there's a big data in health, and there's a big data in education, and there's a big data -- what i know, i tell students, i teach students if i look at the demand for the courses that deal with the data, data science, big data, if that's any indication, then it's very enormous. everybody wants to have the skill. you go to the employers, and they want to know, can you deal with it? do you have an experience with it, you know? because even if you are a grocery firm, even if you are a hospital, everybody realizes that this information has lot of intelligence embedded in it. do we have an ability to extract that intelligence and use it in a meaningful way to either ins hasn't our productivity or improve the quality of our product. and so on and so forth. and why not? i don't know how big it is, but i think it's very big. >> host: hah rule telang of -- rahul telang of carnegie mellon is the co-author of this book, "streaming, sharing, stealing: big data and the future of entertainment." >> c-span, where history unfolds daily. in 1979, c-span was create as a public service by america's cable

it's exploiting big data. i'm not sure if you heard about the story, i think they call it the discover list or discover playlist. what spotify has been doing is they recommend you every week a list of songs that they believe you will like in the story was that it became so popular with people and i was reading and i won't go into the detail but that's a big data exercise and they use deep learning to figure out, were looking at the scale and the scope of the data. that's really where the trend is going. >> the question or statement you write your book and then you answering your book, you can't use data to make creative decisions. if you do you'll interfere with the creative process. >> so that's probably one of the criticisms that you hear from the people in the creative industry. they say g, are you going to tell me and are you going to destroy our creative ability to create the content. >> i think it's a little bit of habitable. we will see how things go. i don't know how this will play out. many times the

citizen s citizens' data or data of persons located in the united states. now, we can debate the specifics of these kinds of proposals and i think there's areas where i would suggest changes but i would suggest that this is the right approach and one that would, if adopted, raise baseline privacy protections as compared to the current situation where governments are increasingly being incentivized to pass things like mandatory data localization requirements. such an approach also reflects the general premise that the united states has a legitimate interest in setting the specific substantive and procedural rules that govern access to data for its citizens and residents but does not have a similar justification in imposing the specific rules of a warrant based on probable cause when a foreign government seeking to access data of its citizens outside the united states so long as certain baseline protections are in place. now, notably the u.s. and uk have a draft agreement that would allow uk law enforcement officials to do exactly what i'm talking about, dire

data driven justice. and this is some of the major accomplishments under this administration we've also brought in over 1,000 law enforcement officers from over 900 agencies to the white house. to hear briefings on the task force on 21st century policing. how many people are locked up? more than anywhere else in the world, that is a problem, but that is where we are right now, we have more people locked up than anywhere else in the world. it has grown by 350% since 1980. how much are we spending? >> $80 billion a year on encarceration. a number of things listed there, we can eliminate the tuition in every one of our public colleges and universities for $80 billion. just a quote from president obama. it's important to realize we have a system that is not fair, that ends up discriminating against people. people of color are more likely to be stopped, frisked, charged and detained. african-americans are more likely to be sentenced to more time for the same crime. and one of the consequences of this around 1

my fantasy football data is better than our criminal justice data. that is a real problem. we need timely data. the 2015 hatet crime numbers in november of 2016. we know that more and more agencies are moving to the national database reporting system, a much better way to collect data. we need everybody to be using it. that important for public safety. crimeed about our hate numbers. the problem with these numbers are that this reflects less than 1/10 of the agencies across the country reporting at least one hate crime. 18,000 agencies and this reflects about 1700 agencies. why do i say these numbers are problematic? california, 117 hate crime's reported. new york, 500 hate crime's reported. alabama 12. mississippi, zero. mississippi has cured the problem with the crimes. that is an incredible problem that these are the numbers we are relying on. we have got to be better. we have something called police data initiative. putting your data out there for the public to see. louisville puts up every single citation they issue in real time aggregated by race and gender. it is the

