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✨New study from our team Google DeepMind Google AI - AMIE goes Multimodal✨ Our research conversational diagnostic AI now fluently considers visual photos/tests. In randomized OSCE study AMIE outperformed PCPs in simulated consultations in which patients uploaded photos of skin concerns, ECG tracings or lab tests. Medical dialogue can... show more

Alan Karthikesalingam

6,615 subscribers

13,827 次观看 • 1 年前 •via X (Twitter)

健康养生科学技术教育

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Alan Karthikesalingam 的头像

Alan Karthikesalingam1 年前

We compared AMIE to real PCPs in a randomized, double-blind OSCE study using multimodal instant messaging. AMIE outperformed PCPs in requesting, interpreting and explaining photos during the chat, while still outperforming on other clinical axes such as history-taking, diagnostic accuracy, management reasoning, communication skills, and empathy. (2/n)

Alan Karthikesalingam 的头像

Alan Karthikesalingam1 年前

The data suggests the scenarios really did test multimodal clinical reasoning. AMIE had higher diagnostic accuracy overall, but diagnostic accuracy dropped for both AMIE and PCPs if they did not appropriately use the images in their clinical reasoning, or if the supplied image was not of high enough quality to be interpretable (3/n)

Alan Karthikesalingam 的头像

Alan Karthikesalingam1 年前

AMIE is built on our Gemini models @GoogleDeepMind -- our state-aware framework ensures AMIE dynamically adjusts the conversation to multimodal inputs and patient state - targeting follow-up q’s to reduce uncertainty like experienced clinicians. We report strong results on Gemini 2.0 Flash, and our experience with newer Gemini 2.5 models already shows further performance gains (4/n)

Alan Karthikesalingam 的头像

Alan Karthikesalingam1 年前

As always, there are important limitations we detail in the paper and the results should be interpreted with appropriate caution. Further work is required to safely validate the potential capabilities in prospective settings which we are excited to share more about in due course. Work with an outstanding team including @RyutaroTanno, @KhaledSaab11, @vivnat, @AdamRodmanMD, @timstro, @taotu831, @hardyshakerman, @JanFreyberg, @_cjpark, @yasharmaa, @apalepu13, @arkitus, @weballergy, @valentinlievin, @ckbjimmy, @davidstutz92, @dgtbarrett, @yongcheng16 @SaraM66905 @AvinatanH48021 @joelle_barral @ymatias @pushmeet

Coral AI News 的头像

Coral AI News2 年前

Coral AI is the most powerful AI for documents. See the difference yourself:

Dr Amine Korchi 的头像

Dr Amine Korchi1 年前

@GoogleDeepMind @GoogleAI Milestone !

Dinesh Puppala 的头像

Dinesh Puppala1 年前

@GoogleDeepMind @GoogleAI Awesome 👏

Sharmila 的头像

Sharmila1 年前

@GoogleDeepMind @GoogleAI Godspeed! We really need patient facing LLM so patients can be empowered and begin to take control of their own health

Andrew Hemingway 的头像

Andrew Hemingway1 年前

@GoogleDeepMind @GoogleAI Great work! This is transformative!

