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๐Ÿšจ SUBNET 35 BREAKTHROUGH: LogicNet AI Rivals HUMAN EXPERTS! ๐Ÿง ๐Ÿ’ฅ@logicnet_ait Choose your weapon: Qwen2, Mistral, Baichuan2, or Falcon models now available! ๐Ÿ› ๏ธ $TAO holders are part-owners of a GLOBAL AI BRAIN trust! As these models improve, so does the VALUE and UTILITY of the entire ecosystem ๐Ÿ”ฅ Bittensor's Subnet...

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Andy ฯ„ฯ„

12,186 subscribers

30,418 Aufrufe โ€ข vor 2 Jahren โ€ขvia X (Twitter)

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5 Kommentare

Profilbild von TemporaryExistence
TemporaryExistencevor 2 Jahren

@logicnet_ait There is no better product than openai and midjourney and they are just getting better which are not decentralized...do you think any decentralize ai can be better than them?

Profilbild von Joshua | Contango Digital
Joshua | Contango Digitalvor 2 Jahren

@logicnet_ait awesome to see... thanks for covering!

Profilbild von GroKuDino ๐Ÿฆ–๐Ÿ’š
GroKuDino ๐Ÿฆ–๐Ÿ’švor 1 Jahr

@logicnet_ait $Tao $ait will follow ๐Ÿ’š๐Ÿ’š๐Ÿ’š๐Ÿš€๐Ÿš€๐Ÿš€

Profilbild von Robin๐Ÿ’ฅ (ฯ„,ฯ„)
Robin๐Ÿ’ฅ (ฯ„,ฯ„)vor 1 Jahr

@logicnet_ait Great article ๐Ÿ‘Œ

Profilbild von B manu
B manuvor 2 Jahren

@logicnet_ait developing applications useful to the greatest number of people would not be a luxury in parallel to your research. in order to promote the adoption of bittensor among all this seems logical to me.

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AI at Meta

381,021 Aufrufe โ€ข vor 2 Jahren

The AI business model is undergoing a transformation. For the last few years, the playbook was simple: put an AI wrapper on a SaaS product and sell it by the seat. That era is ending. The new wave of AI companies are moving beyond simple subscriptions and embracing a more sophisticated approach tied directly to value creation. Hereโ€™s whatโ€™s changing: ๐Ÿ’ฐ From Seats to Spend: The most forward-thinking companies are shifting to usage-based and outcome-driven pricing. Think less about how many people use the AI and more about what the AI does. This includes new revenue streams like "agentic checkout" on ChatGPT, where AI agents complete purchases and transactions directly within a chat interface. The closer the AI is to the dollar, the more value it captures. ๐ŸŽ™๏ธ From Text to Voice & Video: The interface for AI is becoming more human. Voice is mainstream (Sierra for support, Listen Labs for market research). The next frontier is video, where AI will see, understand, and interact with the world in real-time. The keyboard is no longer the only way to talk to a machine. ๐Ÿค– From Advisors to Actors: Early AI copilots gave advice. The next generation takes action. These agents aren't just suggesting what to do; they are executing complex workflows that directly impact the metrics that matter: boosting conversion, reducing average handle time (AHT), improving NPS, and cutting churn. This is about moving from passive assistance to active problem-solving. The common thread? A relentless focus on tangible ROI. Weโ€™re incredibly bullish on founders who understand this shift and are building companies that align their success with the success of their customers. The future of AI isn't just about intelligence; it's about impact.
1:28

