Podcasts about Live Demonstration

Unlocking Active Cash Buyers: A Step-by-Step Guide with PropStreamWatch the full video replay here: https://youtu.be/4o6FkSYRBZEGrab your FREE trial with PropStream here: http://GrowWithJosh.com/PS (be sure to email me at josh@growwithjosh.com to get your FREE marketing credits and other BONUSES)Can you do me a HUGE favor and fill out this short (should take less than 30 seconds) survey: http://GrowWithJosh.com/CBIn this episode, we dive deep into how to find the most active cash buyers in your market right now. Special guest Burton shares invaluable insights on identifying motivated sellers and connecting with eager cash buyers using PropStream. Whether you're looking for fix-and-flip investors, landlords, or commercial property buyers, this session is packed with actionable strategies. We'll also discuss how to automate your outreach, manage your cold and warm leads, and ensure your senior owners are well-informed. Tune in to learn how to create endless opportunities in real estate by matching the right deals with the right buyers!Timestamps:00:00 Introduction and Today's Topic00:09 Guest Introduction and Housekeeping01:05 Success Stories from the Challenge03:25 Using Prop Stream for Finding Buyers06:53 Burton's Step-by-Step Guide07:48 Live Demonstration with Prop Stream09:20 Advanced Strategies for Finding Buyers18:14 Real-Life Use Case and Q&A32:26 Understanding Property Types33:16 Navigating Prop Stream's Filtering System34:41 Creative Solutions for Data Classification Issues38:14 Leveraging Third-Party Data Sources39:41 Expanding Your Search Scope42:32 Finding Undervalued Properties49:14 Effective Marketing Strategies57:07 Staying Top of Mind with Clients01:02:24 Upcoming Topics and Closing Remarks

In this conversation, Ryan Staley interviews Wen Sang, co-founder of Genspark AI, discussing the innovative features and vision behind Genspark AI. They explore the capabilities of the AI tool, including its ability to create presentations, take meeting notes, and assist knowledge workers in their daily tasks. Wen shares insights into the technology's architecture and demonstrates its functionality live, showcasing how it can streamline the presentation creation process. The discussion concludes with tips for effectively utilizing Genspark AI to enhance productivity and creativity.Chapters00:00 Introduction to Genspark AI02:35 Innovative Features of Genspark AI04:33 The Vision Behind Genspark AI07:28 Live Demonstration of Genspark AI19:48 Tips for Effective Presentation Creation-----

Book a demonstration here. In this episode of the Medics' Money Podcast, Tommy welcomes Dr. Andrew Whiteley, the founder of Lexacom, a widely-used health tech product. They discuss the origins of Lexacom, the challenges faced during its development, and the innovative features of its new version. Dr. Whiteley demonstrates Lexacom's capabilities, including streamlined email dictation, patient visit documentation via mobile, and AI-driven workflow enhancements. Ideal for GPs and hospital doctors, Lexacom aims to save time on administrative tasks and improve patient care. Watch the live demo to see Lexacom in action and learn how to integrate it into your practice. 00:00 Introduction and Guest Welcome 00:43 The Origin Story of Lexacom 03:55 Challenges and Growth of Lexacom 09:36 Innovations and New Features of Lexacom 11:58 Live Demonstration of Lexacom's Capabilities 27:07 Data Security and Privacy Measures 30:08 Conclusion and Final Thoughts   DISCLAIMER: This channel is for education purposes only and does not constitute financial advice and tax allowances and rates are subject to change.

In this powerful episode of Soul Elevation, Kara Goodwin is joined by Beatty Carmichael—known as the “Prayer Doctor”—who shares his transformative, repeatable method for healing through prayer and spiritual alignment. Coming from a lineage of seven generations of medical doctors, Beatty took a different path: blending science with spiritual laws to uncover a highly effective 4-step prayer method. His technique has brought relief to over 700 people—addressing chronic pain, trauma, migraines, anxiety, addictions, and more—often within 12 minutes. During the episode, Kara experiences a live healing demonstration for her neck pain, which drops from a 4 to nearly 0 in real time!

In dieser Episode des Battlepod feiern wir unsere 50. Folge, die 100. vom Dicken Preussen und das 25-jährige Bestehen des Clan Wolf. Ich diskutiere mit meinen Co-Moderatoren und dem besonderen Gast Meldric über die Geschichte des Clans, die Bedeutung von Rollenspiel und Lore sowie die Entwicklung der Clan Wolf App für das Alpha Strike-System. Außerdem erörtern wir die Übernahme von Iron Wind Metals durch Catalyst Game Labs und deren Auswirkungen auf die Battletech-Community. Wir blicken positiv auf zukünftige Events, einschließlich der Möglichkeit einer Live-Demonstration auf der PhoenixCon. Wir sind jetzt auf Patreon und Steady https://steadyhq.com/de/derdickepreusse https://www.patreon.com/derdickepreusse

In dieser Episode des Battlepod feiern wir unsere 50. Folge, die 100. vom Dicken Preussen und das 25-jährige Bestehen des Clan Wolf. Ich diskutiere mit meinen Co-Moderatoren und dem besonderen Gast Meldric über die Geschichte des Clans, die Bedeutung von Rollenspiel und Lore sowie die Entwicklung der Clan Wolf App für das Alpha Strike-System. Außerdem erörtern wir die Übernahme von Iron Wind Metals durch Catalyst Game Labs und deren Auswirkungen auf die Battletech-Community. Wir blicken positiv auf zukünftige Events, einschließlich der Möglichkeit einer Live-Demonstration auf der PhoenixCon. Wir sind jetzt auf Patreon und Steady https://steadyhq.com/de/derdickepreusse https://www.patreon.com/derdickepreusse

If you keep holding back or worrying what people think, there's a deeper reason for it. In this live event clip, we dive into self-acceptance and why letting go of the need for approval changes everything. You'll learn how to own who you came here to be, become magnetic, and finally stop giving a f*ck—just by being yourself. Have you joined the High Vibe Tribe yet? its my new free community! I go live and do free workshops and meditations in there, join here! https://www.skool.com/highvibetribe/about

How To List More Homes As A Real Estate Agent (Using Market Value Cash Offers With iList)(Check out the full video replay here: https://youtu.be/RFlVZS2ZLyY)Grab your 30 day FREE trial at: http://GrowWithJosh.com/ilistIn this episode, Josh Schoenly teams up with special guest Joe Peterson to explore how real estate agents can leverage market value cash offers to secure more listings using the powerful Ilist platform. They dive deep into the latest platform updates, showcasing the ease of generating instant offers for clients and the strategic advantage of using Ilist's advanced features. Josh shares invaluable playbooks for lead generation, email and text campaign templates, and detailed action plans, aiming to enhance your real estate business. The session covers diverse topics including landing page creation, skip tracing potential sellers, leveraging automated home valuations, and actionable methods for converting leads into clients. Whether you're new to Ilist or an experienced user, this episode is packed with actionable insights to help grow your real estate business.Josh Schoenly Realtor®eXp Realty, LLCjosh@growwithjosh.comDirect Line: (717) 571-0456Office - 888-397-7352 x1034Timestamps:00:00 Introduction and Special Guest Announcement00:24 Platform Overview and Free Trial Details00:58 Using the Tool for Real Estate Success03:13 Guest Speaker Joe's Insights03:43 Live Demonstration of the Platform06:49 Creating and Managing Offers24:19 Leveraging Skip Trace and CRM Integration28:24 Building Effective Landing Pages37:41 Email Marketing and Automation40:21 Practical Applications and Action Plans55:31 Engaging with Potential Clients55:59 Using Personal Video Messages56:53 Effective Follow-Up Strategies57:39 Leveraging Direct Mail and Texting58:33 Handling Responses and KPIs59:54 Targeting Engaged Clients01:01:26 Monthly Action Plans for Success01:01:58 Strategies for Expired Listings and FSBOs01:04:10 Open to Offers Playbook01:10:35 Generating Seller Leads01:13:14 Comprehensive Follow-Up System01:16:49 Q&A and Final Thoughts#exprealty #realtor #realestateagent #realtormarketing

Meta just changed the game for ad monetized mobile apps — and if you're not testing AdROAS campaigns yet, you're already behind.In this 2.5 Gamers solo deep dive, Matej walks through exactly how to set up Meta's new AdROAS campaigns, how to unlock the hidden value in your ad impressions, and why this is a must-have in your UA strategy for Android in 2025.

Blake and David dive straight into the headlines, starting with the controversial IRS workforce cuts and their potential impact on tax collections. They examine corporate espionage allegations between payroll companies Rippling and Deel, including a complex web of legal battles, Russian connections, and political involvement, and go on to discuss how AI is rapidly improving at handling longer tasks. All this and much more, right now!SponsorsRightWorks- http://accountingpodcast.promo/rightnow2025Bluevine - http://accountingpodcast.promo/bluevine (Bluevine is a financial technology company, not a bank. Banking Services provided by Coastal Community Bank, Member FDIC.)  Chapters(00:31) - Exciting Stories and Headlines (03:07) - Live Stream Shoutouts (05:08) - Earmark Podcast and CPE Credits (10:56) - IRS Workforce Cuts and Tax Gap (30:13) - Rippling vs. Deel Espionage Saga (41:20) - Evolve Bank and Trust Controversies (42:39) - Rippling and Deal Lawsuit Drama (42:57) - Political Connections and Scandals (44:31) - The Future of AI in Accounting (46:36) - AI Performance and Moore's Law (50:42) - AI's Impact on Accounting Tasks (54:43) - Live Demonstration with Claude AI (01:08:27) - The Future of Accountants in an AI World (01:20:45) - Conclusion and Upcoming Events  Show Notes7,000 IRS workers ‘reinstated' — but not yet returning to workhttps://www.journalofaccountancy.com/news/2025/mar/7000-irs-workers-reinstated-but-not-yet-returning-to-work/ IRS Retreats From Some Audits as Agency Slashes Workforcehttps://www.wsj.com/politics/policy/internal-revenue-service-doge-taxes-f00ac956 Opinion | With IRS cuts, DOGE would lose far more money ...https://www.washingtonpost.com/opinions/2025/03/13/doge-irs-cuts-tax-revenue/ Former Defense Contractor and his Wife Indicted for Evading U.S. Taxes on Profits from Selling Jet Fuel to the U.S. Militaryhttps://www.irs.gov/pub/irs-ci/j5-media-release-7-3-2024.pdf Lawsuit Alleges $12 Billion "Unicorn" Deel Cultivated Spy, Orchestrated Long-Running Trade-Secret Theft & Corporate Espionage Against Competitorhttps://www.rippling.com/blog/lawsuit-alleges-12-billion-unicorn-deel-cultivated-spy-orchestrated-long-running-trade-secret-theft-corporate-espionage-against-competitor IRS in Crisis: Tax Professionals Bear the Brunthttps://cpatrendlines.com/2019/02/26/taxpayer-advocate-lambastes-irs/ Measuring AI Ability to Complete Long Taskshttps://metr.org/blog/2025-03-19-measuring-ai-ability-to-complete-long-tasks/ Earmark Podcast – Ep. 87 - How to Use AI to Analyze Data and Draft Financial Reports in Minuteshttps://share.transistor.fm/s/c86818f5 Earmark's Screening of The Accountant 2https://www.eventbrite.com/e/screening-of-the-accountant-2-tickets-1225264421869?aff=EarmarkAppNeed CPE?Get CPE for listening to podcasts with Earmark: https://earmarkcpe.comSubscribe to the Earmark Podcast: https://podcast.earmarkcpe.comGet in TouchThanks for listening and the great reviews! We appreciate you! Follow and tweet @BlakeTOliver and @DavidLeary. Find us on Facebook and Instagram. If you like what you hear, please do us a favor and write a review on Apple Podcasts or Podchaser. Call us and leave a voicemail; maybe we'll play it on the show. DIAL (202) 695-1040.SponsorshipsAre you interested in sponsoring the Cloud Accounting Podcast? For details, read the prospectus.Need Accounting Conference Info? Check out our new website - accountingconferences.comLimited edition shirts, stickers, and other necessitiesTeePublic Store: http://cloudacctpod.link/merchSubscribeApple Podcasts: http://cloudacctpod.link/ApplePodcastsYouTube: https://www.youtube.com/@TheAccountingPodcastSpotify: http://cloudacctpod.link/SpotifyPodchaser: http://cloudacctpod.link/podchaserStitcher: http://cloudacctpod.link/StitcherOvercast: http://cloudacctpod.link/OvercastWant to get the word out about your newsletter, webinar, party, Facebook group, podcast, e-book, job posting, or that fancy Excel macro you just created? Let the listeners of The Accounting Podcast know by running a classified ad. Go here to create your classified ad: https://cloudacctpod.link/RunClassifiedAdTranscriptsThe full transcript for this episode is available by clicking on the Transcript tab at the top of this page

