마크 베니오프 엔터프라이즈 소프트웨어의 자선 활동과 AI 혁신

### 기술과 자선 활동의 비전 있는 영향력: 마크 베니오프와의 대담
* 🌍 마크 베니오프는 **"기술은 좋거나 나쁘지 않으며, 중요한 것은 기술로 무엇을 하느냐입니다."**라고 강조하며 긍정적인 글로벌 영향력을 위한 기술 활용의 중요성을 강조합니다.
* 💡 베니오프는 일을 통해 세상을 변화시키는 것을 목표로 하는 만큼, **자선 활동과 관대함이 회사 설립 초기부터 기업 문화에 필수적인 요소**가 되어야 한다고 믿습니다.
* 🔬 재생 의학 분야의 획기적인 연구, 특히 일반 피부 세포를 줄기세포로 만드는 **야마나카 인자에 대한 연구**로 노벨상을 수상한 연구자 **야마나카 신에 대한 인사이트**를 공유합니다.
* 💉 베니오프는 자신의 혈장을 이용해 아킬레스건을 재생하는 시술을 받은 재생 의학에 대한 개인적인 경험을 이야기하며 **현대 과학의 잠재력**을 보여 줍니다.
* 📈 베니오프는 1999년 창립 이래 Salesforce의 성장을 되돌아보며 **3년마다 꾸준히 매출이 두 배씩 증가**하여 현재 약 **380억 달러에 달한다고 언급**합니다.
* 🤝 그는 자기 자본, 수익, 직원 시간의 1%를 자선 활동에 할당하여 **약 10억 달러의 보조금과 공교육 지원**을 이끌어낸 Salesforce의 자선 활동에 대한 헌신에 대해 설명합니다.
* 💻 엔터프라이즈 소프트웨어의 미래를 바라보는 베니오프는 특히 고객과의 상호작용을 혁신하고 효율성을 높이는 것을 목표로 하는 **새로운 에이전트 포스 기술**을 통해 AI의 잠재력에 큰 기대를 걸고 있습니다.
* 🌟 그는 기술의 미래를 이끌어갈 **신뢰와 지속 가능성**과 같은 가치의 필요성을 강조하며 기업이 사회에서 할 수 있는 긍정적인 역할에 대한 믿음을 강조하며 글을 마무리합니다.

마크 베니오프는 더 나은 세상을 만드는 데 있어 기술과 자선 활동의 혁신적 힘을 강조합니다.

it is the center of the technology world right now. It's not what Mark did, it's when he did it, and the king of the cloud is Salesforce. Please welcome Mark Ben. One of the things that really matters to me is having a positive global impact. Technology is not good or bad, it's what you do with it that matters. In your quest to change the world, don't forget to do something for other people. And that was a moment in time when I said, Wow, when I start a company, I'm going to make sure that philanthropy and giving and generosity and these values are in the culture of the company from day one. You want to stay here, or you want the couch? You want to sit on the couch where you want to sit? I'll give you the couch. I'll sit here. You deserve the couch. You deserve it. The big couch. Okay, it's a little too close. It's nice to see you also. I warned you that I'm not the interviewer in the group, but this is you chose me, so

I'm honored, but you're the nice one. Oh, okay, thank you. Well, it is, am I right? Is he the nice one, and you're the one that all the women really like? Like, I'll talk to my friends at dinner. They're like, You know, Sax, what's he like? He's amazing. Let's just say we're honored to have Mark Benioff here, and truly, who's a visionary in the world of software. And I would say, you know, there's probably a lot of, and I thank my mother for writing that video, by the way. As well, Mom, thank you for writing that for me. Great. You know, in the world of business, offer in particular, we don't have that many people who you can describe as visionaries, but you consistently have been one. You really, it's true. You got the, I think the whole, we're sitting now on the edge of the couch. Okay, here we go. Maybe we'll end up on the floor. I don't know what's going to happen. I'm trying to keep it engag

around a lot. Oh, okay. All right. Is this how it's going to be the whole time? Way worse. Way worse. Okay. All right. Let me finish this little intro here. Um, I forgot where I was, so can I just, before we start, you know, listen. So, I want to just do something I would not normally do, and this is like going to be a little bit of a thing, but I just have to do a little riff on this. But we just heard some extraordinary presentation on an extraordinary man, and there's somebody who's amazing that most people don't get to hear of, and we just heard his name quite a few times. His name is Shin Yamanaka. Yamanaka-san. He is, um, based in Kyoto, Japan, but he works half-time at UCSF, and it's amazing what his vision for the world is, that he thinks basically that we're salamanders and we're going to be able to regenerate ourselves, and that's amazing. And so, I've been friends with him maybe for a decade, but I fund his

research and so a lot of these things to watch him have these breakthroughs, and you heard about the Yamanaka factors. The Yamanaka factors, which are basically this idea that Yamanaka had this breakthrough in Kyoto, you know, basically hanging out there in his lab, eating the sushi, the whole thing, and then boom. And he goes, If I take these four things, I can take an ordinary skin cell, just any little skin cell, and turn it into a stem cell, which is like the heart of human existence. And he did it, and he was able to repeat it and repeat it and repeat it, and he won the Nobel Prize for it. Pretty cool. And then he, and I'm going to get the pronunciation of this wrong, but he then was able to take that stem cell, put it into your eye if you have macular degeneration, and boom, healed the eye because the eye regenerated. Then he worked with a buddy of his in the lab next door, and he took the same thing, took the stem cells, and he turned it into a cookie.

