Loading video...

Video Failed to Load

There was a problem loading this video. This could be due to a temporary network issue or the video might be unavailable.

1.47 billion dots mapped across India - one for every person. Visualized in a browser on a laptop with MapLibre + PMTiles, built with freestiler. I developed freestiler earlier this year to make massive interactive mapping workflows more accessible. Until recently, I hadn't been able to push it above... 1 billion points. The latest batch of optimizations - coming soon to the package - make these sorts of workflows possible. In this workflow, freestiler streams in data from a parquet file, keeps memory in check by partitioning the data, and tiles in parallel with Rust. This tiling session took about 21 minutes on my MacBook with a peak memory usage under 9 GB. I'm working on making this even faster. The map here shows 1 dot for every person in India when fully zoomed in, derived from WorldPop 2026 population projections at 100m grid cells (modeled data, which is why you see uniform densities in large cities). Dots are placed randomly within those cells. I'll write up an article showing you how to do this soon.show more

Kyle Walker

20,220 subscribers

813,078 views • 8 days ago •via X (Twitter)

Education Science & Technology

Anya Rossi• Live Now

Private livecam show

32 Comments

IndieNat8 days ago

@maplibre Great feat. I fail to comprehend it’s usage. Could you elaborate more on that pls? Apart from the technical stuff of working with a huge dataset.

Kyle Walker7 days ago

this is a technical proof-of-concept - I wanted to see how far I could push the tool. In a practical sense, you can create visualizations like comfortably on a laptop. More broadly, if you need to show a lot of data for your app / client project, freestiler makes it possible. It's saved me many times. See this walkthrough:

Satya Gita8 days ago

@maplibre Excellent. Actually, real time position of about 1.2 Billion people of around above 10 years age is possible by tracing their mobile phone location from towers. Similar to Google Maps traffic density.

Kyle Walker8 days ago

For more about freestiler, check out:

Aniruddha7 days ago

@maplibre this such a horse shit visualization ...there seem to be no open space people are distributed like seeds on land

Raj Vira7 days ago

@maplibre This seems so good to understand but see, to make it a little bit hyper realistic, you can consider the building, humans today are not spreaded all on the ground, does not also mean to put people on flight or sky diving 😂 but would be cool if can be, live.

Kyle Walker7 days ago

@maplibre right - it's a proof of concept based on modeled data from WorldPop, which is projected onto a 100m grid. WorldPop's modeled populations are smoothed over within cities, in particular.

Dharmik patel8 days ago

@maplibre Since the dots are sampled inside the 100m cells, the point set is fully regenerable from the grid. Seeding that RNG gets you reproducible tiles without ever storing the 1.47B points anywhere.

S SINGH8 days ago

@maplibre Hyderabad 🇮🇳 ♥️

Alex Pastrana8 days ago

@maplibre

Yogesh Kumar8 days ago

@maplibre Puts my Valhalla server to shame 🥲 Looks so good!

Ak7 days ago

@maplibre Use the correct map of India

Raj Nednur7 days ago

@maplibre Do you have one for US ?

Lioness7 days ago

@maplibre This is reason enough tobecome fully independent in every field and build an Indian firewall against such intrusion. West is notorious with subhuman values. They have no ethics. They have no place here.

MAXPAIN7 days ago

@maplibre Reminds of the mycelium expmt done in Japan

Aveiro7 days ago

@maplibre @grok what is this

Sentinel Island Chief🌐7 days ago

@maplibre @grok what is it used for??

P8 days ago

@maplibre nice

Varun7 days ago

@maplibre @grok, whats this all about, give the background

Aaron Chand7 days ago

@maplibre Crazy how Himachal and Uttarakhand look compared to everywhere else.

Duryodhana7 days ago

Now you will have swarm of Indians following you and getting you more well deserved engagement for this highly optimized visualization involving over 1 billion points! It's commendable what you did there, I just request you to use the correct map of India🇮🇳. Looking forward to your work and using it in my work!

Ritam De8 days ago

@maplibre Baap re

Ch DD7 days ago

@maplibre Kyle There muat be some reason u cant ignore indians.. Whats thr trauma ? Why so much anger?

Valerio Amirani7 days ago

@maplibre Watching where users drop off and fixing broken buttons increases MRR faster than acquiring more cold traffic. That is why we built Zenovay ( with replays and heatmaps in one script. What conversion bottleneck are you working on next?

