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Sync engines enable instantly responsive UI. But the tradeoff is usually slow startup because all data must be pre-loaded. Zero's query-driven sync enables precise control over when data syncs. To demonstrate, we scaled our "zbugs" demo up to 2.5M rows. Introducing Gigabugs:

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Aaron Boodman

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53,422 Aufrufe • vor 9 Monaten •via X (Twitter)

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Quick demo of Zero’s new background queries. Zero’s sync is query-based. Rather than specifying what data you want using rules or some other separate system, you just use queries. Right inside the client app, you do a query using a full sql-style language. You get filters, subqueries , limits, etc. Zero syncs the data backing these queries to the client. It’s important to realize Zero isn’t really a cache. It’s a replica. It’s eagerly replicating a precise snapshot of a slice of your database - the slice covered by the queries you have open. So there is never stale data in Zero. When you close a query we delete the rows uniquely returned by that query because we can no longer keep them up to date. Of course that kind of sucks for the common case of doing a query, navigating, then pressing “back”. Ideally we want that back nav to be fast. To address this Zero 0.17 adds background queries. You can add a ttl to a query and it will keep running and syncing in the background. This is much different than normal caching because this data stays up to date. If you make the same query again, the results will be *instantly* available *and already up to date with server*. If you make a different query the data from the background query is used client-side to answer the new query instantly if possible. This all happens completely automatically. Just by adding the ttl flag.
1:01

Quick demo of Zero’s new background queries. Zero’s sync is query-based. Rather than specifying what data you want using rules or some other separate system, you just use queries. Right inside the client app, you do a query using a full sql-style language. You get filters, subqueries , limits, etc. Zero syncs the data backing these queries to the client. It’s important to realize Zero isn’t really a cache. It’s a replica. It’s eagerly replicating a precise snapshot of a slice of your database - the slice covered by the queries you have open. So there is never stale data in Zero. When you close a query we delete the rows uniquely returned by that query because we can no longer keep them up to date. Of course that kind of sucks for the common case of doing a query, navigating, then pressing “back”. Ideally we want that back nav to be fast. To address this Zero 0.17 adds background queries. You can add a ttl to a query and it will keep running and syncing in the background. This is much different than normal caching because this data stays up to date. If you make the same query again, the results will be *instantly* available *and already up to date with server*. If you make a different query the data from the background query is used client-side to answer the new query instantly if possible. This all happens completely automatically. Just by adding the ttl flag.

Aaron Boodman

18,808 Aufrufe • vor 1 Jahr

OpenCode is about to get more powerful with remote sandboxes I showed a brief demo before, but here's a much more in-depth demo. it's not hard to add basic support for a remote env, but handling all the edge cases like when a remote env gets deleted is difficult. especially if care about good UX You never want to lose session data. so the choices are: run the session in your env, but run all tool calls remotely. that's too complex and painful. The other way is to just let the full session run remotely, but sync back all the session data in your env. We chose this path: we built a syncing system which logs all events in a way that we can always recreate your entire session. That means the remote env could get destroyed, but we can easily restore it. it also opens up other interesting ideas which we'll be exploring
2:32

OpenCode is about to get more powerful with remote sandboxes I showed a brief demo before, but here's a much more in-depth demo. it's not hard to add basic support for a remote env, but handling all the edge cases like when a remote env gets deleted is difficult. especially if care about good UX You never want to lose session data. so the choices are: run the session in your env, but run all tool calls remotely. that's too complex and painful. The other way is to just let the full session run remotely, but sync back all the session data in your env. We chose this path: we built a syncing system which logs all events in a way that we can always recreate your entire session. That means the remote env could get destroyed, but we can easily restore it. it also opens up other interesting ideas which we'll be exploring

James Long

304,885 Aufrufe • vor 4 Monaten

Instagram launches forced Data Collection to use their app If you login and get this prompt, you must accept data all this data collection or you will be promoted to log out and not allowed to use the App Here is a full down of what’s mandatory to give up to use Instagram: Collection and use of personal data: They collect our activity on Instagram (posts, stories, likes, comments, searches, time spent), device info, IP address, contacts (if synced), messages, location (when enabled), demographics, and inferred interests Sharing of data with other Meta companies. They take all the personal data they collected and share across Facebook, WhatsApp, Threads, Oculus, etc. Cross-border transfers of personal data: Your data is sent and stored in the US and other countries where Meta has offices/data centers or partners. Location information: Precise location (GPS when you use features like Stories or check-ins), approximate location from IP/Wi-Fi, and location-based activity history. Stop using META products
2:24

