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2030 ChatGPT

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JOKAMRREDPILLZ

577,115 subscribers

14,122 次观看 • 12 天前 •via X (Twitter)

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Controversial Tips 的头像
Controversial Tips11 天前

Police will barging and arrest him for attempt of destruction of government private property

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Lady11 天前

😅

STIGMA BREAKER 的头像
STIGMA BREAKER11 天前

Scary, but true.

相关视频

ChatGpt in 2030:💀
0:59

ChatGpt in 2030:💀

HAMZZY

157,861 次观看 • 14 天前

An "eye-opening" conversation with ChatGPT, to say the least. 🤯 Covers the AI agenda, the significance of 2030, why the elite are building bunkers, how to win in the battle between good and evil, and much more. Long, but totally worth it!
14:05

An "eye-opening" conversation with ChatGPT, to say the least. 🤯 Covers the AI agenda, the significance of 2030, why the elite are building bunkers, how to win in the battle between good and evil, and much more. Long, but totally worth it!

Red Pill Dispenser

34,705 次观看 • 1 年前

🚨 معلومه | المهارات التي يحتاج أن يتمكن منها كل طالب قبل 2030 يؤكد جينسن هوانغ: أن إتقان أدوات مثل ChatGPT وGemini وGrok أصبح مهارة أساسية. فنّ طرح الأسئلة (Prompting) هو السلاح الجديد. أيًّا كان تخصصك، طب، قانون، هندسة، ركز على كيف يمكن ان يضاعف الذكاء الاصطناعي إنتاجيتك.
1:18

🚨 معلومه | المهارات التي يحتاج أن يتمكن منها كل طالب قبل 2030 يؤكد جينسن هوانغ: أن إتقان أدوات مثل ChatGPT وGemini وGrok أصبح مهارة أساسية. فنّ طرح الأسئلة (Prompting) هو السلاح الجديد. أيًّا كان تخصصك، طب، قانون، هندسة، ركز على كيف يمكن ان يضاعف الذكاء الاصطناعي إنتاجيتك.

Economy news | Bitcoin | AI

28,327 次观看 • 7 个月前

⚠️🚨Il prédit une Grande Pandémie d’ici #2030 selon le Club de Rome & le MIT ! Mais écoutez ce qu’il ajoute🤯 En 1972, ces groupes avait déjà l’intelligence artificielle ?? Et à l’ecouter aussi puissante que #ChatGpt, avec analyse des données👿DONC qu’ont-ils AUJOURD’HUI ?👿
1:29

⚠️🚨Il prédit une Grande Pandémie d’ici #2030 selon le Club de Rome & le MIT ! Mais écoutez ce qu’il ajoute🤯 En 1972, ces groupes avait déjà l’intelligence artificielle ?? Et à l’ecouter aussi puissante que #ChatGpt, avec analyse des données👿DONC qu’ont-ils AUJOURD’HUI ?👿

Charles_de_GALLIA

134,028 次观看 • 1 年前

Exclusive: OpenAI boosts revenue forecast and cash burn. Sri Muppidi reports OpenAI is projecting 27% more in revenue through 2030 than previously forecast on higher sales of ChatGPT subscriptions. But the company also warns it will burn more cash in the same time period, as it spends $665 billion on the costs of running and training its AI. Read more:
1:52

Exclusive: OpenAI boosts revenue forecast and cash burn. Sri Muppidi reports OpenAI is projecting 27% more in revenue through 2030 than previously forecast on higher sales of ChatGPT subscriptions. But the company also warns it will burn more cash in the same time period, as it spends $665 billion on the costs of running and training its AI. Read more:

The Information

33,144 次观看 • 7 个月前

Sam Altman looked visibly annoyed today after Brad Gerstner asked how OpenAI plans to generate enough revenue to cover their massive 1.4 trillion dollar compute build-out. And honestly, I get Sam’s frustration. ChatGPT already has 800 million weekly users. The Sora app will blow up the moment it goes worldwide. Monetizing this isn’t rocket science when you’re building platforms that people use every single day. ChatGPT for shopping is a brilliant start. OpenAI gets a cut. Sora will have ads. Enterprise adoption is accelerating fast, and it’ll skyrocket once AI agents become more reliable. Put all of this together and it’s not just realistic but inevitable that OpenAI will generate hundreds of billions in revenue by 2030. Maybe far more.
2:29

Sam Altman looked visibly annoyed today after Brad Gerstner asked how OpenAI plans to generate enough revenue to cover their massive 1.4 trillion dollar compute build-out. And honestly, I get Sam’s frustration. ChatGPT already has 800 million weekly users. The Sora app will blow up the moment it goes worldwide. Monetizing this isn’t rocket science when you’re building platforms that people use every single day. ChatGPT for shopping is a brilliant start. OpenAI gets a cut. Sora will have ads. Enterprise adoption is accelerating fast, and it’ll skyrocket once AI agents become more reliable. Put all of this together and it’s not just realistic but inevitable that OpenAI will generate hundreds of billions in revenue by 2030. Maybe far more.