martin: well, big data essentially is the collection and use just of massive amounts of data.orporations for example, these companies are collecting all kinds of information about their customers, about their business operations, about the actual processes in industrial environments and factories. about the things that their employees are doing. all of this data essentially becomes a kind of feedstock for these smart algorithms, the information they use to learn and figure out how to do things. that is something that i think is going to be dramatically disruptive going forward. narrator: the total data stored on the world's computers is now believed to be well over 1000 billion gigabytes. and it is big data which is driving the most disruptive advance in technology, the ability of machines to think. martin: one thing that you will very often hear people say even today is that computers only do what they are programmed to do. and you know, this is really not right anymore. and the reason it is not right basically is because of machine learning. because we now have this technolo

so i think the reasons -- there are reasons that we continue to rely on traditional data and big data not transformed what we do. let me say, there is a lot of promise there, because the statistical agencies themselves recognize that there are gaps in the production of statistics and they are looking at big data to try to improve that. that is an important initiative and we are looking -- working closely with those agencies to support their efforts there. second, i would say that there have been some very interesting things done that shed light on an important macro phenomena, that leverage the advantages that big data has, often a huge amount of detail. and in situations where fineaphic detail at a level where it is useful and it is important to have a lot of detail about spending, for example, to know or be able to distinguish between spending at a grocery store and spending at a restaurant, big data has been useful. i could give you a couple of examples. researchers were trying to understand the impact of the recent hurricane matthew on spending and they relied on credit card data

increase in data reaches. as more of our data goes into these data aggregators, where do you think the bad guys are going to go after? they are going to go after the crown jewel, which is your data. we are seeing an increase of data breach, both in health care, financial sector, and education. is privacy really dead? do we just get over it? some people think so. i will leave it up to you to decide. your digital footprint is huge. and it is not getting smaller. we are not getting less connected, we are getting more. everything needs to be connected. it is more than worrying about what you post on facebook and twitter. we have to do a better job with our kids. we have to make them conform -- informed consumers. yes, it can be used for good and evil. we tend to think more on the risk side. can we take steps to control it? yes. are you going to get rid of data collection? absolutely not. what you do need to do, and what is being pushed for is controlling what happens to your information and who uses it after it is

of the data.n you explain how you use deep learning in a real—life application? yes. so, we do a couple of things, basically. one of the things we do is we do recoup addition of passing trains and different kinds of things about it, what is normal, what is not, starting from very simple things like numbers, which was initially how we started it. and, then, moving on to identifying different kinds of issues. lately, we also use this to identify things which, from video feeds, what is happening in the city, like how many pedestrians, cyclists, cyclists with helmets, cyclists without helmets, with child seats, without trial seats in the back, transport all the information you can get from any video stream, transferring this into actually valuable real—life data. vasilios, how do you see deep learning being useful in asia? because you are working here at the advanced science centre in singapore. how far along has the research and the technology become advanced? basically, there is a lot of research in

we need to understand the data. the key thing weez know bat faltyties, my team worked with san francisco general troounderstand cost so there are approximately 50 percent of people at the trauma center at the hospital are there for transportation injuries at a cost of approximately 35 million as annually. i think of it as a health oriented. this helped eliminate for us the opportunity to make a significant impact on the cost we see at the hospital as a third of the severely injuryed patients comprise [inaudible] we also see reduction in the medical costs. we know people walking comsprise over half the people killed thatd seniors are more much moreivaliable and speed is highly correlated with death and know yoi pass #d a resolution last year on automate #d speed enforcement. thank you so much, that is really important for us. we know large vehicles are more deadly particularly people walking and biking and iftalities are trait concentrated on the high injury network. a refresher how we go to today. we asopt dopted vi

data, people think of personal data mid-air in is the eagerness amount of commercial data every time you are on a plane it was selling off a terabytes of data enormous amounts. and the fuel efficiency so there using dead data to make the planes more safe inefficient and that is happening in agriculture and a transportation. in every economic sector depends on the data. is an enormous constitutes customer demands. that data with the ability of the company's it needs to move back and forth we need to set that back to the united states and to measure around the of world war any country around the world you need to be able to share that data around the world. and up problems and we are facing that they're considering policies we don't think they should move across the border. we want to keep that here inside our country one way but to be operating in our country and they require those jobs ago with those status centers. there is a variety of reasons that is a practical way. >> like privacy for commercial? >> yes. there is a variety every since. that they would want to keep data that is t

