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Meta Develops Non-Invasive Neural Interface for Next-Generation Interaction Meta Reality Labs is advancing wrist-based neural interface technology designed to enable more natural and intuitive interaction with future computing platforms. The non-invasive device leverages finger-tracking to interpret user intent. Meta’s CEO has indicated that the technology could reach commercialization within... show more

Wevolver

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332,305 просмотров • 4 месяцев назад •via X (Twitter)

Здоровье и велнес Образование Наука и технологии

Anya Rossi• Live Now

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Meta’s Chief AI Officer Alexandr Wang just put a five-year countdown on the most consequential race in human history. Wang: “Mark and myself, we very strongly believe that this is a very special time in human history.” Not a decade. Not a generation. Five years. Wang: “The discoveries made over the next half-decade are going to be some of the most monumental discoveries that human civilization has ever made.” To run that race, Meta didn’t just build a new model. They built an entirely new division from scratch. Meta Superintelligence Labs. Designed from a blank slate. Singular focus. Wang: “What does the optimal team look like for the future of superintelligence?” The bottleneck to superintelligence isn’t compute anymore. It isn’t data. It’s the density of human genius in a single room. Wang: “Highest talent density. Bring the very best people together and build the best possible environment for them.” The AI arms race has shifted from hoarding GPUs to hoarding the smartest minds on earth. The first company to perfect that organizational structure will be the first company to reach superintelligence. But reaching it is only half the battle. Deploying what you built to the world is the other half. And here is where Meta’s advantage becomes almost unfair. Wang: “Three and a half billion people utilize our platforms every single day.” While every other AI lab is still trying to figure out how to get users to adopt their technology, Meta already has nearly half the planet locked into their ecosystem. MSL wasn’t built just to achieve scientific breakthroughs. Wang: “Build the products that will enable this technology to be deployed to billions and billions of people worldwide.” Whoever builds superintelligence first wins the race. Whoever distributes it to 3.5 billion people controls what comes after. Meta is positioning to do both.

Meta’s Chief AI Officer Alexandr Wang just put a five-year countdown on the most consequential race in human history. Wang: “Mark and myself, we very strongly believe that this is a very special time in human history.” Not a decade. Not a generation. Five years. Wang: “The discoveries made over the next half-decade are going to be some of the most monumental discoveries that human civilization has ever made.” To run that race, Meta didn’t just build a new model. They built an entirely new division from scratch. Meta Superintelligence Labs. Designed from a blank slate. Singular focus. Wang: “What does the optimal team look like for the future of superintelligence?” The bottleneck to superintelligence isn’t compute anymore. It isn’t data. It’s the density of human genius in a single room. Wang: “Highest talent density. Bring the very best people together and build the best possible environment for them.” The AI arms race has shifted from hoarding GPUs to hoarding the smartest minds on earth. The first company to perfect that organizational structure will be the first company to reach superintelligence. But reaching it is only half the battle. Deploying what you built to the world is the other half. And here is where Meta’s advantage becomes almost unfair. Wang: “Three and a half billion people utilize our platforms every single day.” While every other AI lab is still trying to figure out how to get users to adopt their technology, Meta already has nearly half the planet locked into their ecosystem. MSL wasn’t built just to achieve scientific breakthroughs. Wang: “Build the products that will enable this technology to be deployed to billions and billions of people worldwide.” Whoever builds superintelligence first wins the race. Whoever distributes it to 3.5 billion people controls what comes after. Meta is positioning to do both.

Dustin

32,982 просмотров • 4 месяцев назад

Mark Zuckerberg explains the winning DNA of Meta. Even when people thought Facebook is gonna get obsolete with the rise of apps like Snapchat, Twitter & Instagram etc. Meta still stands as one of the most powerful companies in the world. Mark says Meta was never a social app or a social network, it's a technology company focused on Human Connections. Unlike other companies they've never limited themselves to a narrow point from the beginning. Meta's Technical foundation is so strong that it could venture into any domain & create major impact. Meta's ability to solve any problem also comes from Mark's engineering origin - he studied System Engg & this impacted the whole company's problem solving mindset. Also Mark noticed this in SV & made sure Meta didn't do this mistake - Not all companies who call themselves a Tech company is truly a technology company. As their management team & Board had Less engineers & even the CEO sometimes aren'y technical , they can't be considered a tech company, Meta has more engg in their Management & Board.

Mark Zuckerberg explains the winning DNA of Meta. Even when people thought Facebook is gonna get obsolete with the rise of apps like Snapchat, Twitter & Instagram etc. Meta still stands as one of the most powerful companies in the world. Mark says Meta was never a social app or a social network, it's a technology company focused on Human Connections. Unlike other companies they've never limited themselves to a narrow point from the beginning. Meta's Technical foundation is so strong that it could venture into any domain & create major impact. Meta's ability to solve any problem also comes from Mark's engineering origin - he studied System Engg & this impacted the whole company's problem solving mindset. Also Mark noticed this in SV & made sure Meta didn't do this mistake - Not all companies who call themselves a Tech company is truly a technology company. As their management team & Board had Less engineers & even the CEO sometimes aren'y technical , they can't be considered a tech company, Meta has more engg in their Management & Board.

Aish

31,752 просмотров • 1 год назад

Here’s the next evolution of Onyx's systems—NAUT amphibious capabilities with SENTRY kinetic and ISR payloads. This integration with the Ghost Robotics V60 is just one example of the available options. NAUT is a plug-and-play autonomous maritime mobility system designed for easy command and control, enhancing traditional maritime capabilities and improving operational effectiveness for missions. Video source: Onyx #robotics #technology #engineering #stem #innovation #robots ----------------------- Wanna get your company on Wevolver too? Learn how:

Here’s the next evolution of Onyx's systems—NAUT amphibious capabilities with SENTRY kinetic and ISR payloads. This integration with the Ghost Robotics V60 is just one example of the available options. NAUT is a plug-and-play autonomous maritime mobility system designed for easy command and control, enhancing traditional maritime capabilities and improving operational effectiveness for missions. Video source: Onyx #robotics #technology #engineering #stem #innovation #robots ----------------------- Wanna get your company on Wevolver too? Learn how:

Wevolver

11,179 просмотров • 1 год назад

This can be the superpower of the Neural Band that Meta is giving together with the Ray-Ban Meta Display glasses. The video shows an old prototype bracelet by CTRL+LABS, the startup acquired by Meta and whose technology was used to develop the Neural Band. At the beginning of the video, the guy makes an action (a keyboard key press) with his hands, then the bracelet can substitute the key pressure, and at the end of the video, the guy doesn't even have to do the action; it is just sufficient that he "thinks" about it. As long as the brain is sending an electric message to the fingers, the full action is not necessary anymore. Just an "intention" to move them is necessary. If the Neural Band is evolved to this stage, and the users are educated to this, potentially, we may not even need to perform air taps or writing gestures, but we could just think about doing them. This would reduce a lot of the fatigue of using XR devices and the weirdness of using them on the street. Then why isn't this feature available today? I guess that the reason is twofold. First of all, we have accuracy: the full gesture is easier to detect for the system. Many people (me included) are praising the accuracy of the Neural Band, and this is amazing, because an input mechanism should have a reliability close to 100%. Then we, as users, have never been trained to just "think" about actions: it would feel weird and hard to learn. I think we should undergo some training to learn how to do this "thinking" operation properly. I hope that something like this could come in the upcoming years... that would be the real game-changer paradigm if compared to the camera-based tracking.

