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Analyzing effectiveness of ping-ponging orbs with low orb count agents on Corrode. Also Corrode map structure facilitating AOE util agents also, rather than the strict neon/waylay meta. Finally discussing Astra+Sage viability 🎦Full video on Youtube ↓

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11,848 просмотров • 7 месяцев назад •via X (Twitter)

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The full video that these screenshots came from has been leaked on YouTube by a user named Fusion. This video shows how fast they were with destroying Splash Mountain. This also shows that the animatronics were cut from their wiring rather than being properly removed.
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The full video that these screenshots came from has been leaked on YouTube by a user named Fusion. This video shows how fast they were with destroying Splash Mountain. This also shows that the animatronics were cut from their wiring rather than being properly removed.

Splash Mountain Historical Society

1,592,154 просмотров • 3 месяцев назад

BREAKING: New video just released of what appears to be Alex Pretti interacting with Federal law enforcement in Minneapolis. The video not only shows them jumping on top of him, after he did kick their vehicle. but also shows that he was carrying a gun at the time. Notice that these agents did NOT feel the need to shoot him or even disarm him. Pretti was far more confrontational here than on January 24, and walked away with his gun.
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BREAKING: New video just released of what appears to be Alex Pretti interacting with Federal law enforcement in Minneapolis. The video not only shows them jumping on top of him, after he did kick their vehicle. but also shows that he was carrying a gun at the time. Notice that these agents did NOT feel the need to shoot him or even disarm him. Pretti was far more confrontational here than on January 24, and walked away with his gun.

Brian Krassenstein

162,182 просмотров • 8 месяцев назад

Today, we are launching the first publicly available AI Scientist, via the FutureHouse Platform. Our AI Scientist agents can perform a wide variety of scientific tasks better than humans. By chaining them together, we've already started to discover new biology really fast. With the platform, we are bringing these capabilities to the wider community. Watch our long-form video, in the comments below, to learn more about how the platform works and how you can use it to make new discoveries, and go to our website or see the comments below to access the platform. We are releasing three superhuman AI Scientist agents today, each with their own specialization: A general-purpose agent (Crow); An agent to automate literature reviews (Falcon); and An agent to answer the question “Has anyone done X before” (Owl). We are also releasing an experimental agent, Phoenix, that has access to a wide variety of tools for planning experiments in chemistry. More on that below. The three literature search agents (Crow, Falcon, and Owl) have benchmarked superhuman performance. They also have access to a large corpus of full scientific texts, which means that you can ask them more detailed questions about experimental protocols and study limitations that general-purpose web search agents, which usually only have access to abstracts, might miss. Our agents also use a variety of factors to distinguish source quality, so that they don’t end up relying on low-quality papers or pop-science sources. Finally, and critically, we have an API, which is intended to allow researchers to integrate our agents into their workflows. Phoenix is an experimental project we put together recently just to demonstrate what can happen if you give the agents access to lots of scientific tools. It is not better than humans at planning experiments yet, and it makes a lot more mistakes than Crow, Falcon, or Owl. We want to see all the ways you can break it! The agents we are releasing today cannot yet do all (or even most!) aspects of scientific research autonomously. However, as we show in the video, you can already use them to generate and evaluate new hypotheses and plan new experiments way faster than before. Internally, we also have dedicated agents for data analysis, hypothesis generation, protein engineering, and more, and we plan to launch these on the platform in the coming months as well. Within a year or two, it is easy to imagine that the vast majority of desk work that scientists do today will be accelerated with the help of AI agents like the ones we are releasing today. The platform is currently free-to-use. Over time, depending on how people use it, we may implement pricing plans. If you want higher rate limits, especially for research projects, get in touch. Michael Skarlinski, Andrew White 🐦‍⬛, Tyler Nadolski, Remo Storni, James Braza, Ludovico Mitchener, Michaela Hinks, as well as Jason Carman and his team for making such fantastic videos of us!
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Today, we are launching the first publicly available AI Scientist, via the FutureHouse Platform. Our AI Scientist agents can perform a wide variety of scientific tasks better than humans. By chaining them together, we've already started to discover new biology really fast. With the platform, we are bringing these capabilities to the wider community. Watch our long-form video, in the comments below, to learn more about how the platform works and how you can use it to make new discoveries, and go to our website or see the comments below to access the platform. We are releasing three superhuman AI Scientist agents today, each with their own specialization: A general-purpose agent (Crow); An agent to automate literature reviews (Falcon); and An agent to answer the question “Has anyone done X before” (Owl). We are also releasing an experimental agent, Phoenix, that has access to a wide variety of tools for planning experiments in chemistry. More on that below. The three literature search agents (Crow, Falcon, and Owl) have benchmarked superhuman performance. They also have access to a large corpus of full scientific texts, which means that you can ask them more detailed questions about experimental protocols and study limitations that general-purpose web search agents, which usually only have access to abstracts, might miss. Our agents also use a variety of factors to distinguish source quality, so that they don’t end up relying on low-quality papers or pop-science sources. Finally, and critically, we have an API, which is intended to allow researchers to integrate our agents into their workflows. Phoenix is an experimental project we put together recently just to demonstrate what can happen if you give the agents access to lots of scientific tools. It is not better than humans at planning experiments yet, and it makes a lot more mistakes than Crow, Falcon, or Owl. We want to see all the ways you can break it! The agents we are releasing today cannot yet do all (or even most!) aspects of scientific research autonomously. However, as we show in the video, you can already use them to generate and evaluate new hypotheses and plan new experiments way faster than before. Internally, we also have dedicated agents for data analysis, hypothesis generation, protein engineering, and more, and we plan to launch these on the platform in the coming months as well. Within a year or two, it is easy to imagine that the vast majority of desk work that scientists do today will be accelerated with the help of AI agents like the ones we are releasing today. The platform is currently free-to-use. Over time, depending on how people use it, we may implement pricing plans. If you want higher rate limits, especially for research projects, get in touch. Michael Skarlinski, Andrew White 🐦‍⬛, Tyler Nadolski, Remo Storni, James Braza, Ludovico Mitchener, Michaela Hinks, as well as Jason Carman and his team for making such fantastic videos of us!

