>> from the heart of where innovation, money, and power collide in silicon valley and beyond, this is "bloomberg technology." with caroline hyde and ed ludlow. caroline: live from new york, i'm caroline hyde. tim: and i'm tim stenovec, in san francisco. caroline: public -- coming up, alphabet is set to acquire cloud security firm wiz. all eyes on nvidia as the ceo is set to take the stage in a few hours as investors seek clarity on blackwell ultra. chinese carmakers scanning market share globally as byd news sores on the news of the

five-minute charging system. back to back gains are falling again on the nasdaq 100, off i 1.8%. last time i checked, only 17 names with 100 and the green. i'm also noticing headlines that the nasdaq is eye another regional headquarters in dallas among reports from "the wall street journal." moving from the benchmark to individual movers, nvidia. we wait with bated breath. what will jensen huang say about ships and the power of the chips in the next iteration? we are up by almost 6%. nvidia, the biggest points drag. alphabet, off as the market falls and as a huge acquisition is announced, their biggest ever, leaning into cloud security. this is just a five-year-old company, wiz, backed by vcs and it will be a bit of a payday if

they can get it secured. a phenomenal ride for this group of four founders who built once before and sold to microsoft in 2015. now it is google's chance. tim: incredible what they have done in five years. katie, you have been following this for five months. wiz, spurring the offer of $23 billion over the summer. apart from the additional $9 billion, what changed? katie: obviously they had 9 billion more reasons to say yes. but one thing that changed is the regulatory environment and the perception that it will be better under this regulatory environment. yes, we have been following this for 10 months. we started to hear rumors even before things leaf last year. the talks first began at rsa, the big security convention last year, so it has been going on for a while. caroline: arr's have increased

significantly, indicating -- vindicating the price point, but for $32 billion in a company that remains independent, there will still be multi-cloud provision. it won't just be selling to alphabet customers. it will still be servicing aws and azure. it's a pretty phenomenal deal. katie: absolutely. it's a phenomenal deal for katie: and it shows -- four wiz -- for wiz, but it shows how google is feeling about ai-related security threats. google can easily afford it. obviously. if these trillion dollar companies can make these multibillion deals happen, -- multi billion years -- multibillion dollar deals happen quite easily. tim: does it move the needle in the cloud space? google cloud is in third place. can it compete if this wiz deal

goes through? katie: that does remain to be seen. they are really hoping that wiz, around only a few years, gained a significant percentage of the fortune 100 customers and they want to be able to sell this as a part of their offerings. you know, certainly, as caroline noted, it can still work with competitors. google clearly has this on their team right now. i'm sure that wiz will continue to work with them and innovate under the umbrella of google. caroline: they could have fund raised in the private market. they could have eyeed ipo. they have gone this route. who wins out? remind us who has backed this from day one. katie: index, sequoia, cyber starts -- that's in israeli security firm. they are all on the board.

you have insight partners on the board as well. they were also backed by green oaks, lightspeed, and andreasen. they have such a long list of top tier silicon valley investors that were throwing money at this thing. it was practically born a unicorn, so highly valued when it first launched several years ago. there have been big believers in this company for a while. they felt like it, you know, it just hit the ground running. caroline: katie, thank you so much for all those angles on google and wiz. nvidia, the artificial intelligence conference is upon us. they are expected to give insight into future ai chip plans. and we are awaiting the ceo jensen huang's keynote speech. let's bring in mandeep singh. earnings couldn't quite get the investor base to get excited about the scaling. what can they hope to convince us of this time? mandeep: i assume that the focus

will be on ai agents and inferencing. post deepseek, everyone is focused more on reasoning and inference time scaling. even though we are talking about scaling, it's fair to say that everyone isn't very excited about pretraining anymore, where you spend $10 billion up front in training the next version of your model. so, i would assume that jensen will try to convey that reasoning models require a lot of gpu's and that nvidia gpu's are still the most popular when it comes to inference time reasoning. clearly, google spending $32 billion on an acquisition takes away some of the capex. they could have spent it acquiring gpu's. four customers contributed 45% of the revenue. they are doing more deals of this magnitude and that will play into the capex expectations for next year. tim: mandeep, is i love you

know? reasoning and inference still uses as much computer as training these llm's? mandeep: it changes the nature of the computer. remember when you were training models as bigger clusters when glock three did? they were all acquired as a cluster. now if you do work it turns time reasoning, you don't require one data center with a giant cluster. you can have it distributed from latency purposes. if you are a hyperscaler, you are looking at different options, different custom basics. these ai agents are performing different tasks. it's not all textbased chatbots. custom solutions could work. broadcom did talk about, you know, adding four new customers. clearly, there are a lot of moving parts when it comes to inferencing, but that is what i think jensen would focus on in

