How do we deal with doubt? What should a believer do when they have questions about their own relationship to the faith? Daniel Yoder is with us to help us think about this topic and hopefully gain some encouragement. Well I want to start by saying thank you for allowing me to address this important and practical topic. The subject of doubt is one that I enjoy studying. I think it's very important, very relevant, and something that many Christians struggle with and maybe struggle to understand and even know how to address it. So on the subject of doubt I benefited from the writings of Askinus and his definition of doubt is that doubt is not the opposite of faith nor is it the same as unbelief. But doubt is the state of mind in suspension between faith and unbelief so that it is neither of them holy and it's each of them only partly. So essentially, yes, doubt is being in two minds. It's wavering between belief and unbelief. There's another author who's referred to doubt as being a form of intellectual temptation. And I think that's a helpful comment because he's distinguishing between doubt and sin. We might think of doubt as a sin but honest doubt is not sinful. Unbelief is a sin but doubt is not. So I think it is a popular, I should say a popular misconception to equate doubt with unbelief. So doubt reveals a divided mind, a state of uncertainty. There's an inner conflict that the doubter experiences between two options, between belief and disbelief. Yeah, I'm gonna find that really helpful, especially that phrase intellectual temptation because then it'll call back to what do you do with it as to whether it leads to sin and unbelief or not. Yeah, so in the context of a discussion like this, we're thinking about doubt in terms of the inner battle that can be experienced as a person, we could say straddles the fence between trust and distrust of God. So we do want to distinguish between faith and doubt. Faith is a confident unwavering trust in God and doubt is wavering with an inner conflict in loyalties. So doubters are double-minded or we could perhaps even say double-hearted. And that's why it's important to work at resolving doubt because if doubt is double-heartedness and that's unresolved, then that could lead to a double life. Now to answer the second part of your question, are there different kinds of doubt? Yes, there are and we can categorize doubts by kinds or by families. And it is important to know what kind of doubt is being experienced in order to provide a proper response. And I've appreciated the work of Gary Habermas on this subject. He identifies four different varieties of doubt. So factual doubt is the first variety that arises from ignorance and from misinformation. So factual doubt can arise, for example, when a person is confronted with an authoritative claim about a topic that lies outside their area of competence. So an authoritative sounding statement that contradicts Christianity could unsettle a person who's unaware of the evidence that supports Christianity. The second variety of doubt that he mentions is philosophical doubt. And that's the kind of doubt that arises from wrong assumptions or wrong thinking. So our basic assumptions about the nature of ultimate reality determines our view of God. So incorrect presuppositions about the nature of reality will lead to a faulty view of God. And when people hold a distorted concept of God, it shouldn't be a surprise if they struggle then to trust him. An example of philosophical doubt could be seen in, for example, a scientist who declared that he could never accept the resurrection of Jesus. And his rejection of that event was because his naturalistic worldview was opposed to the possibility of miracles. So he had closed his mind to the possibility of miracles not because of the facts, but because of his assumption of naturalism. So he had a faulty assumption and you can't reach a solid conclusion on a subject if you start with an unstable foundation. So those are the first two varieties and then emotional doubt can be mentioned as well. Emotional doubt arises from feelings. This is the kind of doubt that can come when we're discouraged or when we're lonely. This is the kind of doubt that can emerge out of hurts or anxiety or depression. So for example, an experience such as the tragic death of a family member could lead someone to doubt the goodness of God. And that would probably be an instance of emotional doubt. And then the fourth category that Habermas lists is volitional doubt. Volitional doubt arises from the will, from our volition. So doubts of the will come from a desire to be independent of God. And some believers are, I should say, some unbelievers are honest enough to admit that no amount of evidence will persuade them to believe in God. They have volitional doubt and that's a doubt that arises from a stubborn, rebellious will. So the person who wants to be totally self-sufficient and autonomous will doubt God regardless of the evidence. So there's one college student who admitted to the author Paul Little that Little had answered his intellectual questions and doubts. But that student still refused to believe and he explained why he said that belief in Jesus would mess up the way that he's living.  So these are the four varieties of doubt, factual, philosophical, emotional, and volitional. And the many forms of doubt are not unbelief in and of themselves, but doubt can become unbelief if a person persists in it. So that's my summary of the four varieties of doubt. Find those four categories. Yeah, really helpful. Volitional, emotional. The philosophical and factual, we may talk a little bit about in a different episode in this series, but yeah, and I like to focus on, I suppose it's mostly the emotional doubt, maybe it's related to volitional a little bit. And that is, what do you want to say to somebody in summary who doesn't have the factual doubt? They believe that Jesus, his God, come in the flesh, that he died and was raised again. So that doesn't have the factual doubt or even the philosophical doubt there, but it's simply struggling with, am I a believer? Do I belong to God? Am I in the faith, as the one scripture passage says? Yeah, well, that's an important question. And a question like this makes me think of a passage like Romans 10, especially verses five through 13. I'm not going to read that passage, but I will be basing my response on it. So in Romans 10, five through 13, Paul distinguishes between righteousness which is based on the law and righteousness which is based on faith. And the righteousness that is based on faith doesn't require us to do anything dramatic. He refers to something as dramatic as bringing Christ down from heaven or up from the grave. The righteousness based on faith doesn't require something dramatic like that, but Paul teaches in that passage that faith is readily available to those who will simply believe and confess that Jesus is Lord. So Paul lays out the necessity of believing from the heart and he also emphasizes the importance of a public confession. And what must be believed, as Paul explains, there is that Jesus is Lord. There needs to be a declaration that Jesus has universal and unlimited