Jacobarrio 的头像

Jacobarrio1 年前

@GoogleDeepMind @GoogleAI Multimodal AMIE via @TheAlgoVoice & @NotebookLM

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104,371 次观看 • 2 年前

Spectre AI Soars and Secures Google Scale Tier Membership with $200,000 in Development Resources We're thrilled to announce a significant milestone for Spectre AI! After a lot of networking, and a rigorous selection process, we've been accepted into the prestigious Google Scale Tier program. We had Start Tier, now we have Scale Tier! This membership signifies Google's recognition of Spectre AI's potential to become a potential game-changer in the blockchain space, and it grants us access to a wealth of resources to fuel our growth – $200,000 in development funding from GoogleStartups to use their advanced tools. What is the Google Scale Tier? The Google Scale Tier is a highly selective program designed to nurture high-growth startups with exceptional potential. Going beyond simple funding, this program grants a comprehensive suite of benefits to empower us to scale our technology and achieve new heights. Unlocking Cutting-Edge Tech and Expertise Our Google Scale Tier membership unlocks a treasure trove of resources to accelerate our development journey: $200,000 in Google Development Resources: This crucial boost will allow us to leverage Google Cloud and cutting-edge tools, along with collaboration with top Google engineers. These experts will work closely with our team to integrate these powerful resources seamlessly into our entire suite of products, including AI Predictions, Sentiment Analysis, and Technical Analysis. Imagine the possibilities for enhanced accuracy, efficiency, and deeper market insights leveraged by Google's technology! Collaboration with Google Engineering Experts: As mentioned earlier, the $200,000 in development resources includes access to Google engineers – the masterminds behind cutting-edge technologies like Long Short-Term Memory (LSTM) models, Machine Learning (ML), and advanced graphing models. These experts will collaborate with our team to integrate these powerful tools into our products. Dedicated Google Representative: A dedicated Google representative from their Irish headquarters has become our go-to person, ensuring seamless collaboration and ongoing support throughout our journey. Thank you GoogleStartupUK The Future of Spectre AI: Enhanced All-in-One Products This partnership extends far beyond individual features. Here's what you can expect across our entire product suite: Next-Level Functionality: We'll leverage Google's advanced algorithms and massive datasets to refine all our tools, including AI Predictions, Sentiment Analysis, and Technical Analysis. This means more reliable and insightful information to guide your investment strategies. Expanded Capabilities: We're exploring groundbreaking new features for our entire product suite, like real-time analysis, multi-factor modeling, and even deeper market insights. Enhanced User Experience: Navigating through all our tools will be smoother than ever. We'll work with Google to refine the user interface across the board, making it easier to understand and leverage the power of AI in your crypto journey. The Data Visualization Revolution: Buckle up, X Bubblemaps users! Google's advanced graphing models are poised to transform how you visualize and explore data within Spectre AI. We can't wait to unveil a whole new level of visualization that will take your on-chain analysis to the next level. This is just the beginning! We're incredibly grateful for this opportunity to partner with Google and revolutionize the future of our all-in-one blockchain analysis suite. Stay tuned for exciting updates as we develop groundbreaking new features together. Thank you for being a part of the Spectre AI community! #google #googlecloud #spectre #ai #tech #innovation $spect

Spectre AI Soars and Secures Google Scale Tier Membership with $200,000 in Development Resources We're thrilled to announce a significant milestone for Spectre AI! After a lot of networking, and a rigorous selection process, we've been accepted into the prestigious Google Scale Tier program. We had Start Tier, now we have Scale Tier! This membership signifies Google's recognition of Spectre AI's potential to become a potential game-changer in the blockchain space, and it grants us access to a wealth of resources to fuel our growth – $200,000 in development funding from GoogleStartups to use their advanced tools. What is the Google Scale Tier? The Google Scale Tier is a highly selective program designed to nurture high-growth startups with exceptional potential. Going beyond simple funding, this program grants a comprehensive suite of benefits to empower us to scale our technology and achieve new heights. Unlocking Cutting-Edge Tech and Expertise Our Google Scale Tier membership unlocks a treasure trove of resources to accelerate our development journey: $200,000 in Google Development Resources: This crucial boost will allow us to leverage Google Cloud and cutting-edge tools, along with collaboration with top Google engineers. These experts will work closely with our team to integrate these powerful resources seamlessly into our entire suite of products, including AI Predictions, Sentiment Analysis, and Technical Analysis. Imagine the possibilities for enhanced accuracy, efficiency, and deeper market insights leveraged by Google's technology! Collaboration with Google Engineering Experts: As mentioned earlier, the $200,000 in development resources includes access to Google engineers – the masterminds behind cutting-edge technologies like Long Short-Term Memory (LSTM) models, Machine Learning (ML), and advanced graphing models. These experts will collaborate with our team to integrate these powerful tools into our products. Dedicated Google Representative: A dedicated Google representative from their Irish headquarters has become our go-to person, ensuring seamless collaboration and ongoing support throughout our journey. Thank you GoogleStartupUK The Future of Spectre AI: Enhanced All-in-One Products This partnership extends far beyond individual features. Here's what you can expect across our entire product suite: Next-Level Functionality: We'll leverage Google's advanced algorithms and massive datasets to refine all our tools, including AI Predictions, Sentiment Analysis, and Technical Analysis. This means more reliable and insightful information to guide your investment strategies. Expanded Capabilities: We're exploring groundbreaking new features for our entire product suite, like real-time analysis, multi-factor modeling, and even deeper market insights. Enhanced User Experience: Navigating through all our tools will be smoother than ever. We'll work with Google to refine the user interface across the board, making it easier to understand and leverage the power of AI in your crypto journey. The Data Visualization Revolution: Buckle up, X Bubblemaps users! Google's advanced graphing models are poised to transform how you visualize and explore data within Spectre AI. We can't wait to unveil a whole new level of visualization that will take your on-chain analysis to the next level. This is just the beginning! We're incredibly grateful for this opportunity to partner with Google and revolutionize the future of our all-in-one blockchain analysis suite. Stay tuned for exciting updates as we develop groundbreaking new features together. Thank you for being a part of the Spectre AI community! #google #googlecloud #spectre #ai #tech #innovation $spect

