Good morning, everybody. I'm Tommy O'Brien, coming to you live from TFN headquarters in St. Petersburg, Florida at 10 a.m. Eastern time on Tuesday, 30 minutes into the trading day. We've got markets in red territory to start things off. S&P is negative by five points, trading at 29.37. We've got the NASDAQ negative by 51 points.  Notes and bonds, higher price lower yield, 10-year note up five ticks, 123.18, 30-year bond up 11 ticks, 147.10, dollar index negative 337 ticks, trading at 97.245, and golden oil volatility as well. Gold up $2, make that $3, trading at $12.84.50, oil up $0.43 at $63.92. We'll start it off. Let's jump over to the charts. We'll start it off with the Dow. So a little bit of roller coaster this morning, 8 a.m. We spike from about $26,594. We reach a high at $26,640. We're now off more than 100 points from that level, and you can see kind of the escalation. There's your 930 opening bell bar. We're sitting right at about $26,600. The Dow trades down 100 points in the last half hour. NASDAQ 100, volatility as well, backing up the chart to last night on Google Alphabet earnings. You have the NASDAQ 100 trading about $78.58. We're down a solid 60 to 65 points from that level of $77.92 in that NASDAQ 100. S&Ps, early this morning up there at $29.45. We're now off about nine points from that level, trading $29.36. Gold contract, volatility as well, just since about 8 a.m. this morning. You trade from $12.87 down to $12.82. Back up to $12.87. Gold trading at $12.84.58. Crude oil, volatility as well, quite a run from about 2 a.m. You trade from $63.37. We trade all the way up to a high this morning of $64.74, and we're now about $0.90 off that level just in the last hour, $63.85 at the price of June Crude and Euro US Dollar. As we've seen some dollar weakness, Euro strength, Euro trading $1.12.20. Jumping over for that chart on Google last night right now, you got Google Alphabet trading down 8.2% down more than $100 and tonight after the bell, Apple down 1.3% ahead of that, kind of falling off right on that open. Opened above $2.03, Apple trading at $2.096. Stay tuned folks, come back at 10 o'clock with Tom at 11 of course, we've got Fast Market, TD Ameritrade, Kevin Hinks, Tom White and the team, Basil Chapman, Steve Rhodes, Dave White, Tom O'Brien all this afternoon. Stay tuned folks, have a great Tuesday.


All right, so I want to give a quick shout out to everyone that has placed orders over the last day or so. Your tools are on its way and I appreciate it. All the carving combs, the brushes, all that stuff. If you want to get some, freesloneducation.com. Thanks for the support guys. Let's get this vlog started. All right, so we just ended a fun day of cutting in the salon today. I put together a haircut for you guys that I think you're really going to like. It's a consistent layered cut within a medium shape. So let me show you guys what that really means. We have a nice strong fringe, nice consistent layers throughout, medium length hair. They can wear this curly, it can wear it straight, but really what we're going to work on today is focusing on shape and consistency, elevation, over direction, all of those things. So check out this vlog guys. I think you're going to like it. Thank you so much for posting all of the comments that you have been every day and helping support the vlog and sharing it and all of that. So thank you for that. Here we go. Let's get started. All right, so we're going to start off today's technique using the basic four quadrants. This is definitely something that probably the first thing that you learn in beauty school is a section high point of the head down to behind the ear and then directly down center back and a center parting in the cut. And we're going to work from the occipital bone over to behind the ear. That's going to start off really what I want to do. We're going to create a, we'll call it square layers or even layers, whatever is comfortable for you guys. But we want to create a straight line of layers horizontally in the back. We're going to take vertical sections. I broke up the back quadrant into two. So from occipital bone down, we're going to work that to the nape of the neck. But I'm just creating a nice straight line vertically within this haircut. Now the key things that you want to focus on during this cut is your over direction. I'm over directing to the previous section so that I can create a straight line horizontally. So hopefully that makes sense. But you'll see my scissor technique within this is when I'm lower, I'm going to work with my thumb in the opposite direction in the scissor. That's really just for comfort. If you guys are comfortable cutting the normal way, that's fine. But when I work on that top section, I'll be cutting a typical palm to palm way. Now I'm working vertically. You'll see me take some new hair, separate my guide in half, and just make sure that you have a clean guide that you can see through the cut. That's vital to creating that straight line in the back and keeping that consistency. Now when I get to the corner of the cut, this is really what's going to create the square feel and push that weight into the corner. We're over directing everything straight back. So everything straight out of the head from the center back, but then as we move forward, everything's still coming straight back to me. So body position is important in this to make sure that you're standing directly behind the head and that you don't round off that corner and create more of a round shape in the haircut. So now I've moved into my second quadrant, which is on top of the head. This is where the buildup of weight is going to happen. And I think a lot of people have challenge with layers because they don't recognize the fact that the head is starting to move away. This is where we're going to build up a ton of weight in this haircut, which I actually really like and I think it creates a really nice shape for this particular cut. And we're going to go in and do some dry cutting to skinny up that weight later on. So I'm okay with it. But it's really important to understand what is happening with the weight because even though we're over directing this back to the same exact spot and same exact elevation, everything's straight out, it's still shifting the weight differently within the haircut. So make sure that you keep that in mind. Again, we're going to get to this corner and everything's going to come straight back to us. So the best way to check your consistency, we're going to do it in a second. We're going to do a little bit of cross checking. So what I'm going to do is take a horizontal section and pull that out and just check it with my fingers to make sure that I have a nice horizontal straight line. And that lets me know that I stayed consistent throughout that entire panel. Now we're going to take the same thing, occipital bone over. The difference in this part of the cut is that I always want to be combing the new hair that I'm taking into my guideline. My guideline is coming from center back of the head. So now I'm going to be scooping underneath the hair, still using the fine teeth of my comb, but pushing that hair with kind of a backhand motion into my guide so that I keep that guide nice and strong. If I were to do it the opposite way, the same way that I did it on the left hand side, I'd be pushing my guideline from where it lives. And if you do that, you create a shorter guide every time. So you're going to end up with one side of the head longer than the other. So you can see same scissor technique. So as I'm working on the bottom, I have my thumb in the opposite direction. This takes a little bit of getting used to. It's something I've been working on lately, but it definitely helps out a lot. I was just showing you guys right there that everything's going to come straight back. If you over-direct too far back towards center back of the head, you're going to get too much length on one side. If you over-direct too far to the right towards the ear, you're going to get less length and you're going to round off the shape. So you want to make sure you're straight back on the head. So now we're working on top of our fingers. As we work across the head shape, the hardest part when you have your elbow in the air like this is to keep that elevation. So it's really important to have a strong guideline as you work through this part of the haircut. The reason I have my elbow up in the air is because if I was still to continue working palm to palm, which you could, if you put the head low enough, you'd be alright. But this is more comfortable for me, so this is the way that I'm going to do it. But if you guys want to do it the other way, you absolutely can. So working through straight back again, keeping that consistency, keeping that nice straight horizontal line, working those vertical sections and cutting the hair. So you can see that buildup of weight that's happening right around the occipital bone. That's because of the way that the head shape is turned. So if you look at the top of this section, we're cutting at basically zero degrees. So it's definitely going to be at the heaviest point right at the top of the layer. When you guys do those haircuts and you see that you have that kind of top heavy layer in your haircut, it really has everything to do with elevation. We're creating it purposely in this cut, but in future cuts as you're working, you may want to elevate the hair a little bit more to take out that weight. So now we're just going to find the corner of the cut and create a horizontal parting along the parietal ridge, and then we're going to work vertical sections based off of that. So if you see that short point right there, that's our guideline from the back. That's matching up the corners of the cut. We're also going to go through and cut this shorter, this hair shorter. So what this layering is doing around the outline of the haircut is just skinnying it up, and then when we go through, we can cut our solid blunt line at the end. So straight out from the head, same thing, working a traveling guide. I know you guys can't see every angle of this, but everything's coming straight out from the head and just working that horizontal line like we've talked about. Same thing on the opposite side, combing the hair back into my guide. That's the important part, just make sure on both sides of the head that you're always combing that new hair towards the guideline. You don't want to shift your guide from where it should be coming out of the head. As soon as you shift the guide, it diffuses the line, and that's where a lot of questions have come in. How do you keep a strong guideline? You don't move it. You make sure that you move everything that you're combing that's new that you want to cut into a guide and keeping that guide where it should be. We'll work this all the way up to the end where the fringe lives, and then there we go, last section. So you can see those layers popping around. This is a great haircut for curly hair. I think that little extra weight from the layering sits well with curly hair and also allows the curly hair to kind of rest out. On straighter hair, if they're going to iron their hair, we're going to show you that end result as well. That's when you want to go in and remove some of that top heavy weight. I want you to look at the elevation on the fringe as we work this through. This is the Mizutani DB20 scissor I've been using it the entire time. This scissor I love because I use a 5.7 inch blade, and it's really sharp and really powerful. So it doesn't push the hair at all, so I can get these nice bold lines in my haircuts. So the fringe, I'm elevating slightly, pretty much keeping it at a zero degree angle. So if you see it coming off of the head shape, it's held at a zero degree to keep it a nice weight line in there, and then we're going to go in and cut it dry to finish it out at the end.  