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Here is a quick look at the newly announced #DuetAI for Google Cloud which is an always-on AI collaborator that uses generative AI to: 👍 provide contextual code completion 👍 generate entire functions in real-time 👍 provide suggestions tuned to your code base 👍 assist you with code reviews... show more

Priyanka Vergadia

48,898 subscribers

12,809 просмотров • 3 лет назад •via X (Twitter)

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Фото профиля Marvin Ngesa ⚔️ 七 🏴‍☠️

Marvin Ngesa ⚔️ 七 🏴‍☠️3 лет назад

@googlecloud @wayne_gakuo

Фото профиля Raja Vijaya

Raja Vijaya3 лет назад

@googlecloud Registered. Thank you for sharing :)

Фото профиля Biswanath Giri

Biswanath Giri3 лет назад

@googlecloud Excited to use in google cloud

Фото профиля ኢድሪስ ኣደም

ኢድሪስ ኣደም3 лет назад

@googlecloud .

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Slather on personalization with your order of real-time suggestions. ☁️🍔💻 You can customize #AmazonQ Developer to generate even better code suggestions—based on your internal libraries, APIs, & more. It’s innovation—supersized, with the power of #AI. 👉

Slather on personalization with your order of real-time suggestions. ☁️🍔💻 You can customize #AmazonQ Developer to generate even better code suggestions—based on your internal libraries, APIs, & more. It’s innovation—supersized, with the power of #AI. 👉

Amazon Web Services

11,654 просмотров • 2 лет назад

This is kinda cool. I set up a Laracasts Playground that will allow you to interact with the code from the current video you're watching. Uses a container. Seems reasonably snappy. 👍

This is kinda cool. I set up a Laracasts Playground that will allow you to interact with the code from the current video you're watching. Uses a container. Seems reasonably snappy. 👍

Jeffrey Way

23,051 просмотров • 8 месяцев назад

Nobody is writing 90% of their code using AI. Here's the uncomfortable truth: The real productivity gain from using AI to write code is closer to 10%, nowhere near the 90% people claim. Sundar Pichai said in 2024 that 30% of the new code at Google was AI-generated. However, he went on to admit, during Lex Friedman's podcast, that engineering velocity had only increased by about 10%. AI-generated code isn't free code. It still has to be reviewed, tested, and made production-ready. Optimizing a single step (code generation) doesn't boost output if bottlenecks shift elsewhere (code reviews). It doesn't matter how much code you generate if you can't keep up the review process. The solution: Automate as much as you can the review and verification of your code. I'm working with Sonar, who is sponsoring this post, and they will take care of the code quality and security analysis of your code: • They review over 300B lines of code every single day • They cover reliability, security, and maintainability for your code • You can integrate them into your CI/CD pipeline • You can install them in your IDE (I use their VSCode extension) • Support for more than 30 languages Here is a link so you can check them out:

Nobody is writing 90% of their code using AI. Here's the uncomfortable truth: The real productivity gain from using AI to write code is closer to 10%, nowhere near the 90% people claim. Sundar Pichai said in 2024 that 30% of the new code at Google was AI-generated. However, he went on to admit, during Lex Friedman's podcast, that engineering velocity had only increased by about 10%. AI-generated code isn't free code. It still has to be reviewed, tested, and made production-ready. Optimizing a single step (code generation) doesn't boost output if bottlenecks shift elsewhere (code reviews). It doesn't matter how much code you generate if you can't keep up the review process. The solution: Automate as much as you can the review and verification of your code. I'm working with Sonar, who is sponsoring this post, and they will take care of the code quality and security analysis of your code: • They review over 300B lines of code every single day • They cover reliability, security, and maintainability for your code • You can integrate them into your CI/CD pipeline • You can install them in your IDE (I use their VSCode extension) • Support for more than 30 languages Here is a link so you can check them out:

Santiago

296,750 просмотров • 1 год назад

Take a peek at Bard, an early experiment that lets you collaborate with generative AI to accelerate your ideas and fuel your curiosity. Bard is available in the U.S. and U.K. for now, and will expand to more countries and languages over time. Sign up →

Take a peek at Bard, an early experiment that lets you collaborate with generative AI to accelerate your ideas and fuel your curiosity. Bard is available in the U.S. and U.K. for now, and will expand to more countries and languages over time. Sign up →