authority and those who make this confession that are placing themselves under that authority. So there's no salvation apart from submission to Jesus' Lordship. And if you haven't submitted to that authority, then you're not in the faith. Now I do need to clarify that our submission and obedience to Jesus may falter from time to time. We won't obey him perfectly, but we should strive to obey him with an increasing measure of faithfulness. And as Paul explains in this passage, this confession of Jesus' Lordship stems from a heartfelt belief in Jesus' resurrection. The resurrection of Jesus is the cornerstone of the Christian faith. The resurrection confirms that Jesus is who he said he was, the Son of God, and confirms that his death, for our sense, was accepted by his father. And Paul makes an important comment in verse 11 of that passage where he affirms that everyone who believes in Jesus will not be put to shame. And we're given a tremendous promise as well in verse 13, the promise that everyone who calls in the name of the Lord will be saved. So an important point for someone who's struggling, even with something like emotional doubt, an important point for them to remember is that your salvation is ultimately based on God's character, not your own strength. The Lord cannot break his promises, he promises that everyone who calls on the name of the Lord will be saved. So for someone doubting whether they're in the faith, I would encourage them to read Romans 10, 5 through 13 carefully. They should respond then to Jesus as that passage describes, and they need to remember that what makes our faith valid is not simply that we have it. What makes our faith valid is that the object of our trust, the object of our belief, is worthy of that belief. So true faith isn't about the intensity that we feel, but it's about the genuineness of the one in whom we place our trust. Or to put it another way, what ultimately matters for your salvation is not the strength of your faith, but the strength of your God. And yes, we should always seek as we have opportunity to strengthen our faith, but even a weak faith in an all-powerful God is sufficient for salvation because salvation is ultimately about his strength, not ours. And I think that's a tremendously reassuring truth for anyone who's struggling with doubt. Yeah, so let me just echo back what I think I'm hearing from you, and I'll let you comment on that. And then I do have a little bit of a follow-up question with it. So yeah, strength of your faith, sorry, it's the object of your faith, not the strength of your faith. And again, just calling us back to actually focus on Jesus, submit to his Lordship, and that's a very, that's more, that's concrete. You can do that. It's not, it's not this vague, try to drum up faith, which, yeah, so no we can't drum up faith, but that is sometimes our temptation is to think, yeah, we have to muster the faith. To push it there is what makes that different than some of the false faith described in the Bible. And I can see people being worried about this, they're not really a believer. You know, like a passage like James says, well, the demons believe there's one God and they tremble, and it's implied they don't have faith. Or Jesus said, many will say, Lord, Lord, and be convinced that they're believing in Jesus, Lord, evidently, and will say, I never knew, I never knew you. Yeah, what if somebody is worried by those kinds of thoughts? It is about more than belief. It is about submission. It is about obedience. And it's not that we will obey or submit perfectly, but I think we, what should think about the state of our heart is our desire to obey. And if there is a desire to obey, even if it is a struggle, then I think that is a sign that we are in the faith. We certainly would need to grow in that case. And we all have room to grow. But I think the attitude of a person's heart in that regard, are they desiring to obey and submit? Is something important to consider? Yeah, that's helpful. Is the desire there? And then, again, press on with that in the confidence in God. Yeah. Okay, I want to follow that up just a little bit further. Second Corinthians brings this question back around to chapter 13 where he says, test yourself to see if you're in the faith unless you fail the test. Yeah, there's some things going on there with Paul's relationship with the Corinthians, probably, where there's a little bit of antagonism, and he wants them to know that he doesn't fail the test. But yeah, what does it mean to test ourselves in that fashion? Yes, there are some important things to note about the context of Second Corinthians 13-5. As you alluded to, a major part of Paul's purpose in the letter of Second Corinthians is to offer a defense of his apostolic ministry. The Corinthians hadn't insisted on testing Paul, and so Second Corinthians is at least part of Paul's response to that. But now that Paul had withstood their investigation, he asked the Corinthians to examine themselves to test whether they are acting in accordance with the Christian faith. And earlier in the letter, in chapter 7 verse 4 and also chapter 7 verse 16, Paul had expressed confidence about these believers. He genuinely believed that Christ was in them, but he does emphasize that if they don't believe the fundamental truths of the Christian faith, then they would fail the test.  The Corinthians desired to find out whether Paul's apostolic credentials were genuine, but then Paul matches this inquiry with a call for them to see if their own lives are authentic. And he knows that they can pass the test, but he still wants them to contemplate the consequences of failure. So in thinking about how we can examine ourselves, there are a couple of questions that we can use, a couple of very pointed questions that we can reflect on. One is, do I believe in Jesus? That is, have I committed myself to Christ? Have I submitted to his lordship? Am I desiring to obey him? And that does lead into the second question. Am I serious about following him? Has my commitment to Jesus made a difference in my life? And then we can build off of those two questions to ask a third question. Am I learning to know Jesus better? Do I know Jesus better than I did a year ago? And if we can't honestly answer yes to those questions, then we need to commit ourselves to seeking the Lord in a time when he may be found. And we need to continue to seek him because the Christian life is to be lived daily. And it is a sign of spiritual health to continually take stock of our relationship to the Lord. That's a really good reminder. When I asked you that question, I guess in terms of a believer being bothered by doubt, but what I hear in your answer is, well, actually, we should do that regularly, whether or not we're being bothered by doubt. And maybe sometimes we're in the most danger when we are confident and complacent than when we're actually struggling with doubt. Thank you for joining us for this episode. And thanks to our donors and partners for making this possible. We publish essays on our website at anabaptistperspectives.org. We also release these essays in narrated form as their own podcast called Essays for King Jesus.


