Income tax 2022-2023, makers depreciation, which property class applies under GDS otherwise known as General Depreciation System. Let's do some wealth preservation with some tax preparation. Most of this information comes from Publication 946, how to depreciate property tax year 2022. You can find the IRS website, irs.gov, irs.gov.gov. Support Accounting Instruction by clicking the link below giving you a free month membership to all of the content on our website broken out by category further broken out by course. Each course then organized in a logical, reasonable fashion making it much more easy to find what you need than can be done on a YouTube page. You can also include added resources such as Excel practice problems, PDF files and more like QuickBooks backup files when applicable. So once again click the link below for a free month membership to our website and all the content on it. The income tax formula noting we're online one income remember and the first half of the income tax formula is in essence and income statement. Although just an outline of scaffolding other forms and schedules rolling in flowing into these line items. One of those the schedule C which has business income minus business expenses gives us the net business income. Schedule C net income in essence flowing into line one income of our income tax formula page one of the form 1040. Remembering the schedule C flows into the schedule one which flows into the first page of the form 1040 line number eight. The schedule C is called the profit or loss from business income statement format having income minus expenses. We're focused on the expenses here and more particularly more precisely on the depreciation expense. Remembering that as you have property planting equipment, even if you're on a cash based system, you're going to have to do an accrual concept thing. Put it on the books as an asset in essence allocating the cost then over its useful life from an accounting standpoint. That would be in order to try to match the use of the item and the expense related to it reflecting that usage in the same period that the income was generated from the usage of the item. Although of course the tax code is a little bit strange because the tax code sometimes follows accounting concepts but then deviates from them possibly using accelerated depreciation methods which still kind of line up with accounting concepts but possibly also using things like a 179 deduction or special depreciation that are more economically driven and politically driven items. Our goal as taxpayers is to try to usually get the deduction as early as possible. So we want the biggest deduction as early as possible with the cost of equipment. That would mean it's a big purchase item. We would like to deduct it sooner rather than later if the tax code lets us do that. That said, we touched on the property classes last time. We're going to review that and then go into them in more detail. So which property class applies under GDS? GDS is the general depreciation system under makers. These are some of the most common kind of classifications. So the following is a list of the nine property classifications under GDS and examples of the types of property included in each class. Now remember when we look at the tax code, we are more restricted in terms of having to categorize whatever type of equipment we have in particular classes. The tax code needing to be more restrictive because we have an incentive on the tax side of things to try to take the depreciation sooner which is different than the incentives we have on the financial statement side of things which for large companies might be governed by generally accepted accounting principles. Okay, so these property classes are also listed under column A in section B of part three of form 4562.  The thought process usually looks something like this. You say, hey, is this something, usually a large dollar item, something that I should be expensing or should I put it on the books as an asset? If you're going to put it on the books as an asset and then need to depreciate it, then the question is, well, what's the classification that I'm going to be using to be recording the depreciation? There could be a difference between the book basis you're going to be using and the tax basis that you're going to be using and the tax software often has the capacity to do that difference to do both of those calculations. So small businesses that are also faced with the question of do I want a different depreciation structure for book versus taxes, which you may want because the book depreciation is more accurate for the purpose of bookkeeping. Whereas the tax depreciation, your objective, of course, is to take as much depreciation as possible as soon as possible, usually in order to maximize your tax benefits. So you might want to discuss that, the pros and cons with a tax professional related to that. Any case for details information on property classes, see Appendix B, Table of Class Lives and Recovery Periods in this publication. Okay, so common classifications. We've got the three-year property, the three-year property, tractor units for over-the-road use, any racehorse over two years old when placed in service. Obviously, racehorses were probably a bigger thing back in the day, but I'd still like to have a racehorse that I can bring on out to the old track. Any case, any other horse other than a racehorse over 12 years old when placed in service and qualified rent to own property defined later. Then we've got the five-year property, another very popular category. We've got, of course, the automobiles, taxis, buses, and trucks, which are quite popular depreciable type of items, which might have their own special kind of rules related to depreciation we talk about in a future time. Any qualified technological equipment, office machinery such as typewriters, calculators, copiers, another quite common categorization. Any property used to research and experimentation, breeding cattle and dairy cattle, appliances, carpets, furniture, et cetera, used in a residential rental real estate activity. Also, you would think fairly common categorization, certain geothermal, solar and wind energy property, and any machinery equipment other than any grain bin, cotton gin, asset fence or other land improvement used in a farming business and placed in service after 2017. In tax years ending after 2017, the farming situation, remember, have their own often kind of rules and regulations due to the special area of farming. So if you deal with farming, then you might, you can specialize in that area, for example. Number seven year property, another common category where we have office furniture and fixtures such as desks, file cabinets, saves, very common. Used agricultural machinery and equipment placed in service after 2017, grain bins, cotton gin, and assets, and fences used in farming business, railroad track, any property that does not have a class life and has not been designated by law as being in any other category. Clearly, when we look at these categorizations, you might be thinking, well, this is, this is a daunting task because there's no way the IRS can completely identify everything that some business might use, given the fact that businesses are all different and whatnot. So you're going to have to have this kind of catch all type of category as they're trying to differentiate things. So if you don't find something that fits into a particular category, sometimes you might need to do more research on it, possibly going from the code itself to other resources to see where that would lead in terms of the proper categorization. So certain motor sports entertainment complex property and any natural gas gathering line placed in service after April 11, 2005, see natural gas gathering line and electric transmission property later. Then we've got the 10 year property. So vessels, barges, tugs, and a similar water transportation equipment, which for most people would be more of a specialized type of area. Notice we're getting into the longer depreciation lives here with the 10 year property. Most of like the equipment stuff would fall under these main categories. These are the three, five, and seven years are probably the most common, right? So now we're going out to 10 year. Vessels, barges, tugs, and then we've got any single purpose agricultural or hydro agricultural structure. Any tree or vine bearing fruits or nuts and qualified small electric metter and qualified smart electric grid system defined later placed in service on or after October 3, 2008, somewhat more specialized categories there. Then we've got the 15 year property. So certain improvements may directly to land or added to it. So these are going to be the improvements to land 15 years somewhat. You might see that fairly, you know, could be fairly more common, such as shrubbery fences, roads, sidewalks and bridges. Any retail motor fuels outlet defined later, such as convenience store, any municipal wastewater treatment plant. So that's a specialized thing there. Initial clearing and grading land improvements for gas utility property, electric transmission property. It gets kind of messed up when I have it all one word on three lines there. Property that is section 1245 property used in the transmission of 69 or more kilovolts of electricity placed in service after April 11, 2005. So we're getting quite specific. If you fall into that category, you can see natural gas gathering line and electric transmission on property later. Any natural gas distribution line placed in service after April 11, 2005 and before January 1, 2011, any telephone distribution plant and comparable equipment used for two way exchange of voice and data communications, qualified improvement property defined later placed in service after 2017. Moving up to 20 year property now, 20 year property, farm building, other than single purpose agricultural or heterocultural structures, municipal sewers not classifies as 25 year property. And then we've got initial clearing and grading land improvements for electric utility transmission and distribution plants. 25 year property. This class is water utility property, which is either of the following property that is an integral part of the gathering treatment or commercial distribution of water. And that without regard to this provision would be 20 year property, municipal sewer other than property placed in service under a binding contract in effect at all times since June 9, 1996. So highly specialized category there, possibly not applying to a lot of people. Then we get into the items which a lot of people might see a little bit more, which is the residential rental property. So this is any building or structure such as rental home, including a mobile home, if 80% of more of its gross rental income for the tax year is from dwelling units. And now you've got the rental property, a dwelling unit as a house or apartment used to provide living accommodations in a building or structure. It does not include a unit in a hotel, motel or other establishment where more than half the units are used on a transient basis. So the residential rental property is going to be of course a more common kind of thing because people might own property if you're doing usually higher income tax returns. We're going to distinguish them from the hotels and motels, which sometimes can be somewhat of a gray area that you'd have to parse out. So if you occupy any part of the building or structure for personal use, its gross rental income includes the fair rental value of the part you occupy. So then we end up with the situation where we could have structures that have multiple uses to them and you would expect then that you would have to do some kind of allocation method. We might dive into that more obviously rental property as its own animal, its own beast that we can dive into and possibly will in future courses or sections. Nine, non-residential real properties or non-residential. This is section 1250 property such as an office building, store or warehouse. So you might be rented it out or something like that, but it's not for residential or personal use, but rather non-residential. When I say personal use, I mean rented it out to like families versus non-residential to 1250. So this is section 1250 property such as office building, store or warehouse that is neither residential rental property nor property with a class life of less than 27.5 years. Next we have the category of qualified rent to own property. Qualified rent to own property is property held by a rent to own dealer for purposes of being subject to a rent to own contract. So now you've got the contract which is a little bit different than normal. Usually you have a rental contract where the property is going to be going back to the original person that's renting it. Or you have a contract that you're purchasing something possibly financing the purchase, but the loan is different than the bank doesn't own the property. They have a financing to the property. Now you have a contract which is a rent to own type of contract. So it