Podcasts about Omniscience

“Why does God allow evil?” This question challenges many, and Christian philosophers have offered various responses. Additionally, the discussion touches on the nature of the spirit and its consciousness, the concept of apostolic succession and its documentation, and how to articulate the differences in understanding the Eucharist to those unfamiliar with it. Join the Catholic Answers Live Club Newsletter Invite our apologists to speak at your parish! Visit Catholicanswersspeakers.com Questions Covered: 01:30 – Atheists often argue that evil is evidence against God. If God were all-good, they argue, then no evil would exist. Christian philosophers have given a plethora of responses to this objection. But I was wondering how would Dr. Karlo respond. 15:21 – What is the spirit? What does the Church teach about this and does it teach whether the spirit is conscious? 21:23 – Apostolic succession. Which document shows this unbroken line of papal succession? How could you prove this to a protestant? 36:32 – I'm in RCIA. How do I explain the differences in understanding of the eucharist to someone who is not familiar with it? 47:20 – Regarding God's omniscience. Is there ever a point where God knows everything we will do before he creates us?

Our title today comprises two categories: 1st) The character of God & 2nd) Our posture in light of His glory. Because God sees all, because His presence is universal, we ought to fear him. This is a theme resurfacing throughout Proverbs chapter 15 like the base line melody of a movie score. Note verses 3 & 11 expounding the nature of God while verses 16 & 33 exhort us to respond accordingly.  Solomon advocates living in light of the omniscience God and Proverbs chapter 15 provides practical ways to do this. Wisdom realizes that the scope of human liberty, ability, virtue and understanding is delimited by an infinitely wise and sovereign God and the precepts outlining the fear of Him are found in His Word.

