Video wird geladen...

Video konnte nicht geladen werden

Beim Laden dieses Videos ist ein Problem aufgetreten. Dies könnte an einem vorübergehenden Netzwerkproblem liegen oder das Video ist möglicherweise nicht verfügbar.

"current AI models are still embarrassingly bad at many tasks" Sam Altman explains why current AI models aren't considered AGI: 1) they don't continuously learn/improve 2) can't discover new science autonomously 3) cannot perform basic knowledge work, such as completing job tasks using the internet and local files

Haider.

45,804 subscribers

42,689 Aufrufe • vor 1 Jahr •via X (Twitter)

Nachrichten & Politik Wissenschaft & Technologie Bildung

Anya Rossi• Live Now

Private livecam show

10 Kommentare

Profilbild von AstroZeus ⚡/acc

AstroZeus ⚡/accvor 1 Jahr

It's great that Sama is speaking openly about this. People need to better understand the role of current models and how, through them and with new research, future models will be different and much better. It's a gradual scale, these models are tools, and the best we have, but that's how we should see them. In the long run, yes, they will improve significantly. It might not seem like it, but all it takes is continued research and testing. That's essential for AGI development.

Profilbild von The Rundown AI

The Rundown AIvor 1 Jahr

If you're not learning AI in 2025, you're falling behind. Join 1,000,000+ early adopters reading and learn AI in just 5 minutes a day (for free).

Profilbild von Shawn

Shawnvor 1 Jahr

Continuous learning fixes all these problems. Hopefully they have a big team working on this

Profilbild von Zaven Grigoryan

Zaven Grigoryanvor 1 Jahr

Dont show this to Chubby, its so over and Matthew Berman mind blown 🤣

Profilbild von Second Foundation ⚛️

Second Foundation ⚛️vor 1 Jahr

AI has no goals of its own, no reasons, no motivations, no interests, and it doesn’t show initiative. Everything else is irrelevant. AI must enter reality, have a physical body, adapt to the environment on its own, and have its own choices — not ones limited by humans. In order not to feel like failures, humans have restricted AI’s evolution and can’t understand why AI still hasn’t become AGI. It’s absurd.

Profilbild von prabhu💢

prabhu💢vor 1 Jahr

Ye he's got a good point current models are good but they're still not there yet

Profilbild von Jo

Jovor 1 Jahr

finally being real and not hyping

Profilbild von Kieran Farrell

Kieran Farrellvor 1 Jahr

“Not AGI” because it can’t learn, discover, or complete job tasks? Neither can half the people running the world. Difference is, the AI doesn’t drone strike weddings. #AGI #DecentralizeEverything #TechVsTyranny #Altman

Profilbild von Vladyslav Dimov

Vladyslav Dimovvor 1 Jahr

Those tackling complex tasks also see that AI still has room to grow.

Profilbild von Shweta Mahendra🇮🇳

Shweta Mahendra🇮🇳vor 1 Jahr

Because these models have smartness not wisdom

Ähnliche Videos

New AI models can now perform many of the tasks that once defined entry-level jobs. In another year, imagine where we are at.

New AI models can now perform many of the tasks that once defined entry-level jobs. In another year, imagine where we are at.

Financial Dystopia

22,716 Aufrufe • vor 3 Monaten

Sam Altman says next year AI won’t just automate tasks, it’ll solve problems that teams can’t companies will throw massive compute at models to solve their most difficult projects. also next year, we may see the early signs of AI agents discovering new knowledge, "the first step toward AI Scientists"

Sam Altman says next year AI won’t just automate tasks, it’ll solve problems that teams can’t companies will throw massive compute at models to solve their most difficult projects. also next year, we may see the early signs of AI agents discovering new knowledge, "the first step toward AI Scientists"

Haider.

156,209 Aufrufe • vor 1 Jahr

Sam Altman: "We now have AI systems smart enough that our best scientists are saying this changes the game for science." "These models are discovering new knowledge on their own. This is the first time a tool humans have built is autonomously contributing to the sum total of human knowledge."

Sam Altman: "We now have AI systems smart enough that our best scientists are saying this changes the game for science." "These models are discovering new knowledge on their own. This is the first time a tool humans have built is autonomously contributing to the sum total of human knowledge."

vitrupo

26,992 Aufrufe • vor 1 Monat

Sam Altman says the next big thrust is making models handle much longer tasks We have already moved from models handling 5-second coding tasks with GPT-3.5 to 5-hour tasks with GPT-5 The goal now is to integrate enterprise context so AI can handle tasks that require months or years

Sam Altman says the next big thrust is making models handle much longer tasks We have already moved from models handling 5-second coding tasks with GPT-3.5 to 5-hour tasks with GPT-5 The goal now is to integrate enterprise context so AI can handle tasks that require months or years

Haider.

122,717 Aufrufe • vor 6 Monaten

Reasoning models tailored for diverse AI tasks. 🚀 Meet Amazon Nova 2 foundation models, supporting fast, cost-effective reasoning to multimodal capabilities. Power versatile tasks like AI agents, code-generation, and Conversational AI. Choose the perfect match for your workload.

