Destination
Even the latest AI models make three systematic reasoning errors, ARC-AGI-3 analysis shows

The ARC Prize Foundation analyzed 160 game runs of OpenAI's GPT-5.5 and Anthropic's Opus 4.7 on the ARC-AGI-3 benchmark. Three systematic error patterns explain why both models stay below 1 percent on tasks that humans can solve without much trouble.<br /> The article Even the latest AI models make three systematic reasoning errors, ARC-AGI-3 analysis shows appeared first on The Decoder. [...]

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venturebeat
Microsoft built Phi-4-reasoning-vision-15B to know when to think — and when thinking is a waste of time

Microsoft on Tuesday released Phi-4-reasoning-vision-15B, a compact open-weight multimodal AI model that the company says matches or exceeds the performance of systems many times its size — while co [...]

Match Score: 163.99

venturebeat
Samsung AI researcher's new, open reasoning model TRM outperforms models 10,000X larger — on specific problems

The trend of AI researchers developing new, small open source generative models that outperform far larger, proprietary peers continued this week with yet another staggering advancement.Alexia Jolicoe [...]

Match Score: 131.98

venturebeat
AI IQ is here: a new site scores frontier AI models on the human IQ scale. The results are already dividing tech.

For decades, the IQ test has been one of the most familiar — and most contested — yardsticks for human intelligence. Now, a startup project called AI IQ is applying the same metaphor to artificial [...]

Match Score: 105.66

blogspot
How I Get Free Traffic from ChatGPT in 2025 (AIO vs SEO)

Three weeks ago, I tested something that completely changed how I think about organic traffic. I opened ChatGPT and asked a simple question: "What's the best course on building SaaS with Wor [...]

Match Score: 103.53

venturebeat
Phi-4 proves that a 'data-first' SFT methodology is the new differentiator

AI engineers often chase performance by scaling up LLM parameters and data, but the trend toward smaller, more efficient, and better-focused models has accelerated. The Phi-4 fine-tuning methodology [...]

Match Score: 96.83

venturebeat
Meta's new structured prompting technique makes LLMs significantly better at code review — boosting accuracy to 93% in some cases

Deploying AI agents for repository-scale tasks like bug detection, patch verification, and code review requires overcoming significant technical hurdles. One major bottleneck: the need to set up dynam [...]

Match Score: 96.19

venturebeat
Meta researchers open the LLM black box to repair flawed AI reasoning

Researchers at Meta FAIR and the University of Edinburgh have developed a new technique that can predict the correctness of a large language model's (LLM) reasoning and even intervene to fix its [...]

Match Score: 88.12

venturebeat
Microsoft and OpenAI gut their exclusive deal, freeing OpenAI to sell on AWS and Google Cloud

Microsoft and OpenAI on Monday announced a sweeping overhaul of the partnership that has defined the commercial AI era, dismantling key pillars of exclusivity and revenue-sharing that bound the two co [...]

Match Score: 87.34

venturebeat
New training method boosts AI multimodal reasoning with smaller, smarter datasets

Researchers at MiroMind AI and several Chinese universities have released OpenMMReasoner, a new training framework that improves the capabilities of language models in multimodal reasoning.The framewo [...]

Match Score: 81.94