This can be the superpower of the Neural Band that Meta is giving together with the Ray-Ban Meta Display glasses. The video shows an old prototype bracelet by CTRL+LABS, the startup acquired by Meta and whose technology was used to develop the Neural Band. At the beginning of the video, the guy makes an action (a keyboard key press) with his hands, then the bracelet can substitute the key pressure, and at the end of the video, the guy doesn't even have to do the action; it is just sufficient that he "thinks" about it. As long as the brain is sending an electric message to the fingers, the full action is not necessary anymore. Just an "intention" to move them is necessary. If the Neural Band is evolved to this stage, and the users are educated to this, potentially, we may not even need to perform air taps or writing gestures, but we could just think about doing them. This would reduce a lot of the fatigue of using XR devices and the weirdness of using them on the street. Then why isn't this feature available today? I guess that the reason is twofold. First of all, we have accuracy: the full gesture is easier to detect for the system. Many people (me included) are praising the accuracy of the Neural Band, and this is amazing, because an input mechanism should have a reliability close to 100%. Then we, as users, have never been trained to just "think" about actions: it would feel weird and hard to learn. I think we should undergo some training to learn how to do this "thinking" operation properly. I hope that something like this could come in the upcoming years... that would be the real game-changer paradigm if compared to the camera-based tracking.

TonyVT SkarredGhost

11,805 просмотров • 9 месяцев назад

Wrapping up the year and coinciding with #NeurIPS2024, today at Meta FAIR we’re releasing a collection of nine new open source AI research artifacts across our work in developing agents, robustness & safety and new architectures. More in the video from Joelle Pineau. All of this work is part of FAIR’s continued work towards the goal of achieving advanced machine intelligence A few highlights from what we’re releasing today: • Meta Motivo: A first-of-its-kind behavioral foundation model that controls the movements of a virtual embodied humanoid agent to perform complex tasks. • Meta Video Seal: a state-of-the art comprehensive framework for neural video watermarking. • Meta Explore Theory-of-Mind: A program-guided adversarial data generation for theory of mind reasoning. • Meta Large Concept Models: A fundamentally different training paradigm for language modeling that decouples reasoning from language representation. And much more! We’re excited to share this work with the research community and look forward to seeing how it inspires new innovation across the field. Details and access to everything released by FAIR today ➡️

Wrapping up the year and coinciding with #NeurIPS2024, today at Meta FAIR we’re releasing a collection of nine new open source AI research artifacts across our work in developing agents, robustness & safety and new architectures. More in the video from Joelle Pineau. All of this work is part of FAIR’s continued work towards the goal of achieving advanced machine intelligence A few highlights from what we’re releasing today: • Meta Motivo: A first-of-its-kind behavioral foundation model that controls the movements of a virtual embodied humanoid agent to perform complex tasks. • Meta Video Seal: a state-of-the art comprehensive framework for neural video watermarking. • Meta Explore Theory-of-Mind: A program-guided adversarial data generation for theory of mind reasoning. • Meta Large Concept Models: A fundamentally different training paradigm for language modeling that decouples reasoning from language representation. And much more! We’re excited to share this work with the research community and look forward to seeing how it inspires new innovation across the field. Details and access to everything released by FAIR today ➡️

AI at Meta

156,123 просмотров • 1 год назад

Today I’m announcing a major multi-million dollar defamation lawsuit against Meta, the owner of Facebook & Instagram. The case is WILD and has implications for ALL OF US. On top of falsely calling me a criminal, Meta suggested my kids be taken from me. Here’s a summary of events: This all started with Meta’s AI falsely claiming that I was charged with a crime from January 6th but… I wasn’t even in DC that day (I was in TN) and I’ve never been charged with a crime IN MY LIFE. We found this out in August of 2024 when I was exposing woke policies at Harley Davidson. One dealership was unhappy with me and they posted a screenshot from Meta’s AI in an effort to attack me. This screenshot was filled with lies. I couldn’t believe it was real so I checked myself. It was even worse when I checked. From that day I’ve faced a steady stream of false accusations that are deeply damaging to my character and the safety of my family. This sounds bad, right? It gets MUCH worse. Meta was notified LAST YEAR by my lawyers, yet the defamation continues today. Some lies Meta spread about me: • Meta’s AI claims that I’ve appeared on Nick Fuentes show, that I’ve spoken at his rallies, and that I’ve supported him. I’ve never met him and this is all false. • Meta’s AI claims I’ve engaged in Holocaust denial. I’ve NEVER denied the Holocaust. • Meta’s AI tells advertisers NOT to advertise with me because of the lies it invented. • Meta tells employers NOT to hire me because of the lies it invented. • Meta suggested that MY KIDS BE TAKEN FROM ME because it would be better for them to be raised by someone more friendly to DEI and transgenderism. • Meta’s ironically claimed that I’ve been sued for DEFAMATION and EMOTIONAL DISTRESS. I’ve never been sued for either. I’ve tried to fix this privately since last year. Instead of fixing this and instituting safeguards, Meta has given us the runaround. Meta later BLACKLISTED my name from being searched (insane) but it didn’t end the defamation because Meta includes my name in news stories. You can then ask for more info about me. If you do that, Meta goes back to defaming me. In fact, the lies this week are the worst yet! Meta’s AI admits that a false accusation over J6 is extremely harmful to whoever is accused. It even agrees that a court is LIKELY to rule that this was defamation with ACTUAL MALICE. With my lawsuit today, I intend to MAKE Mark Zuckerberg Meta solve this problem. Why is this so important? While I’m the target today, a candidate you like could be the next target, and lies from Meta’s AI could flip votes that decide the election. YOU could be the next target too. That’s why I’m taking on this David vs. Goliath fight. For me, my honor, my family, for our elections, and FOR YOU! If you want to help me fight ALL the battles that I’m fighting, you can help support my team at Timecodes: (0:00) Intro (0:40) Announcing Meta Lawsuit (2:01) Video of Meta’s AI Defaming Me (03:24) Meta’s AI Tells People Not To Hire or Advertise With Me (04:30) How This All Started (05:35) Trying Meta’s AI Myself — Meta Claims I Was Charged With A Crime (06:06) Meta Says I Support Nick Fuentes (06:45) Meta Says I’m A Holocaust Denier (07:07) Meta’s AI Admits Courts Will Likely Find What They Did To Be Malicious (08:08) The Threat To Our Elections (09:11) More Defamation (09:27) Were Meta’s Lies Used In A Corporate Intelligence Report? (10:36) Meta’s AI Says They Need To Apologize And Institute Safeguards (11:15) Meta Admits Their Lies Have Damaged My Reputation (11:30) Our Legal Communication since 2024 (12:28) Meta Blacklists My Name + How It Lies (14:08) Meta Suggests Authorities Take My Kids Away Because I Pose A "Threat To Their Wellbeing" (16:00) Meta Asks Me For PR Help 😳 (16:31) The Consequences Of Lying AI (17:39) Threats and An Arrest Of A Man Who Wanted To Kill Me (18:30) Closing Argument (19:07) Introducing My New Show

