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Strong builds start with common ground. 🧰☁️ Now generally available, Amazon SageMaker Unified Studio brings together familiar tools from analytics & AI/ML services for streamlined collaboration & development. One environment, endless potential. #AWS 👉

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Amazon Web Services

2,228,742 subscribers

10,482 Aufrufe • vor 1 Jahr •via X (Twitter)

Wissenschaft & Technologie#AWS
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Profilbild von Sam Rahimi
Sam Rahimivor 1 Jahr

Interesting

Profilbild von KeySS Inc
KeySS Incvor 1 Jahr

Looks like a game-changer for collaboration! Excited to see how this simplifies workflows and boosts innovation. Congrats on the launch!

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Real results from real teams. 🛠️💡 AWS Data & AI Bytes brings you demos & insights from customers building generative AI apps, scaling data platforms & modernizing with AWS services. Learn more about AWS for Data. 👉
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Real results from real teams. 🛠️💡 AWS Data & AI Bytes brings you demos & insights from customers building generative AI apps, scaling data platforms & modernizing with AWS services. Learn more about AWS for Data. 👉

Amazon Web Services

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Almost 20 years later, AWS is still the most popular cloud in the world. The reason is simple: it just works! They have four services focused on Generative AI: 1. Amazon Q 2. Amazon Bedrock 3. SageMaker JumpStart 4. PartyRock I've been using AWS for around 15 years (honestly, I don't remember well), and their Developer Center is a gold mine. If you open their Developer Center, you'll find a new learning path, "Generative AI for Developers." I'm linking to it below. This is not just a course. This is a collection of courses, examples, videos, tutorials, and code walkthroughs. They will teach you how to use Generative AI on AWS using the four services above. ↑ That right there is a huge selling point: These classes aren't just theoretical. You'll have a chance to learn using the same professional tools everyone else uses. By the way, there are many more resources in the Developer Center: • Machine Learning • Data Operations • DevOps All of these are free. Click, click, and start learning right away. One more thing before I forget: If you are building anything with AWS, check out Amazon Q, their coding assistant. This is the *best* coding assistant for AWS-related work, and it's not even close. It's a Visual Studio Code extension. Install it, and it works like any other code assistant, except this one knows a lot about AWS. Thanks to AWS for sponsoring a post about their free courses and learning resources. There's a special place in Developer Heaven for you.
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Almost 20 years later, AWS is still the most popular cloud in the world. The reason is simple: it just works! They have four services focused on Generative AI: 1. Amazon Q 2. Amazon Bedrock 3. SageMaker JumpStart 4. PartyRock I've been using AWS for around 15 years (honestly, I don't remember well), and their Developer Center is a gold mine. If you open their Developer Center, you'll find a new learning path, "Generative AI for Developers." I'm linking to it below. This is not just a course. This is a collection of courses, examples, videos, tutorials, and code walkthroughs. They will teach you how to use Generative AI on AWS using the four services above. ↑ That right there is a huge selling point: These classes aren't just theoretical. You'll have a chance to learn using the same professional tools everyone else uses. By the way, there are many more resources in the Developer Center: • Machine Learning • Data Operations • DevOps All of these are free. Click, click, and start learning right away. One more thing before I forget: If you are building anything with AWS, check out Amazon Q, their coding assistant. This is the *best* coding assistant for AWS-related work, and it's not even close. It's a Visual Studio Code extension. Install it, and it works like any other code assistant, except this one knows a lot about AWS. Thanks to AWS for sponsoring a post about their free courses and learning resources. There's a special place in Developer Heaven for you.

Santiago

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Tired of switching between 10 apps just to finish one project? Meet Pokee AI — the AI agent that doesn’t just suggest, it executes. ✅ It plans your workflow from start to finish ✅ Chooses the right tools for every step ✅ Handles docs, posts, emails, code, reports, and analytics — across Google, Slack, X, YouTube, Amazon, ClickUp, GitHub & more Need a social post? Pokee AI generates content, designs images, and schedules it. Need a report? Pokee pulls data, analyzes it, and delivers insights. Need code? Pokee writes and refines it — no switching tabs. 🚀 One AI, endless tasks — automated. 👉 Public beta is live →
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Tired of switching between 10 apps just to finish one project? Meet Pokee AI — the AI agent that doesn’t just suggest, it executes. ✅ It plans your workflow from start to finish ✅ Chooses the right tools for every step ✅ Handles docs, posts, emails, code, reports, and analytics — across Google, Slack, X, YouTube, Amazon, ClickUp, GitHub & more Need a social post? Pokee AI generates content, designs images, and schedules it. Need a report? Pokee pulls data, analyzes it, and delivers insights. Need code? Pokee writes and refines it — no switching tabs. 🚀 One AI, endless tasks — automated. 👉 Public beta is live →

