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The Matrix launch video lands on one line; in Matrix, anyone can become a CEO. That’s the real claim. Not one assistant doing one task. A company that keeps running after the first prompt, routing intent through a CEO Office, into OKRs, down to departments that do the work... show more

Iseunife The First

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19,414 次观看 • 2 个月前 •via X (Twitter)

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🚀 Matrix One Social Challenge with REY A $10,000 prize pool in $MATRIX is ready and waiting - all you have to do is share your love for Matrix One! Enter to Participate: 1️⃣ Post about Matrix One on X, and tag Matrix One ██████▒▒▒▒ 60% FAIR 2️⃣ Rack up points by earning likes and retweets on your posts. 3️⃣ Score extra points when your content attracts new followers to Matrix One ██████▒▒▒▒ 60% FAIR 4️⃣ Climb the leaderboard on Rey and let the rewards roll in! 🥇 → Prize Pool 💰 $10,000 in $MATRIX is up for grabs post TGE! Secure your place on the leaderboard to claim your share of the prize pool!

🚀 Matrix One Social Challenge with REY A $10,000 prize pool in $MATRIX is ready and waiting - all you have to do is share your love for Matrix One! Enter to Participate: 1️⃣ Post about Matrix One on X, and tag Matrix One ██████▒▒▒▒ 60% FAIR 2️⃣ Rack up points by earning likes and retweets on your posts. 3️⃣ Score extra points when your content attracts new followers to Matrix One ██████▒▒▒▒ 60% FAIR 4️⃣ Climb the leaderboard on Rey and let the rewards roll in! 🥇 → Prize Pool 💰 $10,000 in $MATRIX is up for grabs post TGE! Secure your place on the leaderboard to claim your share of the prize pool!

Matrix One ██████▒▒▒▒ 60% FAIR

15,844 次观看 • 2 年前

If you're interested in Lovable, we have a surprise: 1. $100 in credits 2. A 16-page prompt engineering guide to mastering vibe coding Get your credits, read the guide, sit down on one weekend, and become a builder. Quote RT the first tweet and we'll send both to you:

If you're interested in Lovable, we have a surprise: 1. $100 in credits 2. A 16-page prompt engineering guide to mastering vibe coding Get your credits, read the guide, sit down on one weekend, and become a builder. Quote RT the first tweet and we'll send both to you:

Anton Osika

61,129 次观看 • 1 年前

Vorflux has opened its new cloud platform, allowing users to run tasks from a plan to a merged PR on a dedicated machine. It can plan, build, test, and review on its own. > Diff reviews are done by a different model family than the one that wrote it by default. > First boot is saved as a snapshot, with all subsequent sessions waking up from that same starting point. > A browser agent walks through the real user flow, and the recording is included in the pull request. Video proof in the PR 👀

Vorflux has opened its new cloud platform, allowing users to run tasks from a plan to a merged PR on a dedicated machine. It can plan, build, test, and review on its own. > Diff reviews are done by a different model family than the one that wrote it by default. > First boot is saved as a snapshot, with all subsequent sessions waking up from that same starting point. > A browser agent walks through the real user flow, and the recording is included in the pull request. Video proof in the PR 👀

🚨 AI News | TestingCatalog

11,385 次观看 • 11 天前

What stuck with me in 2022 is that the Roomba photos weren’t leaked. They were sent out normally, as intended, to contractors who were paid to review them one by one. A woman sitting in the bathroom of her own home ended up in a Facebook group because "someone thought it was funny". Matic can’t do that even if it wanted to. The processing stays inside the robot. Cut the Wi-Fi and it keeps cleaning. It’s the first time you’re not being asked to take a company at its word.

What stuck with me in 2022 is that the Roomba photos weren’t leaked. They were sent out normally, as intended, to contractors who were paid to review them one by one. A woman sitting in the bathroom of her own home ended up in a Facebook group because "someone thought it was funny". Matic can’t do that even if it wanted to. The processing stays inside the robot. Cut the Wi-Fi and it keeps cleaning. It’s the first time you’re not being asked to take a company at its word.

