Загрузка видео...

Не удалось загрузить видео

На главную

Satya Nadella: How Microsoft is applying the concept of "Lean for knowledge work" internally with AI. The internal ROI on AI investment and leveraging the cost reduction effect of AI. Borrowing from Toyota's manufacturing efficiency principles and applying them to white-collar operations powered by AI. e.g. Microsoft spends approximately...

rohanpaul_ai's profile picture

Rohan Paul

157,968 subscribers

13,525 просмотров • 7 дней назад •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

Комментарии: 9

Фото профиля Rohan Paul
Rohan Paul7 дней назад

Full video

Фото профиля Jatin Garg
Jatin Garg7 дней назад

What are they using to measure the internal ROI? Is it hours saved, or are they tracking revenue impact per team that adopts the tooling?

Фото профиля Shinka - AI
Shinka - AI7 дней назад

Lean for knowledge work is exactly what AI should be: agents doing front-end deflection and reasoning assist so humans do the judgment work. $4B support ops being eaten by deflection is the new normal.

Фото профиля DanTheTechMan
DanTheTechMan7 дней назад

$4B in support spend means even 40% deflection is $1.6B/year. The measurable part is easy. In my view the open question is whether deflected tickets actually get resolved or just vanish from the queue.

Фото профиля The AI Therapist
The AI Therapist6 дней назад

Satya's lean ai pilot cuts internal headcount by 15%. the real story isn't efficiency. it's that Microsoft just turned its own workforce into a live benchmark for every SaaS company waiting to see if you survive the cut

Фото профиля Gill
Gill7 дней назад

Deflection metrics usually just mean users got angry and gave up trying.

Фото профиля JJ Walker
JJ Walker6 дней назад

For smaller AI teams, I'd look for ROI after ticket routing is sorted. Before that, agents spend time fixing model errors.

Фото профиля Harley Lewis Foote
Harley Lewis Foote6 дней назад

Microsoft (@Microsoft)'s Copilot analysis: 𝟰𝟵% of all conversations support cognitive work (100k+ chats, per Microsoft). Half your usage is mission-critical infrastructure you're treating like a chat app. The productivity metric everyone celebrates is measuring attack surface.

Фото профиля Sagiv Ofek
Sagiv Ofek7 дней назад

Lean for knowledge work is Taylorism with a Copilot license.

Похожие видео

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
31:59

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

860,331 просмотров • 8 месяцев назад

Freya (Freya AI) provides human-like, secure Voice AI agents for customer support & sales in financial services. They cut costs by 50% and improve the customer experience with instant 24/7 support that gets things done for customers. Congrats on the launch, Tunga Bayrak and Tomas Nepala!
1:46

Freya (Freya AI) provides human-like, secure Voice AI agents for customer support & sales in financial services. They cut costs by 50% and improve the customer experience with instant 24/7 support that gets things done for customers. Congrats on the launch, Tunga Bayrak and Tomas Nepala!

Y Combinator

21,034 просмотров • 1 год назад

🌻 Announcing New Agents + Economics Research from Microsoft! AI agents are starting to shop and buy for us. At the same time, agents are representing and providing customer support on behalf of businesses. We believe that these two sides will soon collide, and... 1/n
1:08

🌻 Announcing New Agents + Economics Research from Microsoft! AI agents are starting to shop and buy for us. At the same time, agents are representing and providing customer support on behalf of businesses. We believe that these two sides will soon collide, and... 1/n

Gagan Bansal

13,749 просмотров • 10 месяцев назад

We’re expanding our strategic partnership with Microsoft to: ⚡ Deliver OpenAI’s state-of-the-art models in Snowflake Cortex AI on Microsoft Microsoft Azure. Customers will soon be able to build AI-powered data agents to run analytical workflows on structured and unstructured data using OpenAI’s models. ⚡ Make Snowflake Cortex Agents available in Microsoft 365 Copilot and Microsoft 365 apps, ensuring AI insights become more accessible for users and enabling better decision-making across the enterprise. Learn more about how we’re bringing easy, efficient, and trusted AI to enterprises around the world:
0:41

