Hello, welcome to our presentation that is going to be focused on optimization of wireless networks by means of reinforcement learning. We are going to start by providing a technology overview and then we're going to focus on the resource that we have achieved when applying this technology in the field. But before that, let us say a few words about us. My name is Juan Ramiro and I work for Ericsson. Inside Ericsson I work for Business Area Management Services, Automation and Artificial Intelligence. And within this team I'm heading up an innovation unit that is focused on network design and optimization. Hello, my name is Jose Autes. I also work for Ericsson in the design unit as Juan. I'm contributing to his team as a research specialist. Okay, so let's start by providing an outline of our talk today. First we're going to set up the context, basically explaining what we mean when we talk about network optimization. Then we're going to review very quickly the basics of reinforcement learning and then we're going to contextualize that within the scope of network optimization. And then at the end we are going to show a real case study in which we have applied this in a live network and we're going to show the conclusions and the learnings we have obtained from this experience. Okay, so what do we mean when we say network design and optimization? Basically we are talking about these four stages that you can see in the slide. First we have network planning in which basically we forecast the traffic and then we tell the operator where and when investments are required in order to expand the capacity of the system so that we can cope with all the expected traffic with the desired quality. Then there is design. In design ones that you know the areas in which you have to carry out an expansion basically you determine where exactly that new equipment needs to be installed and which configuration should it have where it should be the antennas pointing at and so on. Then once you roll out the site or the infrastructure or whatever comes the tuning part in which basically before launching that equipment before making it available to the live traffic you have to adjust a little bit the different settings so that at the end you're providing the expected quality of experience and then at the end once you have launched the system and you have it running with live traffic you have optimization which is basically tuning the different parameters and settings that you have in the current infrastructure so that you can make the most out of it and you can maximize the quality of experience and the capacity with the current level of investment that you have deployed in your system. So as I said before we're going to be focusing on reinforcement learning which is basically a technology that leverages learnings from behavioral psychology and teaches a system how to interact with an environment by basically interacting with it and learning from the outcome. It is basically the same way that we believe that for example children are learning how to work and at the end based on every interaction you take some learnings with a long term goal in mind so that the way that you decide how to modify your decision logic is always guided by the maximization of the long term reward that you are going to get. So here you can see in the slide you have the agents which will be the decision making entity and you have the environment which can be anything in our case it will be a wireless network so the way it works is the following out of an environment you measure the state basically how the environment is behaving in our case it will be the performance indicators of the network then based on the current knowledge of the agent and this input which is the state the agent will make a decision about an interaction to be executed upon the network so we typically refer to this as the action then the action will modify something in the system and as a consequence there will be a reward which is basically the outcome of what happens when you implement that action in the system has the system improved has it degraded and it's always measured within the context of your long term goal so if your long term goal is to improve capacity the reward will be telling you to which extent that change has impacted capacity now in the agent once that you know what is the state that you measured the action that you took and the consequence of that action you are able to extract sound knowledge out of that in order to find your decision logic so this is the learning step that happens in every interaction cycle and then once you have done this you continue doing it further and further until you have fully learned how to interact with the system so at the end of this process the knowledge that you have accumulated in the system is very small and therefore you will have some kind of erratic behavior so let's look at it within the context of learning how to interact with a video game so this is the typical a bricks video video game and in this context we have the video game here then we have the agent and then we have the state which is basically what we see happening in the video game basically we're going to look at this by looking at the screen that you see in the video game then based off the available knowledge at this moment you are going to take an action which is basically how you move your character in the video game and that is going to generate a reward which is the consequence of your action which is typically measured here as the amount of points that you have in the video game the amount of lives that you have left and so on and so forth by the way this is extracted from a publication from from DeepMind who have been working a lot on different learning things so let's look at how this behaves in reality so this is the video game and as more episodes go by you learn more and more so you can see that at the beginning the proficiency of the engine to manipulate the video game is limited and very often you lose very soon but then you get more and more training cycles and you can see how the agent is able to play better and better every time so let's see how this thing is evolving you can see that now it takes longer until you drop the ball at them as we will see in a few seconds when you accumulate more and more learning you end up coming up with sophisticated strategies that allow for example to open these tunnels that will send the ball to the top of the screen so that you are really destroying a lot of bricks over there so you can see what is happening now so at the end you will see how all these strategies that are developed through interaction with the system are really able to outperform whatever a human expert can achieve with this but of course as you have seen at the beginning and this technique has a major drawback which is that at the beginning since you have not accumulated any knowledge about how to interact with the system you will do things that are erratic so this erratic behavior does not really matter when you are interacting with a video game but if you are interacting with the settings of a wireless network that is not acceptable so we need to find a way to overcome that challenge so let's talk a little bit further about this so in this slide you have in the vertical axis you have the optimization capability which we have also described before us what is the knowledge that you have accumulated in the system about how to behave in order to achieve your goals and then in the horizontal axis you have the different learning cycles so as time goes by you move to the right so if you have an expert system which is the typical sound systems based on rules there you have just encoded the knowledge that is stored in the mind of an expert optimizer and you have translated that into a set of rules so at the beginning you already have a very proficient agent because you don't need to accumulate knowledge through interactions basically that knowledge was already there because the expert wrote it in a program so you have a very good optimization capability from the beginning but then you don't improve that over time because basically you're always applying the same knowledge again and again on the other side if you look at the reinforcement learning curve which is the blue one here at the beginning you know nothing about how to interact with the system so your optimization capability is very low and basically you are just doing almost random things in order to explore the system and start learning what are the fundamental tradeoffs that you need to consider but as time goes by you start learning from the consequence of your action and then the optimization capability grows and grows over time and there is a moment in which basically this tailored learning without any previous conception of how the system should behave ends up in an agent that is able to outperform the expert system and this is what we have here in which a reinforcement learning agent will typically as we have seen in the field outperform an expert system however as we said before we have a challenge in the initial stages of the of the training system because the behavior is erratic and that is not acceptable in a system like a real network of course it's acceptable in a video game so what do we do in order to to close this this gap so you can see here different strategies to learn from an environment at the bottom left part you can see the live network which is what we were pitching at the beginning so that is technically possible but you have to leave with some interactions that will be erratic of course the characterization that you will get from the system will be very good but it will have an impact which most operators will not have to will not want to have then on top of that we have the network simulator in which basically we can think of it as imagine that you want to learn how to fly an airplane and then you begin with a flag simulator of course it is a limited representation of reality it's not exactly reality but at least you can very quickly learn about the fundamental mechanisms and trade-offs of the activity that you want to learn how to carry out without any real consequence in case of an action that drives the system down and then there are other ways for example training a system to mimic an expert algorithm at the beginning or recording the consequences of past changes in the network and then replaying all that sequence of events in order to learn from that in our case we have decided to go ahead with the following first we connect our agent to a network simulator and then we carry out the initial learning there basically we learn about the fundamental trade-offs and the fundamental mechanisms of the optimization of the parameters that we want to optimize taking into account what our main goal is in the long term and then once we have achieved a certain degree of proficiency then we switch that to the live network so that we start with an agent that is not empty basically it is an agent that already knows the fundamental trade-offs about how to optimize the system and then we take it from there we start interacting with the system now everything we do is not erratic any longer but still we learn from the consequence of our actions so we continue further tuning our logic as time goes by now we will focus on a real case study and how the use of reinforcement learning can be applied to the optimization of one or more parameters in a wireless network in switzerland there are very strict regulations in terms of the maximum power that can be radiated through the air interface we received a request from one of our customers