I don't believe in the story of the Garden of Eden, but sometimes I'll troll people by saying something like, the serpent did nothing wrong. You know, just for the snake of argument. You've probably been involved in a conversation where someone takes it upon themselves to play Devil's Advocate to pretend as if they disagree with some popular opinion to expose its flaws. The term comes from a discontinued practice in the Catholic Church, where a designated priest would give all the unpleasant reasons that some recently dead Saint-like person wasn't actually deserving of sainthood, just so the decision of whether to canonize them or not would be made fairly. It's an intuitive idea to manufacture dissent in situations where it seems like everyone agrees. Even if a majority of the group has secret doubts about the public consensus, if nobody's brave enough to voice an objection, those doubts will never get a fair hearing, which can lead to unwarranted confidence and disaster. What's more, groups that work through some amount of dissent while they're analyzing a problem tend to enjoy better outcomes. They cover more bases and come up with a more varied set of solutions that are acceptable to more people. A little debate seems to be a good thing. If there isn't any, why not fake it? Unfortunately, those benefits seem to evaporate quickly when the argument is artificial. A 2001 study by Nemet at all provided groups with a puzzle to solve, and compared the performance of those that were given a devil's advocate script to ones that came up with the same objections on their own. The results were striking, even with the same counterpoints to think about. Organic dissent resulted in more creative, diverse, and better solutions. It's kind of weird that there should be any difference in outcomes between genuine dissent and artificial devil's advocacy. Why should it matter if the folks who are raising objections are sincere or just playing a part? After all, the most obvious explanations for the benefits of dissent don't seem like they'd be affected by whatever the naysayer believes or doesn't believe. People still have to weigh the merits of alternatives and justify their position against criticism. From the outside, so long as the devil's advocate is playing their role effectively, it would be hard to distinguish an authentic dispute from a fabricated one. There must be something important happening when someone really believes their dissenting opinion that's not happening when they're just going through the motions. As far as I can tell from the bottom of my Google Scholar rabbit hole, there are a few different ideas about what makes a devil's advocate so much less valuable than an authentic disagreement, and I'd like to add one of my own.  Hugo Mercier and Dan Sperber suggest that our species' incredible mental faculties have evolved to make us very good at argument, which is why their thesis is called the Argumented Theory of Human Reason. According to the theory, the various forms of confirmation bias and motivated reasoning that make individuals hilariously bad at simple logic puzzles are really good for group decision-making, temporarily turning the people who feel strongest about an issue into dedicated engines of rage-fueled research and analysis, while the group looks on, weighs whatever they come up with, and eventually finds consensus or compromise between the two based on their relative strength. It's a great way to divvy up the cognitive labor of finding the best arguments for and against different plausible positions. The thing is, motivated reasoning requires motivation. If you're not actually bought into whatever position you're arguing for, if you're just going through the motions of disagreeing but your heart's not really in it, you're not going to be desperately searching for proof of your position. This is more like playful rhetorical shadowboxing, or what philosopher Harry Frankfurt terms bullshitting, speech that is unconcerned or apathetic about truth. A devil's advocate has no skin in the game. They aren't arguing for anything and won't bring any new information to the table, so the group doesn't get to reap the benefits of a committed brain doing argument stuff. Not great for improving the quality of their final decision. Now let's talk about something a little less confrontational. In episode 135 I discussed finding from cognitive science researchers Fisher et al. that the framing of an argument's goals drastically affects what the arguers get out of it. If you direct someone to argue to learn, to engage in a discussion to figure out what their opponent believes and why they believe it, they tend to walk away from the argument with an open mind, like there might be a few tenable positions a reasonable person might hold. If you tell someone to argue to win, on the other hand, to give a more convincing argument that their opponent can manage, they'll emerge from the discussion utterly convinced that there's only one way of thinking about it, their way. On its own, not that surprising, especially in the context of the argumentative theory, but it does highlight how the context of a disagreement can shape what people get out of it, perhaps even more than the arguments they end up using. When you realize that you disagree with someone who's judgment you respect, rather than scoffing at their beliefs, there's a sense of confusion and curiosity. You don't just launch into a polemic to prove that they're wrong, you want to know why they think what they think. Maybe they have some bit of information that you don't, or maybe they thought of some angle that you haven't considered yet. Whatever the reason, you want to understand whatever's going on in their heads. On the other hand, if you're on a debate team, there's no puzzle of conflicting beliefs to unravel, no information that could pass between two debaters that would change anyone's position. The disagreement is just a rhetorical game. An argument with a devil's advocate falls squarely into the second category. Someone who doesn't actually dissent, but acts like they do out of some sense of obligation, doesn't have anything going on behind the scenes that requires unpacking or figuring out. There's no fact that once revealed will suddenly clarify why they disagree or sparks some sort of epiphany that leads to consensus. The only way out of the dispute is to mount a sufficient rhetorical case for the thing that everyone already believes. We now have two halves of a potential answer for why an authentic disagreement might improve a group's decision making, but devil's advocacy? Not so much. Argument seems to be an important part of how humans figure stuff out, but someone who's just playing a role as a contrarian isn't really invested in their position and won't harness the full power of bias reasoning to make the best possible case for a minority opinion. Meanwhile, because there's nothing to learn from someone who only disagrees out of a sense of obligation, the only recourse for responding to a devil's advocate is to defend the original position well enough. Not to uncover new information, not to explore alternatives, not to compromise, just what can I say that will make this person shut up? Now, of course, when we're forced to reason things through on our own, it's important to consider alternatives and question our intuitions to be sure we're not forgetting anything. It's a good idea to listen to that little voice in the back of your head that meekly asks, uh, but what if you're wrong about that? But in a group setting, maybe it's not surprising that people get annoyed or even angry at those who feel the need to roleplay dissent. The benefits of a pro-former contrarian seem to be outweighed by the advantages of an authentic disagreement, and there are more than enough real differences of opinion without making them up for fun. What do you think? Is playing devil's advocate a pale imitation of the power of real disagreement? Does the gap between the two give any reason to question things like debate club or adversarial justice? Please, leave a comment below and let me know what you think. Thank you very much for watching.