Happy New Year! You may have noticed that in 2025 we had moved toward YouTube as our primary podcasting platform. As we'll explain in the next State of Latent Space post, we'll be doubling down on Substack again and improving the experience for the over 100,000 of you who look out for our emails and website updates!We first mentioned Artificial Analysis in 2024, when it was still a side project in a Sydney basement. They then were one of the few Nat Friedman and Daniel Gross' AIGrant companies to raise a full seed round from them and have now become the independent gold standard for AI benchmarking—trusted by developers, enterprises, and every major lab to navigate the exploding landscape of models, providers, and capabilities.We have chatted with both Clementine Fourrier of HuggingFace's OpenLLM Leaderboard and (the freshly valued at $1.7B) Anastasios Angelopoulos of LMArena on their approaches to LLM evals and trendspotting, but Artificial Analysis have staked out an enduring and important place in the toolkit of the modern AI Engineer by doing the best job of independently running the most comprehensive set of evals across the widest range of open and closed models, and charting their progress for broad industry analyst use.George Cameron and Micah-Hill Smith have spent two years building Artificial Analysis into the platform that answers the questions no one else will: Which model is actually best for your use case? What are the real speed-cost trade-offs? And how open is “open” really?We discuss:* The origin story: built as a side project in 2023 while Micah was building a legal AI assistant, launched publicly in January 2024, and went viral after Swyx's retweet* Why they run evals themselves: labs prompt models differently, cherry-pick chain-of-thought examples (Google Gemini 1.0 Ultra used 32-shot prompts to beat GPT-4 on MMLU), and self-report inflated numbers* The mystery shopper policy: they register accounts not on their own domain and run intelligence + performance benchmarks incognito to prevent labs from serving different models on private endpoints* How they make money: enterprise benchmarking insights subscription (standardized reports on model deployment, serverless vs. managed vs. leasing chips) and private custom benchmarking for AI companies (no one pays to be on the public leaderboard)* The Intelligence Index (V3): synthesizes 10 eval datasets (MMLU, GPQA, agentic benchmarks, long-context reasoning) into a single score, with 95% confidence intervals via repeated runs* Omissions Index (hallucination rate): scores models from -100 to +100 (penalizing incorrect answers, rewarding ”I don't know”), and Claude models lead with the lowest hallucination rates despite not always being the smartest* GDP Val AA: their version of OpenAI's GDP-bench (44 white-collar tasks with spreadsheets, PDFs, PowerPoints), run through their Stirrup agent harness (up to 100 turns, code execution, web search, file system), graded by Gemini 3 Pro as an LLM judge (tested extensively, no self-preference bias)* The Openness Index: scores models 0-18 on transparency of pre-training data, post-training data, methodology, training code, and licensing (AI2 OLMo 2 leads, followed by Nous Hermes and NVIDIA Nemotron)* The smiling curve of AI costs: GPT-4-level intelligence is 100-1000x cheaper than at launch (thanks to smaller models like Amazon Nova), but frontier reasoning models in agentic workflows cost more than ever (sparsity, long context, multi-turn agents)* Why sparsity might go way lower than 5%: GPT-4.5 is ~5% active, Gemini models might be ~3%, and Omissions Index accuracy correlates with total parameters (not active), suggesting massive sparse models are the future* Token efficiency vs. turn efficiency: GPT-5 costs more per token but solves Tau-bench in fewer turns (cheaper overall), and models are getting better at using more tokens only when needed (5.1 Codex has tighter token distributions)* V4 of the Intelligence Index coming soon: adding GDP Val AA, Critical Point, hallucination rate, and dropping some saturated benchmarks (human-eval-style coding is now trivial for small models)Links to Artificial Analysis* Website: https://artificialanalysis.ai* George Cameron on X: https://x.com/georgecameron* Micah-Hill Smith on X: https://x.com/micahhsmithFull Episode on YouTubeTimestamps* 00:00 Introduction: Full Circle Moment and Artificial Analysis Origins* 01:19 Business Model: Independence and Revenue Streams* 04:33 Origin Story: From Legal AI to Benchmarking Need* 16:22 AI Grant and Moving to San Francisco* 19:21 Intelligence Index Evolution: From V1 to V3* 11:47 Benchmarking Challenges: Variance, Contamination, and Methodology* 13:52 Mystery Shopper Policy and Maintaining Independence* 28:01 New Benchmarks: Omissions Index for Hallucination Detection* 33:36 Critical Point: Hard Physics Problems and Research-Level Reasoning* 23:01 GDP Val AA: Agentic Benchmark for Real Work Tasks* 50:19 Stirrup Agent Harness: Open Source Agentic Framework* 52:43 Openness Index: Measuring Model Transparency Beyond Licenses* 58:25 The Smiling Curve: Cost Falling While Spend Rising* 1:02:32 Hardware Efficiency: Blackwell Gains and Sparsity Limits* 1:06:23 Reasoning Models and Token Efficiency: The Spectrum Emerges* 1:11:00 Multimodal Benchmarking: Image, Video, and Speech Arenas* 1:15:05 Looking Ahead: Intelligence Index V4 and Future Directions* 1:16:50 Closing: The Insatiable Demand for IntelligenceTranscriptMicah [00:00:06]: This is kind of a full circle moment for us in a way, because the first time artificial analysis got mentioned on a podcast was you and Alessio on Latent Space. Amazing.swyx [00:00:17]: Which was January 2024. I don't even remember doing that, but yeah, it was very influential to me. Yeah, I'm looking at AI News for Jan 17, or Jan 16, 2024. I said, this gem of a models and host comparison site was just launched. And then I put in a few screenshots, and I said, it's an independent third party. It clearly outlines the quality versus throughput trade-off, and it breaks out by model and hosting provider. I did give you s**t for missing fireworks, and how do you have a model benchmarking thing without fireworks? But you had together, you had perplexity, and I think we just started chatting there. Welcome, George and Micah, to Latent Space. I've been following your progress. Congrats on... It's been an amazing year. You guys have really come together to be the presumptive new gardener of AI, right? Which is something that...George [00:01:09]: Yeah, but you can't pay us for better results.swyx [00:01:12]: Yes, exactly.George [00:01:13]: Very important.Micah [00:01:14]: Start off with a spicy take.swyx [00:01:18]: Okay, how do I pay you?Micah [00:01:20]: Let's get right into that.swyx [00:01:21]: How do you make money?Micah [00:01:24]: Well, very happy to talk about that. So it's been a big journey the last couple of years. Artificial analysis is going to be two years old in January 2026. Which is pretty soon now. We first run the website for free, obviously, and give away a ton of data to help developers and companies navigate AI and make decisions about models, providers, technologies across the AI stack for building stuff. We're very committed to doing that and tend to keep doing that. We have, along the way, built a business that is working out pretty sustainably. We've got just over 20 people now and two main customer groups. So we want to be... We want to be who enterprise look to for data and insights on AI, so we want to help them with their decisions about models and technologies for building stuff. And then on the other side, we do private benchmarking for companies throughout the AI stack who build AI stuff. So no one pays to be on the website. We've been very clear about that from the very start because there's no use doing what we do unless it's independent AI benchmarking. Yeah. But turns out a bunch of our stuff can be pretty useful to companies building AI stuff.swyx [00:02:38]: And is it like, I am a Fortune 500, I need advisors on objective analysis, and I call you guys and you pull up a custom report for me, you come into my office and give me a workshop? What kind of engagement is that?George [00:02:53]: So we have a benchmarking and insight subscription, which looks like standardized reports that cover key topics or key challenges enterprises face when looking to understand AI and choose between all the technologies. And so, for instance, one of the report is a model deployment report, how to think about choosing between serverless inference, managed deployment solutions, or leasing chips. And running inference yourself is an example kind of decision that big enterprises face, and it's hard to reason through, like this AI stuff is really new to everybody. And so we try and help with our reports and insight subscription. Companies navigate that. We also do custom private benchmarking. And so that's very different from the public benchmarking that we publicize, and there's no commercial model around that. For private benchmarking, we'll at times create benchmarks, run benchmarks to specs that enterprises want. And we'll also do that sometimes for AI companies who have built things, and we help them understand what they've built with private benchmarking. Yeah. So that's a piece mainly that we've developed through trying to support everybody publicly with our public benchmarks. Yeah.swyx [00:04:09]: Let's talk about TechStack behind that. But okay, I'm going to rewind all the way to when you guys started this project. You were all the way in Sydney? Yeah. Well, Sydney, Australia for me.Micah [00:04:19]: George was an SF, but he's Australian, but he moved here already. Yeah.swyx [00:04:22]: And I remember I had the Zoom call with you. What was the impetus for starting artificial analysis in the first place? You know, you started with public benchmarks. And so let's start there. We'll go to the private benchmark. Yeah.George [00:04:33]: Why don't we even go back a little bit to like why we, you know, thought that it was needed? Yeah.Micah [00:04:40]: The story kind of begins like in 2022, 2023, like both George and I have been into AI stuff for quite a while. In 2023 specifically, I was trying to build a legal AI research assistant. So it actually worked pretty well for its era, I would say. Yeah. Yeah. So I was finding that the more you go into building something using LLMs, the more each bit of what you're doing ends up being a benchmarking problem. So had like this multistage algorithm thing, trying to figure out what the minimum viable model for each bit was, trying to optimize every bit of it as you build that out, right? Like you're trying to think about accuracy, a bunch of other metrics and performance and cost. And mostly just no one was doing anything to independently evaluate all the models. And certainly not to look at the trade-offs for speed and cost. So we basically set out just to build a thing that developers could look at to see the trade-offs between all of those things measured independently across all the models and providers. Honestly, it was probably meant to be a side project when we first started doing it.swyx [00:05:49]: Like we didn't like get together and say like, Hey, like we're going to stop working on all this stuff. I'm like, this is going to be our main thing. When I first called you, I think you hadn't decided on starting a company yet.Micah [00:05:58]: That's actually true. I don't even think we'd pause like, like George had an acquittance job. I didn't quit working on my legal AI thing. Like it was genuinely a side project.George [00:06:05]: We built it because we needed it as people building in the space and thought, Oh, other people might find it useful too. So we'll buy domain and link it to the Vercel deployment that we had and tweet about it. And, but very quickly it started getting attention. Thank you, Swyx for, I think doing an initial retweet and spotlighting it there. This project that we released. And then very quickly though, it was useful to others, but very quickly it became more useful as the number of models released accelerated. We had Mixtrel 8x7B and it was a key. That's a fun one. Yeah. Like a open source model that really changed the landscape and opened up people's eyes to other serverless inference providers and thinking about speed, thinking about cost. And so that was a key. And so it became more useful quite quickly. Yeah.swyx [00:07:02]: What I love talking to people like you who sit across the ecosystem is, well, I have theories about what people want, but you have data and that's obviously more relevant. But I want to stay on the origin story a little bit more. When you started out, I would say, I think the status quo at the time was every paper would come out and they would report their numbers versus competitor numbers. And that's basically it. And I remember I did the legwork. I think everyone has some knowledge. I think there's some version of Excel sheet or a Google sheet where you just like copy and paste the numbers from every paper and just post it up there. And then sometimes they don't line up because they're independently run. And so your numbers are going to look better than... Your reproductions of other people's numbers are going to look worse because you don't hold their models correctly or whatever the excuse is. I think then Stanford Helm, Percy Liang's project would also have some of these numbers. And I don't know if there's any other source that you can cite. The way that if I were to start artificial analysis at the same time you guys started, I would have used the Luther AI's eval framework harness. Yup.Micah [00:08:06]: Yup. That was some cool stuff. At the end of the day, running these evals, it's like if it's a simple Q&A eval, all you're doing is asking a list of questions and checking if the answers are right, which shouldn't be that crazy. But it turns out there are an enormous number of things that you've got control for. And I mean, back when we started the website. Yeah. Yeah. Like one of the reasons why we realized that we had to run the evals ourselves and couldn't just take rules from the labs was just that they would all prompt the models differently. And when you're competing over a few points, then you can pretty easily get- You can put the answer into the model. Yeah. That in the extreme. And like you get crazy cases like back when I'm Googled a Gemini 1.0 Ultra and needed a number that would say it was better than GPT-4 and like constructed, I think never published like chain of thought examples. 32 of them in every topic in MLU to run it, to get the score, like there are so many things that you- They never shipped Ultra, right? That's the one that never made it up. Not widely. Yeah. Yeah. Yeah. I mean, I'm sure it existed, but yeah. So we were pretty sure that we needed to run them ourselves and just run them in the same way across all the models. Yeah. And we were, we also did certain from the start that you couldn't look at those in isolation. You needed to look at them alongside the cost and performance stuff. Yeah.swyx [00:09:24]: Okay. A couple of technical questions. I mean, so obviously I also thought about this and I didn't do it because of cost. Yep. Did you not worry about costs? Were you funded already? Clearly not, but you know. No. Well, we definitely weren't at the start.Micah [00:09:36]: So like, I mean, we're paying for it personally at the start. There's a lot of money. Well, the numbers weren't nearly as bad a couple of years ago. So we certainly incurred some costs, but we were probably in the order of like hundreds of dollars of spend across all the benchmarking that we were doing. Yeah. So nothing. Yeah. It was like kind of fine. Yeah. Yeah. These days that's gone up an enormous amount for a bunch of reasons that we can talk about. But yeah, it wasn't that bad because you can also remember that like the number of models we were dealing with was hardly any and the complexity of the stuff that we wanted to do to evaluate them was a lot less. Like we were just asking some Q&A type questions and then one specific thing was for a lot of evals initially, we were just like sampling an answer. You know, like, what's the answer for this? Like, we didn't want to go into the answer directly without letting the models think. We weren't even doing chain of thought stuff initially. And that was the most useful way to get some results initially. Yeah.swyx [00:10:33]: And so for people who haven't done this work, literally parsing the responses is a whole thing, right? Like because sometimes the models, the models can answer any way they feel fit and sometimes they actually do have the right answer, but they just returned the wrong format and they will get a zero for that unless you work it into your parser. And that involves more work. And so, I mean, but there's an open question whether you should give it points for not following your instructions on the format.Micah [00:11:00]: It depends what you're looking at, right? Because you can, if you're trying to see whether or not it can solve a particular type of reasoning problem, and you don't want to test it on its ability to do answer formatting at the same time, then you might want to use an LLM as answer extractor approach to make sure that you get the answer out no matter how unanswered. But these days, it's mostly less of a problem. Like, if you instruct a model and give it examples of what the answers should look like, it can get the answers in your format, and then you can do, like, a simple regex.swyx [00:11:28]: Yeah, yeah. And then there's other questions around, I guess, sometimes if you have a multiple choice question, sometimes there's a bias towards the first answer, so you have to randomize the responses. All these nuances, like, once you dig into benchmarks, you're like, I don't know how anyone believes the numbers on all these things. It's so dark magic.Micah [00:11:47]: You've also got, like… You've got, like, the different degrees of variance in different benchmarks, right? Yeah. So, if you run four-question multi-choice on a modern reasoning model at the temperatures suggested by the labs for their own models, the variance that you can see on a four-question multi-choice eval is pretty enormous if you only do a single run of it and it has a small number of questions, especially. So, like, one of the things that we do is run an enormous number of all of our evals when we're developing new ones and doing upgrades to our intelligence index to bring in new things. Yeah. So, that we can dial in the right number of repeats so that we can get to the 95% confidence intervals that we're comfortable with so that when we pull that together, we can be confident in intelligence index to at least as tight as, like, a plus or minus one at a 95% confidence. Yeah.swyx [00:12:32]: And, again, that just adds a straight multiple to the cost. Oh, yeah. Yeah, yeah.George [00:12:37]: So, that's one of many reasons that cost has gone up a lot more than linearly over the last couple of years. We report a cost to run the artificial analysis. We report a cost to run the artificial analysis intelligence index on our website, and currently that's assuming one repeat in terms of how we report it because we want to reflect a bit about the weighting of the index. But our cost is actually a lot higher than what we report there because of the repeats.swyx [00:13:03]: Yeah, yeah, yeah. And probably this is true, but just checking, you don't have any special deals with the labs. They don't discount it. You just pay out of pocket or out of your sort of customer funds. Oh, there is a mix. So, the issue is that sometimes they may give you a special end point, which is… Ah, 100%.Micah [00:13:21]: Yeah, yeah, yeah. Exactly. So, we laser focus, like, on everything we do on having the best independent metrics and making sure that no one can manipulate them in any way. There are quite a lot of processes we've developed over the last couple of years to make that true for, like, the one you bring up, like, right here of the fact that if we're working with a lab, if they're giving us a private endpoint to evaluate a model, that it is totally possible. That what's sitting behind that black box is not the same as they serve on a public endpoint. We're very aware of that. We have what we call a mystery shopper policy. And so, and we're totally transparent with all the labs we work with about this, that we will register accounts not on our own domain and run both intelligence evals and performance benchmarks… Yeah, that's the job. …without them being able to identify it. And no one's ever had a problem with that. Because, like, a thing that turns out to actually be quite a good… …good factor in the industry is that they all want to believe that none of their competitors could manipulate what we're doing either.swyx [00:14:23]: That's true. I never thought about that. I've been in the database data industry prior, and there's a lot of shenanigans around benchmarking, right? So I'm just kind of going through the mental laundry list. Did I miss anything else in this category of shenanigans? Oh, potential shenanigans.Micah [00:14:36]: I mean, okay, the biggest one, like, that I'll bring up, like, is more of a conceptual one, actually, than, like, direct shenanigans. It's that the things that get measured become things that get targeted by labs that they're trying to build, right? Exactly. So that doesn't mean anything that we should really call shenanigans. Like, I'm not talking about training on test set. But if you know that you're going to be great at another particular thing, if you're a researcher, there are a whole bunch of things that you can do to try to get better at that thing that preferably are going to be helpful for a wide range of how actual users want to use the thing that you're building. But will not necessarily work. Will not necessarily do that. So, for instance, the models are exceptional now at answering competition maths problems. There is some relevance of that type of reasoning, that type of work, to, like, how we might use modern coding agents and stuff. But it's clearly not one for one. So the thing that we have to be aware of is that once an eval becomes the thing that everyone's looking at, scores can get better on it without there being a reflection of overall generalized intelligence of these models. Getting better. That has been true for the last couple of years. It'll be true for the next couple of years. There's no silver bullet to defeat that other than building new stuff to stay relevant and measure the capabilities that matter most to real users. Yeah.swyx [00:15:58]: And we'll cover some of the new stuff that you guys are building as well, which is cool. Like, you used to just run other people's evals, but now you're coming up with your own. And I think, obviously, that is a necessary path once you're at the frontier. You've exhausted all the existing evals. I think the next point in history that I have for you is AI Grant that you guys decided to join and move here. What was it like? I think you were in, like, batch two? Batch four. Batch four. Okay.Micah [00:16:26]: I mean, it was great. Nat and Daniel are obviously great. And it's a really cool group of companies that we were in AI Grant alongside. It was really great to get Nat and Daniel on board. Obviously, they've done a whole lot of great work in the space with a lot of leading companies and were extremely aligned. With the mission of what we were trying to do. Like, we're not quite typical of, like, a lot of the other AI startups that they've invested in.swyx [00:16:53]: And they were very much here for the mission of what we want to do. Did they say any advice that really affected you in some way or, like, were one of the events very impactful? That's an interesting question.Micah [00:17:03]: I mean, I remember fondly a bunch of the speakers who came and did fireside chats at AI Grant.swyx [00:17:09]: Which is also, like, a crazy list. Yeah.George [00:17:11]: Oh, totally. Yeah, yeah, yeah. There was something about, you know, speaking to Nat and Daniel about the challenges of working through a startup and just working through the questions that don't have, like, clear answers and how to work through those kind of methodically and just, like, work through the hard decisions. And they've been great mentors to us as we've built artificial analysis. Another benefit for us was that other companies in the batch and other companies in AI Grant are pushing the capabilities. Yeah. And I think that's a big part of what AI can do at this time. And so being in contact with them, making sure that artificial analysis is useful to them has been fantastic for supporting us in working out how should we build out artificial analysis to continue to being useful to those, like, you know, building on AI.swyx [00:17:59]: I think to some extent, I'm mixed opinion on that one because to some extent, your target audience is not people in AI Grants who are obviously at the frontier. Yeah. Do you disagree?Micah [00:18:09]: To some extent. To some extent. But then, so a lot of what the AI Grant companies are doing is taking capabilities coming out of the labs and trying to push the limits of what they can do across the entire stack for building great applications, which actually makes some of them pretty archetypical power users of artificial analysis. Some of the people with the strongest opinions about what we're doing well and what we're not doing well and what they want to see next from us. Yeah. Yeah. Because when you're building any kind of AI application now, chances are you're using a whole bunch of different models. You're maybe switching reasonably frequently for different models and different parts of your application to optimize what you're able to do with them at an accuracy level and to get better speed and cost characteristics. So for many of them, no, they're like not commercial customers of ours, like we don't charge for all our data on the website. Yeah. They are absolutely some of our power users.swyx [00:19:07]: So let's talk about just the evals as well. So you start out from the general like MMU and GPQA stuff. What's next? How do you sort of build up to the overall index? What was in V1 and how did you evolve it? Okay.Micah [00:19:22]: So first, just like background, like we're talking about the artificial analysis intelligence index, which is our synthesis metric that we pulled together currently from 10 different eval data sets to give what? We're pretty much the same as that. Pretty confident is the best single number to look at for how smart the models are. Obviously, it doesn't tell the whole story. That's why we published the whole website of all the charts to dive into every part of it and look at the trade-offs. But best single number. So right now, it's got a bunch of Q&A type data sets that have been very important to the industry, like a couple that you just mentioned. It's also got a couple of agentic data sets. It's got our own long context reasoning data set and some other use case focused stuff. As time goes on. The things that we're most interested in that are going to be important to the capabilities that are becoming more important for AI, what developers are caring about, are going to be first around agentic capabilities. So surprise, surprise. We're all loving our coding agents and how the model is going to perform like that and then do similar things for different types of work are really important to us. The linking to use cases to economically valuable use cases are extremely important to us. And then we've got some of the. Yeah. These things that the models still struggle with, like working really well over long contexts that are not going to go away as specific capabilities and use cases that we need to keep evaluating.swyx [00:20:46]: But I guess one thing I was driving was like the V1 versus the V2 and how bad it was over time.Micah [00:20:53]: Like how we've changed the index to where we are.swyx [00:20:55]: And I think that reflects on the change in the industry. Right. So that's a nice way to tell that story.Micah [00:21:00]: Well, V1 would be completely saturated right now. Almost every model coming out because doing things like writing the Python functions and human evil is now pretty trivial. It's easy to forget, actually, I think how much progress has been made in the last two years. Like we obviously play the game constantly of like the today's version versus last week's version and the week before and all of the small changes in the horse race between the current frontier and who has the best like smaller than 10B model like right now this week. Right. And that's very important to a lot of developers and people and especially in this particular city of San Francisco. But when you zoom out a couple of years ago, literally most of what we were doing to evaluate the models then would all be 100% solved by even pretty small models today. And that's been one of the key things, by the way, that's driven down the cost of intelligence at every tier of intelligence. We can talk about more in a bit. So V1, V2, V3, we made things harder. We covered a wider range of use cases. And we tried to get closer to things developers care about as opposed to like just the Q&A type stuff that MMLU and GPQA represented. Yeah.swyx [00:22:12]: I don't know if you have anything to add there. Or we could just go right into showing people the benchmark and like looking around and asking questions about it. Yeah.Micah [00:22:21]: Let's do it. Okay. This would be a pretty good way to chat about a few of the new things we've launched recently. Yeah.George [00:22:26]: And I think a little bit about the direction that we want to take it. And we want to push benchmarks. Currently, the intelligence index and evals focus a lot on kind of raw intelligence. But we kind of want to diversify how we think about intelligence. And we can talk about it. But kind of new evals that we've kind of built and partnered on focus on topics like hallucination. And we've got a lot of topics that I think are not covered by the current eval set that should be. And so we want to bring that forth. But before we get into that.swyx [00:23:01]: And so for listeners, just as a timestamp, right now, number one is Gemini 3 Pro High. Then followed by Cloud Opus at 70. Just 5.1 high. You don't have 5.2 yet. And Kimi K2 Thinking. Wow. Still hanging in there. So those are the top four. That will date this podcast quickly. Yeah. Yeah. I mean, I love it. I love it. No, no. 100%. Look back this time next year and go, how cute. Yep.George [00:23:25]: Totally. A quick view of that is, okay, there's a lot. I love it. I love this chart. Yeah.Micah [00:23:30]: This is such a favorite, right? Yeah. And almost every talk that George or I give at conferences and stuff, we always put this one up first to just talk about situating where we are in this moment in history. This, I think, is the visual version of what I was saying before about the zooming out and remembering how much progress there's been. If we go back to just over a year ago, before 01, before Cloud Sonnet 3.5, we didn't have reasoning models or coding agents as a thing. And the game was very, very different. If we go back even a little bit before then, we're in the era where, when you look at this chart, open AI was untouchable for well over a year. And, I mean, you would remember that time period well of there being very open questions about whether or not AI was going to be competitive, like full stop, whether or not open AI would just run away with it, whether we would have a few frontier labs and no one else would really be able to do anything other than consume their APIs. I am quite happy overall that the world that we have ended up in is one where... Multi-model. Absolutely. And strictly more competitive every quarter over the last few years. Yeah. This year has been insane. Yeah.George [00:24:42]: You can see it. This chart with everything added is hard to read currently. There's so many dots on it, but I think it reflects a little bit what we felt, like how crazy it's been.swyx [00:24:54]: Why 14 as the default? Is that a manual choice? Because you've got service now in there that are less traditional names. Yeah.George [00:25:01]: It's models that we're kind of highlighting by default in our charts, in our intelligence index. Okay.swyx [00:25:07]: You just have a manually curated list of stuff.George [00:25:10]: Yeah, that's right. But something that I actually don't think every artificial analysis user knows is that you can customize our charts and choose what models are highlighted. Yeah. And so if we take off a few names, it gets a little easier to read.swyx [00:25:25]: Yeah, yeah. A little easier to read. Totally. Yeah. But I love that you can see the all one jump. Look at that. September 2024. And the DeepSeek jump. Yeah.George [00:25:34]: Which got close to OpenAI's leadership. They were so close. I think, yeah, we remember that moment. Around this time last year, actually.Micah [00:25:44]: Yeah, yeah, yeah. I agree. Yeah, well, a couple of weeks. It was Boxing Day in New Zealand when DeepSeek v3 came out. And we'd been tracking DeepSeek and a bunch of the other global players that were less known over the second half of 2024 and had run evals on the earlier ones and stuff. I very distinctly remember Boxing Day in New Zealand, because I was with family for Christmas and stuff, running the evals and getting back result by result on DeepSeek v3. So this was the first of their v3 architecture, the 671b MOE.Micah [00:26:19]: And we were very, very impressed. That was the moment where we were sure that DeepSeek was no longer just one of many players, but had jumped up to be a thing. The world really noticed when they followed that up with the RL working on top of v3 and R1 succeeding a few weeks later. But the groundwork for that absolutely was laid with just extremely strong base model, completely open weights that we had as the best open weights model. So, yeah, that's the thing that you really see in the game. But I think that we got a lot of good feedback on Boxing Day. us on Boxing Day last year.George [00:26:48]: Boxing Day is the day after Christmas for those not familiar.George [00:26:54]: I'm from Singapore.swyx [00:26:55]: A lot of us remember Boxing Day for a different reason, for the tsunami that happened. Oh, of course. Yeah, but that was a long time ago. So yeah. So this is the rough pitch of AAQI. Is it A-A-Q-I or A-A-I-I? I-I. Okay. Good memory, though.Micah [00:27:11]: I don't know. I'm not used to it. Once upon a time, we did call it Quality Index, and we would talk about quality, performance, and price, but we changed it to intelligence.George [00:27:20]: There's been a few naming changes. We added hardware benchmarking to the site, and so benchmarks at a kind of system level. And so then we changed our throughput metric to, we now call it output speed, and thenswyx [00:27:32]: throughput makes sense at a system level, so we took that name. Take me through more charts. What should people know? Obviously, the way you look at the site is probably different than how a beginner might look at it.Micah [00:27:42]: Yeah, that's fair. There's a lot of fun stuff to dive into. Maybe so we can hit past all the, like, we have lots and lots of emails and stuff. The interesting ones to talk about today that would be great to bring up are a few of our recent things, I think, that probably not many people will be familiar with yet. So first one of those is our omniscience index. So this one is a little bit different to most of the intelligence evils that we've run. We built it specifically to look at the embedded knowledge in the models and to test hallucination by looking at when the model doesn't know the answer, so not able to get it correct, what's its probability of saying, I don't know, or giving an incorrect answer. So the metric that we use for omniscience goes from negative 100 to positive 100. Because we're simply taking off a point if you give an incorrect answer to the question. We're pretty convinced that this is an example of where it makes most sense to do that, because it's strictly more helpful to say, I don't know, instead of giving a wrong answer to factual knowledge question. And one of our goals is to shift the incentive that evils create for models and the labs creating them to get higher scores. And almost every evil across all of AI up until this point, it's been graded by simple percentage correct as the main metric, the main thing that gets hyped. And so you should take a shot at everything. There's no incentive to say, I don't know. So we did that for this one here.swyx [00:29:22]: I think there's a general field of calibration as well, like the confidence in your answer versus the rightness of the answer. Yeah, we completely agree. Yeah. Yeah.George [00:29:31]: On that. And one reason that we didn't do that is because. Or put that into this index is that we think that the, the way to do that is not to ask the models how confident they are.swyx [00:29:43]: I don't know. Maybe it might be though. You put it like a JSON field, say, say confidence and maybe it spits out something. Yeah. You know, we have done a few evils podcasts over the, over the years. And when we did one with Clementine of hugging face, who maintains the open source leaderboard, and this was one of her top requests, which is some kind of hallucination slash lack of confidence calibration thing. And so, Hey, this is one of them.Micah [00:30:05]: And I mean, like anything that we do, it's not a perfect metric or the whole story of everything that you think about as hallucination. But yeah, it's pretty useful and has some interesting results. Like one of the things that we saw in the hallucination rate is that anthropics Claude models at the, the, the very left-hand side here with the lowest hallucination rates out of the models that we've evaluated amnesty is on. That is an interesting fact. I think it probably correlates with a lot of the previously, not really measured vibes stuff that people like about some of the Claude models. Is the dataset public or what's is it, is there a held out set? There's a hell of a set for this one. So we, we have published a public test set, but we we've only published 10% of it. The reason is that for this one here specifically, it would be very, very easy to like have data contamination because it is just factual knowledge questions. We would. We'll update it at a time to also prevent that, but with yeah, kept most of it held out so that we can keep it reliable for a long time. It leads us to a bunch of really cool things, including breakdown quite granularly by topic. And so we've got some of that disclosed on the website publicly right now, and there's lots more coming in terms of our ability to break out very specific topics. Yeah.swyx [00:31:23]: I would be interested. Let's, let's dwell a little bit on this hallucination one. I noticed that Haiku hallucinates less than Sonnet hallucinates less than Opus. And yeah. Would that be the other way around in a normal capability environments? I don't know. What's, what do you make of that?George [00:31:37]: One interesting aspect is that we've found that there's not really a, not a strong correlation between intelligence and hallucination, right? That's to say that the smarter the models are in a general sense, isn't correlated with their ability to, when they don't know something, say that they don't know. It's interesting that Gemini three pro preview was a big leap over here. Gemini 2.5. Flash and, and, and 2.5 pro, but, and if I add pro quickly here.swyx [00:32:07]: I bet pro's really good. Uh, actually no, I meant, I meant, uh, the GPT pros.George [00:32:12]: Oh yeah.swyx [00:32:13]: Cause GPT pros are rumored. We don't know for a fact that it's like eight runs and then with the LM judge on top. Yeah.George [00:32:20]: So we saw a big jump in, this is accuracy. So this is just percent that they get, uh, correct and Gemini three pro knew a lot more than the other models. And so big jump in accuracy. But relatively no change between the Google Gemini models, between releases. And the hallucination rate. Exactly. And so it's likely due to just kind of different post-training recipe, between the, the Claude models. Yeah.Micah [00:32:45]: Um, there's, there's driven this. Yeah. You can, uh, you can partially blame us and how we define intelligence having until now not defined hallucination as a negative in the way that we think about intelligence.swyx [00:32:56]: And so that's what we're changing. Uh, I know many smart people who are confidently incorrect.George [00:33:02]: Uh, look, look at that. That, that, that is very humans. Very true. And there's times and a place for that. I think our view is that hallucination rate makes sense in this context where it's around knowledge, but in many cases, people want the models to hallucinate, to have a go. Often that's the case in coding or when you're trying to generate newer ideas. One eval that we added to artificial analysis is, is, is critical point and it's really hard, uh, physics problems. Okay.swyx [00:33:32]: And is it sort of like a human eval type or something different or like a frontier math type?George [00:33:37]: It's not dissimilar to frontier frontier math. So these are kind of research questions that kind of academics in the physics physics world would be able to answer, but models really struggled to answer. So the top score here is not 9%.swyx [00:33:51]: And when the people that, that created this like Minway and, and, and actually off via who was kind of behind sweep and what organization is this? Oh, is this, it's Princeton.George [00:34:01]: Kind of range of academics from, from, uh, different academic institutions, really smart people. They talked about how they turn the models up in terms of the temperature as high temperature as they can, where they're trying to explore kind of new ideas in physics as a, as a thought partner, just because they, they want the models to hallucinate. Um, yeah, sometimes it's something new. Yeah, exactly.swyx [00:34:21]: Um, so not right in every situation, but, um, I think it makes sense, you know, to test hallucination in scenarios where it makes sense. Also, the obvious question is, uh, this is one of. Many that there is there, every lab has a system card that shows some kind of hallucination number, and you've chosen to not, uh, endorse that and you've made your own. And I think that's a, that's a choice. Um, totally in some sense, the rest of artificial analysis is public benchmarks that other people can independently rerun. You provide it as a service here. You have to fight the, well, who are we to, to like do this? And your, your answer is that we have a lot of customers and, you know, but like, I guess, how do you converge the individual?Micah [00:35:08]: I mean, I think, I think for hallucinations specifically, there are a bunch of different things that you might care about reasonably, and that you'd measure quite differently, like we've called this a amnesty and solutionation rate, not trying to declare the, like, it's humanity's last hallucination. You could, uh, you could have some interesting naming conventions and all this stuff. Um, the biggest picture answer to that. It's something that I actually wanted to mention. Just as George was explaining, critical point as well is, so as we go forward, we are building evals internally. We're partnering with academia and partnering with AI companies to build great evals. We have pretty strong views on, in various ways for different parts of the AI stack, where there are things that are not being measured well, or things that developers care about that should be measured more and better. And we intend to be doing that. We're not obsessed necessarily with that. Everything we do, we have to do entirely within our own team. Critical point. As a cool example of where we were a launch partner for it, working with academia, we've got some partnerships coming up with a couple of leading companies. Those ones, obviously we have to be careful with on some of the independent stuff, but with the right disclosure, like we're completely comfortable with that. A lot of the labs have released great data sets in the past that we've used to great success independently. And so it's between all of those techniques, we're going to be releasing more stuff in the future. Cool.swyx [00:36:26]: Let's cover the last couple. And then we'll, I want to talk about your trends analysis stuff, you know? Totally.Micah [00:36:31]: So that actually, I have one like little factoid on omniscience. If you go back up to accuracy on omniscience, an interesting thing about this accuracy metric is that it tracks more closely than anything else that we measure. The total parameter count of models makes a lot of sense intuitively, right? Because this is a knowledge eval. This is the pure knowledge metric. We're not looking at the index and the hallucination rate stuff that we think is much more about how the models are trained. This is just what facts did they recall? And yeah, it tracks parameter count extremely closely. Okay.swyx [00:37:05]: What's the rumored size of GPT-3 Pro? And to be clear, not confirmed for any official source, just rumors. But rumors do fly around. Rumors. I get, I hear all sorts of numbers. I don't know what to trust.Micah [00:37:17]: So if you, if you draw the line on omniscience accuracy versus total parameters, we've got all the open ways models, you can squint and see that likely the leading frontier models right now are quite a lot bigger than the ones that we're seeing right now. And the one trillion parameters that the open weights models cap out at, and the ones that we're looking at here, there's an interesting extra data point that Elon Musk revealed recently about XAI that for three trillion parameters for GROK 3 and 4, 6 trillion for GROK 5, but that's not out yet. Take those together, have a look. You might reasonably form a view that there's a pretty good chance that Gemini 3 Pro is bigger than that, that it could be in the 5 to 10 trillion parameters. To be clear, I have absolutely no idea, but just based on this chart, like that's where you would, you would land if you have a look at it. Yeah.swyx [00:38:07]: And to some extent, I actually kind of discourage people from guessing too much because what does it really matter? Like as long as they can serve it as a sustainable cost, that's about it. Like, yeah, totally.George [00:38:17]: They've also got different incentives in play compared to like open weights models who are thinking to supporting others in self-deployment for the labs who are doing inference at scale. It's I think less about total parameters in many cases. When thinking about inference costs and more around number of active parameters. And so there's a bit of an incentive towards larger sparser models. Agreed.Micah [00:38:38]: Understood. Yeah. Great. I mean, obviously if you're a developer or company using these things, not exactly as you say, it doesn't matter. You should be looking at all the different ways that we measure intelligence. You should be looking at cost to run index number and the different ways of thinking about token efficiency and cost efficiency based on the list prices, because that's all it matters.swyx [00:38:56]: It's not as good for the content creator rumor mill where I can say. Oh, GPT-4 is this small circle. Look at GPT-5 is this big circle. And then there used to be a thing for a while. Yeah.Micah [00:39:07]: But that is like on its own, actually a very interesting one, right? That is it just purely that chances are the last couple of years haven't seen a dramatic scaling up in the total size of these models. And so there's a lot of room to go up properly in total size of the models, especially with the upcoming hardware generations. Yes.swyx [00:39:29]: So, you know. Taking off my shitposting face for a minute. Yes. Yes. At the same time, I do feel like, you know, especially coming back from Europe, people do feel like Ilya is probably right that the paradigm is doesn't have many more orders of magnitude to scale out more. And therefore we need to start exploring at least a different path. GDPVal, I think it's like only like a month or so old. I was also very positive when it first came out. I actually talked to Tejo, who was the lead researcher on that. Oh, cool. And you have your own version.George [00:39:59]: It's a fantastic. It's a fantastic data set. Yeah.swyx [00:40:01]: And maybe it will recap for people who are still out of it. It's like 44 tasks based on some kind of GDP cutoff that's like meant to represent broad white collar work that is not just coding. Yeah.Micah [00:40:12]: Each of the tasks have a whole bunch of detailed instructions, some input files for a lot of them. It's within the 44 is divided into like two hundred and twenty two to five, maybe subtasks that are the level of that we run through the agenda. And yeah, they're really interesting. I will say that it doesn't. It doesn't necessarily capture like all the stuff that people do at work. No avail is perfect is always going to be more things to look at, largely because in order to make the tasks well enough to find that you can run them, they need to only have a handful of input files and very specific instructions for that task. And so I think the easiest way to think about them are that they're like quite hard take home exam tasks that you might do in an interview process.swyx [00:40:56]: Yeah, for listeners, it is not no longer like a long prompt. It is like, well, here's a zip file with like a spreadsheet or a PowerPoint deck or a PDF and go nuts and answer this question.George [00:41:06]: OpenAI released a great data set and they released a good paper which looks at performance across the different web chat bots on the data set. It's a great paper, encourage people to read it. What we've done is taken that data set and turned it into an eval that can be run on any model. So we created a reference agentic harness that can run. Run the models on the data set, and then we developed evaluator approach to compare outputs. That's kind of AI enabled, so it uses Gemini 3 Pro Preview to compare results, which we tested pretty comprehensively to ensure that it's aligned to human preferences. One data point there is that even as an evaluator, Gemini 3 Pro, interestingly, doesn't do actually that well. So that's kind of a good example of what we've done in GDPVal AA.swyx [00:42:01]: Yeah, the thing that you have to watch out for with LLM judge is self-preference that models usually prefer their own output, and in this case, it was not. Totally.Micah [00:42:08]: I think the way that we're thinking about the places where it makes sense to use an LLM as judge approach now, like quite different to some of the early LLM as judge stuff a couple of years ago, because some of that and MTV was a great project that was a good example of some of this a while ago was about judging conversations and like a lot of style type stuff. Here, we've got the task that the grader and grading model is doing is quite different to the task of taking the test. When you're taking the test, you've got all of the agentic tools you're working with, the code interpreter and web search, the file system to go through many, many turns to try to create the documents. Then on the other side, when we're grading it, we're running it through a pipeline to extract visual and text versions of the files and be able to provide that to Gemini, and we're providing the criteria for the task and getting it to pick which one more effectively meets the criteria of the task. Yeah. So we've got the task out of two potential outcomes. It turns out that we proved that it's just very, very good at getting that right, matched with human preference a lot of the time, because I think it's got the raw intelligence, but it's combined with the correct representation of the outputs, the fact that the outputs were created with an agentic task that is quite different to the way the grading model works, and we're comparing it against criteria, not just kind of zero shot trying to ask the model to pick which one is better.swyx [00:43:26]: Got it. Why is this an ELO? And not a percentage, like GDP-VAL?George [00:43:31]: So the outputs look like documents, and there's video outputs or audio outputs from some of the tasks. It has to make a video? Yeah, for some of the tasks. Some of the tasks.swyx [00:43:43]: What task is that?George [00:43:45]: I mean, it's in the data set. Like be a YouTuber? It's a marketing video.Micah [00:43:49]: Oh, wow. What? Like model has to go find clips on the internet and try to put it together. The models are not that good at doing that one, for now, to be clear. It's pretty hard to do that with a code editor. I mean, the computer stuff doesn't work quite well enough and so on and so on, but yeah.George [00:44:02]: And so there's no kind of ground truth, necessarily, to compare against, to work out percentage correct. It's hard to come up with correct or incorrect there. And so it's on a relative basis. And so we use an ELO approach to compare outputs from each of the models between the task.swyx [00:44:23]: You know what you should do? You should pay a contractor, a human, to do the same task. And then give it an ELO and then so you have, you have human there. It's just, I think what's helpful about GDPVal, the OpenAI one, is that 50% is meant to be normal human and maybe Domain Expert is higher than that, but 50% was the bar for like, well, if you've crossed 50, you are superhuman. Yeah.Micah [00:44:47]: So we like, haven't grounded this score in that exactly. I agree that it can be helpful, but we wanted to generalize this to a very large number. It's one of the reasons that presenting it as ELO is quite helpful and allows us to add models and it'll stay relevant for quite a long time. I also think it, it can be tricky looking at these exact tasks compared to the human performance, because the way that you would go about it as a human is quite different to how the models would go about it. Yeah.swyx [00:45:15]: I also liked that you included Lama 4 Maverick in there. Is that like just one last, like...Micah [00:45:20]: Well, no, no, no, no, no, no, it is the, it is the best model released by Meta. And... So it makes it into the homepage default set, still for now.George [00:45:31]: Other inclusion that's quite interesting is we also ran it across the latest versions of the web chatbots. And so we have...swyx [00:45:39]: Oh, that's right.George [00:45:40]: Oh, sorry.swyx [00:45:41]: I, yeah, I completely missed that. Okay.George [00:45:43]: No, not at all. So that, which has a checkered pattern. So that is their harness, not yours, is what you're saying. Exactly. And what's really interesting is that if you compare, for instance, Claude 4.5 Opus using the Claude web chatbot, it performs worse than the model in our agentic harness. And so in every case, the model performs better in our agentic harness than its web chatbot counterpart, the harness that they created.swyx [00:46:13]: Oh, my backwards explanation for that would be that, well, it's meant for consumer use cases and here you're pushing it for something.Micah [00:46:19]: The constraints are different and the amount of freedom that you can give the model is different. Also, you like have a cost goal. We let the models work as long as they want, basically. Yeah. Do you copy paste manually into the chatbot? Yeah. Yeah. That's, that was how we got the chatbot reference. We're not going to be keeping those updated at like quite the same scale as hundreds of models.swyx [00:46:38]: Well, so I don't know, talk to a browser base. They'll, they'll automate it for you. You know, like I have thought about like, well, we should turn these chatbot versions into an API because they are legitimately different agents in themselves. Yes. Right. Yeah.Micah [00:46:53]: And that's grown a huge amount of the last year, right? Like the tools. The tools that are available have actually diverged in my opinion, a fair bit across the major chatbot apps and the amount of data sources that you can connect them to have gone up a lot, meaning that your experience and the way you're using the model is more different than ever.swyx [00:47:10]: What tools and what data connections come to mind when you say what's interesting, what's notable work that people have done?Micah [00:47:15]: Oh, okay. So my favorite example on this is that until very recently, I would argue that it was basically impossible to get an LLM to draft an email for me in any useful way. Because most times that you're sending an email, you're not just writing something for the sake of writing it. Chances are context required is a whole bunch of historical emails. Maybe it's notes that you've made, maybe it's meeting notes, maybe it's, um, pulling something from your, um, any of like wherever you at work store stuff. So for me, like Google drive, one drive, um, in our super base databases, if we need to do some analysis or some data or something, preferably model can be plugged into all of those things and can go do some useful work based on it. The things that like I find most impressive currently that I am somewhat surprised work really well in late 2025, uh, that I can have models use super base MCP to query read only, of course, run a whole bunch of SQL queries to do pretty significant data analysis. And. And make charts and stuff and can read my Gmail and my notion. And okay. You actually use that. That's good. That's, that's, that's good. Is that a cloud thing? To various degrees of order, but chat GPD and Claude right now, I would say that this stuff like barely works in fairness right now. Like.George [00:48:33]: Because people are actually going to try this after they hear it. If you get an email from Micah, odds are it wasn't written by a chatbot.Micah [00:48:38]: So, yeah, I think it is true that I have never actually sent anyone an email drafted by a chatbot. Yet.swyx [00:48:46]: Um, and so you can, you can feel it right. And yeah, this time, this time next year, we'll come back and see where it's going. Totally. Um, super base shout out another famous Kiwi. Uh, I don't know if you've, you've any conversations with him about anything in particular on AI building and AI infra.George [00:49:03]: We have had, uh, Twitter DMS, um, with, with him because we're quite big, uh, super base users and power users. And we probably do some things more manually than we should in. In, in super base support line because you're, you're a little bit being super friendly. One extra, um, point regarding, um, GDP Val AA is that on the basis of the overperformance of the models compared to the chatbots turns out, we realized that, oh, like our reference harness that we built actually white works quite well on like gen generalist agentic tasks. This proves it in a sense. And so the agent harness is very. Minimalist. I think it follows some of the ideas that are in Claude code and we, all that we give it is context management capabilities, a web search, web browsing, uh, tool, uh, code execution, uh, environment. Anything else?Micah [00:50:02]: I mean, we can equip it with more tools, but like by default, yeah, that's it. We, we, we give it for GDP, a tool to, uh, view an image specifically, um, because the models, you know, can just use a terminal to pull stuff in text form into context. But to pull visual stuff into context, we had to give them a custom tool, but yeah, exactly. Um, you, you can explain an expert. No.George [00:50:21]: So it's, it, we turned out that we created a good generalist agentic harness. And so we, um, released that on, on GitHub yesterday. It's called stirrup. So if people want to check it out and, and it's a great, um, you know, base for, you know, generalist, uh, building a generalist agent for more specific tasks.Micah [00:50:39]: I'd say the best way to use it is get clone and then have your favorite coding. Agent make changes to it, to do whatever you want, because it's not that many lines of code and the coding agents can work with it. Super well.swyx [00:50:51]: Well, that's nice for the community to explore and share and hack on it. I think maybe in, in, in other similar environments, the terminal bench guys have done, uh, sort of the Harbor. Uh, and so it's, it's a, it's a bundle of, well, we need our minimal harness, which for them is terminus and we also need the RL environments or Docker deployment thing to, to run independently. So I don't know if you've looked at it. I don't know if you've looked at the harbor at all, is that, is that like a, a standard that people want to adopt?George [00:51:19]: Yeah, we've looked at it from a evals perspective and we love terminal bench and, and host benchmarks of, of, of terminal mention on artificial analysis. Um, we've looked at it from a, from a coding agent perspective, but could see it being a great, um, basis for any kind of agents. I think where we're getting to is that these models have gotten smart enough. They've gotten better, better tools that they can perform better when just given a minimalist. Set of tools and, and let them run, let the model control the, the agentic workflow rather than using another framework that's a bit more built out that tries to dictate the, dictate the flow. Awesome.swyx [00:51:56]: Let's cover the openness index and then let's go into the report stuff. Uh, so that's the, that's the last of the proprietary art numbers, I guess. I don't know how you sort of classify all these. Yeah.Micah [00:52:07]: Or call it, call it, let's call it the last of like the, the three new things that we're talking about from like the last few weeks. Um, cause I mean, there's a, we do a mix of stuff that. Where we're using open source, where we open source and what we do and, um, proprietary stuff that we don't always open source, like long context reasoning data set last year, we did open source. Um, and then all of the work on performance benchmarks across the site, some of them, we looking to open source, but some of them, like we're constantly iterating on and so on and so on and so on. So there's a huge mix, I would say, just of like stuff that is open source and not across the side. So that's a LCR for people. Yeah, yeah, yeah, yeah.swyx [00:52:41]: Uh, but let's, let's, let's talk about open.Micah [00:52:42]: Let's talk about openness index. This. Here is call it like a new way to think about how open models are. We, for a long time, have tracked where the models are open weights and what the licenses on them are. And that's like pretty useful. That tells you what you're allowed to do with the weights of a model, but there is this whole other dimension to how open models are. That is pretty important that we haven't tracked until now. And that's how much is disclosed about how it was made. So transparency about data, pre-training data and post-training data. And whether you're allowed to use that data and transparency about methodology and training code. So basically, those are the components. We bring them together to score an openness index for models so that you can in one place get this full picture of how open models are.swyx [00:53:32]: I feel like I've seen a couple other people try to do this, but they're not maintained. I do think this does matter. I don't know what the numbers mean apart from is there a max number? Is this out of 20?George [00:53:44]: It's out of 18 currently, and so we've got an openness index page, but essentially these are points, you get points for being more open across these different categories and the maximum you can achieve is 18. So AI2 with their extremely open OMO3 32B think model is the leader in a sense.swyx [00:54:04]: It's hooking face.George [00:54:05]: Oh, with their smaller model. It's coming soon. I think we need to run, we need to get the intelligence benchmarks right to get it on the site.swyx [00:54:12]: You can't have it open in the next. We can not include hooking face. We love hooking face. We'll have that, we'll have that up very soon. I mean, you know, the refined web and all that stuff. It's, it's amazing. Or is it called fine web? Fine web. Fine web.Micah [00:54:23]: Yeah, yeah, no, totally. Yep. One of the reasons this is cool, right, is that if you're trying to understand the holistic picture of the models and what you can do with all the stuff the company's contributing, this gives you that picture. And so we are going to keep it up to date alongside all the models that we do intelligence index on, on the site. And it's just an extra view to understand.swyx [00:54:43]: Can you scroll down to this? The, the, the, the trade-offs chart. Yeah, yeah. That one. Yeah. This, this really matters, right? Obviously, because you can b