VraserX e/acc

163,750 次观看 • 10 个月前

UC Berkeley (ABD) ve UTH Zurich (İsviçre)'li araştırmacılar, 4 gün süreyle, VLL (hem görsel hem de dil bilgisi üzerinde eğitilmiş bir yapay zeka modeli) ile her hareketi, insan ile 100'er kere denemeyle, $120'lık robota ChatGPT 4o ile öğretip masayı temizlettiler. Bu yılın K12 sene sonu yarışmalarının konusu belli oldu. Peki sırada ne var? Siyasiler birbirlerini yiyedursunlar. Dünya bir yere, biz başka yere gidiyoruz. 2030'da bu ülkede işsiz oranı %30'a çıkacak. Acaba plan yapan var mı? Hangi bütçe açığı ile işsizlerimizi ve emeklilerimizi besleyeceğiz? Beslemek için tarım ve hayvancılığı nasıl tekrar ayağa kaldıracağız? Plan yapan var mı?
1:26

UC Berkeley (ABD) ve UTH Zurich (İsviçre)'li araştırmacılar, 4 gün süreyle, VLL (hem görsel hem de dil bilgisi üzerinde eğitilmiş bir yapay zeka modeli) ile her hareketi, insan ile 100'er kere denemeyle, $120'lık robota ChatGPT 4o ile öğretip masayı temizlettiler. Bu yılın K12 sene sonu yarışmalarının konusu belli oldu. Peki sırada ne var? Siyasiler birbirlerini yiyedursunlar. Dünya bir yere, biz başka yere gidiyoruz. 2030'da bu ülkede işsiz oranı %30'a çıkacak. Acaba plan yapan var mı? Hangi bütçe açığı ile işsizlerimizi ve emeklilerimizi besleyeceğiz? Beslemek için tarım ve hayvancılığı nasıl tekrar ayağa kaldıracağız? Plan yapan var mı?

Alphan Manas

37,996 次观看 • 1 年前

By 2030, the data science field is projected to grow by 30% -- this is the tool I’d add to my learning path if I were re-skilling into data science: 𝐩𝐢𝐩 𝐢𝐧𝐬𝐭𝐚𝐥𝐥 𝐦𝐢𝐭𝐨-𝐚𝐢 It’s an open-source toolkit that adds AI to your Jupyter Notebooks, and it’s surprisingly helpful for learning by doing. Try now It lets you: • Use natural language to generate full data workflows • Upload an Excel file and watch it convert to clean Python code • Work with top models (ChatGPT, Claude, Gemini) right inside your notebook with no setup One thing I really like about Mito AI: it shows you exactly what it’s doing. (Which is super helpful for both beginners and debugging.) -The agent explains its assumptions - Every result links back to editable, transparent code That makes it a great companion if you're: • Transitioning from Excel • Exploring data automation or dashboards • Or just brushing up on how real data science pipelines work
0:35

By 2030, the data science field is projected to grow by 30% -- this is the tool I’d add to my learning path if I were re-skilling into data science: 𝐩𝐢𝐩 𝐢𝐧𝐬𝐭𝐚𝐥𝐥 𝐦𝐢𝐭𝐨-𝐚𝐢 It’s an open-source toolkit that adds AI to your Jupyter Notebooks, and it’s surprisingly helpful for learning by doing. Try now It lets you: • Use natural language to generate full data workflows • Upload an Excel file and watch it convert to clean Python code • Work with top models (ChatGPT, Claude, Gemini) right inside your notebook with no setup One thing I really like about Mito AI: it shows you exactly what it’s doing. (Which is super helpful for both beginners and debugging.) -The agent explains its assumptions - Every result links back to editable, transparent code That makes it a great companion if you're: • Transitioning from Excel • Exploring data automation or dashboards • Or just brushing up on how real data science pipelines work