Arsalan

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🎉Introducing PyFlue: The Python-Native Agent Harness Framework.🧰 💡Flue for Python: Fred K. Schott fks CEO of HTML has launched Flue: The Agent Harness Framework for TypeScript. It brings programmable harness right into your agents rather than DIY plumbing. Python ecosystem already has 🦾 powerful AI/ML tools and frameworks and research initiatives but most frameworks asked users to build your own harness. Superagentic AI bringing this concept of Flue to Python 🐍 ecosystem. Here is PyFlue even even better 🤖 Agent = Model 💻 + Harness 🧰 + Memory 🧠 Almost all the feature of Flue plugged with LangChain Deepagents harness built by Harrison Chase and team Viv Sydney Runkle and more coming soon. 👉 Stop building agent loops, start using a harness. 💻 Try PyFlue Now : ⭐️ GitHub: 📚Docs: 📙 Blog Post: #HarnessEngineering #AgentHarnesses
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🎉Introducing PyFlue: The Python-Native Agent Harness Framework.🧰 💡Flue for Python: Fred K. Schott fks CEO of HTML has launched Flue: The Agent Harness Framework for TypeScript. It brings programmable harness right into your agents rather than DIY plumbing. Python ecosystem already has 🦾 powerful AI/ML tools and frameworks and research initiatives but most frameworks asked users to build your own harness. Superagentic AI bringing this concept of Flue to Python 🐍 ecosystem. Here is PyFlue even even better 🤖 Agent = Model 💻 + Harness 🧰 + Memory 🧠 Almost all the feature of Flue plugged with LangChain Deepagents harness built by Harrison Chase and team Viv Sydney Runkle and more coming soon. 👉 Stop building agent loops, start using a harness. 💻 Try PyFlue Now : ⭐️ GitHub: 📚Docs: 📙 Blog Post: #HarnessEngineering #AgentHarnesses

Shashi 🇬🇧🇺🇸

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Did you know? WordPress has never had an IDE before CodeWP 3.0 is taking shape, and it's the first IDE for #WordPress. First and foremost it's a development environment - autocomplete for plugins and core. LSP. Multi file support. Terminal with WP-now, (pictured) WP CLI, etc. We then add deep AI integrations, with our plugin-specific modes, AI testing, and AI build processes for blocks. (Re)Introducing Snippet, Plugin and Block Wizards. CodeWP Tools (structured AI generations will be added too. This thing is going to be awesome. Real time collaboration & agency features. Ability to keep all of your snippets, custom plugins and custom blocks in 1 platform, and work from anywhere. Deep integration with sites using AgentWP. The list goes on! To get access to the beta, sign up at When available, you'll have the option to launch into the new IDE experience.
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Did you know? WordPress has never had an IDE before CodeWP 3.0 is taking shape, and it's the first IDE for #WordPress. First and foremost it's a development environment - autocomplete for plugins and core. LSP. Multi file support. Terminal with WP-now, (pictured) WP CLI, etc. We then add deep AI integrations, with our plugin-specific modes, AI testing, and AI build processes for blocks. (Re)Introducing Snippet, Plugin and Block Wizards. CodeWP Tools (structured AI generations will be added too. This thing is going to be awesome. Real time collaboration & agency features. Ability to keep all of your snippets, custom plugins and custom blocks in 1 platform, and work from anywhere. Deep integration with sites using AgentWP. The list goes on! To get access to the beta, sign up at When available, you'll have the option to launch into the new IDE experience.