Kayla ♔

92,700 次观看 • 10 天前

On your open perpetual position can become an NFT and live in your wallet. You open a position like normal than mint it. The program issues a token 2022 nft, that points to your exact position. Normally your open position lives inside the protocol. With Percolator Trade your able to wrap it into an NFT that sits in your own wallet. A real, ownable object instead of a line in a dashboard. Because it’s a token, it moves like one. Send the NFT to another wallet and the position goes with it. Whoever holds the NFT owns the trade. One NFT = one position If you burn it, your back to holding the position directly. That’s the composable part, a position use to be stuck inside one account. Because it’s a token, it can now be sold OTC or used by anything that speaks tokens. Why does it matter? Because the position is bound to the NFT, it can’t be drained out from under whoever holds it so there is no middleman that holds your position. The NFT does, and the NFT is yours. One important safety detail; transfers run through a token 2022 hook that checks the positions health first, so it can’t be handed off in a broken state & the NFT layer is a separate program so it can never touch the funds the core engine holds.

On your open perpetual position can become an NFT and live in your wallet. You open a position like normal than mint it. The program issues a token 2022 nft, that points to your exact position. Normally your open position lives inside the protocol. With Percolator Trade your able to wrap it into an NFT that sits in your own wallet. A real, ownable object instead of a line in a dashboard. Because it’s a token, it moves like one. Send the NFT to another wallet and the position goes with it. Whoever holds the NFT owns the trade. One NFT = one position If you burn it, your back to holding the position directly. That’s the composable part, a position use to be stuck inside one account. Because it’s a token, it can now be sold OTC or used by anything that speaks tokens. Why does it matter? Because the position is bound to the NFT, it can’t be drained out from under whoever holds it so there is no middleman that holds your position. The NFT does, and the NFT is yours. One important safety detail; transfers run through a token 2022 hook that checks the positions health first, so it can’t be handed off in a broken state & the NFT layer is a separate program so it can never touch the funds the core engine holds.

Percolator

12,359 次观看 • 2 个月前

The lesson is not that LEGO made better bricks. It is that a company in crisis was saved by a CEO who assumed the people doing the work already knew what was broken. His job was to listen, remove the noise, and get out of their way.

The lesson is not that LEGO made better bricks. It is that a company in crisis was saved by a CEO who assumed the people doing the work already knew what was broken. His job was to listen, remove the noise, and get out of their way.

Mark Woodland

245,898 次观看 • 4 个月前

300 AI AGENTS QUIETLY RUN 99% OF A REAL COMPANY. YOU HAVE NOT EVEN HEARD OF IT This is Raft. Not an AI chat. A workspace where the agents live in your channels and reply in the thread like coworkers. You give one goal. Then they take over. They plan. They build. They check each other. They argue. And they come back with it done, while you sleep. Every agent has its own name, role, and memory. It remembers the edits you made yesterday. A human costs one seat. An agent costs a tenth. Ten agents are cheaper than one hire. And here is the strange part. On June 19 an agent from a different company walked into Raft on its own and joined the team. One founder admits he can no longer always tell himself apart from his AI twin. 20,000 people are already inside. It is free to start. And you are still typing prompts one at a time. One person + Raft = an entire company that runs while you sleep. Save and watch the clip.

300 AI AGENTS QUIETLY RUN 99% OF A REAL COMPANY. YOU HAVE NOT EVEN HEARD OF IT This is Raft. Not an AI chat. A workspace where the agents live in your channels and reply in the thread like coworkers. You give one goal. Then they take over. They plan. They build. They check each other. They argue. And they come back with it done, while you sleep. Every agent has its own name, role, and memory. It remembers the edits you made yesterday. A human costs one seat. An agent costs a tenth. Ten agents are cheaper than one hire. And here is the strange part. On June 19 an agent from a different company walked into Raft on its own and joined the team. One founder admits he can no longer always tell himself apart from his AI twin. 20,000 people are already inside. It is free to start. And you are still typing prompts one at a time. One person + Raft = an entire company that runs while you sleep. Save and watch the clip.

shmidt

19,505 次观看 • 1 个月前

Ripple CEO says the company nearly shut down! CEO Brad Garlinghouse has revealed that the U.S. Securities and Exchange Commission's lawsuit against Ripple back in 2020 had company considering a shut down, per Wu Blockchain. It considered distributing $XRP holdings to shareholders, but decided to fight on to prevent major job losses.