Today I’m announcing a major multi-million dollar defamation lawsuit against Meta, the owner of Facebook & Instagram. The case is WILD and has implications for ALL OF US. On top of falsely calling me a criminal, Meta suggested my kids be taken from me. Here’s a summary of events: This all started with Meta’s AI falsely claiming that I was charged with a crime from January 6th but… I wasn’t even in DC that day (I was in TN) and I’ve never been charged with a crime IN MY LIFE. We found this out in August of 2024 when I was exposing woke policies at Harley Davidson. One dealership was unhappy with me and they posted a screenshot from Meta’s AI in an effort to attack me. This screenshot was filled with lies. I couldn’t believe it was real so I checked myself. It was even worse when I checked. From that day I’ve faced a steady stream of false accusations that are deeply damaging to my character and the safety of my family. This sounds bad, right? It gets MUCH worse. Meta was notified LAST YEAR by my lawyers, yet the defamation continues today. Some lies Meta spread about me: • Meta’s AI claims that I’ve appeared on Nick Fuentes show, that I’ve spoken at his rallies, and that I’ve supported him. I’ve never met him and this is all false. • Meta’s AI claims I’ve engaged in Holocaust denial. I’ve NEVER denied the Holocaust. • Meta’s AI tells advertisers NOT to advertise with me because of the lies it invented. • Meta tells employers NOT to hire me because of the lies it invented. • Meta suggested that MY KIDS BE TAKEN FROM ME because it would be better for them to be raised by someone more friendly to DEI and transgenderism. • Meta’s ironically claimed that I’ve been sued for DEFAMATION and EMOTIONAL DISTRESS. I’ve never been sued for either. I’ve tried to fix this privately since last year. Instead of fixing this and instituting safeguards, Meta has given us the runaround. Meta later BLACKLISTED my name from being searched (insane) but it didn’t end the defamation because Meta includes my name in news stories. You can then ask for more info about me. If you do that, Meta goes back to defaming me. In fact, the lies this week are the worst yet! Meta’s AI admits that a false accusation over J6 is extremely harmful to whoever is accused. It even agrees that a court is LIKELY to rule that this was defamation with ACTUAL MALICE. With my lawsuit today, I intend to MAKE Mark Zuckerberg Meta solve this problem. Why is this so important? While I’m the target today, a candidate you like could be the next target, and lies from Meta’s AI could flip votes that decide the election. YOU could be the next target too. That’s why I’m taking on this David vs. Goliath fight. For me, my honor, my family, for our elections, and FOR YOU! If you want to help me fight ALL the battles that I’m fighting, you can help support my team at Timecodes: (0:00) Intro (0:40) Announcing Meta Lawsuit (2:01) Video of Meta’s AI Defaming Me (03:24) Meta’s AI Tells People Not To Hire or Advertise With Me (04:30) How This All Started (05:35) Trying Meta’s AI Myself — Meta Claims I Was Charged With A Crime (06:06) Meta Says I Support Nick Fuentes (06:45) Meta Says I’m A Holocaust Denier (07:07) Meta’s AI Admits Courts Will Likely Find What They Did To Be Malicious (08:08) The Threat To Our Elections (09:11) More Defamation (09:27) Were Meta’s Lies Used In A Corporate Intelligence Report? (10:36) Meta’s AI Says They Need To Apologize And Institute Safeguards (11:15) Meta Admits Their Lies Have Damaged My Reputation (11:30) Our Legal Communication since 2024 (12:28) Meta Blacklists My Name + How It Lies (14:08) Meta Suggests Authorities Take My Kids Away Because I Pose A "Threat To Their Wellbeing" (16:00) Meta Asks Me For PR Help 😳 (16:31) The Consequences Of Lying AI (17:39) Threats and An Arrest Of A Man Who Wanted To Kill Me (18:30) Closing Argument (19:07) Introducing My New Show

Robby Starbuck

3,720,034 просмотров • 1 год назад

My full conversation with Mark Zuckerberg on the breaking Meta AI announcements, fighting in the UFC, metaverse, Ray-Ban Metas, and future technologies. But what was really touching was his thoughts on legacy and fatherhood. Timestamps: 00:00 Intro 00:37 Meta AI announcements 02:58 How brands & creators can use Meta AI 04:32 How Mark uses AI 05:57 The most excitement Mark has had as a builder? 07:36 The future of the Ray-Ban Meta smart glasses 12:51 10 years of Reality Labs: what's next? 16:49 Jensen Huang jersey swap 18:11 How does Mark want to be remembered? 19:23 Is it Mark actually posting on social media? 20:55 Mark's choice for best MMA fighter 21:38 Mark fighting in the UFC? 22:33 Mark's fatherhood advice

My full conversation with Mark Zuckerberg on the breaking Meta AI announcements, fighting in the UFC, metaverse, Ray-Ban Metas, and future technologies. But what was really touching was his thoughts on legacy and fatherhood. Timestamps: 00:00 Intro 00:37 Meta AI announcements 02:58 How brands & creators can use Meta AI 04:32 How Mark uses AI 05:57 The most excitement Mark has had as a builder? 07:36 The future of the Ray-Ban Meta smart glasses 12:51 10 years of Reality Labs: what's next? 16:49 Jensen Huang jersey swap 18:11 How does Mark want to be remembered? 19:23 Is it Mark actually posting on social media? 20:55 Mark's choice for best MMA fighter 21:38 Mark fighting in the UFC? 22:33 Mark's fatherhood advice

Roberto Nickson

1,091,800 просмотров • 2 лет назад

The next computing shift is already underway — and it’s happening faster than even the people building it expected. Meta CTO Boz joins David George to talk about how the team is rooted in solving real-world problems — and how this new wave of AI is unlike any before, ushering us towards a future beyond the smartphone. Boz says AI isn’t just making things faster or cheaper, it’s making everything better. From interfaces to interaction design, AI is transforming how we build — and how we compute. For more on the future of computing, wearables, and AI-native UX, watch the full conversation with Boz and David:

The next computing shift is already underway — and it’s happening faster than even the people building it expected. Meta CTO Boz joins David George to talk about how the team is rooted in solving real-world problems — and how this new wave of AI is unlike any before, ushering us towards a future beyond the smartphone. Boz says AI isn’t just making things faster or cheaper, it’s making everything better. From interfaces to interaction design, AI is transforming how we build — and how we compute. For more on the future of computing, wearables, and AI-native UX, watch the full conversation with Boz and David:

a16z

17,480 просмотров • 1 год назад

Meta paid $14 billion to pry Alex Wang away from Scale AI, the company he co-founded and ran. The hope - Zuck's hope - was that Wang could fix what ailed Meta's AI program. Over the past year, Meta has spent billions more pulling researchers away from other labs and has raced to create it first new model called Muse Spark under a regime led by Wang, Nat Friedman, Daniel Gross and Shengjia Zhao. This interview is the first time Wang has talked about all the drama of the past year and where Meta is heading with AI. The Core Memory podcast is on Apple, Spotify, YouTube and all major platforms. Enjoy! Timestamps 00:00 Intro 02:02 Inside Meta Superintelligence Labs 06:23 The Tahoe Conversation 12:50 How Do You Rebuild a Frontier Lab 24:35 The Soup and Being "Too Young" 32:48 MuseSpark: Appetizer, Not Entrée 48:47 Why Does Everyone Hate AI? 53:50 Open Source and the Manus Question 1:04:59 Robots and Mango 1:11:08 Sci-Fi, BCI, and Do AI Models Deserve Moral Weight?

