Following is a presentation of TFNN. Trade what you see with Larry Pezzavento. Call now toll free at 1-877-927-6648 or internationally at<PHONE_NUMBER>. Now Larry Pezzavento. Welcome everyone, uh, not here, Jacob. I'm going to keep pulling in, maybe I need to get a short intro or something like that. We'll look into it. What do we got going on today? Well, we are sideways a little bit down in the market today. Yes, many down 3.7 percent, the Russell up about 0.17 percent. Dow futures up 0.18, gold contract down a 0.63 silver sideways copper. Coming back down a little bit from a minor uptick it had yesterday. Light sweet crude. So at 89, we are pretty high right now. I think the Brent is currently in 92-222. So, you know, with this, we have CPI coming out. CPI is going to be a little bit higher tomorrow because of this uptick in oil. The core CPI has been deflating just a little bit. So, you know, it all depends really what the headline is going to kind of be tomorrow and how people react to that. You know, I've even seen in the past, it doesn't seem like the market is too dependent on this. But I think we will have a higher CPI going into tomorrow and then also for September, it'll be exceptionally high as well. But if there is a, you know, there's a big enough focus on the core CPI coming down a little bit, maybe we'll remain unscathed. Regardless, it seems like the market kind of just does what it wants to do anyway. Take a look today. Well, first here, let's run into this. OK, the dollar 104.75. Just coming down from that 105 mark from a few days prior, I'm at it down almost 2 percent. Google down 0.83 percent and Disney covered a little bit at $84 almost. And then Apple as well. They're releasing the iPhone 15 soon and hopefully that'll get them a little bit back up from what they lost regarding the China news. Steel Dynamics, we hit that major level right here, that 100 mark. We've breezed low it again. That was one of the last days with volume was up at this 101.79 area. Tested it again, kind of shot through it on some light volume though. I'm looking at this. If we can get a rejection of this level on some volume, we might go back up and you see it kind of flirts, right? It hits down here at this 100, no 99 level comes back up and it first with that 1010 level and it's been doing that, you know, really since about June, beginning of June of this year. We'll take a look at Newcore as well. You can see a similar pattern basically with this consolidation coming back. Now, this started really in July. There was a ramp up in June where Steel Dynamics was already kind of trading in that pattern since then. We also have a pull down. So what's going on regarding Steel? Well, you have a lot of factors, right? First of all, let's talk before we get into that, we'll talk in Newcore, right? Regarding Steel, Newcore, it was looking at the short interest for them. And it's only about like, let me get this number exactly. Yeah, a short percent of float has risen to 5.73 percent. The company has recently imported that 5.51 million shares sold short and that's 2.95 percent of all regular shares that are available for trading. The industry standard for Steel is around, I think, 3.25. So there is less short interest open on Newcore. And they're a solid company, people like them. But looking at the fundamental of what's going on with Steel, too, you know, obviously there was a huge, huge price run up in 2021. That's where we saw Steel Dynamics go from around the $58 area busting up to 79 and now are trading in the hundreds. Newcore did equally as well. You have slowing demand worldwide because of inflation for these manufacturing outputs going down. Obviously, you have the global conflict in Ukraine and Russia and everyone's involved in that.  Their slowing economy also has kind of put a price dead. And that's going to be felt a little bit more in India, so not so much impacting us. But, you know, these markets move in somewhat some kind of relation, even if some of these companies aren't exporting on a global level. All right, other large news oracle got shredded. Let's take a look here. Oh, boy. Oh, it wasn't this bad this morning when I was taking a look. Wow. Yeah, trading at the open. Oh, man, what are we at right here? 114 down to 108. So today losing about 14.8 percent. So what the heck is going on with that? So they come up short on revenue. There's other competitors they have as well in this kind of AI field. However, their contracts are pretty good. So their kind of financial team is just trying to rely on that. This is quite a significant sell off. So some of the key points for this is Oracle fell short on license and hardware revenue in the fiscal first quarter. Quarterly revenue guidance was also weaker than expected. And the company announced new database hardware and artificial intelligence software features during the quarter. At the time of this kind of article, which is earlier today, they're down 9 percent, fall in an extra 6 percent since then. The earnings are one dollar 19 per share adjusted versus a one 15 per shares expected by analysts. Revenue 12.45 billion versus 12.47 billion is expected. Now, Oracle's revenue grew 9 percent year of year in the fiscal first quarter ending in August 31st. That income rose to 2.42 billion or 86 cents per share. Obviously, in June 2022, they closed a 28.2 billion acquisition of CERNR, which is an electronic health record software company. And according to them, they're now an accelerated transition of CERNR to the cloud. Oracle's cloud service and license support segment produced 9.5 billion in revenue up 13 percent. But the cloud license and on-premises license segment posted 809 million in revenue, which is off 10 percent and lower than the 892.7 million consensus that was there prior. Hardware revenue declined 6 percent and their cloud infrastructure revenue increased 66 percent. But that was slowing from 76 percent in the prior quarter. So there's a slowdown in the company. Wow. I mean, is this warranted? I'm not really sure. Now, of course, they have a lot of other competitors. So we'll kind of see what goes on regarding that. So pretty pretty nuts shave off from Oracle earlier today. So this is another interesting article, too. And it's asking, you know, we're having kind of this slow it's low volume, but like a slow burn a little bit in some of these stocks. And I lost my headphone there for a second. Give me a moment. And I was mentioning this a little bit last week. But we have a lot of large amounts of wealth kind of exiting the stock market and moving into bonds, especially corporate bonds have seen a lot of interest recently and then private equity as well. More than half of some of the wealthiest families that were polled in America accounting for combined net worth of five hundred and sixty five billion. They increased their allocations and fixed income while 38 percent boosted their private equity holdings. And by contrast, 38 percent reduced their allocation in stocks. Guys, stay tuned. We'll talk a little bit more about this when we get back. Currencies, commodities and bond markets are as important as ever right now with how they're driving the volatility in equity markets across the globe, which is why it's a great time to try out Teddy Kegstad's Tiger Forex report. Teddy Kegstad breaks down the forex markets every Monday using his 30 plus years of experience as a trading veteran of futures, forex, stocks and options. Teddy releases his weekly Tiger Forex report every Monday morning with coverage of all the major currency pairs, including the dollar index, the euro dollar, pound dollar, dollar Swiss, dollar yen, as well as many more. And he also has weekly coverage of the crude oil market and the 30 year T bonds as they both influence forex markets tremendously. When you sign up for the Tiger Forex report, you also gain instant access to Teddy's 60 minute Webinar Archive. He just hosted forex strategies and fundamentals. What is behind the Tiger Forex report? For all the details and to start your 30 day Tiger Forex report subscription today, visit the front page of TFNN.com, TFNN Educating Investors. The Gold Report. As a precious metal, gold is still king. It continues to hold the most effective safe haven and hedging properties across the global major trading hubs of the London OTC market, the US futures market and the Shanghai Gold Exchange. The Gold Report. Tom O'Brien publishes his weekly gold report every Monday morning for subscribers consisting of coverage of the XAU, HUI, GDX, the dollar, bonds, the South African Rand, as well as 25 different mining equities with specific buy sell recommendations. The Gold Report. New subscribers get a 30 day money back guarantee, so you have nothing to risk. Subscribe to Tom O'Brien's Gold Report newsletter now at TFNN.com. Market Insights provides the edge you need to navigate the markets with confidence. Ready to join the ranks of successful traders? Head over to TFNN.com and subscribe to Market Insights today. Don't miss out on this opportunity to supercharge your trading results. Market Insights comes with a 30 day money back guarantee for all new subscribers, so you have nothing to risk. Don't miss out on this opportunity to revolutionize your trading game. Head over to TFNN.com right now to join the thousands of traders who have already experienced the power of Tom O'Brien's award winning newsletter Market Insights firsthand. TFNN Educating Investors. Call now toll free at 1-877-927-6648 internationally at<PHONE_NUMBER>. Welcome back. Before we went to the break, we were talking a little bit about how some wealthier families and some firms are pulling some of their money out of stocks, going into fixed income instruments. So that number again was 38%. These are people with a combined net worth of $565 billion, a demographic with this. Increased allocations, fixed income, 38% boosting private equity holdings. By contrast, 38% reducing their allocations in stocks. This is having to do with some fears, something from U.S.-China tensions and inflation and market volatility and other geopolitical concerns. So there's that for you. Guys, how crazy is this? We talk about cybersecurity on this show all the time. You're talking a little bit about, oh, before I even go into this, talk about some kind of serendipitous moment after my show the other day when I was talking about United Airlines. We were amusing that there might actually be some kind of actually like cyber breach as opposed to just a glitch in their computer systems. I went to a cafe later in the day and actually ran into this guy who did project management in IT for not United Airlines, but another airline company. I brought this up to him and he was dubious too on it being a computer glitch because he says there's so much redundancy in communication between air traffic controllers and pilots and the computers that you could suffer a serious collapse in the network and still get things going and still keep them moving. So something to muse over and again these companies do not need to report if they've had a breach in its capacity. However, MGM resorts did decide to report on it. Slot machines go down in cyber attack on the firm. Certain systems were shut down due to cybersecurity issue the firm said. It added that its facilities remained operational. One customer at the MGM brand in Las Vegas said she had walked into the wrong room and the hotel's digital keys were malfunctioning and said the staff had to distribute physical keys. Staff offered her a complimentary stay as a compensation. She also posted a video on TikTok of slot machines and gambling machines that the resort switched off and a statement posted on the application formally known as Twitter. Oh, it even says that. I thought I was being clever. Anyways, MGM resorts said it has begun an investigation with assistance of leading external cybersecurity experts. Pretty nuts, we get it. This happens more often than you think, folks. I still think