We’re expanding our strategic partnership with Microsoft to: ⚡ Deliver OpenAI’s state-of-the-art models in Snowflake Cortex AI on Microsoft Microsoft Azure. Customers will soon be able to build AI-powered data agents to run analytical workflows on structured and unstructured data using OpenAI’s models. ⚡ Make Snowflake Cortex Agents available in Microsoft 365 Copilot and Microsoft 365 apps, ensuring AI insights become more accessible for users and enabling better decision-making across the enterprise. Learn more about how we’re bringing easy, efficient, and trusted AI to enterprises around the world:

Snowflake

11,027 просмотров • 1 год назад

EXCLUSIVE: Microsoft just launched Copilot Vision in Edge—the first AI that can navigate the internet with you in real time. I sat down with Mustafa Suleyman (CEO of Microsoft AI) to discuss how it works, infinite memory, AI companions, agents, and more. Timestamps: 0:00 Intro 0:58 Microsoft Copilot Vision rundown 02:35 Initial reactions and use cases 04:57 How Copilot Vision works 06:02 Teaching AI to remember 08:13 How Microsoft AI is differentiating from OpenAI 09:27 The push for the true AI companion 11:28 Living with a co-intelligence in 10+ years 14:04 How Microsoft handles your data 16:11 When and how can you try Copilot Vision? 18:15 Agentic AI that controls your computer 20:25 What's next: support, gaming, and more 22:34 Preparing the next generation with Copilot 25:11 Mustafa’s advice for students and businesses
26:21

EXCLUSIVE: Microsoft just launched Copilot Vision in Edge—the first AI that can navigate the internet with you in real time. I sat down with Mustafa Suleyman (CEO of Microsoft AI) to discuss how it works, infinite memory, AI companions, agents, and more. Timestamps: 0:00 Intro 0:58 Microsoft Copilot Vision rundown 02:35 Initial reactions and use cases 04:57 How Copilot Vision works 06:02 Teaching AI to remember 08:13 How Microsoft AI is differentiating from OpenAI 09:27 The push for the true AI companion 11:28 Living with a co-intelligence in 10+ years 14:04 How Microsoft handles your data 16:11 When and how can you try Copilot Vision? 18:15 Agentic AI that controls your computer 20:25 What's next: support, gaming, and more 22:34 Preparing the next generation with Copilot 25:11 Mustafa’s advice for students and businesses

Rowan Cheung

268,106 просмотров • 1 год назад

Introducing The Kyndryl Agentic AI Framework: built to help enterprises scale agentic AI with confidence on-prem, in the cloud or hybrid. Powered by insights from Kyndryl Bridge, our framework deploys self-learning AI agents that adapt in real-time, working alongside human teams to drive smarter operations and faster decisions. Read more about this news: #TheHeartOfProgress
1:05

Introducing The Kyndryl Agentic AI Framework: built to help enterprises scale agentic AI with confidence on-prem, in the cloud or hybrid. Powered by insights from Kyndryl Bridge, our framework deploys self-learning AI agents that adapt in real-time, working alongside human teams to drive smarter operations and faster decisions. Read more about this news: #TheHeartOfProgress

Kyndryl

14,186 просмотров • 1 год назад

We’re launching Judgment Labs today and announcing $32M in funding. As AI agents take on more of the work that creates economic value, they generate massive amounts of production data: the clearest record of how they behave with users, software, and the real world. Judgment builds infrastructure for improving AI agents from production data.
2:00

We’re launching Judgment Labs today and announcing $32M in funding. As AI agents take on more of the work that creates economic value, they generate massive amounts of production data: the clearest record of how they behave with users, software, and the real world. Judgment builds infrastructure for improving AI agents from production data.