Meta paid $14 billion to pry Alex Wang away from Scale AI, the company he co-founded and ran. The hope - Zuck's hope - was that Wang could fix what ailed Meta's AI program. Over the past year, Meta has spent billions more pulling researchers away from other labs and has raced to create it first new model called Muse Spark under a regime led by Wang, Nat Friedman, Daniel Gross and Shengjia Zhao. This interview is the first time Wang has talked about all the drama of the past year and where Meta is heading with AI. The Core Memory podcast is on Apple, Spotify, YouTube and all major platforms. Enjoy! Timestamps 00:00 Intro 02:02 Inside Meta Superintelligence Labs 06:23 The Tahoe Conversation 12:50 How Do You Rebuild a Frontier Lab 24:35 The Soup and Being "Too Young" 32:48 MuseSpark: Appetizer, Not Entrée 48:47 Why Does Everyone Hate AI? 53:50 Open Source and the Manus Question 1:04:59 Robots and Mango 1:11:08 Sci-Fi, BCI, and Do AI Models Deserve Moral Weight?

Ashlee Vance

97,018 просмотров • 2 месяцев назад

Investors may be underestimating the optionality of $META AI glasses. In a conversation with Jensen Huang, Mark Zuckerberg laid out the vision — and it’s bigger than most realize. Ray-Ban $META glasses started with a simple constraint: make something that looks great, and fit as much technology as possible within that form factor. Camera, microphone, speakers, live streaming, WhatsApp video calls. But then the unexpected happened — that same sensor package turned out to be exactly what you need to talk to AI. That wasn’t the plan. It happened organically. And it changes the trajectory of the product potential. Zuckerberg’s projection: displayless AI glasses at a ~$300 price point becoming a product that tens — potentially hundreds — of millions of people eventually own. Ambient AI interaction built into something people already wear. Real-time translation. Visual language understanding. Etc. The optionality here is meaningful. $NVDA $EL.PA ___ YouTube: Nvidia | AI and The Next Computing Platforms With Jensen Huang and Mark Zuckerberg (07/29/2024)

Investors may be underestimating the optionality of $META AI glasses. In a conversation with Jensen Huang, Mark Zuckerberg laid out the vision — and it’s bigger than most realize. Ray-Ban $META glasses started with a simple constraint: make something that looks great, and fit as much technology as possible within that form factor. Camera, microphone, speakers, live streaming, WhatsApp video calls. But then the unexpected happened — that same sensor package turned out to be exactly what you need to talk to AI. That wasn’t the plan. It happened organically. And it changes the trajectory of the product potential. Zuckerberg’s projection: displayless AI glasses at a ~$300 price point becoming a product that tens — potentially hundreds — of millions of people eventually own. Ambient AI interaction built into something people already wear. Real-time translation. Visual language understanding. Etc. The optionality here is meaningful. $NVDA $EL.PA ___ YouTube: Nvidia | AI and The Next Computing Platforms With Jensen Huang and Mark Zuckerberg (07/29/2024)

Dimitry Nakhla | Babylon Capital®

38,695 просмотров • 3 месяцев назад

"Introducing Multimodal Llama 3.2": As promised two weeks ago, here's the short course on Meta's latest open model! This short course is created with Meta and taught by Amit Sangani, Director of AI Partner Engineering at Meta. Meta’s Llama family of models is leading the way in open models, allowing anyone to download, customize, fine-tune, or build new applications on top of them. Learn about the vision capabilities of the Llama 3.2, and use it for image classification, prompting, tokenization, tool-calling. You'll also learn about the open-source Llama stack, which gives building blocks for many different stages of the LLM application life cycle. In detail, you’ll: - Learn what are the features of Meta's four newest models, and when to use which Llama model. - Learn best practices for multimodal prompting, with applications to advanced image reasoning, illustrated by many examples: Understanding errors on a car dashboard, adding up the total of photographed restaurant receipts, grading written math homework. - Use different roles—system, user, assistant, ipython—in the Llama 3.1 and 3.2 models and the prompt format that identifies those roles. - Understand how Llama uses the tiktoken tokenizer, and how it has expanded to a 128k vocabulary size that improves encoding efficiency and multilingual support. - Learn how to prompt Llama to call built-in and custom tools (functions) with examples for web search and solving math equations. - Learn about Llama Stack, a standardized interface for common toolchain components like fine-tuning or synthetic data generation, useful for building agentic applications. By the end of this course, you’ll be equipped to build out new applications with the new Llama 3.2. Thank you to Ahmad Al-Dahle, Amit Sangani, and the whole AI at Meta team AI at Meta for all the hard work on Llama 3.2 — we’re excited to make these open models even more accessible to more developers with this new course! Please sign up here!

"Introducing Multimodal Llama 3.2": As promised two weeks ago, here's the short course on Meta's latest open model! This short course is created with Meta and taught by Amit Sangani, Director of AI Partner Engineering at Meta. Meta’s Llama family of models is leading the way in open models, allowing anyone to download, customize, fine-tune, or build new applications on top of them. Learn about the vision capabilities of the Llama 3.2, and use it for image classification, prompting, tokenization, tool-calling. You'll also learn about the open-source Llama stack, which gives building blocks for many different stages of the LLM application life cycle. In detail, you’ll: - Learn what are the features of Meta's four newest models, and when to use which Llama model. - Learn best practices for multimodal prompting, with applications to advanced image reasoning, illustrated by many examples: Understanding errors on a car dashboard, adding up the total of photographed restaurant receipts, grading written math homework. - Use different roles—system, user, assistant, ipython—in the Llama 3.1 and 3.2 models and the prompt format that identifies those roles. - Understand how Llama uses the tiktoken tokenizer, and how it has expanded to a 128k vocabulary size that improves encoding efficiency and multilingual support. - Learn how to prompt Llama to call built-in and custom tools (functions) with examples for web search and solving math equations. - Learn about Llama Stack, a standardized interface for common toolchain components like fine-tuning or synthetic data generation, useful for building agentic applications. By the end of this course, you’ll be equipped to build out new applications with the new Llama 3.2. Thank you to Ahmad Al-Dahle, Amit Sangani, and the whole AI at Meta team AI at Meta for all the hard work on Llama 3.2 — we’re excited to make these open models even more accessible to more developers with this new course! Please sign up here!

Andrew Ng

131,767 просмотров • 1 год назад

RailScan Multi-Function Robot: Railway Surface Inspection The RailScan robot is designed for track inspection, using a self-moving platform and precise sensors to quickly detect track defects. It assists track inspectors with nighttime inspections, addressing challenges in traditional manual inspections such as heavy workload, missed detections, and difficult tasks. The robot helps reduce inspection costs, improve efficiency, and enhance safety by identifying potential hazards in the rail track. Video source: Shenhao Robotics #robotics #inspection #RailwayRobot #technology #engineering #stem #innovation #robots #automation ----------------------- Wanna get your company on Wevolver too? Learn how:

RailScan Multi-Function Robot: Railway Surface Inspection The RailScan robot is designed for track inspection, using a self-moving platform and precise sensors to quickly detect track defects. It assists track inspectors with nighttime inspections, addressing challenges in traditional manual inspections such as heavy workload, missed detections, and difficult tasks. The robot helps reduce inspection costs, improve efficiency, and enhance safety by identifying potential hazards in the rail track. Video source: Shenhao Robotics #robotics #inspection #RailwayRobot #technology #engineering #stem #innovation #robots #automation ----------------------- Wanna get your company on Wevolver too? Learn how:

Wevolver

26,459 просмотров • 1 год назад

📣 I talk a lot about Meta SDKs because I spend a lot of time with these tools. But also when someone asks me what VR/MR tools they can use for cross platform support, I recommend 𝗨𝗻𝗶𝘁𝘆’𝘀 𝗫𝗥 𝗧𝗼𝗼𝗹𝗸𝗶𝘁 which provides: - 𝗖𝗿𝗼𝘀𝘀-𝗽𝗹𝗮𝘁𝗳𝗼𝗿𝗺 𝘀𝘂𝗽𝗽𝗼𝗿𝘁: Meta Quest, OpenXR, Windows Mixed Reality, + more - 𝗜𝗻𝘁𝗲𝗿𝗮𝗰𝘁𝗶𝗼𝗻𝘀: Hover, select, grab - 𝗙𝗲𝗲𝗱𝗯𝗮𝗰𝗸: Haptic + visual tint/line for possible & active interactions - 𝗨𝗜: Canvas interaction via XR controllers - 𝗨𝘁𝗶𝗹𝗶𝘁𝗶𝗲𝘀: XR Origin support for stationary & room-scale VR - 𝗫𝗥 𝗛𝗮𝗻𝗱𝘀: this is an extended package to support more advanced hand tracking interactions 👉 Also, it supports 𝗔𝗥 𝗳𝗼𝗿 𝗺𝗼𝗯𝗶𝗹𝗲 𝗳𝗲𝗮𝘁𝘂𝗿𝗲𝘀 𝘁𝗵𝗿𝗼𝘂𝗴𝗵 𝗔𝗥 𝗙𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻, the features are: - 𝗔𝗥 𝗴𝗲𝘀𝘁𝘂𝗿𝗲 𝘀𝘆𝘀𝘁𝗲𝗺: Maps screen touches to Input System gesture events via TouchscreenGestureInputController - 𝗦𝗰𝗿𝗲𝗲𝗻-𝘀𝗽𝗮𝗰𝗲 𝗶𝗻𝗽𝘂𝘁: Feeds touch data into XRRayInteractor for AR interaction - 𝗔𝗥𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗲𝗿: Converts place, select, translate, rotate, scale gestures into object manipulation 👨‍💻 And to emulate your apps/games without physical devices I recommend the following: - 𝗫𝗥 𝗗𝗲𝘃𝗶𝗰𝗲 𝗦𝗶𝗺𝘂𝗹𝗮𝘁𝗼𝗿 for VR/MR to test your interactions - 𝗔𝗥 𝗙𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻 𝗥𝗲𝗺𝗼𝘁𝗲 𝟮.𝟬 for AR Foundation testing, this allows you to remotely test all the AR features by connecting the Unity editor to your physical device (iOS or Android) 💡 Are you using Unity’s XR Toolkit? ISDK? any other toolkit?

📣 I talk a lot about Meta SDKs because I spend a lot of time with these tools. But also when someone asks me what VR/MR tools they can use for cross platform support, I recommend 𝗨𝗻𝗶𝘁𝘆’𝘀 𝗫𝗥 𝗧𝗼𝗼𝗹𝗸𝗶𝘁 which provides: - 𝗖𝗿𝗼𝘀𝘀-𝗽𝗹𝗮𝘁𝗳𝗼𝗿𝗺 𝘀𝘂𝗽𝗽𝗼𝗿𝘁: Meta Quest, OpenXR, Windows Mixed Reality, + more - 𝗜𝗻𝘁𝗲𝗿𝗮𝗰𝘁𝗶𝗼𝗻𝘀: Hover, select, grab - 𝗙𝗲𝗲𝗱𝗯𝗮𝗰𝗸: Haptic + visual tint/line for possible & active interactions - 𝗨𝗜: Canvas interaction via XR controllers - 𝗨𝘁𝗶𝗹𝗶𝘁𝗶𝗲𝘀: XR Origin support for stationary & room-scale VR - 𝗫𝗥 𝗛𝗮𝗻𝗱𝘀: this is an extended package to support more advanced hand tracking interactions 👉 Also, it supports 𝗔𝗥 𝗳𝗼𝗿 𝗺𝗼𝗯𝗶𝗹𝗲 𝗳𝗲𝗮𝘁𝘂𝗿𝗲𝘀 𝘁𝗵𝗿𝗼𝘂𝗴𝗵 𝗔𝗥 𝗙𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻, the features are: - 𝗔𝗥 𝗴𝗲𝘀𝘁𝘂𝗿𝗲 𝘀𝘆𝘀𝘁𝗲𝗺: Maps screen touches to Input System gesture events via TouchscreenGestureInputController - 𝗦𝗰𝗿𝗲𝗲𝗻-𝘀𝗽𝗮𝗰𝗲 𝗶𝗻𝗽𝘂𝘁: Feeds touch data into XRRayInteractor for AR interaction - 𝗔𝗥𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗲𝗿: Converts place, select, translate, rotate, scale gestures into object manipulation 👨‍💻 And to emulate your apps/games without physical devices I recommend the following: - 𝗫𝗥 𝗗𝗲𝘃𝗶𝗰𝗲 𝗦𝗶𝗺𝘂𝗹𝗮𝘁𝗼𝗿 for VR/MR to test your interactions - 𝗔𝗥 𝗙𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻 𝗥𝗲𝗺𝗼𝘁𝗲 𝟮.𝟬 for AR Foundation testing, this allows you to remotely test all the AR features by connecting the Unity editor to your physical device (iOS or Android) 💡 Are you using Unity’s XR Toolkit? ISDK? any other toolkit?

Dilmer 👓

12,943 просмотров • 3 месяцев назад

Open science is how we continue to push technology forward and today at Meta FAIR we’re sharing eight new AI research artifacts including new models, datasets and code to inspire innovation in the community. More in the video from Joelle Pineau. This work is another important step towards our goal of achieving Advanced Machine Intelligence (AMI). What we’re releasing: • Meta Spirit LM: An open source language model for seamless speech and text integration. • Meta Segment Anything Model 2.1: An updated checkpoint with improved results on visually similar objects, small objects and occlusion handling. Plus a new developer suite to make it easier for developers to build with SAM 2. • Layer Skip: Inference code and fine-tuned checkpoints demonstrating a new method for enhancing LLM performance. • SALSA: New code to enable researchers to benchmark AI-based attacks in support of validating security for post-quantum cryptography. • Meta Lingua: A lightweight and self-contained codebase designed to train language models at scale. • Meta Open Materials: New open source models and the largest dataset of its kind to accelerate AI-driven discovery of new inorganic materials. • MEXMA: A new research paper and code for our novel pre-trained cross-lingual sentence encoder with coverage across 80 languages. • Self-Taught Evaluator: a new method for generating synthetic preference data to train reward models without relying on human annotations. Access to state-of-the-art AI creates opportunities for everyone. We’re excited to share this work and look forward to seeing the community innovation that results from it. Details and access to everything released by FAIR today ➡️

Open science is how we continue to push technology forward and today at Meta FAIR we’re sharing eight new AI research artifacts including new models, datasets and code to inspire innovation in the community. More in the video from Joelle Pineau. This work is another important step towards our goal of achieving Advanced Machine Intelligence (AMI). What we’re releasing: • Meta Spirit LM: An open source language model for seamless speech and text integration. • Meta Segment Anything Model 2.1: An updated checkpoint with improved results on visually similar objects, small objects and occlusion handling. Plus a new developer suite to make it easier for developers to build with SAM 2. • Layer Skip: Inference code and fine-tuned checkpoints demonstrating a new method for enhancing LLM performance. • SALSA: New code to enable researchers to benchmark AI-based attacks in support of validating security for post-quantum cryptography. • Meta Lingua: A lightweight and self-contained codebase designed to train language models at scale. • Meta Open Materials: New open source models and the largest dataset of its kind to accelerate AI-driven discovery of new inorganic materials. • MEXMA: A new research paper and code for our novel pre-trained cross-lingual sentence encoder with coverage across 80 languages. • Self-Taught Evaluator: a new method for generating synthetic preference data to train reward models without relying on human annotations. Access to state-of-the-art AI creates opportunities for everyone. We’re excited to share this work and look forward to seeing the community innovation that results from it. Details and access to everything released by FAIR today ➡️

