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Imagine an AI application that can type anywhere you can and use the full context of what's on your screen. This is the application we all deserve (at least if you have macOS.) Check out Omnipilot. It's an app that works with every other macOS application and... uses Claude Sonet 3.5 in the background—it also supports Gemini and GPT-4o. Here is the idea: You can use the tool to ask questions about anything on your screen. Or you can use it to autocomplete the text you are typing. You don't need to copy and paste anymore or waste your time providing context to a model. It sees what you see. It works right where you are. That's pretty cool. Here are a couple of cool examples: • Use it to reply to an email • Use it in the terminal to autocomplete a command • Use it to finish a document • Use to send a message on Slack AI at the system level is bonkers. You can read a ton more on their Product Hunt launch page: Thanks to the Omnipilot team for collaborating with me on this post!show more

Santiago

448,124 subscribers

72,306 次观看 • 2 年前 •via X (Twitter)

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11 条评论

Mahesh Jamdade 的头像

Mahesh Jamdade2 年前

@OmnipilotAI That is a cool idea and great implementation.

Safari Web Extensions 的头像

Safari Web Extensions1 年前

Discover the top Safari web extensions to boost productivity, enhance workflow, and customize your browsing experience on Mac, iOS, and iPadOS.

Ibrahim Abdul-Hakim 的头像

Ibrahim Abdul-Hakim2 年前

@OmnipilotAI Nice, but how about privacy?

Santiago 的头像

Santiago2 年前

@OmnipilotAI Here is a comment from the maker of the app in Product Hunt:

🚀🇬🇧 Robert Pitt 的头像

🚀🇬🇧 Robert Pitt2 年前

@OmnipilotAI I have been thinking about this concept for a a few months now, achieving this through the accessibility's api's is also neat. Hope this grows into something larger so you can slash some of those prices

Troublemaker 的头像

Troublemaker2 年前

@OmnipilotAI I'm using Linux! I bet #phidata could do the job. Any idea?

Ayoub H. 的头像

Ayoub H.2 年前

@OmnipilotAI Will give it a try!

Colbert. Bitcoin Malaysia Conference 2024 ▚▘▚▘▚▘ 的头像

Colbert. Bitcoin Malaysia Conference 2024 ▚▘▚▘▚▘2 年前

@OmnipilotAI Nice

Ravi | ML Engineer 的头像

Ravi | ML Engineer2 年前

@OmnipilotAI I'm on windows still - those macbooks are pricey

Santiago 的头像

Santiago2 年前

@RaviDataMind @OmnipilotAI That they are.

Ism 的头像

Ism2 年前

@OmnipilotAI Seems cool

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Building with AI gets easier every day. Here is an open-source library that makes integrating AI into an application extremely easy: Star the repository! This library alone can make React the best front-end framework out there! There are a bunch of cool things I like about CopilotKit. Here are 3 of them: 1. It allows you to take any -powered agent and bring it into your application. (This is a brand-new feature!) 2. You can build an AI-powered chatbot in your application. The chatbot will have access to your context and can act on the application. 3. You can build a RAG workflow to process and answer questions from a real-time knowledge base. I recorded a video to show you how simple it is to make some of this happen. A few lines of code, and you are in business. Here is a link to the sample application: CopilotKit is open-source. You can self-host it. You can use it with any LLM. Thanks to the team for showing me their tool and collaborating with me on this post!

Santiago

108,835 次观看 • 2 年前

What do Zimbabweans need to know about the new Zimbabwean currency called the ZiG? Can Zimbabweans use the new currency called the ZiG to pay for your passport application? Can you use it to buy fuel at the service station? Can you use it to pay customs duty for your car at Beitbridge border post? Can you walk into a bank and use it to buy foreign exchange? Can you buy an airline ticket with it? Zimbabwe has the highest inflation in the world, will it come down after the introduction of the ZiG? The answer to all these questions is an unequivocal NO!

What do Zimbabweans need to know about the new Zimbabwean currency called the ZiG? Can Zimbabweans use the new currency called the ZiG to pay for your passport application? Can you use it to buy fuel at the service station? Can you use it to pay customs duty for your car at Beitbridge border post? Can you walk into a bank and use it to buy foreign exchange? Can you buy an airline ticket with it? Zimbabwe has the highest inflation in the world, will it come down after the introduction of the ZiG? The answer to all these questions is an unequivocal NO!

