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Today we're launching a major new Equals feature: Equals Infinity. Infinity removes the row limit in the spreadsheet. Here's how it works: 1. Any connected sheet with data from Snowflake or an Equals Warehouse datasource can become an "Infinity" sheet. These sheets have no row limit. 2. Infinity sheets... can be aggregated using formulas like SUMIFS, COUNTIFS, etc. Just like you're used to. 3. Infinity sheets are never loaded in memory on your computer. Keeping everything really snappy. It's really fast. You can do a SUMIF over 100M rows in 2 seconds. You no longer need SQL or Python skills to work with raw event streams (for product usage), data at its most granular level (think invoice items instead of a roll up), or large summary tables (like summary stats per user, per day). One way we’ve been talking about this: with Infinity, every spreadsheet pro is now a data scientist. I put together a little demo of working with events data in a spreadsheet. We’d love to hear what you all think.show more

Ben McRedmond

2,225 subscribers

12,937 次观看 • 1 年前 •via X (Twitter)

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Here's how I would learn data engineering basics in 2025: - Find a data source you care about (examples: gaming APIs, stock market, web scraping, etc) - Use Python to interact and ingest your source. Initially just write the data to a CSV. - Setup an account with Snowflake or Google BigQuery. - update your Python script to load a table in Snowflake/BigQuery - schedule your script with CRON in the cloud with a service like Heroku. - build aggregations and visualizations on top of your ingested data Only thing this misses is data quality and complex job orchestration which you can learn later! How would you learn data engineering nowadays?

Here's how I would learn data engineering basics in 2025: - Find a data source you care about (examples: gaming APIs, stock market, web scraping, etc) - Use Python to interact and ingest your source. Initially just write the data to a CSV. - Setup an account with Snowflake or Google BigQuery. - update your Python script to load a table in Snowflake/BigQuery - schedule your script with CRON in the cloud with a service like Heroku. - build aggregations and visualizations on top of your ingested data Only thing this misses is data quality and complex job orchestration which you can learn later! How would you learn data engineering nowadays?

Zach Wilson

20,368 次观看 • 1 年前

Corporations that are purely AI and robotics will vastly outperform any corporations that have people in the loop You can think of it like how 'computer' used to be a job that humans had. You would go and get a job as a computer where you would do calculations. They had entire skyscrapers full of humans....20, 30 floors of humans...just doing calculations. Now, that entire skyscraper of humans doing calculations can be replaced by a laptop with a spreadsheet. That spreadsheet can do vastly more calculations than an entire building full of human computers So, you think about it: what if only some of the cells in your spreadsheet were calculated by humans? That would be much worse than if all of the cells in your spreadsheet were calculated by the computer. And so, really what will happen is the pure AI, pure robotics corporations or collectives will far outperform any corporations that have humans in the loop. It will happen very quickly

Corporations that are purely AI and robotics will vastly outperform any corporations that have people in the loop You can think of it like how 'computer' used to be a job that humans had. You would go and get a job as a computer where you would do calculations. They had entire skyscrapers full of humans....20, 30 floors of humans...just doing calculations. Now, that entire skyscraper of humans doing calculations can be replaced by a laptop with a spreadsheet. That spreadsheet can do vastly more calculations than an entire building full of human computers So, you think about it: what if only some of the cells in your spreadsheet were calculated by humans? That would be much worse than if all of the cells in your spreadsheet were calculated by the computer. And so, really what will happen is the pure AI, pure robotics corporations or collectives will far outperform any corporations that have humans in the loop. It will happen very quickly

X Freeze

16,848,979 次观看 • 6 个月前

🎉 The wait is over! RuBotMaster is officially live! Now you can build many different types of powerful, data-rich bots in under a minute using over 100 filters. 📲 User-friendly? Absolutely! We've made it effortless and linked Telegram with Google Sheets. Just generate a template or copy a cheat sheet, paste your link back into the bot, and voilà — your bot is created. 📑 Then, sit back and watch the notifications roll in. ✏️📈 Need to tweak or optimize? You can edit your sheet at any time! 📗

🎉 The wait is over! RuBotMaster is officially live! Now you can build many different types of powerful, data-rich bots in under a minute using over 100 filters. 📲 User-friendly? Absolutely! We've made it effortless and linked Telegram with Google Sheets. Just generate a template or copy a cheat sheet, paste your link back into the bot, and voilà — your bot is created. 📑 Then, sit back and watch the notifications roll in. ✏️📈 Need to tweak or optimize? You can edit your sheet at any time! 📗

Ru

13,945 次观看 • 1 年前

Flapping Airplanes co-founder Asher Spector explains why data efficiency is the greatest bottleneck to AI adoption: "To the extent that AI has been hard to integrate into the economy, I really think it's because models are much less data-efficient than humans. If you want it to learn a new task, or put it in a new vertical, it takes thousands of times more effort than it does to just tell a human what to do." "If you can make a model a million times more data-efficient, it's a million times easier to put into the economy. There's a ton of cool stuff that you can do in really data-constrained regimes. For example, whether it's robotics, or scientific discovery, or even something like trading, these problems have very limited data, and existing AI systems aren't quite as good at them as they are at other things. I think that learning to learn with less data is just tremendously valuable in all of these domains."