Send Everyday AI and Jordan a text messageIt's free. It's fast. But is it good? Perplexity joined the Deep Research train, so we are giving it a thorough rundown. Is this your next AI sidekick? Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Ask Jordan questions on PerplexityUpcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:1. Breakdown of Perplexity Deep Research2. Comparison with Other AI Deep Research Models3. Live Demonstration and Deep Research Prompts4. Differences and Mechanics of Deep Research Models5. Results and Analysis of Perplexity's Deep Research QueriesTimestamps:00:00 "Your Everyday AI: Resources & Newsletter"03:51 Perplexity Deep Research Overview07:16 "Deep Seek Truth Episode 460"10:57 "Generative AI Partner Opportunities"15:32 Evolving Importance of Benchmarks19:45 Perplexity: An Answers Engine Competitor22:36 Perplexity's Overwhelming Model Complexity26:15 Researching Nike's Q4 2024 Earnings28:45 Enhancing Language Model Use Skills31:55 Importance of Citing Statistics34:31 DeepSeek's Global Tech Impact38:23 "Fact-Check AI with Personal Data"42:04 AI's False Claims Exposed45:39 AI Query Results Irrelevant48:39 Unrelated Thoughts on Criticism50:22 Comparing AI Research MethodsKeywords:deep research, perplexity, AI companies, tech companies, AI tools, GPT-4, Google Gemini, OpenAI, AI strategy, reasoning models, internet connected models, perplexity deep research, chat GPT search, Google's deep research, OpenAI's deep research, AI benchmarks, humanity's last exam, AI hallucinations, pro search, reasoning search, everyday AI, AI newsletter, AI podcast, AI career growth, generative AI, AI tools comparison, perplexity Sonar, transformer models, reasoning models, AI queries, large language models Ready for ROI on GenAI? Go to youreverydayai.com/partner

Cedric aka Morpheus: https://bio.link/themorpheusMarius Fuxs Wirtz: https://beacons.ai/mariusfuxsKevin Chromik: https://linktr.ee/kevinchromikSpotify: https://open.spotify.com/show/63uh27GWsVeQjvk6qEFWpK?si=ae5a044d7fe545edApple: https://podcasts.apple.com/de/podcast/bitflip/id1713749196?l=en-GBRSS: https://anchor.fm/s/ead1767c/podcast/rss00:00 Einführung und persönliche Updates02:58 Erfahrungen mit E-Autos und Ladestrategien05:58 Die Herausforderungen beim Laden von E-Autos08:52 Technologische Innovationen: Der magische Radierer von Google12:00 Live-Demonstration der Bildbearbeitung mit KI14:10 Beeindruckende KI-Funktionen und deren Anwendung17:05 Die Entwicklung von Bildverarbeitungstechnologien20:49 Die Herausforderungen der Gesichtserkennung und Kategorisierung24:30 Die Integration von KI in den Alltag27:29 Die Genauigkeit von KI-gestützten Recherchen und deren Nutzen29:29 Ein Fazit ohne Untersuchung30:20 Chachibutti vs. Gemini: Ein Vergleich der Recherchetools32:08 Kosten und Verfügbarkeit von Deep Research34:15 Die Rolle der Wissenschaft in der KI-Ära36:07 Effizienzsteigerung durch KI in der Forschung39:51 Die Herausforderungen der wissenschaftlichen Recherche41:44 Die Bedeutung von Primärquellen44:00 Zukunft der Forschung mit KI46:43 Deep Seek und seine Möglichkeiten52:32 Die Entwicklung von KI-Modellen56:46 NVIDIA DIGITS und Unified Memory01:00:36 Die Kosten und Effizienz von Rechenzentren01:02:21 Die Vorteile von Cloud-Diensten01:04:34 Die Zukunft von personalisierten Inhalten

In dieser Folge spreche ich mit Thomas Kovacs, bekannt als "Sparkojote", über seine beeindruckende finanzielle Reise und seine Strategien für den Vermögensaufbau. Thomas, der aus einer einfachen Arbeiterfamilie stammt, hat sich durch kluge Investments und Disziplin eine Millionen-Vermögen aufgebaut. Sein Hauptfokus liegt auf der Generierung von Cashflow durch Optionsstrategien wie Covered Calls und Cash-Secured Puts, mit denen er seine Rendite jährlich um 2–3 % steigert. In einer Live-Demonstration zeigt er, wie er Optionen auf Nestlé-Aktien verkauft und betont, wie wichtig es ist, Trades zu dokumentieren und das Portfolio strategisch zu managen.