VJ7 days ago

@maplibre Why only India was chosen?

Jitu 🇮🇳7 days ago

@maplibre Map of India Correct it

Siddhesh7 days ago

@maplibre Interesting for check population density at a much more granular level.

Shubh B7 days ago

@maplibre Deep state asset @kyle_e_walker

AK7 days ago

@maplibre What proves the authenticity ?

femboys over religion7 days ago

@maplibre Nuke east up bihar and bengal

ZEROLINE | Z7 days ago

@maplibre @grok what is this

Namma India ನಮ್ಮ ಭಾರತ 🇮🇳8 days ago

@maplibre _

Related Videos

No more importing PCBs from China when you can make them at a much cheaper rate in India. Just 1 week ago, I sent a sample to Vishal. Last night : ✅ Design locked ✅ Cost calculated ✅ 3D File sent This is will be our first in-house PCB for our fan. Earlier we had to rely on China. Now we build it here, with our people, and Indian machines, at a lower cost. Vishal built the machine himself. He teaches, he builds, he leads. This is more than “Make in India.” It’s believe in India. And it’s working. More details coming soon. 🇮🇳 Vishal Tejwani

No more importing PCBs from China when you can make them at a much cheaper rate in India. Just 1 week ago, I sent a sample to Vishal. Last night : ✅ Design locked ✅ Cost calculated ✅ 3D File sent This is will be our first in-house PCB for our fan. Earlier we had to rely on China. Now we build it here, with our people, and Indian machines, at a lower cost. Vishal built the machine himself. He teaches, he builds, he leads. This is more than “Make in India.” It’s believe in India. And it’s working. More details coming soon. 🇮🇳 Vishal Tejwani

Prakash Dadlani

150,450 views • 1 year ago

Meta spent $40 billion and 10 years trying to make hand tracking feel natural. This guy did it with Claude in a weekend. No code written. No team. No hardware. He described what he wanted, Claude built it. The app tracks every finger, every joint, every movement live on his laptop. Physics bend around his hands in real time. The $40B industry just got embarrassed by one person with a Claude subscription. Everything you need to start building like this is in the article above.

Meta spent $40 billion and 10 years trying to make hand tracking feel natural. This guy did it with Claude in a weekend. No code written. No team. No hardware. He described what he wanted, Claude built it. The app tracks every finger, every joint, every movement live on his laptop. Physics bend around his hands in real time. The $40B industry just got embarrassed by one person with a Claude subscription. Everything you need to start building like this is in the article above.

Anatoli Kopadze

190,411 views • 4 months ago

I got a smart meter recently and saw you can download a HDF file with the data so I had the idea of writing a script that could parse that and show the data in a useful manner. However I discovered that someone has already done this and done a really good job on it. The video explains how it works. In simple terms it uses the ESB smart meter data and shows a breakdown of how much data you are using and when and also recommends plans and estimates what each one would cost based on the data. The tool is available at easier to read on Laptop or Tablet or then your phone to Landscape.

I got a smart meter recently and saw you can download a HDF file with the data so I had the idea of writing a script that could parse that and show the data in a useful manner. However I discovered that someone has already done this and done a really good job on it. The video explains how it works. In simple terms it uses the ESB smart meter data and shows a breakdown of how much data you are using and when and also recommends plans and estimates what each one would cost based on the data. The tool is available at easier to read on Laptop or Tablet or then your phone to Landscape.

Carlow Weather

298,565 views • 2 years ago

Today, Box is announcing major new AI agent capabilities to let customers tap into the full value of their unstructured data. First, we’re announcing all new updates to the Box AI Studio to make it even easier to build AI agents that tap into your enterprise content for any job function, business process, or industry specific use case. We are also expanding our set of foundational agents that customers will be able to use to work with their enterprise content, including new features like search and research on unstructured data. Next, we’re announcing Box Extract to enable customers to use AI agents seamlessly for complex data extraction from any type of document or content. This makes it easier than ever to pull out data from contracts, invoices, research data, marketing assets, medical charts, and more. Finally, we’re introducing Box Automate, a new workflow automation solution within Box that lets you deploy AI agents across enterprise content-centric workflows. With Box Automate, you can design your business process in a simple drag and drop builder and then drop in AI agents at any step in the process. This ensures agents execute tasks at the right steps in a workflow every time. Best of all, our AI agents and workflow tools are designed to work across any system our customers work within, whether it’s leveraging pre-built integrations, Box APIs, or the new Box MCP Server. Ultimately, all of these capabilities come together to transform how companies can work with their enterprise content. Software has historically only been good at automating work that deals with structured data, which is why ERP, CRM, and HR systems have been mainstays of enterprise software for so long. The data in these systems fits neatly into a database, and the workflows are very ripe for automation. But it turns out most of the work in the world deals with unstructured data. It’s ideating through research documents, working with a client on contracts, reviewing details for a new product launch, looking at a patient’s healthcare record to make a diagnosis, working through due diligence documents for an M&A deal, and so on. For the first time ever, we can begin to bring all new insights and automation to this work with AI agents. At Box, we’re incredibly excited to be on this journey to help customers transform how they work with their most important data.