at the best data but it is data. so i can go and look at institutions that i'm considering going to. another employment is but what i don't know what engineering majors make at that school compared to mandy's majors. in order for this to work as a market and use information to make savvy choices we need that. averaging across those disciplines doesn't give sufficient information. we need to change the culture of decision-making around college so those who do not have the luxury of following the heart and study what's inspiring to them can make a decision that's likely to lead them to financial well-being in the future. >> or people are going to college that means they're going to have to hire more people to teach the courses, this doesn't d -- >> more students mean more tuition dollars coming in the door of course too. but yes, point taken. >> i think we have time for one more question will keep it in the front. >> i think we may be approaching the topic using from the wrong end. these are really college loans. there

the best data that we have data. i can in theory look at the set of institutions i'm considering going to. i know what the employment rate in the earnings are for those graduates. why don't know is what engineering majors in that school and humanities majors. in order for it to work as a market and for people to use information to make savvy choices we do need that because averaging across those disciplines does not give people sufficient information but we also need to choose a culture of decision-making around collards of people who do not have the luxury of just following their heart and studying what's inspiring to them can make decisions that are likely to lead them to financial well-being in the future. >> the more people to go to college the more people that the hired to teach the courses. this does raise the cost. >> more students means more tuition dollars coming through the doors but yeah point taken. >> i think we have got time for one more question we will keep it right here in the center. >> i think we m

the google of data mining. i like big data, i cannot lie. what an exciting company.mad money" is back after the break. >> announcer: lightning round is sponsored by td ameritrade. >>> it is time! it is time for the lightning round on cramer's "mad money." that's where i take your calls rapid fire. you tell me the name of the stock. i tell you to buy, buy, buy or sell, sell, sell. we'll play this sound -- [ buzzer ] -- and then the lightning round is over. are you ready, skee-daddy? it's time for the lightning round on cramer's "mad money." start with michael in oregon, michael. >> caller: hey, jim cramer. booyah, jim cramer. >> booyah. >> thank you for all your help in the stock market. >> thank you. >> caller: i worked on harley-davidsons for a living, and i want your opinion of should i short harley-davidson? >> here's the problem with it. i don't know how the quarter is going. i think the brand is terrific, it has great brand equity. i do feel you can own it for the long term, but the short term, it has been a rocky performer. let's go to rupert in new mexico, rup

and it was issued and the data was worth coming. >> the data has subsequently been provided by schimick and i believe nicholson construction is how many millions of gallons? >> so i believe and i double check this for sure, i believe from date of the original permit up through the end of 2016 about 4 million gallons that includes the meters part they know about at the beginning these last few months that were metered we require paragraphs of the meters so we know and the estimated values so about 4.2 million i think. >> and do you have how many millions of gallons were pumped through 301 mission street. >> i i wasn't with the department at the time. >> but that information exists? >> i'm looking for it. >> we would like to see it and more 301 mission street and any other batch to start. >> 301 was an easy project we have all that for you as well that is a subject of one of the public records request. >> do you look at dewatering in cumulative or comprehensive way or doing project by project because your interest is in the integrity of sewer system and discharge? >> we look at it cumulat

have data. so i can look at the institutions i am considering going to. i know the unemployment rate. what i don't know is what engineering majors make. in order for this to work as a market and for people to use the information to make savvy choices, we do need that because averaging across the disciplines doesn't give people sufficient information that we also need to change the culture of the decision-making around college to people that do not have the luxury of just following their heart and studying what is inspiring to them can make a decision that is likely to lead them to financial well-being in the future. >> if more people are going to college that means they have to hire more people to teach courses. this does raise [inaudible] >> it does mean more coming in the door. yes, point taken. >> i think we have time for one more question and we will keep it right here in the front. i think we may be approaching the topic. these are college loans the road to the institutions that have no ski

