With the Watson A1-1325 medium format CNC milling machine, you can perform 3D milling, cutting, engraving, and cutting wood, MDF, chipboard, acrylic, plexiglass, PVC, composite, and soft metals. The basic version is equipped with a 3.2 kilowatt water-cooled spindle and ER20 collet chuck. The milling machine is used in light industry, woodworking, furniture production, interior and exterior decoration, souvenirs, outdoor advertising, industrial products, as well as in prototyping, model, and mold making. The size of the working area is 1,300 by 2,500 millimeters. Increased height on the spindle stroke in the Z-axis is 200 millimeters. The vacuum table makes it possible to fix the workpiece on the table without using additional fasteners. It is possible to install a T-slot slatted table. The 8 millimeter thick heat-treated machine frame is made of welded steel profile and reinforced with additional central bridges. The milling machine weighs at 875 kilograms. The durable, solid body neutralizes vibrations, ensuring that accuracy is maintained at all milling speeds. The framework is fired to remove stress. Therefore, you can be sure that the milling machine will not let you down during operation due to temperature or mechanical factors. Reinforced side posts of the cast iron portal are 21 millimeters thick. The increased rigidity of the portal allows maintaining positioning accuracy up to .05 millimeters. The portal is driven by two phase stepper motors with belt reducers using lead shine drivers. On request, our machines can be equipped with hybrid steppers or servo motors. All three. The reliable high wind guide rails with a thickness of 20 millimeters are part of the equipment. At the Watson factory, all guide rails and helical racks are milled and ground by a robot, as well as holes can be drilled. The installation is done manually. This ensures a particularly accurate setting of the guides. A mechanical lubrication system is used to lubricate all milling parts. The basic version of the milling is controlled via NC studio, but an optional DSP controller makes it easier to use and allows you to work directly from a USB stick. Download control files into memory. Adjust parameters during operation and fully exploit the mill potential. Watson A1-1325 connects to a computer via USB or DSU. Optionally, the milling can be equipped with chip evacuation, a swiveling device for cutting and engraving cylindrical workpieces, vibration supports, a portal leveling system, a tool sensor, an aspiration system and a coolant system, oil mist. If required, a more powerful spindle can be fitted, which speeds up work on some materials and is even suitable for machining aluminum. 18. Watson A1-1325 is a professional equipment that is suitable for any size of the production, including when working with soft metals. All machines are covered by a one-year warranty. If necessary, a specialist from your nearest accredited dealer or a factory employee can pay you a visit. You can always easily find all the necessary and universal parts in any region around the world. You can order the machines by any convenient delivery conditions. CIF, FOB, EXW, CPT. Watson Milling Machine's mission is to guarantee the highest quality of manufactured products. For more information about milling machine specifications and costs, please call or visit our website.


When my brother disappeared, we moved heaven and earth to search for him. I am still searching for him. He left when he was 14. If he is alive today he would be about 46. We just want to know what happened to him. I gave birth four months after he left Ethiopia. You see, you can imagine what happened to me. My heart is broken. He was the only one who took care of me and understood me. He found the land. I don't know how I am going to raise these kids. I sold everything I had to search for information. The sense of loss never leaves you. Living one's country in the midst of violence and losing contact with one's death or losing a family member brings all sorts of negative memories. At first I was trying to look for them but my situation made me stop. I was thinking if I find them, then what? I don't have any money, a place to stay or anything for them. I want to know where they are and if they are well. Many people don't have any idea how to even begin searching. Where should I go? Who should I speak to? I was all on my own.


Hello, ladies and gentlemen, I would like to take this opportunity to thank the International Deliccation Union Secretary-General, Mr. Haolin Sao, for his video message when we opened this ICD day in December 2015 yesterday. I thank you Secretary-General for your message and your very comforting to us to hear your message as we are rebuilding our country since Cyclonoma. I also wish to convey our congratulations to you and members of ITU as we celebrate the 150th anniversary of the foundation of the ITU and we also in the Pacifica are also celebrating this important event. I also wish to thank ITU, in particular Mr. Rahima Sanu who contributed to our Cyclon relief in providing satellite telephones which were very useful when we tried to reach our isolated original senders when most of the telecommunication facilities were down during the Cyclon. Your assistance was very much appreciated by government and the leaders in the provinces. I also wish to thank the contribution given by the ITU Regional Office for Asia and the Pacific, particularly Mr. Sami Salma which with us today and his contribution to this ICD days. Thank you once again ITU for your support during Cyclon bomb and once again I wish you all the best as we celebrate the 150th anniversary of the ITU. Thank you.


Yeah, Energy Justice in Hawaii here at four o'clock on Think Tech. I'm Jay Fiedel and we're co-hosting today. Me and Ali Andrews. Hi, Ali. Hi, Jay. So I want to talk today about weather and to the extent, is Hawaii resilient to extreme weather here on Energy Justice? Because we know that if we don't have resilience, certain parts of our demographic are going to be affected more than others. And usually, as usual, it's the people who are disadvantaged who are affected worse. So there's no justice in not being resilient. It's just Aristotelian. So the question is raised by what happened in Texas a few months ago with their failure to be resilient against a cold snap. I guess it was a really bad cold snap. And what happened in New Orleans just a couple of weeks ago, which is much scarier in the sense that in New Orleans, they had the opportunity to put their power lines underground and they didn't do anything about it. The government didn't do anything about it. And then when the storm came, the towers blew over, the poles blew over, and I think most of New Orleans and on Iran are still now today without power. And that means the people who were disadvantaged without power because the other guys left town already. If you have a few bucks, you leave town. So it's really a problem if you're not resilient. The other thing is, I don't want to tell you anything you don't know, Ali, but we are in climate change and it is getting worse all the time. That's probably why you care so much about energy and energy justice. And although the media doesn't necessarily associate these extreme weather situations and wildfires with climate change, they're definitely part of climate change. They're caused by climate change. Give me a break. We should all know that and live that all day long. And Congress should know that, but unfortunately it doesn't know that. So the problem is that climate change, extreme weather can affect, and we see wildfires too, and drought and flood, all those things are all part of climate change increasingly. And the connection is so obvious. One of these days, Oahu, the most populated island, is going to get a storm. We've been so lucky. And it's going to get a storm when we have a lot of overground electrical connectivity, and towers, and telephone poles, and all this. It's coming. I wake up in the morning, I say to myself, today, what a beautiful day it is. One day closer to the next extreme storm, which will be worse than any storm you can imagine. So that's the problem. And the question before the House is, are we resilient to that storm? And if we are not, what is going to happen to our energy systems? And what is going to happen to the people who are disadvantaged, those who would be affected more than others, by the failure of our energy systems? It really counts. When there was that storm that wasn't Maria in Puerto Rico maybe four or five years ago, now there was a huge field of solar array. And one half the field, we know this because we had a show about it. One half the field had a certain kind of fastener holding down the anchors and the solar cells. And the other side of the field, about half divided, had a different kind of fastener. And when the wind came from Maria and blew through that field, the field with one kind of fastener, it just got destroyed. All the solar arrays, all the anchors all finished on.  So the point is, it really makes a difference if you plan ahead. If you look at those fasteners, if you make things resilient. Now, I know you're an energy buff to the max. And I want to know your thoughts about this. Okay. How resilient are we? Wow, just coming right out there with the big question right away. First of all, thank you for having me on. I'm still grateful to be here either way. And I think this topic is really interesting. I don't, I will admit that I'm not a huge expert in resiliency in general, but you are correct that I am an energy nerd and like to think about this a lot, particularly that question that you posed around what happens to our frontline communities, our most vulnerable communities, which we know from the events though I storm in Texas this winter, and the current outages that are happening in New Orleans, that are low income communities, our communities of color statistically are the ones who are left without power for longer or experience those more extreme impacts because of losing power, because of lack of access, as you said. I would say without being a resiliency expert, I think that renewables in general make us resilient to those events that would isolate us from external resources for longer. If we are dependent upon fossil fuels coming to our islands, those do not come from here. Those come from very far away. So if the ports or the way that we receive those fuels cannot enter, then we have a finite use source. I'm sure that we have a pretty large backup, but the sun comes every day, the wind comes every day. So I think in general renewables and battery storage are looked to as being more resilient. So as Hawaii does the good job of shifting towards renewable energy, I believe that makes us more resilient. And I think that there are also ways of deploying those renewables in ways that make us more resilient, in ways that distribute the energy rather than centralize it. There is a big movement around distributed energy as providing more resilience. The closer it is to where we use it, the less dependent we are upon the infrastructure that has to take to us, aka the distribution lines and the transmission lines in some parts of the island. So if we have a failure in those channels, in those distribution and transmission lines, distributed energy is better. And I think that's a huge buzz. Why we hear so much about micro grids these days is the ability for micro grids to provide that safety, that isolation, that backup in a severe case. I think for me, one of the big questions