Today, Box is announcing major new AI agent capabilities to let customers tap into the full value of their unstructured data. First, we’re announcing all new updates to the Box AI Studio to make it even easier to build AI agents that tap into your enterprise content for any job function, business process, or industry specific use case. We are also expanding our set of foundational agents that customers will be able to use to work with their enterprise content, including new features like search and research on unstructured data. Next, we’re announcing Box Extract to enable customers to use AI agents seamlessly for complex data extraction from any type of document or content. This makes it easier than ever to pull out data from contracts, invoices, research data, marketing assets, medical charts, and more. Finally, we’re introducing Box Automate, a new workflow automation solution within Box that lets you deploy AI agents across enterprise content-centric workflows. With Box Automate, you can design your business process in a simple drag and drop builder and then drop in AI agents at any step in the process. This ensures agents execute tasks at the right steps in a workflow every time. Best of all, our AI agents and workflow tools are designed to work across any system our customers work within, whether it’s leveraging pre-built integrations, Box APIs, or the new Box MCP Server. Ultimately, all of these capabilities come together to transform how companies can work with their enterprise content. Software has historically only been good at automating work that deals with structured data, which is why ERP, CRM, and HR systems have been mainstays of enterprise software for so long. The data in these systems fits neatly into a database, and the workflows are very ripe for automation. But it turns out most of the work in the world deals with unstructured data. It’s ideating through research documents, working with a client on contracts, reviewing details for a new product launch, looking at a patient’s healthcare record to make a diagnosis, working through due diligence documents for an M&A deal, and so on. For the first time ever, we can begin to bring all new insights and automation to this work with AI agents. At Box, we’re incredibly excited to be on this journey to help customers transform how they work with their most important data.

Aaron Levie

91,863 views • 1 year ago

Day 14/90 of Inference Engineering I didn't finish the MNIST in CUDA project today, which made me hesitant to post since I didn't want to put out some slop. But in the spirit of being consistent and showing up, here's a concept I've revisited today now that I've started writing CUDA again. This is an animation on the CUDA memory life cycle. Generally speaking, when writing CUDA, memory management goes through the following stages: 1. Allocate memory on the host 2.Initialize / populate the memory 3.Allocate device memory 4.Copy host data to the device 5. Launch the kernel 6. Copy device data back to the host 7. Free the memory - On a brief reflection, I'm starting to write the matmul kernels in CUDA instead of in C. So this in itself is another paradigm shift in thinking. Excited to hone my technique over the coming week. I'll update you guys when I've completed the project; otherwise I'll just make a post like usual on what I've learned during the day!

Day 14/90 of Inference Engineering I didn't finish the MNIST in CUDA project today, which made me hesitant to post since I didn't want to put out some slop. But in the spirit of being consistent and showing up, here's a concept I've revisited today now that I've started writing CUDA again. This is an animation on the CUDA memory life cycle. Generally speaking, when writing CUDA, memory management goes through the following stages: 1. Allocate memory on the host 2.Initialize / populate the memory 3.Allocate device memory 4.Copy host data to the device 5. Launch the kernel 6. Copy device data back to the host 7. Free the memory - On a brief reflection, I'm starting to write the matmul kernels in CUDA instead of in C. So this in itself is another paradigm shift in thinking. Excited to hone my technique over the coming week. I'll update you guys when I've completed the project; otherwise I'll just make a post like usual on what I've learned during the day!