In this powerful message from Pastor Karl, we journey beyond the manger to discover the timeless roots of Christmas in the Garden of Eden. Christmas is far more than a seasonal vibe—it's the profound story of God's unchanging love, revealed through proximity, provision, and loving parameters.Drawing parallels between Eden and Bethlehem, Pastor Karl shows how God has always pursued us: walking closely with humanity, generously providing what we cannot obtain ourselves, and setting protective boundaries for our good. Yet, from the beginning, humanity has often rejected this love, doubting God's goodness and choosing our own way.The heart of the gospel shines through as Pastor Karl reminds us that even in our rejection, God's love pursues and covers us—first promised in Genesis with the crushing of the serpent's head through the seed of the woman, and perfectly fulfilled in the incarnation of Jesus, Emmanuel, "God with us."This message challenges us: Will we embrace not just the warmth of Christmas, but the weighty claims of Christmas—God's call to love Him fully with our whole heart, soul, mind, and strength through belonging to His family, becoming like Christ, giving generously, and going on mission?A stirring reminder that God's everlasting love didn't begin in Bethlehem—it was set in motion from the very beginning, for you and me.Watch all our sermons on our youtube channel "Flipside Christian Church"Join us in person 8:00am 9:30am & 11:00am every Sunday morning.37193 Ave 12 #3h, Madera, CA 93636For more visit us at flipside.churchFor more podcasts visit flipsidepodcasts.transistor.fm

