the industry doesn't know?[00:04:40] Simon: And today, that I've counted 18 organizations other than GPT 4 who've put out a model which clearly beats that GPT 4 from a year ago thing. Like, maybe they're not better than GPT 4. 0, but that's, that, that, that barrier got completely smashed. And yeah, a few of those I've run on my laptop, which is wild to me.[00:04:59] Simon: Like, [00:05:00] it was very, very wild. It felt very clear to me a year ago that if you want GPT 4, you need a rack of 40, 000 GPUs just to run the thing. And that turned out not to be true. Like the, the, this is that big trend from last year of the models getting more efficient, cheaper to run, just as capable with smaller weights and so forth.[00:05:20] Simon: And I ran another GPT 4 model on my laptop this morning, right? Microsoft 5. 4 just came out. And that, if you look at the benchmarks, it's definitely, it's up there with GPT 4. 0. It's probably not as good when you actually get into the vibes of the thing, but it, it runs on my, it's a 14 gigabyte download and I can run it on a MacBook Pro.[00:05:38] Simon: Like who saw that coming? The most exciting, like the close of the year on Christmas day, just a few weeks ago, was when DeepSeek dropped their DeepSeek v3 model on Hugging Face without even a readme file. It was just like a giant binary blob that I can't run on my laptop. It's too big. But in all of the benchmarks, it's now by far the best available [00:06:00] open, open weights model.[00:06:01] Simon: Like it's, it's, it's beating the, the metalamas and so forth. And that was trained for five and a half million dollars, which is a tenth of the price that people thought it costs to train these things. So everything's trending smaller and faster and more efficient.[00:06:15] Brian: Well, okay.[00:06:16] Challenges and Competition in AI[00:06:16] Brian: I, I kind of was going to get to that later, but let's, let's combine this with what I was going to ask you next, which is, you know, you're talking, you know, Also in the piece about the LLM prices crashing, which I've even seen in projects that I'm working on, but explain Explain that to a general audience, because we hear all the time that LLMs are eye wateringly expensive to run, but what we're suggesting, and we'll come back to the cheap Chinese LLM, but first of all, for the end user, what you're suggesting is that we're starting to see the cost come down sort of in the traditional technology way of Of costs coming down over time,[00:06:49] Simon: yes, but very aggressively.[00:06:51] Simon: I mean, my favorite thing, the example here is if you look at GPT-3, so open AI's g, PT three, which was the best, a developed model in [00:07:00] 2022 and through most of 20 2023. That, the models that we have today, the OpenAI models are a hundred times cheaper. So there was a 100x drop in price for OpenAI from their best available model, like two and a half years ago to today.[00:07:13] Simon: And[00:07:14] Brian: just to be clear, not to train the model, but for the use of tokens and things. Exactly,[00:07:20] Simon: for running prompts through them. And then When you look at the, the really, the top tier model providers right now, I think, are OpenAI, Anthropic, Google, and Meta. And there are a bunch of others that I could list there as well.[00:07:32] Simon: Mistral are very good. The, the DeepSeq and Quen models have got great. There's a whole bunch of providers serving really good models. But even if you just look at the sort of big brand name providers, they all offer models now that are A fraction of the price of the, the, of the models we were using last year.[00:07:49] Simon: I think I've got some numbers that I threw into my blog entry here. Yeah. Like Gemini 1. 5 flash, that's Google's fast high quality model is [00:08:00] how much is that? It's 0. 075 dollars per million tokens. Like these numbers are getting, So we just do cents per million now,[00:08:09] swyx (2): cents per million,[00:08:10] Simon: cents per million makes, makes a lot more sense.[00:08:12] Simon: Yeah they have one model 1. 5 flash 8B, the absolute cheapest of the Google models, is 27 times cheaper than GPT 3. 5 turbo was a year ago. That's it. And GPT 3. 5 turbo, that was the cheap model, right? Now we've got something 27 times cheaper, and the Google, this Google one can do image recognition, it can do million token context, all of those tricks.[00:08:36] Simon: But it's, it's, it's very, it's, it really is startling how inexpensive some of this stuff has got.[00:08:41] Brian: Now, are we assuming that this, that happening is directly the result of competition? Because again, you know, OpenAI, and probably they're doing this for their own almost political reasons, strategic reasons, keeps saying, we're losing money on everything, even the 200.[00:08:56] Brian: So they probably wouldn't, the prices wouldn't be [00:09:00] coming down if there wasn't intense competition in this space.[00:09:04] Simon: The competition is absolutely part of it, but I have it on good authority from sources I trust that Google Gemini is not operating at a loss. Like, the amount of electricity to run a prompt is less than they charge you.[00:09:16] Simon: And the same thing for Amazon Nova. Like, somebody found an Amazon executive and got them to say, Yeah, we're not losing money on this. I don't know about Anthropic and OpenAI, but clearly that demonstrates it is possible to run these things at these ludicrously low prices and still not be running at a loss if you discount the Army of PhDs and the, the training costs and all of that kind of stuff.[00:09:36] Brian: One, one more for me before I let Swyx jump in here. To, to come back to DeepSeek and this idea that you could train, you know, a cutting edge model for 6 million. I, I was saying on the show, like six months ago, that if we are getting to the point where each new model It would cost a billion, ten billion, a hundred billion to train that.[00:09:54] Brian: At some point it would almost, only nation states would be able to train the new models. Do you [00:10:00] expect what DeepSeek and maybe others are proving to sort of blow that up? Or is there like some sort of a parallel track here that maybe I'm not technically, I don't have the mouse to understand the difference.[00:10:11] Brian: Is the model, are the models going to go, you know, Up to a hundred billion dollars or can we get them down? Sort of like DeepSeek has proven[00:10:18] Simon: so I'm the wrong person to answer that because I don't work in the lab training these models. So I can give you my completely uninformed opinion, which is, I felt like the DeepSeek thing.[00:10:27] Simon: That was a bomb shell. That was an absolute bombshell when they came out and said, Hey, look, we've trained. One of the best available models and it cost us six, five and a half million dollars to do it. I feel, and they, the reason, one of the reasons it's so efficient is that we put all of these export controls in to stop Chinese companies from giant buying GPUs.[00:10:44] Simon: So they've, were forced to be, go as efficient as possible. And yet the fact that they've demonstrated that that's possible to do. I think it does completely tear apart this, this, this mental model we had before that yeah, the training runs just keep on getting more and more expensive and the number of [00:11:00] organizations that can afford to run these training runs keeps on shrinking.[00:11:03] Simon: That, that's been blown out of the water. So yeah, that's, again, this was our Christmas gift. This was the thing they dropped on Christmas day. Yeah, it makes me really optimistic that we can, there are, It feels like there was so much low hanging fruit in terms of the efficiency of both inference and training and we spent a whole bunch of last year exploring that and getting results from it.[00:11:22] Simon: I think there's probably a lot left. I think there's probably, well, I would not be surprised to see even better models trained spending even less money over the next six months.[00:11:31] swyx (2): Yeah. So I, I think there's a unspoken angle here on what exactly the Chinese labs are trying to do because DeepSea made a lot of noise.[00:11:41] swyx (2): so much for joining us for around the fact that they train their model for six million dollars and nobody quite quite believes them. Like it's very, very rare for a lab to trumpet the fact that they're doing it for so cheap. They're not trying to get anyone to buy them. So why [00:12:00] are they doing this? They make it very, very obvious.[00:12:05] swyx (2): Deepseek is about 150 employees. It's an order of magnitude smaller than at least Anthropic and maybe, maybe more so for OpenAI. And so what's, what's the end game here? Are they, are they just trying to show that the Chinese are better than us?[00:12:21] Simon: So Deepseek, it's the arm of a hedge, it's a, it's a quant fund, right?[00:12:25] Simon: It's an algorithmic quant trading thing. So I, I, I would love to get more insight into how that organization works. My assumption from what I've seen is it looks like they're basically just flexing. They're like, hey, look at how utterly brilliant we are with this amazing thing that we've done. And it's, it's working, right?[00:12:43] Simon: They but, and so is that it? Are they, is this just their kind of like, this is, this is why our company is so amazing. Look at this thing that we've done, or? I don't know. I'd, I'd love to get Some insight from, from within that industry as to, as to how that's all playing out.[00:12:57] swyx (2): The, the prevailing theory among the Local Llama [00:13:00] crew and the Twitter crew that I indexed for my newsletter is that there is some amount of copying going on.[00:13:06] swyx (2): It's like Sam Altman you know, tweet, tweeting about how they're being copied. And then also there's this, there, there are other sort of opening eye employees that have said, Stuff that is similar that DeepSeek's rate of progress is how U. S. intelligence estimates the number of foreign spies embedded in top labs.[00:13:22] swyx (2): Because a lot of these ideas do spread around, but they surprisingly have a very high density of them in the DeepSeek v3 technical report. So it's, it's interesting. We don't know how much, how many, how much tokens. I think that, you know, people have run analysis on how often DeepSeek thinks it is cloud or thinks it is opening GPC 4.[00:13:40] swyx (2): Thanks for watching! And we don't, we don't know. We don't know. I think for me, like, yeah, we'll, we'll, we basically will never know as, as external commentators. I think what's interesting is how, where does this go? Is there a logical floor or bottom by my estimations for the same amount of ELO started last year to the end of last year cost went down by a thousand X for the [00:14:00] GPT, for, for GPT 4 intelligence.[00:14:02] swyx (2): Would, do they go down a thousand X this year?[00:14:04] Simon: That's a fascinating question. Yeah.[00:14:06] swyx (2): Is there a Moore's law going on, or did we just get a one off benefit last year for some weird reason?[00:14:14] Simon: My uninformed hunch is low hanging fruit. I feel like up until a year ago, people haven't been focusing on efficiency at all. You know, it was all about, what can we get these weird shaped things to do?[00:14:24] Simon: And now once we've sort of hit that, okay, we know that we can get them to do what GPT 4 can do, When thousands of researchers around the world all focus on, okay, how do we make this more efficient? What are the most important, like, how do we strip out all of the weights that have stuff in that doesn't really matter?[00:14:39] Simon: All of that kind of thing. So yeah, maybe that was it. Maybe 2024 was a freak year of all of the low hanging fruit coming out at once. And we'll actually see a reduction in the, in that rate of improvement in terms of efficiency. I wonder, I mean, I think we'll know for sure in about three months time if that trend's going to continue or not.[00:14:58] swyx (2): I agree. You know, I [00:15:00] think the other thing that you mentioned that DeepSeq v3 was the gift that was given from DeepSeq over Christmas, but I feel like the other thing that might be underrated was DeepSeq R1,[00:15:11] Speaker 4: which is[00:15:13] swyx (2): a reasoning model you can run on your laptop. And I think that's something that a lot of people are looking ahead to this year.[00:15:18] swyx (2): Oh, did they[00:15:18] Simon: release the weights for that one?[00:15:20] swyx (2): Yeah.[00:15:21] Simon: Oh my goodness, I missed that. I've been playing with the quen. So the other great, the other big Chinese AI app is Alibaba's quen. Actually, yeah, I, sorry, R1 is an API available. Yeah. Exactly. When that's really cool. So Alibaba's Quen have released two reasoning models that I've run on my laptop.[00:15:38] Simon: Now there was, the first one was Q, Q, WQ. And then the second one was QVQ because the second one's a vision model. So you can like give it vision puzzles and a prompt that these things, they are so much fun to run. Because they think out loud. It's like the OpenAR 01 sort of hides its thinking process. The Query ones don't.[00:15:59] Simon: They just, they [00:16:00] just churn away. And so you'll give it a problem and it will output literally dozens of paragraphs of text about how it's thinking. My favorite thing that happened with QWQ is I asked it to draw me a pelican on a bicycle in SVG. That's like my standard stupid prompt. And for some reason it thought in Chinese.[00:16:18] Simon: It spat out a whole bunch of like Chinese text onto my terminal on my laptop, and then at the end it gave me quite a good sort of artistic pelican on a bicycle. And I ran it all through Google Translate, and yeah, it was like, it was contemplating the nature of SVG files as a starting point. And the fact that my laptop can think in Chinese now is so delightful.[00:16:40] Simon: It's so much fun watching you do that.[00:16:43] swyx (2): Yeah, I think Andrej Karpathy was saying, you know, we, we know that we have achieved proper reasoning inside of these models when they stop thinking in English, and perhaps the best form of thought is in Chinese. But yeah, for listeners who don't know Simon's blog he always, whenever a new model comes out, you, I don't know how you do it, but [00:17:00] you're always the first to run Pelican Bench on these models.[00:17:02] swyx (2): I just did it for 5.[00:17:05] Simon: Yeah.[00:17:07] swyx (2): So I really appreciate that. You should check it out. These are not theoretical. Simon's blog actually shows them.[00:17:12] Brian: Let me put on the investor hat for a second.[00:17:15] AI Agents and Their Limitations[00:17:15] Brian: Because from the investor side of things, a lot of the, the VCs that I know are really hot on agents, and this is the year of agents, but last year was supposed to be the year of agents as well. Lots of money flowing towards, And Gentic startups.[00:17:32] Brian: But in in your piece that again, we're hopefully going to have linked in the show notes, you sort of suggest there's a fundamental flaw in AI agents as they exist right now. Let me let me quote you. And then I'd love to dive into this. You said, I remain skeptical as to their ability based once again, on the Challenge of gullibility.[00:17:49] Brian: LLMs believe anything you tell them, any systems that attempt to make meaningful decisions on your behalf, will run into the same roadblock. How good is a travel agent, or a digital assistant, or even a research tool, if it [00:18:00] can't distinguish truth from fiction? So, essentially, what you're suggesting is that the state of the art now that allows agents is still, it's still that sort of 90 percent problem, the edge problem, getting to the Or, or, or is there a deeper flaw?[00:18:14] Brian: What are you, what are you saying there?[00:18:16] Simon: So this is the fundamental challenge here and honestly my frustration with agents is mainly around definitions Like any if you ask anyone who says they're working on agents to define agents You will get a subtly different definition from each person But everyone always assumes that their definition is the one true one that everyone else understands So I feel like a lot of these agent conversations, people talking past each other because one person's talking about the, the sort of travel agent idea of something that books things on your behalf.[00:18:41] Simon: Somebody else is talking about LLMs with tools running in a loop with a cron job somewhere and all of these different things. You, you ask academics and they'll laugh at you because they've been debating what agents mean for over 30 years at this point. It's like this, this long running, almost sort of an in joke in that community.[00:18:57] Simon: But if we assume that for this purpose of this conversation, an [00:19:00] agent is something that, Which you can give a job and it goes off and it does that thing for you like, like booking travel or things like that. The fundamental challenge is, it's the reliability thing, which comes from this gullibility problem.[00:19:12] Simon: And a lot of my, my interest in this originally came from when I was thinking about prompt injections as a source of this form of attack against LLM systems where you deliberately lay traps out there for this LLM to stumble across,[00:19:24] Brian: and which I should say you have been banging this drum that no one's gotten any far, at least on solving this, that I'm aware of, right.[00:19:31] Brian: Like that's still an open problem. The two years.[00:19:33] Simon: Yeah. Right. We've been talking about this problem and like, a great illustration of this was Claude so Anthropic released Claude computer use a few months ago. Fantastic demo. You could fire up a Docker container and you could literally tell it to do something and watch it open a web browser and navigate to a webpage and click around and so forth.[00:19:51] Simon: Really, really, really interesting and fun to play with. And then, um. One of the first demos somebody tried was, what if you give it a web page that says download and run this [00:20:00] executable, and it did, and the executable was malware that added it to a botnet. So the, the very first most obvious dumb trick that you could play on this thing just worked, right?[00:20:10] Simon: So that's obviously a really big problem. If I'm going to send something out to book travel on my behalf, I mean, it's hard enough for me to figure out which airlines are trying to scam me and which ones aren't. Do I really trust a language model that believes the literal truth of anything that's presented to it to go out and do those things?[00:20:29] swyx (2): Yeah I definitely think there's, it's interesting to see Anthropic doing this because they used to be the safety arm of OpenAI that split out and said, you know, we're worried about letting this thing out in the wild and here they are enabling computer use for agents. Thanks. The, it feels like things have merged.[00:20:49] swyx (2): You know, I'm, I'm also fairly skeptical about, you know, this always being the, the year of Linux on the desktop. And this is the equivalent of this being the year of agents that people [00:21:00] are not predicting so much as wishfully thinking and hoping and praying for their companies and agents to work.[00:21:05] swyx (2): But I, I feel like things are. Coming along a little bit. It's to me, it's kind of like self driving. I remember in 2014 saying that self driving was just around the corner. And I mean, it kind of is, you know, like in, in, in the Bay area. You[00:21:17] Simon: get in a Waymo and you're like, Oh, this works. Yeah, but it's a slow[00:21:21] swyx (2): cook.[00:21:21] swyx (2): It's a slow cook over the next 10 years. We're going to hammer out these things and the cynical people can just point to all the flaws, but like, there are measurable or concrete progress steps that are being made by these builders.[00:21:33] Simon: There is one form of agent that I believe in. I believe, mostly believe in the research assistant form of agents.[00:21:39] Simon: The thing where you've got a difficult problem and, and I've got like, I'm, I'm on the beta for the, the Google Gemini 1. 5 pro with deep research. I think it's called like these names, these names. Right. But. I've been using that. It's good, right? You can give it a difficult problem and it tells you, okay, I'm going to look at 56 different websites [00:22:00] and it goes away and it dumps everything to its context and it comes up with a report for you.[00:22:04] Simon: And it's not, it won't work against adversarial websites, right? If there are websites with deliberate lies in them, it might well get caught out. Most things don't have that as a problem. And so I've had some answers from that which were genuinely really valuable to me. And that feels to me like, I can see how given existing LLM tech, especially with Google Gemini with its like million token contacts and Google with their crawl of the entire web and their, they've got like search, they've got search and cache, they've got a cache of every page and so forth.[00:22:35] Simon: That makes sense to me. And that what they've got right now, I don't think it's, it's not as good as it can be, obviously, but it's, it's, it's, it's a real useful thing, which they're going to start rolling out. So, you know, Perplexity have been building the same thing for a couple of years. That, that I believe in.[00:22:50] Simon: You know, if you tell me that you're going to have an agent that's a research assistant agent, great. The coding agents I mean, chat gpt code interpreter, Nearly two years [00:23:00] ago, that thing started writing Python code, executing the code, getting errors, rewriting it to fix the errors. That pattern obviously works.[00:23:07] Simon: That works really, really well. So, yeah, coding agents that do that sort of error message loop thing, those are proven to work. And they're going to keep on getting better, and that's going to be great. The research assistant agents are just beginning to get there. The things I'm critical of are the ones where you trust, you trust this thing to go out and act autonomously on your behalf, and make decisions on your behalf, especially involving spending money, like that.[00:23:31] Simon: I don't see that working for a very long time. That feels to me like an AGI level problem.[00:23:37] swyx (2): It's it's funny because I think Stripe actually released an agent toolkit which is one of the, the things I featured that is trying to enable these agents each to have a wallet that they can go and spend and have, basically, it's a virtual card.[00:23:49] swyx (2): It's not that, not that difficult with modern infrastructure. can[00:23:51] Simon: stick a 50 cap on it, then at least it's an honor. Can't lose more than 50.[00:23:56] Brian: You know I don't, I don't know if either of you know Rafat Ali [00:24:00] he runs Skift, which is a, a travel news vertical. And he, he, he constantly laughs at the fact that every agent thing is, we're gonna get rid of booking a, a plane flight for you, you know?[00:24:11] Brian: And, and I would point out that, like, historically, when the web started, the first thing everyone talked about is, You can go online and book a trip, right? So it's funny for each generation of like technological advance. The thing they always want to kill is the travel agent. And now they want to kill the webpage travel agent.[00:24:29] Simon: Like it's like I use Google flight search. It's great, right? If you gave me an agent to do that for me, it would save me, I mean, maybe 15 seconds of typing in my things, but I still want to see what my options are and go, yeah, I'm not flying on that airline, no matter how cheap they are.[00:24:44] swyx (2): Yeah. For listeners, go ahead.[00:24:47] swyx (2): For listeners, I think, you know, I think both of you are pretty positive on NotebookLM. And you know, we, we actually interviewed the NotebookLM creators, and there are actually two internal agents going on internally. The reason it takes so long is because they're running an agent loop [00:25:00] inside that is fairly autonomous, which is kind of interesting.[00:25:01] swyx (2): For one,[00:25:02] Simon: for a definition of agent loop, if you picked that particularly well. For one definition. And you're talking about the podcast side of this, right?[00:25:07] swyx (2): Yeah, the podcast side of things. They have a there's, there's going to be a new version coming out that, that we'll be featuring at our, at our conference.[00:25:14] Simon: That one's fascinating to me. Like NotebookLM, I think it's two products, right? On the one hand, it's actually a very good rag product, right? You dump a bunch of things in, you can run searches, that, that, it does a good job of. And then, and then they added the, the podcast thing. It's a bit of a, it's a total gimmick, right?[00:25:30] Simon: But that gimmick got them attention, because they had a great product that nobody paid any attention to at all. And then you add the unfeasibly good voice synthesis of the podcast. Like, it's just, it's, it's, it's the lesson.[00:25:43] Brian: It's the lesson of mid journey and stuff like that. If you can create something that people can post on socials, you don't have to lift a finger again to do any marketing for what you're doing.[00:25:53] Brian: Let me dig into Notebook LLM just for a second as a podcaster. As a [00:26:00] gimmick, it makes sense, and then obviously, you know, you dig into it, it sort of has problems around the edges. It's like, it does the thing that all sort of LLMs kind of do, where it's like, oh, we want to Wrap up with a conclusion.[00:26:12] Multimodal AI and Future Prospects[00:26:12] Brian: I always call that like the the eighth grade book report paper problem where it has to have an intro and then, you know But that's sort of a thing where because I think you spoke about this again in your piece at the year end About how things are going multimodal and how things are that you didn't expect like, you know vision and especially audio I think So that's another thing where, at least over the last year, there's been progress made that maybe you, you didn't think was coming as quick as it came.[00:26:43] Simon: I don't know. I mean, a year ago, we had one really good vision model. We had GPT 4 vision, was, was, was very impressive. And Google Gemini had just dropped Gemini 1. 0, which had vision, but nobody had really played with it yet. Like Google hadn't. People weren't taking Gemini [00:27:00] seriously at that point. I feel like it was 1.[00:27:02] Simon: 5 Pro when it became apparent that actually they were, they, they got over their hump and they were building really good models. And yeah, and they, to be honest, the video models are mostly still using the same trick. The thing where you divide the video up into one image per second and you dump that all into the context.[00:27:16] Simon: So maybe it shouldn't have been so surprising to us that long context models plus vision meant that the video was, was starting to be solved. Of course, it didn't. Not being, you, what you really want with videos, you want to be able to do the audio and the images at the same time. And I think the models are beginning to do that now.[00:27:33] Simon: Like, originally, Gemini 1. 5 Pro originally ignored the audio. It just did the, the, like, one frame per second video trick. As far as I can tell, the most recent ones are actually doing pure multimodal. But the things that opens up are just extraordinary. Like, the the ChatGPT iPhone app feature that they shipped as one of their 12 days of, of OpenAI, I really can be having a conversation and just turn on my video camera and go, Hey, what kind of tree is [00:28:00] this?[00:28:00] Simon: And so forth. And it works. And for all I know, that's just snapping a like picture once a second and feeding it into the model. The, the, the things that you can do with that as an end user are extraordinary. Like that, that to me, I don't think most people have cottoned onto the fact that you can now stream video directly into a model because it, it's only a few weeks old.[00:28:22] Simon: Wow. That's a, that's a, that's a, that's Big boost in terms of what kinds of things you can do with this stuff. Yeah. For[00:28:30] swyx (2): people who are not that close I think Gemini Flashes free tier allows you to do something like capture a photo, one photo every second or a minute and leave it on 24, seven, and you can prompt it to do whatever.[00:28:45] swyx (2): And so you can effectively have your own camera app or monitoring app that that you just prompt and it detects where it changes. It detects for, you know, alerts or anything like that, or describes your day. You know, and, and, and the fact that this is free I think [00:29:00] it's also leads into the previous point of it being the prices haven't come down a lot.[00:29:05] Simon: And even if you're paying for this stuff, like a thing that I put in my blog entry is I ran a calculation on what it would cost to process 68, 000 photographs in my photo collection, and for each one just generate a caption, and using Gemini 1. 5 Flash 8B, it would cost me 1. 