Hey guys, today I want to show you a few things about almond milk, specifically store-bought almond milk that I think that the producers of it don't want you to see. And full disclosure, part of me is pretty aggravated with what I found. We've been buying store-bought almond milk every week for like the last six years. And the other part of me is actually feeling pretty good about what I know now. I think you'll see what I mean in a minute. First of all, store-bought almond milk is so expensive for what's actually in it and the numbers are staggering because we're all led to believe that almonds are really expensive and they are. They're not cheap. The non-fancy, non-organic, non-raw, they're usually around 10 bucks a pound. So how many dollars worth of almonds are you getting in these cartons? It depends on the brand of almond milk. This one from Trader Joe's has about a dollar and 25 cents worth of almonds. And this very popular brand, Almond Breeze, has even less. Under a dollar worth of almonds, 93 cents. And when you buy a carton of these, the one on the left is usually around $2.99. That's a 2.4x markup and the one on the right, Almond Breeze, I just picked up Minnesota, not a remote island or New York City or San Francisco, $4.69. Or even worse, a 5x markup. So what's actually in these almond milks? Well, there's a few almonds. For every eight ounce serving of this almond beverage on the left, there are generously eight almonds. And for both of these Almond Breeze brand almond milks, generously six almonds. In Almond Breeze original, there's seven grams of sugar and then a bunch of ingredients to get it to look and feel like thick, luscious, creamy almond milk, sunflower lectin and other binders to get it to stick together and to thicken it. There's some preservatives for sure. And then there's the additives that help the guys that sell this stuff. Tell the story, they want to tell our almond milk has almost doubled the amount of calcium is cow's milk fortified with vitamin D vitamin E. Here's the other weird thing about store bought almond milk. There's a lot of mysteries. How did they get it to exactly 30 calories? Where's all that sodium coming from? I mean like 1500 times the amount of sodium that's in just almonds. These guys, they don't want you to know what real almond milk tastes like. Tastes like almonds. It's decadent. You put it in your coffee and your coffee is going to taste like you added creamer to it. And the guys behind these almond milks do not want you to know that making your own almond milk is really easy. You might think as I did, well, almonds are brown and water is clear. So how the heck do you make white almond milk? Well, all you have to do is blend up some almonds and water and you get almond milk. Any blender will do people. You can add dates to make it sweet. You can add some cocoa to make a chocolate almond milk. It's literally the easiest thing ever. And if you want to strain it, get rid of some of that dietary fiber, make it more of a smooth consistency. That's pretty easy too. Guys, go easy on yourselves. This is probably still going to be a transition for us to phase out store bought almond milk. And guys, subscribe to our channel if you haven't already hit that bell to get notified. If you appreciate videos like this, hit that thumbs up. Thank you so much for watching and we will see you in the next one.


Hello, my name is Miguel Arnaeth and this is the Intef course on digitally competent educational organizations. I'm going to talk about the impact of technology on the curriculum, the objectives and the contents from an organizational point of view. An actual implementation of technologies in the educational context involves the overall reinterpretation of the curriculum within the organization. But what does that mean, though? It means that we have to rethink all the components of the teaching and learning experience in schools from the perspective of the current social and technological situation. In general, this means shaping a more inclusive curriculum. We have to think of how the decisions we make curriculum wise impact on our school's educational project. The name differs depending on the legislation and whether this is cross and transdisciplinary. The curriculum should ensure that the learning and assessment experience focuses on student needs and skills and exploits the multimodal reality we live in when addressing the contents. This way of understanding the curriculum entails more flexibility of the basic parameters of a school organization. Time, spaces and schedules should be adapted in order to have some margin to include other activities or collaborate among the different subjects. Topics and competencies that should be developed. Furthermore, even if this option is not as well provided for as it should be in our education system, we shouldn't rule out the possibility of offering completely online options that would allow flexible access to basic compulsory education to certain groups with specific needs. Redesigning the curriculum using technology implies creating teaching and learning experiences that exploit the potential of expanded teaching. This can make teaching and learning experiences much more authentic. Broaden the context and make the participants, students and teachers feel more engaged precisely because of the authenticity of the experience. When redesigning the curriculum according to the current technology situation, we should clearly have in mind the image of digitally competent students. Digitally competent students are capable of efficiently facing the world we live in with all the particular features that it has due to technology. Also, they have to take advantage of the possibilities that technology offers in order to enrich their learning process. So far, we have been teaching about the curriculum in generic terms. From now on though, we will address two specific key elements of the curriculum, objectives and contents. Let's talk about the objectives first. In a digitally competent organization, learning objectives should be defined focusing on competencies in the most comprehensive, social and contextualized sense of the concept. The goal is not to create students able to echo contents, but rather to educate individuals that will be able to make informed and ethically and technically desirable decisions in complex situations. Thus, digitally competent schools focus on this approach on competent individuals when they organize teaching and learning experiences. There is another key element that we have to focus on in our digitally competent educational organization, contents. Contents encompass all the educational resources that we use to support our teaching efforts with an emphasis on digital contents. In the current technological situation, it is imperative to remember that the development of technology allows students to become creators of content. They have become what we used to call at the beginning of the 80s, prosumers. That is, not only do they consume contents that others create, but they also create contents setting the reality they live in. In fact, how to make the most of the contents we create within the institution is one of the greatest challenges that we current educational organizations face. Furthermore, our institutions should take advantage of the contents that have already been classified and stored and are available online. The goal is to be able to efficiently turn to online information repositories because we can surely find contents of great quality there. When we talk about digital contents, we shouldn't only think of visual presentations, teaching units, revised class notes and materials. There are plenty of those, but we should also think of collections of learning materials, resource lists, software and application updates. All of them have already been classified and we have them at our disposal. Therefore, there is no need to keep reinventing the wheel. We can simply improve the already existing contents, remixing them or changing them with our input and revisions. When we create contents, we have to be aware that there are ways of allowing others to use them under specific conditions. This implies knowing and properly using the licenses for the reuse of information that are available to us for both giving others permission to use our contents and using other people's contents adequately. We should prioritize the creation and use of open educational resources and generate a climate of respect for intellectual property based on an open approach on producing and using knowledge. It is not a question of placing a special emphasis on what is legal and what is not, but rather on learning basic rules of coexistence in terms of creating contents and using other people's materials. It is important to be aware of the options we have. On one hand, we can control and use what other people make of our content when we share them. And on the other hand, we have the opportunity to be respectful with the decision that other people made with respect to the use of their contents. And how can we achieve this? It is imperative to have a shared vision and a strong leadership in order to establish an approach on the curriculum and to make organizational decisions. Furthermore, reaching an agreement between all the members of the school is also required in order to move forward. Thus, one of the first steps we should take is to open an in-depth dialogue to help us make real changes that will go beyond just renaming concepts, like for instance, objectives or goal, subjects or subject areas, etc. The organization has to put together some procedures and a certain dynamic related to the use and creation of digital contents, preferably open ones. This includes, for instance, creating specific spaces to exhibit them in the institution itself, promoting, using and sharing these contents within the school and outside, and promoting the contents outside the institution. The contents created in school should be acknowledged, not only the physical ones which we traditional exhibit on walls, but also the new multimodal ones which we make in schools with the help of technology. These contents need a place of their own where we can display them. In addition to promoting the contents we create within our school, it is also important to promote resources that others have shared. It would be wonderful if an organization could have access to an institutional content exchange program or to a larger public repository, or even if it could create its own repository. These types of actions could help the promotion of digital contents and open educational resources.