sheet, and it looked like it was like a plastic thing on the cookie sheet. It was really cool. And then he's like, took out somebody's cornea that was all screwed up, cut the material out of the cookie sheet, popped it in the eye, and the guy could see. It was like amazing. Then he's like, listen, this is amazing. I bet I can grow a brain. So he took the stem cells, and he started growing brains called organoids. And he's like, got a cookie sheet of brains, and I'm like, really? He's like, this is amazing. Look at all the brain brains. And I's like, and then I went and saw him and had lunch with him, and like, I'm like, what's happening with the brains? He's like, I stopped the brains. I'm like, why did you stop the brains? I think they can feel the pain. I'm like, oh, scary. Then he's like, then I said to him, now what are you doing? Oh, I'm growing intestines. I'm like, whoa, intestin is

that good. He's like, huge idea. I can now grow intestines on the cookie sheet and taking the, you know, stem cells. I've got a whole intestine here. And then, like, he can do, like, turn it into a lab for all the horrible things that people get in their gut and all these diseases that have never been cured. But now you have a real simulated environment. This is an incredible person. Anyway, where do you want to go with that? I'm going. I'm going with this. You got to stay with me, trying to help bring the energy up in here. Okay, listen, follow. Just hold on, hold on, hold on, hold on, hold wait, wait, wait. This is going to get good. Okay, so then I'm like, You heard the story. Like, at the end, they said, 'Listen, how do I get these regenerative factors going inside myself?' So UCSF just published research based on funding grant that I and others have given them, and they had a breakthrough that the regenerative factor inside your own blood is called pf4. And the way you get pf4, and I'm not

going to get this exactly right because you know I'm in software. I'm not a doctor, so just follow with me. I thought that's what we're going to talk about today, that I know, but I got to tell you this 'cause I'm got so jacked watching that one. Is it was either that or those crazy shots you have backstage. I don't know. Okay, number one is P4. You get more regenerative factors in your body, like what? You know calorie restriction, and if you know David and I, that does not sound very good. Two, working out with weights, also not exactly our top thing. Parabiosis, do you know what that is? So parabiosis kind of came out of research published a decade ago in New York Times and others, which is came from Salval, another person I work with at UCSF, where they took the blood of a young mouse and put it into an old mouse, and then the old mouse got young again, and that was moving the PF4 into that old mouse. So that's, and the fourth thing is cloth.

theapy, which is a genetic therapy that I don't really understand. And these four things can start to generate more of these things inside your body. So then I'm like getting excited. I'm like, God, I have these problems. Maybe I can regenerate different parts of myself, whatever. And so I'm talking to my doctor at UCSF because I'm going through my own serious problem where I'm like, My left leg is like a half an inch shorter than my right leg. And I'm running on the treadmill, and I'm always ripping my Achilles, ripping, ripping. And all of a sudden, my Achilles looks like it has a dut. And in fact, I went to UCSF, and there's like an MRI, you know. Well, how many of you have had an MRI? Raise your hand. So you know what as horrible it is. Anyway, you get in this big machine. They're looking at my Killers. They're come out. They're all like this. Oh, sorry about this. Really horrible. And I'm like, So I kind of took this thought, and I'm

like talking to my doctor. I'm like, why can't we use some of this, figure out what we can do. So he's like, all right, I'm come back on Wednesday. So I come back on Wednesday at 5: CL, you know I'm in Mission Bay at UCSF. And I'm like, hey Anthony, where is everybody? We're going to talk about it. Come into my lab. So I come into the lab. They've got like a centrifuge there, all this stuff going on. I'm like, well, this is interesting. It's like, did you work out today? Yes, I'm work out. Do you're following the P4? I'm doing it. Okay, this is what we're going to do. It's going to be very straightforward because we have two things we can do with you, Mark. Number one, we can just take your kill and we bring you into surgery right now. We'll just shave off half your Achilles and then put you in a boot and see where you are in 6 months. I go, doesn't sound