68 to process 68, 000 images, which is, I mean, that, that doesn't make sense.[00:29:28] Simon: None of that makes sense. Like it's, it's a, for one four hundredth of a cent per image to generate captions now. So you can see why feeding in a day's worth of video just isn't even very expensive to process.[00:29:40] swyx (2): Yeah, I'll tell you what is expensive. It's the other direction. So we're here, we're talking about consuming video.[00:29:46] swyx (2): And this year, we also had a lot of progress, like probably one of the most excited, excited, anticipated launches of the year was Sora. We actually got Sora. And less exciting.[00:29:55] Simon: We did, and then VO2, Google's Sora, came out like three [00:30:00] days later and upstaged it. Like, Sora was exciting until VO2 landed, which was just better.[00:30:05] swyx (2): In general, I feel the media, or the social media, has been very unfair to Sora. Because what was released to the world, generally available, was Sora Lite. It's the distilled version of Sora, right? So you're, I did not[00:30:16] Simon: realize that you're absolutely comparing[00:30:18] swyx (2): the, the most cherry picked version of VO two, the one that they published on the marketing page to the, the most embarrassing version of the soa.[00:30:25] swyx (2): So of course it's gonna look bad, so, well, I got[00:30:27] Simon: access to the VO two I'm in the VO two beta and I've been poking around with it and. Getting it to generate pelicans on bicycles and stuff. I would absolutely[00:30:34] swyx (2): believe that[00:30:35] Simon: VL2 is actually better. Is Sora, so is full fat Sora coming soon? Do you know, when, when do we get to play with that one?[00:30:42] Simon: No one's[00:30:43] swyx (2): mentioned anything. I think basically the strategy is let people play around with Sora Lite and get info there. But the, the, keep developing Sora with the Hollywood studios. That's what they actually care about. Gotcha. Like the rest of us. Don't really know what to do with the video anyway. Right.[00:30:59] Simon: I mean, [00:31:00] that's my thing is I realized that for generative images and images and video like images We've had for a few years and I don't feel like they've broken out into the talented artist community yet Like lots of people are having fun with them and doing and producing stuff. That's kind of cool to look at but what I want you know that that movie everything everywhere all at once, right?[00:31:20] Simon: One, one ton of Oscars, utterly amazing film. The VFX team for that were five people, some of whom were watching YouTube videos to figure out what to do. My big question for, for Sora and and and Midjourney and stuff, what happens when a creative team like that starts using these tools? I want the creative geniuses behind everything, everywhere all at once.[00:31:40] Simon: What are they going to be able to do with this stuff in like a few years time? Because that's really exciting to me. That's where you take artists who are at the very peak of their game. Give them these new capabilities and see, see what they can do with them.[00:31:52] swyx (2): I should, I know a little bit here. So it should mention that, that team actually used RunwayML.[00:31:57] swyx (2): So there was, there was,[00:31:57] Simon: yeah.[00:31:59] swyx (2): I don't know how [00:32:00] much I don't. So, you know, it's possible to overstate this, but there are people integrating it. Generated video within their workflow, even pre SORA. Right, because[00:32:09] Brian: it's not, it's not the thing where it's like, okay, tomorrow we'll be able to do a full two hour movie that you prompt with three sentences.[00:32:15] Brian: It is like, for the very first part of, of, you know video effects in film, it's like, if you can get that three second clip, if you can get that 20 second thing that they did in the matrix that blew everyone's minds and took a million dollars or whatever to do, like, it's the, it's the little bits and pieces that they can fill in now that it's probably already there.[00:32:34] swyx (2): Yeah, it's like, I think actually having a layered view of what assets people need and letting AI fill in the low value assets. Right, like the background video, the background music and, you know, sometimes the sound effects. That, that maybe, maybe more palatable maybe also changes the, the way that you evaluate the stuff that's coming out.[00:32:57] swyx (2): Because people tend to, in social media, try to [00:33:00] emphasize foreground stuff, main character stuff. So you really care about consistency, and you, you really are bothered when, like, for example, Sorad. Botch's image generation of a gymnast doing flips, which is horrible. It's horrible. But for background crowds, like, who cares?[00:33:18] Brian: And by the way, again, I was, I was a film major way, way back in the day, like, that's how it started. Like things like Braveheart, where they filmed 10 people on a field, and then the computer could turn it into 1000 people on a field. Like, that's always been the way it's around the margins and in the background that first comes in.[00:33:36] Brian: The[00:33:36] Simon: Lord of the Rings movies were over 20 years ago. Although they have those giant battle sequences, which were very early, like, I mean, you could almost call it a generative AI approach, right? They were using very sophisticated, like, algorithms to model out those different battles and all of that kind of stuff.[00:33:52] Simon: Yeah, I know very little. I know basically nothing about film production, so I try not to commentate on it. But I am fascinated to [00:34:00] see what happens when, when these tools start being used by the real, the people at the top of their game.[00:34:05] swyx (2): I would say like there's a cultural war that is more that being fought here than a technology war.[00:34:11] swyx (2): Most of the Hollywood people are against any form of AI anyway, so they're busy Fighting that battle instead of thinking about how to adopt it and it's, it's very fringe. I participated here in San Francisco, one generative AI video creative hackathon where the AI positive artists actually met with technologists like myself and then we collaborated together to build short films and that was really nice and I think, you know, I'll be hosting some of those in my events going forward.[00:34:38] swyx (2): One thing that I think like I want to leave it. Give people a sense of it's like this is a recap of last year But then sometimes it's useful to walk away as well with like what can we expect in the future? I don't know if you got anything. I would also call out that the Chinese models here have made a lot of progress Hyde Law and Kling and God knows who like who else in the video arena [00:35:00] Also making a lot of progress like surprising him like I think maybe actually Chinese China is surprisingly ahead with regards to Open8 at least, but also just like specific forms of video generation.[00:35:12] Simon: Wouldn't it be interesting if a film industry sprung up in a country that we don't normally think of having a really strong film industry that was using these tools? Like, that would be a fascinating sort of angle on this. Mm hmm. Mm hmm.[00:35:25] swyx (2): Agreed. I, I, I Oh, sorry. Go ahead.[00:35:29] Exploring Video Avatar Companies[00:35:29] swyx (2): Just for people's Just to put it on people's radar as well, Hey Jen, there's like there's a category of video avatar companies that don't specifically, don't specialize in general video.[00:35:41] swyx (2): They only do talking heads, let's just say. And HeyGen sings very well.[00:35:45] Brian: Swyx, you know that that's what I've been using, right? Like, have, have I, yeah, right. So, if you see some of my recent YouTube videos and things like that, where, because the beauty part of the HeyGen thing is, I, I, I don't want to use the robot voice, so [00:36:00] I record the mp3 file for my computer, And then I put that into HeyGen with the avatar that I've trained it on, and all it does is the lip sync.[00:36:09] Brian: So it looks, it's not 100 percent uncanny valley beatable, but it's good enough that if you weren't looking for it, it's just me sitting there doing one of my clips from the show. And, yeah, so, by the way, HeyGen. Shout out to them.[00:36:24] AI Influencers and Their Future[00:36:24] swyx (2): So I would, you know, in terms of like the look ahead going, like, looking, reviewing 2024, looking at trends for 2025, I would, they basically call this out.[00:36:33] swyx (2): Meta tried to introduce AI influencers and failed horribly because they were just bad at it. But at some point that there will be more and more basically AI influencers Not in a way that Simon is but in a way that they are not human.[00:36:50] Simon: Like the few of those that have done well, I always feel like they're doing well because it's a gimmick, right?[00:36:54] Simon: It's a it's it's novel and fun to like Like that, the AI Seinfeld thing [00:37:00] from last year, the Twitch stream, you know, like those, if you're the only one or one of just a few doing that, you'll get, you'll attract an audience because it's an interesting new thing. But I just, I don't know if that's going to be sustainable longer term or not.[00:37:11] Simon: Like,[00:37:12] Simplifying Content Creation with AI[00:37:12] Brian: I'm going to tell you, Because I've had discussions, I can't name the companies or whatever, but, so think about the workflow for this, like, now we all know that on TikTok and Instagram, like, holding up a phone to your face, and doing like, in my car video, or walking, a walk and talk, you know, that's, that's very common, but also, if you want to do a professional sort of talking head video, you still have to sit in front of a camera, you still have to do the lighting, you still have to do the video editing, versus, if you can just record, what I'm saying right now, the last 30 seconds, If you clip that out as an mp3 and you have a good enough avatar, then you can put that avatar in front of Times Square, on a beach, or whatever.[00:37:50] Brian: So, like, again for creators, the reason I think Simon, we're on the verge of something, it, it just, it's not going to, I think it's not, oh, we're going to have [00:38:00] AI avatars take over, it'll be one of those things where it takes another piece of the workflow out and simplifies it. I'm all[00:38:07] Simon: for that. I, I always love this stuff.[00:38:08] Simon: I like tools. Tools that help human beings do more. Do more ambitious things. I'm always in favor of, like, that, that, that's what excites me about this entire field.[00:38:17] swyx (2): Yeah. We're, we're looking into basically creating one for my podcast. We have this guy Charlie, he's Australian. He's, he's not real, but he pre, he opens every show and we are gonna have him present all the shorts.[00:38:29] Simon: Yeah, go ahead.[00:38:30] The Importance of Credibility in AI[00:38:30] Simon: The thing that I keep coming back to is this idea of credibility like in a world that is full of like AI generated everything and so forth It becomes even more important that people find the sources of information that they trust and find people and find Sources that are credible and I feel like that's the one thing that LLMs and AI can never have is credibility, right?[00:38:49] Simon: ChatGPT can never stake its reputation on telling you something useful and interesting because That means nothing, right? It's a matrix multiplication. It depends on who prompted it and so forth. So [00:39:00] I'm always, and this is when I'm blogging as well, I'm always looking for, okay, who are the reliable people who will tell me useful, interesting information who aren't just going to tell me whatever somebody's paying them to tell, tell them, who aren't going to, like, type a one sentence prompt into an LLM and spit out an essay and stick it online.[00:39:16] Simon: And that, that to me, Like, earning that credibility is really important. That's why a lot of my ethics around the way that I publish are based on the idea that I want people to trust me. I want to do things that, that gain credibility in people's eyes so they will come to me for information as a trustworthy source.[00:39:32] Simon: And it's the same for the sources that I'm, I'm consulting as well. So that's something I've, I've been thinking a lot about that sort of credibility focus on this thing for a while now.[00:39:40] swyx (2): Yeah, you can layer or structure credibility or decompose it like so one thing I would put in front of you I'm not saying that you should Agree with this or accept this at all is that you can use AI to generate different Variations and then and you pick you as the final sort of last mile person that you pick The last output and [00:40:00] you put your stamp of credibility behind that like that everything's human reviewed instead of human origin[00:40:04] Simon: Yeah, if you publish something you need to be able to put it on the ground Publishing it.[00:40:08] Simon: You need to say, I will put my name to this. I will attach my credibility to this thing. And if you're willing to do that, then, then that's great.[00:40:16] swyx (2): For creators, this is huge because there's a fundamental asymmetry between starting with a blank slate versus choosing from five different variations.[00:40:23] Brian: Right.[00:40:24] Brian: And also the key thing that you just said is like, if everything that I do, if all of the words were generated by an LLM, if the voice is generated by an LLM. If the video is also generated by the LLM, then I haven't done anything, right? But if, if one or two of those, you take a shortcut, but it's still, I'm willing to sign off on it.[00:40:47] Brian: Like, I feel like that's where I feel like people are coming around to like, this is maybe acceptable, sort of.[00:40:53] Simon: This is where I've been pushing the definition. I love the term slop. Where I've been pushing the definition of slop as AI generated [00:41:00] content that is both unrequested and unreviewed and the unreviewed thing is really important like that's the thing that elevates something from slop to not slop is if A human being has reviewed it and said, you know what, this is actually worth other people's time.[00:41:12] Simon: And again, I'm willing to attach my credibility to it and say, hey, this is worthwhile.[00:41:16] Brian: It's, it's, it's the cura curational, curatorial and editorial part of it that no matter what the tools are to do shortcuts, to do, as, as Swyx is saying choose between different edits or different cuts, but in the end, if there's a curatorial mind, Or editorial mind behind it.[00:41:32] Brian: Let me I want to wedge this in before we start to close.[00:41:36] The Future of LLM User Interfaces[00:41:36] Brian: One of the things coming back to your year end piece that has been a something that I've been banging the drum about is when you're talking about LLMs. Getting harder to use. You said most users are thrown in at the deep end.[00:41:48] Brian: The default LLM chat UI is like taking brand new computer users, dropping them into a Linux terminal and expecting them to figure it all out. I mean, it's, it's literally going back to the command line. The command line was defeated [00:42:00] by the GUI interface. And this is what I've been banging the drum about is like, this cannot be.[00:42:05] Brian: The user interface, what we have now cannot be the end result. Do you see any hints or seeds of a GUI moment for LLM interfaces?[00:42:17] Simon: I mean, it has to happen. It absolutely has to happen. The the, the, the, the usability of these things is turning into a bit of a crisis. And we are at least seeing some really interesting innovation in little directions.[00:42:28] Simon: Just like OpenAI's chat GPT canvas thing that they just launched. That is at least. Going a little bit more interesting than just chat, chats and responses. You know, you can, they're exploring that space where you're collaborating with an LLM. You're both working in the, on the same document. That makes a lot of sense to me.[00:42:44] Simon: Like that, that feels really smart. The one of the best things is still who was it who did the, the UI where you could, they had a drawing UI where you draw an interface and click a button. TL draw would then make it real thing. That was spectacular, [00:43:00] absolutely spectacular, like, alternative vision of how you'd interact with these models.[00:43:05] Simon: Because yeah, the and that's, you know, so I feel like there is so much scope for innovation there and it is beginning to happen. Like, like, I, I feel like most people do understand that we need to do better in terms of interfaces that both help explain what's going on and give people better tools for working with models.[00:43:23] Simon: I was going to say, I want to[00:43:25] Brian: dig a little deeper into this because think of the conceptual idea behind the GUI, which is instead of typing into a command line open word. exe, it's, you, you click an icon, right? So that's abstracting away sort of the, again, the programming stuff that like, you know, it's, it's a, a, a child can tap on an iPad and, and make a program open, right?[00:43:47] Brian: The problem it seems to me right now with how we're interacting with LLMs is it's sort of like you know a dumb robot where it's like you poke it and it goes over here, but no, I want it, I want to go over here so you poke it this way and you can't get it exactly [00:44:00] right, like, what can we abstract away from the From the current, what's going on that, that makes it more fine tuned and easier to get more precise.[00:44:12] Brian: You see what I'm saying?[00:44:13] Simon: Yes. And the this is the other trend that I've been following from the last year, which I think is super interesting. It's the, the prompt driven UI development thing. Basically, this is the pattern where Claude Artifacts was the first thing to do this really well. You type in a prompt and it goes, Oh, I should answer that by writing a custom HTML and JavaScript application for you that does a certain thing.[00:44:35] Simon: And when you think about that take and since then it turns out This is easy, right? Every decent LLM can produce HTML and JavaScript that does something useful. So we've actually got this alternative way of interacting where they can respond to your prompt with an interactive custom interface that you can work with.[00:44:54] Simon: People haven't quite wired those back up again. Like, ideally, I'd want the LLM ask me a [00:45:00] question where it builds me a custom little UI, For that question, and then it gets to see how I interacted with that. I don't know why, but that's like just such a small step from where we are right now. But that feels like such an obvious next step.[00:45:12] Simon: Like an LLM, why should it, why should you just be communicating with, with text when it can build interfaces on the fly that let you select a point on a map or or move like sliders up and down. It's gonna create knobs and dials. I keep saying knobs and dials. right. We can do that. And the LLMs can build, and Claude artifacts will build you a knobs and dials interface.[00:45:34] Simon: But at the moment they haven't closed the loop. When you twiddle those knobs, Claude doesn't see what you were doing. They're going to close that loop. I'm, I'm shocked that they haven't done it yet. So yeah, I think there's so much scope for innovation and there's so much scope for doing interesting stuff with that model where the LLM, anything you can represent in SVG, which is almost everything, can now be part of that ongoing conversation.[00:45:59] swyx (2): Yeah, [00:46:00] I would say the best executed version of this I've seen so far is Bolt where you can literally type in, make a Spotify clone, make an Airbnb clone, and it actually just does that for you zero shot with a nice design.[00:46:14] Simon: There's a benchmark for that now. The LMRena people now have a benchmark that is zero shot app, app generation, because all of the models can do it.[00:46:22] Simon: Like it's, it's, I've started figuring out. I'm building my own version of this for my own project, because I think within six months. I think it'll just be an expected feature. Like if you have a web application, why don't you have a thing where, oh, look, the, you can add a custom, like, so for my dataset data exploration project, I want you to be able to do things like conjure up a dashboard, just via a prompt.[00:46:43] Simon: You say, oh, I need a pie chart and a bar chart and put them next to each other, and then have a form where submitting the form inserts a row into my database table. And this is all suddenly feasible. It's, it's, it's not even particularly difficult to do, which is great. Utterly bizarre that these things are now easy.[00:47:00][00:47:00] swyx (2): I think for a general audience, that is what I would highlight, that software creation is becoming easier and easier. Gemini is now available in Gmail and Google Sheets. I don't write my own Google Sheets formulas anymore, I just tell Gemini to do it. And so I think those are, I almost wanted to basically somewhat disagree with, with your assertion that LMS got harder to use.[00:47:22] swyx (2): Like, yes, we, we expose more capabilities, but they're, they're in minor forms, like using canvas, like web search in, in in chat GPT and like Gemini being in, in Excel sheets or in Google sheets, like, yeah, we're getting, no,[00:47:37] Simon: no, no, no. Those are the things that make it harder, because the problem is that for each of those features, they're amazing.[00:47:43] Simon: If you understand the edges of the feature, if you're like, okay, so in Google, Gemini, Excel formulas, I can get it to do a certain amount of things, but I can't get it to go and read a web. You probably can't get it to read a webpage, right? But you know, there are, there are things that it can do and things that it can't do, which are completely undocumented.[00:47:58] Simon: If you ask it what it [00:48:00] can and can't do, they're terrible at answering questions about that. So like my favorite example is Claude artifacts. You can't build a Claude artifact that can hit an API somewhere else. Because the cause headers on that iframe prevents accessing anything outside of CDNJS. So, good luck learning cause headers as an end user in order to understand why Like, I've seen people saying, oh, this is rubbish.[00:48:26] Simon: I tried building an artifact that would run a prompt and it couldn't because Claude didn't expose an API with cause headers that all of this stuff is so weird and complicated. And yeah, like that, that, the more that with the more tools we add, the more expertise you need to really, To understand the full scope of what you can do.[00:48:44] Simon: And so it's, it's, I wouldn't say it's, it's, it's, it's like, the question really comes down to what does it take to understand the full extent of what's possible? And honestly, that, that's just getting more and more involved over time.[00:48:58] Local LLMs: A Growing Interest[00:48:58] swyx (2): I have one more topic that I, I [00:49:00] think you, you're kind of a champion of and we've touched on it a little bit, which is local LLMs.[00:49:05] swyx (2): And running AI applications on your desktop, I feel like you are an early adopter of many, many things.[00:49:12] Simon: I had an interesting experience with that over the past year. Six months ago, I almost completely lost interest. And the reason is that six months ago, the best local models you could run, There was no point in using them at all, because the best hosted models were so much better.[00:49:26] Simon: Like, there was no point at which I'd choose to run a model on my laptop if I had API access to Cloud 3. 5 SONNET. They just, they weren't even comparable. And that changed, basically, in the past three months, as the local models had this step changing capability, where now I can run some of these local models, and they're not as good as Cloud 3.[00:49:45] Simon: 5 SONNET, but they're not so far away that It's not worth me even using them. The other, the, the, the, the continuing problem is I've only got 64 gigabytes of RAM, and if you run, like, LLAMA370B, it's not going to work. Most of my RAM is gone. So now I have to shut down my Firefox tabs [00:50:00] and, and my Chrome and my VS Code windows in order to run it.[00:50:03] Simon: But it's got me interested again. Like, like the, the efficiency improvements are such that now, if you were to like stick me on a desert island with my laptop, I'd be very productive using those local models. And that's, that's pretty exciting. And if those trends continue, and also, like, I think my next laptop, if when I buy one is going to have twice the amount of RAM, At which point, maybe I can run the, almost the top tier, like open weights models and still be able to use it as a computer as well.[00:50:32] Simon: NVIDIA just announced their 3, 000 128 gigabyte monstrosity. That's pretty good price. You know, that's that's, if you're going to buy it,[00:50:42] swyx (2): custom OS and all.[00:50:46] Simon: If I get a job, if I, if, if, if I have enough of an income that I can justify blowing $3,000 on it, then yes.[00:50:52] swyx (2): Okay, let's do a GoFundMe to get Simon one it.[00:50:54] swyx (2): Come on. You know, you can get a job anytime you want. Is this, this is just purely discretionary .[00:50:59] Simon: I want, [00:51:00] I want a job that pays me to do exactly what I'm doing already and doesn't tell me what else to do. That's, thats the challenge.[00:51:06] swyx (2): I think Ethan Molik does pretty well. Whatever, whatever it is he's doing.[00:51:11] swyx (2): But yeah, basically I was trying to bring in also, you know, not just local models, but Apple intelligence is on every Mac machine. You're, you're, you seem skeptical. It's rubbish.[00:51:21] Simon: Apple intelligence is so bad. It's like, it does one thing well.[00:51:25] swyx (2): Oh yeah, what's that? It summarizes notifications. And sometimes it's humorous.[00:51:29] Brian: Are you sure it does that well? And also, by the way, the other, again, from a sort of a normie point of view. There's no indication from Apple of when to use it. Like, everybody upgrades their thing and it's like, okay, now you have Apple Intelligence, and you never know when to use it ever again.[00:51:47] swyx (2): Oh, yeah, you consult the Apple docs, which is MKBHD.[00:51:49] swyx (2): The[00:51:51] Simon: one thing, the one thing I'll say about Apple Intelligence is, One of the reasons it's so disappointing is that the models are just weak, but now, like, Llama 3b [00:52:00] is Such a good model in a 2 gigabyte file I think give Apple six months and hopefully they'll catch up to the state of the art on the small models And then maybe it'll start being a lot more interesting.[00:52:10] swyx (2): Yeah. Anyway, I like This was year one And and you know just like our first year of iPhone maybe maybe not that much of a hit and then year three They had the App Store so Hey I would say give it some time, and you know, I think Chrome also shipping Gemini Nano I think this year in Chrome, which means that every app, every web app will have for free access to a local model that just ships in the browser, which is kind of interesting.[00:52:38] swyx (2): And then I, I think I also wanted to just open the floor for any, like, you know, any of us what are the apps that, you know, AI applications that we've adopted that have, that we really recommend because these are all, you know, apps that are running on our browser that like, or apps that are running locally that we should be, that, that other people should be trying.[00:52:55] swyx (2): Right? Like, I, I feel like that's, that's one always one thing that is helpful at the start of the [00:53:00] year.[00:53:00] Simon: Okay. So for running local models. My top picks, firstly, on the iPhone, there's this thing called MLC Chat, which works, and it's easy to install, and it runs Llama 3B, and it's so much fun. Like, it's not necessarily a capable enough novel that I use it for real things, but my party trick right now is I get my phone to write a Netflix Christmas movie plot outline where, like, a bunch of Jeweller falls in love with the King of Sweden or whatever.[00:53:25] Simon: And it does a good job and it comes up with pun names for the movies. And that's, that's deeply entertaining. On my laptop, most recently, I've been getting heavy into, into Olama because the Olama team are very, very good at finding the good models and patching them up and making them work well. It gives you an API.[00:53:42] Simon: My little LLM command line tool that has a plugin that talks to Olama, which works really well. So that's my, my Olama is. I think the easiest on ramp to to running models locally, if you want a nice user interface, LMStudio is, I think, the best user interface [00:54:00] thing at that. It's not open source. It's good.[00:54:02] Simon: It's worth playing with. The other one that I've been trying with recently, there's a thing called, what's it called? Open web UI or something. Yeah. The UI is fantastic. It, if you've got Olama running and you fire this thing up, it spots Olama and it gives you an interface onto your Olama models. And t