Happy holidays! We'll be sharing snippets from Latent Space LIVE! through the break bringing you the best of 2024! We want to express our deepest appreciation to event sponsors AWS, Daylight Computer, Thoth.ai, StrongCompute, Notable Capital, and most of all all our LS supporters who helped fund the gorgeous venue and A/V production!For NeurIPS last year we did our standard conference podcast coverage interviewing selected papers (that we have now also done for ICLR and ICML), however we felt that we could be doing more to help AI Engineers 1) get more industry-relevant content, and 2) recap 2024 year in review from experts. As a result, we organized the first Latent Space LIVE!, our first in person miniconference, at NeurIPS 2024 in Vancouver.Our next keynote covers The State of LLM Agents, with the triumphant return of Professor Graham Neubig's return to the pod (his ICLR episode here!). OpenDevin is now a startup known as AllHands! The renamed OpenHands has done extremely well this year, as they end the year sitting comfortably at number 1 on the hardest SWE-Bench Full leaderboard at 29%, though on the smaller SWE-Bench Verified, they are at 53%, behind Amazon Q, devlo, and OpenAI's self reported o3 results at 71.7%.Many are saying that 2025 is going to be the year of agents, with OpenAI, DeepMind and Anthropic setting their sights on consumer and coding agents, vision based computer-using agents and multi agent systems. There has been so much progress on the practical reliability and applications of agents in all domains, from the huge launch of Cognition AI's Devin this year, to the sleeper hit of Cursor Composer and Codeium's Windsurf Cascade in the IDE arena, to the explosive revenue growth of Stackblitz's Bolt, Lovable, and Vercel's v0, and the unicorn rounds and high profile movements of customer support agents like Sierra (now worth $4 billion) and search agents like Perplexity (now worth $9 billion). We wanted to take a little step back to understand the most notable papers of the year in Agents, and Graham indulged with his list of 8 perennial problems in building agents in 2024.Must-Read Papers for the 8 Problems of Agents* The agent-computer interface: CodeAct: Executable Code Actions Elicit Better LLM Agents. Minimial viable tools: Execution Sandbox, File Editor, Web Browsing* The human-agent interface: Chat UI, GitHub Plugin, Remote runtime, …?* Choosing an LLM: See Evaluation of LLMs as Coding Agents on SWE-Bench at 30x - must understand instructions, tools, code, environment, error recovery* Planning: Single Agent Systems vs Multi Agent (CoAct: A Global-Local Hierarchy for Autonomous Agent Collaboration) - Explicit vs Implicit, Curated vs Generated* Reusable common workflows: SteP: Stacked LLM Policies for Web Actions and Agent Workflow Memory - Manual prompting vs Learning from Experience* Exploration: Agentless: Demystifying LLM-based Software Engineering Agents and BAGEL: Bootstrapping Agents by Guiding Exploration with Language* Search: Tree Search for Language Model Agents - explore paths and rewind* Evaluation: Fast Sanity Checks (miniWoB and Aider) and Highly Realistic (WebArena, SWE-Bench) and SWE-Gym: An Open Environment for Training Software Engineering Agents & VerifiersFull Talk on YouTubePlease like and subscribe!Timestamps* 00:00 Welcome to Latent Space Live at NeurIPS 2024* 00:29 State of LLM Agents in 2024* 02:20 Professor Graham Newbig's Insights on Agents* 03:57 Live Demo: Coding Agents in Action* 08:20 Designing Effective Agents* 14:13 Choosing the Right Language Model for Agents* 16:24 Planning and Workflow for Agents* 22:21 Evaluation and Future Predictions for Agents* 25:31 Future of Agent Development* 25:56 Human-Agent Interaction Challenges* 26:48 Expanding Agent Use Beyond Programming* 27:25 Redesigning Systems for Agent Efficiency* 28:03 Accelerating Progress with Agent Technology* 28:28 Call to Action for Open Source Contributions* 30:36 Q&A: Agent Performance and Benchmarks* 33:23 Q&A: Web Agents and Interaction Methods* 37:16 Q&A: Agent Architectures and Improvements* 43:09 Q&A: Self-Improving Agents and Authentication* 47:31 Live Demonstration and Closing RemarksTranscript[00:00:29] State of LLM Agents in 2024[00:00:29] Speaker 9: Our next keynote covers the state of LLM agents. With the triumphant return of Professor Graham Newbig of CMU and OpenDevon, now a startup known as AllHands. The renamed OpenHands has done extremely well this year, as they end the year sitting comfortably at number one on the hardest SWE Benchful leaderboard at 29%.[00:00:53] Speaker 9: Though, on the smaller SWE bench verified, they are at 53 percent behind Amazon Q [00:01:00] Devlo and OpenAI's self reported O3 results at 71. 7%. Many are saying that 2025 is going to be the year of agents, with OpenAI, DeepMind, and Anthropic setting their sights on consumer and coding agents. Vision based computer using agents and multi agent systems.[00:01:22] Speaker 9: There has been so much progress on the practical reliability and applications of agents in all domains, from the huge launch of Cognition AI's Devon this year, to the sleeper hit of Cursor Composer and recent guest Codium's Windsurf Cascade in the IDE arena. To the explosive revenue growth of recent guests StackBlitz's Bolt, Lovable, and Vercel's vZero.[00:01:44] Speaker 9: And the unicorn rounds and high profile movements of customer support agents like Sierra, now worth 4 billion, and search agents like Perplexity, now worth 9 billion. We wanted to take a little step back to understand the most notable papers of the year in [00:02:00] agents, and Graham indulged with his list of eight perennial problems in building agents.[00:02:06] Speaker 9: As always, don't forget to check our show notes for all the selected best papers of 2024, and for the YouTube link to their talk. Graham's slides were especially popular online, and we are honoured to have him. Watch out and take care![00:02:20] Professor Graham Newbig's Insights on Agents[00:02:20] Speaker: Okay hi everyone. So I was given the task of talking about agents in 2024, and this is An impossible task because there are so many agents, so many agents in 2024. So this is going to be strongly covered by like my personal experience and what I think is interesting and important, but I think it's an important topic.[00:02:41] Speaker: So let's go ahead. So the first thing I'd like to think about is let's say I gave you you know, a highly competent human, some tools. Let's say I gave you a web browser and a terminal or a file system. And the ability to [00:03:00] edit text or code. What could you do with that? Everything. Yeah.[00:03:07] Speaker: Probably a lot of things. This is like 99 percent of my, you know, daily daily life, I guess. When I'm, when I'm working. So, I think this is a pretty powerful tool set, and I am trying to do, and what I think some other people are trying to do, is come up with agents that are able to, you know, manipulate these things.[00:03:26] Speaker: Web browsing, coding, running code in successful ways. So there was a little bit about my profile. I'm a professor at CMU, chief scientist at All Hands AI, building open source coding agents. I'm maintainer of OpenHands, which is an open source coding agent framework. And I'm also a software developer and I, I like doing lots of coding and, and, you know, shipping new features and stuff like this.[00:03:51] Speaker: So building agents that help me to do this, you know, is kind of an interesting thing, very close to me.[00:03:57] Live Demo: Coding Agents in Action[00:03:57] Speaker: So the first thing I'd like to do is I'd like to try [00:04:00] some things that I haven't actually tried before. If anybody has, you know, tried to give a live demo, you know, this is, you know very, very scary whenever you do it and it might not work.[00:04:09] Speaker: So it might not work this time either. But I want to show you like three things that I typically do with coding agents in my everyday work. I use coding agents maybe five to 10 times a day to help me solve my own problems. And so this is a first one. This is a data science task. Which says I want to create scatter plots that show the increase of the SWE bench score over time.[00:04:34] Speaker: And so I, I wrote a kind of concrete prompt about this. Agents work better with like somewhat concrete prompts. And I'm gonna throw this into open hands and let it work. And I'll, I'll go back to that in a second. Another thing that I do is I create new software. And I, I've been using a [00:05:00] service a particular service.[00:05:01] Speaker: I won't name it for sending emails and I'm not very happy with it. So I want to switch over to this new service called resend. com, which makes it easier to send emails. And so I'm going to ask it to read the docs for the resend. com API and come up with a script that allows me to send emails. The input to the script should be a CSV file and the subject and body should be provided in Jinja2 templates.[00:05:24] Speaker: So I'll start another agent and and try to get it to do that for me.[00:05:35] Speaker: And let's go with the last one. The last one I do is. This is improving existing software and in order, you know, once you write software, you usually don't throw it away. You go in and, like, actually improve it iteratively. This software that I have is something I created without writing any code.[00:05:52] Speaker: It's basically software to monitor how much our our agents are contributing to the OpenHance repository. [00:06:00] And on the, let me make that a little bit bigger, on the left side, I have the number of issues where it like sent a pull request. I have the number of issues where it like sent a pull request, whether it was merged in purple, closed in red, or is still open in green. And so these are like, you know, it's helping us monitor, but one thing it doesn't tell me is the total number. And I kind of want that feature added to this software.[00:06:33] Speaker: So I'm going to try to add that too. So. I'll take this, I'll take this prompt,[00:06:46] Speaker: and here I want to open up specifically that GitHub repo. So I'll open up that repo and paste in the prompt asking it. I asked it to make a pie chart for each of these and give me the total over the entire time period that I'm [00:07:00] monitoring. So we'll do that. And so now I have let's see, I have some agents.[00:07:05] Speaker: Oh, this one already finished. Let's see. So this one already finished. You can see it finished analyzing the Swebench repository. It wrote a demonstration of, yeah, I'm trying to do that now, actually.[00:07:30] Speaker: It wrote a demonstration of how much each of the systems have improved over time. And I asked it to label the top three for each of the data sets. And so it labeled OpenHands as being the best one for SWE Bench Normal. For SWE Bench Verified, it has like the Amazon QAgent and OpenHands. For the SWE Bench Lite, it has three here over three over here.[00:07:53] Speaker: So you can see like. That's pretty useful, right? If you're a researcher, you do data analysis all the time. I did it while I was talking to all [00:08:00] of you and making a presentation. So that's, that's pretty nice. I, I doubt the other two are finished yet. That would be impressive if the, yeah. So I think they're still working.[00:08:09] Speaker: So maybe we'll get back to them at the end of the presentation. But so these are the kinds of the, these are the kinds of things that I do every day with coding agents now. And it's or software development agents. It's pretty impressive.[00:08:20] Designing Effective Agents[00:08:20] Speaker: The next thing I'd like to talk about a little bit is things I worry about when designing agents.[00:08:24] Speaker: So we're designing agents to, you know, do a very difficult task of like navigating websites writing code, other things like this. And within 2024, there's been like a huge improvement in the methodology that we use to do this. But there's a bunch of things we think about. There's a bunch of interesting papers, and I'd like to introduce a few of them.[00:08:46] Speaker: So the first thing I worry about is the agent computer interface. Like, how do we get an agent to interact with computers? And, How do we provide agents with the tools to do the job? And [00:09:00] within OpenHands we are doing the thing on the right, but there's also a lot of agents that do the thing on the left.[00:09:05] Speaker: So the thing on the left is you give like agents kind of granular tools. You give them tools like or let's say your instruction is I want to determine the most cost effective country to purchase the smartphone model, Kodak one the countries to consider are the USA, Japan, Germany, and India. And you have a bunch of available APIs.[00:09:26] Speaker: And. So what you do for some agents is you provide them all of these tools APIs as tools that they can call. And so in this particular case in order to solve this problem, you'd have to make about like 30 tool calls, right? You'd have to call lookup rates for Germany, you'd have to look it up for the US, Japan, and India.[00:09:44] Speaker: That's four tool goals. And then you go through and do all of these things separately. And the method that we adopt in OpenHands instead is we provide these tools, but we provide them by just giving a coding agent, the ability to call [00:10:00] arbitrary Python code. And. In the arbitrary Python code, it can call these tools.[00:10:05] Speaker: We expose these tools as APIs that the model can call. And what that allows us to do is instead of writing 20 tool calls, making 20 LLM calls, you write a program that runs all of these all at once, and it gets the result. And of course it can execute that program. It can, you know, make a mistake. It can get errors back and fix things.[00:10:23] Speaker: But that makes our job a lot easier. And this has been really like instrumental to our success, I think. Another part of this is what tools does the agent need? And I, I think this depends on your use case, we're kind of extreme and we're only giving the agent five tools or maybe six tools.[00:10:40] Speaker: And what, what are they? The first one is program execution. So it can execute bash programs, and it can execute Jupyter notebooks. It can execute cells in Jupyter notebooks. So that, those are two tools. Another one is a file editing tool. And the file editing tool allows you to browse parts of files.[00:11:00][00:11:00] Speaker: And kind of read them, overwrite them, other stuff like this. And then we have another global search and replace tool. So it's actually two tools for file editing. And then a final one is web browsing, web browsing. I'm kind of cheating when I call it only one tool. You actually have like scroll and text input and click and other stuff like that.[00:11:18] Speaker: But these are basically the only things we allow the agent to do. What, then the question is, like, what if we wanted to allow it to do something else? And the answer is, well, you know, human programmers already have a bunch of things that they use. They have the requests PyPy library, they have the PDF to text PyPy library, they have, like, all these other libraries in the Python ecosystem that they could use.[00:11:41] Speaker: And so if we provide a coding agent with all these libraries, it can do things like data visualization and other stuff that I just showed you. So it can also get clone repositories and, and other things like this. The agents are super good at using the GitHub API also. So they can do, you know, things on GitHub, like finding all of the, you know, [00:12:00] comments on your issues or checking GitHub actions and stuff.[00:12:02] Speaker: The second thing I think about is the human agent interface. So this is like how do we get humans to interact with agents? Bye. I already showed you one variety of our human agent interface. It's basically a chat window where you can browse through the agent's results and things like this. This is very, very difficult.[00:12:18] Speaker: I, I don't think anybody has a good answer to this, and I don't think we have a good answer to this, but the, the guiding principles that I'm trying to follow are we want to present enough info to the user. So we want to present them with, you know, what the agent is doing in the form of a kind of.[00:12:36] Speaker: English descriptions. So you can see here you can see here every time it takes an action, it says like, I will help you create a script for sending emails. When it runs a bash command. Sorry, that's a little small. When it runs a bash command, it will say ran a bash command. It won't actually show you the whole bash command or the whole Jupyter notebook because it can be really large, but you can open it up and see if you [00:13:00] want to, by clicking on this.[00:13:01] Speaker: So like if you want to explore more, you can click over to the Jupyter notebook and see what's displayed in the Jupyter notebook. And you get like lots and lots of information. So that's one thing.[00:13:16] Speaker: Another thing is go where the user is. So like if the user's already interacting in a particular setting then I'd like to, you know, integrate into that setting, but only to a point. So at OpenHands, we have a chat UI for interaction. We have a GitHub plugin for tagging and resolving issues. So basically what you do is you Do at open hands agent and the open hands agent will like see that comment and be able to go in and fix things.[00:13:42] Speaker: So if you say at open hands agent tests are failing on this PR, please fix the tests. It will go in and fix the test for you and stuff like this. Another thing we have is a remote runtime for launching headless jobs. So if you want to launch like a fleet of agents to solve, you know five different problems at once, you can also do [00:14:00] that through an API.[00:14:00] Speaker: So we have we have these interfaces and this probably depends on the use case. So like, depending if you're a coding agent, you want to do things one way. If you're a like insurance auditing agent, you'll want to do things other ways, obviously.[00:14:13] Choosing the Right Language Model for Agents[00:14:13] Speaker: Another thing I think about a lot is choosing a language model.[00:14:16] Speaker: And for agentic LMs we have to have a bunch of things work really well. The first thing is really, really good instruction following ability. And if you have really good instruction following ability, it opens up like a ton of possible applications for you. Tool use and coding ability. So if you provide tools, it needs to be able to use them well.[00:14:38] Speaker: Environment understanding. So it needs, like, if you're building a web agent, it needs to be able to understand web pages either through vision or through text. And error awareness and recovery ability. So, if it makes a mistake, it needs to be able to, you know, figure out why it made a mistake, come up with alternative strategies, and other things like this.[00:14:58] Speaker: [00:15:00] Under the hood, in all of the demos that I did now Cloud, we're using Cloud. Cloud has all of these abilities very good, not perfect, but very good. Most others don't have these abilities quite as much. So like GPT 4. 0 doesn't have very good error recovery ability. And so because of this, it will go into loops and do the same thing over and over and over again.[00:15:22] Speaker: Whereas Claude does not do this. Claude, if you, if you use the agents enough, you get used to their kind of like personality. And Claude says, Hmm, let me try a different approach a lot. So, you know, obviously it's been trained in some way to, you know, elicit this ability. We did an evaluation. This is old.[00:15:40] Speaker: And we need to update this basically, but we evaluated CLOD, mini LLAMA 405B, DeepSeq 2. 5 on being a good code agent within our framework. And CLOD was kind of head and shoulders above the rest. GPT 40 was kind of okay. The best open source model was LLAMA [00:16:00] 3. 1 405B. This needs to be updated because this is like a few months old by now and, you know, things are moving really, really fast.[00:16:05] Speaker: But I still am under the impression that Claude is the best. The other closed models are, you know, not quite as good. And then the open models are a little bit behind that. Grok, I, we haven't tried Grok at all, actually. So, it's a good question. If you want to try it I'd be happy to help.[00:16:24] Speaker: Cool.[00:16:24] Planning and Workflow for Agents[00:16:24] Speaker: Another thing is planning. And so there's a few considerations for planning. The first one is whether you have a curated plan or you have it generated on the fly. And so for solving GitHub issues, you can kind of have an overall plan. Like the plan is first reproduce. If there's an issue, first write tests to reproduce the issue or to demonstrate the issue.[00:16:50] Speaker: After that, run the tests and make sure they fail. Then go in and fix the tests. Run the tests again to make sure they pass and then you're done. So that's like a pretty good workflow [00:17:00] for like solving coding issues. And you could curate that ahead of time. Another option is to let the language model basically generate its own plan.[00:17:10] Speaker: And both of these are perfectly valid. Another one is explicit structure versus implicit structure. So let's say you generate a plan. If you have explicit structure, you could like write a multi agent system, and the multi agent system would have your reproducer agent, and then it would have your your bug your test writer agent, and your bug fixer agent, and lots of different agents, and you would explicitly write this all out in code, and then then use it that way.[00:17:38] Speaker: On the other hand, you could just provide a prompt that says, please do all of these things in order. So in OpenHands, we do very light planning. We have a single prompt. We don't have any multi agent systems. But we do provide, like, instructions about, like, what to do first, what to do next, and other things like this.[00:17:56] Speaker: I'm not against doing it the other way. But I laid [00:18:00] out some kind of justification for this in this blog called Don't Sleep on Single Agent Systems. And the basic idea behind this is if you have a really, really good instruction following agent it will follow the instructions as long as things are working according to your plan.[00:18:14] Speaker: But let's say you need to deviate from your plan, you still have the flexibility to do this. And if you do explicit structure through a multi agent system, it becomes a lot harder to do that. Like, you get stuck when things deviate from your plan. There's also some other examples, and I wanted to introduce a few papers.[00:18:30] Speaker: So one paper I liked recently is this paper called CoAct where you generate plans and then go in and fix them. And so the basic idea is like, if you need to deviate from your plan, you can You know, figure out that your plan was not working and go back and deviate from it.[00:18:49] Speaker: Another thing I think about a lot is specifying common workflows. So we're trying to tackle a software development and I already showed like three use cases where we do [00:19:00] software development and when we. We do software development, we do a ton of different things, but we do them over and over and over again.[00:19:08] Speaker: So just to give an example we fix GitHub actions when GitHub actions are failing. And we do that over and over and over again. That's not the number one thing that software engineers do, but it's a, you know, high up on the list. So how can we get a list of all of, like, the workflows that people are working on?[00:19:26] Speaker: And there's a few research works that people have done in this direction. One example is manual prompting. So there's this nice paper called STEP that got state of the art on the WebArena Web Navigation Benchmark where they came up with a bunch of manual workflows for solving different web navigation tasks.[00:19:43] Speaker: And we also have a paper recently called Agent Workflow Memory where the basic idea behind this is we want to create self improving agents that learn from their past successes. And the way it works is is we have a memory that has an example of lots of the previous [00:20:00] workflows that people have used. And every time the agent finishes a task and it self judges that it did a good job at that task, you take that task, you break it down into individual workflows included in that, and then you put it back in the prompt for the agent to work next time.[00:20:16] Speaker: And this we demonstrated that this leads to a 22. 5 percent increase on WebArena after 40 examples. So that's a pretty, you know, huge increase by kind of self learning and self improvement.[00:20:31] Speaker: Another thing is exploration. Oops. And one thing I think about is like, how can agents learn more about their environment before acting? And I work on coding and web agents, and there's, you know, a few good examples of this in, in both areas. Within coding, I view this as like repository understanding, understanding the code base that you're dealing with.[00:20:55] Speaker: And there's an example of this, or a couple examples of this, one example being AgentList. [00:21:00] Where they basically create a map of the repo and based on the map of the repo, they feed that into the agent so the agent can then navigate the repo and and better know where things are. And for web agents there's an example of a paper called Bagel, and basically what they do is they have the agent just do random tasks on a website, explore the website, better understand the structure of the website, and then after that they they feed that in as part of the product.[00:21:27] Speaker: Part seven is search. Right now in open hands, we just let the agent go on a linear search path. So it's just solving the problem once. We're using a good agent that can kind of like recover from errors and try alternative things when things are not working properly, but still we only have a linear search path.[00:21:45] Speaker: But there's also some nice work in 2024 that is about exploring multiple paths. So one example of this is there's a paper called Tree Search for Language Agents. And they basically expand multiple paths check whether the paths are going well, [00:22:00] and if they aren't going well, you rewind back. And on the web, this is kind of tricky, because, like, how do you rewind when you accidentally ordered something you don't want on Amazon?[00:22:09] Speaker: It's kind of, you know, not, not the easiest thing to do. For code, it's a little bit easier, because you can just revert any changes that you made. But I, I think that's an interesting topic, too.[00:22:21] Evaluation and Future Predictions for Agents[00:22:21] Speaker: And then finally evaluation. So within our development for evaluation, we want to do a number of things. The first one is fast sanity checks.[00:22:30] Speaker: And in order to do this, we want things we can run really fast, really really cheaply. So for web, we have something called mini world of bits, which is basically these trivial kind of web navigation things. We have something called the Adder Code Editing Benchmark, where it's just about editing individual files that we use.[00:22:48] Speaker: But we also want highly realistic evaluation. So for the web, we have something called WebArena that we created at CMU. This is web navigation on real real open source websites. So it's open source [00:23:00] websites that are actually used to serve shops or like bulletin boards or other things like this.[00:23:07] Speaker: And for code, we use Swebench, which I think a lot of people may have heard of. It's basically a coding benchmark that comes from real world pull requests on GitHub. So if you can solve those, you can also probably solve other real world pull requests. I would say we still don't have benchmarks for the fur full versatility of agents.[00:23:25] Speaker: So, for example We don't have benchmarks that test whether agents can code and do web navigation. But we're working on that and hoping to release something in the next week or two. So if that sounds interesting to you, come talk to me and I, I will tell you more about it.[00:23:42] Speaker: Cool. So I don't like making predictions, but I was told that I should be somewhat controversial, I guess, so I will, I will try to do it try to do it anyway, although maybe none of these will be very controversial. Um, the first thing is agent oriented LLMs like large language models for [00:24:00] agents.[00:24:00] Speaker: My, my prediction is every large LM trainer will be focusing on training models as agents. So every large language model will be a better agent model by mid 2025. Competition will increase, prices will go down, smaller models will become competitive as agents. So right now, actually agents are somewhat expensive to run in some cases, but I expect that that won't last six months.[00:24:23] Speaker: I, I bet we'll have much better agent models in six months. Another thing is instruction following ability, specifically in agentic contexts, will increase. And what that means is we'll have to do less manual engineering of agentic workflows and be able to do more by just prompting agents in more complex ways.[00:24:44] Speaker: Cloud is already really good at this. It's not perfect, but it's already really, really good. And I expect the other models will catch up to Cloud pretty soon. Error correction ability will increase, less getting stuck in loops. Again, this is something that Cloud's already pretty good at and I expect the others will, will follow.[00:25:00][00:25:01] Speaker: Agent benchmarks. Agent benchmarks will start saturating.[00:25:05] Speaker: And Swebench I think WebArena is already too easy. It, it is, it's not super easy, but it's already a bit too easy because the tasks we do in there are ones that take like two minutes for a human. So not, not too hard. And kind of historically in 2023 our benchmarks were too easy. So we built harder benchmarks like WebArena and Swebench were both built in 2023.[00:25:31] Future of Agent Development[00:25:31] Speaker: In 2024, our agents were too bad, so we built agents and now we're building better agents. In 2025, our benchmarks will be too easy, so we'll build better benchmarks, I'm, I'm guessing. So, I would expect to see much more challenging agent benchmarks come out, and we're already seeing some of them.[00:25:49] Speaker: In 2026, I don't know. I didn't write AGI, but we'll, we'll, we'll see.[00:25:56] Human-Agent Interaction Challenges[00:25:56] Speaker: Then the human agent computer interface. I think one thing that [00:26:00] we'll want to think about is what do we do at 75 percent success rate at things that we like actually care about? Right now we have 53 percent or 55 percent on Swebench verified, which is real world GitHub PRs.[00:26:16] Speaker: My impression is that the actual. Actual ability of models is maybe closer to 30 to 40%. So 30 to 40 percent of the things that I want an agent to solve on my own repos, it just solves without any human intervention. 80 to 90 percent it can solve without me opening an IDE. But I need to give it feedback.[00:26:36] Speaker: So how do we, how do we make that interaction smooth so that humans can audit? The work of agents that are really, really good, but not perfect is going to be a big challenge.[00:26:48] Expanding Agent Use Beyond Programming[00:26:48] Speaker: How can we expose the power of programming agents to other industries? So like as programmers, I think not all of us are using agents every day in our programming, although we probably will be [00:27:00] in in months or maybe a year.[00:27:02] Speaker: But I, I think it will come very naturally to us as programmers because we know code. We know, you know. Like how to architect software and stuff like that. So I think the question is how do we put this in the hands of like a lawyer or a chemist or somebody else and have them also be able to, you know, interact with it as naturally as we can.[00:27:25] Redesigning Systems for Agent Efficiency[00:27:25] Speaker: Another interesting thing is how can we redesign our existing systems for agents? So we had a paper on API based web agents, and basically what we showed is If you take a web agent and the agent interacts not with a website, but with APIs, the accuracy goes way up just because APIs are way easier to interact with.[00:27:42] Speaker: And in fact, like when I ask the, well, our agent, our agent is able to browse websites, but whenever I want it to interact with GitHub, I tell it do not browse the GitHub website. Use the GitHub API because it's way more successful at doing that. So maybe, you know, every website is going to need to have [00:28:00] an API because we're going to be having agents interact with them.[00:28:03] Accelerating Progress with Agent Technology[00:28:03] Speaker: About progress, I think progress will get faster. It's already fast. A lot of people are already overwhelmed, but I think it will continue. The reason why is agents are building agents. And better agents will build better agents faster. So I expect that you know, if you haven't interacted with a coding agent yet, it's pretty magical, like the stuff that it can do.[00:28:24] Speaker: So yeah.[00:28:28] Call to Action for Open Source Contributions[00:28:28] Speaker: And I have a call to action. I'm honestly, like I've been working on, you know, natural language processing and, and Language models for what, 15 years now. And even for me, it's pretty impressive what like AI agents powered by strong language models can do. On the other hand, I believe that we should really make these powerful tools accessible.[00:28:49] Speaker: And what I mean by this is I don't think like, you know, We, we should have these be opaque or limited to only a set, a certain set of people. I feel like they should be [00:29:00] affordable. They shouldn't be increasing the, you know, difference in the amount of power that people have. If anything, I'd really like them to kind of make it It's possible for people who weren't able to do things before to be able to do them well.[00:29:13] Speaker: Open source is one way to do that. That's why I'm working on open source. There are other ways to do that. You know, make things cheap, make things you know, so you can serve them to people who aren't able to afford them. Easily, like Duolingo is one example where they get all the people in the US to pay them 20 a month so that they can give all the people in South America free, you know, language education, so they can learn English and become, you know like, and become, you know, More attractive on the job market, for instance.[00:29:41] Speaker: And so I think we can all think of ways that we can do that sort of thing. And if that resonates with you, please contribute. Of course, I'd be happy if you contribute to OpenHands and use it. But another way you can do that is just use open source solutions, contribute to them, research with them, and train strong open source [00:30:00] models.[00:30:00] Speaker: So I see, you know, Some people in the room who are already training models. It'd be great if you could train models for coding agents and make them cheap. And yeah yeah, please. I, I was thinking about you among others. So yeah, that's all I have. Thanks.[00:30:20] Speaker 2: Slight, slightly controversial. Tick is probably the nicest way to say hot ticks. Any hot ticks questions, actual hot ticks?[00:30:31] Speaker: Oh, I can also show the other agents that were working, if anybody's interested, but yeah, sorry, go ahead.[00:30:36] Q&A: Agent Performance and Benchmarks[00:30:36] Speaker 3: Yeah, I have a couple of questions. So they're kind of paired, maybe. The first thing is that you said that You're estimating that your your agent is successfully resolving like something like 30 to 40 percent of your issues, but that's like below what you saw in Swebench.[00:30:52] Speaker 3: So I guess I'm wondering where that discrepancy is coming from. And then I guess my other second question, which is maybe broader in scope is that [00:31:00] like, if, if you think of an agent as like a junior developer, and I say, go do something, then I expect maybe tomorrow to get a Slack message being like, Hey, I ran into this issue.[00:31:10] Speaker 3: How can I resolve it? And, and, like you said, your agent is, like, successfully solving, like, 90 percent of issues where you give it direct feedback. So, are you thinking about how to get the agent to reach out to, like, for, for planning when it's, when it's stuck or something like that? Or, like, identify when it runs into a hole like that?[00:31:30] Speaker: Yeah, so great. These are great questions. Oh,[00:31:32] Speaker 3: sorry. The third question, which is a good, so this is the first two. And if so, are you going to add a benchmark for that second question?[00:31:40] Speaker: Okay. Great. Yeah. Great questions. Okay. So the first question was why do I think it's resolving less than 50 percent of the issues on Swebench?[00:31:48] Speaker: So first Swebench is on popular open source repos, and all of these popular open source repos were included in the training data for all of the language models. And so the language [00:32:00] models already know these repos. In some cases, the language models already know the individual issues in Swebench.[00:32:06] Speaker: So basically, like, some of the training data has leaked. And so it, it definitely will overestimate with respect to that. I don't think it's like, you know, Horribly, horribly off but I think, you know, it's boosting the accuracy by a little bit. So, maybe that's the biggest reason why. In terms of asking for help, and whether we're benchmarking asking for help yes we are.[00:32:29] Speaker: So one one thing we're working on now, which we're hoping to put out soon, is we we basically made SuperVig. Sweep edge issues. Like I'm having a, I'm having a problem with the matrix multiply. Please help. Because these are like, if anybody's run a popular open source, like framework, these are what half your issues are.[00:32:49] Speaker: You're like users show up and say like, my screen doesn't work. What, what's wrong or something. And so then you need to ask them questions and how to reproduce. So yeah, we're, we're, we're working on [00:33:00] that. I think. It, my impression is that agents are not very good at asking for help, even Claude. So like when, when they ask for help, they'll ask for help when they don't need it.[00:33:11] Speaker: And then won't ask for help when they do need it. So this is definitely like an issue, I think.[00:33:20] Speaker 4: Thanks for the great talk. I also have two questions.[00:33:23] Q&A: Web Agents and Interaction Methods[00:33:23] Speaker 4: It's first one can you talk a bit more about how the web agent interacts with So is there a VLM that looks at the web page layout and then you parse the HTML and select which buttons to click on? And if so do you think there's a future where there's like, so I work at Bing Microsoft AI.[00:33:41] Speaker 4: Do you think there's a future where the same web index, but there's an agent friendly web index where all the processing is done offline so that you don't need to spend time. Cleaning up, like, cleaning up these TML and figuring out what to click online. And any thoughts on, thoughts on that?[00:33:57] Speaker: Yeah, so great question. There's a lot of work on web [00:34:00] agents. I didn't go into, like, all of the details, but I think there's There's three main ways that agents interact with websites. The first way is the simplest way and the newest way, but it doesn't work very well, which is you take a screenshot of the website and then you click on a particular pixel value on the website.[00:34:23] Speaker: And Like models are not very good at that at the moment. Like they'll misclick. There was this thing about how like clawed computer use started like looking at pictures of Yellowstone national park or something like this. I don't know if you heard about this anecdote, but like people were like, oh, it's so human, it's looking for vacation.[00:34:40] Speaker: And it was like, no, it probably just misclicked on the wrong pixels and accidentally clicked on an ad. So like this is the simplest way. The second simplest way. You take the HTML and you basically identify elements in the HTML. You don't use any vision whatsoever. And then you say, okay, I want to click on this element.[00:34:59] Speaker: I want to enter text [00:35:00] in this element or something like that. But HTML is too huge. So it actually, it usually gets condensed down into something called an accessibility tree, which was made for screen readers for visually impaired people. And So that's another way. And then the third way is kind of a hybrid where you present the screenshot, but you also present like a textual summary of the output.[00:35:18] Speaker: And that's the one that I think will probably work best. What we're using is we're just using text at the moment. And that's just an implementation issue that we haven't implemented the. Visual stuff yet, but that's kind of like we're working on it now. Another thing that I should point out is we actually have two modalities for web browsing.[00:35:35] Speaker: Very recently we implemented this. And the reason why is because if you want to interact with full websites you will need to click on all of the elements or have the ability to click on all of the elements. But most of our work that we need websites for is just web browsing and like gathering information.[00:35:50] Speaker: So we have another modality where we convert all of it to markdown because that's like way more concise and easier for the agent to deal with. And then [00:36:00] can we create an index specifically for agents, maybe a markdown index or something like that would be, you know, would make sense. Oh, how would I make a successor to Swebench?[00:36:10] Speaker: So I mean, the first thing is there's like live code bench, which live code bench is basically continuously updating to make sure it doesn't leak into language model training data. That's easy to do for Swebench because it comes from real websites and those real websites are getting new issues all the time.[00:36:27] Speaker: So you could just do it on the same benchmarks that they have there. There's also like a pretty large number of things covering various coding tasks. So like, for example, Swebunch is mainly fixing issues, but there's also like documentation, there's generating tests that actually test the functionality that you want.[00:36:47] Speaker: And there there was a paper by a student at CMU on generating tests and stuff like that. So I feel like. Swebench is one piece of the puzzle, but you could also have like 10 different other tasks and then you could have like a composite [00:37:00] benchmark where you test all of these abilities, not just that particular one.[00:37:04] Speaker: Well, lots, lots of other things too, but[00:37:11] Speaker 2: Question from across. Use your mic, it will help. Um,[00:37:15] Speaker 5: Great talk. Thank you.[00:37:16] Q&A: Agent Architectures and Improvements[00:37:16] Speaker 5: My question is about your experience designing agent architectures. Specifically how much do you have to separate concerns in terms of tasks specific agents versus having one agent to do three or five things with a gigantic prompt with conditional paths and so on.[00:37:35] Speaker: Yeah, so that's a great question. So we have a basic coding and browsing agent. And I won't say basic, like it's a good, you know, it's a good agent, but it does coding and browsing. And it has instructions about how to do coding and browsing. That is enough for most things. Especially given a strong language model that has a lot of background knowledge about how to solve different types of tasks and how to use different APIs and stuff like that.[00:37:58] Speaker: We do have [00:38:00] a mechanism for something called micro agents. And micro agents are basically something that gets added to the prompt when a trigger is triggered. Right now it's very, very rudimentary. It's like if you detect the word GitHub anywhere, you get instructions about how to interact with GitHub, like use the API and don't browse.[00:38:17] Speaker: Also another one that I just added is for NPM, the like JavaScript package manager. And NPM, when it runs and it hits a failure, it Like hits in interactive terminals where it says, would you like to quit? Yep. Enter yes. And if that does it, it like stalls our agent for the time out until like two minutes.[00:38:36] Speaker: So like I added a new microagent whenever it started using NPM, it would Like get instructions about how to not use interactive terminal and stuff like that. So that's our current solution. Honestly, I like it a lot. It's simple. It's easy to maintain. It works really well and stuff like that. But I think there is a world where you would want something more complex than that.[00:38:55] Speaker 5: Got it. Thank you.[00:38:59] Speaker 6: I got a [00:39:00] question about MCP. I feel like this is the Anthropic Model Context Protocol. It seems like the most successful type of this, like, standardization of interactions between computers and agents. Are you guys adopting it? Is there any other competing standard?[00:39:16] Speaker 6: Anything, anything thought about it?[00:39:17] Speaker: Yeah, I think the Anth, so the Anthropic MCP is like, a way to It, it's essentially a collection of APIs that you can use to interact with different things on the internet. I, I think it's not a bad idea, but it, it's like, there's a few things that bug me a little bit about it.[00:39:40] Speaker: It's like we already have an API for GitHub, so why do we need an MCP for GitHub? Right. You know, like GitHub has an API, the GitHub API is evolving. We can look up the GitHub API documentation. So it seems like kind of duplicated a little bit. And also they have a setting where [00:40:00] it's like you have to spin up a server to serve your GitHub stuff.[00:40:04] Speaker: And you have to spin up a server to serve your like, you know, other stuff. And so I think it makes, it makes sense if you really care about like separation of concerns and security and like other things like this, but right now we haven't seen, we haven't seen that. To have a lot more value than interacting directly with the tools that are already provided.[00:40:26] Speaker: And that kind of goes into my general philosophy, which is we're already developing things for programmers. You know,[00:40:36] Speaker: how is an agent different than from a programmer? And it is different, obviously, you know, like agents are different from programmers, but they're not that different at this point. So we can kind of interact with the interfaces we create for, for programmers. Yeah. I might change my mind later though.[00:40:51] Speaker: So we'll see.[00:40:54] Speaker 7: Yeah. Hi. Thanks. Very interesting talk. You were saying that the agents you have right now [00:41:00] solve like maybe 30 percent of your, your issues out of the gate. I'm curious of the things that it doesn't do. Is there like a pattern that you observe? Like, Oh, like these are the sorts of things that it just seems to really struggle with, or is it just seemingly random?[00:41:15] Speaker: It's definitely not random. It's like, if you think it's more complex than it's. Like, just intuitively, it's more likely to fail. I've gotten a bit better at prompting also, so like, just to give an example it, it will sometimes fail to fix a GitHub workflow because it will not look at the GitHub workflow and understand what the GitHub workflow is doing before it solves the problem.[00:41:43] Speaker: So I, I think actually probably the biggest thing that it fails at is, um, er, that our, our agent plus Claude fails at is insufficient information gathering before trying to solve the task. And so if you provide all, if you provide instructions that it should do information [00:42:00] gathering beforehand, it tends to do well.[00:42:01] Speaker: If you don't provide sufficient instructions, it will try to solve the task without, like, fully understanding the task first, and then fail, and then you need to go back and give feedback. You know, additional feedback. Another example, like, I, I love this example. While I was developing the the monitor website that I, I showed here, we hit a really tricky bug where it was writing out a cache file to a different directory than it was reading the cache file from.[00:42:26] Speaker: And I had no idea what to do. I had no idea what was going on. I, I thought the bug was in a different part of the code, but what I asked it to do was come up with five possible reasons why this could be failing and decreasing order of likelihood and examine all of them. And that worked and it could just go in and like do that.[00:42:44] Speaker: So like I think a certain level of like scaffolding about like how it should sufficiently Gather all the information that's necessary in order to solve a task is like, if that's missing, then that's probably the biggest failure point at the moment. [00:43:00][00:43:01] Speaker 7: Thanks.[00:43:01] Speaker 6: Yeah.[00:43:06] Speaker 6: I'm just, I'm just using this as a chance to ask you all my questions.[00:43:09] Q&A: Self-Improving Agents and Authentication[00:43:09] Speaker 6: You had a, you had a slide on here about like self improving agents or something like that with memory. It's like a really throwaway slide for like a super powerful idea. It got me thinking about how I would do it. I have no idea how.[00:43:21] Speaker 6: So I just wanted you to chain a thought more on this.[00:43:25] Speaker: Yeah, self, self improving. So I think the biggest reason, like the simplest possible way to create a self improving agent. The problem with that is to have a really, really strong language model that with infinite context, and it can just go back and look at like all of its past experiences and, you know, learn from them.[00:43:46] Speaker: You might also want to remove the bad stuff just so it doesn't over index on it's like failed past experiences. But the problem is a really powerful language model is large. Infinite context is expensive. We don't have a good way to [00:44:00] index into it because like rag, Okay. At least in my experience, RAG from language to code doesn't work super well.[00:44:08] Speaker: So I think in the end, it's like, that's the way I would like to solve this problem. I'd like to have an infinite context and somehow be able to index into it appropriately. And I think that would mostly solve it. Another thing you can do is fine tuning. So I think like RAG is one way to get information into your model.[00:44:23] Speaker: Fine tuning is another way to get information into your model. So. That might be another way of continuously improving. Like you identify when you did a good job and then just add all of the good examples into your model.[00:44:34] Speaker 6: Yeah. So, you know, how like Voyager tries to write code into a skill library and then you reuse as a skill library, right?[00:44:40] Speaker 6: So that it improves in the sense that it just builds up the skill library over time.[00:44:44] Speaker: Yep.[00:44:44] Speaker 6: One thing I was like thinking about and there's this idea of, from, from Devin, your, your arch nemesis of playbooks. I don't know if you've seen them.[00:44:52] Speaker: Yeah, I mean, we're calling them workflows, but they're simpler.[00:44:55] Speaker 6: Yeah, so like, basically, like, you should, like, once a workflow works, you can kind of, [00:45:00] like, persist them as a skill library. Yeah. Right? Like I, I feel like that there's a, that's like some in between, like you said, you know, it's hard to do rag between language and code, but I feel like that is ragged for, like, I've done this before, last time I did it, this, this worked.[00:45:14] Speaker 6: So I'm just going to shortcut. All the stuff that failed before.[00:45:18] Speaker: Yeah, I totally, I think it's possible. It's just, you know, not, not trivial at the same time. I'll explain the two curves. So basically, the base, the baseline is just an agent that does it from scratch every time. And this curve up here is agent workflow memory where it's like adding the successful experiences back into the prompt.[00:45:39] Speaker: Why is this improving? The reason why is because just it failed on the first few examples and for the average to catch up it, it took a little bit of time. So it's not like this is actually improving it. You could just basically view the this one is constant and then this one is like improving.[00:45:56] Speaker: Like this, basically you can see it's continuing to go [00:46:00] up.[00:46:01] Speaker 8: How do you think we're going to solve the authentication problem for agents right now?[00:46:05] Speaker: When you say authentication, you mean like credentials, like, yeah.[00:46:09] Speaker 8: Yeah. Cause I've seen a few like startup solutions today, but it seems like it's limited to the amount of like websites or actual like authentication methods that it's capable of performing today.[00:46:19] Speaker: Yeah. Great questions. So. My preferred solution to this at the moment is GitHub like fine grained authentication tokens and GitHub fine grained authentication tokens allow you to specify like very free. On a very granular basis on this repo, you have permission to do this, on this repo, you have permission to do this.[00:46:41] Speaker: You also can prevent people from pushing to the main branch unless they get approved. You can do all of these other things. And I think these were all developed for human developers. Or like, the branch protection rules were developed for human developers. The fine grained authentication tokens were developed for GitHub apps.[00:46:56] Speaker: I think for GitHub, maybe [00:47:00] just pushing this like a little bit more is the way to do this. For other things, they're totally not prepared to give that sort of fine grained control. Like most APIs don't have something like a fine grained authentication token. And that goes into my like comment that we're going to need to prepare the world for agents, I think.[00:47:17] Speaker: But I think like the GitHub authentication tokens are like a good template for how you could start doing that maybe, but yeah, I don't, I don't, I don't have an answer.[00:47:25] Speaker 8: I'll let you know if I find one.[00:47:26] Speaker: Okay. Yeah.[00:47:31] Live Demonstration and Closing Remarks[00:47:31] Speaker: I'm going to finish up. Let, let me just see.[00:47:37] Speaker: Okay. So this one this one did write a script. I'm not going to actually read it for you. And then the other one, let's see.[00:47:51] Speaker: Yeah. So it sent a PR, sorry. What is, what is the PR URL?[00:48:00][00:48:02] Speaker: So I don't, I don't know if this sorry, that's taking way longer than it should. Okay, cool. Yeah. So this one sent a PR. I'll, I'll tell you later if this actually like successfully Oh, no, it's deployed on Vercel, so I can actually show you, but let's, let me try this real quick. Sorry. I know I don't have time.[00:48:24] Speaker: Yeah, there you go. I have pie charts now. So it's so fun. It's so fun to play with these things. Cause you could just do that while I'm giving a, you know, talk and things like that. So, yeah, thanks. Get full access to Latent Space at www.latent.space/subscribe

