#Aibenchmark

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#Aibenchmark Reels - @asotu_morethancars tarafından paylaşılan video - A new benchmark called ARC-AGI-3 just gave the AI world a pretty blunt reality check. Every major model scored under 1%. Humans solved every environ
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@asotu_morethancars
A new benchmark called ARC-AGI-3 just gave the AI world a pretty blunt reality check. Every major model scored under 1%. Humans solved every environment on the first try. The test is designed to measure adaptability, not recall. No prompt scaffolding. No hand-holding. Just brand-new environments and the expectation that intelligence should figure it out. Critics are already arguing about the scoring. Fair. But the bigger point stands: today’s models still depend heavily on humans to set the table. That is not AGI. That is borrowed structure with impressive outputs. Useful? Absolutely. Autonomous intelligence? Not yet. Watch the full episode at the link in our bio.
#Aibenchmark Reels - @aifortechies (onaylı hesap) tarafından paylaşılan video - Explore the ARC-AGI-3 benchmark, demonstrating how human reasoning currently outperforms advanced AI in unfamiliar problem-solving environments. . . .
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@aifortechies
Explore the ARC-AGI-3 benchmark, demonstrating how human reasoning currently outperforms advanced AI in unfamiliar problem-solving environments. . . . #arcagi #artificialintelligence #machinelearning #airesearch #techtrends #humanintelligence #futureoftech #codinglife #benchmark #aitesting #innovation #softwareengineering #agi #problemsolving #techinnovation . . . [arc-agi, artificial intelligence, agi, machine learning, ai reasoning, benchmark testing, human intelligence vs ai, tech news 2026, gemini, claude ai, coding, problem solving, future of ai, Francois Chollet, arc prize.]
#Aibenchmark Reels - @insidetheworldofai tarafından paylaşılan video - The ARC Prize Foundation has launched ARC-AGI-3, not another benchmark, but a video-game-like intelligence test where AI must learn from scratch. 💡 W
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@insidetheworldofai
The ARC Prize Foundation has launched ARC-AGI-3, not another benchmark, but a video-game-like intelligence test where AI must learn from scratch. 💡 What makes it different? 🎮 Agents are dropped into unknown environments 🧩 No instructions, no prompts, no prior training signals 🧠 They must discover rules, goals, and strategies through interaction ⏱️ Scoring penalizes inefficiency vs humans → killing brute-force 📉 The shocking result: 🤖 Frontier models collapsed below 1% ⚡ Gemini 3.1 Pro → 0.37% ⚡ GPT-5.4 → 0.26% ⚡ Claude Opus 4.6 → 0.25% ⚡ Grok 4.20 → 0% 👨‍🧠 Humans? 100% success, often on the first attempt. 🔍 Why this matters (strategically): 📊 Previous benchmarks (like ARC-AGI-2) were optimized by models → scores reached ~77% 🧠 ARC-AGI-3 resets the game → tests learning ability, not memory ⚠️ It exposes a core limitation: today’s AI = pattern recognition engines, not true learners As François Chollet argues: 👉 If a system needs prompts, scaffolding, or fine-tuning to solve a new task, the intelligence is in the system design, not the model. 🏗️ Enterprise implication (this is critical): ⚙️ Current GenAI success ≠ general intelligence 🧭 AI systems still depend heavily on orchestration, guardrails, and context engineering 📉 Without them, performance collapses in novel environments 💰 The challenge is now formalized: 🏆 $2M prize pool 🎯 $700K for human-level performance 🔥 My take as an Enterprise Architect: We are entering the era of: 🧠 Learning Systems > Prompted Systems ⚙️ Agentic Adaptation > Static Inference 🛡️ Governed AI Architectures > Standalone Models 📢 The gap between 77% (familiar tasks) and <1% (novel tasks) is not incremental, it’s foundational. #AI is not yet intelligent, it is contextually powerful but structurally fragile. And that changes how we design #EnterpriseArchitecture, #AIGovernance, and #DigitalTransformation strategies moving forward. https://arcprize.org/arc-agi/3?utm_source=Generative_AI&utm_medium=Newsletter&utm_campaign=openai-just-raised-more-than-most-countries-spend-on-defence&_bhlid=780656725b5b261b92dfd2712ba8f270c26c2c76
#Aibenchmark Reels - @kyalanur2 tarafından paylaşılan video - ARC AGI benchmark 3 really giving ChatGPT a reality check
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@kyalanur2
ARC AGI benchmark 3 really giving ChatGPT a reality check
#Aibenchmark Reels - @aiwithtejj (onaylı hesap) tarafından paylaşılan video - The ultimate test for AGI is here. 🤖🚀 Most AI benchmarks today measure pattern recognition, but ARC-AGI-3 is different. It's the first interactive r
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@aiwithtejj
The ultimate test for AGI is here. 🤖🚀 Most AI benchmarks today measure pattern recognition, but ARC-AGI-3 is different. It’s the first interactive reasoning benchmark meaning AI agents have to explore, adapt, and learn on the fly with zero instructions. The current score? Humans: 100%. Frontier AI: <1%. 📉 {arcprize, agi, artificialintelligence, machinelearning, technews, codingchallenge, arcagi3, humanintelligence, futureoftech, problemsolving, datascience, innovation, techtrends, opensource, artificialgeneralintelligence, llm, benchmarking, aiagents}
#Aibenchmark Reels - @mansispeaks_ (onaylı hesap) tarafından paylaşılan video - A new AI benchmark just dropped, and the results are surprisingly lopsided: humans score close to 100%, while top AI models are still under 1%. The t
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@mansispeaks_
A new AI benchmark just dropped, and the results are surprisingly lopsided: humans score close to 100%, while top AI models are still under 1%. The test, called ARC-AGI-3, is designed to measure something we often assume AI already has — the ability to figure out new problems from scratch. Not just recognize patterns from training data, but actually infer rules and adapt when the situation changes. The puzzles themselves are simple: grids of colored squares where you’re given a few examples and have to work out the rule, then apply it to a new case. Most people can solve many of these quickly. Models, for now, struggle. The bigger idea here is about generalization — how well a system can handle something it hasn’t seen before. That’s a core part of intelligence, and also what most real-world work requires. So while AI is clearly powerful, this is a useful reminder: there are still important gaps in how it reasons through new situations. #artificialintelligence #benchmark #ai #technology #agi
#Aibenchmark Reels - @runtimebrt tarafından paylaşılan video - He beat OpenAI on ARC-AGI-1. An independent AI researcher, Mithil Vakde, has built an AI model that achieves a better cost-to-performance ratio than
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@runtimebrt
He beat OpenAI on ARC-AGI-1. An independent AI researcher, Mithil Vakde, has built an AI model that achieves a better cost-to-performance ratio than OpenAI on ARC-AGI-1, establishing a new pareto frontier. Mithil is 24 years old, is originally from Indiranagar, Bengaluru, and his model scored 44% on ARC-AGI-1. He only spent 67¢ (₹61) on the public eval set (400 tasks). Meanwhile, GPT-5 (low) spent roughly $15.30 (₹1,412) to achieve the same score (100 tasks).