I'm using the Ergo paddle brush that we have on Friessalon Education and the Ergo blow dryer. We're going to get this blow dryer done really quick. It's a nice flat wrap. You can really see that shape kind of unfolding. Then we're going to go through with our Vibra straight iron and just smooth out the shape. It's really important. You guys see me smoothing hair pretty much every haircut. I don't do this because we're going to always style it that way. I do it so that you can see the weight and see how the weight is moving throughout the haircut. So you're going to see as I'm ironing this how heavy it is around the occipital bone area. You can see that it pretty much shapes out a bob haircut in there. So we're going to keep this a more medium length. We're not going to go too short with it, but you always could if you wanted to go through there and polish it out that way. So we used our Vibra straight iron. We got it all smoothed out.  So a lot of people go in and they cut the baseline first in a haircut. I don't do that all the time because sometimes I want to create the shape on top of the head first and within the layering. And then I go through and create the perimeter, especially when I'm working with a nice solid hard line. So I'm going through with the dry cut. Again, this is still the DB20 scissor. Everybody asked me what is my all around scissor for dry cutting and wet cutting. This is the one. Because it's out of 5.7 inch blade I can cut wet and dry because it still holds the power and doesn't push the hair. So you'll see it going through. I can create those really strong lines in there. The DB20 is made up of nanopowder metal, steel, which is basically it means that it's made of way smaller particles than a typical scissor. Typical scissors are they don't match up well with the metal so you get more of a grinding feel when you cut hair. The nanopowder metal, every molecule is the exact same size and shape. So they match up well together so you just get a cleaner, more precise cut and a sharper edge on this scissor. So you're noticing that I'm going back and forth with cutting. This has a lot to do with the fact that this is a mannequin head. But I do want to work that line. I don't want to push the hair that much. So working back and forth, just getting that line put in there. And I didn't want to take out a lot of this detail work. A lot of, I feel like a lot of DVDs that I've watched in the past, they show you cut, they cut one line and then all of a sudden it's perfect. It takes a lot of work to create those perfect lines in a haircut. You cut the structure wet and then the detail work dry takes a long time. That's why when you go to a hair show and you see Sassoon cutting one haircut for an hour and a half, two hours, it's because they're creating a perfect haircut. Perfect haircuts don't happen in 15 minutes. That's why you have $15 haircuts and you have $150, $200 haircuts because there's time involved in creating a perfect cut. So I'm going to go through, do some point cutting, still using that DB20 scissor. It works for that as well. So I just want to soften the heaviness in this shape. Now the key to point cutting is to make sure that anytime you pull the hair out, you're pulling it out exactly the way that you cut it when it was wet. If you start just pulling the shape around and then carving into it and really taking out chunks, then you're going to change the entire shape of the cut that you created. So you'll notice when I go in with my point cutting, I'm going in nice and vertical, parallel to the hair, so I'm not removing a ton of hair. I'm just softening it and I'm bringing everything out exactly the way I cut it when it was wet so I don't alter anything within the haircut. So here is the end result of the shape. I like to give it a little spin to show you guys really how that shape unfolds within the haircut. So the layering, how it falls together, that shape that it's created. So I hope you guys can use a ton of these techniques in the salon. Let me know what you think in the comments below. Hit the like button, hit the share button, and we'll see you guys tomorrow on the next video. Thanks.


Please tell us your name and where you're from Christie from Las Vegas, Nevada And please tell us what was the problem that brought you here? What what were you seeking? So I faced a little bit of childhood trauma and abandonment issues. My dad was in and out of jail They had me as teenage parents. So my mom was a party girl never really home From the ages of a newborn to five. She was nowhere to be found when she came into my life She would leave me at random people's houses. I was with strangers. I didn't know The garage was literally my babysitter with no food. No nothing to eat. So I was abandoned a lot And she would bring random guys and and then out the house So I seen drugs all over the table. There's something called a trap house That's where we would stay. So I've seen all kinds of drugs Just not a lifestyle for a kid And then I've also encountered a lot of witchcraft in my life So I battled depression anxiety suicidal thoughts When I would get so depressed I would look in the mirror and my demons would literally tell me if you tell anybody We're gonna kill you. So I would not tell anybody about my depression. I'd keep it to myself So I got tired of it I got so tired of it and that's why I came here today to seek deliverance from my demons when my Depression would get really really severe. I would harm myself and I wouldn't be able to stop like I would bite my arm and I would be telling myself Christie Let go, but I would not be able to let go or I would drown myself to the point where I would literally would about pass out, but then I would get right back up because as I Would say from the ages of 10 My dad was in church and I lived in a God fearing home So my demons were never allowed to literally kill me or take me to the point of suicidal, but They would I would cut myself all the time and I even while I'm cutting myself I think I'll this this hurts But I wouldn't be able to stop there to be blood dripping down my arm And I'd just be crying like what am I doing stop stop and I I wouldn't be able to stop So what happened to you today when you came to the prayer line? I Can't thinking that I already had been delivered because I started the process back at home So I'm just like okay. This is gonna be an experience. That's all But once they started talking about demons of mental illness get out I literally fell to the floor at my seat and started crying Then they took me up to the front and as I was walking up to the front I started to to shake and to feel this fear that didn't feel like my fear And as they started to pray for me There is this scream that came that wasn't even my voice and even in the moment I'm thinking like what what's going on. I can't control what's going on. What is this voice? What are these what what's going on all the voices that were in my head were now out loud? Which was something I was scared of but prior in the preaching he said just you just let Jesus do what he has to do And they started to move my body in ways that hurt like arching my back bending my neck Screaming we want her we're not gonna let her go. They didn't want to confess who they were they would laugh It it was crazy So how do you feel now? Now I feel like now I'm the one laughing now I Before when they would try to ask me what's wrong. I would not be able to talk I literally felt like somebody was grabbing my neck and wasn't allowing me to talk now. I could talk Who's gonna stop me from talking? So what would be a word of encouragement for people that have gone through maybe something same? Be patient be patient. I've been going through this since the day I was born. I'm 22 going on 23 God's timing is so perfect. Just be patient. Don't stop praying I've had nights where I feel like God. Where are you? When is this gonna happen for me? Is it gonna happen for me? But the Bible says it'll happen. So I kept praying and I kept insisting and persisting Just keep going do not give up.  Don't stop. And what would you like to share with Jesus? Just I want to get to my knees and worship. That's all I want to do just Speechless he has me speechless in a very beautiful way before the demons wouldn't let me talk now I'm in an all just incomplete all It's only because of Jesus am I allowed to even explain this because I'm just an all that's all I could say them Wow


The Ministry of Education continues to ensure and support an inclusive e-learning environment by providing students with the tools needed to thrive and meet global trends and demands in education. On the eve of the opening of the 2022-2023 academic year, 2,100 Chromebooks and 2,120 tablets will be distributed to secondary and primary school students island-wide. Minister for Education, Sustainable Development, Innovation, Science, Technology and Vocational Training, Hon. Sean Edward joined the orientation exercise of incoming form once at the Castries Comprehensive Secondary School to officially hand over laptops to students, underscoring the Ministry's fervor to ensure that students can receive their devices in time for the reopening, equipped with Google for Education Workspace, offering students a multi-faceted approach to learning and diversifying options for instruction and assessment for teachers. There has never been a better time in the history of our education system to be a form one student than today. It is really, among other things, a way of introducing our children to the rudiments of technology and the application of technology in everyday living so that they can have a greater appreciation for it as they grow and they evolve as young citizens. Minister for the Public Service, Home Affairs, Labour and Gender Affairs, Hon. Virginia Albert Poyotte, whose Ministry is the executing agency of the Caribbean Digital Transformation Programme, says the handover of these devices is one aspect of the programme and forms part of a greater vision to create an enabling environment for the adoption of digital services in St. Lucia. So we have to accelerate the pace so that we can be on par with the OECS, with the region and to compete internationally. The Caribbean Digital Transformation Project will positively impact many sectors of the economy, education, and that is why we are here today to see how this project impacts education. The Minister of Education had a special message for students, encouraging them to be personally responsible and show that the devices are used well and taken good care of. The laptops that we'll be giving to you, we're not renting, we're not looning, we are giving them to you. But, but we will be monitoring very, very closely what you use them for. You have to be responsible users of the technology. Do not go on sites online that are meant for adults. Do not get involved in things you know that children should not be. We cannot pull this every child with every device, but we have a broad mechanism that can give us an insight into how the students are using it. Textbooks, yes, they're necessary, but we are now living in the information age where pen and paper is quickly being replaced by technology. The Caribbean Digital Transformation Program is funded by the World Bank and being rolled out in four OECS countries to the tune of US $20 million. The Ministry of Education from January 2022 has secured over 6,700 Chromebooks for students with more to be secured before the academic school year ends 2023. From the Communications Unit of the Ministry of Education Sustainable Development, Innovation Science Technology and the Vocational Training, I am Daniel Dubois reporting.