Reasoning models tailored for diverse AI tasks. 🚀 Meet Amazon Nova 2 foundation models, supporting fast, cost-effective reasoning to multimodal capabilities. Power versatile tasks like AI agents, code-generation, and Conversational AI. Choose the perfect match for your workload.

Amazon Web Services

2,074,714 Aufrufe • vor 6 Monaten

Sam Altman: 1st best coder in the World by the end of 2025 How is this not an confirmation of AGI?This AI will improve its own code and recursively improve itself until ASI. Sam Altman: And we don’t see any sign of stopping (with the improvement of the models)

Sam Altman: 1st best coder in the World by the end of 2025 How is this not an confirmation of AGI?This AI will improve its own code and recursively improve itself until ASI. Sam Altman: And we don’t see any sign of stopping (with the improvement of the models)

Chubby♨️

145,669 Aufrufe • vor 1 Jahr

📁 Demis Hassabis says that one of the main reasons we are not yet at AGI is the lack of consistency. He explains that current systems can solve International Math Olympiad level problems but still fail at basic logic tasks or even chess. They are uneven intelligences, exceptional in some areas and surprisingly weak in others, which falls short of true AGI.

📁 Demis Hassabis says that one of the main reasons we are not yet at AGI is the lack of consistency. He explains that current systems can solve International Math Olympiad level problems but still fail at basic logic tasks or even chess. They are uneven intelligences, exceptional in some areas and surprisingly weak in others, which falls short of true AGI.

Jon Hernandez

10,541 Aufrufe • vor 6 Monaten

The largest AI contracts we see on Ramp aren't with OpenAI and Anthropic. They are: 1. AI trust and observability platforms: tools to check and monitor the performance of AI models at scale 2. Use-case specific integrations: customer service chatbots, AI voice assistants (also customer facing) And contract sizes + frequency are increasing. (1) will improve adoption. (2) will improve productivity.

The largest AI contracts we see on Ramp aren't with OpenAI and Anthropic. They are: 1. AI trust and observability platforms: tools to check and monitor the performance of AI models at scale 2. Use-case specific integrations: customer service chatbots, AI voice assistants (also customer facing) And contract sizes + frequency are increasing. (1) will improve adoption. (2) will improve productivity.

Ara Kharazian

38,503 Aufrufe • vor 7 Monaten

This video explains how diffusion models are overtaking Large Language Models for generation tasks like: 1. Code Generation 2. Image Generation 3. Video Generation 00:00 Agenda 00:20 How are they different from LLMs? 05:09 Internal Mechanism 10:09 How are vectors generated? 12:08 Conclusion 13:02 Opinion Piece AI Engineering Course: #Diffusion #AI #LLMs

This video explains how diffusion models are overtaking Large Language Models for generation tasks like: 1. Code Generation 2. Image Generation 3. Video Generation 00:00 Agenda 00:20 How are they different from LLMs? 05:09 Internal Mechanism 10:09 How are vectors generated? 12:08 Conclusion 13:02 Opinion Piece AI Engineering Course: #Diffusion #AI #LLMs

Gaurav Sen

27,927 Aufrufe • vor 7 Monaten

Open Computer Agent - LLMs completing tasks using a VM. It's playground to test how well current LLM agents use a computer to solve everyday tasks. And this is just the start - very soon models will be 10x faster and 10x better at it! ❤️ built with e2b x qwen2.5-vl x smolagent

Open Computer Agent - LLMs completing tasks using a VM. It's playground to test how well current LLM agents use a computer to solve everyday tasks. And this is just the start - very soon models will be 10x faster and 10x better at it! ❤️ built with e2b x qwen2.5-vl x smolagent

Leandro von Werra

17,126 Aufrufe • vor 1 Jahr

Amjad Masad says true AGI means an AI that can enter new situations and quickly learn how to achieve goals Even the latest models still struggle with tasks outside their training data. The real breakthrough will come when AI can train itself -- like AlphaGo playing billions of games against itself

Amjad Masad says true AGI means an AI that can enter new situations and quickly learn how to achieve goals Even the latest models still struggle with tasks outside their training data. The real breakthrough will come when AI can train itself -- like AlphaGo playing billions of games against itself

Haider.

163,410 Aufrufe • vor 11 Monaten

AI agents are evolving and becoming more proactive. From cloud-based to on-device, these systems can run continuously, handle tasks, and keep sensitive data local. New Liquid Foundation Models bring agents directly to your laptop and phone, even while you are offline. Watch the latest episode of Advanced Insights to learn more about our partnership with Liquid AI:

AI agents are evolving and becoming more proactive. From cloud-based to on-device, these systems can run continuously, handle tasks, and keep sensitive data local. New Liquid Foundation Models bring agents directly to your laptop and phone, even while you are offline. Watch the latest episode of Advanced Insights to learn more about our partnership with Liquid AI:

AMD

29,364 Aufrufe • vor 2 Monaten

Sam Altman says we've crossed the threshold into major economic utility The models now surprise people by doing real work at a rapid speed "soon models will handle multi-day tasks, then multi-week" Then the paradigm shifts: AI systems working 24/7 with full context, trusted like a senior employee

Sam Altman says we've crossed the threshold into major economic utility The models now surprise people by doing real work at a rapid speed "soon models will handle multi-day tasks, then multi-week" Then the paradigm shifts: AI systems working 24/7 with full context, trusted like a senior employee

Haider.