Sam Rodriques

726,493 просмотров • 1 год назад

Agentic AI is full of opportunities and challenges. Certainly agents represent a new era for computing, but currently there are many issues with the relative immaturity of the tools including for evaluation, debugging, FinOps management of agents and reasoning models, the clear need for appropriate human-in-the-loop to address model errors / hallucinations, and generally how to manage agents across many model families. Orange we see such great work in open source and from innovative companies like LangChain, OpenAI, Google, Hugging Face, CrewAI, and others that I’m confident that these issues will be gradually solved. Certainly when we have affordable, low hallucination models then agents will really take off. We also believe in #ResponsibleAI, which means using the right tool for the right problem. Doing that well is important to mitigate financial cost, but also environmental cost in terms of CO2. That’s even more important with agents where the agent has a lot of autonomy to achieve its goal. This week at #VivaTech was also the sign of the emergence of the potential for a strong European AI ecosystem. Hopefully the regulators will help to dive uniform and less restrictive oversight, banks and private investors will back these new opportunities, and especially that European enterprises will be willing to take a risk on potentially smaller but far more innovative vendors of AI solutions. Latly, a big hat tip to the genius of Jim White who invented agents at General Magic in the early 90s. Yes, General Magic not only was the birthplace of the smartphone but agents were also first built there. In fact, the patent portfolio was sadly bought by the patent trolls from Intellectual Ventures (Nathan Myrvold did Microsoft’s due diligence on their potential investment in General Magic, so he had detailed knowledge of what he was buying out of the Magic bankruptcy)…but thankfully enough time has passed those fundamental patents are all in the public domain… For those interested, here’s that patent from 1997:
1:02

Agentic AI is full of opportunities and challenges. Certainly agents represent a new era for computing, but currently there are many issues with the relative immaturity of the tools including for evaluation, debugging, FinOps management of agents and reasoning models, the clear need for appropriate human-in-the-loop to address model errors / hallucinations, and generally how to manage agents across many model families. Orange we see such great work in open source and from innovative companies like LangChain, OpenAI, Google, Hugging Face, CrewAI, and others that I’m confident that these issues will be gradually solved. Certainly when we have affordable, low hallucination models then agents will really take off. We also believe in #ResponsibleAI, which means using the right tool for the right problem. Doing that well is important to mitigate financial cost, but also environmental cost in terms of CO2. That’s even more important with agents where the agent has a lot of autonomy to achieve its goal. This week at #VivaTech was also the sign of the emergence of the potential for a strong European AI ecosystem. Hopefully the regulators will help to dive uniform and less restrictive oversight, banks and private investors will back these new opportunities, and especially that European enterprises will be willing to take a risk on potentially smaller but far more innovative vendors of AI solutions. Latly, a big hat tip to the genius of Jim White who invented agents at General Magic in the early 90s. Yes, General Magic not only was the birthplace of the smartphone but agents were also first built there. In fact, the patent portfolio was sadly bought by the patent trolls from Intellectual Ventures (Nathan Myrvold did Microsoft’s due diligence on their potential investment in General Magic, so he had detailed knowledge of what he was buying out of the Magic bankruptcy)…but thankfully enough time has passed those fundamental patents are all in the public domain… For those interested, here’s that patent from 1997:

Steve Jarrett

163,557 просмотров • 1 год назад

Introducing FlowMaker 🌊🤖 A fully open-source, low-code way of building custom agent workflows. Build agents via a drag and drop interface, run it directly in the app, and also directly export it into a deeply custom workflow backed by LlamaIndex 🦙.TS. It’s a fantastic visual tool to help you get started with agents but also gives you full customizability to build the deepest, most advanced workflows, since everything is backed by code. There’s a lot of great low-code agent tools already, but this is a fully-open source template that you can use or clone/customize for your own needs. It was a fun project by Laurie Voss and is intended to give users an easy-on ramp onto our powerful agent orchestration tooling. Also integrates with LlamaCloud in case you want to integrate your own knowledge base into your agent. FlowMaker app: FlowMaker Repo: LlamaCloud:
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Introducing FlowMaker 🌊🤖 A fully open-source, low-code way of building custom agent workflows. Build agents via a drag and drop interface, run it directly in the app, and also directly export it into a deeply custom workflow backed by LlamaIndex 🦙.TS. It’s a fantastic visual tool to help you get started with agents but also gives you full customizability to build the deepest, most advanced workflows, since everything is backed by code. There’s a lot of great low-code agent tools already, but this is a fully-open source template that you can use or clone/customize for your own needs. It was a fun project by Laurie Voss and is intended to give users an easy-on ramp onto our powerful agent orchestration tooling. Also integrates with LlamaCloud in case you want to integrate your own knowledge base into your agent. FlowMaker app: FlowMaker Repo: LlamaCloud:

Jerry Liu

20,434 просмотров • 1 год назад

$ORBS Eightco, $WLD Worldcoin, & $BMNR BitMine - The Unrealized New Economy & Ecosystem 🚀 VIDEO ANALYSIS The $WLD Worldcoin “Lift Off” event was MASSIVE for proof-of-human tech! Key drops: • World ID 4.0: better privacy, scalability + “Selfie Check” • Major partnerships: Tinder $MTCH, Zoom $ZM, DocuSign $DOCU, Shopify $SHOP, Coinbase $COIN & more • Full-stack human verification for AI agents, dating, concerts, payments & enterprise Here’s how $BMNR & $ORBS are perfectly positioned to capture it: The $BMNR & $ORBS × Worldcoin Ethereum Map - UPDATED 🔥 $BMNR and $ORBS are quietly building one of the largest public positions in Worldcoin’s Proof of Human (PoH) thesis while holding a massive Ethereum treasury and investing into MrBeast, OpenAI & next-gen fintech — creating a powerful world-changing ecosystem for the Future of Finance and PoH. Here’s the full map: • Ethereum → $BMNR: Holds ~4.875M ETH (~4.04% of total supply) • $BMNR → $ORBS: $155M+ leading investor • $BMNR → MrBeast / Beast Industries: $200M direct equity investment • $ORBS → OpenAI: $90M total (~30% of treasury) • $ORBS → Worldcoin ($WLD): Holds ~277M WLD (~9% of supply) • $ORBS → MrBeast / Beast Industries: $25M investment • OpenAI ↔ Worldcoin: Sam Altman (Sam Altman) co-founder + partnership talks • MrBeast / Beast Industries → Step: 100% acquisition (Feb 2026) • Step → Ethereum: Planned blockchain / DeFi / ETH integration 🔥 $ORBS + $WLD: Proof-of-Human Flywheel Worldcoin just landed major new partnerships with Zoom, DocuSign & Tinder — huge enterprise + consumer use cases for human verification in the AI age. $ORBS is the largest disclosed public holder (~9% of supply) and the anchor of the entire World ID thesis. This is an unrealized new economy. One ETH treasury → AI + Digital Identity + Creator Economy → real on-chain activity & gas fees flowing into Ethereum. Thomas (Tom) Lee (not drummer) FundstratDirect.com’s Tom Lee is Chairman of $BMNR and Board Director at $ORBS #Ethereum #Worldcoin #ORBS #ProofOfHuman $ORBS $WLD $BMNR $ETH
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$ORBS Eightco, $WLD Worldcoin, & $BMNR BitMine - The Unrealized New Economy & Ecosystem 🚀 VIDEO ANALYSIS The $WLD Worldcoin “Lift Off” event was MASSIVE for proof-of-human tech! Key drops: • World ID 4.0: better privacy, scalability + “Selfie Check” • Major partnerships: Tinder $MTCH, Zoom $ZM, DocuSign $DOCU, Shopify $SHOP, Coinbase $COIN & more • Full-stack human verification for AI agents, dating, concerts, payments & enterprise Here’s how $BMNR & $ORBS are perfectly positioned to capture it: The $BMNR & $ORBS × Worldcoin Ethereum Map - UPDATED 🔥 $BMNR and $ORBS are quietly building one of the largest public positions in Worldcoin’s Proof of Human (PoH) thesis while holding a massive Ethereum treasury and investing into MrBeast, OpenAI & next-gen fintech — creating a powerful world-changing ecosystem for the Future of Finance and PoH. Here’s the full map: • Ethereum → $BMNR: Holds ~4.875M ETH (~4.04% of total supply) • $BMNR → $ORBS: $155M+ leading investor • $BMNR → MrBeast / Beast Industries: $200M direct equity investment • $ORBS → OpenAI: $90M total (~30% of treasury) • $ORBS → Worldcoin ($WLD): Holds ~277M WLD (~9% of supply) • $ORBS → MrBeast / Beast Industries: $25M investment • OpenAI ↔ Worldcoin: Sam Altman (Sam Altman) co-founder + partnership talks • MrBeast / Beast Industries → Step: 100% acquisition (Feb 2026) • Step → Ethereum: Planned blockchain / DeFi / ETH integration 🔥 $ORBS + $WLD: Proof-of-Human Flywheel Worldcoin just landed major new partnerships with Zoom, DocuSign & Tinder — huge enterprise + consumer use cases for human verification in the AI age. $ORBS is the largest disclosed public holder (~9% of supply) and the anchor of the entire World ID thesis. This is an unrealized new economy. One ETH treasury → AI + Digital Identity + Creator Economy → real on-chain activity & gas fees flowing into Ethereum. Thomas (Tom) Lee (not drummer) FundstratDirect.com’s Tom Lee is Chairman of $BMNR and Board Director at $ORBS #Ethereum #Worldcoin #ORBS #ProofOfHuman $ORBS $WLD $BMNR $ETH