going forward this is going to be a massive industry. It already is, but commercially speaking it might get a little bit more, you know, gas as time goes on. So one second computers doing that fun freeze up thing. All right, we got to go in now. I'm talking a little bit about steel and just kind of a global slowdown in manufacturing. This happened in America as well, not as much. This is from my financial times, looking what's going over, you know, on the continent out there. This is the German builders are warning of a crisis as they scrap record number of projects. The proportion of construction groups reporting lack of new orders surged to 44.2% in August. So, you know, Germany itself is fixing to have a pretty tough financial year and their economy might contract a little bit. You know, obviously America is far more resilient, but you know, when something is going wrong here, an industry, if the Germans have something similar, it is going pretty negative for them. And we can get a little insight of just what's going on globally with all this kind of stuff. You know, canceled building projects of financial distress among landlords and builders in Germany have hit their highest levels since reunification three decades ago. Intensifying the construction crisis in the EU's biggest economy. Hit by rising interest rates, soaring costs, a weaker demand, 20.7% of construction companies have been forced to scrap a project in August from 18.9% in the previous month according to a survey of 500 businesses by researchers at the Eiffel Institute in Munich. This is a pretty intense kind of situation here. Obviously, there's still some buildings going on in America. It's still relatively strong. And Germany is in a far, far, far worse situation. But just looking on a global level of kind of what's going on and how this new, you know, global interest rate increase is kind of affecting different places, I think is interesting nonetheless. Moving forward, staying with Techbit, I would recommend checking this out. Elon Musk and Zuckerberg are in talks, are going to be in talk within the Senate forum on Wednesday about AI ruling. That'll be interesting to see. Senate Majority Leader Chuck Schumer of New York, a Democrat, is convening an inaugural AI Insight forum on Capitol Hill Wednesday, bringing together some of the biggest names in tech to help lawmakers understand the technology and how to regulate it. Attendees include Tesla, Elon Musk, Bill Gates, Zuckerberg, and Google's CEO, Sundar Pekai, and Schumer Hopes and Meeting will provide a foundation for future legislation. This will be super interesting to listen to and I recommend when you have time and TFNN isn't having their programming that you check this out. Chief Executive of C3.AI said, AI execs are playing a rope-a-dope with lawmakers asking them to please regulate us, but there's not enough money and intellectual capital to ensure millions of algorithms are safe and they know this is impossible. Wednesday's forum is the latest stab by lawmakers and companies to get ahead of potential disruptions wrought by generative AI to jobs and society as a whole. They fear a repeat of being absent after they largely ignored the harmful aspects of social media years earlier, which regulators recall with dread and guilt and even furthermore with what happened with some of the labor drain out of the U.S. around the 80s and stuff like that. I know this is a natural thing when society progresses but it doesn't mean that we can't figure out better ways of progressing forward. So I will definitely be tuning into that. I'll probably watch some of the highlights after work tomorrow, but it seems pretty cool to check that out. I've already spoken about this as well, but there's some more information going on number-wise in particular is the credit card usage is jumping as consumers in July at 10.4 billion in debt. The American consumer really is about to have a hard time right here and then defaults are increasing as well. Revolving credit grew at 9.6 billion, mostly in credit card debt, while consumers also added another 773 million for auto loans and other non-revolving debts. The Federal Reserve report on consumer credit showed a total outstanding credit of nearly $5 trillion. And delinquencies at retailers like Nordstrom and Macy show more credit strain could be coming. And you know, this is so nuts too, but I think about this sometimes and what really led to everyone being able to purchase so much during the past two years. Obviously you had stimulus, but is that really enough? And I think back to a friend I had, and he was an EMT, and he had been an EMT, I think maybe six months or something like that before quarantine really hit. And EMTs do not make a lot of money, which is a shame, so integral to society. I think he was making something like $15 an hour or something like that in the area. And then all these government contracts started coming in regarding COVID. And I'll talk a little bit more when we get back from it. Anyways, these guys were making an insane amount of money. And I'll talk a little bit more when we get back. Folks, stay tuned. We've been trading traders for more than 20 years, with live programming hosted by a variety of professional traders during market hours. And now they are expanding their reach with the Tigers Den, available to all Tigers and Tigresses for just $1 for the year. There's no cash or added costs when you join our community of traders. 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Ready to join the ranks of successful traders? Head over to TFNN.com and subscribe to Market Insights today. Don't miss out on this opportunity to supercharge your trading results. Market Insights comes with a 30-day money-back guarantee for all new subscribers, so you have nothing to risk. Don't miss out on this opportunity to revolutionize your trading game. Head over to TFNN.com right now to learn more about Tom O'Brien's award-winning newsletter Market Insights firsthand. TFNN, Educating Investors. Don't forget, you can listen to TFNN live on your mobile device 24 hours per day. Go to TFNN.com and hit Watch Tiger TV. That's TFNN.com and hit Watch Tiger TV. So we're talking about increasing credit card usage and then delinquencies that are following, and we were kind of using on why people were spending so much over quarantine and how I got to it. I was talking about a guy that I knew whose EMT was making about 15 bucks an hour, then he started going on these government contracts and obviously, you know, especially with nurses, they get hazard pay, which is even more, but then he started making about 38 bucks an hour working at the border and then some nurses that I knew were making unbelievable money. I knew one who was making like 78 bucks an hour as a travel nurse and hazard pay and there's like, at least for RNs, there's something around like 5 million in the U.S. and plenty more healthcare workers and other workers who received hazard pay and were on contracts they're making so much money. I personally think at least in the area that we were in here in St. Pete where headquarters is, that was a major driver for a lot of price increases and so, you know, one could think as well, I mean, we'll talk too about being depressed and things getting a little bit harder for people, especially with price increases which absolutely adds to people using more consumer credit but I think too, some people sort of living within a certain level of means and in some ways haven't really downsized on it. To this article the total consumer credit increased about 10.4 billion and that includes an increase of 773 million for non-revolving credit and that's auto and school loans and that brings the U.S. outstanding consumer credit to about 5 trillion of that 1.27 trillion is in revolving credit and that's credit cards lines of equity and then other lines of credit. Yeah, pretty insane. This is in what they're saying here is inflation pushes the debt higher, which we all know. Furthermore on this, you have a lot of businesses kind of indicating the Federal Reserve that the wage gains are subsiding is over the 12 months ending in June and the wages were increasing by more than 4.5% and we're having a slight decrease and of course also you're getting not as many people hired and job market is getting a little tighter and stuff like that and you might see an increase in default as more people for the short term are moving into using different lines of credit. So this is something to be pretty cognizant of going forward it does show some kind of shaky situation for the U.S. consumer economy. You know it's important to not always look at how the stocks are doing and how the market is doing and how fixed income is doing and all of that. I mean you have to look at what the consumer is going through as well. You know these are two different lines of the economy but they're both equally important. So let's see here, pull it up. Right. Here we are. In further news there's some regulations going on NYC. This is happening in St. Pete too. This is surrounding Airbnb and Verbo regulations. So I can say north of where we live is a city called Largo and I have some family members who live up there and you know these traditional neighborhoods with whatever kind of names like Shady Oak or something like that which are just single family ranch style homes. And he doesn't have a single neighbor in his immediate proximity. So I mean two houses down to the left to the right behind him or in front that have actual families living in them. These are all Airbnb's or Verbo's and I mean obviously he hates it because you get all these young guys moving in for some times and they just want to party and they're coming to the area for a short amount of time and don't really care and I mean this one it increases the price of housing you know because all these are getting like eaten up by people who want to rent them out and it decreases the quality of life for families who actually live in these areas. Now this is a little bit different in New York City just the living style in general but short-term rentals in New York City recently became subject to new restrictions in New York City the mayor's office of special enforcement's administration of the new rules have been underway for just a week with the OSC's initial phase kicking off September 5th under the law anyone who offers short-term rentals has to become registered with the OSC and has to follow rules like ones that bar them from renting an entire registered dwelling unit for less than 30 days according to the regulation local law 18 also prohibits booking platforms from processing transactions for unregistered short-term rentals this creates a clear path for hosts who follow these long-standing laws and protects travelers from illegal and unsafe accommodations you know I still think going on to as there's already laws especially like in New Orleans and Atlanta and stuff like that they're pushing some laws on how many Airbnbs can be in one area, how long you can rent it out for so on and so forth these are still pretty strong companies fundamentally speaking but I think it's important to keep in mind what different local governments are doing regarding because Airbnbs in particular are a massive, massive company so Peloton is in some tough water yet again with their product just being extraordinarily dangerous let me see here we're going to monthly you took a big loss right here furthermore they're under a lawsuit now claiming that the Peloton had instantly killed someone by severing an artery and we've heard this before and this was like a big big kind of mud on their face these were dangerous for children and they just weren't safe kind of devices but this one the man fell and it hit an artery of his so now they're being sued and that opens them up to even more kind of regulation and maybe they have to pull products off which are already in a tough spot because they had such an oversupply product and that really