Instagram launches forced Data Collection to use their app If you login and get this prompt, you must accept data all this data collection or you will be promoted to log out and not allowed to use the App Here is a full down of what’s mandatory to give up to use Instagram: Collection and use of personal data: They collect our activity on Instagram (posts, stories, likes, comments, searches, time spent), device info, IP address, contacts (if synced), messages, location (when enabled), demographics, and inferred interests Sharing of data with other Meta companies. They take all the personal data they collected and share across Facebook, WhatsApp, Threads, Oculus, etc. Cross-border transfers of personal data: Your data is sent and stored in the US and other countries where Meta has offices/data centers or partners. Location information: Precise location (GPS when you use features like Stories or check-ins), approximate location from IP/Wi-Fi, and location-based activity history. Stop using META products

Wall Street Apes

264,539 Aufrufe • vor 1 Monat

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!
9:28

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 Aufrufe • vor 9 Monaten

Humbled to share that we successfully test fired 4 semi-cryogenic rocket engines simultaneously, as a cluster. All the 4 engines are 3d printed as single pieces of hardware - designed and manufactured in-house at AgniKul Cosmos Rocket Factory - 1. As with all our propulsion systems, these 4 engines are also powered by electric motor driven pumps. This test involved calibrating 8 pumps, 8 motors and tuning 8 speed control algorithms to work together in perfect sync to achieve uniform startup, steady state and shutdown performance across the entire system. As with the last cluster test, to the best of our knowledge, this is the first time such a test has been performed in India with semi cryogenic engines. We are extremely grateful to have the opportunity to be building world class, original space technology from India, for the world with the support of IIT Madras ISRO and IN-SPACe From here on, the addition of engines to our clusters will likely increase non-linearly. #Agnibaan #RocketEngineCluster #ElectricPumpFedEngines #Agnilet #SinglePieceEngine #3dprinting #RocketEngineTest #AdditiveManufacturing #Agnikul #AgnikulCosmos #StartupIndia #MakeinIndia #madeinIndiaForTheWorld Srinath Ravichandran MOIN SPM Satyanarayanan Chakravarthy IIT Madras IITMRP IIT Madras Incubation Cell Technology Development Board DSTIndia Anusandhan National Research Foundation TIDCO Startup India StartupTN Guidance Tamil Nadu Kerala Startup Mission SIPCOT
1:06

Humbled to share that we successfully test fired 4 semi-cryogenic rocket engines simultaneously, as a cluster. All the 4 engines are 3d printed as single pieces of hardware - designed and manufactured in-house at AgniKul Cosmos Rocket Factory - 1. As with all our propulsion systems, these 4 engines are also powered by electric motor driven pumps. This test involved calibrating 8 pumps, 8 motors and tuning 8 speed control algorithms to work together in perfect sync to achieve uniform startup, steady state and shutdown performance across the entire system. As with the last cluster test, to the best of our knowledge, this is the first time such a test has been performed in India with semi cryogenic engines. We are extremely grateful to have the opportunity to be building world class, original space technology from India, for the world with the support of IIT Madras ISRO and IN-SPACe From here on, the addition of engines to our clusters will likely increase non-linearly. #Agnibaan #RocketEngineCluster #ElectricPumpFedEngines #Agnilet #SinglePieceEngine #3dprinting #RocketEngineTest #AdditiveManufacturing #Agnikul #AgnikulCosmos #StartupIndia #MakeinIndia #madeinIndiaForTheWorld Srinath Ravichandran MOIN SPM Satyanarayanan Chakravarthy IIT Madras IITMRP IIT Madras Incubation Cell Technology Development Board DSTIndia Anusandhan National Research Foundation TIDCO Startup India StartupTN Guidance Tamil Nadu Kerala Startup Mission SIPCOT