swiss com and the request was to reduce the power transmitted by the 4g base stations with the idea of using the safe power in the future deployments of 5g base stations however reducing the power in 4g can potentially cause coverage and throughput degradation this has the good news that coverage and throughput can be improved with the right configuration of the antenna tilt what is the antenna tilt is the vertical inclination of the antenna or to be more precise what we use was the remote electrical tilt the remote electrical tilt is a device in the antenna that permits modification of the vertical antenna pattern that is the pointing direction of the antenna and this can be done through a remote computer terminal which means that it does not require a very a visit to the site this is also the case when changing the transmission power of the base station that can also be done remotely therefore our proposal is to decrease the transmission power of the 4g base stations in a controlled manner so that it minimizes any performance degradation and can be compensated later with an optimal configuration of the remote electrical tilt in the slides we can see in this slide we can see the complicated scenario that we use to test our solution it is a healing terrain in the alps on top of this the area had been previously maintained and optimized by expert engineers which means that the performance of the baseline scenario was very good and this makes the task of improving the performance very challenging we selected a group of 79 base stations or also known as cells to optimize that is the core area we can see them in the map in there are these little sectors or cells in green but we also monitor a number of cells what we call the buffer area that this these are the cells in red there are 82 surrounding cells and that compose the buffer area that are used to make sure that there's no impact in them when changing parameters in the core area here we can see their enforcement learning approach that we have followed to optimize the remote electrical tilt of the antennas we propose an iterative approach in which the value of the antennas is adjusted incrementally with just one degree per step this way we can minimize the potential negative impact of our own decision with this approach the target is to pre-train the agent as much as possible with a network simulator so that the agent learns the best strategy to optimize their remote electrical tilt this is what we call the offline learning phase the network simulator lets the agent explore the vast space of possible stakes and actions without the inconvenience of degrading the real network due to unfortunate decisions although the network simulator models the basic mechanisms of a real wireless network it cannot behave exactly as a real network but this is enough for our agent since we have to remember that the target at this stage is not to come up with the optimal parameter values but to capture the best logic that permits obtaining those values once connected to the real network which is the second stage of the proposed approach once the agent is connected to the real network it can use the knowledge acquired from the simulator to propose the best remote electrical tilt values and at the same time continue learning from the feedback provided by the real network after every step for the case of the power optimization we have followed a different approach and like the case of the remote electrical tilt with the transmitted power it is easier to estimate the expected impact of a change in the performance of the wireless network in an offline manner to give a simple example double transmitted power implies double received power for this reason it is possible to use an emulator instead of a simulator the emulator mimics the behavior of the exact network scenario that we are optimizing which is not the case of the simulator in which we were looking into many random scenarios to extract the key trade-offs that lead the optimization the performance predicted by the emulator after a change in the transmitted power of one or more base stations will be very similar to the performance in the real network and thanks to this we don't need to connect our agent directly to the real network but we can interact with the emulator which works as a digital twin and then obtain the final optimal values of the transmitted power per base station and this has two main benefits first like in the case of the simulator the agent can learn the optimal optimization algorithm from the digital twin in a safe way without interacting with the real network and second the procedure does not need to be incremental since we can directly come up with the final optimal values in just one step one step in the real network but multiples iterations with the digital twin as we can see in the slide there are two instance in which there is interaction with the real network one here to retrieve the network configuration into the digital twin and another one here to load the final configuration of optimal transmitted power values into the real network at the end what did what we did was one power optimization step to reduce the power in a controlled manner followed by several iterations of the remote electrical tilt optimization approach and then we repeated the procedure another round of power optimization to further reduce the transmission power followed by several optimization steps of the remote electrical tilt to correct the network performance here we can see how every base station achieved a different final optimal value both for power and for tilt while most base stations ended up with a lower transmission power still some of them required a power increase in the case of the remote electrical tilt some cells were down tilted that is tilted down and some of them were up tilted that is tilted up to compensate for the power decrease after the power decrease applied to most base stations in the scenario in the slide in the following slide we will focus on the central area as we can see here most of the base station had a green value which means that they reduce the transmit power and it was compensated with antenna up tilts as we can see here but not all the base stations did this up tilt the final solution is the result of an iterative search of our performance learning agents which gradually steered the configuration towards the optimal values using an optimization logic learned from data and not designed by humans that optimization is contained in a deep neural network it is interesting to see how the combination of both approaches the remote electrical tilt approach and the power approach permit going beyond what a regular optimization would achieve this way after making the most of one of the agents new room appears for the improvement and when using the other agent and again vice versa when the second agent leads the network to a level in which no more gain is possible the first agent finds extra room for improvement and well as you can see here that has been shown some sequence of the different parameter changes as you can see some of them are power some of them are red and they are combined through the time let's summarize the results of the trial in a first iteration a combined power and electrical tilt optimization was used and we managed to reduce the average transmits power in 10 percent with no quality degradation actually it was just the opposite we achieved even a 12 percent improvement in the user throughput then we executed a second round of power plus remote electrical tilt optimization with a target of exploring the limits of our solution this time we reached a 20 percent decrease in the average transmission power compared to the baseline and we still got a user throughput improvement of 5.5 percent this power decrease was translated into a 3.4 percent reduction in energy consumption at the base station we can conclude that we have come up with a useful combined solution for power and remote electrical tilt optimization based on reformer's learning this solution uses the data from digital twins and from the live network to build the optimization logic automatically that is no human intervention and this has been done thanks to artificial intelligence this combined solution is able to reduce the transmission power while still improving the service level experienced by the customers if you're interested in knowing a little bit more about this topic you can read this article that we have written which is available online through the link shown in the screen and here concludes our presentation we are very happy to answer any questions you may have thanks very much for your attention


న౗ికిన్ానింద్నాదిందిందాదింగాజిందువియటంయకకిదెదరంవందింసందిచిదిందికకౕింది. If proper procedure had been used for the purchase of these vaccines that would never happen, Solution is the only government who paid money in advance, mbrelanding నినియణవతాకికాయానిని. చానినిని చాతానియయాని. అలినికిదికికికానికి. 就是 ఆమికామిని. పరరరచ అంమికినిలానితి. The people who pay taxes and some of it is grand money that other people's taxes pay. How can you take 7 million dollars in advance and pay to a supplier? And up to this day, the people of Senusha have not received their 7 million dollars back. And that case now is in the courts of the United States. I haven't been against the supplier. I mean going after the supplier is not my business. My business is the people who took 7 million dollars of tax-payers money and went against all the rules. There is an audit report. There is an audit report on that vaccine situation. We just haven't said anything. There is an audit report which the government will put out when the government sees it fit.


A sleek research vehicle called the National Aerospace Plane may one day take off from the runway on this California desert lake bend. Aerospace plane moves thrice through the hydrogen-fueled air-moving engines to take off like an airliner inclined to the edge of space, pushed into orbit. This technology promises to give efficient and flexible access to space in the 21st century. For now, the X-30, as it's also called, is flown only with simulators. Although the plane does not yet exist, it sponsors NASA and the Department of Defense, along with a team of five major aerospace companies are working together to make it a reality in the next decade. Advanced computer technology and mathematical model are used to design a vehicle capable of speeds up to 17,500 miles per hour. Speeds so fast they can't be duplicated in wind tunnels with other experimental facilities. Computers have to be used to simulate the shock waves and air flows the X-30 will encounter. Materials for the plane's skin must withstand serious temperatures or extended periods of time. Composites such as carbon-carbon, ceramics, and alloys of titanium and aluminum are being tested. NASA and the Air Force flew an experimental aircraft for the X-15 in the 1960s. It used more power to find the seven times the speed of sound at altitudes grazing the fringes of space. The next step is an experimental aerospace plane that can travel 25 times the speed of sound, about 30 times faster than a jet airliner. The ultimate goal? To demonstrate the technologies which will allow efficient, flexible access to space. Vehicles incorporating X-30 technology may someday deliver satellites into orbit and visit Space Station Freedom, the nation's most sophisticated research efforts. The national aerospace plane will help maintain world leadership for the United States in aeronautics and space technology. Meeting this challenge can help today's most ambitious space plans become tomorrow's reality.