Hopewell Chin’ono

176,557 次观看 • 2 年前

I made the worlds best Clipboard for your AI Agents Its called Bluey and its a dumb pointer which you can use to give 10x better context to your agent And you can point at your screen, talk to it, and it will generate a really good annotated screenshot which you can now give to your AI Agent You can use it while designing your website You can use it while explaining something on your screen. And it understands you and you can be really vague about things like "move this" , modify the color "here" and it will understand what you are pointing at. Im loving using it and I built it for myself as I was tired of clicking screenshots all the time and attaching it to my codex or claude code sessions Now I can just point, speak or type and drag and drop it anywhere I am giving free access to it in the comments and I would love for you to try it out. Join the discord and I am sharing the download link there. By the way everything stays 100 percent local. No screenshots are shared anywhere!

I made the worlds best Clipboard for your AI Agents Its called Bluey and its a dumb pointer which you can use to give 10x better context to your agent And you can point at your screen, talk to it, and it will generate a really good annotated screenshot which you can now give to your AI Agent You can use it while designing your website You can use it while explaining something on your screen. And it understands you and you can be really vague about things like "move this" , modify the color "here" and it will understand what you are pointing at. Im loving using it and I built it for myself as I was tired of clicking screenshots all the time and attaching it to my codex or claude code sessions Now I can just point, speak or type and drag and drop it anywhere I am giving free access to it in the comments and I would love for you to try it out. Join the discord and I am sharing the download link there. By the way everything stays 100 percent local. No screenshots are shared anywhere!

Milind S

11,917 次观看 • 2 个月前

Google offers a AI-powered personal assistant that you can use for free. You can talk to it in real time, share your screen with it, and ask it to help you with any given task (sound on 👇). Surprisingly, not many people are using it. Here's how to use it:

Google offers a AI-powered personal assistant that you can use for free. You can talk to it in real time, share your screen with it, and ask it to help you with any given task (sound on 👇). Surprisingly, not many people are using it. Here's how to use it:

Mushtaq Bilal, PhD

44,549 次观看 • 1 年前

I asked Garry Tan how to use meta prompting to get better at AI: "My partners at YC Jared Friedman and Pete Koomen showed me how to do this. You can take almost anything that you do all the time and just drop it into a context window. And then say, “Here’s a bunch of inputs and outputs." And maybe you also add a bunch of notes. And then you tell it, “Write me a prompt that can act as an agent that takes this input and makes this output over here.” You can do this for almost any type of knowledge work. And you can even introspect. "What are things you notice that I did to convert this from the input to the output?”. And then you can just start using the prompt. Initially, it’s going to suck. Because it’s just not that smart yet. But what’s funny is now, I also use it to Iterate my writing. You can be very direct, "I would never say that", "Don’t say it like this", or "Oh, you used the long word there, use the short word". Just speak to it conversationally. And then when you're happy with the output, you can use that new output to make a new prompt. "Based on this conversation, give me a better initial prompt that incorporates all the things we talked about." And you can do this with literally everything. And in theory, there’s so much it applies to that people do day-to-day. You could use it for tweets. You could use it for editing podcasts. You can use it for pretty much everything. I have a folder of prompts that I use all the time. My YouTube prompt is on v27 or something. I'll go through this process with all the different max models. I'll use GPT 5.2 Pro. I’ll use Grok. I'll use Claude. Then, I’ll take all the outputs from all the models and put them into Claude and say "Here’s my prompt, here’s the output from four LLMs, including yourself. Rate each response and tell me what the pros and cons of each approach are." And I usually say "give it to me in numbered form". And then you can agree with one, disagree with two, tell it three is this or that. And then after that, you say given all of this, synthesize it."

I asked Garry Tan how to use meta prompting to get better at AI: "My partners at YC Jared Friedman and Pete Koomen showed me how to do this. You can take almost anything that you do all the time and just drop it into a context window. And then say, “Here’s a bunch of inputs and outputs." And maybe you also add a bunch of notes. And then you tell it, “Write me a prompt that can act as an agent that takes this input and makes this output over here.” You can do this for almost any type of knowledge work. And you can even introspect. "What are things you notice that I did to convert this from the input to the output?”. And then you can just start using the prompt. Initially, it’s going to suck. Because it’s just not that smart yet. But what’s funny is now, I also use it to Iterate my writing. You can be very direct, "I would never say that", "Don’t say it like this", or "Oh, you used the long word there, use the short word". Just speak to it conversationally. And then when you're happy with the output, you can use that new output to make a new prompt. "Based on this conversation, give me a better initial prompt that incorporates all the things we talked about." And you can do this with literally everything. And in theory, there’s so much it applies to that people do day-to-day. You could use it for tweets. You could use it for editing podcasts. You can use it for pretty much everything. I have a folder of prompts that I use all the time. My YouTube prompt is on v27 or something. I'll go through this process with all the different max models. I'll use GPT 5.2 Pro. I’ll use Grok. I'll use Claude. Then, I’ll take all the outputs from all the models and put them into Claude and say "Here’s my prompt, here’s the output from four LLMs, including yourself. Rate each response and tell me what the pros and cons of each approach are." And I usually say "give it to me in numbered form". And then you can agree with one, disagree with two, tell it three is this or that. And then after that, you say given all of this, synthesize it."