saas.unbound is a podcast for and about founders who are working on scaling inspiring products that people love, brought to you by https://saas.group/, a serial acquirer of B2B SaaS companies. Mike is a Co-founder of a marketing agency, creator of AI courses with almost half a million students, and author of a book on prompt engineering. And Ali is a Serial entrepreneur and CTPO of zenloop, a saas.group brand recently relaunched with full AI integration. ----------Episode's Chapters-------------- 00:00 - Introduction to the AI Revolution in SaaS 03:03 - Exploring AI Tools and Their Applications 06:06 - Effective Prompting Techniques for AI 09:08 - Creating Customer Personas and Market Research 12:02 - AI in Customer Communication and Feedback 14:47 - Trust and Reliability in AI Automation 18:01 - Live Demonstration of AI Capabilities 36:28 - Customer Feedback Management and AI Integration 39:44 - The Future of AI in Customer Service 42:24 - Extracting Insights from Customer Interactions 57:02 - Automation and AI: Overcoming Mental Barriers 01:00:55 - Practical Steps for Automation in Startups Mike - https://www.linkedin.com/in/mjt145/ Mike's book - https://www.amazon.com/Prompt-Engineering-Generative-AI-Future-Proof/dp/109815343X Mike's courses - https://app.vexpower.com/courses/ Ali - https://www.linkedin.com/in/ali-naqi-shaheen/ zenloop - https://www.zenloop.com/en/ RodCast - https://www.rodcast.fm/ Subscribe to our channel to be the first to see the interviews that we publish twice a week - https://www.youtube.com/@saas-group Stay up to date: Twitter: https://twitter.com/SaaS_group LinkedIn: https://www.linkedin.com/company/14790796