Threads had a huge onboarding week. A lot of press on how many people had signed up for threads. That was when Twitter was dead, right? Or X at this point. But then there was a huge decline in usage in Threads first month. So what are we thinking? Can it climb back? Let me please clarify my take because I do want it played in the highlight reel when I die. My take was, is that a big number? Because I could see it totally falling apart. And guess what friends? I believe it is proceeding exactly as I have foreseen. Threads is a boring product and it doesn't really bring a lot of anything. I do think that there has been material degradation to the product of X. I do go on to XLS. We'll see on Wednesday whether or not another service can be the place where you talk about the Republican debate. Because that's been Twitter's place in the world. We'll see if it's X's.


Hi, this is the host of New Bhartiya and welcome to here for Let's Talk. And today we have with us Devrat Rishi, CEO and co-founder of Pretty Base. Devrat, it's great to have you on the show. Yeah, really nice to be here. Thanks so much for having me. Yeah, it's my pleasure to host you here today. And this is the first time I'm talking to you. So I would love to know a bit about the history and history of the company. What led you to co-found this company? Yeah, you know, like a lot of, I think, entrepreneurship journeys. It's a long winding one that culminates in some moments that happen quickly. But the long winding journey is, you know, I always had my academic background in computer science, statistics and machine learning. And spent time at a number of years as a product manager at Google. I was working on different teams, Firebase, which is an acquired startup, Google Research on productionizing ML. But I spent most of my time on Google Cloud on the platform that eventually became Vertex AI, which is the way that GCP packages its AI services externally. And while I was there, it was also the first PM for Kaggle, data science and machine learning community Google to acquired in 2017. Kaggle had just under a million users when I joined and has over 14 million users today. And, you know, when I was there, I didn't realize that that many people knew the basics of machine learning or NumPy and Pandas. And so it was really an incredible time to see just the organic lift. At the same time I was seeing that there were a lot of organizations that on Vertex were just really struggling to get any value out of ML. And so I saw like this, you know, two-part dichotomy. And in 2020 I met my co-founders, Piero, Travis and Chris. And actually my co-founder, Piero had the idea for what eventually became Predabase that was just built on top of a tool that he had made for himself while he was at Uber. He was a machine learning researcher that had to work on a number of different projects. And he felt like he was reinventing the wheel each time. So he made a tool called Ludwig that made his life easier, then made the life of other engineers at the company easier, and eventually open sourced it in 2019 and had an idea for how to break it easier for any organization to build models at the end of 2020. So we all got excited about that and we started right at the very beginning of 2021 as soon as the vaccines came out. And we've been working and operating ever since. If I ask you to summarize Predabase, how would you summarize the company? I would say that we're, you know, a platform for developers that want to productionize open source AI models. So if you're an engineer who wants to be able to use one of those open source models that you've been reading a lot about and start to be able to fine-tune it on your data and then serve that model inside of your organization, then Predabase is the right platform for you. And we've actually always been built on a platform and a foundation of deep learning models that support many different types of use cases. But especially in 2023, the primary thing we lead with for our customers is fine-tuning and serving fine-tuned open source large language models. So we think that, you know, some of the large gen AI applications and gen AI APIs are a great place to get started. But increasingly, the future is open source and the future is fine-tuned. And that's where Predabase really plays into. How important is open source of attributes? Predabase is actually a company built on top of open source projects and around the open source ecosystem. So we are both big believers in as well as, you know, the platform to allow people to use open source. And it's been important to us in two ways. One, in the ways that we've contributed to the community and two, the ways that the community has contributed back to us. So we have built two open source projects, one for training machine learning models called Ludwig that has over 10,000 stars on GitHub today. And then the second is a new project that just got open sourced last month called Lorax, which is a really efficient way to be able to serve open source fine-tuned models and especially be able to serve hundreds of models for the cost of one. Lorax is the reason that we have the most cost effective way to be able to deploy open source models in the market today. And so it's been really critical to the way that we've developed technology and the way we've wanted to get back. And then we've, of course, benefited a lot from the fact that some of the best models coming out today are actually open sourced because what we want to do is allow organizations to own their own models and own their own IP. If you use an external commercial API today, that API owner really owns the models, the weights that you're using and you're consuming by an API. And we think as more organizations see AI as core to their strategy, they're actually going to want to own the models, own the weights, own all the direct infrastructure that goes around it and have full agency. And that's only possible with the open source models. And so that's really where we think we want to be able to play in. And beyond models, because when we do talk about AI, especially now, we talk about JTVI a lot. It's not as easy as the old lamp stack, where everything is fully open source because more complicated. Even if you look at open AI, the word open is there, but it's not open source. So talk about JTVI AI in general and open source. What are the things that you feel are should be open source or what are the things that you should, you know, though that cannot be open source, you're so like, no, it can be open source as the lamp stack as well. Yeah, absolutely. I mean, we think that, and this has always been true for AI actually, which is we think that the models and the weights of the models should be open source. And I think Meta and Facebook's AI Research Lab have really led the way here with some of the Llama 2 variants that came out and love to see some other strong open source models come out like the ones that came out recently last week with Mistral. So those essentially concepts open source the architecture and then some of the weights that have been used from the model training job. And we're really grateful to the organizations that released that. The great thing about that is it gives every other company a great starting point. Being able to train some of these models from scratch can cost, you know, tens of millions of dollars in order to be able to do. So if you want to get started, there's a really high barrier to entry, which when a company open sources the model architecture and weights, they reduce and they get easier for any organization and startups and tech companies and any other enterprise to be able to start to adopt it right out of the box without having that large barrier to entry to get started. The piece that we think makes sense to be more commercial is on the infrastructure. So that means, you know, the way that you actually orchestrate the compute so you make it possible to be able to have a customer's model be trained and fine tuned on their own data. The second piece is the data itself. Of course, we don't think, you know, companies should open source the proprietary data. Instead, what we want to be able to do is bring the models to their data and be able to bring the models into a layer that allows them to customize and fine tune that on their data. And then finally, the infrastructure that allows customers to be able to serve these models inside their organization as well. We think that infrastructure, you know, we've open sourced some of the implementations around it. But at the end of the day, you probably want to go use a platform, just like people use AWS today for, you know, managing their compute in order to be able to get the actual underlying access towards it. So the techniques in our mind are, you know, nothing magical and nothing that should be kept away from the broader public. The infrastructure on how to get that, you know, actual, those techniques to work in production, in practice, on your internal data, that's the piece that we see as commercial. When we look at open source, just before you, I had a conversation with someone from Linux Foundation, they came up with the report, you know, how the global communities can get involved because something that is happening is now, which is more or less like techno nationalism, where the companies are trying to keep, you know, there is a lot of different sort of sovereignty is there. And then a war is going on. So the collaboration is becoming more and more hard. And sometimes companies don't want to rely on the product of a particular, from a particular country because, you know, U.S. can have trade embargo and suddenly you get locked out. So open source does become a place where people can go and contribute. But open source, you know, can be a company-owned open source. Open source can be a community-owned open source. Open source can be a neutral foundation-owned open source. When it comes to AI, just a few weeks ago, Biden, especially, they also came up with the executive order around, you know, to make Genetic AI more safe and secure. To just the way Linux kernel being open source, it kind of created the whole adoption. Kubernetes is another great example. So can you talk about when we look at AI, you know, LLMs, how open source and what kind of home should be there for these technologies so that companies don't really have to worry about your competitor may pull the strings because they control it. It creates an even playing field. You also don't have to worry about the whole