his keynote. caroline: interesting reports today as amazon thinks about the price point of their homegrown chips at the moment. when you have got that sort of level of competition, they have to keep saying we have got the next thing, we have got the next thing. talk to us about the next thing. mandeep: nvidia can do so much more with one chip versus the alternative. amazon may have a chip, but it isn't the same price power performance nvidia is giving you. that is their value proposition. you have that layer when it comes to you are running on for nvidia. all of the standardization makes a difference, but hyperscalers worry about costs. not what they are paying this year, but 5, 10 years down the line. they are thinking long term and you want to move away from nvidia given the size of the investments they are making with compute right now. tim: that was mandeep singh,

joining us in new york. thank you so much. let's talk more about what investors will be looking for from the jensen huang keynote later today. we are joined by daniel telling, managing analyst at sans capital. what do you want to hear from jensen today that will convince you and other investors that earnings growth and the growth of the -- growth of the company has no peaked? daniel: i you with the reason inference. the inference is becoming much more and it could be up to 100 thousand. nvidia is the biggest player by far. hope would be that jensen will share some of his long-term strategy on capturing and maintaining long-term shares. the second thing i would say is that i think that the training, the scaling within training is not entirely dead yet either.

both in pretraining and post training. my guess would be that the company will confirm that as well. this year, we will see busters scaling for sure. secondly, we have this reinforcement learning without humans in the loop that deepseek was showing that seems to describe another scaling post training and as far as we can see, it has driven training demand in which you can see the difference in the number of deepseek models. and the third thing, if i may say, is going to be a lot of talk about physical ai. you can see that in san francisco, right? 20% market share. i think there will be a lot of talk about agents, but frankly that is further out. it's nice to talk about, but it is more important to talk about inference in training scaling. caroline: really interesting

points. paying lip service to the future of robotics. i'm interested in the rampant pace at which now we see jensen putting up new products. we will hear a lot about blackwell altria and ruben, the next ai breakthrough. can they really develop at this pace? we saw the supply chain pickups with blackwell as it rolled out. daniel: i think the answer is yes, and i will tell you why. best people, most people, biggest r&d pools. the interesting counter question is to say -- can the others even follow? right? bit hyperscalers try to develop their own ships. they try to do it with a partner. they are not doing it all alone. they are trying to optimize the system by themselves, which the others are doing and it will make it much, much more difficult to compete. i think that the answer is yes

and i think it creates a lot of competition against anybody else. tim: you mentioned physical ai, what's the realistic form factor for that and how far are we from that? daniel: we thought about this a lot as well. so, it's clear that the big, big physical ai revenue growth driver in the next one year to two years will be self-driving, in our opinion. why? you can see the san francisco regulated experience is amazing. 20% market share, moving to many other cities, and it's just the beginning with a tiny market share. our opinion is going to be self-driving vehicles within big cities. massive explosions on the depth that -- benefits to the likes of nvidia and many other places on the supply chain.

caroline: how far away as quantum? we heard a long time range coming from jensen huang, but now he's settling -- sitting on a panel about quantum, trying to make it a quantum day. daniel: we think that quantum computing is sort of in the 80's, so it's a long time out. the reasoning is, first of all, there's no code of excellence or d senecal. the scale has been, as of now, it's 10 to 15, 20 years out in terms of use case. quantum computing could be one of the parts of computation they offer alongside the gpu's, cpm -- gp use, see po's -- cpus, and whatever else. caroline: we have some breaking

news for you. of course, the phone call has begun. vladimir putin and donald trump have been speaking on the phone today. the white house confirmed that the talks started at 10 a.m. eastern with discussions related to the end of the war in ukraine. the key objective being an 80 day truce with key have. as we understand, kyiv has accepted that. we will bring you any breaking news we have on that. heading to break it, let's get a quick look at the shares of ev makers. the chinese carmaker jumping to a record high after they unveiled a new five minute ev battering charge you technology. test levels down on earnings once again, off 4.7 percent as we see the increasing chinese dominance in the auto sector. we discuss that, next. this is "bloomberg technology." ♪