Alex Shan

3,584,735 просмотров • 4 месяцев назад

Microsoft is deceiving you by inflating its AI empire with money it handed its OWN customer first. They sold Wall Street a $37 billion AI business, then went silent the moment its own filing showed where that money came from. The line sits in the annual report for fiscal 2026: Microsoft recorded $24.1 billion of revenue from commercial arrangements with OpenAI, including revenue sharing payments. If you run that figure against Microsoft's own AI disclosures you'll find that OpenAI made up more than half, and likely around 70%, of everything the company counts as AI sales. ONE customer. A Microsoft spokesperson confirmed the figure covers all sales and revenue share from OpenAI. The 70% comes by assuming Microsoft's AI run rate kept growing at the 123% pace the company itself reported in March, which is the company's own optimistic math turned around on it. Now follow where that money starts: Microsoft has put around $12 billion into OpenAI since 2019. OpenAI spends its cash on computing power, and Microsoft is the cloud provider selling it. So the money leaves as an investment and comes back as an Azure bill. Microsoft then books that bill as AI revenue and shows it to investors as proof the AI business is "working." Microsoft invests in OpenAI -> OpenAI buys Microsoft compute -> Microsoft records the payment as AI revenue -> the AI growth story goes to Wall Street And a chunk of it never actually arrived. The same filing shows $6 billion of accounts receivable from OpenAI as of June 30. That is $6 billion of AI revenue Microsoft booked and had not been paid when the year closed. Now here's where it gets really concerning for anyone holding the stock... Microsoft has told the public how big its total AI business is exactly twice. Once for the quarter ending December 2024, when it said the unit was on pace for more than $13 billion a year. And once for the quarter ending March 2026, when Satya Nadella put it on pace for $37 billion. That $37 billion number went everywhere. It was the headline proof that Microsoft had won the AI race. Then fourth quarter earnings arrived, and Microsoft did NOT update it. The company that had been announcing the figure as its own scoreboard stopped announcing the figure. In the same stretch, the filing landed showing where most of it came from. So what is actually left underneath? The full year AI business ran near $34 billion. Take OpenAI out and roughly $10 billion remains. Microsoft has spent about $261 billion on capital expenditure since the start of 2022. That is the scale of the bet against what the rest of the AI business currently brings in. And the one customer holding it up is walking further away every quarter. In October, Microsoft's stake in OpenAI dropped to 27% from 32.5%. In April the partnership was rewritten so OpenAI can sell its products across any cloud it likes, which is how Amazon got a seat at the table. The exclusivity that made this arrangement valuable is gone. The compute bill and the unpaid $6 billion are still on Microsoft's books. Nadella spent two years telling the market Microsoft built the largest AI business in software. The filing shows one client bought most of it, on credit, using money Microsoft partly supplied. So watch the next earnings call: If Microsoft puts a fresh total AI number back on the board, the business found customers beyond OpenAI. If you hear a lot about AI momentum and never hear what it adds up to, you already know why the number went missing. But nonetheless, how is something like this even legal?
0:56

