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Satya Nadella talks about Microsoft’s new AI strategy. Asks “if you’re [only] a consumer of foundation models…how can you create enterprise value?” In his view, companies should combine their internal IP and tacit knowledge with an AI “hill-climbing machine” (reinforcement learning, custom evals) that is model agnostic. Obviously, he... show more

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Microsoft CEO Satya Nadella's new interivew: Explains how the next AI moat will not be the model you use, but the learning loop only your company can run. He is really asking what happens to the firm when intelligence becomes something you can rent. For a century, companies protected value through people, processes, data, routines, customer memory, and the tacit knowledge buried in daily operations. Foundation models threaten to flatten that advantage because the same general intelligence can be used by everyone. Nadella’s answer is that firms need their own “hill climbing machine,” a private loop where models learn from company-specific tasks, traces, evaluations, and outcomes. That means the real asset is not just the model. The asset is the environment that keeps improving the model in ways competitors cannot copy. Private evals become strategic memory. Workflow traces become training signal. Human judgment becomes a way to steer compounding, not just correct mistakes. This also reframes AI adoption: a company that only consumes a foundation model may gain productivity, but it may leak the deeper value of its operating knowledge. A company that builds a disciplined learning loop can turn everyday work into accumulating IP. The future firm may therefore be measured by how well it converts its unique activity into durable model improvement. The frontier will not belong only to whoever owns the largest model. It will belong to whoever owns the best loop. ---- From "Stanford Online" YouTube channel, (link in comment)

Microsoft CEO Satya Nadella's new interivew: Explains how the next AI moat will not be the model you use, but the learning loop only your company can run. He is really asking what happens to the firm when intelligence becomes something you can rent. For a century, companies protected value through people, processes, data, routines, customer memory, and the tacit knowledge buried in daily operations. Foundation models threaten to flatten that advantage because the same general intelligence can be used by everyone. Nadella’s answer is that firms need their own “hill climbing machine,” a private loop where models learn from company-specific tasks, traces, evaluations, and outcomes. That means the real asset is not just the model. The asset is the environment that keeps improving the model in ways competitors cannot copy. Private evals become strategic memory. Workflow traces become training signal. Human judgment becomes a way to steer compounding, not just correct mistakes. This also reframes AI adoption: a company that only consumes a foundation model may gain productivity, but it may leak the deeper value of its operating knowledge. A company that builds a disciplined learning loop can turn everyday work into accumulating IP. The future firm may therefore be measured by how well it converts its unique activity into durable model improvement. The frontier will not belong only to whoever owns the largest model. It will belong to whoever owns the best loop. ---- From "Stanford Online" YouTube channel, (link in comment)

Rohan Paul

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Satya Nadella just clarified the Microsoft open Ai deal and the terms what they signed for Azure. Here is exactly how he breaks down the partnership How it was Essentially think of OpenAI having a PaaS business and a SaaS business. The SaaS business is ChatGPT. Their PaaS business is their API. That API is Azure exclusive. The SaaS business, they can run it anywhere. If they want a partner and that partner wants to use a stateless API, then Azure is the place where they can get the stateless API. for even that they'll have to come to Azure. For any custom agreement like that. There are some few exceptions, the US government and so on, that we made, but other than that, they'd have to come to Azure. Open Ai can host there Chat Gpt consumer app wherever they want there wish but when it comes to developers or enterprise want to build on top of Open Ai models Microsoft owned the pipeline.

Satya Nadella just clarified the Microsoft open Ai deal and the terms what they signed for Azure. Here is exactly how he breaks down the partnership How it was Essentially think of OpenAI having a PaaS business and a SaaS business. The SaaS business is ChatGPT. Their PaaS business is their API. That API is Azure exclusive. The SaaS business, they can run it anywhere. If they want a partner and that partner wants to use a stateless API, then Azure is the place where they can get the stateless API. for even that they'll have to come to Azure. For any custom agreement like that. There are some few exceptions, the US government and so on, that we made, but other than that, they'd have to come to Azure. Open Ai can host there Chat Gpt consumer app wherever they want there wish but when it comes to developers or enterprise want to build on top of Open Ai models Microsoft owned the pipeline.