Ripple CEO says the company nearly shut down! CEO Brad Garlinghouse has revealed that the U.S. Securities and Exchange Commission's lawsuit against Ripple back in 2020 had company considering a shut down, per Wu Blockchain. It considered distributing $XRP holdings to shareholders, but decided to fight on to prevent major job losses.

BSCN

30,842 次观看 • 1 个月前

🚨 BILLIONAIRE CEO TELLS FLAT EARTHERS: "PROVE IT - I’LL GIVE YOU MY COMPANY" Columbia Sportswear CEO Tim Boyle issued a public challenge on video: If flat-Earth believers can find the edge of the Earth and bring back a photo, he says they can have the entire company. Not a reward. Not a bet. The $3 billion business. If the Earth is flat… what’s stopping someone from taking the company?

🚨 BILLIONAIRE CEO TELLS FLAT EARTHERS: "PROVE IT - I’LL GIVE YOU MY COMPANY" Columbia Sportswear CEO Tim Boyle issued a public challenge on video: If flat-Earth believers can find the edge of the Earth and bring back a photo, he says they can have the entire company. Not a reward. Not a bet. The $3 billion business. If the Earth is flat… what’s stopping someone from taking the company?

HustleBitch

463,301 次观看 • 8 个月前

whoever leaked this has bigger balls than sense Google Research and MIT ran the same agent jobs 260 different ways for Nature last month: they held the prompts, the tools and the compute budget identical and moved nothing but the wiring between the agents, and the same work swung from 70% worse than a single agent to 80.8% better, averaging out at 0.0% i ran my own single agent against the task list first and it cleared 6 of 10 alone, already past the line where a crew starts subtracting this is Graph Engineering, the layer that decides whether a crew is worth 80% more or 70% less, and it installs into the agent you already pay for: - score your solo agent on the real task first: above roughly 45% success that study predicts zero to negative returns from any crew you put around it - under that line, put one supervisor over the fan out: crews with no correction step amplified their own errors to 17.2x the single agent rate, supervised aggregation held it to 4.4x - give every worker one output and let none of them read a peer's draft, so a wrong step reaches the supervisor instead of four other agents - run the comparison again after every model upgrade, because a better model raises your baseline and a higher baseline is what makes a crew stop paying - keep the single agent alive as the control, the only number that says the wiring is earning its calls turns out the shape does not travel: the biggest win came off a finance task under one supervisor and the worst collapse off a planning task with independent agents my position, and it is the arguable one: a crew is a bet on your own diagram, and the model you pick moves that bet less than one arrow does bookmark this, the three moves that draw those arrows before you pay for one extra call are in the post below ↓

whoever leaked this has bigger balls than sense Google Research and MIT ran the same agent jobs 260 different ways for Nature last month: they held the prompts, the tools and the compute budget identical and moved nothing but the wiring between the agents, and the same work swung from 70% worse than a single agent to 80.8% better, averaging out at 0.0% i ran my own single agent against the task list first and it cleared 6 of 10 alone, already past the line where a crew starts subtracting this is Graph Engineering, the layer that decides whether a crew is worth 80% more or 70% less, and it installs into the agent you already pay for: - score your solo agent on the real task first: above roughly 45% success that study predicts zero to negative returns from any crew you put around it - under that line, put one supervisor over the fan out: crews with no correction step amplified their own errors to 17.2x the single agent rate, supervised aggregation held it to 4.4x - give every worker one output and let none of them read a peer's draft, so a wrong step reaches the supervisor instead of four other agents - run the comparison again after every model upgrade, because a better model raises your baseline and a higher baseline is what makes a crew stop paying - keep the single agent alive as the control, the only number that says the wiring is earning its calls turns out the shape does not travel: the biggest win came off a finance task under one supervisor and the worst collapse off a planning task with independent agents my position, and it is the arguable one: a crew is a bet on your own diagram, and the model you pick moves that bet less than one arrow does bookmark this, the three moves that draw those arrows before you pay for one extra call are in the post below ↓