Nostalgische Zukunftsmusik – so könnte man den Sound von Dim Fumes beschreiben. Das in Berlin lebende Trio verbindet fragile, ätherische Melodien mit melancholischen Synthie-Flächen und schroffen, pulsierenden Beats. Morgen Abend spielen sie im Acud macht NEU die Album-Release-Show zu ihrem Debüt "Liminal Clouds", heute sind sie zu Besuch im studioeins, um darauf einzustimmen. Entstanden sind Dim Fumes vor gerade mal einem Jahr, als sich der Produzent, Filmscore-Komponist und Sänger Lukas Zepf alias No Bloom Now mit den zuvor unter dem Namen Thrived als Duo agierenden Luca Christakopoulus und Marc Landendinger zusammentat. Alle drei sind "inspiriert von der Kulturszene Berlins um 2010, als Mauern durch die Verschmelzung von Indie, R&B und Clubmusik eingerissen wurden." Dieser setzen sie mit "Liminal Clouds" ein Denkmal und lassen sie zugleich in ihrem Sound weiterleben. Über ihre Faszination für die Hauptstadt von vor anderthalb Dekaden, die große Bedeutung, die Verletzlichkeit in ihren Texten spielt, und darüber, was morgen Abend beim Konzert zu erwarten ist, sprechen wir heute mit Dim Fumes. Natürlich werden die drei auch eine kleine Live-Demonstration abliefern!