SummaryIn this episode of the Inorganic Podcast, host Christian Hassold delves into a case study on the startup Crisp (gocrisp.com), which has successfully executed four acquisitions over the last 2 years. The discussion covers the company's background, the leadership dynamics, and the strategic rationale behind its inorganic investments. The episode serves as a case study to demonstrate what good M&A looks like in an early to mid stage SaaS company and what features of M&A targets companies should be thinking about at that stage. As a part of the discussion, Christian dives into some of the deal specifics and the economic benefits to Crisp based on opinion and publicly accessible information.Takeaways- M&A could be as effective as traditional sales, marketing, and product investments.- What problem is Crisp solving and why is it important- Background on Crisps substantial financing and debt rounds- What kinds of M&A has Crisp executed and why- How the deals Crisp has executed have likely helped fuel their growth- What can other startups learn from Crisp's approach to M&A- Order of the kinds of deals a company might do is a consideration in building the M&A muscle in an early to mid-stage SaaS company- The startup ecosystem often underestimates the value of M&A Chapter Markers0:00 Introduction03:19 The Case for M&A in Early Stage Startups05:14 Crisp's Company Profile08:28 Pre-conditions for M&A in Early Stage Startups13:37 Breakdown of Crisp's Four Acquisitions20:37 Crisp's Acquisition Strategy22:01 Financial Case for Crisp's M&A24:28 Analyzing the Order of Crisp's Deals26:37 Reflecting on Crisp's Strategy28:10 ConclusionConnect with Christian & In/organic PodcastChristian's LinkedIn: https://www.linkedin.com/in/hassold/In/organic on LinkedIn: https://www.linkedin.com/company/inorganic-podcastIn/organic on YouTube: https://www.youtube.com/@InorganicPodcast/featuredEpisode References:https://www.linkedin.com/in/aretraasdahl/https://finance.yahoo.com/news/crisp-raises-50m-series-b-140500449.html?utm_source=chatgpt.comhttps://www.sec.gov/edgar/search/#/ciks=0001818100&entityName=Crisp%252C%2520Inc.%2520(CIK%25200001818100)chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://ir.youradv.com/static-files/d47814ee-084c-4c53-9b0f-9a9753f9e9cfEpisode Outline Hosted on Acast. See acast.com/privacy for more information.