Okay, we're back, this is Dave Vellante. We're live from IBM IOD, thinking big. We've been thinking big all week. This is IBM's big data conference, it's really transformed from kind of a staid information management, governance, you know, legal council event to one that's really dynamic and moving at the speed of data. So we are here live, this is theCUBE, SiliconANGLE TV's production, this is Big Data Week. We're on our way to Strata, we're packing up theCUBE, flying the red eye in, we'll be broadcasting tomorrow, so keep the tweets coming, you guys have a great audience, really appreciate you hanging with us here, I know it's late on the East Coast and really thank you for your continued support and watching us. I'm Dave Vellante, I'm here with my co-host. I'm Jeff Kelly, Big Data Analyst with Wikibon, we're here with our next guest Inhi Cho-Sue, who is the vice president of product management and strategy in the IBM software group, information management, welcome to theCUBE. Welcome back. Thank you, excited to be here. We had you on at Edge in June. In Orlando, it was great. It was great, smaller show than this, but very focused storage, near and dear to my heart. Big Data and storage, they go hand in hand, you've got to store it. I know, where's the storage guys here, I don't hear enough about the storage companies. They have all the types, right, flash and memory, tapes coming back in Big Data. I believe it, I believe it, people don't talk about it, but tape is coming back, why? The cost, right? The price is just amazing. Well, it's an order of magnitude, you know what somebody said today is, Hadoop is the new tape. Did you hear that? Hadoop is the new tape? Hadoop is the new tape. No, I haven't heard that yet. So, so how you been? I've been good, this conference is fantastic. We hit over 12,000 attendees, you know, I had an opportunity on Monday to be on main stage. That was a first on that kind of... Were you there with Jason? Yeah, right after. Yeah, right after. All we did was push a button and then he just went, scream a consciousness for... He's like an energizer bunny, you know? Like I thought I had pretty high energy, no, no. This guy runs on something else.  Oh yeah. It was really fantastic. So talk about your keynote, I would never have a chance to see it because we're doing the Q&A. What did you tell people? We revealed the new Pure Data system. So on main stage, Pure Data is the newest member of the Pure Systems family. It's built on the same tenets as Pure Systems, built in expertise, integration by design and simplified experience. And I talked about the three models of Pure Data. And Pure Data is all about data. We looked at kind of the workloads clients care about most. So data and analytics, transactional applications and analytic applications and said, okay, how do we optimize the systems? Everything from the design to the life cycle of deploying, you know, database deployment or entire clusters to running really advanced and complex in database analytics. I mean, we really tune this thing end to end. You've got strategy in your title. I want to talk about strategy a little bit because IBM is, in my mind, really defining, redefining and defining the big data space. You kind of got the guys we're going to see this week at Stata, you know, the cloud heirs of the world. They did their definitions. You redefined the big data space, really bringing in your analytics mojo to that big data space in a way that I think is very impressive. Talk about that a little bit. Was that deliberate or did it just happen? Very deliberate. Very deliberate. Why? Because you've got to think about, clients have spent millions of dollars on investing in infrastructure and capabilities in their enterprise already to be able to deliver services, customer warehousing capabilities for campaign management or doing fraud detection capabilities. They're already running systems and now we're saying, hey, there's some new technology that's available that can augment what you're doing. Now, in order for clients to be successful in doing that, you've got to take them from where they are to this new place and link the two, right? And to link the two, you have to do it in a thoughtful manner. That's why we talk about four Vs of big data, right? From variety, velocity, and now veracity, truth, and data because data governance and quality matters. I want to add value. It's a fifth. A fifth value. The analytics, information and analytics is the priority, one of the top priority growth areas for the entire IBM Corporation. So Jenny Rometti's been very clear our CEO. Our chairman has said, you know, this is the area where we're going to progress forward. We've spent $16 billion. Why? Because context matters, context, excuse me, context matters, right? Precision matters. Watson generating answers that are 50 answers doesn't help. Watson generating a few answers with a high probability of it being correct helps. That's just understanding large sets of data is one element. Turning that information then to insight is the second. So. There's also a big emphasis on integration. It's a classic IBM playbook, right? We're not just going to throw out point products. We get this ridiculously amazing portfolio, complex portfolio, and we're going to stitch it together in ways that add value for clients. Talk about the integration play. Oh, sure. Well, we have this thought on a couple levels. So one is at a technical level where you say, you know, now more than ever, when you think about big data, there's multiple information coming at you from multiple sources, right? Machine generated data, data generated by people, different types of content, structured data. So how do you unify all of that in a way that it's consumable? So that's one piece. Then you have to think about the way the businesses run. So we have this notion of systems of records, right? Systems of records are traditional systems that are running businesses today. This is where your account information sits. This is where, like, core customer information sits. And now there's kind of this emerging thought of, well, clients want to invest in and understand capabilities to understand systems of engagement. And what's the integration between the systems of engagement and the systems of record, right? It may not care as much or not be upset as much if you load a picture on some site and it's like of a family member or it's, you know, some event you already had. You'd be a little disappointed if that picture got lost, but you would be really upset if it was your paycheck picture photo that, you know, a bank lost, right? So there's a level of integration and quality and security and governance that you want in how clients are dealing with their end-to-end sort of business capabilities. So do you see the world moving from a transaction emphasis to an engagement emphasis? I think it's a balance of both.  Why? Because commerce matters. So commerce isn't going away. Order management isn't going away. But yes, engagement is exciting. Why? Because consumers are now controlling more of the power and they want to interact differently. They want faster response time. They want simplicity in the tooling. So it's an emerging set of needs. We're responding as quickly as possible to it. And a lot of the growth and strategy that we're investing in, like social business, smarter commerce, it's about recognizing those systems of engagements. It's a huge part of IBM's growth. I think it's a virtuous circle too that actually the engagement leads to a transaction ideally. Oh, absolutely. Absolutely. More engagements drives more transactions. Yes. That's the idea. So I want to talk a little bit more about the pure data system and the work that went into that. We were at dinner last night talking a little bit about some of the design, all the hours of design that went into it. You told an interesting anecdote if you could share about the people lining up to have their picture taken with the box. Oh, yeah. But tell us a little bit about why that kind of, you know, it's a really just looking at the machine. I mean, it's a great looking device. We talked a little bit about design. That's beautiful. It's a nice design. Oh, it's amazing. You know, we launched this in Singapore on October 9th and it was amazing. So you forget when you're working in enterprise software, like how difficult it is for people to tangibly touch, you know, tactically touch that or experience it until after they've deployed it or are using it for some time to see the value. And for the first time, on the day of a launch of something, we actually saw the immediate response, not necessarily to their, you know, experiencing and deploying it, but actually just this year, industrial design of it. We call the door, the door is incredibly cool. It's called a triplex door, three dimensional, very slick blue. And the design time took about 12 weeks, just the design time. The team thought through the aerodynamics of it for airflow. We actually even used some baby powder to test the airflow, you know, insulation for soundproofing, thinking through energy levels, power consumption. I think the team went through about four or five total iterations to modify the design. It is an amazing door. So what happened in Singapore is we introduced the box after the meeting. You know, it was on the main tent stage. People were lining up to take a picture next to the box. It is, it is awesome. It was awesome. So you were at the Singapore launch? Yeah. Yeah. I was talking and did the hot topic on pure data. So I introduced the new pure data system to everyone there. And we did dive. We were in Boston. It was a good event. Right? You guys were in Boston with Arvin and Bernie. Yeah. It was the original pure systems launch as well. Oh, in April. In April. Okay. And it was good. I've said several times, IBM was a little late to the party but came in with guns of blazing. Of course, the IBM doesn't agree with that, my analysis there. But you guys do a good job in that space. Well, you know, it's a whole different level of thinking. We're sort of hitting an inflection point and kind of the timing of the technology. And I think we hit the cycle every 25 years or so. But where you have, the clients are saying, you know, I have to deliver my services faster and better. There's some degree of pressure and time in terms of what's lost and them trying to figure out all of the specific components and integrate all the pieces themselves and spend too much time really on the, what I would say, assembly and management of systems rather than focusing their time on delivering the services for their