great second idea. What we're going to do is we're going to take a scalpel B right here. We're going to cut into your Achilles like 20 times and into your ankle. I'm going to take your butt. I'm going to spin it. I'm going to try to find the pf4 in your plasma. I'm going to inject it into your Achilles and into your plasma. Slice into it with my scalpel. I go, sounds great. Goes one problem. I go with that. We don't use anesthesia to do that. Why? Because it destabilizes the PRP and the plasma and all the pf4 and all that. I'm like, let's rock. Let's rock. So he did the whole thing and then boom like an I'm like a salamander. They grew me a new Achilles right in place. So that thing that you just heard that [ __ ] is real and you know it's pretty awesome. What can what and uh it's yeah I have a question for you um so if he can sell

three billion into his startup. I should probably start. I'm ready to go. Got the pitch. Did you ever consider that you missed your calling as a scientific researcher? Definitely not. Definitely not. You're happy with the choices you made? Well, no, that's an incredible story. So, you are one of the first to actually try using the Yamanaka factors on yourself. I wouldn't think I'm one of the first, but I think that it's very real and it's going to have a huge impact on our lives. And I think that we should be supporting these medical researchers. I think it's one of the reasons that I've put almost a billion dollars into UCSF of philanthropy, because I believe in these people who have absolutely, yeah, they've dedicated their lives to basic science and doing and meeting them. They're so inspiring to me. And like, I just had lunch with Yamanaka and Salval and Anthony Luke and another incredible researcher, Mark Moiser, at my house, and

like we're talking about the intersection between oncology and regenerative medicine, which is like two completely different worlds that don't talk to each other. And it's what inspires me that, you know, we can, you know, work with others to kind of give them the entrepreneurial push to go do something incredible. And these people are just awesome. Each one is amazing. That is incredible. So, let's shift gears and talk about something else. Nice coincidence with the, yeah, no, it's incredible. It's a great story. I know you're very philanthropic and do a lot with UCSF, so kudos to you for encouraging that type of research. Let's shift to another thing that's having a huge impact in our lives, which is the cloud and software, where you were a pioneer. You started Salesforce back in 1999, 25 years ago. 25 years ago. And how long have you been a public company for at this point? 24 to 20 years. 20 years. And one of the things I noticed, count 80 earnings calls.

yeah well actually speaking of earnings let's here let's see if we have this slide do we have earnings well first oh yeah oh boy what's what slide is that this is your stock chart over 25 I think 25 years 20 years yeah you're almostly your all I guess there's no linear success exactly right yeah really good point yeah we had a keep basically had a bubble we had a bubble inate 21 we had a huge correction in 22 there was I need to make a note of that we should talk about that but you're your basic back to where you were this is one of your tweets actually this is one of the things I appreciate about the way you do earnings calls is you just put out this really simple tweet and it just and it shows a progression and if you know if you like looking at numbers the way I do and seeing patterns in them one of the things I noticed a while ago was that if you start at the bottom and work your way to the top that Salesforce is

growing by about 20% a year. And if you look at it over 3 years, that's roughly a dou. So every 3 years, Salesforce was doubling, and that means that over a decade, it's growing 10x. And so every decade is basically an exponential if you can stick with it long enough. That was one of the patterns I noticed with sales. Look, I think that the growth obviously is incredible to 38 billion, and obviously, the cash flow is incredible. You know, it's more than Coca-Cola did, I think, last quarter, and the margin is incredible. But let me just say probably the best decision we made in not on the slide, which is the day we started the company, um, we put 1% of our equity, 1% of our profit, 1% of our product, 1% of all of our employees' time into a 50613 foundation. Now, at the time, it was very easy because we had no employees, we had no equity, we had no profit, we had no so.

wasn't very complicated, but that idea though really kind of created the foundation of the company because we're able to do now. And I think you know the numbers right where you know almost 10 million hours of volunteerism. We've been able to give away almost a billion in grants. We run almost 100,000 nonprofits and NGOs for free on our service. And I think it really set the stage that business could be the greatest platform for change when it came for Salesforce. It gave it that philanthropic platform. So is there two billion in equity sitting in that 501c3 at this point? A lot. Well, there's more. I think there's about a half a billion in the foundation. And a lot of has been already given out. And then we give out more every year and every month, every day, whatever. But like on Monday, we'll give another $25 million approximately to the San Francisco and Oakland Public Schools. And that is, you know, we've given them about $150 million. I mean, it's, it's

obviously, I went to public schools. It was very important to me. My mother was a teacher in the San Francisco public schools, but also our employees. You know, have 75,000 employees. Their kids are in the public schools, and so it's a key part of our mantra and our culture that we're trying to support public education. I adopt a public school. I really think that each one of us can needs to focus more on the public education system in the United States. It's something I encourage in not all my employees, but whenever I do a presentation, I'm like, you know, my public school is like a block from my house, Procedo Middle School. And I just went down there and knocked on the door, and they're like, Who are you? And I'm like, What do you, how can I help you, and what can I do to support you? They need a new playground. They need this. They need that. And maybe they just need some me, some support, moral support. But it's been a great thing to really anchor

