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NEW: Inside AI's Biggest Downstream Winner.. the Surge in AI Database Demand "Data is the unsung hero, & data is back." MongoDB CEO CJ Desai (@cj_mongodb) The unexpected result? Hyperscalers are turning away even top-50 accounts. "Sorry, we don't have a capacity." "And they are one of the top...

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Molly O’Shea

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172,019 просмотров • 3 месяцев назад •via X (Twitter)

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Фото профиля Molly O’Shea
Molly O’Shea3 месяцев назад

@cj_mongodb

Фото профиля Molly O’Shea
Molly O’Shea3 месяцев назад

@cj_mongodb

Фото профиля Molly O’Shea
Molly O’Shea3 месяцев назад

@cj_mongodb

Фото профиля Molly O’Shea
Molly O’Shea3 месяцев назад

@cj_mongodb Listen on Spotify: Apple: Watch on YT:

Фото профиля 🇺🇸 Bobby 🗽 Polzer 🇺🇸
🇺🇸 Bobby 🗽 Polzer 🇺🇸3 месяцев назад

@MongoDB @cj_mongodb Bookmarked; gonna watch tonight.

Фото профиля Molly O’Shea
Molly O’Shea3 месяцев назад

@MongoDB @cj_mongodb wahoo

Фото профиля puppybear
puppybear3 месяцев назад

@MongoDB @cj_mongodb If data is back as the trendy thing I'm chill AF

Фото профиля Molly O’Shea
Molly O’Shea3 месяцев назад

@MongoDB @cj_mongodb 😎

Фото профиля Code With Karthiban
Code With Karthiban3 месяцев назад

@MongoDB @cj_mongodb AI is only as powerful as the data behind it. Strong data infrastructure will be one of the biggest competitive advantages in the AI era

Фото профиля Deepak Chaudhary
Deepak Chaudhary3 месяцев назад

@MongoDB @cj_mongodb @MongoDB Hi Team, we got some SOS situation, somehow some important data is deleted from free tier M0, want to recover, plz help #mongoDB #sos #urgent #data #recovery @LearnMongo @lifeatmongodb #plzHelp

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MongoDB CEO CJ Desai (CJ Desai) says ElevenLabs has “north of 50 million agents, depending on when you look at it, all running on MongoDB." “That gives us a lot of confidence that we have the right architecture for agentic workloads.”

Molly O’Shea

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Good news for devs working in Visual Studio Code! The MongoDB MCP Server connects your MongoDB data to AI clients, such as GitHub Copilot in VS Code. Now you can ask for collection schemas and data samples, manage users and access, and generate queries all using natural language, right from your editor. Give it a try 👉

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.Dev Ittycheria, MongoDB CEO, discusses what he's seeing in the NYC tech scene and the latest AI trends:
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.Dev Ittycheria, MongoDB CEO, discusses what he's seeing in the NYC tech scene and the latest AI trends:

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EPISODE 158: Nima Ghamsari on the Power of AI Agents & Infinite Workforce Joe Lonsdale sits down with Nima Ghamsari to cover some favorite stories from Palantir, why he's all-in on AI agents, Blend's comeback story, and more. (00:00) Episode intro (01:45) Making millions playing poker to joining Palantir (06:00) Most important lessons from Palantir (07:30) Founding $BLND / understanding the mortgage industry (11:25) How to win over banks and risk-averse customers (15:50) Blend's meteoric rise and fall (19:00) Going all-in on AI agents / Blend's Act II (22:55) efficient markets / is Blend undervalued today? (26:50) Impact of AI on internal operations / increased productivity (32:00) The future of SaaS (36:20) The optimistic case for AI

American Optimist

158,687 просмотров • 4 месяцев назад

BREAKING: AI has eaten the Internet. Data labeling is so over. & $30 trillion of human work is on the verge of automation. Inside The $2.2B AI Research Accelerator, Turing Founder & CEO, Jonathan Siddharth (), joins Sourcery to break down the severe power shift in AI training: from commodity data labeling → expert research Positioning Turing apart from AI data providers like Scale AI, Mercor, & Surge. (00:00) AI Ate The Internet (00:49) Training Superintelligence: the race to AGI (02:31) Viral tweet (03:24) What Turing actually does (04:43) The internet data is “used up” — where will new data come from? (05:34) Four pillars of superintelligence: multimodality, reasoning, tool use, coding (06:07) Automating $30T of global knowledge work (09:18) The $1B revenue opportunity (10:59) Why Turing is a research-first accelerator, not a data labeler (13:45) Jonathan’s Stanford AI Lab roots & founding DNA (17:57) How models are built: pre-training vs. post-training (20:14) RLHF, reinforcement learning, & “breaking the models” (25:19) GPT-5 and the myth of rapid takeoff (30:46) Safety debates and human-in-the-loop systems (34:53) Closing Enterprise Gap: finance, insurance, & pharma (39:23) Why proprietary enterprise data is the next moat in AI
49:29