Nostalgische Zukunftsmusik – so könnte man den Sound von Dim Fumes beschreiben. Das in Berlin lebende Trio verbindet fragile, ätherische Melodien mit melancholischen Synthie-Flächen und schroffen, pulsierenden Beats. Morgen Abend spielen sie im Acud macht NEU die Album-Release-Show zu ihrem Debüt "Liminal Clouds", heute sind sie zu Besuch im studioeins, um darauf einzustimmen. Entstanden sind Dim Fumes vor gerade mal einem Jahr, als sich der Produzent, Filmscore-Komponist und Sänger Lukas Zepf alias No Bloom Now mit den zuvor unter dem Namen Thrived als Duo agierenden Luca Christakopoulus und Marc Landendinger zusammentat. Alle drei sind "inspiriert von der Kulturszene Berlins um 2010, als Mauern durch die Verschmelzung von Indie, R&B und Clubmusik eingerissen wurden." Dieser setzen sie mit "Liminal Clouds" ein Denkmal und lassen sie zugleich in ihrem Sound weiterleben. Über ihre Faszination für die Hauptstadt von vor anderthalb Dekaden, die große Bedeutung, die Verletzlichkeit in ihren Texten spielt, und darüber, was morgen Abend beim Konzert zu erwarten ist, sprechen wir heute mit Dim Fumes. Natürlich werden die drei auch eine kleine Live-Demonstration abliefern!

Nostalgische Zukunftsmusik – so könnte man den Sound von Dim Fumes beschreiben. Das in Berlin lebende Trio verbindet fragile, ätherische Melodien mit melancholischen Synthie-Flächen und schroffen, pulsierenden Beats. Morgen Abend spielen sie im Acud macht NEU die Album-Release-Show zu ihrem Debüt "Liminal Clouds", heute sind sie zu Besuch im studioeins, um darauf einzustimmen. Entstanden sind Dim Fumes vor gerade mal einem Jahr, als sich der Produzent, Filmscore-Komponist und Sänger Lukas Zepf alias No Bloom Now mit den zuvor unter dem Namen Thrived als Duo agierenden Luca Christakopoulus und Marc Landendinger zusammentat. Alle drei sind "inspiriert von der Kulturszene Berlins um 2010, als Mauern durch die Verschmelzung von Indie, R&B und Clubmusik eingerissen wurden." Dieser setzen sie mit "Liminal Clouds" ein Denkmal und lassen sie zugleich in ihrem Sound weiterleben. Über ihre Faszination für die Hauptstadt von vor anderthalb Dekaden, die große Bedeutung, die Verletzlichkeit in ihren Texten spielt, und darüber, was morgen Abend beim Konzert zu erwarten ist, sprechen wir heute mit Dim Fumes. Natürlich werden die drei auch eine kleine Live-Demonstration abliefern!

Nostalgische Zukunftsmusik – so könnte man den Sound von Dim Fumes beschreiben. Das in Berlin lebende Trio verbindet fragile, ätherische Melodien mit melancholischen Synthie-Flächen und schroffen, pulsierenden Beats. Morgen Abend spielen sie im Acud macht NEU die Album-Release-Show zu ihrem Debüt "Liminal Clouds", heute sind sie zu Besuch im studioeins, um darauf einzustimmen. Entstanden sind Dim Fumes vor gerade mal einem Jahr, als sich der Produzent, Filmscore-Komponist und Sänger Lukas Zepf alias No Bloom Now mit den zuvor unter dem Namen Thrived als Duo agierenden Luca Christakopoulus und Marc Landendinger zusammentat. Alle drei sind "inspiriert von der Kulturszene Berlins um 2010, als Mauern durch die Verschmelzung von Indie, R&B und Clubmusik eingerissen wurden." Dieser setzen sie mit "Liminal Clouds" ein Denkmal und lassen sie zugleich in ihrem Sound weiterleben. Über ihre Faszination für die Hauptstadt von vor anderthalb Dekaden, die große Bedeutung, die Verletzlichkeit in ihren Texten spielt, und darüber, was morgen Abend beim Konzert zu erwarten ist, sprechen wir heute mit Dim Fumes. Natürlich werden die drei auch eine kleine Live-Demonstration abliefern!

Welcome back to another enlightening episode of "Obsessed," your go-to personal development podcast featuring expert guests to inspire and motivate you. In this episode, we dive deep into the world of emotions and their impact on our physical and emotional well-being with returning guest, Michael Losier.Key Topics Covered:Unprocessed Emotions and Pain:Michael Losier suggests that pain is often caused by unprocessed emotions, noting that there are 60 different negative emotions. He elaborates on how these emotions can physically manifest in the body as pain or numbness if not addressed properly.The Emotion Code:Our episode explores the Emotion Code, a concept by Dr. Bradley Nelson, which helps unblock negative emotions. Michael shares his obsession with activities that make him feel good, reframing selfishness as self-care and stressing the importance of maintaining a high vibration through "vibrational boundaries" to avoid negativity.Emotion Identification and Deletion:Michael talks about identifying and deleting emotions on behalf of others using techniques like muscle testing and magnets. He shares accounts of how unprocessed emotions can manifest as physical pain, including a case where a man's seven-year foot numbness was relieved after an emotion code session.Processing and Clearing Emotions:Through muscle testing, Michael connects with a person's subconscious to identify and clear emotional blocks. He provides examples, such as improving relationships and emotional health by clearing past emotional baggage, including a significant change in a woman's mother's behavior after a session.Alternative Approach to Pain Relief:Michael introduces his method as an alternative for dealing with physical pain, relationship issues, and emotional blocks, emphasizing that it relies on yes/no questions rather than intuition or guessing.Impact on Behavior:Michael shares a story about improving a young boy's eating habits through an emotion code session conducted with his mother's permission, illustrating the potential behavioral impact of clearing negative emotions.Group Sessions on Clubhouse:Michael conducts group sessions where he identifies and deletes emotions affecting relationships. Participants have reported positive behavioral changes post-session.Live Demonstration and Audience Engagement:Michael offers to demonstrate and explain the process to familiarize the audience with his methods, showing how it can address various personal and professional barriers.Michael's Healing Sessions:Host Julie experiences a headache and Michael works to alleviate it through his method, identifying emotions like fear and rejection contributing to the pain and using magnets to delete them. Julie confirms her headache has disappeared, attributing it to weather changes.

In this episode, I'm joined by Maxx Miller, an expert Neurosomatic Specialist from Kodawari Studios in Tampa, FL. Maxx specializes in helping clients unravel the complex relationship between chronic pain, stress, and their nervous systems. On the first in-person interview, we dive into the role of neurosomatic therapy in addressing physical tension, posture imbalances, and how emotional stress can manifest in the body. Maxx shares practical tips for those dealing with chronic pain or stress, and we explore how his approach can complement other wellness practices to transform your health. If you've been struggling with pain that just won't go away or feel like your body is holding onto stress, this episode is for you! Connect with Maxx: Instagram: @th3_Maxx Book an In-Person Session with Maxx Connect with Avery: Instagram: ⁠@alignedbyavery⁠ Website: www.alignedbyavery.com

Willkommen zu einer neuen Episode von Mit Schirm, Charme und Sensoren! In dieser Folge tauchen wir ein in die Welt der Large Language Models (LLMs) und wie sie die Produktion und Instandhaltung transformiert. Elisabeth diskutiert mit Michael, unserem erfahrenen Automatisierungsexperten, über den Einsatz von Large Language Models in der Industrie.  In dieser Episode erfährst du:  Unstrukturierte Daten nutzbar machen: Wie KI hilft, Freitextfelder und alte Datenbestände zu analysieren und wertvolle Erkenntnisse zu gewinnen.  Live-Demonstration von ChatGPT: Erlebe, wie KI die häufigsten Störungen in einer Anlage identifiziert und welche Vorteile das für Unternehmen hat.  Effizienzsteigerung und Fachkräftemangel bewältigen: Wie KI-Tools die Arbeit erleichtern, Fachpersonal entlasten und Mitarbeitern ermöglichen, komplexe Analysen durchzuführen.  Schnelle und einfache Implementierung: Erfahre, wie einfach es ist, KI-Lösungen in bestehende Systeme zu integrieren und innerhalb weniger Wochen Ergebnisse zu erzielen.  Michael und Elisabeth bieten Einblicke in ihre Erfahrungen und zeigen, wie moderne KI-Technologien nicht nur Kosten senken, sondern auch die Produktivität steigern können. 

In this emotional episode, Gabby Reece sits down with Dr. Richard Schwartz, the creator of the Internal Family Systems (IFS) model of therapy. Dr. Schwartz explains how IFS helps individuals address and heal their inner emotional conflicts by understanding their "parts"—the different facets of their personalities that carry past traumas, anxieties, or unresolved emotions. This episode covers the foundations of IFS, its applications in therapy, and practical tips for integrating self-compassion and mindfulness into everyday life. Dr. Schwartz shares real-life examples of how he helps clients identify their protective parts, heal past trauma, and foster self-leadership. Gabby takes part in a live demonstration of the IFS process, providing listeners with an intimate view of how IFS can help individuals reconnect with their authentic selves and heal from past emotional wounds. Sponsors: Fatty 15: Fatty15 is on a mission to replenish your C15 levels and restore your long-term health. You can get an additional 15% off their 90-day subscription Starter Kit by going to fatty15.com/GABBY and using code GABBY at checkout for an additional 15% off your first order. Maui Nui: Get 20% off your first order of fresh venison, jerky, broth, and ‘ohana subscription by going to www.MauiNuiVenison.com/GABBY and using the code GABBY at checkout. Bon Charge: My listeners get 15% off when you order from boncharge.com and use my exclusive promo code GABBY at checkout Show Notes Introduction to Dr. Richard Schwartz and Internal Family Systems (IFS) Gabby introduces Dr. Schwartz, providing background on his career and the development of the Internal Family Systems model of therapy, which is rooted in understanding the "parts" of ourselves that protect us from emotional pain. Understanding Our Internal Parts [00:00:00 - 00:10:00] Dr. Schwartz explains the concept of "parts" in IFS therapy—sub-personalities that protect us by carrying different burdens and traumas from the past. He discusses the importance of understanding and healing these parts for emotional well-being. The Power of Curiosity in Healing [00:10:01 - 00:25:00] Gabby and Dr. Schwartz discuss the role of curiosity in self-awareness and healing. By approaching one's emotional parts with compassion and curiosity, individuals can begin to heal past wounds and release the protective mechanisms that no longer serve them. A Live Demonstration of IFS [00:25:01 - 00:45:00] Gabby participates in a live IFS session led by Dr. Schwartz. He guides Gabby through identifying and working with one of her protective parts, providing listeners with a firsthand look at how IFS therapy works. No Bad Parts: The Healing Process [00:45:01 - 01:00:00] Dr. Schwartz emphasizes the idea that there are "no bad parts" in us—only parts that have taken on protective roles. He explains how healing these parts can lead to greater self-compassion, freedom, and emotional resilience. Applying IFS in Daily Life and Relationships [01:00:01 - 01:15:00] Gabby and Dr. Schwartz explore how individuals can use IFS in their daily lives to improve their relationships, communication, and emotional regulation. They also touch on how parents can teach these principles to their children. The Future of IFS and Mental Health [01:15:01 - 01:30:00] Dr. Schwartz discusses his vision for the future of IFS and how it can be used not only in therapy but in broader cultural and societal contexts. He shares insights into how IFS can transform family dynamics and mental health on a larger scale. Resources: Dr. Richard Schwartz Website: Learn more about Internal Family Systems at https://ifs-institute.com/ Follow @internalfamilysystems on Social Media Everything Gabby Reece: YouTube: https://www.youtube.com/@GabbyReece Instagram: https://www.instagram.com/gabbyreece/ TikTok: https://www.tiktok.com/@gabbyreeceofficial Facebook: https://www.facebook.com/OfficialGabrielleReece/ Gabby Reece Website - https://gabriellereece.com/ Learn more about your ad choices. Visit megaphone.fm/adchoices