the company in those values, and I think it's an important thing for every company. So, what did you think when you saw that OpenAI started with a non-profit, not as 1%, but as 100%, but then it became a for-profit? What did you think of that innovation? Confusing? I, you know, I mean, 18,000 companies have now followed our 111 model. You can find out about it at pledge 1.org. That other model, I don't really understand. I think we've proven our model. This is important. You know, we came out with three models: the cloud model, which you also have been part of that, the subscription model, you've also been part of that, and the philanthropic model, and you've been part of that. And those ideas that we're doing three models, that's continues to be the fuel for the company and extremely important. And I think that for a lot of these companies that have followed us, that have gone onto scale and have had huge IPOs, and whether it was Slack or whether it was

at lasan or whether it was eilo or whatever. They have these huge foundations and have had a huge impact, and business can be the greatest platform for change. You can do a lot with your business, and you know, we are all building great products. Okay, that's great, and we're selling them. That's great too, but we can also do a little more with our business, and we can use it in a positive way and try to move the world maybe a little bit more in the right direction. Okay, so let's talk about the cloud part of that innovation. Where do you think we're at right now? I mean, is it all AI all the time? How are you thinking about it? We're at the precipice of the greatest moment in the history of enterprise software and of cloud computing. There's no question. You know, I had a moment, I would say more than a decade ago, which I call my kind of AI freakout moment, where I really felt, I mean, maybe it's, you know

obviously, we've all spent how many of you watched Minority Report. All right, we saw that movie. And what about war games? War Games, anybody remember that from okay, uh, her, um, yeah, we all saw these movies. Terminator, okay, that one's a little scary, but we all seen the movies. And you know, like Peter Schwarz, who wrote or was a key part of writing Minority Report and um, also war games, uh, you know, as our chief futurist at Salesforce. And a decade, more than a decade ago, I had this moment where I was like, okay, this is really happening. Here we go. And bought a bunch of companies and put together Einstein. And Einstein has done amazing, you know, it's doing trillion transactions, trillion and a half transactions a week, predictive, generative. I really thought, okay, this was going to be the moment, but now I'm really convinced that we are now really at the moment right now where enterprise software is going to be completely transformed with artificial intelligence. And we're going to see it, and obviously

I'm getting tuned up for Dreamforce, which is going to be Tuesday of next week. How many of you are coming to Dreamforce? Not enough. Anyway, sad. These aren't my people. I'm leaving now. Well, it's good you well they look but no. Let me just tell, like, since you're not going to be there, let me tell you what's going to happen. Thanks for being part of my team anyway. Number one is, you know, we're going to, you know, we really see a moment right now where we are 100% focused on one thing and one idea. And I can tell you why that is if you're interested, but it's Agent Force. And Agent Force is the most exciting thing I have ever worked on in my career. Um, it's the culmination really of everything that we've done at Salesforce. Because to make Agent Force really deliver, we had to have all of our customer touch points wired up, which we do. We have to have an Amalgamated Data Cloud because we need the data, especially to achieve the AI accuracy.

and the metadata as well, and we have to have the agents. It's these three layers that are really going to deliver this next generation of capability. And I was just with Disney last night, and Disney has agent force. They have the newest version, which we call Atlas, which is our most accurate, not just model, but we have an extremely unusual technique that we'll talk about. And Atlas delivers for Disney, for their cast members, which are their employees, through extremely complex problems that it's solving for them, more than 90% accuracy and almost no hallucinations, and in some cases, 95% accuracy and almost no hallucinations. And that idea that we can kind of come into a very difficult and complex and sophisticated data set now with Disney. If you go to disneystore.com, that's Salesforce. If you go to the Disney parks, do you still go to Disneyland sometimes? Yeah, okay. You ever get a Disney guide sometimes? Yeah, it's great because you get to cut around the lines and all that. How many of you have done the Disney guides thing? We got

like a lot of poor people here actually sad anyway she get these Disney guides cuz they're like get you around the lines you got do 30 rides a day and it's much better than having to wait okay but anyway Disney guides run on sales force they just SL they have slack too they've got we do disneystore.com we have Disney plus because you know the service now like fell over and we had to like replace that inside the Disney plus call center we have we're do the Disney Cruises and the Disney real estate and we have every Disney customer test Point all wired up so The Amalgamated data set that we have around Disney is awesome so when we can take that Disney data set and then we apply Atlas and agent force okay so how do you define we are able to deliver a level of accuracy that has been incredible and I've got a couple more examples I can tell you that are just blowing my mind and I never thought it was really possible but now it really

is go ahead yes well I just wanted to you want me to ask you a question also no no no um what do you mean by agent because we're starting to hear this term a lot but I think a lot of people here may not know what that means in the context of AI did you see the movie The Matrix yes I did so are we talking about agent Smith or what are we talking about well we're at some level I mean I think like I'll give you an example that you know um we're working with a large medical company not so far away from her Kaiser They've got 20 million patients They have a super complex data set They have all of the data from epic They are the largest epic customer in the world and more than 90% of all patient inquiries and scheduling requests and schedule my doctor schedule my CT scan my MRI my this my that are being resolved by agent force and Atlas that idea that we can resolve through a autonomous agent a deep and complex customer interaction is a breakthrough.

