Get on my level. Get on my level. I'm too flat. Quentin Richardson loving everything about this. Got it up and it's stuck. Get on my level. That's right. Right there. 13 seasons in the league. 2005 three point contest winner and love the podcast. Knuckleheads podcast with Darius Miles Quentin Richardson joining us right now. Good morning sir. And we're just going to jump right in because we had a big debut last night. James Harden new uniform. What did you think about his first day out with the Clippers? You know they struggled man. It was just one game.  But I think those guys have figured it out. I think you know all of them have done all the making money in different things. All that's left to do is win now. Lou's been on it since day one. He said keep the starting lineup as is just insert him. Do you like that move? Do you think that will stick at all? Yeah. You know all of those guys are the type of guys that you know you got to start them if you can. And I think it fits and I mean I think like I said I think they'll work it out. You know Kawai being strong enough to guard some of the fours and things like that. They got a lot of length. It's going to be a lot of versatility out there once they you know start hitting a stride together. And I know we just talked about the Lakers game as well so I might as well ask you the last play. How many times we've asked should LeBron have taken the shot or should he have passed it? Would you think the pass to Reddish good? I mean it's always I mean when he makes these plays it's never a question is it a good or bad play. I mean he made the right you know a good basketball play but I mean him being who he is and people want to see him go in and make the basket or get fouled and things like that. But I mean I think you know LeBron is who he is. He's done it the way he's done it. You know last night it didn't really work out for him because you know Reddish missed the shot but I think it was still a great play at the end of the game.  How did that come about? What made you guys do that? Man it's crazy. So the story behind that is you know we played there in LA and we was you know Darius was 18 I was 19 we fresh out of high school and we still was you know into high school basketball so at the time Westchester high school was like the top team in the city or whatever so that was coincidentally right up the street from where we practiced at LA Southwest Junior College so we we started to go to their games and they had Trevor Reza sign Adams Bobby Brown they had a whole bunch of guys over there man that you know ended up making it and doing well but that was actually their celebration and they were you know they were doing it in their games and you know we started to go to their practices and practice with them and stuff and they asked like oh man y'all need to do rep our stuff in the game one time so you know we did it we had only did it really one game but after we did it that one game the fans was like the next game they was like what y'all should they they was all doing it so you know it kind of became a thing and took off from there but it's crazy that definitely you know started out that was the Westchester high school that was that was their celebration you know they they asked us to do it and then you know the rest is basically history that is like the that's the original influencing like that's what an influencer right gentlemen so I hope kids are watching so on the on the podcast you said before the season started that Wemby was not your pick for rookie of the year but then sounds like you're maybe coming around to some things on women Yama what what have you seen that has been maybe the most eye-opening for you from him. I like his aggressiveness man I like I didn't think he would come out and and in shot hunting like look for the look for the ball and be as aggressive as he's been offensively I mean I knew he was going to be special and have a chance to you know block shots and change shots and do some crazy things defensively at the rim but I didn't know he was going to come out this aggressive offensively and really be looking to go to work like that. Q what's good bro. So I gotta I gotta how you so I gotta ask man the defending champion nuggets have started the season 71 Celtic suffered their first loss they fall to 5-1 which one of those teams you like better. Man listen I jay Tate on my young fella that's my guy so I'm pulling for him to you know him in the Celtic to go ahead and get over the hump but man I be lying about if I said that I'm not seeing what I'm seeing out there and Denver they they are back and they ready to defend their title and I feel like they haven't missed the beat I feel like Coach Michael Malone like he said he's got them in the mind space where last year is over with they not having some hangover like some teams have when they come back and start slow he got them right out the gates they hitting on all cylinders so I mean you gotta you gotta you gotta respect them and today today give you some reason not to so I mean right now Denver is still my favorite but I mean I I'm definitely pulling hard for the Celtic. You know the the west is interesting we we expect big things from the Suns we haven't gotten their big three yet we haven't been able to see that but if you have a game on the line and you got to pick Katie or Booker which one gets the ball.  You played one season for coach Spoe and his second year of coaching who did you see did you see what he was going to become that you knew he could possibly become one of the best coach in the NBA. I felt he was one of the best coaches I had played for at that time and I played for some great coaches you know I'm saying I played for coach Larry Brown you know coach d'Antoni coach Gentry a lot of guys a lot of guys it was great coaches I felt like me and Spoe got a crazy relationship because I feel like I played with them for like five years but I only played with them the one season and you know obviously we hit it off I had a chance to join the staff but I was doing other things and couldn't do that but yeah man I think I think I respected about Spoe was that that even in his second year he didn't back down he didn't care who you were like Jermaine O'Neill was it was a strong personality obviously you had D-Way he had you Don and she had a lot of guys on that team you know strong personalities but Spoe he didn't he didn't back down he he he would engage with you he would you know all of that like you seen on the court on the game when he got to with Jimmy like Spoe's not backing down and in any situation and I think that's that's how we got to be what he is because when it came to D-Way he did the hard things he when they had to go head to head I watched him and he did that and that's how you gain in respect to the whole team and the whole organization and when you when you challenge the guy to set the top that you know everybody's kind of afraid to challenge and he wasn't afraid to do that and I think you know that was a big part of him becoming what he is but I think everything else X's and O's Spoe works so damn hard and he's so overprepared it was no way he was gonna fail at that but I think the biggest challenges was the personalities and the egos and and he took it straight on man so you know that I think that was a big part of him getting over that hump and becoming what he is that's awesome I like hearing about that back in the day you and Paul Pierce were trash talking the art form trash you got ejected first trash talking which by the way in and of itself is special what so what was that is that a real feud is it just fun fun trash talk like take us through that man he does talk a lot so we had Paul on the show and we talked about it you know that started way back in day and it was a UCLA or it might have been like when we're high school when the runs were there instead of UCLA when you know just two dudes in there did neither one of them ain't gonna back down both of them gonna say what they gotta say and if it go further we could do that too but you know we we just was competitive and I think from that that that day back then we kind of marked each other that whenever I see you is gonna be on site and that's what it really was like it was it was it was like that several I mean the funny thing it was several games like people was thinking like the child when y'all mess with each other's girl or something like it was never nothing like that it was just I we go that's just what it is and that's what it was the whole time I love that I miss some of that from from today's game Julius Randall okay so you may might have better insight than most Julius Randall we know about his struggles last night he had a hell of a game and there's a lot of frustration here in New York from the fans towards Julius how hard do you first of all as a Nick do you hear the mumbling do you hear the talking are you able to put it out like what's he going through when he's struggling here first of all when I was there you you heard everything you knew what was going on somehow somewhere you knew and it to me and and in this generation there's no way with the with the social media and with the phones and with everybody having a voice there's no way but I mean in New York on man it's it's the garden those fans gonna come right down behind the bench and say whatever they want to say to you and they gonna say it loud and in demonstrative or whatever and it's like to play I've said it a million times man to be a Nick to play in New York to to be a giant Yankee any of that stuff like you gotta have a you gotta have a different type of toughness like a mental toughness about you because I've watched teammates literally get taken out of it and like like quit like damn this get me out of here like I'm I don't want I don't want any parts of this like I like enjoying my life and things like that and sometimes if you in New York and you're on the wrong end of it you might not enjoy yourself and if you're not the you know the the the right type of person mentally and you don't got that mental makeup it could it could affect you big time I've definitely seen that keeping it with the next Q when you were on the next Kobe job 61 at MSG. Yes. What do you remember? What do you remember about that game? Anything in particular?  It was I think Kobe said that too. Kobe said it was it was yeah it was I was looking like yo he's talking to him and like Wilson is out here getting put through the through the business because of it. He was he was doing everything that night bro. He was pump faking spending stepping through. I was like love like like great. Gladfully that you know Wilson was a Wilson had the mental makeup you need to have because you know a little bit of challenge. Some dudes don't recover from a night like that when it's really just almost all on you. It was crazy but you know Wilson was a different type of dude. He didn't really trip in care. He got back to it right away but it was like yeah we all looked at it that night like that was that was on spike.  I never had so what was your game plan going against so what's the scouting report on Kobe. Man for me whenever I played him you know I'ma try and be physical and everything and try and use that type of stuff against me.  