geopolitics that, hey, this project is coming from this country. Talk about what do you see would be beneficial for, because we have to increase that option. So talk about. Definitely. And so in terms of why open source, you know, I think there are a number of reasons, but one of the customer quotes that actually encapsulated, said the best for me is, look, generalized intelligence is great, but I don't need my point of sale system to recite French poetry. It's this idea that especially when organizations are deploying AI models, they don't need the full spectrum of artificial general intelligence to be able to solve every all tasks all in one place necessarily. What they need is a surgical toolkit where they can use the right scalpel, the right task for the individual thing they're looking to be able to automate. And open source actually provides that option and opportunity, where you can go ahead and say, I don't need the 1 trillion parameter model or even the 100 billion parameter model. What I need is something small and right-sized to be able to automate my customer support tasks or to be able to do help me with fraud prediction. It's really about making sure you have the right tool for the job. And that's where the breadth of the open source community is really helpful. So taking a step back, what are the reasons why open source is really useful and like why we think it's going to dominate the overall industry? There's really three key reasons. The first is all about what you were talking about, which is vendor lock-in and preventing that. So today, if you're using for a service like OpenAI, customers I think consistently notice strange patterns, whether that has to do with latency and availability. So sometimes the models will just fail to give a response at a certain point, if you're querying them at too large of a rate. And if you've been on Twitter or X recently, you've probably noticed a lot of announcements about how OpenAI's performance has degraded over the last month. That's not anything you have control or agency over. And if AI is going to be core to your roadmap, then it seems really weird to be able to defer all of that control and agency towards like a third party. And so the first is really around agency and preventing vendor lock-in. The second core reason people really go into open source is for performance reasons. And so here, you might have a task or a model. We see this all the time. It does really well in building the prototype. It's a really good way to be able to start to show how you can summarize emails or something along those lines. But when you want to use it inside your organization, you need to go from like 80% to 99% overall. And that's where the combination of open source and fine tuning I think have been the most useful. We worked on an experiment on JSON generation where we're trying to extract information from text and basically come up with a structured representation. And GPT-4 got about 66% coverage out of the box on that task. But when we fine-tuned Lama 2.7 billion, a much smaller model and much less capable than GPT-4 in a general purpose sense. But when we fine-tuned it on that data, we got up to 93%. And that was really impactful because it basically shows a larger performance gain for a lot more bang for your buck. And that final bang for your buck point is actually the third large reason why people go with open source, which is today the models that people are deploying are really expensive. They're quite slow. And instead what open source allows you to do is right size the right model task. If you want a 1 billion parameter model, a 3 billion parameter model, a 7, a 13, a 34, a 70, all of those are available in the open source community. They're not all available through like commercial APIs, but they're all open source models that are available and you can choose the one that actually makes the right, the most sense for your task. And so that's where we think users are increasingly starting to see that adoption. You know, to end on this point, the number one thing I hear from customers today that are using GenAI and production is, yeah, we built our prototype on OpenAI or we built our demo using another commercial API. But we want to move off of it in the next six to 12 months. And we want to move off of it for exactly those three reasons that I was just mentioning. We can talk about open source. We can talk about all these projects as much as we want. But open source, these open source projects can solve only day zero or day one problem. Where you can get the code base, get it installed, get it up and running. What about day two, day three, day four?  Big players can of course have all the, but not everybody's Google, Microsoft, and Apple. At the same time, the projects, they have their own limitations because they cannot take every use case and start, you know, embedding those codes to cater to a specific, you know, customer, commercial players, you folks can vary. Just talk about the role of commercialization in the open source, you know, LLM space. And of course, let's talk about your company, what role are you folks playing there? Exactly. So I like the day zero, day one analogy, right? And if open source discovery, or even just finding out and building your first, you know, demo with a GenAI application is day zero, then Predabase is really day one and on. You know, it's the point at which you've seen the power of some of these models that exist. And now you have the questions of, how do I deploy this inside of my organization? How do I bring this to my data in a secure way that allows me to be able to get a performance lift and a customization? How do I make this available to be able to iterate across other collaborators in my organization? Those are all the key things that we think about inside of an organization. So when we started off, I described Predabase as, you know, the developer platform to productionize open source AI. And so that's really what we're all oriented around. It's not us inventing anything novel in the underlying models. It's about us making it easy to take those models that people have put out, great research labs, and make it something you can fit into that organization. Now, how do we do that? We have a platform today that anyone can try out for free. It's on predabase.com. We have one of the best free trials actually on the market because you can both fine tune an open source large language model and serve it. And we give you the GPUs to do that out of the box. You can go ahead and try it out today and you'll really do three key things. The first is you'll connect your data. The second is you'll fine tune and train a model. And we make it easy for anyone to fine tune and train a model. And then the third is you'll be able to deploy that model so you can start to prompt it and start to get your answers and requests back from it. We have a bunch of quick starts and guides that help you kind of walk through that. But we really think that's kind of the key thing that people need. They see these models out in the open source and they're curious, how do I get it to work inside my organization? How do I connect it to my data? How do I serve it? And that's what predabase is really oriented on. As the adoption is growing, of course, it really depends from one use case to other use case. We cannot generalize it. But from predabase point of view, from your perspective, what are some of the challenges of pain points that at least your customers or users fees that you're like, hey, these are needed to be addressed because these are still the problem that are cropping up? Yeah, absolutely. So just actually both KubeCon as well as the Linux AI.dev conference, we actually had talks at both of those. So hopefully you'll have a chance to check those out and we'll consent over a recording as well. On the second point about what are the challenges that people are seeing, whether it's trust and safety and hallucinations or others. The key challenge that I'd say customers come to predabase for are two things. Number one, it's actually efficiency. So they've gotten something working with a platform like OpenAI. They've found a use case where they've been able to either get a human in the loop system going or it's a use case where the kind of erratic behavior of the model is still acceptable. So for example, maybe it's writing advertising copy and some of the advertising copy is a little bit strange, but that's okay if 95% of the advertising copy is good most of the time. And there's a review process for it. They found that use case where they come to us is they want to actually get to the point where this use case can be served in production at the most cost effective way in the most tailored way to be able to eke out the last bits of performance and to be able to make sure that's low latency and cost effective. So when you think about who's the normal predabase customer persona, it's somebody that probably started their experimentation with OpenAI as an example but has figured out what use case they want to apply it to and want to go to the next level where they're actually thinking about a production setting for that model and they want to own that model. And the reason they come to us is to be able to get that maximum efficiency. The second reason people come to us is I think that we're one of the forefront companies like in fine tuning LLMs overall. And so they want to understand from us like what are the use cases? We talked to both like very large technology companies on a partnerships angle here. We talked to many mid market other companies that are looking to integrate this directly for their own use cases. But we're really kind of talking in joint collaboration about some of the technology we've put out and how do we actually think about brainstorming the use cases around it all the way if they're deploying it inside their industry. What kind of cultural shift either you're seeing it's too early actually and I don't like just the labels and jargons because the reality is different than what we here see or what kind of cultural changes you think are needed once again from a very practical and realistic manner versus just throwing another jargon out there. Yeah absolutely and you know just very being data driven about it actually when I was at Kaggle by the time I left that community we had about just over five million users I want to say. Now there's a kind of common thought process that people do that do machine learning are all these PhDs and deeply embedded and kind