This paper proposes a novel approach for forecasting monthly electricity consumption based on decomposition techniques followed by various time series models. First, the authors decompose the time series into three components, the long-term trend, seasonality, and stochastic component. Then, they compared the forecast accuracy of various combinations of time series models for each component. Finally, the forecasted values were combined to form the overall forecast. The authors found that the proposed modeling and forecasting framework gave more accurate and efficient results than the benchmarks. Additionally, the final forecasting models produced lower mean errors than those reported in the literature. This article was authored by Hassan Iftiker, Nadeela Bidi, Paolo Conest Rodriguez, and others.


Hi, this is George Gilbert. We have an extra special guest today on our CubeCast. Aman Neymar, Senior Vice President and CTO of DemandBase, started with a five-person startup, Spider Book, and almost like a reverse IPO. DemandBase bought Spider Book, but it sounds like Spider Book took over DemandBase. So Aman, welcome. Thank you. Excited to be here. Almost good to see you. So DemandBase is a next-gen CRM program. Let's talk about, just to set some context, for those who aren't intimately familiar with traditional CRM, what problems do they solve, and how did they start, and how did they evolve? Right, that's a really good question. So for the audience, I mean, CRM really started as a contact manager. And it was replicating what a sales person did in their own private notebook, writing contact phone numbers in an electronic version of it. So you had products that were really built for salespeople on an individual basis. But it slowly evolved, particularly with Siebel, into more of a different twist. It evolved into more of a management tool, a reporting tool, because Tom Siebel was himself a sales manager, ran a sales team at Oracle. And so it actually turned from an individual-focused product to an organization management reporting product. And I've been building this stuff since I was 19. And so it's interesting that with the products today, we're going, actually, pivoting back into products that help salespeople or help individual marketers and add value, and not just focus on management reporting. That's an interesting perspective. So it's more now empowering, as opposed to reporting. Right. And I think some of it is cultural influence of the, over the last decade, we have seen consumer apps actually take a much more predominant position, rather than traditional earlier in the 80s and 90s, the advanced applications were corporate applications, your large computers and companies. But over the last year, consumer technology is much has taken off. And actually, I would argue, has advanced more than even enterprise technology. So in essence, that's influencing the business. So even ERP was a system of record, which is the state of the enterprise. And this is much more an organizational productivity tool. Right. OK. So tell us now the mental leap, the conceptual leap that demand-based made in terms of trying to solve a different problem. Right. So demand-based started on the premise around marketing automation and marketing application, which was around identifying who you are. As we move towards more digital transaction and web, web was becoming the predominant way of doing business. As people say, that's 70%, 80% of all businesses start using online digital research. There was no way to know it, right? Majority of the internet is this dark, unknown place. You don't know who's on your website. You're referring to the anonymity and not knowing who is interacting with you until very late. And you can't do anything intelligent if you don't know somebody, right? If you didn't know me, you couldn't really ask what would you do.  And really, when we, as humans, can only communicate if you know somebody. So the innovation behind demand-based was, and it still continues to be, to actually bring around and identify who you're talking to, be it online, on your website, and now off even your website. And that allows you to have a much more sort of personalized conversation. Because ultimately, in marketing, and perhaps even in sales, it comes down to having a personal conversation. So that's really what, you know, which if you could have a billion people who could talk to every person coming to your website in a personalized manner, that would be fantastic. But that's just not possible. So how do you identify a person before they even get to a vendor's website so that you can start, you know, on a personalized level? Right. So demand-based has been building this for a long time. But really, it's a hard problem. And it's harder now than ever before, because of security and privacy. You know, lots of hackers out there, people are actually trying to hide or at least prevent this from leaking out. So in the, you know, eight, nine years ago, it was, you know, we could buy registries or reverse DNS, but now with ISPs, and, you know, we are behind probably Comcast or level three. So how do you even know who this IP address is registered to? So we would, you know, in the, about eight years ago, we started mapping IP addresses, because that's how you browse the internet to companies that they work at, right? But it turned out like that was no longer effective. So we have built over the last eight year proprietary methods that, you know, knows how companies, you know, relate to the IP addresses that they have. But we have gone to doing partnerships.  