Hey, thanks, Tony. First of all, I want to congratulate the Haskeek team for organizing such a cool event. It has been very streamless, streamlines, sorry. And the talks have been really, really interesting today. I hope you guys are caffeinated after the evening tea to have another session. So to give a brief intro about myself, my name is Aditya Patel. I'm part of the data science team at Stasis. Stasis is a health care startup company working in continuous vitals monitoring space. And what we are here is basically we're trying to develop ML systems to detect patient deterioration. Previously, in my past, I've been part of research groups at Tata. And before that, I've been part of Metronik, which is one of the biggest medical device companies in the world. Today, I want to talk about time series classification. Now, traditionally, time series classification in neural nets is associated with LSTMs. But in this talk, I want to shed some light on different architectures, which can be used when you're working on this time series classification in real time settings. To give a brief outline of my talk, I want to start out with giving the context of the problem, why we started working on this problem, and what caused it, and what caused us to actually start working on this, then move on to actually explain one of the most frequently used algorithm, its advantages and disadvantages, and then move on to talk about our methodology and in the end, we also want to talk about some other noteworthy methodologies and takeaways. Sorry. So time series data. Time series data is ubiquitous, from IoT devices to self-driving car. It affects all our lives in ways we can't even imagine. And when you're working on IoT devices, as anybody who's working in IoT devices would tell you that the expectation is very different than reality. Now, at Stasis, we have five different vitals which you are measuring. We have blood pressure, heart rate, blood oxygen, restoration, and temperature from four different probes. And for us as well, our expectation was very different than reality. In reality, what we got was a data which was really noisy because of the patient movements. And there was a lot of missing data as well, because not all the time patients wear all the sensors. So building a predictive model on top of it was really, really challenging. So given the importance of time series classification, machine learning domain has a lot of research being done in the past few decades regarding it. We have the similarity measure approach where you apply dynamic time warping to actually align your time series and then apply supervised classification on top of it to do time series classification. But with this technique, what happens is because of the dynamic time warping, the time complexity is really high, which actually causes it incapable to actually work in real time. There have been methods to actually improve the dynamic time warping methodology, but in general, it's really, really slow. From the statistical part, we have the ARIMA modeling, where you actually exploit the auto-regressive nature of your time series, and based on that, you try to predict the sequence. But with this, the assumption is basically that there is linearity in your past which causes it to actually predict the future correctly. But with physiological vital science, the data is actually really non-stationary. Thus, ARIMA modeling wasn't working well for us. And with the advent of deep learning, we have recurrent neural nets. And in the past few years, there have been an influx of papers working on time series classification using recurrent neural nets. You would see recurrent neural nets employed everywhere in time series, from music generation to machine translation to speech recognition. And rightly so, recurrent neural nets are sequence models where you actually exploit the sequential nature of time series. You have your hidden vector, which is actually propagated through time. And the intuitive appeal of a recurrent neural net is essentially the hidden activation vector is actually the representation of the entire time series seen so far. But when we applied it to physiological vital science data, we didn't get as good results as we expected out to be. On the left, or on your right, you can see an autoencoder experiment where we actually tried classifying two different classes of patient deterioration. One class was stable patient and the other class was unstable patient. And the feature representation wasn't working well for us. And when we started digging into it, what we saw was the noisy data and the missing data was actually causing the representation to not come out correctly. The other two disadvantages which we saw in the LSTM architecture was, basically because of the recurrence nature of the LSTM networks, it's really, really slow to train. It takes a lot of time to actually train your network and iterate over it. And the other thing which we saw was because of the data limitation, it's not able to generalize well. So given the disadvantages, we started looking more into other methods. And one method which really spoke to us was convolutional networks. Now convolutional, so our hypothesis was that the convolution layer and the dropout layer will actually be able to mitigate the negative effects of noisy data and missing data.  To experiment with this architecture, we decided to take the label as patients mortality to as an output label. So our experimental setting was pretty standard. We actually had a very basic convolution architecture. We had the convolution layer. Then to introduce non-linearity, we had the relu. And for regularization, we had the dropout. And for classifying, we had the softmax. To give a brief summary of our training data, we basically worked on a data set which is open source by MIT called MIMIC. If anybody, at this point I would say if anybody's working on healthcare data, they should definitely look into MIMIC data. It's a really, really good baseline for working on healthcare data. Moving on, so basically what we were working on was these physical logical vital signs such as blood pressure, temperature, heart rate, and SPO2. And what we were trying to predict was basically can we predict about patient mortality in the next hour? And what we saw was pretty interesting. The recurrent neural nets performed reasonably well. The AUC, it was 80% in this. But what was really interesting for us was basically the CNN had an AUC of 87%. And it was working really, really well when we had noisy data and missing data as well. The other interesting thing was basically because of the parallel processing, the training time was really less. It was actually one fourth of the time which was taken in LSTM. To give more information on this, we also worked on trying to create a baseline using handheld features. So we actually did feature engineering and then applied your traditional supervised algorithm such as logistic regression, densely MLPs. But you can get more information on the paper. But in this, we just wanted to concentrate on the CNN and LSTM. So what we saw was basically the CNN was much better in performance, was much faster, and was robust against missing noise as well. Also, I would say at this point, if somebody wants to check out some more papers on convolutional networks, they should definitely check out Google's FaveNet paper. They have been using convolutional networks to actually generate raw audio signals. And last month, there was a paper by Facebook which actually did natural language processing using convolutional network. They're calling it convolutional sequences. If you were actually in the talk given by Arnold, he also talked about sentiment, sarcasm detection using convolutional networks, which was pretty interesting to me. So given the success of convolutional networks, we started looking into more and different kind of generic convolutional networks. And what we wanted to test out was the representational power of these networks. And one paper which really spoke to us was this paper proposed by our group from CMU, and they named this architecture temporal convolutional networks. Now temporal convolutional networks have three characteristics. The first characteristic is that the convolution is actually causal in nature, that there is no future leakage in the convolution process. So for example, if you have a kernel of size three and you are at actually applying convolution at time t equals to two, your convolution would be limited till w1x1 and w2x0, because you cannot actually access the future values. The second characteristic which they introduced was actually what they called something called dilation, where you actually have an adjacent step between two filter tabs. So if you have a dilation size of one, you actually have your normal convolution. And as you increase your dilation size, your adjacent distance between the two elements in the convolution starts increasing. And what it does actually, it starts increasing the receptive field of the convolution, which actually entails the increase in the representation as well. And third was basically they encompassed this entire dilated causal convolution into a residual block. And the reason behind they putting up in a, they encompassing it in a residual block was basically to actually go deeper. Since if you have a residual block, it actually takes care of some of the issues when you're going deeper, such as vanishing and exploding gradient reduces, because you're actually solving, because when you're solving for an identity matrix, it's much easier to solve. In our case, since we weren't actually going deeper, like we weren't having more than four or five layers, the residual block was actually not needed for us, but to have a generic analysis, we actually placed it in our analysis as well. And a one cross one convolution is usually needed when your input size is equal to output size, but in our case, since we were doing classification, the one cross one convolution was also not needed. So in this scenario, we actually moved ahead from an open source dataset to the dataset which we collected at Stasis. And we went one step further in to actually go from a binary classifier to a multi-class classifier. And what we ended up doing was basically we had three classes, one class for patients who are stable, and two classes for patients with a different severity of the patient's health. So there were three categories, one for stable patient, one for mediumly risky patients, and one which actually needed immediate attention in the future. Our input was pretty standard. We actually were taking two hours of data to predict in the next 20 to 25 minutes. And our sampling rate was every five minutes. So we had 150 in our input matrix. And the results were as follows. Our one DCNN still outperformed the DCN network, not by much, but both the networks which were based on convolutional networks outperformed the RNN. When I'm talking about RNN here, I'm mostly talking about LSTM networks because that's the one which actually gave us the best results between all the different architectures. But the other interesting thing which we saw was basically the temporal convolutional networks for the highest risk of patients was 91%, which was really interesting to us because these are the patients which actually require immediate help. These are the patients which if you can identify them will reduce the burden on nurses to actually get them immediate help and cause and actually save lives. So what we ended up doing was actually combining our temporal network and one DCNN into an ensemble model which would give us the robustness and the precision which was required in the R case. Sorry. So this is a retrospective data analysis of a real patient. And what you can see is basically there is a lot of missing data. The patient is actually not wearing a BP cuff and there is also variability and respiration and temperature. And the ensemble model of one DCNN or a TCN was actually able to predict well ahead of time that the patient is gonna deteriorate. And the time period and the deterioration is significant enough that it would actually entail a nurse alert and a nurse visit or a clinician visit. So this system is currently in beta program in multiple hospitals in Bangalore and so far we have received good feedback from the clinicians. Moving on, I also want to talk about some other techniques which people should be looking into when they're working on time series classification. We have something called bag of words approach. It's a pretty simple approach in which you essentially what you do is you quantize your time series into different bins and then you assign a character for each bin. So what you actually get is a time series converted into a character array. And using this character array, you can actually apply any supervised technique to do the classification. For