Google

276,521 просмотров • 3 лет назад

Google just did it again. They just launched "Google Skills" a free platform to turn anyone into an AI expert. 3,000+ courses, labs & certificates from Google Cloud, DeepMind, and Grow with Google all in one place. → Learn AI, data, and coding from real Google engineers → Earn credentials that actually get you hired → Build hands-on projects with Gemini Code Assist → Compete on global leaderboards and share your wins No paywalls. No BS. Just world-class AI education free. This might be the biggest AI upskilling move of the decade. 👉

Google just did it again. They just launched "Google Skills" a free platform to turn anyone into an AI expert. 3,000+ courses, labs & certificates from Google Cloud, DeepMind, and Grow with Google all in one place. → Learn AI, data, and coding from real Google engineers → Earn credentials that actually get you hired → Build hands-on projects with Gemini Code Assist → Compete on global leaderboards and share your wins No paywalls. No BS. Just world-class AI education free. This might be the biggest AI upskilling move of the decade. 👉

Alex Veremeyenko

41,961 просмотров • 11 месяцев назад

🚨 Big news: Google just launched Google Skills... giving you access to the same content universities charge $50K+ is now open to everyone. Here’s how it works: - Go to - Pick any AI skill you want to learn - Learn through 700+ hands-on labs with real Google Cloud tools -Earn Google Skill Badges to showcase your expertise ... recruiters actively look for these - Work toward certifications that rank among the highest-paying in IT What’s inside: - 3,000+ AI courses from Google Cloud, DeepMind & Google Edu - $500 in free cloud credits to practice - Built-in Gemini Code Assist - Certificates employers actually recognize (82% hiring preference) Like, REPOST

🚨 Big news: Google just launched Google Skills... giving you access to the same content universities charge $50K+ is now open to everyone. Here’s how it works: - Go to - Pick any AI skill you want to learn - Learn through 700+ hands-on labs with real Google Cloud tools -Earn Google Skill Badges to showcase your expertise ... recruiters actively look for these - Work toward certifications that rank among the highest-paying in IT What’s inside: - 3,000+ AI courses from Google Cloud, DeepMind & Google Edu - $500 in free cloud credits to practice - Built-in Gemini Code Assist - Certificates employers actually recognize (82% hiring preference) Like, REPOST

Beginnersblog

142,634 просмотров • 11 месяцев назад

Reviewing AI-generated code is the new bottleneck. Writing code was slow before. Now, in a few minutes, you can generate virtually unlimited lines of code using AI. But developers are now spending 70% of their time checking that code. That's the new bottleneck. I've been using Cline, and they have a feature that actually helps with this: You can click a button and have Cline generate an inline explanation for every single line of AI-generated code. Take a look at the attached video. What it does: 1. You can read the code and the explanation together 2. You don't lose context while reviewing code 3. You understand the "why" behind each change And here is the best part: It works on any git diff. You can use it to review PRs, understand commits from other people, or catch up on a codebase you haven't touched in a while.

Reviewing AI-generated code is the new bottleneck. Writing code was slow before. Now, in a few minutes, you can generate virtually unlimited lines of code using AI. But developers are now spending 70% of their time checking that code. That's the new bottleneck. I've been using Cline, and they have a feature that actually helps with this: You can click a button and have Cline generate an inline explanation for every single line of AI-generated code. Take a look at the attached video. What it does: 1. You can read the code and the explanation together 2. You don't lose context while reviewing code 3. You understand the "why" behind each change And here is the best part: It works on any git diff. You can use it to review PRs, understand commits from other people, or catch up on a codebase you haven't touched in a while.

Santiago

64,438 просмотров • 10 месяцев назад

Let's face it: AI can check your code 100x faster and catch 10x more issues than you can. "Code reviews" as a widespread practice is not coming back. There are only two reasons we should consider code reviews today: 1. To transfer knowledge within a team. 2. To ensure AI didn't miss critical aspects in the code. We are getting closer to a point where manually reviewing code will be as relevant as punching holes in a punch card. Here is one idea for you:

Let's face it: AI can check your code 100x faster and catch 10x more issues than you can. "Code reviews" as a widespread practice is not coming back. There are only two reasons we should consider code reviews today: 1. To transfer knowledge within a team. 2. To ensure AI didn't miss critical aspects in the code. We are getting closer to a point where manually reviewing code will be as relevant as punching holes in a punch card. Here is one idea for you:

Santiago

48,783 просмотров • 1 год назад

I'm teaching a new course! AI Python for Beginners is a series of four short courses that teach anyone to code, regardless of current technical skill. We are offering these courses free for a limited time. Generative AI is transforming coding. This course teaches coding in a way that’s aligned with where the field is going, rather than where it has been: (1) AI as a Coding Companion. Experienced coders are using AI to help write snippets of code, debug code, and the like. We embrace this approach and describe best-practices for coding with a chatbot. Throughout the course, you'll have access to an AI chatbot that will be your own coding companion that can assist you every step of the way as you code. (2) Learning by Building AI Applications. You'll write code that interacts with large language models to quickly create fun applications to customize poems, write recipes, and manage a to-do list. This hands-on approach helps you see how writing code that calls on powerful AI models will make you more effective in your work and personal projects. With this approach, beginning programmers can learn to do useful things with code far faster than they could have even a year ago. Knowing a little bit of coding is increasingly helping people in job roles other than software engineers. For example, I've seen a marketing professional write code to download web pages and use generative AI to derive insights; a reporter write code to flag important stories; and an investor automate the initial drafts of contracts. With this course you’ll be equipped to automate repetitive tasks, analyze data more efficiently, and leverage AI to enhance your productivity. If you are already an experienced developer, please help me spread the word and encourage your non-developer friends to learn a little bit of coding. I hope you'll check out the first two short courses here!

I'm teaching a new course! AI Python for Beginners is a series of four short courses that teach anyone to code, regardless of current technical skill. We are offering these courses free for a limited time. Generative AI is transforming coding. This course teaches coding in a way that’s aligned with where the field is going, rather than where it has been: (1) AI as a Coding Companion. Experienced coders are using AI to help write snippets of code, debug code, and the like. We embrace this approach and describe best-practices for coding with a chatbot. Throughout the course, you'll have access to an AI chatbot that will be your own coding companion that can assist you every step of the way as you code. (2) Learning by Building AI Applications. You'll write code that interacts with large language models to quickly create fun applications to customize poems, write recipes, and manage a to-do list. This hands-on approach helps you see how writing code that calls on powerful AI models will make you more effective in your work and personal projects. With this approach, beginning programmers can learn to do useful things with code far faster than they could have even a year ago. Knowing a little bit of coding is increasingly helping people in job roles other than software engineers. For example, I've seen a marketing professional write code to download web pages and use generative AI to derive insights; a reporter write code to flag important stories; and an investor automate the initial drafts of contracts. With this course you’ll be equipped to automate repetitive tasks, analyze data more efficiently, and leverage AI to enhance your productivity. If you are already an experienced developer, please help me spread the word and encourage your non-developer friends to learn a little bit of coding. I hope you'll check out the first two short courses here!

Andrew Ng

1,226,235 просмотров • 2 лет назад

Here is how to use Claude Code with Unity 6! 🤝 Unity has a native MCP server to let AI handle the boilerplate code while you focus on your game! 🤩 ➡️ Read more at: #unitytips #gamedev #unity3d #unity6 #ai

Here is how to use Claude Code with Unity 6! 🤝 Unity has a native MCP server to let AI handle the boilerplate code while you focus on your game! 🤩 ➡️ Read more at: #unitytips #gamedev #unity3d #unity6 #ai

Sunny Valley Studio

35,833 просмотров • 6 месяцев назад

New short course: Building Code Agents with Hugging Face smolagents! Learn how to build code agents in this course, created in collaboration with Hugging Face, and taught by Thomas Wolf, its co-founder and CSO, and m_ric, Hugging Face’s Project Lead on Agents. Tool-calling agents use LLMs to generate multiple function calls sequentially to complete a complex sequence of tasks. They generate one function call, execute it, observe, reason, and decide what to do next. Code agents take a different approach. They consolidate all these calls into a single block of code, letting the LLM lay out an entire action plan at once, which can be executed efficiently to provide more reliable results. You’ll learn how to code agents using smolagents, a lightweight agentic framework from Hugging Face. Along the way, you’ll learn how to run LLM-generated code safely and develop an evaluation system to optimize your code agent for production. In detail, you’ll learn: - How agentic systems have evolved, gaining greater levels of agency over time—and why code agents are a next step. - How code agents write their actions in code. - When code agents outperform function-calling agents. - How to run code agents safely in your system using a constrained Python interpreter and sandboxing using E2B. - To trace, debug, and assess the code agent to optimize its behaviours for complex requests. - How to build a research multi-agent system that can find information online and organize it into an interactive report. By the end of this course, you’ll know how to build and run code agents using smolagents, and deploy them safely with a structured evaluation system in your projects. Please sign up here!