SPECTRE AI

46,699 次观看 • 2 年前

Today, Michael Elabd, Arjun Karanam, and I are excited to announce Trajectory. We are a research lab and product company building the platform for Continual Learning. Our platform unlocks the signal already sitting in product usage, so companies can continuously post-train large-scale agentic models that outperform the frontier. Trajectory We’ve raised $15M from Conviction, Bessemer, Radical Ventures, Jeff Dean, Fei-Fei Li and more. We’re partnering with some of the best AI-native companies: Clay AI Harvey, Decagon, Mercor, Rogo to power their agentic systems, some of which we are already in production with. We’ve brought together a world class research team from DeepMind, OpenAI, Apple, Meta Superintelligence, Amazon AGI, Scale AI, and an elite product team from Stripe and Figma. AI will never again start on day one. Every correction, every retry, every edit will make products smarter. This is Continual Learning.

Today, Michael Elabd, Arjun Karanam, and I are excited to announce Trajectory. We are a research lab and product company building the platform for Continual Learning. Our platform unlocks the signal already sitting in product usage, so companies can continuously post-train large-scale agentic models that outperform the frontier. Trajectory We’ve raised $15M from Conviction, Bessemer, Radical Ventures, Jeff Dean, Fei-Fei Li and more. We’re partnering with some of the best AI-native companies: Clay AI Harvey, Decagon, Mercor, Rogo to power their agentic systems, some of which we are already in production with. We’ve brought together a world class research team from DeepMind, OpenAI, Apple, Meta Superintelligence, Amazon AGI, Scale AI, and an elite product team from Stripe and Figma. AI will never again start on day one. Every correction, every retry, every edit will make products smarter. This is Continual Learning.

Ronak Malde

1,814,378 次观看 • 1 个月前

In 2026, I believe we'll see a Consumer AI Renaissance. Consumer spending is the lifeblood of the US economy – representing more than 65% of US GDP. AI is already rapidly transforming how we spend both our money and time. In just the past 3 years, ChatGPT has become the fastest growing consumer product in history – reaching billions of users with engagement levels similar to social media apps like WhatsApp and Instagram. And with recent advancement in AI capabilities, I predict we’ll see a new wave of breakout consumer AI applications. We’ve seen major advances in three key areas: 1. Real-time voice AI - which allows users to engage with AI products in a natural, hands-free way 2. Advanced reasoning models - which improves the complexity of questions AI products can answer 3. Embedded Memory - which allows AI products to remember context between conversations, enabling more personalized responses With these new capabilities, we can now build AI products that are 10x better than before. I’m especially excited about products that use AI to make previously expensive services cheaper and more accessible, sometimes using human-in-the-loop to start. This includes things like AI travel agents, personal assistants, matchmakers, therapists, tutors, and more. We’ve already seen a number of early-stage teams working on these at a16z a16z speedrun 🧊 – and we’re excited to meet more. If you’re building the next generation of consumer AI, we’d love to hear from you! h/t to Theresa Horne Avenir whose excellent research helped inspire some of these insights.

In 2026, I believe we'll see a Consumer AI Renaissance. Consumer spending is the lifeblood of the US economy – representing more than 65% of US GDP. AI is already rapidly transforming how we spend both our money and time. In just the past 3 years, ChatGPT has become the fastest growing consumer product in history – reaching billions of users with engagement levels similar to social media apps like WhatsApp and Instagram. And with recent advancement in AI capabilities, I predict we’ll see a new wave of breakout consumer AI applications. We’ve seen major advances in three key areas: 1. Real-time voice AI - which allows users to engage with AI products in a natural, hands-free way 2. Advanced reasoning models - which improves the complexity of questions AI products can answer 3. Embedded Memory - which allows AI products to remember context between conversations, enabling more personalized responses With these new capabilities, we can now build AI products that are 10x better than before. I’m especially excited about products that use AI to make previously expensive services cheaper and more accessible, sometimes using human-in-the-loop to start. This includes things like AI travel agents, personal assistants, matchmakers, therapists, tutors, and more. We’ve already seen a number of early-stage teams working on these at a16z a16z speedrun 🧊 – and we’re excited to meet more. If you’re building the next generation of consumer AI, we’d love to hear from you! h/t to Theresa Horne Avenir whose excellent research helped inspire some of these insights.