Flapping Airplanes co-founder Asher Spector explains why data efficiency is the greatest bottleneck to AI adoption: "To the extent that AI has been hard to integrate into the economy, I really think it's because models are much less data-efficient than humans. If you want it to learn a new task, or put it in a new vertical, it takes thousands of times more effort than it does to just tell a human what to do." "If you can make a model a million times more data-efficient, it's a million times easier to put into the economy. There's a ton of cool stuff that you can do in really data-constrained regimes. For example, whether it's robotics, or scientific discovery, or even something like trading, these problems have very limited data, and existing AI systems aren't quite as good at them as they are at other things. I think that learning to learn with less data is just tremendously valuable in all of these domains."

TBPN

91,955 次观看 • 6 个月前

is our AI project to make computing feel more human L A N D E R Here are the 4 best demo videos of the magic of DATA in action. DATA is a personalized assistant who knows and remembers every conversation you have with it accross your iPhone, Mac, iPad, Watch, Texts, Emails, and HomePods. You can talk to DATA right in your AirPods or text it just like a person. DATA can read, write, understand, speak any language, and translate between them. It can help with real work and home life tasks like research, writing, scheduling, reminders, and triage. And it's easily customizable so you can have DATA automatically do whatever you want whenever you want with just a few taps and natural language instructions - no code required. DATA can do just about anything you can do on your phone on your behalf automatically including very advanced things Siri can't, like summarizing, analyzing, and drafting replies or writing documents. It can read web pages, texts or emails you show it, or PDFs of any kind. It can do other real world tasks that require complex analysis and common sense too, like: - figure out where the nearest beach is (even when you're in Colorado) and instantly fetch the current surf report up to the current minute. - summarize and drafting replies to entire email chains - plan out entire work projects or multi-day vacations on your calendar - sketch out ideas for you in picture form or drafting Notion pages with charts and graphs. DATA can also use its own judgement to determine when to run an action or not, even if you've scheduled it, allowing you to make VERY complex automations that require many different inputs to make a decision, like for example: - only opening the blinds on your lunch break if it's sunny out and you're working from home. DATA works natively and easily with Apple HomeKit & other shortcuts. DATA can also take initiative and check in with you throughout the day by voice or text and proactively send messages to you and others on your behalf based on your personal and professional goals, current tasks, and calendar. DATA can integrate with many apps on your phone, and is compatible with multiple large AI language models. I've gotten to make a few demo videos that I think really capture how powerful DATA can be for every day life. Here they are all in one tweet. Make sure your sound is on as you watch them. 1. This is the first demo video I ever made from April 19th, 2023. It walks through all the ways you can interact with and use the DATA shortcuts. Everything from saying "Hey Siri" to tapping on custom apps on your home-screen. 2. The second demo video was made May 5 and is an example use case I made of how commands work - commands allow DATA to actually run actions on your phone like taking pictures and sending messages. This demo shows me taking a picture of an email template, and data drafting an email based on that template. It's gotten much better at realizing when it has just run a command and incorporating that information naturally into the conversation now, especially on GPT-4. 3. This third Commands video, May 12 is a walkthrough of ALL the phone functions that commands allow DATA to do: sending texts and emails, making pictures, seeing pictures, reading things, and scheduling events. Since this video we've added auto-replies to texts and emails, summarizing documents, writing documents, health app data retrieval, web surfing, scheduling alarms, making playlists, and more. 4. This last demo I made today, June 15, shows everything DATA does working in concert to generate a crazy detailed morning briefing with background music - including making a unique playlist and giving a detailed analysis of current events complete with Ski & Surf conditions near me other live information from the internet. So now that you've seen everything DATA can do, what's the coolest feature? What features should we add? What would you use DATA for first?