BREAKING: AI has eaten the Internet. Data labeling is so over. & $30 trillion of human work is on the verge of automation. Inside The $2.2B AI Research Accelerator, Turing Founder & CEO, Jonathan Siddharth (), joins Sourcery to break down the severe power shift in AI training: from commodity data labeling → expert research Positioning Turing apart from AI data providers like Scale AI, Mercor, & Surge. (00:00) AI Ate The Internet (00:49) Training Superintelligence: the race to AGI (02:31) Viral tweet (03:24) What Turing actually does (04:43) The internet data is “used up” — where will new data come from? (05:34) Four pillars of superintelligence: multimodality, reasoning, tool use, coding (06:07) Automating $30T of global knowledge work (09:18) The $1B revenue opportunity (10:59) Why Turing is a research-first accelerator, not a data labeler (13:45) Jonathan’s Stanford AI Lab roots & founding DNA (17:57) How models are built: pre-training vs. post-training (20:14) RLHF, reinforcement learning, & “breaking the models” (25:19) GPT-5 and the myth of rapid takeoff (30:46) Safety debates and human-in-the-loop systems (34:53) Closing Enterprise Gap: finance, insurance, & pharma (39:23) Why proprietary enterprise data is the next moat in AI

Molly O’Shea

70,147 просмотров • 1 год назад

"I don't want to rent myself back from Sam Altman. That is my personal Black Mirror." Kanjun 🐙 (Imbue) on why open source agents are the only way out. Carina Hong (Axiom) on why nobody should trust a single line of unverified AI code. Jonathan Siddharth (Turing) on the data loop making the models smarter. They join @jason on This Week in AI Episode 8: 00:00 Intro 01:31 Open source agents vs. total lock-in 05:10 AI that aced the hardest math exam 09:52 The superintelligence accelerator 15:53 Anthropic's $30B run rate 22:27 OpenAI's identity crisis 28:27 Meta's token-burning leaderboard 44:08 Commodification of developers 58:27 Superintelligence in 36 months 01:08:41 Big Tech is failing at AI
1:26:39

"I don't want to rent myself back from Sam Altman. That is my personal Black Mirror." Kanjun 🐙 (Imbue) on why open source agents are the only way out. Carina Hong (Axiom) on why nobody should trust a single line of unverified AI code. Jonathan Siddharth (Turing) on the data loop making the models smarter. They join @jason on This Week in AI Episode 8: 00:00 Intro 01:31 Open source agents vs. total lock-in 05:10 AI that aced the hardest math exam 09:52 The superintelligence accelerator 15:53 Anthropic's $30B run rate 22:27 OpenAI's identity crisis 28:27 Meta's token-burning leaderboard 44:08 Commodification of developers 58:27 Superintelligence in 36 months 01:08:41 Big Tech is failing at AI

This Week in AI

39,984 просмотров • 7 месяцев назад

NEW: I sat down w/ Perplexity Founder & CEO Aravind Srinivas (Aravind Srinivas) on why AI-native SMBs could drive the next American millionaire economic boom. Perplexity, valued at ~$20B with ~$2B in reported funding, $750M in annualized revenue as of August, seeing 5x YoY revenue growth as it expands from search into autonomous agents. One example Aravind shared is a single-person company generating $3M in annual revenue while spending over $1M a year on Perplexity Computer. His thesis is that AI could fundamentally change the economics of building a business. Smaller teams, less capital, higher productivity, & entirely new business models. At the infrastructure layer, Aravind sees a shift toward local & hybrid inference, with AI agents operating across personal devices and the cloud. As context windows expand and workloads become more personalized, local compute becomes increasingly cost-competitive, while offering greater privacy, control & data sovereignty. We cover: › Why SMBs could become a major driver of US GDP growth › The shift from AI models to agents & recursive economics › Why Perplexity is betting on your Mac instead of building data centers › NVIDIA, Apple Silicon, local inference & sovereign AI › Why writing code is no longer the bottleneck, but problem-solving is 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 (00:00) Aravind Srinivas, Co-founder & CEO of Perplexity (01:30) Why Perplexity's brand is built on curiosity (04:47) Every great invention starts with one question (08:18) How to build a $1T company in America alone (12:36) The next big companies will be tiny (13:45) Is the American dream still alive? (16:28) Stop blaming users for bad prompts (22:55) How Perplexity quietly grew 5x (26:51) The solopreneur spending $1M a year on Perplexity (28:28) "We don't have competitors, we have contributors" (29:20) The data center is coming to your laptop (34:32) Orchestrating up with NVIDIA, down with Apple (36:11) What happens when your AI agent knows everything (39:17) Why Perplexity is skipping the data center race (41:25) Stop asking AI to write code, ask it to think (45:47) Perplexity’s answer to AI security (48:27) The Hugging Face incident & multi-agent threats (50:45) Turning everyone into a scientist (53:31) Why Perplexity isn’t chasing a billion users
54:44