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Spectre AI Soars and Secures Google Scale Tier Membership with $200,000 in Development Resources We're thrilled to announce a significant milestone for Spectre AI! After a lot of networking, and a rigorous selection process, we've been accepted into the prestigious Google Scale Tier program. We had Start Tier, now we have Scale Tier! This membership signifies Google's recognition of Spectre AI's potential to become a potential game-changer in the blockchain space, and it grants us access to a wealth of resources to fuel our growth – $200,000 in development funding from GoogleStartups to use their advanced tools. What is the Google Scale Tier? The Google Scale Tier is a highly selective program designed to nurture high-growth startups with exceptional potential. Going beyond simple funding, this program grants a comprehensive suite of benefits to empower us to scale our technology and achieve new heights. Unlocking Cutting-Edge Tech and Expertise Our Google Scale Tier membership unlocks a treasure trove of resources to accelerate our development journey: $200,000 in Google Development Resources: This crucial boost will allow us to leverage Google Cloud and cutting-edge tools, along with collaboration with top Google engineers. These experts will work closely with our team to integrate these powerful resources seamlessly into our entire suite of products, including AI Predictions, Sentiment Analysis, and Technical Analysis. Imagine the possibilities for enhanced accuracy, efficiency, and deeper market insights leveraged by Google's technology! Collaboration with Google Engineering Experts: As mentioned earlier, the $200,000 in development resources includes access to Google engineers – the masterminds behind cutting-edge technologies like Long Short-Term Memory (LSTM) models, Machine Learning (ML), and advanced graphing models. These experts will collaborate with our team to integrate these powerful tools into our products. Dedicated Google Representative: A dedicated Google representative from their Irish headquarters has become our go-to person, ensuring seamless collaboration and ongoing support throughout our journey. Thank you GoogleStartupUK The Future of Spectre AI: Enhanced All-in-One Products This partnership extends far beyond individual features. Here's what you can expect across our entire product suite: Next-Level Functionality: We'll leverage Google's advanced algorithms and massive datasets to refine all our tools, including AI Predictions, Sentiment Analysis, and Technical Analysis. This means more reliable and insightful information to guide your investment strategies. Expanded Capabilities: We're exploring groundbreaking new features for our entire product suite, like real-time analysis, multi-factor modeling, and even deeper market insights. Enhanced User Experience: Navigating through all our tools will be smoother than ever. We'll work with Google to refine the user interface across the board, making it easier to understand and leverage the power of AI in your crypto journey. The Data Visualization Revolution: Buckle up, X Bubblemaps users! Google's advanced graphing models are poised to transform how you visualize and explore data within Spectre AI. We can't wait to unveil a whole new level of visualization that will take your on-chain analysis to the next level. This is just the beginning! We're incredibly grateful for this opportunity to partner with Google and revolutionize the future of our all-in-one blockchain analysis suite. Stay tuned for exciting updates as we develop groundbreaking new features together. Thank you for being a part of the Spectre AI community! #google #googlecloud #spectre #ai #tech #innovation $spect

SPECTRE AI

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We've all experienced how consumer AI can help in our personal lives, but that same experience hasn't been available at work. Most enterprise data is siloed, consumer AI can't access your work tools, and many orgs won't allow it due to security concerns. We built Amazon Quick Suite to solve those problems. It’s an agentic AI app that acts as your AI teammate at work – connecting to your business data and apps, and letting you interact with AI agents that can find insights, conduct research, and even take actions across your systems – with the security and privacy enterprises need. Quick works across your existing ecosystem, from emails to Salesforce to Slack to AWS services. You can create custom agents to draft content in your personal style, use Quick Research for in-depth analysis, or set up Quick Flow to automate tasks. And most importantly, your interactions never train the underlying models. We've been testing with Amazon employees and select customers and early results show just how transformational Quick is… cutting analysis time from months to days, and turning week-long tasks into minutes. This is an exciting moment and we're just getting started. Quick is available now, so have at it!
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Excited to share a new product (and a new category for Adobe): Mood-boarding and concepting in the age of AI with Project Concept. Project Concept is an AI-first product for the early stages of every creative journey - designed for an era where we will spend LESS time on the mundane and repetitive parts of production, and MORE time exploring the full surface area of possibility and finding better ideas. It features the very latest capabilities from Adobe’s Firefly Generative AI models to help you rapidly explore potential artistic directions, mix images together, transform regions of an asset, and remix styles, backgrounds, and other ingredient assets. You can start a project using your own assets or other sources of inspiration. Project Concept then uses AI and collaborative tools to assist with both divergent thinking, illuminating the far-reaching possibilities of any creative project, and convergent thinking to bring ideas together, apply controls, and ultimately select the final direction to go with. Excited about this one. Project Concept goes into Private Beta today, now back to work… #AdobeMAX