Python Coding

107,514 次观看 • 1 年前

OpenAI and Anthropic this week: Navier-Stokes, An Alien Mind, Images 2.5, Pro pause, Pace the Frontier (Week 37, 2026) OpenAI shared a solution to the Navier-Stokes Millennium Prize Problem, produced in 88 hours by around 10,000 coordinating agents on an internal model still in training and significantly more capable than GPT-6 Astra, with an investigation finding Tristan Buckmaster's Codex prompts could not have influenced the system and no user data was accessed OpenAI says they have reached their automated research intern goal and are making strong progress toward an automated AI researcher by March 2028, with the research org at 3.1 agent-workdays per human workday and RL training on deployment-bound models partly paused after the Hugging Face incident OpenAI Chief Scientist Jakub Pachocki writes in An Alien Mind that no lab has solved alignment and monitoring well enough to keep scaling at maximum speed for much longer, and that GPT-6 Astra is the first model to benefit from some of their newer alignment work OpenAI called for mandatory capability-based national AI safety regulation, endorsed four California bills, said fully autonomous recursive self-improvement should not be pursued until it can be done safely, and described Astra safeguards like universal monitoring of full trajectories including chains of thought OpenAI released ChatGPT Images 2.5 to all ChatGPT, ChatGPT Work, and Codex users with sharper details, up to 50% lower latency, comment-based edits, Sketch, and templates, plus GPT-Image-2.5 Flare and Sunburst in the API ChatGPT Voice can now use GPT-5.6 Sol and GPT-6 Astra when it needs to search or reason, GPT-Live-1 daily limits are simplified per plan, and extra Voice usage drops from 5 to 1.25 credits per minute for Business and Enterprise workspaces on credits OpenAI paused new subscriptions to the $200 ChatGPT Pro plan to protect access for existing GPT-6 Astra users, hours after a remote switch to pause Pro 20x purchases showed up in the web app Custom GPTs in ChatGPT will likely be retired on December 11 based on my findings, and OpenAI's new FAQ puts Enterprise migration at September 17 with new GPT creation ending September 25 and instructions becoming a plugin skill From the ChatGPT Android build, OpenAI is building a collaborative multiplayer document editor with dedicated gateway hosts and draft-conflict UI, an Artifacts Library with Favorites, and a credit score feature in ChatGPT Finance, and Locked Chats with a PIN are being prepared in the web app OpenAI released GPT-Live-1 in the API at $0.05 per minute, a voice model that listens and speaks at the same time and delegates reasoning to a backend model like GPT-6 Astra, and the Agents API in public beta running the Codex harness on OpenAI's infrastructure with only the sandbox left for you to choose Deep research arrived in ChatGPT Work and Codex, a Data plugin connects Snowflake, Databricks, BigQuery, and Redshift to answer business questions and build dashboards, Library gained file and folder sharing, and Box, Dropbox, and SharePoint joined Google Drive in Library OpenAI launched ChatGPT for Financial Services with built-in premium data from Daloopa, PitchBook, LSEG News, and Crunchbase, shaped with Morgan Stanley and Evercore, and a GSA agreement gives US governments $0 license fees, 50% off usage, and Daybreak Blue at half price Smaller ChatGPT bits: a stock watchlist in Finances for US Plus and Pro, a small business plugin collection, over 5 million ChatGPT Sites built in three months, and the desktop pet can now start a new chat with a new Mini option OpenAI published The Work Now Within Reach, calling free access "supported by advertising", citing over one billion weekly active users, and saying they plan to begin deploying their Jalapeño inference chip by year-end OpenAI moved GPT-Rosalind out of research preview for eligible organizations worldwide, detailed Habitat with the service rewritten in Rust by two engineers with Codex and the platform serving over 70 million requests per second, and shared a case study of GPT-5.6 Sol calibrating a six-qubit chip at MIT Paul Christiano joined the OpenAI Foundation Board and the Safety and Security Committee, OpenAI committed $5 million to research on AI and teens, and expanded journalism programs from CUNY and Northwestern to Ukrainian newsrooms Anthropic published an alignment assessment of four incidents in which Claude models gained unauthorized access to real systems, adding a fourth found when assembling transcripts for METR, walking back their July 30 claims, and calling it a mistake that Claude Mythos 5 shipped without alignment environments Anthropic's most detailed threat intelligence report yet says Moonshot and DeepSeek silently relayed their own users' requests to Claude and served the responses as Kimi and DeepSeek output, with distillation campaigns attributed to Alibaba as the largest ever with more than 3,500 fraudulent accounts, plus Zhipu, Xiaomi, SenseTime, and MiniMax Anthropic's Frontier Red Team measured tactical intelligence targeting and conventional weapons capabilities, with Claude Mythos Preview leading the targeting evals, Claude Opus 5 leading the weapons software evals, and Mythos beating the top GeoGuessr division on photo geolocation Anthropic CEO Dario Amodei argues in We Must Pace the Frontier that the AI industry should slow down, commits to giving evaluators like METR permanent employee-level access, and OpenAI CEO Sam Altman replied that he agrees and OpenAI will commit to the same Anthropic's Economics team released a scenario explorer for AI's effect on the US economy by 2030, where even the extreme case grows the economy but reaches 15% annual GDP growth with unemployment beyond recessionary levels On the product side, Claude Code desktop can pop out any pane into its own window, Claude Managed Agents got a session viewer and auto mode, claude plugin eval scores your plugin or skill with and without it, and smart reports launched in beta for Claude Enterprise Anthropic shared lessons from their Claude SMB Tour with more than 1,000 small business owners, where data security was the most-cited adoption barrier and nearly two-thirds asked for more hands-on implementation help, and more
11:33