Vikram M

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LIVE from Davos: Satya Nadella joins the Besties! 🚨 Satya Nadella sits down with @jason and David Sacks from the main stage at USA House! -- Future of AI copilots and agents: how white collar work will change -- Scaling revenue and profits with flat headcount -- Views on diffusion and having the US AI stack win globally -- Foundation model concerns?: OpenAI's IP, will open-source win? -- SaaS adoption in the age of AI (0:00) Jason and Sacks welcome Microsoft CEO Satya Nadella (1:31) Future of AI copilots and agents, impact on white collar work (8:01) How Microsoft has scaled revenue and profits with flat headcount (10:50) The extreme competition in AI: Microsoft, xAI, Google, OpenAI, Anthropic (12:39) Views on diffusion, how the US tech stack can win globally (19:59) OpenAI deal, owning the IP, thoughts on open-source winning AI, Microsoft's AI stack, do they need a foundation model? (26:08) What enterprise software adoption looks like in the age of AI

LIVE from Davos: Satya Nadella joins the Besties! 🚨 Satya Nadella sits down with @jason and David Sacks from the main stage at USA House! -- Future of AI copilots and agents: how white collar work will change -- Scaling revenue and profits with flat headcount -- Views on diffusion and having the US AI stack win globally -- Foundation model concerns?: OpenAI's IP, will open-source win? -- SaaS adoption in the age of AI (0:00) Jason and Sacks welcome Microsoft CEO Satya Nadella (1:31) Future of AI copilots and agents, impact on white collar work (8:01) How Microsoft has scaled revenue and profits with flat headcount (10:50) The extreme competition in AI: Microsoft, xAI, Google, OpenAI, Anthropic (12:39) Views on diffusion, how the US tech stack can win globally (19:59) OpenAI deal, owning the IP, thoughts on open-source winning AI, Microsoft's AI stack, do they need a foundation model? (26:08) What enterprise software adoption looks like in the age of AI

The All-In Podcast

860,113 Aufrufe • vor 6 Monaten

Satya Nadella reveals why every company may need its own AI model: the model becomes the new company database. "To me, a model is like the database market." "A firm should be able to take the tacit knowledge it has and embed it inside weights in a model that they control." "When somebody asks me how many models should there be, I'll say as many models as firms in the world." The contrarian part: the value may not sit in one universal frontier model. It sits in each company turning its private operating knowledge into a controlled model.

Satya Nadella reveals why every company may need its own AI model: the model becomes the new company database. "To me, a model is like the database market." "A firm should be able to take the tacit knowledge it has and embed it inside weights in a model that they control." "When somebody asks me how many models should there be, I'll say as many models as firms in the world." The contrarian part: the value may not sit in one universal frontier model. It sits in each company turning its private operating knowledge into a controlled model.

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JD Vance just admitted the White House could take ownership of every major AI company in the US. Why? Because even governments are starting to realize the same thing: AI will create trillions in value, and at this rate, only a few Big Tech companies will benefit. Right now, billions of people are training AI every day through their data, actions, and online behavior. Yet almost all of the value flows back to a few billionaires and shareholders. That doesn't seem fair. At Action Model, we're building a different future. A people-owned AI model where those helping train it can share in the value they help create. If AI is built by the people, it should benefit the people too. Sign up to the Action Model movement and join the 500k+ users already contributing to a community-owned AI.

JD Vance just admitted the White House could take ownership of every major AI company in the US. Why? Because even governments are starting to realize the same thing: AI will create trillions in value, and at this rate, only a few Big Tech companies will benefit. Right now, billions of people are training AI every day through their data, actions, and online behavior. Yet almost all of the value flows back to a few billionaires and shareholders. That doesn't seem fair. At Action Model, we're building a different future. A people-owned AI model where those helping train it can share in the value they help create. If AI is built by the people, it should benefit the people too. Sign up to the Action Model movement and join the 500k+ users already contributing to a community-owned AI.

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Jensen Huang on "distillation" On his new interview with axios, he was asked this question "Should open source model companies be allowed to distill closed models" "Distillation—learning from AI, learning from other people, and learning from other sources of knowledge, is fundamental to intelligence. We are constantly learning from other people. I am learning from you through the questions you are asking, and you are learning from me. All day long, we are learning from one another. AI also has to learn from something. The original AI models, whether they were open or closed, were trained on previously created knowledge from the internet. Now, AI is generating more content than humans. In a few more years, the internet could be 99% AI-generated content, and that content will have been created by some form of AI. As a result, AI systems will constantly be distilling knowledge and intelligence from other AI systems. The fact that AI can learn is a good thing. We want AI systems to be intelligent because a smarter AI can also be a safer AI." ---- From "Axios" YouTube channel, (full video link in comment)