tanked their stock price when they weren't able to move it out according to the lawsuit this individual was completing a core workout which required him to dismount from his Peloton bike and do some exercise on the floor when he attempted to rise again he used his bike to help him get up and the equipment allegedly spun around and impacted him in his neck and it just so some pretty nuts kind of news with that and it's just some more bad news on going forward we were talking about some scams yesterday about some people using AI to mimic loved ones in distress and they would basically extract money from the target and with student loan forgiveness and one of the things I was saying is anytime there's something new going on that's going to involve some kind of financial transaction and I brought up for instance like aid to the Ukraine or something like that right? there's going to be a scam and it's getting very complex this one since student loans are resuming pretty soon is basically a forgiveness scam and it's quoting the full discharge of all your federal student loans and you click this link here so scammers are trying to prey on some of the 44 million Americans who start making their first payments in more than three years more than 350,000 student loan related robo calls have been placed in two weeks roughly as many as in the nine prior weeks and this is from an organization that analyzes calls jumping student debt related scams has come as the first payments in college loans are set to resume in October following a pandemic era pause that began in 2020 and yeah essentially what this is going to do is try to give them sensitive information and you'll forgive the loans and they'll be helped out that's obviously not true if you get this call you'll be very wary folks stay tuned we'll be right back sharpening your skills as an investor is like getting better at playing a musical instrument you have to practice sure but you also need excellent 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the prospectus or summary prospectus should be read carefully before investing an investment in the funds is subject to risk including possible loss of principle the funds are designed to be utilized only by risk-kitted investors such as traders and active investors distributor four-side fund services LLC this program is brought to you by Vista Gold traded on the NYSE American and TSX under the symbol VGZ welcome back folks alright so we have a kind of sideways market right now the N and Q down almost a full percentage point Dow futures up point 12 percent and the ES kind of moving down here let's get on the daily yes so retesting its lows here almost we'll see where we close with that again it's so hard to tell especially with you know we can we're gonna you know it's probably gonna be safe to say that the CPI will be higher than had been originally anticipated tomorrow due to the increase in oil prices we'll see really what the what the core CPI is gonna look like and that in my opinion will be the major mover if it's not good we you know I think in the past people hadn't really fully gathered that these interest rate hikes were gonna increase and I just remember like I think like in May or something like that when pal was talking I mean he said like these interest rate hikes weren't over yet and the resounding response by a lot of the market at least you know online was gay right on the economy is doing okay and it's you know there's just a disconnect there with what leadership is saying and what people are wanting to do and maybe the reality of the situation is really coming through so you know we're seeing you know a flocking out from stocks again into these fixed incomes and you know securities so this particularly corporate bonds but you know if core CPI isn't good tomorrow we might see an even larger drop as well when in the past it was kind of a shake up of what was gonna happen with the market depending on inflation numbers take a look still dynamics are pretty flat Tesla selling off just a little bit at 2.27% I think it was just profit taking honestly they had such a significant run up the past few days the dollar still staying pretty steady at 104 meta down 1.87% not much has changed since the beginning of the show draft kings got into some hot water yesterday I don't know if it really meant anything for them they are down 2.66% right now what had happened is you know they had the Jets game yesterday and the Mets and the Yankees they had like a New York kinda this is rough man yeah the promotion that required three New York based teams which are the Yankees Mets and the Jets to win their games Monday and the header above that was in memory of September 11th obviously a little bit tone depth so they got a little bit of hot water on that say if this price decrease really has anything to do with that hard to say but regardless that's what they've been up to not a good not a good look some more social kind of developments going on California fast food and health care workers poised to win major salary increases nearly one million California workers are poised to win major salary increases after labor unions flexed their collective muscle and the state's democratic led legislature and it really is insane to see kind of almost a major resurgence of some of the unions you know there's been a lot of especially this year especially with inflation going up you know in an attempt to kind of depress wage growth by the Fed and even employment by the Fed so one could probably assume that you would hear more noise from unions going forward most of the state's 500,000 fast food workers would be paid at least $20 per hour next year under a new bill aimed at ending a standoff between the industry and labor unions over wages and working conditions about 455,000 health care workers not doctors nurses but people who do everything else at hospitals which diocese clinics and other facilities will see their salaries rise to at least $25 per hour over the next 10 years in a separate bill and how you could be making that much in California and surviving I'm not really privy to because that seems like it I mean that's rough to live even in this area on that kind of salary. Both proposals must first pass the state legislator and be signed into law by new some proposal been blessed by both labor unions and industry groups and that would be a huge win for unions going forward the minimum wage is already high excuse me among the highest in the country at 1550 but still I feel like that's just that would be a rough time working with that kind of especially in California it's just so expensive and you know this is one of the positive things with unions you know it helps people get together and maybe argue for higher pay so regardless moving forward with that sales force has some more developments they've launched an AI assistant across its apps that's slack ant blue tableau okay enterprise software maker sales force on Tuesday launched a generative AI tool that be available across its suite of apps from instant messaging services slack and data visualization tool tableau and can be tailored by its clients to meet their needs again this is the major thing that generative AI will do is act as your own kind of personal assistant the assistant called the Einstein co-pilot can summarize video calls deliver personalized answers to customer questions and generate emails for marketing campaigns among others the company said ahead of its dream force conference I'm laughing at that because there's been this like meme going on online people who are in arguments with their significant others and they're using AI to kind of write apologies or argue for them which you know kind of sketchy but regardless the San Francisco based company had launched the Einstein GPT gen AI product in March the company doubled its venture capital fund for generative AI startups to 500 million in June so that's pretty good look out for sales force they've been doing pretty okay this year as well let's see crypto big sell-off the past few days we get the exact number on it's 185 million liquidated in crypto sell-offs as Bitcoin Ethereum and Dogecoin plummet amid a volatile market I also think you know Elon Musk can kind of influence these things as well especially Dogecoin that's been his pump and dump thing and he came out recently saying but he doesn't see the blockchain as such a positive thing and that had some ripples at least within the Dogecoin community but over the past 24 hours it would have been 48 by this point the cryptocurrency market experience significant liquidations totally over 185.97 million these liquidations included long and short positions with longs accounting for over 144 million and shorts totaling 41 million blockchain data reveals most prominent firms such as Jump Trading Winter Mute in Abraxas Capital made substantial deposits of cryptocurrency to various exchanges during Monday's market sell-off these deposits were made in Bitcoin Ethereum and Arbitrum's Arb Token an asset manager at Abraxas Capital transferred 14,000 ETH worth about 22.5 million so there's a big exodus out of this and so he goes again I still think the relationship between upper market beyond interest rates the relationship between the dollar, cryptocurrency other assets and stuff like bonds and bills and stuff like that I don't know if it's so set out right now but there's obviously a movement taking quite a bit really what's happening is there is talk in the G20 about doing some kind of global regulation on crypto which would be a huge L for all holders and especially for those that have some kind of ideological attachment to things like Bitcoin and Ethereum as a way to kind of extricate themselves from the traditional financial system I think that was a hard drive to sell anyway I personally believe this is why they're moving it out just to get some extra cash and protect themselves if anything happens in the near future folks stay tuned we'll be right back for a short segment you might think that if you want to be successful at trading in the stock market you're going to need a crystal ball after all it's impossible to predict 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and tiger's for just $1 for the year there's no cash or added costs when you join our community of traders sign up today and become a part of this educational community of traders just visit the front page of tfnn.com the Tom O'Brien show next on tfnn welcome back folks we're taking a look here the ESMIDI down about 5.5 6% Russell sideways the NQ still down just cracked over 1% right now on some lower volume this crack down here at least in the ESMIDI was at as high as what we've had earlier especially during the open on that uptick some quicker news and this is regarding Tesla they're about to invest 15 billion in the Mexican factories that they have a state governor in Mexico said on Monday that Tesla and its suppliers would invest 15 billion over the next two years in a factory that is still under construction an amount that is triple what the Mexican officials previously previously announced Musk said his company would open a gigafactory in northern Nuevo León state part of electric car makers push to expand its global footprint at the time Musk did not detail the investment but Mexican officials said the factory would involve a 5 billion investment at the time of it being initially disclosed on some interesting news for the day kind of along the lines of some of the science information I like to bring at the end it turns out that FDA says Sudafed doesn't work which is wild to me the leading decongestant used by millions of Americans looking for relief from a stuffy nose is likely no better than a dummy according to the government experts who review the latest research on the long question drug ingredient advisors to the Food and Drug Administration voted unanimously on Tuesday against the effectiveness of the ingredient found in popular versions of Sudafed, Allegra, Dayquil and other medications bottom studies when well conducted are not showing any improvement and congestion with phenolephrine that's one of the doctors we're looking at and he's an allergy specialist which is just nuts FDA assembled its outside advisors take a look at phenolephrine which became the main drug in the over-the-counter decongestants when medicines with an older ingredient Pseudoephedrine were moved behind pharmacy counters how about that guys anyways thank you so much for joining me we have Tom O'Brien up next the man himself I will be with you tomorrow and throughout the rest of the week and then we'll have Tommy back the week following have a great rest of your day