the same multi-class classification task, this simplistic technique, it's also called piecewise aggregation, gave us the best results when we use this with a gradient boosting with a F1 score of 74%, which is really close to the LSTM network, which is much more complicated and much more harder to explain as well. And you can also apply other techniques as well. There is something called converting your time series into images and how you are actually converting your time series into images is essentially, if you think about your time series, it's actually into in Cartesian coordinates. And what you can do is you can convert your time series from Cartesian to polar coordinates. And then what you can do is essentially take each point's interaction with every other point. And what it gives you is from a time series of time sequence N, an image of N cross N. There are various ways of doing it. There's something called Gramian matrices, which actually takes the summation and the differential between each and every point and gives you these images. And then you can actually take them as input channels for your convolutional network to classify our time series. In our case, we had five different time series at any given point of time. Thus, stacking them all together was not giving us a valid performance increase. So for us, the most simplistic one was actually applying GADF with CNN, which actually outperformed the LSTM again. Takeaways. So machine learning is an exciting field. There is recent research coming up every day, every day of the week. And as machine learning practitioners, we actually want to apply those techniques everywhere. Like whenever a new algorithm comes, I actually want to apply it on the problem which I'm working on. But at this point of time, I want to give a word of caution. I want to actually reiterate that everybody should think about what problem they are trying to solve. Like for us, the biggest problem or the biggest hurdle was actually the noisy data issue, which was solved by convolution. Thus, working on convolutional networks made sense to us. At this point of time, I also want to say that this entire presentation was to understand the representational power of each and every network in the most generic sense. There has been recent advances in recurrent neural nets, which actually negates some of the drawbacks I mentioned. There is something called attention mechanism. I think there is a talk in Audi 2 about it, which actually rectifies some of these techniques, some of these drawbacks which I talked about. And in the end, I also want to talk about the need for working on one DCNN as a starting point when you're working on real-time settings. As shown in the presentation, it's actually a pretty robust starting point if you're working on a real-time setting. Future work, we are actually working on understanding what's causing these activations in a time series sequence. So we want to understand what's causing our patient to deteriorate. For that, we are actually working on deconvolution networks. And hopefully, we'll get some validation from clinicians on that as well. Happy to take any questions or comments. Yeah, so I saw that you converted the time series into a sequence of characters, right? So that is sort of a discretization of the continuous waveform, right? Yeah, exactly. So that is some amount of information loss out there. Sorry? There will be some amount of information lost out there, right? So does it, and what are the kinds of techniques that you apply on the top of it because that's a lot of information loss out happening out there? Because I've tried it out a couple of years back and didn't work out very well for me. So what is the kind of things that you've tried out? Good question. So when I talked about piecewise aggregation, we were also, so I was also trying to point out the simplicity of the techniques and it can be used as a base model. Like you mentioned, it is basically you are quantizing your time series into different bins. So you're actually using a lot of coherence between your point. And that's why convolutional networks works better than this. Because in this, you have a linear quantization metric. Whereas when you are applying convolution locally, it's actually giving you a non-linear convolution, non-linear quantization, which actually gives you better results. So these are my contact details. Yeah, so for a patient, for a patient to be... I can't, Arjun. I can't place. Okay, sorry, thanks. So for a patient to be diagnosed correctly. So for how long should we see his observations? Like this technique works for, let's say, half an hour of historic data set or it can be month long or it can be... Okay, so for in our case, we are actually looking for something on the order of half an hour to 40 minutes because that's the time which is required by our clinicians to actually administer medicine to actually take effect. If we actually do it any sooner, the clinicians would wait for some time before they administer something because they want to validate it completely. And what's your opinion about applying these techniques for a large scale? I mean, for a higher duration of time, let's say we take one year of data and try to figure out what's going wrong with the person. Is it applicable or it doesn't work well? So there is a paper on palliative care by Anand Devati. He actually worked on, he actually took 10 years of data and he was trying to see if in the next year a patient is gonna pass away or not. And what he was working on was essentially the point where you should stop trying to improve the patient's care and actually start administrating care for comfort. So his task was basically in a 10 year long, he also used something very similar. I think he used an LSTM network in that case to actually take a 10 years time stream. In our case, we want to be more immediate because we want to actually employ it for patients who are actually in the hospital after a surgery or before a surgery is what we are trying to look for. So for us, two to four is good enough, two to four hours. Thank you. Thank you. I have two questions. One, when you applied the one dimensional CNN, so in addition to looking at the model performance and prediction accuracy, precision, et cetera, did you also look at interpretability in? Yeah, so that's what we are currently working on. So we are trying to understand how to interpret this.  So you can understand what's happening. The other way is to work backward using, if you were in Dr. Vinit's talk, he used something called Gradcam where you can actually backprop the activations and actually see it. So those are some of the things even we are working on right now is the interpretability and the explainability because that's what's important as well. Like if something is getting activated, why it's activated and why that is related to patient deterioration. So that is also something which we are working on actively right now. Okay, and I have one more question. The one that you mentioned about converting the data into binning the data, then treating each bin as a character and then using FUNLP techniques. Have you come across using LDA or anything like that with this data one? So we haven't done LDA on it. I'll be honest. We tried taking the representation and seeing if actually something like a PCA or something like a PCA can actually make the representation better. The piecewise aggregation we didn't apply it on, we were mostly focusing on the one which was best performing for us, which was one DCNN. In that we were able to see different bunch of clusters as well. Okay, yeah. And one last question. Did you look at any anomalies in the data while when you use this methods and did you have any observations on that? Anomalous patterns. So there are anomalies patterns always and that's why the results is not perfect. As you can see, it's still, if you check out our results, even the best one is 83, 84%. So it's still not like up to the best one. And this is also when we are limiting some of the constraints here. For example, like you need to have an X percentage of data available for us to make a prediction. I think if we can improve our signal quality, remove some of the, sorry, I just want to show you something. So if we can remove some of those noisy data issues which are actually happening because a patient is moving and we can actually include that in our model or if we can detect patient movement and include that in our model, definitely our accuracy is gonna improve. Hello. Yeah, if you wanna include some, let's say external variables, like in Arima you call them exogenous variables. For example, past patient information, his gender, these kind of things. How can you include this in this model? So one of the ways is basically if you can get the last layer of your CNN and club them with all the exogenous elements which you spoke about and then feed it into a classifier, it will obviously give us better accuracy. In this, we even shied away from using the demographic information, such as age, sex and other patient information like patient nodes, because what we are trying to build right now is we want to make it as real-time as possible. And when you're working on an IoT device because that kind of information is actually gonna come from another server, it's very hard. So we are trying to shy away from that and trying to understand how much we can leverage what we have right now to make it as real-time as possible. Got it. So within a short span of time, it adapts to the whatever is the context. Exactly. Yeah. Okay. Yeah. Feel free to reach me at the thirdstaceslabs.com. Would love to chat if anybody has any questions offline. Thank you.


Live from Boston, Massachusetts, it's theCUBE. Covering IBM Chief Data Officer Summit. Brought to you by IBM. Welcome back to theCUBE's live coverage of IBM's Chief Data Strategy Summit. I'm your host, Rebecca Knight, along with my co-host, Dave Vellante. We have a big panel today. These are our social influencers. Starting at the top, we have Christopher Penn, VP, Marketing of Shift Communications. Then Tripp Braden, Executive Coach and Growth Strategist at Strategic Performance Partners. Mike Tamir, Chief Data Science Officer at TACT. Bob Hayes, President of Business over Broadway. Thanks so much for joining us. Thank you. So we're talking about data as a way to engage customers, a way to engage employees. What business functions would you say stand to benefit the most from using data? I think a lot of that. I don't know if it's the biggest function, but I think the customer experience and customer success, how do you use data to help predict what customers will do and how do you then use that information to kind of personalize that experience for them and drive up recommendations, retention, upselling, things like that? So it's really the customer experience that you're focusing on. Yes, and I just released a study. I found that analytical leading companies tend to use analytics to understand their customers more than say analytical laggards. So those kind of companies who can actually get value from data, they focus their efforts around improving customer loyalty and just gaining a deeper understanding about their customers. Chris, do you want to jump in here? I was just going to say, as many of us said, we have three things we really care about as business people, right? We want to save money, save time, or make money. And so any function that meets those qualifications is a functional benefit from data. I think there's also another interesting dimension to this. When you start to look at the leadership team in the company, now having the ability to anticipate the future. I mean, now this, we are no longer just looking at static data, but we are now looking at anticipatory capability and seeing around corners so that the person comes to the team, they're bringing something completely different than the team has had in the past. This whole competency of being able to anticipate the future and then take from that where you take your organization in the future. So follow up on that. Does data now finally trump gut feel? You remember the HBR article of 10, 15 years ago? Can't beat gut feel, is that? Are we in a new era now? Well, I think we're moving into an era where you have both. I think it's no longer neither or. If you have intuition or we have data, now we have both. The organizations who can leverage both at the same time and develop that capability and earn the trust of the other members by doing that. I see the Chief Data Officer really being a catalyst for organizational change. So Dr. Tim, I wonder if I could ask you a question. Maybe the whole panel, but so we've all followed the big data trend and the meme. AI, deep learning, machine learning, same wine, new bottle, or is there something substantive behind it? So sir, our capabilities are growing, our capabilities in