what we look at that the future operations clearing board is at four different areas which we try to you want to triage to try to combine so the first area looking at the management of the health area of the health system and for that I will come to that for that the app is a part of the solution it's not the whole solution unfortunately it would be nice if we just had one app


that can solve everything but we need to find a way to track trace and test in significant numbers to be able to manage this containment so that is the first area is managing the the infection and managing it in a very differentiated way and we'll come to that mode EP the second area just for for your information the second area is what recall the provisioning of basic

What extent can mobile apps solve the COVID-19 crisis?


services you know so looking at the logistics chains looking at the food chain at other critical areas like medicines how are they impacted by possible lock ups in different countries in different companies and so that is something that we are we are analytically trying to capture and to see whether we have significant trigger point and breakup points in the overall


supply chains that's the second area the third area is economy at large and its economy it's the financial system it's the tourism system it's anything which has to do with with the workforce with with the impact that it has on the economic activity that is where the focus over time will certainly become more important because that is where the full impact is is visible already now


and well we need to create the prerequisites for a quick restart and also for I would call it a reset because we will have different areas well which will become more important and certain areas which will be which will be impacted in a sustained way let me put it this way and you know it's a certainly we can go in more detail and the last area is the psychosocial impact


needless to say people are impacted by what is going on there is a great angst in people there is a lack of there was a lack of security at the beginning particularly the more we manage the particular health element properly the more we will have you know the less you know the burden is on on people and particularly there let me highlight one point what we see is that certain groups


of the population are more impacted than others and particularly women and women with small children of much impacted by that so we are tracking that and trying to make it possible to take the burden from this from these groups and that many others were really impacted just let me come to the first area because that is where we feel that technology is definitely part of the


solution actually apps can help in many areas but particularly you know the the t-t-t-that testing tracking and tracing is one of the critical areas so making sure that we have enough capacity to track and trace when we open the borders when we have more tourists where tourists coming in where we have a stronger mixing of population I think is very important and


that is why we feel that it's it's critical to have an app that is very much accepted by the population so what do we mean by they're much accepted it has to fulfill three three key criteria it needs to fully comply with the privacy expectations of the population and that we are very clear and I think you know Michael was very explicit you know we have very clear guidelines with


it needs to be privacy compliant and it needs to be accepted second thing it's usability now on the usability we all agree that it was a minimal Viable Product what was introduced and I think it's a it's a it was a great proof of speed of bringing it to the market it's still not as function as you know as performing as as we would love it to be the more performing it gets and more usable it


gets the higher the acceptance and I think that then people will like to to use it the third thing and that is also mission critical is interoperability because clearly why do we need it we need it because we want to make sure that we are able to act once we open the borders so these are three key elements but let me come to the fourth essential element its individual responsibility we


will never get control of this health crisis of this infection if people don't take the individual responsibility of making sure that we manage this in the proper way and I do not think that we can forever managing top-down I don't think that's the that's what we want and it's also makes no sense it's not what we what were used to and it's also not going to work in general we need to enforce you


know enforce a sense of responsibility if anything but not enforce tools or other stuff you know and that is what we that that is what we totally think and that is what we are clearly factoring in in our considerations in the future operation spot under which preconditions taking us back to the topic of that under which preconditions does the corona have fulfilled its purpose I


think it's it will fulfill its purpose if it really works you know in a hassle-free mode I mean usability as I said is essential and you know I think that you know there are non-debatable switches privacy clearly that's a known debatable we don't need to discuss about that but the usability is the essential thing it needs to be it needs to be working you know easy in an easy way and


clearly you know and I think you know we could we could start to see a broader a broader usage once the usability gets better but then interoperability is then the the other key problem that's that I think is really the it's the to maker or breakers because then we can we can make sure that we move around and we are we have a sent not only a sense but a real


tool for individual security and I think that's and for individual control for self control I think this was moving to a responsible behavior - self-control is essential ok which what percentage of the Austrian population has to install and use the app in order for it to be effective I don't think that it's about broad percentages of the total population I think that we need to have this


particularly you know brought in in broader usage where where the risk of super spreading is highest so I think that we need to be you know we need to see that the risk of being infected of encounter of a infected person is very different if I'm somewhere in at the if I'm you know someone Berglund or if I'm at the border of German Austrian border and Tirol so I think


it's very or in Vienna which has a very high you know confluence of a lot of people so I don't think that we should aim at broad percentages let us try to look at how if it's used where its most needed and that is where the encounters of different of groups from different people more more expected to happen mm-hmm but I mean I did a little bit of research and there's like experts or


experts suggesting that 60 to 70 percent of the population should be should have installed and be using that prefer to be effective from what Michael just said were right now around 7% a little bit a little bit below 7% don't you feel that we need to get a much higher rate of usage in the next month in order for the project to work no absolutely I think that we need to


increase the use of the users rate we need to increase it and and if you and it were clear you know about that it is about making sure that for example companies start to introduce you know to recommend the usage of an app and the people in a company which are usually working together that they also ask their the people that they are working with and and there you know


other people that they are interacting with to also use it so that there is a bit of a control but I think you know it's not abroad I mean if it's if 60 to 70 percent of their awesome population is expected to use it then we can forget about it you know I think we should not define irrational high bars we should introduce sensible D averaged targets and make


sure that it's used where the risk is highest okay now obviously the whole topic of the app has created quite a media frenzy a bit of a heated discussion on relevant or less relevant topics and actually might have been taken out of context one of the topics that the the whole discussion focuses on at least what I've been reading on is that there is kind of two different


aspects of the whole situation the one aspect is saving lives because let's face it it is at the end of the day a virus that causes a lot of death and saving life is the priority and a responsibility that that we need to take care of but on the other hand we have the topic of freedom of choice democracy and what do you think is more important I mean what I mean freedom of choice


democracy is always more important than anything else it's there that's more important than anything else but I think yet we need to be I mean the if if we look at the discussion I think that we are mixing a lot of things you know you you rightly said it is a matter of balancing the needs for for health control with other needs and given that we have a very very performing data


privacy regime in in Europe we are in a match that situation because we have the possibility to create things that are totally compliant with this data regime which is extremely essential it's it's totally fitting the the belief in democracy and in individual free choice that is you know a pillar in Europe so I think that's as I said it's a non debatable about that but then we need to


be also very clear about what does it mean if people you know willingly and the mind the discussion about these apps you know because of I don't know what reasons because it's makes no sense but at the same time the same people have a broadly used commercial apps and have profit sharing agreements and and then which you know the user of their services don't even know about and and


these commercially commercial companies fully capture the data not for protecting the health of anybody apart from the economic business health of the company so I think that we need to be we need to have a serious discussion about what is the right governance for for this kind of health and and life-saving apps clearly I mean compliance with the privacy rules is essential and and then


there are some elements that I feel a very important like making sure that open technology and also that you make sure that that they are used in the spirit of individual responsibility I think that's essential okay you mentioned previously that one of the four pillars that the future operations clearing board is working on is the topic of the economy the financial


system and tourism so since Austria is heavily dependent on tourism as a pillar of our economic prosperity how do we handle how do we tackle the challenge that tourists are entering the country and they're not using the corona app how do we what we can do if we have look I think you know the tourists the individual tourists comes to Austria because he wants to have a fantastic


time he wants to be nature wants to experience our beautiful country so that is what what they want they don't come primarily to either to get into quarantine you know or to get or to infect others so I think that if we have if we make sure that we get what Michael has promised to deliver which is a very usable very performing app that helps them control I think that everybody will


happily download it and make sure that that he or she is neither risk to others but also that others are not a risk for him or her and I think you know that is what we feel is very important and clearly one can it's our duty to make them aware I think that Michael was mentioning the fact that we need perhaps to to have a more stronger communication campaign at least we need to make them


aware that there is a stop Karuna app you know if they don't know about it it's difficult they come from countries where the the app is not yet there so how should they know that we have an app I think that we should make them aware we should invite them to use it I think that's that's quite important and and then make sure that people really take their individual responsibility


seriously so are you also working on measures to communicate the availability of the app to tourists coming to Austria not not directly I mean this is something that red cross has on top of the mind and and is working on what we are looking at is looking at the processes and looking at the prerequisites for TTT for tracking testing tracing so that that is in that is


really available in the right way in Austria so that when people come in they can experience experience a really very safe country if we're not one of the safest countries in Europe I would like to touch upon something that Michael sets in the beginning obviously Corbett 19 is causing a global crisis it's affecting nearly every country in the world so do you think it makes sense to


treat a global problem on a local basis I think it's I think you need to treat the global problem at a global and at a local level if you want to tackle it and I think that's true for most of the huge problems that we are facing not only for Corbett but also for the environmental problems we need we do not have the right governance for many of these problems because in a sense you need the