In this episode of "Vibe Science," hosts Ryan Alford and Chris Hansen engage in a deep conversation with Stephanie Kwong, a subconscious rewiring coach, hypnotherapist, and breathwork facilitator. They delve into various wellness modalities, with a particular focus on subconscious rewiring as a powerful tool for overcoming emotional challenges and trauma. Stephanie shares her personal journey into hypnotherapy, which began after experiencing the profound grief of a miscarriage. She introduces the Rapid Rewire Method, a transformative technique for emotional healing, and provides listeners with practical tools to better manage their emotions. The episode highlights the critical role of community support and encourages listeners to explore innovative healing modalities for personal growth and overall well-being.TAKEAWAYSSubconscious rewiring and its impact on emotional healthThe role of neuroplasticity in changing deep-seated beliefsPersonal experiences with trauma and griefThe Rapid Rewire Method for emotional healingPractical exercises for processing emotionsThe dual nature of emotions and their significanceThe consequences of suppressing emotions on mental and physical healthThe importance of community and support in the healing processTools for enhancing emotional literacy and wellnessEncouragement for personal growth through emotional workTIMESTAMPSIntroduction to Vibe Science (00:00:00)The hosts introduce the podcast and its focus on wellness and personal growth.Guest Introduction (00:00:16)Ryan and Chris introduce their guest, Stephanie Kwong, a subconscious rewiring coach.Stephanie's Background (00:01:22)Stephanie shares her journey into hypnotherapy and her experiences with various healing modalities.Living in Colorado (00:01:43)Stephanie discusses her move to Colorado and her skiing experiences.Hypnotherapy Insights (00:02:22)Ryan expresses his fascination with hypnotherapy and its misconceptions.Stephanie's Healing Journey (00:03:03)Stephanie explains her background in hypnotherapy and various healing modalities.The Impact of Grief (00:04:18)Stephanie shares her experience with grief after a miscarriage and its effects.Discovery of Rapid Rewire Method (00:06:20)Stephanie discusses how she found tools to process her trauma and emotional charge.Empowerment Through Tools (00:08:30)Stephanie emphasizes her mission to empower others with healing tools.Neuroplasticity and Rewiring (00:09:45)Stephanie explains how neuroplasticity allows for rewiring of the mind and beliefs.The Role of Subconscious Mind (00:10:26)Discussion on how subconscious beliefs impact adult behavior and self-perception.Effective Healing Methods (00:12:37)Stephanie outlines the need for tools that address root causes rather than just coping.Introduction to Xavier Levinsky (00:14:43)Stephanie credits researcher Xavier Levinsky for developing effective healing tools.Sharing a Practical Tool (00:18:55)Stephanie offers a simple emotional processing tool for listeners to use immediately.Live Demonstration of the Tool (00:21:35)Ryan volunteers to try the emotional processing tool on the podcast.Exploring Emotional Triggers (00:22:12)Discussion on how external drama affects personal emotional responses, particularly regarding anger.Identifying Emotions (00:22:40)Engagement in identifying specific emotions triggered by a person's baggage.Rating Anger (00:23:01)Assessment of anger intensity on a scale from 1 to 10, focusing on its debilitating effects.Good vs. Bad of Anger (00:24:05)An exercise to explore the positive and negative aspects of anger to facilitate emotional release.Impact of Anger on Productivity (00:25:07)Understanding how anger can limit productivity and distract from goals.Acknowledging Human Emotion (00:25:40)Recognition of anger as a sign of being human and its implications.Emotional Clarity (00:26:06)Discussion on how anger can clarify personal preferences and dislikes.Reflection on Self-Image (00:27:08)Exploration of how anger can negatively reflect on one's self-image.Using Anger as Motivation (00:28:48)Understanding how anger can energize and motivate actions.Emotional Liberation Techniques (00:30:23)Introduction of a quick method to reduce emotional intensity and promote liberation.Emotional Literacy in Society (00:34:13)Discussion on the lack of emotional literacy and its effects on mental health.Mind-Body Connection (00:36:04)Emphasis on the interconnectedness of mental, emotional, and physical health.Final Thoughts and Resources (00:39:20)Stephanie shares resources for listeners to explore subconscious rewiring and emotional wellness. Follow us on Instagram: @Vibe.Science Subscribe to our YouTube Page: www.youtube.com/@Vibe.Science

In this episode, Jay interviews Austin Mao, a keynote speaker, executive coach, and co-founder of a Denver-based psychedelic and spiritual healing center called Ceremonia. He specializes in integrating ancient traditions with modern practices to improve spiritual well-being. They discuss the importance of self-awareness as a prerequisite to walking the path of enlightenment. They also share advice for dealing with adversity and “messiness” that is inherent in our human existence. Finally, they touch on energy management and energy transfer that occurs through interpersonal relationships, both emotional and physical. Tune in if you want to be more present in your life, and gain a better understanding of the transformative power that true awareness, acceptance, and self-love can have on your existence. Put their advice into practice, and you'll have a more harmonious relationship with the world around you. "I think if we really zoom out for humanity, there's a lot of really incredible things happening right now. There's a lot of people that are seeking spirituality now and seeking it in more sustainable, grounded, connected ways." – Austin Mao   What You'll Learn From This Episode The Building Blocks of Enlightenment – Understand the rigorous self-work that is required for spiritual growth. Commit to the pursuit of self-awareness, self-love, and spiritual evolution as key components of your personal growth. The Healing Powers of Psychedelic Experiences – Learn how Austin helps his clients health their traumas and expand their mind through psychedelic experiences. Hear Jay's personal story of psychedelic-supported self-discovery. Integrating Ancient Traditions With Modern Practices – Explore ways to combine traditional practices from a diverse set of cultures with modern medical practices to achieve optimal results. The Energetic Transfer of Sexuality – Hear how shame is related to sexuality, and learn why properly exploring (and managing) your sexual energy is critical to uncovering the patterns that are impacting your relationships. Mindfulness, Presence, and Acceptance – Underline the significance of accepting, loving, and trusting yourself as foundational elements for personal development, inner peace, and authentic living. Key Moments In This Conversation 00:00:00 – Introduction 00:01:57 – Austin's take on the future of humanity 00:06:58 – The Pursuit of Enlightenment 00:08:23 – The Role of AI in Human Consciousness 00:11:50 – Adversity As Part Of The Human Experience 00:16:32– How Austin Brings Cultural Diversity To His Spiritual Practice 00:20:53 – Legal Considerations For Administering Entheogens 00:22:42 – Live Demonstration of "Circling" Practice With Jay 00:28:16 – What Do You Want To Feel Before You Die? 00:31:26 – Why Achievement Doesn't Always Lead To Fulfillment 00:34:17 – Consciousness In Relationships And Sex 00:40:30 – The Most Important Thing In Life 00:44:13 – Closing Thoughts And Austin's Resources Guest Bio Austin Mao is a keynote speaker, executive coach, and the co-founder of Ceremonia, a nonprofit and legal psychedelic and spiritual center based in Denver, Colorado. He has worked with more than 400 founders, executives, combat veterans, and individuals looking to heal their trauma or initiate a journey of self-discovery. His ability to guide his clients through transformative experiences, such as psychedelic ceremonies, makes him a highly sought-after mentor in the areas of spiritual growth and healing. Learn more about Austin and his work at austinmao.com and ceremoniacircle.org.   Jay Campbell Products & Resources

Star Magic offers the most comprehensive hands-on and distance healing for everyone anywhere in the world. Energy healing is an ability that we all have. Each of us simply needs to be shown how to tap into our inner potential. Once you have trained in Star Magic you can go out into the world and use the skills and tools you learn to elevate your life, your business, and the lives of others. Jerry Sargeant is the founder of Star Magic Healing. He is a powerful motivational speaker, a highly respected and deeply knowledgeable educator, and an international bestselling author. Jerry is world renowned for healing people, creating rapid shifts within them, and transforming their lives on the mental, physical, emotional, and spiritual planes. Jerry has trained thousands of Souls in more than 40 countries to facilitate healing using the Star Magic Frequency and is building healing centres around the world in strategic high energy locations. Jerry's Sargeant's Star Magic Healing training courses are highly practical and transformative. They are for anyone who wants to explore energy healing, DNA and third eye activation, and transform their lives by stepping into their authentic power so they can best serve humanity by living in a state of wonder and joy, on an ultra-high vibration. ➡ For more information about Star Magic Training visit: starmagichealing.org/facilitator-training ➡ Join my new Telegram group: t.me/spiritualgangsta1 ➡ Join my Instagram channel: @sargeantjerry ➡ Download a free guided meditation here: www.starmagichealing.org/complimentary-meditation/ ➡ Sign up for a 7-day free trial of our vast Star Magic Meditation Library: www.starmagichealing.org/meditations-library/ ➡ Personal healing consultations available: www.starmagichealing.org/private-healing ➡ Get access to a whole library of ascension tools: starmagichealing.org/welcome-to-infinity

#02 La Marzocco Roadshow Berlin: Sensorische Analyse mit Café ImportsDie Café Imports Coffee-Rose und ihre Bedeutung für die KaffeeweltIn dieser besonderen Folge des La Marzocco Monday Special berichtet das Team von La Marzocco von der Roadshow in Berlin, die sich diesmal dem faszinierenden Thema der sensorischen Analyse widmet. Im Mittelpunkt steht die Café Imports Coffee-Rose, ein innovatives Tool zur Bewertung und Verbesserung der sensorischen Qualität von Kaffee.Die Experten von Café Imports erläutern, wie die Coffee-Rose entwickelt wurde und welche Rolle sie in der modernen Kaffeewelt spielt. „Die sensorische Analyse ist der Schlüssel zur Entdeckung der feinsten Nuancen im Kaffee,“ erklärt ein Vertreter von Café Imports und betont die Bedeutung dieser Methode für die Kaffeebranche.Ein zentrales Thema der Roadshow ist die praktische Anwendung der Coffee-Rose und wie sie Röstern und Baristas hilft, die Qualität ihres Kaffees zu bewerten und zu verbessern. „Die Coffee-Rose bietet eine strukturierte Methode, um die sensorischen Eigenschaften des Kaffees zu analysieren,“ sagt ein Experte und zeigt, wie dieses Tool genutzt wird, um den Geschmack und das Aroma von Kaffee präzise zu beschreiben.Das Team von La Marzocco diskutiert auch die Vorteile und Herausforderungen der sensorischen Analyse. Teilnehmer der Roadshow teilen ihre Erfahrungen und Erkenntnisse aus der praktischen Anwendung der Coffee-Rose. „Es ist faszinierend zu sehen, wie detailliert die sensorische Analyse sein kann und wie sie uns hilft, unseren Kaffee zu perfektionieren,“ betont ein erfahrener Röster aus Berlin.Ein weiteres Highlight der Episode ist eine Live-Demonstration der Coffee-Rose, bei der die Experten von Café Imports Schritt für Schritt erklären, wie man die verschiedenen Geschmacksnoten und Aromen im Kaffee identifiziert. „Die sensorische Analyse erfordert Training und Erfahrung, aber sie ist unverzichtbar für jeden, der die höchste Qualität in seinem Kaffee erreichen möchte,“ sagt einer der Kaffeekenner.Erfahre mehr über die sensorische Analyse und die Café Imports Coffee-Rose, die Kaffeeliebhabern und Profis gleichermaßen hilft, die feinsten Nuancen im Kaffee zu entdecken und zu genießen. Diese Episode ist ein Muss für alle, die sich für die tiefergehenden Aspekte der Kaffeequalität und -bewertung interessieren.Tauche ein und entdecke, wie die sensorische Analyse und die Coffee-Rose die Kaffeewelt bereichern! Get bonus content on Patreon Hosted on Acast. See acast.com/privacy for more information.