machine learning and I think that's part of why now there's this new branding of AI. AI is not what your mother might have thought. AI is it's not robots and xylons and that sort of thing that are going to be able to think intelligently. They just did intelligence tests on the different Siri and Alexa quote, AI is from different companies and they scored horribly. They scored worse than much worse than my very intelligent seven year old. And that's not a comment on the deficiencies in Alexa or in Siri, it's a comment on these are not actually artificial intelligences. These are just tools that apply machine learning strategically. So you are all thinking about data and how it is going to change the future and one of the things you said, Tripp, is that we can now see the future. Talk to me about some of the most exciting things that you're seeing that companies do that are anticipating what customers want. Okay, so for example, in the customer success space, a lot of SaaS businesses have a monthly subscription so they're very worried about customer churn. So companies are now leveraging all the user behavior to understand which customers are likely to leave next month. And if they know that, they can reach out to them with maybe some retention campaigns or even use that data to find out who's most likely to buy more from you in the next month and then market to those in an effective way. So don't just do a blast for everybody, focus on particular customers, their needs and try to service them or market to them in a way that resonates with them that increases retention, upselling and recommendations. So they've already seen certain behaviors that show a customer is maybe not going to react. Exactly, so you just, you throw this data into machine learning, right? You find the predictors of your outcome that interest you and then using that information, you say, oh, maybe predictors A, B and C are the ones that actually drive loyalty behaviors. Then you can use that information to segment your customers and market to them appropriately. It's pretty cool stuff. February 18th, 2018. So we did a study recently just for fun of when people search for the term outlook out of office. Yeah, and you really only search for that term for one reason, you're going on vacation and you want to figure out how to turn the feature on. So we did a five-year data poll of people of the search volume for that and then inverted it. So when do people search least for that term? That's when they're in the office. And it's the week of February 18th, 2018 will be that time when people like, yeah, I'm at the office, I gotta work. And knowing that the prediction and data give us specificity. Like, yeah, we know the first quarter is busy. We know between Memorial Day and Labor Day is not as busy in the B2B world. But as a marketer, we need specificity. Data and predictive analytics gives us specificity. We know what week to send our email campaigns, what week to turn our ad budgets all the way to full and so on and so forth. If someone's looking for the cue, when will they be doing that going forward? That's the power of this stuff is that specificity. They know what we're going to search for before we search for it. I'd like to know where I'm going to be next week. Why that date? That's the date that people least search for the term outlook out of office. Okay, so they're not looking for that feature, which logically means they're in the office. They're on vacation. All right, I'm just saying. That brings up a good point on not just what you're predicting for interactions right now, but also anticipating the trends. So Bob brought up a good point about figuring out when people are churning. There's a flip side of that, which is how do you get your customers to be more engaged? And now we have really an explosion in enforcement learning in particular, which is a tool for figuring out not just how to interact with you right now as a one-off statically, but how do I interact with you over time this week, next week, the week after that? And using reinforcement learning, you can actually do that. This is the sort of technique that they used to beat AlphaGo, or to beat humans with AlphaGo. Machine learning algorithms, supervised learning works well when you get that immediate feedback. But if you're playing a game, you don't get that feedback that you're going to win 300 turns from now right now. You have to create more advanced value functions in ways of anticipating where things are going. This move, so that you see that you're on track for winning, and 20, 30, 40 moves down the road. And it's the same thing when you're dealing with customer engagement. You want to, you can make a decision, I'm going to give this customer a coupon that's going to make them spend 50 cents more today, or you can make decisions algorithmically that are going to give them a 50 cent discount this week, next week, the week after that, that are going to make them become a coffee drinker for life, or customer for life. It's about finding those customers for life. IBM uses the term cognitive business. We go to these conferences. Everybody talks about digital transformation. At the end of the day, it's all about how you use data. So my question is, if you think about the bell curve of organizations that you work with, how do they, you know, what's the shape of that curve? Part one, and then part two is, where do you see IBM on that curve? Well, I think a lot of my clients make a living predicting the future of their insurance companies, their financial services. That's where the CDO currently resides. And they get a lot of benefit. But one of the things we're all talking about, but talking around is that human element. So now how do we take the human element and incorporate this into the structure of how we make our decisions? And how do we take this information? And how do we learn to trust that? The one thing I hear from most of the executives I talk to when they talk about how data is being used in their organizations is the lack of trust. Now, when you have that, and you start to look at the trends that we're dealing with, and we call them data points versus calling them people, now you'll have a problem because people become very, almost analytically challenged, right? So how do we get people to start saying, okay, let's look at this from the point of view of, it's not a neither or solution in the world we live in today. Cognitive organizations are not gonna happen tomorrow morning. Even the most progressive organizations are probably five years away from really deploying them completely. But the organizations who take a little bit of an edge, a five, 10% edge out of there, they now have a really a different advantage in their markets. And that's what we're talking about. Hyper critical thinking skills. I mean, when you start to say, how do I think like Warren Buffett? How do I start to look and make these kinds of decisions analytically? How do I recreate an artificial intelligence or machine learning practice and program that's going to solve that solution for people? And that's where I think organizations that are forward leaning now are looking and saying, how do I get my people to use these capabilities and ultimately trust the data that they're told? So I forget who said it, but it was early on in the big data movement. Somebody said that we're further away from a single version of the truth than ever. And it's just going to get worse. So as a data scientist, what say you? Not familiar with the truth quote, but I think it's very relevant, very relevant to where we are today with, there's almost an arms race of, you hear all the time about automating, putting out fake news, putting out misinformation and how that can be done using all the technology that we have our disposals for dispersing that information. The only way that that's going to get solved is also with algorithmic solutions, with creating algorithms that are going to be able to detect, is this news? Is this something that is trying to attack my emotions and convince me just based on fear? Or is this an article that's trying to present actual facts to me? And you can do that with machine learning algorithms. Now we have the technology to do that algorithmically. Better algos than like and share. From a technological perspective to your question about where IBM is, IBM has a ton of stuff that's called AI as a service essentially where if you're a developer on Bloomix, for example, you can plug into the different components of Watson at literally pennies per usage to say I want to do sentiment analysis, I want to do tone analysis, I want personality insights about this piece of who wrote this piece of content. And to Dr. Tamir's point, this is stuff that we need these tools to do things like fingerprint this piece of text did the supposed author actually write this? You can tell that. So of all of the four magi we call it, the Microsoft, Amazon, Google, IBM, getting on board and adding that five or 10% edge that Tripp was talking about is easiest with IBM Bloomix. Great. Well, one of the other parts of this is you start to talk about what we're doing and you start to look at the players that are doing this. They are all organizations that I would not call classical technology organizations. They were 10 years ago, you look at a Microsoft, but you look at the leadership of Microsoft today and they're much more about figuring out what the formula is for successful business. And that's the other place I think we're seeing a transformation occurring in the early adopters, is they have gone through the first generation in the pain of having to have these kinds of things. And now they're moving to that second generation where they're looking for the game and they're looking for people who can bring them capability and have the conversation and discuss them in ways that they can see the landscape. I mean, part of this is if you get caught in the bits and bytes, you missed the landscape that you should be seeing in the market. And that's where I think there's a tremendous opportunity for us to really look at multiple markets off the same data. I mean, imagine looking and saying, here's what I see, everyone in this group would have a different opinion in what they're seeing. But now we have the ability to see it five different ways and share that with our executive team and what we're seeing so we can make better decisions. I wonder if we could have a frank conversation, honest conversation about the data and the data ownership. You heard IBM this morning saying, hey, we're going to protect your data, but I love you guys as independents to weigh in. You got this data, the data, you guys are involved with your clients, building models, the data trains the model. I got to believe that that model gets used in a lot of different places within an industry like insurance or across retail, whatever it is. So I'm afraid that my data is going to, my IP is going to seep across the industry. Should I not be worried about that? I wonder if you guys could weigh in. Well, if you work with a particular vendor, sometimes vendors have a stipulation that we will not share your models with other clients. So then you just got to stick to that. So, I mean, but in terms of science, I mean, you build a model, right? You want to generalize that to other businesses. Right. So maybe if you could work with, work somehow with your existing clients, say here, this is what we want to do. We just want to elevate the water for everybody, right? So everybody wins when all boats rise, right? So if you can get that, if you can kind of convince your clients that we just want to help the world be better and function better, make employees happier, customers happier, let's take that approach and just use models that maybe generalize to other situations and use them. And if you don't, then you just don't. Right, that's your choice. It's a choice. It's always you're transparent about it. Exactly. I'm not super worried. You, Dave, and Tripp and I are all dressed similarly, right? We have the model of, if I put on your clothes we wouldn't, but if I were to put on your clothes it would not be, even though it's the same model, it's just not going to be the same outcome. It's going to look really bad, right? So yes, companies can share the models and the general flow and stuff, but there's so much, if a company's doing machine learning well, there's so much feature engineering that's unique to that company. They're trying to apply it somewhere else.  Yeah, but we could switch ties. That's the first. That's the first. Really cool tie, I've been using that tie in July 4th. This is turning into a different cut. We've got to wait. Chris, Tripp, Mike, and Bob, thanks so much for joining us. This has been a really fun and interesting panel. Thank you very much. Thank you guys. We will have more from the IBM Summit in Boston just after this.


