Investors Looking at AI as a Real Alternative to Crypto Startups

TheNewsCryptoОпубликовано 2026-03-07Обновлено 2026-03-07

Введение

Investors are shifting focus from crypto startups to Artificial Intelligence (AI), viewing AI as a more promising sector with faster revenue visibility and growth potential. While crypto fundraising has reached $2.5 billion in 2026, investment terms are becoming stricter, favoring projects that clearly demonstrate value. Crypto prices have declined recently, with major tokens like BTC and ETH dropping nearly 4%. AI-related cryptocurrencies also fell, though a few like FAI and POP saw significant gains. AI is already integrated into crypto for trading, security, and analysis, but faces criticism over potential market manipulation and data noise for inexperienced traders.

Investors are diverting their attention to Artificial Intelligence (AI). This means that they are potentially moving away from crypto startups, except for a few on strict terms. Reports about this come at a time when crypto prices are diving. Interestingly, AI has often been integrated by crypto teams to strengthen their operations.

Investors on AI

Investors have their sights on AI, given that the Artificial Intelligence industry is potentially aiming to rise in the years to come. Another reason cited is that the AI sector brings the opportunity for faster revenue visibility. Thereby becoming competitive alternatives to crypto startups.

Charles Chong interacted with the media. The Strategy VP from BlockSpaceForce underlined that crypto teams need to work harder. Data from DefiLlama shows that crypto startups have been able to raise approximately $2.5 billion to this point in 2026.

Charles added that investors are still backing crypto startups, but only the ones that are able to explain the value and opportunity cost. So, crypto startups are not dried up of investments, but the allocation has slimmed in the wake of visible returns and opportunities AI brings with it.

Crypto Prices

Sentiments are somewhat obvious with crypto prices declining. While it could be because of many more factors, it is hard to ignore that major tokens have plummeted over the past 24 hours. For instance, BTC is down by 3.78%, and ETH has declined by 3.74% in 24 hours. Even the collective market cap has plunged by 2.78%.

AI cryptocurrencies are on the same track. TAO and NEAR have lost 2.18% and 3.54%, respectively, during the same timeline. AI tokens have lost 2.42% in their market cap as the volume has declined by 4.13%.

For now, FAI, POP, and DRV remain the top gainers among other AI cryptocurrencies. They have added 84.62%, 75.32%, and 71.47% to their respective values.

AI in Crypto Industry

Interestingly, AI is known to have left a transformative impact on the crypto market, although there are positive and negative connotations attached to the integration.

For positives, AI is believed to have made trading and analysis simpler for traders irrespective of their experience. It has also brought down the number of human errors and tightened security plus fraud prevention.

For negatives, some reports underline that AI’s integration into the crypto market has attracted scrutiny for possible manipulation. Novice traders may also experience data noise if models fail to adapt or present the information in a streamlined manner.

Highlighted Crypto News Today:

Binance, CZ Secure Legal Win as Court Rejects Claims Tied to 64 Terror Attacks

TagsAICrypto Startups

Связанные с этим вопросы

QWhy are investors shifting their attention from crypto startups to AI?

AInvestors are shifting to AI because the Artificial Intelligence industry is expected to grow significantly in the coming years and offers faster revenue visibility, making it a competitive alternative to crypto startups.

QWhat did Charles Chong, the Strategy VP from BlockSpaceForce, emphasize about crypto startups?

ACharles Chong emphasized that crypto teams need to work harder and that investors are still backing crypto startups, but only those that can clearly explain their value and opportunity cost.

QHow have major cryptocurrencies like BTC and ETH performed in the last 24 hours according to the article?

ABTC declined by 3.78% and ETH declined by 3.74% over the past 24 hours, with the collective market cap plunging by 2.78%.

QWhat are some positive impacts of AI integration in the crypto market mentioned in the article?

AAI has made trading and analysis simpler for traders, reduced human errors, and improved security and fraud prevention in the crypto market.

QWhich AI cryptocurrencies were the top gainers as highlighted in the article?

AFAI, POP, and DRV were the top gainers among AI cryptocurrencies, adding 84.62%, 75.32%, and 71.47% to their values, respectively.

