# Сопутствующие статьи по теме AI

Новостной центр HTX предлагает последние статьи и углубленный анализ по "AI", охватывающие рыночные тренды, новости проектов, развитие технологий и политику регулирования в криптоиндустрии.

The AI Cycle Is Here: Should Web3 Entrepreneurs Pivot to AI?

The article discusses whether Web3 entrepreneurs should pivot to AI amid the growing AI trend, using the metaphor of "raising lobsters" to symbolize the current hype. It notes that while Web3 projects are exploring AI agents for blockchain interactions, identity systems, and payments, many teams are merely chasing narratives rather than building sustainable products. The author cautions against abrupt shifts to AI, highlighting the high barriers, intense competition, and the risk of abandoning hard-earned Web3 expertise. Instead, they suggest a hybrid approach: leveraging Web3’s strengths—such as decentralized data verification, identity management, and micro-payment systems—to address AI’s unresolved challenges like data provenance, agent collaboration, and automated settlements. Key considerations for Web3 teams include assessing their core competencies (e.g., data infrastructure, identity protocols, or application layers), identifying real-world use cases with paying users, and evaluating existing resources (data networks, developer ecosystems) to avoid building in isolation. The goal is to abandon narrative-driven pivots and focus on practical integrations where crypto and AI complement each other.

marsbit03/19 00:33

The AI Cycle Is Here: Should Web3 Entrepreneurs Pivot to AI?

marsbit03/19 00:33

Disney's Olaf Robot Goes Viral, Trump Postpones Visit to China...

Here is a summary of the key discussions from crypto KOLs on X over the past 24 hours: **Disney's Olaf Robot Steals the Show at GTC:** A highly advanced, animatronic Snowman Olaf from Disney became a major talking point at the conference. Users noted its "humanized interaction" capabilities, powered by the Jetson AGX Thor chip, which allows for real-time multi-modal reasoning and complex motion training. This was seen as a significant milestone for AI scaling laws entering the physical world. Some pointed out that the on-stage dialogue was pre-recorded and that a similar robot has existed for years. **Trump Postpones Visit to China:** Former President Donald Trump's decision to delay a planned trip to China was widely discussed. Commentators characterized the move as typical of his unpredictable, "随心所欲" (whimsical) nature. Some speculated he might be "operating a prediction market," with one user quipping, "The first rule of winning: never go where you lose." **Yi Lihua Announces New Fund:** Crypto investor Yi Lihua announced he is preparing a new fund platform. The community response was mixed and skeptical. Replies ranged from praising his good attitude to accusations of market manipulation, suggesting his public statements are often contrary to his actual actions, such as secretly shorting the market or encouraging others to "lift the sedan chair" for his exit. **KOLs on Passive Income:** Several key opinion leaders shared their views and strategies for generating passive income, though specific details of these discussions were not elaborated in the provided text.

比推03/19 00:31

Disney's Olaf Robot Goes Viral, Trump Postpones Visit to China...

比推03/19 00:31

Ozak AI’s Token Value Could Multiply Over 700× From Presale Price With Exchange Listing Catalysts on the Horizon

Ozak AI ($OZ) is gaining attention as a potential early crypto investment, combining AI analytics with decentralized physical infrastructure (DePIN) for real-world applications. Its ongoing presale, priced at $0.014, has raised nearly $6.5 million, showing steady organic growth. Analysts speculate that exchange listings could catalyze significant price increases, with some projecting up to 700x returns based on past AI token performances. Key features include multi-chain functionality, staking, governance, and partnerships with firms like SINT, Hive Intel, and Pyth Network, enhancing its ecosystem. While speculative, the project's solid fundamentals and growing interest position it for potential massive growth in the next market cycle.

TheNewsCrypto03/18 13:33

Ozak AI’s Token Value Could Multiply Over 700× From Presale Price With Exchange Listing Catalysts on the Horizon

TheNewsCrypto03/18 13:33

Using AI for Weather Prediction: Earn $200 a Day While Doing Nothing?