I den delen av samhället som gör rör mig mycket i så pratar vi mycket eller pratas det mycket om Mindfulness nu. Det är ett väldigt trendigt ord och det handlar egentligen om att vara närvarande och vi var lite inne på det förut när Sudscharmen Andersson pratade om våran liksom obsess kring våran e-post att vi är på den hela tiden och kollar var 50 minut i princip vad har vi fått något nytt och då kan fundera lite hur närvarande är vi i det vi gör precis som hon sa. Det tar de där 64 sekundrarna från att vi har kollat e-posten till att sedan få tillbaks tanken till vad gjorde jag innan och vart var jag egentligen på väg. Så frågan är vad kan vi tjäna som personer och som yrkesverksamma genom att fokusera på det vi verkligen gör. Och nu ska vi göra ett nytt så nänt lite spännande hopp i programmet. Vi har bjudit in en kille som är expert på närvaro. Vågar påstå Daniel Strauser som är yoga lärare på Joga Kendra ska komma hit och hjälpa oss att förklara och lite granna visa vad närvaro är så att vi vet skillnaden och kan känna den. Så ska ta fram en mikrofon till Daniel så får han komma fram och riktigt vad som ska hända nu. Det vet inte jag så kom hit Daniel så får vi se om du vet. Välkommen. Tack. Spännande var här eller hur mycket spännande. Jag har ingen aning om vad som ska hända. Här är det lite vi gjort här en gång förut men då kunde man rösta nu kommer ingen möjlighet att rösta vad vi ska göra underbart så att närvaro vi är här och nu och du får tala om för oss vad vi ska göra. Hur lång tid har jag på mig om vi säger att du ska vara färdig till tio över senast. Perfekt Daniel Strauser. Tack i en horror movie. When you want to increase the sense of presence. I turn up the background sound the crickets. The wind can you hear the background sound the sound that has been here all along. Not one sound that sound in which all sounds manifest or like a record like an old vinyl record. You put the needle on just before the first beat comes. You hear something. What is that you all use computers. If you have 15 programs running at the same time how efficient are you. You have ACDC running on your Spotify loudly. Then you are fixing up a picture in Photoshop while using word and you have your mail programming on at the same time. Everything's going on. Even if you have a new computer it starts to run slow. You start to work inefficiently. So you buy a better computer. But you can't buy a better mind. How many programs are running in your head right now. I bet you were thinking when I was silent in the beginning. I bet your thinking right now. Whatever I say has to penetrate through those filters in your head. Whatever you see here feel whatever you can sense through your senses has to penetrate the filters of your mind. Så what about being present. We don't see the present moment. The present present like a Christmas present. You can open it up inside of it. You find a presence. That is your true self. Not your intellect. At your thoughts or feelings. Something much bigger. Extremely beautiful. Resting peacefully everywhere at all times. By centering yourself regularly. Not once every 15 years. By returning to that center again and again. You tap in to tremendous power. The computer you use has more power than the computer they had when they. Shot up the first rockets to the moon. But what do you do with it? Yes, so you don't need more power. Just need to use what is here. But what is here. What is now. You have to look at it and be patient. Have to have to lots of have to if you want to. You don't want to. You can just be happy. You can relax. But we can do a little test. If you please move your back free from the back of your seat if you move a little forward and both your feet on the floor. And both your hands on your knee don't use don't lean to the side just sit straight. This is called sitting up not sitting down. When you sit up your present the spine is straight. That means the channels the nervous channels in your body are open. That means you're more attentive. When you look at it the spine with the brain that's the central nervous system. The very core of your being the sperm that once swam around in your father's skrotum. That is now sitting straight. It's like an antenna. Yes. En och män i lävels. You perceive everything as coming in through the sense organs. But subtle inspirations. Also come to the antenna anyhow. Now it is straight and there are two worlds. There is the outer world. That we know so well. But behind your closed eyes there is the inner world and you interpret the outer world through the inner world. So we look at the inner. Så you can just close the eyes. If you want to but don't stop looking. When you close the eyes you can actually start to look.  The screen the cinema screen. Then you actively look into the back of your eyelids in the same way. You don't have to listen to the sounds around you anymore. Try to listen inside your ear. You don't have to feel the world around you either. You can feel the world inside. Perhaps you can feel heat. Warmth. Pulsating your body.  You're the lucky one. So by returning to our center. Let's do that now. All you have to do is to let go. It's like a computer when you don't use it it automatically shuts off. You see there is one thing that doesn't shut down. Never. And that is your breath. So you can feel the breath. You don't have to pull it. The body knows how to do that on its own. Just feel the inhalation. Fill you up. Very fresh. There is some tension. Some lingering stuff in your head. Feel it just melting away from you with the exhalation. It is kind of as if you're sinking into the present moment with each exhalation. Really feel the exhalation. It's quite lovely. Letting go of all that tension that tends to build up during the day with each exhalation. You might see that your mind is not quite going with this program.  All this stuff bubbles up, sounds distract. The outer world keeps knocking for your attention. So you need some discipline to focus without focus. What can you do? Just feel the floor under your feet. Feel the seat below you. Feel the straight spine. Feel the breath. And try just for one minute, not to think. Try to stay with the feeling of this moment for one minute. Still actively looking at the back of those eyelids, aware of breath or maybe something else. Just you open the eyes and relax. You can sink back into your seat. There are different ways to experience everything. I experienced this room from up there before was very different from this place. You can experience life through a lot of thoughts running around or you can experience life through another place, a more silent place, a calmer place. And you will see that it's very different. If you want new ideas, you want to make new connections, you want inspiration. Where does inspiration come from? Where does energy come from? We tend to seek everything outside of us. But really the inner is the primary. This wonderful building. Where did it come from? First this was in someone's mind. Then they drew it on a piece of paper. Then they build it. But it comes from the mind first. Then we manifest. So spending a little time inward, focusing within, connecting. We see something beautiful that behind our thoughts and programming and all that stuff. Really inspiration comes through intuition from a higher source. We don't have to talk about garden stuff. I like to talk about the presence in the present moment that you really are to establish more of a contact with that is highly beneficial. No matter what you do, but I should warn you. Yes, by actually relaxing and starting to listen.  Thing that seemed really important tend to fall away. You don't take stuff so seriously anymore. So what if you didn't check your email five minutes ago? You can do it when you come home. You know, it's all about being present. If you're not present, if you're not connected with the presence in the present, you're like my first computer I got in 1995. My mother, she didn't use hers. She bought, she could buy it cheaply from work, but we had no internet connection. Talk about a boring computer. You couldn't do anything with it. Just some programs were inside. Passions. Vad Världla Street program. You could use a CD and put it in and, you know, get a funnier program into it. But when you got internet, my God, did the world open up or what? You could connect all other humans and everything. I'm not here to convince anyone, but I personally know that when your thoughts stop and you're simply present, you are connected to everything. Still science is baffled about how could some ancient cultures know some things that we know first now with our powerful instruments. Obviously they didn't have them. Well, they were connected. You are connected. And imagine if you yourself connect, then what can you not do with the media we have today? So get online. Be happy. Mm. Normligen har vi ett tennor i introduktion, så det är lite difficult för mig. Vad är det? Thank you for having me. Och tack så väldigt mycket. Daniel Strauss är tack, tack, tack.