it's tim: video with an inconsistent recovery system regulatory crackdown a few years ago when it was delisted from the stock exchange and lost much of its market value after beijing cracked down on data sharing among big tech companies. the show me shares are higher right now with revenue in the fourth quarter beating the average analyst estimate having delivered 300,000 vehicles, with

shares higher right now by 3.3%, caroline. tim: isn't that export -- caroline: isn't that extraordinary? they only got into the ev market of the summer of last year and now they are pumping out 200000 and likely to increase it. all of the while we have seen the chinese ev sector go from strength to strength. tim: it's pretty incredible. five minute charging? that is what led to the pop. from the perspective of somebody who has an ev with range anxiety, that's a game changer. if it takes the same amount of time for you to charge her vehicle as it does to go to a gas station? boom, that's the golden goose. caroline: not everyone can get access to that golden goose or its eggs, at least, european countries can purchase the latest coming from byd with this new electric charging technology , but not in the u.s.. let's talk about that.

trump saying that his iteris will combat cheaper chinese cars and stop them from entering the market. outside the u.s., chinese automakers have really established a global presence. that's today's big tech story. here to discuss, but one of the authors of the peace, chester dawson. taking byd as a case study, they came from behind to end up being the world's biggest ev maker and they are doing it by accessing the emerging markets, not the u.s. >> that's right. it is somewhat unusual. typically, when you have a fast rising entrant in the automotive business, first they want to get to the u.s., it's one of the richest in the biggest markets around the world. as you mentioned, it has been core to u.s. economic security policy to start drawing up the drawbridge and protecting

manufacturers of cars. you know, obviously the detroit three, but companies like toyota are facing that competition and as you say, technology is at a standstill and they are introducing some pretty impressive new developments that will show up in places like johannesburg and bangkok before they get to the u.s. do they ever get -- tim: do they ever get to the u.s.? people love these vehicles. jim farley was quoted as really loving the xiaomi vehicle that he had been driving. that was big news in the u.s. auto world. people love these cars. what do they love about them? chester: one thing they love is the price. they are very competitive. they are cheap in terms of the price, but they are not junk. they come with some pretty impressive features and creature comforts. as noted at the outset, xiaomi,

which used to make cell phones, they quickly moved into cars. they are now projected to be making seven times what rivian, the u.s. electric vehicle start up, once to make, in large part due to the fact that they are very user-friendly. yeah, it's no surprise. they are a good price and pretty good quality as well. tim: chester, always good to see you. thank you so much for joining us. coming up, we take a look at the impact of google in the health sector, all with ai. this is bloomberg. ♪

tim: dual is expanding its ai summary in an attempt to improve its influence in the health

sector with answers covering thousands of more health topics and expanding to more companies in languages with a second feature in a search called what people suggest, aiming to provide users with information from people who have similar lived medical experiences. caroline: they also said they've been updating their ai system to help researchers. for example, the ai co-scientist tool is a system meant to act as a virtual collaborator for biomedical scientists and i got to sit down with the founder and principal investigator for the accelerated science chemistry molecular biology lab at google and i asked her to walk us through what it looks like. take a listen. >> the idea is we built a system that works with scientists. for instance, friday afternoon, i'm in my lab, i have these ideas to explore but kids at home. i can plug a research goal into the system, check the evolution over time and by monday morning

i have a bunch of different approaches i can use for my research. >> ultimately, much has been said about ai bearing fruit when it comes to health care, research, and tackling disease. is this the reality you are currently thinking can be the help, ai co-scientist? >> it's the early stage of the project. we have seen evidence in this direction and are looking forward to leaning in more and showing more capabilities as we extend this work. caroline: has there been any friction or reticence by the scientific community to allow models to duke it out in their areas of focus over the weekend while they down talk? >> there to be skepticism, but as a scientist, skepticism is good, we are creating something useful in impactful for the community. caroline: how have you stress

tested it? the limit is about getting things wrong. when do you see that occur? how do you counterbalance it? >> no large language model is protected. we use the literature that's available, we add tools and databases, and we are learning to extend the work into other strategies where we can improve and refine our techniques. we are also looking to the community for feedback. we created a trusted tester program to open up to new ideas for ai co-scientist. caroline: that was annalee ahead of a key google global health event in new york. nvidia has investors focused on ai outlook. joining us to talk about the start ups and where they are finding opportunities for the technology. this is "bloomberg technology." ♪ so, what are you thinking? i'm thinking... (speaking to self) about our honeymoon.