That was that was it like you had to you know make things as difficult as possible and then you know hope he having some type of off night which didn't happen is you know hoping it all but I mean that was definitely you know we doubling we doing different things but ultimately you just want to try and make everything as difficult as possible for him knowing that he still could get 30 40 with it being you know your best effort and all of that stuff. Yesterday we were talking a little bit about the in season tournament because it's obviously it started on Friday. Most of us are still a little bit confused but we do understand money and Lou was right in saying that 500 grand is incentive I don't care who you are. Do you agree. I mean it's 500 out like who cares right it's the in season tournament is that good enough to to make you try a little harder. Absolutely I think absolutely I mean people would be lying if they say they don't I think some of the dudes with the biggest contract still looking at that 500,000 like yeah we need that I mean that's the nature of the competitor man like we'd rather get it than see somebody else get it and say they got it like that's that's how you know the competitive dudes are they just want to win if it's a chance to win something else like this is the first ever tournament of this kind so I know you know some of those dudes who who are competitive like that like a Yannis or something he want to go win like I don't know nobody that's at this level that you know there's a championship out there they just gonna say they don't care nah that's not true they want to go win it and be known as that champion or whatever and if it's a MVP or something to be one that they want to win that too that's why we here. Absolutely Q we shared a lot of stories when I came on the Knuckle heads podcast with you and D Miles and you guys have known each other since kids you got to give me a great D Miles story. Oh bruh I give you a D Miles man it's too many I the best story I could give you about D Miles is when I first met him right so D Miles came to play he's from East St. Louis I'm from Chicago but he came to play AAU with us the Illinois Warriors because Larry Butler was our coach so he came to us when he was in I want to say eighth grade so when he first got there we we had already went on a couple tournaments and play now we going to Nike camp right so he the week before Nike camp he crashed his mama car he like broke his arm something he got his arm in the sling and he had this one D Miles before like he started getting content he had the glasses on so we go to Nike camp he basically got ranked just because he was with us and we was calling him KG because he you know he was tall he was tall dark and skinny superman but like that was literally like he got because you know how it is when you young you play on the older team and that older team is killing everybody we were smacking everybody up the warriors beating all of the top teams and stuff and he was there all D Miles had to do was get a dump like catch a live get a black shot and it was like next thing you know he was the number one player in America he he took to form like by playing with us like once we went on like he took over over like next time I come see him he getting quadruple doubles like all of that with blocks rebound like he was he was going crazy like when you go see him in high school it was legit a one man show he out there six nine and nobody else bigger than six four and he played one through five doing everything it was crazy okay so pranks either you've been a part of one or you witness one what is the best one that you can remember oh man so when I was with the nicks we had we had Nate Robinson we had Nate Robinson Eddie Curry Jared Jeffries and Matt Barnes these dudes were children literally were children like it was like you know at this time we had to wear suits to everything that we did we had to wear a force flare suit so one game you come out we come out of the game and we get dressed and Matt goes I want to say it was Matt Matt goes to put his dress shoes on and like Nate had put like cream cheese under the soul so as soon as he stepped down like the cream cheese came all up so then the next game after that you come we were in Boston I remember this we were in Boston and Nate we come out of the game we get you know the game is over you better get dressed Jared had Jared had no Jared and Matt had took Nate's suit and cut all of his buttons off of his furthest suit and then they like twisted it and you know how you get the ice wrap when you get the little wrap go around the ice bags they had took his suit and like twisted it and wrapped it all the way up in the whole thing then when he unwrapped he noticed he had no buttons to button anything one of them all was when Nate Nate literally this is the sense how the wings that Nate would go to do a prank he was late for the plane number one he was late for a plane took that little $500 fine so but he was late because he went to the he stopped at the store to get XLACS the man put XLACS and Nate I mean and Eddie's cereal and they would bring like 10 boxes of cereal on the plane they would eat cereal when you going to travel XLACS and Eddie's cereal no and then obviously Eddie had the runs Eddie ended up missing the game the next day because it is because he was so he got to be hydrated and all type of stuff like these I'm telling you listen I'll tell you talk about a book that New York next team was unreal bro it was unreal it was always something I love messing with bodily fluids is the ultimate prank and I have the utmost respect for Nate Robinson that is no it's nasty Quentin we appreciate the time so much thank you love love the podcast I hope we have you back on appreciate it thanks for having me and keep doing our thing


lie detection takes a high-tech twist there are markers in the eyes that are able to accurately determine if an individual is being deceptive the new test claiming to see the truth how it works and why the creator calls it better than old-school polygraph this is San Antonio's Fox News at 9 well they say the eyes of the window to the soul and one technology company believes they're also the most efficient way to tell if a person is lying Gabby Hart takes a look at this new technology that claims it knows if you're telling the truth a new form of lie detection claims it can see the truth there are markers in the eyes that are able to accurately determine if an individual is being Neal Harris is the vice president of Converis the company that created this new technology called I detect it uses only the eyes to determine if a person is lying when a human being is being deceptive that there are these micro dilation of the pupils it's the extra mental energy that it takes to be deceptive I detect has been in the work since 2003 only taking 30 minutes to complete this new testing technology could be faster and more efficient than the old-school polygraph its creators argue that I detect may have the edge because it isn't influenced by any human bias so by re removing the human element we believe we can make the assessment of credibility far more forensic in nature Ron Slay is a security consultant who administers polygraph exams he says in his 40 years of experience he's seen all forms of deception and he thinks it takes more than a computer system and answering a few questions to detect a lie you can't automate the human mind we wanted to put both methods to the test so I sat down to see which machine would best read my line in the hot seat first we put the standard polygraph to the test slay asked me two questions that were simple enough to answer honestly I want everybody to watch the blue line is today Tuesday yes but before he even finished asking me the third question at work did you ever look at a boss with sincere eyes when you knew the reaction is already over but took off and it's barely coming back again then we tested I detect Harris had me write down a number between two and eight and then hide it I chose the number seven the examiner told me to lie about my number to the machine but to tell the truth on all the other questions as the eye detect system calibrated my eyes and then monitored my pupil dilation I did not choose the number seven it was not the number that I picked look at the spike on the seven safe to say that I got caught lying or preparing to lie on both tests but slay says it can sometimes be harder to catch the people you want to catch because they have their own truths they're not really answering your questions at all they are answering what they perceive to be your question slay and Harris agree that both I detect and polygraphs can get it wrong sometimes there will be some false positives and false negatives with I detect as it exists today but Harris says the beauty of computer algorithms is that they get smarter over time I trust computers and algorithms far more than I would another human being still the polygraph remains a powerful detection tool not likely to be replaced anytime soon I think it's the age old argument of man against the machine big time technology company apple has taken notice of I detect apple purchased the sensor technology that's used to calibrate and read the eyes does this mean our iPhones could eventually become handheld lie detectors Harris says only time will tell I'm Gabby Hart reporting


Hello, my name is Larry McCork and I'm a Tel Analyst at Atumbria University and today I'm going to talk about the Tel Technical Mentoring Program at Atumbria University. So first of all I'd like to talk a little bit about the Tel team at Atumbria. The Tel team are part of IT services at Atumbria University. The team is managed by Lee Hall and comprises of 32 members of staff across four service areas. These are Tel Training and Innovation, Tel Content Development, Tel Client Software and Tel Customer Success. The main remer of the Tel team is to use technology solutions to improve the teaching, learning and assessment experience for both students and staff using innovative and creative approaches with a strategic objective of enhancing learning through the effective deployment of technology, supporting both the IT strategy and the university strategies. The current support offered to staff by the Tel Training and Innovation team consists of bookable online daily one-to-one sessions. These can be booked by both professional support staff and academic staff and can last up to one hour. During these sessions staff can get support and advice on a wide range of Tel technologies. There's also Tel Central. This includes help guides, videos, best practice guidance, as well as case studies and other useful information. There's also organised a face-to-face and online group training sessions and also each department within the university has a Tel liaison contact. The Tel Technical Mentor Programme. The Tel Technical Mentoring Programme, what is it? The programme is a 12-week in-house programme for Tel staff which develops and builds on existing coaching and mentoring skills. It introduces several established coaching models and techniques such as Gibbs, the grow model and the jihari window. Upon completion of this programme Tel staff would go on to mentor academic staff at Atumbria University. The mentoring programme was also one of the initiatives of Tel Strategy Tel 2008 and was employed to support Tel Strategy Tel 2003 digital induction. The Tel Technical Mentoring Programme has several stages. Step one is that members of the Tel team take part in the Tel Technical Mentoring Programme. Once these Tel staff finish the programme they are allocated mentees. These mentees are typically new staff at Atumbria with teaching responsibilities. These will normally need to be able to use technologies such as Blackboard, Pinotto, Office, Turn It In, which Tel staff can support them with and provide guidance on. Once Tel staff have been allocated their mentees they will email them and agree an initial meeting. At this meeting initial goals and objectives are agreed as well as a timeframe such as the frequency of meetings and the length of meetings. As mentees are mentored their level and understanding of Tel technologies increases. This can have many benefits including increased student engagement, creating more accessible learning materials as well as creating more inclusive learning environments. So how was the programme structured? It was structured over 12 weeks and applied using a Blackboard organisation. It offered both synchronous and asynchronous learning activities and typically took between two to four hours each week to complete. So what activities were included in the mentoring programme? There were one-to-one and group coaching sessions, formative summative assessments, role-playing, observation, self-reflection, research and problem-based learning, PBL. The problem-based learning activities used real-world problems to increase knowledge and understanding. While the role-playing activities in particular strongly encouraged team participation and allowed opportunities to employ various mentoring techniques in dealing with staff with several pre-designed scenarios. What were the programme outcomes? A non-exhaustive list of these include learning about a variety of mentoring tools, the grow model, give perspective cycle and the jihari window. Also selecting and applying the most appropriate tool in a variety of situations and contexts. An equipping staff was an essay skills and knowledge needed to mentor new academic staff in the use of digital and tel technologies. How are academics supported? So to support offering, new Natumbia staff are sending an email which outlines two support pathways depending on their roles. The email also provides some context to what tel is and what support is an offer. Both pathways offer asynchronous support with staff sent a link to the online staff digital induction e-learning module. This contains comprehensive guidance and tutorials on all of the tel technologies used on Natumbia. Staff with teaching