Contact Welcomed HereResponsibility is the ability to respond - responsibly. Accountablity is the ability to count. Accounting done correctly adds up. Feeling like you don't count is the natural byproduct of thoughts that don't add up since they have no substantive basis. ALL Reality has substance. While substance is largely invisible it is also indivisible - which means it has no parts or pieces to separate or divide so cannot be in conflict. To think we can be separate from It is to think divisively about it and feel disconnected and alone is the natural byproduct of feeling unsubstantive thoughts. Essence is essential and not optional.  Indivisbility cannot be added to, reduced or fractured. IT IS Perfect Peace Silent and Still Presence. We now this or could not notice conflicts or disturbances. Splitting thougths into fractional concepts with a denominator of zero means no numerator can not be big enought to amount to anyting. When enough is never enough the mental impossbility of turning thoughts into reality has been induced. We do not struggle with Reality, Truth or LIfe. Our mentality struggles with how and what we think of them - along with the imagined self we can think we've become. Addiction is not impossible - but to continue the same thinking while wishfully hoping more insanity will resolve the problem only addes fuel to the fire of more obsessive thinking imagining nothing else can ever be done. If we didn't know better there would be nothing we could do.  We Know We Know. We Are Aware We Are Aware. We Are as We Are. Reality is unlimited and never changes. The idea that how and what we think creates reality suggests otherwise. Acting on backward thoughts leads to behaviors that are out of order reflecting a reversal of our natural fortune that are accurately called disorders. Anxious, nervous and systemic disorders reflect this impossible attempt to reverse Nature's Law and Order and our Universe's Essence. Dis-ease is the lack of ease created and maintained by such twisted mental acrobatics. Stress and Anxiety inhibit healing and compound and degrade health. Mentality is a bodily function. Mental disease is a physcial ailment. For as long as it is misdiagnosed - any cure or treatment will perpetuate its contagion. Principles affirm Our Indivisible nature. Sharing Principles confirms our natural indivisibility. Inspiration is natural while desperation, depression, degradation and acting oblivious to what is obvious is an unnatural choice to oppose reality which is impossible to accomplish though we are free to try. Ignoring what is happening, acting as though it shouldn't be or isn't happening, produces the unintelligible gibberish of ignorance - not reality.