is our AI project to make computing feel more human L A N D E R Here are the 4 best demo videos of the magic of DATA in action. DATA is a personalized assistant who knows and remembers every conversation you have with it accross your iPhone, Mac, iPad, Watch, Texts, Emails, and HomePods. You can talk to DATA right in your AirPods or text it just like a person. DATA can read, write, understand, speak any language, and translate between them. It can help with real work and home life tasks like research, writing, scheduling, reminders, and triage. And it's easily customizable so you can have DATA automatically do whatever you want whenever you want with just a few taps and natural language instructions - no code required. DATA can do just about anything you can do on your phone on your behalf automatically including very advanced things Siri can't, like summarizing, analyzing, and drafting replies or writing documents. It can read web pages, texts or emails you show it, or PDFs of any kind. It can do other real world tasks that require complex analysis and common sense too, like: - figure out where the nearest beach is (even when you're in Colorado) and instantly fetch the current surf report up to the current minute. - summarize and drafting replies to entire email chains - plan out entire work projects or multi-day vacations on your calendar - sketch out ideas for you in picture form or drafting Notion pages with charts and graphs. DATA can also use its own judgement to determine when to run an action or not, even if you've scheduled it, allowing you to make VERY complex automations that require many different inputs to make a decision, like for example: - only opening the blinds on your lunch break if it's sunny out and you're working from home. DATA works natively and easily with Apple HomeKit & other shortcuts. DATA can also take initiative and check in with you throughout the day by voice or text and proactively send messages to you and others on your behalf based on your personal and professional goals, current tasks, and calendar. DATA can integrate with many apps on your phone, and is compatible with multiple large AI language models. I've gotten to make a few demo videos that I think really capture how powerful DATA can be for every day life. Here they are all in one tweet. Make sure your sound is on as you watch them. 1. This is the first demo video I ever made from April 19th, 2023. It walks through all the ways you can interact with and use the DATA shortcuts. Everything from saying "Hey Siri" to tapping on custom apps on your home-screen. 2. The second demo video was made May 5 and is an example use case I made of how commands work - commands allow DATA to actually run actions on your phone like taking pictures and sending messages. This demo shows me taking a picture of an email template, and data drafting an email based on that template. It's gotten much better at realizing when it has just run a command and incorporating that information naturally into the conversation now, especially on GPT-4. 3. This third Commands video, May 12 is a walkthrough of ALL the phone functions that commands allow DATA to do: sending texts and emails, making pictures, seeing pictures, reading things, and scheduling events. Since this video we've added auto-replies to texts and emails, summarizing documents, writing documents, health app data retrieval, web surfing, scheduling alarms, making playlists, and more. 4. This last demo I made today, June 15, shows everything DATA does working in concert to generate a crazy detailed morning briefing with background music - including making a unique playlist and giving a detailed analysis of current events complete with Ski & Surf conditions near me other live information from the internet. So now that you've seen everything DATA can do, what's the coolest feature? What features should we add? What would you use DATA for first?

steve

640,176 次观看 • 3 年前

Today I’m excited to announce Spreadsheet Agents 📊🤖 - a brand-new LlamaIndex feature that allows users to both do data transformation and QA over unnormalized Excel sheets. A lot of knowledge work happens in Excel (or Sheets, Numbers, etc.) - from insurance to tax to corporate finance. It is an extremely nonstandard format that is unsolved by LLMs - neither text-to-CSV nor RAG nor code interpreter work well over these use cases. We built an agent that has really advanced technical capabilities: 1. We do RL-based semantic structure parsing to understand the structure of the Excel sheet 2. We expose these data models through specialized tools to allow an Excel agent to interact with these sheets Huge shoutout to Daniel B. and Zhaoqi Li for working on this 🙌 Currently available in private preview, check out our blog: Come talk to us if you’re interested: Come talk to us if you’re interested:

Jerry Liu

37,901 次观看 • 1 年前

i wish i could just upload a CSV and it would automatically create a dashboard so we built this today we're launching graphed .com graphed is an AI data analytics and dashboard generator upload data into Graphed and it's gonna one shot generate a dashboard you can chat with the entire dashboard to make changes and you can click into the graph and chat with it to make updates everything you create in Graphed can easily be shared with your team by sending a link or you can download a screenshot and drop it into a Slack channel or add it to a presentation the Graphed source data can either be a CSV or a data integration data integrations allow you to create live dashboards that are constantly updating in the background we're launching with Google Analytics 4 as our first data integration but we have Shopify, Facebook ads, Google Ads, MongoDB, and hundreds more are on our product roadmap you can sign up for free at graphed .com and if you want a 40% discount code that will only be available during launch comment "graphed" below

i wish i could just upload a CSV and it would automatically create a dashboard so we built this today we're launching graphed .com graphed is an AI data analytics and dashboard generator upload data into Graphed and it's gonna one shot generate a dashboard you can chat with the entire dashboard to make changes and you can click into the graph and chat with it to make updates everything you create in Graphed can easily be shared with your team by sending a link or you can download a screenshot and drop it into a Slack channel or add it to a presentation the Graphed source data can either be a CSV or a data integration data integrations allow you to create live dashboards that are constantly updating in the background we're launching with Google Analytics 4 as our first data integration but we have Shopify, Facebook ads, Google Ads, MongoDB, and hundreds more are on our product roadmap you can sign up for free at graphed .com and if you want a 40% discount code that will only be available during launch comment "graphed" below