business, right? So pure data is really about saving our clients a lot of time, money and energy and resource. So you can then put into adding value or adding value, which is they want to run the values. They want to run the analytics. They want to run their applications. I mean, they shouldn't be spending time trying to like construct and tune general purpose components to get the optimal performance when we really designed it from an outside in view that says, okay, what are the workloads that matter? What's the optimal way for it to be, you know, work? So I'll give you an example. We've thought through things like the balance of in memory versus disc. And we've actually put that and prescribed it in the system. So you don't have to think about it. That's the ideal scenario for transactional workloads or in the analytics. We actually put the storage closer to the compute, you know, because it, it makes sense from an, I mean, the network, sorry, the network closer to the compute because of the path physical distance it has to travel in order or the analytics to run. I mean, these are levels of detail that we've gone through in the entire system, the cabling on the back. I mean, if you've ever walked into a data center, it's like a spaghetti mess, spaghetti mess, right? We actually designed and developed patents just around the cabling so that it's not only done for the initial deployment, but as you scale the box, you don't have to recable and you change compute nodes. So how do you spend your time these days? Oh my gosh, that's a loaded question. Customers, how do you break it down for us? So here at this conference, a lot with customers. I mean, probably the demand and interest in big data is really hot, huge, huge interest in integrated systems. A lot of interest in industry specific applications and dimensions. I mean, I'm probably spending every day at least at this conference easily with anywhere between 15 and 50 clients a day, depending on the day and the number of meetings. So share with us, what are they asking you? What are their, what are their big challenges? Yeah. So okay, so one client is saying, you know what, we're kind of wanting to transform what we do around enterprise data warehousing and saying, hey, let's do this in a much more creative way and in a new way. How do I bring together both my structured information with unstructured information? So that was one dimension. Another client is saying, you know what, my performance around my SAP applications just are hitting a max. Should I be investing in kind of alternative solutions or how can I improve the performance of that? What's the underlying infrastructure about it? The other topic that's been coming up is big data and security, right? There is none, meaning, you know, think about it and how is IBM investing in security? And we've spent a tremendous amount of investment over the last year and actually Robert LeBlanc has set up an entire security division around it. Cloud, cloud management, managed service providers I've met with a few saying, you know, in this kind of new world where we're trying to deliver more services, we've got to figure out a way to more easily consume the infrastructure capital costs too in the way we operate our business. So the range has been pretty broad. Another client said, you know what, I want to apply big data analytics to understand kind of new services. One of the clients on stage actually was Conoco Phillips on Monday about well drilling and well placement. I mean, think about it, Iceberg, in trying to place a well in an ocean moving full of glaciers is not an easy thing. That is a big data challenge. Big data challenge. So you mentioned, the first one you mentioned was the enterprise data warehouse, like the transform. To me, that's kind of a euphemism for, there's a lot of frustration out there existing enterprise data warehouses. And so, Jeff just wrote a great piece talking about how, you know, data warehouses is critical infrastructure but in a way it failed to live up to the promises and now we're seeing with big data, new hope. Do you sense that from customers? I do, I do. Well, the possibilities, right? What's interesting is when I engage with clients, they actually give me new ideas. So one of our clients is John Deere and they've been using some of our technology around Vivissimo but other capabilities across our software business. But one of the things that they're trying to evolve to is smarter farming. And what does that mean? Well now, you know, these tractors, I'll just put it very simply, can actually send a picture image of let's say a 10 by 10 meter square foot of the plot, send it to headquarters, they run the analytics on what, based on the topology and soil content mixture, and then sends a message back says exactly how much water or fertilizer that should be spread across that same space and then the tractor can memorize it and repeat the pattern. So then the question is underlying in the technology pieces is how do you capture that data? How do you capture the GPS location data? How do you run the analytics as fast as possible? How do you dispense? And then that has an entire implication to the supply chain of that entire industry. But you think about something like that, that is transforming even the nature of the business that a company like John Deere is even in. I noticed, I mean, I've observed and it's pretty obvious I guess that IBM's really attacking these problems on an industry by industry basis.  But why is that? I mean, talk about that a little bit. Well, because we live in a world where the information is so transparent, right? And everyone has, we live in a world that's hyper connected. Everyone has access to the internet. Everyone has, and that's created this kind of need that's fueling another need, which is the quick response, faster response, faster precision, transparency and pricing, transparency and quality of service. And then because of social context, people have a greater voice, regardless of let's say their prior experience or stature or role in a particular industry or supply chain. So when you think about that and that competitive dynamic, if you don't really understand the mechanics of a particular industry, you can't really support the data requirements because most industries actually are kind of mixed in terms of the degree of regulation, the types of data. The data could be standardized and have unique requirements. The taxonomy and ontology of the data is very different by industry. So another good example, there was a sports apparel company. They designed like running shoes as an example and they were able to compress the design time to a matter of a couple hours, meaning in terms of the response, how quickly of how well the shoe's going to sell by putting it in the open sort of social kind of crowdsourcing area and then feed that back in. Historically, that would have taken like a year because you go through qualitative research, you have a focus group, you decide whether or not they're going to like it and then within like a matter of few hours, they actually know very quickly how well this product's going to do and what segment of the market, what price range it should be at even before they go into production of the shoe. I mean, this is a whole different kind of world we live in. I want to ask you about the innovators dilemma. I mean, if you're familiar with the concept. So a lot of people think it's a fate, a complete that a large company with a big install base is going to have difficulty managing. I'm sure there are challenges. Why, I mean, I'm sure IBM is cognizant of that. It's not like you're asleep at the wheel. You've seen this movie before. I mean, IBM, the whole company changed because it couldn't, almost didn't cross the chasm, you know, whatever, 20 years ago. Why and how do you manage that old and new? How do you guys do that? And why will you be successful? You know, that is a tough question. And I think anyone in the technology industry struggles with it. But quite frankly, the answer is easier than you might expect. And the reason is, is you got to focus on extreme client value. And if that is the driving factor, then the innovations will drive from that. So extreme value. So let's say if you think about the capabilities that you deliver and how clients are consuming it, unless you're going to give them significant amount of cost savings, right? On the order of 30, 40, 50% of what, against what they're already currently doing, you're not going to be able to capture their attention, right? Because of the, let's say, the challenges of switching, the skills requirement, cultural change required. So cost is one element. Performance. If you get something that gives you 10,000 times the workload performance, improvement of something you're already doing versus a 10%, that's a huge difference in the factors. Even in terms of some of the things that we're doing in analytics, which I can't fully talk about yet, is we're actually looking at some capabilities that say, okay, now, how do we optimize, not just for specific types of tactical queries, but entire analytic workloads? And could we do that and multiply that by 100 times? And if we do it by 100 times, how does the fundamental engineering change? I mean, Netease is a fantastic example of it. They simplified the integration of the entire appliance and leveraging FPGA. FPGA has been around for a while. But the way in which the workload and elements of some of the work was done before, you've actually improved the performance of the entire warehouse appliance, right? So these are some of the techniques that we're also thinking about in the whole engineering. So what can you do analytics? What are we doing around compression? What are we doing around scaling of data? So it's, I think, focused on extreme value. And I think risk factors into that value equation as well. I mean, IBM de-risks the engagement and the solution in a large way. People don't buy from startups because they want you, they buy from startups because they have to. If you make it harder by closing that gap on performance or cost. That's an interesting way of saying it. But IBM does that. They wrap that big blue blanket around clients and they say, okay, yeah, maybe it's a little bit more expensive in the transaction, but in the long run, it's all about the value. So I think that's how you win in this game. And you say you've got that model down. I mean, it's... Well, we really are trying to put the client first in almost every scenario. And even if you look at what we do from a technology roadmap, we do it in increments of five, 10 years. And we say, okay, what's going to be the next wave in terms of new areas of investment? Whether it's security, analytics, systems management, cloud, big data, mobile. I mean, we're really on the edges of that. Yeah, and I should say that. You got it down in your software business. I mean, the software business, the transformation that you have made in the software business has been phenomenal. So really one of the bright spots. I want to ask you about IT spending. And since Nick Carr wrote this IT matter, IT spending as a percentage of revenue has declined. While his premise of this book was off base, it was symbolic. And in a lot of ways he was right, just for a lot of the wrong reasons. But nonetheless, IT spending has declined. Do you think that big data has the potential to reverse that trend by delivering hyper value to clients and getting CEOs to say, you know what, let's start spending again? Yes, because I do think big data has that potential.  