is those systems historically have cost more. And so micro grids as awesome as they are, and as much as I love to hear about their buzz and the new technologies that enable them, they still do micro grids cost more than not having that islanded backup ability. I think that should be on the final exam, Molly. The question on the final exam would be, does resilience cost more? And the answer is yes. What would you rather have? A blackout like in New Orleans that lasts for days, weeks, months, maybe more? Or would you like to have your power back? And people don't realize what happens. Wake up in the morning, nothing works in your house. You want to watch the tube, no tube. You want to do internet, no internet, no nothing. What's that worth? Anyway, there's a question. It's funny that you should raise that because there's a question I want to read it to you from a viewer, viewer question. We appreciate all viewer questions, question. What is the value of resilience? I guess that means the value economically. And what is the cost of resilience? Who pays, who should pay for the cost of resilience? And this is something you've covered tangentially. Does having solar panels on your roof make you more resilient? Okay, that's a compound multiple question, but let's see what you can do with it, Ali. I will start with the last one first. I think in general, having solar panels on your roof does not surprisingly ensure that you will have power in the case of a power outage. In fact, most rooftop installations are connected to the grid in a way that the utility has the ability to shut it off as soon as there's an outage on the line in general. And there's a safety reason for that, because if they're sending out individuals line people to service the lines and you, they think that the power is out on this circuit, but your solar system is sending power on the grid, that can be a very dangerous situation. I'd suggest that I'm better off if I'm free of the grid. Thank you, but I don't want to be connected kind of thing. Now, a lot of people wouldn't do that because they want to back up from the utility, but if you did do that and you weren't connected, this problem would not exist, right?  I would say that there are ways now, particularly with more batteries, that you can have a system, at least in California anyways, and I assume that the same is true in Hawaii, that you can have a rooftop system as long as it's connected in the right way to be able to island itself and you would be able to use that. You know, one of the things that has happened in New Orleans is that people have brought in generator systems, generator sets, running fossil fuel into their homes in order to generate power for all those things I mentioned, you know, right down to your electric toothbrush, you know, and these generator sets have exhausts and the exhaust has noxious toxic fuel fumes and so they have actually died from the fumes of these generator sets being used indoors. So there's a certain danger in doing the generator sets, but it also strikes me that if you have solar panels on your roof and whether or not you're connected to the grid, and for this discussion we'll assume you're not connected to the grid, and those solar panels are feeding the rest of your house except that, you know, the wiring was damaged, the panels, the system was damaged, and you're in the house and it's feeding, you know, electricity into the house and it's broken. There's a danger there too, isn't there? I would guess you are right, yes, without being an electrician I cannot confirm the full certainty, but yeah, I guess that probably would create a dangerous situation in some cases. I have to be able to turn it off. Anyway, okay, so the rest of my question or the viewer's question is what is the value economically of resilience to you and to the community? This is a wonderful question. And what is the cost of that resilience to you or to the utility or to the community? And I suppose that all that means is who enjoys the value of the resilience and who pays the cost. I think there's an answer that the energy industry, I think there's not one answer to the value of resilience, but there's a there's a way that the energy industry tries to monetize, to account for the monetary value of resilience, but Jay, I might put this on you for a moment. How much do you think, let's say you were expecting in the future for one power outage that would last a full day every year? How much would you be willing to pay extra to Hawaiian Electric if you got to keep power during that full day that would just happen once a year? Okay, that's me now. I am not particularly disadvantaged, although my wife thinks I am. I would pay whatever the freight was. I would pay whatever it was. I believe in resilience. I believe in survival, not only for me and my family, but also for the community. So I would pay whatever whatever cost, whatever the actual cost was, I would pay that. And if utility calculated it at X dollars, I'd be happy to pay that. However, I would like to add, pursuant to the title of our show, there are some people that can't afford that. They may make a much closer analysis of it. You want $100 for me for resilience for one day? I can't afford that. I'm out of work, COVID has busted my budget. I'm in terrible shape. I'm not even paying my electric bill now, much less then. So it would be a different answer for different demographic groups, wouldn't it? Yes, yeah, I think that's exactly right. I think and also different groups and how necessary electricity is to them on a daily basis. I think when you're talking about Texas during a winter storm, a lot of the attributable deaths in Texas were hypothermia related. And so if you don't have electricity, that means something more dire than hypothermia related deaths here in Hawaii. In the Central Valley in California, which I have lived for a couple of years there, when I lost power for three hours at the hottest time of the day, I was 105. And it was time to have the AC on. I was very uncomfortable. And I think others would be in an even more uncomfortable situation if they were dependent upon that, if they were elderly, if they had medical devices. So I was reading a study earlier today about the value of lost load. The VOLL is an acronym in the energy industry. And it varies from a dollar per kilowatt hour, which a kilowatt hour is a unit of electricity. We typically use about three to 500 of those units in a month here in Hawaii in a household. So a dollar per kilowatt hour to $300 per kilowatt hour, depending on what you're using that electricity for. If you're a hospital, you're on the other end of the spectrum. If you're Allie, who's kind of uncomfortable and sweaty in her apartment in Fresno for three hours, you're probably on the $1 end of the spectrum. And having the resources to be able to adapt to loss of electricity, just like you mentioned before, that you can leave town. I think there was a senator who got criticized in the Texas ice storm for heading off on a semi-tropical vacation in the middle of the ice. Everybody knows Ted, he's a friend of the country in his own strange way. The country meeting Mexico. Let me make a distinction for you, Allie. And that is, you mentioned, I think it's really important that renewables, specifically solar, are resilient because they don't require outside help, outside fuel, and so forth. But that is not necessarily the test of resilience because you could have a fossil fuel. I think this would be clear for the analysis. You can have a fossil fuel system. One of those generator sets has been running for longer than I have, which is really a long time. You can have that running on fossil fuel, and you have to be resilient with that too. So renewables do not solve the problem completely. I guess the problem with the old-fashioned renewables with fossil fuel is if I have a generator set that's old and it breaks, I have engineering issues. I have to find an engineer who was around when it was designed. I may have to go to long distances to find replacement parts, and that's not resiliency at all. That's the opposite of resiliency. If, for example, this generator set was made in Germany or somewhere in Europe, Scandinavia would have you, we know they do manufacture, they have manufactured this equipment. It means I have to call a right and get them to ship that air freight, hopefully, and if it's a big, heavy piece of equipment, it's not going to be air freight, so I can start up that generator again. That's not resiliency, is it? Yeah, I think that's a really good point. I think the parts are a really good point, as well as the labor. I think having local individuals who are knowledgeable about operating, maintaining problem-solving our renewables is super important, and local workforce development is another reason for that. I mean, another component of that. I think the group that has come onto the show before that I worked with on Moloka-i, the whole Afu Energy Cooperative Moloka-i, that's a huge effort of theirs is we're not just going to build this with outside labor and maintain it with outside labor, both because we want local economic development and we want our community to know how to repair, maintain in moments of crisis and in moments of not crisis. I think that makes us resilient, as well, if we are all not, maybe not all of us need to be knowledgeable, but we need to have people among us who know what's going on. Well, let's talk about justice for a moment. So, suppose it cost me X dollars to be resilient. Whatever system I'm using, however I'm connecting or not, whether I'm using, for example, community solar, whether I'm using fossil fuel generators, it's going to cost some money. Now, what is the equitable allocation of that cost? It's really important, especially in a time when people are economically stressed in our community and they don't have money and how are you going to raise that sum? It could be expensive and maybe it should be expensive. It should be, you know, what is President Biden saying? Build back better. Don't just have resilience to achieve what you already have. Have resilience to achieve better than what you already have. So, my question is who pays the freight? How do you allocate that in accordance with, may I say, energy justice? I think that it's an amazing question and I think that our, I'm going to just solve it for us real quick in the next seven minutes that we have. I'm not going to do that, but I believe that the reasons that are some of our low-income communities and communities of color are more vulnerable are due to systematic oppression. And so, just giving everybody a hundred dollars across the board per household to make yourself more resilient is not going to create an equitable situation. It's going to perpetuate the inequities that have led us to some neighborhoods being more vulnerable to outages than others because of the resources that the utility has prioritized to keep the lights on for the hospital in this neighborhood versus the just purely residential over here. So, I personally believe that the system as a whole, that the ratepayers as a whole need to pay for the resilience that brings us all to the same vulnerability. And hopefully that's the same resilience, not the same vulnerability because that's taking a negative tone on it. But I believe that electricity is a human right and access to that should be equitable equal access. So, how do you raise the money? Do you include it in the rates that people pay? Some of them aren't paying any rates, they're, you