thought. Obviously, we have to do a few things to make it really work for our customers. Number one is it's got to be trusted because our customers trust. We're running the largest banks, insurance companies, media companies, CPG companies, blah, blah, blah, blah, blah in the world. Number two is it's got to be easy for them. It can't be some separate team that they're going to spin up. It's their existing Salesforce team. It's happening within the Salesforce platform. It's got to be open. It has to have the ability to work with and interoperate with other systems. It's going to have to be multimodal, so it's going to have to speak to them and have voice and video and do all of those kinds of incredible capabilities. And one other key thing, because evidently the humans have not gone away, the doctors have not gone away from Kaiser, and the cast members have not gone away from Disney, and on and on. So we're going to have to handshake seamlessly with our apps. So even though we have all these apps and we've wired

up all these customer touchpoints the agents are autonomously interacting with and building the data and metadata and extending it. By the end of this month, we'll have more than a thousand customers on our agent force platform. The efficiency and productivity that we've had with agent force is like nothing I have ever seen with any of our customers or technology in the history of software. But there's a second point. It isn't just about this kind of ease of use. It's that they have the ability to do things that are truly astonishing, and that is also generate revenue. So they can go out and, like on a day like today, like it's 10-something degrees outside, or if you've been out there, it's pretty hot, and Disneyland may not be as full today as it's going to be. And they knew that was going to be true two days ago, that a heat wave was coming. Disney can proactively go out to their consumers and their customers and say, Hey, come enjoy the heat with us, all you know Disneyland, and we're going to give you a

special promotion or price or contest or whatever it is to come to Disneyland. So, we want to be able to proactively go out and generate revenue, and we also want to be able to kind of bring that customer service in. I think last night I had dinner at Beverly Hills at the grill. Have you been there? Great right cream spinach. Well, I did something different. B, what do you want? What do you prefer? Um, well, I like potatoes, you know, potatoes. Okay, po, you know any kind of potato you like? Any kind of potato, baked potato, steak fries, all. So, I'm on Open Table. Right? Anybody here use Open Table? Not. It's a very weird group. Anyway, so, oh, I'm using. Anyway, you can use Open Table to make restaurant reservations, and there's 160 million consumers on Open Table. They're not in this room, but they're somewhere, and they've got also 60,000 restaurants, and they've got a lot of complex issues, you know, in regard, you know, I didn't get my table or my food wasn't right, my potato.

didn't get cooked. Whatever it is, these things are going to get worked out. But also, all of a sudden, the restaurant's like, Oh, look, we're not as full tonight as we want to be, and we're willing to do. Let's go out to our customer base and bring them in, but let's do it through a complex conversation, you know, an empathic conversation as an agent with our customers. I think it's going to be a rocket ship. Okay, so how long will it be until when you call a customer support center, you're talking to an AI that sounds like a human, and you can't tell the difference? Are we there yet, or we're there yet? We are already at that point. We already have that live, and we will have that scaled for thousands of customers before the end of um live for with thousands of customers live before the end of this year. And we just, I just demoed it. I was just at a conference and spoke a mile, couple miles away from here at KPMG, and we

showed them that exact situation where you know through you know we used to call you know this kind of voice response system whatever but you would kind of hit a wall pretty quickly with your Bot you know but these aren't Bots these are not the Bots you're looking for. These are like we're really getting to like another level capability and I think that it's pretty impressive. And I think in the example of Disney you know Google has some great products. I know Serj was here yesterday and they've done a great job with AI as you know but in a head-to-head Benchmark of sales forces agent force against Google's AI uh we twox them on accuracy. And the reason why is we'll explain it next week um you know it's a couple of things not only is there our NextGen models but it's also new techniques involving Next Generation retrieval augmented generation rag techniques that no one has seen before and it's really incredible what's possible. So you're kicking Google's ass. I'm cool with that. Well they're good

partner also customer, and I love them, but yeah, it's competitive. Just yeah, let me keep holding on this. We're trying to all make AI a little more accurate and a lot of less, a little few less hallucinations along the way. Let me give the audience a little update about something we just heard at OpenAI. They just did a day where they brought in a relatively small number of investors and kind of gave us all an update on their product roadmap, and it sounds kind of similar because everyone's moving in the same direction. So, there are three big takeaways. Number one was that they said that LLMs would soon be at PhD-level reasoning. Right now, it's more like a smart high school or college student in terms of the answers. We're going to be at the next level shortly. Behind that is agents, like you're talking about, and then third, and closely related, is that agents will have the ability to use tools, and a tool can be a website. So, if you think about it

now you've got this LLM. It's really smart. It's got, you know, it's like a PhD. You can give it an objective. It will break that objective into a list of tasks, and those tasks can include using other pieces of software. And thanks to things like OpenAI just launched the audio API, which developers can use. It's in private beta. We have some companies using it. The LLM can now basically pretend to be a human. And you know, there won't be hard to find a piece of software to enable a phone call. So you can imagine telling a personal assistant agent that. And it could be, you know, it could be OpenTable that, Hey, book me a dinner reservation at the grill. And it could place a phone call on your behalf and actually talk to the grill. It could also go on OpenTable and just use OpenTable and book it. But if for some reason that didn't work, it could literally place a phone call on your behalf. And the person picking up at

