#GPT unsolved problems
52 related articles
·2 min
14 PDF Parsers Compared: Semantic Fidelity Is the Real Bottleneck for RAG Applications
A benchmark of 14 PDF parsers focused on Meaning Survival, not just character accuracy. Covers GPT, Mistral OCR, Azure DI, and key insights for RAG pipeline optimization.
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·3 min
AI Is Conquering World-Class Math Conjectures — Will Mathematicians Become "Curators"?
AI is cracking world-class math conjectures at scale — from IMO gold medals to the Langlands Program. Terence Tao says math has entered a "proof abundance" era, but AI can't judge research significance. The mathematician's edge is shifting from proving to curating.
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·4 min
OpenAI's 5% Equity Offer for Political Cover: Rescue Mission or High-Stakes Business Gamble?
OpenAI offers Trump's government a 5% stake for regulatory relief. We analyze the financial black hole, regulatory capture risks, and nationalization undercurrents behind this high-stakes equity gamble.
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·3 min
GPT-5.6 Proves 50-Year Math Conjecture in One Hour — AI Independently Cracks a Scientific Problem
GPT-5.6 Sol Ultra proved the 50-year-old Cycle Double Cover Conjecture in one hour for under $500. Plus: Apple sues OpenAI, Google open-sources Gemma 4, and Zhipu AI targets AGI.
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·3 min
Can GPT-5.6 Prove a 50-Year Graph Theory Conjecture? The Boundaries and Verification of AI Mathematical Reasoning
GPT-5.6 Soul Ultra claims to prove the 50-year-old Cycle Double Cover Conjecture in under an hour using 64 parallel agents. We examine the technical path, missing peer review, and formal verification gaps.
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·2 min
GPT-5.6 Used 64 Sub-Agents to Tackle a Graph Theory Conjecture — How Far Are We from a Real Proof?
GPT-5.6 Soul Ultra used 64 parallel sub-agents to generate a proof draft for the Cycle Double Cover Conjecture in one hour. We break down the multi-agent pipeline and explain what's still missing before this counts as a real mathematical result.
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·3 min
AI Cracks a 50-Year Math Problem in Under an Hour: A Deep Dive into GPT-5.6 and the Cycle Double Cover Conjecture
OpenAI's latest AI model solved the 50-year-old Cycle Double Cover Conjecture in under an hour. We break down the three-tier architecture, 64-agent workflow, and what this means for math.
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·3 min
GPT-5.6 Proves 50-Year Graph Theory Conjecture in Under an Hour — A Milestone for AI Mathematical Reasoning
GPT-5.6 Soul Ultra proves the 50-year-old Cycle Double Cover Conjecture in under an hour. Plus: BCI clinical breakthrough, Apple vs. OpenAI, xAI privacy concerns, and EU dark pattern rules.
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AI Model Alignment Unpacked: The Guard…
·2 min
AI Model Alignment Unpacked: The Guardrail Battle Between Sol and Fable
A deep dive into AI alignment strategy differences: how Sol and Fable diverge on guardrail design, what drives over-refusal, and how developers can choose the right AI tool for their needs.
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·2 min
The AI Model Release Frenzy: The Industry Logic Behind the Tech Arms Race
OpenAI, Google, Anthropic and others are releasing models back to back. We analyze the competitive logic, double-edged effects, and what it means for developers, users, and creators.
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·4 min
Claude Sonnet 5 In-Depth Review: Impressive Performance, but Hidden Traps in the Pricing Strategy
A full review of Claude Sonnet 5: major agentic gains, benchmarks near Opus 4.8, but a Tokenizer switch inflates real costs, nearly erasing the price gap with Opus. We break down the pricing traps.
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The Documentation Dilemma: Why Enterpr…
·3 min
The Documentation Dilemma: Why Enterprise Knowledge Remains Locked in the 'Filing Cabinet'
From retrieval difficulties to lagging updates and disconnected workflows, three dilemmas plague traditional documentation. Explore how the AI era can break the deadlock and get knowledge flowing.
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·2 min
Can AI Really Solve Hard Math Problems? A Rational Look at LLM Research Breakthroughs
Claims that GPT solved "unsolved math problems" keep going viral, but do they hold up? A deep dive into LLMs' real problem-solving ability, hallucinations, and verification standards.
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Can AI Prove Mathematical Conjectures?…
·5 min
Can AI Prove Mathematical Conjectures? The Truth Behind the GPT-5.6 Incident and the Limits of Large Language Models
A PDF claiming GPT-5.6 Sol Ultra proved the Cycle Double Cover Conjecture sparked debate on Hacker News. We unpack the truth and the limits of LLMs in math proofs.
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·8 min
GPT-5.6 Hands-On: Farm Automation, Mathematical Breakthroughs, and End-to-End AI Execution
GPT-5.6 (Sol, Terra, Luna) hands-on testing: a Hokkaido farmer controls a greenhouse with AI, a NYC small business builds custom software, and a Polish mathematician breaks a 3-year problem. A deep dive into end-to-end autonomous execution.
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·4 min
The AI Story Bubble: Cutting Through the Hype to Find Real Value
When "AI-powered" becomes a magic phrase for valuation premiums, are companies paying for technology or for a story? A deep analysis of AI hype cycles, the gap between narrative and reality, and how to identify genuine AI value.
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·5 min
The Attention Bottleneck in AI Coding: Hands-On Agent Workflows from the Father of Crayfish
OpenClaw author Peter shares his thinking on AI coding: when compute is no longer the bottleneck, developer attention becomes the new ceiling. Learn three practical skills—Agent Transcript, Auto-Review, and the Crapbox sandbox.
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Pliny's Jailbreak Experiments Reveal t…
·2 min
Pliny's Jailbreak Experiments Reveal the Deep Tensions Between AI Safety and Open-Source Models
Pliny the Liberator's satirical tweet exposes core issues in AI safety and open-source governance — from alignment failures to open-weight risks and AGI hype.
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Tutorials·3 min
ChatGPT Plus Subscription Guide: Are GPT-5.5, image-2, and Codex Worth the Upgrade?
A detailed look at ChatGPT Plus features — GPT-5.5, image-2, and Codex — with a Plus vs Pro comparison and a complete step-by-step subscription guide for users outside the US.
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·3 min
AI Coding Showdown: Four Major Models Show Shocking Performance Gaps on a Dynamic Web Scraping Task
Real-world test of ChatGPT 5.4, Gemini 3.1, DeepSeek V4 Pro, and Kimi 5.1 on a Baidu dynamic web scraping task reveals surprising gaps in AI coding ability.
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