Contact Welcomed HereWhen we are accountable things add up so we feel like we count. Absolute Reality has no reservations or exceptions. We can think IT does and feel isolated and alone while nursing baseless thoughts.  We do not need to understand any story we make-up to recognize the disturbing effects caused by sick thinking. The idea that facing Reality is complicated is not true. Trying to avoid it for any length of time is infinitely more complicated than facing it honestly. We Know We Know and are also readily and obviously aware even while and when we think and this say we aren't. We are free to choose to think whatever and however we think so when we create a sense of condemnation and doom it is the sum of how and what we are thinking about things that is felt. Practicing this is talking about how and what you think openly and honestly as thought.  Taking seriously the idea that thoughts are reality turns the idea of expressing what we are thinking openly into a seeming external threat - that does not feel funny no matter how silly the premise. Honesty does not require we be right. Honesty includes talking openly about whatever we are thinking about right or wrong.  To chronically think thoughts are right and never apply them is like sitting in the couch all day wondering how to be productive.  Thinking we ever keep these ideas to our seeming self becomes another secret we think we can keep even while we secrete blood, sweat and anxious, pitiful tears. Self-pity reflects the pitiful useless self we think is all we are. Usefulness is determined by how well we read our body language. Our functional literacy determines the degree to which we utilize our full functional capacity.  If our limited thoughts are imagine to be Reality the potential to rehabilitated and redeem any useless thinking will, by choice, be limited as evidence our wrong thoughts are right. We can create a mess and then blame the mess for the scarcity of our situation.  This only makes sense in induced insanity. To impose doubt where there is none is something we are free to do - but it doesn't make any sense beyond the limited ideas we make believe are our own seeming reality and truth.  The basis of Existence is Absolute and thus so is Nature. The nature of Nature is our nature; no exceptions, no other options, no doubts since there is no question. All the questionable doubts we encounters are not mysteries of the universe but a mystery as to why we don't bother to simply mention them.  We Know We Know. We Are Aware We Are Aware. We Are as We Are. Reality is unlimited and never changes. The idea that how and what we think creates reality suggests otherwise. Acting on backward thoughts leads to behaviors that are out of order reflecting a reversal of our natural fortune that are accurately called disorders. Anxious, nervous and systemic disorders reflect this impossible attempt to reverse Nature's Law and Order and our Universe's Essence. Dis-ease is the lack of ease created and maintained by such twisted mental acrobatics. Stress and Anxiety inhibit healing and compound and degrade health. Mentality is a bodily function. Mental disease is a physcial ailment. For as long as it is misdiagnosed - any cure or treatment will perpetuate its contagion. Principles affirm Our Indivisible nature. Sharing Principles confirms our natural indivisibility. Inspiration is natural while desperation, depression, degradation and acting oblivious to what is obvious is an unnatural choice to oppose reality which is impossible to accomplish though we are free to try. Ignoring what is happening, acting as though it shouldn't be or isn't happening, produces the unintelligible gibberish of ignorance - not reality.

When dealing with an eternal God who knows everything within time & outside of it, it is integral that we approach Him based on our faith in His omniscience. The happenings in our lives are not a mystery to Him. In prayers, our connection and every syllable of our lips to Him should be from the depths of our heart and not vain paganistic repetitions and noises that assume His ignorance of us and our situation. In His omniscient love, He prepares routes, paths, things & people to assist us in navigating our losses into a better place of His perfect will. Be Radiant!  

Contact Welcomed HereEgo = I. When I am talking to myself there must be a person in second place I am talking to. And if I am trying to fix that self that is pretty good evidence I think of it as broken while real enough to fix. Imposter syndrome is not an accident.Ego as a false self is a narrative created to blame for thoughtless shameful choices. This semi-clever ruse of twisted language has been developed to have insanity appear sane, normal and moral. The fact that it has no basis or substance is of little consequence to the maker believing in it. Illusions as reality is induced insanity. All matter and things that matter have substance  - lies do not.  We have developed a story around all we are is who and what we think we are. If we think how and what we think is reality, then we think there is no other reality. To face an illusions as reality can have us think we can turn our back on Reality while Reality does not flinch. Thinking insanely about reality does not change Reality it dysfunctionally changes our mentality. The fact that we can think we have nothing to do with anything precedes the thought that we have no place, value or benefit to offer anyone. Lies foster lies so trying to fix a lie while lying is to continue to maintain baseless, worthless ideas about everything. We cannot be what we have so think we become liars makes the idea of not lying seem preposterous since it would involve killing the self we identify as our self. That which has no life cannot be killed - though while we think it is real, just like a nighmare, it feels real till we wake up. Thinking is not the problem. What and how we think, once we think it is reality and truth, becomes a highly suspect fight for a life that never existed.  Obsessvive thinking is an unnatural attempt to turn our thoughts into reality by using pain to claim the effort must be true.  If insanity were sane it wouldn't be hard to admit. Insane thoughts are easy to fix once we see they are something we are choosing rather than who, what and how we are. We Know We Know. We Are Aware We Are Aware. We Are as We Are. Reality is unlimited and never changes. The idea that how and what we think creates reality suggests otherwise. Acting on backward thoughts leads to behaviors that are out of order reflecting a reversal of our natural fortune that are accurately called disorders. Anxious, nervous and systemic disorders reflect this impossible attempt to reverse Nature's Law and Order and our Universe's Essence. Dis-ease is the lack of ease created and maintained by such twisted mental acrobatics. Stress and Anxiety inhibit healing and compound and degrade health. Mentality is a bodily function. Mental disease is a physcial ailment. For as long as it is misdiagnosed - any cure or treatment will perpetuate its contagion. Principles affirm Our Indivisible nature. Sharing Principles confirms our natural indivisibility. Inspiration is natural while desperation, depression, degradation and acting oblivious to what is obvious is an unnatural choice to oppose reality which is impossible to accomplish though we are free to try. Ignoring what is happening, acting as though it shouldn't be or isn't happening, produces the unintelligible gibberish of ignorance - not reality.

Philosopher Stefan Molyneux challenges the existence of God from a philosophical perspective, drawing on decades of study. He defines existence and categorizes entities into three groups: those that exist, those that may exist without proof, and self-contradictory entities. Focusing on the latter, the lecture critiques God's traits of omniscience and omnipotence, posing logical dilemmas. Additionally, the relationship between consciousness and the brain is explored. Ultimately, he concludes that God's existence fails to meet criteria of evidence and logic, inviting reflection on the implications of believing in a non-existent entity.SUBSCRIBE TO ME ON X! https://x.com/StefanMolyneuxFollow me on Youtube! https://www.youtube.com/@freedomain1GET MY NEW BOOK 'PEACEFUL PARENTING', THE INTERACTIVE PEACEFUL PARENTING AI, AND THE FULL AUDIOBOOK!https://peacefulparenting.com/Join the PREMIUM philosophy community on the web for free!Subscribers get 12 HOURS on the "Truth About the French Revolution," multiple interactive multi-lingual philosophy AIs trained on thousands of hours of my material - as well as AIs for Real-Time Relationships, Bitcoin, Peaceful Parenting, and Call-In Shows!You also receive private livestreams, HUNDREDS of exclusive premium shows, early release podcasts, the 22 Part History of Philosophers series and much more!See you soon!https://freedomain.locals.com/support/promo/UPB2025

Philosopher Stefan Molyneux explores a challenging listener question about the relationship between God's omnipotence, omniscience, and the concept of free will. He begins by defining omniscience as God's complete knowledge of all events throughout time, which raises questions about human autonomy in light of divine foreknowledge. We delve into thought experiments on free will, highlighting the interplay between subconscious decision-making and moral agency. Using relatable examples, he argues that true free will exists in our ability to make moral choices aligned with our values. Transitioning to the divine perspective, he discusses how God's perfect nature means He cannot change His mind, ultimately reconciling the complexities of divine knowledge and human freedom. This exploration reveals important implications for our understanding of moral responsibility and the nature of God.The listener's question:"I believe you said (forgive me if you haven't) that God can't change his mind, therefore he is not omnipotent. This doesn't make sense to my personal experience. Why would I even want to change my mind if I were omniscient? Why would anyone want to change their mind if omniscient?"SUBSCRIBE TO ME ON X! https://x.com/StefanMolyneuxFollow me on Youtube! https://www.youtube.com/@freedomain1GET MY NEW BOOK 'PEACEFUL PARENTING', THE INTERACTIVE PEACEFUL PARENTING AI, AND THE FULL AUDIOBOOK!https://peacefulparenting.com/Join the PREMIUM philosophy community on the web for free!Subscribers get 12 HOURS on the "Truth About the French Revolution," multiple interactive multi-lingual philosophy AIs trained on thousands of hours of my material - as well as AIs for Real-Time Relationships, Bitcoin, Peaceful Parenting, and Call-In Shows!You also receive private livestreams, HUNDREDS of exclusive premium shows, early release podcasts, the 22 Part History of Philosophers series and much more!See you soon!https://freedomain.locals.com/support/promo/UPB2025

Experiencing the fringes of God's power through the gifts of the Spirit leads us to quantify the totality of God's power based on our limited experiences. God's Omnipotency goes beyond that, the creation of the Universe & the Earth in terms of size, matter and days taken might also not suffice in quantifying it. He can make dead things come back to life and calls those things that are not as if they were. His Omnipotence sets the basis of our trust in His ability and promises. Be blessed as you listen to this sermon.

Brendan explores psalms 139 in the context of God's Omniscience. God's knowledge includes knowing what we are doing, what we are thinking, where we are going, and what we say.

Lorsqu'une personne fait du mal, a-t-elle le choix de le faire (en vertu de son libre-arbitre), ou ne fait-elle qu'accomplir la volonté de D.ieu (puisque rien ne peut se produire sans qu'Il l'ait décidé) ? Comment concilier ces deux idées, apparemment contradictoires ? Réponse à travers un passage du livre de Chmouel.