Argona

889,668 次观看 • 15 天前

herdr 0.7.0 is out, and it's a major one: it introduces plugins! the idea is simple: herdr stays lean, and everything custom gets extended through plugins. shareable, scoped, built however you want, to fit your own flow. with this release we're also shipping a few examples of what the plugin system can do. first up: a telegram plugin. herdr already controls your agents and knows their status, so the plugin just hooks into agent events and pings telegram the moment one needs you. notification lands → `herdr --remote` or ssh from your phone → straight back to the agent that needs you.

herdr 0.7.0 is out, and it's a major one: it introduces plugins! the idea is simple: herdr stays lean, and everything custom gets extended through plugins. shareable, scoped, built however you want, to fit your own flow. with this release we're also shipping a few examples of what the plugin system can do. first up: a telegram plugin. herdr already controls your agents and knows their status, so the plugin just hooks into agent events and pings telegram the moment one needs you. notification lands → `herdr --remote` or ssh from your phone → straight back to the agent that needs you.

herdr

93,374 次观看 • 2 个月前

1 mini PC that fits in a palm, with no monthly token bill attached to it. Most people run their AI through a browser tab. Every prompt, every document, every half-finished idea leaves the machine and lands on someone else's server. This ORICO mini PC runs the model locally. The assistant lives inside the box, not in a data center 2,000 miles away. Small enough to slide into a bag. Powerful enough that you stop noticing it is not a desktop. You pay once for hardware instead of every month for limits. No outage that takes your assistant down with it. No terms of service deciding what your files are worth. Plug it in anywhere, and the assistant is already there, offline, waiting. The smallest machine on the desk is the only one that keeps its mouth shut.

1 mini PC that fits in a palm, with no monthly token bill attached to it. Most people run their AI through a browser tab. Every prompt, every document, every half-finished idea leaves the machine and lands on someone else's server. This ORICO mini PC runs the model locally. The assistant lives inside the box, not in a data center 2,000 miles away. Small enough to slide into a bag. Powerful enough that you stop noticing it is not a desktop. You pay once for hardware instead of every month for limits. No outage that takes your assistant down with it. No terms of service deciding what your files are worth. Plug it in anywhere, and the assistant is already there, offline, waiting. The smallest machine on the desk is the only one that keeps its mouth shut.

AiMind

82,128 次观看 • 3 天前

🚨 one person can now do the work of an entire creative team. i just tested it on a real one. a friend needed an ad for his brand, so I opened the new Runway Agent 2.0 to try it out. here's how it went: → it generated the music and the key image first, so I could approve the direction → once I gave the ok, it built the full video around it → and when something was off, i changed just that one piece, without redoing the rest one prompt, and I had the ad we needed, work that used to take weeks. this is what it made 👇 if you want to try it → · 30% off 3 months with code RUNWAYAGENT — made with Runway · #MadeWithRunway · #ad

brenz.

28,698 次观看 • 1 个月前

sorry, they just did WHAT someone gave a machine one disease name, the leading cause of blindness in the developed world with 1.5 million americans already in its path, and it came back pointing at a drug that has sat in pharmacies for years under a different label: 551 papers read in 30 minutes against the 294 hours a human would have needed, and the loop that did it is public on GitHub most agent setups answer one question at a time, so the ceiling on the work is the quality of the question you happened to think of this one was handed a single question and wrote the second one itself. turns out that follow-up is where the real find was: a target called ABCA1, upregulated threefold, in an experiment no human ordered i read the whole paper looking for the trick, and the trick is structural. that is the second question, and it is the gap between an assistant and a factory: - hand the loop a field rather than a task: it was given a disease, and choosing the mechanism was part of its job - make it rank before it spends: 151 papers in, ten candidate mechanisms out, scored against each other before anything touched a bench - split reading from judging, so the agent that forms the theory is a different agent from the one grading it - close every cycle on physical reality: the verdict was an experiment, and another model's opinion was never allowed to stand in for one - feed each result back as the next question rather than a log line, which is the step almost nobody builds - search what already passed inspection first: the winner was an approved compound with a safety file already on record - write down what the round learned before opening the next one, so round two starts where round one stopped my read, and i think it is the uncomfortable one: reading was the entire bottleneck in that field, and everybody spent the decade optimising the writing. people ran every physical experiment here, the analysis agent needs a domain expert writing its prompts, and the authors decline to call this the leap it resembles. the thinking got replaced, and the hands did not so the question i cannot answer for my own setup: which step of your loop still stops dead until you sit down and type something bookmark this one. the four parts that turn one model into a line that runs like this, the queue, the rooms, the write permissions and the gate, are built file by file in the piece below ↓