Open Table wouldn't even know that your agent actually isn't a human; it's an AI. But here's where I think it gets really crazy: is when the phone gets picked up on the other end, that could be an AI too, pretending to be a human. So, you could have two AIs pretend to be humans talking to each other and resolving tasks on your behalf. And I literally, I think that's where it's at. We're definitely moving in this direction, but there's a cautionary tale here. And I think that I'll just tell you the real-world experience with my customers and what I'm the problems that I'm trying to solve for them. I think in the last few years, we've kind of heard, and you know, some of it has come from OpenAI, but especially from Microsoft, that we're in this co-pilot world. And these co-pilots have universally failed. The level of accuracy, the spillage of information, the lack of trusted environment, co-pilot has been a complete disaster.

and that idea that this kind of amount of technology got, you know, released and sold into these very large customers, telling them that the all promise of AI is here, but didn't do it in a trusted way, didn't do it with the level of accuracy, didn't do it with the level of security needed. And one of the things that was interesting, because I was with one of the customers, was trying to do this exact technique that you're talking about, which is a large telecommunications company in Seattle. And what this company did is take model of nope, going to just tell you training a model, retraining a model, building their own model. Mark, we have to have our own models, we're going to DIY it, we're going to DIY our AI, and it's going to be awesome. Then we're going to write our own agents, and we're going to do this, we're going to do that, the other thing. And I'm sitting there, and I'm going through it, and whatever, and I'm then I finally, I'm like, now show me your

benchmarks and show me all these different pieces. And, you know, for them, it's a bit of a science project. And I've seen this now with a number of our customers that they're kind of DIY-ing their AI. And, you know, DIY, I think it's fine if you're like Neil Young and it's homegrown and it's Canada and it's, you know, Ontario. But this is not what you should be doing with your artificial intelligence. But what are you guys using as your foundation model? Is it Llama 2? Like, what do you guys use? We have a lot of our own models, our own techniques, our own. And then we let you bring in the model that you want. But we are all about achieving your accuracy. Because what I've seen with these kind of approaches, especially the one that you just outlined, is that, yeah, you can get maybe 30 or 40% accuracy. You know, in this case, this customer is 25%. You had somebody on the stage yesterday. I won't tell who it is, who's a common friend of both of ours.

who tried to take this approach for a large telecommunications company that he owns. He said he was getting about a 25% accuracy with this homegrown model. I'm like, why are you doing that instead in our platform? The platform is building the model for you. You're not having to train and retrain your own models. You're building your own models in our platform, and we're going to deliver much higher levels of accuracy for you. We're going to deliver AI. This is the AI that you want. This is this next generation of AI. I think that we'll have to prove that with benchmarks and with bake-offs and to show customers because the promise is amazing, but at a very deep level, customers are going to need what you and I have done for the last 20 years of our life, which is build professional enterprise software and deliver it to them in a capability. In regards to an agent running enterprise software, I mean, you just saw, like, that was the fundamental business model of Adept.

which was David Lewan's company. You know, and that's he built GPT-3. Then he left OpenAI to start Adept and this idea to build agents that are going to drive apps. I'm sure that all of those things are going to happen, but again, you have to get to a level of accuracy because everyone in this room and you and I, we've all had this experience where on these models, and it's like this is not really more than hallucinations, and that's no good or as we say here in Los Angeles, no es bueno. When it comes to, okay, Kaiser, and you're dealing with health care, you know, when you're dealing with health care and you've got a patient and you're reading their medical records, you better be delivering more than 90 or 95% accuracy because the 50% accuracy thing is no good. Well, I can see you're ready for Dreamforce. I'm trying to go find it. I'm testing Matt out here a little bit. What do you guys think? I'm

like are you guys excited for the rise of Agents? Yeah, it's going to be a really big deal. I think that everything we've seen so far with LLMs has been, again, about reasoning and generating, but with agents, the AI is going to be able to take actions, and they're going to know how to use tools, which until now has been some of the only human. I got to tell you a really good story because you're inspiring me around, you know, Steve Jobs had a huge impact on my life. I worked at Apple in 1984 when I was in high school and coming into college. I was an assembly language programmer. I wrote the first Native Assembly Language on this Macintosh, the 68,000 assembler, and sitting there in the cubes, and Steve is running whatever it is. Thank God, you know, I have this relationship and influenced me so much in my life, and then called me on a series of times, and after I started.