Microsoft is deceiving you by inflating its AI empire with money it handed its OWN customer first. They sold Wall Street a $37 billion AI business, then went silent the moment its own filing showed where that money came from. The line sits in the annual report for fiscal 2026: Microsoft recorded $24.1 billion of revenue from commercial arrangements with OpenAI, including revenue sharing payments. If you run that figure against Microsoft's own AI disclosures you'll find that OpenAI made up more than half, and likely around 70%, of everything the company counts as AI sales. ONE customer. A Microsoft spokesperson confirmed the figure covers all sales and revenue share from OpenAI. The 70% comes by assuming Microsoft's AI run rate kept growing at the 123% pace the company itself reported in March, which is the company's own optimistic math turned around on it. Now follow where that money starts: Microsoft has put around $12 billion into OpenAI since 2019. OpenAI spends its cash on computing power, and Microsoft is the cloud provider selling it. So the money leaves as an investment and comes back as an Azure bill. Microsoft then books that bill as AI revenue and shows it to investors as proof the AI business is "working." Microsoft invests in OpenAI -> OpenAI buys Microsoft compute -> Microsoft records the payment as AI revenue -> the AI growth story goes to Wall Street And a chunk of it never actually arrived. The same filing shows $6 billion of accounts receivable from OpenAI as of June 30. That is $6 billion of AI revenue Microsoft booked and had not been paid when the year closed. Now here's where it gets really concerning for anyone holding the stock... Microsoft has told the public how big its total AI business is exactly twice. Once for the quarter ending December 2024, when it said the unit was on pace for more than $13 billion a year. And once for the quarter ending March 2026, when Satya Nadella put it on pace for $37 billion. That $37 billion number went everywhere. It was the headline proof that Microsoft had won the AI race. Then fourth quarter earnings arrived, and Microsoft did NOT update it. The company that had been announcing the figure as its own scoreboard stopped announcing the figure. In the same stretch, the filing landed showing where most of it came from. So what is actually left underneath? The full year AI business ran near $34 billion. Take OpenAI out and roughly $10 billion remains. Microsoft has spent about $261 billion on capital expenditure since the start of 2022. That is the scale of the bet against what the rest of the AI business currently brings in. And the one customer holding it up is walking further away every quarter. In October, Microsoft's stake in OpenAI dropped to 27% from 32.5%. In April the partnership was rewritten so OpenAI can sell its products across any cloud it likes, which is how Amazon got a seat at the table. The exclusivity that made this arrangement valuable is gone. The compute bill and the unpaid $6 billion are still on Microsoft's books. Nadella spent two years telling the market Microsoft built the largest AI business in software. The filing shows one client bought most of it, on credit, using money Microsoft partly supplied. So watch the next earnings call: If Microsoft puts a fresh total AI number back on the board, the business found customers beyond OpenAI. If you hear a lot about AI momentum and never hear what it adds up to, you already know why the number went missing. But nonetheless, how is something like this even legal?

Ricardo

24,389 просмотров • 1 месяц назад

I found an AI browser that is actually awesome FlowithOS is a web browser COMPLETELY powered by AI You give it tasks, the agents work for you in the background It's like an army of AI agents working for you 24/7 Here's a guide on how it works and how you can get started today
12:09

I found an AI browser that is actually awesome FlowithOS is a web browser COMPLETELY powered by AI You give it tasks, the agents work for you in the background It's like an army of AI agents working for you 24/7 Here's a guide on how it works and how you can get started today

Alex Finn

25,490 просмотров • 9 месяцев назад

Here we go again 🚀! Excited to announce that we're building A1Zap (YC W25) with Pennie Li and that we're in the Y Combinator W25 batch in San Francisco! What is A1Base? A1Base gives AI Agents a real world identity for work. We do that by rebuilding Twilio and Okta from the ground up, putting AI Agents first. This means developers can make AI-first agentic applications 10x easier with our API's. ⁉️ Why are we doing this? Because there's a huge torrent of new valuable companies possible with AI agents, but to get their AI Agents to users, they have to chain custom apps, chat interfaces, awkward Slack integrations, browser bots, and wrestle with Twilio’s legacy API (which is built for marketing). We solve this by providing developers with an easy to use API to interface your AI agent with humans/coworkers/users where they are in this case in Whatsapp, Slack, Teams, SMS and more) - with AI Agent features built in. These digital workers are poised to transform how we work and we're the critical infrastructure to help them interact naturally in human workflows. We're not just building another AI tool. We're creating the infrastructure that will enable AI agents to become a natural part of the workforce - handling everything from customer support to sales development to creative work. We're backed by Y Combinator and working with founding teams who share our vision. We believe that in the near future, AI Agents with human coworkers will enable us to pursue more creative and impactful work. Our mission is to help developers build AI Agents that people can partner with and rely on as trusted allies—always with a human-first mindset. If you're thinking about the Agentic future of your company reach out! If you're looking to build your first AI Agentic company - reach out too - we have some amazing open source templates to get you started on the journey. Excited to share more of what we're up to soon 🔜.
1:52