So when you log in, we do a deal and we have hundreds of partners and data providers. But now, the state of the art where we are, is we are now looking at behavioral signals to identify who you are. In other words, not just touch points with partners where they can, where they collect an identity. You have a signature of behavior. It's really interesting that humans are very unique. And based on what they're reading online and what they're reading about, you can actually identify a person. And certainly identify enough things about them to know that this is an executive at Tesla who is interested in IoT manufacturing. So you don't need to resolve down to the name level. No. You need to know sort of the profile, the persona. And that's enough for marketing, right? So if I knew that this is a C-level supply chain executive from Tesla, you know, who lives in Palo Alto and has interest in these areas or problems, that's enough for Siemens to then have an intelligent conversation to this person, even if they're anonymous on their website or if they call on the phone or anything else. So, OK, tell us the next step. Once you have a persona, is it demand-based that helps and put together a personalized profile and lead it through the conversation? Yeah. So earlier, well, not earlier, but very recently, we've been building this technology, which is a very hard problem to identify now hundreds of millions of people, I think, around 700 business people globally, which is majority of the business world. But we realize that in AI, making recommendations or giving you data in advanced analytics is just not good enough. Because you need a way to actually take action and have a personalized conversation because there are 100,000 people in your website making recommendations. It's just overwhelming for humans to get that much data. So the better sort of idea now that we're working on is just take the action. So if somebody from Tesla visits your website and they are an executable by your product, take them to the right application. If they go back and leave your website, then display them the right message in a personalized ad. So it's all about taking actions and then, obviously, whenever possible, guiding humans towards a personalized conversation that will maximize your relationship. So it sounds like sometimes it's anticipating and recommending a next best action. And sometimes it's your program taking the next best action. Because it's just not possible to scale people to take actions. I mean, we have 30, 40 sales reps in demand-based. We can't handle the volume. And it's difficult to create that personalized letter. So we make recommendations, but we found that it's just too overwhelming. So in other words, when you're talking about recommendations, you're talking about recommendations for demand-based for... Or our clients' employees or salespeople. But whenever possible, we're looking to now build systems that, in essence, are in autopilot mode. And they take the action. They drive themselves. Give us some examples of the actions. That's right. Some actions could be without... If you know that a qualified person came to your website, is notify the salesperson and open a chat window, saying, this is an executive. This is similar to a person who will buy a product from you. They're looking for this thing. Do you want to connect with a salesperson? And obviously, only the people that will buy from you. Or the action could be send them an email automatically based on something that it will be interested in. And in essence, have a conversation. So it's all about conversation and an ad. Or an email or a person are just ways of having a conversation in different channels. So there was a... It sounds like there was an intermediate marketing automation generation. After traditional CRM, which was reporting, where it was basically... It didn't work until you registered on the website. And then they could email you. They could call you. Inside sales reps, if you took a demo, you had to put an ID in there. That's still... So when demand-based came around, that was the predominant between the CRM we were talking about. There was a gap, there was a generation which started B2B marketing. It was all about formfills. And it was all about nurturing. But I think that's just spam. And today, their effectiveness is close to nothing. Because it's basically email or outbound calls. Yeah, it's email, spam. We all have email boxes filled with this stuff. Yeah. And why doesn't it work? Because not only because it's becoming ineffective, and that's one reason. Because they don't know me. Right. And it boils down to if the email was really good and it related to you, it related to what you're looking for, or who you are, then it will be effective. But spam or generic email is just not effective. So to some extent, we lost the intimacy. And with the new generation of what we call account-based marketing, we're trying to build intimacy at scale. Okay, so tell us first the philosophy behind account-based marketing, and then the mechanics of how you do it. Sure, yeah.  So if you walk into a corporation, they have these really sophisticated salespeople who understand their clients, and they focus on one-on-one, and it's very effective. So if you had Google as a client, or Tesla as a client in your Siemens, you would have two people working and keeping that relationship working because you make millions of dollars. But that's not a scalable model. It's certainly not scalable for startups here to work with or to scale your organization to be more effective. So really the idea behind account-based marketing is to scale that same efficacy, the same personalized conversation, but at higher volume, right? And take, maximize, and the only way to really do that is using artificial intelligence. Because in essence, we're trying to replicate human behavior, human knowledge at scale, right? And to be able to harvest and know what somebody who knows about pharma would know. So tell, give me an example of, let's stay in pharma for a sec. And what are the decision points where based on what a customer does or responds to, you determine the next step or demand-based determines what next step to take. What are some of those options? Like a decision tree, maybe? You can think of it, it's quite fetish in our industry now, it's reinforcement learning, which is what Google used in the Go system, AlphaGo, right? And we were inspired by that. And in essence, what we're trying to do is predict not only what will keep you going, but where you will win. So we give rewards at each point and the ultimate goal is to convert you to a customer. So it looks at all your possible futures and then it figures out in what possible futures you will be a customer. And then it works backwards to figure out where should you take you next. Wow, okay, so this is very different from the- You can plan six months ahead. So it's a planning system. Okay. Because your sales cycle's a six months ahead. So help us understand the difference between the traditional statistical machine learning that is a little more mainstream now. Then the deep learning and the neural nets and then reinforcement learning, like where are the sweet spots? What are the sweet spots for the problems they solve?  In my opinion, you can achieve a lot and solve real world problems with simpler machine learning algorithms. In fact, for the data science team that I run, I always say start with the most simplest algorithm. Because if the data is there and there's you have the intuition, you can get to a 60% F score or quality with the most naive implementation. 