Video wird geladen...

Video konnte nicht geladen werden

Beim Laden dieses Videos ist ein Problem aufgetreten. Dies könnte an einem vorübergehenden Netzwerkproblem liegen oder das Video ist möglicherweise nicht verfügbar.

Validating your backend infrastructure requires traffic that mimics user behavior, but writing custom load-testing scripts that handle concurrency and specific user journeys is time consuming. See how these tasks are well suited for Gemini 3 Flash →

Google Cloud Tech

1,311,377 subscribers

18,097 Aufrufe • vor 7 Monaten •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

0 Kommentare

Keine Kommentare verfügbar

Kommentare vom Original-Post werden hier angezeigt

Ähnliche Videos

Listen up 🔊 We’ve made some updates to our Gemini Audio models and capabilities: — Gemini’s live speech-to-speech translation capability is rolling out in a beta experience to the Google Translate app, bringing you real-time audio translation that captures the nuance of human speech — Gemini 2.5 Flash and 2.5 Pro Text-to-Speech preview models bring improved adherence to style prompts, precision pacing with context-aware speed adjustments, and character voice consistency for multi-speaker scenarios — Gemini 2.5 Flash Native Audio is now updated, with improvements to handle complex workflows, navigate user instructions, and hold natural conversations

Listen up 🔊 We’ve made some updates to our Gemini Audio models and capabilities: — Gemini’s live speech-to-speech translation capability is rolling out in a beta experience to the Google Translate app, bringing you real-time audio translation that captures the nuance of human speech — Gemini 2.5 Flash and 2.5 Pro Text-to-Speech preview models bring improved adherence to style prompts, precision pacing with context-aware speed adjustments, and character voice consistency for multi-speaker scenarios — Gemini 2.5 Flash Native Audio is now updated, with improvements to handle complex workflows, navigate user instructions, and hold natural conversations

Google AI

1,093,874 Aufrufe • vor 8 Monaten

If your online dynasty uses custom coaches, you'll likely have some really solid coordinators in the carousel after your first season. The head coaches that user teams replace come back as OC and DC options for 0 dynasty points. And they stay free for the whole 3 year contract. But you only have one shot at this. Here's how it works:

If your online dynasty uses custom coaches, you'll likely have some really solid coordinators in the carousel after your first season. The head coaches that user teams replace come back as OC and DC options for 0 dynasty points. And they stay free for the whole 3 year contract. But you only have one shot at this. Here's how it works:

Dominate CFB Dynasty

21,815 Aufrufe • vor 18 Tagen

Websites should have personalized UIs for every single user, not the same UI for everyone (with Magnus Müller from Browser Use) - Legacy systems (like banks) are already being reimagined with better UIs that fill out the ugly backend forms automatically - First-time Photoshop users face overwhelming interfaces that could be simplified based on their experience level - AI can generate custom UIs on the fly based on user context, preferences, and needs - The future: Hundreds of different UIs for the same website instead of one UI for millions of users - "Generative UIs" could serve as an intermediary between websites and what users actually see

Websites should have personalized UIs for every single user, not the same UI for everyone (with Magnus Müller from Browser Use) - Legacy systems (like banks) are already being reimagined with better UIs that fill out the ugly backend forms automatically - First-time Photoshop users face overwhelming interfaces that could be simplified based on their experience level - AI can generate custom UIs on the fly based on user context, preferences, and needs - The future: Hundreds of different UIs for the same website instead of one UI for millions of users - "Generative UIs" could serve as an intermediary between websites and what users actually see

Shane Thomas

15,260 Aufrufe • vor 1 Jahr

"The future of AI is agentic. That includes browsers!" Imagine having an AI agent in your browser that can help you complete complex tasks, answer your questions, and streamline your workflow. Today I'm thrilled to share a sneak peek at Project Mariner, a cutting-edge research collaboration between Chrome and Google DeepMind, exploring the future of agentic AI within the browser! Building on the power of Gemini 2.0, Mariner envisions AI agents seamlessly guiding users through online tasks, streamlining workflows and enriching browsing experiences. Imagine having an intelligent co-pilot in your browser, anticipating your needs and proactively offering assistance. We're in the early stages of experimentation, focusing on core functionalities like understanding user intent, automating actions, and providing personalized recommendations. This prototype leverages Gemini's advanced natural language understanding and reasoning capabilities to interpret user requests, both typed and spoken. Mariner can then interact with web pages, retrieve information, and even perform actions like filling out forms or navigating to specific sites. For example, a user could simply ask "Find me a job near me," and Mariner would understand the request, navigate to a relevant job search site, and tailor the search based on the user's location and preferences. This is just one example of how we're exploring Gemini 2.0's potential to unlock agentic experiences through a series of prototypes, including: 1. Agents with multimodal reasoning: Project Astra, our research prototype exploring the capabilities of a universal AI assistant, is enhanced by Gemini 2.0. 2. Agents that can help you accomplish complex tasks: Project Mariner itself focuses on the future of human-agent interaction within the browser. 3. Agents for developers: Jules is an experimental AI-powered coding agent that integrates directly into a GitHub workflow. 4. Agents applied across domains: We're exploring agents for navigating video games and even applying Gemini 2.0's spatial reasoning to robotics. We believe that integrating AI agents directly into the browser has the potential to revolutionize how we interact with the web. Project Mariner aims to make browsing more intuitive, efficient, and personalized. By understanding user context and proactively offering assistance, Mariner can simplify complex tasks, save users time, and empower them to achieve more online. This aligns perfectly with the vision of Gemini 2.0 to create more helpful and intuitive AI experiences. We’re currently testing Mariner with a small group of trusted users to gather feedback and refine the user experience. We believe that this technology holds immense potential to transform the way we browse and interact with information online.

