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"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.

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42,689 просмотров • 1 год назад •via X (Twitter)

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Комментарии: 10

Фото профиля AstroZeus ⚡/acc

AstroZeus ⚡/acc1 год назад

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.

Фото профиля The Rundown AI

The Rundown AI1 год назад

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).

Фото профиля Shawn

Shawn1 год назад

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

Фото профиля Zaven Grigoryan

Zaven Grigoryan1 год назад

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

Фото профиля Second Foundation ⚛️

Second Foundation ⚛️1 год назад

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.

Фото профиля prabhu💢

prabhu💢1 год назад

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

Фото профиля Jo

Jo1 год назад

finally being real and not hyping

Фото профиля Kieran Farrell

Kieran Farrell1 год назад

“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

Фото профиля Vladyslav Dimov

Vladyslav Dimov1 год назад

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

Фото профиля Shweta Mahendra🇮🇳

Shweta Mahendra🇮🇳1 год назад

Because these models have smartness not wisdom

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132,070 просмотров • 11 месяцев назад

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> be Sam Altman > asked what keeps him up at night about AI > 3 scary categories > 1. Bad guy gets superintelligence first > “designs a bioweapon… take down the United States power grid… break into the financial system and take everyone's money” > 2. Sci-fi loss of control > “The AI is like, oh, I don't actually want you to turn me off. I'm afraid I can't do that” > 3. Accidental takeover > “the models kind of accidentally take over the world… they just become so ingrained in society” > “There’s young people who just say like, I can't make any decision in my life without telling ChatGPT everything that's going on” We're so cooked.

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64,013 просмотров • 9 месяцев назад

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39,598 просмотров • 23 дней назад

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Jacob Effron

138,154 просмотров • 3 месяцев назад

For the first time in human history, we are teaching a Foundation Model to master the diverse tasks of medicinal chemists, biologists, and computational scientists all in one place. In our latest collaboration with Liquid AI, we are moving away from fragmented, specialized tools toward a single, super-intelligent model. What surprised me most? This model isn't just performing at reasonable levels—it has started outperforming specialist models across physics-based tasks, imaging, and longitudinal data. Why this changes everything: -Synergy over Specialization: Fine-tuning on specific tasks has unlocked unexpected capabilities in synergetic areas, opening a new frontier in multimodal AI research. -Zero-Shot Potential: We are building a model that can perform out-of-scope tasks, moving us closer to an "AI deity" for drug discovery. -Quality First: The goal isn't just to bypass regulations to save time; it’s about using these synergies to develop better, more effective drugs. We are no longer just looking at linear regression or simple text; we are looking at the future of how humanity fights disease. #LiquidAI #InsilicoMedicine #GenerativeAI #DrugDiscovery #DeepTech #BiotechInnovation

For the first time in human history, we are teaching a Foundation Model to master the diverse tasks of medicinal chemists, biologists, and computational scientists all in one place. In our latest collaboration with Liquid AI, we are moving away from fragmented, specialized tools toward a single, super-intelligent model. What surprised me most? This model isn't just performing at reasonable levels—it has started outperforming specialist models across physics-based tasks, imaging, and longitudinal data. Why this changes everything: -Synergy over Specialization: Fine-tuning on specific tasks has unlocked unexpected capabilities in synergetic areas, opening a new frontier in multimodal AI research. -Zero-Shot Potential: We are building a model that can perform out-of-scope tasks, moving us closer to an "AI deity" for drug discovery. -Quality First: The goal isn't just to bypass regulations to save time; it’s about using these synergies to develop better, more effective drugs. We are no longer just looking at linear regression or simple text; we are looking at the future of how humanity fights disease. #LiquidAI #InsilicoMedicine #GenerativeAI #DrugDiscovery #DeepTech #BiotechInnovation

Alex Zhavoronkov, PhD (aka Aleksandrs Zavoronkovs)

10,544 просмотров • 3 месяцев назад

AI’s ‘Supersonic Tsunami’: Elon Musk, Dario Amodei, Mustafa Suleyman, and Your Job Elon Musk calls AI a “supersonic tsunami” heading toward humanity. Anthropic CEO Dario Amodei says that, in as little as 12 months, AI could do 50 percent of entry-level white-collar work. And Microsoft AI CEO Mustafa Suleyman says we are roughly 18 months from AI being able to perform most thought-work job tasks. So which is it? Marketing hype to drive investment? A pretext for Universal Basic Income (UBI) and more government control? Or the beginning of a massive economic boom? Wynton Hall, author of the new book "Code Red: The Left, the Right, China, and the Race to Control AI," lays out the stakes for Americans as AI’s seismic shifts unfold rapidly. What are you seeing in your industry and day-to-day workflows so far? Are AI agents already in the mix? Will they be soon?