Summary In this episode of the ESPC podcast, Josh Abner Vizcay discusses the intersection of sports betting, mental health, and financial literacy. He emphasizes the importance of collaboration and sharing information in making informed betting decisions. The conversation covers various NFL games, analyzing team dynamics, coaching strategies, and player performances, while also highlighting the significance of maintaining mental health and relationships in the gambling world. The episode concludes with predictions for upcoming games and a call to action for listeners to engage with the content. Takeaways The ESPC podcast aims to monetize time spent watching sports. Collaboration and sharing information are key to success in sports betting. Mental health is an important aspect of gambling and investing. Fundamental analysis is more effective than technical analysis in betting. Time management is crucial; time equals money. Understanding team dynamics and coaching strategies can lead to better betting decisions. Double-digit dogs in the division have a high cover rate. Situational intelligence is vital in making informed decisions. The air raid offense has its strengths and weaknesses in the NFL. Maintaining relationships is essential for mental health in the gambling community. Sound Bites "Time is money." "Sports is an investable asset class." "The air raid wins early, loses late." Chapters 00:00 Monetizing Time: The Purpose of the Podcast 03:51 Mental Health and Financial Literacy in Sports Betting 06:37 Analyzing the Chargers vs. Texans Game 09:52 Pittsburgh Steelers vs. Baltimore Ravens: A Tactical Breakdown 12:44 Buffalo Bills vs. Denver Broncos: Quarterback Dynamics 15:54 Coaching Mismatches: Packers vs. Eagles 29:33 Analyzing Jordan Love's Progression 30:54 Game Predictions and Coaching Mismatches 33:21 The Importance of Collaboration and Diversity in Analysis 34:50 Understanding Quarterback Challenges in Air Raid Offense 38:44 Defensive Strategies: Zone Blitz and Simulated Pressure 42:34 Evaluating the Tampa Bay Buccaneers' Game Plan 46:39 Quarterback Performance and Game Strategy 51:42 Final Thoughts on the Vikings vs. Rams Matchup 56:46 SlickRickClosing copy.mp3