"The future of AI is agentic. That includes browsers!" Imagine having an AI agent in your browser that can help you complete complex tasks, answer your questions, and streamline your workflow. Today I'm thrilled to share a sneak peek at Project Mariner, a cutting-edge research collaboration between Chrome and Google DeepMind, exploring the future of agentic AI within the browser! Building on the power of Gemini 2.0, Mariner envisions AI agents seamlessly guiding users through online tasks, streamlining workflows and enriching browsing experiences. Imagine having an intelligent co-pilot in your browser, anticipating your needs and proactively offering assistance. We're in the early stages of experimentation, focusing on core functionalities like understanding user intent, automating actions, and providing personalized recommendations. This prototype leverages Gemini's advanced natural language understanding and reasoning capabilities to interpret user requests, both typed and spoken. Mariner can then interact with web pages, retrieve information, and even perform actions like filling out forms or navigating to specific sites. For example, a user could simply ask "Find me a job near me," and Mariner would understand the request, navigate to a relevant job search site, and tailor the search based on the user's location and preferences. This is just one example of how we're exploring Gemini 2.0's potential to unlock agentic experiences through a series of prototypes, including: 1. Agents with multimodal reasoning: Project Astra, our research prototype exploring the capabilities of a universal AI assistant, is enhanced by Gemini 2.0. 2. Agents that can help you accomplish complex tasks: Project Mariner itself focuses on the future of human-agent interaction within the browser. 3. Agents for developers: Jules is an experimental AI-powered coding agent that integrates directly into a GitHub workflow. 4. Agents applied across domains: We're exploring agents for navigating video games and even applying Gemini 2.0's spatial reasoning to robotics. We believe that integrating AI agents directly into the browser has the potential to revolutionize how we interact with the web. Project Mariner aims to make browsing more intuitive, efficient, and personalized. By understanding user context and proactively offering assistance, Mariner can simplify complex tasks, save users time, and empower them to achieve more online. This aligns perfectly with the vision of Gemini 2.0 to create more helpful and intuitive AI experiences. We’re currently testing Mariner with a small group of trusted users to gather feedback and refine the user experience. We believe that this technology holds immense potential to transform the way we browse and interact with information online.

Addy Osmani

29,518 Aufrufe • vor 1 Jahr

Here's my new episode with Alex Albert, who shared an inside look at how Anthropic is building the next Claude. We talked about how the research team: → Plans for the model and harness together → Uses Claude to turn user feedback into evals → Trains Claude's character & personality Some quotes from Alex: "We use Claude to cluster user feedback, find top themes, and create synthetic versions of user problems that we then turn into evals." "We need to think about how the model is exposed through all our surfaces, whether it's API or Claude Code or Cowork. The product has a blend with the model and that affects your end user's experience." ""As these things become agents running tasks for a long time and making judgment decisions, what its character is and what it cares about are very important." 📌 Watch now: Thanks to our sponsors: Wispr Flow: Don't type, just speak Oceans: Hire AI-native executive assistants

Here's my new episode with Alex Albert, who shared an inside look at how Anthropic is building the next Claude. We talked about how the research team: → Plans for the model and harness together → Uses Claude to turn user feedback into evals → Trains Claude's character & personality Some quotes from Alex: "We use Claude to cluster user feedback, find top themes, and create synthetic versions of user problems that we then turn into evals." "We need to think about how the model is exposed through all our surfaces, whether it's API or Claude Code or Cowork. The product has a blend with the model and that affects your end user's experience." ""As these things become agents running tasks for a long time and making judgment decisions, what its character is and what it cares about are very important." 📌 Watch now: Thanks to our sponsors: Wispr Flow: Don't type, just speak Oceans: Hire AI-native executive assistants

Peter Yang

95,921 Aufrufe • vor 3 Monaten

The lack of "feature design" is why so many products over time feel hollow or messy. This isn't visual design. This isn't architectural design. I thought that a short video lecture of what feature design is and a real case study of applying it in Ghostty would be helpful. Feature design is the planning step behind how you're going to solve one or more user problems with a product feature: what that feature looks like, how it feels, and not just how its going to tactically solve these specific problems, but how that solution is going to interface with the edges of other features that currently exist or are planned to exist in the future.

