Introduction
The intersection of Artificial Intelligence (AI) and Web3 technologies is a burgeoning field that promises to redefine the way we interact with the digital world. “The convergences are quite large,” said Brian Roemmele, emphasizing the importance of the human element in AI. Two recent #AI town hall debates on the 24 August ‘Tokenizing Intelligence: The Synergy of AI and Web3’ and on ‘AI Crypto Solutions’31 August have provided a wealth of insights into this exciting frontier. This article delves into the key topics discussed, offering a comprehensive look at the future of AI and Web3.

Tune in.. this project will be game changer. https://t.co/U3yngwTCxB

— 0xCryptoUniverse (@0xCryptoUnivers) August 31, 2023

The human context in AI
“The human experience is central to the development and application of AI,” said a participant in the recent town hall. Roemmele echoed this sentiment, stating, “We need to approach this from different dimensions because the convergences are quite large.” “AI is not just about algorithms; it’s about understanding human behavior,” he added.

The discussion extended to the ethical implications of AI, with another speaker adding, “Ethical considerations are not just an add-on; they are integral to AI development.” In the second town hall, Anand Iyer emphasized the importance of understanding the human context when developing AI algorithms. “We can’t just focus on the technology; we have to consider how it impacts people’s lives,” he said. This sentiment was echoed by other participants who stressed the need for AI to be more empathetic and understanding of human emotions and complexities.

Two more awesome @Frogland_io deribbitives by @NFToadjam made with the @aiblocks_net bot in @satributes discord! Try it out today! pic.twitter.com/k7ZGcrbRla

— Satributes.art (@satributes) September 1, 2023

Data ownership and intellectual property
Nick St. Pierre delved deep into the intricacies of data ownership, stating, ” Ownership in the digital realm is a complex issue that we’re just beginning to understand. The easy way to do it is if an artist’s name is specifically used in the creation of the image.” The recent town hall also touched on the need to protect people’s intellectual property. “We need to verify and protect people’s intellectual property and their cautiousness,” said one participant. The debate extended into the realm of data privacy, with experts calling for robust encryption methods to protect user data. “Data privacy is not just a technical issue; it’s a human rights issue,” emphasized another speaker. Anand Iyer also touched upon the ethical implications of data ownership. “Who owns the data, especially when it’s generated by AI? These are questions we need to answer,” he said. The panelists agreed that as AI continues to evolve, so too must the laws and regulations governing data ownership and intellectual property.

The future of work and commercial real estate
LDJ brought up the point that the future of work is not just about remote working but also about the kind of work we will be doing. “AI will take over repetitive tasks, but it will also create new kinds of jobs that we can’t even imagine right now. The office of the future is not a place you go; it’s a task you do,” he said. This underscores the need for adaptability and continuous learning in the workforce. “We’re going to have a future where we don’t need to sit at a desk anymore,” said a participant in the recent town hall. This sentiment echoes the broader industry perspective that remote work and decentralized offices could become the norm. “The traditional office space is becoming obsolete. We need to rethink our approach to workspaces,” added another expert. The discussion also touched on the role of AI in automating tasks, with one speaker stating, “AI will not replace humans; it will augment human capabilities.”

Ethical and regulatory concerns
“We need international standards and guidelines. AI is a global phenomenon, and its regulation should be too,” said Eugene Chung. The recent town hall also emphasized the need for ethical considerations. “Ethical AI is not just a catchphrase; it’s a necessity,” said a participant. The discussion further delved into the regulatory landscape, with one speaker stating, “Regulation should not stifle innovation but should ensure ethical practices.” St. Pierre raised concerns about the potential misuse of AI, stating, “We need to be vigilant about how AI is used, especially in critical areas like healthcare and national security.” The panelists concurred that ethical guidelines are essential but also pointed out that these guidelines need to be adaptable to keep pace with rapid technological advancements. “Ethics in AI is not a destination; it’s a journey,” concluded Chung.

via GIPHY

Using AI to tackle financial crime in the cryptoasset world is a powerful tool, but it brings up important ethical questions. Market practitioners have to be cautious about privacy, as AI could potentially dig into customers’ financial lives without their knowledge or consent. Ensuring these systems are fair and don’t discriminate is vital too. And let’s not forget the balance between security and personal freedom; society shouldn’t undermine the very idea of privacy that cryptocurrencies were built on. Striking the right balance is a challenge worth addressing as we navigate this new digital frontier. As Michael Charles Borrelli of AI & Partners added, “We should see AI as a key tool to help us in preserving market integrity while bearing in mind its various characteristics that may result in negative outcomes.”