As a freelance writer, I find it interesting to examine the analytics of last year's posts to determine which were the most popular. As I write this diary, the answers have been surprising. The number of likes, comments, opens and clicks all indicate interest. Thank you, thank you! And, I also adore interaction and reader opinions.Having said all this, I am going with Substack analytics and adding a few more notables to the mix. I hope you agree with me!Ta da ta da!The number one spot goes to:Love Language. About my summer adventures and the introduction of Tarzan. I have never received more private notes and phone calls. Ever.It chronicles summer travel adventures and possible love interests. Wow! Tarzan is now in our lexicon, and we talk about this mystical person with giggles and total abandon. Referring to a Tarzan has become a source of hilarity. Seriously. I will continue to let you know if anything new happens to me. A notable mention is Feeding Tarzan, an article about cooking for loved ones.The second one was:Making Marmalade, which, as the name implies, is about making different types of marmalade with recipes for variations.It was a great way to spend a few cold January days. This article has also led to endless conversations about starting a new project called Lady Anson Preserves. (Absolutely not! I have done it once and will not do it again!) However, I have made marmalade this year following my recipe with great success.And the third, well, it was:Sandwiches 101 is about an after-party I organized at home and the hundreds of sandwiches I made for the event.Who would have thought that writing about making something as simple as this could actually become a "thing?" It is more about making something mundane work in a more elevated setting. I'll take the compliment!Analyzing these three articles, I can see a pattern. After all, I write to share insights and advice about things that happen to me, aiming to amuse you and give ideas on what to do. I don't claim that my way is the best; it is just how I do things after years of experience and making many mistakes.I should also mention the most popular article ever, published in September 2023, which is still at the top of my feed. It is titled At a Loss for Words and is about mourning and how to reach out to our friends. Hopefully, I won't need to write about this any time soon.As I plan this year's posts, I realize that personal stories are more fun to share, that experiences and love interests are what we all want to know, and that this diary will continue to be about food, style, travel, and all the things and places that I think are interesting. Some of the projects I will share this year include a new house I bought in southern Spain. I am still waiting to get licenses and permits from the archeological team at the mayor's office. I will report as soon as construction can start. My architects assure me it will take four months to complete the construction, but I am thinking that eight months is a more reasonable estimate. We will see!"Hams have been delivered; drinks with the team will ensue."I also have many entertaining events at home that are already on the books. A group of ladies from Savannah, some old friends from Palm Beach, and new friends from South Africa are some of the parties I'll tell you about. And this is only in the first quarter!Thank you for staying with me and following my musings. It is wonderful to receive notes and comments; please keep them coming!And with this, I leave you. SincerelyThe Serial Hostess Thank you for subscribing. Leave a comment or share this episode.