max fu

42,808 views • 2 months ago

2 billion people use spreadsheets every month. Their lives are about to change. Here is ChatGPT integrated natively on spreadsheets. It's one of the best applications of AI that will spread in 2024. You now have access to: • Generate content based on other cells • Summarize, translate, and rewrite • Analyze reviews at scale • Reformatting and extracting information • Enriching existing data And it's as simple as using ChatGPT as a spreadsheet formula. This is Numerous.ai. They collaborated with me on this post. Their tool came out in March last year. I think it will explode in the coming months. Check it out here:

2 billion people use spreadsheets every month. Their lives are about to change. Here is ChatGPT integrated natively on spreadsheets. It's one of the best applications of AI that will spread in 2024. You now have access to: • Generate content based on other cells • Summarize, translate, and rewrite • Analyze reviews at scale • Reformatting and extracting information • Enriching existing data And it's as simple as using ChatGPT as a spreadsheet formula. This is Numerous.ai. They collaborated with me on this post. Their tool came out in March last year. I think it will explode in the coming months. Check it out here:

Santiago

431,344 views • 2 years ago

The Indian SaaS market is expected to grow to $50 billion by 2030! The future of software as a service (SaaS) seems exciting globally, and more so in India. In a study by Bessemer, it is estimated that the Indian SaaS market is expected to grow from $13 billion in 2022 to $50 billion by 2030. So, what’s stopping an Indian company from becoming the next Salesforce? Join me in the latest episode of the Create Wealth podcast to know exactly this! In this all new episode I speak to kuldeep, founder of one of India’s leading SaaS companies. With over 20 years of experience across Nokia, Microsoft and CleverTap his journey building brands and solving problems for businesses is a masterclass for those who work in SaaS businesses and sales roles across industries. This is in the longest episode of our podcast, and with good reason! Kuldeep’s deep knowledge of emerging technologies, the SaaS segment in India and his intensive insights from global tech companies makes this episode a treasure trove of experiences and learnings. In this episode, you'll learn: - Why India is a goldmine for SaaS companies - How to build a winning SaaS product from the ground up - The secret sauce to scaling your SaaS sales - How VCs see the booming SaaS landscape in India For more such gems watch the entire episode.

The Indian SaaS market is expected to grow to $50 billion by 2030! The future of software as a service (SaaS) seems exciting globally, and more so in India. In a study by Bessemer, it is estimated that the Indian SaaS market is expected to grow from $13 billion in 2022 to $50 billion by 2030. So, what’s stopping an Indian company from becoming the next Salesforce? Join me in the latest episode of the Create Wealth podcast to know exactly this! In this all new episode I speak to kuldeep, founder of one of India’s leading SaaS companies. With over 20 years of experience across Nokia, Microsoft and CleverTap his journey building brands and solving problems for businesses is a masterclass for those who work in SaaS businesses and sales roles across industries. This is in the longest episode of our podcast, and with good reason! Kuldeep’s deep knowledge of emerging technologies, the SaaS segment in India and his intensive insights from global tech companies makes this episode a treasure trove of experiences and learnings. In this episode, you'll learn: - Why India is a goldmine for SaaS companies - How to build a winning SaaS product from the ground up - The secret sauce to scaling your SaaS sales - How VCs see the booming SaaS landscape in India For more such gems watch the entire episode.

Sandeep Jethwani

41,233 views • 2 years ago

This is Anagha Rajesh. And she is crazy. She wants to store data in bacterial DNA. Her startup is called BioCompute. And last year, they actually did it. They stored data in DNA and retrieved it in their tiny lab in Bengaluru. This is a huge moment. But why is she even doing it? Because DNA is the ultimate storage tool available to us. Just 1 gm of DNA can store about 215 petabytes of data - that's like storing over 2 million movies in 4K. On top of that - this data can last for literally 1000s of years. Right now, they still need to figure out a way to make the reading and writing process faster and cheaper. But if BioCompute solves this problem - we could theoretically store all the data created in the world every year in the palm of our hands. And that would be insane. P.S. Check out this video from vyom going to Anagha's lab and actually doing it.

This is Anagha Rajesh. And she is crazy. She wants to store data in bacterial DNA. Her startup is called BioCompute. And last year, they actually did it. They stored data in DNA and retrieved it in their tiny lab in Bengaluru. This is a huge moment. But why is she even doing it? Because DNA is the ultimate storage tool available to us. Just 1 gm of DNA can store about 215 petabytes of data - that's like storing over 2 million movies in 4K. On top of that - this data can last for literally 1000s of years. Right now, they still need to figure out a way to make the reading and writing process faster and cheaper. But if BioCompute solves this problem - we could theoretically store all the data created in the world every year in the palm of our hands. And that would be insane. P.S. Check out this video from vyom going to Anagha's lab and actually doing it.