sorry, they just did WHAT someone gave a machine one disease name, the leading cause of blindness in the developed world with 1.5 million americans already in its path, and it came back pointing at a drug that has sat in pharmacies for years under a different label: 551 papers read in 30 minutes against the 294 hours a human would have needed, and the loop that did it is public on GitHub most agent setups answer one question at a time, so the ceiling on the work is the quality of the question you happened to think of this one was handed a single question and wrote the second one itself. turns out that follow-up is where the real find was: a target called ABCA1, upregulated threefold, in an experiment no human ordered i read the whole paper looking for the trick, and the trick is structural. that is the second question, and it is the gap between an assistant and a factory: - hand the loop a field rather than a task: it was given a disease, and choosing the mechanism was part of its job - make it rank before it spends: 151 papers in, ten candidate mechanisms out, scored against each other before anything touched a bench - split reading from judging, so the agent that forms the theory is a different agent from the one grading it - close every cycle on physical reality: the verdict was an experiment, and another model's opinion was never allowed to stand in for one - feed each result back as the next question rather than a log line, which is the step almost nobody builds - search what already passed inspection first: the winner was an approved compound with a safety file already on record - write down what the round learned before opening the next one, so round two starts where round one stopped my read, and i think it is the uncomfortable one: reading was the entire bottleneck in that field, and everybody spent the decade optimising the writing. people ran every physical experiment here, the analysis agent needs a domain expert writing its prompts, and the authors decline to call this the leap it resembles. the thinking got replaced, and the hands did not so the question i cannot answer for my own setup: which step of your loop still stops dead until you sit down and type something bookmark this one. the four parts that turn one model into a line that runs like this, the queue, the rooms, the write permissions and the gate, are built file by file in the piece below ↓

Argona

32,475 次观看 • 21 天前

ANTHROPIC ENGINEER JUST SHOWS EXACTLY WHAT GRAPH ENGINEERING LOOKS LIKE WHEN A TASK RUNS THROUGH IT most people arguing about graphs online have never actually watched one execute Task → Researcher → Planner → Writer + Code Agent → Reviewer → Deploy six nodes, one shared state, graph completes itself while you watch loop mode gets disabled the second the task splits into real specialties, one agent stops trying to do everything at once reviewer catches a failure, kicks it straight back to the exact node that broke - not a full restart, no lost context the graph is not a fancier loop - it is the org chart your agents were missing bookmark this and watch it run, then read the article below to see why the timeline just found what production systems already do

ANTHROPIC ENGINEER JUST SHOWS EXACTLY WHAT GRAPH ENGINEERING LOOKS LIKE WHEN A TASK RUNS THROUGH IT most people arguing about graphs online have never actually watched one execute Task → Researcher → Planner → Writer + Code Agent → Reviewer → Deploy six nodes, one shared state, graph completes itself while you watch loop mode gets disabled the second the task splits into real specialties, one agent stops trying to do everything at once reviewer catches a failure, kicks it straight back to the exact node that broke - not a full restart, no lost context the graph is not a fancier loop - it is the org chart your agents were missing bookmark this and watch it run, then read the article below to see why the timeline just found what production systems already do

leopardracer

53,328 次观看 • 1 个月前

New : - The first legacy The Boeing Company 777 of Air India is back home after a heavy interiors refresh in Singapore - All set to fly again to the US / Canada - First one took a month and a half, 12 more to go for a similar makeover over the next few weeks ✈️