Anastasia is joined by Tony Wright, a coaching pro and podcaster from California, for an engaging conversation, discussing the intricacies of the Australian Open, including the draw process, seeding, and the impact of current events on the tournament. They share insights on key matches to watch, strategies for attending tournaments, and how to effectively follow the action from home. The episode emphasizes the importance of planning ahead for tournaments like this and fan engagement in the world of tennis.Chapters00:00 Introduction and Background of Tony Wright02:48 Current Events: California Fires and Their Impact05:36 Understanding the Australian Open Draw08:43 The Importance of Seeding and Qualifiers11:23 How Draws Are Conducted in Tournaments14:19 Fan Engagement and the Draw Experience17:09 Analyzing the Australian Open Draw Matchups19:01 First round matches we are looking forward to23:30 American Players in the Draw24:23 Player Dynamics and Rivalries26:31 Qualifiers and Their Challenges28:37 WTA Highlights and Key Matchups30:30 Revisiting Familiar Faces31:26 Emerging Talents and Gritty Competitors33:05 Player Personalities and Off-Court Lives34:49 Strategies for Tournament Viewing37:53 Navigating the Tournament Schedule39:31 Maximizing Your Grand Slam Experience47:31 Strategizing Your Match Schedule55:08 Essential Tips for Tournament Days56:41 Upcoming Podcast AnnouncementsRelevant Links:Relief links for California Wildfires:Tennis Channel - https://www.tennis.com/californiawildfiresreliefBrain Dead clothing brand - https://www.instagram.com/p/DEpvpNSvzLK/?igsh=MXRiOGZ5eGozZ3AxYw==Balanced Tennis on Instagram - https://www.instagram.com/balanced_tennis?igsh=MTI2b3Q5cDA0NmE5Zw==Tennis Today Podcast - https://podfollow.com/1725696267Tennis Today on Instagram - https://www.instagram.com/tennistodaypodcast?igsh=NnFkZDlwZmtncGJzAustralian Open Daily Schedule- https://ausopen.com/schedule#!41183 Hosted on Acast. See acast.com/privacy for more information.