The grand ballroom at the main Charter Mechanic Association recently opened to the public for the first time in over 50 years. We spoke with Michael Levine of Acorn Productions at the gallery opening about his group's plans for the space. We are planning to do a variety of educational programs, acting classes, some stage readings of new plays and of course naked Shakespeare performances on first Friday of every month. And what attracted you to the It's beautiful and it's located right on Congress Street. Tell us a little bit about Acorn, your history and what you do. Acorn has been around since the late 90s. We've been through a number of incarnations. The first space we were located in was actually on Congress Street at 496th Congress Street and we were mostly just acting classes and we branched out in Westbrook and we started doing some children's theater productions, some full-length productions, both classics and new plays. And we also started our naked Shakespeare group which does free performances of Shakespeare for the public and also for educational institutions like colleges, libraries and other schools, things like that. And basically our mission is just to get people involved in the arts by having them act. Like we believe that acting is the most exciting thing that someone can do to get turned on to the arts. And what kind of acts are we going to see here tonight at the opening of the hall? We have a lot of different folks involved. We have dark follies, vaudeville. We have the apparatus dance theater. We have the improvised puppet project. Then we have people improv with running with scissors. We have our naked Shakespeare group. We have Michael Troutman who's a physical comedian, kind of a clown. And our last group is Stages Academy doing teen Shakespeare. And there's quite a variety of things that you have for tonight. Is that indicative of the kind of things that you put on? Well, we're pretty much straight theater. Like we do Shakespeare and we do new plays. That's pretty much our gig. But this space is a multi-purpose space. Acorn is only one of the tenants. We're kind of the lead tenant and the collaborator helping to fundraise the space and get it up and running and get the modern equipment we need in here to be able to use it as a professional venue. But these groups that are coming in are all their own companies. They all do their own thing. And we're just kind of helping to facilitate bringing it together. Tom, there was a lot of work that had to be done to get the certificate of occupancy to allow the Gallaudet Open tonight. What kind of work had to be done? We had to install emergency lights, exit signs. We had to upgrade the fire alarm system so that we had pull stations and modernized all of the existing horn and strobe systems.  So we had to increase the supports and just do some minor repairs. Actually, it's a remarkably good condition because the steel from 1870, from the 1850s is much better than it is today. In building this old, what kind of challenges do you face trying to do all of that kind of work? Well, the challenge is it's an old building. And so in this particular case, there's a lot of deferred maintenance. There's windows that need to be replaced because they're very old window. We're not replacing windows, we're restoring windows. We're also putting new storm windows to give us some better thermal protection. You also had some work done on the classic black front door. Tell us about that. Yes. We were fortunate to receive a facade grant from the city of Portland for $20,000, which we matched with our own $20,000. And that included restoring those doors. It involved repainting the front. The old granite had a number of anchor holes that were iron and it was a rusted stain. So we had all that cleaned up and we put in some new grouting so that it matched the existing granite and basically just kind of brought it back to life. And as you walk in, you'll see this beautiful mosaic. And we had that repaired by Caposa Tile, who donated their effort. So what kind of work still has to be done, major project? Well, we also have a grant through the main historic preservation commission to restore all of the front windows of this building on the Congress Street side. That's about a $36,000 grant. But we need to replace the other windows on the sides. There's another seven windows and each big arch window represents three windows in themselves. And what are your plans for the future for this space? We're hoping, besides doing First Friday Naked Shakespeare, that we'll be doing ongoing play readings and, of course, acting classes of various types. And if people want more information about Acorn or about fundraising to help out, where can they get more information? It's all on our website, which is acorn-productions.org.


In this discussion we will discuss the discussion question of describe the sales budget and how it is prepared. If we see a discussion question like this or an essay question like this we might want to fit in and start out with what the budget is. Remember when we think about the essay questions or discussion questions we're often trying to expand we're trying to put more information in there. First a word from our sponsor. Yeah actually we're sponsoring ourselves on this one because apparently the merchandisers they don't want to be seen with us but but that's okay whatever because our merchandise is is better than their stupid stuff anyways like this CPA thinking cap for example CPA thinking CAP you see what we did with like with the letters and this CPA thinking cap is not just for CPAs either anyone can and should have at least one possibly multiple CPA thinking caps why because based on our scientific survey of five people all of whom directly profit from the sale of these CPA thinking caps wearing this CPA thinking cap without a doubt according to the survey increases accounting productivity 10 fold yeah at least yeah apparently the hat actually channels like accounting energy from the quantum field ether directly into your head allowing you to navigate spreadsheets faster it's kind of like how in like the matrix when Neo learns kung fu or at least that's what the scientific survey saying so get one because the scientific survey participants could really use some extra cash if you would like a commercial free experience consider subscribing to our website at accounting instruction dot com or accounting instruction dot think of it dot com because we're more likely to pick up points if it's a discussion type forum just participating typically we'll pick up points if we're talking about an essay question then even if we kind of talk around the topic if we even if we don't know exactly what it is we may still be touching on some items that are necessary and then pick up some points in that way so we could start off that the sales budget is going to be part of the master budget type process it's going to be a formal process that we go in for the master budget and we can go into the objectives of the master budget to plan for the future to organize people to get people on on the same page hopefully to provide incentives for people then we can go into basically the ordering of the master budget when we consider a master budget we are typically considering in terms of a manufacturing company in this case because that's going to be like the most complex case and therefore we can go into it and say hey there's got to be an order in which the budgeting process must happen the end result will typically be those financial statements the budgeted balance sheet the budgeted income statement the starting point will typically be here the sales budget the sales budgets usually that's one thing that we would want to point out in an essay question or discussion question hey the sales budget that's where we begin typically because many of the other components of the rest of the budget will be dependent on the sales budget and you can think of the budgeting process as kind of a timing account it's more of an income statement related type of process typically because the income statement deals with timing and the top item on the income statement is of course sales so sales you can think you know that's kind of like the starting point as it would be the starting point of our budget the sales budget will include the sales typically in units and then we'll have the units times you know the unit price and that will give us the budgeted dollar amount of sales both will be important we're going to have to consider this in depth we're going to have to do analysis on this because we want to project into the future how many units we're going to sell and how many how much we're going to charge for those units and of course we might have to consider things like advertisement and whatnot to determine how many units we're going to sell we need the units in order to calculate things like a production budget that will be producing soon and a raw materials budget these things are going to be dependent on the units that we will be producing and of course the sales dollars is going to be kind of the starting point the top line in terms of revenue as we go through the rest of the budgeting process as well


Hey, this is Michelle Getzinger and I'm here with the Pittsburgh Your City show at the IV Center here in Aspenwall and Linda's gonna go ahead and she's gonna get me all juiced up with an IV. Hey, Linda, how are you? Good, so tell me what are we gonna do today? So I was thinking for today, we would do the eye prevent IV and I'll juice you up with some B vitamins, get you a high dose of vitamin C since it's cold and flu season, worried about all those viruses out there. I'm ready to get you still. All right. So this IV what's great about IV therapy in general is you don't have to take any of these supplements orally. 100% is available to you. You can have a higher dose. So you get all that vitamin C right to your cells. This one in particular, tell me about what's in this mixture. So this, it's our base IV, which is called the Eye Energize. So it's the B vitamins, B complex, which is B1, 2, 3, 5 and 6 with an addition of B12. And then magnesium, calcium and then the high dose of vitamin C. How long will one one bag take? They range for about 45 minutes is the average that it takes from start to finish. We do have a liter bag. This is half a liter and that takes about an hour and a half. But about 45 minutes. So why did you choose Aspymol? I grew up in this area. So I had known Aspymol for a long time and it's just a cute neighborhood. It is. So when I thought of opening, there was really no other spot in my mind. We're really excited. We're having some new changes coming up. We're gonna offer a couple new IVs and we're planning on doing mini bags. So if you just want to pop in and you don't have time for that 45 minutes and you just need a quick little boost. Hoping to get you in and out in about 15 minutes. How do you feel? I feel wonderful. My hands are freezing though.  Yeah. Fluids are room temperature in your body. It's obviously warmer, so you will feel a little chill. Thank you. Linda, thanks again. I had a great time. It's been so nice getting to know you and what you're doing here in Aspymol has been great. Thanks for coming in. Hope to see you again next time.