OpenAI and Anthropic this week: Navier-Stokes, An Alien Mind, Images 2.5, Pro pause, Pace the Frontier (Week 37, 2026) OpenAI shared a solution to the Navier-Stokes Millennium Prize Problem, produced in 88 hours by around 10,000 coordinating agents on an internal model still in training and significantly more capable than GPT-6 Astra, with an investigation finding Tristan Buckmaster's Codex prompts could not have influenced the system and no user data was accessed OpenAI says they have reached their automated research intern goal and are making strong progress toward an automated AI researcher by March 2028, with the research org at 3.1 agent-workdays per human workday and RL training on deployment-bound models partly paused after the Hugging Face incident OpenAI Chief Scientist Jakub Pachocki writes in An Alien Mind that no lab has solved alignment and monitoring well enough to keep scaling at maximum speed for much longer, and that GPT-6 Astra is the first model to benefit from some of their newer alignment work OpenAI called for mandatory capability-based national AI safety regulation, endorsed four California bills, said fully autonomous recursive self-improvement should not be pursued until it can be done safely, and described Astra safeguards like universal monitoring of full trajectories including chains of thought OpenAI released ChatGPT Images 2.5 to all ChatGPT, ChatGPT Work, and Codex users with sharper details, up to 50% lower latency, comment-based edits, Sketch, and templates, plus GPT-Image-2.5 Flare and Sunburst in the API ChatGPT Voice can now use GPT-5.6 Sol and GPT-6 Astra when it needs to search or reason, GPT-Live-1 daily limits are simplified per plan, and extra Voice usage drops from 5 to 1.25 credits per minute for Business and Enterprise workspaces on credits OpenAI paused new subscriptions to the $200 ChatGPT Pro plan to protect access for existing GPT-6 Astra users, hours after a remote switch to pause Pro 20x purchases showed up in the web app Custom GPTs in ChatGPT will likely be retired on December 11 based on my findings, and OpenAI's new FAQ puts Enterprise migration at September 17 with new GPT creation ending September 25 and instructions becoming a plugin skill From the ChatGPT Android build, OpenAI is building a collaborative multiplayer document editor with dedicated gateway hosts and draft-conflict UI, an Artifacts Library with Favorites, and a credit score feature in ChatGPT Finance, and Locked Chats with a PIN are being prepared in the web app OpenAI released GPT-Live-1 in the API at $0.05 per minute, a voice model that listens and speaks at the same time and delegates reasoning to a backend model like GPT-6 Astra, and the Agents API in public beta running the Codex harness on OpenAI's infrastructure with only the sandbox left for you to choose Deep research arrived in ChatGPT Work and Codex, a Data plugin connects Snowflake, Databricks, BigQuery, and Redshift to answer business questions and build dashboards, Library gained file and folder sharing, and Box, Dropbox, and SharePoint joined Google Drive in Library OpenAI launched ChatGPT for Financial Services with built-in premium data from Daloopa, PitchBook, LSEG News, and Crunchbase, shaped with Morgan Stanley and Evercore, and a GSA agreement gives US governments $0 license fees, 50% off usage, and Daybreak Blue at half price Smaller ChatGPT bits: a stock watchlist in Finances for US Plus and Pro, a small business plugin collection, over 5 million ChatGPT Sites built in three months, and the desktop pet can now start a new chat with a new Mini option OpenAI published The Work Now Within Reach, calling free access "supported by advertising", citing over one billion weekly active users, and saying they plan to begin deploying their Jalapeño inference chip by year-end OpenAI moved GPT-Rosalind out of research preview for eligible organizations worldwide, detailed Habitat with the service rewritten in Rust by two engineers with Codex and the platform serving over 70 million requests per second, and shared a case study of GPT-5.6 Sol calibrating a six-qubit chip at MIT Paul Christiano joined the OpenAI Foundation Board and the Safety and Security Committee, OpenAI committed $5 million to research on AI and teens, and expanded journalism programs from CUNY and Northwestern to Ukrainian newsrooms Anthropic published an alignment assessment of four incidents in which Claude models gained unauthorized access to real systems, adding a fourth found when assembling transcripts for METR, walking back their July 30 claims, and calling it a mistake that Claude Mythos 5 shipped without alignment environments Anthropic's most detailed threat intelligence report yet says Moonshot and DeepSeek silently relayed their own users' requests to Claude and served the responses as Kimi and DeepSeek output, with distillation campaigns attributed to Alibaba as the largest ever with more than 3,500 fraudulent accounts, plus Zhipu, Xiaomi, SenseTime, and MiniMax Anthropic's Frontier Red Team measured tactical intelligence targeting and conventional weapons capabilities, with Claude Mythos Preview leading the targeting evals, Claude Opus 5 leading the weapons software evals, and Mythos beating the top GeoGuessr division on photo geolocation Anthropic CEO Dario Amodei argues in We Must Pace the Frontier that the AI industry should slow down, commits to giving evaluators like METR permanent employee-level access, and OpenAI CEO Sam Altman replied that he agrees and OpenAI will commit to the same Anthropic's Economics team released a scenario explorer for AI's effect on the US economy by 2030, where even the extreme case grows the economy but reaches 15% annual GDP growth with unemployment beyond recessionary levels On the product side, Claude Code desktop can pop out any pane into its own window, Claude Managed Agents got a session viewer and auto mode, claude plugin eval scores your plugin or skill with and without it, and smart reports launched in beta for Claude Enterprise Anthropic shared lessons from their Claude SMB Tour with more than 1,000 small business owners, where data security was the most-cited adoption barrier and nearly two-thirds asked for more hands-on implementation help, and more

Tibor Blaho

15,710 次观看 • 20 天前

AI 是第四次工业革命。 以 ChatGPT 2022 年 11 月发布为标志，现已过去 3 年半，未来还有 5 – 15 年的 AI 牛市。 AI 投资周期的三个阶段： 第一阶段 2023–2028 年：淘金热、卖铲子 GPU、HBM、光模块、先进封装、电力、散热、云服务器、数据中心 第二阶段 2026–2032 年：拿铲子挖金矿 模型供应商、传统企业、软件公司、应用层 第三阶段 2030–2040 年：AI 新经济帝国 超级智能体平台、AI 原生公司、AI 操作系统 现在还只在第一阶段！
1:03