The lack of "feature design" is why so many products over time feel hollow or messy. This isn't visual design. This isn't architectural design. I thought that a short video lecture of what feature design is and a real case study of applying it in Ghostty would be helpful. Feature design is the planning step behind how you're going to solve one or more user problems with a product feature: what that feature looks like, how it feels, and not just how its going to tactically solve these specific problems, but how that solution is going to interface with the edges of other features that currently exist or are planned to exist in the future.

Mitchell Hashimoto

156,456 Aufrufe • vor 8 Monaten

Really happy to see the interest around our “Hands-on with Gemini” video. In our developer blog yesterday, we broke down how Gemini was used to create it. We gave Gemini sequences of different modalities — image and text in this case — and had it respond by predicting what might come next. Devs can try similar things when access to Pro opens on 12/13 🚀. The knitting demo used Ultra⚡ All the user prompts and outputs in the video are real, shortened for brevity. The video illustrates what the multimodal user experiences built with Gemini could look like. We made it to inspire developers. When you’re building an app, you can get similar results (there’s always some variability with LLMs) by prompting Gemini with an instruction that allows the user to "configure" the behavior of the model, like inputting “you are an expert in science …” before a user can engage in the same kind of back and forth dialogue. Here’s a clip of what this looks like in AI Studio with Gemini Pro. We’ve come a long way since Flamingo 🦩 & PALI, looking forward to seeing what people build with it!

Really happy to see the interest around our “Hands-on with Gemini” video. In our developer blog yesterday, we broke down how Gemini was used to create it. We gave Gemini sequences of different modalities — image and text in this case — and had it respond by predicting what might come next. Devs can try similar things when access to Pro opens on 12/13 🚀. The knitting demo used Ultra⚡ All the user prompts and outputs in the video are real, shortened for brevity. The video illustrates what the multimodal user experiences built with Gemini could look like. We made it to inspire developers. When you’re building an app, you can get similar results (there’s always some variability with LLMs) by prompting Gemini with an instruction that allows the user to "configure" the behavior of the model, like inputting “you are an expert in science …” before a user can engage in the same kind of back and forth dialogue. Here’s a clip of what this looks like in AI Studio with Gemini Pro. We’ve come a long way since Flamingo 🦩 & PALI, looking forward to seeing what people build with it!

Oriol Vinyals

180,995 Aufrufe • vor 2 Jahren

This One Technique Will Completely Change How You Play Run Defense in #CollegeFootball27 🔥 Ghost Walking is a conservative run defense that helps prevent offensive linemen from pancaking your user and creating explosive runs. How to do it: 1️⃣ Turn your user completely around before engaging the blocker 2️⃣ Wait for the RB to enter your area 3️⃣ Turn back around or dive at the runner to make the tackle Why it works: 🏈 Turning your back prevents the offensive line from triggering a pancake animation on your user. Instead of risking a huge gain every time you shoot a run, you're forcing the offense to consistently earn 3-5 yards at a time. It won't create as many tackles for loss, but if your goal is eliminating explosive runs, Ghost Walking is one of the most reliable techniques you can learn. 🎥 Full breakdown in the video. 📌 Bookmark this and follow Swolosimo for more College Football 27 tips 🔥

This One Technique Will Completely Change How You Play Run Defense in #CollegeFootball27 🔥 Ghost Walking is a conservative run defense that helps prevent offensive linemen from pancaking your user and creating explosive runs. How to do it: 1️⃣ Turn your user completely around before engaging the blocker 2️⃣ Wait for the RB to enter your area 3️⃣ Turn back around or dive at the runner to make the tackle Why it works: 🏈 Turning your back prevents the offensive line from triggering a pancake animation on your user. Instead of risking a huge gain every time you shoot a run, you're forcing the offense to consistently earn 3-5 yards at a time. It won't create as many tackles for loss, but if your goal is eliminating explosive runs, Ghost Walking is one of the most reliable techniques you can learn. 🎥 Full breakdown in the video. 📌 Bookmark this and follow Swolosimo for more College Football 27 tips 🔥