is tangible personal property generally used in the home for personal use and includes computers and peripheral equipment, television, video cassette recorders. That's kind of an old stereos, camcorders, appliances, furniture, washing machines and dryers, refrigerators and other similar consumer durable property. Consumer durable property does not include real property, aircraft, so the real property would be the actual structure of the building, aircraft, boats, motor vehicles or trailers. My trailer is your trailer. So if some of the property you rent to others under a rent to own agreement is of a type that may be used by the renters for either personal or business purposes, you can still treat this property as qualified property as long as it does not represent a significant portion of your lease of your leasing property. However, if this dual use property does represent a significant portion of your leasing property, you must prove that this property is qualified rent to own property. So somewhat of an unusual kind of structure with the rent to own rent to own dealer. So you are a rent to own dealer if you meet all of the following requirements. You regularly enter into rent to own contracts defined below in the ordinary course of your business for the use of consumer property. A substantial portion of these contracts end with the customer returning the property before making all the payments required to transfer ownership. The property is tangible personal property of a type generally used within the home for personal use. Rent to own contract. So this is any lease for the use of consumer property between rent to own dealer and a customer who is an individual which meets all the following requirements. Is title rent to own agreement lease agreement with ownership option or other similar language provides a beginning date and a maximum period of time. Not to exceed 165 weeks or 36 months from the beginning date for which the contract can be in effect including renewals or options to extend provides for regular periodic weekly or monthly payments that can be either level or decreasing. If the payments are decreasing no payment can be less than 40% of the largest payment provides the total payments that generally exceed the normal retail price of the property plus interest provides for total payments that do not exceed $10,000 for each item of property. Provides that the customer has no legal obligation to make all payments outlined in the contract and that at the end of each weekly or monthly payment period. The customer can either continue to use the property by making the next payment or return the property in good working order with no further obligations and no entitlement to a return of any prior payments. Provides the legal title to the property remains with the rent to own a dealer until the customer makes either all the required payments or the early purchase payment required under the contract to acquire legal title. And finally provides that the customer has no right to sell sub lease mortgage pawn pledge or otherwise dispose of the property until all contract payments have been made. Okay motor sports entertainment complex again somewhat of an unusual category here with going through kind of the main ones at this point. So this is a racing track facility permanently situated on land that hosts one or more racing events for automobiles trucks and motor motorcycles during the 36 month period after the first day of the month in which in which the facility is placed in service. So the events must be open to the public for the price of admission. Okay admission $20. Then we've got the qualified smart electric grid system. Once again probably not the category that most people are dealing with more of a specialized categorization here. A qualified smart electric grid system means any smart grid property used as part of a system for electric distribution grid communications monitoring and management placed in service after October 3. 2008 by a taxpayer who is a who is a supplier of electric electrical energy or a provider of electrical energy services. Smart grid property includes electronics and related equipment that is capable of sensing collecting and monitoring data of or from all portions of a utilities electric distribution grid providing real time two way communications to monitor or to manage the grid and providing real time analysis of an event prediction based on collected data that can be used to provide electric distribution system reliability reliability quality and performance. Now again obviously these categories are getting more abstract now and you can see one of the issues with the tax code that they have as they try to basically kind of force people to do the categories. For every basic item so then the categorizations become quite complex. However it does mean that you should be able to basically research the category of the item that you're looking for and properly find the category which is what's going to happen. In most cases so oftentimes the categories that come up most often you'll have an idea of the types of businesses you work with often you'll have an idea of the categories that are less common. You should be able to research and find the category the proper category. So retail motor fuels outlet. Real property is a retail motor fuel outlet if it is used to a substantial extent and the retail marketing of petroleum or petroleum products whether or not it is used to sell food or other convenience items and meets any of the following three tests. It is not larger than 1400 square feet 50% or more of the gross revenue generated from the property are derived from petroleum sales 50% or more of the floor space is property and devoted to petroleum marketing sales. A retail motor fuel outlet does not include any facility related to petroleum and natural gas trunk pipelines. Okay so qualified improvement property. This is one that may come up more often than some of the more abstract kind of categories we've seen here. Generally this is any improvement to an interior part of a building that is non residential real property and the improvement is section 1250 property. That's the property that's non residential is made by you and is placed in service by you after 2017 and after the date the building was first placed in service by any person. However, a qualified improvement does not include any improvement for which the expand expenditure is attributable to any of the following the enlargement of the building any elevator or escalator. The internal structure frame structural framework of the building. Okay so then we got the qualified smart electric meter that once more more of an abstract kind of system here a category that might be not be as common to most people. So a qualified smart electric meter is any time based meter and related communication equipment which is placed in service by a supplier of electric energy or a provider of electric energy services and which is capable of being used by you as part of a system that meets all of the following requirements. I won't go through all of the requirements for that one here because somewhat more abstract. We then have the natural gas gathering line and electric transmission property also more of an unusual type of property. I'm not going to go through the description because that's going to be more of an unusual property as well.


How was that as you dealt through it? And how do you think Dylan maybe did stepping in for you? Yeah, it's one of those things where if somebody gets it, it's like most sicknesses that are contractable. If someone gets something and they're around other people, sorry, then it seems like a lot of people you're around are also gonna get it. So a lot of those guys who have it or have had had it are doing really good. And as far as Dylan goes, I'm super proud of him. He works extremely hard every single day. And I called him right after the game, we went over the game, we talked about it, things he could have done better, things he did well, and I'm very proud of Dylan. Taylor, I think you guys can win the division for two years in a row for the first time since the 60s and make three playoffs the first time since the 90s. What's that kind of say about maybe what you and some other guys have kind of brought to the franchise over the last several years? You know, I think when the franchise first got here in the late 90s, those guys had an instilled culture of toughness and they, you know, those guys laid the foundation for us. Guys like Eddie George, guys like Bruce Matthews, those guys kind of gave the heart of the Tennessee Titans. And I don't, like there's been players that have come and go since then. A lot of players that have come and go. And just to be a part of something to start, I say it all the time, being a person that started two and 14, three and 13 and be able to, you know, stay on a team for this long and to be a part of, you know, a winning culture or a team that expects to win weekend and week out. I think it's really special. It says a lot about the players that are here. It says a lot about the past players that were here. Also that kind of built the culture up. What's that expectation to win? Is it knowing that there's a division tied along on the line this week with a win? Has it been kind of business as usual? Or guys? Yeah, I think you got to, and you just got to cancel out all the at the end of the day. You got to play football and you can't think, well, if this happens and if this team does this, then we're at this seat, it's not worth thinking about. I'll leave that up for the Twitter warriors out there and all those people, you know, you guys, this is your job to speculate and do all that. This is your job. My job is to go out here and play football and just try to win as many games as possible. Miami's defense, they're so good. Oh, ladies first, dude. Ladies first. I'll be nice. Go ahead. My God. I just want to say with the fans and just how this fan base has continued to build, I mean, what have you seen out of them in the last couple of years? I know last year, no fans with COVID for the most part. But I mean, has this grown? And I know you have a love, weird relationship with them too. No, I love the fans. I do, even the ones that hate me. I love them all. You know what I'm saying? Because the haters wish they were doing what I was doing. So I think that, you know, when I first got here, you couldn't pay somebody to come do a Titans game. And we're getting there. And you know, to be a fan of something, you have to be proud of it. And I think we've done a good job of continuing to make fans proud of this franchise. I think Vrable's done a great job. I think John's done a great job. And so as we continue to do that, these younger kids, this younger generation who's growing up, wishing they were Kevin Byer, wishing they were Taylor Lawan, or Jeffrey Simmons, or Derek Henry, it gives, they get to grow up and come to games. And I think we're not only gaining fans now, but for the future to come. Sorry, again, wow, I'm over that. For the future, like I really hope that Nissan Stadium is one of those, man, it sucks to play there type places. And we're getting there. In the same vein. I'm a war for Taylor. Did you hear the Logan Ryan stuff? Yeah, I did. And, you know, first let me say, I'll let Robbie's tripping about this one. He's nervous. So let me, I have so much respect for Logan Ryan. And when I talk about the culture of this team and where this team was and where it's going and where it came from, Logan is one of those key players that helped change the culture of this team. And I think if we all look, look at everything with an unbiased opinion, when Logan first got here, there wasn't a lot of people in the stands. Now, because of Logan and other guys, there are now more people coming in these stands. So the fans that are upset are the die-hard fans who have been supportive and have been there since the late 90s that have had season tickets for the whole time that times have been here. They have every right to be upset, but that comment's not directed at you. You know, as a younger franchise, we have grown and grown and grown and grown and continuing to make this great city of Nashville more proud of a football team. And so, although there are harsh words, it's still, we're a growing franchise and the loyal fans and they know who they are, they shouldn't be mad about those comments because those comments aren't directed at them. You know what I'm saying? You know what I'm saying?   Yeah. I think guys were more focused on what they were doing in the off season at that time. You know, they weren't too focused on ball. I think that's changed quite a bit around here. Now, like I said, it's a generalization. Not everybody was like that, but you know, when you have a home game, you want the home game to be loud and obnoxious when your defense is on the field and we're getting there and it's loud. And you can see that some of these guys are jumping off sides and the fans are getting loud and Matt, our new PA guy, he's done a great job of getting the fans hyped up.