global concepts to to fight the problem but then you need really to break it down on an individual and on a local level you cannot enforce the top-down it needs to come from the bottom up and the better the concepts that are developed on a global level the more they will be taken up and as we know we live in very different types of countries and every country will have their own way of


communicating with their citizen and making sure that their citizens are made aware about what solutions are best so clearly we saw the example of China we saw the example of Singapore we see the example of Taiwan and we see the example of Austria or Italy they are totally different that we need to be mindful about what is working in our specific cultural context and political context


and I think that that's very important so yes it's it's a it's a Savola at South in German you know it's a clearly you need to work on a global level but you need us to work on a local level and are there activities to work on a europe-wide corona apps because Germany is working on one Austria already published its app are there activities going in this direction there is a lot


of activity on a European level but I think that at the moment I think that Michael can probably say more to this bilateral working bilaterally is probably one of the other routes but you know I think that we need to start somewhere and having having a working app somewhere is a good starting point okay thank you very much Tomas I would like to continue with you also focusing on a


topic that has cost for heated discussion so SEO of iron steel camasta which is one of the largest telco providers in the CEA and region and in Austria you've provided the government with anonymized data on the movement of groups and individuals in collaboration with in vain IAM which is a spinoff from the Technical University of god´s some insights on how this initiative has


contributed to the management and the containment of the current crisis well for sure thanks for the invitation once again first of all let me start with saying that when this crisis started and actually the first lockdown measures were implemented in Austria middle of March we somehow went through a similar experience as marketed because when we were discussing internally how can we sa


technology company contribute to the handling of this crisis and when we actually went into discussions with the crisis management of the Republic of Austria very soon after we got some significant media backlash where maybe some fair concerns were addressed but much of the issues raised were really based on a fundamental lack of information and when people said we cannot use big data


as a means in tackling these crisis I must say I was somehow concerned if not to say shocked to see that the to see the amount of resistance versus using facts data evidence to take valuable decisions in technique this crisis and I was shocked to see that people don't understand that not every use of data in handling these crisis does necessarily imply an infringement of fundamental


rights such as the privacy let me explain what we do in a mobile network you always need and have so-called signalling information that is the information which you need to set up for example a call of a mobile phone which you need to know to which sales site mobile site a phone has to connect itself it's about controlling the network and in the signaling traffic we


are already using an IDE called the MZ that's the international mobile subscriber identity which is in the systems attached to name of a person but in the signalling systems it's only a number of any given cell phone attached to the network we use this information and we immediately anonymize this because we attach to each of these energy numbers in a normalized hashtag


which is by the way exchanged every 24 hours so also we don't have any historical individual patterns of customers the collaborate with a spin-off of the Technical University cards called indium which have very sophisticated algorithms in using these information to get insights on the mobility of people when I say people and referring to anonymized aggregated clouds of


people's with a minimum website of 20 people or more we do not have information on the any individual movement of people and this is by the way not a use case of this information and that's another learning that people really tend to mix up the different use cases in handling this crisis but we were interested in and what we're providing to the crisis part of the


Republic of Austria is information of the kind of how how many how many people less have moved for example in the inner city of Vienna how many people have not moved beyond a parameter of 10 kilometers from their assumed and we cannot only assume because we don't have this information from the assumed whole because what we wanted to understand and what proved to be very at at least what


the crisis management tells us what proved to be very helpful to the crisis management is to understand to the extent of reduction of mobility when the lockdown measures were implemented and the extent of additional movement with every step of lifting these lockdown measures the solution is fully gdpr compliant it has been tested by external auditors even the head of the board of


the Austrian so-called attitudes behind the regulatory body taking care of the implementation and enforcement of gdpr has confirmed that the solution is gbbr compliant and we believe there is a very valuable piece of information in assessing the effectiveness of the lockdown measures now having said this I fully agree with what - Michael and Antonella said before I do believe that


especially as technology companies we do have a responsibility to provide technology and we do have a moral obligation to provide technology which helps addressing these major crisis and even if the solution we are providing would constitute an infringement of fundamental rights I really want to point out affected in all these use cases we are using technology to lessen


the impact of the infringement on fundamental rights because every day we are subject to much more material infringement of our fundamental human rights such as the right to live the right to live a healthy life the life - the right to an adequate standard of living just think about the existential threats to many businesses to many individuals which is at risk every day


we are speaking every day think about the freedom of movement which has been inhibited all across the globe significantly or just the right of peaceful assembly in the using technology in order to get back to at least more normal way of life with less infringement of fundamental rights every day and I think it's a moral obligation actually to do this and we should be


asking ourselves what we would be asked if he would not prove up I think the last sentence was cut off could you distribute that if you could not provide well if we are asked whether its moral morally defendable to use technology we also have to ask the question the other way around is it more about just morally justifiable not to use technology which we have available


to take it is crisis and I think that's one of the learnings also of this crisis not only when we talk about apps or mobility insights without technology we would not at all be in a position to handle the crisis we are handling it today think about how we would deal with the situation 10 or 20 years ago or what happened a hundred years ago in the Spanish Flu we would not even


understand the DNA of the virus today we will not be able to test it within hours we would not be able to continue working in our home offices we would not be able to educate our students and pupils at home he cetera et cetera et cetera so I understand and I take very seriously all the concerns also with regards to privacy within when we use these pieces of technology but I believe we really


need to calibrate also our approach to technology and really embrace the fact that without technology we would be in much better shape in handling this crisis but this this again brings us back to this topic of the ability to save lives but at the same time somehow infringing the freedom of choice of the population correct and that's why I believe and I think


Antonella has beautifully described the important criteria when using these these tools and first we need to be clear that we should not mix abuse cases and there is a fundamental difference between what we do when we do general assessments on the amount of mobility of large groups of persons versus personalized even if it's anonymous but still personalized contact


tracing and when we look into international examples there are other examples around of voluntary or imposed Tracking's of quarantine measures which is again another topic but I do believe that in the public debate people tend to put this all in one basket and that's an issue that's a real to be frank an education issue I don't believe that with these measures you


avail advice to do it in a top-down approach in non-voluntary approaches in turn Ella has described it because especially in these crisis in in crisis mode and we also know it from our businesses it's about changing behaviors of large masses of people and that's like a large transformation project in a company it does not work top-down you need some enforcement enforcement


measures for people who come let's say completely off track and to completely disregard all let's say all reasonable behavior but for a large amount of people you need to get buy-in in the buy-in requires trust and looking forward Trust will be extremely important in handling the crisis also when we talk about handling the economic crisis and we need more trust in


institutions not less and we will get trapped only if we consider design principles like the privacy like using anonymous thought data as long as as much as we can use it by using decentralized solutions by storing data carefully and by especially feeling on the voluntary participation of people and not on the obligation enforcement um I did a bit of research on how you


collect the data how you analyze the movements of groups of 20 plus individuals is it correct that you're solely tracking the data of mobile phones in the telecom master Network yes that's correct however and by the way this use case has been around for some time we also use this data for example to measure how many people are traveling on the train because it's also quite a challenge


because train you don't have you know it's not like on the plane where you have dedicated seating or you have physical barriers to enter the Train but as we do know our market share is in given areas and as this model has been calibrated also with external health we have at least very high confidence to calculate on the entire basis would it make sense to collaborate with the other


two telco operators in Austria to get a more granular they're granular database well we would be open to do so however I do believe that the data we are able to provide the sufficient is sufficiently concise in order to draw similar conclusions today already ok I have a bit of a another example I don't agree with the approach that was taken but if we look at what


the Israelis did in mid March of this year it became public that Prime Minister Binyamin Netanyahu authorized Israel's Internal Security Agency Shin Bet to use the location data of cellphones to help contain the coronavirus so what they did is they actually track the movements of individuals who tested positively for Kovach 19 and identified the individuals who came in touch with


these infected people and these individuals receive text messages informing them anonymously of the fact that they had been in touch with an infected person just from a technological standpoint would you be able to do this would you be able to build a system that allows us to basically cover the entire user base of the ions tilaka monster network anonymously in a safe and private method


in order to effectively have the same result as what Michael and his team at Accenture had created with the corona no clearly not based on the technology we using when we do the mobility insights we are using more or less triangulation out of the mobile network we are not using for example any GPS data from the cell phones and with that we can see if people move let's say from one community


to to another one or if they move from Vienna to Lynch or whatever but we cannot sufficiently assess whether I would be sitting in the Train next to you or you are sitting at the beginning of the Train and then actually also where we are not even interested in the information and we don't have to technologically I set access to that information I think that's more a topic


