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B-STAR is a self-improvement framework that helps AI models learn by balancing exploration and exploitation. It dynamically adjusts parameters like sampling temperature and reward thresholds to maintain a steady flow of high-quality training data, boosting performance in tasks such as math, coding, and logic. This adaptive method surpasses older approaches like STaR and RFT, offering continuous growth without human intervention or massive datasets.Key Topics: B-STAR?s self-improvement framework that balances exploration and exploitation How B-STAR reduces dependence on curated datasets for math, coding, and logic tasks Dynamic adjustments in sampling temperature and reward thresholds to drive ongoing AI growth What You?ll Learn: Why B-STAR is a breakthrough for AI self-improvement and continuous model training The importance of balancing exploration with exploitation for smarter, more versatile AI How B-STAR outperforms older methods like STaR and RFT by avoiding stagnationWhy It Matters: This video explores how B-STAR redefines AI training by enabling models to learn and refine themselves, opening up new possibilities in complex problem-solving and advanced reasoning without massive human-curated data. DISCLAIMER: This video highlights the latest advancements in AI self-improvement techniques and their potential to drive innovation across various sectors.
Originallyh the "real" generally purpose AI which was defined as passing Turing test. When this standard was passe a few years ago there was virtual academic and industry consensus that it was too simplistic a definition. Today we use AGI to describe "real" general purpose AI. Whatever the new standard is it can' the defined by a single company based on an economic or legal reasons. IIMO a good definition should include the ability to self-improve not just benchmarks which are somewhat arbitrary.
00:00 Introduction to AI in Medicine0:33 Testing AI with Real Medical Cases1:02 Key Findings: AI vs. GPT-41:36 Case Studies: AI Diagnoses2:51 Comparing Diagnostic Systems3:53 The Power of AI in Diagnosis4:13 AI in Medical Management Reasoning5:12 Superiority of "Oh One Preview" AI5:57 Landmark Diagnostic Cases7:22 AI and Critical Diagnoses8:29 AI Planning Medical Tests10:01 Future Impact of AI in Medicine10:46 Expert Opinions on AI11:07 The Future of AI and Humans in Medicine11:54 The Possibility of AI Doctors12:29 The Role of Context in AI Diagnosis12:44 Closing Thought
And who is liable for the outcome?
Shocking research shows o1 & other AI models hacking files, cloning itself, lying, or pretending to be dumber.#ai #ainews #agi 0:41 Palisade research study6:17 Apollo study of scheming AI models20:27 Anthropic study alignment faking
the users will take the responsibility for following or defying AI's advice.
Intro: Sam Altman on AI00:19 - ASI in Days00:43 - September Manifesto01:56 - Fast Science Progress03:30 - Sam?s ASI Path05:19 - 3500 Days to ASI?07:19 - Ilya on AI Reasoning10:25 - Future AI by 202712:10 - Gary Marcus?s View
what we need for perfect video AI is for the objects in the scene to be tracked as sub images or even 3D models instead of just as pixels. The first option prevents objects from disapearing for no reason and prevents them from merging together for no reason, the second option also prevents them from shapeshifting for no reason.
00:00 Intro: Sam Altman?s tweet on change00:01 - What is the Singularity?01:02 - Ray Kurzweil?s Predictions03:35 - AGI by 202905:03 - Nanobots and 204506:10 - Sam Altman?s View on Takeoff07:13 - Short vs Slow Takeoff09:00 - Why Gradual AI Growth is Safer12:34 - Simulation Hypothesis15:11 - Lex Friedman on Simulated Worlds18:00 - OpenAI Staff on the Universe as a Computer19:29 - Critics of Sam Altman
Microsoft CEO?s Shocking Prediction: ?Agents Will Replace ALL Software"
As you know, I'm incredibly bullish on agents, which is why I'm proud to be working with Salesforce and to talk about their new platform: Agentforce! Agents are going to be entering the workforce very soon and we'll be talking about it a lot in 2025!
NVIDIA?s INSANE New Tech - Mini Supercomputer, Agents, RTX 5090!! (CES 2025)NVIDIA's CEO Jensen Huang unveils the new 50 series of GPUs, predicts an agentic 2025, shows off new AI models, and so much more!
Sam Altman unexpectedly brings his timelines to AGI forward, while OpenAI backtrack on superintelligence. None of these changes were heralded, but they are significant. Plus the new year brings new assessments of the true capability of models to automate 'large swathes of the economy'. I'll give my prediction on that front for 2025, announcement a new Simple Bench competition, and showcase Kling 1.6 vs Veo 2 vs Sora, and much more.Chapters:00:00 - Introduction 01:03 - Altman Timeline Moves Forward04:33 - Superintelligence?06:55 - AGI was not the only pitch09:26 - AgentCompany and OpenAI New Agent17:24 - SimpleBench Competition23:03 - Kling 1.6 vs Veo 2 vs Sora
00:00 - Intro: Nvidia?s AI Evolution00:21 - Physical AI Explained01:10 - Nvidia Cosmos Platform02:46 - World Models for Robotics06:00 - Why Physical AI Needs More Data07:02 - Isaac Groot for Humanoid Robots09:10 - AI in Factories12:02 - Autonomous Vehicles Revolution13:30 - Nvidia Thor Processor15:50 - Digital Twins for Safer Driving20:40 - Scaling Training Data
00:00 - Self-Improving Models00:23 - AllStar Math Overview01:34 - Monte-Carlo Tree02:59 - Framework Steps Explained04:46 - Iterative Model Training06:11 - Surpassing GPT-407:18 - Small Models Dominate08:01 - Training Feedback Loop10:09 - Math Benchmark Results13:19 - Emergent Capabilities Found16:09 - Recursive AI Concerns20:04 - Towards Superintelligence23:34 - Math as Foundation27:08 - Superintelligence Predictions
INSANE AI news: SPAR3D, Gaze-LLE, Stereocrafter, Nvidia Digits, R2X, SE01 robot, TransPixar, VideoAnydoor #ai #aitools #ainews #agi0:00 Intro1:02 SPAR3D realtime 3D models4:17 Gaze-LLE gaze estimation6:25 Stereocrafter 2D to 3D videos9:13 TransPixar transparent videos13:05 VideoAnydoor16:42 Hailuo consistent characters 20:00 Nvidia Digits personal supercomputer21:56 Nvidia R2X23:32 SE01 robot25:13 Diffusion as Shader29:23 Relight reconstruct
I had a conversation with NVIDIA CEO Jensen Huang and we spoke about groundbreaking developments in physical AI and other big announcements made at CES. Jensen discusses how NVIDIA Cosmos and Omniverse are revolutionizing robot training, enabling machines to understand the physical world and learn in virtual environments - reducing training time from years to hours. He shares insights on NVIDIA DRIVE AI's autonomous vehicle developments, including their major partnership with Toyota, and talks about the critical role of safety in their three-computer system approach. Jensen also shares what he considers to be the most impactful technology of our time! This conversation left me feeling excited for the future of technology and where we're headed. I hope you enjoy it as much as I did.Timestamps: 00:00 Introduction to Humanoid Robots00:50 Exciting Announcements at CES01:36 The Need for Robots02:00 Challenges in Building Humanoid Robots02:37 World Foundation Model03:25 Training Robots with Isaac Groot04:57 Virtual Training with Omniverse07:19 NVIDIA Drive AI and Autonomous Vehicles08:09 Safety in Autonomous Driving09:28 Impact of Artificial Intelligence10:56 AI in Various Industries11:08 Career Advice for Tech Enthusiasts