i'm wondering sp there data collected on suicide in relationship to the traffic and where is that data deposited and it will be helpful for monetal health sunch services we look at that as a issue. you dont have to have a answer today. when you said that it struck me that it doesn't make sense to add it here but it needs to be somewhere. >> i think that is a good point and something that we have discussed with respect to institutionalizing the protocol and getting more into detailoffs the fatalities raised other issues. >> thank you. >> thank you very much. >> thank you. >> our next item, >> item 8 is assisted out 237 patient treatment. aot. >> thank you. let me know if you need help getting there. >> i think i'm okay, thank you. >> good afternoon and happy new year. angelica [inaudible] director of outpatient treatment and pleasure to give you a update. i want to start out the conversation by reoriented to what assisted out 37 patient treatment is. it is outpatient treatment aot and not something new to the united states. the first program was 1972 in washington dc and 44 states curre

commercial data pilot program. further, it directs noaa to consider commercial data options rather than rely on slow, costly and continually delayed government-owned slights. for too long our government has relied on these massive multibillion-dollar government weather satellites. the science committee has jurisdiction over noaa's satellite office and has conducted ongoing oversight of the agency's satellite program. our conclusion is that it is in real need of reform. over the years, events at noaa have revealed mismanagement, cost overruns and delays of its weather satellites. this detracts from our ability to accurately predict our weather, which unnecessarily endangers americans. this bill will right the ship and allows noaa the flexibility to buy new, affordable and potentially better sources of data from the private sector, which has the power to make real improvements to our weather forecasting capabilities. it also creates a much-needed technology transfer of fund in noaa's office of oceanic and atmospheric

how much can we read into this data? what does the numbers tell us about an outlook for china for the year ahead? might likeeconomists to say is never look at one data point but we saw a strong finish across a number of indicators. today's number coming in and a full point higher than expected and the highest since january 2013. that was encouraging. blends nicely with the official data out new year's day where we had the manufacturing ad services both ticking down little bit but still close to multiyear highs. strength eating painted across -- strength being painted across the calendar. in february, things were not looking so bright. by thes also confirmed december rating on the satellite index. satellite photos are used to track thousands of industrial sites. it ticked down a little bit but remains at a five-year high. all is looking pretty good for the economists. they are raising their growth estimates to 6.7. that would be in line with the first three quarters. we have had a pboc advisor proposing a lower growth tar

there's been lots of data out of europe this morning. in general the pmi data was 54.9.n line with the flash estimate. we've seen the likes of germany, france, spain, ireland, all slightly ahead. greece was the one negative. either way, you can see the net effect is positive on european equity markets. up across the board today. banking sector is doing well. seeming to applaud thus far the attempts to bail out the italian banks gains across the board for european markets. here's the boards for the year as a whole. let's look back at last year. ftse 100 doing particularly well. most gains not coming in the fourth quarter, but the third quarter when the pound fell after the brexit vote. france and germany doing well in the fourth quarter. about 9% gains each, which took them into positive territory for the year. germany ending up about 7%. it was not positive across the board last year. important to note that. lots of different stories happening within the different individual eurozone countries. italy and spain ending in negative territory. >> an interesting year for the

and it was issued and the data was worth coming. >> the data has subsequently been provided by schimick and i believe nicholson construction is how many millions of gallons? >> so i believe and i double check this for sure, i believe from date of the original permit up through the end of 2016 about 4 million gallons that includes the meters part they know about at the beginning these last few months that were metered we require paragraphs of the meters so we know and the estimated values so about 4.2 million i think. >> and do you have how many millions of gallons were pumped through 301 mission street. >> i i wasn't with the department at the time. >> but that information exists? >> i'm looking for it. >> we would like to see it and more 301 mission street and any other batch to start. >> 301 was an easy project we have all that for you as well that is a subject of one of the public records request. >> do you look at dewatering in cumulative or comprehensive way or doing project by project because your interest is in the integrity of sewer system and discharge? >> we look at it cumulat