The AI business model is undergoing a transformation. For the last few years, the playbook was simple: put an AI wrapper on a SaaS product and sell it by the seat. That era is ending. The new wave of AI companies are moving beyond simple subscriptions and embracing a more sophisticated approach tied directly to value creation. Hereโ€™s whatโ€™s changing: ๐Ÿ’ฐ From Seats to Spend: The most forward-thinking companies are shifting to usage-based and outcome-driven pricing. Think less about how many people use the AI and more about what the AI does. This includes new revenue streams like "agentic checkout" on ChatGPT, where AI agents complete purchases and transactions directly within a chat interface. The closer the AI is to the dollar, the more value it captures. ๐ŸŽ™๏ธ From Text to Voice & Video: The interface for AI is becoming more human. Voice is mainstream (Sierra for support, Listen Labs for market research). The next frontier is video, where AI will see, understand, and interact with the world in real-time. The keyboard is no longer the only way to talk to a machine. ๐Ÿค– From Advisors to Actors: Early AI copilots gave advice. The next generation takes action. These agents aren't just suggesting what to do; they are executing complex workflows that directly impact the metrics that matter: boosting conversion, reducing average handle time (AHT), improving NPS, and cutting churn. This is about moving from passive assistance to active problem-solving. The common thread? A relentless focus on tangible ROI. Weโ€™re incredibly bullish on founders who understand this shift and are building companies that align their success with the success of their customers. The future of AI isn't just about intelligence; it's about impact.

Konstantine Buhler

24,887 Aufrufe โ€ข vor 10 Monaten

A Bittensor subnet just outscored Claude and Cursor on the SWE benchmark. They spent less than $1 million to get there. Anthropic spent billions. I sat down with Mark Jeffrey, one of the most connected people in the Bittensor ecosystem, and he broke down everything. Here's what most people don't know about TAO. Bittensor takes Bitcoin's mining concept and makes it programmable. Instead of solving meaningless hash puzzles, miners compete on real AI tasks. Best freelancer wins. Blockchain pays them. No company. No CEO. No permission needed. Bitcoin did this for energy. Bittensor does it for talent. The numbers are wild: โ€ข Ridges (Subnet 62) built a Claude/Cursor competitor for under $1M โ€ข Miners on Ridges were earning $50K per day at peak โ€ข The Bittensor network has 128 subnets, each like its own AI startup โ€ข Mark says 20-30 of them could become multi-billion dollar companies โ€ข Only 20% of TAO is staked in subnets right now โ€ข Stakers are earning up to 80% yield on some subnets Mark has been in crypto since 2013. He was in the Ethereum ICO. He's seen every cycle. His take: Bittensor is the most important thing to happen in crypto since Ethereum. He calls TAO the "third great coin" alongside Bitcoin and ETH. The comparison to early Bitcoin is hard to ignore. TAO just had its first halving in December. Same 21 million supply cap. Same post-halving setup. When Bitcoin went through this phase, it jumped from $250 to $10,000. Mark's conservative target for TAO by end of 2026: $3,000. But the real insight was about demand. More subnets means more TAO gets locked up. Subnet cap going from 128 to 256. Staking will absorb most of the supply. And AI agents need crypto to transact. They can't open bank accounts. Bittensor is building the rails for that. Jensen Huang just talked about Templar, a Bittensor subnet, on stage. This isn't theoretical anymore. People are using this stuff. The products on Bittensor are 10 to 100x better than what we saw in early Ethereum. And we're still early.
0:37

A Bittensor subnet just outscored Claude and Cursor on the SWE benchmark. They spent less than $1 million to get there. Anthropic spent billions. I sat down with Mark Jeffrey, one of the most connected people in the Bittensor ecosystem, and he broke down everything. Here's what most people don't know about TAO. Bittensor takes Bitcoin's mining concept and makes it programmable. Instead of solving meaningless hash puzzles, miners compete on real AI tasks. Best freelancer wins. Blockchain pays them. No company. No CEO. No permission needed. Bitcoin did this for energy. Bittensor does it for talent. The numbers are wild: โ€ข Ridges (Subnet 62) built a Claude/Cursor competitor for under $1M โ€ข Miners on Ridges were earning $50K per day at peak โ€ข The Bittensor network has 128 subnets, each like its own AI startup โ€ข Mark says 20-30 of them could become multi-billion dollar companies โ€ข Only 20% of TAO is staked in subnets right now โ€ข Stakers are earning up to 80% yield on some subnets Mark has been in crypto since 2013. He was in the Ethereum ICO. He's seen every cycle. His take: Bittensor is the most important thing to happen in crypto since Ethereum. He calls TAO the "third great coin" alongside Bitcoin and ETH. The comparison to early Bitcoin is hard to ignore. TAO just had its first halving in December. Same 21 million supply cap. Same post-halving setup. When Bitcoin went through this phase, it jumped from $250 to $10,000. Mark's conservative target for TAO by end of 2026: $3,000. But the real insight was about demand. More subnets means more TAO gets locked up. Subnet cap going from 128 to 256. Staking will absorb most of the supply. And AI agents need crypto to transact. They can't open bank accounts. Bittensor is building the rails for that. Jensen Huang just talked about Templar, a Bittensor subnet, on stage. This isn't theoretical anymore. People are using this stuff. The products on Bittensor are 10 to 100x better than what we saw in early Ethereum. And we're still early.