Filling all things… Journey to Reality Chapter Five: Sacramental Thinking St John 14: 1-7.  Let not your heart be troubled: ye believe in God, believe also in me. In my Father's house are many mansions: if it were not so, I would have told you. I go to prepare a place for you. And if I go and prepare a place for you, I will come again, and receive you unto myself; that where I am, there ye may be also. And whither I go ye know, and the way ye know. Thomas saith unto him, Lord, we know not whither thou goest; and how can we know the way? Jesus saith unto him, I am the way, the truth, and the life: no man cometh unto the Father, but by me. If ye had known me, ye should have known my Father also: and from henceforth ye know him, and have seen him. St. Basil the Great (On the Holy Spirit).  We understand the “way” to be the road to perfection, advancing in order step by step through the words of righteousness and the illumination of knowledge, always yearning for that which lies ahead and straining toward the last mile, until we reach that blessed end, the knowledge of God, with which the Lord blesses those who believe in him. For truly our Lord is a good way, a straight road with no confusing forks or turns, leading us directly to the Father. For “no one comes to the Father,” he says, “except through me.” Such is our way up to God through his Son. ON THE HOLY SPIRIT 8.18.  “Modern, westernized people tend to think about the world from the starting point of physicality.  The physical world, as we would say, is the primary reality… It is the objective, measurable world on which we can all agree.”  Page 50 of 142. The assumption of materialists is that if a thing cannot be measured, then it is unprovable, a matter of opinion, AND of lesser importance. The natural world is everyone's baseline.  Religious or spiritual people have an added category, that of the “supernatural,” but as long as we operate in the material paradigm, these are the things that BY DEFINITION cannot be measured and are thus kind of optional.  Belief then becomes a way to stand up and assert that there are some things that are important that cannot be measured directly.  “I believe…” is our assertion that there is a supernatural reality and that it is well-ordered and that there are supernatural outcomes that should matter to us: ·      Forgiveness of sins ·      Sacramental marriage (vs. an agreement or contract) ·      Eternal life When we talk about religion, it is often in materialist terms. ·      What good is it (for health, family, society)? ·      What does it cost in terms of time and money? ·      Does its system make sense?  E.g. Juridical vs. Therapeutic vs. Holistic Healing But this worldview can only take us so far.  It “misses the mark” when it comes to understanding the world and how it works. An irony:  the materialist world may allow us to see things objectively, but not truly.  I am playing with words here, but it points to the difficulty. Objectivity refers to the quality of being unbiased and fair, making decisions based solely on facts rather than personal feelings or beliefs. It is often considered essential in fields like science and journalism to ensure accurate and impartial reporting or analysis. Objects have attributes that can be measured.  As a social scientist, I was taught that we have a poor understanding of something if we cannot put a number to it and that if we took enough measurements, we could explain everything.  Omniscience – or godhood – then is a matter of having enough data and the computing power to run the numbers.  Omnipotence involves the ability to manipulate everything towards a desired outcome.  This is no longer just the stuff of science fiction.  This is another one of those areas where claims are being made for technology that should not be made.  We can rightly question double-predestination, but what will keep us from doing the same thing as we grow in material understanding and power? A step in the right direction is to recognize that there is a moral dimension to the world.  But the problem is that it cannot be measured.  Outcomes can be measured, but their values can only be asserted.  This is why both secular philosophers like Nichze and religious ones like C.S. Lewis and Fr. Seraphim Rose claim that this kind of worldview leads to nihilism and the assertion of will.  Religious and spiritual people who believe in the supernatural will then say that God (or spirit, or Arche) is the solution to this problem.  Again, this gets us heading in a good direction, but it usually keeps within the materialist worldview.  Again, which system makes sense, agrees with what I prefer, has the best agape meal, and so on. But it really is strange to come at God in this manner.  All we are doing is taking the “God of the Gaps” concept and applying to morality and value.  This is like looking at the world through a two-dimensional, black and white filter. We can do better.  Let's see how our ancestors did it. They did not see the natural and supernatural as separate.  It was just “the world.” Some things were visible and some things were invisible.  Just as we cannot see radiation, atoms, and gravity know them to be part of reality, so it was with our ancestors for the invisible things.  “This idea that the physical and the spiritual are not seperable has a few important implications.  If we say that the physical and the spiritual have to go together, then what we're really saying is that there is a spiritual quality to everything physical, and a physical quality to everything spiritual.  This means, among other things, that physical objects and actions can have intrinsic meaning.” (Page 53 of 142) The example of two bisecting lines.  A Cross.  There is a story behind it, and that gives it subjective meaning, but there is more to it.  The things that are described in that story create meaning.  The cross is part of something primal and real it has “cosmic significance” (ibid).  And this is true regardless of whether people recognize it as such (example of vampires). Another way of describing this older view is as “enchanted” (vs. disenchanted).  Another way is that we are part of a grand story.  Stories are excellent at conveying meaning.  This is why some stories are said to be true even though they are fiction.  This is complete nonsense to the materialist mind. What about objectivity?  Isn't this view biased?  Isn't it subjective? It certainly is biased.  But it is only subjective because our perception of the world is incomplete and often wrong, and we really do assert our wills to create and share meaning.  We have to go beyond thinking about things primarily as either objective – meaning things that can be measured, or subjective – meaning things that cannot.  A refresher on objective vs. subjective: Pizza. ·      Objectively, it has bread, sauce, and topics of a certain type and consistency and spices that affect the olfactory system in certain measurable ways.  This is seen as what the pizza IS. ·      Subjectively, we prefer certain kinds of bread, sauce, topics, and spices.  This is our opinion about the pizza.  ·      We can argue about what belongs on a pizza or how it should be prepared, but it's easy to come to an agreement on what the pizza actually is.  The problem with this kind of a dichotomy is that it turns value and meaning into a matter of opinion and not only does that lead to disaster – it doesn't describe the way the world really is. Why disaster? Disagreeing about pizza can lead to arguments and bringing home a pizza one person sees as valuable and another doesn't may lead to temper tantrums; but what if the thing being described is something like human life or someone else's freedom?  Why is it wrong? Because everything has intrinsic value.  And this is because it has being through it's connection to the source of value – the Arche.' Personal Knowledge Another step in getting us to where we need to go is to look at knowledge that is gained personally, from the inside.  But even in relationships, we miss the mark.  Vices and virtues affect how well we can know things and people.  An angry person is going to notice – and even create – things in people and their behaviors that stoke their anger.  Humility allows the person to be open to the truth.  Vice clouds our vision. “The practice of virtue is, therefore, an essential element in seeking knowledge and the ultimate truth of things.  Why?  Because reality is participatory.  Or, to put it more simply, if you're a bad person, you're also going to be a bad friend.  If you're jealous, resentful, petty, or arrogant, your going to have a hard time building a relationship with anyone to the extent that those impulses control your life.  To have better relationships, you have to be a better person.  And if Truth itself is a Person, you're only going to be able to know Truth to the extent that you're able to have a relationship with Him.” (Page 61 of 142) In summary: the physical and spiritual world are inseparable.  This gives everything meaning.  We learn that meaning through participation; this involves both intellectual and moral growth.  How can this work?  Tune in next week! Some questions:  ·      How is personal knowledge more than just data? ·      How do we keep from pretending our subjective opinions are illumined? ·      How does anyone know how clean their mirror is or how true their sight is?                    

In today's episode I cover two objections: (1) Divine omniscience is incompatible with human freedom; (2) A Person without a body is impossible. Web: ThinkingtoBelieve.comEmail: ThinkingToBelieve@gmail.comFacebook: facebook.com/thinkingtobelieveTwitter & Gettr: @thinking2believTruth: @ThinkingToBelieveParler: @thinkingtobelieve

2 Kings 10 tells of the fear from the rulers of Ahab's household of retaliation of Jehu upon the eunuchs who brought up Ahab's sons in Jezreel. Jehu tricks the eunuchs to kill Ahab's 70 sons in order to save their own lives. Jehu now conceives a plan to Jehu follows this by telling Jehonadab of his zeal to fulfill the word of Yahweh. Jehu next slays 42 of Ahaziah's relatives, before carrying out his great ruse to eliminate Baal worship in Israel. All of Baal's worshippers who were beguiled into believing that Jehu intends to become the greatest of Baal's worshippers. These deluded worshippers of Baal come into his house and are slaughtered to the very last person by Jehu's appointed executioners. Jehu was promoted by God and promised to have a dynasty of four generations because of the service done that he did for the Almighty. However, Jehu himself did it not out of zeal for God but for himself. Sadly, Jehu perpetuated the calf worship of Jeroboam 1st of Israel - the man who made Israel to sin. Ezekiel is the priest of Yahweh and is introduced to us in chapter 1. His name means 'El establishes'. He was a prophet among the Babylonian exiles in Chebar who had been taken to Babylon approximately BC 606. The prophecy opens with the wonderful vision of the four living creatures, or cherubim, these creatures are symbols of Yahweh's vehicle for accomplishing His purpose. The presentation put before us in chapter 1 is a mathematical impossibility. But this is not so in the divine scheme of things. The theme of the cherubim permeates Scripture from Genesis 3 to the book of Revelation. The eyes of the four-faced living creatures portray Yahweh's Omniscience - symbolised in the eyes within the wheels. 2nd Corinthians 5 outlines the Almighty's Word, or His campaign for the reconciliation of the world. The Lord Jesus Christ's life, death and resurrection are its foundation and form the logical and heart-binding basis for our attachment to the great salvation of God. We become in Christ part of God's new creation. The Apostle Paul urges his readers to take up this ministry of reconciliation as Christ's ambassadors. In chapter 6 the great Apostle outlines his faithful commitment to the task of preaching the saving gospel message. Paul also establishes that this work is a call which embraces each believer in becoming a child of our Sovereign king. On our part we must embrace a complete commitment to holiness as God's beloved children. In the seventh chapter Paul entreats the Corinthians to find a place in their hearts for those whose love for them was unquestionable; and to embrace wholeheartedly the great task of receiving back into fellowship the repentant brother who had been disciplined by the ecclesia in the hope of restoring the erring brother to the company of fellow believers - the saints in our Lord Jesus Christ. Verses 13-16 speak of Paul's joy at receiving the news from Titus that the ecclesia at Corinth had followed the Apostle's advice and through ecclesial discipline achieved the result that Paul had hoped.Thanks for joining us - we pray you found these comments helpful in your appreciation of God's words, join again tomorrow at https://christadelphianvideo.org/christadelphian-daily-readings/

Does God change? If we answer yes how can we know whether our salvation is certain? And here, 2000 years into the fray, the question is more pertinent than ever. We have, what, half?!, the Church that thinks God has changed his mind about several critical matters: the mode of salvation, morality, truth, and even whether male and female are essential human qualities. But then if we answer no, God cannot change does that mean God is frozen inside his own self? Is he unmoved by what happens in time, on the earth? With my friend Mark I explore these questions with regard to pertinent Bible passages, theological formulation, philosophical infiltration, and the issue of Christian mission. Just how do we partner with God? With which God are we partnering? Is following Christ a matter of divine fatalism? Is God really causing every single thing that happens in life? Come think and laugh with us! We mean to help you hone your faith.

Hi welcome to Christadelphian video.org Thoughts on the Bible Readings September 5th (2 Kings 10; Ezekiel 1; 2 Corinthians 5, 6, 7)2 Kings 10 tells of the fear from the rulers of Ahab's household of retaliation of Jehu upon the eunuchs who brought up Ahab's sons in Jezreel. Jehu tricks the eunuchs to kill Ahab's 70 sons in order to save their own lives. Jehu now conceives a plan to Jehu follows this by telling Jehonadab of his zeal to fulfill the word of Yahweh. Jehu next slays 42 of Ahaziah's relatives, before carrying out his great ruse to eliminate Baal worship in Israel. All of Baal's worshippers who were beguiled into believing that Jehu intends to become the greatest of Baal's worshippers. These deluded worshippers of Baal come into his house and are slaughtered to the very last person by Jehu's appointed executioners. Jehu was promoted by God and promised to have a dynasty of four generations because of the service done that he did for the Almighty. However, Jehu himself did it not out of zeal for God but for himself. Sadly, Jehu perpetuated the calf worship of Jeroboam 1st of Israel - the man who made Israel to sin. Ezekiel is the priest of Yahweh and is introduced to us in chapter 1. His name means 'El establishes'. He was a prophet among the Babylonian exiles in Chebar who had been taken to Babylon approximately BC 606. The prophecy opens with the wonderful vision of the four living creatures, or cherubim, these creatures are symbols of Yahweh's vehicle for accomplishing His purpose. The presentation put before us in chapter 1 is a mathematical impossibility. But this is not so in the divine scheme of things. The theme of the cherubim permeates Scripture from Genesis 3 to the book of Revelation. The eyes of the four-faced living creatures portray Yahweh's Omniscience - symbolised in the eyes within the wheels. 2nd Corinthians 5 outlines the Almighty's Word, or His campaign for the reconciliation of the world. The Lord Jesus Christ's life, death and resurrection are its foundation and form the logical and heart-binding basis for our attachment to the great salvation of God. We become in Christ part of God's new creation. The Apostle Paul urges his readers to take up this ministry of reconciliation as Christ's ambassadors. In chapter 6 the great Apostle outlines his faithful commitment to the task of preaching the saving gospel message. Paul also establishes that this work is a call which embraces each believer in becoming a child of our Sovereign king. On our part we must embrace a complete commitment to holiness as God's beloved children. In the seventh chapter Paul entreats the Corinthians to find a place in their hearts for those whose love for them was unquestionable; and to embrace wholeheartedly the great task of receiving back into fellowship the repentant brother who had been disciplined by the ecclesia in the hope of restoring the erring brother to the company of fellow believers - the saints in our Lord Jesus Christ. Verses 13-16 speak of Paul's joy at receiving the news from Titus that the ecclesia at Corinth had followed the Apostle's advice and through ecclesial discipline achieved the result that Paul had hoped.Thanks for joining us - we pray you found these comments helpful in your appreciation of God's words, join again tomorrow at https://christadelphianvideo.org/christadelphian-daily-readings/

“O LORD, thou hast searched me, and known me.” (Psalm 139:1) The marvelous 139th Psalm consists of a prayer by King David to his King, the omniscient, omnipresent, holy Creator God, the King of ... More...

Contact Welcomed HereThe contagion of mentally obsessive thinking is not carried by bacteria or viruses but toxic silence when thoughtful but not always welcome words could help, or by speaking up with words that reinforce the sick thoughtlessness of this induced mental state. The imposition of this addiction is not a state of Mind but of a brain that has been mis-used and abused by imagining it is the creator of reality and truth and our self. It is not and we are not who we think we are. We Know We Know. We Are Aware We Are Aware. We Are as We Are. Reality is unlimited and never changes. The idea that how and what we think creates reality suggests otherwise. Acting on backward thoughts leads to behaviors that are out of order reflecting a reversal of our natural fortune. Anxious, nervous and systemic disorders reflect this impossible attempt to reverse the Law and Order of our Universe's Essence. Dis-ease is the lack of ease created and maintained by such twisted mental acrobatics. Stress and Anxiety inhibit healing. Mentality is a bodily function. Mental disease is a physcial ailment. For as long as it is misdiagnosed - any cure or treatment will perpetuate its contagion. Principles affirm Our indivisible nature. Sharing Principles confirms our natural indivisibility. Inspiration is natural while desperation, depression, degradation and acting oblivious to what is obvious is an unnatural choice to oppose reality Ignoring what is happening, acting as though it shouldn't be or isn't happening, produces the unintelligible jibbersh of ignorance - not reality.

In this first of two episodes on the attributes of God, we discuss divine simplicity, God's immutability, omniscience, and more.