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Nihan

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Development containers are awesome, especially when you can swap the hardware running your environment without changing a single thing. Apparently, I've been living under a rock because I didn't know about this. I recorded a 3-min video to show you Gitpod Flex running on my laptop. This takes less than 5 minutes to configure and run. Here is a quick summary: 1. One click to run any of my GitHub projects in a container, isolated from everything else. 2. I can use Visual Studio Code, JetBrains, Cursor, or any other IDE that supports development containers. 3. I don't have to mess up with my computer anymore (or have 17 versions of Python installed) ← this alone is awesome! 4. I can spin up a runner in AWS with my dev container and have access to any hardware I want while developing. 5. I can configure one-click buttons to run services and tasks I need every day. 6. I can share the environment with anyone on my team. I left this for the end, but I know this is one of the most important features of Gitpod Flex: They built a zero-trust architecture to manage these development environments. This is huge for those working at companies where security is crucial. Below is the link with an explanation of how they built their architecture. Thanks to the Gitpod team for their work on Flex and for sponsoring this post. I have it running now, and I'm planning to keep using it!
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Development containers are awesome, especially when you can swap the hardware running your environment without changing a single thing. Apparently, I've been living under a rock because I didn't know about this. I recorded a 3-min video to show you Gitpod Flex running on my laptop. This takes less than 5 minutes to configure and run. Here is a quick summary: 1. One click to run any of my GitHub projects in a container, isolated from everything else. 2. I can use Visual Studio Code, JetBrains, Cursor, or any other IDE that supports development containers. 3. I don't have to mess up with my computer anymore (or have 17 versions of Python installed) ← this alone is awesome! 4. I can spin up a runner in AWS with my dev container and have access to any hardware I want while developing. 5. I can configure one-click buttons to run services and tasks I need every day. 6. I can share the environment with anyone on my team. I left this for the end, but I know this is one of the most important features of Gitpod Flex: They built a zero-trust architecture to manage these development environments. This is huge for those working at companies where security is crucial. Below is the link with an explanation of how they built their architecture. Thanks to the Gitpod team for their work on Flex and for sponsoring this post. I have it running now, and I'm planning to keep using it!

Santiago

33,098 Aufrufe • vor 1 Jahr

Still spending hours on repetitive work that should’ve been automated by now? Most teams waste valuable time creating documents from scratch, rewriting the same emails, reformatting data, and manually producing content that could be generated in seconds — with the right tools. Meet |Context — The AI Office Suite built to transform how work gets done. 🚀 Not just where you work — but what you work on. Context doesn’t just assist you. It acts like a teammate: learning, reasoning, writing, researching, and adapting to your workflow. Here’s how transforms your workday: ✅ Unified Workspace: Connect over 300 tools like Slack, Google Docs, Salesforce, and Excel in one place, and streamline your entire workflow. ✅ AI-Powered Automation: Let AI handle repetitive tasks, generate content, and update documents in real time, saving you hours every week. ✅ Real-Time Collaboration: Collaborate seamlessly with your team on shared workspaces, making edits, updates, and feedback simple and quick. ✅ Top-Tier Security: With enterprise-grade security, including SOC 2, GDPR compliance, and AES-256 encryption, your data stays safe and secure. ✅ Endless Customization: Build custom templates, automate research, and tailor workflows to meet the unique needs of your business. Ready to level up your workflow? Try it now👉 #ContextAI #Automation #AIWorkspace #Productivity #SmartWork #NoCodeTools #AIIntegration #Teamworkrder
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Manish Kumar Shah