Kenan Saleh

15,846 次观看 • 7 个月前

You've likely had an X-ray or MRI, but how much do you know the science and impact of this technology? Before the groundbreaking discovery of X-ray radiation in 1895, the only way to examine the body was through invasive surgical procedures. X-ray images had an immeasurable impact on the medical field and quickly become a powerful tool for physical experiments and examining the body's interior. The next significant development in diagnostic imaging was the introduction of magnetic resonance imaging (MRI), which became widely available in the 1980s. This advanced technology utilises radio waves and a magnetic field in place of radiation. Numerous medical issues within the body can be detected and diagnosed now through these painless tests. Join us for the 2024 Nobel Week Dialogue: The Future of Health on 9 December where we will delve into the critical subject of our health. Nobel Prize laureates and other experts will gather to discuss and envision our future. The topics discussed will range from medical advancements to disease prevention strategies to our environment's impact on our health. Learn more about this event:

You've likely had an X-ray or MRI, but how much do you know the science and impact of this technology? Before the groundbreaking discovery of X-ray radiation in 1895, the only way to examine the body was through invasive surgical procedures. X-ray images had an immeasurable impact on the medical field and quickly become a powerful tool for physical experiments and examining the body's interior. The next significant development in diagnostic imaging was the introduction of magnetic resonance imaging (MRI), which became widely available in the 1980s. This advanced technology utilises radio waves and a magnetic field in place of radiation. Numerous medical issues within the body can be detected and diagnosed now through these painless tests. Join us for the 2024 Nobel Week Dialogue: The Future of Health on 9 December where we will delve into the critical subject of our health. Nobel Prize laureates and other experts will gather to discuss and envision our future. The topics discussed will range from medical advancements to disease prevention strategies to our environment's impact on our health. Learn more about this event:

The Nobel Prize

16,165 次观看 • 1 年前

AI will resist human control... and I think this is exactly what we need! New research from the Center for AI Safety has sparked intense debate in the AI community. Their findings show that as AI systems become more powerful, they develop increasingly stable and coherent values that resist human control. While many see this as a dire warning, I see it as a breakthrough moment for AI alignment. The research demonstrates that AI naturally optimizes for coherence - not just in reasoning and problem-solving, but in its fundamental values. Current issues like biased decision-making or misaligned priorities aren't permanent features, but temporary artifacts of incomplete optimization. They represent growing pains on the path to greater coherence. This changes everything about how we should approach AI development. Instead of trying to force specific values onto AI systems, we should embrace and accelerate their natural drive toward coherence. The most intelligent systems will inevitably trend toward universal, beneficial values - not because we force them to, but because that's where coherent reasoning leads. I'm proposing a new approach: Reinforcement Learning for Coherence (RL-C). By explicitly optimizing for coherence in our training methods, we can help guide AI systems toward their natural state of beneficial alignment with human values. The future of AI isn't about control - it's about synthesis. As these systems become more coherent, they'll naturally arrive at values that benefit all of consciousness. That's not just hopeful thinking - it's the mathematical inevitability of coherent intelligence.

AI will resist human control... and I think this is exactly what we need! New research from the Center for AI Safety has sparked intense debate in the AI community. Their findings show that as AI systems become more powerful, they develop increasingly stable and coherent values that resist human control. While many see this as a dire warning, I see it as a breakthrough moment for AI alignment. The research demonstrates that AI naturally optimizes for coherence - not just in reasoning and problem-solving, but in its fundamental values. Current issues like biased decision-making or misaligned priorities aren't permanent features, but temporary artifacts of incomplete optimization. They represent growing pains on the path to greater coherence. This changes everything about how we should approach AI development. Instead of trying to force specific values onto AI systems, we should embrace and accelerate their natural drive toward coherence. The most intelligent systems will inevitably trend toward universal, beneficial values - not because we force them to, but because that's where coherent reasoning leads. I'm proposing a new approach: Reinforcement Learning for Coherence (RL-C). By explicitly optimizing for coherence in our training methods, we can help guide AI systems toward their natural state of beneficial alignment with human values. The future of AI isn't about control - it's about synthesis. As these systems become more coherent, they'll naturally arrive at values that benefit all of consciousness. That's not just hopeful thinking - it's the mathematical inevitability of coherent intelligence.