Contact Welcomed HereObsessive thinking does not hear what is said but what is thought to be said. Nor does it see what is visibly clear but only what is thought to be seen. To hear and see things that don't exist is well defined as insanity. Definitions are explicit. Connotations are used to claim semantics reduce our culpability. Thinking about our self is a hallmark of so-called selfish, self centered, self serving problems. To worship thought and reason as our god is to imagine there is no other reality or truth. Healthy species do not act irrationally. Mental health determines our physical and societal health.   The natural process of change occurs every moment as all that is happening adapts to all that is newly happening now. Denial induces a sense of psychic anesthesia sufficient to imagine acting oblivious to what is obvious makes sense.. Fear naturally notices this risk. Any fixation requires thoughts be held like chained hostages, against change, to maintain their fierce compliance with baseless ideas. Trying to get over by feeling better about the discomforting feelings has the effect seem like the cause to maintain the lie we have nothing to do with it. Even within the debate over evolution vs. creation the process of change is encouraged to muster sufficient faith that never seems to be enough to finally qualify the believer as worthy of a connection to any named creator.To fight for finite ideas as absolute is to use hyper- reactive desperation to defend and pretend that false ideals as divine. This twist leads to imagining the effects we produce and feel are caused by a separate deity so pitiful as to have created us so we can be singled out, hated and destroyed. This deity is what we call ego - a false self. To think of the basis of our relations as dammed is to think of damning behavior as the only right thing to do. Holy shit is not accidental terminology as it openly though wrongly confirms wasteful, thoughtless ideas as our only possibility. It is our thinking we feel so profoundly. The Self we share indivisibly allows us to see disturbances clearly. This permanence is not obsessive but Ever-Present Omniscience. We would not know so clearly what is wrong if we did not have an Absolute basis in Truth and Reality that Is Right.  Self Realization and Self Actualization are intimately seamless partners actually realizing all that is happening Now. If this IS so - so Be It. Things are not as they seem but as they are. We are not as we seem but as We Are.  Thinking is something we do. We cannot Be or become what and how we think as it is unbending to imagine we do  We Know We Know. We Are Aware We Are Aware. We Are as We Are. Reality is unlimited and never changes. The idea that how and what we think creates reality suggests otherwise. Acting on backward thoughts leads to behaviors that are out of order reflecting a reversal of our natural fortune. Anxious, nervous and systemic disorders reflect this impossible attempt to reverse the Law and Order of our Universe's Essence. Dis-ease is the lack of ease created and maintained by such twisted mental acrobatics. Stress and Anxiety inhibit healing. Mentality is a bodily function. Mental disease is a physcial ailment. For as long as it is misdiagnosed - any cure or treatment will perpetuate its contagion. Principles affirm Our indivisible nature. Sharing Principles confirms our natural indivisibility. Inspiration is natural while desperation, depression, degradation and acting oblivious to what is obvious is an unnatural choice to oppose reality Ignoring what is happening, acting as though it shouldn't be or isn't happening, produces the unintelligible jibbersh of ignorance - not reality.

Last week, we noted that the Scriptures, both the Hebrew and New Testament Scriptures, teach that the Spirit of God is a person. The question is, what kind of a person?The Scriptures further teach that He is a divine person. By divine, it does not mean "excellent," or "delightful," although He is certainly that. Rather, by divine, it is meant He is deity. As the third person of the triune God, He is God, just as the other members of the triune God, the Father and the Son. This is seen in that He manifests the four essential attributes or characteristics of God: eternity, omnipotence, omniscience and omnipresence.With respect to his eternal existence we read in Hebrews 9:14:"How much more will the blood of Messiah — who, through the eternal Spirit, offered himself unblemished to God — cleanse our consciences from acts that lead to death, so that we may serve the living God!"The Spirit of God is also omnipotent, all powerful. He was engaged in the creation of the world, ordering, arranging, and giving life to what otherwise would have remained "void," "formless" and shrouded in darkness (Genesis 1:1-2).The Spirit of God is also omniscient, all knowing. Paul writes, "...The Spirit searches all things, even the deep things of God. For who among men, knows the thoughts of a man, except the man's spirit within him? In the same way, no one knows the thoughts of God except the Spirit of God" (I Corinthians 2:10-11).Lastly, the Spirit of God is omnipresent, everywhere. David writes, "Where can I go from Your Spirit? Where can I flee from Your presence? If I go up to the heavens, You are there; if I make my bed in the depths, You are there. If I rise on the wings of the dawn, if I settle on the far side of the sea, even there Your hand will guide me, Your right hand will hold me fast" (Psalm 139:7-10).How wonderful is this for believers in Yeshua. He imparts His Spirit to us, to be with us everywhere and anywhere we might be in this life, and for all of eternity. His presence serves to guide and protect us always!YouTube: https://youtube.com/live/593cdTdFuB4Send us a text

In this "Identity" episode you will learn about the incredible Creator and how His Omni-truths are revealed in creation.  What is the unique signature of God in Creation?  How does His order and patterns reveal His fingerprint? Dr. Patty shows how each of the Omni-Truth of God's Omnibenevolence, Omniscience, Omnipresence, and Omnipotence show up in scripture and in creation.  What can we learn about God from quantum physics principles? Dr. Patty shares some encounters where the Lord showed her a simple way to understand these complex concepts.  And Jesus takes you on an adventure in your Experience Jesus encounter time to help you understand why He created all that you can see and more importantly, why He created you.   Links referenced in this episode: New to the Podcast?  Check out the Trailer Episode for the Biblical Foundation for Experiencing Jesus!  https://PattyEJ.Podbean.com/e/trailer-episode-experience-jesus-with-dr-patty-sadallah   The Special Place Encounter Exercise   https://tinyurl.com/j742vpz4   Fibonacci Sequence: The Fingerprint of God https://youtu.be/fX8gy9EWZ_Y   Brian Greene The Elegant Universe  http://www.briangreene.org/the-elegant-universe/   Quantum Glory by Phil Mason  https://www.philmason.org/quantum-glory/   Check out our two workshop opportunities at https://SpiritLifeWorkshops.com/Upcoming-Workshop   Check out Dr. Patty's latest book- Encountering the POWER  of God: Experience Jesus Book 4 https://pattysadallah.com/product/encountering-the-power-of-god-experience-jesus-book-4/   Get Two Free Chapters of the Experience Jesus Book Series                               Check out all of Dr. Patty's books, journals, and downloadable resources at her bookstore, and don't forget to use the code EJPOD to receive 10% off everything, even the things on sale.  https://PattySadallah.com/shop/     And please make sure you share this podcast and share how you were blessed by this episode by commenting below!  THANKS!      

Join Prestonwood Women in welcoming guest teachers to partner with She Reads Truth in studying Attributes of God. Today's guest is Karen Harmon, teaching on God's omnipotence and Omniscience.

Psalm 147 (LSB)Andrew, Isack, and Edwin discuss the omniscience and omnipotence of God and how His numbering and naming the stars connects back to His promises to Abraham.Read the written devo that goes along with this episode by clicking here.    Let us know what you are learning or any questions you have. Email us at TextTalk@ChristiansMeetHere.org.    Join the Facebook community and join the conversation by clicking here. We'd love to meet you. Be a guest among the Christians who meet on Livingston Avenue. Click here to find out more. Michael Eldridge sang all four parts of our theme song. Find more from him by clicking here.   Thanks for talking about the text with us today.________________________________________________If the hyperlinks do not work, copy the following addresses and paste them into the URL bar of your web browser: Daily Written Devo: https://readthebiblemakedisciples.wordpress.com/?p=22495The Christians Who Meet on Livingston Avenue: http://www.christiansmeethere.org/Facebook Page: https://www.facebook.com/TalkAboutTheTextFacebook Group: https://www.facebook.com/groups/texttalkMichael Eldridge: https://acapeldridge.com/ 

Contact Welcomed Here“Suffering reveals the soul, not to others, but to oneself.”Dostoevsky“And still, in all my suffering, I wondered if there was even a self to reveal.”Kafka“I held on because I believed pain meant it was real”Dostoyevsky“I let go because nothing real should hurt that long”KafkaWe Know We Know. We Are Aware We Are Aware. We Are as We Are. Reality is unlimited and never changes. The idea that how and what we think creates reality suggests otherwise. Acting on backward thoughts leads to behaviors that are out of order reflecting a reversal of our natural fortune. Anxious, nervous and systemic disorders reflect this impossible attempt to reverse the Law and order of our universe's Essence. Dis-ease is the lack of ease created and maintained by such twisted mental acrobatics. Stress and Anxiety inhibit healing. Mentality is a bodily function. Mental disease is a physcial ailment leading to others as long as it is improperly diagnosed - any treatment will perpetuate its contagion. Principles affirm our indivisible nature. Sharing principles affirms and confirms our indivisibility as our nature. Inspiration is natural while desperation, depression, degradation an acting oblivious to what is obvious is a choice. Absolute Intelligence, Peace and Silence is Nature's nature since It does not change. Nature is naturally our nature. Ignoring what is happening, acting as though it shouldn't be or isn't happening, produces the unintelligible jibbersh of ignorance - not reality.

The Matt Slick Live (Live Broadcast of 07-18-2025) is a production of the Christian Apologetics Research Ministry (CARM). Matt answers questions on topics such as: The Bible, Apologetics, Theology, World Religions, Atheism, and other issues! You can also email questions to Matt using: info@carm.org, Put "Radio Show Question" in the Subject line! Answers will be discussed in a future show. Topics Include:What About The “Flat-Earth” Hypothesis?/ A Caller Asks About Christ's Ascension/ What About The Mark of The Beast?/What is Dispensationalism?/Luke 1:15-John The Baptist/ God's Omniscience and The Book of Life/ Are Muslims Coming to Faith Because of Dreams and Visions?/Matt Discusses CARM's Missionaries/ Is it Fair That the Gay Community Criticize Christians for Their Hypocrisy?/ July 17, 2025

The Matt Slick Live (Live Broadcast of 07-18-2025) is a production of the Christian Apologetics Research Ministry (CARM). Matt answers questions on topics such as: The Bible, Apologetics, Theology, World Religions, Atheism, and other issues! You can also email questions to Matt using: info@carm.org, Put "Radio Show Question" in the Subject line! Answers will be discussed in a future show. Topics Include: What About The "Flat-Earth" Hypothesis?/ A Caller Asks About Christ's Ascension/ What About The Mark of The Beast?/What is Dispensationalism?/Luke 1:15-John The Baptist/ God's Omniscience and The Book of Life/ Are Muslims Coming to Faith Because of Dreams and Visions?/Matt Discusses CARM's Missionaries/ Is it Fair That the Gay Community Criticize Christians for Their Hypocrisy?/ July 17, 2025

The Matt Slick Live (Live Broadcast of 07-18-2025) is a production of the Christian Apologetics Research Ministry (CARM). Matt answers questions on topics such as: The Bible, Apologetics, Theology, World Religions, Atheism, and other issues! You can also email questions to Matt using: info@carm.org, Put "Radio Show Question" in the Subject line! Answers will be discussed in a future show. Topics Include:What About The “Flat-Earth” Hypothesis?/ A Caller Asks About Christ's Ascension/ What About The Mark of The Beast?/What is Dispensationalism?/Luke 1:15-John The Baptist/ God's Omniscience and The Book of Life/ Are Muslims Coming to Faith Because of Dreams and Visions?/Matt Discusses CARM's Missionaries/ Is it Fair That the Gay Community Criticize Christians for Their Hypocrisy?/ July 17, 2025

Contact Welcomed HereMOD episodes have no shelf-life or expiration date.  Our focus is principled so each episode reflects the immediate peace and stability of our Ever-Present Knowing Awareness that clarifies conflicted impressions manifest by the instability and hyper-reactivity of obsessive thoughts purely induced, “imagined reality”.While the Absolute nature of Life is an unadulterated gift - we earn our human experience. Good or bad, like it or not, it is how and what we think of Life, Reality, and Truth that complicate all the consequential forms of conflicted dysfunctional incapacities incorrectly blamed on life and human nature. It is not Life that is impossible, hard, or a struggle but imagining that our thoughts about it are omnipotent and as a result unchangeable. This addictive mental trend has the world of things and people seem in chronic need of change while we choose to inflict others with our thoughts to pretend we are not capable of causing such conflicts. This induced form of insanity once seen clearly is laughable. The only thoughts induced insanity seemingly overlook are the mistaken beliefs of their perpetrator. Acting like we're in a coma to maintain unnatural conditions does not affect our essence but causes over-dramatic mental and inter-reactive consequences. We choose how and what we think - and this news is good or bad dependent on how accurately, or honestly, our choices are conceded.  We Know We Know. We Are Aware We Are Aware. We Are as We Are. Reality is unlimited and never changes. The idea that how and what we think creates reality suggests otherwise. Acting on backward thoughts leads to behaviors that are out of order reflecting a reversal of our natural fortune. Anxious, nervous and systemic disorders reflect this impossible attempt to reverse the Law and order of the universe. Dis-ease is the lack of ease created and maintained by such twisted mental acrobatics. Stress and Anxiety inhibit healing and so contribute to any ailments. Mentality is a bodily function. Mental disease is a physcial ailment leading to others as long as it is improperly diagnosed - any treatment will perpetuate its contagion. Principles affirm our indivisible nature. Sharing principles affirms and confirms our indivisibility as our nature. Inspiration is natural while desperation, depression, degradation and acting oblivious to what is obvious is a choice. Absolute Intelligence, Peace and Silence is Nature's nature since It does not change. The nature of nature is naturally our nature. Ignoring what is happening, acting as though it shouldn't be or isn't happening, produces the unintelligible jibbersh of ignorance - not reality.

In this video, Eli explores what seem to be two unrelated topics: Molinism & Presuppostionalism. Is Molinism (View of God's Omniscience) compatible with Presuppositional Apologetics (Apologetic Method)? The answer might surprise you.

Know-it alls.

Sunday School

Psalm 139 & Romans 11 Jason McClanahan

Send us a textHave you ever wondered if God truly knows everything.  Omniscience can be a difficult concept alongside agency but the two can live together.  And when they do, the impossible becomes possible and the Atonement of the Savior demonstrates its divine power.

A Study on the great Bible Doctrine of God being All Knowing!

In this thought-provoking episode of the Kindred podcast, Garrett McGeein dives deep into the tension between divine omniscience and human free will, exploring the philosophical and theological implications of middle knowledge. Using passages from the book of Acts as a springboard, Garrett unpacks how God's foreknowledge and human agency coexist, challenging traditional views while inviting open discussion and thoughtful reflection. Tune in as we navigate this complex but crucial aspect of faith and theology.Kindred Church is a Christian community gathering in Reno, Nevada. We are a 501c3 non-profit organization. If you believe in the ministry of Kindred Church and would like to support our efforts, visit kindredchurchreno.com/donate to make a contribution. If you'd like to join us for a gathering, please visit kindredchurchreno.com/gatherings for our location and service times.Thanks for listening.

In this sermon, pastor Matt continues to look at David's tragic fall and reminds us that no sin can be hidden from god's sight. Despite every attempt to cover up our selfish and rebellious choices, our omniscient God searches and knows all hearts

Send us a textW3: James and Drey discuss unresolved issues they have regarding scripture.Main Topic: In this episode, we explore the profound depths of Kenotic Theology, a Christian perspective on divine self-emptying. Discover how the concept of Jesus 'emptying himself' in the Incarnation reveals a God who embraces human limitation and suffering out of love. We'll unpack its biblical roots, theological debates, and what it means for understanding divine humility in a modern world.