of ML and they've been doing this for a while and I can tell you for sure right now of the five million users the vast majority were not PhDs in machine learning the vast majority had never academically studied machine learning right. What they were were they were folks that we will call and at Predebase we call ML curious. They were engineers that maybe were a data engineer at some point they were analysts that had a little bit of a statistical background you know and other kind of types of folks like that and they were the type of persona this is why we at Predebase we love developers it's because they were the type of persona that were like give me some good documentation and some good abstractions and I will figure this out. That is the type of user we see the most often in our open source communities that picked us up even before Predebase became a company. They were organizations like Coup which is a social networking application based in India that basically you know we're looking to be able to build their first models what they really cared about was not the theory behind machine learning it wasn't like what is the right way to optimize a convex loss function it was hey I have content and I need to be able to go ahead and moderate that content give me the set of tools that I need that will allow me to do that in the simplest way possible and that doesn't lock me in so as I get more advanced I can dig deeper and deeper and that's what we've seen increasingly I think the shift left movement has been most commonly referred like you know associated with security over the time and like with DevSecOps but I actually think that machine learning has been shifting left silently for a while why I say silently it's because three years ago it's not like in organizations you actually saw a lot of engineers starting to do machine learning themselves but you saw it in the communities if you looked at the people that used Huggingface if you looked at the people in Kaggle they weren't the MLX like PhDs and MLPHDs were also there but there's 10 to one ratio in terms of like you know who's actually active in those communities and the really cool thing about moving to an API-centric model in the last year is now we start to see that in industry and organizations and so I think that you know it was a silent shift that now we brought to the forefront really in this year also do you see that there are certain industries which can benefit more from LLMs and Genetimo or do you see that you know just the way we say you know at one point we were trying to every industry every company should be seen as a software company right if you don't have a soft you was right so over time certainly think it's going to be a case where like software rate the world so will AI and I think that that's going to be where it goes in the short term though it's actually useful to be tactical and what are the types of organizations that use cases in particular where you know Gen AI will start to attack first I think number one it's going to be organizations that have and deal with a lot of unstructured and especially text data now there's a lot of generative AI models that are coming out and other modalities like images and you know videos and we even put out some work earlier that had to do with tabular data but text has really led the the kind of charge here and so I think the first type of the area to consider is where is there a lots of text data whether that's customer support automations whether that's code and others where you can actually start to see this tactically unfold and the second key area is areas where you know over the near term and Gen AI is going to be capable of making mistakes or hallucinating you know which is in part really a feature rather than a bug the fact that it can come up with some new creative answers you know that might be unexpected and so what we also need to do is make sure we're concentrated in industries and use cases where that type of you know behavior is acceptable and it's acceptable for either one of two reasons one you know it's a use case where every once in a while if it says the wrong thing it's not going to cause a critical cascading downstream failure or and you know when it's not in a regulated industry where you need to be able to have heavy emphasis on that explainability or number two if it's the case where there's a human in the review human in the loop process overall and so those are the types of use cases we're going to likely see and so I think you know generally we've seen these applications picked up the most by tech companies so far but every organization has interest against it and I think it's identifying the right use cases the data that you know are going to be best suited for it one more question I want to ask you it has nothing with open source it's more or less like there is also a fear hey you know what genitive AI is going to take away our jobs but I see that the good analogy is Photoshop Photoshop did not eliminate the jobs of photographers actually it enabled a lot of you know even mob and pop shop regular people to become great photographers it is a very powerful tool in the right hands so same I see is the case with genitive AI it will actually enable it would take care of a lot of mundane you know like even the developers they really don't have to worry about a lot of low-level thing they can focus on higher which also means that they can charge more and they can use quality time for quality things what is your opinion I think my opinion is genitive AI is going to replace a lot of jobs and create a lot more new ones and I think that the you know value creation out of jobs that generated gen AI is going to create is going to be higher than the jobs that it's going to automate and so in general I think what we're going to see is net productivity increase you know across the economy of users that uses this I think we're going to see people no longer have to do those rotten mundane tasks like you were talking about like really just think about the processes to be able to do things like you know automate extracting information out of documents and putting them into a database and other things along those lines right like those types of tasks should not be the ones that we really deploy a lot of human labor against instead the types of tasks which deploy human labor against I think increasingly will be new ones that get created where humans work side by side with kind of gen AI in the loop doing review and just increase in the cadence and pace at which they're putting out productive applications David, thank you so much for taking time out today and talk about the database and also the whole larger growing ecosystem thanks for all those great insights and I would love to chat with you again soon thank you really appreciate the time thanks for having us


Good afternoon. Welcome to CMC Markets on Friday the 6th of August, 2021, and this month's non-farm payrolls webinar with me, Michael Houston, and I'll be taking you through the numbers today, obviously giving you a quick overview of what markets are expecting, looking at some of the key levels with respect to currencies, commodities, and the major indexes, and hopefully try and make sense of the direction of travel when it comes to where markets are likely to go. You've also got to be cognizant of the fact that we're coming into a weekend, so we've seen a fairly decent week for equity markets this week. We've seen record highs for the stock 600, the 5250, the NASDAQ, and it looks like at the moment we could well open at a record high or for the S&P 500 when that opens just over an hour from now at 230 UK time. But I think today's payrolls number is, well, obviously it's an important number in the overall scheme of things, but I think what it tells us is that no one really has any idea what today's payroll number is likely to be. The guesstimates, and I use the word advisedly, the guesstimates are between 350,000 to 1.3, 1.4 million jobs to be added in July. Now, there are only a number of reasons as to why today's July number should be a good number. We saw some fairly decent employment components in the ISM surveys out this week. Manufacturing and services were both very, very positive numbers, and the employment components jumped above 50 to 52.3 and 52.8 here or there as makes no difference. However, the weekly jobless claims over the course of the past month or so have here to have found a little bit of a base around 400,000. We haven't really seen a significant improvement in claims, and ADP data, the ADP payrolls report was particularly disappointing. You could argue that expectations for today's payrolls report, I think anything in the region of around about 950 is probably priced in. Anything less, probably not. Anything less than 700, probably not. Anything over a million, probably not. If you look at the way the dollar has behaved this week, the dollar is high. You're looking at Euro dollar at the moment. It's dropped below 118.50. Those of you who basically follow my daily notes will know that I've been calling for Euro dollar to go to 117.5. Over the course of the past few sessions, definitely very much a sell the rally type of trade Euro dollar. I can't bring myself to be in any way positive about it. Simply on the basis of the fact that Federal Reserve and the ECB are likely to be going in completely different directions over the course of the next two years. I want to say different directions. I mean, the ECB is not going to be tightening policy, tapering, asset purchases, or doing anything along those lines over the next two years where the likelihood is the Federal Reserve will. So it's really about, I think, what today's payrolls report is about. It's about a direction of travel rather than the actual headline number itself. And I think, you know, in amongst all the noise and the narrative, I think that's probably the most important takeaway that I could say. So say, for example, we look at the payrolls numbers over the course of the past few months. So, you know, this is the number from March. So costume on back to the payrolls report, the March payrolls report in April, when we're expecting a jobs number of around about 1 million. Sorry, it was the, it was the April report in May, we're expecting a million and we got 278, 266,000. That was subsequently revised higher than the 1 million number, the nearly 1 million number was subsequently revised lower. What we're seeing here is a slow move higher. Okay, we saw a little bit of a dip back in