we do not have good data on this.at mean get ahead of the inflation rate hike, get ahead of the recession with a rate cut? guest: that is the problem you might have. they are mindful of the rise in the inflation rate mindful of dataconomy, the employment looked too slow. the great job generating machine that they u.k. has been, that looks to have studied off. there was a good speech about the view that the labor market -- ando be listening loosening again. it is on hold. let's watch the data. if they government does something silly the markets will respond. manus: are you a buyer of the great reflation trade? big day,y that great we are off to the races again. threest: i spent the last days i came back to the u.k. and i spent the weekend watching what was going on in the united states and it wanted to hunker down. reflation trade coming. thanks for joining us. now at 7:24 a.m. in london. is aboutancine lacqua to sit down with the bank's executive chairman for an exclusive interview in a few minutes. good to see you. y

we got fresh inflation data out of the u.s. yesterday, latest cpi data, kind of a mixed bag.asures are clearly trending up. this is different ways of looking at it, the white light is cpi service and x energy. line is cpi service and next energy. is this another head fake, great transitory period of 2011? >> it looks to me like this is the real deal. you go back to 2011, employment must be two or three percentage points lower. the atlanta fed index today was down some, 3.5%. or 8bably look at 6 inflation measures per country. as of 10 days ago, i decided inflation is turning up. for example, in the eurozone, their pmi for output prices, not including input prices which are mainly driven by energy, apple prices, their index has clearly turned up for europe, for the u.k. would call it pricing power, more than inflation. economists scalded inflation. if you can sell an airplane ticket or a car or a starbucks for more, you call it pricing power. scarlet: ibm just reported results as well, fourth-quarter -- operated earnings-per-share $5.01. that is higher than the consensus estim

clearly, the data. you're exactly right. they cannot get the data. almost held hostage. many of these clinician are tracking in rural or urban areas, they are trapped by the challenges that their patients, comorbid diseases and challenges, social, you know health care is far more than health. what were some solutions that you as policymakers and analyzing this around this dhr, one of f the biggest barriers that across the the system, but particularly, with the small rule docs are facing, so that's one question around ehr. how do we get through this debacle around all of f that. that's one. two, is what are some thoughts around risk adjusted mamts. there's the option of cherry picking. don't like to say that. but that's how do we manage that. thoesz two big issues, with adjusted payment, particularly with the focus on the small dots. thank you. >> i'd love to make not a mac row point. there was a copy of "the wall street journal" in front of my door. for the hotel and said i'd like having "the wall street journal" in the morning. there needed to be no. to the hotel to del

competitiveness but have been restrictions on data in for those companies for the best data services in the world but then the last thing i would say is then my world we are predicting data analytics everything that happens right now is very evident but i would also say it is clear we are just at the beginning. there are so many things happening but it is all within the last two years we at the beginning of the data revolution so to the extent of the future of class computing or predictive data analytics and policies this is a relative lead new industry so from the inception will have a negative impact not just those using it today but where it could go was the global economy long term. >> i agree with theaters on the trade aboard issue my advice is lose the fascination with bilaterals. the argument that you have been taken to the cleaners is wrong. anybody who negotiates will tell you that it is wrong. and the u.k. is probably one of them but the idea that it they are bad is misplaced. also because going for word negation -- negotiations are what you are talking about. and then to a

all of this, the data is supportive of, and we'll continue to evaluate the data and take learnings from. but we certainly feel very good that this data supports our actions in our phase three study. >> i like to think that's not your only product. you have won approved which is high la next. can you quantify how that therapy has grown since it was launched? >> yes. this is a product that, as you mentioned, is useds aa spreading agent. it's mostly using in opthalmic surgery. it's in the range of $15 million a year, but it does help patients. >> okay. and then finally for the drug we've mostly been talking about, when do you expect data from phase three because i know that there will be people out there watching the show who know loved ones or people who have it and say, look, we'll try anything. can we get on this drug? >> so we do have our phase three study ongoing. it's going to explore 420 patients with high levels of this sugar. it's at 200 centers around the world. we enrolled the first patient in march of 2016, and we really are still in our enrollment ramp, so it's probably premat