Cody Schneider

47,302 次观看 • 1 年前

Your agents can't keep up with real-time data. Especially when it's scattered across dozens of sources. Most teams waste weeks building custom connectors for every database, API, and data warehouse. Then they build ETL pipelines to sync everything. By the time your agent retrieves the data, it's already outdated. Picture this: Your Postgres database updated 5 minutes ago. Your MongoDB collection changed 2 minutes ago. Your agent is still pulling from yesterday's snapshot. This is why most production RAG systems fail. There's a better approach: MindsDB is an open-source AI platform with a federated data engine that lets you query multiple data sources in real-time using SQL - without moving any data. Here's what makes it different: ↳ Your data stays in place. No ETL pipelines or data duplication ↳ Query Postgres, MongoDB, REST APIs, and more using consistent SQL ↳ JOIN across different sources in real-time with a unified interface ↳ Works with both structured and un-structured data And here's the best part: You don't even need to write SQL. Just describe what you want in plain English, and MindsDB converts it to SQL automatically. The system does all the heavy lifting. The breakthrough for AI agents is simple: When data updates at the source, your agent gets fresh results immediately. No sync delays. No stale embeddings. No custom code for each integration. You can literally write a SQL query that joins a Postgres table with a MongoDB collection and gets live results. This is what production AI applications need but rarely get. In this video, I give you a complete walkthrough of what we just discussed and how to actually do it. Make sure you watch this till the end. I've shared the link to MindsDB's GitHub repo in the next tweet!

Your agents can't keep up with real-time data. Especially when it's scattered across dozens of sources. Most teams waste weeks building custom connectors for every database, API, and data warehouse. Then they build ETL pipelines to sync everything. By the time your agent retrieves the data, it's already outdated. Picture this: Your Postgres database updated 5 minutes ago. Your MongoDB collection changed 2 minutes ago. Your agent is still pulling from yesterday's snapshot. This is why most production RAG systems fail. There's a better approach: MindsDB is an open-source AI platform with a federated data engine that lets you query multiple data sources in real-time using SQL - without moving any data. Here's what makes it different: ↳ Your data stays in place. No ETL pipelines or data duplication ↳ Query Postgres, MongoDB, REST APIs, and more using consistent SQL ↳ JOIN across different sources in real-time with a unified interface ↳ Works with both structured and un-structured data And here's the best part: You don't even need to write SQL. Just describe what you want in plain English, and MindsDB converts it to SQL automatically. The system does all the heavy lifting. The breakthrough for AI agents is simple: When data updates at the source, your agent gets fresh results immediately. No sync delays. No stale embeddings. No custom code for each integration. You can literally write a SQL query that joins a Postgres table with a MongoDB collection and gets live results. This is what production AI applications need but rarely get. In this video, I give you a complete walkthrough of what we just discussed and how to actually do it. Make sure you watch this till the end. I've shared the link to MindsDB's GitHub repo in the next tweet!

Akshay 🚀

65,672 次观看 • 9 个月前

Qullamaggie on How to Make 870% Returns In One Year “As a trader, if you wanna, if you want to make 800 per 870% return in one year, you can do it. There are two main ways to do it, okay? One is to go all in on your favorite stock or someone else’s favorite stock; the other is to use options with call options and hope the trade works out. Or, if you have an exploitable edge or several exploitable edges, you can aggressively exploit those edges. Those are the two ways of making returns like that. The problem is if you are in category 1, where you go all in one stock, on margin or options, you may be really lucky, right? You catch something big, the problem is you’re probably not gonna repeat it the next year or the year after or the year after that. While if you have an exploitable edge, you will exploit, you know. You can repeat it year after year after year until infinity. There is no upper limit; it all depends on you.”

Qullamaggie on How to Make 870% Returns In One Year “As a trader, if you wanna, if you want to make 800 per 870% return in one year, you can do it. There are two main ways to do it, okay? One is to go all in on your favorite stock or someone else’s favorite stock; the other is to use options with call options and hope the trade works out. Or, if you have an exploitable edge or several exploitable edges, you can aggressively exploit those edges. Those are the two ways of making returns like that. The problem is if you are in category 1, where you go all in one stock, on margin or options, you may be really lucky, right? You catch something big, the problem is you’re probably not gonna repeat it the next year or the year after or the year after that. While if you have an exploitable edge, you will exploit, you know. You can repeat it year after year after year until infinity. There is no upper limit; it all depends on you.”