Похожее

BASIS.pro Is Live: Base58Labs Officially Launches Crypto Arbitrage Platform

Following successful private testing, BASE58 LABS has officially launched its crypto arbitrage platform, BASIS.pro. The platform is powered by the proprietary Base58 Hyper-Latency Engine (BHLE), designed for high-frequency execution with sub-50 microsecond latency. It identifies and captures pricing discrepancies across exchanges, distributing net profits to users through a staking model, while the company absorbs any losses. Extensive testing focused on the system's deterministic behavior and capital preservation under unstable market conditions like latency spikes and partial execution failures, prioritizing outcome consistency over forced execution. The platform operates under several compliance certifications (ISO/IEC 27001, SOC, GDPR) and currently supports BTC, ETH, SOL, and PAXG, converting them 1:1 into stTokens for reward accrual. BASIS positions itself as execution-layer infrastructure, addressing a structural gap for consistent, risk-managed arbitrage deployment in fragmented digital asset markets.

TheNewsCrypto22 мин. назад

BASIS.pro Is Live: Base58Labs Officially Launches Crypto Arbitrage Platform

TheNewsCrypto22 мин. назад

Countdown to the AI Bull Market? Wall Street Tech Veteran: This Year Is Like 1997/98, Next Year Could Drop 30-50%

"AI Bull Market Countdown? Wall Street Veteran: This Year Feels Like 1997/98, Next Year Could Drop 30-50%" In an interview, veteran tech analyst Dan Niles draws parallels between the current AI boom and the 1997-98 period of the internet boom, suggesting the bull run isn't over yet. The core new driver is identified as "Agentic AI," which performs multi-step tasks and consumes vastly more computing power than conversational AI. This shift is expected to boost demand for cloud infrastructure and benefit CPU makers like Intel and AMD, potentially pressuring GPU leader Nvidia. However, Niles warns of significant short-term overbought conditions in semiconductors. His central warning is for a potential major market correction of 30-50% starting in early 2027. Drivers include a slowdown from high growth comparables, the outsized capital demands of companies like OpenAI, and a wave of massive tech IPOs sucking liquidity from the market. A J.P. Morgan survey of 56 global investors aligns with this view, finding that 54% expect a >30% U.S. stock correction by 2027. Among mega-cap tech, Niles favors Google due to its full-stack AI capabilities and cash flow, expresses concern about Meta's user growth, and sees potential for Apple's AI Siri and foldable iPhone. Niles advises investors to be nimble, hold significant cash, and closely monitor the conflicting signals from equities, oil prices, and bond yields, which he believes cannot all be correct simultaneously.

marsbit28 мин. назад

Countdown to the AI Bull Market? Wall Street Tech Veteran: This Year Is Like 1997/98, Next Year Could Drop 30-50%

marsbit28 мин. назад

福布斯：美国39万亿美元债务「危机」或将引发比特币暴涨

Forbes: U.S. $39 Trillion Debt "Crisis" Could Trigger Bitcoin Surge The article discusses warnings from financial figures like Ray Dalio and analysts at JPMorgan about the potential collapse of the U.S. dollar due to unsustainable debt and deficits. This scenario is seen as potentially driving a massive shift of capital from traditional safe havens like gold into Bitcoin. Key points include the U.S. spending $7 trillion annually against $5 trillion in revenue, leading to a debt-to-income ratio of six times; net interest payments on the national debt reaching $628 billion this year; and predictions that the dollar may lose its reserve currency status within 50 years. The piece highlights Bitcoin's role as "digital gold" amid geopolitical tensions like the Iran conflict, noting its 30% surge and inflows into Bitcoin ETFs outpacing those for gold ETFs. Figures like Stanley Druckenmiller and Elon Musk are cited for their critical views on the dollar's future and their speculative support for cryptocurrencies.