AgniKul Cosmos

118,928 Aufrufe • vor 2 Monaten

Humbled to share that we successfully test fired 3 semi-cryogenic rocket engines simultaneously, as a cluster. All the 3 engines are 3d printed as single pieces of hardware - designed and manufactured in-house at AgniKul Cosmos Rocket Factory - 1. As with all our propulsion systems, these 3 engines are also powered by electric motor driven pumps. This test involved calibrating 6 pumps, 6 motors and tuning 6 speed control algorithms to work together in perfect sync to achieve uniform startup, steady state and shutdown performance across the entire system. To the best of our knowledge, this is the first time such a test has been performed in India with semi cryogenic engines. We are extremely grateful to have the opportunity to be building world class, original space technology from India, for the world with the support of ISRO and IN-SPACe #Agnibaan #RocketEngineCluster #ElectricPumpFedEngines #Agnilet #SinglePieceEngine #3dprinting #RocketEngineTest #AdditiveManufacturing #Agnikul #AgnikulCosmos #StartupIndia #MakeinIndia #madeinIndiaForTheWorld Srinath Ravichandran MOIN SPM Satyanarayanan Chakravarthy IIT Madras IITMRP IIT Madras Incubation Cell Technology Development Board DSTIndia Anusandhan National Research Foundation TIDCO Startup India StartupTN Guidance Tamil Nadu Kerala Startup Mission
1:02

Humbled to share that we successfully test fired 3 semi-cryogenic rocket engines simultaneously, as a cluster. All the 3 engines are 3d printed as single pieces of hardware - designed and manufactured in-house at AgniKul Cosmos Rocket Factory - 1. As with all our propulsion systems, these 3 engines are also powered by electric motor driven pumps. This test involved calibrating 6 pumps, 6 motors and tuning 6 speed control algorithms to work together in perfect sync to achieve uniform startup, steady state and shutdown performance across the entire system. To the best of our knowledge, this is the first time such a test has been performed in India with semi cryogenic engines. We are extremely grateful to have the opportunity to be building world class, original space technology from India, for the world with the support of ISRO and IN-SPACe #Agnibaan #RocketEngineCluster #ElectricPumpFedEngines #Agnilet #SinglePieceEngine #3dprinting #RocketEngineTest #AdditiveManufacturing #Agnikul #AgnikulCosmos #StartupIndia #MakeinIndia #madeinIndiaForTheWorld Srinath Ravichandran MOIN SPM Satyanarayanan Chakravarthy IIT Madras IITMRP IIT Madras Incubation Cell Technology Development Board DSTIndia Anusandhan National Research Foundation TIDCO Startup India StartupTN Guidance Tamil Nadu Kerala Startup Mission

AgniKul Cosmos

363,531 Aufrufe • vor 5 Monaten

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.
0:21

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

254,019 Aufrufe • vor 1 Monat

At CVS in New York, the pasties that are lighter colors are not locked up But right next to them are pasties that are darker colors. All of them have security devices that must be unlocked by employees This is one of the clearest examples of one group of people stealing and another group not stealing Th proof to this is because it’s a 100% fact that CVS uses a data-driven loss prevention system that locks up or tags items based primarily on theft rates and shrinkage data
0:45

At CVS in New York, the pasties that are lighter colors are not locked up But right next to them are pasties that are darker colors. All of them have security devices that must be unlocked by employees This is one of the clearest examples of one group of people stealing and another group not stealing Th proof to this is because it’s a 100% fact that CVS uses a data-driven loss prevention system that locks up or tags items based primarily on theft rates and shrinkage data

Wall Street Apes

79,676 Aufrufe • vor 1 Monat

“We're continuing to work in partnership with Palantir to develop state-of-the-art data targeting as we develop the Stagwell ID Graph, and we are testing it with clients now. All of these new tools and systems will significantly upgrade our media offerings to be fully competitive against the majors when it comes to digital marketing, which in the world of AI is driven not by scale, but by effective technology, and that's exactly what we're developing.”
0:25

“We're continuing to work in partnership with Palantir to develop state-of-the-art data targeting as we develop the Stagwell ID Graph, and we are testing it with clients now. All of these new tools and systems will significantly upgrade our media offerings to be fully competitive against the majors when it comes to digital marketing, which in the world of AI is driven not by scale, but by effective technology, and that's exactly what we're developing.”