Jesus Martinez

73,314 Aufrufe โ€ข vor 5 Monaten

Everyone says โ€œlearn AI.โ€ No one shows you how to use it for your job, skill level, or daily workflow. So we're launching the worldโ€™s first personalized AI education platform: Tailored training, use cases, and live workshops for your career. Hereโ€™s what's inside: 1. Industry-specific AI certificate courses across 16 tech verticals 2. 300+ real-world AI use cases filtered by what's relevant to you 3. Live, expert-led workshops with our in-house AI research team + AI tool partners 4. A personalized community and network of AI-minded professionals in your industry 5. $1,000+ in exclusive discounts on top AI tools We've all heard โ€œuse AI or be replaced.โ€ But beyond ChatGPT prompts and expensive AI consultants, thereโ€™s no real roadmap. So we built one -- by crowdsourcing the best workflows across the 1M+ AI early adopters in our community and turning them into personalized playbooks. That means whether you're in marketing, dev, ops, or any of the 16 industries we cover, youโ€™ll only see whatโ€™s actually working in your field. No more noise. We'll show you the vetted AI tools and workflows actually being used in the real world by the early adopters in your industry. We believe the future of work belongs to those who combine AI with domain expertise. And now, thereโ€™s no excuse not to start. The first 14 days are 100% free, enough to earn your first certificate ๐Ÿ‘‡
1:40

Everyone says โ€œlearn AI.โ€ No one shows you how to use it for your job, skill level, or daily workflow. So we're launching the worldโ€™s first personalized AI education platform: Tailored training, use cases, and live workshops for your career. Hereโ€™s what's inside: 1. Industry-specific AI certificate courses across 16 tech verticals 2. 300+ real-world AI use cases filtered by what's relevant to you 3. Live, expert-led workshops with our in-house AI research team + AI tool partners 4. A personalized community and network of AI-minded professionals in your industry 5. $1,000+ in exclusive discounts on top AI tools We've all heard โ€œuse AI or be replaced.โ€ But beyond ChatGPT prompts and expensive AI consultants, thereโ€™s no real roadmap. So we built one -- by crowdsourcing the best workflows across the 1M+ AI early adopters in our community and turning them into personalized playbooks. That means whether you're in marketing, dev, ops, or any of the 16 industries we cover, youโ€™ll only see whatโ€™s actually working in your field. No more noise. We'll show you the vetted AI tools and workflows actually being used in the real world by the early adopters in your industry. We believe the future of work belongs to those who combine AI with domain expertise. And now, thereโ€™s no excuse not to start. The first 14 days are 100% free, enough to earn your first certificate ๐Ÿ‘‡