of the very front okay but combining your data with GPS and Wi-Fi data would that be an option and perhaps with with Michael's app for us it's not an option because I do believe that the app is a very smart approach I do have the upon myself on myself I agree with them Antonella and and Michael I think it's quite a long way to go in order to have it let's say fully


functional and fully performing but we also have to consider that I think in Austria we have the advantage of having head very early start we have the advantage of having from my non expert view the right setup from the beginning with a decentralized approach with an voluntary approach with a very transparent approach based on open source so I think we are going in the


right direction and I have quite some confidence that at the end of the day it will help us tackling this pandemic and we shouldn't forget this pandemic from all what we hear and know will be around for months if not years and we have now to prepare in order to handle what comes in months and years right so we are not at the end of the tunnel I think we are at the beginning of the tunnel and we


have an early start in using technology I think the app and the use case of Traken traces one thing and what we can do in the network in assessing the amount of mobility is another use case but we should mix it - thanks Tomas a question to all of you what are the international kind of best practices that you've seen when it comes to using technology in order to tackle the


library if you want I can start because this is what we have been looking into a lot I think it depends you know clearly you can find a lot of interesting examples particularly a shoe where they had already the experience the previous Czar's experience and that has has sharpened their view on how to manage pandemics in general and also sharpen the view on how to make the best use of


of technology so I think that you know what we saw in South Korea they had both and I think that Thomas was also mentioning it we speaking always of apps but there are so many different apps you know there are symptoms checking apps which are very broadly used in Korea symptom checking apps are very interesting because they are a first line sort of defense if you want or a


first line of information that everyone can take before going into a system that is certainly easily burdened of going into fully testing and tracking and tracing so symptom tracking apps are broadly used in Konya and I think that is something that is super useful then they have tracking and tracing Epson use but mainly also parent time surveillance apps which are used also not only in


Korea but also used in Singapore and also used in Poland you know that we have quite exciting interesting examples you mentioned the Israeli example I think that it's we have to see Israel is a country which is on constant high alert and I think this being constant high alert allows allows to interact with the population in a very different way you know so we are not in a constant


high alert as we have seen we need to create the sense of alert so that people can act you know responsibly and so what is working there there are very interesting tools there but they would not work here so that is the other thing what we have been also looking at is the potential use of immunity of the immunity apps which allow you to fully capture your testing process and the


tests result on your app so that you have it easily usable I think this would be a very interesting solution particularly on a European level or on a global level but part you know a European level because then you can really travel and make sure that you you know you minimize the risk so that is also something that that we've seen and then they're clearly your traffic


management apps broadly speaking I mean anything which allows to book things upfront viewing the menus in restaurants without having physical menus be presented I think it's something that is being discussed anything which is sort of touch free which are touch free solutions touch free solutions beyond you're attaching your own phone I think that is something that are being used


and I think that if we look around we have some countries which have been very active in working with that Australia has introduced a very good tracking and tracing app Singapore as use a combination of these apps so these are the countries but with that we look into but then we need to sort of factor it in that it should be used in Europe okay would you like to add anything


Tomas or Michael I think there was already a very comprehensive summary of technologies available by Antonella but a really one would like to reiterate is that I think actually with the two solutions used in Austria you have mentioned your Italy at least leading one of the leaders in Europe which the stop Corona app with I think as I said earlier a which was taking technology as


well as in timing or those on our side I must say after the first I should have put his surprise in the public attention our initiative has a stake we got a lot of international requests actually also from other operators who by the way have similar solutions in place but many of them do not prove a creators hours to us and here and by the way I was also invited to a court


with a commissioner Kato with the ambition to have similar use cases on European level because I agree with what was said before interoperability in all what we do will be key because especially in Europe with our small structures we need to open up the borders as soon as possible and if technology can help you it's for sure - so I think we in this respect we are


also leading to take you within Europe in let me just add one thing thanks Thomas also for the acknowledgments that we are leading in Europe I think helps in speaking more general is health is one of the most under penetrated areas for the use of technology for good so I truly hope that we see a push towards the use of technology in health chain in in a more general way such as using


telemedicine for to give one example and and for a couple of other use cases where we could use technology in a far better way than we do today based on say resistance in society where technology really could make a difference and that's what at least I hope that we can catch up on that and help to improve the overall situation of the health systems with technology but


may I just build on something that told us I said before I think the critical thing is really making sure that the population appreciates truly the value of technology in liberating us in making us freer in giving us our individual freedom of movement freedom of speech freedom of everything you know and the technology can help absolutely but we need to probably invest significantly


more educating people because there is a lot of mixing up things you know and in general suspiciousness big suspiciousness towards certain certain you know solutions that are very very important for for the individuals and for the society for the collective solution of this of the problems and i think that that's where we we jointly need to need to act and make sure that


particularly you know the younger generations are totally you know just have a full understanding of where the risks are and where the risks are not and that they develop a good sense of trust and mistrust and not just you know just ad averaged mistrust about certain people and total trust towards others and i think and going down to naivete yeah and i think that's what we need to


be careful about okay well i think we're we're solely coming to an end i would really like to thank the three of you for your great contributions internet i think it's great that you're taking such a helicopter perspective and tackling so many topics at the same time also thanks for for clarifying the the data protection and the data privacy aspects that i think are very important to the


Transcriber: asma youssef Reviewer: Denise RQ What do you think is the key to achieve our goals, our success? Some people suggest things like hard work, focus, persistence. But research shows these are all by-products of something else, something much more powerful that we can all develop. It is this very special something that is really critical to success,

The Power of belief -- mindset and success | Eduardo Briceno | TEDxManhattanBeach


and is what I am here to discuss with you today. Someone who has achieved great success is Josh Waitzkin, a chess international master and the subject of the movie "Searching for Bobby Fischer". Nobody has won all the national chess championships that Josh has. But even more impressive, when he turned 21, he took on the challenge of mastering something completely new


and very different from chess: martial arts. He realized that he had learned how to grow and succeed, and he could apply that understanding to other domains. And so, he devoted himself relentlessly to tai chi chuan. And after lots of hard work, many failures, and some broken joints, he became a great martial artist, and he won two world championships. Now he is off to jiu-jitsu.


So what does Josh say is the greatest thing ever happened to him? Believe it or not, he says, "Losing my first national chess championship, because it helped me avoid many of the psychological traps." The key trap that Josh avoided was believing that he was special, that he was smarter than other people, and that he didn't have to work hard. He could have thought of himself as a prodigy,


but he doesn't think that he has extraordinary intelligence. He says, "The moment we believe that success is determined by an ingrained level of ability, we will be brittle in the face of adversity." Josh often quotes Stanford Professor Carol Dweck who discovered that some people see intelligence or abilities as fixed what is called a fixed mindset, while other people see them as Josh does,


as qualities that can be developed; a growth mindset. More important, Dr. Dweck discovered that these two different mindsets lead to very different behaviors and results. In a study she did with Dr. Lisa Blackwell, several hundreds seventh graders were surveyed to determine which mindset each student had, and then they were tracked for two years. Results showed that the students with a growth mindset,


those who thought they could change their own intelligence increased their grades over time. While those with a fixed mindset did not. You can see the trend, the gap in performance just widens and widens over time. The difference between these two groups: a different perspective on intelligence. Other studies have shown similar effects for our mindset about other abilities


like problem solving, playing sports, managing people, or anything else you'd like, dancing La Macarena. The key to success is not simply effort, or focus, or resilience, but it is the growth mindset that creates them, the mindset itself is critical. Research shows that when we directly try to build grit or persistence, it's not nearly as effective as addressing the mindset that underlies them.


How many of us think of ourselves as not math people, or creative, or sociable, or athletic, or conversely, that we are naturals? If we are to fulfill our potential, we have to start thinking differently. We have to realize we are not chained to our current capabilities. Neuroscience shows the brain is very malleable. And we can change our own ability to think and to perform.


In fact, many of the most accomplished people of our era were thought of, by experts, to have no future. People like Charles Darwin, Lucille Ball, Marcel Proust, and many others. But they, along with all great achievers from Mozart to Einstein, built their abilities. But the key insight I would like you to walk away with today is that when we realize that, when we realize we can change our own abilities,


when we have a growth mindset, we bring our game to new levels. So how does a growth mindset do that? It turns out that there are physiological manifestations to mindset. Brain scans show that for people with a fixed mindset, the brain becomes most active when receiving information about how the person performed such as a grade or a score. But for people with a growth mindset, the brain becomes most active


when receiving information about what they could do better next time. In other words, people with a fixed mindset worry the most about how they are judged, while those with a growth mindset focus the most on learning. There are other consequences of mindset: people with a fixed mindset see effort as a bad thing, something that only people with low capabilities need,


while those with a growth mindset see effort as what makes us smart, as the way to grow. And when they hit a set back or a failure, people with a fixed mindset tend to conclude that they are incapable. So to protect their ego, they lose interest or withdraw. We observe that as lack of motivation. But behind it is a fixed mindset, whereas people with a growth mindset


understand that set backs are part of growth. So when they hit one, they find a way around it. Like Josh Waitzkin did when he lost in chess or in martial arts. Research clearly shows these effects of mindset. In one study Dr. Dweck did with Dr. Claudia Mueller, they had children do a set of puzzles, and then they praised the kids. To some of the kids, they said,


"Wow, that's a really good score, you must be smart at this." That's fixed mindset praise because it portrays intelligence or abilities as a fixed quality. To other kids they said, "Wow, that's a really good score, you must have tried really hard." That's growth mindset praise because it focuses on the process. Then, they asked the kids, "OK, what kind of puzzle would you like to do next? An easy one or a hard one?"