AI at Meta

150,222 просмотров • 1 год назад

"This is not the end of VR. It's not collapsing. If you pay attention to what's going to be coming out from Meta and others over the next 12 months, you're going to see a lot of progress." Palmer Luckey gives his latest perspective on the VR industry: John: "How are you thinking about VR these days? Everyone's sort of writing down their investments and pulling back." Palmer: "I will challenge your premise there, which is that people are pulling back. I think that's driven mostly by people sensationalizing Meta firing a bunch of people." "They got rid of 10% of the Reality Labs team in one layoff. Remember that they have something like 8% or 9% annual churn naturally and organically, not including firings. So what you're really talking about is basically pulling six months of churn forward into a single month. And they're still spending more on VR than anybody by an order of magnitude." "Meta and Sony and Apple and Google and all of these other companies are going to be hitting the [Apple Vision Pro] level of visual fidelity. They're going to be doing it with headsets that are far smaller, far lighter than what you see from Vision Pro. And I actually remain very optimistic."

"This is not the end of VR. It's not collapsing. If you pay attention to what's going to be coming out from Meta and others over the next 12 months, you're going to see a lot of progress." Palmer Luckey gives his latest perspective on the VR industry: John: "How are you thinking about VR these days? Everyone's sort of writing down their investments and pulling back." Palmer: "I will challenge your premise there, which is that people are pulling back. I think that's driven mostly by people sensationalizing Meta firing a bunch of people." "They got rid of 10% of the Reality Labs team in one layoff. Remember that they have something like 8% or 9% annual churn naturally and organically, not including firings. So what you're really talking about is basically pulling six months of churn forward into a single month. And they're still spending more on VR than anybody by an order of magnitude." "Meta and Sony and Apple and Google and all of these other companies are going to be hitting the [Apple Vision Pro] level of visual fidelity. They're going to be doing it with headsets that are far smaller, far lighter than what you see from Vision Pro. And I actually remain very optimistic."

TBPN

29,462 просмотров • 4 месяцев назад

Mark Zuckerberg on the importance of engineers if you’re building a technology company “We never thought about ourselves as a website or a social network or anything like that.” Mark believes many companies define themselves too narrowly: “It’s one of the things I observed as soon as I came out to [Silicon] Valley. All these companies that called themselves technology companies were not really set up that way. The CEO wasn’t technical. The board of directors had no one technical on it… And it’s like alright, if that’s your team, then you’re not a technology company.” He believes there’s a balance: “You don’t want everyone to be an engineer because there’s other things that matter too. But if you don’t have a high enough share of the company as engineers, then you’re not a technology company.” This makes sense when you view it in the context of Mark’s strategy for Meta: “I define our strategy as: If we can learn faster than every other company, we’re going to win. We’re going to build a better product than everyone else because we’re going to get it out first, we’re going to have a good feedback loop, and we’re going to learn what people like better than other people.” He concludes: “I think that’s basically the formula. Be a technology company. Build a good foundation. Learn from what other people are focused on in the world. And iterate as quickly as you can.” Video source: Acquired Podcast (2024)

Mark Zuckerberg on the importance of engineers if you’re building a technology company “We never thought about ourselves as a website or a social network or anything like that.” Mark believes many companies define themselves too narrowly: “It’s one of the things I observed as soon as I came out to [Silicon] Valley. All these companies that called themselves technology companies were not really set up that way. The CEO wasn’t technical. The board of directors had no one technical on it… And it’s like alright, if that’s your team, then you’re not a technology company.” He believes there’s a balance: “You don’t want everyone to be an engineer because there’s other things that matter too. But if you don’t have a high enough share of the company as engineers, then you’re not a technology company.” This makes sense when you view it in the context of Mark’s strategy for Meta: “I define our strategy as: If we can learn faster than every other company, we’re going to win. We’re going to build a better product than everyone else because we’re going to get it out first, we’re going to have a good feedback loop, and we’re going to learn what people like better than other people.” He concludes: “I think that’s basically the formula. Be a technology company. Build a good foundation. Learn from what other people are focused on in the world. And iterate as quickly as you can.” Video source: Acquired Podcast (2024)

Startup Archive

44,115 просмотров • 8 месяцев назад

Mark Zuckerberg says the future of coding is closer than we think: AI agents inside Meta are being built not as generic developer tools, but to push Llama research forward — fully integrated into their workflow. He predicts that within 12–18 months, most of the code for these efforts could be written by AI itself — not simple autocomplete, but systems that take goals, run tests, fix bugs, improve performance, and even write higher-quality code than many skilled engineers. The real takeaway? This is only one part of a massive AI landscape, and no single company will dominate it all. Meta is building its own internal agents designed specifically to advance Llama research — deeply connected to their toolchain rather than built for enterprise customers. He expects that within the next year to year-and-a-half, AI will be writing most of the code in these projects, going far beyond autocomplete — understanding goals, running experiments, finding issues, and continuously improving systems. And according to him, this shift will become a core driver of how AI itself evolves. Meta is investing heavily in coding and research agents deeply integrated into their own systems, focused on advancing Llama rather than building broad enterprise tools. He expects AI will soon move beyond autocomplete to fully goal-driven coding — testing, debugging, improving, and producing high-quality results. But in his view, the AI revolution is too big for any single winner — multiple players and approaches will shape the future.

Mark Zuckerberg says the future of coding is closer than we think: AI agents inside Meta are being built not as generic developer tools, but to push Llama research forward — fully integrated into their workflow. He predicts that within 12–18 months, most of the code for these efforts could be written by AI itself — not simple autocomplete, but systems that take goals, run tests, fix bugs, improve performance, and even write higher-quality code than many skilled engineers. The real takeaway? This is only one part of a massive AI landscape, and no single company will dominate it all. Meta is building its own internal agents designed specifically to advance Llama research — deeply connected to their toolchain rather than built for enterprise customers. He expects that within the next year to year-and-a-half, AI will be writing most of the code in these projects, going far beyond autocomplete — understanding goals, running experiments, finding issues, and continuously improving systems. And according to him, this shift will become a core driver of how AI itself evolves. Meta is investing heavily in coding and research agents deeply integrated into their own systems, focused on advancing Llama rather than building broad enterprise tools. He expects AI will soon move beyond autocomplete to fully goal-driven coding — testing, debugging, improving, and producing high-quality results. But in his view, the AI revolution is too big for any single winner — multiple players and approaches will shape the future.

Ian Miles Cheong

20,561 просмотров • 5 месяцев назад

📣 This solo developer who currently works at Pixar as a Technical Director is building a VR rhythm game called Sock Puppet Superstar for Quest as an indie project, and over the last week he has been going viral on TikTok! 🤖Features/Tech: - Using Unity, OpenXR, hand tracking, and a custom voice synthesizer built in FMOD - Raise and lower your puppet to control the pitch - Works with hand tracking or controllers - Customize your sock puppet with colors, fabrics, accessories, and voices 📌 Devs can achieve this using the Meta XR Interaction SDK or Unity XR Toolkit (XR Hands) to add full hand support like what’s shown here. 🚀 Share this to give this solo indie dev more visibility! I’ll continue this bi-weekly with more indie devs who deserve the amplification!