33,734 Aufrufe • vor 1 Jahr

🚀 Expanding the Renta Network Ecosystem: Welcoming New Partners! 🎉 At Renta Network, we believe that strategic partnerships are key to the growth of Web3 rentals and tokenized assets. We’ve previously highlighted our strong allies – check out the full list here 👉 🚀 Now, let’s introduce our new partners who are driving Renta Network forward! - HyperGPT – AI-powered Web3 infrastructure for intelligent automation. - UQUID | Digital Commerce Infrastructure – Bridging DeFi with real-world payments through crypto solutions. - Conduit – Simplifying blockchain development with modular rollups. - DAOBase 🐝 – Enhancing decentralized governance with AI-DAO tools. - @UniLendFinance – Enabling permissionless lending and borrowing in DeFi. - @BitDocAI – AI-driven document management for secure smart contracts. - Lance Walley – Transforming real-world asset financing with DeFi liquidity. - @RoxiAI_bot – AI bot for automated blockchain analytics and insights. - LIFT⚡️ – Leveraging AI for real-time data processing and DeFi optimization. - Kima Network – Bridging traditional finance and blockchain seamlessly. - Hooked Protocol🪝 – Gamifying Web3 adoption for mass engagement. - Polyhedra – Enabling privacy-focused zero-knowledge (ZK) solutions for Web3. - Warden – Strengthening cross-chain security with trustless verification. - Owlto Finance(🦉💛🦉) – Enhancing cross-chain liquidity and fast asset transfers. - Clearpool – Providing institutional-grade credit solutions for DeFi. - jennifer oinn.io – A Web3-native networking and collaboration platform. - Novastro 2.0 🔜 – AI-powered RWA tokenization and next-gen DeFi solutions. - Plena Finance – The ultimate crypto super app optimizing the DeFi experience. 💡 With these powerful new partnerships, we are moving even faster: expanding AI integrations, scaling RWA tokenization, increasing liquidity, and bringing new opportunities to Web3 rentals. 📢 Stay tuned – the best is yet to come! 🚀 - 🔔 Don’t miss out on important updates and giveaways! Follow us on Twitter — Renta Network If you're a beginner, start here ➡️ ⬅️ 📢 Join Our Ambassador Program - 📈 Trade here: All relevant links -- #RentaNetwork #Partnerships #Web3 #Blockchain #Crypto #DeFi #AI #PropertyNFT
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🚀 Expanding the Renta Network Ecosystem: Welcoming New Partners! 🎉 At Renta Network, we believe that strategic partnerships are key to the growth of Web3 rentals and tokenized assets. We’ve previously highlighted our strong allies – check out the full list here 👉 🚀 Now, let’s introduce our new partners who are driving Renta Network forward! - HyperGPT – AI-powered Web3 infrastructure for intelligent automation. - UQUID | Digital Commerce Infrastructure – Bridging DeFi with real-world payments through crypto solutions. - Conduit – Simplifying blockchain development with modular rollups. - DAOBase 🐝 – Enhancing decentralized governance with AI-DAO tools. - @UniLendFinance – Enabling permissionless lending and borrowing in DeFi. - @BitDocAI – AI-driven document management for secure smart contracts. - Lance Walley – Transforming real-world asset financing with DeFi liquidity. - @RoxiAI_bot – AI bot for automated blockchain analytics and insights. - LIFT⚡️ – Leveraging AI for real-time data processing and DeFi optimization. - Kima Network – Bridging traditional finance and blockchain seamlessly. - Hooked Protocol🪝 – Gamifying Web3 adoption for mass engagement. - Polyhedra – Enabling privacy-focused zero-knowledge (ZK) solutions for Web3. - Warden – Strengthening cross-chain security with trustless verification. - Owlto Finance(🦉💛🦉) – Enhancing cross-chain liquidity and fast asset transfers. - Clearpool – Providing institutional-grade credit solutions for DeFi. - jennifer oinn.io – A Web3-native networking and collaboration platform. - Novastro 2.0 🔜 – AI-powered RWA tokenization and next-gen DeFi solutions. - Plena Finance – The ultimate crypto super app optimizing the DeFi experience. 💡 With these powerful new partnerships, we are moving even faster: expanding AI integrations, scaling RWA tokenization, increasing liquidity, and bringing new opportunities to Web3 rentals. 📢 Stay tuned – the best is yet to come! 🚀 - 🔔 Don’t miss out on important updates and giveaways! Follow us on Twitter — Renta Network If you're a beginner, start here ➡️ ⬅️ 📢 Join Our Ambassador Program - 📈 Trade here: All relevant links -- #RentaNetwork #Partnerships #Web3 #Blockchain #Crypto #DeFi #AI #PropertyNFT

Renta Network

103,000 Aufrufe • vor 1 Jahr

NotebookLM is one of the most delightful, inspiring, and viral AI products out there right now, and I got a chance to chat with the PM behind the product, Raiza Martin (@raiza_abubakar). In our conversation, we cover: 🔸 The origin story of NotebookLM 🔸 The future road map for NotebookLM 🔸 How Google Labs operates differently from the rest of Google 🔸 The development of the “Audio Overviews” feature 🔸 Key metrics and growth of NotebookLM 🔸 Stories about collaborating with author Steven Johnson 🔸 Navigating potential misuse of AI technology 🔸 More Listen now 👇 - YouTube: - Spotify: - Apple: Raiza is a senior product manager for AI at Google Labs for AI at Google Labs, where she leads the team behind NotebookLM, an AI-powered research tool that includes a mind-blowing podcast-on-demand feature called “Audio Overviews.” NotebookLM started as a 20% project and has grown into a product that’s spreading across social media and has a Discord server with over 60,000 users. Raiza previously worked on AI Test Kitchen and has a background in startups, payments, and ads. Thank you to our wonderful sponsors for supporting the podcast: 🏆 Explo — Embed customer-facing analytics in your product: 🏆 Sprig — Build products for people, not data points: 🏆 Sidebar — Accelerate your career by surrounding yourself with extraordinary peers: Some key takeaways: 1. Embrace a startup mentality within large organizations: Google Labs operates with fewer processes and more agility than typical Google teams. This allows them to move faster and iterate quickly, much like a startup. 2. Often, powerful technology is already available; the magic lies in how you interact with it. For instance, by integrating powerful audio models with existing LLMs, NotebookLM created an innovative way for users to interact with content. Look for unique applications of the tools you already have. 3. Don’t wait for a perfect launch. Start with a working version of your product and use user feedback to iterate and improve. This approach can reveal unexpected insights and user preferences, helping you shape the final product.
1:07