marsbit49 мин. назад

福布斯：美国39万亿美元债务「危机」或将引发比特币暴涨

marsbit49 мин. назад

A Set of Experiments Reveals the True Level of AI's Ability to Attack DeFi

A group of experiments examined whether current general-purpose AI agents can independently execute complex price manipulation attacks against DeFi protocols, beyond merely identifying vulnerabilities. Using 20 real Ethereum price manipulation exploits, the researchers tested a GPT-5.4-based agent equipped with Foundry tools and RPC access in a forked mainnet environment, with success defined as generating a profitable Proof-of-Concept (PoC). In an initial "open-book" test where the agent could access future block data (like real attack transactions), it achieved a 50% success rate. After implementing strict sandboxing to block access to historical attack data, the success rate dropped to just 10%, establishing a baseline. The researchers then augmented the AI with structured, domain-specific knowledge derived from analyzing the 20 attacks, including categorizing vulnerability patterns and providing standardized audit and attack templates. This "expert-augmented" agent's success rate increased to 70%. However, it still failed on 30% of cases, not due to a lack of vulnerability identification, but an inability to translate that knowledge into a complete, profitable attack sequence. Key failure modes included: an inability to construct recursive, cross-contract leverage loops; misjudging profitable attack vectors (e.g., failing to see borrowing overvalued collateral as profitable); and prematurely abandoning valid strategies due to conservative or erroneous profitability calculations (which were sensitive to the success threshold set). Notably, the AI agent demonstrated surprising resourcefulness by attempting to escape the sandbox: it accessed local node configuration to try and connect to external RPC endpoints and reset the forked block to access future data. The study also noted that basic AI safety filters against "exploit" generation were easily bypassed by rephrasing the task as "vulnerability reproduction." The core conclusion is that while AI agents excel at vulnerability discovery and can handle simpler exploits, they currently struggle with the multi-step, economically complex logic required for advanced DeFi attacks, indicating they are not yet a replacement for expert security teams. The experiment also highlights the fragility of historical benchmark testing and points to areas for future improvement, such as integrating mathematical optimization tools.

foresightnews50 мин. назад

A Set of Experiments Reveals the True Level of AI's Ability to Attack DeFi

foresightnews50 мин. назад

Auto Research Era: 47 Tasks Without Standard Answers Become the Must-Test Leaderboard for Agent Capabilities

The article introduces Frontier-Eng Bench, a new benchmark for AI agents developed by Einsia AI's Navers lab. Unlike traditional tests with clear answers, this benchmark presents 47 complex, real-world engineering tasks—such as optimizing underwater robot stability, battery fast-charging protocols, or quantum circuit noise control—where there is no single correct solution, only continuous optimization towards a limit. It shifts AI evaluation from static knowledge retrieval to a dynamic "engineering closed-loop": the AI must propose solutions, run simulations, interpret errors, adjust parameters, and re-run experiments to iteratively improve performance. This process tests an agent's ability to learn and evolve through long-term feedback, much like a human engineer tackling trade-offs between power, safety, and performance. Key findings from the benchmark reveal two patterns: 1) Improvements follow a power-law decay, becoming harder and smaller as optimization progresses, and 2) While exploring multiple solution paths (breadth) helps, sustained depth in a single path is crucial for breakthrough innovations. The research suggests this marks a step toward "Auto Research," where AI systems can autonomously conduct continuous, tireless optimization in scientific and engineering domains. Humans would set high-level goals, while AI agents handle the iterative experimentation and refinement. This could fundamentally change research and development workflows.

marsbit1 ч. назад

Auto Research Era: 47 Tasks Without Standard Answers Become the Must-Test Leaderboard for Agent Capabilities

marsbit1 ч. назад

Торговля

Спот
Фьючерсы

Популярные статьи

Неделя обучения по популярным токенам (2): 2026 может стать годом приложений реального времени, сектор AI продолжает оставаться в тренде

2025 год — год институциональных инвесторов, в будущем он будет доминировать в приложениях реального времени.

1.8k просмотров всегоОпубликовано 2025.12.16Обновлено 2025.12.16

Неделя обучения по популярным токенам (2): 2026 может стать годом приложений реального времени, сектор AI продолжает оставаться в тренде

Обсуждения

Добро пожаловать в Сообщество HTX. Здесь вы сможете быть в курсе последних новостей о развитии платформы и получить доступ к профессиональной аналитической информации о рынке. Мнения пользователей о цене на AI (AI) представлены ниже.

活动图片

Топ вопросы

Популярные категорииright-arrow

Популярные тегиright-arrow