Rowan Cheung

288,577 Aufrufe โ€ข vor 1 Jahr

Scale alone is not enough for AI data. Quality and complexity are equally critical. Excited to support all of these for LLM developers with Snorkel AI Data-as-a-Service, and to share our new leaderboard! โ€” Our decade-plus of research and work in AI data has a simple point: scale alone is not enough. AI success is all about the quality, complexity, and distribution of dataโ€”in addition to volume. Weโ€™re excited to be powering leading LLM developers with Snorkel AI Expert Data-as-a-Service, our white glove service for custom, expert-level AI datasetsโ€”and to now preview some of what weโ€™re building via our new Expert Data Leaderboard (๐Ÿ”— in ๐Ÿงต) + upcoming OSS dataset releases! Snorkel Expert Data-as-a-Service is built to meet the rapidly evolving data needs of the agentic AI worldโ€”where success is built on the quality, complexity, and distribution of datasets, in addition to size and scale. This kind of high-quality, frontier AI data can only come from a union of technology and human expertise. With Snorkel Expert Data-as-a-Service, weโ€™re powering frontier LLM developers across agentic, expert knowledge, reasoning, coding, multi-modal, and other task types via the combination of these two key components: - (1) The Snorkel Expert Network: A global team of subject matter experts focused wholly on specialized knowledgeโ€“spanning thousands of topics in STEM/academic, vertical/professional, and consumer/lifestyle domains. - (2) Snorkel AI Data Development Platform: Our unique programmatic data curation and quality control platform, accelerating and improving expert authoring and review through principled techniques developed over the last decade of R&D. Now: weโ€™re incredibly excited to showcase some of the power of Snorkel Expert Data-as-a-Service via the new Snorkel Leaderboardโ€”putting frontier models to the test in complex, agentic, and reasoning settings inspired by real industry scenarios (not esoteric puzzles)! Weโ€™ll be releasing new leaderboards and accompanying expert-verified open source datasets (coming soon!) regularly. To start, weโ€™re sharing three initial ones in preview: - SnorkelFinance: Q&A over financial documents requiring agentic tool-calling and reasoning - SnorkelUnderwrite: Agentic insurance tasks requiring industry-specific reasoning and tool use - SnorkelSequences: Mathematical tasks requiring compositional multi-step reasoning
1:11

Scale alone is not enough for AI data. Quality and complexity are equally critical. Excited to support all of these for LLM developers with Snorkel AI Data-as-a-Service, and to share our new leaderboard! โ€” Our decade-plus of research and work in AI data has a simple point: scale alone is not enough. AI success is all about the quality, complexity, and distribution of dataโ€”in addition to volume. Weโ€™re excited to be powering leading LLM developers with Snorkel AI Expert Data-as-a-Service, our white glove service for custom, expert-level AI datasetsโ€”and to now preview some of what weโ€™re building via our new Expert Data Leaderboard (๐Ÿ”— in ๐Ÿงต) + upcoming OSS dataset releases! Snorkel Expert Data-as-a-Service is built to meet the rapidly evolving data needs of the agentic AI worldโ€”where success is built on the quality, complexity, and distribution of datasets, in addition to size and scale. This kind of high-quality, frontier AI data can only come from a union of technology and human expertise. With Snorkel Expert Data-as-a-Service, weโ€™re powering frontier LLM developers across agentic, expert knowledge, reasoning, coding, multi-modal, and other task types via the combination of these two key components: - (1) The Snorkel Expert Network: A global team of subject matter experts focused wholly on specialized knowledgeโ€“spanning thousands of topics in STEM/academic, vertical/professional, and consumer/lifestyle domains. - (2) Snorkel AI Data Development Platform: Our unique programmatic data curation and quality control platform, accelerating and improving expert authoring and review through principled techniques developed over the last decade of R&D. Now: weโ€™re incredibly excited to showcase some of the power of Snorkel Expert Data-as-a-Service via the new Snorkel Leaderboardโ€”putting frontier models to the test in complex, agentic, and reasoning settings inspired by real industry scenarios (not esoteric puzzles)! Weโ€™ll be releasing new leaderboards and accompanying expert-verified open source datasets (coming soon!) regularly. To start, weโ€™re sharing three initial ones in preview: - SnorkelFinance: Q&A over financial documents requiring agentic tool-calling and reasoning - SnorkelUnderwrite: Agentic insurance tasks requiring industry-specific reasoning and tool use - SnorkelSequences: Mathematical tasks requiring compositional multi-step reasoning