The majority of the kids who received the fixed mindset praise chose to do the easy puzzle. While the great majority of those who received the growth mindset praise chose to do challenge themselves. Then the researchers gave a hard puzzle to all of the kids because they were interested in seeing what confronting difficulty would do to their performance. Look at what happened when the kids later went back


to the set of easier problems that they started with. The kids who received the fixed mindset praise did significantly worse than they had originally, while those who received a growth mindset praise did better. And to top it off, at they very end, kids were asked to report their scores; and the kids who received the fixed mindset praise lied about their scores over three times more often


than those who received the growth mindset praise. They did not have another way to cope with their failure. The difference between these two groups: one short little sentence. How often do we praise kids for being smart or for being great at something? We have been told that this will raise their self-esteem. But instead, it puts them in a fixed mindset. They become afraid of challenges,


and they lose confidence when things hit hard. As Josh Waitzkin says, "It is incredibly important for parents to make their feedback process related as oppose to praising or criticizing talent. If we win because we are winners, then when we lose, it must make us losers." These studies show not only the mechanisms by which mindset affects performance, but they also show something else that is very important:


they show that we can change mindsets, and that's important, because most of us have fixed mindsets about something. Another study that showed that we can change mindsets is one in which Dweck and Blackwell did a workshop with seventh graders to instill a growth mindset in them. As a result of the workshop, the students gained more interest in learning, and they worked harder;


and as a result of that, their grades improved. Other studies have shown that when we teach a growth mindset, not only that it improves achievements for students as a whole but it also narrows the achievement gap, because the effects are most pronounced for the students who face negative stereotypes such as minority students, and girls in math. I have spoken mostly about children, but mindsets affects all of us.


In our work places, managers with fixed mindsets don't welcome feedback as much, and they don't mentor employees as much. And employees with growth mindsets about specific skills like negotiations become far better at those skills than people with fixed views. Mindsets can even help us solve big social issues. A recent study showed that when we expose Israelis and Palestinians


to the idea that groups can change, they increase their attitudes towards towards one another, they improve them. and they enhance their willingness to compromise and to work for peace. We also see the effects of mindsets on relationships, sports, health. How is it possible that as a society, we are not asking schools to develop a growth mindset in children?


Our myopic efforts to teach them facts, concepts, and even critical critical thinking skills is likely to fail, if we don't also deliberately teach them the essential beliefs that will allow them to succeed not only in school but also beyond. There is a lot that we can do to change mindsets, but here are three things that any of us can do to instill a growth mindset


in ourselves and in those around us. First, recognize that the growth mindset is not only beneficial but it is also supported by science. Neuroscience shows that the brain changes and becomes more capable when we work hard to improve ourselves. Second, learn and teach others about how to develop our abilities. Learn about deliberate practice and what makes for effective effort.


When we understand how to develop our abilities, we strengthen our conviction that we are in charge of them. And third, listen for your fixed mindset voice, and when you hear it, talk back with a growth mindset voice. If you hear, "I can't do it," add, "Yet." My request to you today is that you share this knowledge about the growth mindset with your family, friends, and schools


but steel bath with a temperature of 1,500 degrees sparks fly is a diesel engine is about to be born a veritable Colossus the huge engine will soon power a modern ship it will have to withstand enormous pressure and extremely high temperatures for many years manufacturing such a giant calls for high tech and precision one of the most powerful high speed diesel engines in the world it is part

Exceptional Engineering | Mega Diesel Engine | Free Documentary


of the MTU concerned series 8000 made in Germany the engines are produced in philosophical on lake constance malte from here the high speed ferry Jean de la Villette transports passengers as well as cars and other goods to and from Italy the catamaran ferry is the most modern of its kind in the Mediterranean and it is powered by four series 8000 engines from MTU


three levels below deck the crew start up the ferries for mega diesel engines at idling speed the men check that everything is technically in order this takes ten minutes and is a must before every voyage the team then head back up because down here things are about to get very loud and above all extremely hot Dejan de la Villette leaves Malta bound for the Italian island of Sicily 120


kilometres away [Music] weather permitting the 52 thousand horsepower ferry takes less than two hours for the crossing on the open sea the 1500 ton catamaran can reach a speed of up to 42 knots that's 75 kilometers an hour this extreme performance is achieved through its 4 MTU series 8000 diesel engines [Music] MTU series 8000 consists of 20 cylinder common-rail diesel engines each unit is


7 meters long 2 metres wide and three and a half meters high roughly the same size as a steam locomotive it also weighs as much around 48 tons the 20 cylinders have a capacity of 350 liters and produced thirteen thousand six hundred horsepower fuel consumption is 2,000 liters an hour the core element of the engine and its biggest component is the huge crankcase


[Music] like all the engines components the crankcase also comes from Germany this foundry and phone bag in Bavaria is the birthplace of the mega diesel engine and a location with a long tradition a small smithy existed here way back in the 15th century so hot iron has been molded in phone bag for nearly 600 years today the foundries three smelting furnaces are operating at full speed to


cast a series 8000 crankcase for 10 hours now the steel workers have been feeding the voracious furnaces different materials the materials we need for the series 8000 are steel scrap pig iron and deep drawn sheet metal we also need electrode graphite and silicon carbide the composition is calculated by our superiors in this case by the engineers in our production planning department


casting a crankcase calls for 16 tons of material hot hard work for the smelters who have to keep a constant eye on the temperature only when the molten metal has reached a temperature of 1500 degrees is it ready to be transported to the mold here we have a measuring sleeve made of press board inserted at the front here is a thermal element it's attached to a measuring probe and used


to measure the temperature of the melt every steelworks has its own recipe time and again the smelters add this or that material the better the composition of the smelt the harder and more durable the crankcase will be from time to time the smelt is checked in a modern foundry a sample of the molten metal is poured into a crucible containing a small measuring sleeve


which in a matter of seconds transmits the temperature profile to a computer in the office the smelt has the perfect composition when the sample cools down in a certain way and then heats up again the enormous heat is no longer generated with fire but with electricity the principle is similar to the way an induction cooker functions in a domestic kitchen the big


difference is that the three electric induction furnaces in the foundry have the power of five thousand microwave ovens [Music] therefore megawatt have heated the molten metal to a temperature of over 1500 degrees 200 meters away the mold is already waiting speed is now essential the steel workers transfer the molten mass the final ingredient magnesium is added via chutes the bubbling sound you


can hear stems partly from the magnesium at temperatures of over 1500 degrees magnesium vaporizes much faster and that's what causes the bubbling sound the magnesium vapour flows through the molten metal like carbon dioxide through mineral water this changes the molecular lattice structure of the steel and will make the crankcase slightly elastic [Music] the 19 tons of molten mass now flow into


two huge casting ladles there would be no point in having more than two because the crankcase mold has only two intake funnels [Music] this is what the various parts of a crankcase mold look like these two discourse consist of resin soaked quartz and which after setting has become rock-hard ten of these cores and sequence comprised the mold of a series 8000 crankcase prior to casting each


template is given a coating which has a horrific smell to it the coating prevents the sand from mixing with the steel during casting the molten steel flows into the mold via this channel it passes through the filter chamber with its ceramic filter and enters the mold cavity via this feed channel and then spreads throughout the entire mold but before that the ten disk cores are


placed in a casting box the cavities are filled with special sand without this sand parts of the mold would fly off during casting it's a job which calls for a lot of experience any mistake could render the mold useless all this takes place days before the actual casting which also demands total precision the clock is ticking the molten mass is cooling by the minute


so the smelters have to check its temperature time and again on no account must have dropped below 1,400 degrees then the mass would no longer be suitable for casting a huge overhead gantry transports the cauldrons to the mold the big moment is close the birth of a mega diesel engine the two casting ladles are positioned over the to filling funnels from now on


everything will have to take place with absolute synchronicity the head smelter starts the countdown three two one go in a fascinating spectacle the molten metal flows into the two funnels for the moment the two plugs are still in place because the mass first has to settle once again the command to remove the two plugs is given by the head smelter now pull the mass can now flow in it takes