Profit-driven systems are driving us to our doom. I just read a disturbing paragraph in a New Yorker article about the Instant Pot, a popular electronic pressure cooker whose parent company recently filed for Chapter 11 bankruptcy. Quote, So what doomed the Instant Pot? How could something that was so beloved sputter? Is the arc of kitchen goods long but bends toward obsolescence? Business schools may someday make a case study of one of the Instant Pot's vulnerabilities, namely, that it was simply too well made.  It didn't break, it didn't wear out, and the company hasn't introduced major innovations that make you want to level up. As a customer, you were one and done, which might make you a happy customer, but is hell on profit and growth performance metrics, end quote. Just think about that for a second. Under our current systems for profit generation, which is the primary driver of human behavior on this planet, making a quality product that lasts a long time instead of quickly going obsolete or turning into landfill will actually drive you into bankruptcy. An article in The Atlantic about the bankruptcy filing similarly illustrated this point last month, quote. From the point of view of the consumer, this makes the Instant Pot a dream product. It does what it says, and it doesn't cost you much or any additional money after that first purchase. It doesn't appear to have any planned obsolescence built into it, which would prompt you to replace it at a regular clip. But from the point of view of owners and investors trying to maximize value, that makes the Instant Pot a problem. A company can't just toodle along in perpetuity, debuting new products according to the actual pace of its good ideas, and otherwise manufacturing and selling a few versions of a durable, beloved device and its accessories updated every few years with new features. A company needs to grow, end quote. This just says such dismal things about why our planet is facing the existential crises it's now facing.  Our entire civilization is driven by the pursuit of profit, and to keep turning large profits your corporation needs to continually grow, and your corporation can't continually grow unless you're manufacturing a crappy product that needs to be continually replaced or supplemented. And you can't manufacture those replacements and supplementations without harvesting them from the flesh of a dying world. As writer Robert Moore recently observed on Twitter, the fact that Instant Pot is already being framed as a corporate cautionary tale, the company that went bankrupt because they made a product so durable and versatile that its customers had little need to buy another one, instead of as a critique of capitalism is deeply, deeply depressing. It's really heartbreaking to think about all the ways human potential is being starved and constricted by these ridiculous limitations we've placed on the way we operate as a collective. Resources being allocated based on how well they can turn a profit stymies technological innovation, because the most profitable model will always lose out to less profitable ones that are more beneficial to people and our environment. Someone could invent a free energy machine that lasts forever and costs next to nothing, and even though it would save the world, you can be certain it would never see the light of day under our current systems, because it couldn't yield huge and continuous profits, and it would destroy many current means of profit generation. Science should be the most collaborative endeavor in the world. Every scientist on Earth should be collaborating and communicating. Instead, because of our competition-based models, it's the exact opposite. Scientific exploration is divided up into innovators competing against other innovators, corporations competing against other corporations, nations competing against other nations. If we could see how much we are losing to these competition-based models, how much innovation is going unrealized, how much human thriving is being sacrificed, how we're losing almost all of our brain power potential to these models, we'd fall to our knees and scream with rage. If science had been a fully collaborative, worldwide, hive mind endeavor instead of divided and turned against itself for profit and military power, our civilization would be unimaginably more advanced than it is. This is doubtless. We gave up paradise to make a few bastards rich. Our competition-based, profit-motivated systems limit scientific innovation, and they also greatly limit the scope of solutions we can avail ourselves of. There's a whole vast spectrum of political solutions to the troubles we face as a species, and we're limiting ourselves to a very small, very inferior fraction of it. By limiting solutions to ones that are profitable, we're emitting any which involve using less, consuming less, leaving resources in the ground, and leaving nature the hell alone. We're also shrinking the incentive to cure sicknesses and eliminate problems rather than offer expensive, ongoing treatments and services for them. Or even a project as fundamental to our survival as getting all the pollution out of our oceans. The profit-motiv offers no solution to this problem because there's no way to make a surplus of money from doing so, and in fact it would be very costly. So the pollution stays in our seas year after year. People have come up with plenty of solutions for removing pollution from the sea, but they never get rolled out at the necessary scale because there's no way to make it profitable. And people would come up with far more solutions if they knew those solutions could be implemented. How many times have you had an awesome idea and gotten all excited about it, only to do the math and figure out that it's unfeasible because it wouldn't be profitable? This is a very common experience, and it's happening to ideas for potential solutions to our problems every day. The profit-motiv system assumes the ecocidal premise of infinite growth on a finite world. Without that, the entire system collapses. So there are no solutions which involve not growing, manufacturing less, consuming less, not artificially driving up demand with advertising, etc. It's hard to appreciate the significance of this artificial limitation when you're inside it and lived your whole life under its rules. It's like if we were only allowed to make things out of wood, if our whole civilization banned the entire spectrum of non-woodcraft innovation. Sure, such a civilization would get very good at making wooden things, and would probably have some wood-crafting innovations that our civilization does not have. But it would also be greatly developmentally stunted. That's how badly we're handicapping ourselves with the profit-motiv model from the pursuit of viable solutions. And some solutions would be really great right now. This planet just had its warmest week in recorded history, and Antarctic sea ice is now failing to form in what, for the southern hemisphere, is the dead of winter. Even if you still want to pretend global warming isn't real, this planet's biosphere is giving us plenty of other signs of looming collapse, including plummeting insect populations, a loss of two-thirds of Earth's wildlife over the last 50 years, ecosystems dying off, forests disappearing, soil becoming rapidly less fertile, mass extinctions, and oceans gasping for oxygen and becoming lifeless deserts, while continents of plastic form in their waters. So our need for immediate solutions for our environmental crisis is not seriously debatable. But we're not getting solutions. We're getting a world ruled by corporations whose leaders are required to place growth above all other concerns, even concerns about whether the future will contain an ecosystem which corporations can exist in, or a human species for them to sell goods and services to. Corporations function as giant, world-eating sociopaths, because our current models let their leaders and lawyers wash their hands of all the consequences of the damage their monsters inflict, in the name of growth and the duty to maximize shareholder profits. People worry about the world getting destroyed by machines driven by a heartless artificial intelligence, but we might end up destroying it with a kind of artificial mind we invented long before microchips, the corporation. So much of humanity's dysfunction can be explained by the fact that corporations, A, pretty much run the world, and B, are required to act like sociopaths by placing profit above all other concerns. As long as human behavior remains driven by profit, ecocide will continue, because ecocide is profitable. As long as human behavior remains driven by profit, wars will continue, because war is profitable. As long as human behavior remains driven by profit, exploitation will continue, because exploitation is profitable. As long as human behavior remains driven by profit, corruption will continue, because corruption is profitable. There is no good model in which human behavior can remain driven by profit without these destructive behaviors continuing, because so many kinds of destructive behavior will always necessarily be profitable. No proponents of any iteration of capitalism have ever been able to provide any satisfactory answers to this. The call, then, is to move from competition-based, profit- driven systems to systems which are based on collaboration toward the common good of all. We're a long way off from that, but a long way can be cleared in a short time under the right conditions. Our species is at adapt or die time, and the adaptation that must be made is clear.


