Сеть AIOZ сотрудничает с Абердинским Университетом, чтобы произвести революцию в медицинской визуализации с помощью DePIN

cryptonews.ruPubblicato 2023-08-23Pubblicato ultima volta 2024-08-23

Недавно сеть AIOZ подписала новое партнерство с Абердинским Университетом с целью дальнейшего развития медицинской визуализации. Партнерство направлено на решение перспективных технологий для 3D-реконструкции инструментов, используемых в эндоваскулярных процедурах. Основная цель — усовершенствовать процесс медицинской визуализации и визуализации, которая играет решающую роль в хирургии и медицинских областях в целом.

Исследовательский проект будет использовать DePIN от AIOZ, а именно, Decentralized Physical Infrastructure Network. Эта технология лучше всего подходит для безопасного обмена информацией, что является предпосылкой для управления большими наборами медицинских данных. Внедрение технологии DePIN увеличит скорость исследований и качество данных, полученных для медицинских изображений.

Такие процедуры, как эндоваскулярные операции, которые проводятся внутри и вокруг кровеносных сосудов, требуют подробных изображений для позиционирования и подтверждения функциональности используемых инструментов. Процесс реконструкции этих инструментов в 3D на основе данных визуализации является сложной задачей, и ее решение может потенциально привести к изменению точности хирургии и, возможно, даже спасти жизни людей.

Изображение: Bitcoinsensus

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Introduction to the Concept of World Models: A Story from Psychology to the Main Battlefield of AI

**World Models: From Psychology to AI's Core Concept** "World model" is a trending but often confusing term in AI, describing a system that allows machines to internally simulate, predict, and rehearse potential outcomes before taking real-world action—like a mental "sandbox." While definitions vary—Yann LeCun emphasizes physical understanding, OpenAI's Sora is a video-based "world simulator," Google DeepMind's Genie 3 creates interactive 3D environments, and companies like Alibaba and Tesla focus on practical applications—the core goal is consistent: reduce reliance on vast real-world data by creating an internal, predictive model for safer and more efficient AI. The concept has deep roots, tracing back to psychologist Kenneth Craik (1943). In AI, it was revitalized by researchers like David Ha and Jürgen Schmidhuber (2018). Major technical approaches include: 1) generative video models (e.g., Sora) for visual realism; 2) abstract predictive models (e.g., LeCun's JEPA) for efficiency and physical reasoning; and 3) explicit 3D simulators (e.g., NVIDIA Omniverse) for precision. Fei-Fei Li proposes a classification based on the AI action loop: renderers (output observations), simulators (output world states), and planners (output actions). The emerging "World Action Model" (WAM) paradigm aims to unify future prediction and action generation. An industry framework is forming: upstream (data, compute, sensors), midstream (general and vertical platforms), and downstream applications (autonomous driving, robotics, gaming, etc.). Autonomous driving is currently the most mature use case. The current lack of a unified definition reflects the field's early, dynamic stage, similar to past tech revolutions. Different approaches—focusing on pixels, physics, or behavior—represent parallel explorations of how best to compress and understand the world. This diversity, while seemingly chaotic, signals that world models have moved from an academic idea to a critical industrial battleground, ultimately aiming to give machines the ability to understand, imagine, and reason about the world.

marsbit26 min fa

Introduction to the Concept of World Models: A Story from Psychology to the Main Battlefield of AI

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Building the Bright Path While Secretly Crossing Chencang: Is Walsh Paving the Way for a September "Rate Cut"?

The title "Building the Plank Road Openly While Secretly Crossing at Chencang: Is Walsh Paving the Way for a September 'Rate Cut'?" suggests Federal Reserve Chair Kevin Walsh's hawkish stance may be a deliberate smokescreen. Academy Securities analyst Peter Tchir argues in a report that markets, currently pricing a 75% chance of a September hike, are missing a potential path to a September rate cut that Walsh himself might be quietly preparing. Tchir posits that Walsh's hawkish rhetoric aims to suppress long-term yield risks (with the 10-year Treasury yield falling recently) while creating room for a narrative shift based on upcoming data. The potential political endgame, according to this view, could be rate cuts in September and October, ahead of the midterm elections. This hinges on a political logic where the Trump administration's preference for lower rates remains unchanged. A core part of Tchir's argument involves redefining inflation metrics. He contends the Fed under Walsh may deprioritize the PCE index, criticizing its lagging components like Owners' Equivalent Rent (OER). Instead, he points to alternative, more real-time indicators like the New Tenant Repeat Rent Index (NTRR) and the Truflation daily index, which shows core inflation around 1.45%. He suggests the Fed could shift its data narrative to justify policy easing. Furthermore, Tchir downplays AI-driven inflation fears. He argues that consumer price sensitivity, evidenced by negative market reactions to price hikes (e.g., Apple), contradicts persistent inflation narratives. He also separates AI/data center spending—which he sees as relatively rate-insensitive—from broader consumer affordability issues, implying rate hikes are misdirected. Based on this analysis, Tchir sees a re-pricing of rate cut expectations as likely, creating opportunities in short-duration Treasuries. He maintains a neutral-to-slightly-bullish view on the long end of the yield curve. For equities, he recommends a significant overweight in energy (especially global nuclear assets) and, within defense/security themes, an overweight in biotech/pharma versus an underweight in semiconductors, expressing caution on AI/data center valuations.