responsibilities are also offered synchronous support with an invitation to have a tel technical mentor and are prompted to suggest a suitable time for an initial 45-minute induction session either in person or online. All staff on Natumbia, regardless of their role, can also receive synchronous one-to-one online support sessions and face-to-face or online group training sessions. How are academics contacted? So there are several steps in this. The first one is a new starter list is received once a month from human resources. Next, mentors are allocated mentees at a monthly meeting. In this case, mentors are those tel staff who have completed the tel mentoring programme. These mentors then send an email to allocated mentees and the email will include what the mentoring programme is, information on the online staff digital induction e-learning course and also a link to an introductory video. Once responses are received, initial meetings are scheduled between the mentors and their allocated mentees. Feedback So several types of feedback were collected. The first level of feedback was a 10D feedback and this was an evaluation form. Each 10D completed in the programme evaluation form. The evaluation form consisted of 18 open and closed questions. The form had a 100% respondent rate. The initial evaluation feedback was used in developing and enhancing the second intake of the programme structure. This feedback aligns with level one and two of the Kirkpatrick feedback model reaction and learning. A focus group was also used to gather attendee feedback. Five tel staff from the first and second intake of the programme took part. Both online and in person attendees participated. It was an informal conversation which lasts about one hour with six open questions. The main email of the focus group was looking at if mentor behaviour had changed. Again, this aligns with level two and three of the Kirkpatrick feedback model learning and behavioural change. Various feedback was received. Attendees strongly agreed they could apply various coaching and mentoring techniques such as the grow model to a variety of contexts and situations. Attendees also agreed they were encouraged to develop effective practitioner skills. They also felt that the programme was challenging. Attendee feedback also consisted of a focus group, which again had five or six questions. The data from the evaluation form and focus group strongly suggests that attendees had a positive outcome after completing the programme, resulting in behavioural change in how they supported sessions, with staff now asking more questions and encouraging a more conversational approach. One member of staff in the focus group also commented that they tried to encourage those staff they were mentoring to come to their own conclusions. Staff also said that they used both the grow model and Gibbs. As well as feedback from those tel staff who completed the tel technical mentoring programme, feedback was also received by academics who were being mentored by tel staff who had completed the tel technical mentoring programme. A feedback form was emailed to approximately six academics with nine respondents. Responses were anonymous and the form consisted of four closed questions and three open questions. Again, some of the responses on the screen are visible now. Feedback academic staff would suggest that they used to have tel technologies and having a tel technical mentor had not only enhanced their teaching and learning, but also had encouraged student engagement and increased their confidence in the use of tel technology. Staff also reported a greater knowledge of accessibility issues. Final conclusions on impact. Tel staff, so those staff that had taken part in the tel technical mentoring programme agreed that they had employed various mentoring and coaching tools to a variety of situations. They had adopted the Gibbs model and reflected more on situations. They listened more. They offered more options. They established more conversational tone and encouraged staff to reach a conclusion themselves rather than just be told what to do. Academic staff agreed that having a tel technical mentor helped them use more tel technologies leading to greater student engagement. Delivered confidence in using tel and increased. They were more aware of accessibility issues and helped them create a more inclusive learning environment. Overall, the tel technical mentoring programme at Atumbria has been a success and has received positive feedback from both those members of staff who completed the programme as well as academic staff who have been mentored. Final conclusion. In developing the tel technical mentoring programme, tel staff have been equipped with the skills and knowledge needed to move beyond a traditional didactic approach of teaching where the learner is largely passive and form a more collaborative relationship with academic and professional support staff. Data from the online questionnaire would indicate that tel support sessions are becoming more collaborative in nature and encourage empowerment and problem solving and they are an evolution from the Sage on the Stage behaviours approach to a more constructivist, student-centred learning approach where staff are presented with choice and play a more active part in their learning. Furthermore, this approach also acknowledges the diversity and different levels of digital literacy from Atumbria staff and presents an opportunity for a constructive and collaborative support framework suited to individual needs in an agreed timeframe and schedule. Thank you for listening to the presentation. If you have any questions regarding this presentation, please email me at larry.magurg.atumbria.ac.uk where I'll be very happy to answer any of your questions. Thank you.


Welcome to this talk about Prometheus when we see what it is, what is new, and what's coming. I am Jean-Pyvoteau, I work at InWitz and I have joined the Prometheus team in 2020. And I'm Richard, I work at Grafana Labs and I have joined the team, I think, in 2016. So let's talk about what Prometheus is. That is the Quick 101. It's inspired by Google's Borgman. It's a time series database internally working with 64-bit values for all numerical data. There is over a thousand community-created instrumentations and exporters, way more non-public ones. It is for metrics, not for logs, dashboarding, standby, Grafana, even before a joint Grafana Labs. It's a highly dynamic and built-in services covering, which means that you have a lot of different ways to put data or information about what systems to monitor into Prometheus quite easily. It's built-in with Kubernetes. You can do zone transfers through DNS. You can have a Firebase services covering where you can put in your own stuff from your own systems. And there's dozens of other things, how you can get the information about what to monitor into Prometheus without any additional work on your, it's literally taking it from your operators, from your orchestration, from everything which you might have. It doesn't have a hierarchical data model. It has an in-dimensional label set. What that means is, normally if you have hierarchical models, you might have continent, country and customer, and then you need to select your data by customer across all continents and all of a sudden your hierarchical data model is already wrong for that type of theory. So by just attaching labels and allowing you to slice and dice your in-dimensional matrix however you want, you can simply select by whatever you want. For this, you are using Promco, which is a functional language, which is basically doing vector math. What that means is you set your language up once or your calculations, and then you just toss whatever amount of data into this calculation and get the results set up. No matter how much data comes or goes away, you always get out what you want. That's similar to how weather predictions and such are made. This language is used for everything with imprimices, for processing, graphing, alerting, exporting, everything where you work with the data, you always go through Promco. Super nice. It's really a simple operate. You don't need teams upon teams or anything. It is a monolith, even though it's cloud native, and it's super highly efficient. We'll be seeing a few numbers later. It's a pull-based system which gives you super nice properties around a certaining that everything which should be there or is part of your service coverage is also monitored, and you always know what the latest status is, and if it goes away or if it goes down, you see this immediately, which gives you very nice alerting properties. Very important concept. Concepts are black box monitoring where you look at things from the outside. For example, do you reply to HTTP requests versus white box monitoring where you look in the inside of your code and you instrument from the inside? Usually in Prometheus Land, every service should have its own metrics endpoint which is unfamiliar for people who are used to agents. There are various advantages to having distant metric endpoint because you are not tied with your versions and you don't have this huge uplift when you have an upgrade or anything. That being said, we'll be talking about agents in a bit. And we have super hard API commitments. We even historically treated pretty much everything which was experimental as stable. What are time series? Time series are recorded values which change over time, temperature, your memory usage, how many requests you got. What you can do with individual events is that you merge them into counters or histograms, which is something which is also done extremely often in the networking scene, which had a lot of those, what is now cloud native scaling issues, like two decades ago, where you have this super cheap way of compressing data along the access which you care about and then emitting this distilled information about whatever you're looking at. It's super highly efficiency for both storage and transmitting. The examples are, you probably read them by now. Those are examples of how an extra exposition might look like. I even know people who literally print F in their C code and then just dump this file on the web endpoint and that is their premises integration and it works. Like we have all the tooling such to make this nicer, but if you so choose, you can literally print F or even just echo in your shell script. It is really easy. Talking about scaling. Kubernetes is roughly equivalent to Google's Borg. Prometheus is roughly equivalent to Google's Borgman, but with the Monarch APIs. And Google couldn't have run Borg without Borgman and that means also not their services for the last X amount of time. One of the indirect effects of this is that while Kubernetes and Prometheus were created completely distinctly of each other, they have inherently been designed for each other and they're also written with each other in mind. So we have people who are on second instrumentation at Kubernetes and they're also on Prometheus team, which already tells you how much coordination goes on between the two projects. And the one thing which is actually recommended by Kubernetes to monitor Kubernetes itself is Prometheus and they put insane amounts of work into Cube State metrics to make this super high efficient to get all this data out of Kubernetes. On the just instance of monolithic Prometheus level, there's long-term storages and such, but if you run a single Prometheus, you can get more than 2.5 million samples per second an instance. We've seen more than 60,000 samples per second in core. We actually went quite a bit above this in some more artificial testing, but this includes the storage, the alerting, the curing, all of a normal Prometheus and we compress quite aggressively. The largest Prometheus instance, which we saw had 125 million active time series and it was running. Long-term starch, there are two long-term starch solutions which have actual Prometheus team members working on them. These are Thanos and Cortex. Thanos is historically easier to set up and run, but slower in curing and such and the initial scale or their initial point where Thanos started scaling was the storage. Cortex on the other hand is not as easy to run, but it has gotten a lot easier. It started with scaling ingesters and curios and then took the code of Thanos to scale a storage horizontally. If you're guessing that Thanos is playing to do the same with the Cortex scaling code for ingestion curing, you would be right. As a pipe dream of myself, I would like to see Cort Thanos at some point. Maybe we'll do, maybe we won't. So, what's new? So, yes, so now we will see