NotebookLM is one of the most delightful, inspiring, and viral AI products out there right now, and I got a chance to chat with the PM behind the product, Raiza Martin (@raiza_abubakar). In our conversation, we cover: 🔸 The origin story of NotebookLM 🔸 The future road map for NotebookLM 🔸 How Google Labs operates differently from the rest of Google 🔸 The development of the “Audio Overviews” feature 🔸 Key metrics and growth of NotebookLM 🔸 Stories about collaborating with author Steven Johnson 🔸 Navigating potential misuse of AI technology 🔸 More Listen now 👇 - YouTube: - Spotify: - Apple: Raiza is a senior product manager for AI at Google Labs for AI at Google Labs, where she leads the team behind NotebookLM, an AI-powered research tool that includes a mind-blowing podcast-on-demand feature called “Audio Overviews.” NotebookLM started as a 20% project and has grown into a product that’s spreading across social media and has a Discord server with over 60,000 users. Raiza previously worked on AI Test Kitchen and has a background in startups, payments, and ads. Thank you to our wonderful sponsors for supporting the podcast: 🏆 Explo — Embed customer-facing analytics in your product: 🏆 Sprig — Build products for people, not data points: 🏆 Sidebar — Accelerate your career by surrounding yourself with extraordinary peers: Some key takeaways: 1. Embrace a startup mentality within large organizations: Google Labs operates with fewer processes and more agility than typical Google teams. This allows them to move faster and iterate quickly, much like a startup. 2. Often, powerful technology is already available; the magic lies in how you interact with it. For instance, by integrating powerful audio models with existing LLMs, NotebookLM created an innovative way for users to interact with content. Look for unique applications of the tools you already have. 3. Don’t wait for a perfect launch. Start with a working version of your product and use user feedback to iterate and improve. This approach can reveal unexpected insights and user preferences, helping you shape the final product.

Lenny Rachitsky

75,439 Aufrufe • vor 1 Jahr

Just six months ago, DHH (creator of Ruby on Rails and Omarchy) said how he doesn’t really use AI tools to write code, because they are not good enough. Things have changed, a lot. Timestamps: 00:00 Intro 02:11 Omarchy and Ruby on Rails 08:25 37signals overview 10:12 Launching HEY 18:38 Building HEY 22:47 Designers at 37signals 28:08 The craft of design 31:52 Why DHH now embraces AI workflows 39:45 The AI inflection point 44:23 DHH’s agent-first workflow 55:09 AI’s impact on junior developers 1:03:08 Developer experience with AI 1:16:43 What does AI mean for developers? 1:23:33 37signals teams and hiring 1:38:20 Work-life balance with AI 1:41:41 Why DHH keeps building 1:45:24 Closing Brought to you by: • Statsig – ⁠ The unified platform for flags, analytics, experiments, and more. Stop switching between different tools, and have them all in one place. • WorkOS – Everything you need to make your app enterprise ready. WorkOS gives you APIs to ship enterprise features in days. Check out • Sonar – The makers of SonarQube, the industry standard for automated code review. See how SonarQube Advanced Security is empowering the Agent Centric Development Cycle (AC/DC) with new capabilities. Three interesting observations from this conversation: #1 DHH's philosophy on AI has not changed, but the available tools very much have. Autocomplete-style coding assistants were genuinely annoying for experienced developers six months ago. Things changed with the shift from tab-completion to agent harnesses, plus the emergence of powerful models like Opus 4.5 – when agents started producing code which DHH does want to merge with little to no alteration. #2 Beautiful code and products aren’t matters of vanity; they’re signals of correctness. Dipping into philosophy, DHH says: “When something is beautiful, it’s likely to be correct.” He argues that Steve Jobs wanted the inside of a computer to be beautiful because people who care about circuit board layout are also those who sweat on the details of the UI. #3 DHH’s development workflow, today: He runs tmux to have two models running, and neovim in the center. Specifics: - One fast LLM running (typically Gemini 2.5) in one split terminal - A slow but more powerful model in another terminal (usually Opus) - NeoVim for reviewing diffs via Lazygit
1:47:20