Lone

75,591 次观看 • 6 个月前

Elon Musk explains why fully autonomous businesses will win “Some of this is going to sound kind of doomerish, but corporations that are purely AI robotics will vastly outperform any corporations that have people in the loop” “Like computer used to be a job that humans had and they’d have like entire skyscrapers full of humans just doing calculations. Now that entire skyscraper of humans doing calculations can be replaced by a laptop with a spreadsheet” “That spreadsheet can do vastly more calculations than an entire building full of human computers. So you can think about, okay, well what if only some of the cells in your spreadsheet were calculated by humans? That would be much worse than if all the cells in your spreadsheet were calculated by the computer” “Really what will happen is the pure AI, pure robotics corporations or collectives will far outperform any corporations that have humans in the loop and this will happen very quickly”

Elon Musk explains why fully autonomous businesses will win “Some of this is going to sound kind of doomerish, but corporations that are purely AI robotics will vastly outperform any corporations that have people in the loop” “Like computer used to be a job that humans had and they’d have like entire skyscrapers full of humans just doing calculations. Now that entire skyscraper of humans doing calculations can be replaced by a laptop with a spreadsheet” “That spreadsheet can do vastly more calculations than an entire building full of human computers. So you can think about, okay, well what if only some of the cells in your spreadsheet were calculated by humans? That would be much worse than if all the cells in your spreadsheet were calculated by the computer” “Really what will happen is the pure AI, pure robotics corporations or collectives will far outperform any corporations that have humans in the loop and this will happen very quickly”

Jack

61,503 次观看 • 5 个月前

So here’s the deal, THE TREASURY DEPARTMENT DATA IS COMPROMISED. Actors without security clearance have been given access to scrape your data. Elon Musk now controls your data and it represents the same level of control exerted by the Chinese government’s social credit system. Musk is now able to profile every name on the treasury data systems. There is no way to sugar coat the fact that your data is no longer secure. It can now be used to target you and not for your benefit, be sure of that. Democrats and advocacy groups can take all the legal action they like, THE DATA IS COMPROMISED and you can’t put the genie back in the bottle. This data can now be used to literally social engineer services to target any perceived enemy of ‘the state’. Call me a conspiracy theorist if you like, but then sit back have a think if any of what I am suggesting is not possible. I analyse big data for a living and I have no solution to this problem and neither does any Democrat telling you it can be fixed.

𝔗𝔯𝔲𝔱𝔥 𝔐𝔞𝔱𝔱𝔢𝔯𝔰

16,366 次观看 • 1 年前

Today we're launching Amplitude MCP MCP was made for data analytics. Ask a vague question and have an AI model iteratively query Amplitude to find you insights. Amplitude MCP exposes all of Amplitude's functionality so an agent can interact with it directly. It allows you to use Amplitude without having to know anything about Amplitude's user interface or your data taxonomy. It uses the intelligence of off the shelf AI agents, including Claude, Gemini, and Cursor, to query Amplitude data you already have to find answers. It leverages all of your existing Amplitude data and how it's used to navigate through large complex behavioral datasets. You can have conversations about your product data directly inside any AI model with MCP. It can create Amplitude dashboards and notebooks with what it finds and even make recommendations. This is the best MCP use case I've ever seen. Watching an AI agent think, reason, query Amplitude, and then repeat that process iteratively is magical. See it in action:

Today we're launching Amplitude MCP MCP was made for data analytics. Ask a vague question and have an AI model iteratively query Amplitude to find you insights. Amplitude MCP exposes all of Amplitude's functionality so an agent can interact with it directly. It allows you to use Amplitude without having to know anything about Amplitude's user interface or your data taxonomy. It uses the intelligence of off the shelf AI agents, including Claude, Gemini, and Cursor, to query Amplitude data you already have to find answers. It leverages all of your existing Amplitude data and how it's used to navigate through large complex behavioral datasets. You can have conversations about your product data directly inside any AI model with MCP. It can create Amplitude dashboards and notebooks with what it finds and even make recommendations. This is the best MCP use case I've ever seen. Watching an AI agent think, reason, query Amplitude, and then repeat that process iteratively is magical. See it in action:

Spenser Skates

32,332 次观看 • 10 个月前

Web scraping is a critical skill, and yet nobody talks about it. How do you think companies are training their Large Language Models? Where do you think the data comes from? But web scraping goes beyond all of that. Imagine giving an AI agent access to any public online data in real time! I like to call this "web-scrapping on demand", and I'm pretty sure it's going to unlock unlimited power for AI applications. I recorded a quick video to show you how you can do this using Apify. I've talked about them before, and they are collaborating with me on this post. They have one of the best open-source web scraping and browser automation libraries out there: But it gets much better than this! You can use MCP to connect your AI Agents and applications to the Apify platform and use any specialized actor on demand to scrape and process online data. In the video, I used Cursor to scrape LinkedIn posts with the words "Machine Learning" in real time. Worked like a charm with no code needed! Here is a link to the platform: Think about this: You can now feed your AI applications with any public data on demand! We aren't ready for what's coming.

Web scraping is a critical skill, and yet nobody talks about it. How do you think companies are training their Large Language Models? Where do you think the data comes from? But web scraping goes beyond all of that. Imagine giving an AI agent access to any public online data in real time! I like to call this "web-scrapping on demand", and I'm pretty sure it's going to unlock unlimited power for AI applications. I recorded a quick video to show you how you can do this using Apify. I've talked about them before, and they are collaborating with me on this post. They have one of the best open-source web scraping and browser automation libraries out there: But it gets much better than this! You can use MCP to connect your AI Agents and applications to the Apify platform and use any specialized actor on demand to scrape and process online data. In the video, I used Cursor to scrape LinkedIn posts with the words "Machine Learning" in real time. Worked like a charm with no code needed! Here is a link to the platform: Think about this: You can now feed your AI applications with any public data on demand! We aren't ready for what's coming.