Jensen Huang on "distillation" On his new interview with axios, he was asked this question "Should open source model companies be allowed to distill closed models" "Distillation—learning from AI, learning from other people, and learning from other sources of knowledge, is fundamental to intelligence. We are constantly learning from other people. I am learning from you through the questions you are asking, and you are learning from me. All day long, we are learning from one another. AI also has to learn from something. The original AI models, whether they were open or closed, were trained on previously created knowledge from the internet. Now, AI is generating more content than humans. In a few more years, the internet could be 99% AI-generated content, and that content will have been created by some form of AI. As a result, AI systems will constantly be distilling knowledge and intelligence from other AI systems. The fact that AI can learn is a good thing. We want AI systems to be intelligent because a smarter AI can also be a safer AI." ---- From "Axios" YouTube channel, (full video link in comment)

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$An OpenAI insider just revealed why the AI race is moving so fast. Daniel Kokotajlo, a former OpenAI researcher, says the race isn't just about building better AI. It's about economic power. Whoever builds the leading AI systems could shape the next global economy. He also believes AI has the potential to dramatically improve humanity. But if that power ends up concentrated in the hands of just a few companies, the consequences could be enormous. That's why we built Action Model. A community-owned AI model where the people helping train, grow, and build the ecosystem can earn a fractional stake in the value they help create. AI is inevitable. An AI future owned by only a handful of companies isn't.$

An OpenAI insider just revealed why the AI race is moving so fast. Daniel Kokotajlo, a former OpenAI researcher, says the race isn't just about building better AI. It's about economic power. Whoever builds the leading AI systems could shape the next global economy. He also believes AI has the potential to dramatically improve humanity. But if that power ends up concentrated in the hands of just a few companies, the consequences could be enormous. That's why we built Action Model. A community-owned AI model where the people helping train, grow, and build the ecosystem can earn a fractional stake in the value they help create. AI is inevitable. An AI future owned by only a handful of companies isn't.

Action Model

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AI artist Refik Anadol shows how images are curated, converted into data points, and then plotted into a multi-dimensional space he navigates through with a gaming controller. “This is AI dreaming this world,” he says, adding that the creation is only “in the mind of a machine.”

AI artist Refik Anadol shows how images are curated, converted into data points, and then plotted into a multi-dimensional space he navigates through with a gaming controller. “This is AI dreaming this world,” he says, adding that the creation is only “in the mind of a machine.”

60 Minutes

38,645 Aufrufe • vor 5 Monaten

Satya Nadella says the AI industry has talked so much doom that people have stopped wanting it to succeed: "All economic opportunity will go away for knowledge workers." "White-collar jobs are gone. And then you're saying, I'm excited about building that technology." "Why would anyone want you to be successful? I mean, I don't want you to be successful. I mean, this just makes no social sense." "When you have someone in a college commencement be booed because they're saying AI, it means we have now crossed over to people who don't believe us, and rightfully so." "If you're building a data center, let's make sure that that community believes that this data center is great for them. It's for their tax base, for their community efforts, their real estate value, their schools, their water use, their electricity prices." "We can't abstractly even say... there's going to be new jobs. What are the new jobs? What are the wages of the new jobs that I can now go apply for, train myself for?" Notice who is saying this. Nadella runs one of the largest AI buildouts in the world, and he is saying in public that people have stopped believing the industry, and that they are right. And his fix is specific. Name the new jobs and the wages someone can actually train for. Make the data center pencil out for the town that hosts it, in taxes, schools, water use and electricity prices residents can check for themselves. Every one of those claims can be verified or shown false. Almost nobody building AI talks this way today. - Satya Nadella (Satya Nadella), Chairman and CEO of Microsoft, on Possible with Reid Hoffman (Reid Hoffman).

Satya Nadella says the AI industry has talked so much doom that people have stopped wanting it to succeed: "All economic opportunity will go away for knowledge workers." "White-collar jobs are gone. And then you're saying, I'm excited about building that technology." "Why would anyone want you to be successful? I mean, I don't want you to be successful. I mean, this just makes no social sense." "When you have someone in a college commencement be booed because they're saying AI, it means we have now crossed over to people who don't believe us, and rightfully so." "If you're building a data center, let's make sure that that community believes that this data center is great for them. It's for their tax base, for their community efforts, their real estate value, their schools, their water use, their electricity prices." "We can't abstractly even say... there's going to be new jobs. What are the new jobs? What are the wages of the new jobs that I can now go apply for, train myself for?" Notice who is saying this. Nadella runs one of the largest AI buildouts in the world, and he is saying in public that people have stopped believing the industry, and that they are right. And his fix is specific. Name the new jobs and the wages someone can actually train for. Make the data center pencil out for the town that hosts it, in taxes, schools, water use and electricity prices residents can check for themselves. Every one of those claims can be verified or shown false. Almost nobody building AI talks this way today. - Satya Nadella (Satya Nadella), Chairman and CEO of Microsoft, on Possible with Reid Hoffman (Reid Hoffman).