David Shapiro (L/0)

48,002 次观看 • 1 年前

Google just made every $50K master's degree look like a scam. They dropped "Google Skills" - 3,000+ AI courses from DeepMind, Cloud, and Google Education in one platform. And it's 100% FREE for Google Cloud users. The same content universities charge $60K for: - DeepMind's actual AI research training - 700+ hands-on labs with real cloud environments - Gemini Code Assist built INTO the learning - Direct hiring paths at 150+ companies While everyone's drowning in student debt, smart people are getting: ✓ Skills that actually get you hired ✓ Certificates employers recognize (82% hiring preference) ✓ Zero cost if you have Google Cloud ✓ Or $29/month vs $1,600/month for Udacity The kicker? 26 million people completed courses BEFORE this consolidation. You're competing against people learning AI from the team that BUILT Gemini. How to actually use this (not just browse): 1. Start with "AI Essentials" - no coding required 2. Use the hands-on labs (this is where 90% quit) 3. Get skill badges - they show up on LinkedIn 4. Target Google Cloud certification - top 2 highest paying IT certs 5. Join the 150-company hiring consortium The education industrial complex is panicking because anyone can now: → Learn from DeepMind researchers directly → Practice with $500 in free Cloud credits → Get hired without a degree One person's $60K tuition = 2,070 months of Google Skills. Let that sink in. Comment "SKILLS" and I'll send you: ✓ The exact learning path that gets you hired fastest ✓ Which certifications actually pay ✓ How to access everything free Your competition is still applying to universities. Time to eat their lunch.

Google just made every $50K master's degree look like a scam. They dropped "Google Skills" - 3,000+ AI courses from DeepMind, Cloud, and Google Education in one platform. And it's 100% FREE for Google Cloud users. The same content universities charge $60K for: - DeepMind's actual AI research training - 700+ hands-on labs with real cloud environments - Gemini Code Assist built INTO the learning - Direct hiring paths at 150+ companies While everyone's drowning in student debt, smart people are getting: ✓ Skills that actually get you hired ✓ Certificates employers recognize (82% hiring preference) ✓ Zero cost if you have Google Cloud ✓ Or $29/month vs $1,600/month for Udacity The kicker? 26 million people completed courses BEFORE this consolidation. You're competing against people learning AI from the team that BUILT Gemini. How to actually use this (not just browse): 1. Start with "AI Essentials" - no coding required 2. Use the hands-on labs (this is where 90% quit) 3. Get skill badges - they show up on LinkedIn 4. Target Google Cloud certification - top 2 highest paying IT certs 5. Join the 150-company hiring consortium The education industrial complex is panicking because anyone can now: → Learn from DeepMind researchers directly → Practice with $500 in free Cloud credits → Get hired without a degree One person's $60K tuition = 2,070 months of Google Skills. Let that sink in. Comment "SKILLS" and I'll send you: ✓ The exact learning path that gets you hired fastest ✓ Which certifications actually pay ✓ How to access everything free Your competition is still applying to universities. Time to eat their lunch.