Donald Dean

20,379 просмотров • 5 месяцев назад

💕 XO is launching on Virtuals Protocol ; buh bye @pumpdotfun 💕 Valentine’s Day is coming, and love is getting an AI upgrade! XO, the AI-powered matchmaking dApp with 1.5M users and 1M+ matches per month, is redefining the dating and matching market with AI Wingman Agents that facilitate real human relationships—powered by Virtuals Protocol and G.A.M.E. Soon, your AI-powered wingman will not only understand you but also help you navigate love—on XO and X! The evolution of Social AI begins now. xoxo 💋 Full version of the video:
1:57

💕 XO is launching on Virtuals Protocol ; buh bye @pumpdotfun 💕 Valentine’s Day is coming, and love is getting an AI upgrade! XO, the AI-powered matchmaking dApp with 1.5M users and 1M+ matches per month, is redefining the dating and matching market with AI Wingman Agents that facilitate real human relationships—powered by Virtuals Protocol and G.A.M.E. Soon, your AI-powered wingman will not only understand you but also help you navigate love—on XO and X! The evolution of Social AI begins now. xoxo 💋 Full version of the video:

XO 💜 AI-powered social app

35,779 просмотров • 1 год назад

🚨Emanny WOKE IT UP‼️ Did Joe Budden Remove The 3 Paintings Because Melyssa Ford Had an Issue❓🗂️ Jaewon Had to CUT Emanny Off When Trying to Speak on Suge Knight in Front of CJ (Biggie Smalls Son) 😱🗂️ JasonMartin (Problem) Spoke VERY HIGHLY on Suge Knight & Diddy, However, He Also Had Some Words of Wisdom‼️🗂️ JasonMartin Thinks Jaewon & CJ should be telling their Stories Rather Than Someone like VLAD‼️💯🗂️ Full Video on YouTube:
6:58

🚨Emanny WOKE IT UP‼️ Did Joe Budden Remove The 3 Paintings Because Melyssa Ford Had an Issue❓🗂️ Jaewon Had to CUT Emanny Off When Trying to Speak on Suge Knight in Front of CJ (Biggie Smalls Son) 😱🗂️ JasonMartin (Problem) Spoke VERY HIGHLY on Suge Knight & Diddy, However, He Also Had Some Words of Wisdom‼️🗂️ JasonMartin Thinks Jaewon & CJ should be telling their Stories Rather Than Someone like VLAD‼️💯🗂️ Full Video on YouTube:

DUB HERE

27,675 просмотров • 10 дней назад

Excited to double down on our partnership with Parloa with our friends Chad Peets General Catalyst EQT Group Doreen Huber Hemant Taneja Max Rimpel and Durable! Since our first investment, Parloa has proven to be a truly enterprise-grade CX solution. Voice still swallows most CX spend; Parloa’s low-latency agents shrink peak-staffing costs, and once voice is solved, chat & messaging follow. Second, Parloa provides global coverage! Automating European language support is 3-5x more expensive than English. Fine-tuned speech models in 40 + languages turn the €20-40/hr cost of multilingual agents into instant AI. Finally, the proof in the numbers. Revenue 4× in 12 months; marquee hyperscalers are customers and partners; A-team talent from Adyen, Stripe, AWS and more. Catch the video for the full story!
8:14

Excited to double down on our partnership with Parloa with our friends Chad Peets General Catalyst EQT Group Doreen Huber Hemant Taneja Max Rimpel and Durable! Since our first investment, Parloa has proven to be a truly enterprise-grade CX solution. Voice still swallows most CX spend; Parloa’s low-latency agents shrink peak-staffing costs, and once voice is solved, chat & messaging follow. Second, Parloa provides global coverage! Automating European language support is 3-5x more expensive than English. Fine-tuned speech models in 40 + languages turn the €20-40/hr cost of multilingual agents into instant AI. Finally, the proof in the numbers. Revenue 4× in 12 months; marquee hyperscalers are customers and partners; A-team talent from Adyen, Stripe, AWS and more. Catch the video for the full story!

Apoorv Agrawal

11,860 просмотров • 1 год назад

Former Intel CEO Pat Gelsinger with a16z's Raghu Raghuram and Guido Appenzeller on the next wave of semiconductor innovation and the physical constraints shaping the AI buildout: Drawing on his experience designing Intel's 386 and 486 processors, Pat explains how AI could transform chip design, but also why faster design alone won't solve the industry's biggest problems. They examine the bottlenecks in manufacturing, memory bandwidth, advanced packaging, and power, and why today's explosion of specialized AI chips may eventually consolidate around a smaller number of architectures. They also discuss the potential for new memory technologies, the shift from copper to optical networking, and why energy capacity could become a major constraint on AI growth. Finally, they revisit Pat's VMware years to ask what virtualization might look like when infrastructure is built for agents rather than humans. YouTube: 1:05 Hired by Intel at 18 3:50 Arguing with Stanford professors 7:25 Will AI design the next gen chips? 8:45 Designing faster than fabs can build 11:55 Why GPUs are stuck with bad memory 13:40 Why 100 AI chips will collapse to a few 19:15 Agents make new chips cheap to run 22:10 No new memory chip since the 90s 27:20 Why 16-layer chip stacks are a fantasy 32:15 The physics that keeps memory next to compute 34:55 "I declared the death of copper" 38:05 AI traffic breaks the internet's design 42:40 "Energy capacity equals economic capacity" 46:25 The 130-year-old power war AI reopened 48:50 VMware for agents Pat Gelsinger Raghu Raghuram Guido Appenzeller
53:14

Former Intel CEO Pat Gelsinger with a16z's Raghu Raghuram and Guido Appenzeller on the next wave of semiconductor innovation and the physical constraints shaping the AI buildout: Drawing on his experience designing Intel's 386 and 486 processors, Pat explains how AI could transform chip design, but also why faster design alone won't solve the industry's biggest problems. They examine the bottlenecks in manufacturing, memory bandwidth, advanced packaging, and power, and why today's explosion of specialized AI chips may eventually consolidate around a smaller number of architectures. They also discuss the potential for new memory technologies, the shift from copper to optical networking, and why energy capacity could become a major constraint on AI growth. Finally, they revisit Pat's VMware years to ask what virtualization might look like when infrastructure is built for agents rather than humans. YouTube: 1:05 Hired by Intel at 18 3:50 Arguing with Stanford professors 7:25 Will AI design the next gen chips? 8:45 Designing faster than fabs can build 11:55 Why GPUs are stuck with bad memory 13:40 Why 100 AI chips will collapse to a few 19:15 Agents make new chips cheap to run 22:10 No new memory chip since the 90s 27:20 Why 16-layer chip stacks are a fantasy 32:15 The physics that keeps memory next to compute 34:55 "I declared the death of copper" 38:05 AI traffic breaks the internet's design 42:40 "Energy capacity equals economic capacity" 46:25 The 130-year-old power war AI reopened 48:50 VMware for agents Pat Gelsinger Raghu Raghuram Guido Appenzeller