The Peel

51,632 次观看 • 5 个月前

I can't stop thinking about this... Michael Caine on his defining philosophy on life: Use the Difficulty As a young actor, he was rehearsing a play scene when a chair got stuck in the door and blocked his path. He told the other actor he couldn't get by the chair to enter the room in the scene. The actor's response: "Use the difficulty...if it's a comedy, fall over it, if it's a drama, pick it up and smash it." This idea—of using the difficulty—became a defining mantra for Michael Caine's life. "There's never anything so bad that you cannot use that difficulty...if you can use it a quarter of one percent to your advantage, you're ahead, you didn't let it get you down." This idea hit me hard... How can you use the difficulty you're currently facing? How can you embrace the struggle? How can you find flow through the friction? How can you sow the seeds of your light during the periods of darkness? As with everything in life, control the controllable: The difficulty is already there, you can't control it. You can control how you react to it. You can control your response to it. You can control your attitude towards it. Lesson: Difficulty is inevitable. Use it.

I can't stop thinking about this... Michael Caine on his defining philosophy on life: Use the Difficulty As a young actor, he was rehearsing a play scene when a chair got stuck in the door and blocked his path. He told the other actor he couldn't get by the chair to enter the room in the scene. The actor's response: "Use the difficulty...if it's a comedy, fall over it, if it's a drama, pick it up and smash it." This idea—of using the difficulty—became a defining mantra for Michael Caine's life. "There's never anything so bad that you cannot use that difficulty...if you can use it a quarter of one percent to your advantage, you're ahead, you didn't let it get you down." This idea hit me hard... How can you use the difficulty you're currently facing? How can you embrace the struggle? How can you find flow through the friction? How can you sow the seeds of your light during the periods of darkness? As with everything in life, control the controllable: The difficulty is already there, you can't control it. You can control how you react to it. You can control your response to it. You can control your attitude towards it. Lesson: Difficulty is inevitable. Use it.

Sahil Bloom

1,360,055 次观看 • 2 年前

Your Ai twin, that you can put on your work table or at the bed side. With a working touch screen, can connect / cast to a TV. Creates a fully dynamic UI for the task at hand. Works with All your docs, Email, Slack & 5000+ apps. What would you use it for ?

Your Ai twin, that you can put on your work table or at the bed side. With a working touch screen, can connect / cast to a TV. Creates a fully dynamic UI for the task at hand. Works with All your docs, Email, Slack & 5000+ apps. What would you use it for ?

Subhash Choudhary

27,602 次观看 • 2 年前

I vibe coded an application with Gemini 3 that let's you pick up a pencil and actually start drawing on a piece of paper. The assets are 3D which adds another layer of immersion just purely for fun. Try it here You can't start drawing until you literally click on the pencil to pick it up. You can also switch to a marker or use the eraser on the pencil. If you don't like the drawing you can crumple the paper and throw it in the trash. It will then place a new piece of paper on the table and you have to pick up the pencil again to start drawing again. I added a learn section on the app that links to youtube channels where you can also learn how to draw. It's quite fun to use, it's basically like using a super simplified version of photoshop or paint. It works with a wacom tablet, just can't seem to figure out how to get pressure sensitivity enabled.

I vibe coded an application with Gemini 3 that let's you pick up a pencil and actually start drawing on a piece of paper. The assets are 3D which adds another layer of immersion just purely for fun. Try it here You can't start drawing until you literally click on the pencil to pick it up. You can also switch to a marker or use the eraser on the pencil. If you don't like the drawing you can crumple the paper and throw it in the trash. It will then place a new piece of paper on the table and you have to pick up the pencil again to start drawing again. I added a learn section on the app that links to youtube channels where you can also learn how to draw. It's quite fun to use, it's basically like using a super simplified version of photoshop or paint. It works with a wacom tablet, just can't seem to figure out how to get pressure sensitivity enabled.