Using AI for Weather Prediction: Can You Really Earn $200 a Day? This article explores how to leverage AI and data analysis to profit from weather prediction markets like Polymarket, focusing on Shanghai’s temperature forecasts. The system relies on Shanghai Pudong Airport (ZSPD) weather station data, sourced via Wunderground, rather than general city forecasts. Key insights include: - Temperature data is reported in whole Fahrenheit values in METAR format, not Celsius, affecting precision. - Historical data shows daily high temperatures most frequently occur between 11:00-13:00, peaking at 12:00 in summer (27.6% of days). Three effective prediction methods were implemented: 1. **Integrated Forecasting**: Combines Weather Company (WC) and ECMWF model data, weighted by weather conditions (e.g., sunny days favor WC). 2. **Real-Time Correction**: Uses morning temperature rise data and historical patterns to extrapolate the daily high, adjusted for cloud cover and wind. A Kalman filter dynamically weights real-time data vs. forecasts. 3. **Temperature Trend Model**: Predicts whether the day will be warmer/cooler than the previous day using pre-dawn data (pressure changes, wind, cloud cover, recent trends). It performs best in winter (clear signals) but poorly in autumn (63.7% accuracy). Two failed methods—Fourier analysis (systematic underestimation) and ERA5 peak-time prediction (insufficient precision)—were discarded. Case studies demonstrate the system identifying mispriced market opportunities, such as recognizing nighttime warming from moist air during rainfall, when public sentiment lagged. Limitations include autumn inaccuracy, lack of real-time pressure data, and unresolved coastal wind effects. Ultimately, the goal isn’t perfect accuracy but leveraging informational edges when odds are favorable.

marsbit03/18 12:18

Using AI for Weather Prediction: Earn $200 a Day While Doing Nothing?

marsbit03/18 12:18

Robinhood Founder Vlad Tenev on the Great Wealth Transfer, Tokenization, and Gen Z's Investment Future

In a Bankless interview, Robinhood CEO Vlad Tenev discusses the future of finance, driven by generational wealth transfer, tokenization, and Gen Z's investing behavior. He reveals that Gen Z are serious long-term investors, starting retirement planning as early as age 19 on average. Tenev addresses the $70-90 trillion "Great Wealth Transfer," emphasizing Robinhood's strategy to serve both younger generations and older asset owners through products like banking services and trust accounts. He predicts 24/7 markets and asset tokenization will become standard, with Robinhood already offering tokenized stocks in the EU. Robinhood is building a hybrid CeFi/DeFi infrastructure, including its own Layer 2 chain, to improve accessibility and utility for real-world assets. Tenev dismisses the notion that young investors are solely driven by "financial entertainment," highlighting data showing 40% of platform assets are in passive investments. Other key points include: the social value of prediction markets as "truth machines," plans for a Robinhood Social feature, the potential of AI-powered financial agents, and efforts to democratize access to private equity investments. He also discusses regulatory challenges and the strategic focus on global expansion if U.S. clarity remains limited.

marsbit03/18 11:02

Robinhood Founder Vlad Tenev on the Great Wealth Transfer, Tokenization, and Gen Z's Investment Future

marsbit03/18 11:02

Models Can Also "Nest"? MiniMax Releases M2.7: The First Domestic Large Model Deeply Involved in Self-Iteration

Artificial intelligence is evolving from monthly updates to self-evolution. On March 18, MiniMax released its first new model version deeply involved in its own iteration—MiniMax M2.7. This marks a new stage in model development: large models are no longer solely trained by human programmers but have begun to "train themselves." The core breakthrough of MiniMax M2.7 lies in its strong autonomous construction capability. It can independently build complex Agent Harness (intelligent agent testing frameworks) and, relying on underlying capabilities such as Agent Teams, complex Skills, and Tool Search tools, complete highly complex productivity tasks autonomously. In simple terms, M2.7 is not just a smarter conversational agent but also a "digital engineer" capable of self-diagnosis and self-optimization. This "self-participatory iteration" model will significantly enhance the model’s logical reasoning and tool invocation accuracy when facing unknown complex tasks. Currently, this self-evolving MiniMax M2.7 model has been fully launched on the MiniMax Agent platform and open platform. As large models begin to deeply participate in their own "growth" process, the ceiling of AI may be raised once again.