what you have missed if you have not upgraded Prometheus in the last year and we see a lot of shows there actually, not updating very often the Prometheus instance, but let's have a look. The first point is service discoveries. So, in the last year, so it means like since I think July last year, we have added five new service discoveries to Prometheus which brings a number of service discoveries by, for instance, like to 13 or something like that. We have added Digital Oceans, Gateway, Ethner, Eureka, Docker and Docker Swarm. And this is only the beginning since we know that we are getting at least three more new service discoveries in the very next release of Prometheus and there is even more to come from the community. This enables you to use Prometheus in a lot of new use cases as well. Then you have TLS and basic authentication. So, while Prometheus has always been able to scrape using TLS and basic authentication, the targets, now it is also able to export its metrics and to export its interface using TLS and basic authentication, which means that you don't no longer need a reverse proxy if you want to secure your Prometheus, proxy your Prometheus instance. We have also designed and written a new exporter toolkit for your go exporters if you want to also benefit from the TLS and basic authentication that we have done for the Prometheus server so that you can instrument your own exporter using that toolkit. And this is what we are using also for the official Prometheus exporter like the node exporter at your proxy might SQL the exporters. So we are using that, but we are also encouraging the community to contribute to it and to reuse it. PromQL also has seen a lot of changes in the last year. First of all, we have including new functions, some of them which we are really like really wanted by the community like last of our time which enables you to take the latest sample over a certain range. We also have some new features to write better queries and to get more insightful data like the ad modifier in PromQL. It's disabled by default because it can break some assumptions that some caching proxy might have about the PromQL. But basically what it enables you to do is to run a certain selector at a certain date and time which means that you can now see like over the last hour the four CPU that the four containers that take the more CPU know. And that is like a change in the behavior because like before you could only have like at each moment the four more containers that use the most CPU. The next feature is like the negative offset. So when you are storing your data informatives, you can decide to apply an offset to your data to say, hey, I want to see the data but like one hour back. Now you can also do that like one hour upfront which will help you debug and deep dive into your metrics a lot more easily. And then we have also composite duration which have landed which means that you no longer need to think about like, oh, how do I write one hour 30 minutes? Oh, I need to write 90 minutes. No, you can directly write one hour and 30 minutes.  We have enabled informatives a remote write receiver. So remote write is a process by which formatives can send its metrics to a remote system. No formatives can also receive the remote write metrics. It is a different way to share metrics than the federation which exists in formatives because like the remote write also enables you to pass on like the still markers and a lot of other information. And basically like what it enables you is like if you want to run a formatives on the edge or if you have a use cases that requires for like a more like push model while still keeping all the promises of formatives you can now do that. So formatives still remains a monitoring system still remains pool based but now you have new possibilities to move your metrics around and that will definitely enable new use cases for our users. The next and this is one of the most weighted features that we have seen and one of the most exciting it is the exemplars. So basically what is an exemplar? An exemplar is a way to attach an external data to a metric set, which means that next to your metric you can now have like for example a trace ID. This is the more common use case. So it enables you like when you have when you have an actual alert or a dashboard you can directly see an example of a slow metric. You can see an example of a fast query and then you can jump from your metric to your traces. And the nice thing is that Grafana already supports that they already support the exemplars and you can directly plug your point tracing Grafana plug your tracing backend like tempo or digger into your Grafana and jump from your metric to your traces. If the trace ID that you are seeing there seems some familiarities because like this is directly taken from the W3C tracing specifications. And last let's finish with the alert manager. So we have two new features coming to the alert manager. One of them which is time-based muting which means that you can decide now directly in the manager to decide that some teams should not receive some alerts during the weekend or out of business hours. And you can control that for each route. So this is like a nice addition that's required before that a lot of stuff happening in PromQL or in the Prometheus upfront. Now you can do that directly in the alert manager. And the second feature is the negative matchers. So now you can match, you can create a salons that will match the alert that do not match certain labels. So you can decide for example to put everything but production in silence. You can decide to put everything but something in silence, which is like also going to be helpful for the people who actually operate and are on call with the alert manager. So what's coming next? What's coming in the future? The first most important part or the first most important point is that we as a community are trying to be even more aggressively open than before. That has several different dimensions. The maybe most obvious one is that historically, as I said initially, we have treated even experimental features and interfaces as functionally stable and immutable, which is great for stability. But as Julin just said, it would not enable certain use cases. Like for example, if you have cash in process and you know that you have cash in front of you and you don't want to ever break them, you're kind of locked in. So by being more willing to have experimental features, A, which change current behavior and B, which just to change what it means to be experimental, we want to open up more flexibility, more innovation. Or in the case of remote read write where we literally just brand the experiment as the first version. So we have this stable basis and then we can innovate on top of this. A lot of our old assumptions are being revisited and we are deliberately enabling more use cases. Julin was also just talking about this with more services coverage or the exported toolkit also noted here. We try to make more of a box and use cases which are maybe not recommended by primitives like the agents, but still valid use cases from the end user perspective. Of course, while we would like everyone to be able to run their own metrics endpoint, for example, that's not the view which a usual enterprise security team will take. That you have like two dozen different ports open which are not even continuous and they cannot tell from the outside which ports should be open on this and that machine that tends to make people nervous. Putting all of this behind one single port and then either using paths within that port or to just push stuff through remote read write are totally valid use cases. And so we are trying to enable more and more of those use cases to actually enable people to operate with the stuff within the premises main org and not spreading this out to the wider community and as such creating differences in different approaches by upstreaming all of this or re-upstreaming in all of this, we hope to just make it easier to reuse the code which we have and to just make it easier to use. We have a few design docs. The slides will be linked and these are clickable. So you can just, you can read through them. You can give feedback. Another thing, a large focus point of mine will be imitation is the sincerest form of flattery and premises is the defecto system within all of cloud native and also beyond, which is great adoption wise and it is great for the project but it also means that at some point there start to be certain issues. If you look at the most current SIP observability end user radar, I made that wrong, the title is wrong that is the current CNCF end user observability questionnaire. You see that permittes and open metrics are in the adopt and in place one or respectively place five in all of the CNCF end user sort of part which is quite a statement. And if you look into the market be it open source projects, be it closed source, be it near to two permittes, be it super far away from permittes, there is a lot of interest in permittes and then parts of permittes. And we want to ascertain that everyone who chooses to use any of those is actually able to use them within the permittes ecosystem as they expect. So this is an ask which is coming from CNCF, from the end users, from vendors, from projects to support this cross testing, basically becoming more of a standard for cloud native observability. We already have two specifications out. This is one of the metrics which is the exposition format as you saw earlier and the permittes remote write specification which is how you can bulk push data from, for example, an agent or a permittes server, two long-term storages or in certain pipelines where you can then handle your data and put it onwards. The nice thing about starting with those two it's basically once the interface to get any data out of systems into a permittes compatible system and then at the second step, once it is already in a permittes compatible system, emitting all that data to whatever the consumer long-term storage or whatever is, that also automatically covers both pull and push, which is super nice for a lot of operational reasons with the guarantees that in between you have a permittes compatible thing which actually does all the cleanups and all the everything which you need to do for just plain expositions, once to basically have it in TSTP compatible format and then remote read write it. We have a variety of test suites already. We have a prompt compliance test suite. We have a remote write compliance test suite and open metrics compliance test suite. We are thinking about having TSTP and data correctness test suites as well. We might even have more that remains to be seen. It's also a little bit of how and who wants to have what basically just where we see usage of aspects of permittes. We want to just make sure that all of this is done in a compatible format. We'll also publish all of this on the main website, permittes.io, where we have regular tests. As of right now, the rough intention is to have versioned tests. So you know you have 2021-4 or whatever and that is the version of that particular test. And then it is valid for, I don't know how long, one, two, three minor versions of permittes, which translates to a few months. And then you can just really run those tests. So everyone using this knows that there is a certain expectation of what version range of permittes this thing is compliant with or not compliant with. Yeah, and also we'll be working with things. You have to actually have a mark of approval or some such, the calls with the lawyers and everything with the logo and such, that's still outstanding. And coming to all of those things which are coming and there's lots more in those documents which are also all links. So you can just click them through in the slides. Everything which we do is as of this year, recorded and open to join. We already always publish like our meeting notes and everything, but it was a remnants of this all being in-person that we didn't truly realize that we could just make all of this online and public to join and everything. We have always invited people to the in-person things but that doesn't scale. Whereas doing it online is supervised as being just recorded and published. But also it is open to join. So all of those just drop in, there is a calendar. We publish all of this on the YouTube channel. And I hope we were quick enough that we get lots and lots of questions. Of course, we tried to optimize for basically giving you this team in three levels. And now for actual questions which we are very much looking forward to. Thank you very much. Thank you.