Here we go again 🚀! Excited to announce that we're building A1Zap (YC W25) with Pennie Li and that we're in the Y Combinator W25 batch in San Francisco! What is A1Base? A1Base gives AI Agents a real world identity for work. We do that by rebuilding Twilio and Okta from the ground up, putting AI Agents first. This means developers can make AI-first agentic applications 10x easier with our API's. ⁉️ Why are we doing this? Because there's a huge torrent of new valuable companies possible with AI agents, but to get their AI Agents to users, they have to chain custom apps, chat interfaces, awkward Slack integrations, browser bots, and wrestle with Twilio’s legacy API (which is built for marketing). We solve this by providing developers with an easy to use API to interface your AI agent with humans/coworkers/users where they are in this case in Whatsapp, Slack, Teams, SMS and more) - with AI Agent features built in. These digital workers are poised to transform how we work and we're the critical infrastructure to help them interact naturally in human workflows. We're not just building another AI tool. We're creating the infrastructure that will enable AI agents to become a natural part of the workforce - handling everything from customer support to sales development to creative work. We're backed by Y Combinator and working with founding teams who share our vision. We believe that in the near future, AI Agents with human coworkers will enable us to pursue more creative and impactful work. Our mission is to help developers build AI Agents that people can partner with and rely on as trusted allies—always with a human-first mindset. If you're thinking about the Agentic future of your company reach out! If you're looking to build your first AI Agentic company - reach out too - we have some amazing open source templates to get you started on the journey. Excited to share more of what we're up to soon 🔜.

Pasha Rayan

53,998 просмотров • 1 год назад

Mustafa Suleyman on why the AGI race is FAKE, the coming $1 million agent revolution, and Microsoft's ultimate plan for self-sufficiency. - The new Turing Test: agents turning $100K into $1M in the real economy - Containment > alignment in the short term - Why AI personhood is an extinction-level mistake - Short-term social unrest is inevitable - How AGI is bigger than math, science, or any single discovery (00:00) - The Evolution of AI and Microsoft's Role (09:12) - Economic Benchmarks for AI Agents (18:37) - The Future of AI in Science and Engineering (27:54) - AI Alignment and Containment Strategies (36:42) - Anthropomorphism and AI Personhood (46:10) - The Role of AI in Government and Society Mustafa Suleyman is the CEO of Microsoft AI and a co-founder of DeepMind and Inflection AI. He joined me, @DavidBlundin, and Dr. Alex Wissner-Gross for a conversation on why the “AGI race” is a misleading frame, how AI agents will reshape the economy before they solve scientific problems, the potential for future social unrest, and why AI legal personhood is a red line for human survival.
1:24:58

Mustafa Suleyman on why the AGI race is FAKE, the coming $1 million agent revolution, and Microsoft's ultimate plan for self-sufficiency. - The new Turing Test: agents turning $100K into $1M in the real economy - Containment > alignment in the short term - Why AI personhood is an extinction-level mistake - Short-term social unrest is inevitable - How AGI is bigger than math, science, or any single discovery (00:00) - The Evolution of AI and Microsoft's Role (09:12) - Economic Benchmarks for AI Agents (18:37) - The Future of AI in Science and Engineering (27:54) - AI Alignment and Containment Strategies (36:42) - Anthropomorphism and AI Personhood (46:10) - The Role of AI in Government and Society Mustafa Suleyman is the CEO of Microsoft AI and a co-founder of DeepMind and Inflection AI. He joined me, @DavidBlundin, and Dr. Alex Wissner-Gross for a conversation on why the “AGI race” is a misleading frame, how AI agents will reshape the economy before they solve scientific problems, the potential for future social unrest, and why AI legal personhood is a red line for human survival.