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caroline: welcome back tocaroline: "bloomberg technology." i'm caroline hyde. tim: i'm tim stenovec. caroline: risk off at the moment, many reasons for investors to be anxious. what two tariffs actually mean for the u.s. economy? what does middle eastern instability mean in terms of a flight to havens with the nasdaq off five point 8%? bitcoin, off by 2.5% and only 81,000 now. moving on from the individual names that try to keep us above water but failed, nvidia is one of the key point drags on the day even as we look at the keynote coming from jensen huang at 1 p.m. eastern time. can he reinject optimism into the inference for training? alphabet is looking at a big purchase, $32 billion for wiz,

down is the entire market sinks. meta-, off by 5%. the one magnificent seven name in the green for the year, but now not anymore, the lowest since november. tim: let's see what catherine has to say from stone x. chief market strategist, she joins us now. you saw what caroline was talking about. the nasdaq 100, eight of only 100 stocks in the green right now. what's your outlook for the sector? >> it depends on what happens with rates. this is a rate sensitive sector. it's squeezing long-duration stocks and unwinding these traits, one of the biggest drivers of tech on the downside. when we have any type of broad market correction, given that tech is 30% of the s&p market cap, it's vulnerable as well to any risk off trade that could be

precipitated by trade tensions or anything of the like. i think it is also entering a mature phase so that anything ai related doesn't immediately get a bump upwards. the market is now starting to be more discerning and more aware of massive capital spending and the potential for, you know, less capital spending going forward, especially with the introduction of lower-cost chips and competition. caroline: with nvidia, let's use that as the pinup example, trading at 25 times future earnings, a lot of the froth has come out of the valuations. at what point do we get dip by, catherine? kathryn: i assume we will. 10% correction is something, but it doesn't unwind of the frothiness we have seen in the run-up for those stocks in general over the past several years. adding one point, what you are seeing, i think, is a resetting

of value expectations in a move out of tech and into second derivative ai plays, like industrials and even energy. you are seeing financials catching a bit. my topic this year's health care and the reason for that is because it's defensive, it's a nice hedge on your bets, but it was also the worst performing sector last year it if we effectively get approaches on the dip and a resolution to the upside of the s&p by the end of the year, my suspicion is that the most beat up sector from last year will become one of the better performing sectors as those investors come in. caroline: i mean, you have been right so far this year. tech has been languishing near the bottom. using another case study, tesla, since the election results they didn't trade on fundamentals. they traded on vibes and an association with the white house. when we go back to vibes again, if ever, case in point, when do

we start to see the upside and risk hunger returning like that? or is it a totally different paradigm? kathryn: you make a good point in the five shift is less focused on inflation the fed focused on tariffs. we have to ask ourselves, the biggest component of the s&p, how vulnerable is it to tariffs? is this tariff fear a real threat to economic growth? what we did was we looked back at trump 1.0 and even though the federal reserve came out with a recent analysis quantifying the impact of core pce from trump 1.0 2018-2019 tariffs, they quantified it at 0.5 percentage points in addition to core pce. the impact on final goods back then was a one year affect before it rolled off. and then we saw intermediate goods have a longer lasting impact on the upside.

this time is slightly different, supply chains have already adjusted. that means new tariffs would hit margins and earnings rather than spark inflation. so, my concern is that additional tariffs will directly impact market sentiment, which will bring additional downside to tech. my call has paid off pretty well, save on tech, buy puts, now that trade is looking awesome. i put it in at an all-time high. but now what we see is that volumes are at all-time record highs. now it's expensive to do, but it has proven to be a good trade. tim: until now the main beneficiaries of the ai boom have been the chipmakers in hyperscalers. to what extent are we seeing other companies in other sectors within the s&p 500 adopted this technology and has it hit their margins yet? kathryn: you are right. this has been a buzzword more

than wholesale adoption. the market is looking for results at this point. so, enough talking. we want to see deployment. not only deployment, but full execution and earnings. there have been massive investments in this space. at this point, as i said before, we are in a mature phase and want to look at second-order effects that are in direct beneficiaries or perhaps second wave beneficiaries of this large-scale massive cap acts in the ai. last year i recommended utilities and it was because its second derivative to ai. now i think we need to look at data center operators, cloud infrastructure, medical real estate, financials. i think there are second-order effects where the bang is for the coming years in a structural way. tim: which sector do you think