Varun Guru

255,644 views • 3 months ago

Just gave a demo at Every 📧's Vibe Code Camp showing how I use a kanban board to stay sane while overseeing Claude Code agents😎 Here's a quick recap video showing the whole flow: 1) Monitor progress on all tasks in one view 2) See when Claude is blocked, and respond in context 3) Read Claude's plans with nice formatting, not raw Markdown 4) Use AI to process voice notes into structured tasks 5) Get explanations of code changes... with an interactive quiz to check if you understood 🙃 I've had mixed feelings about kanban workflows in the past, but as the agents get stronger I'm warming up to them—especially for churning through small well-specified tasks. In that context, it feels like the challenge is managing my working memory for what's going on. And having a stable "zoomed-out map" of all the tasks really helps me with offloading some of that cognitive load to a visualization of everything that's going on!

Just gave a demo at Every 📧's Vibe Code Camp showing how I use a kanban board to stay sane while overseeing Claude Code agents😎 Here's a quick recap video showing the whole flow: 1) Monitor progress on all tasks in one view 2) See when Claude is blocked, and respond in context 3) Read Claude's plans with nice formatting, not raw Markdown 4) Use AI to process voice notes into structured tasks 5) Get explanations of code changes... with an interactive quiz to check if you understood 🙃 I've had mixed feelings about kanban workflows in the past, but as the agents get stronger I'm warming up to them—especially for churning through small well-specified tasks. In that context, it feels like the challenge is managing my working memory for what's going on. And having a stable "zoomed-out map" of all the tasks really helps me with offloading some of that cognitive load to a visualization of everything that's going on!

Geoffrey Litt

78,473 views • 8 months ago

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 views • 1 year ago

Experiments in progress. The one on the right has been learning for ~3 hours, the one in the middle for ~1 hour, and the one on the left just started a few minutes ago. The initial motivation for making the physical Atari was just to commit ourselves to a subset of algorithms that can make progress in this setup. This commitment rules out algorithms that require billions of samples to learn (or worse, require multiple environments running in parallel). Atari games are simple enough that we should be able to show learning on them in a short amount of time with no prior knowledge. Since then, I've realized that this setup is also a good way to compare different paradigms in robotics in a principled way. These paradigms are sim2real, learning from tele-operated data, and learning directly on the robots. So far, I have observed that getting sim2real to work reliably is hard. It requires tweaks that don't scale. Policies that can play perfectly in simulation fall apart because of latencies and the messiness of the real world. These aspects could be modeled to improve the simulation, but not without sinking significant human engineering hours. I have higher hopes for learning from tele-operated data, but that requires a human to learn the task first. These experiments are on my to-do list. I have to learn to play some of the games well through the robot. I’m half-decent at playing Pong and Ms Pacman now. Learning directly on robots is looking like the most promising approach. This approach takes away pesky distribution shifts and makes it possible to have algorithms that continually improve with more data and time without any human intervention. It feels great to let experiments run overnight and wake up to find improved policies. With learning on robots, I should, in principle, be able to go on a long vacation and come back to find better policies for complex tasks beyond Atari games. Whether that is possible with current learning algorithms is a different question.

Experiments in progress. The one on the right has been learning for ~3 hours, the one in the middle for ~1 hour, and the one on the left just started a few minutes ago. The initial motivation for making the physical Atari was just to commit ourselves to a subset of algorithms that can make progress in this setup. This commitment rules out algorithms that require billions of samples to learn (or worse, require multiple environments running in parallel). Atari games are simple enough that we should be able to show learning on them in a short amount of time with no prior knowledge. Since then, I've realized that this setup is also a good way to compare different paradigms in robotics in a principled way. These paradigms are sim2real, learning from tele-operated data, and learning directly on the robots. So far, I have observed that getting sim2real to work reliably is hard. It requires tweaks that don't scale. Policies that can play perfectly in simulation fall apart because of latencies and the messiness of the real world. These aspects could be modeled to improve the simulation, but not without sinking significant human engineering hours. I have higher hopes for learning from tele-operated data, but that requires a human to learn the task first. These experiments are on my to-do list. I have to learn to play some of the games well through the robot. I’m half-decent at playing Pong and Ms Pacman now. Learning directly on robots is looking like the most promising approach. This approach takes away pesky distribution shifts and makes it possible to have algorithms that continually improve with more data and time without any human intervention. It feels great to let experiments run overnight and wake up to find improved policies. With learning on robots, I should, in principle, be able to go on a long vacation and come back to find better policies for complex tasks beyond Atari games. Whether that is possible with current learning algorithms is a different question.