Swolosimo

16,352 Aufrufe • vor 1 Monat

Better/faster/cheaper voice AI turn detection with Gemini 2.0 The code that determines when the agent should respond to the user is some of the most important code in your voice AI agent. The technical terms for this job are "turn detection" or "phrase endpointing." If the voice AI responds before the user has finished their thought, the conversation is choppy and unproductive. If the AI waits too long, the conversation is slow and frustrating. There are a number of ways to approach this. You can: 1. Use a fast "voice activity detection" model to detect pauses in speech. Respond when the user pauses. 2. Use a specialized phrase endpointing model that operates on transcribed text, pattern-matching on text semantics. 3. Train a specialized phrase endpointing model that operates directly on audio. 4. Leverage the native audio capabilities of a SOTA LLM like Gemini 2.0. We've benchmarked all four of these, and Gemini 2.0 currently beats other approaches. Using Gemini is also cheaper than transcribing the audio separately using a transcription service or model. Here's a short video showing Gemini phrase endpointing in two scenarios. First, correctly handling pauses in natural conversation. Second, requesting a phone number (which is a common activity in a use case like customer support). You can see the Completeness check lines in the terminal output, printed each time Gemini processes a chunk of audio.

Better/faster/cheaper voice AI turn detection with Gemini 2.0 The code that determines when the agent should respond to the user is some of the most important code in your voice AI agent. The technical terms for this job are "turn detection" or "phrase endpointing." If the voice AI responds before the user has finished their thought, the conversation is choppy and unproductive. If the AI waits too long, the conversation is slow and frustrating. There are a number of ways to approach this. You can: 1. Use a fast "voice activity detection" model to detect pauses in speech. Respond when the user pauses. 2. Use a specialized phrase endpointing model that operates on transcribed text, pattern-matching on text semantics. 3. Train a specialized phrase endpointing model that operates directly on audio. 4. Leverage the native audio capabilities of a SOTA LLM like Gemini 2.0. We've benchmarked all four of these, and Gemini 2.0 currently beats other approaches. Using Gemini is also cheaper than transcribing the audio separately using a transcription service or model. Here's a short video showing Gemini phrase endpointing in two scenarios. First, correctly handling pauses in natural conversation. Second, requesting a phone number (which is a common activity in a use case like customer support). You can see the Completeness check lines in the terminal output, printed each time Gemini processes a chunk of audio.

kwindla

64,190 Aufrufe • vor 1 Jahr

NORAH O'DONNELL: So why do we need to test our nuclear weapons? US PRESIDENT TRUMP: Well, because you have to see how they work, you know. You do have to, and the reason I'm saying testing is because Russia announced that they're gonna be doing a test. If you noticed, North Korea is testing constantly, other countries are testing. We're the only country that doesn't test, and I don't wanna be the only country that doesn't test. NORAH O'DONNELL: Are you saying that after more than 30 years, the United States is going to start detonating nuclear weapons? US PRESIDENT TRUMP: I'm saying that we're going to test nuclear weapons like other countries do, yes. NORAH O'DONNELL: But the only country that is testing nuclear weapons is North Korea. China and Russia are not... US PRESIDENT TRUMP: No, no. Russia is testing nuclear weapons. And China is testing them too. You just don't know about it. NORAH O'DONNELL: That would be certainly newsworthy. My understanding is that what Russia did recently was test essentially the delivery system for nuclear weapons. Essentially - missiles. Which we can do that, but not with nuclear warheads. US PRESIDENT TRUMP: Russia is testing and China is testing, but they don't talk about it, you know. We're an open society, we're different. We talk about it, we have to talk about it. Because otherwise you people gonna report. They don't have reporters that gonna be writing about it, we do.

NORAH O'DONNELL: So why do we need to test our nuclear weapons? US PRESIDENT TRUMP: Well, because you have to see how they work, you know. You do have to, and the reason I'm saying testing is because Russia announced that they're gonna be doing a test. If you noticed, North Korea is testing constantly, other countries are testing. We're the only country that doesn't test, and I don't wanna be the only country that doesn't test. NORAH O'DONNELL: Are you saying that after more than 30 years, the United States is going to start detonating nuclear weapons? US PRESIDENT TRUMP: I'm saying that we're going to test nuclear weapons like other countries do, yes. NORAH O'DONNELL: But the only country that is testing nuclear weapons is North Korea. China and Russia are not... US PRESIDENT TRUMP: No, no. Russia is testing nuclear weapons. And China is testing them too. You just don't know about it. NORAH O'DONNELL: That would be certainly newsworthy. My understanding is that what Russia did recently was test essentially the delivery system for nuclear weapons. Essentially - missiles. Which we can do that, but not with nuclear warheads. US PRESIDENT TRUMP: Russia is testing and China is testing, but they don't talk about it, you know. We're an open society, we're different. We talk about it, we have to talk about it. Because otherwise you people gonna report. They don't have reporters that gonna be writing about it, we do.