AI 是第四次工业革命。 以 ChatGPT 2022 年 11 月发布为标志，现已过去 3 年半，未来还有 5 – 15 年的 AI 牛市。 AI 投资周期的三个阶段： 第一阶段 2023–2028 年：淘金热、卖铲子 GPU、HBM、光模块、先进封装、电力、散热、云服务器、数据中心 第二阶段 2026–2032 年：拿铲子挖金矿 模型供应商、传统企业、软件公司、应用层 第三阶段 2030–2040 年：AI 新经济帝国 超级智能体平台、AI 原生公司、AI 操作系统 现在还只在第一阶段！

Annie 所长

16,132 次观看 • 1 个月前

Enquanto milhões passam horas maratonando séries que esquecerão na próxima semana, existe uma palestra de Stanford que pode mudar completamente a forma como você enxerga o futuro. Em apenas duas horas, você aprende mais sobre como modelos como ChatGPT, Claude e Gemini são realmente construídos do que a maioria das pessoas imagina ser possível. Não é uma palestra sobre promessas de marketing. Não é sobre "IA vai dominar o mundo". É sobre arquitetura, treinamento, alinhamento, inferência, escalabilidade e os desafios reais por trás dos sistemas que estão redefinindo a economia global. A maioria das pessoas usa IA. Pouquíssimas entendem como ela funciona. E existe uma enorme diferença entre apertar um botão e compreender a tecnologia que está transformando profissões, empresas e governos. Quem entender IA apenas como usuário ficará para trás. Quem entender como ela é construída terá uma vantagem que só ficará mais valiosa nos próximos anos. Troque uma hora de entretenimento por duas horas de conhecimento. Seu eu de 2030 provavelmente agradecerá.
1:44:23

Enquanto milhões passam horas maratonando séries que esquecerão na próxima semana, existe uma palestra de Stanford que pode mudar completamente a forma como você enxerga o futuro. Em apenas duas horas, você aprende mais sobre como modelos como ChatGPT, Claude e Gemini são realmente construídos do que a maioria das pessoas imagina ser possível. Não é uma palestra sobre promessas de marketing. Não é sobre "IA vai dominar o mundo". É sobre arquitetura, treinamento, alinhamento, inferência, escalabilidade e os desafios reais por trás dos sistemas que estão redefinindo a economia global. A maioria das pessoas usa IA. Pouquíssimas entendem como ela funciona. E existe uma enorme diferença entre apertar um botão e compreender a tecnologia que está transformando profissões, empresas e governos. Quem entender IA apenas como usuário ficará para trás. Quem entender como ela é construída terá uma vantagem que só ficará mais valiosa nos próximos anos. Troque uma hora de entretenimento por duas horas de conhecimento. Seu eu de 2030 provavelmente agradecerá.

･ Ice ･  Ⅹ ･

105,268 次观看 • 3 个月前

"AI will reduce your bottom line and stablecoins will ultimately increase your top line." kareem saw this coming early. He positioned Entendre to build FOR stablecoin native companies, instead of building one himself. As stablecoins began to solve real problems, the winners would grow into massive businesses onchain with complex books to close. So he built the accounting tooling those companies would need to scale. Before Entendre, he built cash management systems at Workday, then joined WeWork at peak valuation, where 300+ accountants couldn't keep up with the accounting at scale. When ChatGPT launched, he founded Entendre with his brother Omar and designer Andy, and the three of them built AI accounting software for some of the fastest growing organizations in the world. They built agents to automate stablecoin and digital asset accounting for companies like Polygon Labs, Brale, Courtyard, and Babylon Labs. In the last 12 months, their customers have raised over $1 billion in venture capital. Last month MoonPay 🟣 acquired the company to power the financial operations layer of the stablecoin economy. His bet: by 2030 half the accountants will have retired, every dollar moving onchain still has to land in a ledger, and agents are how the books get kept. Kareem's conversation with : 1:30 - Youngest engineer on Workday's financial side 6:44 - Why everyone used to fight over the general ledger 10:11 - WeWork at peak valuation and 300 accountants falling behind 13:05 - How he built Cloud Kitchens' money platform from scratch 19:22 - 3 million CPAs, $100T GDP, and 50% retiring by 2030 21:04 - Why stablecoins grow top line and AI cuts bottom line 23:41 - Three levels of AI adoption and where most people are stuck 29:00 - How ChatGPT's launch led to founding Entendre 31:29 - Customers who've raised over $1 billion in VC 35:37 - Polygon Labs: 32 legal entities on one platform 37:51 - Dual Entry and the $90M AI-native ERP partnership 38:33 - Why MoonPay acquired Entendre 43:17 - First startup, first exit, first time raising capital 52:44 - 10x revenue growth and the 2025 inflection point Episode 0052. Presented to you by Altitude
54:42

