#artificial intelligence investing
112 related articles
·3 min
14-Byte AI Brain Takes on a Maze: Pushing the Intelligence Limits of Minimalist Neural Networks
A tiny 14-byte AI brain attempts to solve a 2D maze, exploring the limits of information compression and intelligence. Discover evolutionary algorithms, memory constraints, and the value of minimal AI.
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·4 min
The Truly Scarce Skills of the AI Era: Why Focus and Execution Are the New Moat
When AI tools let everyone code and design, where is your edge? A deep analysis of why focus and execution are the scarcest superpowers in the AI era.
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·5 min
DeepSeek's Five-Step Ladder to AGI: A Restrained Roadmap Built on Twenty Thousand GPUs
DeepSeek founder Liang Wenfeng reveals a five-step AGI roadmap from chain-of-thought to embodied intelligence. How does TileLang crack domestic GPU substitution under a 20,000-card constraint?
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·5 min
DeepSeek's Five-Step Ladder to AGI: A Restrained Roadmap Built on 20,000 GPUs
DeepSeek founder Liang Wenfeng reveals a five-step AGI roadmap—from chain-of-thought to embodied intelligence—under a 20,000-GPU constraint, using the TileLang compiler to break domestic substitution challenges while API cash flow backs AGI exploration.
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·5 min
Why Are China's Open-Source AI Models Getting Stronger? A Deep Dive Into Three Comeback Strategies
Facing US chip bans and closed-source monopoly, how do China's open-source AI models keep fighting back? A deep dive into three core paths: open-source pricing games, optical interconnect positioning, and on-device scenarios.
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·5 min
Why Are China's Open-Source AI Models Getting Stronger? A Deep Dive into Three Comeback Paths
Facing US chip bans and closed-source monopolies, how do China's open-source AI models keep striking back? A deep dive into three core paths: open-source pricing-power games, optical interconnect positioning, and edge-side use cases.
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·6 min
Claude Sonnet 5 In-Depth Testing: 8 Real-World Tasks Reveal Its True Capability Boundaries
Bilibili creator KaterSony tests Claude Sonnet 5 across 8 real-world tasks—image recognition, 3D modeling, web generation—comparing it against GPT-5.5, Gemini 3.1 Pro, and revealing its true capability limits and cost traps.
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·2 min
ROS2 for Beginners: The Essential Framework for Robot Development
A complete introduction to ROS2 for beginners: what ROS is, how ROS1 and ROS2 differ, and how to choose the right version to kickstart your robot development journey.
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·4 min
Former OpenAI Researcher Warns: 70% Chance AI Spins Out of Control
Former OpenAI researcher Daniel Kokotajlo, who forfeited $2M in equity, warns of a 70% chance AI leads to catastrophic outcomes and superintelligence by 2029.
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Financing the AI Boom: How Tech Giants…
·3 min
Financing the AI Boom: How Tech Giants Are Shifting from Cash Flows to Debt
Tech giants are shifting AI investment financing from free cash flow to large-scale debt. This deep dive explores the structural logic, systemic risks, and macro implications for bond markets.
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Why We Must Actively Fund Open Source …
·2 min
Why We Must Actively Fund Open Source AI: A Public Goods Perspective on Technology Democratization
Open source AI faces soaring compute costs and fierce talent competition that markets alone can't solve. This deep dive explores why actively funding open source AI is essential for tech democratization.
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·2 min
Reinforce: A Developer's Open-Source Python Library for Reinforcement Learning — Lightweight and Readable
Developer Denis Drobyshev releases Reinforce, his first open-source RL Python library on GitHub. Learn about its value for beginners, common challenges in new open-source projects, and how to contribute.
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Continual Learning: The Overlooked Cor…
·3 min
Continual Learning: The Overlooked Core Bottleneck on the Road to AGI
Why is Continual Learning the biggest barrier to AGI? This deep dive covers catastrophic forgetting, real-world deployment challenges, and the Amodei vs. Dwarkesh debate on AGI pathways.
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·4 min
The Complete Roadmap from DevOps to MLOps: Skill Transfer and Toolchain Guide
How can DevOps engineers transition to MLOps? This guide explains the core differences between MLOps and DevOps, offers a phased learning path, tool recommendations (MLflow, DVC, Kubeflow), and practical project ideas.
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·2 min
Vox's Science Podcast 'Unexplainable' Lands on Netflix: Visualizing the Great Unknowns of Science
Vox's science podcast 'Unexplainable' officially arrives on Netflix, with new episodes every Monday. It explores the unsolved mysteries at science's frontier.
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·6 min
1X NEO Robotic Hand and GPT-5.6: A Full Breakdown of Dual Breakthroughs in Robot Hardware and Software
1X releases a new robotic hand for the NEO humanoid robot—25 DOF, force transparency, and tactile skin enabling data self-labeling. OpenAI launches the three-tier GPT-5.6, boosting coding and cost-efficiency. Hardware and AI brains evolve together, accelerating humanoid robot commercialization.
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·6 min
Is AI Really Smart? The Future Directions and Capability Boundaries of Next-Generation Artificial Intelligence
Are large language models truly intelligent? This article analyzes core AI limitations — pattern matching, hallucinations, reasoning deficits — and explores next-gen directions like inference-time compute, neuro-symbolic AI, and embodied intelligence.
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·2 min
Nilekani Steps Back as GP, Fundamentum Launches $200M Fund III Targeting AI and Fintech
Nandan Nilekani steps back as GP of Fundamentum but stays on as anchor investor. The firm launches a $200M Fund III targeting AI and fintech startups in India.
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·7 min
Prompt Engineering in Practice: A Programmer's Core Methodology for Prompt Tuning
A deep dive into the underlying logic of prompt engineering from a programmer's perspective: understand token-probability generation, master the three principles of specific, rich, and low-ambiguity, and learn iterative prompt tuning.
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·6 min
Prompt Engineering in Practice: A Programmer's Core Methodology for Tuning Prompts
An in-depth analysis of prompt engineering from a programmer's perspective: understand token probability generation, master the three principles—specific, rich, low-ambiguity—and learn iterative prompt tuning.
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