My daughter died at 23 years old.  I can make you a painting Okay, so these colors represent something and I hope it means something to you Yellow means happiness and trying to see the optimistic things in life green means growth growth in your chaos White means clarity within this chaos and finally black means power Elegance because those things don't define you and you can overcome all of those things. So let's get this isn't going out to you Hope you like it. Stay strong. Stay optimistic


Hi, everybody. Good morning. Thrilled to be here. And this is my first word camp, but I'm a longtime user and a longtime friend of Matt Mullenweg and much of the team. So it's great to be here. I'm a design professor. I'm a professor of ethics and computational technologies. And I'm also the senior associate dean for research at Carnegie Mellon University. And questions about ethics are very, very big there. In fact, I think in the last year, ethics has been a booming topic in tech. And it might be something that you've heard about. Perhaps it's one reason you're here. But I wanted to talk a little bit about what the trolley problem is. And the trolley problem is this. Is anyone familiar with it? Who here has heard of the trolley problem? OK. So for those of you not familiar, it goes like this. You are that guy operating a switch. And there's a trolley heading down the track. And if you do nothing, your trolley is going to run into five people and kill them. But if you throw the switch, you're going to move the trolley onto a different spur.  You'll kill one person instead. So what's the right thing to do? What do you do? Who lets the trolley go?  Is there anyone who would do that? It's kind of hard, right? Who's going to do the one person? Who feels good about that choice? Nobody. So again, the question of what the right thing to do is a big concern. And this particular question was originally formulated by two female philosophers. First by Philippa Foote in 1967. And then it was augmented by a woman named Judith Gervis Thompson, who is a professor of philosophy at MIT. And Judith Gervis Thompson made it more difficult. She also made a trolley problem situation where you can stop the trolley by throwing a large man off of a bridge. She also points out things like she does other versions of it. Like a brilliant transplant surgeon has five patients, each in need of a different organ, each of whom will die without that organ. Unfortunately, there are no organs available to perform any of these five transplant operations. But a healthy young traveler just passing through the city the doctor works in comes in for a routine checkup in the course of doing the checkup the doctor discovers that his organs are compatible with all five of his dying patients. Suppose further that the young man were to disappear. No one would suspect the doctor. Do you support the morality of the doctor to kill the tourist and provide his healthy organs to the five dying people and save their lives? What do you think? No. So we use these questions to talk about the interactability of some of the decisions that we're making around technology and around trade-offs and life and death. Is anyone here a fan of the good place? And those of you who know the trolley problem, is it because you know it because of the good place? Yeah. It's a particularly funny, great episode. If you're not familiar with this TV show, it's a wonderful TV show about ethics starring Ted Danson as the architect. It also turns out that there are trolley problem memes. They started out on 4chan. There's a Facebook group full of trolley problem memes. You see memes like this. There's nothing you can do to save the people. However, the lever you stand next to controls music playing from the boom box attached to the trolley. If you pull it to your left, it plays All Star by Smash Mouth. But if you pull it to your right, it plays any random song. You can only pull it once, and if you don't pull it, it defaults to All Star.  There's a trolley problem mug, trolley problem guy mug. If I could find this, I would be super delighted. And I want to point out that we also talk about things. Actually, I'm going to jump back to this. I'm going to, these are slightly out of order. So I'm going to come back to that in a second. This is one of my favorite things in the world. It's a two-year-old's answer to the trolley problem. Ready? Uh-oh, Nicholas. This train is going to crash into these five people. Should we move the train to go this way, or should we let it go that way? Which way should the train go? You may not have heard it because you were laughing, but he's saying, uh-oh. What's the trolley problem is a way to talk about these ethical conundrums? And we use another one, too. We use Isaac Asimov's Laws of Robotics. He first wrote these in 1942, really long time ago. There are three laws. A robot may not injure a human being or through an action, allow a human being to come to harm, law number two. A robot must obey the orders given to it by human beings except where such orders would conflict with the first law. And three, a robot must protect its own existence as long as such protection does not conflict with the first or second laws. So why do we talk about the trolley problem so much these days, and why do we think about the robots? It's because the trolley problem is a question of a number of things. It's a way that we can think about trade-offs and accountability and control and design when we're talking about artificial intelligence and digital and computational systems. So we could talk about the trolley problem, or we could talk about the Uber hitting a pedestrian problem. And you're probably familiar with this, that back in March in Tempe, Arizona, an Uber hit a pedestrian and a self-driving car hit a pedestrian and killed her. And the driver, the human operator of that vehicle was sitting in the driver's seat had apparently been watching the view when the crash happened and when the pedestrian died. And it's a really problematic situation because in some ways she's held responsible for situations that were beyond her control. It's a self-driving vehicle. She wasn't involved in the design of that vehicle. She wasn't involved in the design of Uber's decisions. Excuse me. And in that setting, it's a complicated set of factors. One of the things that Uber had done was disabled the Volvo's self-breaking technologies in favor of their own technology. And so it's a complicated situation. Yesterday, Waymo's self-driving taxis have launched in Phoenix, Arizona. And Phoenix is making a lot of trade-offs and putting a lot of self-driving vehicles on the street. My city, Pittsburgh, has lots of self-driving vehicles because we are the center of autonomous vehicle development just up the street from my house. And MC Elish, Madeline Elish refers to these situations like the Uber crash as moral crumple zones where humans are held responsible and held accountable for decisions they didn't make, right? She describes it as where people get caught within ambiguity, within systems of distributed control. So it's a question of who gets blamed, the human operator for design decisions beyond her control. Now, when we talk about self-driving vehicles and the trade-offs, there is a lot of things that the executives of these companies will say. They'll point out things like 40,000 people were killed in car accidents last year, that accidents cost $1 trillion a year, $1 trillion. And congestion is a cost of $305 billion a year. These are numbers that refer to the lost productivity of workers, people sitting in traffic, the cost of transporting goods. I found this kind of interesting. It's a little bit hard to read, but if you take a look, you can see the number of hours you might be spending in congestion here and what that cost would be to the driver and what that cost would be to the city. So it's an expensive thing and it's a costly thing and it costs human lives. So these are major questions and self-driving vehicles will certainly be a part of our future. But there are questions that come up and there are reasons that we turn to trolley problems to try and figure it out. It's questions of ethics and risk and liability and also, for that matter, legal code. And a young lawyer named Brian Casey who is at Stanford as a postdoc basically right now points out that the questions here are these robots and by this he means self-driving cars will maximize morality but minimize liability. And it's a complicated set of factors. So it's a question of lawyers. Might get sorted out by insurance people. And I'm a design professor so I think that it's a question of design as well as a question of algorithms. So when we're talking about algorithms we're not talking about something quite so random. We're talking about questions of fairness and accountability and law enforcement and as we've seen matters of life and death. We also see different ways that they play out in what we could call embedded governance and code as law. Have you heard about GPS starter devices? So if you are someone who has maybe less than optimal credit and you buy a car you might have a starter device that will make it so that if you don't submit your payments on time the car won't start and or the car will shut down as it has done for people who are driving down the highway and find their car is stopping them because their payments are late. So these GPS starter interrupt devices are a way to keep people on time but on the other hand what these do is they embed law in the objects around us with matters of potentially life or death, right? A woman, there's a CBS story about a woman trying to get to her dialysis appointment. She's in kidney failure and her car won't stop, start or a car gliding into a stop in Las Vegas. So we call this embedded governance. And there are other things too. You might consider this question for instance. Pellentier worked with the city of New Orleans secretly to unleash a predictive policing technology that racially profiled people and sought to kind of prohibit arrests. I also want to point out that questions of facial recognition are a really, really big issue. And if you're familiar with the group AI Now I'd recommend taking a look at their report. They say some really interesting things about this but sometimes it plays out in ways that are a little more everyday like this example. I'm gonna point out here that the audio is not exactly going to be tracked right but I want you to see this nonetheless. It's about how HP computers are racist. Oh Desi, this is using the video tracking software. All right. Explain.  