Status-6 (Military & Conflict News)

19,263 Aufrufe • vor 10 Monaten

Gemini 3.5 Pro vs Grok 4.6 Please read entire post before coming to conclusion :) Both are present in arena first of all let me clear i really want that google cook great comeback but this model is disaster it make stuff that you didnot asked for , have crappy ui guys at this point we have grok with better ui compared to gemini > gemini was good in webdev now its bad > gemini 2.5 DT was good in 3d now its bad > gemini was less restrictive and prompt following in 2.5 pro was so good , now its corporate slop with template , at this time you will feel that there is template for coding , writing and researching all sucks I will write a long review if you guys want that , this is first time i am writing long tweet , i will now follow this for every big release

Gemini 3.5 Pro vs Grok 4.6 Please read entire post before coming to conclusion :) Both are present in arena first of all let me clear i really want that google cook great comeback but this model is disaster it make stuff that you didnot asked for , have crappy ui guys at this point we have grok with better ui compared to gemini > gemini was good in webdev now its bad > gemini 2.5 DT was good in 3d now its bad > gemini was less restrictive and prompt following in 2.5 pro was so good , now its corporate slop with template , at this time you will feel that there is template for coding , writing and researching all sucks I will write a long review if you guys want that , this is first time i am writing long tweet , i will now follow this for every big release

Chetaslua

39,085 Aufrufe • vor 27 Tagen

Learning from Human Demonstrations: Show the Robot How to Act! The pipeline is very similar to older experiments using Gemini & pi0 with LeRobot. Pi-zero runs locally, while Gemini Flash generates the affordances and the high-level task. (More details are in the thread.) The new component is learning from demonstrations via Gemini 2.5 Pro. I capture a video while demoing & take one of the last frames. Gemini 2.5 Pro then extracts the instructions & passes them to Gemini Flash to process the scene. The fun part is that there's no fancy insight that came from me; other than the days spent figuring out the right prompts. It's the bitter lesson hitting you in the face -> Enhanced Gemini capabilities make this possible. For example, Gemini Flash cannot do Russian doll stacking, but Gemini 2.5 Pro can do it consistently. The current limitation is low-level manipulation: - As you can see, I'm aligning the objects so they are easy to grasp using the same technique from the training data. I couldn't get Gemini Flash to consistently output an accurate grasping angle, and Gemini 1.5 Pro was too expensive and slow for real-time deployment. - Getting a symmetrical gripper should also help a lot. Adding rubber to the tips would probably also help prevent objects from slipping. Collecting & curating the data was the most time consuming & labor intensive part. Next, to improve low-level manipulation and make the system more real-time, I'm shifting to focus more on sims & synthetic data. This aligns better with my core competence. I'm open to tips and suggestions.

Learning from Human Demonstrations: Show the Robot How to Act! The pipeline is very similar to older experiments using Gemini & pi0 with LeRobot. Pi-zero runs locally, while Gemini Flash generates the affordances and the high-level task. (More details are in the thread.) The new component is learning from demonstrations via Gemini 2.5 Pro. I capture a video while demoing & take one of the last frames. Gemini 2.5 Pro then extracts the instructions & passes them to Gemini Flash to process the scene. The fun part is that there's no fancy insight that came from me; other than the days spent figuring out the right prompts. It's the bitter lesson hitting you in the face -> Enhanced Gemini capabilities make this possible. For example, Gemini Flash cannot do Russian doll stacking, but Gemini 2.5 Pro can do it consistently. The current limitation is low-level manipulation: - As you can see, I'm aligning the objects so they are easy to grasp using the same technique from the training data. I couldn't get Gemini Flash to consistently output an accurate grasping angle, and Gemini 1.5 Pro was too expensive and slow for real-time deployment. - Getting a symmetrical gripper should also help a lot. Adding rubber to the tips would probably also help prevent objects from slipping. Collecting & curating the data was the most time consuming & labor intensive part. Next, to improve low-level manipulation and make the system more real-time, I'm shifting to focus more on sims & synthetic data. This aligns better with my core competence. I'm open to tips and suggestions.

Shreyas Gite

22,555 Aufrufe • vor 1 Jahr

AI answers your questions in seconds, but behind that speed is something called inference—the compute-intensive process where trained models generate responses. At AWS, we've built custom chips like Trainium, intelligent routing systems, and unified infrastructure to make inference faster and more affordable. As AI agents handle complex multi-step tasks, inference accounts for 80-90% of AI computing power. We're engineering at planetary scale to keep those milliseconds reliable.