know, they're not able. And do you include it in the somehow you make the utility company pay out of their funds? Do you make the state pay? Do you spread it among the taxpayers, the ratepayers of the utility? Where are you going to get the money to build back better? Wow. Okay. All right. I think I can answer that. I think that the ratepayers, the people who have chosen to be on the grid system on our shared system and share in those resources, I think that recovering those costs across all of our ratepayers makes sense. And keeping, as you mentioned, you know, some folks have assistance on their utility bills from federal subsidies. And I believe that those should stay in place because I think, again, those are addressing systematic inequities. So we shouldn't take those out so that everybody pays their fair share of resilience. But I think I support those systems staying in place as well as these extra costs that we are going to incur over the next several years will hopefully pay off. Like they're going to cost us money now. But as PG&E's CEO was arguing when they were arguing for, I think it was $15 billion worth of transmission cost upgrades to bring their transmission lines underground. They said it's a huge cost now, but we're going to save money in the long run because we're going to cut out the risk of wildfires and the loss of property and life as a result of that. So I think if we share the cost now, we will share in the benefits later. That's the takeaway. That is so important. What you just said, that is really, that is also going to be on the final exam. Okay. The other thing is the essential question, the title question, we need to answer I think in greater detail. And that is, you know, how resilient is Hawaii right now? Remember that Hawaii is, you know, 2,500 miles away from the mainland. It's not clear that anybody's going to come and save us or repair our equipment, refurbish our, you know, broken equipment. Nobody's going to come from Asia. We may or may not have the workforce or the equipment or spare parts. We probably don't in order to repair everything. And looking at the footage that came out of New Orleans, those towers fall down. The wind blows them right over. And, you know, it's not like we have a storehouse of new towers that we can replace. We have to bring them in. We have to build them and so forth. And we have towers in Hawaii that would fall over in extreme weather for sure. We also have the telephone poles in so many neighborhoods, including my neighborhood where, you know, it's for sure they would fall over and somebody's got to build them back. So the issue in New Orleans was why didn't we bury these lines a long time ago? Not the same issue exists here. Why didn't we bury these lines a long time ago? We would be so much more resilient if we had done that. Can we do it now? It's not going to be cheap in any way, including legally, to bury them. So, query, how resilient are we now, Ali? This is not an easy question. And maybe the answer is not very, either. Okay. I think that's a question that I'm not very well equipped to answer just because there are lots of uncertainties in that. What I do know is that I learned that about the 3,000 miles of Hawaiian electric-owned distribution and transmission lines across the Hawaiian electric territory, I did not look up about 40% of those lines are underground already. So underground lines tend to be more resilient, although they do have their own risks to people digging them up when they're building new things or planting a really deep garden. And they're more prone to potential water damage because they're under the ground there, which is another vulnerability that we have with sea level rise. And I know that in new development, there's a policy around underground lines. If a new development, I think it's over four units gets built, then they go underground. So there's a movement generally towards undergrounding. But I think it's something like a million dollars a mile, or maybe it's three quarters of a million dollars a mile somewhere around there for building a new underground distribution line. So multiply that by 60% of 3,000 lines. I could get out my calculator, but that's a pretty penny. Yeah, one thing strikes me from what you said with the 60%, 40% and all that is the weakest link is the one that determines resiliency. If I have one part of the system that's not underground and it feeds the part that's underground, and a storm comes, the whole thing is going to go down. So you've got to put it all underground. Ultimately, that's better resiliency. I agree with you that maybe it's subject to water, but that can be dealt with. I think wind is a more serious problem for extreme weather here in Hawaii. But let me, we don't have a lot of time left, and I want to ask you another compound question.  It's looking at Christmas future with Ebenezer Scrooge, if you remember. And I don't mean to refer to his willingness to spend money, by the way. So what is your warning to all of us about the dark side of the future if we do nothing to enhance our resilience? If we do nothing for whatever reason it might be to make our systems more resilient. And the second part of that question is if we were to do something to meet that warning, that admonition, that dark side out of Charles Dickens, what would we do? What step would we put out first? What would the action point be? Okay. The first part of the question was sort of the pessimistic. What are we in for if we do nothing? And I think that's a scary thing to think about. But we've probably seen some flashes of what's to come. Flashes may be flash flooding, flash storms. I think that what is happening in New Orleans right now with over 400,000 people still being without power, I think we could see a very real scenario like that in 40 weeks after a storm. If we do not address the infrastructure issues, I'm not much of a doomsday or so. I'm going to focus on the second part of your question, which is more about what should we do to address that. I think that the most powerful way to make our communities more resilient is to tap into the knowledge of what our communities already know about what risks and vulnerabilities there are. I think I have learned so much from working with the Moloka'i community about where good places and bad places to develop are, what areas are vulnerable to flooding and not at what times of year. And I've only just scratched the surface of that discussion. I think that there's a lot to learn. And there are already communities that are taking steps towards that. I learned about an awesome resiliency hub that is spearheaded by a community group to create a resilient hub that can serve as a multi-use shelter in the case of bad weather. That's an awesome project. I think more projects like that where we use local knowledge, we build up local capacity to know and maintain and repair and construct. I think that's where we're going to be resilient both to outages and from a social and economic perspective. I think that's how we become resilient. You know, a lot of the best laid plans of mice and men and women in Hawaii get put on the shelf and we do a great job at talking it up and then we don't do action. And that's deeply ingrained in our DNA and our culture here, I'm sorry to say. And this is a time in climate change where we really can't afford to be like that. So my last question to you, Alec, to what extent do the experiences in Texas and in New Orleans, to what extent are they wake up calls or should they be wake up calls for us, the consumers, for the utility, for the legislature, for the governor? To what extent should we be concerned and treat that as a wake up call to get on it and develop action points? I think to a huge extent that's a wake up call. And I think that is something that seeing the devastation that has happened, the loss of life, the loss of property, the pandemonium, I think that that is certainly something that can and well I won't say will. But it could happen here for sure. And I do think that it's a huge wake up call. And I think it's something that our frontline communities have been aware of for a long time. And I think it's that vulnerability, that sense of we need to be resilient for ourselves. That I think we need to heed their voices and their call in this as well, take their lead. And yeah, I think you're exactly right. It should be a call to action for all of our people in power who can help make a difference, direct resources and direct policies to booster, bolster, bolster our resilience. Alie Andrews, energy nerd, energy follower, energy justice person, community person. Thank you so much for for having this discussion with me. And I'm looking forward to your next show two weeks from now. Alie Andrews, thank you very much. Aloha. Aloha. Thanks, Jane.


From DailyDoseOfWeirdNews.com, I'm Darren Marlar and this is your Daily Dose of Weird News. ***Nearly one in four millennials live with their mom. The other three millennials don't live at home, but they still visit daily for food and laundry services. Your diet might be changing soon for the more disgusting. Scientists believe that the cockroach milk produced by the Pacific beetle cockroach could one day become the ultimate superfood. The Pacific beetle cockroach is viviparous, meaning the female gives birth to live babies that have developed within their body, instead of laying eggs. As the embryos grow inside the mother's body, she feeds them a pale yellowish liquid like milk that scientists discovered has three times the energy content of buffalo milk, making it one of the most nutritious substances on Earth. Researcher Leonard Chavez told CNN, ***It's what one would need, protein, essential amino acids, lipids and sugars. The nutritious substance can be extracted in either liquid or crystal form through a process called cockroach milking. However, as you might have guessed, milking cockroaches is not the easiest thing in the world to do, not to mention that it reportedly takes a thousand cockroaches to harvest only 100 grams of milk. So for the time being, scientists are looking at ways of re-creating the stuff in the lab, or coming up with a cockroach milk pill. De Beers is going to begin selling diamonds that are made in a lab. ***Don't we already have that? It's called cubic zirconia. Easy on that cinnamon, that advice from Denmark's food authority has rankled pastry chefs whose cinnamon rolls were found to violate the European Union's spice rules. Danish veterinary and food administration recently discovered that Danish cinnamon rolls and twists contained more coumarin, it's a chemical compound in the most common variety of cinnamon than the EU rules allow, so the agency asked Danish bakers to reduce the amount of cinnamon that they sprinkle in the dough for sweet treats like the cinnamon roll and cinnamon twist. Danish bakers protested, saying the EU limit is too strict and would make it hard if not impossible to make their cherished pastries. Now I'm confused here, since when did former New York Mayor Michael Bloomberg move to Denmark? The NBA Championship Series will feature the Golden State Warriors against the Cleveland Cavaliers. Again, this makes the fourth year in a row. Hey, here's a suggestion, why don't we call them the deja vu games? Mexico is looking to battle the bulging waistlines of its children by banning the sale of junk food in its schools, including many of the traditional treats generations of kids have grown up with. Getting the axe along with modern soft drinks and sweets will be salted tamarind candy, pork rinds and a toll, which is a thick and sweet cornstarch-based beverage served piping hot in the morning. On the plus side, candy-filled pinatas are still allowed because they're good for cardiovascular exercise. How's this for embarrassing?  