MarsBit revisits the 70-year arc of artificial intelligence through a current flashpoint: Jensen Huang’s remark on Nvidia’s August 26, 2026 earnings call that, "for a lot of tasks, we can say that we have achieved AGI." The article does not treat that line as settled fact. Instead, it uses the debate around it to trace AI from the 1955 Dartmouth proposal, where John McCarthy, Marvin Minsky, Nathaniel Rochester and Claude Shannon outlined a summer project built on the idea that learning and intelligence could, in principle, be described precisely enough for a machine to simulate them. The piece walks through the field’s early optimism, the perceptron era, symbolic AI, the Lighthill report, expert systems, the two AI winters, and the period when researchers avoided the term "AI" altogether in favor of machine learning, pattern recognition and related labels. It then follows the buildup to the deep learning turn, including ImageNet, AlexNet, DeepMind’s reinforcement learning work, AlphaGo, and the Transformer paper "Attention Is All You Need," before moving into BERT, GPT, scaling laws, Chinchilla, diffusion models and ChatGPT. The central argument is that AI history keeps repeating a few patterns: promises outrun capabilities, definitions keep moving, and methods built to scale with compute often overtake systems packed with hand-crafted human knowledge. On that basis, the question of whether AGI has been achieved remains unresolved not only because capability is contested, but because the term itself has never had a fixed, falsifiable definition.

Prediction markets have existed for centuries, from papal betting in 1503 to U.S. election wagers in 1916, but they long struggled to become a durable product category. This article traces the field from Robin Hanson’s early theories and the Iowa Electronic Markets to failed experiments such as DARPA’s policy market, Intrade, and Augur. The breakthrough came with two very different approaches. Polymarket leaned into low-cost crypto infrastructure and fast iteration, while Kalshi chose regulation-first execution and won federal approval as a designated contract market. Their rise accelerated during the 2024 U.S. presidential election, when market prices were widely cited by major media outlets and helped push prediction markets into the mainstream. By 2026, the two platforms had become the sector’s dominant players, with more than $580 million in monthly trading volume. The article also examines what remains unsolved: prediction markets still struggle to attract savers, even as sports, politics, crypto and culture markets gain traction. Looking ahead, the piece argues that prediction markets could evolve into a global information pricing infrastructure, with new use cases in hedging, AI-driven discovery, media, and yield-bearing collateral.

Whitney Webb’s new investigation claims Polymarket’s roots go back to a 2017 crypto venture, not a 2020 startup story, and ties its rise to Peter Thiel’s network and DARPA’s scrapped Policy Analysis Market.

The Geode Foundation said GEODE has been listed on BitMart, while outlining its Layer 1 network, native apps, 34 months of continuous mainnet operation, and community growth data.

A viral clip from the Jack Neel Podcast revives the theory by Chinese-Canadian commentator Jack Xueqin Jiang that the CIA created Bitcoin as a deep state surveillance tool. Despite technical flaws, the theory has attracted 2.3 million subscribers.

A viral podcast clip has reignited claims that Bitcoin was created by the CIA or the U.S. deep state. But the argument presented by Jiang Xueqin lacks documentary evidence and has been challenged by crypto analysts citing Bitcoin’s open-source code and anti-centralization design.

US government agencies, the Pentagon, NATO, and DARPA are examining blockchain and Bitcoin-related technologies for military security, logistics, finance, and secure communications.

The Pentagon, NATO, and DARPA are actively researching blockchain technology to leverage its tamper-resistant features for protecting military systems from hacking, counterintelligence, and supply chain disruptions, including developing encrypted messaging apps.