The role of community in web3
“What blockchain can be useful for is community,” said Satributes.art. “In Web3, the community is the network,” he added. The sentiment was echoed in the recent town hall, where participants discussed the importance of trusted communities. “Community-driven projects are the backbone of the Web3 ecosystem,” said another participant. The discussion also touched on the role of governance in decentralized networks, with one speaker stating, “Decentralized governance will be the cornerstone of successful Web3 projects.” Roemmele highlighted the importance of community-driven governance in Web3 projects. “The community is not just an audience; they are stakeholders who should have a say in the project’s direction,” he said. This democratic approach to governance could serve as a model for other types of organizations and communities.

Technological advancements and challenges
“Just recently, we released a 70 billion parameter model,” said LDJ, highlighting the rapid advancements in AI. “The next frontier in AI is not just more data but better-quality data,” he noted. The most recent town hall also touched on the challenges of countering AI drone technology. “We need to be prepared for the challenges that come with rapid technological advancements,” warned an expert. The discussion also covered the limitations of current AI models, with one speaker stating, “Current models are data-hungry and computationally intensive; we need more efficient algorithms.” Satributes.art discussed the challenges of keeping up with technological advancements, stating, “The pace of innovation is so fast that even experts have a hard time keeping up.” He emphasized the need for continuous education and adaptability, especially for those working in the AI and Web3 spaces.

Closing remarks
“Great job to the new folks. Welcome to the space thanks to the regulars, everyone did so great. Audience, thank you for being very interesting,” Chung said, encapsulating the collaborative and insightful nature of the debates. As these technologies continue to evolve, the discussions around them are sure to become even more critical. Anand Iyer summed up the collective sentiment of both town halls: “We’re at the beginning of a new era, and the discussions we’re having today will shape the future of AI and Web3 for years to come. The conversations we’re having now will be the textbooks of the future,” The debates served not just as a platform for sharing insights but also as a call to action for everyone involved in these rapidly evolving fields.

Groundbreaking event reminiscent of the ‘Deep Blue’ era: drone racing just experienced its own seismic technological shift. 🚁🏁

Developed by the University of Zurich, an autonomous AI system named Swift, armed with single-camera vision and onboard inertial measurement data, has… pic.twitter.com/DBrJXlCWhm

— EYC (@eyc) August 31, 2023

Follow on LinkedIn

The world of artificial intelligence (AI) is abuzz with discussions about the potential and implications of Large Language Models (LLMs). A recent Twitter Space discussion titled “Biden Cracks Down | China’s $5Bn Nvidia Splurge #AITownHall” delved deep into this topic, with experts from various fields sharing their insights.

Geopolitical Implications and China’s AI Ambitions
The conversation took a geopolitical turn when Robert Scoble highlighted China’s significant investment in Nvidia chips. “China’s move isn’t just technological; it’s strategic. They’re positioning themselves as global AI leaders,” he remarked. Graham dePenros chimed in, noting, “China’s approach to AI, especially LLMs, is holistic. They’re looking at the bigger picture, from data collection to real-world applications.” Marcus, reflecting on the geopolitical implications, said, “In the short term, there’s no question that throttling China’s chip supply makes a difference. But I wonder what the long-term reaction is from a country that has that many resources and can’t afford to be cut out of this.”