marsbit52 min fa

Building the Bright Path While Secretly Crossing Chencang: Is Walsh Paving the Way for a September "Rate Cut"?

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"King of Shilling" Hayes Strikes Again, This Time Setting His Sights on Deribit

On June 29, BitMEX co-founder Arthur Hayes acquired approximately 6.16 million SYN tokens via OTC platform Flowdesk, valued at around $2.2 million. Subsequently, Hayes publicly endorsed SYN on X, calling it one of the most asymmetric investments he's seen since HYPE and declaring it time for an on-chain options DEX to challenge industry leader Deribit, naming Hypercall as that challenger. The article details the evolution of the Synapse Protocol, originally launched in 2021 as a cross-chain messaging and liquidity network. While its TVL peaked above $1 billion during the last bull market, it has since declined. The protocol's team has since built Hypercall, an on-chain options trading platform on Hyperliquid's HyperEVM, which supports trading options on "any asset" with features like 24/7 trading and defined risk limited to the premium paid. Deribit, founded in 2016, is highlighted as the dominant centralized crypto options exchange, commanding roughly 85% market share in BTC and ETH options. Its strengths include deep liquidity and professional tools, though it faces critiques over custody risk, KYC requirements, and regulatory uncertainty. The analysis suggests Hypercall's potential lies in decentralization, permissionless access, and transparency, potentially carving a niche in DeFi-native and emerging asset options. However, it faces significant challenges competing with Deribit's established network effect and liquidity depth. The piece concludes by noting Hayes's recent and mixed "call" history, referencing his previous promotion and subsequent sale of HYPE, as well as a controversial price target report for CARDS from his family office, Maelstrom, which was followed by a significant price drop for the asset. This activity has drawn criticism, with some accusing Hayes of creating exit liquidity for his followers.

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"King of Shilling" Hayes Strikes Again, This Time Setting His Sights on Deribit

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Benvenuto in HTX.com! Abbiamo reso l'acquisto di AIOZ NETWORK INC (AIOZ) semplice e conveniente. Segui la nostra guida passo passo per intraprendere il tuo viaggio nel mondo delle criptovalute.Step 1: Crea il tuo Account HTXUsa la tua email o numero di telefono per registrarti il tuo account gratuito su HTX. Vivi un'esperienza facile e sblocca tutte le funzionalità,Crea il mio accountStep 2: Vai in Acquista crypto e seleziona il tuo metodo di pagamentoCarta di credito/debito: utilizza la tua Visa o Mastercard per acquistare immediatamente AIOZ NETWORK INCAIOZ.Bilancio: Usa i fondi dal bilancio del tuo account HTX per fare trading senza problemi.Terze parti: abbiamo aggiunto metodi di pagamento molto utilizzati come Google Pay e Apple Pay per maggiore comodità.P2P: Fai trading direttamente con altri utenti HTX.Over-the-Counter (OTC): Offriamo servizi su misura e tassi di cambio competitivi per i trader.Step 3: Conserva AIOZ NETWORK INC (AIOZ)Dopo aver acquistato AIOZ NETWORK INC (AIOZ), conserva nel tuo account HTX. In alternativa, puoi inviare tramite trasferimento blockchain o scambiare per altre criptovalute.Step 4: Scambia AIOZ NETWORK INC (AIOZ)Scambia facilmente AIOZ NETWORK INC (AIOZ) nel mercato spot di HTX. Accedi al tuo account, seleziona la tua coppia di trading, esegui le tue operazioni e monitora in tempo reale. Offriamo un'esperienza user-friendly sia per chi ha appena iniziato che per i trader più esperti.

279 Totale visualizzazioniPubblicato il 2024.12.10Aggiornato il 2026.06.02

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