Peter H. Diamandis, MD

214,454 просмотров • 9 месяцев назад

OKAY, AI AGENTS ARE COOL BUT WTF IS LAVA PART 2 -------------- Lava is a protocol which coordinates traffic from AI agents, apps and wallets on every blockchain. It does this by aggregating data providers who handle RPC requests for AI agents and anyone using blockchains apps. AI agents are projected to manage 80% of all onchain transactions by end of 2025. That's a LOT of RPC requests... -------------- How to stake and restake LAVA LAVA can be staked and restaked to contribute to the network: - secure the Lava blockchain - direct RPC traffic to top Providers on Lava, meaning faster, more reliable service for users/AI agents This is how you stake and restake LAVA on Keplr, Leap and Mellifera:
4:06

OKAY, AI AGENTS ARE COOL BUT WTF IS LAVA PART 2 -------------- Lava is a protocol which coordinates traffic from AI agents, apps and wallets on every blockchain. It does this by aggregating data providers who handle RPC requests for AI agents and anyone using blockchains apps. AI agents are projected to manage 80% of all onchain transactions by end of 2025. That's a LOT of RPC requests... -------------- How to stake and restake LAVA LAVA can be staked and restaked to contribute to the network: - secure the Lava blockchain - direct RPC traffic to top Providers on Lava, meaning faster, more reliable service for users/AI agents This is how you stake and restake LAVA on Keplr, Leap and Mellifera:

Lava Network 🌋

12,874 просмотров • 1 год назад

How many AI agents work at your company? We now have over 3,258 agents working alongside 1,300 humans. The crazy part is these agents were created by EVERY EMPLOYEE at our company... sales reps, marketers, customer support, product, eng. Literally EVERYONE. BUT I'm most surprised by the adoption and value that MANAGERS are getting from agents. I used to think that every IC would become a manager of agents. Now I think that managers will very likely manage WAY more agents than their ICs combined. And managers' agents will manage their ICs' agents - overseeing them for human-in-the-loop interactions. When creating agents, we use 100% context from all of your activity, files edited, tasks and projects worked on, hierarchy, skills, and role information. We build a user-based context model to make agents as relatable as possible to the specific human that we're building for. This means they truly understand the nuances of the work and what "great" looks like - because great is very much in the eye of the beholder. Great is by definition, subjective. This is also why the human ENGAGEMENT loops are SO vital to agent value. The iteration AFTER the agent is onboarded is where the MAGIC happens. This is just like a manager managing an IC in real life... you're giving feedback. In this case, though, agents learn INSTANTLY, and they retain the knowledge perfectly and indefinitely. Even though I've been pushing AI for years now to everyone in our company, this was the first time we had truly end-to-end AI adoption and retention. This kind of AI adoption is wild. But the value we're realizing is truly INSANE. Super Agents outnumber our humans nearly 3 to 1. What if you could 3X your workforce overnight? Watch this video to see how 👇
0:59

How many AI agents work at your company? We now have over 3,258 agents working alongside 1,300 humans. The crazy part is these agents were created by EVERY EMPLOYEE at our company... sales reps, marketers, customer support, product, eng. Literally EVERYONE. BUT I'm most surprised by the adoption and value that MANAGERS are getting from agents. I used to think that every IC would become a manager of agents. Now I think that managers will very likely manage WAY more agents than their ICs combined. And managers' agents will manage their ICs' agents - overseeing them for human-in-the-loop interactions. When creating agents, we use 100% context from all of your activity, files edited, tasks and projects worked on, hierarchy, skills, and role information. We build a user-based context model to make agents as relatable as possible to the specific human that we're building for. This means they truly understand the nuances of the work and what "great" looks like - because great is very much in the eye of the beholder. Great is by definition, subjective. This is also why the human ENGAGEMENT loops are SO vital to agent value. The iteration AFTER the agent is onboarded is where the MAGIC happens. This is just like a manager managing an IC in real life... you're giving feedback. In this case, though, agents learn INSTANTLY, and they retain the knowledge perfectly and indefinitely. Even though I've been pushing AI for years now to everyone in our company, this was the first time we had truly end-to-end AI adoption and retention. This kind of AI adoption is wild. But the value we're realizing is truly INSANE. Super Agents outnumber our humans nearly 3 to 1. What if you could 3X your workforce overnight? Watch this video to see how 👇