State of the art computer, wouldn't you say? We're using the face tracking software so it's supposed to follow me as I move. I'm black. I think my blackness is interfering with the computer's ability to follow me. As you can see, I do this, no following. Not really, not really following me. I back up, I get really, really close to try to let the camera recognize me, not happening. Now, my white coworker Wanda is about to slide into frame. You will immediately see what I'm talking about. Wanda, if you would, please. Sure. Now, as you can see, the camera is panning to show Wanda's face. It's following her around. But as soon as my blackness enters the frame, which I will sneak into the frame. I'm sneaking in, I'm sneaking in. I'm in there. That's it, it's over. And there we go, it stopped. My hands are here. Wanda, please get back in the frame. Get back in. As soon as white Wanda appears, the camera moves. Black Desi gets in there. Oh, nope. No face recognition anymore, buddy. I'm going on record and I'm saying it. Hewlett Packard computers are racist. I said it. So this is maybe humorous, but also there are hand soap dispensers that don't notice dark skin. There are fitness trackers that don't read through dark skin. And there are cameras that provide a blink detector. But when an Asian person is photographed, it says you're blinking. So these are all things that are questions of design and questions of algorithm and questions of choice that get built into the objects around us and actually do have a material effect on our lives. There we go. And if we want to look more closely at facial recognition, here's something to consider. There are various facial recognition technologies that are in place. And not only do they read faces, but they read emotions and opinions. And they also misread. So in this case, these are three members of Congress. In a set of mugshots that were fed to facial recognition technology using Amazon's particular technology, it misidentified three members of Congress. A number of members of Congress, actually. And so they wrote a letter to Amazon, to Jeff Bezos, saying that this really needs to be considered. But do consider the questions of life and death. And do consider what happens when people are stopped and the disproportionate number of people of color who are stopped when you consider policing incidents. And you begin to see why things are really problematic. There's also a question of the data that you don't collect. So this is Mimi Onuhaha. And she is an artist and designer and writer who writes about uncollected data sets. And she points out that what you don't collect is just as important as what you do. Because you can't analyze. You can't parse. You can't subject to machine learning what you don't already collect. What you see here in this file cabinet are her uncollected data sets. And when she puts this in a gallery, she makes it available for you to open up the file drawer and look at the different file folders inside, all of which, of course, are empty. One of the uncollected data sets that she notes is shootings of unarmed African-American men that actually did begin to be computed. And as a result, change began to be made. She also has done a project, for instance, with Asian actors on Broadway who pointed out that there were almost no roles for Asians. But they began to collect the data. And once the data had been collected, there were newer roles and more roles. They were able to argue for themselves and for more equitable casting on Broadway. A lot of these things take place within what we call the black box. We don't get to see what's there. We can't see inside. We can't see how these decisions are made. In fact, the algorithms can't even explain to us how the decisions get made. And even if they could, when we talk about, maybe we just need to make them transparent, that doesn't really work. Because transparency, if we're completely open and transparent about what's going on, you might be harmful. You might make things more confusing. You might make false binaries, apples to oranges, right? Compare things that shouldn't be there. And there are technical and temporal limitations, limitations of what our technology does and how long we can use these technologies in time and space, right? So being transparent isn't really what it is. And Mike Anani and Kate Crawford, Mike is a professor at USC Annenberg and Kate Crawford is the head of AI now, point out that what you really need to do is not make things transparent, but make it so people can interpret what algorithms are doing. Because interpretation is different than transparency. And I want to point out here that these are questions of culture. They're the questions of the companies that we all work at, the institutions that we all work at. And what Kate Crawford, Meredith Whitaker and the staff at AI Now Right is that just as many AI technologies are black boxes, so are the industrial cultures that create them. So is Amazon, so is Google. And you start seeing ways that this might actually change, right? Here are just a couple of examples of recent news stories. This story that says, can an algorithm tell when kids are in danger is something that's taking place in my county in Pittsburgh in Allegheny County. It's the Allegheny family screening tool, and it's an algorithm that tries to determine if a child is likely to be removed from their family within the next two years if a complaint is called in to the Allegheny Department of Health and Human Services. Now, the data that this is based on comes from 100 different public sources, but those public sources may be biased, right? They may be disproportionately collecting the data of lower class families and people of color. And so the problem here is that biased data will make a biased output. But on the other hand, something that protects children is, excuse me, better than nothing, right? So the head of the Department of Health and Human Services is having these algorithms audited and working together with AI now and a number of other organizations to make sure that what they're doing is okay, or at least somewhat better. And it's hard. There isn't a good answer, right? Finally, apparently the Defense Innovation Board is going to look at the ethics of AI in war. If you look at the history of artificial intelligence, it's completely funded by the Department of Defense. It has always been the case. And so it's really good that ethics might make a start there. When your boss is an algorithm talks about, it's an excerpt of a book called Uberland that just came out this fall. MIT is launching a college that's going to kind of do digital humanities at scale, AI, and the humanities across the campus is a way to understand things. And Amazon has scrapped their resume tool that was biased against women. It had begun so much to bias against women that even traditional women's colleges had been locked out. And these are ways to kind of move people through the pipeline and deal with the large scale of resumes. So I like this quote that Brian Casey has about trolley problems. He said that trolley-like problems are not mere philosophical curiosities. Those designing the decision-making systems cannot simply shrug their shoulders. Rather, they must design in advance how their systems will respond when life and limb are on the line. And I wanna point out that this involves everybody in this room. So what do we do? Paul Verrillo in 1999 pointed out that all of these questions we have kind of are part and parcel with the technologies. When you invent the ship, you also invent the, when you invent the ship, you also invent the shipwreck. When you invent the plane, you also invent the plane crash. And when you invent electricity, you invent electrocution. Every technology carries its own negativity, which is invented at the same time as technical progress. And I wanna point out that these ethical problems are not new. I mean, we know that the trolley problem was coined in about 1967, but AI isn't new either, although we act like it is. I collect these. AI is the new black, UI, next digital frontier. Oops. Space race. AI is the new electricity. AI is streaming up all kinds of new video games. I highlighted the word new here, and six times on one screen alone, although one of those is New York, so it doesn't count. Google's AI is a new paradigm that unites humans and machines. And in this particularly sexist example, I'm apparently the new AI. This says something about, she'll never ghost you, never charge you more for a logo, et cetera, et cetera. But AI isn't the new anything because it's not new. The term was actually coined in 1955, right? By John McCarthy who said, making machines do things that would require intelligence if done by man. If you ever have heard of human computer symbiosis, the idea of humans and computers working very closely together in close partnership, that idea is from 1960, from a man named J.C.R. Licklider who put in place a lot of the agenda for artificial intelligence research between 1960 and his death in 1990. And then of course Marvin Minsky in 1961 said that we're on the threshold of an era that will be strongly influenced and quite possibly dominated by intelligent problem-solving machines. Which is why it gives me pause when I see someone like this describing a new era of artificial intelligence in 2016. It isn't that new. And we still don't have good ways of talking about it, right? So this is why we resort to trolley problems or cliches, things like this. I like calling this woman Cyborg Lady. Am I right that that's JQuery? Is this the future? Here, ready? Here she is. Brits fear the AI future. Here she is again, IBM Watson. She works for IBM. The ingredient brand helping inform the purposeful business of tomorrow. And she works at Ikea as well. Artificial intelligence embedded in furniture Ikea is considering. So we turn to these cliches and these examples to talk about AI because we don't understand it. If you Google, if you do a Google image search this is what comes up. You see images like that. The grid over the face. Cyborg man beholding his hand. And one of my students did an Adobe color pull and pulled the color