Khurram Javed

52,110 views • 9 months ago

I woke up this morning to the news that our debut album, “catharsis,” has crossed 1 billion streams across all platforms. It’s crazy to think that we did this in exactly one year. I want to use this moment to thank God, everyone who has shown me kindness on this journey, every collaborator, every team involved, and most importantly, everyone who listened, shared, and connected with this music. You gave these songs a life I could’ve never imagined. A billion is just a number. I’ll hold the memories forever. Oro mi, lowo Olorun lowa (My life is in the hands of God)

I woke up this morning to the news that our debut album, “catharsis,” has crossed 1 billion streams across all platforms. It’s crazy to think that we did this in exactly one year. I want to use this moment to thank God, everyone who has shown me kindness on this journey, every collaborator, every team involved, and most importantly, everyone who listened, shared, and connected with this music. You gave these songs a life I could’ve never imagined. A billion is just a number. I’ll hold the memories forever. Oro mi, lowo Olorun lowa (My life is in the hands of God)

FOLA

200,695 views • 23 days ago

Right now the main paradigm that we think of agents in is chatting back and forth, but the biggest use of tokens will come from agents that are just always on running in the background doing work for us, or ones triggered from a workflow. Agents will be working 24/7 in our workflows processing data, reviewing and generating documents, moving data between systems, writing code, accelerating decision making steps, and more. In Claude's new Managed Agents feature, in a couple minutes you can wire up an agent that can read contracts when they come into Box to review them, and then assign a task in Linear with the critical information from the contract. But this could have been any workflow, like reviewing documents for client onboarding, invoice processing, M&A due-diligence, data extraction pipelines, and millions of other use-cases. And integrating data across any system. This is only possible when you can have long-running agents that can complete real work in the background, accurately. Agents have the ability to execute code safely, leverage tools, access a compute sandbox, and connect across systems is clearly the architecture of the future. The industry is now making it easier and easier for enterprises to build and deploy these agents.

Right now the main paradigm that we think of agents in is chatting back and forth, but the biggest use of tokens will come from agents that are just always on running in the background doing work for us, or ones triggered from a workflow. Agents will be working 24/7 in our workflows processing data, reviewing and generating documents, moving data between systems, writing code, accelerating decision making steps, and more. In Claude's new Managed Agents feature, in a couple minutes you can wire up an agent that can read contracts when they come into Box to review them, and then assign a task in Linear with the critical information from the contract. But this could have been any workflow, like reviewing documents for client onboarding, invoice processing, M&A due-diligence, data extraction pipelines, and millions of other use-cases. And integrating data across any system. This is only possible when you can have long-running agents that can complete real work in the background, accurately. Agents have the ability to execute code safely, leverage tools, access a compute sandbox, and connect across systems is clearly the architecture of the future. The industry is now making it easier and easier for enterprises to build and deploy these agents.

Aaron Levie

17,543 views • 5 months ago

Collective Reading 🩷🥹 There’s someone about to come in with a love message or a heartfelt message to you. For some they’re gonna have a friend relate this message. Apart of the lyrics say “Cause I got plans, give me your hand. How long will it take for you to understand? I'm your biggest fan, I'm your biggest fan”. -Rod Wave- IRAN You or this person could be #Libra #Virgo #Sagittarius #Cancer #Scorpio #Pisces #Taurus #Capricorn Someone woke up thinking about you. Even had a dream about you. Soulmate/a twin flame connection. This person is so mad at themselves and has a deep love for you. You walking away and not looking back and leaving this person behind has this person all messed up. This person is on a search to see if they can make this right. They’re willing to do whatever for you, be there for you. This person will move mountains for you if they have to. The memories are forever stuck with this person. Your in this person plans on their mind. Expect a random message with a song or lyrics. You will see this person soon.

