正在加载视频...

视频加载失败

We are working to secure the Artificial Superintelligence Alliance's leadership in decentralized AGI. More details coming soon. $FET

54,198 次观看 • 1 年前 •via X (Twitter)

11 条评论

jaybird86👨‍🚀 ᛤᛤ 的头像
jaybird86👨‍🚀 ᛤᛤ1 年前

@ASI_Alliance Looks like some heavy compute right there!

Lab4crypto 的头像
Lab4crypto1 年前

🚀 Don't gamble with your portfolio! Use our advanced hybrid quant risk tool using on/off-chain data and make informed decisions. 📈 Acess to 1000+ charts for your crypto journey. 📚Join our Premium Telegram for daily alerts. 📊+21 projects supported. 🏗️ Beginners and experts.

$CPUMP😉 的头像
$CPUMP😉1 年前

@ASI_Alliance Are there any updates on the next burn? 😅

cryptoFOXXY 的头像
cryptoFOXXY1 年前

@ASI_Alliance 👀

Eric 的头像
Eric1 年前

@ASI_Alliance 👀

The Legend 的头像
The Legend1 年前

@ASI_Alliance 👌

Kartal 的头像
Kartal1 年前

@ASI_Alliance 👍

Ascend Chain Capital 的头像
Ascend Chain Capital1 年前

@ASI_Alliance 👀

CryptoHash 的头像
CryptoHash1 年前

@ASI_Alliance What is it ?

Habakuk it is 的头像
Habakuk it is1 年前

@ASI_Alliance Quantum computers 🌹❤️🌹.

Derek 的头像
Derek1 年前

@ASI_Alliance All nations unite! All humans unite! All religions come together. We are entering the next phase!

相关视频

As Big Tech companies continue channeling billions of research dollars and attention into developing and scaling LLMs, a fundamental question is emerging in tech circles: Are LLMs actually leading us away from true AGI? At a #Consensus2025 panel addressing whether Web3 is losing the AI race, our CEO, Dr. Ben Goertzel, challenged the conventional wisdom driving investment strategies at many leading AI companies and sovereign wealth funds, including the recent multi-billion-dollar investments from Saudi Arabia and the UAE in US AI infrastructure. "I would quote Yan LeCun, a pioneer of deep learning and the head of AI at Facebook, who said on the highway to AGI, LLMs are an off-ramp," Dr. Goertzel told attendees, rejecting the premise that Web3 approaches are falling behind centralized AI development: "If you've gotten off the off-ramp, it doesn't matter if you're going 1,000 miles an hour and the other guy's only going 300 miles an hour if they're going on the right highway to the destination." The panel, which featured Ben Fielding (Founder, Gensyn), Jesus Rodriguez (CEO, IntoTheBlock), Clara Tsao (Founding Officer, Filecoin Foundation), and Jeff Wilser (Founder and Host, The People's AI Podcast), revealed a stark divide in how industry experts view the future of decentralized AI. While other panelists pointed to Web3's current disadvantages in talent, datasets, and infrastructure, Dr. Goertzel addressed a deeper issue: the incremental improvement of LLMs is not a viable approach to achieving human-level AGI. However, "If scaling up transformer neural nets is the crux of how you get to AGI, it's hard to see how the US and Chinese governments and the Big Tech companies in their orbit don't win the race," Dr. Goertzel acknowledged, noting the immense capital these entities are deploying. Our AGI R&D efforts at SingularityNET suggest a different path forward. "My own research intuition is that LLMs are not suited to be the central hub of a human-level AGI, let alone a Superintelligence, although they can be a powerful ingredient in a hybrid architecture for AGI," Dr. Goertzel explained. Our team is developing OpenCog Hyperon, a "hybrid, deep neural net, symbolic reasoning, evolutionary learning, approach to AGI within more sophisticated cognitive architectures than LLMs comprise," as described by Dr. Goertzel. This cognition-level approach represents a fundamentally different direction from most mainstream AI development. Dr. Goertzel closed with a prediction that would have seemed outlandish just a few years ago but now reflects our growing confidence in decentralized approaches through which AGI will be in the hands of humanity at large and without a single owner or controller: "Within the Artificial Superintelligence Alliance, we will launch the first AGI within one to three years from now on a decentralized infrastructure, and Big Tech will play catchup."

SingularityNET

39,110 次观看 • 1 年前

Computing hardware architecture has evolved from maximizing single-core performance to multiplying parallel processing capacity through more cores, more threads, and higher computational density. This transition demands software architectures specifically designed to exploit parallel processing, especially in advanced AI and blockchain-based systems. As Greg Meredith, CEO of our partner F1R3FLY. io, notes, "We need software architectures that can eat physical threads of computation and turn that into throughput." Traditional sequential programming models often struggle to effectively leverage the potential of these multi-core systems, creating a bottleneck in performance scaling. Rholang addresses this challenge through its foundation in the Rho-Calculus, a reflective higher-order process calculus specifically designed for inherent concurrency and reflection. Unlike computational models based on sequential execution or those that bolt on concurrency primitives, Rholang can leverage its process-oriented nature to detect and distribute non-interfering logical computation threads across available physical processing units, creating a more direct correlation between hardware resources and performance scaling. The Rho-Calculus was specifically designed to provide the minimal set of operations needed to model autonomous agents operating in parallel while maintaining the ability to represent their own reasoning processes. This structure mirrors the operational characteristics of intelligent systems, where autonomous processes run independently while communicating and coordinating. For our novel decentralized AI platform, MeTTaCycle, this future-proof architectural foundation enables more than just enhanced transactional throughput; it fosters an environment where independent computational processes can efficiently coexist and interact, forming a critical layer for the Artificial Superintelligence Alliance's decentralized AGI infrastructure and products.

SingularityNET

29,366 次观看 • 1 年前