Just six months ago, DHH (creator of Ruby on Rails and Omarchy) said how he doesn’t really use AI tools to write code, because they are not good enough. Things have changed, a lot. Timestamps: 00:00 Intro 02:11 Omarchy and Ruby on Rails 08:25 37signals overview 10:12 Launching HEY 18:38 Building HEY 22:47 Designers at 37signals 28:08 The craft of design 31:52 Why DHH now embraces AI workflows 39:45 The AI inflection point 44:23 DHH’s agent-first workflow 55:09 AI’s impact on junior developers 1:03:08 Developer experience with AI 1:16:43 What does AI mean for developers? 1:23:33 37signals teams and hiring 1:38:20 Work-life balance with AI 1:41:41 Why DHH keeps building 1:45:24 Closing Brought to you by: • Statsig – ⁠ The unified platform for flags, analytics, experiments, and more. Stop switching between different tools, and have them all in one place. • WorkOS – Everything you need to make your app enterprise ready. WorkOS gives you APIs to ship enterprise features in days. Check out • Sonar – The makers of SonarQube, the industry standard for automated code review. See how SonarQube Advanced Security is empowering the Agent Centric Development Cycle (AC/DC) with new capabilities. Three interesting observations from this conversation: #1 DHH's philosophy on AI has not changed, but the available tools very much have. Autocomplete-style coding assistants were genuinely annoying for experienced developers six months ago. Things changed with the shift from tab-completion to agent harnesses, plus the emergence of powerful models like Opus 4.5 – when agents started producing code which DHH does want to merge with little to no alteration. #2 Beautiful code and products aren’t matters of vanity; they’re signals of correctness. Dipping into philosophy, DHH says: “When something is beautiful, it’s likely to be correct.” He argues that Steve Jobs wanted the inside of a computer to be beautiful because people who care about circuit board layout are also those who sweat on the details of the UI. #3 DHH’s development workflow, today: He runs tmux to have two models running, and neovim in the center. Specifics: - One fast LLM running (typically Gemini 2.5) in one split terminal - A slow but more powerful model in another terminal (usually Opus) - NeoVim for reviewing diffs via Lazygit

Gergely Orosz

329,135 Aufrufe • vor 3 Monaten

Announcing Gemini 2.5 Flash Image! (Nano Banana) from Google DeepMind. This model brings you state of the art image generation! Here's 7m of demos. Today marks a leap forward in AI-powered image creativity with the launch of stronger native image generation and editing in Gemini 2.5 Flash. Here's what's new: 👤 Consistent character design: Maintain a character's identity across multiple images, changing their outfits, poses, and scenes without losing their core look. 🎨 Creative composition: Seamlessly merge elements from up to three different images into a single, cohesive masterpiece. The potential for surrealist art and unique compositions is endless. ✍️ Targeted edits with natural language: Go beyond the prompt. You can now make highly specific edits like "change the background," "restore this faded photo," or "edit the character's outfit" with simple commands. ✨ Design & identity adaptation: Apply a specific style, texture, or pattern from one image to another, unlocking new possibilities for fashion, product design, and architectural visualization. I've put together a ~7-minute video demo to walk you through these features and show just how powerful they are in action. We can't wait to see what you all create! Try the model out in Google AI Studio, Gemini app or the Gemini API.
7:27

Announcing Gemini 2.5 Flash Image! (Nano Banana) from Google DeepMind. This model brings you state of the art image generation! Here's 7m of demos. Today marks a leap forward in AI-powered image creativity with the launch of stronger native image generation and editing in Gemini 2.5 Flash. Here's what's new: 👤 Consistent character design: Maintain a character's identity across multiple images, changing their outfits, poses, and scenes without losing their core look. 🎨 Creative composition: Seamlessly merge elements from up to three different images into a single, cohesive masterpiece. The potential for surrealist art and unique compositions is endless. ✍️ Targeted edits with natural language: Go beyond the prompt. You can now make highly specific edits like "change the background," "restore this faded photo," or "edit the character's outfit" with simple commands. ✨ Design & identity adaptation: Apply a specific style, texture, or pattern from one image to another, unlocking new possibilities for fashion, product design, and architectural visualization. I've put together a ~7-minute video demo to walk you through these features and show just how powerful they are in action. We can't wait to see what you all create! Try the model out in Google AI Studio, Gemini app or the Gemini API.