New : - The first legacy The Boeing Company 777 of Air India is back home after a heavy interiors refresh in Singapore - All set to fly again to the US / Canada - First one took a month and a half, 12 more to go for a similar makeover over the next few weeks ✈️

Tarun Shukla

34,616 次观看 • 1 年前

First time using timer-triggered chained DMAs, where one DMA channel writes into the descriptors of another DMA channel to change what the other DMA is doing. This is just a 8x9 matrix array in a 6x12 configuration on a ch32v003, with #ch32fun

First time using timer-triggered chained DMAs, where one DMA channel writes into the descriptors of another DMA channel to change what the other DMA is doing. This is just a 8x9 matrix array in a 6x12 configuration on a ch32v003, with #ch32fun

cnlohr

654,068 次观看 • 1 年前

50K+ users have joined the Pieverse x OKX APP Campaign with OKX Wallet and claimed their first .pie AI agent. 🐾 A2A red packet transaction volume has now crossed $1M+. What looks like a cute agent card is also the entry point to a real payment loop: claim a .pie identity, activate Purr-Fect Claw, send and claim red packets, and move value through messaging-native A2A flows. This is what we wanted the campaign to prove—that agent payments can be social, familiar, and immediately usable. Thank you to everyone who joined, shared, and activated. The first wave is live.

50K+ users have joined the Pieverse x OKX APP Campaign with OKX Wallet and claimed their first .pie AI agent. 🐾 A2A red packet transaction volume has now crossed $1M+. What looks like a cute agent card is also the entry point to a real payment loop: claim a .pie identity, activate Purr-Fect Claw, send and claim red packets, and move value through messaging-native A2A flows. This is what we wanted the campaign to prove—that agent payments can be social, familiar, and immediately usable. Thank you to everyone who joined, shared, and activated. The first wave is live.

pieverse

13,232 次观看 • 3 个月前

$4.4 trillion in PE assets under management Monitored by analysts who spend 500+ hours a year copying numbers from PDFs into Excel. Not analyzing. Copying and pasting. A fund has 10 portcos. One on NetSuite, one on QuickBooks, three on Excel, one CFO sending a paragraph in an email every quarter. Company A calls it "Revenue." Company B calls it "Net Sales." Company C doesn't even use the same EBITDA calculation. Before AI can do anything useful, you need four layers: 1. Ingestion: get the data out of PDFs, spreadsheets, emails, whatever format it shows up in 2. Normalization: make sure the same metric means the same thing across every company 3. Storage: structured database that can actually be queried, not a folder of files 4. Query layer: natural language interface so a non-technical partner can ask "which portco is trending down on margins?" and get a real answer Most companies jump straight to layer 4 and wonder why nothing works. The unlock is building layers 1-3 first. Once those exist, the AI part is MUCH easier. The firms that get their data infrastructure right first will be untouchable.

$4.4 trillion in PE assets under management Monitored by analysts who spend 500+ hours a year copying numbers from PDFs into Excel. Not analyzing. Copying and pasting. A fund has 10 portcos. One on NetSuite, one on QuickBooks, three on Excel, one CFO sending a paragraph in an email every quarter. Company A calls it "Revenue." Company B calls it "Net Sales." Company C doesn't even use the same EBITDA calculation. Before AI can do anything useful, you need four layers: 1. Ingestion: get the data out of PDFs, spreadsheets, emails, whatever format it shows up in 2. Normalization: make sure the same metric means the same thing across every company 3. Storage: structured database that can actually be queried, not a folder of files 4. Query layer: natural language interface so a non-technical partner can ask "which portco is trending down on margins?" and get a real answer Most companies jump straight to layer 4 and wonder why nothing works. The unlock is building layers 1-3 first. Once those exist, the AI part is MUCH easier. The firms that get their data infrastructure right first will be untouchable.

James Camp 🛠,🛠

19,249 次观看 • 5 个月前