Good morning, everybody. Let me introduce myself and our team. My name is Vladimir Anisimov. I am chief of department of cardiogenesis and oncology at Petrov National Medical Research Center of oncology in St. Petersburg. Professor Zharinov is head of radiology department at Russian National Center Radiology Surgical Technology was opened in 1918. Our institute was opened in 1927. Dr. Bogomolov and Dr. Niklasova were working together with Professor Zharinov. Dr. Cheprunaya was working at St. Petersburg Clinical Scientific and Practical Center for specialized types of medical care. Low picture. It picture of free hour institute. Next couple words about history of our research. In 1961 Dr. Mordechai Schwartz published paper showing the patients died when the tumor reached its critical size. Approximately 10 in certain power. The survival of patients depends on the tumor rate. There are a lot of data on tumor doubling time. Mainly paper devoted to proliferation. But cell loss, which is very important part of the natural history of tumor growth, is much less paper. So in 1989 it was shown for the first time by Dr. Zharinov, that in the patients of cervical cancer patients who have fast growing tumors have less cell loss than people, women who have cervical cancer slowly growing. It is a second paper by Dr. Gennady Zharinov, that our team shown that cell loss plays a principal role in tumor growth. You see, local prostatic cancer have much more cell loss frequency, incomprehensible to metastatic. Баланс-терапия is non-dimagine treatment aimed at maintaining balance between proliferation and cell loss in order to increase the life span of cancer patients. Efficiency of combined treatment of prostatic cancer patients was improved by use of melatonin as an element of balance therapy. Хистерия of melatonin rather short. It was firstly isolated, melatonin was firstly isolated in 1958 by our own learner from Paneo-Gland of Kalf. In 1973 we have shown melatonin in Hibis mammary tumor mice. It was first paper on this matter. In 1974 melatonin was discovered in enterechromatine cells in testines in some other tissue by Igor Kvitnoi. In 1980 it was shown by IFF-2-2 France-Paris. The H-rated declares production secretion of melatonin. Вайтер Перпауле, в 1987, first published paper, The Melatonin increased life span mice. And a writer from San Antonio, Texas, showed melatonin as potent antioxidant. In this picture you can see that melatonin Hibis tumor adgenesis in rodents a lot of size, localization, mammary, cervix, colon, skin, soft, libre, lung. МайорITY was done in our lab. We also study effect of melatonin treatment in stomach cancer and colon cancer patients. Recurrence time was extremely increased by 27% in patients with stomach cancer. Meta-analysis of 10 randomized trials showed decrease in one year mortality up to 0.66 in solid tumor patients. Some illustration of our research. Melatonin sufficiently inhibits colon cancer and adgenesis induced by dimethylgitrazine in rods. It's accomplished by the depletion of mitotic index and stimulation of apoptosis. Tumor incidence was dramatically decreased. Another paper was published in International Journal of Cancer. We have shown the constant elimination increase accelerated the mammary carcinogenesis in transgenic mice. A treatment with melatonin inhibits expression of disengagement at decreased number of tumors, size of tumors and number of tumors per animal. Thus, let me show the design of our study. It was involved 955 patients with prostate cancer which received combined treatment, hormonal radiation, since 2000 up to last year. Тритая группа 396 patients were treated with melatonin. It was around 30 minutes before sleeping, except winter, because winter level of melatonin is good enough. Control group was not treated with melatonin. It was 559 patients. Groups were subdivided according to prognosis. Good prognosis, favorable prognosis, localized prostate cancer. Intermediate prognosis, localized spread. At metastatic prostate cancer it's bad, poor prognosis. It's much maximum number of patients. Main result are shown on this slide. Good prognosis and intermediate prognosis have not strong effect on survival of prostate cancer patients. However, median survival of melatonin treated poor prognosis patients was more than two times higher than in control group. 40, 64 months for control group and 153 months treated with melatonin. We conclude the methods of balanced therapy and improving survival of cancer patients. We plan to continue studying the factors influence the rate of tumor growth proliferation and cell loss in cancer patients. At present we have data on good effect of melatonin in breast cancer in women but melanoma was unsuccessful. Thank you for your attention.


Hello, everyone. We welcome to today's sections on democratizing ML pipelines and bringing ML workflow to heterogeneous cloud-native ML platforms. My name is Tommy. I'm a senior software developers at IBM Open Tech Teams. And I also have my colleagues, Yi Hong Wang, here to help me as well. And let's go into today's sections. So in the ML workflows, we can see in the high level we have different phrases. From the data phrase, we have teams that need to draw data, analyze data. And we have data science team. They need to do machine learning, deep learning, and create the models. And finally, we have operation team to deploy the model and maintain the model. So we can see a lot of different teams working on different parts of the ML life cycles. But when we actually break it down into automation and have different teams responsible for each different sections, we can see it could break down into a lot of smaller sections as well, like from data preparations, cleansing, ingesting, analyzing, transforming. It could all break down into different teams and different workflows. And when we need to connect all these kind of workflows together, we could see a bit overheads on team need to porting different components into a different platform with different technology sections and stacks. So that's why we want to have a heterogeneous pipeline that could be able to run with different kind of environments. And based on different requirements, they could actually pour into a same type of information and metadata that could be shared among each other. And when we actually look into how to do that on Kubernetes, there's two popular projects that could actually do that. One is actually Agar workflows. So Agar workflow is a project that is able to containerize workflow engines for orchestrating parallel jobs and able to implement the whole pipeline as a Kubernetes CRD. And you could see Agar workflows provide very nice UIs. And all the components actually wrap it into a pod, so actually have a dedicated environment. And then it also could run as a DAG, so it's a subtext. So it's actually very easy for you to create very complex graph when you have very complex machine learning workflow as well. And then there's another option called Tecton pipeline. That's where IBM's and a lot of the company working on OpenShift that's using, because Tecton pipeline project also provides Kubernetes-style resource for decorating CI-CD-style pipelines. And they actually able to break into two different kind of runs. So you could actually have runs that is wrapped into a pod, have a dedicated environment. But you have common tasks where you need to just run it in the same environment. You could also have a dedicated controller to do a very fast job. Let's say like primary storing or just caching. You could use a controller to actually handle that without creating a dedicated pod environment. And why this is important to run on OpenShift? Because OpenShift pipeline is a project that OpenShift container platform have created. And this is the de facto CI-CD capability on top of OpenShift. And it's actually certified by Red Hat have dedicated security scans. And it also have the enterprise version available on OpenShift. So all enterprise users that want to run on OpenShift have a secure environment. This is kind of the de facto pipeline they need to run. So we can see from different user in different department they might have different pipeline system they want to run their ML flow flows. So now how can we connect all of them together? This is when we actually look into a project called Q4 Pipelines. So Q4 Pipelines is actually another stack that's run on top of Argo workflows and Tecton workflows as a connected layers. So Q4 Pipeline actually provides any ML framework that you could do. Let's say you want to use PyTorch for model training. You want to do like prompting. You can all done on QFloats. And it also provide a very nice Python SDK and DSL for DSI users to craft their pipelines. As we can see, a lot of the CI-CD workflow environment, they don't really have a robust interface for prompting pipeline. So Q4 Pipeline provide a very nice interface for client DSLs. And the DSL actually give capability to define inputs and outputs and conditions. So you could just actually craft the pipeline just like how you do a regular programming language. And I think the very needed feature is actually parallel loops. As we can see in machine learning workflows, a lot of the problems need to be parallel executed under different environments. Let's say you want to train models with different parameters. Looping feature is very common within ML workflow platforms. And the very nice optimization that Q4 Pipeline provides is that you're actually not executing the pipeline itself. You're actually leveraging whatever platform you have. Let's say you have all-go host stacks as your CI-CD. You could leverage that. You have an enterprise requirement that you need to run an OpenShift pipeline. You could also leverage OpenShift pipeline to run all your actual workflows. And on top of that, it actually provides good experiment metadata tracking. So all the metadata could be shared between different platforms. And also provide garbage clean-ups as the default workflow environment usually don't have garbage clean-up and caching. And this is what Q4 Pipeline aims to provide. And as we work on Q4 Pipeline, especially on the TACCOM versions, we see in the early stage, you create a very dedicated UI to have version control for the pipeline. And they build a display of a very nice graph for the pipelines. And do garbage collection have a dedicated DSL and API to reduce Kubernetes costs to the Kubernetes APIs or reduce the actual traffic to the Kubernetes stack itself? And then because we don't want to intervene the actual workflows under the back end, in the V1 version, we actually just caching using part mutations, which is actually one of the bottlenecks we will actually discuss, how we mitigate that later on. And another benefit is actually have experiment and run trackings, where you actually provide a very good way for data science to organize their runs and able to put them into different experiments as you create different models. And they also have metadata trackings, where you can actually see how your input and outputs is being leveraged between different components. And the powerful part of metadata tracking is that it actually gives you information on what data the model is training on. And actually compute different model runs and compute different metrics. And then let's say you have a caching capability. You've got to carry over the state from previous models. And then we use the computer outputs so we don't have to like, we do the training process. Let's say, oh, the pre-processing process, you expect the result