All right, hello everyone. How's everyone doing? Good. It's a 10 a.m. Talk on a Friday. So thank you for coming out So as I was introduced my name is Adrienne corn also known as a k-47 Intel if you follow me on Twitter or anything a little bit about myself, so I am a Canadian born and raised in Toronto area. So sorry for that if I say sorry a lot my presentation typical Canadian here My professional background in my career has been really around intelligence side doing things like threat intelligence O-scent threat actor tracking stuff like that I've worked in financial services in the tech industry right now I work for an enterprise DNS provider called blue cat networks. I do threat intel over there right now As I was introduced I also work for an offer profit called trace labs where I'm a member of the leadership team over there and Something else I do is I organize a DEF CON Toronto events over in Toronto So we meet every month. We do workshops ETFs talks and that type of stuff So now everyone knows a little bit more about me.  We'll talk about some common uses of O-scent we're seeing out there The challenges we're seeing with the O-scent today And new applications of it seen out there and then what the future holds for that So with that being said what is O-scent and where did it all start? So there's a lot of terms going around there about what O-scent is very broad industry There's some terms that are a bit outdated some that are current some opinionated So I'm gonna go and give you my opinion of what I think O-scent is So in my opinion O-scent refers to the collection Processing analysis of publicly available data to extract meaningful intelligence and get intelligence value out of that That's really what I see O-scent as if you can extract any intelligence value, then you've actually done O-scent And where does this come from so there's many different sources of O-scent out there We have the surface web deep web dark web social media news media Academic sources government records and extends to pretty much anything on internet. That's publicly available So why don't we take a moment to take a step back and figure out, you know, where did we all start with this? How did O-scent to get here today? So before I dive into like the timeline of that Curious if anyone in the audience knows what year O-scent actually became a thing if anyone had to guess a year No, okay So O-scent actually started close to 80 years ago Back during the World War two era where the US Looked for new ways to gather intelligence one way to do this was they started up a branch of FCC called the Foreign Broadcast Monitoring service and what they were tasked with doing was monitoring public radio waves that were beamed at the US for any Propaganda material that their enemy combatants were trying to spread to their country That was very the first use of O-scent seen out there They did start to see intelligence value out of this and that's why they continued to do work in O-scent space And they later expanded this to start looking at stuff like Newspaper clippings from countries around the world. They actually stood up over 40 monitoring stations Internationally to start collecting the cataloging all this intelligence from just public data out there That's kind of where we started Moving forward to 2005. This is really where O-scent took the next stage in evolution So you saw the rise of the internet people began adopting it, you know The common household had a computer with internet access Social media started to emerge. We had sites like MySpace Twitter Facebook even YouTube This all came out around this time area So the sources of O-scent started to emerge out there in terms of social media and such Also around this time period we had the CIA open up the open source center where the government was actually Interested in now taking advantage of all these new sources of open source intelligence Collecting it from you know digital media and all of that and starting to catalog that for their purposes Moving forward to 2009. This is really where social media usage took off. This is where O-scent space started to boom We saw smartphones becoming accessible where anyone could have a smartphone download their social media apps Had a camera and a smartphone and it could start sharing more moments of your life Than ever before and a lot of these social media sites would have more of a default Public state where if you post something it's public to internet and more non tech savvy users may not have been aware of it So they were kind of inadvertently sharing O-scent without knowing it Then fast forward to a few years ago to today we saw O-scent being applied to many different use cases. So businesses investment firms Political campaigns if you want to do some oppo research you can use O-scent for that if you want to look at Target voter audience O-scent can help you there if you're an investor looking to invest in a company You might want to look at the public presence of that Organization and you can do that was an O-scent as well Now moving forward to talking about More common uses of O-scent that we're seeing here today So you have your typical security use cases like blue teaming red teaming using O-scent give your threat actor attribution You also have the business side as well for stuff like business intelligence. So I'll be diving into all that right now So on the blue team side our blue teamers using O-scent So if any of you have ever worked in a sock before you've probably done O-scent without even knowing it I have a scenario here. We'll talk about So typical sock analysts you get an alert in your queue Let's say in this example. We have a malicious word document was detected by some endpoint device Maybe the context we're getting here is date of detection File name hash and maybe that's all we get so as an analyst I might not know what to do with that might say hey, this could be a false positive I'm not sure but how can I validate that? How can I use open source intelligence to further get some contextual information and investigation like that? So if I'm using O-scent For this type of stuff. I might take that hash that we saw there Pop it into a tool like virus total see what it knows about it. It's public available source So you can see here in this scenario. We have 46 of AV engine saying that this is a bad file So that's probably indication. We're not at a false positive here But if I want to go deeper and figure out, you know, what threat might be associated with that actual word document You might pop that hash into Google and see what it knows about it Typically when I do investigation, I pop stuff into Google and see what other threat and tell related websites are telling me about it So here we can see we have some context that this word doc might be associated with Emotep, which is a very prevailing banking erosion out there in industry today If I want to go further here and see, you know, maybe where did this word doc come from? I might go look at some of the URLs that are showing up on the Google here as well So we got here URL house, which is like a public Open source feed site for malicious URLs We can take that URL and see what else we know about it here using another O-scent tool URL scan.io This is one of my favorite ones. I like to use we can go and search up that domain See if it knows anything about it without actually like sending it there for analysis So you see here someone analyzed this URL at some point before it's confirmed to be malicious But what's interesting here is you can see the content that was returned from the web server side was an actual word document So that would support our claim that this malicious word document that was detected might have come from this URL here And then if I'm in a sock I might pivot off that to try to find a source of that infection So just using O-scent I can go from just a hash to figure it out where an infection actually came from This might be an example of an email you would see here. These are your typical, you know Your scan is ready themed fishing emails up there Now let's look at how red teamers are using O-scent today. So a lot of you are probably red teamers in audience here I know where recon village Typically when you're using O-scent you're in the reconnaissance phase of your engagements So doing stuff like recon on domains, IPs, any applications you're targeting looking for stuff like open ports, services, etc If I want to do some recon on domain I might use a public tool like who is to see registration information See if maybe someone's exposed their personal phone number there or address that I can use to pivot off of and find other information on my target If I'm looking for open ports and services I can use a public tool like showdan to see what's open without actually probing the application itself and When we look at targeting personnel on aside from infrastructure a lot of engagements You're always looking for the weakest link in a company trying to target the employees to see what info they're gonna give you So if I'm targeting personnel, I'm gonna be looking at stuff like their social media email addresses that might be public Frequent locations they might be at See if I can actually scour their social media and find things like the posting pictures of their ID badge This is common people start a new job and they say like hey, here's my ID badge. Check out. I started job at Facebook today You might also find stuff like passwords on sticky notes up on the wall That could be a public available source So There's just ways you can use O-scent to like gather enough information to know where you're gonna start with your engagement in the recon phase and Then another technique you can kind of use O-scent for it's not Directly doing O-scent against someone. It's kind of using their O-scent against you I like to call it counter O-scent where you're setting up Google ads or Google analytics on some of your infrastructure to see if people are searching for it So if I spin up a custom domain for a campaign and you know I send a payload to someone and it calls out to a domain if I see someone matching an ad Based on a keyword for that domain It's there's a good chance that my target is aware that I'm looking at them or you know targeting them and that can kind of shift tactics from there Another use of this is using virus total to see if someone's uploading your payload there to see if they're looking to see What other AV engines are thinking about it? This is another way to be tipped off So a lot of red teamers threat actors to their monitoring virus total all the time to see if anyone's like looking at their stuff there Now another use for O-scent is attribution. So this can be targeting someone trying to find out their identity. It could be threat actor attribution Someone who's famous for this is Brian Kribes. He'll he loves the Docs people. So a few years back His site was actually DDoS by the Mariah botnet and this kind of set him out on a mission to uncover