Addy Osmani

159,059 Aufrufe • vor 10 Monaten

Data teams spend weeks on simple requests. (This AI answers them in minutes.) Most data analysis is repetitive manual tasks. Data teams spend more time on setup than actual analysis. The workflow usually looks like this: → Run some exploratory data analysis in a local Jupyter notebook or environment → Pull data from multiple disconnected sources → Write code from scratch for every analysis → Export static charts that stakeholders can't explore (or wrestle with legacy BI to create a dashboard) → Manually send updates via email or Slack when data changes → Start over for each new request Most teams accept this as "how data analysis works." While business decisions wait for insights. That's where Fabi changes the entire approach. It's a powerful, AI-native platform built for teams that want to boost productivity and supercharge their data workflows. Instead of working on separate tools and manual processes, you collaborate on analysis that automatically delivers insights where teams work. Here's what makes Fabi different: AI-Native Analysis Environment ↳ SQL and Python work together with AI assistance that handles coding and debugging automatically. Smart Automation Workflows ↳ Automatically send AI-powered reports and summaries right where business works in Slack, email, and spreadsheets. Universal Data Integration ↳ Analyze data from files, Google Sheets, Airtable, plus your data warehouse and databases in one place. Collaborative Data Apps ↳ Create interactive dashboards that stakeholders can explore and ask follow-up questions directly. What you can do with Fabi that legacy BI can't: ➟ Send AI-generated insights directly to Slack channels ➟ Automatically email data summaries to stakeholders ➟ Analyze uploaded files without complex ETL processes ➟ Collaborate on analysis like Google Docs for data ➟ Build workflows that push insights to spreadsheets Perfect for teams that want to move beyond the constraints of legacy and increase their impact. Teams using Fabi see immediate results: ✓ Insights delivered in minutes instead of days ✓ Reduced context switching between tools ✓ Stakeholders explore data independently ✓ Workflows automated to save hours of manual work From analysis to automated delivery - all in one AI-native environment. 📌 Try Fabi today: 👉 Follow Fabi.ai and marc for Fabi updates. 🔄 Repost to help other teams streamline data analysis #DataAnalysis #ModernBI #DataOps #InteractiveDashboards #FabiPartnership #SponsoredByFabi
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Data teams spend weeks on simple requests. (This AI answers them in minutes.) Most data analysis is repetitive manual tasks. Data teams spend more time on setup than actual analysis. The workflow usually looks like this: → Run some exploratory data analysis in a local Jupyter notebook or environment → Pull data from multiple disconnected sources → Write code from scratch for every analysis → Export static charts that stakeholders can't explore (or wrestle with legacy BI to create a dashboard) → Manually send updates via email or Slack when data changes → Start over for each new request Most teams accept this as "how data analysis works." While business decisions wait for insights. That's where Fabi changes the entire approach. It's a powerful, AI-native platform built for teams that want to boost productivity and supercharge their data workflows. Instead of working on separate tools and manual processes, you collaborate on analysis that automatically delivers insights where teams work. Here's what makes Fabi different: AI-Native Analysis Environment ↳ SQL and Python work together with AI assistance that handles coding and debugging automatically. Smart Automation Workflows ↳ Automatically send AI-powered reports and summaries right where business works in Slack, email, and spreadsheets. Universal Data Integration ↳ Analyze data from files, Google Sheets, Airtable, plus your data warehouse and databases in one place. Collaborative Data Apps ↳ Create interactive dashboards that stakeholders can explore and ask follow-up questions directly. What you can do with Fabi that legacy BI can't: ➟ Send AI-generated insights directly to Slack channels ➟ Automatically email data summaries to stakeholders ➟ Analyze uploaded files without complex ETL processes ➟ Collaborate on analysis like Google Docs for data ➟ Build workflows that push insights to spreadsheets Perfect for teams that want to move beyond the constraints of legacy and increase their impact. Teams using Fabi see immediate results: ✓ Insights delivered in minutes instead of days ✓ Reduced context switching between tools ✓ Stakeholders explore data independently ✓ Workflows automated to save hours of manual work From analysis to automated delivery - all in one AI-native environment. 📌 Try Fabi today: 👉 Follow Fabi.ai and marc for Fabi updates. 🔄 Repost to help other teams streamline data analysis #DataAnalysis #ModernBI #DataOps #InteractiveDashboards #FabiPartnership #SponsoredByFabi

Andrew Bolis

36,504 Aufrufe • vor 10 Monaten