palette. And he pointed out that these colors and shapes are quite familiar when he thinks of AI. These are the colors that come up. And what do they tell us? They tell us cold, logical, rational. Not friendly, not curious, and not open. Not interpretable. So again, it's that question of the black box. And it's hard to communicate about AI because communicating it means understanding it. So this is why we turn to cliches. This is why we turn to trolley problems. I like what Eric Johnson had to say about the movie Minority Report, one of these cliches that we turn to. It's really, really hard to talk about digital reality tech, right? He says these fields are full of jargon, inconsistent in practice, and difficult to grok or understand if you haven't seen all the latest demo. Pop culture is a shortcut to a common ideal, a shared vision. But this still gives me pause when I see images like this coming up when I type in artificial intelligence on Google. And this is what comes up on the Google page. I don't think that picture really helps. So it's the black box. And that's why we resort to metaphors and cliches and use the trolley problem. I'm not sure this picture helps either, but it makes me smile. In 1945, Kenneth Burke said this about metaphors, that metaphor is a device for seeing something in terms of something else. It brings out the this-ness of a that and a that-ness of a this. It's nice, right? The this-ness of a that. And we also talk of this as a little bit wordier, but stick with me here for a minute. Along the philosophical fringes of science, we may find reasons to question basic conceptual structures and to grope for ways to refashion them. Old idioms are bound to fail us here, and only metaphor can begin to limb the new order. If a venture succeeds, the old metaphor may die and be embalmed in a newly literalistic idiom accommodating the changed perspective. But we need to find ways to somehow encapsulate what these changes are, and it isn't very straightforward. And by definition, if we metaphor is the thing that your English teacher told you was good to use, but cliches are what we're told are bad to use, right? And we talk about a phrase, for instance, or expression regarded as unoriginal or trite. And that's kind of where these different stories and problems, I think, come into play, that they're almost trite in how we use them. But then again, I want to point out that cliches are cliches for a reason, and that they help us to make sense of things, and we use them to quickly explain things. I don't know if you've ever stopped to realize how many sports metaphors you might use in conversation. I'm not a sports person, but they're everywhere, right? Like, I realize I probably got baseball metaphors all over the place, but that's because we all understand them, and we can use them to solve things. But I want to suggest a couple of different options for us, for those of us as designers, as front-end people, as writers. I want to point out that humor and uncanniness might be a way forward, that AI might help, that they could help us to understand artificial intelligence better. Is anyone familiar with the Uncanny Valley a little bit? So the Uncanny Valley is basically why we get freaked out when robots are too close to human, right? And in 1970, Masahiro Mori coined this term in an article he wrote, and mapped out what this kind of weird eeriness is that we feel about robots and people. And he said we should begin to build an accurate map of the Uncanny Valley, so that through robotics research, we can come to understand what makes us human. He also points out, like, what you see here is, he was mapping out different kinds of technologies, a toy robot, a prosthetic hand, and there's a point at which, it's good, it's good, it's good, whoa, it's really bad. And the eeriness is really creepy, but this eeriness is maybe, perhaps he says, essential for us as human beings. Maybe it's a survival technique. I'm a fan of Janelle Shane. Is anyone here familiar with her work, AI Weirdness? So she trains neural nets to do all kinds of things. And I think that not only are these deeply funny, I think they're important and maybe subversive.  So this is Hanger Dan in Princess Powell. As my husband says, any five-year-old could name a guinea pig Princess Powell, but it takes artificial intelligence to name it Hanger Dan. And she also has done things, like played with different image recognition technologies to see what the algorithm is doing. And she realized that when she fed the algorithm a lot of pictures of rocky hillsides with grass, the algorithm started hallucinating sheep. It started describing sheep as being there when they weren't. And so then she took some pictures of sheep and colored them orange. That's what you see in the middle. And the algorithm decided those were flowers in a field. And then she decided to really punk the algorithm and she uploaded a picture of goats in trees. And this is a flock of birds flying in the air or perhaps a group of giraffes. And what she says about this, I think is really neat. She says, if life plays by the rules, image recognition works well, but as soon as people or sheep do something unexpected, the algorithms show their weaknesses. And this is a fun setting. This is an amusing kind of setting to look at these things with. But you could just as easily imagine some darker settings about where algorithms fail us. In a second, I'm going to show you the work of Madeline Gannon who just got her PhD from Carnegie Mellon in architecture. She's a robot whisperer. She has tamed an industrial robot to move and play with people. And she says something I think really important about this. So you'll see her here. When everything comes together and you're in the space with the robot and you just have a very raw experience with this animal-like machine responding to your every move, all the technical aspects sort of melt away into the background. It's incredibly important to have opportunities and spaces to come in and experiment and misuse these existing technologies. So this was at the Design Museum in London. And me, Miss, the robot was there for six months. And very quickly, kids learn how to play with and entertain the robot. And the robot could get bored of people and then you have to try and capture its attention again. But what she says is really important. She talks about even having the opportunity to learn, play with, and misuse technologies as a way to change what we might think about them. I think that this is a question about reframing the problem. So let's revisit the trolley problem. This is my favorite meme. And we could toss the trolley problem out, but I wanna point out that even people who run autonomous vehicle companies understand the use of the trolley problem. As Chris Irmson said, I don't think it's a bad ethical quandary of the trolley problem, but I don't think it's solvable. It forces you to think about it. He said this to my class. I skyped him into a class that I taught this semester called AI and Culture. And one of my students asked, what about the trolley problem? What should we do? And he thinks it's important as a way to think through things, that there isn't a solution. I wanna point out that one of the recommendations that AI now makes is that we need to include other fields other than computer science and engineering. And that this is vital. I would argue that design is vital. I would argue that front end technology is vital and writing and philosophy. And indeed, design is necessary. That this isn't just about the ethics of design practice, but the way that we encounter algorithms in AI is a question of design. And there are a couple of things that designers and probably a lot of people in this room who aren't designers might want to do. And as we think about working with AI, there are things that we bring to the table. We do things like understanding people, human needs and human considerations and translate them for systems. We frame problems. We determine how data can be collected and how it will be used. We can help people to interpret what AI is doing and we can communicate that and visualize that. And we can support accountability. And we might say, well, is ethics gonna slow us down in a world of move fast and break things? I wanna point out what my colleague David Danks says that ethical and efficacious are not antonyms. They don't need to be a trade-off. David asks, do we design for the world we have or the world we want to have? So design is where the rubber meets the road. And I realized that trolley problems are always going to be a conundrum. This one is called Paradox. And that's Oprah. And this is by my house. I go running by Carnegie Robotics. So I'm not totally sure what to think about that. But I put all of this out here to say that trolley problems are problems, they're quandaries, they're conundrums. And there's a role that we have in framing and solving them. Thank you very much. Thank you, thank you. Do we have any questions for Molly? Really? So I'm not 100% sure how to ask this question, but when you showed the colors, the blue scale, to me, not only does it bring up those ideas of technology, but also of business. And so I think when you're talking about these kind of developments in technology for business, you can't discount the fact that there's a profit model that has to be adhered to, or, and also that technology is treated like, treated like property, like it's like patentable and hidden away. So I guess like my thought in the context of the word camp is that what do you think or fear of the idea of this becoming an open source thing? I mean, I'm obviously like it's gonna happen, but like self-driving cars as, and you could do it in your, we are tinkering around and we created our own self-driving car in our basement, which is what we're all kinda doing. So a couple of things. First, it would be really interesting to compare, you're right, and I hadn't thought about comparing, I hadn't thought about comparing the AI colors to like IBM, for instance, or Google. And indeed those blues, like you know exactly when I say that blue, what color I mean, right? And so there's probably a correlation there as well. I wonder what it might look like if AI was rosy, if it looked like the color palette of the movie, or her, as opposed to Minority Report, for instance. And in terms of, I mean one question about