70 seconds for the 16 tons of molten metal to flood the mold and fill every cavity completely the head smelter closely monitors the entire process giving instructions to his colleagues controlling the casting ladles a little bit faster faster although speed is of the essence all movements have to take place simultaneously otherwise swirls could form in the funnels


now after a good minute the job is done within a few hours the metal cast in the mold will cool by several hundred degrees but it will be two weeks before the men can peel the crankcase from its mold only then will it be hard and elastic enough and extremely durable LaShonda la Valette is surging through the Mediterranean at a rate of over 40 knots the high speed ferry is heading


for the Sicilian port of Port Salut it's not a propeller that the four mega diesel engines in its hull are driving but water jet power units which function on the recoil principle water is sucked in under the ship and then expelled again with tremendous force the engine on this vessel pumps out 9.1 megawatts of power at eleven hundred and fifty rpm the the aggregate power is


36.4 megawatts so in actual fact losing an engine will not affect the the vessel drastically the immense power from the diesel engines is a big help especially in berthing the 1500 ton ferry the ship is highly maneuverable and can be steered easily even in a confined space the captain slowly brings the 107 meter long jean de la Villette against the key wall in sicily


in just eight hours time the catamaran will be heading back to Malta that's not a long time because today a team of mechanics specialists in marine engines has come on board one of the four mega diesel engines needs two new cylinders and the old ones require maintenance the men have to dismantle the diesel engine and replace the cylinders since a stay in Port is


very expensive the specialists need to get to work straight away this means heading down to levels awaiting the men at a temperature of 50 degrees in the engine room are a booming auxiliary power unit and the 48 ton diesel engine they all know that this means a lot of work under time pressure brakes are out of the question back at the foundry and phone back two


weeks have now passed that is how long the steel block has taken to cool down completely the heavy and in so far as steel permits elastic crankcase for the mega diesel engine is about to see daylight for the first time with the help of the overhead gantry the 16 ton Colossus is lifted out of the casting pit this causes the courts and cocoon to crumble exposing


the brand-new series 8000 crankcase what we now see here is the down sprue and the path taken by the steel into the mold the first task now falls to a welder who has to sever the two down sprues the gas jet slowly cuts its way through the tubes which are as thick as tank Armour other superfluous parts are also still attached to the seven meter long cast body they were needed for the casting


process now they too are cut off [Music] there's another four to higher up and to lower down then we'll tear everything down and it will remain standing in the middle the experienced welder burns his way along the crankcase bit by bit after an hour the block is fully exposed the casting channel can be removed but the material that has been cut off is by no means scrap it will be needed


for the next melt the overhead gantry then comes into action again it lifts the block to the next station a huge mechanical vibrator the deafeningly loud vibrations cause any remaining quartz sand to fall off it too will be recycled after being cleaned the sand will be used to produce the next casting three minutes later the mega diesel crankcase is roughly clean


it's next stop is the shot blasting chamber where the crankcase will be bombarded with a storm of tiny steel pellets [Music] these are the steel pellets they're made of ordinary steel and have a maximum diameter of 2.5 millimeters so we can roughly estimate what the surface will look like afterwards and how clean it will be millions of the steel pellets are fired


to the chamber at a speed of 200 kilometers an hour this not only cleans the surface of the component the bombardment makes the steel harder and more corrosion resistant the process takes an hour then the doors are opened and with the help of a crane the men remove a perfectly cleaned engine block from the shot blasting chamber the razor-sharp casting noses also have


to be cut off the crankcase can then leave its birthplace for transportation to Lake Constance Assembly of the mega engines takes place at the NTU plant in fleet lease often the firm specializes in large high speed diesel engines ships submarines military vehicles and locomotives worldwide are powered by MTU systems [Music] a series 8000 naval engine has to pass


through six assembly stations twenty-five of these mega diesel engines leave the plant every year prior to assembly the raw part is milled the Colossus is machined to the right dimensions in several stages losing up to a ton of material in the process this takes several days engines of this size are machined with extreme precision the tolerances to be adhere to are so


minut that they can no longer be perceived with the naked eye Lonnegan now we're talking about an accuracy of three or four hundredths of a millimeter such dimensions pose quite a challenge in other words a component the size of a small bus must not deviate from the ideal by one hundredth of the width of a human hair to check this the Colossus is placed on Europe's biggest


measuring table Engineers measure every opening every drilled hole indeed every square millimeter to ensure that no disaster can occur when the engine is in operation after two weeks the crankcase is ready now main assembly can get underway over the next five weeks these 35 fitters will turn the barre crankcase into an extra extra-large mega diesel engine the overhead gantry transports


the 10-ton parts of the rotary station where it is positioned with millimeter accuracy during this process the entire area is sealed off little towards you now got it it's in [Music] first of all the crankcase is given a serial number in the past this had to be hammered in with effort now a special tool performs the task mechanically in seconds the green light for assembly is


about to be given by Foreman : ooh huh he is in charge of the workshop but first the fitters check the surfaces and the bearings once again large axis will illuminate the entire crankcase starting with the inlets and then continue with the main oil channels the two fitters job is to detect any contamination tiny burrs or metal splinters in one of the channels could cause serious problems


later the main oil channel here has to remain free of dirt dust and splinters which could of course destroy the engine then it is the turn of the camshaft components when it is fully assembled the shaft will be 6 meters long and weigh 400 kilograms to ensure that everything fits together the mechanics work with liquid nitrogen they sink dozens of small guide pins in a nitrogen


bath with a temperature of minus 198 degrees Celsius the liquid gas chills the metal pins and makes them contract the super-cold guide pins can be tapped into the flange of the camshaft segment with ease as they heat up they expand to give a really firm fit guide connections have to be greased and running surfaces oiled the men then push the camshaft into the 6 metre long channel section by


section making sure nothing gets tilted a bit lower okay the next babies like then you'll see it coming down a bit more the initial phase is completed the guide neck is now in the channel the men slowly push it in further once again this is precision work there is ZERO room for error should something tilt the engine would be blocked up again optimal just hold it like that when the three


segments have been bolted together the two fitters carefully push the unwieldy component through the engine the camshaft is made of surface hardened steel and will not be replaced throughout the entire life of the engine after two days the work at station 1 is completed one of the 25 mega diesel engines manufactured here each year is transported to the next station by


overhead gantry the rotary station is even bigger than the first station here fitters will turn and wheel the Colossus several times and even turn it upside down the crankcase is the biggest component of the mega diesel engine now the second biggest is added the gigantic crankshaft six meters long and weighing six thousand kilograms it is the crucial element at the heart


of the engine [Music] operating at full speed the heavy crankshaft will rotate at a staggering twenty revolutions per second [Music] for installation of the crankshaft the engine has to be turned upside down the fitters wheel the cage suspended from the overhead gantry the huge chef now moves towards the crankcase once again every millimeter counts very slowly six tons of high-grade metal are


approaching the interior of the engine if the component were to slough the irreparable damage would be caused [Music] after 20 minutes the difficult task is completed the fitters now turn the huge frame a few more degrees to gain better access to the engines inlets over the next few hours they will install 20 of these cylinder Pistons later the entire combustion process will take place in


the power units as they are known each power unit has a capacity of 17.5 litres and is basically an independent single cylinder engine the workshop also contains the pre assembly site for the power units before assembly of the cylinders can get underway the huge connecting rods have to be measured this includes measuring the bearing shells because if the bearing


shells are too small this could damage the crankshaft all the measurements are recorded exactly to ensure precise positioning then the war can begin the fitters first prepare the Pistons each of which has a diameter of 27 centimeters weighing 100 kilograms each con rod can only be moved with a crane the con rod is carefully lowered into the piston the retaining bolt is


then slid into place it takes a quarter of an hour to install the first of 20 Pistons next the focus is on the complex cylinder head on the rotary table the fitter inserts four bolts and secures the cylinder liner with another 24 bolts to guarantee precision they are tightened automatically by a machine the process is fully automated and monitored to ensure that I haven't forgotten the


bolt and that every bolt has the right torque the computer determines the next operation and records every action by the fitter now the piston together with the con rod is introduced carefully and slowly into the cylinder a single error would cause considerable damage later 20 of these power units will make the 16 crankshaft rotate at a speed of 1,150 revolutions a


minute a final components and assembly will be complete this is part of the exhaust the power unit weighs 750 kilograms in future it will have to withstand a great deal the ignition phase forces the piston downwards turning vertical motion into the circular motion of the crankshaft the crankcase is turned once more and again the overhead gantry comes into action as it brings up the power unit