Crews at the station found heavy smoke inside the front bay around 1pm. Assistant Chief Sharon Davis said firefighters were able to start the truck and pull it outside away from the other equipment. They then worked for about 15 minutes to put the fire out. Davis said they believed the fire was electrical in nature and didn't know if the truck could be salvaged. So far they have no one to blame, but the fire chief is definitely hot under the collar and might fire someone before the heat dies down. Meghan Markle now has her own official coat of arms. I guess a jacket with just two arms isn't enough for royalty? While fires strike suddenly and unexpectedly, destroying homes, taking lives and costing billions of dollars every year. Well, now scientists say that new satellite technology developed by NASA could help predict where fires will strike next. According to Time magazine, the system, known as Firesat, uses infrared sensors to identify wildfires when they have grown to be at least 35 to 50 feet wide. Detection by the system occurs within 15 minutes of the beginning of that fire. Next, they hope to create another early warning system to let people know of oncoming Kardashians. Andrew Lincoln is going to be leaving The Walking Dead this next season with Norman Redis taking over the lead role. They plan to have Rick just walk off limping into the sunset, much like the latest ratings of The Walking Dead. Residents of Papua New Guinea will have to forget about using Facebook for a month. The country's communication minister, Sam Basil, says his government plans to ban the social media side for a month to call out fake users and see how Facebook is affecting people's lives. Is it possible to go a full month without Facebook? Do they have medications to make available for those who suffer withdrawal? Fruit Loops cereal is added a new flavor, wild berry. I can't help but think the word ask or ish should be added to that. Before you check out, remember that the hotel towels aren't yours. And just because they are owned by a big corporation doesn't make it right to steal them. Visitors steal roughly $50 million worth of towels every year in the United States. You know, I am suddenly feeling guilty about taking that half-full bottle of conditioner. Disney World announced they are finally serving alcohol at every restaurant in the Magic Kingdom. It's their last-ditch effort to make Stitch's great escape somewhat entertaining. Over in Indonesia, police say 10 passengers on a lion-air flight preparing to take off from Borneo were injured after a passenger falsely claimed there was a bomb on board. Thousands of the injuries were head wounds and broken bones as the 189 passengers panicked and scrambled to get off the plane. Videos showed dozens of people standing on the Boeing 737's right wing. Some slid down the right engine and landed on the tarmac. Police say 26-year-old friend Tina Snoriji told a flight attendant there was a bomb on board. Another passenger broke the emergency exit windows. Both men were arrested. Police inspectors, by the way, found no bomb. You gotta admit, though, that is a good way to clear out some space to get more leg room. A new study says people adding more seafood to their diet can improve their sex lives. Yeah, maybe so, but I am still not eating oysters, unless they're covered in Cheetos dust.  In a survey, one in five Americans said, yeah, they would. Hey, can I add something else to the tattoo, then? I mean, along with the letters IRS, if so, I'd like to add the letter F at the beginning and the letter T at the end. See, there you go. Now stop taxing me into oblivion. The oceanfront estate in San Clemente that was once owned by Richard M. Nixon and known as the Western White House during his presidency is back up for sale at $63.5 million. An opportunity if they can somehow, somewhere against all odds, find somebody who admires Richard M. Nixon. A Dubai couple's marriage has got to be a contender for the title of shortest marriage in history. It seems the groom asked for a divorce less than 15 minutes after the wedding ceremony. Sadly, the reason comes down to money. Specifically, the dowry payment he had agreed to pay the bride's father. As per the contract, the groom and his father-in-law had signed, the newly married man agreed to pay the bride's father $100,000, which is about $27,000 in two installments, half up front and then the other half after the wedding. But the newly married man asked the bride's father to wait just five minutes, assuring him that the money was in the car, but the father-in-law insisted the groom send somebody to get the money so he could be paid immediately. As the whole, ugly exchange played out in front of the newly wed's friends and family, the groom became embarrassed and insulted, so he marched right back into the courthouse and divorced his wife less than 15 minutes after marrying her. Which you can totally do over there. Thanks, Daddy!


Live from San Jose, it's theCUBE, presenting Big Data Silicon Valley, brought to you by SiliconANGLE Media and its ecosystem partners. Welcome back to theCUBE on day two of our coverage of our event, Big Data SB. I'm Lisa Martin, my co-host is Peter Burris. We are down the street from the Strata Data Conference. We've had a great day yesterday and great morning already. Really learning and peeling back the layers of Big Data challenges, opportunities, next generation. We're welcoming back to theCUBE an alumni, the CMO of Connecticut, Dan Raskin. Hey, Dan, welcome back to theCUBE. Thank you, thank you for having me. So, I'm a messaging girl, look at your website, the insight engine for the extreme data economy. Tell us about the extreme data economy and what does that mean for your customers? Yeah, so it's a great question and from our perspective, we sit, we're here at Strata and you see all the different vendors kind of talking about what's going on and there's a little bit of word spaghetti out there that makes it really hard for customers to think about how Big Data is affecting them today. And so what we're actually looking at is the idea of the world's change, that Big Data from five years ago doesn't necessarily address all the use cases today. If you think about what customers are going through, you have more users devices and things coming on, there's more data coming back than ever before. And it's not just about creating the data-driven business and building these massive data lakes that turn into data swamps, it's really about how do you create the data-powered business. So when we're using that term, we're really trying to call out that the world's changed that in order for businesses to compete in this new world, they have to think about how to take data and create core IP that differentiates. How do I use it to affect the Omni channel? How do I use it to deal with new things in the realm of banking and fintech? How do I use it to protect myself against disruption and telco? And so the extreme data economy is really this idea that you have business in motion, more things coming online ever before. How do I create a data strategy where data is infused in my business and creates core IP that helps me maintain category leadership or growth? So as you think about that challenge, there's a number of technologies that come into play. Not the least of which is the industry, while it's always to a degree been driven by what hardware can do, that's moderated a bit over time. But today, in many respects, a lot of what is possible is made possible by what hardware can do and what hardware is going to be able to do. We've been using similar AI algorithms for a long time. We didn't have the power to use them. We had access to data, but we didn't have the power to acquire it and bring it in. So how is the relationship between your software and your platform and some of the new hardware that's becoming available, starting to play out in a way of creating value for customers? Right, so if you think about this in terms of this extreme data concept and you think about it in terms of a couple of things. One, streaming data, just massive amounts of streaming data coming in. Billions of rows that people want to take and translate into value. And that data is coming from? And that it's coming from users, devices, things interacting with all the different assets, more edge devices that are coming online. And, you know, the Wild West essentially. You know, you look at the world of IoT and it's absolutely insane with the number of protocols and device data that's coming back to a company. And then you think about how do you actually translate this into real-time insight? Not near real-time where it's taking seconds, but true millisecond response times where you can infuse this into your business. And what one of our whole premises of Connecticut is the idea of this massive parallel compute. So the idea of not using CPUs anymore to actually drive the powering behind your intelligence but leveraging GPUs. And if you think about this, a CPU has 64 cores, 64 parallel things that you can do at a time. A GPU can have up to 6,000 cores, 6,000 parallel things. So it's kind of like lizard brain versus modern brain. How do you actually create this next generation brain that has all these neural networks for processing the data in a way that you couldn't? And then on top of that, you're using it not just the technology of GPUs, you're trying to operationalize it. So how do you actually bring the data scientist, the BI folks, the business folks all together to actually create a unified operational process? And the underlying piece is the Connecticut engine and the GPUs to do this, but the power is really in the use cases of what you can do with it and how you actually affect different industries. So can you elaborate a little bit more on the use cases in this kind of game changing environment? Yeah, so there's a couple of common use cases that we're seeing. You know, one that affects every enterprise is the idea of breaking down silos of business units and creating the customer 360 view. So how do I actually take all these disparate data feeds, bring them into an engine where I can visualize concepts about my customer and the environment that they're living in and provide more insight. So if you think about things like whole foods and Amazon merging together, you now have this power of how do I actually bridge the digital and physical world to create a better omnichannel experience for the user? How do I think about things in terms of what preferences they have, personalization? How do I actually pair that with sensor data to affect how they actually navigate in a whole food store more efficiently? And that's affecting every industry. You could take that to banking as well and think about the banking omnichannel and ATMs and the digital bank and all these fintech upstarts that are working to disrupt them. A great example for us is the United States Postal Service where we're actually looking at all the data, the environmental data around the US Postal Service. We're able to visualize it in real time. We're able to affect the logistics of how they actually navigate through their routes. We're able to look at things like postal workers separating out of their zones and potentially kicking off alerts around that. So