like hey Who is behind this botnet? Why are they targeting me? Can I doc some? So what what did he actually use to help uncover the identity? Well, he did use some closed source intelligence, you know talking to his contacts and stuff like he typically does But he also use O-scent as well. So things like looking at archived Twitter posts related to the person he thought was a The person behind Mariah looking at stuff like LinkedIn profiles to find out employment information Pacemen way back machine. These are all O-scent tools that people like Brian Kribes are using to do docs in your due attribution Now another use of O-scent is business intelligence And we're starting to see this emerge more and more before O-scent was kind of seen as Something used for like cyber security something's for engagements Maybe government but now you're seeing businesses start to adopt this as well So if you're looking to investigate new markets They might use O-scent to see what companies in that space are actually doing They also might use O-scent to identify things like business risk So something common is corporations are now spinning up Internal investigation teams where they're looking into their employees are looking into any Associations with their company that could have risk to their reputation and such So actually recently I was a beast as LV this week and I was talking to some guys who do a pen test Internally and they were actually given a challenge to take their boss's business card Take only the information on there and pivot off of that using O-scent to try to find out you know what risk there is to the company with this Individual and what they were able to find was his personal address his salary information They're able to find information about his family which they were able to use to unlock security questions to his accounts And this is all with just an email address name and phone number So you're starting to see businesses look at this stuff more and more Now O-scent is a very broad space. We're seeing it's applying to many different uses We're seeing it expand into the other areas of intelligence as well So typically in the past if you're doing stuff like Q mint or geo int you have to have Special access to tools or physically be there surveilling someone but now using O-scent you're able to do things like geo int using Google Maps Google Street view Google Earth Google satellite all that stuff. It's publicly available And now you can start using O-scent to apply to these other intelligence disciplines as well If you're doing human you can surveil someone social media to see places a frequent and kind of build a profile of you know where they're gonna be at So really because of the passive nature of O-scent it's becoming a more attractive intelligence technique to People in intelligence community because if you're doing this right no one should know that you're ever looking it's passive in nature You're not querying systems to get new information. It's already information that's out there Now I did say the O-scent industry is very broad and with this there come some challenges So the first one I see a lot is there's really no clear definition of what good O-scent is Everyone has their own definition, but there's a lot going out out there Another challenge we're seeing is there's new sources of O-scent popping up very fast You're also seeing a lot of them being taken down as well I'll talk about that a little bit more and then another problem I see is there's a majority of tools being falling into two different categories I like to call it single use tools for very specific purposes or use case specific tools that are more your Enterprise platforms that serve a very specific use case So why don't we dive into what is good O-scent? So if I'm doing O-scent is me gathering, you know Someone's whole friend list on Facebook good O-scent if I map out 500 people on a map here Is a good O-scent? Well, if you can get intelligence out of that maybe it is but just plotting public data on a link graph maybe not So why don't we play a game of O-scent trivia? Let's see I'm gonna put some definitions up of what good O-scent has been defined as in industry and curious to see what you guys think Would be the most correct answer. So if we look at the first one A good O-scent is pivoting from one public data point to another in an efficient manner to produce intelligence That's number one Number two good O-scent would be collecting processing and analyzing large amounts of data to produce intelligence Or three driving meaningful and actionable intelligence from open source data So let's do a vote who thinks it's number one Okay, who thinks it's number two Okay, you guys are too good who thinks it's number three Gave it away So trick question, they're all Correct to some extent But the most correct answer and I'm gonna be that guy if you've ever done like a CISP exam or anything The most correct answer here is getting meaningful and actionable intelligence Really, it shouldn't matter how much data you're processing or analyzing It only matters about the finished intelligence product like can I produce actual intelligence that can inform my stakeholders? So typically you'll see when someone does intelligence. They have key intelligence requirements So unless you meet those you're really not doing good O-scent And also looking at doing O-scent in an efficient manner Sure, it's nice if you can pivot from one point to another fast But unless you're really getting meaningful and actionable intelligence, it shouldn't really matter So that's just my opinion on that point there Now the next challenge we're seeing there's so many new sources of O-scent popping up It almost seems That as well for every five O-scent sources that disappear ten more pop up And it's just we're playing a game of whack-mole. It's just like okay, which one do I look at now? There's so many tools popping up so many platforms APIs are changing. So how do we tackle this? So the main way to do this is to really stay up-to-date with all the O-scent tools listen to your podcasts Look at your blogs see what tools are being more commonly used to serve the specific purposes that you need them to So why don't we take a look at some examples of what O-scent tools have been changing out there in the landscape? So One thing that happens is typically a company will tighten up their privacy or security Which closes off a source of O-scent? You'll also see individuals become more aware of their privacy close off those sources of O-scent as well We look at things like Facebook profiles before they were typically public by default now everyone is locking them down So maybe you know five years ago you had a lot of O-scent from there, but now you're starting to see people become more aware So how do we handle that? If we look at Facebook again Recently after the Cambridge Analytica scandal they had they started tightening up the privacy of their users So they had this really good Facebook graph search tool out there that leveraged a Facebook API To do a lot of mass-scale searching across the public Facebook data Now this was being used in a legitimate way by Investigators out there and such for good purposes But was also being abused by some malicious people as well so you saw Facebook close off their API a lot to this and In turn you saw a lot of O-scent tools that used this API Starting to go down to say that hey We can't support this functionality anymore because the Facebook API got closed off for the Facebook graph search So that's the challenge as well. How do we keep up with that? In addition if we look at the tool landscape There's a lot of different tools out there One of the websites I like to use is O-scent framework it kind of spreads out How we can pivot from one data point to another using public tools? If you look here just taking a username you can pop it into I don't know 10 different tools and look to see if there's other profiles out there that use it You look at email address there's so many different email tools But which ones do we use which ones are the you know most legitimate good for my use cases? It's it's hard to tell Especially if there's someone that's new to the O-scent industry and you know doesn't know where to start It can be a little bit overwhelming And if we look further at the landscape of O-scent tooling here I kind of separate O-scent tools into two categories You have your single use ones on the right things like have I been owned where you're looking for breach information? Virus total you're looking for malware information who is domain Tools like ten I you know reverse image search people have their custom scripts And they serve very specific use cases and they can be flexible because you can customize them But the challenge is there is that if you go into one tool and you find one piece of intelligence You pivot let's say from an email address to a domain name Now you got to take that domain name pop into another tool and pivot from there And then you're going to keep going down rabbit hole of opening up a million tools and your Chrome browser is going to have a hundred tabs That's the challenge here Then on the left here we have our enterprise tools. These are more full-fledged platforms They have use case specific criteria things like searching a dark web for stuff. They're refined to Meet certain business needs and these are great for you know specific use cases But what if I'm an organization who has a very weird O-scent use case How do I handle that? Do I go right my own tools every time or is there something out there that I can leverage to do what I want? And that's where I really see The gap here in O-scent landscape There's really no platforms out there where you can define your own O-scent workflows where you can define your own O-scent use cases What I think we're going to start to see in the future is platforms where you can kind of Build your own workflows to say I have this input take me to here take me to there And then take me to here and that's gonna be my finished intelligence I find a lot of tools already have that built in but for very specific use cases So I think this is a need that we have in the industry Now, why don't we talk about some new applications of O-scent? We're seeing out there So things like blockchain and Bitcoin They're known as a cryptocurrency, you know for financial purposes, but how can we apply O-scent to that? There's definitely some use there then there's things like the trade slabs crowdstores to O-scent for missing persons We look at missing persons before in the space and We didn't see O-scent being applied there that much from the greater industry. So we'll talk about these So if you look at O-scent for stuff like Bitcoin Because of the way Bitcoin is designed, you know to the general public they might see it as being secure and anonymous But in reality you have this public ledger on the blockchain of all the transaction information associated to Bitcoin address So if I'm looking into someone's