the April numbers, but 166, 468, 770, 278, 583. I think we could well see something in the region of perhaps 700, 750. And if we come in and around that number, the overall trend is in place. The only real question is all of these people who weren't in the labour force, who aren't in the labour force now, but were pre-pandemic, where have they gone? And I think that's the key question that an awful lot of people are wrestling with. And if you've read my morning note from this morning, and listened to my payrolls webinar a month ago, you'll know that an awful lot of fed officials are paying very close attention to the labour participation rate, because the labour participation rate will give a decent indication as to how many people are still not feeling particularly incentivised to return to the labour market. And there are only a number of reasons as to why that might be happening. You know, I think it's important to consider that, because how many of these six or seven million people that are no longer in the labour force and not reflected in the current participation rate will come back? How many have retired early? How many have set up their own businesses? Quite simply, it's too early to know, these unemployment benefits ran out in September. So, while we're still expecting a fairly decent payrolls report, and despite the comments of Vice-Chair Richard Clarider earlier this week, they can talk about a taper as much as they like. The big question is, when will it happen? Will it happen towards the end of this year? I think that it will, but the moment the reluctance to discuss it to me is neither here nor there. It will happen. The big question really is about timing. Will it happen Q4? Will it happen Q1? And unless there's a significant setback in the global economy, and we'll talk about China later because of the rise in infection rates across not only China, but in Asia as well, there is a possibility that we could see a little bit of divergence when it comes to the economic recovery in Asia and the economic recovery in Europe and the United States, because the higher vaccination rates here in Europe and the UK and the United States. Nonetheless, I think fairly decent payrolls report with the participation rate edging higher. The unemployment rate, it went up last month while the under-employment rate went down. That gives you an indication of how confused things are. Unemployment goes up, but under-employment goes down. Suggests that more people potentially are going back early, going back part-time. So when the schools go back in September, when the unemployment benefits roll over, roll off, that will be the asset test when the September payrolls report comes out in October. So that will give us a better indication of where we are in terms of the labor market once we come to the end, potentially start to come to the end of Q3 and begin Q4. So still likely that we'll see a tapering of asset purchases at some point. And to be quite honest, whether it's $120 billion, $100 billion, $80 billion, what does it matter? Really, it's about the timing or otherwise of when the Fed is likely to start raising rates, whether it's going to be the end of 2022 or the beginning of 2023. And I think that more than anything is what's, I think, got an awful lot of people a little bit uncertain. The Fed's gone from not raising rates before 2024 to potentially coming in at the end of 2022 or the beginning of 2023. So that's how the debates moved, even though bond yields haven't reflected that. You know, we can see that quite clearly in the way that the US 10-year yield has behaved over the course of the past few weeks. This is since March. And really, I think this is just being reflected by concerns about slightly weaker growth trajectory for not only the global economy, but the US economy. I think expectations were too high here. They started to become an awful lot more realistic down here. The big question is now, will the US 10-year yield a break below this double area of support around about 1,260? Or will we break higher and head back towards 1,40 over the course of the next few days and weeks? Decent payrolls report could well give an upward nudge to yields, but we also have to be cognizant of the fact that we've been higher three days in a row. So again, a decent payrolls report could well be already priced into a certain extent by this rally in long term treasury yields. Or it could just be a consequence of a little bit of profit taking as we head into the weekend after the declines that we've seen all the way from here. So the big question is, I think, first and foremost, what's already priced in? And how is the market likely to react in the event of a number that comes in anywhere below 700,000 anywhere above 950? So million will be significant because obviously it'll be a digit change in terms of the number of zeros after the number. So psychologically, that will be positive. On the other hand, if we come in anywhere near 700,000, that's going to be okay, fine, it's higher, but it's still not, it's in the right direction, but it's perhaps not as good as perhaps we thought it would be. And I think that for me, I think that for me is the main thing to be concerned about. So I'm guessing you can, I'm getting some people saying that they can't hear me. Because you just confirm that you can and I'm actually not talking to myself. So I'll just stop for a minute before someone says anything. Yeah, great. Excellent. Super stuff. So everyone can hear me loud and clear. Okay, so yeah, we can, I'm guessing the problem is to do with speakers, perhaps or a technical problem your side. So all good. All right, so, so let's let's look at the overall numbers. We've also got the Canada jobs report. So that's obviously going to have a significant impact on the dollar CAD exchange rate. So I think let's cover that off first. For those of you who follow dollar CAD, because if we look at the dollar CAD chart, there's a really nice little trend playing out at the moment, which has been in place pretty much since the beginning of June. So a decent Canada jobs report, and a slightly weaker US jobs report could actually see dollar CAD drift down towards here. But overall, we're starting to see very much a case of a move to the upside in dollar CAD. So in terms of the Canada numbers, any dips back to around about 124 could could see a little bit of a rebound, could see the rebound continue as long as we hold above this key support line from the lows that I've drawn in here. Trend is very much your friend here. We've got the 50 day moving average, the momentum turning positive. We've got these double lows here on the on this on this candle on the 14th of July. And this candle here on the 30th of July, and that low comes in around about 124 20. So there's fairly solid support dollar CAD at 124 20. And if we get a drift back down to that sort of area 124 40, then the uptrend that's been in place since June is likely to continue on that basis. Obviously, if it drops below 124, then the uptrend is over and we could we'll see a correction back towards the 123 area, but certainly looking for a slight slow down from the numbers that we saw back last month, 177 and a half full time, and most of which are expected to be part time jobs. So that's not particularly great, but nonetheless, the unemployment rate is expected to drop to 7.4%. But my my main focus is very much on the headline for non farm payrolls. So that's the consensus forecast. Bloomberg have got 858. We've got the unemployment rate which is expected to fall from 5.9 to 5.7. And according to Bloomberg, the participation rate is expected to improve from 61.6% to 61.8. So just close that window down. Let's have a look at some of the major chart points. Well here currently the FTSE, FTSE, FTSE, what am I talking about? The S&P 500. It's trading at an all time high. 44.30. Obviously, the cash markets aren't yet open. They won't open until 2.30. But the likelihood is assuming that we've got a fairly decent payrolls report that US markets will open or the S&P 500 rather will open at a new record high. We've found over the course of the past couple of weeks decent support anywhere near 43.70. So what I'm going to do with this is basically draw a horizontal line straight across there. So you can see that line and then I'm going to drill it down into a 30 minute chart so that you can see it right there. There we go. I mean, it's no more complicated than that for the past two weeks or so. The S&P 500 has been trading in a sideways range. The bottom of that range is 43.70. The top of that range is roughly where we are now. So if I was looking to get in now and it may surprise you to hear me say this, I wouldn't be looking to get in at the moment. If anything, if I was already long, I'd be looking to take a little bit of profit. We're coming into the weekend. I don't really want to run anything into the weekend given the fact that there's an infrastructure bill going through the US Congress at the moment. So we could be susceptible to weekend event risk and I think that's something that we really don't want to be thinking too much about when it comes to running positions over the weekend. They can be problematic when I was trading currencies. I used to run positions over the weekend all the time. As I've got older, I've become more risk averse or just wise. I think it really depends on your point of view. The problem with running positions over a weekend, particularly now, is that sometimes they can gap against you on Sunday night and generally they end up costing you money than they do making you money, particularly if you're the wrong, obviously if you're the wrong side of them. So that's just a personal preference. It really depends on your risk profile but certainly in terms of novice traders it's not something that I would actively encourage. So the S&P looks, it's trading towards the top end of its recent range and it's probably a similar sort of story when it comes to, say for example, the DAX. Just give me one second, ladies and gentlemen. Quickly replying to a message. Again, it's a similar sort of story. We've got the record highs here, 13th of July, 15,816. We're not far off that. Well, I'd say we're quite a bit off that but again if the S&P rolls over towards the open then that's likely to act as a little bit of a break on the DAX. Having said that, even though the stock S&P 600 has made new record highs, I think it's notable by the fact that the DAX and the CAC Caron have not. That doesn't mean that they won't but I