AI’s ‘Supersonic Tsunami’: Elon Musk, Dario Amodei, Mustafa Suleyman, and Your Job Elon Musk calls AI a “supersonic tsunami” heading toward humanity. Anthropic CEO Dario Amodei says that, in as little as 12 months, AI could do 50 percent of entry-level white-collar work. And Microsoft AI CEO Mustafa Suleyman says we are roughly 18 months from AI being able to perform most thought-work job tasks. So which is it? Marketing hype to drive investment? A pretext for Universal Basic Income (UBI) and more government control? Or the beginning of a massive economic boom? Wynton Hall, author of the new book "Code Red: The Left, the Right, China, and the Race to Control AI," lays out the stakes for Americans as AI’s seismic shifts unfold rapidly. What are you seeing in your industry and day-to-day workflows so far? Are AI agents already in the mix? Will they be soon?

Breitbart News

75,030 просмотров • 4 месяцев назад

Unsloth AI and NVIDIA are Revolutionizing Local LLM Fine-Tuning: From RTX Desktops to DGX Spark Fine-tune popular AI models faster with Unsloth on NVIDIA RTX AI PCs such as GeForce RTX desktops and laptops to RTX PRO workstations and the new DGX Spark to build personalized assistants for coding, creative work, and complex agentic workflows. The landscape of modern AI is shifting. We are moving away from a total reliance on massive, generalized cloud models and entering the era of local, agentic AI. Whether it is tuning a chatbot to handle hyper-specific product support or building a personal assistant that manages intricate schedules, the potential for generative AI on local hardware is boundless. However, developers face a persistent bottleneck: How do you get a Small Language Model (SLM) to punch above its weight class and respond with high accuracy for specialized tasks? The answer is Fine-Tuning, and the tool of choice is Unsloth. Unsloth provides an easy and high-speed method to customize models. Optimized for efficient, low-memory training on NVIDIA GPUs, Unsloth scales effortlessly from GeForce RTX desktops and laptop all the way to the DGX Spark, the world’s smallest AI supercomputer...... Full analysis: NVIDIA NVIDIA AI NVIDIA AIDev NVIDIAnewsroom Unsloth AI Unsloth

Unsloth AI and NVIDIA are Revolutionizing Local LLM Fine-Tuning: From RTX Desktops to DGX Spark Fine-tune popular AI models faster with Unsloth on NVIDIA RTX AI PCs such as GeForce RTX desktops and laptops to RTX PRO workstations and the new DGX Spark to build personalized assistants for coding, creative work, and complex agentic workflows. The landscape of modern AI is shifting. We are moving away from a total reliance on massive, generalized cloud models and entering the era of local, agentic AI. Whether it is tuning a chatbot to handle hyper-specific product support or building a personal assistant that manages intricate schedules, the potential for generative AI on local hardware is boundless. However, developers face a persistent bottleneck: How do you get a Small Language Model (SLM) to punch above its weight class and respond with high accuracy for specialized tasks? The answer is Fine-Tuning, and the tool of choice is Unsloth. Unsloth provides an easy and high-speed method to customize models. Optimized for efficient, low-memory training on NVIDIA GPUs, Unsloth scales effortlessly from GeForce RTX desktops and laptop all the way to the DGX Spark, the world’s smallest AI supercomputer...... Full analysis: NVIDIA NVIDIA AI NVIDIA AIDev NVIDIAnewsroom Unsloth AI Unsloth

Marktechpost AI Dev News ⚡

31,551 просмотров • 7 месяцев назад

"Attention is All You Need" co‑author and NEAR Protocol founder Ilia Polosukhin reveals why centralized AI is doomed and the radical blueprint for user‑owned models. The next wave could erase your job or hand you god‑mode. In this podcast we're exploring how the cybernetic world is coming to life and what core components are needed for it. 1:47 Ilia’s journey: AI → blockchain → AI 3:58 How transformers were born at Google 9:50 Scaling laws 11:58 RL loops, new architectures, hardware limits 18:00 Creating NEAR to fix crypto‑payments for AI crowdsourcing 23:25 User‑owned AI: why decentralize models 29:46 Confidential computing & verifiable decentralized training 33:33 Agent era: AITP and multi‑agent negotiation 44:24 Enterprise adoption, SaaS disruption, economic shake‑up 52:54 Security, formal verification, AI courts 1:04:07 Jobs, status games, future of work 1:14:00 Post-AGI

"Attention is All You Need" co‑author and NEAR Protocol founder Ilia Polosukhin reveals why centralized AI is doomed and the radical blueprint for user‑owned models. The next wave could erase your job or hand you god‑mode. In this podcast we're exploring how the cybernetic world is coming to life and what core components are needed for it. 1:47 Ilia’s journey: AI → blockchain → AI 3:58 How transformers were born at Google 9:50 Scaling laws 11:58 RL loops, new architectures, hardware limits 18:00 Creating NEAR to fix crypto‑payments for AI crowdsourcing 23:25 User‑owned AI: why decentralize models 29:46 Confidential computing & verifiable decentralized training 33:33 Agent era: AITP and multi‑agent negotiation 44:24 Enterprise adoption, SaaS disruption, economic shake‑up 52:54 Security, formal verification, AI courts 1:04:07 Jobs, status games, future of work 1:14:00 Post-AGI

cyber•Fund

35,361 просмотров • 1 год назад