Scott and Canadian union whistleblower Ken Pereira analyze and discuss the brutal war between the Montreal Mob and Hells Angels that finally came to an end in December of 2024 after a peace summit between Mob Boss Leo Rizzuto and Hells Angels Leader Marty Robert.

Packet capture and packet analysis is incredibly useful for problem-solving and troubleshooting. Analyzing packets is also a difficult skill to master. With the incredible array of network troubleshooting tools at our disposal, including emerging networking models for artificial intelligence, do we still need to fuss around with Wireshark in 2025? Our guest Chris Greer says... Read more »

Packet capture and packet analysis is incredibly useful for problem-solving and troubleshooting. Analyzing packets is also a difficult skill to master. With the incredible array of network troubleshooting tools at our disposal, including emerging networking models for artificial intelligence, do we still need to fuss around with Wireshark in 2025? Our guest Chris Greer says... Read more »

Dave and Tracy talk about basketball's loss to Michigan, what's going on with the personnel and rotations, and football's continued pursuit of transfers. To learn more about listener data and our privacy practices visit: https://www.audacyinc.com/privacy-policy Learn more about your ad choices. Visit https://podcastchoices.com/adchoices

In this episode of the Perfectly Good Podcast, hosts Jessie Jackson and Sylvan Groth, along with guest Mike (TFG1Mike), delve into the song 'Is Anybody There?' by John Hiatt. The panel reflects on the emotional depth of the song, its themes of seeking direction, confronting loneliness, and the importance of asking for help in relationships. They also discuss live performances, cover versions, and personal anecdotes that resonate with the lyrics. The conversation is insightful and filled with heartfelt moments, underlining the significance of Hiatt's work within the broader context of his discography. 00:00 Welcome to Perfectly Good Podcast 02:12 Introducing the Hosts and Guest 03:47 Discussing 'Is Anybody There?' 04:04 Song Facts and Covers 07:00 Personal Reflections and Reviews 11:38 Analyzing the Lyrics 25:12 Chorus Breakdown and Emotional Intimacy 27:05 Sibling Relationships and Loneliness 29:37 Exploring Emotional Vulnerability in Lyrics 32:44 Reflections on Relationships and Love 37:08 Personal Stories and Song Ratings 45:02 Final Thoughts and Contact Information Support the show here - buymeacoffee.com/setlustingbruce  Learn more about your ad choices. Visit megaphone.fm/adchoices

Packet capture and packet analysis is incredibly useful for problem-solving and troubleshooting. Analyzing packets is also a difficult skill to master. With the incredible array of network troubleshooting tools at our disposal, including emerging networking models for artificial intelligence, do we still need to fuss around with Wireshark in 2025? Our guest Chris Greer says... Read more »

The Guys break down the upcoming Wild Card weekend!00:00 - Packers vs Eagles06:27 - Steelers vs Ravens16:40 - Vikings vs Rams23:50 - Commanders vs Buccaneers30:31 - Broncos vs Bills36:20 - Chargers vs TexansVisit https://Captainmorgan.com to find Captain near you. Please drink responsibly. CAPTAIN MORGAN Original Spiced Rum 35 percent alcohol by volume. Captain Morgan Rum Company, New York, NY.Download the DraftKings Sportsbook app and use promo code FOOTBALLTODAYWatch Blitzball Battle 5 NOW: https://www.youtube.com/channel/UCIBJINNTKXHp7fkfpJqcpjwFeaturing: Bobby Skinner and Chris RoseEdited by: Connor KurpatFollow all of our content on https://jomboymedia.comGAMBLING PROBLEM? CALL 1-800-GAMBLER, (800) 327-5050 or visit gamblinghelplinema.org (MA). Call 877-8-HOPENY/text HOPENY (467369) (NY). Please Gamble Responsibly. 888-789-7777/visit ccpg.org (CT), or visit www.mdgamblinghelp.org (MD). 21+ and present in most states. (18+ DC/KY/NH/WY). Void in ONT/OR/NH. Eligibility restrictions apply. On behalf of Boot Hill Casino & Resort (KS). 1 per new customer. Min. $5 deposit. Min. $5 bet. Max. $150 issued as 6 $25 Bonus Bets if your bet wins. Bonus Bets are single-use, non-withdrawable, and expire in 7 days (168 hours). Stake removed from payout. Terms: dkng.co/dk-offer-terms. Ends 1/5/25 at 11:59 PM ET. Sponsored by DK.

My guest today is Jonathon Wilson-Hartgrove. Wilson-Hartgrove is a writer, preacher, and moral activist. He is an assistant director at the Center for Public Theology and Public Policy at Yale Divinity School. Wilson-Hartgrove lives with his family at the Rutba House, a house of hospitality in Durham, North Carolina that he founded with H his wife, Leah. Wilson-Hartgrove directs the School for Conversion, a popular education center in Durham committed to "making surprising friendships possible," and is an associate minister at St. John's Missionary Baptist Church. Jonathan is the author or coauthor of more than a dozen books, including Reconstructing the Gospel, The Third Reconstruction, and Strangers at My Door.  About White Poverty: How Exposing Myths About Race and Class Can Reconstruct American Democracy (Liveright, 2024): One of the most pernicious and persistent myths in the United States is the association of Black skin with poverty. Though there are forty million more poor white people than Black people, most Americans, both Republicans and Democrats, continue to think of poverty--along with issues like welfare, unemployment, and food stamps--as solely a Black problem. Why is this so? What are the historical causes? And what are the political consequences that result? These are among the questions that the Reverend Dr. William J. Barber II, a leading advocate for the rights of the poor and the "closest person we have to Dr. King" (Cornel West), addresses in White Poverty, a groundbreaking work that exposes a legacy of historical myths that continue to define both white and Black people, creating in the process what might seem like an insuperable divide. Analyzing what has changed since the 1930s, when the face of American poverty was white, Barber, along with Jonathan Wilson-Hartgrove, addresses white poverty as a hugely neglected subject that just might provide the key to mitigating racism and bringing together tens of millions of working class and impoverished Americans. Thus challenging the very definition of who is poor in America, Barber writes about the lies that prevent us from seeing the pain of poor white families who have been offered little more than their "whiteness" and angry social media posts to sustain them in an economy where the costs of housing, healthcare, and education have skyrocketed while wages have stagnated for all but the very rich. Asserting in Biblically inspired language that there should never be shame in being poor, White Poverty lifts the hope for a new "moral fusion movement" that seeks to unite people "who have been pitted against one another by politicians (and billionaires) who depend on the poorest of us not being here." Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/new-books-network

In this special recap episode, I look back at the ten big predictions I made for 2024—and rate how each one actually turned out. From continued tech layoffs to a surge in AI-driven content (and even a bold guess about a marketing conference with good food), I evaluate which predictions nailed it, which ones fizzled, and what surprised me the most. Tune in to hear the year-in-review of AI's rise, the state of SaaS, Hollywood hits, and more! Episode Breakdown 1. Layoffs & Tech Restructuring How many companies really did another round of layoffs in 2024? The role AI and offshoring played in driving deeper cost cuts. Did Apple avoid massive layoffs as predicted? 2. SaaS & AI Acquisition Frenzy Which big SaaS players scooped up AI startups—did smaller companies with little traction get acquired? Why Gong didn't get bought by a giant (yet). The state of SaaS valuations in 2024—did they return to record highs? 3. AI Content Takes Center Stage Checking in on fully AI-generated commercials, shorts, or movies that took the internet by storm. The reality of AI plus human co-creation. How close we got to truly tear-jerking or hyper-realistic AI productions. 4. Rise of the “Head of AI” Role Did companies from every sector really start hiring for AI leadership roles? The mix of responsibilities and how quickly these roles grew in 2024. 5. Marketing Conference Food Miracle A lighthearted prediction that a marketing event might finally serve amazing food—did it happen? Listener stories and personal experiences from 2024 conferences. 6. AI-Generated Super Bowl Ads Which brands used AI in their creative process for the Big Game? How much of the final product was truly AI vs. human-driven editing? 7. AI Companions: Breakthrough or Bust? Analyzing the rise of AI girlfriend/boyfriend apps for companionship and mental-health support. Any major bans or government crackdowns on “fake companion” apps? Surprising ways these tools impacted real people's lives. 8. Mr. Beast's Next Big Venture Did 2024 see Mr. Beast launch a project that pushed him into billionaire territory? A look at how he expanded his brand or philanthropic efforts. 9. Bad Boys 4 at the Box Office Did Will Smith's return pull in the predicted $600M+ globally? Exploring the film's performance and reception post-controversy. 10. Influencer Retires for Politics Did we see a well-known social media star hang up the mic and announce a run for office? The blurry line between internet fame and political ambition. —

Gm! In this episode, we're joined by Dan Smith to discuss avoiding noise in crypto data, the issue with FDV, and stablecoin supply across chains. Finally, we end the podcast by diving into the concept of conditional liquidity, MEV, and Solana's sandwich attack problem. Enjoy! Resources Solana MEV Landscape From Helius Labs: https://x.com/__lostin__/status/1877444749298381156 Dan's Post on the Wash Trading Bot: https://x.com/smyyguy/status/1873461466541486096 Top 10 Chains by Stablecoins: https://x.com/smyyguy/status/1875613474774249724 -- Follow Dan: https://x.com/smyyguy Follow Mert: https://x.com/0xMert_ Follow Jack: https://x.com/whosknave Follow Lightspeed: https://twitter.com/Lightspeedpodhq Subscribe to the Lightspeed Newsletter: https://blockworks.co/newsletter/lightspeed Utilize the Solana Dashboard by Blockworks Research: http://solana.blockworksresearch.com/ -- Ledger, the global leader in digital asset security, proudly sponsors the Lightspeed podcast. As Ledger celebrates 10 years of securing 20% of global crypto, it remains the top choice for securing your Solana assets. Buy a LEDGER™ device now and build confidently, knowing your SOL are safe. Buy now on https://shop.ledger.com/?r=1da180a5de00. -- Renaud Partners has built the most elite network of native crypto marketers globally. They create custom, expert teams to support founders with transformative strategy work. Trusted by some of the best founders, VC firms, and ecosystem leaders in the business, helping their teams expedite their marketing success and catalyze their growth. If you're a founder or a VC looking for support for your teams, I highly recommend connecting with them at RenaudPartners.com -- Subscribe on YouTube: https://bit.ly/43o3Syk Subscribe on Apple: https://apple.co/3OhiXgV Subscribe on Spotify: https://spoti.fi/3OkF7PD Get top market insights and the latest in crypto news. Subscribe to Blockworks Daily Newsletter: https://blockworks.co/newsletter/ -- (00:00) Introduction (03:01) Analyzing a Wash Trading Bot (09:15) Avoiding Noise in Crypto Data (16:18) Ledger Ad (17:18) Renaud Partners Ad (18:06) The Issue with FDV (30:43) Stablecoin Supply Across Chains (42:29) Thoughts on Conditional Liquidity and MEV (50:21) Solana's Sandwiching Problem -- Disclaimers: Lightspeed was kickstarted by a grant from the Solana Foundation. Nothing said on Lightspeed is a recommendation to buy or sell securities or tokens. This podcast is for informational purposes only, and any views expressed by anyone on the show are solely our opinions, not financial advice. Mert, Jack, and our guests may hold positions in the companies, funds, or projects discussed.