clearly the data, you're exactly right, they just can't get the data.my question, appreciate your your comment around the social determinants because many of these are trapped whether her in rule areas or urban areas, the trapped by the challenges by morbid diseases and challenges of, social healthcare which is far more than health. my question to you is what are some solutions that you as policymakers around and across the system, particularly particularly with the small role docs, that they are facing. how do we get through this debacle around interoperability and two ,-comma what are your thoughts around risk-adjusted payments because clearly there's the option of cherry picking, i don't like to say that, but ultimately how do we manage those. thr and risk adjustment, particularly with the focus on the small role doctors. when i left my hotel this morning to come over to aai, there is a copy of the wall street journal in front of my hotel room door because the hotel had in their database that i liked having the wall street journal when i got checked

to collect the ground data that sophisticated high-tech science depends on, students have to cross vast distances through the isolated heart of the icefield. in order to traverse the icefield safely, we train them extensively for the dangers of this rugged field experience. here at camp 17, they learn adventure skiing, safe glacier travel on a rope, and how to rescue a colleague from a crevice. the training equips and inspires these students for a career i in extre environmental research, collecting data that the g globl scienentific commununity depends upon t to further r the understandining of our changing worlds. >> it's just a useful tool in itself. >> first off we practice tying knots. that was like the basis of all this, and then from those knots, then we learned different ways to use ththe knots on a ro, whwhich then you learn how t toi with a r rope teteam and what to in case anything bad happens on a rope team, like a fall into a crevice and how to save a team memember that has fallen. >> yay! >> after science and safety training at camp 17, the participants start their travers

it's data dependent.is that the hard data will not follow the sir va data over the course of the next several months. so i'm cautious on the green back. >> david, danielle, thank you for joining us. pleasure to see you both. >> not a lot of animal spirits there. that's it for us. have a great weekend. e, in l tiss?th sghuranyo'0 ins ptoso onmatt >>> good morning. it's jobs friday. really? so fast these things are flying by. the final u.s. employment report before president-elect trump takes office. expectations and market implications are straight ahead. shares of retailer gap surging after the company posted a surprise increase in same-store sales. plus a political fight. toyota the latest company to face the ire of the president-elect on twitter. now this morning the automaker's home country of japan is responding. it's friday january 6, 2017. "squawk box" begins now. ♪ >>> live from new york where business never sleeps, this is "squawk box." >>> it is time to celebrate. good morning. welcome to "squawk

both japan and china's data has been decent but tepid.t off the charts. >> moving in the right direction, but credit led in china and yen weakness led in japan. the question is how sustainable is this throughout the year. >> we'll take it. >> not derailing u.s. equity markets. >>> now, to the trump administration, and what is on his agenda today. tracie potts joins us from washington with more. good morning. >> reporter: good morning. we're actually focusing today here in washington where president obama and lawmakers on two different committees here are getting briefings on allegations that it was russia trying to hack democrats and others before the presidential election. >> reporter: today america's intelligence experts present president obama with the report he asked for. details and evidence supporting their belief that russia hacked democrats to influence the presidential election. >> those same intelligence agencies are the ones that targeted the state department, white house and joints chief of staff. >> reporter: the senate forei

spaine decent data out of but not such great data out of italy.n and weonly a week have seen strong inflation data from germany and the eurozone and the german press is full of talk that the ecb policy is to dovish. dragu like, the ecb will its foot forward on what it will do. it announced last month that it will have quantitative easing going through to the end of the year. we have a year to debate this but i do think there will be resolution in the next few months whether or not the market will face a steeper tapering in the early months of next year. matt: telegraph had an alarming article over the weekend. an interview with the boss voicing not new concerns but saying that if the ecb is going to try to insulate countriesrperforming out of their debt at the expense of the over performing countries like germany, that will be a problem. do you see that as a european front -- a european problem on the front? >> it has been a bubbling problem all the way. you can draw it back to the concerned that we had during the crisis. it is difficult to run a

and to build upon that it is the data piece in getting feedback data. and macra, i think part of the reason people view it so favorably is because it tried to address many of these issues. macra has information in there talking about from the medicare perspective making sure the medicare agencies give feedback data to physicians so that physicians can see what's going on, not only for themselves, what they're doing, but when their patient gets into a hospital. what about post-acute care? what's going on with their patients? it's by far not perfect. i would say one of the issues is that the government and the medicare agencies don't have probably the systems they really need in place to efficiently turn it around. but there's recognition that needs to be done and in the midst of everything else that's being done these are areas that probably need to be looked at. when we look at value the other thing we've been seeing as these alternative payment models and value-based purchasing and readmission programs have been taking place is we're learning more. and