Sensitive content

Collective Reading 🩷🥹 There’s someone about to come in with a love message or a heartfelt message to you. For some they’re gonna have a friend relate this message. Apart of the lyrics say “Cause I got plans, give me your hand. How long will it take for you to understand? I'm your biggest fan, I'm your biggest fan”. -Rod Wave- IRAN You or this person could be #Libra #Virgo #Sagittarius #Cancer #Scorpio #Pisces #Taurus #Capricorn Someone woke up thinking about you. Even had a dream about you. Soulmate/a twin flame connection. This person is so mad at themselves and has a deep love for you. You walking away and not looking back and leaving this person behind has this person all messed up. This person is on a search to see if they can make this right. They’re willing to do whatever for you, be there for you. This person will move mountains for you if they have to. The memories are forever stuck with this person. Your in this person plans on their mind. Expect a random message with a song or lyrics. You will see this person soon.

✨HOTGIRLTAROTSHA✨

28,106 views • 1 year ago

🇮🇳An apology to all my readers, especially those from India Saturday, I was looking for videos of aircraft landing in the highest airports in the world. I googled for a video, found this on Reddit, from an Airport in Tibet, and shared it with the description. I should have been suspicious that reverse searches were not getting more videos of the place, and that the Reddit account from the post was from a deleted user. Anyway, this isn´t in Tibet, it´s in INDIA! This is actually Kushok Bakula Rimpochee Airport (VILH/IXL) in Leh, Ladakh. (On what could be salvaged from my goof, it is what I intended to show. The aircraft seen here is landing in one of the highest commercial airports in the world, sitting at over 10800 feet - over 3 kms up in the air!) I want to thank Captain The Joker for the help on this one, who also noted that only Captains are allowed to land here - it requires a special qualification to operate here Once again, sorry for my mistake, goods happen here and then, but this one was really far from the correct info (literally)

🇮🇳An apology to all my readers, especially those from India Saturday, I was looking for videos of aircraft landing in the highest airports in the world. I googled for a video, found this on Reddit, from an Airport in Tibet, and shared it with the description. I should have been suspicious that reverse searches were not getting more videos of the place, and that the Reddit account from the post was from a deleted user. Anyway, this isn´t in Tibet, it´s in INDIA! This is actually Kushok Bakula Rimpochee Airport (VILH/IXL) in Leh, Ladakh. (On what could be salvaged from my goof, it is what I intended to show. The aircraft seen here is landing in one of the highest commercial airports in the world, sitting at over 10800 feet - over 3 kms up in the air!) I want to thank Captain The Joker for the help on this one, who also noted that only Captains are allowed to land here - it requires a special qualification to operate here Once again, sorry for my mistake, goods happen here and then, but this one was really far from the correct info (literally)

Francisco Cunha - ✈️ Aviation et al

396,287 views • 7 months ago

More progress! I now have two Dockerized Gradio | Rerun apps. The first one takes as input a "raw" rrd file that consists of the synchronized egocentric and exocentric MP4 files. This runs the pipeline and produces an "annotated" rrd file. This has the camera parameters, 3D joints, and projected 2D joints (with 6DOF mano soon). The second app takes this "annotated" rrd file and allows for manual labeling. This is a crucial step in addressing any major failures in the pipeline. Right now, it is only the ego view that can be modified. But I'll eventually extend to all. This results in a final "gt" rrd file. From here, the plan is to improve quality and start building a data loop. Excited to start really scaling this. I'm basically going all in on keeping my data stored as Rerun rrd files. As always, I want to emphasize how crucial it is to LOOK AT YOUR data! The rrd format makes it incredibly easy to do so. Getting the data out to use is a bit of a hassle right now, but for me, it's well worth the tradeoff.

More progress! I now have two Dockerized Gradio | Rerun apps. The first one takes as input a "raw" rrd file that consists of the synchronized egocentric and exocentric MP4 files. This runs the pipeline and produces an "annotated" rrd file. This has the camera parameters, 3D joints, and projected 2D joints (with 6DOF mano soon). The second app takes this "annotated" rrd file and allows for manual labeling. This is a crucial step in addressing any major failures in the pipeline. Right now, it is only the ego view that can be modified. But I'll eventually extend to all. This results in a final "gt" rrd file. From here, the plan is to improve quality and start building a data loop. Excited to start really scaling this. I'm basically going all in on keeping my data stored as Rerun rrd files. As always, I want to emphasize how crucial it is to LOOK AT YOUR data! The rrd format makes it incredibly easy to do so. Getting the data out to use is a bit of a hassle right now, but for me, it's well worth the tradeoff.