effectively making the business more efficient. But we've moved into this world where we always used to talk about brick and mortar going to cloud. We're now in this world where the true value is how you bridge the digital and physical world and create more transformative experiences and that's what we want to do with data. So it could be logistics, it could be omnichannel, it could be security, you name it. It affects every single industry that we're talking about. So I got two questions. What is Connecticut's contribution to that? And then very importantly as a CMO, how are you thinking about making sure that the value that people are creating or can't create with Connecticut gets more broadly diffused into an ecosystem? Yeah, so the power that we're bringing is the idea of how to operationalize this in a way where again you're using your data to create value. So having a single engine where you're collecting all this data, massive volumes of data, terabytes upon terabytes of data, enabling it where you can query the data with millisecond response times, visualize it with millisecond response times, run machine learning algorithms against it to augment it with, you still have that human ability to look at massive sets of data and do ad hoc discovery but can run machine learning algorithms against that and complement it with machine learning. And then the operational piece of bringing the data scientist into the same platform that the business is using so you don't have data recency issues is a really powerful mix. The other piece I would just add is the whole piece around data discovery. You can't really call it big data. If in order to analyze the data you have to downsize and downsample to look at a subset of data. It's all about looking at the entire set. So that's where we really bring value. So to summarize very quickly, you are providing a platform that can run very, very fast in a parallel system and memories in these parallel systems so that large amounts of data can be acted upon. That's right. Right, so the next question is there's not going to be a billion people who are going to use your tool to do things. How are you going to work with an ecosystem and partners to get the value that you're able to create with this data out into the hands of an enterprise? Yeah, it's a great question and probably the biggest challenge that I have which is how do you get above the word spaghetti and just get into education around this? And so I think the key is getting into examples of how it's affecting the industry. So don't talk about the technology and streaming from Kafka into a GPU powered engine. Talk about the impact of the business in terms of what it brings in terms of the Omni Channel. You look at something like Japan in the 2020 Olympics and you think about that in terms of telco and how are the mobile providers going to be able to take all the data of what people are doing and relate that to ad tech, to relate that to customer insight, to relate that to new business models of how they could sell the data. That's the world of education we have to focus on is talk about the transformative value it brings from the customer perspective, the outside in as opposed to the inside out. On that educational perspective, as a CMO I'm sure you meet with a lot of customers. Do you find that you might be in this role of trying to help bridge the gaps between different roles in an organization where there's data silos and there's probably still some territorial culture going on? What are you finding in terms of Connecticut's ability to really help educate and maybe bring more stakeholders, not just to the table, but kind of build a foundation of collaboration. Yeah, so it's a really interesting question because I think it means, not just for Connecticut, but all vendors in the space have to get out of their comfort zone and just stop talking speeds and feeds and scale. And in fact, when we were looking at how to tell our story, we did an analysis of where most companies were talking and they were focusing a lot more on the technical aspirations that developers sell, which is important. You still need to court the developer, you have community products that they can download and kick the tires with, but we need to extend our dialogue, get out of our customer comfort zone and start talking more to CIOs, CTOs, CDOs. And that's just reaching out to different avenues of communication, different ways of engaging. And so I think that's kind of a core piece that I'm taking away from Strata is we do a wonderful job of speaking to developers. We all need to get out of our comfort zone and talk to a broader set of folks, so business folks. Right, because that opens up so many new potential products, new revenue streams on a marketing side theme with a really target, your customer base audience with relevant timely offers to be able to be more competitive. The worst scenario is talking to an enterprise around the wonders of a technology that they're super excited about, but they don't know the use case that they're trying to solve. Start with the use case they're trying to solve, start with thinking about how this could affect their position in the market and work on that in partnership. We have to do that in collaboration with the customers. We can't just do that alone. It's about building the partnership and learning together around how you use data in a different way. So as you imagine the investments that you're going to, Connecticut's going to make over the next few years with partners, with customers, what do you hope Connecticut will be in 2020? Yeah, so we want it to be that transformative engine for enterprises. We think we are delivering something that's quite unique in the world and you want to see this on a global basis, affecting our customer's value. I almost want to take us out of the story and if I'm successful, you're going to hear wonderful enterprise companies across Telco, banking and other areas just telling their story and we happen to be the engine behind it. So you're an ingredient in their success? Yes, a core ingredient in their success. So if we think about over the course of the next technology, set of technology waves, are there any particular applications that you think you're going to be stronger in? So I'll give you an example. Do you envision that Connecticut can have a major play in how automation happens inside infrastructure or how developers start seeing patterns in data and imagine how those assets get created? Where are some of the kind of practical but not really talked about applications that you might find yourselves becoming more of an ingredient because they themselves become ingredients to some of these other big use cases? There are a lot of commonalities that we're starting to see and the interesting piece is the architecture that you implement tends to be the same but the context of how you talk about it and the impact it has tends to be different. So I already mentioned the customer 360 view, first and foremost, break down silos across your organization, figure out how do you get your data into one place where you can run queries against it, you can visualize it, you can do machine learning analysis. That's a foundational element and I have a company in Asia called Lippo that is doing that in their space where all of a sudden they're starting to glean things they didn't know about their customer before to create doing that ad hoc discovery. So that's one area. The other piece is this use case of how do you actually operationalize data scientists and machine learning into your core business? So that's another area that we focus on. There are simple entry points, things like a Tableau acceleration where you put us underneath the existing BI infrastructure and all of a sudden you're 100 times faster and now your business folks can sit at the table and make real time business decisions where in the past if they clicked on certain things they'd have to wait to get those results. Geospatial visualizations and no brainer, the idea of taking environmental data, pairing it with your customer data for example and now learning about interactions. And then I'd say the other piece is more innovation driven where we would love to sit down with different innovation groups in different verticals and talk with them about how are you looking to monetize your data in the future? What are the new business models? How does things like voice interaction affect your data strategy? What are the different ways you want to engage with your data? So there's a lot of different realms we can go to. One of the things you said as we wrap up here that I couldn't agree with more is the best value articulation I think a brand can have period is through the voice of their customer. And being able to be, and I think that's one of the things that Paul said yesterday is, defining Connecticut's success based on the success of your customers across industry. And I think it really doesn't get any more objective than a customer who has, not just from a developer perspective, maybe improved productivity or even workforce productivity, but actually moved the business forward to your point early, maybe bridging the gaps between the digital and physical and actually enabling that business to be more profitable, open up new revenue streams because this foundation of collaboration has been established. No, I think that's a great way to think about it. Which is good, because he's your CEO. Yes, yes, that sustains my job. But the other piece is, I almost get embarrassed talking about Connecticut. You know, I don't want to be the car salesman or the vacuum salesman that sprinkles dirt on the floor and then vacuums it up. I'd rather us kind of fade to the behind the scenes power where our customers are out there telling wonderful stories that have an impact on how people live in this world. To me, that's the best marketing you can do is real stories, real value. Can do great more. Well Dan, thanks so much for stopping by sharing what things that Connecticut is doing, some of the things you're hearing and how you're working to really build this foundation of collaboration and enablement within your customers across industries. We look forward to hearing the kind of cool stuff that happens with Connecticut throughout the rest of the year. And again, thanks for stopping by and sharing your insight. Thank you for having me. I want to thank you for watching theCUBE. I'm Lisa Martin with my co-host Peter Burris. We are at Big Data SV, our second day of coverage at a cool place called the Forager Tasting Room downtown San Jose. Stop by, check us out and have a chance to talk with some of our amazing analysts on all things big data. Stick around though, we'll be right back with our next guest after a short break.


My name is Erin Seacort and I am an Artifact Conservator at Inginium, Canada's Museums of Science and Innovation. I chose to pursue a career in science because I've always been fascinated by how the world around me works. I followed my curiosity and earned a Bachelor's of Applied Science in Mechanical and Materials Engineering. My love of museums steered me towards a further Bachelor's of Science in Archaeological and Museum Artifact Conservation. I currently combine my two fields at the museums here in Ottawa. I hope I inspire girls and women to choose science in everyday ways they may otherwise take for granted. To think critically about the materials, the systems and the technologies in our lives and to savor each time we increase our own understanding of science.