60% meaning you- Like accuracy of the model. Like confidence model, okay. But how good the model is, how precise it is. Okay. And sure, then you can make it better by using more advanced algorithms. The reinforcement learning, the interesting thing is that it's ability to plan ahead. Most machine learning can only make a decision, they're classifiers of sorts, right? They say, is this good or bad or is this blue or is this a cat or not, right? They're mostly Boolean in nature or you can simulate that and have multi-class classifiers. But reinforcement learning allows you to sort of plan ahead. And in CRM or as humans, we're always planning ahead. A really good salesperson knows that for this stage opportunity or for this person in pharma, I need to invite them to the dinner because their friends are coming and they know that last year when they did that, then in the future, that person converted, right? If they go to the next stage, so it plans ahead the possible futures and figures out what to do next. So for those who are familiar with the term AB testing and who are familiar with the notion that most machine learning models have to be trained on data where the answer, the answer exists and then they test it out on, well, they train it on one set of data where they know the answers, then they hold some back. And test it and see if it works. So how does reinforcement learning change that? I mean, it's still testing on supervised models to know it can be used to derive. You still need data to understand what the reward function would be, right? And you still need to have historical data to understand what you should give it and you sure have humans influence it as well, right? At some point, we always need data, right? If you don't have the data, you're nowhere, right? And if you don't have, but it also turns out that most of the times there is a way to either derive the data from some unsupervised method or have a proxy for the data that you really need. So pick a key feature in demand base and then where you can derive the data you need to make a decision, just as an example. Yeah, that's a really good question, right? We derive data as all the time, right? So let me do something quite interesting that I wish more companies and people used is the internet data, right? The internet today is the largest source of human knowledge and it actually knows more than you could imagine. And even simple queries, so we use the Bing API a lot, right? And to know, so one of the simple problems we ran into many years ago, and that's when we realized how we should be using internet data, which in academia has been used, but not as, and it's not as used as it should be. So you can buy APIs from Bing and I wish Google would give their API, but they don't, so that's the next best choice. We wanted to understand who people are. So there's their common names, right? So George Gilbert is a common name or Alan Fletcher who was my co-founder and is that a common name? And if you search that, just that name, if you get that name in various contexts or co-occurring with other words, you can see that there are many Alan Fletchers, right? Or if you get versus if you type my name, my name, you will always find the same kind of context. So you'll know it's one person or it's a unique name. So it sounds to me that like reinforcement learning is online learning where you're using context, it's not perfectly labeled data. Right. And I think there is no perfectly labeled data. So there's a misunderstanding of data scientists coming out of perfectly labeled data courses from Stanford or whatever machine learning program. And we realized very quickly that the world doesn't have any perfect labeled data. Then we think we're going to crowdsource that data. And it turns out we've tried it multiple times and after a year, I realized that it's just a waste of time. You can't get 20 cents or 25 cents per item, workers somewhere and wherever to label data of any quality to you. So it's much more effective to, and we were a startup so we didn't have money like Google to pay. And even if you have the money, it generally never works out. We find it more effective to bootstrap or use unsupervised models to actually create data. Help us elaborate on that. Yeah. The unsupervised and the bootstrapping where maybe it's sort of like a lawnmower where you give it that first, that's right. You know, tug. I mean, we have used it extensively. So let me give you an example. Let's say you wanted to create a list of cities, right? Or a list of the classic example, actually it was a paper written by Sergey Brin. I think he was trying to figure out the names of all authors in the world and this is 1998, right? And basically if you search on Google, the term has written the book, right? Right, just the term has written a book. These are called patterns or Hearst patterns, I think. Then you can imagine that it's always preceded what a name of a person was an author. And so George Gilbert has written the book and then the name of the book, right? Or William Shakespeare has written the book X. And you'll see it with William Shakespeare and you get some books or you put Shakespeare and you get some authors, right? And then you use it to learn other patterns that also co-occur between William Shakespeare and the book, you know, and then you learn more patterns and you use it to extract more authors. And in the case of demand-based, that's how you go from learning, starting bootstrapping within, say, pharma terminology and learning the rest of pharma. And then using genetic terminology to enter an industry and then learning terminology that we ourselves don't understand. Yet it means, like, you know, for example, I always use this example where, you know, if we read a sentence like, Takeda has inlicensed a molecule from, you know, Roche, it may mean nothing to us, but it means that they've partnered and bought a product, right, in pharma lingo. So we use it to learn new language and it's a common technique. We use it extensively, but so, you know, it goes down to, while we do use, you know, highly sophisticated algorithms for some problems, I think most problems can be solved with simple models and, you know, thinking through how to apply domain expertise and data intuition and having the data to do it. Okay, let's pause on that point and come back to it because that sounds like a rich vein to explore. So this is George Gilbert on the ground at Demand Base. We'll be right back in a few minutes.