think it's more likely that if we are going to see those record highs on the DAX and the CAC Caron we'll probably see them next week and not this week. Again, it depends on the payrolls report and again it depends on your risk profile. Do you want to run anything into the weekend? FTSE 100, it's a serial party blue, purple, annual, under performer this week. The good thing is we're now back above my 50-day moving average which I generally tend to use as an arbiter of momentum for the FTSE 100. The only concern I do have is again, even though it's higher on the week, it's looking a little bit stretched and it still doesn't want to go through 70-150. I don't know what problem it has with 71-50. It just finds the air a little bit thin anywhere near these series of highs through here. So again, it's about trading what you see and for me at the moment the FTSE 100 looking a little bit toppy at current levels. That's not to say that I don't like it, I do. I still think that it's got potential to go an awful lot higher by year end. The only concern that I have, the only frustrating thing that I have is everything else is going up except the FTSE 100 but that's not to say that it won't continue to go higher. When you've got Goldman Sachs, companies like Goldman Sachs raising their targets for the S&P then the likelihood is that the direction of travel is likely to continue to push higher. Simply on the basis that where else do you put your excess capital, your liquidity and what have you. The trend is everything in terms of this. So we've got fairly decent support at around about 7100 on this hourly chart. We can see it there. There's a low there, there's a low there, there's a series of peaks there. So I think any drops back to around about 7100 should see fairly decent interest on the FTSE 100. Right so let's talk about, let's talk quickly, talk about Brent Crude for Leanne as she asked me and I said that I would show her. So here we go, decent uptrend, three down days, one, two, three, an awful lot of this decline that we've seen over the course of the past few days and there's a consequence of concern about Asian economies. We've got China trade numbers over the weekend which could drive the oil price particularly if they're disappointing, imports and export data. We're expecting to see another slowdown there over concern about the Chinese economy. So pay particular attention I think to the $70 a barrel level. I think that's a very key chart point on the downside but it looks like the oil prices are likely to finish the week lower for the first time in a couple of weeks and gold will be very much driven by what U.S. yields are doing so if yields pop higher then gold is likely to drift back towards this trend line support here which comes in round about 1780, 1785 there or thereabouts. So again a decent jobs number, a positive employment report is already starting to get priced in a little bit so we could see a test of 1785 if U.S. 10 year yields spike higher from where they are now and they're currently around about 125 at the moment. I'll just move this interview. Let's just do this again. GP we got 125 so there we go 125 83 and year to date there. So if we if we head back towards this 200 day moving average around 128 that's likely to knock gold lower. EUR a dollar very very quickly. Let's do the analysis on this. Again those of you who've been following my daily updates will know that I've been calling for this to retest this series of lows through here. So again a positive number if it's a bad number then we could well see a pull back to around about 118.5, 118.60 but I'm still very much of the opinion that EUR a dollar is set on the rally momentum should take us back down to 117.60. That was a course of the next few sessions. Cable I'm slightly more bullish on largely on the basis of that shift this week by the Bank of England. Decent support at 138.70 so if there is about a dollar strength it'll probably not cable down to 138.70 potentially could go as low as 138 but overall I'm still of the opinion that we need to get through 140.20 to head quite a bit higher. So that's essentially what I'm looking for when it comes to the cable and I'm basing that on weakness in euro sterling. So any dollar strength should be mitigated by the weakness in euro sterling which is now seeing euro sterling head back towards these lows here and potentially back to these lows here. So very much a case of sell euro sterling on rallies ahead of the payrolls numbers. Looking at Dolly Yen again fairly decent rally in Dolly Yen over the course of the past few days we could well head back to 110.20 in the event of a decent payrolls number. So we're coming up to 13.29 and 30 seconds so before I wind up completely just a quick reminder 858 on the headline number unemployment to come down to 5.7% from 5.9 and the participation rate to improve slightly to 61.8 so I'll just wait now and we can digest the numbers as they break. Seven point in the gap unemployment rates dropped to 5.4% non-farm payrolls 943 fairly decent number that we like that but it's pretty much back where it was in terms of consensus a week ago so let's have a look 943 5.4 participation rate ages up 61.7 so all in all that's a fairly decent number for and you can see that all now by the fact that dollars going up not so much because of the headline number but because of the fact the unemployment rate has dropped back quite sharply and the participation rate has actually gone up so very much a positive number for non-farms and also a positive revision to the june number that's been revised up as well from 850,938 so a very very positive number again two positive numbers in fact and we should get a retest of 117.5 on the headline on the headline payrolls number let's have a look at Dolly Ennessy if we get that test of 110.20 and there we go there it is quickly looking at US 10 year yield and that's higher as well up to 126.84 so all in all fairly decent set of numbers all pointing to the US economy that's recovering very nicely all pointing to the fact that despite the fact that weekly jobless claims have been plateauing around 400,000 the labor market is still recovering and it's recovering quite nicely which means that once again the prospect of a taper is very much back on the table for some time in October there was some doubt about that I think it's quite likely now that we will probably hear the noise about that start to increase and as a consequence the dollar is likely to potentially go higher the big question now is really what does this do to equity markets personally I think it's I think it's pretty much positive all around it's a Goldilocks report we've got higher equity markets we've got a headline number that's positive an upward revision that's positive a unemployment rate that's down from 5.9 to 5.4 and average earnings average early earnings have ticked up to 0.4 so there is an element there also of a little bit of inflation starting to creep in as well now that might make some people a little bit nervous but given how many people have dropped out of the workforce since the beginning of last year I'm not overly concerned about that you know average early earnings on an annual basis is 4% yeah fine on a monthly basis it's up to 0.4% you could argue that slightly inflationary but how much of that is as a consequence of people returning to the workforce and how much of it is as a consequence of employers having to pay slightly more for to get headcount and fill job vacancies there certainly will be an element of that and I certainly think that's a good thing though it may it may impact on companies bottom line and profit margins maybe further down the line and then really it's just a question of whether or not that then feeds into price increases or goods and services going forward what does it mean for gold well it means weaker gold essentially we're going to see a test of this trend line Phil I think we're going to see a test of this trend line here really is a question of now whether or not this trend line holds or whether or not we see a rebound in the short to medium term got to say that I don't think gold is going to rally today I don't think it's going to rally into the end of the week but I think if we can hold above this trend line today then we could see a little bit of a rebound next week if on the other hand we break below it we'll probably retest the lows back in June of around about 1760 but that is not a good report if you're longer gold it's a bad report if you're longer gold because it's very much dollar positive and it's very much positive for the yields as well so I think the key test for me is how it reacts when it gets to this trend line here so in short gold prices to trend lower towards trend line down here any other questions sterling yen that's my old favorite I used to trade dolly yen so that's a good one all right we've got sterling yen let's get rid of some of these lines on here until I haven't looked at this in a while right running into a bit of resistance at the moment on sterling yen but you've got to say that when we look at when I look at this here we're heading into a bit of a resistance zone on sterling yen up and around 153.5 on 54 why because we've got trend line from the highs here but we've also got cloud resistance as well normally what happens is cloud ecimoku is something that I use an awful lot on yen in yen crosses simply because I found that it actually works quite well in terms of support and resistance but I only use the kumo cloud resistance lines I remove all the others when we what happens is they tend to act as support or resistance and when they break below the support the the market tends to trade away from it then access resistance goes into the cloud access resistance comes back down breaks below it turns away now we look as if we're heading back into it so I think there's potential for us to head back into this resistance level here on the kumo cloud a bit of resistance if we can hold below that then we should start to trend lower but because we're starting to trade into a bit of a range at the moment volatility is starting to compress and as a result these signals may not be as significant if they do break through having said that if we break above this cloud here then we could well see a significant move higher but at the moment we look as if we've got a little bit of strong resistance coming in around about 153 and a half 154 so hopefully that makes some sense to you if it doesn't what I'll try and do if you want we'll try and record