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📣 𝗖𝗮𝗹𝗹 𝗳𝗼𝗿 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗶𝗻𝘀𝘁𝗶𝘁𝘂𝘁𝗶𝗼𝗻𝘀 𝗮𝗻𝗱 𝗰𝗼𝗿𝗽𝗼𝗿𝗮𝘁𝗲𝘀 with projects and use cases focusing on the intersection of XR+AI! With Meta's release of 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝗔𝗿𝗶𝗮 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗞𝗶𝘁, your innovators will work with XR Bootcamp, 𝗫𝗥 𝗣𝗿𝗼 𝗖𝗼𝗹𝗹𝗲𝗰𝘁𝗶𝘃𝗲 and xraihack's greatest minds who have already built over 𝟮𝟲 𝗔𝗜-𝗽𝗼𝘄𝗲𝗿𝗲𝗱 𝗫𝗥 𝗽𝗿𝗼𝗷𝗲𝗰𝘁𝘀... to date on various use cases and will get the chance to make use of this new kit. Retweet or comment below if you are interested! We are also planning to unlock funding opportunities for promising projects with the help of our regional partners. So many use cases to explore like embodied AI, contextualized AI, human-computer interaction (HCI), robotics, and more... There is no better time to start your first 100% context-aware projects or apps than today! More details about Meta Reality Labs announcement: Aria Research Kit includes: - Aria Glasses - Machine Perception Cloud Services - Client SDK and Companion appshow more

XR Bootcamp

4,000 subscribers

14,250 Aufrufe • vor 1 Jahr •via X (Twitter)

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Anya Rossi• Live Now

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8 Kommentare

Profilbild von Rafael Grossmann, MD, MSHS, FACS 🇻🇪🇺🇸

Rafael Grossmann, MD, MSHS, FACS 🇻🇪🇺🇸vor 1 Jahr

@Meta Healthcare. Healthcare. Healthcare We should tackle this! It will radically change medical care!! @williamsullivan @Dilmerv

Profilbild von Gopi Gautam

Gopi Gautamvor 1 Jahr

@Meta I MA INTERESTED. I AM LOOKING THIS SINCE 2 YEARS . GIVE ME YOUR 5 MINUTES I HAVE EVERYTHING RAEDY . FROM PLAN TO CUSTOMERS

Profilbild von erks.io ᯅ

erks.io ᯅvor 1 Jahr

@Meta Super interested!

Profilbild von Ingmar Büchner

Ingmar Büchnervor 1 Jahr

@Meta Robotics teleoperation for immersive collaborative bot workflows with precise and intuitive control systems

Profilbild von bird

birdvor 1 Jahr

@Meta I’m currently working on research with XR + Gaussian Splatting, this would be a game changer

Profilbild von Mario Deutschmann ☀️

Mario Deutschmann ☀️vor 1 Jahr

@Meta Would love to port our @XR_Bootcamp Hackathon Winner project to Aria research kit and Llama 3.2 ❤️😎 Are you with us @RealityLabs @AIatMeta ?

Profilbild von Dr. Marco Lazzeri ᯅ CES 🇮🇹

Dr. Marco Lazzeri ᯅ CES 🇮🇹vor 1 Jahr

@Meta Meta's vision of the future is something wonderful ❤️

Profilbild von Ashraf Addani

Ashraf Addanivor 1 Jahr

@Dilmerv @Meta OMG finally!! @DavidSven are you aware of this!?

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SPECTRE AI

41,243 Aufrufe • vor 2 Jahren

Here we go again 🚀! Excited to announce that we're building A1Zap (YC W25) with Pennie Li and that we're in the Y Combinator W25 batch in San Francisco! What is A1Base? A1Base gives AI Agents a real world identity for work. We do that by rebuilding Twilio and Okta from the ground up, putting AI Agents first. This means developers can make AI-first agentic applications 10x easier with our API's. ⁉️ Why are we doing this? Because there's a huge torrent of new valuable companies possible with AI agents, but to get their AI Agents to users, they have to chain custom apps, chat interfaces, awkward Slack integrations, browser bots, and wrestle with Twilio’s legacy API (which is built for marketing). We solve this by providing developers with an easy to use API to interface your AI agent with humans/coworkers/users where they are in this case in Whatsapp, Slack, Teams, SMS and more) - with AI Agent features built in. These digital workers are poised to transform how we work and we're the critical infrastructure to help them interact naturally in human workflows. We're not just building another AI tool. We're creating the infrastructure that will enable AI agents to become a natural part of the workforce - handling everything from customer support to sales development to creative work. We're backed by Y Combinator and working with founding teams who share our vision. We believe that in the near future, AI Agents with human coworkers will enable us to pursue more creative and impactful work. Our mission is to help developers build AI Agents that people can partner with and rely on as trusted allies—always with a human-first mindset. If you're thinking about the Agentic future of your company reach out! If you're looking to build your first AI Agentic company - reach out too - we have some amazing open source templates to get you started on the journey. Excited to share more of what we're up to soon 🔜.