Chad Wahlquist

15,858 Aufrufe • vor 1 Jahr

Maajid Nawaz: The Great War of Our Age Isn’t With Weapons—It’s With Data "We are in an ideological war—not over land or nukes, but over the future of humanity itself. The real battleground? Data. Yuval Noah Harari, on the other side of this conflict, calls it ‘Dataism’—a belief system where AI dictates our choices, our thoughts, even our desires. Autocorrect, algorithmic nudges, predictive search—step by step, we are conditioned to surrender autonomy in exchange for convenience. But this is a Faustian bargain. If every decision is made for us, what remains of free will? If data is the new nuclear weapon, then consciousness is our last line of defense. Our duty—yours and mine—is to protect what it means to be human: to elevate reason, guard the sacred, and resist the commodification of the soul. Because when nothing is sacred, everything is for sale. And when everything is for sale, that’s just another word for slavery. The war is here. Which side will you stand on?" — Maajid Nawaz
1:48

Maajid Nawaz: The Great War of Our Age Isn’t With Weapons—It’s With Data "We are in an ideological war—not over land or nukes, but over the future of humanity itself. The real battleground? Data. Yuval Noah Harari, on the other side of this conflict, calls it ‘Dataism’—a belief system where AI dictates our choices, our thoughts, even our desires. Autocorrect, algorithmic nudges, predictive search—step by step, we are conditioned to surrender autonomy in exchange for convenience. But this is a Faustian bargain. If every decision is made for us, what remains of free will? If data is the new nuclear weapon, then consciousness is our last line of defense. Our duty—yours and mine—is to protect what it means to be human: to elevate reason, guard the sacred, and resist the commodification of the soul. Because when nothing is sacred, everything is for sale. And when everything is for sale, that’s just another word for slavery. The war is here. Which side will you stand on?" — Maajid Nawaz

Camus

18,608 Aufrufe • vor 1 Jahr

What surprises me is what happened in the US-India Trade Deal. If the INDIA Alliance were negotiating with President Trump, we would make one thing clear: the most important asset in this equation is Indian data. If the U.S. wants to protect the dollar, it must recognise that Indian data is a critical asset, and any discussion must happen between equals, not as masters and servants. We would also make it clear that India’s energy security is non-negotiable and that while the U.S. may need to protect its farmers, we will protect ours. An INDIA Alliance government would negotiate as an equal power, not allow India to be treated on par with Pakistan, and firmly object to any such symbolism. Let me tell you what is written in the trade deal about data - our most valuable asset, the force that will transform India in the 21st century and make us a superpower. This is what the Modi government has done with our data: The Modi government has given up control over digital trade rules, removed data localisation, allowed free flow of data to the U.S., capped digital taxes, and waived source code disclosure, while offering long tax holidays to big tech companies. This is what has been done with India’s data. : LoP Shri Rahul Gandhi in Lok Sabha
4:09

What surprises me is what happened in the US-India Trade Deal. If the INDIA Alliance were negotiating with President Trump, we would make one thing clear: the most important asset in this equation is Indian data. If the U.S. wants to protect the dollar, it must recognise that Indian data is a critical asset, and any discussion must happen between equals, not as masters and servants. We would also make it clear that India’s energy security is non-negotiable and that while the U.S. may need to protect its farmers, we will protect ours. An INDIA Alliance government would negotiate as an equal power, not allow India to be treated on par with Pakistan, and firmly object to any such symbolism. Let me tell you what is written in the trade deal about data - our most valuable asset, the force that will transform India in the 21st century and make us a superpower. This is what the Modi government has done with our data: The Modi government has given up control over digital trade rules, removed data localisation, allowed free flow of data to the U.S., capped digital taxes, and waived source code disclosure, while offering long tax holidays to big tech companies. This is what has been done with India’s data. : LoP Shri Rahul Gandhi in Lok Sabha