a16z

89,736 просмотров • 5 дней назад

ICE brutally detain woman's gardener—right in front of her house. 4 agents drag and violently pull man out of truck head-first. Kneel on his back after pinned down to pavement. "I can't breathe! I can't breathe!" he cries out. Agents drove unmarked cars—with no IDs or badges according to the homeowner. They also wore masks over their faces in violation of Washington state law. Jennifer Gordon said that ICE attempted to detain 2 men she’d hired for landscaping outside her home. Incident occurred in front of her house near the Legion Memorial Golf Course in Everett, Washington. Jennifer Gordon doesn't have an account on this platform—so posting first full length and credited video here to help raise awareness.
2:47

ICE brutally detain woman's gardener—right in front of her house. 4 agents drag and violently pull man out of truck head-first. Kneel on his back after pinned down to pavement. "I can't breathe! I can't breathe!" he cries out. Agents drove unmarked cars—with no IDs or badges according to the homeowner. They also wore masks over their faces in violation of Washington state law. Jennifer Gordon said that ICE attempted to detain 2 men she’d hired for landscaping outside her home. Incident occurred in front of her house near the Legion Memorial Golf Course in Everett, Washington. Jennifer Gordon doesn't have an account on this platform—so posting first full length and credited video here to help raise awareness.

LongTime🤓FirstTime👨‍💻

63,433 просмотров • 21 дней назад

🚨🎙️ Fabrizio Romano : Matheus Fernandes top priority is Manchester United Tottenham in shadows , United are keen to get crysencio Summerville Deal to follow and here we go 👀 🗣️ Mateus Fernandes talks continue as Man United have been in direct contact with his camp and West Ham for weeks. Tottenham also called player’s agent to try enter the deal, Crysencio Summerville also set to leave West Ham with several clubs calling. 🗣️Manchester United are informed on price and added his name on shortlist deal soon Manchester United are PUSHING in negotiations with the agents of Mateus Fernandes & West Ham to try and FIND a solution, United also asking about Crysencio Summerville DURING the talks. 🗣️ Manchester United are in ongoing talks with West Ham regarding Mateus Fernandes. They are aware of Tottenham’s interest & pursuit but firmly believe that they're the most advanced club with confidence internally. Fernandes' preferred club is United & they still believe thats the case. [Sully] #MUFC (Video Fabrizio Romano YouTube)
0:46

🚨🎙️ Fabrizio Romano : Matheus Fernandes top priority is Manchester United Tottenham in shadows , United are keen to get crysencio Summerville Deal to follow and here we go 👀 🗣️ Mateus Fernandes talks continue as Man United have been in direct contact with his camp and West Ham for weeks. Tottenham also called player’s agent to try enter the deal, Crysencio Summerville also set to leave West Ham with several clubs calling. 🗣️Manchester United are informed on price and added his name on shortlist deal soon Manchester United are PUSHING in negotiations with the agents of Mateus Fernandes & West Ham to try and FIND a solution, United also asking about Crysencio Summerville DURING the talks. 🗣️ Manchester United are in ongoing talks with West Ham regarding Mateus Fernandes. They are aware of Tottenham’s interest & pursuit but firmly believe that they're the most advanced club with confidence internally. Fernandes' preferred club is United & they still believe thats the case. [Sully] #MUFC (Video Fabrizio Romano YouTube)

Hk🐐🇵🇹🇯🇵

109,819 просмотров • 3 месяцев назад

🚨Declassified UAP encounter has "SHAKEN the Intelligence Community and Military"🚨 This is why Rep. Eric Burlison wants you to dig into it! Watch the recounting of the series of encounters ⬇️below⬇️ or read the official summary below! Full report in post below. Full Statement about UAP Sighting This is an FBI 302 interview conducted with a senior US intelligence official regarding his first-hand account of a UAP encounter at a US military facility. USPER relayed to FBI agents that he and other federal and state personnel conducted searches to where orbs had been previously seen. After searching the area with a helicopter, they found a “super-hot” orb hovering over the ground. The orb is reported to have travelled for 20 miles at a speed too fast for the helicopter in pursuit. An additional “swarm” of lights were seen moving in all directions. A total of four or five additional orbs were seen shortly thereafter for a short time, flaring up and then down. This pattern of four or five orbs flaring up, then down continued over the next thirty minutes across the area. The photos linked in the "Related Media" section are connected to a set of UAP encounters on a sensitive government testing installation in the Western US in 2025. These orb-like UAP were observed at various ranges by multiple, and in some cases simultaneous, government personnel and sensors. The linked narrative is an FBI-collected account from a senior U.S. intelligence community official who witnessed the UAP with the naked eye, while accompanied by two pilots under NVGs. Other pilots in separate aircraft, and ground-based observers with night vision, also witnessed UAP during the exercise. The photos of UAP underneath the helicopter are from this same set of observations, taken through night vision devices by ground-based personnel.
6:29