a video on how I use kumo cloud lines on yen and yen crosses I don't use them on anything else generally they were designed with the Japanese yen in mind a bit like Japanese candlesticks only Japanese candlesticks generally tend to transfer quite well kumo cloud lines not so much they're sterling in looking a little bit toppy in the short term anything else ladies and gents anything else that I haven't covered that you'd like me to cover I'll quickly have a quick look back at dollar CAD see what effect that's had those those prospective payrolls report where on the CAD not much really let's have a look at a five minute chart a little bit of volatility but nothing spectacular as from as we can we see from the five minute chart I think somebody asked me if I use five minute charts a lot um not so much is the answer to your question um what I used to when I was actually trading a book but if you're trading five minutes chart five minute charts you really need to have quite a bit of time on your hands I'm really focused on it to the exclusion of everything else I generally don't tend to use them that much because obviously I have to do a whole host of other stuff do I believe in the transitory inflation view not really no um I'll look at um there's that 100 and big tech in the dowel in a second I mean transitory to a point but I don't think that all of the inflation that central bankers are talking about will be transitory I think an awful lot of it will be persistent let's take shipping rates container shipping rates they're not likely to be transitory which means there will be some stickiness to inflation and I think it's inevitable that we will see um slightly higher price pressures you've only got to look um at the petrol pumps to see how transitory or otherwise inflation is likely to be now the t-word is a good excuse for central bankers to do nothing you know it's there it's there it's their fallback position you know it's their raison d'etre oh yeah we think inflation will be transitory well believe you me some of it probably will be so use car prices will probably fall back down new car prices will go back up so that part of it I think is transitory but certainly I don't think all of it is so and I think that is the debate that's currently being currently currently being taken place unfortunately we won't know until it's too late um you know and I think that that's that's the big question how much will companies be able to absorb before they start to push prices higher um longer term positive view for gold but yeah absolutely um I think that's absolutely the case but not now um you know the way things are at the moment gold has generally tended to um be uh moving in the opposite direction to to yields which is slightly counter-intuitive if anything gold has been a deflation rehege not an inflation rehege so things of you've got a certain amount of dislocation in financial markets in terms of the Dow again you know it's positive for markets absolutely it's absolutely positive for markets and we should see equity markets go higher it comes back to what I was saying earlier do you you know say for example you bought the Dow now you bought the US 30 now and it suddenly dipped back would you be happy to run it over the weekend or would you try and get in and get out before the end of the day you know at the end of the day that's an arbitrary decision that you have to make on on that basis I still think you know that the Dow can go higher most definitely but the big question is will it go higher um from here and continue to go higher next week you know you're asking you're asking me where it's going to go in the next half hour hour or two hours I can tell you where I think it's going to go over the next week yeah I think it's going to go higher but you know as with everything timing is key um and sometimes the markets can have a habit being very unforgiving if your timing is ever so slightly off as I found out on quite a number of occasions um as a result of that and the fact that the S&P is is actually off its highs I think it's really dependent on what US traders do when they come in in in around about 45 minutes time I think the initial reaction could well be to try and take it higher the big question is whether there's the momentum there to continue to do that or whether we get end of week profit taking um as we head into next week we also have to remember August trading is very you know it can be very very um can be very very thin on occasion NASDAQ 100 or no price for guessing there the NASDAQ is actually down so um you've got a little bit of a drag on the tech which may limit the upside on the Dow and this is something that I've really been struggling to get my head around because if you look at what the US small cap the Russell 2000 has been doing you would think if the US economy is going as well as the data would suggest then small caps should do should be doing very very well indeed but the US small cap has been lagging behind pretty much everything else you know that's a bit of a red flag for me it's a bit of a warning sign for me let's look at it I mean that's a good payroll report and and the small cap reflects that but why hasn't that been reflected since we put in those highs back in March and in June while the S&P the Dow and the NASDAQ have all continued to make record highs small cap hasn't um and that's a bit of a head scratch for me but hopefully those two decent jobs reports with the with the revision and everything else should see the Russell start to push higher now if that happens and we get flow of funds back into the Russell we could see money start to flow out of the NASDAQ because of the valuation element because of the elevated valuations in the NASDAQ and we did see some element of that earlier this earlier this year where the NASDAQ came under pressure a little bit valued and the market went into growth so recovery stocks and that's something that we do need to be aware of when we talk about the NASDAQ and by definition big tech so you asked me about big tech let's look at share baskets and I'm guessing that's what you mean by big tech um so let's have a look at big tech well all right that's a little bit of a comparison that I was doing there let's just bring up a new chart for big tech there we go font slightly bigger so everyone can see what I'm doing there we go well there's no surprise there's no prize for guessing the direction of travel there but again it's so far out over its skis that for me it is susceptible to a little bit of a correction so let's go and draw that and there we have big tech but it still remains very much by the dip you know these share baskets are quite useful in terms of looking at the overall direction of travel of particular sectors uh and what have you yeah I saw that as well um the arc innovation etf has a record yeah I mean it definitely does I mean if we want to look at the arc innovation etf we can have a look at it in here because we've got it lock you know here we go there it is that's the fintech innovation and that's the innovation there so just get rid of the fintech one let's just redraw that line for the innovation etf and we've got this series of peaks on the arc innovation so that's an interesting that's an interesting line there on the innovation etf it's worth keeping an eye on if you're interested in that all right what else have we got have I missed any other questions silver I missed silver just scrolling back sorry about that gents so if you're looking for a particular asset class use the product library it's really useful um and if you can't find it it's because we don't have it again silver it's going to do what gold's done strong dollar retest these lows through here let me just zoom the chart up for you so you can actually see what I'm talking about though keep an eye on that low there oops oops so is that as with anything with this it's all about it's all about trend and at the moment the trend does look fairly decent for silver but it's likely to come under pressure if we break below break below 24 and a half dollars in the same way that gold is coming under pressure as a result of today's positive payrolls report okay let me just scroll down see if there are any other questions okay so um okay so anything else ladies and gentlemen's before ladies and gentlemen before I wrap this up um can you just show me how to turn on that snap pointer on your charts yeah absolutely I can um so basically you have a chart okay so what we've got here is the draw the draw facilities so bring them up that should be here somewhere oh my goodness gracious me what have I done well that's interesting they've obviously moved it they used to be a feature and I think they probably moved it here we go there's an option on settings where it says snap type and the snap type Richard is high and low it used to be on the used to be on the um used to be on the trend line feature itself but they've since removed it and decided not to tell me even though I asked them to do it but they've obviously run an upgrade and it's there so settings snap type high low and make sure that's selected okay thanks Thomas Thomas telling me how to use my own platform oh that's funny um so that's that's how you do it it's a fairly nifty piece of a functionality um but also means that you're an awful lot more accurate as well in terms of uh getting the right support and resistance levels on your trend line any other questions on RSI how do I get 80 and 20 levels they they come on by default I thought they were on by default I've always put them on by default so basically what you do with them is have you not got them on let me just put one on for you so you want 80 20 oh I see what you mean you want to change them fine okay I see what I follow you I follow you okay I'm not sure that you can but what I'll do is I'll inquire for you to I'll inquire for you to see whether or not you can and come back to you how does that sound I know so I'll come back to you on that one okay I'll just leave that on there so I remember to follow it up okay I'm getting off is crude oil is crude oil what okay you're not finishing the question so it looks like you'll have to follow that one up a little bit later otherwise I'm just gonna I'm just gonna wind this up now ladies and gentlemen thank you very much for tuning in um hope you all have a great weekend and I'll see you all same time same place next month thanks very much for listening and hope you all have a great weekend I'll speak to you all see you all again thanks a lot