Congress

12,393 Aufrufe • vor 5 Monaten

Exciting updates on Project GR00T! We discover a systematic way to scale up robot data, tackling the most painful pain point in robotics. The idea is simple: human collects demonstration on a real robot, and we multiply that data 1000x or more in simulation. Let’s break it down: 1. We use Apple Vision Pro (yes!!) to give the human operator first person control of the humanoid. Vision Pro parses human hand pose and retargets the motion to the robot hand, all in real time. From the human’s point of view, they are immersed in another body like the Avatar. Teleoperation is slow and time-consuming, but we can afford to collect a small amount of data. 2. We use RoboCasa, a generative simulation framework, to multiply the demonstration data by varying the visual appearance and layout of the environment. In Jensen’s keynote video below, the humanoid is now placing the cup in hundreds of kitchens with a huge diversity of textures, furniture, and object placement. We only have 1 physical kitchen at the GEAR Lab in NVIDIA HQ, but we can conjure up infinite ones in simulation. 3. Finally, we apply MimicGen, a technique to multiply the above data even more by varying the *motion* of the robot. MimicGen generates vast number of new action trajectories based on the original human data, and filters out failed ones (e.g. those that drop the cup) to form a much larger dataset. To sum up, given 1 human trajectory with Vision Pro -> RoboCasa produces N (varying visuals) -> MimicGen further augments to NxM (varying motions). This is the way to trade compute for expensive human data by GPU-accelerated simulation. A while ago, I mentioned that teleoperation is fundamentally not scalable, because we are always limited by 24 hrs/robot/day in the world of atoms. Our new GR00T synthetic data pipeline breaks this barrier in the world of bits. Scaling has been so much fun for LLMs, and it's finally our turn to have fun in robotics! We are building tools to enable everyone in the ecosystem to scale up with us. Links in thread:
1:21

Exciting updates on Project GR00T! We discover a systematic way to scale up robot data, tackling the most painful pain point in robotics. The idea is simple: human collects demonstration on a real robot, and we multiply that data 1000x or more in simulation. Let’s break it down: 1. We use Apple Vision Pro (yes!!) to give the human operator first person control of the humanoid. Vision Pro parses human hand pose and retargets the motion to the robot hand, all in real time. From the human’s point of view, they are immersed in another body like the Avatar. Teleoperation is slow and time-consuming, but we can afford to collect a small amount of data. 2. We use RoboCasa, a generative simulation framework, to multiply the demonstration data by varying the visual appearance and layout of the environment. In Jensen’s keynote video below, the humanoid is now placing the cup in hundreds of kitchens with a huge diversity of textures, furniture, and object placement. We only have 1 physical kitchen at the GEAR Lab in NVIDIA HQ, but we can conjure up infinite ones in simulation. 3. Finally, we apply MimicGen, a technique to multiply the above data even more by varying the *motion* of the robot. MimicGen generates vast number of new action trajectories based on the original human data, and filters out failed ones (e.g. those that drop the cup) to form a much larger dataset. To sum up, given 1 human trajectory with Vision Pro -> RoboCasa produces N (varying visuals) -> MimicGen further augments to NxM (varying motions). This is the way to trade compute for expensive human data by GPU-accelerated simulation. A while ago, I mentioned that teleoperation is fundamentally not scalable, because we are always limited by 24 hrs/robot/day in the world of atoms. Our new GR00T synthetic data pipeline breaks this barrier in the world of bits. Scaling has been so much fun for LLMs, and it's finally our turn to have fun in robotics! We are building tools to enable everyone in the ecosystem to scale up with us. Links in thread:

Jim Fan

364,514 Aufrufe • vor 2 Jahren

Which one is our priority for securing a digital future for Zimbabwe? The Honourable Speaker's position while providing a clear, logical, and data-informed counter-argument we appreciate his efforts and submission. Let us have a conversation on our priorities in the current Zimbabwean context which we presented yesterday: This is a critical national conversation on our digital future. The proposition of a Google data centre is undoubtedly appealing. Building a centre of Technological Excellence that houses multiple Tech companies and a Start-up Ecosystem is also prudent, though we are calling it a Technology Park. However, I was of the following view which I am willing to be criticised and guided on. The strategic prioritisation of a national ICT Park ecosystem currently is the foundational path to sustainable, sovereign growth and capacity for Zimbabwe. We are reaching out to every province through the Digital Centres, Innovation Hubs at Universities and Colleges. Infrastructure which we need to capacitate better. This is a decentralised system utilising and expanding the infrastructure we have. The central question is not if we want major players like Google; that is not questionable, but when, how and on what terms. Why are we building our own foundation, house, techno park and mini ICT Parks in the provinces and districts? We absolutely need at least a one hyperscale data centre, but centralisation in the current and future environment can be restrictive. This was our plan: 1.The Foundation Before the Skyscraper: Capacity and Traffic We need to increase our national data volumes and internet traffic . Our urgent priority should be upgrading our national backbone, specifically the Optical Fibre on Power Transmission Lines (e.g., Powertel's network from Insukamini to Johannesburg), to peer efficiently with global giants. This builds the foundational "digital highway" we manage. 2.Generating Traffic Through Digitalization A data centre is a response to demand, not a creator of it. We must first drive digitalization aggressively through digital payments, process automation, and e-governance to generate the significant local traffic that would make a data centre viable. Furthermore, we must incorporate Edge Computing strategies to process data closer to the source, a more efficient model for our current needs and in compliance to our Cyber and Data Protection Act which we can amend if need be. Being a regional internet and cybersecurity hub is crucial as the Speaker alluded to me mentioning it to SADC Parliamentary Forum, this is the ultimate goal. 3.PPPs are key to lessen the burden to the fiscus and we are ready to accommodate organisations willing to assist government.(Cont)
3:05