Salesforce gave me really key advice. Anyway, it was 2010, and he calls me, Come down here. I need to talk to you. I'm like, [__] what the hell. What did I do this time? So, I go down there to his office, and I always bring a few Salesforce employees with me, and I've got some great folks with me, and we're sitting there, and he's like, I'm going to show you this, and I'm like, All right, let's go. And he brings out the iPad, and he's got two of them. He's got the big one and the small one, and he's like, Yeah, Mark, here it is. You know, but I don't like the small one. I'm only going to have one size, you know. And I'm like, Yes, sir. And he's like, Uh, listen, you know, I've been working on this concept for a long time, and you know, in 2007, um, I introduced the iPhone, and you know, I said, 'Thank you for sending me one. I love it. It's great.' Like, but do you

know why now we're doing the iPad. I'm like, no, because I know you had that too in 2007. Oh yeah, but you know what the real situation here is that couple. I'm like, what is it, Steve? He's like, we only have one A team here, one A team, so we're only focused on one thing at a time. And then he lays out like five or six products on his coffee table, and he goes, and we will never have more products than can fit on my coffee table. And I'm like, well, that's really awesome. And he's like, I've been focused on 2007 on the iPhone, and now I'm gonna zero in, and I'm only going to do iPad, one focus at a time. Remember that, Mark? That's the way you need to rent Salesforce. And I'm like, okay, is that why you brought me down here? Yes, you may go. And that's how I feel right now about agent force. This is all I am doing, just trying to take our company. You know, we have a great company, 38 billion revenue.

75,000 employees, hundreds of thousands of customers, and one Focus agent force. This is the moment, this is the greatest opportunity in the history of enterprise software, and it must be executed with absolute acuity and excellence. And that is what I think we all need to do. You know, so I agree with you. I mean, I think the agents are going to be huge. And Elon said something kind of similar the other day. He said we got him talking about Optimus, you know, his robot. Heard about the farm animals? I didn't know about the what was, was there another part of the presentation? He said, Well, he was talking about, he's talking about Optimist and, um, oh you, the thing about these jokes are all, each one is kind of dying very fast. It's sad. Took me a second to realize that you were talking about his [ __ ] um, but now I got it. Okay, um, no, he was referring to um, it's great how you bring

this humor into uh the Allin yes it's very subtle I understand um so what Elon mentioned that really stuck with me is he said that humanoid robots the creation of these humanoid robots are the biggest Economic Opportunity in the history of the world the average person is he making some of them by any chance he is but well it's kind of like you saying that uh agents are the biggest opportunity in the history of Enterprise software let me write that down thank you for letting me know that it's it strikes me that there's something similar here which isan is a good salesman is that your point well I'm I'm saying there's an analogy here between he didn't give you the regenerative pitch is that my well no what here me the point is this is that is that where we're going with AI is it's going to be able to take real actions and in the case of Optimus is in the physical world and it's going to be the brain for these humanoid robots in the Enterprise it's basically the brain.

for these agents. I think these things are actually pretty. They're on parallel tracks. I wouldn't say they're competing. And these are the droids you're looking for. So, I think anyway. I think that uh. I think you're right about this opportunity. And what I'm saying is I think it's analogous to what Elon is seeing with robotics. I think there's no question. And I think that for our customers. They're going to augment their employees. They're going to make things lower cost. They're going to increase their revenues. They're going to increase their margins. We're going to take some customers and just turn them into margin machines. And I think that the opportunity in the enterprise is unbelievable. He's also directly addressing the consumer market. Which I think is very exciting. Obviously, he's an expert in that area. And yeah, we're about to move into this new world of AI. Of droids. Of all these things. And you know, it's a bunch of waves of you know where you know look technology is getting

lower cost and easier to use. It's a continuum, and we're all riding that continuum. This is extremely important, but also what's very important is, especially as we move into this, we all have to think about what are the values that are going to guide this technology. Because each of us have seen the movies, we all watched the movies, that was the one place where I got the hands to go up, right? So, we know how it can go really wrong, right? Everybody saw that part of the movie. So, what are the values? What's going to be really important to us? Will it be trust? Is it customer success? Is it innovation? Is it equality? Is it sustainability? What are the values as we kind of guide into the next level of the future? Because those core values that we need to manifest and really focus on, that is, I think, still out there as a major discussion item. It's got to be figured out, and that is why we're very lucky that you are one of the great visionaries of our industry, because

you're not just a great entrepreneur and CEO, but you're a great human being. So, thank you, Mark. Thank you.

Marc Benioff | All-In Summit 2024

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All-In Podcast

기술과 자선 활동에 대한 마크 베니오프의 비전

마크 베니오프는 회사를 설립할 때부터 기술을 통해 전 세계에 긍정적인 영향을 미치는 것의 중요성을 강조하고 자선 활동을 중시했습니다.