ABA's success with autism has a long history and continues to be one shining example of the application of the science. You may wonder why that is. Just what is the reason that ABA has been so successful for people with autism? Before I answer that, let us digress further into some other areas of success. ABA has been applied across the mental health field and has a long history of being used to help those with other disorders as well. Individuals with schizophrenia, ADHD, Down syndrome, diabetes, depression, anxiety, addictions, and eating disorders have all benefited from the application of behavior analysis. The successes in these various areas are for the same reasons we have been extremely successful in the educational settings, from teaching children to read or teaching basic and advanced arithmetic skills, or complex scientific topics, or helping struggling students catch up to and exceed their peers. Our tools have been applied, studied, verified, modified, and re-applied. Have you heard of Head Sprout? It is an award-winning tool to teach the skill of reading its behavior analysis. Many other commercially available and widely used educational programs are developed by behavior analysts and based on the principles of behavior analysis. Further, the What Works Claring House is developed by the Institute of Education Sciences and comprises scientifically supported academic interventions for all topics. And we identify basic ABA principles in many of those interventions. So why is it that applied behavior analysis is used so widely and works so well? It's simple. Behavior analysts take careful observational data. The data are also carefully reviewed for patterns and trends. Feedback is then given to individuals and programs are designed for each person and modified based on the individual's own performance, preferences, and needs. For example, people with autism who have trouble communicating have a program designed just to focus on one thing at a time and will receive support tailored to their individual needs, just like a person who has trouble using a cell phone while driving or getting enough exercise. That support comes from a direct observation and analysis of objective and individualized data, not from guesses about what is happening or why. This evidence-based approach is exactly what makes ABA different. You see, in behavior analysis, there is no need to search for labels or diagnoses, only a search for why people behave the way they do, and an application of the findings that help a person reduce the obstacles in their world and meet their goals. While ABA has had a profound effect on the lives of people diagnosed with autism, the next time you hear about ABA, we hope you also think of the other areas ABA has successfully used, including education, goal setting, and behavior change in general. More importantly, we hope you think about improving the quality of life for all.


Everybody forced here ripping 2021 flawless football hobby 1 box number 45 left side serial numbers I'll show the results here. There's a link in chat. You can always find the late in sports cards calm I'll be calling out whose hit is who just we go along as well You bring them you bring them Mike that's what happens There's no trading so yeah, I would I would guess you just get the you would just get the $10,000 shopping spree online I guess There's no there's no trading prizes or switching there's like stipulations and that stuff Hey, there's one where you get to have dinner with us Very romantic dinner. I might add You just have to go out of Mike I guess Yeah, you guys get to have Taco Bell with us pizza hook All right, here we go Yeah, one of the prizes is an entrance into the One spot and super will make sure this year which last year would have been worth 14 and a half K Another one is one almanac spot per almanac runs a one spot in every almanac for a calendar year Dual patch three out of ten is Jamal Charles three spot with the first hit Jason S Heck yeah Vaughn Group of on now. Yeah Three of ten triple patch Barry Sanders Jason S again nice Barry Those Charles were game-worn, I don't think the Barry will be those Charles were game-worn Alan Fannica career progressions auto 8 of 15 eight spot is James M. Alan Fannica couples massage with rich Rookie signature glove Travis ETN junior for a 15 Congrats to the four spot great hit here That's Dean Dean.  That's sweet patch auto numbered 14 to 15 Jerry Judy 14 spot Where are you 14 spot Matt a I? Don't know Shane. I don't know laundry tag patch auto captain Kirk Two out of three big hit two spot. That's Anthony V Kirk Cousins dude nicest auto in the game. Heck. Yeah, dude. That's beautiful Player worn laundry tag auto big laundry tag The box so far and nice a Derek car auto numbered three of three Jason. You are crushing it with the three spot Nice car DC Really good inner box for sure Let's see we've got a diamond gem one out of ten for the Lions or not for TJ Hawkinson one spot is Daniel K Hawkinson one spot again quad rookie laundry tag Javons. Hey Williams Out of three the one spot Daniel K Very nice. There's a diamond guarantee for that Hawkinson And on the back We've got Jumbo patch auto booklet Aaron Rogers boom Seven of seven Lucky number for Andrew H That's gotta be a nameplate I would guess the RO. Yeah, I Think I'm not a hundred percent sure I would guess that but monster hit there on the back seven to seven on the a-rod Really good box, man What's a back pretty darn good that will do it we got one more one boxer coming up next. Thanks everybody


Hello my dear friends and welcome back to Plants in Lucia. My name is Lucia and these are Danila and Gaia and today we are going to be grafting a moon cactus. Okay, coming up. Okay my friends, so according to my book Root Nurture Grow, which I love to use for all my propagation projects, grafting is a technique that we use to attach one plant to another plant. So we usually use this technique to attach for example fruit trees, different types of fruit trees or plants, or actually cacti. And a very good example for this is the moon cactus. So the moon cactus actually has a base cactus and a top cactus. This top part is actually grafted to the base and it cannot survive by itself. So it has to be attached to the base. One interesting thing about this is that the top cactus actually will produce babies. So I can show you there. Here's our babies here on the side, right there, and we can actually detach these babies and graft them to another base cactus. And then these babies will grow as big as this one and produce more babies. So when I learned about grafting, I thought, okay, I really gotta try this.  And I will take you step by step in the process. So now, let's see what we need to graft our cactus. Okay, so in order to graft our cactus, we will need our moon cactus with babies, of course. And make sure that you water this cactus three days before you graft it. Our base cactus, we're gonna graft the top. Now this one was actually a moon cactus, but it was actually standing in bright direct sunlight. So the top got burned. So what I'm gonna do today is I'm gonna cut it and graft a new top. Some hydrogen peroxide to clean our tools, a sharp cutter, scissors, and rubber bands or a string. Okay, so now let's get to grafting. So the first thing that we will do is clean our knife with hydrogen peroxide or you can also use rubbing alcohol. Okay, so now we're gonna cut our baby here. Okay, so I'm gonna try to detach it like this just so I don't cut my hand. Maybe just trying to make that is breaking a little bit. Yeah, there we go. As you can see, you can see actually there how it was attached. This cactus right here, it was attached to the other one. And there you go, the other one is right there. So I think the previous top was really attached to this one, so I had to go really low. And what we're gonna do now is actually connect it to this circle right here in the center. But before we connect it, we need to smoothen it out. So I'm going to try to cut a little bit so I can smooth, I can make it smooth. I'm gonna try really softly. Now with force, we're just trying to go slowly. Okay, so now we're gonna cut this one so we can actually find the same center to connect with the base. And I don't know if you can see it, but there is a circle right here in the center. So we're gonna connect this circle with this circle here. But before that, we're just gonna have to put a little bit more angles in this here. Okay guys, and now let's attach the circle to the circle here. Like so. So I'm gonna take this one out of the decorative pot now. And this is where we use our string. The string is gonna help us keep this one on its place. So let me show you, we're gonna go like this. We have it my friends, we have attached our first moon cactus to the base together. This is the first time that I do it. So I'm gonna keep a very close eye on it and I will let you know the progress on Instagram and whether it works or it doesn't. I hope that it actually attaches and I will let you know. Also, let me know how it goes for you and if you have any tips, just comment below so we can all learn together. And as always, I will see you in the next video. Okay.