Hi everyone, my name is Asami. I'm a software engineer in the Chrome browser team. Today I'm gonna talk about the new logic to detect PWA offline support. PWA is a technology to turn a web application into a native app like stuff so that we can take advantage of both web and native app features. Because PWA offers native app-like experience for websites, websites that support PWA can be installed as if they were native apps. When you visit an offline capable PWA, the browser asks if you want to install it. If your answer is yes, the icon for the PWA is added to the app launcher on desktop and to home screen on mobile. Once installed, PWA can and should work even without internet connection. Let's see a little bit more about the flow of how to install a PWA. If you want to install a PWA on desktop, first you visit a PWA capable website and click a plus in circle button in Omnibox. Then you can see the install pop-up. You can install a PWA by clicking the install button. Now you can see the icon in Chrome Chrome Slash Slash apps in the browser. When you install a PWA on mobile, the icon will appear on home screen like this. However, when you open an installed PWA without an internet connection, you sometimes see the screen, the dinosaur page, telling us no internet connection. This is so frustrating and definitely not an app like user experience, right? This is the problem we are currently improving. We are hoping all PWAs work correctly without an internet connection. We encourage web developers to make their PWAs work offline by handling the offline situation correctly. So we are raising the bar for websites to display the PWA install prompts. In short, if your PWA doesn't work offline, Chrome will not show the prompts for installation, starting from the near future. That change will affect both mobile and desktop. Before we dive into how to check offline capability of a site, let me quickly review four requirements to make PWA installable. You need a manifest JSON with the correct field-filling, a secure domain, icons, and a service worker to allow the app to work offline. When the site satisfies all of the requirements, install buttons will show up. On mobile, you can see an install button in the three-dot menu and add to home screen button at the bottom of the page when the site satisfies the requirements. On desktop, you can see a pressing circle button in omnibox and an install button in the three-dot menu when the site satisfies the requirements. Service worker is the thing that is responsible for offline support. Here is how it works. Service worker can install a FEDG event handler to steal or interrupt an HTTP request from the PWA before they get to the network. Using the feature, service worker can and is expected to handle all HTTP requests by itself. When you are offline, a FEDG event handler is expected to return resources on behalf of actual website using cache resources as if an internet connection is available. The behavior should be implemented by developers. If it's not implemented, the install prompts wouldn't appear. But the problem is the logic to detect if the site works offline is not very accurate. Consequently, install prompts may appear even if the site doesn't actually support offline directory. This is a reason why you sometimes see the dinosaur page in an installed PWA. The current logic to detect PWA offline support is just checking the existence of a FEDG event handler in service worker. I mean, even an empty event handler like this is considered an offline support. But what happens if a FEDG event handler is empty? If a FEDG event handler is empty, it does nothing so HTTP requests fail. It leads to the dinosaur page. This is a problem that I'm working on right now. Concretary speaking, Chrome will stop considering the empty event handler as an offline support. We are updating the offline capability detection logic as follows. In the new logic, Chrome will create a fake HTTP request and send it to a PWA main page, which is specified as start URL in Manifest JSON to see if the PWA responds with a 200 response. During the test, PWA runs in a sandbox that doesn't have an internet connection. A PWA is considered offline capable if and only if it returns a 200 response for the fake request. This is a naive and simplest example. In service worker, they can be considered as offline capable. The FEDG event handler returns a response object when a FEDG request fails. So users can see Harold offline page text when they access an installed PWA offline. This is another example in service worker that can be considered as offline capable. This code uses cache straight to store resources when users install a service worker online. Once users install a service worker and store resources to cache straight, the FEDG event handler can return the resources without internet connection. This is yet another example with Workbox. Workbox is a JavaScript library to make it easy to support offline pages. First, you need to supply an array of resources to the play cache and root method. It will do caching as soon as the service worker is activated. Second, you can use the navigation root method to return a specific response for all navigation requests. Using Workbox is easy and practical, so we recommend using it for your site. Here is a timeline we are currently planning. The new offline detection logic is not available yet, but most implementation was done in the current stable Chrome version, 87. In the next milestone, Chrome 88, the future is enabled behind a flag. You can enable check-off offline capability flag in Chrome colon slash slash flags. Also, we are going to run experiment for some dev and canary users to make sure any regression doesn't happen. We are planning to roll out the future in Chrome 89 with warning mode. The warning mode means the new check happens without enforcement. It will show a warning message in the developer console if the site doesn't pass the new offline capability detection logic. After a grace period, the new requirement will be enforced to all sites. We are very excited to see the new offline detection logic, and we believe that it will lead to a better user experience. We welcome your feedback, so please input what you think about the new offline capability check. Thank you.


Goat and sheep are ruminants with a four-compartment stomach that is made primarily to digest grasses and forages and convert them into energy products for ruminants. The diet should consist of at least 60% grass or forage. Some of the varieties commonly found and used in the tropics will be discussed. African star is native to East Africa and is found widespread throughout the tropics and subtropics. It is a robust perennial grass species that is palatable to all classes of livestock and it is cultivated as a forage, fodder and pasture grass and can be grazed or used for hay or silage. It can be established by seeds and vegetatively by stolons also called cuttings. This species is drought tolerant and can also withstand temporary flooding. It grows better in full sunlight areas and may survive some frost but low temperatures reduce its growth. Once established, it competes well with other grasses, native species and weeds due to its aggressive growth and rapid propagation. It is best harvested at four to five week intervals. Pangola grass is a tropical grass widespread in many humid tropical and subtropical regions used extensively for grazing, hay and silage. It is often considered to be one of the higher quality tropical grasses. It is tolerant of drought but low rainfall is the main limiting factor for good yields. The best yields have been produced in full sun or well-drained moist soils. The production of Pangola grass pasture is sensitive to photoperidism and the grass grows dormant during short to day length. During the growing season it can be harvested at three to four week intervals. Guinea grass is a major tropical grass used for pasture, cut and carry, silage and hay. Guinea grass is a perennial species and may form quite large clumps and is propagated by seeds. It is a fast growing and leafy grass which is palatable to livestock with good nutritional value. It is generally recommended to include sources of protein, for example, leucine or mulberry forages to meet the nutritional requirements or improve animal performance. King grass is a fast growing, high yielding hybrid grass that grows in a variety of soil conditions. King grass is a perennial and can be harvested several times per year at 40 to 60 day intervals and can be fed as freshly cut grass, green chop, silage or hay. It has fair protein and high palatability. In a mixed ration, giant king grass provides fiber, energy and protein and can reduce the amount of the high cost materials needed in the ration to provide optimal nutrition. Sorghum is used for both grain and forage. Some varieties are grown solely for grains, others have been developed for forage production and some varieties are dual purpose. The sorghum plant is a tall erect annual grass with broad smooth leaves. Sorghum has an adventitious root system making it tolerant to drought. It can be grazed, green chopped, ensiled and made into hay. Young sorghum can be toxic due to hydrogen cyanide and should not be used until it reaches at least a height of 45 centimeters. Farmers must consider conserving grasses and forages for long term storage.


Patrick, a member of the Institute. Mr. Question, specifically about Bombardier and the DUP. As a hard test case for a lot of the, what you're describing, as chaotic and mutually contradictory positions have been taken up, how do you interpret what's happening with Bombardier in the light of what you've just been saying about evolving trade policy in the UK? Well, Bombardier reveals an administration compared with which the British are a model of coherence and unity. The US administration is pulling in endless numbers of different directions, and I think the issue over Bombardier and over the wider issues of the aircraft sector as a whole and trade in it is subject to quite remarkable differences of interest. So if I find it difficult to read the British government for a coherent and simple answer to your question, I find at least they've got the excuse there that they don't know which bit of the Trump administration they should best be talking to. So I am not the best place to answer the question on how this experience is or might affect attitudes in the North. I don't know. I think that one thing is problematic for the government's immediate management of things. The 1 billion pounds that have been earmarked for the DUP can't actually be delivered. So it's because of the impasse in the North, in Northern Ireland, over the executive and so on. So I ask myself the question. We know that in the referendum there was a clear remain majority in Northern Ireland, and we know that that could not happen without there being a significant section of Unionist opinion who voted that way, even if it wasn't the majority of Unionist opinion. Would all of this, the longer it go on, make the position of the leave supporters more difficult in Northern Ireland to be able to justify to their own voters? I'm talking about their own voters. It's a question that people here would probably be able to answer. It's all overshadowed by the wider question of the border. And gosh, I wish I knew something new to say. There may be something new in Dublin to say about this. I hope there is, but I don't really know what it is. Thanks, Don. Colm? Colored after Retired Foreign Affairs. John, thank you very much for your honest insights. Would you current comment on the attitude and approaches of the EU 27 Commission and Barnier? Have they managed things well? Have they managed these attention? As far as I'm aware, they have. I had the advantage of a briefing from Barnier and some of his team on two occasions in the last few months. I was, I mean, I've known Michel Barnier for some time in his different incarnations. He's a very able, cool customer. And my impression is that he enjoys and the Commission enjoy thus far the confidence of the Council. The most recent meetings of the Council didn't indicate any serious questioning of the way the Commission have handled the negotiations thus far. Might it emerge in future? I guess it might. But something we discussed before this meeting, and it relates to the Northern Ireland question. How can I put this? Ireland is in probably a stronger position to influence events at this stage, even than it would be when we moved to the second stage. Because the conduct of the second, if and when we do move to the second stage, the conduct of the second stage will be subtly different. Instead of just occasional reports back by the Barnier team, the Commission, I think there would be much more ongoing invigilation of the negotiations in the second