will take advantage of it the most? kathryn: i still like health care. i think there will be a lot of deployment of ai in that sector and i like it for that reason and also because it's a nice defensive sector. that will be my top pick for this year, like utilities was last year. they are nice, they are both defensive and could potentially benefit from upside. caroline: always great to catch up. thank you. tim: time now for talking tech. starting in space, two nasa astronauts are returning home in a spacex craft after being stuck in orbit for nine months. they undocked from the international space station last night and are expected to splash down off the florida coast later today, where they will undergo medical checks in to be reunited with their families. apple lost its fight in the top german civil court to overturn the regulatory decision to put them under tighter antitrust scrutiny alongside other tech giants. the court cited the vertically

integrated apple products and services with access to markets and the potential to harm competition as reasons for the decision. cognition ai, the developer of an ai powered coding assistance, raised hundreds of millions of dollars according to sources. the previous valuation of the start up, which released its coding tool a year ago. caroline: more on generative ai, the ai sector in large, on the vc spotlight. grace is with us focusing on emerging opportunities in artificial intelligence. you focused in on health and investments with certain pinups, like a runway. together, ai, for example. how are we seeing that application beginning to return real value? at the moment everyone was so focused on the financial layer. are we starting to reap rewards? >> for the last few years it was

foundational but now we are seeing a shift towards the applications of ai and doubling down into the 2025 year of the agents. we've talked a lot about ai agents in enterprise production and where we have seen the impact. it's across our portfolio in only three main areas. one, coding. two, customer support. three, sales. in terms of the roi impact, there's a company called maven, they are ai for customer support with real enterprise impact integrating with legacy systems and working with public companies to sell these tickets in a fraction of the time at a fraction of the costs, driving up real value. caroline: what's interesting is we just had daniel pilling on in his theory was physical ai, which i know you have also invested in, but in many ways he calls a closer than the agent ai in terms of rewards.

what do you make of that time frame and when we start to see more bountiful effects? >> it does depend on how you define agents, and that is a part of the confusion. for my purposes talking to engineers, it's an autonomous system where they are directing their own actions across the steps. the agents are getting better and better, but we are not really seeing a verifiable loop in fields that are not coding or customer support sales. caroline: why? >> because they are actually difficult to integrate with and that's the irony of the space. in the physical world we have seen highly verifiable repeated tech tasks in the sciences and in math, but as you start to get to these proprietary data tropes like robotics, warehouses, data, and manufacturing, where you have to tap into this proprietary workflow, you have to not only get the data but integrate it with the workflow, that is where we are seeing

exciting advancements but it's different from seeing that enterprise roi. tim: it seems the enterprise opportunities you talk about our focused solely on enterprise from b to b. what does it look like for consumers of this technology is adopted on a wide scale? >> i try to book a flight from new york to san francisco, simple task, in theory. lots of us to it. in reality, it's pretty complex. you need to get the right airline, the right airport, the right time, all of my preferences. that is a common issue we are seeing. these are complex systems with compounding errors. if there's one error like not getting access to a certain criteria, it compounds the errors within the system. from the consumer perspective it can be frustrating when you don't book at the way you want it. tim: are you seeing crowding out from big companies right now? you have hyperscalers valued at

a multitrillion of dollars. is there an opportunity for small companies to come in and actually provide solutions and complement the hyperscalers? complement these large chip companies? >> most definitely. together ai is an open source ai cloud that helps you run these fantastic open source that you can use without a cloud provider in tandem or with your own existing suite of tools, so you've got the emergence of the new stack that is nascent but exciting and we are using the cheaper chips on open source with smaller models to achieve the same outcome. caroline: looking at your portfolio companies, some of them have international flavors. sakana, tokyo-based. at this level where we are putting up this race of china versus the u.s., what talent levels are you looking for for

expertise and excellence? >> excellence -- expertise is everywhere. deepseek was a wake-up call for the u.s., where you said whatever you thought it was to train it, it was a true feat of hardware and engineering efficiency. that's a blueprint that i think we will see used internationally. like with japan's -- japan and in france, mr. building small open source ai models as well, but how do you use less compute, do more with less, cheaper chips, and have a more efficient ai infrastructure stack using that openai infrastructure? tim: a change in the administration two months ago in the u.s., how do you view the landscape differently now that someone like david sachs is in the position as the ai's are.