Bitcoin wallet address, I know it's associated to them I can now see all their transactions on the blockchain like number of transactions full timeline of those Amount of money sent or received where it's coming from where it's going to and then any other associated Bitcoin addresses Maybe in the same wallet as that one that can be very valuable for investigation purposes So before you were seeing people want to do financial crime analysis They had to have special access to banks now you can do it publicly using O-scent With things like the blockchain Now looking at trace labs, so I do work for trace labs not for profit We do crowd source O-scent for missing persons It's actually just a couple years ago that this new model was born around crowd source O-scent to helping to find missing people Before we saw like a lot of vigilante sites pop up that did this but not really in a structured way So oops the idea here was to really pair people in the O-scent community Together to work in teams and crowds versus a collection of O-scent to help solve the social problem So problem statement here We have a number of missing persons cases worldwide not enough resources to tackle them all with the same level of urgency Sometimes law enforcement can be understaffed in that area So how can O-scent help here well now? We've built this community where you can bring together skilled investigators with more senior members as well to track A digital footprint of an individual to help find valuable intelligence on them to provide law enforcement with So the goal here is to really get intelligence value for law enforcement Provide them new leads on investigations that they can actually follow up on and help out We've really seen this starting to be adopted also by the general public So people who haven't done O-scent before are learning about us and saying hey Can I try it out and you know with a little bit of O-scent training they can actually go and start looking for stuff on these missing people So really we're starting to see that like 2019 is the year O-scent is going mainstream more people are becoming aware of it More people are getting involved there So how does our model work exactly so what we really try to do is bring together the investigators also known as intelligence operators and this diagram here and pair them with our more volunteer team of Intelligence administrators where people are collecting O-scent Submitting it to us and we have our administrators vetting it to check for relevance and context and such and then if it's vetted We store it in a database package it up after and share directly the law enforcement So that starts in the model here as well and what we really do is we look at only public cases as well So if law enforcement is asked for the public's assistance with a missing person's case We can push that to our platform and people can start working on that right away So this is actually an example of one case just a sanitized case There's not a real person But this is what you would see typically in one of our captured a flag events where we put up a case We give the known information that's publicly available We give the source link and it's up to the contestants to start crowdsourcing O-scent on these people doing Pivots from one piece of information to another We have a number of different categories for flags that they can submit this O-scent against Here's an example of what one submission might look like We have a category called advanced subject info Maybe what I'm doing is looking at someone's phone number that I found Pivying off there to see something like their used car for a sale up on Kijiji That can be a valuable piece of intelligence that can help out in a case These are just some examples of you know what we're seeing And this is actually an example of a recent event. We ran last month We ran a global international remote event where we had over 200 people on the platform collecting O-scent We had about 25 intelligence administrators and here's a breakup of intelligence regards So you're seeing different things here like dark web information day last seen of the individual Employment information family friends. There's just so much you can find from O-scent here So now I'm moving forward. Where do I see the future of O-scent going from here? So I talked about, you know, the challenges we're seeing I'm talking about the uses where it's come from What are the new applications of it? But what I really see happening in the future is More crowdsource models are taking advantage of O-scent to solve specific social problems like the missing persons Trace labs also I expect to see more dedicated O-scent platforms spinning up There's a number of startups in the space doing this work already But I think we're gonna see more of this as O-scent becomes a more well-known space I also think we're gonna continue to see the shifting of O-scent sources I don't think that's ever gonna change. There's always gonna be sources popping up going down We just have to stay up to date with that and there's gonna continue to be roadblocks there as Companies start to tighten up their security. Users start to become more privacy aware We're gonna see roadblocks here and collecting O-scent, but that's okay because we're gonna figure out a way to get around it So that actually concludes my talk If anyone has any questions at this time, I'd be happy to answer And if you want to learn more about what we're doing at Trace Labs that I talked about We're actually running a full day O-scent to CTF tomorrow in the contest area I'll be there if you want to come up and chat more about that as well But right now I'll open up the floor to questions Good. How are we doing on time? Good. Awesome. Thank you


Sometimes these stories they just write themselves. So we remember a couple years back We had a pending free agent in one Zadaria Smith the Baltimore Ravens did and he was just on the come up His play got better every year and year and year But that's because his opportunity got increased every year and year and year But then it got to his final year his contract year and boy He showed out he showed out big time and he made himself a lot of money Unfortunately for Ravens fans. He did not make that money with the Baltimore Ravens. He made it with the Packers But most Raven fans we weren't surprised because we know that Ravens one thing that they would try to do They would draft these late-round past rushes like a Matt Judon like a Zadaria Smith And when they started ascending when they started getting better and better Ravens would be like We can replace that guy. No problem. We'll be good. We'll be fine not worried about that He's just a fifth round pick. We can get another fifth round picking drafts another fifth round pick and he'll do the same thing He'll go through the same process, but it hasn't been so sweet So now a report came out that the Ravens are apparently Trying to right their wrongs with one Zadaria Smith Tom Pellecero said that the Ravens are pursuing Zadaria Smith right here right now and this doesn't really come as a shock or anything It doesn't come as a surprise anything like that It would almost kind of be expected. I mean he played good ball for the Raven He played great ball for the Packers because he became a starter there. He was a starter there He was a full-time guy now if They are Pursuing him if this report is true, which I do believe it is My only concern would be his back. How good is his back? I know they said he's healthy now But is he really all the way back? I know he's posted the videos of him working out and stuff And doing all that and he motivated me. I'm like man. I need to work out some more too But anyway, that's beside the point But with Zadaria Smith, is he all the way red is his back like really good to go because you know with back injuries like They really scare me when it comes to football players because back and neck injuries the most Because you just feel like they linger and linger and linger and linger So hopefully for Zadaria Smith if that doesn't end up being the case Hopefully for Zadaria Smith, even if he doesn't sign with the Ravens Hopefully he is good to go. No issues. No setbacks. None of that. So wherever he goes. He can ball out, man Wherever he ends up being Could it be with the Ravens? Could it be with somewhere else? We'll see if I had to really guess ah I wouldn't I wouldn't think that it happens I wouldn't think that it happens. I'm sure he would be interested in coming back to the Ravens I'm sure that Ravens will be interested in him coming back But I think that he's gonna be able to generate more money elsewhere I think there's gonna be another team that ends up being able to pay him more money than the Ravens can Ravens can provide him with a great opportunity. They can try to sell them on their new defensive coordinator They could try to sell them on their new scheme how that's gonna be even though They said it's gonna resemble the old scheme a lot too and they can sell I mean, he knows Baltimore stuff. He knows the team. He knows a lot of the coaches and all that He knows the culture. So that's already a sale right there But the biggest sale when it comes to bringing in a free agent is money it's money and Will the Ravens be able to really offer Zadaria Smith the best money? No, they won't they won't But that's that would be the biggest hold up I think and that is of course the most important thing because you could tell a football player Hey, you want to win you come here you come through. Oh, yeah, that's great You can tell a football player. Oh, you love a great culture a winning culture You come through. Oh, yeah. Yeah. Yeah, you can tell a football player. Oh, we got a people's coach He loves the players, you know this coach you play for this coach before already come through. Oh, yeah. Yeah. He said well, but But we can't pay you that much money my friend and then that player would be like, ah, you know what? I'm not gonna come through. I'm out. Bye


This photograph marked the beginning of my work documenting Palestinian women activists in the West Bank. March 15, 2011 was the day of national unity demonstrations across Palestine. As I was taking pictures in the Ramallah, I noticed that many of the key figures there were women. I became aware that day of a unique group of women activists. In this photograph, we see a woman standing on the balcony of a building draped in a large banner. Two historic figures are depicted on the banner. On the left, Fatih Shkaki, founder of Islamic Jihad. And on the right, Yasir Arafat, leader of the PLO and the Fatah. This young woman had cut a hole in the banner to look out beyond Palestine's veteran male leaders. Looking up from street level, I noticed her lit by the late afternoon sun, holding her national flag, framed, albeit smaller in size, but side by side, with two of Palestine's iconic leaders. In order to stand there with them, she had to literally cut a place for herself in the national political fabric.