Not just as a, can I improve the operational efficiency of an existing process, right? Sometimes technology is leveraged for operational efficiency or compliance reasons in terms of the initial purchase. But when you think about new revenue sources and strategic intent and brand association, those are new spend categories, which force then new investments. Now, what most IT clients are saying in their budgets are their remain relatively flat. So how do they optimize within the existing investment so they can allocate that new spend appropriately into big data? I would contend that spend around technology is actually going to increase in the next two years. Why? We do an annual CEO study. And we've been doing this for several years. So the new CEO study showed for the first time, technology in 2006, 2004, sorry, last eight years. So technology in 2004 was the number six factor in driving the most important factor in organizational transformation. Now CEOs are saying in 2012, the number one factor is technology. Technology hasn't been number one ever. Ever. Ever. Oh really? Based on the study. Okay, yeah, we probably weren't doing it in the early days of the PC productivity. So the top factors were skills and market economy and globalization. Those were the factors for the last eight years. What's happened is technology has moved from six to one. And I think the reason is, is because of going back to the fact that we're hyper connected, people realize they can't just compete based on the traditional ways in which they've set up their business models. They've got to leverage technology to give them an advantage in the things that they could leverage their valuable resources doing the work that they should be doing. I think we're seeing that reflected in the, the CMO now is becoming as important in terms of technology spend as the CIO. And that's, people are predicting that's actually going to, the CMO is going to be one of the more important people when it comes to spending around IT. How does that impact from a strategy perspective, product perspective, how you engage? That's a really interesting question. You know, the CMO kind of agenda initiative and smarter commerce has been incredibly successful so far. And what's also interesting is for some clients in some of the meetings, we're actually introducing the CMO and CIO together because it's been such different portions of the organization. And now with the need to drive more, let's say, awareness and understanding a brand sentiment. Now, why? Companies have spent years, 20 years building a brand and building an entire organization. And with the social and internet kind of transparency, within less than 20 seconds, a company could be ruined, right? So you think about that kind of, that dynamic. Second is because of the choice and you know, certain industries, there's a greater push toward commodization or it's easier for clients to switch vendors or preferences for different products and services and the only way to differentiate is to actually understand what is it that they value, what are the core brand attributes and then try to build off of that. So it's a huge opportunity and there's every bit of that supply chain if you think about it in terms of how you engage clients, how you market to them, how you grow, retain and supply your partnership. It's a huge opportunity. That's interesting. One of the big trends of the last decade was the consumerization of IT. And it kind of made the enterprise a boring place even though companies made a lot of money, there was a lot of consolidation. I mean, clearly free cash flow was good but innovation was kind of down in the enterprise last decade. Do you think that the enterprise is figuring out that consumerization piece and embracing that in a way that can have beneficial impacts to the enterprise tech business? Oh yeah, absolutely. Probably the best example of that is mobile, mobile applications, mobile devices.  Now it's something that is a top of mind item for most CIO, CTOs and even organizations that say, okay, there's such a blending of the way people work and live and smartphones and devices are a good example of that. And now you think about, okay, how do I service those applications? So we had a bank yesterday talk about the need for clients to be able to take a picture of their paycheck and then process that very quickly and how do you do that in a secure way? That's a new application. That means your ability now to response is very different. You don't have to live near a, you know, ATM and or a physical bank in order to bank with that company. You got my ATM with me. Right, you're walking ATM, right? It completely changes it. I think about every industry, it's happening. I just talked to you about the farming industry. I mean, energy utilities, telecommunications. The number of call detail records that happen on a daily basis for a lot of these telecommunication providers is staggering. Like one client, one Asian global telecommunications provider handles six billion call records a day. Six billion, right? So that's all driven. Why? Because of mobile devices and applications, but they want to make sure their quality of service is good. Now they want to figure out, okay, if this is a walking device that not only is indicating where a person is at what point, what they're looking at, what's of interest, how they communicate, could I use that also as a vehicle to, you know, market to them at any given point? So one of the questions we actually had a discussion was, you know, imagine you're in the subway and all of a sudden the billboard changes because they know that you're standing there, right? Based on your preferences, which is I know that you like to bike now. There's a brand new, right?  And, you know, how do you balance, just, you know, I think I've written before about how, just because you can do something with big data doesn't necessarily mean you should do it. So you've got to balance, you know, the...  Forget the balance. It's all about the reaction you engender in the customer. So if it's the creepiness factor is played up too much, then that kind of backfires. And you can use analytics to understand that as well, what works and what doesn't work. Yeah, and there's also, a lot of this has to do with respect, both for your clients and the partners and the industries that you're a part of, and we realize that every industry is connected. You know, the world is interconnected. We talk about that. That's really the genesis of a smarter planet, which is there's got to be a smarter way in which we do things. It doesn't mean that there aren't necessarily repercussions of certain types of investments or certain types of activity, but you've got to be a little bit more thoughtful about the energy consumption. You've got to be thoughtful about privacy and protecting privacy. You've got to think about security elements and individual security as well as national security, as well as organizational security of licensed IP. There's multiple elements. And we try to balance that. That's a core element of, I would say, forget our solutions and technology for a second. I would say that's a core element of the value of IBM in terms of the way we operate. But don't you think that society is comfortable with things like, I think about search. When I search on something, it's throwing, and Google's throwing ads at me, and I'm very comfortable. In fact, a lot of times I want them to throw the best ads at me so I can find a supplier, but you think about, I don't want to have to go find this stuff. I want it to find me. So, I mean, I think there's a cultural shift in where I think people are going to become much more comfortable with sharing information about themselves, because they're getting more value out of that. Well, part of social business, which is one of our strategy areas and investment areas, is really about the shared community thought, because you're a part of it, and you have a voice. And what that means is, as you learn things, you share back to the community. And I think people appreciate that there is a level of truth that comes out through those relationships, and that whether it's done intentionally or not, or maliciously or not, right? So, in this kind of new context, I think people appreciate when things are done thoughtfully for them, right? It's a higher level of service.  You're going to have a better experience. It's like the ultimate hotel experience. When you go, and they know exactly what your preferences are, you're greeted in a certain way, all the shampoos and soaps are exactly the brands you prefer. Let's say you had the mattresses a certain way. Any service industry. I mean, really think about it. Well, that's why I respect the fact that Senator Rockefeller in Congress is asking Equifax and Experian, Experian, what data are you collecting? I want them to protect me at the same time. The potential of value creation by sharing our own information is so enormous that I think it's just going to swamp the current mindset that we have in society. I think it's important we, as an industry, have that conversation and more effectively communicate that message before legislators who perhaps don't understand it quite to the degree that people in the industry do, take actions that could potentially constrict what we can do.  So, thank you so much for coming on theCUBE. Really appreciate you coming on. Always a great guest. And please come back. Thank you. This was fun. Great to see you. All right, keep it right there. We'll be back with our last guest of the day before we close out and pack up and head to Strata. Keep it right there. We'll be right back. This is theCUBE.