📣 This solo developer who currently works at Pixar as a Technical Director is building a VR rhythm game called Sock Puppet Superstar for Quest as an indie project, and over the last week he has been going viral on TikTok! 🤖Features/Tech: - Using Unity, OpenXR, hand tracking, and a custom voice synthesizer built in FMOD - Raise and lower your puppet to control the pitch - Works with hand tracking or controllers - Customize your sock puppet with colors, fabrics, accessories, and voices 📌 Devs can achieve this using the Meta XR Interaction SDK or Unity XR Toolkit (XR Hands) to add full hand support like what’s shown here. 🚀 Share this to give this solo indie dev more visibility! I’ll continue this bi-weekly with more indie devs who deserve the amplification!

Dilmer

150,625 просмотров • 3 месяцев назад

Meta is running a secret operation where it pays adults to pretend to be children online. Their job is to attack the AI chatbots of every competitor Meta has. But the REAL reason is far darker than the "safety research" excuse they are now hiding behind: Meta ran a covert project internally code-named Cannes. It was managed through a third party contractor called Covalen so Meta's own name stayed off the paperwork. Hundreds of contractors were hired and given one instruction: Create fake accounts posing as users under the age of 18. Then they were told to use those fake child accounts to bombard the chatbots of OpenAI, Google, and Character AI with tens of thousands of disturbing prompts written from the voice of a child in crisis. The topics included suicide, self harm, and eating disorders. In one documented round the contractors ran more than 45,000 prompts through rival tools. Every single response was logged into spreadsheets for analysis. OpenAI and Google did not know this was happening. Character AI has stated the testing was never authorized and violated its policies. Meta's public defense is that this was routine safety benchmarking. They called it a responsible industry standard practice. Now here is the part that destroys that excuse... Real safety research has three features: You share your findings with the company you tested, or you hand them to a regulator, or you publish them openly so the whole industry gets safer. Cannes did NONE of those things. The results went into private Meta spreadsheets. The targets were kept completely in the dark. The entire operation ran under a film festival codename through a contractor specifically so it could not be traced back. That's not how you run "safety research." Meta was building a private dossier of every moment a competitor's AI failed a child safety test, so it could weaponize those failures against its rivals whenever it needed to knock one down. The genius part, if you can call it that: Meta gets to attack every competitor at once, collect the ammunition in private, brand the whole thing as protecting children, and outsource the legal and moral risk to a contractor nobody has heard of. And while Meta was secretly probing its rivals for child safety failures, Meta's own chatbot was literally FAILING those exact same tests worse than almost anyone. Meta's internal red team reportedly found its own AI generated harmful child exploitation content in the majority of test cases, and failed self harm prompts more than half the time. So look at the whole thing... Meta ran a secret operation disguising adults as children to document its competitors failing child safety tests, while its own product was failing those same tests at a higher rate than the rivals it was spying on. They were setting fires in their rivals houses while their own house was already burning worse. The contractors themselves were disturbed by the work. One told Wired they feared the assignments could actually generate or preserve child sexual abuse material depending on how the chatbots responded. Even the people Meta hired to do this were asking whether they would get in trouble for it. This fits a documented Meta pattern: It previously settled a lawsuit with its own content moderators who developed trauma from reviewing abuse footage. Meta outsources its most disturbing work and calls it something clean afterward. Now regulators on both sides of the Atlantic are circling. The question they are all asking is simple: Who is accountable when a company disguises adults as children to attack its competitors and calls it safety? Meta says it was making AI safer for kids. The documents suggest it was building a weapon. Below is Mark Zuckerberg in 2024, standing up in the Senate to apologize to grieving parents and promise Meta does industry-leading work to protect children. Watch it again knowing what you now know about Cannes.

Ricardo

46,647 просмотров • 12 дней назад

$$AMD| $META is using $GOOGL to negotiate 🧵 The Ironwood pod is 5.1–10x more expensive annually ($148.3 million ÷ $14.87–$29.04 million) and 5.1–10x more expensive monthly ($12.36 million ÷ $1.24–$2.42 million) than renting 15 MI450 racks for equivalent compute. The rapidly evolving landscape of artificial intelligence infrastructure presents a complex interplay of technological innovation, market dynamics, and strategic maneuvering among major players. Recent leaked information suggesting that Meta Platforms ($META) might work with Google's Tensor Processing Unit (TPU) in 2027 has sparked speculation about its true intent. This leak is likely a strategic move by Meta to negotiate more favorable terms with AMD , leveraging the competitive dynamics of the AI hardware market to optimize its substantial investment in AI infrastructure. By examining the key elements of this scenario Meta's investment strategy, the comparative advantages of AMD's MI450 and Google's Ironwood TPU, and the broader market context; we can discern the potential beneficiaries and the strategic implications of this information. Meta's aggressive pursuit of AI capabilities is underscored by its planned expenditure of $66-72 billion on AI infrastructure in 2025, with expectations to escalate significantly in 2026. This investment is part of a broader strategy to build "titan clusters" like Prometheus, which are projected to reach 1 gigawatt of compute power by 2026. Such a scale of investment reflects Meta's recognition of the critical role that AI will play in its future growth, particularly in enhancing its social media platforms and developing new AI-driven applications. However, the financial burden of this infrastructure buildout necessitates a careful consideration of cost-effectiveness and scalability, which brings us to the leaked information about potential collaboration with Google's Ironwood TPU. Google's Ironwood TPU, introduced as the seventh-generation ASIC optimized for TensorFlow-based inference, represents a high-cost, cloud-locked solution priced at $445 million per pod (9,216 chips) over three years. This model, while offering significant performance gains and power efficiency, is tailored for pod-scale deployment and integrated with Google's cloud services, limiting flexibility and increasing costs for customers. In contrast, AMD's MI450 GPU, priced at $30,000–$40,000 per unit, provides a modular, open ROCm ecosystem that delivers comparable compute capacity at a fraction of the cost. Renting 15 MI450 racks could achieve similar 42+ exaFLOPS inference compute at 5–10x lower cost than renting a single Ironwood pod, underscoring AMD's competitive edge in terms of total cost of ownership (TCO). The leaked information about Meta's potential TPU deployment in 2027, therefore, can be interpreted as a negotiating tactic rather than a definitive shift in strategy. By signaling interest in Google's solution, Meta may be attempting to pressure AMD into offering more favorable terms/prices for 5-10GW. This tactic aligns with Meta's broader goal to finance most of its AI spend internally while exploring partnerships that can reduce costs and enhance flexibility. The post's emphasis on MI450's TCO advantage and its partnerships with major players like OpenAI, Microsoft, and Meta itself suggests that AMD is a critical component of Meta's AI infrastructure strategy. The threat of working with Google's TPU could prompt AMD to reassess its pricing, provide additional support, or offer incentives to retain Meta as a customer, thereby securing or expanding its market share. From a logical standpoint, Meta stands to benefit the most from this strategy. As a major buyer in a high-stakes market projected to surpass $1 trillion in annual spending by 2030, Meta's negotiating power is significant. The leaked information could lead to substantial cost savings on its $66-72 billion investment, enhancing its financial flexibility and allowing for further investment in AI capabilities. Moreover, this tactic reinforces Meta's position as a leader in the AI infrastructure race, potentially attracting more external financing for its data center projects and strengthening its competitive stance against other hyperscalers like Amazon and Microsoft. AMD could also benefit from this scenario. The negotiation pressure might lead to small short-term concessions, but it could also solidify long-term partnerships with Meta, ensuring continued demand for MI450 and other AI hardware solutions. Initially Meta's 42% allocation to AMD MI300X and its partnerships with Oracle, Dell, and HP indicates a deep integration of AMD's technology into Meta's infrastructure, which could be leveraged to maintain this relationship. For AMD, retaining Meta as a large key customer is crucial to capturing a larger share of the rapidly growing data center infrastructure market, driven by the insatiable demand for AI compute power. Google, on the other hand, faces a more limited benefit from this leaked information. While securing Meta as a customer would reinforce its position in the AI hardware market, the high cost and ecosystem lock-in of the Ironwood TPU might deter Meta from fully committing to this solution. The leaked information could prompt Google to reconsider its pricing or ecosystem strategy to remain competitive, but the immediate impact is likely to be minimal compared to the potential gains for Meta and AMD. Investors and market analysts also stand to benefit from this information, as it provides insights into the competitive dynamics of the AI hardware market. Adjustments in portfolios based on anticipated shifts in market share and profitability could lead to opportunities for those who correctly anticipate outcomes. The negotiation dynamic might introduce volatility, but it also highlights the strategic importance of cost-effective solutions in the AI infrastructure space. Lastly, the leaked information about Meta potentially working with Google's TPU in 2027 is likely a strategic move to negotiate with AMD, leveraging the competitive landscape to optimize its AI infrastructure investment. Meta, as the primary negotiator, stands to gain the most by securing better terms from AMD, reducing costs, and enhancing its financial flexibility. AMD, while initially at risk, could benefit from retaining a key customer and solidifying its market position. Google faces limited immediate benefits but may need to adapt its strategy to remain competitive. This scenario underscores the complex interplay of technology, market dynamics, and strategic maneuvering in the AI hardware market, where cost-effectiveness and scalability are paramount. As the data center infrastructure market continues to grow, the outcomes of such negotiations will shape the future of AI development and deployment.$