As we step into 2025, there’s one issue that’s more important than anything else you will encounter this year, and that issue is your eternal destination. Where will you spend eternity—Heaven or Hell? Let Pastor Jack encourage you to settle this issue with certainty in today’s podcast episode. (00:00) God's Omniscience and Predestination(10:06) Flesh vs. God's Children(16:52) The Necessity of Spiritual Rebirth CONNECT WITH PASTOR JACK Get Updates via Text:  https://text.whisp.io/jack-hibbs-podcastWebsite: https://jackhibbs.com/ Instagram: http://bit.ly/2FCyXpO Facebook: https://bit.ly/2WZBWV0 YouTube:  https://bit.ly/437xMHn DAZE OF DECEPTION BOOK:https://jackhibbs.com/daze-of-deception/ Did you know we have a Real Life Network? Sign up for free for more exclusive content:https://bit.ly/3CIP3M99

Questions about whether the concept of God's omniscience is just a fear tactic to control your mind and what to say to someone who thinks it's possible for God to lie and that Jesus' coming might have been an elaborate scheme to make us think he loves us.   I would love to hear your thoughts on God's omniscience. God uses fear tactics to control your mind. He loves you so much that he's watching your every move and knows your every thought? Is this good? What do I say to someone who thinks it's possible for God to lie, that he treats us like his playthings, and that Jesus' coming might have been some elaborate scheme to make us think he loves us?

God is omniscient . . . He’s all-knowing. We’re . . . not. There are so many things God understands that we can’t quite grasp. We don’t even know how many things we don’t know. Well today on A NEW BEGINNING, Pastor Greg Laurie points out one of the most often-asked questions falls into this category. But Pastor Greg tackles it head-on and offers some encouraging biblical perspective. It’s a message from his candid new series called “Hot Button Issues.” Listen on harvest.org --- Learn more and subscribe to Harvest updates at harvest.org A New Beginning is the daily half-hour program hosted by Greg Laurie, pastor of Harvest Christian Fellowship in Southern California. For over 30 years, Pastor Greg and Harvest Ministries have endeavored to know God and make Him known through media and large-scale evangelism. This podcast is supported by the generosity of our Harvest Partners.Support the show: https://harvest.org/supportSee omnystudio.com/listener for privacy information.

God is omniscient . . . He’s all-knowing. We’re . . . not. There are so many things God understands that we can’t quite grasp. We don’t even know how many things we don’t know. Well today on A NEW BEGINNING, Pastor Greg Laurie points out one of the most often-asked questions falls into this category. But Pastor Greg tackles it head-on and offers some encouraging biblical perspective. It’s a message from his candid new series called “Hot Button Issues.” Listen on harvest.org --- Learn more and subscribe to Harvest updates at harvest.org A New Beginning is the daily half-hour program hosted by Greg Laurie, pastor of Harvest Christian Fellowship in Southern California. For over 30 years, Pastor Greg and Harvest Ministries have endeavored to know God and make Him known through media and large-scale evangelism. This podcast is supported by the generosity of our Harvest Partners.Support the show: https://harvest.org/supportSee omnystudio.com/listener for privacy information.

(Proverbs 9:10) While there are many things we do not know about God, there is much that we can know about God. He wrote it down for us! The deeper we go into Scripture the deeper we can go into our knowledge of God. (0941250214) ----more----   The Mystery of God There are many things that I do not know about God. There are many things that are beyond my understanding. And why is that? Because I am a finite being and He is an infinite God. And yet, isn't it glorious? Isn't it wonderful? That God, through His Word, has revealed Himself in such a way that there are many things we do know about God. So many people get stuck on the things they don't know and can't understand but they miss in that what they should know and what we can understand.  The Fear of the Lord Is Beginning of Wisdom Proverbs chapter 9, verse number 10 says this, "The fear of the Lord is the beginning of wisdom, and the knowledge of the holy. Is understanding." Did you hear that expression? The knowledge of the holy, not of holy things, but of the holy one.  Understanding God's Holiness In fact, holiness is the one attribute that is most often attached to God in Scripture. That does not mean that He is more holy than He is any of His other attributes. He's the perfection of all of them. You can't chop God up. You can't divide Him. He's not one. He is all. He's not more of one. He is perfectly all. But the reason Holiness is attributed to God more than any other thing in Scripture is that His holiness is the perfection of all of His attributes. Everything about God is holy. His knowledge, His power, His love, His mercy, His judgment, everything is a revelation of our holy God. Knowing God Through Scripture And I want to say to you that We should begin, when we are studying what the Bible says, by saying, Lord, we want to know our Holy God. We want to know Him personally. It's one of the great marvels of our God. He is both infinite and knowable at the same time. There's no limit to Him. There's no end to Him, and yet, there is a place to begin. We can know Him by finding out what Scripture says about Him. This is God's revelation of Himself. I heard for years preachers say that when we get to heaven, we're going to know everything. I don't believe that's what scripture teaches. The Bible says we will know even as we are known. But I believe when we get to Heaven, when we get into Eternity, we're going to spend the rest of Eternity entering in our knowledge and understanding more and more to the depths of our great God. I don't think you'll ever exhaust who God is. That's what's going to make Eternity such an ongoing adventure. More and more of His love and beauty and perfection. And friend, that journey is not to begin when we die or Jesus comes. It is to begin right here. And right now, it is to begin by us discovering what the Bible says about God. So what does the Bible say? We can't be exhaustive about this, certainly not in this brief time we have to study together. But may I just give you a few thoughts to, to meditate on today? Some things that you can study further for yourself and look for in Scripture.  Attributes of God: Self-Existence and Immutability In Scripture, we learn that He is self-existent and self-sufficient. It means He is the Great I Am. The only limits on God are the ones He places on Himself. The limits of His own holy will. He holds back, for example, His justice with His mercy. God may limit Himself in certain areas at particular times, but there is no limit to Him. He is I Am. He's the only one who can say I Am and put nothing after it. He is the self existent and self sufficient one. Imagine Him saying to Moses, Tell them I Am sent you. I Am what? Yes. All of the above. More than you could ever imagine. Not only that, He's immutable. That means he never changes. James chapter 1 and verse number 17, Malachi chapter 3, verse number 6, all through scripture we get this truth. He says in Malachi 3 verse 6, "I am the Lord, I change not." God's Eternal Nature and Omnipresence And then, He is eternal. Eternity has no beginning and no end. It's like an open ended front and an open ended back. And God is beyond the limits in both directions. God's not in time. Time is in God. God holds time in the palm of His hand. He's the eternal God. Did you know that the word eternity is only found one time in all of Scripture? I would challenge you to find it. I could give you the reference, but I'm going to challenge you. I'll give you a homework assignment. See if you can find the one verse in the Bible where the word eternity is found, and in that verse, The Bible references the God who inhabits eternity. Think of a God so big, He fills up eternity. God is not bound by anything. Not by time or not by space. No, because He is the great I Am.  God's Omnipotence, Omniscience, and Omnipresence Then we know He's all powerful. Some people refer to that as His omnipotence. He is all powerful. He is omniscient. That means He knows everything. He's omnipresent. That means He's everywhere at once. If I say to you, where's God, some people say he's in heaven, other people say he's in my heart. The truth of the matter is, you can't limit Him to either place. He may be in both places, but He's everywhere at once. Psalm 139, the psalmist cries out, "Where then shall I go from thy spirit? Where then shall I flee from thy presence? If I ascend up into heaven, thou art there. If I make my bed in hell, behold, thou art there.If I take the wings of the morning and dwell in the uttermost parts of the sea, even there, thy right hand shall hold me." God's everywhere.  God's Faithfulness and Mercy And then we know that God is faithful. He is true. He never lies. He never fails to keep His word. He is a God of truth. Jesus said, I am the way, the truth, and the life. We know He's a God of mercy and of goodness. That means He holds back what we don't deserve. And He, or what we do deserve rather, and He gives what we don't deserve. Think of that. He holds back the judgment and He gives good things. What was the Psalmist saying in Psalm 23, "Surely, goodness and mercy shall follow me all the days of my life, and I shall dwell in the house of the Lord forever." I tell you, you can't beat the Christian life. Mercy and goodness come to live with you now, and you go to live with the God of mercy and goodness for all eternity. I hope you know the Lord as your personal Savior.  God's Justice and Love And then, we know He's a God of justice. And a God of righteousness. That's what the cross was all about. That's what Calvary revealed. God doesn't laugh at sin. He doesn't simply turn a blind. Turn a blind eye to our unrighteousness. Isaiah 53, verse 11. He saw the travail of Christ's soul and was satisfied his justice, his righteousness was satisfied at that moment. Then, praise God, we know He's a God of love. First John 4:16 says, "God is love." It's not just something He does, it's who He is. And then we come full circle back to where we started, He's a holy God. He's the thrice holy God. Do you remember? Isaiah chapter 6, what are they saying? Holy, Lord God Almighty. When you come to the revelation of Christ, what are they saying? "Holy, holy, holy, Lord God Almighty, which was and is to come." The Father is holy, the Son is holy, the Spirit is holy. He was holy in the past, He is holy in the present, He always will be holy for all eternity He is the Holy God.  Loving and Sharing the Knowledge of God I would challenge you to study the names of God all through scripture because his names reveal His character. Study His attributes, learn more about the God of the Bible, and I'll tell you what I think you'll find. Number one, you're going to love him more. To know him is to love him. And the more you come to see what the Bible says about God, the more you're going to say to the Father, I love you, I'm so glad to be your child. The more you're going to say to the Son, thank you for saving me and bringing me into this family. And the more you're going to say to the Holy Spirit, I'm so glad you're with me right now. Learn what the Bible says for your own soul, but then don't keep it to yourself. Pass it along to somebody else. Peter says, "Sanctify the Lord God in your hearts and be ready always to give an answer to every man that asketh you a reason of the hope that is in you with meekness and fear." I hope today you'll both learn and share what the Bible says about our great God. Repeating what other people have said about the Bible is not enough. Outro We must know the biblical reason behind what we believe. We hope you will visit us at etj.bible to access our library of Bible teaching resources, including book by book studies of Scripture. You'll also find studies to watch, listen to, or read. We are so grateful for those who pray for us, who share the biblical content, and for those who invest to help us advance this ministry worldwide. Again, thank you for listening, and we hope you'll join us next time on Enjoying the Journey.

Nothing is hidden from the mind of God—past, present, or future—so nothing can surprise or confuse Him. Today, Barry Cooper introduces us to God's attribute of omniscience. Read the transcript: https://ligonier.org/podcasts/simply-put/omniscience/ A donor-supported outreach of Ligonier Ministries. Donate: https://donate.ligonier.org/ Explore all of our podcasts: https://www.ligonier.org/podcasts

Watch Part 1: Creating a Transformational Sunday School | An Interview with Dan Duckworth. Dan Duckworth is the founder and host of LeaderQuest, an elite leadership program that transforms managers and executives into dynamic changemakers. He speaks, teaches, and writes on leadership and leadership development, and provides one-on-one coaching to leaders aiming to drive transformational change. Dan has served as a board member for Leading Saints since 2019. To learn more, visit idylli.co or find Dan on LinkedIn. Links Part 1: Creating a Transformational Sunday School | An Interview with Dan Duckworth The True Purpose of Sunday School Why Testimony is Not the Only Goal for Latter-day Youth—Part 1 | A Presentation by Dan Duckworth Sunday School Session Template From Aspirational Principles to Practical Principles Share your thoughts in the Leading Saints community Transcript coming soon Get 14-day access to the Core Leader Library Highlights This is the second of a two-part podcast. The conversation continues, focusing on the transformative role of mentorship in youth leadership and the dynamics of effective Sunday school teaching. Dan shares insights on the nature of transformation in leadership. He stresses that effective teaching is not merely about mastering tactics but involves a fundamental shift in belief systems. This transformation requires educators to engage in a cycle of experimentation and reflection, challenging their preconceived notions of what it means to teach and learn. Dan illustrates this with examples from his own experiences, emphasizing the need for teachers to create an environment where students can co-create their learning experiences rather than passively consume information. The episode delves into the concept of culture within church settings, with Dan advocating for a proactive approach to challenging and reshaping cultural norms. He encourages leaders to embrace discomfort and uncertainty as they experiment with new teaching methods, using the metaphor of pushing against the walls of culture to gather valuable insights. The discussion also touches on the importance of fostering authentic community within Sunday school classes, where trust and openness can lead to deeper engagement and meaningful dialogue. Dan outlines practical principles for effective teaching, including the necessity of a single driving question to guide discussions and the importance of creating a safe space for students to share their thoughts and experiences. He shares a structured approach to lesson planning that prioritizes engagement and interaction, allowing for a more dynamic and impactful learning environment. Throughout the episode, Dan emphasizes the value of personal experiences and the need for teachers to be vulnerable and authentic in their interactions, ultimately aiming to facilitate a transformative experience for both educators and students alike. 02:09 - Discussion on Culture and Sunday School 03:39 - The Importance of Transformation in Leadership 04:55 - The Cycle of Experimentation and Reflection 05:43 - Challenging Belief Systems in Teaching 06:25 - The Nature of Culture and Disruption 07:28 - Building Confidence in Change 08:13 - The Role of Disruption in Teaching 09:17 - Avoiding the "Ex-Girlfriend Syndrome" in Change 10:20 - Learning from Failed Experiments 11:25 - The Role of Discernment in Leadership 12:29 - God's Omniscience and Leadership 13:03 - Teaching as Experience Design 14:07 - The Journey of Becoming a Transformational Teacher 15:20 - The Challenge of Teaching Transformational Principles 16:25 - The Importance of Actionable Principles 17:41 - Empowering Co-Creation in the Classroom 19:04 - The Pareto Principle in Teaching 20:22 - Structuring Class Time for Engagement 21:58 - Creating Positive Tensions in Lessons 23:00 - Building Authentic Community in Class 24:36 - The Role of Icebreakers in Fostering Connection