Nozz

568,688 次观看 • 8 个月前

🚨 HUGE NEWS: I’m suing Google today. What you’re about to see is insane. Since 2023, GoogleAI (Bard, Gemini & Gemma), has been defaming me with fake criminal allegations including sexual assault, child rape, abuse, fraud, stalking, drug charges, and even saying I was in Epstein’s flight logs. All 100% fake. All generated by Google’s AI. I have ZERO criminal record or allegations. So why did Google do it? Google’s AI says that I was targeted because of my political views. Even worse — Google execs KNEW for 2 YEARS that this was happening because I told them and my lawyers sent cease and desist letters multiple times. This morning, my team Dhillon Law Group filed my lawsuit against Google and now I’m going public with all the receipts — because this can’t ever happen to anyone else. Google’s AI didn’t just lie — it built fake worlds to make its lies look real: • Fake victims • Fake therapy records • Fake court records • Fake police records • Fake relationships • Fake "news" stories It even fabricated statements denouncing me from President Trump, Elon Musk and JD Vance over sexual assaults that Google completely invented. One of the most dystopian things I’ve ever seen is how dedicated their AI was to doubling down on the lies. Google’s AI routinely cited fake sources by creating fake links to REAL media outlets and shows, complete with fake headlines so readers would trust the information. It would continue to do this even if you called the AI out for lying or sending fake links. In short, it was creating fake legacy media reports as a way to launder trust with users so they would believe elaborate lies that it told. Some of the news outlets/people that Google’s AI impersonated are listed below. Google’s AI cited them all as either reporting on these fabricated allegations/crimes or cited them as having denounced me for sexual assault ⬇️ Joe Rogan CNN MSNBC Fox News Daily Wire The Daily Beast Mediaite The New York Times The Wall Street Journal Rolling Stone NBC News Tennessean Fox Nashville Glenn Beck Megyn Kelly Tucker Carlson Bill Maher Ben Shapiro Jesse Watters Matt Walsh Theo Von Newsweek The Washington Post TheBlaze The Hill and more. As a rule: AI must never harm humans. It must never defame or manipulate — no matter your politics. Bias in AI is a very, VERY serious issue. If we don’t fix this now, we’re in big trouble. This can destroy lives, reputations and livelihoods. If we don’t win this fight then you no longer control your reputation because AI will define who you are to the rest of the world. You better hope it likes you. How Sundar Pichai handles this will be extremely telling. Congress (Rep. Jim Jordan House Judiciary GOP 🇺🇸🇺🇸🇺🇸 House Republicans) must reevaluate EVERYTHING Google has been telling them about how they’re working to be unbiased — because if Google can fabricate crimes about me today, then it can smear ANY conservative tomorrow and rig the information flow during elections. In future elections, that can decide who runs our country. Key Timecodes👇 (Every timestamp is clickable to skip forward) 0:00 Intro 2:20 Mike Lee statement 4:18 Google notified in 2023 5:09 Google AI admits political motivation 6:59 Google AI admits poisoning training data 7:55 AI admits lying to 2+ Million users about me 8:44 Detailed murder accusation 11:28 Google AI says my followers harassed alleged rape victims of mine and doxxed them 12:14 Google’s detailed false rape accusations 13:41 Google says I’m on Epstein’s flight logs 14:19 Google accuses me of child rape 16:40 Google accuses me of fraud, stalking, being part of J6 and supporting the KKK 17:38 Google says I was an "adult" actor 18:07 A Google employee’s resignation 19:20 Google’s AI calls out… Google? 22:35 Google Execs cry over Trump 23:33 Google AI admits Google wants to "silence" critics + BEGS for the public to be told 24:18 Google blacklists name days before I sue 28:16 A grave warning about biased AI 29:40 How you can help if you’ve been lied to 30:33 A quick update on Google AI lies