marsbit03/18 08:40

Models Can Also "Nest"? MiniMax Releases M2.7: The First Domestic Large Model Deeply Involved in Self-Iteration

marsbit03/18 08:40

$0.014 Presale Token Buyers Could Gain 300× From Current Market, Highlighting Early Accumulation Advantage

Capital continues flowing into AI-driven blockchain projects, with early-stage positioning becoming critical for long-term gains. Ozak AI ($OZ), available in presale for $0.014, is highlighted as a project with significant growth potential, targeting a $1 listing price. Having already raised over $6.4 million and sold 1.04 billion tokens, it remains in early-stage valuation territory. A 300× return from the current price could place $OZ between $4–$5, turning a $100 investment into over $30,000. The platform offers predictive analytics through real-time data processing, decentralized infrastructure (DePIN), encrypted data storage, and customizable AI prediction agents. Strategic partnerships with SINT and Weblume enhance its utility, positioning it as a modular intelligence layer for Web3. The emphasis is on early accumulation advantages, as post-listing market dynamics often reduce upside potential for late entrants.

TheNewsCrypto03/18 03:54

$0.014 Presale Token Buyers Could Gain 300× From Current Market, Highlighting Early Accumulation Advantage

TheNewsCrypto03/18 03:54

Ozak AI Presale Surges Beyond Expectations: $0.014 Entry Could Capture Up to 20,000 Tokens With $1 Listing Value

Ozak AI ($OZ) is generating significant attention as a promising AI crypto project that merges artificial intelligence with decentralized physical infrastructure (DePIN). Its presale has exceeded expectations, raising nearly $5 million at an entry price of $0.014 per token. This allows early investors to accumulate substantial amounts, such as 20,000 tokens for $280, with potential for significant gains if the token reaches its projected $1 listing value. The project distinguishes itself through real utility, including staking, governance, and cross-chain functionality, rather than relying on hype. Key partnerships with entities like SINT, Hive Intel, Weblume, Pyth Network, and Dex3 aim to accelerate adoption and enhance the ecosystem’s capabilities. With strong fundamentals and a low entry point, Ozak AI presents a calculated opportunity for early participants.

TheNewsCrypto03/18 03:43

Ozak AI Presale Surges Beyond Expectations: $0.014 Entry Could Capture Up to 20,000 Tokens With $1 Listing Value

TheNewsCrypto03/18 03:43

Private Equity's "Detroit: Become Human" Moment: When AI Takes Over Alpha, What's Left for Human Fund Managers?

A recent report by Anthropic highlights that 94% of financial roles are susceptible to AI replacement, though only 28% have been automated so far. The private fund industry is rapidly adopting AI to enhance efficiency and reduce costs, especially in research, operations, and sales. AI researchers, such as tools like OpenClaw, offer advantages over human analysts: they work 24/7, require no salary or benefits, and avoid human limitations like bias or job-hopping. Quantitative funds, with strong computational infrastructure, are already deploying multi-agent systems that minimize human involvement. In contrast, subjective fund managers face pressure to adopt AI to stay competitive, as散户 investors also use AI to narrow information gaps. However, AI has limitations: it cannot fully grasp market sentiment, human irrationality, or emotional nuances in investing. If AI eventually replaces most fund managers and researchers, markets may become efficient, eliminating alpha opportunities. The future role of humans in asset management may lie in intuition, passion for investing, and handling uncertainty—areas where AI falls short. The industry must determine how humans and AI can collaborate effectively, rather than merely reacting to technological change.

marsbit03/18 02:54

Private Equity's "Detroit: Become Human" Moment: When AI Takes Over Alpha, What's Left for Human Fund Managers?

marsbit03/18 02:54

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