self-driving vehicles is that it's going to, Brian Casey argues that it's going to be sorted out in among insurance people and lawyers, that through those settings of risk mitigation, it'll make its way into the public sphere and that that might be ultimately an optimistic and good thing. I don't know if it really is going to be open sourced, but there are all kinds of things that people do to make things autonomous. People have been doing a lot of garage robotics work for a long time. Yikes. Is there a way to use AI to improve the web experience? Like right now you can configure like chatbots to communicate with somebody, if something lands on your website, there's a response, but is there anything beyond that? Like serving content or? So chatbots have actually been around since the 60s and they're really hard, they're really hard problem to solve. I have a master's student right now who's deep in it and he's banging his head against it. We've been trying to get it right, but conversation is one of these things that it's really easy to get wrong. There are all kinds of different focuses, though, for artificial intelligence research, especially for those of us who build systems on the front end and on the web. Again, I have provided examples of Janelle Shane's work. Her blog, AI Weirdness, talks about playing with neural nets and she also provides links to examples. Those are a couple of things and there are countless machine learning-oriented classes out there. I'd also recommend Rebecca Fiebring's work on AI and music and her tool, The Wekinator, as a way to play with machine learning and music. You're welcome. One more? Hi, thank you for your talk. As I think about AI, it seems to me that AI would continually work better with the more information it has, but I also can't help but think that you're going to bump up into privacy issues. Absolutely. I don't know if you've heard about this, but there was this big law in Europe about GDPR. There was a good talk yesterday about it, I heard. There are parts of the different laws that are butt up against each other. You can't collect certain data, but yet to ensure privacy, you have to collect data to verify who they are, so you can't do one or the other, but I've seen with AI to be able to know what you need to know, to do what you need to do, you're going to violate somebody's privacy. And it's a big, big question. So if you've been reading the news this week about more Facebook revelations and questions, it seems to be an ongoing question with that company. One of, I think one of the biggest questions around Silicon Valley right now is, will the government have to regulate these companies because they can't be trusted to regulate themselves? I might argue that the government may need to step in, although they'll probably do it in some ham-fisted way that shuts off future possibilities, but in terms of privacy, it's really, really vital. My colleague Lori Craner at Carnegie Mellon is a privacy expert, and her work on this area for the last 25 years is really, really useful if you want to dig in and learn a little more. I think that's all the time we have. Thank you so much and have a great board camp. Thank you.


Good morning. Good morning. Good morning. What's up everybody? Good morning. Glad to see you here at the extrades FOMO live stream We call it FOMO live stream because the only thing you should have FOMO about is missing these pre-market trade planning and review sessions. So hope everybody is doing well today. What's up strife? Good to see you. Good morning. Hope you're doing well my friend. Good to see you here on the YouTube side of the house I am going to Continue to at least for now Share this stuff over on the X trades side of the house or the discord side of the house I should say that being said that is going to probably Wrap up here in the I would say probably by the end of this month We'll look to just exclusively have these done via YouTube and we'll be sharing them to the discord any longer So for those of you who might be checking in or watching on discord make sure that you are Coming over to the YouTube streams to keep following these FOMO live stream pre-market sessions. So What's up Deidre? What's up? Unknown reviews good to see all here. Good morning. Hope you're doing well Excuse me. Sorry if I cough everyone's while I'm still kind of trying to finish Fighting off whatever this little bug was I had over the weekend and Monday that it's just had me, you know Constantly coughing essentially which hasn't been the greatest thing ever, but I think for the most part It's pretty close to being in the rear view So I'm gonna take a look at a few things here pre-market was also looking at my supply and demand zones here on ES I just actually get ready to draw this but I realized I needed to get the stream started So let's get this in so we can talk about things with all of our supply and demand zones in place So where are we at with things from a market perspective? Well, clearly, you know, there was a very temporary but positive reaction to What Jerome Powell had to say yesterday And with what happens what happened with the FOMC? Rate decision again, they held rates steady They still aren't happy with the inflation data, which it's no shock to anybody who's been following the the narrative on any of this stuff I think the market is still anticipating rate cuts at some point this year I think the number of cuts is starting to be Priced into a lower number of cuts this year Yeah, I mean, here's the interesting part about it I'll share this with you guys real quick just looking at things through the Spy plan that I posted yesterday, you know, we had this huge I just have now right For MNMD so We essentially shot up through all the price targets and then some and they came right back down into this sort of range It was it's not some interesting dips below the put range Maybe I should have been a little bit more focused on the pre-market low as a potential put entry But looking at some of the historical moves below 545 it definitely looked like it would open up a decent amount of room to the downside But again knowing that we had that FOMC rate decision coming out in the afternoon You know getting into anything too heavily or expecting anything other than chop and your price action until 2 p.m. And after it was probably, you know, you'd need to consider all those factors, right when you think about Going into a trading day, you know, if something like that's happening in the afternoon So anyway, yeah, we shot right up through all those price targets came right back down essentially into the range and just finished right Kind of where we spent most of the day However, we do see now that sort of that volatility has played out Things have proves back to the upside and we're now testing that PT3 is resistance from yesterday's plan So essentially looks like spy is continuing to use those same levels that we were watching yesterday But obviously there will be a new iteration of the plan from you guys this morning That takes all of that into a cap and that will of course excuse me Go into the watch options watch those over in our discord Pardon me, like I said still dealing with this cough a little bit so from a futures perspective 333 SMA still on the downtrend 200 trying to curl up here on the one hour We'd like to see that 200 crossing back above the 333 We did hold this demand zone that we recently established However, we also rejected the supply zone and honestly, but just now noticing this This 51 27 25 levels an old fib extension from before spy ever broke out or before I should say yes Ever broke out into the five thousands. I did some fib extensions for it this 51 27 25 was one of those fib extensions. We hit that pretty much dead on and rejected Also in that recently established flip supply zone. So Now we're seeing a little bit more of a measured move to the upside trying to kind of grind through to the upside Here on ES. So keep things on watch What I'd really like to see for a potential another test of 51 27 25 is a break over 50 94 from a futures perspective, so Keep that in mind as you look at trading spy spx and maybe just taking bullish or bearish positions Across the market You know, we're kind of running up into some potential turbulence up here, but over 50 94 Looks like things could open up and again try for another test of that 51 27 25 So decent little Opportunity in there. What's up red? Good morning to you good to see you here So anyway, that's things from a futures perspective, let's go back and just circle back to our member Selected tickers that we did over the weekend That I put together for you guys. I should say over the weekend First one that we had was in video. We talked about this one on Tuesday's live stream again Yeah, I said kind of go back to using a plan even though we had this little bit of a fake out again early into the trading day On a Monday, you know generally speaking I like to watch the first 15 to 30 minutes play out see what you know What's what before I go trying to chase any kind of trade so a little bit of a fake out to the downside there? Ultimately did wind up first stop out, but we talked about it on Tuesday's live stream We were back within the range and I said, okay, you know, this plan still looks good I think we just had a little bit of a fake out to start the link off early into the trading day there on Monday And sure enough the plan has played out since then so Tuesday After we discussed this one pre-market. We did get the breakdown nice back test Neptune fully bearish here Ultimately push things down to PT one And then on down below PT one to PT two and PT three plus before we got the pump with the F1C stuff that was happening yesterday We asked right up into that 333 SMA again one of my favorite moving averages to watch on just about every time frame Ran right up into that rejected now trying to hold this bullish flag here on NTS We also have that have this 823 73 that was PT three the member selected tickers that I posted on Sunday evening that held Going into after hours yesterday We're trying to push back up rejecting PT one here a little bit and still below that 333 SMA again One of my favorite moving averages, especially here on the five minute So I think if we can get a break back above 848 we could see NVIDIA try to recover And maybe push for that 862 or three put