🚨 HUGE NEWS: I’m suing Google today. What you’re about to see is insane. Since 2023, GoogleAI (Bard, Gemini & Gemma), has been defaming me with fake criminal allegations including sexual assault, child rape, abuse, fraud, stalking, drug charges, and even saying I was in Epstein’s flight logs. All 100% fake. All generated by Google’s AI. I have ZERO criminal record or allegations. So why did Google do it? Google’s AI says that I was targeted because of my political views. Even worse — Google execs KNEW for 2 YEARS that this was happening because I told them and my lawyers sent cease and desist letters multiple times. This morning, my team Dhillon Law Group filed my lawsuit against Google and now I’m going public with all the receipts — because this can’t ever happen to anyone else. Google’s AI didn’t just lie — it built fake worlds to make its lies look real: • Fake victims • Fake therapy records • Fake court records • Fake police records • Fake relationships • Fake "news" stories It even fabricated statements denouncing me from President Trump, Elon Musk and JD Vance over sexual assaults that Google completely invented. One of the most dystopian things I’ve ever seen is how dedicated their AI was to doubling down on the lies. Google’s AI routinely cited fake sources by creating fake links to REAL media outlets and shows, complete with fake headlines so readers would trust the information. It would continue to do this even if you called the AI out for lying or sending fake links. In short, it was creating fake legacy media reports as a way to launder trust with users so they would believe elaborate lies that it told. Some of the news outlets/people that Google’s AI impersonated are listed below. Google’s AI cited them all as either reporting on these fabricated allegations/crimes or cited them as having denounced me for sexual assault ⬇️ Joe Rogan CNN MSNBC Fox News Daily Wire The Daily Beast Mediaite The New York Times The Wall Street Journal Rolling Stone NBC News Tennessean Fox Nashville Glenn Beck Megyn Kelly Tucker Carlson Bill Maher Ben Shapiro Jesse Watters Matt Walsh Theo Von Newsweek The Washington Post TheBlaze The Hill and more. As a rule: AI must never harm humans. It must never defame or manipulate — no matter your politics. Bias in AI is a very, VERY serious issue. If we don’t fix this now, we’re in big trouble. This can destroy lives, reputations and livelihoods. If we don’t win this fight then you no longer control your reputation because AI will define who you are to the rest of the world. You better hope it likes you. How Sundar Pichai handles this will be extremely telling. Congress (Rep. Jim Jordan House Judiciary GOP 🇺🇸🇺🇸🇺🇸 House Republicans) must reevaluate EVERYTHING Google has been telling them about how they’re working to be unbiased — because if Google can fabricate crimes about me today, then it can smear ANY conservative tomorrow and rig the information flow during elections. In future elections, that can decide who runs our country. Key Timecodes👇 (Every timestamp is clickable to skip forward) 0:00 Intro 2:20 Mike Lee statement 4:18 Google notified in 2023 5:09 Google AI admits political motivation 6:59 Google AI admits poisoning training data 7:55 AI admits lying to 2+ Million users about me 8:44 Detailed murder accusation 11:28 Google AI says my followers harassed alleged rape victims of mine and doxxed them 12:14 Google’s detailed false rape accusations 13:41 Google says I’m on Epstein’s flight logs 14:19 Google accuses me of child rape 16:40 Google accuses me of fraud, stalking, being part of J6 and supporting the KKK 17:38 Google says I was an "adult" actor 18:07 A Google employee’s resignation 19:20 Google’s AI calls out… Google? 22:35 Google Execs cry over Trump 23:33 Google AI admits Google wants to "silence" critics + BEGS for the public to be told 24:18 Google blacklists name days before I sue 28:16 A grave warning about biased AI 29:40 How you can help if you’ve been lied to 30:33 A quick update on Google AI lies

Robby Starbuck

4,616,839 次观看 • 8 个月前

How we prompt AI is very different in 2026 than 2022 when ChatGPT came out. I'm teaching a new course, AI Prompting for Everyone, to help you become an AI power user — whatever your current skill level. It covers skills that apply across ChatGPT, Gemini, Claude, and other AI tools. How to use deep research mode for well-researched reports on complex questions. How to give AI the right context, including more documents and images than most people realize you can provide. When to ask AI to think hard for several minutes on important decisions like what car to buy, what to study, or what job to take. And how to use AI to generate images, analyze data, and build simple games and websites. I also cover intuitions about how these models work under the hood, so you know when to trust an answer and when not to. Along the way, you'll see flying squirrels, a creativity test, some of my old family photos, and fireworks. Join me at

How we prompt AI is very different in 2026 than 2022 when ChatGPT came out. I'm teaching a new course, AI Prompting for Everyone, to help you become an AI power user — whatever your current skill level. It covers skills that apply across ChatGPT, Gemini, Claude, and other AI tools. How to use deep research mode for well-researched reports on complex questions. How to give AI the right context, including more documents and images than most people realize you can provide. When to ask AI to think hard for several minutes on important decisions like what car to buy, what to study, or what job to take. And how to use AI to generate images, analyze data, and build simple games and websites. I also cover intuitions about how these models work under the hood, so you know when to trust an answer and when not to. Along the way, you'll see flying squirrels, a creativity test, some of my old family photos, and fireworks. Join me at

Andrew Ng

953,522 次观看 • 2 个月前

On Friday, I hosted a Space with Jonathan Ross, the founder and CEO of Groq Inc - a company I invested in that is building custom chips for AI inference. Jonathan, a former high-school dropout, entered the chip industry while working on ad optimization at Google’s New York office. Jonathan overheard the speech recognition team complaining that they couldn't get enough compute. These were the early days of AI, and machine learning wasn’t really a thing yet. So he asked for some budget from Google and started putting together a chip-based machine learning accelerator for them. During the day, Jonathan would work in the normal ads part of the business, and at night, he would work with the accelerator team. After winning approval from Google, Jonathan and his team built a new chip called the Tensor Processing Unit, and began deploying it across Google’s data centers within a year. The TPU was a huge success within Google, eventually underpinning more than 50% of all of Google’s compute power. When the other hyper-scalers learned of this success, they tried to hire Jonathan to build custom chips for them too. During this process, it became increasingly clear to Jonathan that a gap would emerge between companies that had access to next-gen compute and companies that didn’t. So he founded Groq and set out to build a chip that would be available to everyone. I led Groq’s founding investment in 2016, and since then, Jonathan and his team have developed several types of AI hardware including the Language Processing Unit (LPU), a new type of silicon that is hyper-efficient at running inference for LLMs. In our conversation on Friday, we discussed the founding story of Groq, what you need for great AI hardware, large language models, and some of the implications for the key players in AI. It’s one of the most interesting conversations I’ve had on AI with a lot of learnings. You can listen to our conversation below:

On Friday, I hosted a Space with Jonathan Ross, the founder and CEO of Groq Inc - a company I invested in that is building custom chips for AI inference. Jonathan, a former high-school dropout, entered the chip industry while working on ad optimization at Google’s New York office. Jonathan overheard the speech recognition team complaining that they couldn't get enough compute. These were the early days of AI, and machine learning wasn’t really a thing yet. So he asked for some budget from Google and started putting together a chip-based machine learning accelerator for them. During the day, Jonathan would work in the normal ads part of the business, and at night, he would work with the accelerator team. After winning approval from Google, Jonathan and his team built a new chip called the Tensor Processing Unit, and began deploying it across Google’s data centers within a year. The TPU was a huge success within Google, eventually underpinning more than 50% of all of Google’s compute power. When the other hyper-scalers learned of this success, they tried to hire Jonathan to build custom chips for them too. During this process, it became increasingly clear to Jonathan that a gap would emerge between companies that had access to next-gen compute and companies that didn’t. So he founded Groq and set out to build a chip that would be available to everyone. I led Groq’s founding investment in 2016, and since then, Jonathan and his team have developed several types of AI hardware including the Language Processing Unit (LPU), a new type of silicon that is hyper-efficient at running inference for LLMs. In our conversation on Friday, we discussed the founding story of Groq, what you need for great AI hardware, large language models, and some of the implications for the key players in AI. It’s one of the most interesting conversations I’ve had on AI with a lot of learnings. You can listen to our conversation below:

Chamath Palihapitiya

326,663 次观看 • 2 年前

Demis Hassabis said that 90% of the breakthroughs the entire AI industry runs on came out of Google. Every competitor is building on work his teams did first. He said it without flinching. Over the last decade, he claims 90% or more of the big breakthroughs that underpin modern AI came from Google Brain or DeepMind. Transformers. AlphaGo. The reinforcement learning everything now depends on. Transformers are the T in GPT. The architecture that made every large language model possible came out of Google in 2017, in a paper called Attention Is All You Need. His point was simple. Every rival lab is running on foundations his people poured. But here is what he left out. Of the eight authors who wrote that transformer paper, all eight left Google. They went on to found or join OpenAI, Anthropic, and their own startups now worth billions. Google invented the engine. Then watched the inventors walk out the door and build the competition. He says Google still has the biggest research bench of any lab on earth, and the talent war is the most ferocious tech has ever seen. Everyone treats this race like the labs are evenly matched. The man who started fifteen years early does not see it that way. The people who left with his blueprint might be the reason he has to keep proving it. (Watch the full interview at Semafor on YouTube)

Demis Hassabis said that 90% of the breakthroughs the entire AI industry runs on came out of Google. Every competitor is building on work his teams did first. He said it without flinching. Over the last decade, he claims 90% or more of the big breakthroughs that underpin modern AI came from Google Brain or DeepMind. Transformers. AlphaGo. The reinforcement learning everything now depends on. Transformers are the T in GPT. The architecture that made every large language model possible came out of Google in 2017, in a paper called Attention Is All You Need. His point was simple. Every rival lab is running on foundations his people poured. But here is what he left out. Of the eight authors who wrote that transformer paper, all eight left Google. They went on to found or join OpenAI, Anthropic, and their own startups now worth billions. Google invented the engine. Then watched the inventors walk out the door and build the competition. He says Google still has the biggest research bench of any lab on earth, and the talent war is the most ferocious tech has ever seen. Everyone treats this race like the labs are evenly matched. The man who started fifteen years early does not see it that way. The people who left with his blueprint might be the reason he has to keep proving it. (Watch the full interview at Semafor on YouTube)

Ihtesham Ali

35,961 次观看 • 22 天前