Alex Ratner

495,851 Aufrufe โ€ข vor 1 Jahr

Today, weโ€™re excited to launch Attention Labs. For almost 400,000 years, humanity has progressed through a simple but powerful cycle: we learn, we build, and we pass knowledge forward. Every major leap in civilization, from fire to medicine to computing, has expanded what humans are capable of achieving. We believe AI is the next great tool in that journey. While much of the world is focused on how AI can replace human work, we are focused on a different question: How can AI amplify human potential? At Attention Labs, we are building AI to discover brain-enhancing therapeutics, solve neurocognitive diseases, and accelerate the discovery of medicines for the human mind. We believe the greatest opportunity for AI is not creating a world with fewer humans in the loop, but a world where every human can think more clearly, learn faster, create more boldly, and live more fully. The biggest source of alpha in the age of AI will not come from replacing people. It will come from empowering them. Our mission is simple: Make humans the most intelligent entity on Earth. The future belongs to those who amplify human intelligence, not those who seek to replace it. We're just getting started. Attention Labs
1:57

Today, weโ€™re excited to launch Attention Labs. For almost 400,000 years, humanity has progressed through a simple but powerful cycle: we learn, we build, and we pass knowledge forward. Every major leap in civilization, from fire to medicine to computing, has expanded what humans are capable of achieving. We believe AI is the next great tool in that journey. While much of the world is focused on how AI can replace human work, we are focused on a different question: How can AI amplify human potential? At Attention Labs, we are building AI to discover brain-enhancing therapeutics, solve neurocognitive diseases, and accelerate the discovery of medicines for the human mind. We believe the greatest opportunity for AI is not creating a world with fewer humans in the loop, but a world where every human can think more clearly, learn faster, create more boldly, and live more fully. The biggest source of alpha in the age of AI will not come from replacing people. It will come from empowering them. Our mission is simple: Make humans the most intelligent entity on Earth. The future belongs to those who amplify human intelligence, not those who seek to replace it. We're just getting started. Attention Labs

Temi

37,046 Aufrufe โ€ข vor 3 Monaten

Revolutionizing Bladder Cancer Diagnosis with ZayaAI We heard you Zayans, From our last videos we understood you all want a much easier to understand explanation of our AI models. So let's dive into the latest breakthrough in AI-powered healthcare, our Bladder Cancer Detection Model. This isn't just another AI tool, it's a game-changer for pathologists. Precision, Speed and Seamless Integration: Traditional diagnosis of urothelial carcinoma (bladder cancer) is often slow and prone to errors. Our AI model automatically detects low and high-grade tumors, along with lymphovascular invasion, with unmatched accuracy and speed. That means faster results, fewer mistakes and a more efficient workflow for medical professionals. Why This Matters: 1.Faster Diagnoses โ†’ AI speeds up the process, allowing pathologists to focus on critical cases. 2.Higher Accuracy โ†’ Reduces human error and reliance on costly, time-consuming tests. 3.Seamless Integration โ†’ No need for complex system overhauls. ZayaAI fits right into existing workflows. The Future of AI in Healthcare: Embracing our AI models isnโ€™t just about using new technology, itโ€™s an investment in a future where healthcare is more precise, efficient and patient-focused. Pathologists get to make faster, more informed decisions and ultimately, patient outcomes improve. This is how AI is redefining medical diagnostics and can help save lives. DeSci + AI = $ZAI ! ๐Ÿ”ฌโš•๏ธ
1:39