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hello you guys welcome to a new video so today I'm just about to go to the gym but today I'm gonna try to consecutively do things that push me out of my comfort zone because I was thinking and I was like what have I done recently that I've like pushed myself out of my comfort zone and I can't really think of anything so it's like you know what I have to freaking step it up because that's how you excel in life and that's how you learn new things that's how you grow is stepping out of your comfort zone and I haven't in I feel like a long time like maybe I haven't I just don't realize it but I just don't feel like I've done anything out of the way to step out of my comfort zone so that's what we're gonna do in this video so we're just going to the gym which is something I would normally do it's not that big of a deal but after the gym we're going to take a cold shower so that's the first thing that we're gonna do but right now we're just gonna gym and then take it from there so anyways can't wait for today it's gonna be a fun time and yeah I'm gonna go to him now and I will talk to you guys throughout my day one thing that's kind of out of my comfort zone is coming to like a public park area alone and just like meditating journaling and just kind of like sitting myself down and being alone I've never honestly really done that before in like a public area I found kind of like a couple of spots that I like knew where no one comes and like that is like fine to me like that's comfortable but I'm kind of in like a public park right now and it's like a beautiful lake with just like greenery around but like there's people so it's definitely out of my comfort zone and honestly just going on walks alone is kind of out of my comfort zone just because I don't know for one like I'm always just like really paranoid about people trying to kidnap me because obviously you always gotta like keep an eye out for that so that's kind of always on the back of my head but two I don't know it's just because I don't want to be lonely on a walk I don't know I just like something that I don't really do that often I have gone on walks alone with like my dog before but like never alone alone so we're here alone alone and we're gonna go on a hot girl walk which is basically like a trend that you kind of like put your headphones in and you just kind of like walk alone and you just kind of listen to music that like pumps you up and yeah that's basically what like a hot girl walk is so we're gonna do that and I also brought like my journal and everything and I really just want to sit down connected nature and journal and this is definitely out of outside of my comfort zone not doing the journaling and the meditating but doing it in a public place so gotta push myself because like I always want to do this okay I truly do always want to come to like area where there's lots of greenery and like pretty scenery but like I'm also scared of people judging me for some reason but like I don't know why like that just that's so stupid that's what we're gonna do brought my shit and it's gonna hot girl walk do some meditation some journaling in public and we got this it's a beautiful day I do see like the rain clouds coming so I feel like it's gonna rain any second now so let's get out before to start raining did some meditating journaling walking at the park it was so good like the weather was perfect when I was sitting the sun was just beaming on me and it felt so good like I am full of energy right now like nature and the sun oh my goodness like I feel like my battery is recharge to be honest and I just feel so mentally clear and mentally happy this is your sign to go out and just like sit in nature like you don't even need to go that far just find a tree even to sit against or somewhere peaceful just oh my god like I just feel so good I'm so glad that I did that so seeing people it's so cool to think that like everybody has their own little separate lives and you're the main character of your life and they're the main characters of their life and you've known nothing about them and they have their whole life that you know nothing about which is just so crazy that we're all strangers but we're all on this planet together experiencing this life on the same planet but we're all strangers to each other which is crazy but like in terms of like our core I believe that we're all connected on this earth because like we're all here for a reason together and we're all just here on earth together and I believe there's like a reason and I believe we're all connected in that way but we act like we're all just strangers which is so weird anyways okay so I think I'm gonna take myself out to sushi right now I don't think I've ever in my ever in my life like I'm trying to think back I don't think I've ever gone out to eat alone like completely alone just sat down at a table like at a restaurant I don't think I've ever done it like I'm I don't think I have I'm trying to think back so first time for everything I guess and that is definitely out of my comfort zone because like I don't know I just feel awkward going to go eat alone but like it's it should be so normal so we're doing that let's go to sushi I'm so hungry honestly so yay I'm currently at a sushi restaurant alone I just ordered a chicken teriyaki roll I'm so excited I'm actually so hungry I only have a smoothie today and then I love the house and now I'm really hungry so I can't wait it's actually peaceful being here alone I thought it'd be more boring but it's honestly kind of peaceful there's actually like another girl here that's alone too so my hey like I'm not weird for doing it like taking myself on a little date which is actually cute hey guys so I'm currently driving because I'm going to the mall with Julia she just kind of texted me and she was like do you want to go shopping the other day and I was like sure I can't really buy anything but just because my visa is maxed out because I just bought the couch I put a down payment on it but now since like we're actually getting it next week I had to like buy it so my visa is maxed out and I literally like I can't buy anything because I have no money so I'm just gonna go shopping with her I do like shopping it's something to do I mean especially with the weather being so crappy lately at least something to do you know what I mean like I was just thinking and I was like there's really not much to do when it's raining like when it's sunny you can just be like oh let's go on a walk let's go to the beach let's go to the park like there's a lot more things to do that's free outdoors but when it's raining it's like there's not really much selection so going shopping is just kind of something to do walk around browse you know what I mean even if you're not buying anything I still enjoy it so that's what we're doing and oh my goodness I we just had like the worst experience with the company that we bought our couch from it just has been the worst experience the worst customer service and and I really wanted to like promote this couch you guys it's so cute but like I don't want to promote this company at all because of the way that they've treated us I think I'll go more to depth into it like when I get the couch and tell you guys the whole story but it's just been honestly horrible and not just because of how long it's been delayed but also just like the way that they the customer services and like how they're treating us and what like they're not I don't know I will tell you guys when we get the couch and do more of a story time on that because there's tea there's tea on the couch and I do not want to promote them at all like typically every single like product and stuff that I show you guys and tell you guys is promotion for that brand even if it's not sponsored they didn't pay me to do it it's free promotion and so me putting the couch link in the description that's free promotion which I don't want to give them in the video when I get the couch just like really annoying me honestly and like I just don't know what to do because I know a lot of people are gonna want the link to it but they just don't deserve they just do not deserve to have that promotion because they suck and I don't want to be rude but they they've honestly kind of been rude to us just like a sticky situation and also my tongue is so very you guys like I burnt my tongue the other day on dinner I think I don't really remember specifically what I just remember burning it and it's just been burned for the past couple of days and I haven't been able to eat properly because of it and having a burnt tongue is really just shitty anyways that's like the least of my problems it gets fine it'll heal soon with every record I've been asking the masses to tune your hearts to me I represent intelligent niggas that grew up partially but lately I've been questioning second guessing whether or not I've got something the office inside of me losing poverty or has the money okay you guys so I literally said that I wouldn't buy anything but I bought stuff because there's a store like it's a random store in the mall that had a sale and it was like the tank tops were just like so cheap and I'm like I can't best look this opportunity because especially since the summer's coming up I feel like I'm always just like wearing random tank tops and it's nice to switch it up and even like I know this sounds kind of dumb but like even for filming it's nice to have like new clothes to wear to switch up the vibe you know what I mean I don't know I just bought a couple of tank tops with my debit card because my visa was maxed out because of the couch but anyways so I'm gonna give you guys a little bit of a haul it was I don't even know that remember the store name it was just random store in mall but anyways so I just got this basic gray tank top and I just don't really have a basic gray tank so this is kind of just perfect for the summer and stuff like this I wear all of the time just to have to throw on is so nice even in the winter I wear tank tops to you like so that's great and then I got this one shoulder top and I think that this color is so freaking cute and yeah just a little pop of pink one shoulder the materials actually really nice and like stretchy so one shoulder top this would be just so cute in the summer with like some sweatshorts or something in love with this and then the next thing I got is just a basic gray tank top but it has like stripes on it and I don't know I just like this and I feel like it would be really cute with just like sweatshorts so pants in the summer just like another tank to throw on and then I got this halter neck and I just really am have been in love with like this pattern recently like these colors together I love it so much and this isn't a medium I'm usually like a small but they only had a medium and I kind of just like tried it on over top of my sweater and it fit me so yeah it's so cute and it's just like a different vibe if I wear this with like shorts in the summer and it's something like different than just being a plain tank top you know so really like that yeah and then the last thing I got is just these yellow sweatpants they're a really pale yellow and they're just really baggy and comfortable I just can't have enough sweatpants because I I'm constantly you guys know this I'm constantly wearing sweatpants you don't want to go out staying home I'm always in sweatpants so these were so cheap and I was like you know what I have to take advantage of the sale okay I was like I think I think they were closing or something because everything was just like more than half off like it was so good yeah I honestly like really love fashion and I I don't know whatever I go shopping I always kind of have this limiting belief of like I can't spend too much money shopping like spending money on clothes is stupid and I have this kind of limiting belief about that in my mind that I kind of want to get rid