"AI will reduce your bottom line and stablecoins will ultimately increase your top line." kareem saw this coming early. He positioned Entendre to build FOR stablecoin native companies, instead of building one himself. As stablecoins began to solve real problems, the winners would grow into massive businesses onchain with complex books to close. So he built the accounting tooling those companies would need to scale. Before Entendre, he built cash management systems at Workday, then joined WeWork at peak valuation, where 300+ accountants couldn't keep up with the accounting at scale. When ChatGPT launched, he founded Entendre with his brother Omar and designer Andy, and the three of them built AI accounting software for some of the fastest growing organizations in the world. They built agents to automate stablecoin and digital asset accounting for companies like Polygon Labs, Brale, Courtyard, and Babylon Labs. In the last 12 months, their customers have raised over $1 billion in venture capital. Last month MoonPay 🟣 acquired the company to power the financial operations layer of the stablecoin economy. His bet: by 2030 half the accountants will have retired, every dollar moving onchain still has to land in a ledger, and agents are how the books get kept. Kareem's conversation with : 1:30 - Youngest engineer on Workday's financial side 6:44 - Why everyone used to fight over the general ledger 10:11 - WeWork at peak valuation and 300 accountants falling behind 13:05 - How he built Cloud Kitchens' money platform from scratch 19:22 - 3 million CPAs, $100T GDP, and 50% retiring by 2030 21:04 - Why stablecoins grow top line and AI cuts bottom line 23:41 - Three levels of AI adoption and where most people are stuck 29:00 - How ChatGPT's launch led to founding Entendre 31:29 - Customers who've raised over $1 billion in VC 35:37 - Polygon Labs: 32 legal entities on one platform 37:51 - Dual Entry and the $90M AI-native ERP partnership 38:33 - Why MoonPay acquired Entendre 43:17 - First startup, first exit, first time raising capital 52:44 - 10x revenue growth and the 2025 inflection point Episode 0052. Presented to you by Altitude

Stabledash

22,377 次观看 • 3 个月前

How could you possibly be bearish on compute right now? (Save this). Every 10 seconds in 2026, the world generates 31.7 billion tokens and by 2030, that number hits 1.27 trillion, every 10 seconds. That's a 40x increase and that's before the full agent economy comes online. The Qualcomm CEO said total token demand by 2030 is in the quintillions. Here's what most people miss because when you use ChatGPT, you generate tokens one conversation at a time but agents don't sleep. ] They run 24/7, spawning sub-agents, carrying context, updating memory, catching mistakes and every single one of those actions burns tokens. The shift from human paced to agent paced activity is the single biggest structural change in compute demand we've ever seen. You don't need a perfect forecast but rather just need to believe agents become persistent and if they do, compute demand goes vertical. The infrastructure has to be built before the demand fully arrives, which means the window to own the picks and shovels is right now. That's where neoclouds like Nebius come in. Nebius isn't trying to be AWS, it is a pure-play AI cloud, GPU clusters, inference infrastructure, and developer tooling built from scratch for AI workloads. Q1 2026 revenue hit $399M, up 684% year over year and they're guiding for $7–$9 billion annualized run rate by end of 2026. Analysts are modeling roughly 2,000% total revenue growth from end of 2025 to end of 2027. They already have contracts with Microsoft and Meta already signed. Capex guidance raised to $20–$25 billion because customer commitments justified it. They are sold out of capacity because the constraint isn't customers, it's how fast they can build. Adjusted EBITDA margin on the core AI business hit 45% in Q1 and Jensen Huang called Nebius a close partner at GTC 2026. And in a world where GPU access is the single biggest competitive moat, that relationship matters more than most people realize. The bear case on compute requires you to believe the agent economy stalls and that's a very lonely bet to make right now. Bullish on Nebius and Milk Pro subscribers are already up massively on this trade, come join us using the link below to get our full AI trades and we have a HUGE 33% off right now!
0:34

How could you possibly be bearish on compute right now? (Save this). Every 10 seconds in 2026, the world generates 31.7 billion tokens and by 2030, that number hits 1.27 trillion, every 10 seconds. That's a 40x increase and that's before the full agent economy comes online. The Qualcomm CEO said total token demand by 2030 is in the quintillions. Here's what most people miss because when you use ChatGPT, you generate tokens one conversation at a time but agents don't sleep. ] They run 24/7, spawning sub-agents, carrying context, updating memory, catching mistakes and every single one of those actions burns tokens. The shift from human paced to agent paced activity is the single biggest structural change in compute demand we've ever seen. You don't need a perfect forecast but rather just need to believe agents become persistent and if they do, compute demand goes vertical. The infrastructure has to be built before the demand fully arrives, which means the window to own the picks and shovels is right now. That's where neoclouds like Nebius come in. Nebius isn't trying to be AWS, it is a pure-play AI cloud, GPU clusters, inference infrastructure, and developer tooling built from scratch for AI workloads. Q1 2026 revenue hit $399M, up 684% year over year and they're guiding for $7–$9 billion annualized run rate by end of 2026. Analysts are modeling roughly 2,000% total revenue growth from end of 2025 to end of 2027. They already have contracts with Microsoft and Meta already signed. Capex guidance raised to $20–$25 billion because customer commitments justified it. They are sold out of capacity because the constraint isn't customers, it's how fast they can build. Adjusted EBITDA margin on the core AI business hit 45% in Q1 and Jensen Huang called Nebius a close partner at GTC 2026. And in a world where GPU access is the single biggest competitive moat, that relationship matters more than most people realize. The bear case on compute requires you to believe the agent economy stalls and that's a very lonely bet to make right now. Bullish on Nebius and Milk Pro subscribers are already up massively on this trade, come join us using the link below to get our full AI trades and we have a HUGE 33% off right now!