to be the same. And as we kind of discussed with the earlier approach of the Q4 pipelines, we kind of see that as we just caching using part mutations, we kind of see there's still bottleneck on. A lot of the caching students need to create that they get a part because we don't want to intervene the actual pipeline flows. So we got to see a big bottleneck on the part creation and also on the scheduler itself. Because as we have thousands of parts needed to be created. And even with caching, all those parts do need to be created. And that kind of create a very big bottleneck on large scale ML workflows. So we can see from a schedule perspective, creating a new part actually takes a lot of time. And I think the most important case is that with the Kubernetes limitation, where with each GRPC call, you're kind of limited on four megabytes of data. We kind of wrap everything into one single graph. You could start seeing the bottlenecks on graph traversal and validations. And this is what we actually need to mitigate as well to break down the graph into multiple smaller ones on Kubernetes. So it can actually scale to like thousands or tens of thousands of tasks. As we can see with the modern AI and ML workflow, it can actually grow to that scale. And now we're going to pass to Ihan to talk about what we actually improved in the new version of Kubeflow Pipelines. Yeah. Thanks, Tommy. So in here, we just have a high level design for you to reference that this is for the Kubeflow Pipeline V1 design. So like Tommy mentioned earlier, actually, we run the Argo implementation and Tecton implementation. It's kind of two separate side-all projects. But that's for the V1. So if you are familiar with Kubeflow Pipeline, it has been out there for several years. And a lot of people adopt it and use it. But meanwhile, I mean, the concept of the ML workflow and ML apps and even the best practice for the ML workflow are kept involving. So it's actually unsurprisingly that Kubeflow Pipeline actually was at a pivot point where in order to fulfill those new features that are coming in that and also have a better integration with those internal components altogether, actually having a better design and big change were inevitable. So actually, about one or two years ago, probably, the Kubeflow Pipeline team, kudo to the Google team, they start to work on a new design and then also review the design at their community meetings regularly and then work on the implementation in both Argo and also Tecton. There are many work on the Argo side. And me and Tommy, we are many work on the Tecton side. And finally, we got the new release version earlier, I think, one or two months ago. So actually, I encourage you to actually try it out. And we would like to get some big feedback from you. And at the same time, we will also keep working on it and make it more complete and stable. So the reason I bring up the view and design here is that you can see, like Tommy mentioned, we start with the KP. We provide the DSL so you can use the Python to compose your ML pipeline for and use the SDK to actually to compile and compile the Python program. And you will get the pipeline specifications. And at that moment, actually, for the V1, when you are using Argo, it's actually give you the workflow custom resource, which will run on Argo, definitely. And if you are using a Tecton, it's give you the pipeline run custom object. So it's totally different. So when we try to, during the design phase for the V2, we actually gather all those lessons learned and the requirement from the V1. And there are a lot of new feature and requirement. So I try to characterize them into actually two main goals actually we want to achieve in the V2. The first one is because you can see here, we are using the pipeline. The pipeline spec that we are using is actually different from each runtime. So we want to consolidate the pipeline spec into a uniform language that is not it's detached from the underlying runtime. And also the metadata that Tommy mentioned earlier, the data we store in the metadata store and also the way we use it is not ideal. So we actually want to improve it and to make it more efficient in the whole system. And the second one is that we also want to, you can see that we actually very, very, very tied to the underlying runtime engine to run those pipeline. So we want to actually decouple some of the ML execution for from the underlying runtime engine. In that case, we can get more control. And then the ultimate goal is that you can actually easily bring the cool flow pipeline, actually, to other runtime engine if you want. So that's the ultimate goal. So actually, instead of 10,000 feet perspective, so I would try to dive into the detail of the new design in this session. So let's start with the first one, the pipeline spec. So in the V1, like I mentioned, the pipeline spec is directly tied to the underlying runtime engine. So even in the UI, you also need to understand two different languages. One is from Argo, one is from the tech town. And because that pipeline artifact is directly run on Argo and tech town, we also need to build in a lot of backend logic into the pipeline. So in the V2, we try to introduce another spec. We call it intermediate representation. We call it IR. So we define the IR as actually the pipeline spec. So it's actually easier for you to understand because it's also in the EMO format, but it's easier to understand because when you compose a pipeline, like Tommy mentioned, you will try to compose the DAC in your pipeline. So we are using more intuitive syntax to help you to compose the IR. And it's also a platform agnostic because we will use this IR in every runtime that we support. And it's also exchangeable because I will talk about it later. And the bonus part is the UI because right now UI don't have to understand Argo. You don't have to understand the tech town. The only language you need to know is the IR. And based on the IR, if you are using it, we try to promote it as kind of the open standard to define an ML workflow and even the small task. So if you share this kind of IR, you can actually share it to the whole community. And even you can phone maybe a central repository to store those IRs. And it's actually opened up the possibility that actually you can actually build an ML component ecosystem for a computer user, even from the vendor. So they can all use this IR to share the component or maybe the piece of the pipeline into this kind of central repository just like you have the, we store all the image on the Docker Hub or the Quail IO. So if you use the IR to share the component and also someone build a central repository to store it, it will be perfect. So people will, in the ML world, we can easily exchange those IR with each other. And furthermore, I think, inside, based on this assumption, actually inside the KP SDK, we also provide a register client that you can actually talk to this kind of compatible component registry. So you can actually pull the component or the pipeline on the flight when you are composing your ML flow. And actually the ultimate goal is that we try to promote the local and local approach to compose ML pipeline. So you can imagine that if there is a platform that can support the component registry, so you can actually automatically pull down those components from the component registry and show up, for example, on your right-hand side. So you can just easily drag and drop those components and link those pieces together and compose your ML workflow. It will be perfect and easy, right? So that's the ultimate goal. And so that's why we introduced the IR. And the next step is that, since we introduced the IR, so you can see that the design is a little bit different. So we, but it starts from here, right? Originally, we have the artifact that comes from the ARGO or Tectang. Right now we replace it with the IR and then you submit the IR to the pipeline service. But one thing that we also need to introduce is another component we call the back-end compiler because ultimately those pipelines still need to be executed on the ARGO or Tectang, right? So although we define the IR as the pipeline spec, so inside the pipeline service, we introduce another component we call the back-end compiler, which you can think is like an interpreter that he can interpret the IR and into the runtime engine that which you are using right now. For example, if you are using ARGO, it will, like I said, you will transform it to the workflow if you are using the Tectang, it will transform it to the pipeline run. So you can, with this kind of design, you can easily actually swap out the underlying runtime engine. But wait for it, we still need to have another extra component here to actually fulfill the whole lifecycle. It's called the abstract layer. So you are thinking the pipeline service actually right now need to talk to different engine right now. So we are trying to come up with a plug-in mechanism that actually help the pipeline service to actually talk to the whole underlying different engines.  So for the pipeline service, it won't touch directly to, for example, the ARGO controller. It won't touch directly to the Tectang controller. It will talk to this unified interface. So like I mentioned, I think here we want to promote this kind of mechanism is that if you have your own runtime, you can easily just implement this interface and plug in your runtime into the KUFO pipeline system and now he can support your own runtime to run the pipeline. So that's enough for the IR. So if you remember the second topic we want to tackle is that ML metadata. I think in the V1, you can see the design for the V1. We have a component called MLMD writer. It's actually running as a synchronous Python program and it's actively monitored the Kubernetes part. That is created when you run in the pipeline. So you can see it's actually and kind of running a synchronous fashion, right? So it's only way, it's keep waiting for when that task is finished, the part is finished so it grab those data, input data, and output data and store into the metadata. That's not efficient and in this way it's actually hard to actually integrate, to reuse the metadata information inside each step of your pipeline. So in the V2 we try to actually embed the MLMD into the pipeline execution. As you can see here, all the component is meaning that it's a subset of the pipeline. So it's actually directly talked to the MLMD so we remove the MLMD writer. So in this way, actually the MLMD will provide extra benefit for the whole pipeline. For example, you can actually use the MLMD to support caching because all the tasks are output input and output are stored in MLMD immediately after the task finished. So if you have another task, actually it depends on that finished task, you can actually immediately talk to the MLMD and grab those data. And the other thing is that you can support caching because when you spin up another pipeline wrong and the pipeline is actually ask you the same component with exactly the same parameters, you actually don't need to run that component again. You can just grab those results from the metadata and then show it to the user. And the other benefit is that in the UI right now when we show the real-time pipeline wrong status, we can also get those status from MLMD directly. So furthermore, I think when you look at the component here, right now I will dive into a little bit for how the components are wrong and how the component are leveraging the MLMD because earlier in the V1, when we run these components, this