stage, which allows for the earlier expression of maybe national interest divisions to emerge over trade, over a variety of issues. In theory, that might make a satisfactory settlement of the border question a bit more difficult than it would be at this stage. On the other hand, it's difficult to question the logic of the UK when they say, but we can't give you that answer until we know the nature of the relationship we'll have with the Customs Union and the single market, et cetera. Then we can put flesh and blood, they imply, on the bones of a no-hard border, maximum freedom of travel trade, et cetera, et cetera. So I think so far they've handled it very well. I have no reason to think that will change, but it will be more difficult for the Barnier-Yonker team and so on. I mean, they've also got to watch the Parliament, though. I don't think the Parliament's role should be over-exaggerated when it comes to the final decision, where there has to be a qualified majority of member states, and in those circumstances that affects the kind of majorities that the Parliament can produce that are different. But so far, so good. Thank you, John. Oric? Thank you for the important member of the issue. It seems to me that the United Kingdom has never regarded itself as a third country like other third countries, and indeed Theresa May has been quite explicit about it. There's going to be no Norway-type arrangement. There's going to be no Canada-type arrangement. There's going to be some kind of tailor-made arrangement which, in London's eyes, will take account of the very special position in their eyes that the UK has not only in the European system, but in the world system. And it seems to me that it's quite conceivable that the agenda of the British government is to bring about a situation where the European Union itself will modulate in a direction which is more acceptable to the UK. We all know that all that is ever wanted was a large free trade area in Europe. And for the purpose of doing this, do you not think that they will be playing with a certain number of member states we have seen recently, members of the Royal Family being sent to Warsaw, for instance? One could see prospects of certain things being done in Hungary, not to speak of our own near country here and you have yourself adverted to the kind of leverage that the United Kingdom could bring to bear on a country like this in order to resolve the seemingly impossible problems of the border on this island. So perhaps the British agenda has never changed very much and they're really aiming through another route to achieve a kind of result that they always wanted. Trading on that also on the apparent non-commissionedness of many of the others to the more integrationist objectives of the Union as set out in the treaties. Yeah, thank you for that. That's a very complex and difficult question. I'm not sure I can give you an entirely satisfactory answer. There's always been the sense of the UK being a bit different. We should be treated with a bit more respect because we're a bigger power with more outreach and all the rest of it. That has been the inspiration of the skeptical attitude all along. However, even among the skeptics, there is now an awareness of the much diminished status of the great power. Look, we have some of the symbols of external power status in the United Kingdom. Armed forces, regarded as professional, et cetera and so on. But they're now having to handle state-of-the-art aircraft carriers that can't actually handle any of the planes that the British armed forces fly in. I'm saying this is kind of like a revealing symptom of a decline. The decline has been economic. The decline has been in the area of power and influence projection. So this is not the Britain of Enoch Powell when he launched his opposition to UK membership, which of course failed in the referendum, 75. This is a much more diminished. It's also an internally diminished, a large part of the UK has an ambivalent relationship to the rest of it, Scotland. And not to speak of the problems here in this island and even questions elsewhere. So, and also power centers are shifting in Britain. One of the interesting things that's happening in England, I have to say, this is nothing direct to do at Brexit, but it will make itself felt eventually is power is moving to the cities, the big city regions. I mean, really serious power. I mean, funnily enough, it was begun by a conservative in a sense of a former Chancellor of the Exchequer Osborne, but it's much more has a life of its own now. And I think we're going to see a debate about the constitution in Britain becoming less London centric. I'm only saying all of that because the picture of the great power isn't quite any longer where they're at. Though they talk the talks, they can't deliver on the results very easily. So all of that, I think, complicates it. However, that said, undoubtedly on intelligence, criminal terrorist intelligence, the British have resources and sources that many other EU countries do not have. They also need Europol. I mean, of course, when you look at the way the government talks about our participation, we will remain in your atom, they say. Of course, there's no alternative. We will remain part of Europol. Yeah, nobody thinks we should set up a separate one. We will remain as yet not fully clearly determined a partner in science, education, research. I could go on. There are other things. So what some of the hard line skeptics say is, hang on, what kind of an exit is this? And if you add to that a slightly indeterminate transition, I think it looks like we remain with all, many, most of the obligations that you would judge membership by, but we've no vote and no voice. And when I discussed this with somebody in the opposition, I said it will invite from me and for many others the slogan, no taxation without representation. So, I mean, all of these things are happening. Yes, they will try to play, they have to be careful with their European allies. Orban is still largely untouchable in Budapest.  They are the main people who've migrated for work and so on and so forth. They're in quite a strong position to say, to demand much. So they're not, they would in the past been allies against Brussels, but they're not on the same side of the actual immediate issues in Brexit. That's the thing. So, they will try, of course, that will be a major part of the British diplomatic effort in the final stages of these negotiations. They will use every trick. Thus far, they've been disappointed, they had assumed that they'd have these allies beginning to mobilize and that they would have words of comfort from the federal chancellor. And they've not had that. I wouldn't always rule out that they wouldn't get something at it, but she's not going to give it now. The British have not accepted their status, the real truth and the reality of their status. So neither she and certainly not Macron are going to give that. And without that, you know, the odd speech from a Danish minister or a Lithuanian minister is not going to be enough. Thank you, John. I have five hands up. I'll take them in the order. I saw them. Donald. Thank you, Dohy. Thank you for a very interesting perspective. Donald Adam, I'm a member of the Institute. It's interesting and, of course, not at all surprising that much of the focus, especially in the media today, it has been on British positions. And Mr. Barnier, whenever he's interviewed, comes up with the question, will we need to know more, tell us more, give us more detail, et cetera. But the one clear consistent line from Brussels from the very beginning has been that Britain should not get as good a deal outside membership of the European Union as it had as a member. Now, does that not imply, at the very least, a poor deal for Britain? I mean, the short answer to that is yes, absolutely. I cannot see how it can be comparable, let alone identical. I can't see it. So part of the game is perhaps to disguise for as long as they can that the deal isn't going to be a great one. And it's going to be subject, that's why I talk about the fragmentation of the whole debate in Britain. The more a possible consensus emerges, if it emerges, the more it begins to emerge, the more it will be subject to the critique on both sides. It will not suit the pro-Europeans and it certainly won't suit some anti-Europeans. That leaves you with a very fragile power base with which to carry through such a deal. And already, when she made the speech yesterday about the Court of Justice, they were all out, the usual suspect, saying this is absolutely out of the question that we should accept in advance. The whole idea of getting out of the European Union was to get out of the Court of Justice, et cetera, et cetera, et cetera. So, you can't. I agree with your belief, Colin. Thank you. Tom Ferris, member of the Institute. Very brief question, and it is fragmentation. Do you see any significance in the fact that the two position papers published on trade and customs are not from the Department of EU exit, but from Department of International Trade and the Treasury today? It's a good point. I hadn't fully reflected on that, but it is. I mean, under Hammond, the Treasury has tried to insert itself as where possible because the Treasury want an agreement, and they want an agreement that is viable because they know already, no, I mustn't exaggerate, the wheels are not coming off the economy, but it's creaking. Productivity levels are down, real incomes are falling. Still, trade balance is dodgy, investment rates are beginning to tail off. That's before we've got to the serious stage. So they are trying, and I think that's part of the reason why the Prime Minister has brought a chunk of the trade negotiating team, answerable Hitherto to Davis, away from him into her. I can't see any reason for doing it other than that. Thanks, Jess. John, given what you described as the political confusion in the Conservative Party, we're likely to be faced with some sort of a general election maybe before the date set, do you see any scope for a better dialogue with the British Labour Party on a kind of an agenda that strikes me could be saleable, and that is a remain and reform kind of agenda, and the fact that Macron has made the speech he's made and a number of other people that said that they hire all over the European Union, recognised the disaffection of many citizens, Spain, Greece, so on, and it would seem to me that it might be timely for a better dialogue with the British Labour Party, maybe through civil society, I know governments can't do it, I'm sticking to trade unions maybe myself and through civil society organisations to get a fair more grip in the British Labour Party on a remain and reform kind of agenda. Now, they have a legitimacy, you're right about the post-war perspective, most citizens have legitimacy which is not racism about cheap labour being coming in to take their jobs, so it's perfectly reasonable for big areas of working class Britain to worry about that. I think it was more affected by the Middle East incident than European workers, which was a fact that that's a reality, and also there's a lot of disillusionment over the way Greece was handled, the way Cyprus was handled, about how solidarity Europe that most people signed up to doesn't appear to have a lot of meaning, so is there a time where you see scope for a better dialogue made with British Labour? Now, I'm also thinking Jeremy Corbyn is elected in Irish constituency, my own family vote for him, they live in Islington, you know, and Corbyn must be, he certainly was interested in the Northern issue, but I think the East-West relationship with Britain is even more important than the North's outcome, they forget the number of jobs are affected by the industry in commerce and so on, so I'd be interested to live with more, I know you have a good insight into that in what's going on in Labour. Well, there's one surprise you to know that I agree. I think I kind of tried to imply, and what I said earlier on, that the debate in the Labour Party itself is only beginning to move now out of a state of paralysis, and this is being brought about by the remarkable election result, which is not to be underestimated, and it is generating a wider debate than the narrow remain leave formula allowed to happen. Secondly, discussions between the institutions and the Labour leaders have begun. I know they've begun, I know that Stammer, here Stammer, the official shadow minister, has had extensive briefings from the Barnier team and others, and that he's also met with Jeremy Corbyn and so on. Some of us are very active in precisely arguing that there is a remain and reform strategy, which is a, not just convenient, it may not be convenient, if it is actually necessary. I wouldn't exaggerate the extent to which the