>> i mean, our data, our best data would suggest that nobody who was a noncitizen voted in 2016.t's possible that there's a handful of people nationwide out there that, you know, were missing, but that there's anything systemic or anything that would have swung an election is just not plausible. there's no evidence for that whatsoever. >> you've done a lot of academic research in this area. if president trump is watching right now, what's your message to him on this very important and sensitive issue? >> my message is that this is very dangerous thing. you are calling into question the validity of american elections using data that's clearly false. that it's dangerous to -- dangerous message to send to the american people. i think, you know, the member of congress you had on just before me, you know, said it quite right, that this is not the kind of thing we want to do, we don't want to be using false data to basically make people question how valid our elections are. it's just -- it's totally baseless and it's very dangerous. >> professor brian schaffner, thanks very much for jo

good,ent data has been but the actual hard data has been very weak in the last number of months. on.her when we concentrate a little bit of a mixed data there. and capitalrs goods, nondefense. reaction some market from abigail doolittle. >> basically in-line jobs report. we are looking at unchanged markets for the major averages. and the nasdaq up 3/10 of 1%. the nasdaq is on pace for another record close. in fact all three major averages are on pace for a weekly gain. turning to a market where there is a little more volatility on the day. that oil had been higher and starting to treat lower. iran sold maybe 13 million ahead off offshore oil the supply cut deal. basically taking advantage of those higher prices ahead of the deal. great -- the hear two year rate trading higher. this tells us bonds are selling off area the two year yield is actually up on the week. these rising yields are helping the bloomberg dollar index. rising rates in the bloomberg dollar index. think the rates will rise more, in light we have the bloomberg dollar index. in blue we have dollar positioning. the

we need to generate more data, but we are quite optimistic that the data rate -- that the data we generateen though it is behind, could prove to be best in class. in that case, second is fine. eric: the cart 15 trial is dealing with leukemia. why is that proving such a tough not to crack? hans: when you treat an adult patient with acute lymphoblastic leukemia, they see the tumor and then they start, the cells start growing quickly. we believe the toxicity from these treatments relate to how fast the cells grow. in a.l.l., there is so much growth to be found, they tend to grow faster. that is why we believe a.l.l. as additional challenges. hans: is it too hard now and you should focus your efforts on lymphoma? hans: i don't think so. we are far from giving up. the patients that we are treating have no therapeutic options. i think all the data we had today acknowledging the challenges you pointed out, in aggregate really encourages that we come up with therapy that may even be curative. eric: there are some people that worry that the industry, companies like yours, are moving too fast with m

this is a big data points. erik: what is your expectation?lair: the expectation is it will be lumpy, and it will not necessarily be a policy that at least through 2017 you can see there are enough data points that you know how it will play out. every situation will have to be examined very carefully on its merits. erik: do i interpret lumpy as inconsistent? blair: we need to know more. yeah. i think inconsistent -- maybe your word. i look at it as you need a body of deals to go through the pipeline to figure out where we really stand. erik: will the president-elect, once he is in office, bully companies into doing different kinds of deals, the way he has started with offshore and trade, for example? blair: i think it is very difficult for anyone outside the company to bully someone into doing something. we saw it with the financial crisis, highly unusual. erik: what about what we have seen with ford and toyota an -- toyota? blair: that is not m and a. matters,y, language and in some ways it becomes self-enforcing. erik: so it is difficult to