New short course: Building Code Agents with Hugging Face smolagents! Learn how to build code agents in this course, created in collaboration with Hugging Face, and taught by Thomas Wolf, its co-founder and CSO, and m_ric, Hugging Face’s Project Lead on Agents. Tool-calling agents use LLMs to generate multiple function calls sequentially to complete a complex sequence of tasks. They generate one function call, execute it, observe, reason, and decide what to do next. Code agents take a different approach. They consolidate all these calls into a single block of code, letting the LLM lay out an entire action plan at once, which can be executed efficiently to provide more reliable results. You’ll learn how to code agents using smolagents, a lightweight agentic framework from Hugging Face. Along the way, you’ll learn how to run LLM-generated code safely and develop an evaluation system to optimize your code agent for production. In detail, you’ll learn: - How agentic systems have evolved, gaining greater levels of agency over time—and why code agents are a next step. - How code agents write their actions in code. - When code agents outperform function-calling agents. - How to run code agents safely in your system using a constrained Python interpreter and sandboxing using E2B. - To trace, debug, and assess the code agent to optimize its behaviours for complex requests. - How to build a research multi-agent system that can find information online and organize it into an interactive report. By the end of this course, you’ll know how to build and run code agents using smolagents, and deploy them safely with a structured evaluation system in your projects. Please sign up here!

Andrew Ng

127,724 просмотров • 1 год назад

AR GenAI by AR Code is transforming the food industry. Creating an AR experience for a dish can now start with a single photo. As shown in the video, a single dessert photo is converted into an AR-ready 3D model with realistic textures and depth. AR Code SaaS then instantly generates an AR QR Code to share the experience anywhere. Customers can launch it immediately with a quick QR Code scan. No app required. Photo → AI 3D generation → AR QR Code → Instant WebAR What once required specialized software, costly workflows, and advanced 3D skills is now becoming accessible in minutes. This is reshaping how restaurants and food brands create, publish, and distribute immersive content at scale. Learn more: Follow AR Code for updates. #ARGenAI #ARCode #FoodTech #RestaurantTech #ImageTo3D #ImageToAR #GenerativeAI #GenAI #AI3D #AI #3DFromImage #WebAR

AR GenAI by AR Code is transforming the food industry. Creating an AR experience for a dish can now start with a single photo. As shown in the video, a single dessert photo is converted into an AR-ready 3D model with realistic textures and depth. AR Code SaaS then instantly generates an AR QR Code to share the experience anywhere. Customers can launch it immediately with a quick QR Code scan. No app required. Photo → AI 3D generation → AR QR Code → Instant WebAR What once required specialized software, costly workflows, and advanced 3D skills is now becoming accessible in minutes. This is reshaping how restaurants and food brands create, publish, and distribute immersive content at scale. Learn more: Follow AR Code for updates. #ARGenAI #ARCode #FoodTech #RestaurantTech #ImageTo3D #ImageToAR #GenerativeAI #GenAI #AI3D #AI #3DFromImage #WebAR

Maxime Maisonneuve

21,170 просмотров • 8 месяцев назад

Before GenAI, prototyping an app, especially one powered by data or AI, meant hours of setup and boilerplate code before you could even test your idea. In this clip from the course Fast Prototyping of GenAI Apps with Streamlit, you’ll see how that changes. Watch how GenAI flips the development process, so instead of planning every step in advance, you start with intent and get working code in seconds. Learn to prototype faster, test more ideas, and go from concept to app. 👉 Take the course here: Snowflake Chanin Nantasenamat

Before GenAI, prototyping an app, especially one powered by data or AI, meant hours of setup and boilerplate code before you could even test your idea. In this clip from the course Fast Prototyping of GenAI Apps with Streamlit, you’ll see how that changes. Watch how GenAI flips the development process, so instead of planning every step in advance, you start with intent and get working code in seconds. Learn to prototype faster, test more ideas, and go from concept to app. 👉 Take the course here: Snowflake Chanin Nantasenamat