Travis Davids

12,836 次观看 • 8 个月前

Everyone needs to hear this... Michael Caine on his defining philosophy for life: Use the Difficulty As a young actor, he was rehearsing a play when a chair got stuck in the door and blocked his path. He told the other actor he couldn't get by the chair to enter the scene. The actor's response: "Use the difficulty...if it's a comedy, fall over it, if it's a drama, pick it up and smash it." This idea became a defining mantra for his life. "There's never anything so bad that you cannot use that difficulty...if you can use it a quarter of one percent to your advantage, you're ahead, you didn't let it get you down." I can't stop thinking about this... How can you use the difficulty you're currently facing? How can you embrace the struggle? How can you find flow through the friction? As with everything in life, control the controllable: The difficulty is already there. You can't control it. But you can control how you react to it. You can control your response to it. You can control your attitude towards it. Lesson: Difficulty is inevitable. Use it.

Everyone needs to hear this... Michael Caine on his defining philosophy for life: Use the Difficulty As a young actor, he was rehearsing a play when a chair got stuck in the door and blocked his path. He told the other actor he couldn't get by the chair to enter the scene. The actor's response: "Use the difficulty...if it's a comedy, fall over it, if it's a drama, pick it up and smash it." This idea became a defining mantra for his life. "There's never anything so bad that you cannot use that difficulty...if you can use it a quarter of one percent to your advantage, you're ahead, you didn't let it get you down." I can't stop thinking about this... How can you use the difficulty you're currently facing? How can you embrace the struggle? How can you find flow through the friction? As with everything in life, control the controllable: The difficulty is already there. You can't control it. But you can control how you react to it. You can control your response to it. You can control your attitude towards it. Lesson: Difficulty is inevitable. Use it.

Sahil Bloom

294,273 次观看 • 4 个月前

108 workflow templates you can use to build AI applications without writing any code. You can use these templates with n8n. I recorded the attached video to show you how it works. n8n is the workhorse behind an open-source, self-hosted AI starter kit you can install on your computer. They are sponsoring this post. Here is the link to the starter kit repository: And here is the spreadsheet with the 108 templates: Whatever idea you have, search for something similar in the list of templates, and you'll save a ton of time. Lately, I've talked to many non-coders who want to start using AI more seriously to build things. n8n is perfect for that.

108 workflow templates you can use to build AI applications without writing any code. You can use these templates with n8n. I recorded the attached video to show you how it works. n8n is the workhorse behind an open-source, self-hosted AI starter kit you can install on your computer. They are sponsoring this post. Here is the link to the starter kit repository: And here is the spreadsheet with the 108 templates: Whatever idea you have, search for something similar in the list of templates, and you'll save a ton of time. Lately, I've talked to many non-coders who want to start using AI more seriously to build things. n8n is perfect for that.

Santiago

78,133 次观看 • 1 年前

Another weekend project: GridStore Jean Cavallera and I are building simple but useful dApps that make LUKSO more accessible and easier to use. This is GridStore, an “app store” for Grid templates. You can choose a template you like and, with a single transaction, upload it to your Universal Profile and use it as your Grid. This is made possible by LSP28 The Grid, where the configurations of your Grid are stored in a JSON file on IPFS. The value stored under your ⁩LSP28TheGrid⁨ data key stored on your Universal Profile points to your grid configuration JSON file. By adding the value of a grid template you like under the ⁩LSP28TheGriddata key, you can set immediately that template on your Grid and start customizing it, saving you time. If you have ideas for useful templates for brands, artists, influencers, or any other use case: set up the Grid on a Universal Profile, go to look up the profile, and send me the “Raw value” together with a short explanation of the Grid so it can be added to the store. Or add your own templates to the store by opening a PR: It would really help if we can create some high-quality templates that the whole community can use. You can check out the store here:

JordyDutch

14,060 次观看 • 6 个月前

Here is how simple it is to build a UI front-end for an AI agent (assuming you are using . The video here is 90 seconds and will show you everything you need to connect an agent to a web app: 1. Set up CopilotKit🪁 in your app 1. Copy the agent's localhost URL from LangGraph Studio 2. Paste that URL into a CopilotKit🪁 remote endpoint That's all you need to get a front-end to interact with the agent! The secret sauce here is CoAgents, an open-source library. You can use CoAgents to integrate any agent with your web application. Here is what you get: • Human-in-the-loop to steer and correct the agent • Stream intermediate agent state • Real-time state sharing between the agent and the application • Agentic generative UI to build trust that the agent is on the right path Watch the attached demo so you see it in action.