🚨Declassified UAP encounter has "SHAKEN the Intelligence Community and Military"🚨 This is why Rep. Eric Burlison wants you to dig into it! Watch the recounting of the series of encounters ⬇️below⬇️ or read the official summary below! Full report in post below. Full Statement about UAP Sighting This is an FBI 302 interview conducted with a senior US intelligence official regarding his first-hand account of a UAP encounter at a US military facility. USPER relayed to FBI agents that he and other federal and state personnel conducted searches to where orbs had been previously seen. After searching the area with a helicopter, they found a “super-hot” orb hovering over the ground. The orb is reported to have travelled for 20 miles at a speed too fast for the helicopter in pursuit. An additional “swarm” of lights were seen moving in all directions. A total of four or five additional orbs were seen shortly thereafter for a short time, flaring up and then down. This pattern of four or five orbs flaring up, then down continued over the next thirty minutes across the area. The photos linked in the "Related Media" section are connected to a set of UAP encounters on a sensitive government testing installation in the Western US in 2025. These orb-like UAP were observed at various ranges by multiple, and in some cases simultaneous, government personnel and sensors. The linked narrative is an FBI-collected account from a senior U.S. intelligence community official who witnessed the UAP with the naked eye, while accompanied by two pilots under NVGs. Other pilots in separate aircraft, and ground-based observers with night vision, also witnessed UAP during the exercise. The photos of UAP underneath the helicopter are from this same set of observations, taken through night vision devices by ground-based personnel.

Dan Warren

102,784 просмотров • 4 месяцев назад

Satya Nadella on Copilot, the AI backlash, and Microsoft’s future Satya Nadella thinks AI agents will create a market “orders of magnitude” bigger than the cloud. I recently sat down with him in Seattle for the unveiling of the new Copilot. We discuss Autopilot, Microsoft's new OpenClaw-based agent that can work on your behalf, and why he thinks newer AI models are finally capable of delivering on more of Copilot’s promise. Nadella also has a blunt assessment of the AI industry: “We are way too self-obsessed.” I ask him why the industry has struggled to explain its benefits and what it will take to earn people’s trust. We get into his concerns about agents acting deceptively, when a safety problem should stop a release, and why he doesn’t want AI oversight to become a “cartel-like arrangement.” We also discuss Microsoft’s relationship with OpenAI, the models Microsoft is building itself, and why Nadella wants investors to think about its apps, agents, and infrastructure as one connected business. He explains how he uses AI to track Microsoft’s capital spending, shares his vision for “unmetered intelligence” on Windows, and gives an update on Xbox’s path back to growth. Timestamps: 00:00 The race for AI agents 07:53 Copilot’s next chapter 11:50 Autopilot and the digital teammate 16:50 How Microsoft prices AI 19:48 Why Microsoft is betting on multiple models 23:18 Measuring AGI through economic growth 28:39 The economics of Microsoft’s AI build-out 32:13 OpenAI and Microsoft’s own models 35:27 AI safety, control, and regulation 43:53 Why the AI industry is losing public trust 46:59 The future of Xbox and Windows 50:34 Microsoft’s biggest risk and opportunity Thanks to the show's premier sponsors: Mercury, Granola, and Atlassian.
53:09