of because like honestly shopping makes me happy and it's just like really fun and it's a way to express yourself like buying clothing and wearing clothing it's really a way to express yourself and so I think I just have to give myself more wiggle room with that it's like if I really like something I know I'm gonna use it I know I'm gonna wear it but it's a little bit more on the pricey side you know what like it's fine to just do it and not feel guilty about it I usually feel guilty going shopping just because it's not like I don't have the money to do it it's just because I'm like oh shit like was that done for me to spend my money on shopping I don't need it blah blah blah but sometimes you have to spend money on stuff that you don't need but that makes you happy just like when a Starbucks it's like do I need that no but it doesn't make me happy yes so it's kind of like the same thing and I just kind of like want to get rid of that you know limiting belief in my mind that like shopping is a dumb way to spend your money because honestly it's not and money is honestly energy you guys it's energy it's just at the end of the day it's just a number in a bank account and it's energy the more that you think that you have the more wealthy feel the more that you attract and vice versa and when I think about it like that it's like you kind of have to like spend your money to attract more money because you're not putting that limiting belief on yourself about money that like oh that's stupid to spend my money here because if you had unlimited money you would spend it however you want without feeling guilty so if you want unlimited money then you kind of have to match that vibration and match that energy that's something that I've been trying to kind of reprogram my mind to do but yeah money is literally an energy so gotta match that energy sometimes and obviously I'm not gonna go blow all my money on shopping that's not what I'm trying to say but like just not having like that limiting belief in my mind I feel like it's just like importance and I'm just trying to get rid of that and yeah so anyways that was my little mall haul Joel and me are just making dinner tonight I'm just gonna put this stuff away in my closet right now but I'm really happy with the stuff I got I mean it's not too much but it's still like a little bit like just spicing on my wardrobe a bit so also Eritzia if you're watching this calling out to Eritzia okay if you're watching this like I would literally die to get sent clothing I would die like please if anyone from Eritzia is watching this like please come my way my business emails in the in the description I represent intelligent niggas that grew up partially but lately I've been questioned


But let me first tell you about how the IPCC has been operating and how we've completed this fifth assessment report. Just to give you an indication, when we start an assessment cycle, we organise what is called a scoping meeting. And typically in a scoping meeting, as was the case this time, we have about 200 people and these are scientists, these are government officials and a whole lot of other very distinguished professionals who get together over a period of four or five days and then map out the outline of the report. What is it that the report should contain? Based on that, which is finalised by the panel as a whole, the Intergovernmental Panel incidentally consists of 195 member countries and all their decisions have to be taken by consensus. So the scoping document which is produced, as I just described, will then be presented to the panel. The panel may make some modifications and changes and finally approve of it. So that then becomes our charter for carrying out an assessment. And for the fifth assessment report, we actually carried out the scoping meeting in 2008 and then got moving with the assessment itself. In order to mobilise the best scientific talent from all over the world, we write to all the governments and several international organisations to solicit the nominations of authors and just to give you a set of numbers, in this last assessment we got roughly 3,000 nominations of excellent authors with their CVs and their track record of publications and so on and out of that we selected 831. And then they start working on the report and at various stages of the draft they send these out for expert reviews and the final version goes to governments as well for review by governments and they give us comments and each comment has to be taken into account. Now of course not all of them may be accepted but the authors have to consider each single comment and record whether it was accepted or not accepted. If it's not accepted then you have to assign reasons why a comment was not accepted. So I'm describing this only to highlight the fact that this is an extremely rigorous process and a very transparent process. It's not as though these are things that are done by a small group of people, overall each assessment is the final effort of thousands of scientists. Just to give you a set of numbers, the working group one report had 209 lead authors, they had 50 review editors. Review editors are like monitors, they make sure that every comment that is received from the review is taken into account by the authors and properly dealt with. And we got for the working group one report about 54,700 comments and the report itself assessed 9,200 scientific publications. The IPCC does not carry out any research itself. It basically carries out an assessment of published literature on a set of subjects and then comes up with an assessment. And similarly in the working group three report which came out less than a month ago, we had 235 lead authors and 38 review editors and we had about 10,000 references that were quoted in the report. And we received about 38,000 comments. So I merely wanted to start with this brief introduction because I'm afraid these are facts which are not very well known. Now some of the findings of this report and I'll go into the general findings in a short while. But let me say as far as forests are concerned, they are being affected by climate change in a variety of ways. Firstly forests have grown in different regions, different locations over thousands of years and they are therefore attuned to the climatic, the agricultural soil conditions of a particular location. But with changes in climate, clearly some of them may not be entirely suitable for a particular location. So as a result, there's a migration of species that is taking place. Typically if you are in a mountain area and you've got a certain set of species which grow in the lower reaches, then as let's say the temperature in the lower reaches goes up, then those species will migrate to higher levels, to higher altitudes. This actually is happening with all kinds of species. If you go to some parts of the world where there was a certain set of fish that were in abundance, typically with climate change you would find those stocks of fish moving to locations which are more in keeping with climatic conditions that existed where they were earlier on. So one of the implications of climate change is the fact that forests are going to move, trees are going to move from one location to the other. Another major impact of climate change is that we are seeing a substantial increase in heat waves as well as extreme precipitation events. Now in the case of heat waves, clearly your creating conditions, or the world is creating conditions by which fires will break out far more often and far more seriously. And that may be one reason that you find an outbreak of forest fires on the increase in different parts of the world, ranging from Australia to Russia to California and so on. So that's another one of the impacts of climate change on the forestry sector. And undoubtedly there would also be other impacts that might not allow certain species to grow in as healthy a manner as has been the case historically. But I'll say a little more about these issues. Let me go into some of the major findings of the three working group reports that we have brought out. Well, one major finding that we came up with was that warming of the climate system is unequivocal. And since the 1950s, many of the observed changes are unprecedented over decades to millennia. So in other words, in a short period of time, we have influenced the climate of this planet in a manner that has not happened for millennia. The atmosphere and the oceans have warmed, the amounts of snow and ice have diminished, sea level has risen, and the concentrations of greenhouse gases have gone up. And these are facts that I'm stating on the basis of observations and measurements that go back at least a couple of hundred years, in some cases even longer. Now, what's particularly relevant is the fact that each of the last three decades has been successively warmer at the Earth's surface than any preceding decade since 1850. So you can say, in fact, that in the Northern Hemisphere, the period 1983 to 2012 was likely the warmest 30-year period of the last 1400 years. And this means that clearly the rate of increase of temperature is going up. Now, it's also true that ocean warming in recent decades has dominated the increase in energy stored in the climate system. In fact, ocean warming or the heat absorbed by the oceans accounts for about 90 percent of the energy accumulated between 1971 and 2010. So as a result, we have found that the oceans have now warmed at least to a depth of 700 meters, and this has major implications for marine life and marine ecosystems. Not directly affecting forests as such, but after all, land areas are also affected substantially by what happens in the oceans because of changes in circulation, changes in wind patterns, and so on. But most importantly, this has major implications for marine species and marine ecosystems. Frankly speaking, not enough research has been done in this area, and there is some concern that warming of the oceans could have far more serious implications than we know at this point of time. The other thing that we have to be concerned about as citizens of planet Earth is the fact that on account of melting of the bodies of ice across the globe and thermal expansion of the oceans, the sea level has been rising, and it has risen much more rapidly in recent years than was the case earlier. So much so that we can say that the rate of sea level rise since the mid-19th century has been larger than the mean rate during the previous two millennia. So since industrialization, sea level rise has been much faster than the period going back two millennia in time. And in the period 1901 to 2010, global mean sea level rose by about 19 centimetres. So this may not be of great concern to a mountain top in Switzerland, but if you're living in an island nation, as indeed is the case with Indonesia, or perhaps even worse, the small island states and low-lying coastal areas as you have in Bangladesh, then there is a reason for concern. I also want to mention that all of this is driven by an increase in the concentration of greenhouse gases across the globe. And as a matter of fact, the atmospheric concentrations of carbon dioxide, methane, and nitrous oxide have increased to levels unpreferented in at least the last 800,000 years. Now here again, there is an important impact on the oceans in the sense that the oceans have absorbed 30% of the emitted anthropogenic carbon dioxide, and this is causing ocean acidification. This has already affected some of the coral reefs in different parts of the world, but we really don't know all the impacts that this is going to have on marine life and marine ecosystems. It's also true that the Arctic sea ice cover will continue to shrink and thin. The Arctic incidentally is warming at twice the rate of the rest of the globe. And so much so that based on some models, a nearly ice-free Arctic ocean in September before mid-century is likely for one of the scenarios, we have actually assessed