Here is how simple it is to build a UI front-end for an AI agent (assuming you are using . The video here is 90 seconds and will show you everything you need to connect an agent to a web app: 1. Set up CopilotKit🪁 in your app 1. Copy the agent's localhost URL from LangGraph Studio 2. Paste that URL into a CopilotKit🪁 remote endpoint That's all you need to get a front-end to interact with the agent! The secret sauce here is CoAgents, an open-source library. You can use CoAgents to integrate any agent with your web application. Here is what you get: • Human-in-the-loop to steer and correct the agent • Stream intermediate agent state • Real-time state sharing between the agent and the application • Agentic generative UI to build trust that the agent is on the right path Watch the attached demo so you see it in action.

Santiago

46,109 次观看 • 1 年前

Building AI agents and tools is getting ridiculously easy! Here is a pretty impressive FREE and Open-Source AI agent builder that runs on your computer. It's a desktop app you can install on Mac or Windows. Link: • Free • 100% no-code: You can type what you want, and the tool will build everything for you. • You can use local models like DeepSeek or Qwen, or connect to cloud models like GPT-4o, Claude, or Gemini with your API key. • You can turn the tools you build into MCP Servers. I recorded a quick video to show you how easy it is to build something from scratch.

Building AI agents and tools is getting ridiculously easy! Here is a pretty impressive FREE and Open-Source AI agent builder that runs on your computer. It's a desktop app you can install on Mac or Windows. Link: • Free • 100% no-code: You can type what you want, and the tool will build everything for you. • You can use local models like DeepSeek or Qwen, or connect to cloud models like GPT-4o, Claude, or Gemini with your API key. • You can turn the tools you build into MCP Servers. I recorded a quick video to show you how easy it is to build something from scratch.

Santiago

56,815 次观看 • 1 年前

How can you solve complex tasks using a Large Language Model? Here is a 2-minute introduction to everything you need to know to 10x the quality of your results. Let's talk about three techniques, in order of complexity, starting with the easiest one: • In-Context Learning • Indexing + In-Context Learning • Fine-tuning In-Context Learning The team that trained GPT-3 found something they couldn't explain: You can condition a model using examples of how you want it to behave. I included an example prompt in the attached video. You can "teach" the model how you want it to interpret questions, select the correct answers, and format the results by giving a few examples. You can also give specific knowledge to the model that will be helpful when formulating answers. We call this approach "grounding the model." There's another example in the video. Indexing + In-Context Learning Unfortunately, there is a limit to how much data you can include in a prompt. We call this the "context size." One version of GPT-4 supports a context of approximately 6,000 words, while the other supports 25,000 words. Although this sounds like a lot, many applications need more than that. Imagine you wrote a book and want to build an application to answer any questions about your story. What happens if your book is longer than the context? That's where Indexing comes in. Using a model, you can turn every book passage into an embedding. These are vectors, numbers that "encode" the passage's text. You can then store these embeddings in a particular database that supports fast retrieval of these vectors. You can then turn any question into an embedding and search the database for the list of passages that are similar to that query. Instead of using the entire book to ask the model, you can now use the relevant passages as in-context information, effectively working around the context size limitation. Fine-tuning Fine-tuning can give you an extra boost to get reliable outputs from your LLM. It is, however, the most complex approach on the list. There are different approaches to fine-tuning a model with your data. A popular technique is to process your data with your LLM and use the outputs to train a new classifier that solves your specific task. Notice that here you aren't modifying the LLM. Instead, you are chaining it with your trained classifier. Another approach is to modify the parameters of the LLM using your data. Think of this as "rewiring" the model in a way that solves your particular task. The results and costs will vary depending on how many layers you want to fine-tune from the original model. Many companies think that fine-tuning is the solution to their problems. In my experience, many will benefit from exploring the other two approaches. I love explaining Machine Learning and Artificial Intelligence ideas. If you enjoy in-depth content like this, follow me Santiago so you don't miss what comes next.