Hi everyone, I'm Joe for JaspysCaseRakes.com with another wax party break. Nice, we'll do that giveaway randomizer at the end. But first, maculate break, the maculate basketball one box number 39, the second to last box of this case. And if you're watching live, the last box has been loaded up if you want to finish this case off tonight. Big thanks to everybody here, thanks to the people who bought their spots straight up. Congrats again to the people who won spots in the filler. All 30 basketball teams are in high risk, high reward. Let's see what happens. Let's randomize names and teams one and a six, seven times. One, two, three, four, five, six, and seventh and final time. After seven we got Nick down to David. One and a six, seven times for the teams. One, two, three, four, five, six, and seventh and final time. Good luck. We got the Pistons down to the Pacers after seven.  Nick you got my Lakers, Kevin with the Sixers, David with the Blazers, Jose with the Kings, Carl with the Raptors, David with the Minnesota Timberwolves. Nick with the Miami Heat, Jimmy with the Jazz, Buntai with the Knicks, Nick Smith with the Rockets and Cavs, David, you got the Warriors, last but not the Mojo, Nick with the Spurs, Carl with the Bucks, Canard with the Nets, Kevin with the Gris, Michael with the Clippers and Celtics, Nick with the Bulls, John with the Wizards, Nick with the Mavs, Michael with the Suns, Nick with the Hawks, and David with the Pacers. Let's alphabetize this by team name and we're going to pause the video. When we come back we're going to see if there's any trades and then we'll have that one box break. Stick around, BRB. All right, welcome back. No deals were done so that list remains the same. Thanks everybody for getting in and so we got two boxes left in that case so let's select that die and we'll go one, two, three for the top box, four, five, six for the bottom box. Six, one, two, three, four, five, six for the top box will be for random team 4-0, which is already on the side right now.  There's a redemption in the middle. I was like, this box looked a little shallow. So there's a redempt in the middle. Good luck. Blank card behind the end. This is a wax party break, too. All right, 47 out of 49, CJ McCollum, Portland edition. This will go to David. He's been looking good with the the Palakins. We've got a quad relic. It's a randomizer. Tyrese Halliburne. Emanuel Quickley. Tyrese Maxine. Cole Anthony. It's a nice quartet there. Three out of 25. So there'll be one person happy, three people sad. Are these all guards? Is that the connection? All right. Another randomizer. James Weissman. Obi-Toppin. Patrick Williams. One person happy, two people sad. 38 out of 49. The redemption is going to be premium patch autographs red. Anna Lewis Jr., I believe is a pelican. Yeah, he's a pelican. So another pelican for Nick Smith. Couple more here. We've got Danilo Gallinari. 18 out of 25 modern marks autograph for Nick Smith and the Atlanta Hawks. Nice. And the last one here is going to be... What do we got here? What do we have? It's a nice patch, nice Otto, Jordan and Wara. 23 out of 50. This rookie, this patch, this autograph. Going to Carl. There you go, Carl. And that's that boys and girls. So let's do some randomizing. We'll use one dice roll for all of the lists. Flip over here for a second. Let's do the triple first. Golden State Warriors. James Weissman. Obi-Toppin. New York Knicks. Patrick Williams. Chicago Bulls. The next one will be Tyrese Halliburton. That's still King's edition there. Emmanuel Quickley for the Knicks. Tyrese Maxi. Philadelphia. Cole Anthony. Orlando. And then everyone gets a shot at the one wax party spot. So let's gather up your names again. Put you in the last blank list here. All right. One dice roll for all three randomizer lists. And it's going to be four and a two, six times. Four and a two, six times. One, two, three, four, five, and a sixth and final time. After six, the triple relic is going to go to Chicago. So that will be for Nick Smith and the Bulls. Nice run for Nick Smith in this break. All right. The quad relic. Four and a two, six times once again. Good luck. One, two, three, four, five, and a sixth and final time. After six goes to Orlando. And that will be for Petra in Orlando. It's the quad relic. 25. And the wax party giveaway part. So once again, four and a two, six times. Good luck. One, two, three, four, five, and a sixth and final time. That's a tough one. There can only be one winner. So a huge congratulations to the name on top. Michael just on the outside looking in. Sorry. Get him next time. Name on top though is happy times for Nick Smith. Thanks for your break. Congrats to you with a spot that you won in the filler. Your name's on top. You're guaranteed something in our wax party promo. Check out the details on jazpiececasebrakes.com. Congrats again. We'll see you next time for the next break. Bye-bye.