Pablo Vela

19,527 views • 11 months ago

This is incredibly useful for those using Claude Code! I have two computers, and sharing your Claude Code sessions is almost impossible without this. I often start working on something on my desktop, and then want to continue working on the same session (same context, conversation, etc.) on my laptop. The folks at Depot built an integration that solves this problem: You can now start a session on one computer and resume it anywhere else in the world! You can even share it with other team members so they can also contribute to it. Here is an article showing you how the Depot team uses this feature with Claude Code to automate their GitHub Actions Runner updates: Thanks to the team for the effort in building this integration and collaborating with me on this post.

This is incredibly useful for those using Claude Code! I have two computers, and sharing your Claude Code sessions is almost impossible without this. I often start working on something on my desktop, and then want to continue working on the same session (same context, conversation, etc.) on my laptop. The folks at Depot built an integration that solves this problem: You can now start a session on one computer and resume it anywhere else in the world! You can even share it with other team members so they can also contribute to it. Here is an article showing you how the Depot team uses this feature with Claude Code to automate their GitHub Actions Runner updates: Thanks to the team for the effort in building this integration and collaborating with me on this post.

Santiago

43,943 views • 11 months ago

$🚨MAJOR ANNOUNCEMENT: I have been accepted into Daniel O'Shea 's AI software Accelerator This is a BIG deal Over the past couple months I've been building something huge in private. It's an AI powered X content tool that I believe will change the world This accelerator was a dream of mine to join. I'm now going to have the support and resources to make this the most powerful AI tool in content history I'm not just an algo guy. I'm not just a growth guy. I'm not just a Trader Joe's ice cream sandwich guy After this accelerator I will be the 1 person billion dollar business guy My tool is called Creator Buddy and it will make your content 1000x better You'll come up with more ideas and create greater content in a fraction of the time With Creator Buddy you'll be able to: • Create posts quickly • Use AI to repurpose posts for multiple platforms • Have an AI content coach that is trained on ALL of your content and can tell you how to make better content and get more followers • Generate endless content ideas • Use proven post templates • The most powerful AI content analytics on planet earth And much much much more The best part is I'll be building this entire thing in public I'm already 80% done. But once I launch I'll be going live every day to build in front of you. You can give me ideas and I'll ship those ideas live Beta testing starts in the next month and I'm letting a bunch of you guys in I'll be choosing 10 people who like/repost/and comment down below to beta test on day 1 Let me know 1 thing you'd want in a tool like this. Subscribers will get in the beta automatically Will be reaching out over DM shortly to the 10 winners This accelerator is a MASSIVE step for me in my career and life I will be the first person ever to build a 1 man billion dollar business in public I absolutely can't wait to take you along for the ride (after you like/reply/repost check DM in a little for beta invite)$

🚨MAJOR ANNOUNCEMENT: I have been accepted into Daniel O'Shea 's AI software Accelerator This is a BIG deal Over the past couple months I've been building something huge in private. It's an AI powered X content tool that I believe will change the world This accelerator was a dream of mine to join. I'm now going to have the support and resources to make this the most powerful AI tool in content history I'm not just an algo guy. I'm not just a growth guy. I'm not just a Trader Joe's ice cream sandwich guy After this accelerator I will be the 1 person billion dollar business guy My tool is called Creator Buddy and it will make your content 1000x better You'll come up with more ideas and create greater content in a fraction of the time With Creator Buddy you'll be able to: • Create posts quickly • Use AI to repurpose posts for multiple platforms • Have an AI content coach that is trained on ALL of your content and can tell you how to make better content and get more followers • Generate endless content ideas • Use proven post templates • The most powerful AI content analytics on planet earth And much much much more The best part is I'll be building this entire thing in public I'm already 80% done. But once I launch I'll be going live every day to build in front of you. You can give me ideas and I'll ship those ideas live Beta testing starts in the next month and I'm letting a bunch of you guys in I'll be choosing 10 people who like/repost/and comment down below to beta test on day 1 Let me know 1 thing you'd want in a tool like this. Subscribers will get in the beta automatically Will be reaching out over DM shortly to the 10 winners This accelerator is a MASSIVE step for me in my career and life I will be the first person ever to build a 1 man billion dollar business in public I absolutely can't wait to take you along for the ride (after you like/reply/repost check DM in a little for beta invite)

Alex Finn

51,952 views • 1 year ago