AI answers your questions in seconds, but behind that speed is something called inference—the compute-intensive process where trained models generate responses. At AWS, we've built custom chips like Trainium, intelligent routing systems, and unified infrastructure to make inference faster and more affordable. As AI agents handle complex multi-step tasks, inference accounts for 80-90% of AI computing power. We're engineering at planetary scale to keep those milliseconds reliable.

Amazon Web Services

27,021 Aufrufe • vor 6 Monaten

.Tucker Carlson Addresses the Mental Health Crisis: 'It's a Crime' to Only Treat Patients With Pills "It [anxiety] is a warning that you are not living in a way that brings you peace. So why don't we just pause for a second and go through how you're living? How are your relationships with other people? Are you drinking too much? Do you have a fulfilling job? Are you getting fresh air in nature? How about sunlight? Are you spending your entire life behind a screen?" asked Tucker Carlson. "Maybe that's why you're feeling anxious! None of those factors are ever addressed," he lamented. "People who are addicted to pharmaceuticals prescribed faithfully by their doctors, who never check in to see how the patient is doing. They just keep writing these scripts. People should go to jail for that — and I mean it."

.Tucker Carlson Addresses the Mental Health Crisis: 'It's a Crime' to Only Treat Patients With Pills "It [anxiety] is a warning that you are not living in a way that brings you peace. So why don't we just pause for a second and go through how you're living? How are your relationships with other people? Are you drinking too much? Do you have a fulfilling job? Are you getting fresh air in nature? How about sunlight? Are you spending your entire life behind a screen?" asked Tucker Carlson. "Maybe that's why you're feeling anxious! None of those factors are ever addressed," he lamented. "People who are addicted to pharmaceuticals prescribed faithfully by their doctors, who never check in to see how the patient is doing. They just keep writing these scripts. People should go to jail for that — and I mean it."

The Vigilant Fox 🦊

642,463 Aufrufe • vor 3 Jahren

Introducing Kiro, an all-new agentic IDE that has a chance to transform how developers build software. Let me highlight three key innovations that make Kiro special: 1 - Kiro introduces spec-driven development, helping developers express their intent clearly through natural language specifications and architecture diagrams for complex features. This comprehensive context helps Kiro’s AI agents deliver better results with fewer iterations. 2 - Kiro features intelligent agent hooks that automatically handle critical but time-consuming tasks like generating documentation, writing tests, and optimizing performance. These hooks work in the background, triggered by events like saving files or making commits. It’s like having an experienced developer constantly reviewing your work and handling the maintenance tasks that often get delayed. 3 - Kiro provides a purpose-built interface that adapts to how developers work. Whether you prefer chat interactions or working with specifications, Kiro supports your workflow while keeping you in control of the development process. Kiro is really good at "vibe coding" but goes well beyond that. While other AI coding assistants might help you prototype quickly, Kiro helps you take those prototypes all the way to production by following a mature, structured development process out of the box. This means developers can spend less time on boilerplate code and more time where it matters most – innovating and building solutions that customers will love. Starting today, Kiro is available for free during preview and supports most popular programming languages. Here’s how to get started with Kiro today: Excited to see how developers use Kiro, and to work with the developer community to continue to shape Kiro moving forward.

Introducing Kiro, an all-new agentic IDE that has a chance to transform how developers build software. Let me highlight three key innovations that make Kiro special: 1 - Kiro introduces spec-driven development, helping developers express their intent clearly through natural language specifications and architecture diagrams for complex features. This comprehensive context helps Kiro’s AI agents deliver better results with fewer iterations. 2 - Kiro features intelligent agent hooks that automatically handle critical but time-consuming tasks like generating documentation, writing tests, and optimizing performance. These hooks work in the background, triggered by events like saving files or making commits. It’s like having an experienced developer constantly reviewing your work and handling the maintenance tasks that often get delayed. 3 - Kiro provides a purpose-built interface that adapts to how developers work. Whether you prefer chat interactions or working with specifications, Kiro supports your workflow while keeping you in control of the development process. Kiro is really good at "vibe coding" but goes well beyond that. While other AI coding assistants might help you prototype quickly, Kiro helps you take those prototypes all the way to production by following a mature, structured development process out of the box. This means developers can spend less time on boilerplate code and more time where it matters most – innovating and building solutions that customers will love. Starting today, Kiro is available for free during preview and supports most popular programming languages. Here’s how to get started with Kiro today: Excited to see how developers use Kiro, and to work with the developer community to continue to shape Kiro moving forward.