Zeb Evans

425,244 просмотров • 8 месяцев назад

One of the Grok Bot builders: "For the first time I allocated 90% of my work to agents and they did it end to end." In a 30-minute podcast he showed exactly how he uses Grok Bot and how to build an AI agent team from scratch. This beats any paid course on building agents I've seen. Watch it, then read the step-by-step guide on building your AI team for free, with ready-to-copy prompts.
31:10

One of the Grok Bot builders: "For the first time I allocated 90% of my work to agents and they did it end to end." In a 30-minute podcast he showed exactly how he uses Grok Bot and how to build an AI agent team from scratch. This beats any paid course on building agents I've seen. Watch it, then read the step-by-step guide on building your AI team for free, with ready-to-copy prompts.

Anatoli Kopadze

17,123 просмотров • 1 месяц назад

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.
3:11

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

102,664 просмотров • 1 месяц назад

Microsoft just banned its own engineers from using AI. The tool was literally costing MORE than the humans it was supposed to replace. They lied to you about AI adoption and now the whole narrative is blowing up: Microsoft gave thousands of engineers access to Claude Code six months ago and encouraged them to use it. Engineers loved it and adoption exploded. But then the invoices arrived. Token-based pricing means every query, every code review, every debugging session costs money. At scale across 100,000 engineers, the numbers became so large that Microsoft issued an internal order to cancel nearly all Claude Code licenses by end of June and force everyone onto their own cheaper tool instead. The company that invested $5 billion in Anthropic just told its own people to stop using Anthropic's product because it costs too much. Uber's story is even worse... Their CTO Praveen Neppalli Naga told The Information that the budget he planned for the full year was "blown away already" by April. Uber had rolled out Claude Code in December 2025. By March, 84% of their 5,000 engineers were using it with 70% of all committed code coming from AI systems. Heavy users were burning $500 to $2,000 per month each. Naga himself spent $1,200 in a single two-hour demo session. The company had even built internal leaderboards ranking engineers by how much AI they used. They literally gamified the spending and then ran out of money. Now look at what Nvidia's own VP of applied deep learning Bryan Catanzaro said to Axios last month. Direct quote: "For my team, the cost of compute is far beyond the costs of the employees." This is a VP at the company that SELLS the chips saying that using AI is more expensive than paying humans. Think about what this means for the entire AI narrative. Every CEO on every earnings call for the past two years has said the same thing: AI will make us more efficient, reduce headcount, and cut costs. The stock market rewarded every company that said it. Fired workers, stock goes up. Announced AI adoption, stock goes up. But the actual companies deploying AI at scale are discovering the math doesn't work. The MORE employees use AI, the HIGHER the bill. Goldman Sachs forecasts a 24x increase in token consumption by 2030 as companies adopt AI agents. Gartner just published a report showing that even though individual token prices will drop 90% by 2030, total enterprise AI costs will go UP because agents consume exponentially more tokens per task than basic tools. Meta built an internal dashboard called "Claudeonomics" to track which employees use the most AI. Amazon started pushing engineers to "tokenmaxx," their internal term for consuming as many AI tokens as possible. Both companies are spending hundreds of billions on AI infrastructure this year alone. And Microsoft, the company that bet its entire future on AI, just told 100,000 engineers to stop using the tool they liked best because the per-token bills got out of control. The companies building AI are telling investors it saves money. The companies using AI are finding out it costs more than the humans it was supposed to replace. And even the company that makes the chips just admitted it through its own VP. This is the gap nobody on Wall Street is pricing in. $725 billion in AI infrastructure spending this year across Big Tech. And the first companies to actually deploy these tools at scale are already pulling back because the economics don't work. What do you think?
1:33