So, I am going to talk about a recent exciting result of Julia Shuzoi about a classical problem known as the edge disjoint path problem in networks. So, let me just start by defining the problem, you are given a graph along with the collection of sourcing pairs let us say S1 T1, S2 T2 through SKTK and your goal is to route a maximum number of these sourcing pairs in the graph in an edge disjoint manner. So, when I say routing a pair what it means is if you route a pair SITI you assign a path in the graph to the pair SITI. So, you connect SITI to TI along this path. The phrase edge disjoint here means that if I look at the routing of any two pairs SITI and SKTJ then they do not share any edges. So, let us look at an example here in this graph I am routing the pair S1 T1 along the red path S2 T2 along the green path and S3 T3 along the blue path. Once I have routed these pairs if you look at the pair S4 T4 there is no way to assign a path to this pair without violating the edge disjoint property. Any path that connects S4 to T4 at this point would intersect with one of the previously assigned paths. So, this is an extremely well studied problem there is a long and rich history of results on this problem. For now let me just review some classical results about the problem and I will say more as we go along. So, for one thing I should just point out about the expressive power of this problem even these EDP problem on star graphs which are trees of height 1. So, you have a single vertex connected to another vertices by direct edges even EDP on star graphs is equivalent to the general matching problem. We know how to solve matching in polynomial time, but that is a non trivial thing ok. So, EDP captures this very easily. When the graph is directed even on two pairs just S1 T1 S2 T2 the problem is NP hard to solve. If the graph is undirected the problem is poly time solvable for any constant number of pairs, but this requires heavy machinery of the graph miners work developed by Robertson and Seymour. So, this is a highly non trivial algorithm and of course once even in the undirected graph once the number of pairs is unbounded the problem is NP hard to solve and I should point out that even on undirected trees if the edges of the trees have capacities then the problem is NP hard ok. But in this talk we will not worry about capacities we will talk of always assume all edges of the graph have unit capacity. So, since the problem is intractable there has been much work on designing approximation algorithm for this problem and in this regard almost all the work on approximation algorithm starts with one common starting point which is a linear programming relaxation a very natural linear programming relaxation for this problem which is known as the multi commodity flow relaxation. So, what does the relaxation do? First thing it does is that instead of routing a pair SITI along a single path it allows you to simply supply a unit of flow from SI to TI ok. So, this means you can use multiple paths each path carrying some different fractions of the flow. The second thing you do not even have to write route a pair SITI for a full unit amount of flow you could say I am routing it for an epsilon amount of flow ok. So, now we can just define a variable XI which indicates for each pair SITI how much flow for the pair is routed using a flow system.  Your goal is to maximize summation XI which is the total amount of flow you route. And the main constraint here is to make sure that if you look at any edge E in the graph and you look at total flow on paths that go through the edge E this flow should not exceed 1. That is the implementation of the edge disjoint condition ok. So, as a warm up let us just look at a very simple rounding algorithm for this relaxation. It is an iterative process you start with the fractional solution for this multi commutative flow relaxation among all the pairs which you have not yet considered for routing pick the pair SITI pair which has the shortest flow path on which LP routes some flow. So, this is shortest in the length of the path route the pair SITI along this path p. And now any other flow paths which intersect the path p you discard them. You keep repeating this process until no fractional flow is left. It is clear what you get at the end is an edge edge disjoint routing ok because each time you route along a path p you discard every flow path which intersects with it ok. What is not clear is how good is this algorithm. So, let us fix some notation and we will just analyze this algorithm it is a very simple analysis. So, throughout the talk I am going to assume n denotes the number of vertices and m denotes number of edges and let us say opt is the optimal fractional solution ok. So, let us first consider a case when I end up picking a pair to route and I route the pair along the path whose length is less than square root m ok. In this case when I route the pair how much flow could I throw away well at most root m right. I have only root m edges on the path and I might be throwing a unit amount of flow crossing every one of those edges right. So, as long as I am routing pass on pass of length less than root m I am within a root m factor of the optimal solution. At some point if the shortest available flow path has length more than root m then notice that the total amount of flow that remains in the solution can be no more than root m. Why? The total routing capacity of this graph is m and every unit of flow being routed would consume root m amount of this capacity you have no more than root amount root m amount of flow. So, at this point even if you route just one more pair you would be within factor root m of the optimal solution. So, if you combine these two observations you get here is a rounding which is within root m of the optimal solution ok. So, one may think that you could do better than this by being more sophisticated after all as Madhu is pointing out I am not I do not seem to be using the power of LP too strongly. Turns out there is a simple graph an instance which was shown by identified by Garg Vazirani and Yanaka case almost 20 years ago which shows that this LP has an integrality gap of square root m ok and this instance is actually just a grid like graph ok. So, here is the instance so you have along the x axis the sources and along the y axis you have the sync vertices and the green blobs actually correspond to that little gadget up there which ensures that paths which enter the green blob they have to traverse through a common edge to get to the other side of the green blob ok. So, once I put this gadget in this instance let us see how good is an LP solution you can always route half half unit of flow for every SITI pair how? Pick a pair SITI started SITI go up all the way to the level of the sync T I and just turn towards the sync T I at that level so just the straight forward right routing up and then left. Everyone does that any two paths will intersect just once and when they intersect their only constraint is they do not cause they do not have flow of more than one passing through the common edge that is ensured if you are routing only half units of flow. So, you can route k over two units of flow but now let us look at an integral routing take any pair SITI moment you route SITI to T I no matter in what fashion you essentially create a wall no other pair can reach there no other source can reach it sync without crossing this wall and that means causing a congestion of two on some edge. So, you can actually just route integrally one pair k can be set to made roughly root M and this will show you an integrity gap of root M for this LP. And this gap holds for planar undirected graph so it is happening on a very simple class of graph and actually the news is bit worse if the graph happens to be directed you can turn this integrity gap into a hardness of approximation result remember I pointed out earlier that the two pair problem on directed graph is NP hard to solve. So, now those green blobs I can just replace them by a gadget which is the two pair gadget and if the two pair gadget admits a solution that means both pairs can be routed in an edge disjoint fashion you will be able to route all SITI pairs and if there is no solution then it serves as an obstruction as before and you will not be able to route more than one pair. So, this intractability where it seems even hard to approximate the problem motivates naturally the question can be relaxed the problems slightly and get stronger approximation guarantees root M is not a very appealing approximation guarantee and a natural relaxation is to consider EDP with congestion. So from here on I will when I say EDP with congestion C I mean the following version of the problem I would let you violate the edge disjoint condition in the following manner through every edge in the graph I will allow up to C paths to use the edge. So, the case we have been talking about so far is with congestion value C equal to 1 and what we want to understand is what happens when the congestion is allowed to exceed 1. In particular the question that is focus of this talk is is it possible that with constant congestion EDP becomes well approximable like approximable to within a polylog factor and if you notice the integrity gap example that I showed it completely breaks down if the congestion of 2 is allowed it relied very strongly on no congestion condition congestion of 2 you can just route like the fractional solution. So, once we start looking at EDP with congestion there is a beautiful result of Raghavan and Thompson from 1987 which case gives a randomized rounding scheme for solving EDP with congestion that goes as follows. Take the fractional solution look at a pair SITI toss a coin which let us say comes up heads with probability XI XI is the amount of flow that is routed for the pair SITI in the fractional solution. If it comes up heads you say I am going to route this pair so you are routing a pair SITI with probability proportional to XI and once you make the decision to route the pair you look at the flow paths used in the LP solution for this pair and you sample one of these flow paths the probability proportional to the flow on them and that is it that is how you will do the routing. How good is this routing? It turns out if you allow a congestion of roughly log n over log log n you can get a constant factor approximation to EDP and then building on the same ideas it was shown subsequently that for any constant congestion C you can get a n to the 1 over C approximation with congestion C for EDP. So things do improve once you allow congestion but notice that as long as the congestion value C is a constant the approximation factor is still a polynomial factor so it is better it is improved it goes down the ratios go down as C increases but they remain polynomial factor for constant C. So could we do better than this rounding framework okay so can we do better? Well turns out if the graph is directed this randomized rounding approach is pretty much the best you could do. In fact there is a hardness result of the form n to the omega 1 over C for EDP with congestion C in directed graph okay and also if you wanted to get something like close to the constant factor approximation you cannot avoid having a congestion which is log n over log log n okay. So this for directed graphs qualitatively at least right we are not matching the exponents exactly in the hardness and in the upper bounds but qualitatively the question seems to be well understood right. Things are not so clear for undirected graph you do have hardness results even when congestion is allowed but these hardness results are of the form log n to the 1 over C. So the upper bounds looks like n to the 1 over C and the hardness looks like log n to the 1 over C. So from this point onwards I am going to focus only on undirected graph and this is the state of the art for undirected graph or this was the state of the art as of month two months ago okay. So what is the state of the art for any constant congestion C you can get log n to 1 over C hardness and you get n to the 1 over C approximation okay so this is the striking gap between upper and lower bounds. So this gap has essentially disappeared with the remarkable result of Julia Shuzai which shows the following with constant congestion it is possible to get a poly logarithmic approximation to EDP in undirected graph. So we really the truth here really was closer to the hardness results okay. So this result builds very strongly on number of developments that happened over the last six seven years and then adds to those developments a very powerful machinery of its own. So in the remaining time what I would like to