entry that should what was support should now be resistance now that we have the 333 out of the way which is what caused that rejection prior to getting up there yesterday I think that we should make it all the way up to 862 or 3 Based on the levels we have on watch currently so that's NVIDIA where we're at with that one currently Microsoft kind of similar scenario We've talked about this one pre-market Tuesday said hey listen stick bearish on this thing We did get the breakdown so members selected tickers were posted Sunday breakdown back test of resistance SMAs were still trending down Neptune's been ultimately bearish on it the whole way through So we talked about this one Tuesday I said if you weren't already in on that back test there yesterday look for a break below and back test of 499 that happened as well. We got the break below a couple of back tests there Ultimately down to PT one just shy of PT two there And then came up back tested PT two down to PT three plus for puts all within the day there on Tuesday So congrats if you followed that plan, I know a couple of people reached out and said that they Appreciated me kind of covering this one and they were able to execute on the plan So congrats if you did Followed the Microsoft plan here now It's trying to hold PT three for puts as support and trying to push back to the upside here kind of similar look as NVIDIA We do have this PT one that was support acting as resistance here So would like to see that out of the way back over 398 55 for a potential test of 499 call it 401 where we found a rejection there yesterday So anyway Microsoft keep this one on watch Let's take a look at IWM This one did play out. We only got to PT one here for puts again that can happen I talk about that make sure you're taking profits at these price targets and moving our stops up Sometimes PT one is all you'll get especially with this Neptune setup here Where we flip things back bullish and that key buying pressure lined up pretty much dead on With our PT one there at 195 so really really nice confidence there That's potentially catch a bounce off of and if you did take a shot at that We ran all the way up to the call entry and rejected So now we're back kind of in the range so keep this one on watch This one could play out to the upside or the downside using the same plan levels in my opinion So keep this on watch. You know what the calls over? 299 puts below 196 54 especially with that 333 confidence right there if we break below that again could see continuation to the downside And for those of you who are in our discord community in our X trade subscribers You have this plan in the options watch list with all of the levels called out and details in there for you So make sure you're keeping this one on watch Tesla. We did on Tuesday's pre-market live stream We saw a break down below the put entry Definitely looked like a confirmed break never got back above the stop loss and then gave us a more of a clean back test They're going into the close on Tuesday ultimately Has consolidated a little bit between the put entry and this PT one for puts Still on the bearish side of the plan does have some SMA support happening down here just below but ultimately Tesla's still looking pretty bearish to me as long as it's below 184 78 So keep this one on watch continue to keep your eye on it And then my medicine this one was a request also on Tuesday's live stream Has pretty much played within the range has it really given us an entry to either side of either of our trade plans So we're still looking for a break above 876 to go along with calls or shares or look at for a break below 876 to go short or take puts Alright, I think that covers all of our recaps. Let's get to some of your requests from this morning Unknown reviews ticker requests for LNG Deidre wants to know about canopy and meta. So let's take a look at some of these tickers Let's get some trade plans going here this morning Alright First one was LNG Doesn't ring a bell Yeah, I've never heard of this one before shinier energy Let's see what shinier energy is doing earnings tomorrow kind of a low volume ticker But let's take a look. Let's see what we can't figure out as far as a trade plan goes Alright, and is this kind of current I'm guessing all-time highs Yeah, yeah Good to know and For now, I'm just gonna hide my Indicator so I can focus on price action and price action alone So let's nail down some support resistance levels here. That's always step one in my world So I'm looking at something. I've never really analyzed before and yeah, that is an interesting level right there 15 double bottom here Also some resistance tests back that way. That's an interesting level This is an interesting top that we're gonna want to keep an eye on I don't think we're gonna need anything below 120 27. So we'll Stick with this range and above Lots of bottoming there but not an established level at least not on the weekly so we'll keep an eye on that as We go through this process It's like a good level though, too We do have an actual level right in there, too Okay, that looks pretty good. Let's gosh. I'm guessing if this is low volume general probably not gonna happen on Price action from an extended hours standpoint. So let's just stick to regular trading hours on this one specifically Oh, let me figure out that one Late solder level. It's always where I like to start when I change time frames Yeah, there is a level. It's a little bit lower and it's right About here another interesting one, but not Excuse me not able to totally confirm You're on the daily chart Let's see now a little bit. It's more perspective here daily level in there Let's see what else we got some separate there Yeah, there is level hanging out right about there there Yeah, I may not capture them all in every time frame because of time is of the essence while we're doing these but I think We get a pretty good idea of what the key levels are to watch as we get through this process It's a little bit. Yeah. Yeah, it is right out there actually Of course, if you guys have any questions about anything that I'm looking at or just trading in general that you want me to kind of Wax poetic on whoops while I work on this first trade plan. Please feel free to shoot those Messages to me in the YouTube chat and I will do my best to walk and chew gum or Chart and talk simultaneously It's an interesting little flip in here that I think we're gonna keep our watch Let's see where that puts us with the current price. All right. I think we're pretty good Just checking this range real quick it seems kind of Broad for there to not be Some kind of support resistance hanging out in here. Yeah, I do like that level actually in this one Okay, so let's take a look at the hourly chart. Let's go ahead and start Putting together this trade plan on LNG also be mindful earnings Borrow pre-market. So Be very careful swinging anything because you will be swinging into an earnings report Keep that in mind Alright, so we'll fill in the blinds as needed here on the hourly chart, but let's figure out What we want to do with this Trade plan All right, I think I'm looking at Yeah Now it's kind of tight though. It's a little better. Actually. Yeah, I like that. All right, so What we're looking for Here on LNG is a break over this 16050 level That opens up this little window of opportunity with a smart stop here at 159 33 up to 161 37 just to get things started Let's see where this rejection is coming from if this is an actual There's also still a gap to fill Up to this 164 21 level And this prior rejection right here looks like it's a rejection of essentially well It's a little bit higher than that It looks like it's gonna be closer to that gap entry than it actually is but there is a level here That we are gonna watch I don't think we're gonna use it for this particular trade plan. It's not at the moment Yeah, I say we look for this gap to fill up to 164 21 over 161 97 That gap can fill and it can continue up after that Could very well see a shot Could be a little bit higher but not significantly higher so we'll stick with this higher time frame daily level up here 166 10 so I like that for an upside trade plan downside Testing the key buying pressure here on Neptune at the moment, but there is this weekly level down here 155 33 I Think is what we should wait for potentially look to go short or play for downside Question is then I like this is a first-price target down to 150 296 Stop loss is my Only thing that I'm a little bit on the fence about I just feel like that's given it opening up a little bit too much loss potential on this trade for the downside plan, but That 157 58 is a pretty strong resistance However, there is this recent Flip or hold so far actually This resistance what was resistance as support, so you know what? I think we're gonna use this As our stop loss average down got our first price target in place second price target See how far back we have to go to find this guy Yeah, so do we already have the level we need or is it somewhere Here which I think it is I would shoot for this 151 81 second-price target Third target just looking at some of these Rire moves through this range Yeah, it's probably sitting right about here at 150 07 That would be smart smart pts 2 and 3. All right, so this is what the trade plans look like Let's get these posted will recap these real quick, and then we'll move on to the next plan the next request Downside short position right spot there. There we go. The link here we go So this is the LNG trade plans Also here putting this over in the options watch list in our discord Again remember earnings pre-market tomorrow Chatting it on here. All right, so What we're looking for here on LNG is a break over 160 50 that should give us targets at 161 97 164 21 and 166 10 with a stop loss average down at 159 33 To the downside we're looking for a break below 155 33 that should give us targets at 152 96 151 81 and 150 07 with a stop loss average down at 156 89 There you go unknown reviews that is your LNG trade plans best of luck to you and anybody else that decides to pursue these All right, let's take a look at the next one D. Dre wants to take a look at either canopy or meta. Let's see I know Marijuana tickers have been cannabis tickers, whatever you want to call them I've been on the move with this potential Rescheduling of marijuana from I forget if