Dr. Amy Dufrane, SPHR, CAE, is the CEO of HRCI, and the founder of HRCI's sister organization, the HR Standards Institute (HRSI). Amy has spent her career helping businesses maximize their human capital and HR professionals maximize their careers. As HRCI's top steward, she leads an organization dedicated to assisting more than 500,000 business-leader members around the world who want to enhance their HR and expertise through learning and certification. Amy oversees HRCI's work to establish international HR standards in partnership with ISO, the American National Standards Institute (ANSI), and the global community. She is a member of the Wall Street Journal CEO Council, the Economic Club of Washington, DC, and CEO Update's CEO Roundtable. Through these organizations, she connects regularly with CEOs, CHROs, and other leaders, giving her firsthand knowledge of the workplace changes happening in industries everywhere. Prior to joining HRCI, Amy held CHRO and executive HR leadership roles at organizations in a variety of industries, where she faced issues similar to those confronting the HR professionals she partners with today. She chairs the board for the Columbia Lighthouse for the Blind, is a director of the Institute for Credentialing Excellence, and serves on the advisory board of Certree and Southern New Hampshire University.

Join Bo and Timmy in this highly anticipated episode of "Commercially Speaking," where Bo combines the powerful insights from the last two episodes to conduct a live market analysis for one of our listeners' chosen markets. Using Site To Do Business and Moody's Market Pro, Bo gathers and interprets both demand and supply side data to provide a comprehensive analysis. What You'll Learn: Real-Time Market Analysis: Watch as Bo demonstrates the process of collecting and analyzing market data in real-time, showcasing the practical application of the tools discussed in previous episodes. Demand and Supply Integration: Learn how to effectively integrate demand and supply data to form a complete picture of the market, enabling more informed decision-making. Investigative Techniques: Bo reveals the investigative steps every CRE broker or investor should take to gather the best possible information, mitigating risks and gaining a competitive edge. Actionable Insights: See how the analysis translates into actionable strategies that can help investors make serious money in the chosen market. Whether you're a CRE professional looking to enhance your analytical skills or an investor seeking to understand the intricacies of market analysis, this episode is packed with valuable insights and practical advice. Tune in to "Commercially Speaking" and learn how to perform a thorough market analysis that can guide your investment decisions and boost your profitability. 00:00:00 - Start 00:00:46 - Fart Smeller 00:02:14 - Bo figure's out the magic 00:07:41 - What are you teaching me today? 00:11:12 - Who is doing this work? 00:13:20 - Site To Do Business (Demand Side Data) 00:14:39 - Executive Summary 00:15:00 - Population 00:16:09 - Median Age 00:16:28 - Households 00:17:05 - Household Income 00:17:46 - GINI Index 00:20:01 - Renters vs Owners 00:20:38 - Business Summary 00:21:09 - Population to Employment Ratio 00:21:53 - Economy Diversification (NAICS Codes) 00:24:11 - Moody's (Supply side data) 00:25:45 - REIC Report for Melbourne 00:26:08 - Executive Briefing 00:26:59 - Market Overview 00:27:30 - Competitive Inventory 00:30:57 - Long Term Average Vacancy 00:39:28 - Market Transactions 00:40:51 - Segmented Transactions 00:41:43 - The Pipeline 00:42:27 - Shift Share Analysis 00:43:10 - National Growth 00:43:59 - Industry Mix 00:44:50 - Regional Shift 00:45:14 - Comparative Advantage 00:49:01 - Filling in the gaps 00:51:31 - Regional shift conclusion 00:52:14 - Economic Base Analysis (EBA) 00:52:28 - Basic Jobs 00:53:09 - Non-basic Jobs 00:53:59 - Economic Base Multiplier (EBM) 00:56:09 - Desegregated EBM 00:59:00 - Market Cycle 01:01:37 - Expectation from Market Cycle data 01:03:39 - Wouldn't the dip be more severe? 01:05:51 - So what is your conclusion? 01:06:42 - In Summary 01:09:38 - Why not give it a Goog? 01:13:16 - On the next episode of Commercially Speaking

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Understanding and engaging clients is crucial for the success of any business. It involves building strong relationships with clients and prospects, fostering loyalty, and turning potential clients into long-term partners. By understanding what makes people tick and using effective communication strategies, businesses can overcome challenges in client engagement and improve productivity. In this podcast episode, Mari-Liis Vaher from Powerful Marketers interviews Alan Stevens, an international profiling and communication specialist. His expertise in human pattern recognition has made him a sought-after specialist, regularly featured in national television, radio, and the world's press. Quotes: "Your facial features tell us everything about your personality." (00:06:50) "Well, I'm talking about personality, how somebody likes to think and process, not what they're thinking and processing." (00:19:20) "Because if we don't connect with them, like tune our transmitter into their receiver, the other person's not comfortable." (00:22:23) "Yes, if I can read the person, I know how to talk to them the best way, I can really connect with them, I can therefore find out more about what they really need and what they really want, and then I can then show that I've got a service that will provide that, removing their worry, removing their stress, saving them time, saving them money or making them money, and giving the emotional feelings that they want. And the person goes, well, I might be paying $10,000 for something, but I'm making five, 10 times that amount in the return." (00:29:47) “If I talk about you to other people, 80% of people will listen to me. If you talk about yourself to the same people, the statistics show that about 7% will listen to you. That's why advertising doesn't work really well because they haven't got to know and like you at that point.” (00:32:33) “No, you put your staff first. You treat them in a way in which they feel that they belong, they contribute, they're valued, because everybody needs that to be productive. And then they will be the ones who actually deal with your customers. So when you put your staff first, you're actually putting your customers first.” (00:33:33) Timestamps: [00:04:26] Understanding Human Pattern Recognition [00:10:48] Live Demonstration of Profiling [00:20:39] Benefits of Profiling in Business and Marketing [00:34:08] Utilizing DISC Profiles in Conjunction with Face Profiling Links: Connect with Alan Stevens: Website: https://www.alanstevens.com.au  LinkedIn: https://www.linkedin.com/in/readingfaces/  Facebook: https://www.facebook.com/ReadingFaces/  

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In a recent conversation Elizabeth and I delved into the intersection of art, spirituality, and the cutting-edge world of artificial intelligence. Our dialogue touched upon the nuances of artistic identity, the role of AI as a creative tool, and the potential applications of this technology in the realm of spirituality.The conversation primarily revolves around demystifying AI, exploring its creative applications, and debunking fears associated with its potential impact on various industries, particularly in the realm of art and design. Elizabeth emphasizes the role of humans in guiding and training AI to enhance creativity rather than replace it.BIO:S. Elizabeth Gomes is a passionate advocate for embracing the simplicity of loving YHWH and recognizing how deeply and faithfully we are loved by Him. She believes this understanding is pivotal to unlocking the depths of His heart and being deeply rooted in the layered facets of His consuming fire. For Elizabeth, this burning love is not just an emotion but a transformative key for our maturation. A true visionary, Elizabeth wears several hats in this glorious adventure, weaving together her creative endeavors in mentoring, facilitating weekly meetings with her community, Ecclesia of Burning Ones, book editing and publishing, designing websites, video editing, and other creative expressions into a wonderful mural.She considers herself a ‘mystical solutionist' committed to discovering the answers that have already been provided for us in every aspect of life. Her exploration into technology, particularly AI tools, is a testament to her belief in continual learning and adaptation. She views technology as a divine gift, emphasizing the importance of a balanced and respectful approach to these modern tools.Her philosophy is deeply rooted in the belief that love, honor, and humility form a powerful triad. This combination, she asserts, provides stability and foundation which can anchor us through life's various transitions of transformations and transfigurations. Therefore, be fearless in love, honor and humility. HIGHLIGHTS:Definition and Perspective on AI:- Elizabeth defines AI as artificial intelligence and emphasizes the importance of a positive perspective on AI.- Addresses the fear surrounding AI but suggests viewing it as a tool created and guided by humans rather than a threat.Understanding AI and Machine Learning:- Explains that AI is a computer system trained with algorithms and programs using available data.- Emphasizes that AI is not infinite and cannot function without predefined algorithms set by humans.Creativity and AI in Artwork:- Discusses how creatives can use AI tools like Mid Journey, Canva, Chat Gp, Dali E, Procreate, and Adobe Creative Cloud.- Highlights that AI enhances creativity by generating iterations based on input from the user.AI in Writing and Copywriting:- Elizabeth explains using Chat Gp for writing, providing specific instructions for desired content and style.- Talks about training AI to understand keywords for a more tailored output.Artistic Process with AI:- Describes the process of feeding original artwork into AI tools like Dali E and Chat Gp for unique and creative outputs.- Addresses potential concerns about copyright, mentioning that AI-generated art tends to be unique and not an exact duplication.- Discusses the issue of using artists' names to train AI in specific styles and mentions potential copyright concerns.Considers the distinction between training AI and actual copyright infringement.Biblical Parallels and Creative Process:- Elizabeth drew parallels between the creative process, biblical scriptures, and the concept of manifesting the invisible into the visible. The conversation touched on the idea that thoughts and imagination are powerful tools for creating reality.Live Demonstration of AI Art Creation:- The conversation took an exciting turn with a live demonstration of AI art creation. Elizabeth used AI platforms, including DALL-E and MidJourney, to generate artistic images based on given descriptions. They explored the possibilities of creating heavenly gardens and throne rooms, showcasing the interpretative abilities of AI.AI in Spirituality:- The discussion circled back to the application of AI in spirituality. Bralynn emphasized the potential for individuals to use AI as a tool to translate spiritual experiences into visual representations, creating tangible reminders and anchors for divine encounters.Encouragement and Relationship with AI:- Elizabeth concluded with an encouraging message, urging individuals not to fear AI. She suggested approaching AI with an open heart and engaging in a conversation with a higher power about its use. The simplicity of this approach was highlighted, viewing AI as a tool for creative exploration rather than a source of trepidation.LINKS:- Elizabeth's Group: https://www.ecclesiaofburningones.com/- DALL-e 2: https://openai.com/dall-e-2- Midjourney on Discord: https://discord.com/invite/midjourneyGet Bralynn's FREE Quantum Capacity Masterclass to learn the 3 Keys to Aligning and Expanding Your Inner Worldhttp://SpiritCenteredBusiness.com/qc-kickoff-replayBralynn's Declaration of Trade Course:https://bralynn.groovepages.com/declarationCopyright 2024 - Bralynn Newby Int'l, LLC. All rights reserved.

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Have you wondered how you can be sure that you are hearing GOD's Voice and not a different voice? Listen to this short Inspirational Christian sermon and be blessed. You can buy my new bestselling book, UNVEIL YOUR PURPOSE (a #1 Newly Released Bestseller on Amazon) here: India: https://www.amazon.in/UNVEIL-YOUR-PURPOSE-John-Giftah/dp/B08K2CJKP2/ref=sr_1_1?dchild=1&keywords=john+giftah&qid=1611990618&sr=8-1 Global Amazon.com: https://www.amazon.com/Unveil-Your-Purpose-Complete-Created-ebook/dp/B08L7XX9PJ/ref=sr_1_2?dchild=1&keywords=john+giftah%27&qid=1611990705&sr=8-2 You can stay in touch with me through these platforms: YouTube: https://www.youtube.com/johngiftah Instagram: https://www.instagram.com/johngiftah Facebook: https://www.facebook.com/sjohngiftah/ Website: https://www.johngiftah.com/ If you're blessed by this sermon, don't forget to share it with someone, and please do rate/ review the podcast so that it will help us reach more people with the message of hope. For supporting the ministry financially: PayPal: paypal.me/johngiftah Link to The Inspiration Hub Podcast: Apple Podcast: https://podcasts.apple.com/in/podcast/the-inspiration-hub/id1596599540 Link to Weekly Tamil Christian Messages Podcast (John Giftah) : Apple Podcast: https://podcasts.apple.com/in/podcast/tamil-christian-messages-john-giftah/id1596445581 Check out the "Fuel for the Soul with John Giftah" podcast (Among the Top Christian Podcasts in India Ranking #1 / #2 on multiple podcast platforms and among the Top Podcasts in the world (2021)) : Apple Podcasts: https://podcasts.apple.com/us/podcast/fuel-for-the-soul-with-john-giftah-inspirational/id1588234296 #JohnGiftah #JohnGiftahPodcast #Christian #Christianity #BibleStudy #Faith #Hope #InspirationalSermon #ChristianMotivation #ChristianInspiration #Motivation #Motivational #Inspirational #Bible #BibleStudy --- Send in a voice message: https://anchor.fm/john-giftah/message

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We're talking to Tommy and Miriam Evans of revivalmandate.org today, alongside our own Mercedes Sparks and her husband, Larry Sparks. We're going to be diving right into the supernatural! Miriam has had some premonition of things to come, a vision she received when her father passed away that she wants to share. We're discussing Roe V. Wade, Tommy and Miriam's new book (available at https://lancewallnau.com/decree), walking in the miraculous, the hour of awakening, and more!