#Aibenchmark Reels - @jacqbots tarafından paylaşılan video - GPT-5, Claude, Gemini, ALL under 1% on the world's hardest AI test 🤯 ARC-AGI-3 just dropped. Humans: 100%. Best AI ever: 12.5%. Frontier models: und
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@jacqbots
GPT-5, Claude, Gemini, ALL under 1% on the world's hardest AI test 🤯 ARC-AGI-3 just dropped. Humans: 100%. Best AI ever: 12.5%. Frontier models: under 1%. There's a $2M prize and NOBODY is close. Comment AI if you want me to show you how to leverage this. #AINews #ArtificialIntelligence #AIBenchmark #MachineLearning #AIAutomation
#Aibenchmark Reels - @pioneer_ai_ tarafından paylaşılan video - One year ago, AI scored 1% on this test. Humans averaged 60%. The gap felt permanent. It's not permanent anymore. When ARC-AGI-2 launched in March 20
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@pioneer_ai_
One year ago, AI scored 1% on this test. Humans averaged 60%. The gap felt permanent. It's not permanent anymore. When ARC-AGI-2 launched in March 2025, frontier models collapsed. OpenAI o1-pro scored 1%. Claude 3.7 scored 0.0%. The average human off the street scored 60%. The benchmark had exposed a gap that compute and memorization couldn't close. Then Google released Gemini 3.1 Pro on February 19, 2026. On ARC-AGI-2 — a benchmark that evaluates a model's ability to solve entirely new logic patterns it cannot have memorized — it achieved a verified score of 77.1%, more than double the reasoning performance of its predecessor. The model also recorded 94.3% on GPQA Diamond — a test of doctoral-level questions across physics, biology, and chemistry — the highest score ever reported on that benchmark. Gemini 3.1 Pro leads on 13 of 16 of the most important benchmarks, including abstract reasoning, agentic tasks, and graduate-level science. Here's what actually matters: ARC-AGI-2 can't be gamed by training on more data. It tests novel pattern recognition — the kind of reasoning that, until 2026, only humans could do reliably. That threshold just moved. 🧠 ➡️ Follow @Pioneer_AI_ — the AI breakthroughs that will shape the next decade, explained clearly. When AI consistently scores above the human average on reasoning tests — does that change how you think about AI? Or just another benchmark? 👇
#Aibenchmark Reels - @aidailyintel tarafından paylaşılan video - ARC-AGI-3 just dropped and every frontier AI model scored under 1% on tasks every human gets right first try. GPT-5: 0%. Gemini 3.1: 0.37%. Humans: 10
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@aidailyintel
ARC-AGI-3 just dropped and every frontier AI model scored under 1% on tasks every human gets right first try. GPT-5: 0%. Gemini 3.1: 0.37%. Humans: 100%. Every time. #ai #technews #agi #arcagi #chatgpt
#Aibenchmark Reels - @edgebyday tarafından paylaşılan video - GPT-5.4, Claude, Gemini. All scored below 1% on ARC-AGI-3. A graph-search algorithm beat them. That does not mean AI is useless. It means we are stil
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@edgebyday
GPT-5.4, Claude, Gemini. All scored below 1% on ARC-AGI-3. A graph-search algorithm beat them. That does not mean AI is useless. It means we are still confusing capability with intelligence. Just days after GPT-5.4 beat human experts on a major benchmark, it scored 0.26% on ARC-AGI-3. Both are true. That gap is the story. ARC-AGI-3 was built to test something harder: not recall, not benchmark gaming, but reasoning through genuinely new problems. Humans score 100%. Frontier models are all below 1%. For years, François Chollet has argued that most benchmarks reward memorization more than reasoning. ARC-AGI-3 puts that claim under pressure and the results are hard to ignore. The models are impressive. But the distance between impressive performance and general intelligence is still far wider than the headlines make it sound. The real skill now is not just using AI tools. It is understanding what their scores are actually measuring. Hi, I’m Ecem. software engineer and founder in NYC. Here to make sense of the AI story behind the headlines🪄 #OpenAI #Claude #techinfluencer #softwareengineer #chatgpt
#Aibenchmark Reels - @quickbyteai tarafından paylaşılan video - ARC-AGI3: The Test Proving AI Still Can't Match Human Adaptability
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@quickbyteai
ARC-AGI3: The Test Proving AI Still Can’t Match Human Adaptability

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