Revolutionizing Bladder Cancer Diagnosis with ZayaAI We heard you Zayans, From our last videos we understood you all want a much easier to understand explanation of our AI models. So let's dive into the latest breakthrough in AI-powered healthcare, our Bladder Cancer Detection Model. This isn't just another AI tool, it's a game-changer for pathologists. Precision, Speed and Seamless Integration: Traditional diagnosis of urothelial carcinoma (bladder cancer) is often slow and prone to errors. Our AI model automatically detects low and high-grade tumors, along with lymphovascular invasion, with unmatched accuracy and speed. That means faster results, fewer mistakes and a more efficient workflow for medical professionals. Why This Matters: 1.Faster Diagnoses โ†’ AI speeds up the process, allowing pathologists to focus on critical cases. 2.Higher Accuracy โ†’ Reduces human error and reliance on costly, time-consuming tests. 3.Seamless Integration โ†’ No need for complex system overhauls. ZayaAI fits right into existing workflows. The Future of AI in Healthcare: Embracing our AI models isnโ€™t just about using new technology, itโ€™s an investment in a future where healthcare is more precise, efficient and patient-focused. Pathologists get to make faster, more informed decisions and ultimately, patient outcomes improve. This is how AI is redefining medical diagnostics and can help save lives. DeSci + AI = $ZAI ! ๐Ÿ”ฌโš•๏ธ

ZayaAI

18,015 Aufrufe โ€ข vor 1 Jahr

What's the Big Deal with DeepSeek in AI? Here's why DeepSeek is making everyone take notice: 1. Super Smart on a Budget: DeepSeek showed you can make awesome AI without breaking the bank. Their latest model, DeepSeek-V3, was trained for only about $10 million, which is a lot less than the usual big bucks spent on AI, like the rumored $78 million for some of OpenAI's models. They did this in just two months with fewer fancy computers. 2. Open for Everyone: DeepSeek isn't keeping their tech a secret. They've made it open-source, meaning anyone can use, tweak, and learn from it. It's like they're saying, "Come join the party!" 3. Beating the Big Names: DeepSeek-V3 has done better than some top dogs from companies like OpenAI and Google in solving puzzles, math, and coding. This proves you can get great AI results without spending a fortune. 4. Challenging NVIDIA: NVIDIA's chips are usually the choice for AI because they're really powerful. But since DeepSeek did so well with less expensive chips, it might make people think twice about always going for NVIDIA's priciest options. 5. The DeepSeek Crew: The team at DeepSeek is young and smart, mostly from top Chinese schools, with brains in physics, math, and computer science. They learned AI in about six months by themselves! They use first principle thinking, which means they break down problems to the basics and build from there. This has helped them come up with cool new ways to do AI. 6. Changing AI for Good: DeepSeek is showing that AI can be cheaper and more open to everyone. They're changing how we think AI should be made and shared, which could shake up the whole AI world. So, as we watch DeepSeek, it's clear they're not just another player; they're changing the rules of the game. I predicted that this would be a make or break year for all the massive investments made in AI by American VC's. A few weeks later, DeepSeek happens! Watch the rest of my predictions in my 2025 outlook video . Link in replies #AIInnovation #DeepSeek #NVIDIA #OpenAI #TechDisruption
0:44

What's the Big Deal with DeepSeek in AI? Here's why DeepSeek is making everyone take notice: 1. Super Smart on a Budget: DeepSeek showed you can make awesome AI without breaking the bank. Their latest model, DeepSeek-V3, was trained for only about $10 million, which is a lot less than the usual big bucks spent on AI, like the rumored $78 million for some of OpenAI's models. They did this in just two months with fewer fancy computers. 2. Open for Everyone: DeepSeek isn't keeping their tech a secret. They've made it open-source, meaning anyone can use, tweak, and learn from it. It's like they're saying, "Come join the party!" 3. Beating the Big Names: DeepSeek-V3 has done better than some top dogs from companies like OpenAI and Google in solving puzzles, math, and coding. This proves you can get great AI results without spending a fortune. 4. Challenging NVIDIA: NVIDIA's chips are usually the choice for AI because they're really powerful. But since DeepSeek did so well with less expensive chips, it might make people think twice about always going for NVIDIA's priciest options. 5. The DeepSeek Crew: The team at DeepSeek is young and smart, mostly from top Chinese schools, with brains in physics, math, and computer science. They learned AI in about six months by themselves! They use first principle thinking, which means they break down problems to the basics and build from there. This has helped them come up with cool new ways to do AI. 6. Changing AI for Good: DeepSeek is showing that AI can be cheaper and more open to everyone. They're changing how we think AI should be made and shared, which could shake up the whole AI world. So, as we watch DeepSeek, it's clear they're not just another player; they're changing the rules of the game. I predicted that this would be a make or break year for all the massive investments made in AI by American VC's. A few weeks later, DeepSeek happens! Watch the rest of my predictions in my 2025 outlook video . Link in replies #AIInnovation #DeepSeek #NVIDIA #OpenAI #TechDisruption