Andy Jassy

668,263 Aufrufe • vor 1 Jahr

It truly is unfathomable that Synk sits at sub $3M MC. With what is being built. $SYNK bridges the gaps on where it's predecessors have failed. What $SYNK offers is more complex than 70% of what I see trading. The time is now here, SynkOS is almost here. Now I'm confident with saying Synk is bottomed here and offering huge potential. $Synk is capable of hosting a multitude of dApp's, ONSIT tools and much more that we we see rolled out. The release of the DeOS is far from the end of the line. Now, does hosting multiple dApps from integrated partnerships jeopardize security integrity? No! As the infrastructure is designed to host each application in isolation. What traffic can $SYNK OS handle. Well, synk is built with highly scalable infrastructure. Kubernetes auto scales dependent on workload. So, user acquisition is infinite to a degree. "As part of this exciting trajectory for $Synk, we’re also preparing the release of Osynk, your personal AI-powered agent designed to trace and consolidate all your online activity and information left on the web." We are aligning all partnerships ahead of the DeOS launch. For those that trusted the process, you're appreciated. For the doubters ... cope!

It truly is unfathomable that Synk sits at sub $3M MC. With what is being built. $SYNK bridges the gaps on where it's predecessors have failed. What $SYNK offers is more complex than 70% of what I see trading. The time is now here, SynkOS is almost here. Now I'm confident with saying Synk is bottomed here and offering huge potential. $Synk is capable of hosting a multitude of dApp's, ONSIT tools and much more that we we see rolled out. The release of the DeOS is far from the end of the line. Now, does hosting multiple dApps from integrated partnerships jeopardize security integrity? No! As the infrastructure is designed to host each application in isolation. What traffic can $SYNK OS handle. Well, synk is built with highly scalable infrastructure. Kubernetes auto scales dependent on workload. So, user acquisition is infinite to a degree. "As part of this exciting trajectory for $Synk, we’re also preparing the release of Osynk, your personal AI-powered agent designed to trace and consolidate all your online activity and information left on the web." We are aligning all partnerships ahead of the DeOS launch. For those that trusted the process, you're appreciated. For the doubters ... cope!

🇦🇺🌌 Čhenž_Ťradeš 🌌🇦🇺

14,315 Aufrufe • vor 1 Jahr

Kled Version 3 is coming. Over $20M+ in rewards will be paid directly to users from leading AI labs across robotics, legal services, image and video generation, world modeling, and more. In the last seven days, we’ve received inbound data requests from several decacorn AI labs and enterprises for datasets our human data marketplace is uniquely positioned to provide. Since receiving the specs for these requests, we now have a much better picture and understanding of how to reshape the systems that collect this data, so here’s what’s coming: 1. A fully redesigned home experience: The home feed is being rebuilt to surface the highest-value, most relevant tasks for each user, similar to how Uber Eats surfaces top restaurants. The goal is to turn every user into their most effective version as a data contributor. 2. Automated quality enforcement at scale: New ML systems are being built to evaluate task-specific requirements in real time. For example, if a task requires “two hands visible on camera at all times,” any video that fails that spec will be automatically rejected. This logic will apply across thousands of tasks and specifications using a general ML. 3. Kled Shop: Some tasks require better capture hardware. We’re introducing Kled Shop, where users can redeem points or tokens for equipment like Meta glasses, drones, and other tools. Points and tokens can be converted directly from payouts. 4. Partner-run data labeling and evaluation work: Some of our partners operate high-paying data labeling and model evaluation programs. We’re integrating their workflows directly into Kled so qualified users can access these roles in one place. These jobs are owned and managed by our partners. Kled’s role is to route the right people to the right work. Some opportunities pay $50–$1,000 per hour depending on expertise. 5. Global payouts and localization: We’re partnering with a major payment processor to enable cashouts in users’ native currencies. This unlocks broader global participation. Multi-language support is also coming to accelerate user growth. This full suite of tools will be rolling out soon, directly to Kled users. Top earners are currently making ~$7,000 per month. With this update, we should see the first ~$10,000 per month earner.

Kled Version 3 is coming. Over $20M+ in rewards will be paid directly to users from leading AI labs across robotics, legal services, image and video generation, world modeling, and more. In the last seven days, we’ve received inbound data requests from several decacorn AI labs and enterprises for datasets our human data marketplace is uniquely positioned to provide. Since receiving the specs for these requests, we now have a much better picture and understanding of how to reshape the systems that collect this data, so here’s what’s coming: 1. A fully redesigned home experience: The home feed is being rebuilt to surface the highest-value, most relevant tasks for each user, similar to how Uber Eats surfaces top restaurants. The goal is to turn every user into their most effective version as a data contributor. 2. Automated quality enforcement at scale: New ML systems are being built to evaluate task-specific requirements in real time. For example, if a task requires “two hands visible on camera at all times,” any video that fails that spec will be automatically rejected. This logic will apply across thousands of tasks and specifications using a general ML. 3. Kled Shop: Some tasks require better capture hardware. We’re introducing Kled Shop, where users can redeem points or tokens for equipment like Meta glasses, drones, and other tools. Points and tokens can be converted directly from payouts. 4. Partner-run data labeling and evaluation work: Some of our partners operate high-paying data labeling and model evaluation programs. We’re integrating their workflows directly into Kled so qualified users can access these roles in one place. These jobs are owned and managed by our partners. Kled’s role is to route the right people to the right work. Some opportunities pay $50–$1,000 per hour depending on expertise. 5. Global payouts and localization: We’re partnering with a major payment processor to enable cashouts in users’ native currencies. This unlocks broader global participation. Multi-language support is also coming to accelerate user growth. This full suite of tools will be rolling out soon, directly to Kled users. Top earners are currently making ~$7,000 per month. With this update, we should see the first ~$10,000 per month earner.