Which one is our priority for securing a digital future for Zimbabwe? The Honourable Speaker's position while providing a clear, logical, and data-informed counter-argument we appreciate his efforts and submission. Let us have a conversation on our priorities in the current Zimbabwean context which we presented yesterday: This is a critical national conversation on our digital future. The proposition of a Google data centre is undoubtedly appealing. Building a centre of Technological Excellence that houses multiple Tech companies and a Start-up Ecosystem is also prudent, though we are calling it a Technology Park. However, I was of the following view which I am willing to be criticised and guided on. The strategic prioritisation of a national ICT Park ecosystem currently is the foundational path to sustainable, sovereign growth and capacity for Zimbabwe. We are reaching out to every province through the Digital Centres, Innovation Hubs at Universities and Colleges. Infrastructure which we need to capacitate better. This is a decentralised system utilising and expanding the infrastructure we have. The central question is not if we want major players like Google; that is not questionable, but when, how and on what terms. Why are we building our own foundation, house, techno park and mini ICT Parks in the provinces and districts? We absolutely need at least a one hyperscale data centre, but centralisation in the current and future environment can be restrictive. This was our plan: 1.The Foundation Before the Skyscraper: Capacity and Traffic We need to increase our national data volumes and internet traffic . Our urgent priority should be upgrading our national backbone, specifically the Optical Fibre on Power Transmission Lines (e.g., Powertel's network from Insukamini to Johannesburg), to peer efficiently with global giants. This builds the foundational "digital highway" we manage. 2.Generating Traffic Through Digitalization A data centre is a response to demand, not a creator of it. We must first drive digitalization aggressively through digital payments, process automation, and e-governance to generate the significant local traffic that would make a data centre viable. Furthermore, we must incorporate Edge Computing strategies to process data closer to the source, a more efficient model for our current needs and in compliance to our Cyber and Data Protection Act which we can amend if need be. Being a regional internet and cybersecurity hub is crucial as the Speaker alluded to me mentioning it to SADC Parliamentary Forum, this is the ultimate goal. 3.PPPs are key to lessen the burden to the fiscus and we are ready to accommodate organisations willing to assist government.(Cont)

Hon Tatenda.A. Mavetera

490,394 Aufrufe • vor 9 Monaten

Everyone is talking about AI models, but almost no one is talking about data ownership. For years, centralized systems have dominated data pipelines, opaque processes, hidden biases, and zero contributor visibility. We call it innovation…, but in reality, it’s a black box. And that’s exactly how we ended up facing model degradation risks today. Because here’s the truth: AI is only as good as the data it learns from. That’s why Sovereign AI Data matters. To me, it means control, traceability, and accountability. Perle Labs is approaching this differently: ◈ On-chain provenance → Every data point is verifiable ◈ Expert-driven input → Quality over quantity ◈ Reputation systems → Trust becomes measurable This isn’t just a technical upgrade. It’s a paradigm shift. Instead of: Anonymous contributors ➠Unverified datasets ➠Centralized ownership ➠We move toward: Transparent data flows, Credible expertise and Distributed value creation If AI is the brain, then data is the memory. And right now most systems are learning from memory, which they can’t verify. Perle is solving that. While others focus on scaling models… This is about fixing the foundation they stand on. And foundations decide everything. #PerleAI #ToPerle participating in Perle Labs community campaign
1:37