My guest today is Jonathon Wilson-Hartgrove. Wilson-Hartgrove is a writer, preacher, and moral activist. He is an assistant director at the Center for Public Theology and Public Policy at Yale Divinity School. Wilson-Hartgrove lives with his family at the Rutba House, a house of hospitality in Durham, North Carolina that he founded with H his wife, Leah. Wilson-Hartgrove directs the School for Conversion, a popular education center in Durham committed to "making surprising friendships possible," and is an associate minister at St. John's Missionary Baptist Church. Jonathan is the author or coauthor of more than a dozen books, including Reconstructing the Gospel, The Third Reconstruction, and Strangers at My Door.  About White Poverty: How Exposing Myths About Race and Class Can Reconstruct American Democracy (Liveright, 2024): One of the most pernicious and persistent myths in the United States is the association of Black skin with poverty. Though there are forty million more poor white people than Black people, most Americans, both Republicans and Democrats, continue to think of poverty--along with issues like welfare, unemployment, and food stamps--as solely a Black problem. Why is this so? What are the historical causes? And what are the political consequences that result? These are among the questions that the Reverend Dr. William J. Barber II, a leading advocate for the rights of the poor and the "closest person we have to Dr. King" (Cornel West), addresses in White Poverty, a groundbreaking work that exposes a legacy of historical myths that continue to define both white and Black people, creating in the process what might seem like an insuperable divide. Analyzing what has changed since the 1930s, when the face of American poverty was white, Barber, along with Jonathan Wilson-Hartgrove, addresses white poverty as a hugely neglected subject that just might provide the key to mitigating racism and bringing together tens of millions of working class and impoverished Americans. Thus challenging the very definition of who is poor in America, Barber writes about the lies that prevent us from seeing the pain of poor white families who have been offered little more than their "whiteness" and angry social media posts to sustain them in an economy where the costs of housing, healthcare, and education have skyrocketed while wages have stagnated for all but the very rich. Asserting in Biblically inspired language that there should never be shame in being poor, White Poverty lifts the hope for a new "moral fusion movement" that seeks to unite people "who have been pitted against one another by politicians (and billionaires) who depend on the poorest of us not being here." Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/sociology

Scott and Canadian union whistleblower Ken Pereira analyze and discuss the brutal war between the Montreal Mob and Hells Angels that finally came to an end in December of 2024 after a peace summit between Mob Boss Leo Rizzuto and Hells Angels Leader Marty Robert.

My guest today is Jonathon Wilson-Hartgrove. Wilson-Hartgrove is a writer, preacher, and moral activist. He is an assistant director at the Center for Public Theology and Public Policy at Yale Divinity School. Wilson-Hartgrove lives with his family at the Rutba House, a house of hospitality in Durham, North Carolina that he founded with H his wife, Leah. Wilson-Hartgrove directs the School for Conversion, a popular education center in Durham committed to "making surprising friendships possible," and is an associate minister at St. John's Missionary Baptist Church. Jonathan is the author or coauthor of more than a dozen books, including Reconstructing the Gospel, The Third Reconstruction, and Strangers at My Door.  About White Poverty: How Exposing Myths About Race and Class Can Reconstruct American Democracy (Liveright, 2024): One of the most pernicious and persistent myths in the United States is the association of Black skin with poverty. Though there are forty million more poor white people than Black people, most Americans, both Republicans and Democrats, continue to think of poverty--along with issues like welfare, unemployment, and food stamps--as solely a Black problem. Why is this so? What are the historical causes? And what are the political consequences that result? These are among the questions that the Reverend Dr. William J. Barber II, a leading advocate for the rights of the poor and the "closest person we have to Dr. King" (Cornel West), addresses in White Poverty, a groundbreaking work that exposes a legacy of historical myths that continue to define both white and Black people, creating in the process what might seem like an insuperable divide. Analyzing what has changed since the 1930s, when the face of American poverty was white, Barber, along with Jonathan Wilson-Hartgrove, addresses white poverty as a hugely neglected subject that just might provide the key to mitigating racism and bringing together tens of millions of working class and impoverished Americans. Thus challenging the very definition of who is poor in America, Barber writes about the lies that prevent us from seeing the pain of poor white families who have been offered little more than their "whiteness" and angry social media posts to sustain them in an economy where the costs of housing, healthcare, and education have skyrocketed while wages have stagnated for all but the very rich. Asserting in Biblically inspired language that there should never be shame in being poor, White Poverty lifts the hope for a new "moral fusion movement" that seeks to unite people "who have been pitted against one another by politicians (and billionaires) who depend on the poorest of us not being here." Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/american-studies

My guest today is Jonathon Wilson-Hartgrove. Wilson-Hartgrove is a writer, preacher, and moral activist. He is an assistant director at the Center for Public Theology and Public Policy at Yale Divinity School. Wilson-Hartgrove lives with his family at the Rutba House, a house of hospitality in Durham, North Carolina that he founded with H his wife, Leah. Wilson-Hartgrove directs the School for Conversion, a popular education center in Durham committed to "making surprising friendships possible," and is an associate minister at St. John's Missionary Baptist Church. Jonathan is the author or coauthor of more than a dozen books, including Reconstructing the Gospel, The Third Reconstruction, and Strangers at My Door.  About White Poverty: How Exposing Myths About Race and Class Can Reconstruct American Democracy (Liveright, 2024): One of the most pernicious and persistent myths in the United States is the association of Black skin with poverty. Though there are forty million more poor white people than Black people, most Americans, both Republicans and Democrats, continue to think of poverty--along with issues like welfare, unemployment, and food stamps--as solely a Black problem. Why is this so? What are the historical causes? And what are the political consequences that result? These are among the questions that the Reverend Dr. William J. Barber II, a leading advocate for the rights of the poor and the "closest person we have to Dr. King" (Cornel West), addresses in White Poverty, a groundbreaking work that exposes a legacy of historical myths that continue to define both white and Black people, creating in the process what might seem like an insuperable divide. Analyzing what has changed since the 1930s, when the face of American poverty was white, Barber, along with Jonathan Wilson-Hartgrove, addresses white poverty as a hugely neglected subject that just might provide the key to mitigating racism and bringing together tens of millions of working class and impoverished Americans. Thus challenging the very definition of who is poor in America, Barber writes about the lies that prevent us from seeing the pain of poor white families who have been offered little more than their "whiteness" and angry social media posts to sustain them in an economy where the costs of housing, healthcare, and education have skyrocketed while wages have stagnated for all but the very rich. Asserting in Biblically inspired language that there should never be shame in being poor, White Poverty lifts the hope for a new "moral fusion movement" that seeks to unite people "who have been pitted against one another by politicians (and billionaires) who depend on the poorest of us not being here." Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/public-policy

My guest today is Jonathon Wilson-Hartgrove. Wilson-Hartgrove is a writer, preacher, and moral activist. He is an assistant director at the Center for Public Theology and Public Policy at Yale Divinity School. Wilson-Hartgrove lives with his family at the Rutba House, a house of hospitality in Durham, North Carolina that he founded with H his wife, Leah. Wilson-Hartgrove directs the School for Conversion, a popular education center in Durham committed to "making surprising friendships possible," and is an associate minister at St. John's Missionary Baptist Church. Jonathan is the author or coauthor of more than a dozen books, including Reconstructing the Gospel, The Third Reconstruction, and Strangers at My Door.  About White Poverty: How Exposing Myths About Race and Class Can Reconstruct American Democracy (Liveright, 2024): One of the most pernicious and persistent myths in the United States is the association of Black skin with poverty. Though there are forty million more poor white people than Black people, most Americans, both Republicans and Democrats, continue to think of poverty--along with issues like welfare, unemployment, and food stamps--as solely a Black problem. Why is this so? What are the historical causes? And what are the political consequences that result? These are among the questions that the Reverend Dr. William J. Barber II, a leading advocate for the rights of the poor and the "closest person we have to Dr. King" (Cornel West), addresses in White Poverty, a groundbreaking work that exposes a legacy of historical myths that continue to define both white and Black people, creating in the process what might seem like an insuperable divide. Analyzing what has changed since the 1930s, when the face of American poverty was white, Barber, along with Jonathan Wilson-Hartgrove, addresses white poverty as a hugely neglected subject that just might provide the key to mitigating racism and bringing together tens of millions of working class and impoverished Americans. Thus challenging the very definition of who is poor in America, Barber writes about the lies that prevent us from seeing the pain of poor white families who have been offered little more than their "whiteness" and angry social media posts to sustain them in an economy where the costs of housing, healthcare, and education have skyrocketed while wages have stagnated for all but the very rich. Asserting in Biblically inspired language that there should never be shame in being poor, White Poverty lifts the hope for a new "moral fusion movement" that seeks to unite people "who have been pitted against one another by politicians (and billionaires) who depend on the poorest of us not being here." Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/politics-and-polemics

We're recapping Arkansas' SEC home opener against Ole Miss. Plus we're making our picks for the college football playoff semifinals.