Here we go again 🚀! Excited to announce that we're building A1Zap (YC W25) with Pennie Li and that we're in the Y Combinator W25 batch in San Francisco! What is A1Base? A1Base gives AI Agents a real world identity for work. We do that by rebuilding Twilio and Okta from the ground up, putting AI Agents first. This means developers can make AI-first agentic applications 10x easier with our API's. ⁉️ Why are we doing this? Because there's a huge torrent of new valuable companies possible with AI agents, but to get their AI Agents to users, they have to chain custom apps, chat interfaces, awkward Slack integrations, browser bots, and wrestle with Twilio’s legacy API (which is built for marketing). We solve this by providing developers with an easy to use API to interface your AI agent with humans/coworkers/users where they are in this case in Whatsapp, Slack, Teams, SMS and more) - with AI Agent features built in. These digital workers are poised to transform how we work and we're the critical infrastructure to help them interact naturally in human workflows. We're not just building another AI tool. We're creating the infrastructure that will enable AI agents to become a natural part of the workforce - handling everything from customer support to sales development to creative work. We're backed by Y Combinator and working with founding teams who share our vision. We believe that in the near future, AI Agents with human coworkers will enable us to pursue more creative and impactful work. Our mission is to help developers build AI Agents that people can partner with and rely on as trusted allies—always with a human-first mindset. If you're thinking about the Agentic future of your company reach out! If you're looking to build your first AI Agentic company - reach out too - we have some amazing open source templates to get you started on the journey. Excited to share more of what we're up to soon 🔜.

Pasha Rayan

53,998 Aufrufe • vor 1 Jahr

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!

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

726,150 Aufrufe • vor 1 Jahr

Palo Alto Networks CEO Nikesh Arora says roughly 50% of the company’s new hires over the last six months have been early-career. Three talent profiles PAN is prioritizing in the AI era: 1 – People who can actually use coding agents “One set of people we want are people who are AI-savvy, who know how to use AI to get their jobs done better, who know how to use coding agents.” “These are people who are learning, and they’re typically having to run through hackathons to get to Palo Alto. We don’t look at where you went to school. We care about whether you can use coding agents, whether you can use AI.” “If we keep following that trend, it’s reasonably likely that we will overwhelm the non-AI-savvy people with more AI-savvy people. That’s kind of ground zero. You’ve got to get that done.” 2 - Cybersecurity experts who know AI “The second part is there are people who are really good at cybersecurity and know AI and they’d like to get involved.” “If you want to work in cybersecurity, there’s no better place to work than Palo Alto Networks. We’re the largest cybersecurity company in the world. You want to have an impact? You want lots of proprietary training data? We’ve got it.” 3 – Pure AI researchers “The third part is raw, pure AI researchers who can do wonders with small language models and large language models.” “There we have people who are AI literate. We have some PhDs in AI who work here who have a cybersecurity bent, but they can go back to their roots in AI.”

Palo Alto Networks CEO Nikesh Arora says roughly 50% of the company’s new hires over the last six months have been early-career. Three talent profiles PAN is prioritizing in the AI era: 1 – People who can actually use coding agents “One set of people we want are people who are AI-savvy, who know how to use AI to get their jobs done better, who know how to use coding agents.” “These are people who are learning, and they’re typically having to run through hackathons to get to Palo Alto. We don’t look at where you went to school. We care about whether you can use coding agents, whether you can use AI.” “If we keep following that trend, it’s reasonably likely that we will overwhelm the non-AI-savvy people with more AI-savvy people. That’s kind of ground zero. You’ve got to get that done.” 2 - Cybersecurity experts who know AI “The second part is there are people who are really good at cybersecurity and know AI and they’d like to get involved.” “If you want to work in cybersecurity, there’s no better place to work than Palo Alto Networks. We’re the largest cybersecurity company in the world. You want to have an impact? You want lots of proprietary training data? We’ve got it.” 3 – Pure AI researchers “The third part is raw, pure AI researchers who can do wonders with small language models and large language models.” “There we have people who are AI literate. We have some PhDs in AI who work here who have a cybersecurity bent, but they can go back to their roots in AI.”

TBPN

44,698 Aufrufe • vor 20 Tagen