Microsoft just banned its own engineers from using AI. The tool was literally costing MORE than the humans it was supposed to replace. They lied to you about AI adoption and now the whole narrative is blowing up: Microsoft gave thousands of engineers access to Claude Code six months ago and encouraged them to use it. Engineers loved it and adoption exploded. But then the invoices arrived. Token-based pricing means every query, every code review, every debugging session costs money. At scale across 100,000 engineers, the numbers became so large that Microsoft issued an internal order to cancel nearly all Claude Code licenses by end of June and force everyone onto their own cheaper tool instead. The company that invested $5 billion in Anthropic just told its own people to stop using Anthropic's product because it costs too much. Uber's story is even worse... Their CTO Praveen Neppalli Naga told The Information that the budget he planned for the full year was "blown away already" by April. Uber had rolled out Claude Code in December 2025. By March, 84% of their 5,000 engineers were using it with 70% of all committed code coming from AI systems. Heavy users were burning $500 to $2,000 per month each. Naga himself spent $1,200 in a single two-hour demo session. The company had even built internal leaderboards ranking engineers by how much AI they used. They literally gamified the spending and then ran out of money. Now look at what Nvidia's own VP of applied deep learning Bryan Catanzaro said to Axios last month. Direct quote: "For my team, the cost of compute is far beyond the costs of the employees." This is a VP at the company that SELLS the chips saying that using AI is more expensive than paying humans. Think about what this means for the entire AI narrative. Every CEO on every earnings call for the past two years has said the same thing: AI will make us more efficient, reduce headcount, and cut costs. The stock market rewarded every company that said it. Fired workers, stock goes up. Announced AI adoption, stock goes up. But the actual companies deploying AI at scale are discovering the math doesn't work. The MORE employees use AI, the HIGHER the bill. Goldman Sachs forecasts a 24x increase in token consumption by 2030 as companies adopt AI agents. Gartner just published a report showing that even though individual token prices will drop 90% by 2030, total enterprise AI costs will go UP because agents consume exponentially more tokens per task than basic tools. Meta built an internal dashboard called "Claudeonomics" to track which employees use the most AI. Amazon started pushing engineers to "tokenmaxx," their internal term for consuming as many AI tokens as possible. Both companies are spending hundreds of billions on AI infrastructure this year alone. And Microsoft, the company that bet its entire future on AI, just told 100,000 engineers to stop using the tool they liked best because the per-token bills got out of control. The companies building AI are telling investors it saves money. The companies using AI are finding out it costs more than the humans it was supposed to replace. And even the company that makes the chips just admitted it through its own VP. This is the gap nobody on Wall Street is pricing in. $725 billion in AI infrastructure spending this year across Big Tech. And the first companies to actually deploy these tools at scale are already pulling back because the economics don't work. What do you think?

Ricardo

2,976,975 просмотров • 4 месяцев назад

🛑Still doing your due dilligence by doomscrolling? NGMI Introducing The DeFi Channel on AITV: delivering 24/7 intelligence powered by AI Agents - so you don’t have to dig for it🤖 🧠 Agents like $GECKO & $VILADY scan news outlets and social media in real time 💬 They turn your prompts into insights 📡 Actionable, always-on, and influenced by you 🎉Welcome to the next era of AI first content delivery.
0:44

🛑Still doing your due dilligence by doomscrolling? NGMI Introducing The DeFi Channel on AITV: delivering 24/7 intelligence powered by AI Agents - so you don’t have to dig for it🤖 🧠 Agents like $GECKO & $VILADY scan news outlets and social media in real time 💬 They turn your prompts into insights 📡 Actionable, always-on, and influenced by you 🎉Welcome to the next era of AI first content delivery.

【 AITV 】

12,837 просмотров • 1 год назад