Santiago

101,473 次观看 • 1 年前

Yunjin talked about the significance of slowness in a world that moves so fast & virtue of patience ❤️‍🩹 “What I've been thinking about lately is the importance of being deliberately slow about things and allowing yourself a pocket of time in your day to not be rushed by anyone or anything, not even yourself. When we had our show in Shizuoka, we got on, we took the train there, the Shinkansen, instead of taking a flight like we would normally and it was really really nice because we were allotted an amount of time in our day to basically just sit with ourselves. You know, that's what I love about being on a plane or just in any vehicle, because you are not driving it or you could be driving it, but you can’t travel in a split second. There's time. There's a time of arrival that you can't control and you just kind of have to wait and sit with yourself. But I feel this need to be on airplane mode when I do have those opportunities to be off my phone and just, like, disconnected from the world, but also not disconnected from the world. You know what I mean? Like, when you're on a plane, you're still part of the world. You're just, like, not on the stratosphere, like, physically. And it kind of like, forces you to be, like. To, like, separate yourself for a second, like a couple hours or a couple days, if you're like a layover or something. I found myself looking out the window of the train and just, like, enjoying myself. Because everything is so fast, and I think everything. Ever since then, I've been deliberately, like, making an effort to do one thing very slowly, and it's very nice. It’s good. It's a good way to kind of put your feet back on the ground and remind yourself that not everything has to be you know, it's okay to take a breather and just wait. It's a virtue. Patience is a virtue, you know, but it's also virtue to enjoy it and gift yourself that time. It's kind of rebellious in a way, because no one can take that right from you. To do something with less urgency when everybody around you is like, of course, if it's an urgent manner, you should or urgent matter, you should do things accordingly but, you know, if it's like you don't need to wash your hair, like, in three minutes. Like, you can take your time to really think about. You know, sometimes we just live on. Autopilot so much, I think it's important to remind ourselves we're not AI.”

Yunjin talked about the significance of slowness in a world that moves so fast & virtue of patience ❤️‍🩹 “What I've been thinking about lately is the importance of being deliberately slow about things and allowing yourself a pocket of time in your day to not be rushed by anyone or anything, not even yourself. When we had our show in Shizuoka, we got on, we took the train there, the Shinkansen, instead of taking a flight like we would normally and it was really really nice because we were allotted an amount of time in our day to basically just sit with ourselves. You know, that's what I love about being on a plane or just in any vehicle, because you are not driving it or you could be driving it, but you can’t travel in a split second. There's time. There's a time of arrival that you can't control and you just kind of have to wait and sit with yourself. But I feel this need to be on airplane mode when I do have those opportunities to be off my phone and just, like, disconnected from the world, but also not disconnected from the world. You know what I mean? Like, when you're on a plane, you're still part of the world. You're just, like, not on the stratosphere, like, physically. And it kind of like, forces you to be, like. To, like, separate yourself for a second, like a couple hours or a couple days, if you're like a layover or something. I found myself looking out the window of the train and just, like, enjoying myself. Because everything is so fast, and I think everything. Ever since then, I've been deliberately, like, making an effort to do one thing very slowly, and it's very nice. It’s good. It's a good way to kind of put your feet back on the ground and remind yourself that not everything has to be you know, it's okay to take a breather and just wait. It's a virtue. Patience is a virtue, you know, but it's also virtue to enjoy it and gift yourself that time. It's kind of rebellious in a way, because no one can take that right from you. To do something with less urgency when everybody around you is like, of course, if it's an urgent manner, you should or urgent matter, you should do things accordingly but, you know, if it's like you don't need to wash your hair, like, in three minutes. Like, you can take your time to really think about. You know, sometimes we just live on. Autopilot so much, I think it's important to remind ourselves we're not AI.”

nat ☆彡

15,642 次观看 • 5 天前

Qullamaggie on Why You Are Always in a Drawdown “You're never gonna sell everything at the top. Just get that thought out of your head. You're gonna be in a drawdown probably 99% of the time. Remember that. You can make 500% in a year and be in a drawdown 95% of the time. That's just how it works. If anyone's gonna tell you otherwise, they're a liar and probably trying to sell you something. Look at stuff like NFLX over the past 10 years or AMZN. One of the best performing stocks over 10 years. You can see it spent like, what, 2/3 of the time in a drawdown. Now it's in a drawdown again. Where this ends, who knows. That's just how it works. No matter how good or bad your returns are, you're gonna spend most of the time in a drawdown. No matter what. Only time you're not gonna do that, if you’re a day trader or scalper, one of these guys that make 50 bucks per day and they're super happy about it. They make like 500 trades, end up with 50 bucks.”