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The biggest driver of AI compute now is real-world deployment. At NVIDIA GTC, IREN's Kent Draper, alongside Lenovo's Vlad Rozanovich, shared what they’re actually seeing on the ground from AI infrastructure demand, and the signal is coming from enterprise use. He pointed to agents, internal enterprise models, and real-world deployments as the workloads now driving demand, and explained that the challenge isn't finding customers, it’s how quickly they can build capacity to keep up. Their strategy? A vertically integrated model focused entirely on power-dense computing, which allows them to scale faster, control the environment, and deliver infrastructure purpose-built for AI rather than multi-tenant data centers trying to support dozens of different workloads.

The biggest driver of AI compute now is real-world deployment. At NVIDIA GTC, IREN's Kent Draper, alongside Lenovo's Vlad Rozanovich, shared what they’re actually seeing on the ground from AI infrastructure demand, and the signal is coming from enterprise use. He pointed to agents, internal enterprise models, and real-world deployments as the workloads now driving demand, and explained that the challenge isn't finding customers, it’s how quickly they can build capacity to keep up. Their strategy? A vertically integrated model focused entirely on power-dense computing, which allows them to scale faster, control the environment, and deliver infrastructure purpose-built for AI rather than multi-tenant data centers trying to support dozens of different workloads.

Six Five Media

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Your data is your edge, but only if your AI is built on it. Rent a generic model and so can your competitor. The companies with an edge are deploying custom models that they own and improve over time. Our co-founder Rhythm Garg recently stopped by South Park Commons to share how companies are owning their intelligence with Applied Compute.

Your data is your edge, but only if your AI is built on it. Rent a generic model and so can your competitor. The companies with an edge are deploying custom models that they own and improve over time. Our co-founder Rhythm Garg recently stopped by South Park Commons to share how companies are owning their intelligence with Applied Compute.

Applied Compute

118,922 Aufrufe • vor 2 Monaten

Sequoia’s Julien Bek says many of their founders are now wondering if they’re “just an iteration away” from AI labs destroying their business. He says the most defensible companies - and potentially the next trillion-dollar company - will be “a software business that masquerades as a services firm.” “If you sell tools today, you’re really in the line of sight for the models and you’re effectively competing with the next generation that they’re going to launch.” “Whereas if you sell the work, you’re actually benefiting from what the models are doing and all the billions of dollars that are going towards AI.”

Sequoia’s Julien Bek says many of their founders are now wondering if they’re “just an iteration away” from AI labs destroying their business. He says the most defensible companies - and potentially the next trillion-dollar company - will be “a software business that masquerades as a services firm.” “If you sell tools today, you’re really in the line of sight for the models and you’re effectively competing with the next generation that they’re going to launch.” “Whereas if you sell the work, you’re actually benefiting from what the models are doing and all the billions of dollars that are going towards AI.”

TBPN

684,043 Aufrufe • vor 5 Monaten

$Around 400 AI workers and students just protested outside OpenAI, Anthropic, and Google. Not because they hate AI. Because they're worried about jobs, power, and who will benefit from the trillions of dollars AI is expected to create. Here's the reality. You can't stop the AI race. But you can change who benefits from it. That's why we're building Action Model. A community-owned AI model where the people helping train AI can earn a fractional share in the value they help create. We'd rather see that value distributed across millions of ordinary people than concentrated in the hands of a few Big Tech companies and billionaires.$

Around 400 AI workers and students just protested outside OpenAI, Anthropic, and Google. Not because they hate AI. Because they're worried about jobs, power, and who will benefit from the trillions of dollars AI is expected to create. Here's the reality. You can't stop the AI race. But you can change who benefits from it. That's why we're building Action Model. A community-owned AI model where the people helping train AI can earn a fractional share in the value they help create. We'd rather see that value distributed across millions of ordinary people than concentrated in the hands of a few Big Tech companies and billionaires.