Avi Patel

124,728 Aufrufe • vor 7 Monaten

i genuinely can't understand why this isn't the first thing every claude user builds... anthropic quietly shipped a folder system where claude loads specialized instructions on its own based on what you ask. no prompt engineering after setup. almost nobody uses it here's how it actually works... you drop a folder into your skills directory. inside: a SKILL.md that says "trigger this when the user asks about X". claude reads the description once at startup. next time you ask about X, it silently pulls in the whole skill - custom instructions, scripts, examples - like a specialist walking into the room 1. skill for your writing voice - loads only when you draft, never when you analyze 2. skill for your codebase conventions - loads only when you edit that repo, not others 3. skill for your accounting flow - loads only when you say invoice, receipt, or expense your context window stays empty until you need it. one claude behaves like 30 different specialists in one chat and you never manage the switching full breakdown in the article below i test things like this on myself and share the results. follow kai if you want to see what's next

i genuinely can't understand why this isn't the first thing every claude user builds... anthropic quietly shipped a folder system where claude loads specialized instructions on its own based on what you ask. no prompt engineering after setup. almost nobody uses it here's how it actually works... you drop a folder into your skills directory. inside: a SKILL.md that says "trigger this when the user asks about X". claude reads the description once at startup. next time you ask about X, it silently pulls in the whole skill - custom instructions, scripts, examples - like a specialist walking into the room 1. skill for your writing voice - loads only when you draft, never when you analyze 2. skill for your codebase conventions - loads only when you edit that repo, not others 3. skill for your accounting flow - loads only when you say invoice, receipt, or expense your context window stays empty until you need it. one claude behaves like 30 different specialists in one chat and you never manage the switching full breakdown in the article below i test things like this on myself and share the results. follow kai if you want to see what's next

kai

69,978 Aufrufe • vor 1 Monat

You can create an AI Agent that answers your email with a few clicks. 1. Go to ChatLLM ( 2. Click on AI Engineer 3. Select Create an AI Agent 4. Choose the Email Answering Agent ChatLLM will do the rest: it will code, test, and deploy the agent for you. You can also create a custom agent in English. The Agent Economy is coming (somebody should write a book and use this title.) We are going to see examples like this, times 1,000 in 2025. Just think about how many repetitive tasks you perform every day. Some of these tasks are involved enough that we couldn't automate them with pre-AI solutions. That's where we'll see agents explode, and I'm here for it.

You can create an AI Agent that answers your email with a few clicks. 1. Go to ChatLLM ( 2. Click on AI Engineer 3. Select Create an AI Agent 4. Choose the Email Answering Agent ChatLLM will do the rest: it will code, test, and deploy the agent for you. You can also create a custom agent in English. The Agent Economy is coming (somebody should write a book and use this title.) We are going to see examples like this, times 1,000 in 2025. Just think about how many repetitive tasks you perform every day. Some of these tasks are involved enough that we couldn't automate them with pre-AI solutions. That's where we'll see agents explode, and I'm here for it.

Santiago

79,974 Aufrufe • vor 1 Jahr

As a first step, we are launching NaijaCivicTech, an open source platform where Nigerian in tech curate and build tiny tools that solve specific Nigerian problems together this is not a startup, not a pitch deck, just working software in the open, built for Nigeria for ease. The current goal is to achieve two things: 1. Community to curate all existing tools that have attempted to solve a problem but are not well known. 2. Community to suggest problems, tools and project that solves a specific problem It's day 1, let's see how far we can go.

As a first step, we are launching NaijaCivicTech, an open source platform where Nigerian in tech curate and build tiny tools that solve specific Nigerian problems together this is not a startup, not a pitch deck, just working software in the open, built for Nigeria for ease. The current goal is to achieve two things: 1. Community to curate all existing tools that have attempted to solve a problem but are not well known. 2. Community to suggest problems, tools and project that solves a specific problem It's day 1, let's see how far we can go.

U N C L E BIGBAY ✨

33,864 Aufrufe • vor 5 Monaten