DeepLearning.AI

12,373 просмотров • 1 год назад

Hack from literally anywhere! 📲 Learn how to use Claude Code from your phone by setting up a remote terminal that never goes down so you can always access Cloud Code. Unlock the freedom to code at the airport, on the couch, in the shower, or on the toilet! Watch how I did it here:

Hack from literally anywhere! 📲 Learn how to use Claude Code from your phone by setting up a remote terminal that never goes down so you can always access Cloud Code. Unlock the freedom to code at the airport, on the couch, in the shower, or on the toilet! Watch how I did it here:

NetworkChuck

24,824 просмотров • 7 месяцев назад

Today, the FDA launched Elsa, a generative AI tool designed to help employees—from scientific reviewers to investigators—work more efficiently. This innovative tool modernizes agency functions and leverages AI capabilities to better serve the American people. Elsa in Action ➤ Accelerate clinical protocol reviews ➤ Shorten the time needed for scientific evaluations ➤ Identify high-priority inspections targets ➤ Perform faster label comparisons ➤ Summarize adverse events to support safety profile assessments ➤ Generate code to help develop databases for nonclinical applications

U.S. FDA

474,941 просмотров • 1 год назад

Introducing OpenReview An AI code review system I'm building to learn how real systems work. No noise. No generic comments. Just reviews that actually understand your code. Open source. Currently in build. Everything I'm exploring: • AI PR reviews with real context • Full repo indexing (embeddings + vector search) • Inline comments + detailed summaries • Similar code retrieval across your codebase • Smart diff-based re-indexing • Scalable workers + queue-based architecture … and a lot more.

Introducing OpenReview An AI code review system I'm building to learn how real systems work. No noise. No generic comments. Just reviews that actually understand your code. Open source. Currently in build. Everything I'm exploring: • AI PR reviews with real context • Full repo indexing (embeddings + vector search) • Inline comments + detailed summaries • Similar code retrieval across your codebase • Smart diff-based re-indexing • Scalable workers + queue-based architecture … and a lot more.

OPM

11,249 просмотров • 6 месяцев назад

How to build an AI SEO Loop with Claude Code. I just launched a Free course on how to setup Claude Code, Hermes, Codex or any agent to become your Chief SEO that gets you customers on autopilot. Comment "Loop" and I'll send an access in your DMs. You'll learn: - How to install the SEO Skill. - Audit and Fix your website through Google Search Console. - Find keywords that convert. - Publish content automatically. - Track your positions on Google and your AI visibility. - Get recommended by AI. - and more bonuses.

How to build an AI SEO Loop with Claude Code. I just launched a Free course on how to setup Claude Code, Hermes, Codex or any agent to become your Chief SEO that gets you customers on autopilot. Comment "Loop" and I'll send an access in your DMs. You'll learn: - How to install the SEO Skill. - Audit and Fix your website through Google Search Console. - Find keywords that convert. - Publish content automatically. - Track your positions on Google and your AI visibility. - Get recommended by AI. - and more bonuses.

Florian Darroman

24,104 просмотров • 3 месяцев назад

Today, I'm excited to launch Entelligence AI DeepReviews, the next generation AI-powered code reviews. Vibe coded PRs are not production ready often creating more subtle bugs throughout the codebase than before. Entelligence fixes this by understanding the entire codebase and flags bugs, regressions, and breakages across files before you ship. But it goes beyond review comments: ✅ Auto-generated docs with architecture diagrams ✅ Team Insights to improve process, not just code ✅ Real time code reviews within your editor If you're building or leading a dev team, this is what smarter, context-aware reviews look like. Try it out in the link below 👇

Today, I'm excited to launch Entelligence AI DeepReviews, the next generation AI-powered code reviews. Vibe coded PRs are not production ready often creating more subtle bugs throughout the codebase than before. Entelligence fixes this by understanding the entire codebase and flags bugs, regressions, and breakages across files before you ship. But it goes beyond review comments: ✅ Auto-generated docs with architecture diagrams ✅ Team Insights to improve process, not just code ✅ Real time code reviews within your editor If you're building or leading a dev team, this is what smarter, context-aware reviews look like. Try it out in the link below 👇

Aiswarya Sankar

96,309 просмотров • 1 год назад