Dr Ola Brown

83,460 Aufrufe โ€ข vor 1 Jahr

This AI can read emotions better than you can. It was created by Hume (Hume AI) an AI research lab developing models that can read your face and your voice with uncanny accuracy. Their hope is that models that can read your emotions will help create AI that optimizes for human well-being. I sat down with Alan Cowen (Alan Cowen), the co-founder and CEO of Hume to talk about how all of this works: the science of emotion, AI that optimizes for human well-being, and more. Before starting Hume, Alan helped set up Googleโ€™s research into affective computing and got a Ph.D. in computational psychology from Berkeley. He's one of the bright lights in AI, and this was an incredible conversation. We get into: - What an emotion actually is - Why traditional psychological theories of emotion are inadequate - How Hume is able to model human emotions - How Hume's API enables developers to build empathetic voice interfaces - Applications of the model in customer service, gaming, and therapy - Why Hume is designed to optimize for human well-being instead of engagement - The ethical concerns around creating an AI that can interpret human emotions - The future of psychology as a science This is a must-watch for anyone interested in the science of emotion and the future of human-AI interactions. Watch! --- Timestamps: I tell Humeโ€™s empathetic AI model a secret: 00:00:00 Introduction: 00:01:13 What traditional psychology tells us about emotions: 00:10:17 Alanโ€™s radical approach to studying human emotion: 00:13:46 Methods that Humeโ€™s AI model uses to understand emotion: 00:16:46 How the model accounts for individual differences: 00:21:08 My pet theory on why itโ€™s been hard to make progress in psychology: 00:27:19 The ways in which Alan thinks Hume can be used: 00:38:12 How Alan is thinking about the API v. consumer product question: 00:41:22
56:12

This AI can read emotions better than you can. It was created by Hume (Hume AI) an AI research lab developing models that can read your face and your voice with uncanny accuracy. Their hope is that models that can read your emotions will help create AI that optimizes for human well-being. I sat down with Alan Cowen (Alan Cowen), the co-founder and CEO of Hume to talk about how all of this works: the science of emotion, AI that optimizes for human well-being, and more. Before starting Hume, Alan helped set up Googleโ€™s research into affective computing and got a Ph.D. in computational psychology from Berkeley. He's one of the bright lights in AI, and this was an incredible conversation. We get into: - What an emotion actually is - Why traditional psychological theories of emotion are inadequate - How Hume is able to model human emotions - How Hume's API enables developers to build empathetic voice interfaces - Applications of the model in customer service, gaming, and therapy - Why Hume is designed to optimize for human well-being instead of engagement - The ethical concerns around creating an AI that can interpret human emotions - The future of psychology as a science This is a must-watch for anyone interested in the science of emotion and the future of human-AI interactions. Watch! --- Timestamps: I tell Humeโ€™s empathetic AI model a secret: 00:00:00 Introduction: 00:01:13 What traditional psychology tells us about emotions: 00:10:17 Alanโ€™s radical approach to studying human emotion: 00:13:46 Methods that Humeโ€™s AI model uses to understand emotion: 00:16:46 How the model accounts for individual differences: 00:21:08 My pet theory on why itโ€™s been hard to make progress in psychology: 00:27:19 The ways in which Alan thinks Hume can be used: 00:38:12 How Alan is thinking about the API v. consumer product question: 00:41:22