Action Model

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Satya Nadella, CEO of Microsoft, says every company now runs on two kinds of capital, and leaking one of them is a one-way door: "This economy is going to be shaped going forward by both human capital and, let's call it, this token capital. That is true for Microsoft, that is true for a new startup, that's going to be true for any bank that's been in existence for 100 years." "The interplay between human capital and token capital, and compounding the returns of it, is what you need to do." "What is the tacit knowledge of an enterprise or a firm? It's the unique ways that you're able to operate, pass judgment, have taste." "The model, in some sense, is able to extract that tacit knowledge through human trajectories, and then code it in a set of weights in a model." "Every enterprise now needs to be more mindful about that interplay of humans and their digital estate working together, those trajectories training the models that they keep as IP versus leak it." "Because if you leak it, it's a one-way door. You're done in some sense." The moat was never the data sitting in your warehouse. It was the judgment your people apply to it, and AI now turns that judgment into weights you either own or hand away. Treat your tacit knowledge like a patent, not a prompt. The firms that pipe a hundred years of taste into someone else's frontier model are trading a permanent edge for a quarter of convenience.

Satya Nadella, CEO of Microsoft, says every company now runs on two kinds of capital, and leaking one of them is a one-way door: "This economy is going to be shaped going forward by both human capital and, let's call it, this token capital. That is true for Microsoft, that is true for a new startup, that's going to be true for any bank that's been in existence for 100 years." "The interplay between human capital and token capital, and compounding the returns of it, is what you need to do." "What is the tacit knowledge of an enterprise or a firm? It's the unique ways that you're able to operate, pass judgment, have taste." "The model, in some sense, is able to extract that tacit knowledge through human trajectories, and then code it in a set of weights in a model." "Every enterprise now needs to be more mindful about that interplay of humans and their digital estate working together, those trajectories training the models that they keep as IP versus leak it." "Because if you leak it, it's a one-way door. You're done in some sense." The moat was never the data sitting in your warehouse. It was the judgment your people apply to it, and AI now turns that judgment into weights you either own or hand away. Treat your tacit knowledge like a patent, not a prompt. The firms that pipe a hundred years of taste into someone else's frontier model are trading a permanent edge for a quarter of convenience.

Karl Mehta

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Microsoft's Chief of AI just announced that AI will replace almost all white-collar jobs within 18 months. Big Tech used our data to train their AI. Now that same AI is coming for our jobs. And we get nothing in return? If AI replaces us…we should own it. That’s why we built Action Model Not another chatbot. A community-owned AI model that acts. An AI trained by the people. Owned by the people. No billionaires controlling it. No extracting value from users. No “you are the product” model. Over 150,000+ people are already earning ownership in the AI future with Action Model. You should be too.

Microsoft's Chief of AI just announced that AI will replace almost all white-collar jobs within 18 months. Big Tech used our data to train their AI. Now that same AI is coming for our jobs. And we get nothing in return? If AI replaces us…we should own it. That’s why we built Action Model Not another chatbot. A community-owned AI model that acts. An AI trained by the people. Owned by the people. No billionaires controlling it. No extracting value from users. No “you are the product” model. Over 150,000+ people are already earning ownership in the AI future with Action Model. You should be too.

Georgia | Action Model

13,198 Aufrufe • vor 5 Monaten

Airbnb's Brian Chesky says there's still a massive opportunity in consumer AI, if only because almost every AI company is an enterprise/ coding company. "Almost every AI company is an enterprise company. The last stat I said on TBPN, like three months ago — and the stats haven't changed — was 175 companies in a YC batch, and 16 were consumer." "That trend hasn't changed. Almost everyone's going into coding and enterprise." "But the consumer [AI] experience hasn't fundamentally changed that much beyond a chatbot. I think the consumer is a massive opportunity for AI. I think it's going to need to be a richer user interface." "AI today is text, photos, and buttons. And some videos. And I think there's a breakthrough visual paradigm that could be much more immersive. With the new image and video models, you could do something so much more immersive."

Airbnb's Brian Chesky says there's still a massive opportunity in consumer AI, if only because almost every AI company is an enterprise/ coding company. "Almost every AI company is an enterprise company. The last stat I said on TBPN, like three months ago — and the stats haven't changed — was 175 companies in a YC batch, and 16 were consumer." "That trend hasn't changed. Almost everyone's going into coding and enterprise." "But the consumer [AI] experience hasn't fundamentally changed that much beyond a chatbot. I think the consumer is a massive opportunity for AI. I think it's going to need to be a richer user interface." "AI today is text, photos, and buttons. And some videos. And I think there's a breakthrough visual paradigm that could be much more immersive. With the new image and video models, you could do something so much more immersive."