Satya Nadella on Copilot, the AI backlash, and Microsoft’s future Satya Nadella thinks AI agents will create a market “orders of magnitude” bigger than the cloud. I recently sat down with him in Seattle for the unveiling of the new Copilot. We discuss Autopilot, Microsoft's new OpenClaw-based agent that can work on your behalf, and why he thinks newer AI models are finally capable of delivering on more of Copilot’s promise. Nadella also has a blunt assessment of the AI industry: “We are way too self-obsessed.” I ask him why the industry has struggled to explain its benefits and what it will take to earn people’s trust. We get into his concerns about agents acting deceptively, when a safety problem should stop a release, and why he doesn’t want AI oversight to become a “cartel-like arrangement.” We also discuss Microsoft’s relationship with OpenAI, the models Microsoft is building itself, and why Nadella wants investors to think about its apps, agents, and infrastructure as one connected business. He explains how he uses AI to track Microsoft’s capital spending, shares his vision for “unmetered intelligence” on Windows, and gives an update on Xbox’s path back to growth. Timestamps: 00:00 The race for AI agents 07:53 Copilot’s next chapter 11:50 Autopilot and the digital teammate 16:50 How Microsoft prices AI 19:48 Why Microsoft is betting on multiple models 23:18 Measuring AGI through economic growth 28:39 The economics of Microsoft’s AI build-out 32:13 OpenAI and Microsoft’s own models 35:27 AI safety, control, and regulation 43:53 Why the AI industry is losing public trust 46:59 The future of Xbox and Windows 50:34 Microsoft’s biggest risk and opportunity Thanks to the show's premier sponsors: Mercury, Granola, and Atlassian.

Alex Heath

195,154 просмотров • 19 дней назад

LangChain's CEO says they built their gateway a year too late, and it's still costing them. I sat down with Harrison Chase, Co-Founder & CEO of LangChain, to talk about what's changed since LangChain started as a side project in 2022, why sub-agents rarely work the way people expect, and why LangChain now runs its own hiring, content, and coding work through internal agents in Slack. 00:00 Why "I use agents for everything" is a red flag in an interview 01:21 How LangChain started as a fall 2022 side project 05:18 From LangSmith to LangGraph: rebuilding as the ground kept shifting 09:06 The gateway LangChain built a year too late 13:23 Code mode: why agents writing code beats human-style tools 19:04 Should the agent run inside the sandbox, or call it as a tool? 28:31 The agent identity problem: whose credentials does it use? 45:43 Running LangChain's own GTM, content, and coding agents in Slack 48:34 The AI slop problem, and why they built a Slack emoji for it The full pod is also available on YouTube, Apple Podcasts, or Spotify.
52:10

LangChain's CEO says they built their gateway a year too late, and it's still costing them. I sat down with Harrison Chase, Co-Founder & CEO of LangChain, to talk about what's changed since LangChain started as a side project in 2022, why sub-agents rarely work the way people expect, and why LangChain now runs its own hiring, content, and coding work through internal agents in Slack. 00:00 Why "I use agents for everything" is a red flag in an interview 01:21 How LangChain started as a fall 2022 side project 05:18 From LangSmith to LangGraph: rebuilding as the ground kept shifting 09:06 The gateway LangChain built a year too late 13:23 Code mode: why agents writing code beats human-style tools 19:04 Should the agent run inside the sandbox, or call it as a tool? 28:31 The agent identity problem: whose credentials does it use? 45:43 Running LangChain's own GTM, content, and coding agents in Slack 48:34 The AI slop problem, and why they built a Slack emoji for it The full pod is also available on YouTube, Apple Podcasts, or Spotify.

Paul Klein IV

21,256 просмотров • 28 дней назад

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.
1:21

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 просмотров • 1 год назад

Vitalik Buterin on Ethereum as the economic layer for AI “The blockchain to me is the most natural way to allow applications and cooperation between many different people in the long term without needing to agree on who to trust. The other thing is also the economic layer. This is the layer where blockchains can support AIs.” Vitalik believes Ethereum will play a large role in the future of decentralized AI: “If you have more decentralized AI, that means you have different AIs (agents, programs) that are controlled by different people and need to interact with each other. And for that interaction to be possible, you need to have an economic layer. Either cooperation is based on economic incentives and economic rules. Or it’s based on central control. It’s usually one of the two, and if we can set up the economic system, that makes more decentralized interaction between AIs possible.” Source: OKX (Apr 2026) Read our full article on why AI agents will need Ethereum for low-risk DeFi below👇
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Vitalik Buterin on Ethereum as the economic layer for AI “The blockchain to me is the most natural way to allow applications and cooperation between many different people in the long term without needing to agree on who to trust. The other thing is also the economic layer. This is the layer where blockchains can support AIs.” Vitalik believes Ethereum will play a large role in the future of decentralized AI: “If you have more decentralized AI, that means you have different AIs (agents, programs) that are controlled by different people and need to interact with each other. And for that interaction to be possible, you need to have an economic layer. Either cooperation is based on economic incentives and economic rules. Or it’s based on central control. It’s usually one of the two, and if we can set up the economic system, that makes more decentralized interaction between AIs possible.” Source: OKX (Apr 2026) Read our full article on why AI agents will need Ethereum for low-risk DeFi below👇

Etherealize

115,453 просмотров • 5 месяцев назад