Dan Shipper ๐Ÿ“ง

45,941 Aufrufe โ€ข vor 2 Jahren

India AI Impact Summit is about many stories on indigenous innovations and achievements. It is a marquee event for display of present and future AI technologies at international level. Each such story is a testament to India's growing AI ecosystem. There are hundreds of stalls displaying futuristic tech being developed in India. From ground zero, I covered the innovations shaping India's AI future. BharatGen AI: Building foundational models in all 22 official Indian languages. ParadigmIT's Sovereign AI Box: Strengthening data security and aligning with the IndiaAI Mission. Skye Air Mobility: 3.6 million autonomous deliveries and 1,000+ tonnes of COโ‚‚ saved. I brought forward stories that matter: Tarakram Maram's AI Trainer Machine, democratizing AI education. Frontier Markets which is empowering rural women entrepreneurs through AI. Drublet Innovation Private Limited, Founded by two students, Agniva and Aaditya, pushing the boundaries of autonomous navigation and robotics. I also explored state pavilions like Bihar's, interacted with international delegations, and highlighted how startups across India are solving real, local challenges with AI. As a journalist on the ground, my focus was simple: bringing the stories of innovation, impact, and aspiration to the viewers. The AI Summit also displays various budding innovations from startups like Sarvam to presence of Indian tech giants like HCL, Airtel, Tata. Top names in the field of AI from across the world like an NVIDIA, Google, OpenAI and many more have also lined up to participate in the Summit. One story about Galgotia University which seemed to go wrong is just an isolated droplet of an otherwise vast reservoir of innovation and future ready technology. If 1 out of hundreds of exhibitors wasnโ€™t being upfront about their innovation, I would not give up on the entire Indiaโ€™s youth who are very innovative. Would you also trash the entire India story just because of one episode? For all tech enthusiasts and those interested in the future of AI, the Summit is a vibrant opportunity to understand how India is at the forefront of the AI revolution. Do visit! #IndiaAISummit2026 #IndiaAIMegaEvent #IndiaForAI #IndiaAIImpactSummit2026 #IndiaAISummit2026 #IndiaAIExpo #ViksitBharat
2:52

India AI Impact Summit is about many stories on indigenous innovations and achievements. It is a marquee event for display of present and future AI technologies at international level. Each such story is a testament to India's growing AI ecosystem. There are hundreds of stalls displaying futuristic tech being developed in India. From ground zero, I covered the innovations shaping India's AI future. BharatGen AI: Building foundational models in all 22 official Indian languages. ParadigmIT's Sovereign AI Box: Strengthening data security and aligning with the IndiaAI Mission. Skye Air Mobility: 3.6 million autonomous deliveries and 1,000+ tonnes of COโ‚‚ saved. I brought forward stories that matter: Tarakram Maram's AI Trainer Machine, democratizing AI education. Frontier Markets which is empowering rural women entrepreneurs through AI. Drublet Innovation Private Limited, Founded by two students, Agniva and Aaditya, pushing the boundaries of autonomous navigation and robotics. I also explored state pavilions like Bihar's, interacted with international delegations, and highlighted how startups across India are solving real, local challenges with AI. As a journalist on the ground, my focus was simple: bringing the stories of innovation, impact, and aspiration to the viewers. The AI Summit also displays various budding innovations from startups like Sarvam to presence of Indian tech giants like HCL, Airtel, Tata. Top names in the field of AI from across the world like an NVIDIA, Google, OpenAI and many more have also lined up to participate in the Summit. One story about Galgotia University which seemed to go wrong is just an isolated droplet of an otherwise vast reservoir of innovation and future ready technology. If 1 out of hundreds of exhibitors wasnโ€™t being upfront about their innovation, I would not give up on the entire Indiaโ€™s youth who are very innovative. Would you also trash the entire India story just because of one episode? For all tech enthusiasts and those interested in the future of AI, the Summit is a vibrant opportunity to understand how India is at the forefront of the AI revolution. Do visit! #IndiaAISummit2026 #IndiaAIMegaEvent #IndiaForAI #IndiaAIImpactSummit2026 #IndiaAISummit2026 #IndiaAIExpo #ViksitBharat

Tapas Bhattachary

25,109 Aufrufe โ€ข vor 6 Monaten