Qullamaggie on Why You Are Always in a Drawdown “You're never gonna sell everything at the top. Just get that thought out of your head. You're gonna be in a drawdown probably 99% of the time. Remember that. You can make 500% in a year and be in a drawdown 95% of the time. That's just how it works. If anyone's gonna tell you otherwise, they're a liar and probably trying to sell you something. Look at stuff like NFLX over the past 10 years or AMZN. One of the best performing stocks over 10 years. You can see it spent like, what, 2/3 of the time in a drawdown. Now it's in a drawdown again. Where this ends, who knows. That's just how it works. No matter how good or bad your returns are, you're gonna spend most of the time in a drawdown. No matter what. Only time you're not gonna do that, if you’re a day trader or scalper, one of these guys that make 50 bucks per day and they're super happy about it. They make like 500 trades, end up with 50 bucks.”

Lone

13,508 次观看 • 1 年前

"If you're an analytical SaaS company, it's over. It's over." - Palo Alto Networks CEO Nikesh Arora "What is an analytical SaaS company? It is a company that says, “I'm going to collect a lot of data for you and analyze it for you.” I don't need you to analyze it for me. I can run models against the data and analyze it myself. Think about it: almost every SaaS company has a marketplace. You can buy applications from the Salesforce Marketplace. What do those applications say? “You have Salesforce data. I'm a marketplace app. Use me, and I'll help you analyze that data.” But I don't need to do that. You don't need those applications anymore. I can simply run an LLM against the data. Therefore, all the additional functionality that has traditionally been sold to us as incremental software modules may no longer need to be sold separately. I would much rather have an LLM run against the data." ---- From "All-In Podcast" YouTube channel, (full video link in comment)

"If you're an analytical SaaS company, it's over. It's over." - Palo Alto Networks CEO Nikesh Arora "What is an analytical SaaS company? It is a company that says, “I'm going to collect a lot of data for you and analyze it for you.” I don't need you to analyze it for me. I can run models against the data and analyze it myself. Think about it: almost every SaaS company has a marketplace. You can buy applications from the Salesforce Marketplace. What do those applications say? “You have Salesforce data. I'm a marketplace app. Use me, and I'll help you analyze that data.” But I don't need to do that. You don't need those applications anymore. I can simply run an LLM against the data. Therefore, all the additional functionality that has traditionally been sold to us as incremental software modules may no longer need to be sold separately. I would much rather have an LLM run against the data." ---- From "All-In Podcast" YouTube channel, (full video link in comment)

Rohan Paul

40,959 次观看 • 14 天前

you can now export THOUSANDS of negative reviews off of the app store and feed it directly to claude opus 4.6 here's how it works: 1. choose any app category (fitness, productivity, social media, etc) 2. export the data as json (thousands of reviews + user pain points/feature requests) 3. upload it to claude and ask it anything i exported meal planner app data (10k reviews analyzed across 100+ apps) asked claude: "what features do users actually want in a meal planner app?" got back 60+ specific feature requests with validated demand so many opportunities with this data no more guessing what to build or what features to add just get exact features people are already begging for in reviews export the data, ask claude questions, get your entire product roadmap in seconds

you can now export THOUSANDS of negative reviews off of the app store and feed it directly to claude opus 4.6 here's how it works: 1. choose any app category (fitness, productivity, social media, etc) 2. export the data as json (thousands of reviews + user pain points/feature requests) 3. upload it to claude and ask it anything i exported meal planner app data (10k reviews analyzed across 100+ apps) asked claude: "what features do users actually want in a meal planner app?" got back 60+ specific feature requests with validated demand so many opportunities with this data no more guessing what to build or what features to add just get exact features people are already begging for in reviews export the data, ask claude questions, get your entire product roadmap in seconds

Om Patel

99,021 次观看 • 6 个月前

Introducing: Pulsar Scroll Accel At Pulsar, our focus is on creating esports equipment designed to empower pro gamers. No compromises: we won’t add unnecessary weight, complexity, or office/productivity features that don’t serve competitive gaming. Many in the community have requested an infinity scroll wheel on our mice. While one of the original inventors of the Infinity Wheel is part of our engineering team, we believe this feature doesn’t align with the needs of pro gaming. The added weight and mechanical complexity simply aren’t justified for high-level competitive play. Instead, we developed Scroll Accel—a firmware feature that makes any scroll wheel feel like an infinity wheel. Scroll slowly for precise, one-line increments, or spin quickly for ultra-fast scrolling. This feature will be turned off by default and can be turned on in our upcoming mice web drivers. (Including the #X2F) We’re always listening to the community and pro players to push innovation forward. Join the conversation at