four different scenarios for the future, and the one that I'm referring to is the one which you could call a do-nothing scenario. In other words, the world says we're not going to do anything about climate change. We're not going to reduce emissions of greenhouse gases. Let's continue with growth of these emissions, growth of the economy the way it is with business as usual. Well, in that case, we have assessed that by the middle of the century, you could have a September ice-free Arctic region, or at least Arctic ocean. So this clearly is a very serious change. I also want to mention that one of our findings was that if we want to maintain temperature increase below two degrees Celsius, and if we take into account all the greenhouse gases, then really speaking, we have a budget, you might say, or ranging from 800 gigatons of CO2 equivalent to 1,000 gigatons of CO2 equivalent. Now, by 2011, we had already used up 515 gigatons of this capacity because 515 gigatons is the cumulative emissions of anthropogenic greenhouse gases that have been produced between the period 1750 to 2010, that means in the period of industrialization. So we have a very small space that is available to us now if we want to maintain temperature increase below two degrees Celsius. And as it is in 2010, the world was emitting 49 gigatons of CO2 equivalent of greenhouse gases. And this 49 gigatons incidentally includes 10 gigatons, which have increased in the period 2000 to 2010. In other words, each year we are emitting one gigaton more than the previous year, beginning 2000. So it's interesting that we have a UN framework convention on climate change, which came into existence in 1992. We had the Kyoto Protocol, which was essentially the offshoot, and what you might say, the operational arm of the UN framework convention on climate change. But in terms of emissions of greenhouse gases, if anything, they are growing faster than any time in the past. So there is reason for concern, there is reason for action. I'm conscious of the time, so I'm not going to get into too much detail. But let me say that the risk of climate-related impacts result from interaction of climate-related hazards with the vulnerability and exposure of human and natural systems. And clearly, some human systems are far more vulnerable than others. As it happens, the impacts of climate change are extremely heavy for some of the poorest sections of society. And we have also clearly found that in those societies where you have a large difference between the rich and the poor, then both for developed and developing countries, climate change is likely to lead to expanding pockets of poverty. So if anyone in a prosperous nation believes that climate change is not going to be of any significance to them, is obviously wrong. Because climate change will have impacts across the globe. I already mentioned the fact that, excuse me, we'll have many more heatwaves and extreme precipitation events. Now these obviously cause a lot of damage.  In fact, I'd like to mention key risks across sectors and regions. Some are unique and threatened ecosystems that are already at risk from climate change. And climate change risks, of course, range from extreme events that I've mentioned, two of them at least. And these are generally unevenly distributed. They are, of course, across the globe, but there are some areas that are going to be far more vulnerable than others. I also want to mention that, excuse me, there's extensive biodiversity loss, which results from high risks around three degrees additional warming. So in other words, if we allow climate change to continue unmitigated, if we go to add three more degrees to average global temperature, then there's a huge and very serious loss of biodiversity that we would be confronted with. And in fact, so much so that if we allow temperatures to increase further, we could see some irreversible and abrupt changes. These incidentally could include things like complete loss of the Greenland ice sheet that would occur, of course, over a long period of time. And this, if it happens, could contribute to sea level rise, which could be as high as seven meters. Now I want to mention that there is an urgency in our being able to deal with climate change. And we need a set of measures involving adaptation as well as mitigation. It can't be that we confine our efforts only to one or the other, because in order to deal with climate change, you need a combination of both. Now in the case of mitigation, we have found for instance that, again, if you want to maintain temperature increase to below two degrees Celsius, then we would have to bring about a major change in energy supply. And another sector that would have to be targeted is what we call the AFOLU sector. But let me first talk about the energy supply sector. Well, what would be required by the middle of this century is essentially a trebling or quadrupling of low-carbon or zero-carbon energy supply. So this clearly means that we have to move very rapidly towards the use of renewable energy. We certainly have to improve the efficiency of energy use. And that will have to be done sector by sector, ranging from, say, transport to industry to, of course, even in our homes. And all of this is certainly within reach, because several of the technologies by which we can start implementing mitigation measures are available to us today. I also want to mention that the AFOLU sector, which is agriculture, forestry and land use sector, combined account for about 24% of the total emissions of greenhouse gases. And we therefore find that this is another sector which has great opportunities for mitigation. And towards the end of the century, if we want to stabilize emissions of greenhouse gases, such that temperature increase will not exceed two degrees Celsius, we would probably have to get into a zone of negative emissions. And that can only happen if we're able to use carbon capture and storage technologies and we're able to use bioenergy combined with carbon capture and storage. So I think the path that we have to follow is very clear if the world wants to limit temperature increase to two degrees Celsius. And that, in a sense, should be seen as an opportunity rather than something that would add a burden to different societies across the globe. And the good news also is that the cost of this pathway of mitigation is really very low. We have estimated that in order to bring about this kind of reduction in emissions, the loss in consumption per year globally would be no more than 0.06% of the global GDP. And if you want to look at this, let's say for a particular year like 2030, this would amount to barely 1.7% of the global GDP being lost in the form of lost consumption. But there are huge co-benefits in bringing this about. What are the co-benefits? Well, firstly, there would be much higher energy security. Secondly, the level of pollution at the local level would be much lower. Thirdly, ecosystems would be protected. Fourthly, there is growing evidence that even employment opportunities would be much higher. So if you look at the co-benefits, which often don't get accounted for, then clearly even this cost, which I mentioned of say 1.7% of the global GDP, will be reduced considerably. The other side of the coin is something that we should also look at. And that is the benefits of avoiding some of the worst impacts of climate change. And the worst impacts of climate change are going to be not only in the nature of the extreme events that I mentioned, heat waves, extreme precipitation events, but also in respect of the impacts on human health, on agriculture, therefore on food security. In fact, we have found particularly in the fifth assessment report that the impacts of climate change on agriculture are far more serious than what we had known earlier. And this is particularly so for crops like wheat, maize, and rice. The other day I was listening to a fairly enlightened discussion on what's going to happen to coffee plantations. Now coffee plantations and several plantation crops in general are very vulnerable to the impacts of climate change. And therefore you could see a significant decline in productivity in some of these areas. When that happens, the price of coffee would go up significantly. So if C4 is going to organize this meeting maybe 10 years from now, you would be better off not serving us so much coffee as you've generously been doing so far. So I think these are issues that we need to take into account. And the impacts of climate change, of course, in the case of sea level rise, can be quite harmful. We have estimated that if let us say we go along what I call the do nothing scenario, let's call the RCP 8.5 scenario, then by the end of this century we could get sea level rise of as much as 0.98 meters. That's almost a meter, I mean virtually a meter. And if that happens, then obviously the geography of the planet would be changed because there's some parts of the world which clearly would be submerged. What is even more serious is the fact that even those regions which are not going to be submerged will suffer from storm surges, from coastal flooding which would cause enormous damage even without being submerged. So overall I think dealing with climate change is essentially an exercise in risk management. What we need to do is to evaluate the risks of not taking any action and therefore the risks associated with some of the growing impacts of climate change and on the other hand looking at actions by which we can bring about a stabilization of the Earth's atmosphere by mitigating emissions of greenhouse gases and at the same time harvesting what one might call some of the numerous co-benefits from mitigation. So overall since I am conscious of the time and I should possibly end now, overall may I say that what we really are confronting is the possibility of some serious damages if we don't take action or setting on a course by which we bring about mitigation of emissions of greenhouse gases and in the bargain create a much cleaner planet, a whole set of conditions by which hopefully we would have a better world to live in and I also want to highlight in closing the fact that we have estimated if we don't do anything then indirectly there could also be the possibility of a disruption of peace because you can imagine in those parts of the world where water scarcity is going to increase clearly as a result of the impact of climate change we could have conflict taking place on a local basis which often has a tendency to multiply and become a global issue and there would also be a large scale displacement of people that can also create serious problems. So overall it's not merely a mechanical or an economic assessment that one has to be concerned with but also the very root of society, the very basis on which we have had tradition, societal practices and I would say the evolution of human civilization. Now this is something that is not a matter that could be exaggerated but I think these are issues that we need to take into account. So overall may I say that while forests are an extremely important part of the ecosystems that would be affected by the impacts of climate change and therefore we will have to take some adaptation measures at least for the next few decades because we are already locked into a certain level of climate change on account of the emissions that have taken place in the past and those that will take place in the next few decades but that in itself will not be enough. Adaptation will have to be combined with mitigation at the global level by which we are able to stabilize the concentration of greenhouse gases in the earth's atmosphere and that I think is the challenge that I think is the requirement that we have before us and I hope the science of climate change will be an important determinant of what human society does in order to give people and all species that live on this planet a far more secure and a better future. Thank you very much.