그는 줄기세포를 이용한 재생 의학 분야의 획기적인 연구로 노벨상을 수상한 야마나카 신의 감동적인 이야기를 들려줍니다.

야마나카의 연구는 황반변성 치료와 장기 성장 등 놀라운 의학적 혁신을 이끌어냈으며, 의료 서비스를 혁신하는 데 있어 재생 인자의 잠재력을 보여주었습니다.

연사는 칼로리 제한, 웨이트 트레이닝, 파라바이오시스(젊은 수혈), 유전자 치료 등 체내 재생 인자를 증가시키는 네 가지 주요 방법에 대해 설명합니다.

연사는 개인적인 건강 문제를 경험한 후 아킬레스건 재생을 위해 PF4 플라즈마 주사와 메스를 이용한 독특한 치료를 받습니다.

연사는 의학 연구 지원의 중요성을 강조하고 혁신적인 과학 연구를 촉진하기 위한 UCSF의 자선 활동을 공유합니다.

Salesforce의 성장과 자선 활동의 영향력

Salesforce는 3년마다 매출을 두 배로 늘리고 10년 동안 10배의 성장을 목표로 하는 등 괄목할 만한 성장을 거듭해 왔습니다.

창립 초기부터 시작된 자선 활동으로 10억 달러에 가까운 기부금과 1,000만 시간의 자원봉사가 이루어졌습니다.

비즈니스 성공과 사회적 영향력을 통합하는 Salesforce의 모델은 18,000개 이상의 기업이 유사한 접근 방식을 채택하도록 영감을 주었습니다.

AI로 엔터프라이즈 소프트웨어 혁신

연사는 마이너리티 리포트와 워 게임과 같은 영화에서 영감을 얻은 AI의 영향력을 되돌아보고 Salesforce의 아인슈타인의 성공에 대해 이야기합니다.

또한 고객 접점, 데이터 클라우드, 에이전트라는 세 가지 계층적 접근 방식을 통해 엔터프라이즈 소프트웨어를 혁신하는 것을 목표로 하는 Salesforce의 최신 이니셔티브인 에이전트 포스의 중요성을 강조합니다.

연사는 Disney와 대형 의료 회사 같은 고객을 위해 복잡한 문제 해결에 90% 이상의 정확도를 제공함으로써 고객 상호 작용에 혁신을 가져온 에이전트 포스와 Atlas의 성공을 강조합니다.

AI 에이전트 포스 플랫폼은 신뢰할 수 있고 사용하기 쉬우며 상호 운용성을 위해 개방적이고 멀티모달 커뮤니케이션이 가능하도록 설계되었습니다.

기존 앱 및 고객 접점과 원활하게 통합되어 놀라운 효율성과 생산성을 제공하는 것을 목표로 합니다.

또한 이 플랫폼은 특별 프로모션과 콘테스트를 통해 고객의 참여를 유도하여 비즈니스의 수익을 선제적으로 창출할 수 있는 기능도 갖추고 있습니다.

AI의 미래: 주요 업데이트 및 과제

OpenAI의 최근 투자자 업데이트에 따르면 LLM은 곧 박사 수준의 추론 능력을 갖추게 될 것이며, 전화 걸기 등의 도구를 사용할 수 있는 에이전트를 보유하게 될 것이라고 합니다.

AI가 대화에서 인간을 사칭할 수 있는 가능성은 윤리적 우려를 불러일으킵니다.

많은 기업이 AI 모델을 직접 만들려고 시도하고 있지만 이러한 접근 방식은 정확도가 낮고 효과가 입증되지 않았습니다.

AI와 엔터프라이즈 소프트웨어의 미래

한 통신 회사 소유주가 자체 개발한 모델로 25%의 정확도만 달성하고 있어 모델 구축에 전용 플랫폼을 사용할 때의 이점에 대한 토론이 진행되었습니다.

연사는 특히 의료와 같은 중요한 분야에서 높은 정확도를 제공하는 것이 중요하다고 강조합니다.

AI 에이전트의 부상은 조치를 취하고 도구를 사용할 수 있는 잠재력과 함께 게임 체인저로 강조되며, 연사는 스티브 잡스의 영향력과 한 번에 하나의 제품에 집중했던 개인적인 이야기를 공유합니다.

AI와 휴머노이드 로봇의 영향력

AI와 휴머노이드 로봇의 통합은 엔터프라이즈 소프트웨어와 그 밖의 분야에서 가장 큰 경제적 기회로 여겨지고 있습니다.

AI 에이전트와 휴머노이드 로봇은 모두 직원을 보강하고 비용을 절감하며 기업의 수익을 증대할 것으로 기대됩니다.

이 토론에서는 새로운 기술 시대로 나아갈 때 신뢰와 혁신과 같은 기본 가치의 중요성을 강조합니다.