Destination
New math benchmark reveals AI models confidently solve problems that have no solution

A consortium of 64 mathematicians built SOOHAK, a new AI benchmark with 439 handwritten tasks, including 99 that are deliberately unsolvable. Google's Gemini 3 Pro leads on research-level problems at 30 percent. But no model cracks 50 percent on spotting broken tasks. More compute makes models better at solving. It doesn't improve them at admitting a problem has no answer. SOOHAK tries to pin down the gap between a few flashy results and the broad research skills AI systems still lack.<br /> The article New math benchmark reveals AI models confidently solve problems that have no solution appeared first on The Decoder. [...]

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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: 102.83

venturebeat
Lean4: How the theorem prover works and why it's the new competitive edge in AI

Large language models (LLMs) have astounded the world with their capabilities, yet they remain plagued by unpredictability and hallucinations – confidently outputting incorrect information. In high- [...]

Match Score: 91.22

venturebeat
Why Weibo’s tiny VibeThinker-3B has the AI world arguing over benchmarks again

On Sunday, a team of nine researchers at Sina Weibo — the Chinese social media giant better known for its microblogging platform than for cutting-edge artificial intelligence — quietly posted a 14 [...]

Match Score: 88.89

venturebeat
DeepSWE blows up the AI coding leaderboard, crowns GPT-5.5, and finds Claude Opus exploiting a benchmark loophole

For months, the leading AI coding benchmarks have told enterprise buyers a comforting but misleading story: the top models are all roughly the same. OpenAI's GPT-5 family, Anthropic's Claude [...]

Match Score: 64.99

venturebeat
Nvidia's Nemotron-Cascade 2 wins math and coding gold medals with 3B active parameters — and its post-training recipe is now open-source

The prevailing assumption in AI development has been straightforward: larger models trained on more data produce better results. Nvidia's latest release directly challenges that size assumption â [...]

Match Score: 64.77

venturebeat
Frontier models are failing one in three production attempts — and getting harder to audit

AI agents are now embedded in real enterprise workflows, and they're still failing roughly one in three attempts on structured benchmarks. That gap between capability and reliability is the defin [...]

Match Score: 62.95

venturebeat
Nous Research's NousCoder-14B is an open-source coding model landing right in the Claude Code moment

Nous Research, the open-source artificial intelligence startup backed by crypto venture firm Paradigm, released a new competitive programming model on Monday that it says matches or exceeds several la [...]

Match Score: 60.44

venturebeat
The 70% factuality ceiling: why Google’s new ‘FACTS’ benchmark is a wake-up call for enterprise AI

There's no shortage of generative AI benchmarks designed to measure the performance and accuracy of a given model on completing various helpful enterprise tasks — from coding to instruction fol [...]

Match Score: 52.96

venturebeat
Artificial Analysis overhauls its AI Intelligence Index, replacing popular benchmarks with 'real-world' tests

The arms race to build smarter AI models has a measurement problem: the tests used to rank them are becoming obsolete almost as quickly as the models improve. On Monday, Artificial Analysis, an indepe [...]

Match Score: 51.96