How can you solve complex tasks using a Large Language Model? Here is a 2-minute introduction to everything you need to know to 10x the quality of your results. Let's talk about three techniques, in order of complexity, starting with the easiest one: • In-Context Learning • Indexing + In-Context Learning • Fine-tuning In-Context Learning The team that trained GPT-3 found something they couldn't explain: You can condition a model using examples of how you want it to behave. I included an example prompt in the attached video. You can "teach" the model how you want it to interpret questions, select the correct answers, and format the results by giving a few examples. You can also give specific knowledge to the model that will be helpful when formulating answers. We call this approach "grounding the model." There's another example in the video. Indexing + In-Context Learning Unfortunately, there is a limit to how much data you can include in a prompt. We call this the "context size." One version of GPT-4 supports a context of approximately 6,000 words, while the other supports 25,000 words. Although this sounds like a lot, many applications need more than that. Imagine you wrote a book and want to build an application to answer any questions about your story. What happens if your book is longer than the context? That's where Indexing comes in. Using a model, you can turn every book passage into an embedding. These are vectors, numbers that "encode" the passage's text. You can then store these embeddings in a particular database that supports fast retrieval of these vectors. You can then turn any question into an embedding and search the database for the list of passages that are similar to that query. Instead of using the entire book to ask the model, you can now use the relevant passages as in-context information, effectively working around the context size limitation. Fine-tuning Fine-tuning can give you an extra boost to get reliable outputs from your LLM. It is, however, the most complex approach on the list. There are different approaches to fine-tuning a model with your data. A popular technique is to process your data with your LLM and use the outputs to train a new classifier that solves your specific task. Notice that here you aren't modifying the LLM. Instead, you are chaining it with your trained classifier. Another approach is to modify the parameters of the LLM using your data. Think of this as "rewiring" the model in a way that solves your particular task. The results and costs will vary depending on how many layers you want to fine-tune from the original model. Many companies think that fine-tuning is the solution to their problems. In my experience, many will benefit from exploring the other two approaches. I love explaining Machine Learning and Artificial Intelligence ideas. If you enjoy in-depth content like this, follow me Santiago so you don't miss what comes next.

Santiago

384,510 次观看 • 3 年前

Right now, I have a few dozen tools to automate my life. Every single thing that I do more than once every week is now a tool: either a Claude Code skill, a scheduled workflow, or an application. • I spend the time doing this once. • I schedule it. • I forget about it (or at least, try to) CREAO is one of the platforms I've used extensively for building some of these automations. They are partnering with me on this post. They are one of the only platforms where you can go from a conversation to a scheduled agent that quickly. This is how it works: 1. You describe the problem you want to solve 2. CREAO's agent builds the logic and executes it 3. You can iterate with the agent to improve the solution 4. When you are done, you turn that solution into a mini app 5. You can schedule that app to run any time you need it Something important: These agents are deterministic. They don't use an LLM to generate answers, so they will always return the same output given the same input. This is critical: when you're automating something that runs every Monday at 9 am, you need it to return the same result every time, not a "creative" answer.

Right now, I have a few dozen tools to automate my life. Every single thing that I do more than once every week is now a tool: either a Claude Code skill, a scheduled workflow, or an application. • I spend the time doing this once. • I schedule it. • I forget about it (or at least, try to) CREAO is one of the platforms I've used extensively for building some of these automations. They are partnering with me on this post. They are one of the only platforms where you can go from a conversation to a scheduled agent that quickly. This is how it works: 1. You describe the problem you want to solve 2. CREAO's agent builds the logic and executes it 3. You can iterate with the agent to improve the solution 4. When you are done, you turn that solution into a mini app 5. You can schedule that app to run any time you need it Something important: These agents are deterministic. They don't use an LLM to generate answers, so they will always return the same output given the same input. This is critical: when you're automating something that runs every Monday at 9 am, you need it to return the same result every time, not a "creative" answer.

Santiago

13,712 次观看 • 4 个月前

Today we're excited to launch Action: a Claude computer use launcher for macOS. Action is a macOS launcher that can take actions (click, type, and more) on your Mac using Claude’s computer use API. The interface is a floating window triggered by a keyboard shortcut, similar to Spotlight. This lets you see what the model outputs as it performs actions.

Today we're excited to launch Action: a Claude computer use launcher for macOS. Action is a macOS launcher that can take actions (click, type, and more) on your Mac using Claude’s computer use API. The interface is a floating window triggered by a keyboard shortcut, similar to Spotlight. This lets you see what the model outputs as it performs actions.