leave voted was motivated by a subtle analysis of the failings of the European Union, which, by the way, are many, many. I think that the immigration issue, people saw pictures, nothing to do with the European workers, by the way, they saw pictures of millions and millions of desperate people fleeing from war and dictatorship and persecution and worse horrors and said, this is all what the European Union brings us. That was the mindset. So, if you said to people, I know this because I took part in part of the candidacy, in the Rwanda, which you will know was so solid for Labour that you couldn't ever have it. But there was a big leave vote there, and they were talking about this, they said, well, we don't want all these Middle East people coming in, they have mixed up that with the whole question of the free movement of workers. And there is no doubt about it. More generally, I have long believed and written, and it's public, the need for drastic changes in the way the European Union handles some issues. At the core, my main complaint has been the quite needlessly excessive obsession, doctrinal obsession with austerity, which I'm afraid to say the blame must be put on the door primarily of the government in Berlin, and in specifically with the finance ministerium, with Herr Scheuble, who pursued this doctrine to an extent that has been massively, massively counterproductive. There is a, he's now being moved out of that job. We know whoever else takes it, we don't know, whether it's any better or not, we remain to be seen. I agree with you about what I have called publicly the crucifixion of Greece on not that there weren't massive problems of the Greek system, and above all taxation and corruption and all the rest of it. But it's, when you get the IMF saying, this can't continue, these debts should not be maintained on the Greek, they are ultimately debts which have to be shared by those responsible for which were the banks, and particularly in the case of Greece, the German and French banks in the first place. So all of that now is part of a new discussion that's emerging, and there is a lot of debate. And by the way, the commission has finally come out of a long period of almost monk-like silence with quite important new proposals for recovery, for massive investment, infrastructure, et cetera, et cetera, et cetera. It's all gotta be seen, I'm not in a position to make any judgment about how this will end up, but there is a new framework. I've mentioned the European Labour Authority. It's worth it, people haven't seen it, it's worth looking at the details of this. This is a much stronger, if it's passed, and it's got both Berlin and Rome and Madrid and Paris strongly behind it, so difficult to see, won't pass, is a bit of a game changer for some of the issues that people have had on social policy and so on.  I have to say that I'm not sure how much that poisoned the British debate. It didn't help, but I think there were other more historic issues which have long played in the British public debate about Britain's place in Europe, et cetera. And I mean, it's very interesting, Scotland voted overwhelmingly for Romain. And by the way, the cities voted Romain everywhere in Britain. The big cities all voted Romain. Working class city like Liverpool voted by a massive majority Romain. So it's not a, but it's the areas that were left deserted like in America, I'm sorry, the left behind have taken their revenge. And the left behind are the responsibility of the center of political life, both in the United States and in Europe and above all in Britain, where two generations after the mines disappeared and the shipyards disappeared and the steel industry disappeared, very little ever done to replace it or to provide comparable economic opportunities. And that has hit some of the traditional labor vote, particularly hard. It's only now coming back as a result of recent changes. So, I agree. Thank you, John. There are two down at the back, but before I go down to the back, I'd just like to ask the supplementary to this. Where do the British trade unions fit into this debate? They were very active before the referendum, but I've heard very little from them since. Most of the unions in Britain are for Romain. I can't immediately think of any, somebody will correct me now, but I can't think of any that have official position of leave, none. Unison and Unite, which are the two biggest unions, certainly the GNM, the general and municipal, they got what they call themselves now, the names have changed, and others are very strongly pro. Something that you may not know, which is quite important to know. This is not a left-right issue. The body, which is the main partisan body for Jeremy Corbyn is called momentum, and they have hundreds of thousands of members. They are overwhelmingly Romain. So they're not coming at it from the traditional. They're coming at it more Romain and reform, if you like. So that has affected some of the position of the union, the fire brigade union, very left-wing union, very strongly pro-Romain. So it doesn't fit into the traditional. 1975 was a totally different story. Then a large part of the Labour Party and the trade union movement was on the anti-side, as were other currents in this country at that time who changed, and they've changed in Britain too. Thank you, Brendan. Brendan Lynch, I have a question just about the transition period. The Reuters has a story today that Theresa May, she was addressing a group of business leaders, and she told them that a transition period was certain in her words, and she also, Reuters are saying that she said that there would only be one change in the trading relationships, if you like. The business would have to only deal with one change in the relationship between the UK and the EU. Do you have a comment on that report? And secondly, what are the chances of all of the 27 other member states agreeing to a long transition period, or is the agreement of all 27 necessary? Well, certainly the agreement of all 27 is necessary. That's right. I think the final vote is a qualified majority, but it would have to be a pretty overwhelming majority, I think, in the final terms of the deal, if I remember correctly, at the level of the European Council. I haven't seen that particular statement, but it fits in with what I'm saying, that we're talking about a transition period, as one of the ministers said. Hammond said, it'll be a transition where you'll not really notice anything has changed. That means the change will come only when we exit the transitional period. So that brings us back to the point, well, when would that be? Two variables, when will it start? It should start in 2019 to 2019. If it has to be delayed, then that will affect its duration, and it may be extended, there's talk of three years, there's talk of this comes back, and then you have a much bigger change. So this is all about defer. What's the expression they use? You know, where you put it on the long finger. You put it on the long finger, that's right, that's right. I think that's the best the government thinks it can get in its political horizon, which is limited by the factors I described. Okay, I think it's time, is it at the back, and then the last one will be up here, Tom. Thank you very much, Chairman, and thank you for a fascinating presentation. First, a very quick observation.  We had debates going back to early 2015, I think here with some leaders of the Conservative Party, where we said the only workable Brexit border would be in the Irish Sea, and with Arlene Foster supporting the government, that seems like a pretty remote possibility. Secondly, I'd just like to say, perhaps as a member of the Institute, this may color my position, but the discussion in the UK, viewed from this side of the Irish Sea, is characterized by ignorance. We hear ministers making comments that seem to be unbelievably uninformed. We hear even people from the business community speaking in a relatively uninformed way, and this is hard to accept when such a huge decision is in play, which will also affect us here. But finally, in terms, it's not a free trade area, it's an internal market, and you can't have a game without rules. You can't play the game without a referee to enforce the rules and linesmen and all the other officials you need. You can't have an internal market without the commission. You can't have challenges to the rules without the ECJ. So if that's a red line issue for the UK, it's extremely difficult to see where we can come out the other end. When somebody said earlier on that maybe a Norway-type agreement is the best they could get, which the British say is not acceptable, it's got to be custom-made for the UK, Norway has one or two exceptions to the single market being given fishing, and I think some aspects of agriculture, I'm not sure I know all of them, but other than that, they are fully in, but no vote, no voice, no vote. They're told what the decisions are. Something like that is about the best that I can see, but this is for a country which has had a voice and had a vote, so it makes absolutely no sense. It is a hallmark of the desperation of a party that knows its foundations are rocking, so it is driven to one more fanciful extemporization after another, it's the only way I can put it with the best will in the world, and they're going to try and dodge the bullets from both sides of this debate, but increasingly their horizon gets shorter and shorter, which I think is about becoming almost a question of this week, next week, few months time kind of thing. Thank you, this will have to be the last one. William Scali, member of the Institute, thank you for everything. Just two points, and you did touch on the Irish, I've been an issue a couple of times, I'm sort of left behind there, but if you were a half competent British negotiator, wouldn't you do what they are now doing? I mean, of course, you can have an all-in-all, you can have the Good Friday Agreement, you can have your common travel area, but how in the name of any logic can we agree a final solution on that issue without getting into trade, single market, customs unions and issues? I mean, if the British weren't saying that, they would be arguably totally incompetent, but how you get that sort of addressed and advanced, now it's a very difficult question, but I'm just throwing it out to you. The second one is that from someone looking at this from a distance, and you did talk about spies and that sort of world, but is there any serious plan in either the European Union, which of course, because apart from countries like Ireland to mean the effects are more diffuse unless if the whole thing breaks down, but certainly obviously great for Ireland, but is there any master plan that is, apart from being theoretical or on paper, is in any way capable of implementation if the whole thing breaks down? I mean, you were sort of implied maybe there is, looking at it, I don't know, but it doesn't look as if there is. Listen, before I directly answer your question, there's something I should have said earlier on. Quite rightly, the previous question raised the question of the border controls on the Irish Sea, and that doesn't look as though it's going to fly in the North and therefore in London. I think there may be some parts of West Whitehall that might have viewed it with something we could live with. And of course, people forget, everybody here I'm sure knows, it existed, 1941 to 1950. 54. 54, 52, there we are, so it has a precedent. It doesn't look as though it's going to fly with the DUP and so that's not there. But on what you say about the kind of what, how would they begin to tackle if this breaks down? I don't know, in her statement yesterday, she said, we are beginning now, preparations, we don't want them, it's not what we want, it's not what we're expecting, but it might happen for a failure of the negotiations. So among the, God knows what list of issues the civil service have given, the number 10 Downing Street, no deal will involve, home office, et cetera, missed ministry that many, ports, airports, travel, will the planes fly, et cetera. How are they going to do it? I haven't a clue and more to the point, nor have they. They haven't a clue and in a way this is, I come back to my, if there's one thing that I'm saying, the name of the game now is by tomorrow or next week, by a transition where the minimum changes from our present status has kept the loss of vote and the loss of membership, but everything else, the obligations of business arrangements remain in place because the whole ship of status too fragile for anything else, and let somebody else deal with the future. I think that's what it's amounts to. On that note, John, may I thank you for a very, very interesting comments, but also for stimulating a very interesting debate. Thank you, John.