Everyone is talking about AI models, but almost no one is talking about data ownership. For years, centralized systems have dominated data pipelines, opaque processes, hidden biases, and zero contributor visibility. We call it innovation…, but in reality, it’s a black box. And that’s exactly how we ended up facing model degradation risks today. Because here’s the truth: AI is only as good as the data it learns from. That’s why Sovereign AI Data matters. To me, it means control, traceability, and accountability. Perle Labs is approaching this differently: ◈ On-chain provenance → Every data point is verifiable ◈ Expert-driven input → Quality over quantity ◈ Reputation systems → Trust becomes measurable This isn’t just a technical upgrade. It’s a paradigm shift. Instead of: Anonymous contributors ➠Unverified datasets ➠Centralized ownership ➠We move toward: Transparent data flows, Credible expertise and Distributed value creation If AI is the brain, then data is the memory. And right now most systems are learning from memory, which they can’t verify. Perle is solving that. While others focus on scaling models… This is about fixing the foundation they stand on. And foundations decide everything. #PerleAI #ToPerle participating in Perle Labs community campaign

Big_Wealth❤️‍🔥

11,486 Aufrufe • vor 4 Monaten

what have I been working on for the last 2 weeks at OpenCode? we are bringing workspaces in as a first-class concept: agents will be able to run anywhere: local directory/container/worktree, remote sandbox, or anything. instead of having a single server that only knows about local directories, the server will act as a "control plane" that routes prompts to where they should go it will manage all of the sessions across these environments and provide a unified layer for all clients to interact with them we will be smart about this: it's not *only* about routing. we will sync all data from remote environments into the local control plane server. this means the remote env can be destroyed, and we will be able to later recreate a new env with exactly the same state. it's reproducible note: this is very early and experimental, the UI you see the video is just a prototype and not guaranteed to make it to prod. We hope to start shipping something soon-ish though!
1:29

what have I been working on for the last 2 weeks at OpenCode? we are bringing workspaces in as a first-class concept: agents will be able to run anywhere: local directory/container/worktree, remote sandbox, or anything. instead of having a single server that only knows about local directories, the server will act as a "control plane" that routes prompts to where they should go it will manage all of the sessions across these environments and provide a unified layer for all clients to interact with them we will be smart about this: it's not *only* about routing. we will sync all data from remote environments into the local control plane server. this means the remote env can be destroyed, and we will be able to later recreate a new env with exactly the same state. it's reproducible note: this is very early and experimental, the UI you see the video is just a prototype and not guaranteed to make it to prod. We hope to start shipping something soon-ish though!

James Long

170,530 Aufrufe • vor 5 Monaten

David Sacks warns that New York’s data center ban is a power play. "The Democrats aren't going to pause the data centers forever. They're going to pause them until they feel like they're in enough control that they can dictate all the rules. Eventually, they're going to be in a position to say, 'Okay, here are our terms if you want to turn these things back on.' That’s when we get this big government Democrat-defined AI regime — a new regulatory agency, new speech controls, and the whole trust and safety agenda from social media ported over." Dangerous precedent or strategic move?
1:45

David Sacks warns that New York’s data center ban is a power play. "The Democrats aren't going to pause the data centers forever. They're going to pause them until they feel like they're in enough control that they can dictate all the rules. Eventually, they're going to be in a position to say, 'Okay, here are our terms if you want to turn these things back on.' That’s when we get this big government Democrat-defined AI regime — a new regulatory agency, new speech controls, and the whole trust and safety agenda from social media ported over." Dangerous precedent or strategic move?

jay plemons

92,755 Aufrufe • vor 22 Tagen

Apeel’s second act is dedicated to actively equipping suppliers, shippers, and retailers with the technology they need to modernize logistics for the future of food. As our CEO Luiz Beling shared on the Joel Beasley podcast, we are moving past legacy treatments to focus on the digitization of produce quality. By deploying our tech stack from growing all the way to delivery, we put precise, real-time data directly into the hands of our partners. Instead of guessing, they now have clear visibility into the quality of every piece of fruit in transit. With this level of visibility, shippers and suppliers can confidently optimize routes, open new markets, and choose sustainable shipping methods over expensive air freight. Retailers gain reliable, year-round inventory with protected margins—all while ensuring that fresh food actually retains its taste, affordability, and nutritional value on the shelf. We are building a more efficient, data-driven supply chain from the ground up, and we invite you to build it with us.
1:13