Introducing: Pulsar Scroll Accel At Pulsar, our focus is on creating esports equipment designed to empower pro gamers. No compromises: we won’t add unnecessary weight, complexity, or office/productivity features that don’t serve competitive gaming. Many in the community have requested an infinity scroll wheel on our mice. While one of the original inventors of the Infinity Wheel is part of our engineering team, we believe this feature doesn’t align with the needs of pro gaming. The added weight and mechanical complexity simply aren’t justified for high-level competitive play. Instead, we developed Scroll Accel—a firmware feature that makes any scroll wheel feel like an infinity wheel. Scroll slowly for precise, one-line increments, or spin quickly for ultra-fast scrolling. This feature will be turned off by default and can be turned on in our upcoming mice web drivers. (Including the #X2F) We’re always listening to the community and pro players to push innovation forward. Join the conversation at

Pulsar Gaming Gears

38,566 次观看 • 1 年前

New Andrej Karpathy interview Says AI agent failures stem from user skill, not model capability. Poor instructions cause errors. He suggests delegating 20-minute macro actions like coding and research to parallel agents and reviewing their work. --- "I think everything, like so many things, even if they don't work, I think to a large extent you feel like it's a skill issue. It's not that the capability is not there; it's that you just haven't found a way to string together what's available. Like, I didn't give good enough instructions to the agents in the file, or whatever it may be. I don't have a nice enough memory tool that I put in there, or something like that. So, it all kind of feels like a skill issue when it doesn't work to some extent. You want to see how you can parallelize them, and you want to be a 'Pierce tender,' basically. Pierce famously has a funny photo where he's in front of lots of these Codex agents behind the monitor. They all take about 20 minutes if you run them correctly and use high effort. You have multiple—you know, 10 or 20—pull requests checked out. It's just like you can do much larger macro actions. It's not just, 'Here's a line of code, here's a new function.' It's like, 'Here's a new functionality, delegate it to agent one. Here's a new functionality that's not going to interfere with the other one, give it to agent two.' Then, you try to review their work as best as you can, depending on how much you care about that code. You look for these macro actions that you can manipulate your software repository by. Another agent is doing some research, another agent is writing code, another one is coming up with a plan for some new implementation. Everything just happens in these macro actions over your repository. You're just trying to become really good at it and develop a muscle memory for it. It's very rewarding when it actually works, but it's also a new thing to learn. Hence, the psychosis." --- From No Priors YT channel (link in comment)

New Andrej Karpathy interview Says AI agent failures stem from user skill, not model capability. Poor instructions cause errors. He suggests delegating 20-minute macro actions like coding and research to parallel agents and reviewing their work. --- "I think everything, like so many things, even if they don't work, I think to a large extent you feel like it's a skill issue. It's not that the capability is not there; it's that you just haven't found a way to string together what's available. Like, I didn't give good enough instructions to the agents in the file, or whatever it may be. I don't have a nice enough memory tool that I put in there, or something like that. So, it all kind of feels like a skill issue when it doesn't work to some extent. You want to see how you can parallelize them, and you want to be a 'Pierce tender,' basically. Pierce famously has a funny photo where he's in front of lots of these Codex agents behind the monitor. They all take about 20 minutes if you run them correctly and use high effort. You have multiple—you know, 10 or 20—pull requests checked out. It's just like you can do much larger macro actions. It's not just, 'Here's a line of code, here's a new function.' It's like, 'Here's a new functionality, delegate it to agent one. Here's a new functionality that's not going to interfere with the other one, give it to agent two.' Then, you try to review their work as best as you can, depending on how much you care about that code. You look for these macro actions that you can manipulate your software repository by. Another agent is doing some research, another agent is writing code, another one is coming up with a plan for some new implementation. Everything just happens in these macro actions over your repository. You're just trying to become really good at it and develop a muscle memory for it. It's very rewarding when it actually works, but it's also a new thing to learn. Hence, the psychosis." --- From No Priors YT channel (link in comment)

Rohan Paul

23,187 次观看 • 4 个月前

"In the future, you won't need any software at all. The neural network will completely replace it." - stephen balaban, co-founder of Lambda "Here's the idea: instead of generating a program, just go to ChatGPT and say, 'Hi, please behave like a calculator or a spreadsheet.'" "'Generate an ASCII user interface for me. And I want you to essentially just respond, implement the logic of that program in your mind.'" "This is what I call neural software. Normal software is really brittle. 'Neural software' can't have bugs, only misunderstandings." "Large language models will be the software you interact with."

"In the future, you won't need any software at all. The neural network will completely replace it." - stephen balaban, co-founder of Lambda "Here's the idea: instead of generating a program, just go to ChatGPT and say, 'Hi, please behave like a calculator or a spreadsheet.'" "'Generate an ASCII user interface for me. And I want you to essentially just respond, implement the logic of that program in your mind.'" "This is what I call neural software. Normal software is really brittle. 'Neural software' can't have bugs, only misunderstandings." "Large language models will be the software you interact with."

TBPN

178,100 次观看 • 1 年前