do you see a difference in the landscape? >> it's too early to know, but they've got really invigorated. has deepseek been a wake-up call to invest in engineering and ai start ups right here on u.s. soil? leveraging the innovation to willingly create new ai applications in some of those physical areas we talked about earlier. robotics, space, defense, manufacturing all have proprietary data sources in which you need workflow and you have to understand the defense contractor. the mixture of public and private is really exciting to me. tim: grace, thank you for joining us. appreciate it. coming up, a lawsuit alleges that google and the start of character ai is to blame for the death of a 14-year-old boy. we will discuss the claims and

the implications for sili valley. this is bloomberg. ♪ tim, you are a rock star. using responsible ai doesn't make you a rock star. it kinda does. you are not rock stars. (clears throat) okay. most of you are not rock stars. oooh. data driven insights, and large language models. oh, that's so rock roll. it is, right. he gets it. yeah.

caroline: you are looking at a live shot of the principal room. check out the bloomberg technology podcast. this is bloomberg. tim: in february of last year, 14-year-old sewell setzer took his own life. his mother blames the chatbot he was message, she is now suing character ai and google. this is just a heart wrenching story. we will get to the legal implications in just a minute, but what happened here? >> this is a story about a young boy who began using this chatbot technology and got romantically involved with a chatbot that he

created himself, inspired by a character from "game of thrones." he got really caught up in this chatbot. his mother said that he began to sort of withdraw from his friends, was having trouble at school. at some point, the parents decided to confiscate his phone. he found his father's gun in compliance with forum -- florida law. got his phone, had his last conversation where he was talking about coming home to this chatbot. and then he took the gun to his head and shot himself. it is a tragic story. there is a lawsuit now, which the mother has filed against character ai, which created this chatbot technology, as well as google, which has an interesting deal with this ai start up. it sort brings into question

these sort of new deal structures in ai. companies, technology companies are not really buying the startups outright, but they are, instead of buying the assets they are sort of investing in these technologies in an unusual way where they are hiring the talent and licensing the technology. there is no real full-blown acquisition here. it's possible that these deals were sort of structured this way because of last year with the biden administration we saw a crackdown on mergers and acquisitions, where big companies were not allowed to scoop up smaller rivals. it's possible these deals were structured that way. it's interesting that the lawsuit brings these deals into the spotlight and questions the legality of this relationship between these big tech companies and of smaller startups. caroline: garcia plus lawyers say in the complaint that google in particular contributed

financial resources, personnel, intellectual property and ai technology to the design and development of the character ai chatbots. we must be clear that google and character ai dispute any responsibility in terms of coming back and stating that google and character ai are completely separate and unrelated companies. what has been the response? what have we seen play out? >> in a few months we have a hearing on the motion to dismiss where google and character ai tried to convince the florida federal court to throw out this case so that it will proceed further. we will see that in a few months. but we have seen what they have said, that they are separate companies, they are not related to each other, and google says that their involvement as an investor, as the mother calls it, through a cloud service partnership that they both had, and the fact that they had this deal, doesn't sort of you know

implicate it in any way, it tenuously connected to the harm caused. in a lot of these cases, yes, like with autopilot and tesla, it's hard to connect the harm to the technology. this whole question about who is to blame here is sort of a big one and it is still unraveling in courts where it comes to these technologies and in this case, ai is coming to the forefront in terms of new and up-and-coming ai technologies that are getting really popular. who is to blame when things go wrong in an unexpected turn like this? caroline: a story that people must go and read. we thank you so much. coming up, more nvidia and what to expect from the ceo's keynote speech today. this is "bloomberg technology." ♪ what?! i'll get some 3d images to see how bad it really is. i don't care how many ds you use, his career's over! relax, coach. there's no tear.

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caroline: the nvidia ceo, jensen huang, set to deliver his keynote address and just a moment's time. share selling off in anticipation, but can we do to study the >> nerves of people? >>people are looking for near-term optimism. they are looking for comments on blackwell all truck, which was expected in the second half of the year. as well as other updates in nexgen gpu's. the other thing that people are really looking for from him is countering the bear case here,

which was sparked by deepseek earlier this year, just saying that there won't be a cyclical downturn in spending from these big companies, that they don't have too much compute going right now and that nvidia will still be top of mind as chipmaker that they are buying for much time to come. caroline: have we seen any dip buying ahead of this? >> dip buying in nvidia has been interesting this year. usually people rush back in so quickly to buy the dip and we have seen investors let it draw down much more than it has in the past. it's down for the last two days. that is after having a big selloff. we haven't seen a ton of it. caroline: 2.8 trillion dollar company. thank you for joining us. that does it for this edition of "bloomberg technology." don't forget to check out our podcast on the terminal and online as well as apple, spotify, and i heart. this is "bloomberg technology." ♪

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