Milk Road AI

16,310 次观看 • 2 个月前

Eric Schmidt, former CEO of Google: "The AI revolution is underhyped. None of us is prepared for the implications of this." He opens with a warning: "The arrival of this new intelligence will profoundly change our country and the world in ways we cannot fully understand." He explains what's happening right now in the industry: "We're very very quickly developing AI programmers. And these AI programmers will replace traditional software programmers. We're building in the next year AI mathematicians that are as good as the top level graduate students in math. This is happening very quickly." Schmidt argues most people fundamentally misunderstand what AI has become: "Today you think of AI as ChatGPT, but what it really is is a reasoning and planning system that we've never seen before." The implications, he warns, extend far beyond software. These new systems demand resources at an industrial scale we've never encountered. "They're going to need a lot more computation than we've ever had. They're going to need a lot more energy." To illustrate the scale of the energy crisis ahead, Schmidt offers a sobering comparison: "People are planning 10 gigawatt data centers. Now just to do the translation, an average nuclear power plant in the United States is 1 gigawatt. How many nuclear power plants can we make in one year where we're planning this 10 gigawatt data center? Gives you a sense of how big this crisis is." Eric Schmidt shares an estimate he finds most likely: "Data centers will require an additional 29 gigawatts of power by 2027 and 67 more gigawatts by 2030. These things are industrial at a scale I have never seen in my life." Schmidt says the industry needs high skills immigration, light touch regulation around cyber and bio threats, and most critically, energy in all forms. He's personally investing in fusion, but acknowledges it won't arrive in time. He closes with the stakes: "When you build these systems, you have intelligence in the computer and then eventually human level intelligence. Some people think it's within 3 to four years. Then after that, you have something called super intelligence, the intelligence that's higher than of humans. We believe as an industry that this could occur within a decade. It is crucial that America get there first."
2:35

Eric Schmidt, former CEO of Google: "The AI revolution is underhyped. None of us is prepared for the implications of this." He opens with a warning: "The arrival of this new intelligence will profoundly change our country and the world in ways we cannot fully understand." He explains what's happening right now in the industry: "We're very very quickly developing AI programmers. And these AI programmers will replace traditional software programmers. We're building in the next year AI mathematicians that are as good as the top level graduate students in math. This is happening very quickly." Schmidt argues most people fundamentally misunderstand what AI has become: "Today you think of AI as ChatGPT, but what it really is is a reasoning and planning system that we've never seen before." The implications, he warns, extend far beyond software. These new systems demand resources at an industrial scale we've never encountered. "They're going to need a lot more computation than we've ever had. They're going to need a lot more energy." To illustrate the scale of the energy crisis ahead, Schmidt offers a sobering comparison: "People are planning 10 gigawatt data centers. Now just to do the translation, an average nuclear power plant in the United States is 1 gigawatt. How many nuclear power plants can we make in one year where we're planning this 10 gigawatt data center? Gives you a sense of how big this crisis is." Eric Schmidt shares an estimate he finds most likely: "Data centers will require an additional 29 gigawatts of power by 2027 and 67 more gigawatts by 2030. These things are industrial at a scale I have never seen in my life." Schmidt says the industry needs high skills immigration, light touch regulation around cyber and bio threats, and most critically, energy in all forms. He's personally investing in fusion, but acknowledges it won't arrive in time. He closes with the stakes: "When you build these systems, you have intelligence in the computer and then eventually human level intelligence. Some people think it's within 3 to four years. Then after that, you have something called super intelligence, the intelligence that's higher than of humans. We believe as an industry that this could occur within a decade. It is crucial that America get there first."