NEW: I sat down w/ Perplexity Founder & CEO Aravind Srinivas (Aravind Srinivas) on why AI-native SMBs could drive the next American millionaire economic boom. Perplexity, valued at ~$20B with ~$2B in reported funding, $750M in annualized revenue as of August, seeing 5x YoY revenue growth as it expands from search into autonomous agents. One example Aravind shared is a single-person company generating $3M in annual revenue while spending over $1M a year on Perplexity Computer. His thesis is that AI could fundamentally change the economics of building a business. Smaller teams, less capital, higher productivity, & entirely new business models. At the infrastructure layer, Aravind sees a shift toward local & hybrid inference, with AI agents operating across personal devices and the cloud. As context windows expand and workloads become more personalized, local compute becomes increasingly cost-competitive, while offering greater privacy, control & data sovereignty. We cover: › Why SMBs could become a major driver of US GDP growth › The shift from AI models to agents & recursive economics › Why Perplexity is betting on your Mac instead of building data centers › NVIDIA, Apple Silicon, local inference & sovereign AI › Why writing code is no longer the bottleneck, but problem-solving is 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 (00:00) Aravind Srinivas, Co-founder & CEO of Perplexity (01:30) Why Perplexity's brand is built on curiosity (04:47) Every great invention starts with one question (08:18) How to build a $1T company in America alone (12:36) The next big companies will be tiny (13:45) Is the American dream still alive? (16:28) Stop blaming users for bad prompts (22:55) How Perplexity quietly grew 5x (26:51) The solopreneur spending $1M a year on Perplexity (28:28) "We don't have competitors, we have contributors" (29:20) The data center is coming to your laptop (34:32) Orchestrating up with NVIDIA, down with Apple (36:11) What happens when your AI agent knows everything (39:17) Why Perplexity is skipping the data center race (41:25) Stop asking AI to write code, ask it to think (45:47) Perplexity’s answer to AI security (48:27) The Hugging Face incident & multi-agent threats (50:45) Turning everyone into a scientist (53:31) Why Perplexity isn’t chasing a billion users

Molly O’Shea

1,858,645 просмотров • 26 дней назад

AI models are upgrading at a new speed. OpenAI’s GPT-6 Astra model, released last week, follows a self-controlled “chain-of-thought” reasoning pattern that can evade certain kinds of monitoring. The next value differentiator for improved models may be less about performance and more about auditability. More on Lightwork this week: → ByteDance is working towards releasing a new real-time world model, pressuring Western frontier labs to keep pace. → Personal agents like Meta’s Muse and Instinct are gaining popularity, raising a conversation over personal autonomy with agents. → Some applications are throttling agent traffic. What does this mean for the companies building them? Claire Zau Josh Machiz Bucky Moore 0:00 Welcome, Bucky Moore! 1:12 OpenAI's Astra 3:50 The New AI Model’s Architecture 4:40 AI Safety and Guardrails 8:01 Trusting AI Agents 11:09 The Future of AI Models 12:06 The AI Agent Land Grab 17:09 AI, Trust, and Personal Data 20:12 Improving AI Agent Capabilities 22:11 Enterprise AI Assistants and Personal Context 24:05 AI Agents and the Future of the Web 25:50 ByteDance and World Models 28:19 World Models and Consumer Content 30:56 Reactor and World Model Infrastructure 34:13 Real-Time Video Models and Scaling
36:26

AI models are upgrading at a new speed. OpenAI’s GPT-6 Astra model, released last week, follows a self-controlled “chain-of-thought” reasoning pattern that can evade certain kinds of monitoring. The next value differentiator for improved models may be less about performance and more about auditability. More on Lightwork this week: → ByteDance is working towards releasing a new real-time world model, pressuring Western frontier labs to keep pace. → Personal agents like Meta’s Muse and Instinct are gaining popularity, raising a conversation over personal autonomy with agents. → Some applications are throttling agent traffic. What does this mean for the companies building them? Claire Zau Josh Machiz Bucky Moore 0:00 Welcome, Bucky Moore! 1:12 OpenAI's Astra 3:50 The New AI Model’s Architecture 4:40 AI Safety and Guardrails 8:01 Trusting AI Agents 11:09 The Future of AI Models 12:06 The AI Agent Land Grab 17:09 AI, Trust, and Personal Data 20:12 Improving AI Agent Capabilities 22:11 Enterprise AI Assistants and Personal Context 24:05 AI Agents and the Future of the Web 25:50 ByteDance and World Models 28:19 World Models and Consumer Content 30:56 Reactor and World Model Infrastructure 34:13 Real-Time Video Models and Scaling

Lightspeed

15,012 просмотров • 1 месяц назад

We are in an industry of skills. Industry of agents. For the very first time we have AI agents sitting on top of tools. Agents now can use the tools. The opportunity for agents is gigantic. —Nvidia CEO Jensen Huang and Salesforce CEO Marc Marc Benioff #DF24
7:43

We are in an industry of skills. Industry of agents. For the very first time we have AI agents sitting on top of tools. Agents now can use the tools. The opportunity for agents is gigantic. —Nvidia CEO Jensen Huang and Salesforce CEO Marc Marc Benioff #DF24

Vala Afshar

48,108 просмотров • 2 лет назад