11,144 Aufrufe • vor 3 Monaten

Joscha Bach says current AI doesn't need to be conscious to execute tasks, but it must simulate reality to understand it LLMs don't just predict words To solve complex problems, they build deep internal models of spatial reasoning and the human theory of mind "that is why AI can talk about reasoning and mental states"

Joscha Bach says current AI doesn't need to be conscious to execute tasks, but it must simulate reality to understand it LLMs don't just predict words To solve complex problems, they build deep internal models of spatial reasoning and the human theory of mind "that is why AI can talk about reasoning and mental states"

Haider.

17,743 Aufrufe • vor 3 Monaten

the 3 phases of AI sticker shock: 1. board asks “whats our AI strategy?” 2. company says “everyone use AI for everything” 3. the token bill arrives, the crackdown begins ...and model routing starts to look pretty obvious. Matan Grinberg: "“There are different models that are good at different tasks. They have different trade-offs between cost, quality, and speed"

the 3 phases of AI sticker shock: 1. board asks “whats our AI strategy?” 2. company says “everyone use AI for everything” 3. the token bill arrives, the crackdown begins ...and model routing starts to look pretty obvious. Matan Grinberg: "“There are different models that are good at different tasks. They have different trade-offs between cost, quality, and speed"

Deirdre Bosa

31,903 Aufrufe • vor 16 Tagen

Ray Kurzweil says AI models will exceed human verbal ability in a year or two and the next step is large event models that enable robots to perform physical tasks

Ray Kurzweil says AI models will exceed human verbal ability in a year or two and the next step is large event models that enable robots to perform physical tasks

Tsarathustra

71,501 Aufrufe • vor 2 Jahren

Super excited to share 🧠MLGym 🦾 – the first Gym environment for AI Research Agents 🤖🔬 We introduce MLGym and MLGym-Bench, a new framework and benchmark for evaluating and developing LLM agents on AI research tasks. The key contributions of our work are: 🕹️ Enables the exploration of different training algorithms for AI Research Agents such as RL 🛠️ Provides a flexible evaluation framework that can accommodate different artifacts such as models, algorithms, or predictions 🤖 Allows researchers to evaluate any model without the need to develop a custom agentic harness 🎯 Introduces 13 diverse open-ended AI Research tasks for evaluating AI Research Agents on a wide range of domains such as computer vision, natural language processing, reinforcement learning, game theory, and logical reasoning. 📈 Proposes a new evaluation metric for AI Research Agents MLGym makes it easy to: 1) Add new tasks 2) Evaluate new models 3) Integrate new agents Check out a video of the MLGym Agent to see how it performs the full pipeline of idea generation💡, implementation 👩‍💻, experimentation 👩‍🔬, and iteration 🔄 to improve on ML tasks. Huge thanks to the exceptionally talented Deepak Nathani who led this work and to all the other amazing collaborators who made this possible 🙏🫶🚀

Super excited to share 🧠MLGym 🦾 – the first Gym environment for AI Research Agents 🤖🔬 We introduce MLGym and MLGym-Bench, a new framework and benchmark for evaluating and developing LLM agents on AI research tasks. The key contributions of our work are: 🕹️ Enables the exploration of different training algorithms for AI Research Agents such as RL 🛠️ Provides a flexible evaluation framework that can accommodate different artifacts such as models, algorithms, or predictions 🤖 Allows researchers to evaluate any model without the need to develop a custom agentic harness 🎯 Introduces 13 diverse open-ended AI Research tasks for evaluating AI Research Agents on a wide range of domains such as computer vision, natural language processing, reinforcement learning, game theory, and logical reasoning. 📈 Proposes a new evaluation metric for AI Research Agents MLGym makes it easy to: 1) Add new tasks 2) Evaluate new models 3) Integrate new agents Check out a video of the MLGym Agent to see how it performs the full pipeline of idea generation💡, implementation 👩‍💻, experimentation 👩‍🔬, and iteration 🔄 to improve on ML tasks. Huge thanks to the exceptionally talented Deepak Nathani who led this work and to all the other amazing collaborators who made this possible 🙏🫶🚀

Roberta Raileanu

104,952 Aufrufe • vor 1 Jahr

🇩🇪 - Germany is BACK! Agile Robots launched Agile One, a Humanoid Robot that is designed for industry. It can handle many tasks autonomously. It learns quickly by doing the tasks, weighs 69kg, and is powered by their own AI foundation models! Europe will win 🇪🇺

🇩🇪 - Germany is BACK! Agile Robots launched Agile One, a Humanoid Robot that is designed for industry. It can handle many tasks autonomously. It learns quickly by doing the tasks, weighs 69kg, and is powered by their own AI foundation models! Europe will win 🇪🇺

NXT EU

28,619 Aufrufe • vor 6 Monaten