[Music] the men slowly lower the cylinder unit into the engine in its interior the connecting rod grips the crankshaft with millimeter accuracy the team installed 20 power units in one day the con rods are provisionally secured with white dummies because the engine will be turned once again and nothing must be allowed to shift its position the fitters reposition the engine block


in order to install the 20 bearing shells in its underside the shell weighs 25 kilograms and is pushed on to the bolts of a con rod later it is this area that will have to withstand the greatest forces the up and down motion of the piston causes the crank shaft to rotate 20 times a second the forces involved are extreme and all the components will have to withstand


them for many years a special procedure is followed to secure the con rod the men equipped the bolt with a hydraulic clamping cylinder they then attached oil pressure lines [Music] the hydraulic system forces the bolt apart at a pressure of 1,600 bar now the nut can be screwed on and the pressure reduced again the threads of bolt and nut are pulled together in a


solid link installation of the power units is now finished along with the preliminary work on the fuel lines and the exhaust and cooling systems the gantry transports the engine block on to station 3 where a two-man team focus on the gear train here it is about to be sealed with a cover but beforehand the main coat the edges with a special sealing compound [Music]


weighing 200 kilograms the cover is now attached it is secured with dozens of bolts in the years ahead the gear train will not be opened again depending on its application the mega diesel engine will have a service life of up to 35 years only then will maintenance be required back to the Mediterranean and put Salah Harbor on Sicily where the high speed ferry jean de la Villette is


birthed three levels below deck a team is working against the clock the men have eight hours in which to replace two power units from one of the four diesel engines the maintenance work can only be carried out by specialists while the covering is being removed at the top one of the men crawls under the still warm engine to drain the cooling liquid he then opens the heavy covers to gain


access to the interior of the engine above him two mechanics are loosening the bolts on the cylinder unit so far everything is going according to plan a crucial moment the power unit has to be taken out the fitter has to open the eye of the connecting rod which encloses the crankshaft the nuts can only be loosened with a hydraulic bolt tensioning cylinder now pressure of up


to 1,600 bars applied through hoses to ensure that all the bolts are loosened the four main bolts on the upper side of the power unit are also loosened with the help of the hydraulic system finally the power unit is free using nothing more than a pulley and their own strength the men maneuver the power unit out of the crankcase centimeter by centimeter 750 kilograms make their way


upwards working at a temperature of 50 degrees Celsius the men now all the unit through the engine room until it is under the service hatch where the hook from the small truck mounted crane on deck is already waiting after three hours the first power unit is taken aloft care is still vital because the component is by no means scrapped it will be given a complete overhaul and at


some time or other be installed in another series 8000 mega diesel engine today the part is first placed in a special transport frame but why did it actually need to be replaced it is suspected that because of minut cracks in the cylinder head cooling water was able to get into the combustion chamber but only examination under a microscope will provide exact


information in flicks half and on lake constance mt you technicians have made good progress the mega diesel engine is now being fitted with a turbocharger group a complex component the supercharger group gives the engine it's impressive height of 3 meters 50 comprised of several thousand separate parts the turbochargers are responsible for a huge increase in the performance


of the marine diesel engine every year fitter Tobias Haider assembles 25 such turbochargers for series 8000 engines the purpose of the turbocharger is to increase the oxygen content of the combustion chamber this is the intake for the exhaust gases here we have the blade wheel which can rotate here exhaust gases flow out again and on this side drive the blade wheel this is where


the air is then drawn in here it is compressed and here it enters the intercooler 40,000 revs per minute and the boost pressure the four and a half bar compared with two and a half to 3 bar for a car tire lyta needs about a week to assemble the two-ton turbocharger today he's sealing the housing airtight to prevent any toxic exhaust fumes getting into the machine room later


the turbocharger group is then transported by overhead gantry to station five now the turbocharger can be attached to the engine block two men connect apart with the exhaust circuit the series 8000 mega diesel engine now weighs around 40 tons the clutches then flange mounted the fitters maneuver the huge part to the end of the crankshaft and once again they need special tools the 15 this is


the cylinder with which the clutch flange will later be pushed to the back [Music] here to the components have to expand hoses ensure a high oil pressure of 1500 bar [Music] the flange expands and little by little the clutch moves on to the shaft two minutes later the men release the pressure again the connection is solid the second part of the clutch is now


bolted on above all the giant torque damper is designed to prevent the clutch breaking off when the mega diesel engine enters operation once again in fleet lease often it's a case of ready for takeoff then the overhead gantry transports the massive engine through the workshop it will now be lowered on to the mega diesel engines oil pan the 40-ton Colossus is placed securely on six


stilts the oil pan is filled with two-thirds of maximum capacity that's 1600 liters which is the volume pumped through the engine twice every minute with total precision a hydraulic hoist raises the sump to be bolted on to more in the middle should be fine the fleet leaks off an engine plant all the tasks for the day have been completed but on Sicily there is still a


lot to be done the high speed ferry jean de la Villette is still birthed at the key side the maintenance team on board the catamaran have got a tough job in their hands to power units need to be replaced and the men now have only six hours to install them the replacement unit which has been given a complete overhaul is lowered into the machine room through the


service hatch the seven-man team are all specialists who have been specifically trained for this engine series slowly they lower the 750 kilogram part in the crankcase tough manual work with the help of a pulley and the confines of the machine room there is no space for an automatic ceiling crane the con rod cover then makes its descent since it weighs only 25 kilograms it is no problem for the


mechanics skillful hands easily slip the cover on to the threaded bolts to nuts and the job is done the team don't talk much each man knows what he has to do only in this way will they be able to meet their deadline the next step is to get the injector ready it has to be cleaned greased and have new seals fitted on the cylinder head the tolerance of the rocker arms and the


valves also has to be reset each feeler gauge has a specific thickness enabling the mechanic to adjust the valve clearance exactly [Music] the cover is put on and the men have reached the halfway stage the first of the two power units has been replaced the teams still have four hours for the repeat procedure removing the cylinder unit lifting it on deck with the crane


and packing it safely for transport the new power unit is then lowered into the machine room installed bolted greased and adjusted all the men can do now is hope that the engine will spring to life immediately the fitters are still working but the ship's crew are already closing the maintenance hatch the first trucks will soon be driven on board everything is


still going to plan but will the overhauled engines start up [Music] at MTU on lake constance the new engine block is again being transported by crane through the workshop in the meantime the mega diesel engine has become even heavier just before its final assembly station it now weighs nearly 48 tons at station six the fitters focus on the electronic system


and on pumps and lines of all kinds the series 8,000 marine diesel engine is a complex structure of circulation lines for fuel oil air and exhaust fumes several hundred meters of copper pipes tubes cables and hoses have been installed in and on the engine two thousand liters of diesel fuel per hour and hundreds of cubic meters of air in exhaust gases along with three thousand


liters of oil every minute will flow through the engine all the lines are special home and custom-made products like the pipe for the sea water cooling system the fitter assembles the separate elements of the coiled pipe in a gauge anything that's slightly out is ground to size so that it fits with millimeter precision [Music] this is I this site needs to fit now it


fits first of all a welder joins the various sections loosely together they're made of a very special material it's a cute print achill ferrous alloy the ship's engine is exposed to salt water but that can't affect this pipe welding curved sections while the workpiece is turning is a big challenge for any welder the seam has to be absolutely watertight if any sea water


got into the engine it would destroy it the final pipe for the engine block is now ready it has been a long road over the last five weeks around 20,000 parts have been attached to the crankcase the result is an extra-large marine diesel engine made in Germany once again the team of 35 fitters has done a great job but one thing is still missing the test run no engine leaves


the plant without having been tested there are 46 test benches here and our mega diesel engine from series 8000 is placed on the biggest we start up the engine with an air starter that operates with 40 bar it drives the flywheel which causes the engine to start up before it started immortal finally the big moment comes the mega diesel engine springs to life for the first time at the control


console hold on Luthor and a colleague increased the speed the engine's performance is measured with the help of a water break attached to its transmission the water break has a paddle wheel which rotates in the water creating an artificial resistance [Music] after half an hour it is clear that the engine has passed the test it functions flawlessly in the hull of the Jean de la Villette


ferry still birthed in Sicily another diesel engine of the same type still has to pass its test a team of fitters had just eight hours in which to replace the heart of the engine the two power units with cars and trucks now queued up in front of the ferries loading ramp the engine just has to start up otherwise well that doesn't bear thinking about no way but in fact the engine won't start so


the fitters have to check all the lines and try again [Applause] success the engine is running again and to the ears of the fitters the deafening noise sounds like music the pitstop has taken 8 hours and cost thousands of euros but the high speed ferry is now ready once again to make the crossing to Malta the ship's engineer just has to give the green light then the team of


fitters can call it a day the diesel engine can now look forward to a long service life these engines run virtually forever and ever under typical conditions we're talking about 70 mm to operating hours after that the engines are taken out and checked for wear and if everything is okay they are reassembled and put back into service it's already dark when the Jean de la