do is there are many technical details and I can't I won't have time to get into many of those technical details but what I would like to do in the remaining time is to give you a flavor of the various ideas that are put together in getting this result okay. Okay so the rest of the talk I am going to divide into four parts and I am going to start by talking about a framework for solving the EDP problems called the well-linked decomposition framework which is the starting point for all the recent results. And at a high level what the framework allows you to do is to take an arbitrary instance of EDP and reduce it to an instance of EDP where all the sourcing pairs have very high connectivity to each other okay. Once you have these instances of EDP with this special property that the sourcing pairs have very high connectivity to each other, remember in the original problem all you care is to connect S1 to T1, S2 to T2 and so on. You don't care about their connectivity of S1 to T2 or S2 to T1. Here we would care about their connectivity of even the sources and syncs which are not involved in any pair okay. So the second step after that is once you have these instances where sourcing pairs have very high connectivity to each other. We would like to exploit this connectivity to show existence of some interesting routing structures in the graph and in particular we will end up showing that you can embed expanders in such instances okay. And in order to do this embedding of expanders we are going to use, we are going to use a beautiful recent approach for embedding expanders which was highlighted in the work of Kandekar Ravan Vazirani which breaks us down into a cut matching game that I will talk about and this view of embedding expander turns out to be very useful for the EDP framework. So the third thing here is EDP in graphs with large minimum cut. That was really the first result which combines both these two ideas together and shows that you can get a polylog approximation for EDP with actually even I think the result was just congestion one provided the graph you start with has a large minimum cut that it's reasonably well connected to begin with okay. So that was the proof of concept that there is some hope that EDP may after all be approximable to within a polylog factor. And finally I will talk about how Julia Shozoy extends this approach to arbitrary graphs which do not obey the large min cut condition okay. So let's start with the well-linked decomposition okay. So what's the idea of well-linked decomposition? As before we are going to start with the multi-commodity flow solution but this time we will look at the solution and use it only to partition the original instance into a collection of smaller instances where these smaller instances will have property that all the sources and sinks in them are going to be well connected. The key point of departure from the earlier approaches is in doing this decomposition I'll totally ignore the flow paths that are used by the LP solution. The only information we will carry forward from the multi-commodity flow solution is what was the fraction for which a pair was routed okay. And from this point onwards I wouldn't care once I've done the decomposition I wouldn't even care about the original multi-commodity flow solution. The second step of this framework is to show that once you have these well-linked instances and I'm going to define this more precisely in a moment. Once you have these well-linked instances you can embed in them routing structures which I'll call cross parts. And these are basically structures on which the EDP problem is easy to solve. And if you could do that then you are in good shape because now you have, you started with an arbitrary instance, you reduced it to well-linked instances. Well-linked instances have cross parts on which EDP you already know how to solve. And now you will just use these cross parts to route your original instance inside them okay. So that's the idea of the framework. So let's define these just a few definitions and then I'll also show you right away a quick, simple application of this framework. So what's the well-linked set? So suppose you have a graph G and a subset X of vertices, special vertices in this graph. I'll say that the set X of vertices in the graph is well-linked if they satisfy the following property. If you wanted to separate some k vertices in this set X from the remaining vertices in X, then you must delete at least k edges. So in other words, with respect to set X, the graph looks like an expander okay, just with respect to this subset X okay. The whole graph is not an expander but it satisfies this expander like condition for this set X okay. So once I know what's the well-linked set, I can now define what's the well-linked instance of EDP. So first what's the instance of EDP once again? It consists of a graph G along with a collection of sourcing pairs and from here on, I'm going to refer to the sourcing vertices as terminals okay. I will refer to them as terminals and I'll denote them by the set X. Whenever I use the set X, it refers to these terminals okay. And I can assume without loss of generality that all SITIs are distinct okay. There's a simple trick which can allow you to do that. So if a vertex was occurring multiple times, you can just replicate it okay in a suitable way. So in this view, an instance of EDP is actually the following. You're given a graph G, you're given a set X of terminals and the instance gives you a matching M on the terminals and tells you route that matching okay. It just pairs up these terminals in some fashion and says, give me a routing of them okay. What's a well-linked instance of EDP? Well, it's just an instance of EDP with the property that the set of terminals is well-linked. So here is a useful result for our purposes. Given any instance of EDP, you can convert it into a collection of well-linked instances with only a polylog factor loss in the solution value. So you start with some multi-instance with some multi-commonity slow solution value. Let's say this value was opt. You will be able to convert this instance into collection of well-linked instances such that in the remaining, the well-linked instances, the flow value is at least opt over polylog. Once you have that, we'll see how this could be very useful for solving the problem. So now the second word phrase that I was using, I was talking about these crossbar structures. So let me just briefly define what's a crossbar. If you give me a graph H, I'll say that it is crossbar. It serves as a crossbar with respect to some special subset of vertices i that I'll call the interface of this crossbar. If you have the following property, give me any matching on this interface i. I can route it on edge-to-joint paths using inside this crossbar graph, integrally. So here is an example of a crossbar, a complete graph is a crossbar. You give me any matching and I just have a one-hop path, a simple trivial integral. But complete graphs are not, they're not very interesting and they're not the only crossbar structures. It is a slightly more interesting crossbar structure, a grid graph. A grid is a crossbar with respect to the first row here. Why? Suppose you give me this grid and you give me a collection of sourcing pairs lined up on the first row and you ask me to route them. So S1 wants to go to T1, S22, T2, it's some arbitrary collection. I could do this routing. S1 will move up to the second row, just use the second row to go all the way up to T1 and then come straight down. S2 would use the next row and so on. It's a crossbar. I did this routing and it was easy. This already gives us one new result as a direct application of the framework, which is a result on how well EDP can be solved in planar undirected graphs. There is an old result of Robertson, Seymour and Thomas, which says that if you gave me a planar graph G, which has k well-linked terminals, then with congestion two, you can embed in that graph essentially a k by k grid. Combined with the well-linked decomposition framework, you now can show that EDP in planar graph is approximable to within an order log n factor with congestion two. So this already was a strong improvement over what we knew before because at that point, even for planar graphs, only a polynomial factor approximation was known with constant congestion and you get it very quickly from this framework. So here is how the picture looks. You have your terminals. You have this crossbar structure sitting somewhere in the graph. You will route these terminals to the first row, the interface of the crossbar, and then pair them up at the crossbar. Okay, what about general graphs? That's our agenda for today, EDP in general graphs. So here's a natural conjecture which emerges from this framework and from this approach, which I'll just refer to as a crossbar conjecture and says the following. Suppose you give me a well-linked instance of EDP, you give me a graph G with a set X of terminals which are well-linked. Then the conjecture says, then give me any matching M on this set of terminals. I can integrally route one over poly log fraction of the pairs with only constant congestion. Not only the specific pairing you were interested in to begin with initially at time zero when the game began, you give me a well-linked instance, give me any matching, it is possible to route. And in a way, what this is saying is that the whole graph G, if you have a well-linked instance, the whole graph G serves as a crossbar whose interface are the terminal. So if the crossbar conjecture is true, it's clear that the integrity gap of the flow relaxation is only poly log N with constant congestion. That direction is easy. The converse is also true. If the integrity gap of flow relaxation is poly log N with constant congestion, then the crossbar conjecture holds. And why is that? For any well-linked instance given any matching M on the terminals, there is a fraction flow of value at least cardinality of X, Y log N. Why? Because these terminals, they satisfy the cut condition for routing any matching and there is a flow cut gap is log N. So you would be able to route at least this much flow. But she told me that the integrity gap is only poly log N with constant congestion. So then I will be able to integrally route one over poly log N fraction of pairs in M. So this means this integrity gap question, what is the integrity gap of the flow relaxation with constant congestion is equivalent to understanding or settling the crossbar conjecture. It's not just one approach, it's essentially. So here is the plan for the rest of the talk. Okay, so here is the plan for the rest of this talk. So we're going to try to prove this crossbar conjecture. And the specific way we're going to try to prove it is as follows. We're going to try to show that given any well-linked instance on K terminals, we can embed with constant congestion a low degree expander of size K over poly log N. Once we have this embedding, we are in good shape. I won't go over this again, but I won't go over this right now. But it's just a well-known fact that routing on expanders on edge distance paths is an easy thing to do. In fact, a greedy routing scheme works. And intuitively the reason is this pairs can be connected by short paths. Each time you route a pair SATI, the damage you're going to cause is roughly the length of this path, even if you were not very clever in choosing your path. If paths are of length only order log N, the damage you cause each time is only order log N, okay? In fact, if the expander is low degree, you can even go ahead and do vertex disjoint routing and the same would be true. And this is a fact which is useful to Julia's results, okay? So now we move to part two, which is we want to embed an expander. How could we possibly try to do that? And this is where the cut matching game of Khandekar Ravan Vazirani comes into play. So in this game, you start with a graph, empty graph. And let's say you start with an empty graph on N vertices. You want to build an expander on these vertices. There are two players who are going to play this game. There is a cut player who wants to build an expander as quickly as possible. And there is a matching player whose goal is to delay the construction of this expander, and the game goes as follows. At step one, the cut player is going to give an equal size partition of the vertices of the graph to the matching player. Matching player's job is to return some perfect matching between these two sets A1 and B1. And he's going to figure out the worst possible matching he could give to you to delay the construction of the expander. You take those edges, you put them on your vertices