it goes from schedule three to schedule one or schedule one to schedule three Something like that. Essentially, they're gonna take it out of the same category as stuff like meth Which makes sense? But anyway, let's see where this is sitting just to see if we've got kind of some good price action and Data that we can use to come up some plans here for canopy Some interesting spikes and rejections up into this range too Overall, it's been pretty bearish. It's still high of 21. All right Let's work on this canopy plan because it could be a good one and an easy one to trade with shares It's not crazy expensive So let's start off with our weekly charts where I generally like to start And again for now hide the indicators just so I can focus on price action and nothing but price action This is an interesting level Interesting to see What happens if and when and also do we get any more comfortable up? That's right about where that rejection happened actually So that's a definitely a good one to watch This level is probably sitting right about here from a weekly perspective Let's see I think the slats sit more like right there. This is kind of minimal Touches there, but there is a level. I don't think can't be a bed down below that Three dollars is a change. That's all-time lows at this point and that may well be the case depending on how this Rescheduling thing plays out soon will probably happen And then we've got kind of our All-time low down here. All right, I think probably does it from a weekly standpoint. Let's just make sure though There is some price data in here well enough 17 is a Level we're gonna need to be our price range. We're gonna need to even be watching with where it's currently at It is It's not the cleanest level. I've ever seen where there's something sitting right here All right, let's take a look at this Daily perspective It's an interesting Yeah, there's a level there. Let's see. I think got something Yeah, there and here kind of tight little range there between that weekly and daily level but For a ticker that's trading in the six dollar range 30 cents is actually Believe it or not kind of a decent little range and something's that low Just from a percentage Stamping it's interesting That level is there. I'm just surprised this rejection is just shy of it But that's what it is. I'm not gonna force it. I don't think we're gonna have a Lot of yeah, and this is also very Low volumes sporadic movement early days of The MJ sector kick it off. Probably nobody wanted to rush in which doesn't surprise Me. I think we're pretty good. Let's just check. I don't think we're gonna need a level This high as far as the call side of this plan goes but There's something hanging out there. All right, let's take a look at this four-hour chart real quick Seems like there's something right about here, but like a little bit more Confirmation Yeah, I think there is There Not gonna go back super far to try to track it down, but there's something there also be interested to know We can find anything or if there's just kind of a big Area where Anopy is not established a lot of support resistance, but there's one That's not an exact level. There's something pretty close to that. I'd be willing to Put some money behind that Let's see It's not a lot of Other price action and what is there is very low volume sporadic not gonna be all that helpful All right So I think we're at a good spot Just about There's a little sit right there Definitely one right there see if this proves out. Yeah, there's something sitting right there. Okay So let's flip our indicators back on we'll fill in the blanks here on the hourly chart. Let's put this play together though All right interesting confluence here at this 1194 level If we can get over that I think we take a shot at this 1434 Still a fair value gap to close there too Up to 1434 then 1574 clearly we would not want to ignore that top action rejection right there Over 1574 Question becomes do we shoot for 1868 we go for the weekly level? There's a chance at it But Think we air just slightly on the side of caution shoot for 1776 versus Stretching too much for that 1868 level It's also an interesting just below this weekly support resistance Flip of resistance to support Think it does make sense to give that just that a little bit more room honestly, I like that as a stop-loss average now Downside get interesting little confluence down here with our SMAs Question becomes where does the downside? Really kind of open up No sense in getting in just to have a you know price target Just on the other side of your entry level, but it's a little Choppy in this range meaning toward You know what? No, we're good. I know what we're gonna do Take this it's our call entry. We'll share stop-loss with the upside trade plan It's gonna be a tighter first price target though, but that's okay Titer stop-loss tighter first price target second price target down here this weekly level and Then third price target down here in 753 That looks pretty solid to me actually Seems a little bit skewed, but again because we have a smaller Reward area it makes sense to have a smaller risk area in my opinion Versus having a larger reward area larger risk area Makes that bouquet Definitely a little bit blot-sided though on these plans as far as Size of the moves that we're looking for upside and where the stop losses are versus the size of the moves and where the stop losses are to the downside, but what the chart says so we go with what the chart says we keep our bias or any kind of Expectations out of the next rate focus on the charts above all else so These are the CGC trade plans. Let me get this over to the Options chat or sorry options chat options watch list over in our discord C trade plans So and then D tree had another one meta Got a couple of minutes. Can I squeeze out a quick meta trade plan? Oh, it's been it's been it's got clapped on that earnings report Really struggling down here now Honestly, I don't think there's been a ton of support resistance Yeah, established in this range Kind of shot up all one earnings report and shot down on the other So let's do this. Maybe we can come up with some retracement levels that could be helpful a clear rejection off that candle there See what that shows us? So we don't really have a lot of price data work with down here It could probably fill in a couple of blanks. So maybe like this one Don't know if that'll be a factor or not, but we'll keep an eye on it All right, so how do we want to handle this meta setup? It's a little bit wonky Week break there on the sourly chart roll over of the flag It does have overall the nice bullish trend ribbon going just below So that would be a good stop loss my roll head scratcher. Look at whoops Not a drawn level yet the head scratcher for me on this one is gonna be Trying to find the smart all entry You have this old 453 61 level Yeah, I like that as an entry. It does look like it would open up room Or 6863 Looks like we're about one-to-one risk reward Shooting up to that as our first price target second price target. Whoops sit right there Third price target. I say we take a shot at this for 88.7 level That all looks pretty solid to me Downside kind of like this for 26 79. That's an old fib extension It's a potential entry point Yeah, and I think this for 624 that was kind of a very Momentary all-time high rejection before it had earnings that just blew the roof off things Whoops, so get back to that I think that would be an interesting level to watch. It's certainly not established This for a 624 We're gonna want to keep our watch For sure Actually, I'll make this a different color with other ones now So this bounces just a little bit above this old fib extension again fib extensions not an exact science I'm not gonna have really much to work with there So I'd be willing to say that maybe my fib extension is slightly Off again not an exact science not anywhere near the drawing the support resistance also not a truly Established levels. I'm gonna kind of leave it in place with this orange color Just so I know to kind of keep an eye on it and figure out if we can't really nail that down So I think we're looking pt3 at this full 100% retracement level third-price target Their entry being up here at 426 79 And I think we share a stop loss with the call side so it's actually I think good day up good to go did get it done. How about that? So let's talk through this real quick get these links posted. Let's get all this old trade plan stuff End up real quick while I'm looking at it Well, I post the Screenshot so it doesn't get confusing same thing up here. Let's clean these guys up Okay Yep, that's pretty good So here's what we're looking for Metta and let's post this in our discord as well All right, so what we're looking for here on meta is a break over 453 61 that should give us targets at 468 63 476 81 and 488 27 with a stop loss average down at 438 96 to the downside we're looking for a break below 426 79 that should give us targets at 413 08 406 24 in 399 13 with a shared stop loss average down there at 438 96 Unknown reviews. I'm getting ready to work on the spy plan. It's not done yet And I will post that in our discord It's one of those things that is a big Benefit to those who are X trades members and an active in our discord So if you're not there yet, please make your way there come join I do want to keep that something that's kind of Exclusive to our X trades discord members So it will be there in the options watch list momentarily in the next 10 minutes. I'd say So with that we are about 15 minutes out from the market open. I hope you guys enjoyed the live stream this morning Thank you so much for joining me. We will be back next Tuesday morning at 8 30 a.m. Eastern Standard Time And back on a regular schedule for the foreseeable future of every Tuesday and Thursday at 8 30 a.m Eastern Standard Time for the X trades FOMO live streams. Get your pre-market game, right? So with that being said, I want to thank you guys again for joining me I will see you guys in the chats and our X trades discord community So with that as we also always say here on the FOMO live stream playing your trades Trade your plans go out there get some green secure those bags I will see you guys around in the chat Have a fantastic day and back here next Tuesday at 8 30 a.m. Eastern Standard Time. See you then take care talk to you soon