cloud data center doing well.re seeing it in microsoft, vmware. we'll have the ceo of vmware on in just a few minutes talking about the same thing. how is that affecting the view on the ground in silicon valley and the business case that start-ups are making for investment? >> yeah, really good question. i mean, one of the things that's interesting is lots of things are talked about in silicon valley and become sort of mainstream, and then you know, then they stop talking about it and just do it. and then the rest of the world is sort of catching pup ining . the debate over cloud is something that happened maybe 10 years ago, maybe 15 in the valley. and then with sgoogle maps and so on, what they did in the early 2000s like gmail in 2004, gmaps in 2005, sales force's rise over the course of the 2000s, the technical debate over cloud versus on-prem, folks pretty much use cloud for everything. you'll build an api and that will have all your clients work with it. now what's interesting is kind of the reverse kind of

. >> new data on where money is being put to work by individual investors.nvestors pulled $5.7 billion in u.s. stock funds in the week that ended wednesday. during the same period money market funds took in 19.8 billion, and taxable bond funds added 2.8 billion. there has been a bit of a reversal of the rapid november/december inflows into stock funds. we'll see if there's real response out there. kind of noisy in january. >> that is the question. whether dow 20,000 ushered in a new wave of money being put to work in this market. >> a lot of reserve of conservatism out there in households. >> we'll go through the individual tech movers. was there anything in the earnings report last night, you were on "closing bell," to derail the rally? >> stock by stock, a lot to of them had run up, including alphabet, but no severe losses. nothing said severe macro issues. >> starbucks with its mobile order crowding issues. >>> now to politics, the mexican peso continuing to slide against the dollar this morning amid rising u.s./mexican tensions. the tension is now on how

data space.ven as you say, they're much older than even the term smart data itself. force is in smart data. abigail: how have they managed to stay around for so long? >> strategies that investors are familiar with dating back to actively managed funds. a lot of smart data etf's are trying to convince investors there is another way, whereas value and growth etf's has sort of replaced active management to some degree with a sort of lower-cost strategy. abigail: what does the performance look like? >> value really took off after the election, up more than 8% at one point, the iwf. growth underperformed. changed now. people are looking for the shift between the strategies. i think was more happenstance this time. if you look at the value etf's, it was dominated by financial firms -- banks like jpmorgan, wells fargo, as well is a lot of oil and gas producers. you had the yield curves in interest rates really start rising after the election, and of the same time you had oil really pick up once the supp

so, i think that you can feel good and the data feels good and the investment that we made inn the data was unequivocally worth it because one of the things we knew is exactly where the undecideds were and what was going to move them and we knew how to go after them whether it would be a door knock, phone call followed up by this and that. but there is no question that i think the magnitude of the wind considering what the conventional wisdom was was enormous. >> you mentioned twitter, can we talk about the? >> sure. >> do you know what the president elect is going to tweet or do you get it on your phone like everybody else?nce in >> every once in a while he says i'm going to tweet something. >> i know everyone says who is doing this one because it is ios, he has multiple devices. >> its follow-up, when you wake up in the morning -- if you sleep -- do you book with a certain sense of dread? [laughter] >> no, but i do look first. that's what's going to drive the news. whatever he tweets is going to drive the news. news. use all the other day he sends out a single one and the idea that ho

so you can feel good, the data feels good. -- the investment we made a data was worth it because one thing that we knew is we knew exactly where the undecideds were and what was going november em. the and we knew how to go after them. whether at door knob or phone call, volunteer phone called and then followed up. how to chase that a absentee. but the magnitude of the win was enormous. >> you mentioned twitter. can we talk about twitter? >> sure. >> do you know what the president-elect is going to tweet before he tweets it or do you get it on your phone like everybody else does some of them are at 3:00 in morning, which is pretty weird. >> i do not. >> you don't get them ahead of time. no once in a while he'll say i'm going to tweet something or, hey what do you think about this? he drives the train on this. >> how does do that -- on his phone? >> yes. sometimes -- he's got an ipad. everyone is like who is doing this. this one ios. she has multiple devices. >> when you wake up -- when you wake up in the morning, if you sleep,. >> one eye open. >> do you look with a certain sense of d