big component, we actually directly rely on the underlying engine. We just put that task to the Argo to the task for the Tecton and you will run it for us because the MLMD is run asynchronously and collect the part information separately. But in here, we try to promote the task directly push the input and also the output to MLMD. So we introduce another mechanism we call smart runtime. It's actually a driver executor and published wrapper. So in this kind of fashion, actually driver will, when the text starts, it will actually start with the driver. So driver will help to do some, the preparation steps. For example, if there is any parameter that you want to get from the upstream task, you can actually talk to the MLMD and get those value and substitute those value as the real value and put it there for the executors. And when the executor finish, actually you can see just like a wrapper, wrap around user's task. So it will actually run the user's task and by the end of the user task, it will also publish all the results into the MLMD immediately. So that in this kind of mechanism, like I mentioned, if you have any downstream task, which depends on your upstream, you can immediately pull in those data from MLMD. So I think those are the mechanism and new implementation we bring into the V2. And I think the goal is actually making the V2 could be actually porting into, to support different kind of runtime engines. So I think here I will just hand back to Tommy. He will cover about some of the performance improvements that we did in the V2. Thank you, Lihang. So as you have learned from Ihang, so Ihang have demonstrated a new way to implement Q4 pipelines where now all the Q4 pipeline components actually represent intermediate representation. So in the actual Kubernetes layers, you just have to store all the pipeline into one single custom resource definition. So we can actually break down pipeline into smaller pieces. But I think one of the downfall of this is that as we kind of implement this whole, all the features and have features complete, able to pull different pipeline DPP between different backends from different users, we see that we introduced the driver publisher and executed components. And because of those components, we have now introduced a new smaller layers of like code need to be executed. And what optimization we have done in the beginning is that from a tactile inside, we actually introduced custom task controller where all these common tasks just publishing and retrieving information could be done in a common controller, so we don't have to create extra part for that. In the algo world, the committee is working on the HVT template to replicate the same approach. And the result is pretty promising. And we could see like the runtime could be reduced significantly, which we'll show it later on. And the second phrase we want to improve is that as we introduce this new driver and publisher task, the graph complexity actually gets very bad when it scale up. As we can see, each graph, when you connect the driver layers down to all the tasks you need to run, you actually need to connect all the roof notes and for the publisher, you need to connect all the leaf notes to actually publish all the information once the sub graph is finished. So this actually introduces a big graph complexity and we need to improve that. And so I think the first phrase we have done in the current state is that we kind of combine, at least from the container, from the task level, publisher and drivers, we merge them into one and also give the capabilities of the task able to run anything that's not a part as well. Because over to the design, we expect all the user tasks to be just a part of the containers. And as we can see, in real world scenario, you actually have different training platforms and preprocessing platform that leverage Kubernetes resource. For example, you might want to use Spark jobs for preprocessing, you just want to create a Spark component and you don't want to just run your components in a pod, right? You just don't want to run a client. You just want to run a CRD in your Kubernetes platform and we're able to provide that capabilities in these new designs where the user component doesn't have to be a container. It could just be a custom resource as well. And some of the, so I just kind of like high level, we cap on what a Q4 problem V2 brings. With this new design, the caching is actually handled by the new driver code so we don't have to do like part mutations. That's significantly reduced the amount of part that we need to schedule and we need to create on the Kubernetes clusters. And all the code would be uploaded, all the parameter and all the fact are actually uploaded by the driver and publisher itself. So we actually need to bypass some of the workflow like workflow engine level limitation as we can see from a performance, at least from TecTons. TecTons have a limitation on parameter passing because even in August, well parameter passing is very difficult on the workflow level because they need to watch a user container to be finished and then publish those information back to the workflow itself. So usually they need to run a cycle or have to run some process right after the user component is finished. So that's why that creates this kind of limitation. And with the Q4 problem, the new design we have to create our own binary to push all our information to our dedicated metadata server. So no matter what platform you use, those metadata will be shared and the workflow engine itself doesn't have to handle like a big chunk of data. And finally, because we need to integrate and also merge all the information because right now we're actually breaking a lot of pipelines into smaller pipeline on Kubernetes, all those suddenly to be aggregated together. And this is also what the new design going to bring where when your subcomponent is finished those information will be pushed to Q4 pipeline and Q4 pipeline will aggregate a very nice graph for you. And behind the scenes all those smaller graph actually execute individually on Kubernetes. So you actually reduce the limitation on the Kubernetes custom resource definition limit on itself. And with this I'm going to just demo what it looks like with the new design and how you actually see Q4 pipeline bring a very nice UI and how it could actually pass different metadata across different backends. So in the Q4 pipeline UI you could actually see this multiple pipeline you could create. And on the pipeline you create we actually have added credibility with how to create different versions. For example, in this case, by default I have Q4 pipeline will have all the components enableable caching but let's say you don't want to have caching for the training you could actually easily I just pick the version where I make training without cache you could actually enable that in the SDK as well. So once the compiler finished the compilation into IR you could actually see the cursor is a bit problematic. Give me one second. You could see like for example so pre-processing you want always enable like true because pre-processing you're always processing the data into the same results so it makes sense to always have a truth. But as we can see for the training things should have a false over here. Sorry, the cursor is a little bit problematic. This one, make sure I'm in the right version. You can do search. I think on the training side I think the caching should be set to false. So that way when you actually do the training part the training itself is actually always been executed and you want to make sure the algorithm itself using the same data always converge to the same results so sometimes you might want to have the training set to false. As we can see that once you have the caching enables when you have all the components being cached all those components you could see could be executed in less than one second. So with all this information if you have everything cached you only have like two second bottlenecks on traversing the whole graph and able to pass all the information and metadata information displayed over here. And I could kind of show you examples just to run. I think this one might upload by mistakes but let's see. It will kind of run these pipelines over here. For the component that is being cached you could see the cached component would be completed immediately and give you this results because the results are stored in a centralized ML metadata service. And then the training steps where you always want to train so it would just take the cached components into the training process as you could see from the log it would just start the training and from a data science perspective you want to always make sure your models converge to the same results using the same data. So in this case it makes sense to actually always train and produce a new model to make sure all the models when they use the same data able to converge to the same results. And all this metadata could be shared with different backends. So as you could see this actually able to improve the performance significantly. For examples, you just want everything without caching with the pipeline you actually take about 30 seconds for this but if you're able to like at least cache the pre-processing if you're able to reduce at least the performance by one third of it. And if you have more information need to cache you actually significantly improve your overall pipeline runtime as well. And that kind of concludes the demo itself. I'm going to go over what will be happening next with the Q4 pipeline projects. As we can see we have done a lot of improvement in terms of caching breaking down the graph itself and able to scale out significantly. But we could still see like the extra abstract that we introduced from the driver and publisher logic itself kind of makes the graph transfer a little bit more complicated. So in the next phase we want to actually embed all those driver and publisher logic into as part of the controller and we were working with different backend workflow community to actually make this as pluggable. So this way we were able to reduce the graph complexity from the new design as well but also have all the nice feature of uploading and downloading all the information and aggregate all the status into a centralized metadata service where it could share between different backends. And the beauty of having a centralized metadata service is that not only the current phrase Argo and Tecton could use it but also when you introduce a new let's say workflow, let's say ML flow or let's say a very workflow we want to introduce that's not run on Kubernetes. You could easily leverage the new abstracted layer from Q4 pipeline introduce a new backend and share the same metadata service between different teams. So this is kind of like the angle we want to aim for Q4 pipelines. And you want to learn more about the projects here are the links to the core Tecton product itself. We have the Q4 pipelines on tower Tectons and also you want to join the community meeting could come check on the Q4 stack. And also at the end, our IBM Watson X products also run on Q4 pipeline to leverage the orchestration on all the workflow components. So you go and also check out what's actually interesting using large language model and also create a new workflows for your own model as well. That's it. Thank you very much. Any questions? I think we're wrong over. Sure. I think we're running out of time. So you have any questions to review the access? Yeah. Thank you. Thank you.