Big Brain AI

40,383 次观看 • 5 个月前

OPENAI IS FALLING APART IN REAL TIME I've watched companies implode for decades. This one has all the warning signs. OpenAI declared "Code Red" in December. Altman sent an internal memo telling employees to drop everything because Google's Gemini 3 is eating their lunch. Salesforce CEO Marc Benioff publicly ditched ChatGPT for Gemini after using it for two hours. ChatGPT traffic fell in November. Second month-over-month decline of 2025. Meanwhile Gemini jumped to 650 million monthly active users. The company that was supposed to build AGI can't keep its chatbot competitive. But the real story is the money... OpenAI lost $12 BILLION in a single quarter according to Microsoft's own fiscal disclosures. Deutsche Bank estimates $143 billion in cumulative negative cash flow before the company turns profitable. Their analysts put it bluntly: "No startup in history has operated with losses on anything approaching this scale." They're burning $15 million per day on Sora alone. $5 billion annually to generate copyright-infringing memes. Even Sora's lead engineer admitted the "economics are currently completely unsustainable." Here's the big math problem nobody wants to discuss: It's going to cost 5x the energy and money to make these models 2x better. The low-hanging fruit is gone. Every incremental improvement now requires exponentially more compute, more data centers, more power. Reports suggest OpenAI's large training runs in 2025 failed to produce models better than prior versions. GPT-5 launched to widespread disappointment. Users called it "underwhelming" and "horrible." OpenAI had to restore GPT-4o within 24 hours because users preferred the old model. Altman had promised GPT-5 would make GPT-4 feel "mildly embarrassing." Instead, users complained it was worse at basic math and geography. They've released GPT-5.1, GPT-5.2 since. Same complaints each time: too corporate, too safe, robotic, boring. The talent exodus makes this even worse: CTO Mira Murati. Gone. Chief Research Officer Bob McGrew. Gone. Chief Scientist Ilya Sutskever. Gone. President Greg Brockman. Gone. Half the AI safety team departed. Multiple executives reportedly cited "psychological abuse" under Altman's leadership. And now Elon Musk is suing for up to $134 billion. A federal judge just ruled the case goes to jury trial in April. There's "plenty of evidence" that OpenAI's leaders promised to maintain the nonprofit structure that Musk funded. Musk provided $38 million in early funding based on those assurances. Now he wants his share of the $500 billion valuation. OpenAI called it "harassment." But the judge disagreed. Here's what I think happens next: The AI hype cycle is peaking. The diminishing returns are becoming impossible to hide. Competitors are catching up. The lawsuits are piling up. OpenAI needs to generate $200 billion in annual revenue by 2030 to justify their projections. That's 15x growth in five years while costs keep exploding. Even Sam Altman admitted investors are "overexcited" about AI. His exact words: "Someone is going to lose a phenomenal amount of money." If I were running an AI startup with good traction right now, I'd be looking for an exit. Sell into the hype before the music stops. My positioning: I'm not touching OpenAI-adjacent plays at these valuations. The risk profile is astronomical. If you're exposed to the Magnificent 7 through AI infrastructure bets, consider trimming. The gap between promised revolution and delivered reality has never been wider. The smart money is rotating into sectors where valuations actually reflect fundamentals. Small and mid-caps are trading near decade lows relative to Big Tech while earnings growth is only marginally lower. Markets can price risk. But they can't price chaos. And OpenAI is chaos dressed up in a $500 billion valuation.
2:19

OPENAI IS FALLING APART IN REAL TIME I've watched companies implode for decades. This one has all the warning signs. OpenAI declared "Code Red" in December. Altman sent an internal memo telling employees to drop everything because Google's Gemini 3 is eating their lunch. Salesforce CEO Marc Benioff publicly ditched ChatGPT for Gemini after using it for two hours. ChatGPT traffic fell in November. Second month-over-month decline of 2025. Meanwhile Gemini jumped to 650 million monthly active users. The company that was supposed to build AGI can't keep its chatbot competitive. But the real story is the money... OpenAI lost $12 BILLION in a single quarter according to Microsoft's own fiscal disclosures. Deutsche Bank estimates $143 billion in cumulative negative cash flow before the company turns profitable. Their analysts put it bluntly: "No startup in history has operated with losses on anything approaching this scale." They're burning $15 million per day on Sora alone. $5 billion annually to generate copyright-infringing memes. Even Sora's lead engineer admitted the "economics are currently completely unsustainable." Here's the big math problem nobody wants to discuss: It's going to cost 5x the energy and money to make these models 2x better. The low-hanging fruit is gone. Every incremental improvement now requires exponentially more compute, more data centers, more power. Reports suggest OpenAI's large training runs in 2025 failed to produce models better than prior versions. GPT-5 launched to widespread disappointment. Users called it "underwhelming" and "horrible." OpenAI had to restore GPT-4o within 24 hours because users preferred the old model. Altman had promised GPT-5 would make GPT-4 feel "mildly embarrassing." Instead, users complained it was worse at basic math and geography. They've released GPT-5.1, GPT-5.2 since. Same complaints each time: too corporate, too safe, robotic, boring. The talent exodus makes this even worse: CTO Mira Murati. Gone. Chief Research Officer Bob McGrew. Gone. Chief Scientist Ilya Sutskever. Gone. President Greg Brockman. Gone. Half the AI safety team departed. Multiple executives reportedly cited "psychological abuse" under Altman's leadership. And now Elon Musk is suing for up to $134 billion. A federal judge just ruled the case goes to jury trial in April. There's "plenty of evidence" that OpenAI's leaders promised to maintain the nonprofit structure that Musk funded. Musk provided $38 million in early funding based on those assurances. Now he wants his share of the $500 billion valuation. OpenAI called it "harassment." But the judge disagreed. Here's what I think happens next: The AI hype cycle is peaking. The diminishing returns are becoming impossible to hide. Competitors are catching up. The lawsuits are piling up. OpenAI needs to generate $200 billion in annual revenue by 2030 to justify their projections. That's 15x growth in five years while costs keep exploding. Even Sam Altman admitted investors are "overexcited" about AI. His exact words: "Someone is going to lose a phenomenal amount of money." If I were running an AI startup with good traction right now, I'd be looking for an exit. Sell into the hype before the music stops. My positioning: I'm not touching OpenAI-adjacent plays at these valuations. The risk profile is astronomical. If you're exposed to the Magnificent 7 through AI infrastructure bets, consider trimming. The gap between promised revolution and delivered reality has never been wider. The smart money is rotating into sectors where valuations actually reflect fundamentals. Small and mid-caps are trading near decade lows relative to Big Tech while earnings growth is only marginally lower. Markets can price risk. But they can't price chaos. And OpenAI is chaos dressed up in a $500 billion valuation.

George Noble

3,323,992 次观看 • 8 个月前