Welcome to Spotlight. I'm Liz Wade. And I'm Mike Proctor. Spotlight uses a special English method of broadcasting. It is easier for people to understand no matter where in the world they live. In 2005, many people watched the documentary March of the Penguins. This film continues to be popular today. The film shows a real group of birds in Antarctica. It is about their journey to mate and raise their young. But these birds do not fly. The penguins walk together across the ice of Antarctica.  Suddenly, one penguin loses his balance. He falls on the ice. This happens a few times in the film. Every time penguins fall down, people watching the film laugh. The penguins are cute. People liked the film very much. So much, in fact, that police in England think that it may be the reason behind a crime. A man went to a zoo in London and stole a baby penguin. Authorities think that the man stole the penguin after seeing the film. They believe he wanted to give it away as a Christmas gift. What is it about these animals that makes people spend money to see the film many times? Why would someone break the law to steal an animal? Today's spotlight is on the science behind what makes something cute. Michel Gaultier-Clairek studies penguins. He thinks that many people like penguins, but some people do not understand them. He told the New York Times newspaper, People love the penguins way of standing straight upright. They like its colors, which look like human clothes, a tuxedo suit, and they like the way it waddles as it walks.  These things make penguins seem cute to people. But there are good reasons for all of these things. For example, look at the way penguins walk. Penguins move from side to side when they walk. People call this way of walking, waddling. The penguins may seem to be out of balance, but Dr. Gaultier-Clairek says that the penguins waddle to save energy. In cold Antarctica, penguins must keep warm. The penguin's color also has a special purpose. It protects the penguins when they are swimming. From below, larger animals cannot see the penguin's white underside. It looks the same as the bright sky or ice. And from above, other animals cannot see the penguin's black back against the dark ocean floor. The penguins' colors protect them in nature, but scientists have found that some of these physical details also have an effect on humans. These scientists study visual signaling. The way an animal looks sends a message to other animals and to people. Some of these visual signals make animals seem cute to people. If something is cute, it is beautiful in a special way. Cuteness is a special kind of beauty that makes people happy. Some physical characteristics that people think are cute are big round ears and arms and legs that seem weak. Scientists call these physical details cute cues. Cute cues are those things that make something look young, weak, harmless or needy. Scientists say that humans react to these cues. Humans have a desire to care for things that look and act similar to babies. People often find babies to be very cute.  Spotlight producer Joshua Leo has a baby daughter. He describes why she is so cute. My baby has a very round head. Her head is still very big compared to her body.  She has smooth skin and soft hair. My baby daughter does not have much control over her body. She cannot yet move her arms and legs very well. Scientists believe that humans are very sensitive to things that are cute. Humans react to anything that looks similar to a human baby. Humans even react to objects that may look like parts of a baby. Humans react to the soft hair on a baby bird, the movement of a round balloon, a small round car, or even a large round rock on top of a smaller rock. The more cute cues that an animal or object has, the more people may like it. Researchers are still learning about the science of cuteness. Recent studies show that cute images affect the brain in a special way. Cute images make the brain react in a similar way to a good meal or some drugs. Cute things make us feel happy. Cute images have a lot of power. A study done at the University of Michigan in the United States showed this to be true. The study tested young people's reactions to images. It found that young people believed messages more if the message was joined by a cute picture. The researchers showed the young people two messages. One was a simple anti-smoking message. The other showed a cute animal telling them that smoking was bad. Then the researchers tested the young people's reactions. The young people trusted the cute messages more than the simple message. Experts say that every human on the planet is made to react to cute images. But some cultures react to cuteness more than others. They say this is similar to the love of sugar. Everyone is able to taste sweet things. But some people and some countries eat more sweet foods than other people. For example, many people in the country of Japan like cute things very much. In Japan, cute things are called kawaii. Images of people and animals with big heads and big eyes are on many things. Children love kawaii animals. But these cute things are not only for children. Many Japanese men and women also like kawaii. Cuteness attracts people. People want to hold and care for cute things. God made humans in a special way. He made us to naturally react to cute things. People are made to protect the helpless things in life, such as small babies. When people see something cute, they want to care for it. God gave people this reaction. This way, we remember to take good care of things that cannot care for themselves. The writer of this program was Joshua Leo. The producer was Rina Dam. The voices you heard were from the United States and the United Kingdom. All quotes were adapted for this program and voiced by Spotlight. You can listen to this program again and read it on the internet at www.radioenglish.net. This program is called The Science of Being Cute. You can also leave your comments on our website or you can email us at radio at radioenglish.net. You can also find us on Facebook. Just search for Spotlight Radio. We hope you can join us again for the next Spotlight program. Goodbye!


Hey guys, welcome back to yet another GCSE lesson now guys I'm super excited to say that myself and Aliyah from light up hub have decided to team up to help you guys prepare for your Upcoming mocks at the end of the February half-term. So guys, we're gonna be kicking off our collab by going over The three mistakes that all GCSE students make in their creative writing and how you can avoid them So Aliyah start us off with the first mistake that all students tend to make in their creative writing Yes, let's absolutely start with it. So let's first of all look at No ambitious vocab now. This is a massive mistake students make during their creative writing They don't really further their vocab. They're not looking at expanding their ideas and using that ambitious vocabulary So rather than saying something is cold think about it How can we up level that how can we add in a layer different techniques to make sure that our vocabulary? particularly the fact you're martin if you're 24 marks a Massive part of your exam making sure you up level it. So Barbara tell us how can they up level their vocabulary? How you can improve your ambitious vocabulary is firstly of course use ambitious vocabulary in your writing and Specifically make sure you try to commit to memory at least 10 really powerful Ambitious words. I'm gonna start you off with at least three that you can use in any creative writing story And you'll instantly see the quality of your writing increases number one gilded This is a really powerful ambitious word that you could use especially to set the scene and using it as part of pathetic fallacy Gilded simply means golden so you can talk about for example the gilded Sun number two Iridescent which means beautiful colors that shimmer and move with movement for example The iridescent ocean which is swishing and swaying under the sunlight and number three Festooned which is one of my favorite ambitious words for those of you that are studying Lord of the Flies You'll find that William Golden uses it a lot. Okay festoon just simply means Decorated so for example, you could talk about the balloons that are festooning a wall for instance in a birthday party So Nia, what's the second mistake that all GCSE students make in their creative writing? Okay, so second mistake is a lack of sensory language Now sensory language is so important to set the scene for us to understand especially if you're doing it for a first-person Narrative perspective to understand how they're feeling What are they seeing what they spending to really immerse the reader the examinal the teacher whoever is marking your work? Immerse them in it You want to paint a picture so when you're reading a book or even when you're watching a film? Why do you feel so involved? Why do you feel so invested because everything is painted out for you? You almost feel like you can smell you feel like you can see what they conceal what the character can see and that is what builds a good Narrative or a good creative writing story So but what kind of things can they put in to make sure they are ticking off? Sensory language and they're not avoiding it. Okay, so five Techniques that you could use which include all five senses are Firstly, for example, if you're describing what you can see you can talk about for example The misty city or even the misty clouds for instance, then number two when you're thinking about feel, right? The word numbing is really powerful sensory language number three a barret for instance Describing something that refers to this the sensory language of taste number four Bellowing this is really really powerful sensory language relating to what you can hear and number five and this relates to what you can smell Pungent okay, so anything that's pungent is really disgusting really smelly and so on okay now Leah was the third technique that or rather the third mistake that students make in the creative writing Okay, so the third mistake is poor structure Now I cannot emphasize enough the amount of students who have no structure going into their creative writing They're just writing maybe they're describing something they're trying to put in a bit of a narrative But there is no set structure So it is so important to pre-learn a structure or have something in place You know when you go into that creative writing exam You've got something that you can follow because again in terms of the mark scheme the examiner is looking 16 marks for your actual the way that you're writing not just the words that you're putting in but the way that you structure it your Sentences your paragraph lengths is there a cyclical structure? So does it start to the end in the same way all of these different structural techniques are so so so important for you to Boost your creative writing and also they're not hard to do you can pre-learn it the things that Barbara is about to Go through you you can pre-learn and then just put your ideas into it and done you can tick off structure How can we make sure that we don't have a poor structure? It's so easy to solve this mistake Just simply use the story mountain structure when I mention story mountain I'm literally referring to something as basic and as easy as a five paragraph structure We start off with your beginning paragraph you establish a setting you establish the scene then in your build up This is where you introduce a character who's going on some form of adventure It doesn't have to be a dramatic adventure Okay, it can literally be then simply waking up going and opening the door before you get to the problem paragraph Which is where maybe they see something really crazy to meet the villain whatever then in your fourth paragraph as you're going down The story mountain you resolve they somehow resolve this issue again As I said you can have a dramatic story or it can simply be a case of them slamming the door shut right? That's also counts as a resolution before you end your story with either a cliffhanger or some kind of interesting ending Remember when you use in this story mountain framework number one Make sure you keep these paragraphs distinct to show you a teacher and your examiner that you are developing a really robust Structure right a really nice and easy to follow story, but also try and avoid things like cliche endings Just try and generally avoid cliches. Okay, so that's really it when it comes to creative writing This is the common mistakes that a lot of GCSE students make in the creative writing and of course hopefully guys as you can see Also the solutions that you could take in order to avoid that and see some amazing marks When you're doing your final round of GCSE marks and of course ultimately you're preparing for your final GCSE exams But thank you so much Leah for joining and guys don't forget over on Leah's channel on YouTube We will be doing a Macbeth collapse for those of you guys who are studying with bet and are desperate to know How you can effectively revise for it and the key context points, etc That you need to know make sure you now head over to light up tutoring for that video. Thanks so much guys for listening Number three a borat for instance describing something that It's like it's like disgusting like taste or yeah, I'm gonna see something That's gonna read you know you're gone. It just occurred to me that you're studying in front of this