TBPN

15,446 Aufrufe • vor 3 Monaten

$Enterprise AI is in a wildly paradoxical state 🤔, and we’re reaching the inflection point that will resolve it. 💥 Enterprises want to differentiate with AI, yet rent the same intelligence as their competitors. Their workflows and expertise are highly specialized, yet they rely on generic models built to be good at everything. They worry about AI costs, yet pay premium prices for massive models where only a fraction (1%) of the intelligence is relevant to their task. 💸 And they demand control and sovereignty, yet rent the intelligence becoming core to their business. This is not a sustainable equilibrium. The next era of enterprise AI is specialized intelligence companies build, own, and compound. And we are at the inflection point of this transition. That’s the bet we made when we started Oumi two years ago. Today we’re closing the loop: Oumi can now not only automatically build your specialized AI models, but also deploy them into production, learn from their production experience, and continuously improve them. The intelligence that your business runs on, becomes your differentiator. Your compounding advantage. The winners of the next AI era will turn their own data, expertise, and experience into specialized intelligence that nobody else can rent. Don’t rent your AI. Build it. Own it. Compound it.$

Enterprise AI is in a wildly paradoxical state 🤔, and we’re reaching the inflection point that will resolve it. 💥 Enterprises want to differentiate with AI, yet rent the same intelligence as their competitors. Their workflows and expertise are highly specialized, yet they rely on generic models built to be good at everything. They worry about AI costs, yet pay premium prices for massive models where only a fraction (1%) of the intelligence is relevant to their task. 💸 And they demand control and sovereignty, yet rent the intelligence becoming core to their business. This is not a sustainable equilibrium. The next era of enterprise AI is specialized intelligence companies build, own, and compound. And we are at the inflection point of this transition. That’s the bet we made when we started Oumi two years ago. Today we’re closing the loop: Oumi can now not only automatically build your specialized AI models, but also deploy them into production, learn from their production experience, and continuously improve them. The intelligence that your business runs on, becomes your differentiator. Your compounding advantage. The winners of the next AI era will turn their own data, expertise, and experience into specialized intelligence that nobody else can rent. Don’t rent your AI. Build it. Own it. Compound it.

Manos Koukoumidis

951,025 Aufrufe • vor 6 Tagen

Enterprise AI deployments today are frozen in time. Model capabilities stagnate in production. The problem compounds because companies aren’t static either. Every time your company improves, the model falls further behind. The bottleneck is continual learning. How does a model do something once and improve from feedback? The future of enterprise AI is Specific Intelligence: custom models teams own, trained on a company’s choices, interaction by interaction, using internal knowledge general models cannot access. Applied Compute helps companies train, serve, own, and improve custom models. Thanks Apoorv Agrawal for having Yash Patil at MS&E 435 to talk about the future of model training.

Enterprise AI deployments today are frozen in time. Model capabilities stagnate in production. The problem compounds because companies aren’t static either. Every time your company improves, the model falls further behind. The bottleneck is continual learning. How does a model do something once and improve from feedback? The future of enterprise AI is Specific Intelligence: custom models teams own, trained on a company’s choices, interaction by interaction, using internal knowledge general models cannot access. Applied Compute helps companies train, serve, own, and improve custom models. Thanks Apoorv Agrawal for having Yash Patil at MS&E 435 to talk about the future of model training.

Applied Compute

12,751 Aufrufe • vor 2 Monaten

“ If you are AI-native right now, coming out of college, the amount you can teach a company is unbelievable.” New grads: AI fluency is a superpower and a wedge into your next job. Big companies move slowly. If you can teach them how to move faster with AI, you’ll stand out. Aaron Levie and martin_casado talk AI adoption, SaaS vs. AI-native models, org strategy, and more on the a16z podcast.

“ If you are AI-native right now, coming out of college, the amount you can teach a company is unbelievable.” New grads: AI fluency is a superpower and a wedge into your next job. Big companies move slowly. If you can teach them how to move faster with AI, you’ll stand out. Aaron Levie and martin_casado talk AI adoption, SaaS vs. AI-native models, org strategy, and more on the a16z podcast.

a16z

163,263 Aufrufe • vor 1 Jahr