Apeel’s second act is dedicated to actively equipping suppliers, shippers, and retailers with the technology they need to modernize logistics for the future of food. As our CEO Luiz Beling shared on the Joel Beasley podcast, we are moving past legacy treatments to focus on the digitization of produce quality. By deploying our tech stack from growing all the way to delivery, we put precise, real-time data directly into the hands of our partners. Instead of guessing, they now have clear visibility into the quality of every piece of fruit in transit. With this level of visibility, shippers and suppliers can confidently optimize routes, open new markets, and choose sustainable shipping methods over expensive air freight. Retailers gain reliable, year-round inventory with protected margins—all while ensuring that fresh food actually retains its taste, affordability, and nutritional value on the shelf. We are building a more efficient, data-driven supply chain from the ground up, and we invite you to build it with us.

Apeel Sciences

25,845 Aufrufe • vor 24 Tagen

Introducing Tether 🪢, a fun little idea to scale data by having our robot “play” in the real world for over 24 hours, throughout the day and overnight—improving policies from zero to mastery with minimal supervision! But play is messy, with out-of-distribution scenarios that are hard to anticipate. To perform autonomous functional play in the real world, from just a handful of demos, we propose a highly robust few-shot imitation method that warps demo trajectories using visual correspondences. Then, continuously running it within a multi-task VLM-guided cycle, we generate a data stream that produces 1000+ expert-level demos. This generated data is finally funneled downstream to train imitation learning policies, which improve from zero to near-perfect success rates. We’ll be presenting Tether at #ICLR2026 in just a few weeks! But before that, deep dive with me… 🧵
0:30

Introducing Tether 🪢, a fun little idea to scale data by having our robot “play” in the real world for over 24 hours, throughout the day and overnight—improving policies from zero to mastery with minimal supervision! But play is messy, with out-of-distribution scenarios that are hard to anticipate. To perform autonomous functional play in the real world, from just a handful of demos, we propose a highly robust few-shot imitation method that warps demo trajectories using visual correspondences. Then, continuously running it within a multi-task VLM-guided cycle, we generate a data stream that produces 1000+ expert-level demos. This generated data is finally funneled downstream to train imitation learning policies, which improve from zero to near-perfect success rates. We’ll be presenting Tether at #ICLR2026 in just a few weeks! But before that, deep dive with me… 🧵

Will Liang

45,671 Aufrufe • vor 5 Monaten

#WATCH | Chicago, US: Chairman of Indian Overseas Congress, Sam Pitroda says, "...This is a policy issue. Congress party would frame a policy through which the wealth distribution would be better...We don't have a minimum wage (in India)...If we come up with a minimum wage in the country saying you must pay so much money to the poor, that's the distribution of wealth. Today, rich people don't pay their peons, servants, and home help enough but they spend that money on vacation in Dubai and London...When you talk about the distribution of wealth, it is not that you sit on a chair and say I have this much money and I'll be distributing it to everybody. It's naive to think like that. The PM of a country thinks like that, that means I got some concerns about his brain...You are really dealing with the policy issues to redistribute wealth and when you ask for the data, you are really trying to understand what is the distribution today. We don't have good data on all this. I think we need data to decide on policy issues. We don't need data to distribute wealth. We need data to decide on policy issues going forward..."
3:30

#WATCH | Chicago, US: Chairman of Indian Overseas Congress, Sam Pitroda says, "...This is a policy issue. Congress party would frame a policy through which the wealth distribution would be better...We don't have a minimum wage (in India)...If we come up with a minimum wage in the country saying you must pay so much money to the poor, that's the distribution of wealth. Today, rich people don't pay their peons, servants, and home help enough but they spend that money on vacation in Dubai and London...When you talk about the distribution of wealth, it is not that you sit on a chair and say I have this much money and I'll be distributing it to everybody. It's naive to think like that. The PM of a country thinks like that, that means I got some concerns about his brain...You are really dealing with the policy issues to redistribute wealth and when you ask for the data, you are really trying to understand what is the distribution today. We don't have good data on all this. I think we need data to decide on policy issues. We don't need data to distribute wealth. We need data to decide on policy issues going forward..."

ANI

244,459 Aufrufe • vor 2 Jahren