Lawrence Chen

21,622 次观看 • 1 年前

Koinos 101: Mana Do you think the internet would have taken off if you had to pay just 1 cent to visit a website? That's why we invented the Mana system which makes Koinos ... the first and only free-to-use blockchain. Owning the network It’s natural to think that holding a token like ETH, BTC, or SOL makes you an owner of those platforms, but if you were an owner, you would have a right to use those platforms forever. But you don't have that right. You only have the “right” to spend those tokens down as you use the network, which isn’t much of a right at all. On Koinos, the KOIN token works exactly like you think it would! Holding KOIN gives you a perpetual right to use the network, thanks to the Mana system. The more KOIN you hold, the more free usage, forever. Simple. Every KOIN token contains 1 Mana. When you use the blockchain, some of your Mana is consumed, but it regenerates in 5 days and if you only use a small percentage of your Mana it can regenerate in as little as a few minutes! Frictionless Access Mana can also be shared with people who have no tokens at all, which is what enables Koinos to deliver that familiar free-to-use experience that we get from the internet, and without forcing developers to pay the fees, because remember there are no fees. For the first time ever... developers can onboard users and allow them to the use the blockchain without first making them jump through the hoops of understanding and buying a cryptocurrency which is going to weed out the vast majority of mainstream users. That’s why we don’t have mainstream adoption! In short, KOIN has real utility; it gives you ownership over a certain amount of the network’s resources, a right which you can share with others. Koinos doesn’t force you to pay ever-changing fees all the time and it does all of this while preventing people from abusing the network. Be Free Because you never have to part with your KOIN which gives you the right to a certain amount of the network’s resources, this frees you, and every other KOIN holder, to focus on what matters; adding utility and making Koinos an even greater force for good. You can learn more about Koinos at and

Koinos 101: Mana Do you think the internet would have taken off if you had to pay just 1 cent to visit a website? That's why we invented the Mana system which makes Koinos ... the first and only free-to-use blockchain. Owning the network It’s natural to think that holding a token like ETH, BTC, or SOL makes you an owner of those platforms, but if you were an owner, you would have a right to use those platforms forever. But you don't have that right. You only have the “right” to spend those tokens down as you use the network, which isn’t much of a right at all. On Koinos, the KOIN token works exactly like you think it would! Holding KOIN gives you a perpetual right to use the network, thanks to the Mana system. The more KOIN you hold, the more free usage, forever. Simple. Every KOIN token contains 1 Mana. When you use the blockchain, some of your Mana is consumed, but it regenerates in 5 days and if you only use a small percentage of your Mana it can regenerate in as little as a few minutes! Frictionless Access Mana can also be shared with people who have no tokens at all, which is what enables Koinos to deliver that familiar free-to-use experience that we get from the internet, and without forcing developers to pay the fees, because remember there are no fees. For the first time ever... developers can onboard users and allow them to the use the blockchain without first making them jump through the hoops of understanding and buying a cryptocurrency which is going to weed out the vast majority of mainstream users. That’s why we don’t have mainstream adoption! In short, KOIN has real utility; it gives you ownership over a certain amount of the network’s resources, a right which you can share with others. Koinos doesn’t force you to pay ever-changing fees all the time and it does all of this while preventing people from abusing the network. Be Free Because you never have to part with your KOIN which gives you the right to a certain amount of the network’s resources, this frees you, and every other KOIN holder, to focus on what matters; adding utility and making Koinos an even greater force for good. You can learn more about Koinos at and

KoinosGroup 🔮

337,618 次观看 • 2 年前

I’m reverse-engineering the Google AI mouse pointer and making it Open Source! It sees your screen. You can freeform paint anything and ask AI to modify it. It understands the app or window you mean. It can click, type, edit, navigate, and even write + execute code. A tiny cursor becoming a real computer-use agent. Made with the help of Cua which is an AMAZING reference for computer use Sorry Google DeepMind but I had to do this heyclicky Started a revolution and we will be the ones to win Also credits to Omkar Satpute for the help Feel free to modify it , update it and make it your own, we gotta beat them at this. Link to the repo in the comments:

I’m reverse-engineering the Google AI mouse pointer and making it Open Source! It sees your screen. You can freeform paint anything and ask AI to modify it. It understands the app or window you mean. It can click, type, edit, navigate, and even write + execute code. A tiny cursor becoming a real computer-use agent. Made with the help of Cua which is an AMAZING reference for computer use Sorry Google DeepMind but I had to do this heyclicky Started a revolution and we will be the ones to win Also credits to Omkar Satpute for the help Feel free to modify it , update it and make it your own, we gotta beat them at this. Link to the repo in the comments:

Milind S

213,009 次观看 • 2 个月前

99% of AI applications are cool-looking demos. Impressive, but don't get fooled by the hype. It takes a lot to build enterprise-grade products that deliver real value. I have at least three weekly conversations with companies that want to use a Large Language Model with their data. The demand is huge! Here is one idea about what you can do to help. The use cases that most of these companies want to solve are similar: They have an extensive knowledge base and want to build a simple application that uses that information to answer questions. In other words, they need help building Retrieval Augmented Generation (RAG) applications they can use in many different scenarios: 1. To train new employees 2. To help their support team 3. To search old meetings and documents 4. To help with their research However, building these systems is not straightforward. Yes, there's a lot of information online, but there aren't enough people who know how to create solutions that work. Here is the idea: Today, you can build an enterprise-grade RAG application without writing code. A couple of MIT PhDs with 10+ years of experience building AI applications created . It's a no-code platform for building applications using Large Language Models. They are partnering with me on this post. You can use Stack AI to create, test, and deploy an end-to-end production-ready AI system. It's SOC-2, HIPAA, and GDPR compliant and offers SSO, role management, access control, and on-premise deployments. Of course, you can use the platform with any LLM on the market now. It's the whole nine yards for building AI applications. Check them out here: 2023 was about models. 2024 is about the tools using these models to build production-ready applications. That's where I'd start.

99% of AI applications are cool-looking demos. Impressive, but don't get fooled by the hype. It takes a lot to build enterprise-grade products that deliver real value. I have at least three weekly conversations with companies that want to use a Large Language Model with their data. The demand is huge! Here is one idea about what you can do to help. The use cases that most of these companies want to solve are similar: They have an extensive knowledge base and want to build a simple application that uses that information to answer questions. In other words, they need help building Retrieval Augmented Generation (RAG) applications they can use in many different scenarios: 1. To train new employees 2. To help their support team 3. To search old meetings and documents 4. To help with their research However, building these systems is not straightforward. Yes, there's a lot of information online, but there aren't enough people who know how to create solutions that work. Here is the idea: Today, you can build an enterprise-grade RAG application without writing code. A couple of MIT PhDs with 10+ years of experience building AI applications created . It's a no-code platform for building applications using Large Language Models. They are partnering with me on this post. You can use Stack AI to create, test, and deploy an end-to-end production-ready AI system. It's SOC-2, HIPAA, and GDPR compliant and offers SSO, role management, access control, and on-premise deployments. Of course, you can use the platform with any LLM on the market now. It's the whole nine yards for building AI applications. Check them out here: 2023 was about models. 2024 is about the tools using these models to build production-ready applications. That's where I'd start.

Santiago

197,702 次观看 • 2 年前

Tune Studio is an end-to-end platform for developing applications using Large Language Models. So far, I haven't seen any other platform like this one. You can do everything here: 1. You can curate your data. 2. Use the playground to play with different models and try your ideas. 3. Fine-tune an open-source model on your data. 4. Deploy the model when you are done. This is awesome for anyone building generative AI applications. You can use Tune Studio to work with any of the open-source models out there. They were one of the few companies to host Llama 2 and Llama 3 before anyone else. Here is a link to check it out: One of their main selling points is that Tune Studio scales! You don't have to worry about serving your model to lots of users. They also have built-in user management, authentication, on-prem support, user context management, and pretty much everything you need to build generative AI applications. Thanks to the Tune team for collaborating with me on this post. We are living through the best years of development tools for AI developers. The field is unstoppable.

Tune Studio is an end-to-end platform for developing applications using Large Language Models. So far, I haven't seen any other platform like this one. You can do everything here: 1. You can curate your data. 2. Use the playground to play with different models and try your ideas. 3. Fine-tune an open-source model on your data. 4. Deploy the model when you are done. This is awesome for anyone building generative AI applications. You can use Tune Studio to work with any of the open-source models out there. They were one of the few companies to host Llama 2 and Llama 3 before anyone else. Here is a link to check it out: One of their main selling points is that Tune Studio scales! You don't have to worry about serving your model to lots of users. They also have built-in user management, authentication, on-prem support, user context management, and pretty much everything you need to build generative AI applications. Thanks to the Tune team for collaborating with me on this post. We are living through the best years of development tools for AI developers. The field is unstoppable.

Santiago

39,101 次观看 • 2 年前