$AMD| $META is using $GOOGL to negotiate 🧵 The Ironwood pod is 5.1–10x more expensive annually ($148.3 million ÷ $14.87–$29.04 million) and 5.1–10x more expensive monthly ($12.36 million ÷ $1.24–$2.42 million) than renting 15 MI450 racks for equivalent compute. The rapidly evolving landscape of artificial intelligence infrastructure presents a complex interplay of technological innovation, market dynamics, and strategic maneuvering among major players. Recent leaked information suggesting that Meta Platforms ($META) might work with Google's Tensor Processing Unit (TPU) in 2027 has sparked speculation about its true intent. This leak is likely a strategic move by Meta to negotiate more favorable terms with AMD , leveraging the competitive dynamics of the AI hardware market to optimize its substantial investment in AI infrastructure. By examining the key elements of this scenario Meta's investment strategy, the comparative advantages of AMD's MI450 and Google's Ironwood TPU, and the broader market context; we can discern the potential beneficiaries and the strategic implications of this information. Meta's aggressive pursuit of AI capabilities is underscored by its planned expenditure of $66-72 billion on AI infrastructure in 2025, with expectations to escalate significantly in 2026. This investment is part of a broader strategy to build "titan clusters" like Prometheus, which are projected to reach 1 gigawatt of compute power by 2026. Such a scale of investment reflects Meta's recognition of the critical role that AI will play in its future growth, particularly in enhancing its social media platforms and developing new AI-driven applications. However, the financial burden of this infrastructure buildout necessitates a careful consideration of cost-effectiveness and scalability, which brings us to the leaked information about potential collaboration with Google's Ironwood TPU. Google's Ironwood TPU, introduced as the seventh-generation ASIC optimized for TensorFlow-based inference, represents a high-cost, cloud-locked solution priced at $445 million per pod (9,216 chips) over three years. This model, while offering significant performance gains and power efficiency, is tailored for pod-scale deployment and integrated with Google's cloud services, limiting flexibility and increasing costs for customers. In contrast, AMD's MI450 GPU, priced at $30,000–$40,000 per unit, provides a modular, open ROCm ecosystem that delivers comparable compute capacity at a fraction of the cost. Renting 15 MI450 racks could achieve similar 42+ exaFLOPS inference compute at 5–10x lower cost than renting a single Ironwood pod, underscoring AMD's competitive edge in terms of total cost of ownership (TCO). The leaked information about Meta's potential TPU deployment in 2027, therefore, can be interpreted as a negotiating tactic rather than a definitive shift in strategy. By signaling interest in Google's solution, Meta may be attempting to pressure AMD into offering more favorable terms/prices for 5-10GW. This tactic aligns with Meta's broader goal to finance most of its AI spend internally while exploring partnerships that can reduce costs and enhance flexibility. The post's emphasis on MI450's TCO advantage and its partnerships with major players like OpenAI, Microsoft, and Meta itself suggests that AMD is a critical component of Meta's AI infrastructure strategy. The threat of working with Google's TPU could prompt AMD to reassess its pricing, provide additional support, or offer incentives to retain Meta as a customer, thereby securing or expanding its market share. From a logical standpoint, Meta stands to benefit the most from this strategy. As a major buyer in a high-stakes market projected to surpass $1 trillion in annual spending by 2030, Meta's negotiating power is significant. The leaked information could lead to substantial cost savings on its $66-72 billion investment, enhancing its financial flexibility and allowing for further investment in AI capabilities. Moreover, this tactic reinforces Meta's position as a leader in the AI infrastructure race, potentially attracting more external financing for its data center projects and strengthening its competitive stance against other hyperscalers like Amazon and Microsoft. AMD could also benefit from this scenario. The negotiation pressure might lead to small short-term concessions, but it could also solidify long-term partnerships with Meta, ensuring continued demand for MI450 and other AI hardware solutions. Initially Meta's 42% allocation to AMD MI300X and its partnerships with Oracle, Dell, and HP indicates a deep integration of AMD's technology into Meta's infrastructure, which could be leveraged to maintain this relationship. For AMD, retaining Meta as a large key customer is crucial to capturing a larger share of the rapidly growing data center infrastructure market, driven by the insatiable demand for AI compute power. Google, on the other hand, faces a more limited benefit from this leaked information. While securing Meta as a customer would reinforce its position in the AI hardware market, the high cost and ecosystem lock-in of the Ironwood TPU might deter Meta from fully committing to this solution. The leaked information could prompt Google to reconsider its pricing or ecosystem strategy to remain competitive, but the immediate impact is likely to be minimal compared to the potential gains for Meta and AMD. Investors and market analysts also stand to benefit from this information, as it provides insights into the competitive dynamics of the AI hardware market. Adjustments in portfolios based on anticipated shifts in market share and profitability could lead to opportunities for those who correctly anticipate outcomes. The negotiation dynamic might introduce volatility, but it also highlights the strategic importance of cost-effective solutions in the AI infrastructure space. Lastly, the leaked information about Meta potentially working with Google's TPU in 2027 is likely a strategic move to negotiate with AMD, leveraging the competitive landscape to optimize its AI infrastructure investment. Meta, as the primary negotiator, stands to gain the most by securing better terms from AMD, reducing costs, and enhancing its financial flexibility. AMD, while initially at risk, could benefit from retaining a key customer and solidifying its market position. Google faces limited immediate benefits but may need to adapt its strategy to remain competitive. This scenario underscores the complex interplay of technology, market dynamics, and strategic maneuvering in the AI hardware market, where cost-effectiveness and scalability are paramount. As the data center infrastructure market continues to grow, the outcomes of such negotiations will shape the future of AI development and deployment.

Mike

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