Villette reaches malta its engine is working perfectly after performing a final skillful turn in the narrow Basin the captain reverses the ship alongside the key [Music] the high-speed catamaran will again be able to cross the Mediterranean three times a day taking cars and trucks boots and tourists for Malta to Sicily and back in record time and reliably thanks


to four mega diesel engines in its hull power made in Germany [Music] by lake constance the brand new engine has passed its test with flying colors now the 7 meter long Colossus is heading for the wash unit the biggest of its kind far and wide you have molecules every large engine is washed here on average the procedure takes five hours at a temperature of 70


degrees the engine is washed with the detergent and then dried for paint spraying it's a really tough job clad in a heavy protective suit the man with the high-pressure cleaner has to cope with heat noise and damp after five hours the engine is spotless above all it is free from grease essential if it is to be sprayed later with a special type of paint the roughly one thousand cubic meters of


water that are used will be treated and recycled [Music] prior to paint spraying parts of the engine are masked the sensitive cables and pipes must be kept free of the paint which could change their thermal and electrical properties finally the engine has given its coat this too is a process that takes time the Motown big slice we apply two coats first a primer then it's left to dry for


about four hours then we apply a thick coat which also takes about four hours to dry it's a lot of work for the two paint sprayers who go through 200 leaders of paints including drying time the mega diesel engines spend 16 hours in the cabin now it is ready the colossus took five weeks to manufacture and will power a vessel for several years the series 8000 mega diesel engine has a capacity of 350


liters and an output of thirteen thousand six hundred horsepower total cost the lower end of a scale between 1 and 10 million euros well packed the engine is ready for delivery worldwide for up to 35 years it will operate maintenance-free as a marine diesel engine or as an emergency generator in a nuclear power station or an industrial facility manufacturing an extra large


well active learning is the idea that students to really learn something to really understand something have to be actively involved and that just sitting passively and listening to a lecture really doesn't help students develop the higher order cognitive processes that they need to really really understand something so you can listen to something you can watch a movie you can watch TV

Active Learning Overview


and you can generally get the plot but if you're asked to to recall specific details or to to even explain a particular nuance associated with the TV show or movie you can't really do it and that's what happens often in the lecture is that students will sit in the lecture though write down what's being said but they're not really engaged with the material so active learning is this idea

Active Learning Overview


of people say minds on always hands-on sometimes those students have to to be actively with their mind thinking about the material applying what's being said and given opportunities within the lecture to apply what's being taught or what's being the topic at hand and then active learning strictly speaking means that you just you're just one a particular individual

Active Learning Overview


is active interactive we tend to parse that a little bit and say interactive learning would mean the student has been active in his or her own mind in thinking about the material but then is also interacting with others peers or potentially the faculty member or TA in order to to further develop understanding construct meaning for for the topic I always start maybe the

Active Learning Overview


second session of the class the second class meeting is a discussion of what we know about how people learn so a discussion of the literature and the research on human cognition and learning and and if you take a constructivist point of view or constructionist point of view which really says that as I said before to understand people have to make meaning of a topic they have to

Active Learning Overview


construct their own meaning and we show the research that really shows that this is true for a higher level of processes people have to be actively engaged and there's research to show that we also show the classroom based research so Freeman's 2014 paper that was a meta-analysis of 225 other studies that showed that in courses in college-level courses with we're active

Active Learning Overview


learning was used there was a 12% decrease in the failure rate and they normalized it to all of the important factors that they should be normalized to the experience of the instructor the size of the class the type of the institution the the situation the way the position that the class is situated within the larger curriculum and and across the board it was shown that there

Active Learning Overview


was a 12% decrease on average of the failure rate and they make a comment in the paper that if that had been a clinical trial of a drug and 12% of the people on the drug head showed marked improvement they would have had to stop the trial and and give everyone the drug so this idea that there's a 12% decrease in the failure rate in courses that use active learning to me is pretty

Active Learning Overview


compelling that we should all be using active learning so whenever possible because we have an MIT our students our MIT students we use data we use the research and we we try to find really good research solid research that shows the the way people learn and then how to support that with specific Act classroom practices so many of the students haven't had the experience of being in a

Active Learning Overview


class where active learning was used so they don't really understand it so when we start to talk about it as a way of teaching they may not really get it so throughout the course from the first the first class all the way through we I try to use several different types of active learning exercises each class so the students themselves are actively engaged with the material from the first day so

Active Learning Overview


I may have them break into pairs and discuss a particular topic or identify something they didn't they didn't understand from the pre class readings and then after three minutes week they can either share their comments with someone else or maybe we just report out to the larger group that that if they just report if they just write down and then report back that's a pretty good

Active Learning Overview


example of active learning it's a pretty simple it's what what you might call low-hanging fruit in terms of what it would take what it takes for a faculty member to do that so I'll do that I'll have them do that and then I step back and say okay why did I ask you to think about it why did I ask you to take three minutes before we had this discussion so I try to deconstruct the exercise for

Active Learning Overview


I just feel I feel the Ludvig has young legs that's all set anyway great to see everyone right so where to begin so this is this is joint work with a bunch of awesome people and I think really pushing on a lot of really interesting empirical work and I think I'm not gonna say that the talk will be uncontroversial so if I say a thing that makes you angry that's for me and if you

Training on the Test Set and Other Heresies


say anything that's like well that's awesome that's from one of these fours alright so I know this is works up on deep learning I'd like to start with machine learning that's why I talk about machine learning and I want to talk about kind of the conventional wisdom that we give to our undergraduates Jonathan here teaches hundreds of them and so I hope I don't know how many of


these things you tell them one they're like some how to have a good predictor you have to balance bias and variance alright and that you really should not perfectly fit your training data that's a no-no t something we definitely teach them that in right yeah you have to oh he already knows you don't the punch line this is the sad part and we know that high capacity models right wouldn't


have really big ones shouldn't generalize that you got to keep them small because if you you know said on the first day trying to do one-dimensional polynomial regression right and optimize high precision non convex optimization that's hard and I think everybody in this room at this point knows that none of these are true right it's a it's weird right so we keep


all kind of come to the terms that none of these things are true and yet we teach in our undergraduate classes I'm trying it's really hard to teach them anything else to be honest nuance is really difficult at the undergraduate level especially when there are 700 of them so I think that's a kind of complicated thing but it is this weird thing that we're in the square in this


weird regime where everybody here knows that none of these are true so how I want to push in a little bit on some other things that we tell people that also maybe aren't true kind of in this talk just in case you you don't believe me what are we okay first of all what do I mean by machine learning I mean something very narrow right for me when I say machine learning yes I would


upset some of my colleagues nobly Mike Jordan but I assess on my college might say this is all machine learning is it's just predict making predictions from examples I have a set of something I have a set of something else and I want to find prediction functions that map X to Y I know there's more than that but this is the backbone this is why all of you are here this is why they're


building our semester than this and so the whole idea is that how do we actually estimate these things we ask to make them from data we collect as many training data points as we can we ask them ate them from data and then we just hope that this works on other data a big hope big hope is that we have a lot of data if we collect enough of it we get all edge cases we can drive our cars


whatever those cases are right and so that's the notion of what machine learning people mean by generalization I actually think generalization is one of the machine learning is full of words that confuse the the listener they're just designed to confuse you so generalization when I say that to you that means that you know you learn how to throw a baseball and then you can


throw a softball that is not what we mean in machine learning at all and machine learning mean if you throw a baseball you know how to throw a baseball as long as this regulation baseball made to regulation wait you're gonna be able to throw that baseball and that's not at all what would moral people think right so the idea is that you give me an examples from a


distribution I would like to find a good prediction function on these examples I have some loss function that I believe is a reasonable thing that I would like to minimize an expected value meaning that if I have some new thing that comes from this distributions I'd like to be able to do well that's not known and so what you do instead is you replace it with the sample average and the


empirical risk and you minimize this and like the only thing we're allowed to do what's wrong the only thing we're to do now is minimize this using one of two algorithm and they're like three things we can do we minimize it that way and then of course our generalization error is just the difference between these two things and so the question is you know if we can compute this one when is that


a good or bad proxy for the other one right that's our whole that's what we mean by realization it's a very it's just a badly named term but it's very interesting couple problem and it's kind of like the core problem in machine learning right and the core theorem of machine learning is that the the population error that we really care about is just equal to the training