in the, initially the graph was empty, now you put this set of edges. At this point, the cut player will look at what it has got, and will identify another set A2, B2, and you will repeat this process. And the beautiful result is that after order log square N iteration of this game, you do get an expander. So no matter how these edges were given, you would get an expander after log square N iteration. We could use this to solve the EDP problem now as follows, to prove the crossbar conjecture. We have our graph G, and we're going to build an expander on the terminals in this graph G. This is a well-linked instance. When you compute a partition of the terminals A1, B1, and you want a perfect matching between them, all I will do is ask the graph for you to give me a flow, a unit flow on terminals from A1 to B1. And that is possible, why? Because the instance is well-linked. So the edges of the matching now correspond to flow paths in the graph. And this is integral flow. You get this flow path routing, and here is the expander being built on the left side. Second round, some other partition comes. You will once again use the well-linked property to find me a matching, which is actually finding me flow paths, which connect the terminals on the two sides of the partition. You continue this game after log square k iterations, you're going to get an expander on the terminals embedded in your graph. So that's the good news, right? What's the bad news? No, these paths will intersect each other, so yes, and so what is the bad news? Just that, yeah. Because at each step, I am using these edges afresh. I have no way of separating them, right? So problem is, it gives you log square k congestion, okay? But the plan is clear at this point, okay? So this is where Robin Jue came, and they made a really clever observation. They showed that if the minimum cut in your graph was large, and how large? No, not too large, it's just something like log-suban. Then you can embed an expander with congestion one by playing this exact game, and how do they do that? Here is a very quick summary of their approach. They're going to take the graph G, and they're going to randomly partition this graph into log square k, h disjoints graph. So for every h in the graph, you assign it a number at random between one and log square k, and edges with number i go to the copy gi of the graph. The fact that you started with a graph which had a large min cut to begin with, they're able to use this fact to show that even after this random partition, each gi is well linked with respect to the terminals, okay? And now, you play each round of the cut matching game in the private copy gi, okay? That's it, okay? There is work in step two, okay? Which is, you start with the large min cut condition, and then you turn that into showing that each gi is still well linked. But it's technically involved, but it's not too difficult, okay? To do that. So after this result, there was a lot of excitement, and it really seemed to suggest that people should try to get the polylog approximation result for EDP with constant congestion. This condition seems not too daunting, log cube n, right? That's not a very high cut requirement, right? But that just means, since you have some congestion at play, maybe with constant congestion, you could turn your graph to satisfy a condition like this, and indeed that's what was tried next, okay? So I'll just briefly say a few words about another very exciting result which came last year, and which was the final, which was the final word on this problem until Julia's result. That's a result due to Matthew Andrews, which took this framework of raw and shoe and you can get around the min cut condition. And here is the high level plan, which was used by Matthew Andrews. You're given a graph J which doesn't satisfy the min cut condition. You contract regions in this graph which are violators of this min cut condition. And in this contracted graph, these regions are collapsed down to a single node. And you boost the connectivity of this graph, okay? After you do these contractions. You boost it to satisfy the log cube and min cut condition. And at this point, you invoke the raw and shoe framework. But there is a problem. You contracted regions of graph into nodes, paths which are just going through these nodes. When you uncontract, they have to actually go through the complicated graph contained inside. And what Matthew was able to show is that with polylog log n congestion, he can manage the routing inside these contracted regions, okay? And intuitively, the amount of flow the contracted regions are dealing with is roughly polylog n, okay? And if the congestion you create inside is log of the amount of flow they are dealing with, okay? But that's a very simplified, okay? This is quite non-trivial to make it all work. Okay, so where does finally to Julia shows us the approach. How does she take care of this problem by using only constant congestion? So she, at a high level, she's just going to sidestep from the plan of boosting the min cut of the graph, okay? So this approach of completely relying on the raw shoe approach, and only focus on turning your initial graph into a high min cut graph. She's going to move away from that. What she does is, she's able to identify in the graph log square k vertex restraints subsets of vertices. These are vertex restraints subsets. Such that each one of these subsets S j is well connected to the terminals. And I'll make precise what this well connectivity means. But for now, just imagine that all the terminals could reach without causing congestion to each one of these sets S j. Each S j is well linked inside with respect to it's boundary. So if you view it's boundary as terminal vertices, each S j is a well linked instance with respect to it's boundary. Boundary is just the edges crossing S j to the rest of the graph, okay? I'll make it all of this more precise in just a minute. And then the idea now is, when you want to implement the jth round of this cut matching game, you will bring your terminals to S j. S j is well linked inside.  That's the idea. Julia calls this a good family of sets. I would have called it really good family of sets. So this is a very powerful construct, okay? And the hard part of our work is really showing that you can, such sets exist and you can find them, okay? So let's look at this in bit more detail. So these good sets are sitting up there, S 1, S 2, S R. And the way you should view this picture is as follows. Look at S 1 and look at the edges which are just leaving the boundary of S 1. The number of edges which are leaving the boundary of S 1 is exactly equal to the number of terminals you have. So if you have k terminals, there will be exactly k edges leaving the boundary of S 1. Every single terminal will have a private edge assigned to it on this boundary, okay? So the set S 1 has a representative for every terminal, okay? It's private and unique, okay? Same for S 2, same for S R. And now if I look at a terminal, so let's look at the blue terminal. It has this additional property that it can connect to all its representatives in these R sets, okay, by a spanning tree, okay? So there is a spanning tree which allows it to reach all of them, okay? Not in an edge-to-short fashion, it's just a tree, okay? But it's able to connect. It is connected to all its representatives, that's all. So, STs are well-linked with respect to their boundaries. Terminals are well-linked to the boundaries, that is, each terminal can reach one represented in boundary of each one of these SSRs. That is the structure. And now once you have this, you can play the game of embedding an expander as follows. So those are my terminals, and I want to build an expander. I play the first round of the cut matching game, and that gives me this partition of the terminals, and it says match them. I go to my set S1. This partition has an image in the set S1 because terminals have a representation in each set, and the set S1 is well-linked, and I will now say, play the game in there, find me a matching, okay? I get those edges here, I go to the next round. This time, I go to the set S2, play the game. I continue. In log square k iterations, we will obtain an expander embedded in G, just as before. So here is the picture, okay? So this embedding is more complicated than the embeddings of expanders we looked at earlier. Why? Before, each vertex of the expander corresponded to a single terminal in the graph, this time, for each terminal, the vertex I have in the graph is not a single vertex. It is actually a connected component. What is a connected component? It's the tree, which was spanning that terminal. What's an edge in the expander? Well, an edge connecting TI and TJ now corresponds to a path connecting a vertex in the component of TI to a vertex in component of TJ. So like this. So if you look at an edge on the right-hand side, which connects those two terminals, that really just corresponds to some path connecting some vertex in the tree of TI to some vertex in the tree of TJ. But routing on vertex which we saw in paths on X is still a good thing for us in that it will give us a low congestion routing in G. Let's look at a path from S to T on which you wanted to route in the expander. Let's see how it looks in the embedding. The expander edges appears here as paths between some pairs of vertices in their corresponding component, but each one of these blobs is a connected component by itself is a tree. I can now use the tree to hook up to the right points and go through all these intermediate vertices to reach all the way at T. And I'm going to use vertex ratio and routings. So these components, once I've used them, once I throw them, and that's it. So as I said, the hard part is in finding these sets and just a high level one sentence intuition as to why such structures should exist is you start with an instance which has K well-linked terminals. So that means well-linked means there is a lot of connectivity among these K guys. You scale down your goal of building an expander sufficiently down. You don't want to build an expander on K terminals. You would be happy to build it on K over poly log K terminals. So since you have this huge connectivity and capacity in the graph, if you scale down your goal by a large poly log K factor, in principle you could identify dedicated regions which are well connected, well linked, and are of size only K over poly log K. The difficulty is in showing that not only you have these nice dedicated regions, but they satisfy all these additional constraints, which is the terminals can reach them and you have this nice property of well-linkedness in each one of these regions which terminals can arrive at. Okay, that's all I'm going to say about this result. And I'll conclude with a couple of open questions which still remain. I think this result is really like it cleans up lots of things, but there is still stuff to be done on understanding EDP of undirected graphs. So I think there are only two questions which I would like to highlight. So the first question is we started with EDP defined in a very strict manner that the routing had to be on an edge disjoint path. And then we relaxed it to EDP with congestion and we get these nice results. But let's now return, now that we understand the power of congestion, let's return to the basic question, what happens to EDP with no congestion? Here is the state of affairs. The best known approximation algorithm is a square root n approximation. The best known hardness is square root log n. Pretty much the state of affairs we had for EDP with congestion up until Julia's result. Except in this case, the upper bound of square root n matches the integrity gap result. So you couldn't start with the, or you couldn't entirely rely on the multi-common duty flow relaxation as your benchmark. You would not get past the root n barrier. The second problem is something I didn't talk about directly much is, but it's just really the natural analog of the EDP question. It's the congestion minimization problem. Same input as in EDP, but this time I tell you, you must route all SITI pairs. Everything has to be routed. Your goal is to minimize the maximum congestion you will cause at any edge. So I pointed out a result of Raghavan and Thomson from 1987 already tells you how to do this with log n over log log n congestion. For directed graphs, that's the best possible. But for undirected graphs, the hardness is really a level below. It sits at around log log n. So it's a very interesting question. If it turns out, even for congestion minimization, the right answer turns out to be in the log log n regime. That's all I wanted to say. Thank you.