error plus the generalization error right sorry that's like the foundation of ten thousand ten thousand papers right we've all done that at one point in our lives right so we can measure this one and then we do a lot of thinking about why this should be small I mean this requires like the associative property there's stuff to be done here right I think we can equip a


little it about derive versus actually Matic right so I think right so what can we take away from this we know that if you have a small training error that means that the risk itself is just you're really only in leveraging generalization error right so if your training error for example is zero you're just hopefully know somehow that the generalization error is small and


sorry and zero training error we know does not imply overfitting even though that's another thing that we do tend to sometimes gets lost in the weeds like for example the the paper I really like which one test of time and we're at knits last year by um Bruce K and Mbutu right has this has this thing saying that you shouldn't train you shouldn't run an SGD too long because at some


point all of these terms should be one over square root of n but we know that's not really true right I mean just because this is whatever squared event doesn't mean this one is one over square root of n and just cuz this is zero doesn't mean this one's small so you know we it's useful it's a useful way of thinking about it but sometimes we over fit to what kind of these papers say all


right so don't want to say it's not always true but it's a useful way of thinking about it another way that this one ends up sometimes is presented this is how I learned it not everybody possess it this way is that you decompose is this it's it's the same same proof though it's you did you put the error it's three parts right so there you compare your error of your


estimator versus the error the best thing in that in the class of stuff you've been looking at right and then you compare the error the best in the class - like what the true prediction function the best population risk monument monitor is and then you are stuck with some bias at the end which is this is just the irreducible error that you can never get away from


and to whichever one you like more I don't care I like this one just because it allows me to attack this most my least favorite figure I'm kind of gonna be like the core the core of the talk today right so this is my least favorite figure it's from hasty and tip shirani I like those guys buns in this figure we read way too much into this right so somehow the idea here is that we have to


balance bias and variance in order to get good model complexity again you can do that you can do that but this is by no means by knowing is the only way to generalize and we know this okay I learned this because of deep learning and to be fair I learned this before and had forgotten it and I'm gonna talk to you about that in a second but I learned it again recently because of deep


learning that you can just get make these models gigantic and and they generalize so in a very unpopular paper that I know lots of people who are have my back tear right now don't like sorry maybe just one anyway so we read we read a bunch of experiments on this if our 10 dataset everybody's favorite dataset where we have chickens frogs deer in trucks and you know you rut so this is a


10 class classification problem it's relatively high dimensional has three thousand dimensions because the pixels 50,000 data points and if you take you know what we found is that you can either get a loss to be nonzero here this is the loss is the log loss which is not the classification accuracy you can work really hard to get this to get your generalization error down and in


this case the test error or you could just run it to zero essentially just taking this configuration and turning off all the regularization round to zero and while you see a drop in accuracy you don't see a gigantic drop so the test error increases but only by about 5% and moreover if you just pick a bigger model now you're considerably better than the original Alex net if you pick an even


bigger model you keep going down she wants here I'm sure he tried something even larger we just ran out of time so right so somehow here that the the the regularization parameters turned out to be just knobs that you can tune in terms of you could also tune architectures you could do lots of things and keep pushing this error down and indeed we saw the same thing on image


net where here we have chicken frog Deere and truck much more clear right I think at that point anyway and so we looked at an inception model inside Google I really don't like this experiment I just want to show it just to kind of give evidence that this happens and larger datasets the reason I don't like this experiment is that because of the way that these things


were trained Inc site Google at the time we were able to run about six experiments six runs I think have we used I think one of the more valuable things that's happened to the community is this add-on benchmark and we just used the DA benchmark we've been enabled around hundreds of experiments much better here but all we were able to do here was toggle flags inside some Google


3 models and so in particular you know in this case what we could do is we could turn off the LT regularization and we could turn off the the drop out sorry the UM data augmentation and you could still get perfect dieter palatial and even note that the top five accuracy here is only 19 point three sorry tight error top tight five errors only ninety point three you try to get to something


that has a 19 point three percent error it's really hard so it's significantly worse than what the inception model is getting but again it's not it's not catastrophic about this would have won this would have beat Alex net the first time around so still if it's good accuracy yeah let's ever talk like that regularization before my control variance so what yeah


so okay there is talk of implicit regularization I guess what I would say is that we started to just look at more models when we started to do is stop looking at just this individual models or for we just started download more this actually became a big trend in the research group um it's there's something that Becca roll-off started kind of kind of pushed us on this direction and the


mood became sitting here kind of really pushed us even further in this context it huh Baz an experimental resource so you just get pull some some models and then see what happens and a bunch of things so this is the scatter pot I don't really buy that parameters the neural network is actually meaningful but you can see that essentially as you make the number of parameters bigger the


models continue to get bigger blue line is just the minimum error and the red is just a scatter plot isn't models at a particular model size I'm just taking the minimum error of the Reds yeah I mean like I'm not saying that they're all true I'm just saying you could do a pull request over here I go fine I say I can call Fernando get him on this one this is even better what you do


here is just remove models and so now you see the trend this is there's no Alex net or vgd on here they kind of ruin that but they're just up here some ways fundings like the Curt you really care about this lower envelope but this is the same thing kind of happens on imagenet you just keep making them bigger well you'll know he's like we have log axis on the X and and and and


linear on the Y so semi-log this I pulled from a paper by some Google folks because only Google folks would think it would be fun to train something with 600 billion parameters million million million ok that's reasonable 600 billion was stupid but six our million perfectly reasonable anyway so that's that one he's getting bigger here's your visa this is from misha's


talk yesterday well I made it but it's fine it's the same same plot right we see the double descents this is now we're random feature models where we just keep adding random features and see how the accuracy goes and even though it does go up it kind of comes back down as you make the models bigger and bigger am i i'm just interpolating so this one is just interpolate I'm not doing this


case is man we minimum euclidian arm although although what's interesting is that I like this plot better is that if you don't do minimal Euclidean norm but you just go use read regression so you allow yourself a tunable parameter now that dip goes away no it just gets better oh so I don't know all right so this is not minimum nor mystique this is regression and then that bump goes away


yeah you've picked the best Ridge you pick the best Ridge it's not a constable I picked the best one for each and you're gonna see why in a second this is the best one for each it's the only done with a number of features give it like for that the best value goes down every number is so yes so sorry in this case I'm not taking the best one from here I'm not taking the best of these two it


is just if I tuned this what's the best I can do just on this one fiber here is a paper something I stole from Peter this is from an inner UPS actually was nipped at the time but nerves tutorial from 20 years ago here he was doing boosting some of us what do you see here well I have first of all note the semi-log axis there we go semi log X on the you know that's pretty neat and


you add parameters I mean boosting right you increase your model size with every step and so now I have the models get bigger and bigger and bigger and the test error keeps going down I think the the so that's that was interesting right so that was small data machine learning but I still seem to have a thing this is another really interesting one which I pulled from a C ACM article by Bell and


Koren describing how they won the Netflix prize and they saw exam the same thing that they have different kinds of models but they kept making their models larger again we have semi log X on the routers linear in error and you see this thing kind of continue to keep going down to bigger and bigger you make your model so I think there is something interesting there so there you're seeing


two things one making the model really huge doesn't doesn't you know it has a ton of capacity maybe you're controlling it with various kinds of regularization of some form or another but oh it just seems make it bigger worry about that later does seem to be a good take home and the other thing is that you see significant diminishing returns right I mean if you


have a log x axis I mean this doesn't mean that eventually you have to give up even Google eventually you have to give up so I'm not sure that this is necessary how to get a suit like that that irreducible error we'd like to get you no no no no no it's not a typo not a typo a hundred thousand million that's like Carl Sagan it's a hundred thousand million parameters that's a big deep I


didn't make this plot they don't get their ice log these need different things you have to read the caption that's not here sorry I maybe should've edited these things do not mean don't they're in the caption whatever those mean I don't know what those numbers are these number factors are you sure paper [Laughter] anyway so we could look it up and think see a cm it's cool they did a lot of


good work let's go back to this one so look here's what I would like to say like there are crazy diminishing returns - it does seem making the model bare for a fixed holdout set that we fix in time for the history of the universe does make that test error go down but that's also not generalization error alright if you do a holdout split or you take a train set and you take a holdout set and


then you just fix that holdout set forever maybe what's happening here is you have this these giant models have enough fluctuations in them that they can you now over you could actually leak a lot to the test set and over fit to this one holdout set that you fixed forever so this leads to a question this leads to a question we're all spend most of the rest of the time of the talk


there it's perfect I mean I know we have planet I'm good so yeah that's the rest of the talk so maybe maybe what's happening here is you make these models really big and that allows you to overfit on this one holdout set and so there's only one way to check right which is make a new holdout set okay there a better way I don't know but we'd that's what we did that's what we did we