Drawing on news of China’s new programme ‘Artificial Intelligence for Science’ to promote AI, Eugene Chung highlighted the broader implications: “China’s AI strategy isn’t just about outpacing the West. It’s about setting global standards and norms.” As reported in the South China Morning Post article: “The central government has been promoting research and development in AI and has pledged favourable policies to drive more investment. AI was identified as a key industry in China’s controversial ‘Made in China 2025’ industrial plan in which it was stated that China’s goal was to become a global leader in the field by 2030.” China, as the world’s second-largest economy, is rapidly advancing in the AI domain, leading in academic publications, patents, and both cross-border and global AI funding. A projection by the consulting firm IDC from last year suggests that by 2026, China’s investment in AI will likely touch US$26.69 billion, representing approximately 8.9% of worldwide investment. This positions China as second in the world for AI investment.

The Ethical Quandary
The ethical dimensions of LLMs were a significant point of discussion. “With great power comes great responsibility,” said Boucher, emphasizing the potential risks associated with unchecked AI capabilities. Scoble also raised concerns about misinformation, stating, “LLMs can be double-edged swords. Their ability to generate content is unparalleled, but what if they’re used to spread falsehoods?” Chung responded with a call for global collaboration: “We need international standards and guidelines. AI is a global phenomenon, and its regulation should be too.” Marcus weighed in on the ethical dimensions, highlighting the need for global collaboration and understanding. He remarked, “We need some coherent understanding. The UN is forming a body to try to think about AI in a broader perspective. We don’t want a piecemeal thing that’s just sort of everybody putting their autograph on some piece of legislation.”

The Power and Potential of LLMs
Vincent Boucher, an AI enthusiast, kicked off the discussion with a powerful statement: “The power of LLMs is undeniable. We’re seeing capabilities that were once thought to be decades away.” His sentiment was echoed by Chung, who added, “LLMs are not just about understanding language; they’re about understanding human thought.”

Gary Marcus, however, emphasized the importance of software over hardware in the AI race. He stated, “I think it’s a risk that it’s just going to make trying to move faster making these chips. But the war here is not over hardware, but over software. You could have all of the chips in the world with large language models, and they still have a lot of deep and fundamental problems.”

The Debate Over Multiple LLMs
The value of having multiple LLMs was a contentious topic. Scoble remarked, “The sheer scale of these models is mind-boggling. But do we need so many? It’s a question of quality over quantity.” Brian Roemmele countered, “Diversity in LLMs is essential. Different models bring different strengths and perspectives.” @Neuro_tarun added, “It’s not just about having multiple models. It’s about how they interact, complement, and sometimes even compete with each other.” Boucher countered, “In the world of AI, diversity is strength. Multiple LLMs mean multiple perspectives, which can only be a good thing.”

Marcus, diving deep into the debate, stated, “We don’t want the world training 195 large language models, destroying the environment in the process. We actually do want to have some alignment in the original sense of that word around what are best practices here.” He also emphasized the importance of reasoning over symbolic information, saying, “There’s a lot yet to be figured out. We don’t have very good control of large language models. We don’t want our fate of the universe to be in the hands of whether somebody wrote the right prompt or not.”

Conclusion: The Road Ahead
The future of AI, particularly LLMs, is a complex tapestry woven with potential, ethical considerations, geopolitical implications, and a profound reflection on what it means to be human. Zolayola CEO Patrick O’Connor-Read warns of the dangers of over-relying on LLMs, stating, “The danger with LLMs is we over-rely on them to provide deep insight to domains we have superficial understanding of, with the result that we are unable to discern full correctness from partial correctness. LLM’s actually need skillful handling, direction and redirection, to arrive at a useful outcome for non-trivial matters.” His concerns echo the broader debate over the nature of human cognition and reasoning, and the role of emotions and experiences in our understanding of the world.

Co-CEO/COO, AI & Partners Michael Charles Borrelli emphasizes the transformative potential of LLMs, noting, “LLMs hold the transformative potential to revolutionize communication, content generation, and knowledge dissemination across industries.” However, he also acknowledges the complexities surrounding the debate over multiple LLMs and the need to balance specialized AI models with resource allocation.

O’Connor-Read’s call for transparency resonates with Borrelli’s perspective on the ethical quandary of AI. O’Connor-Read asserts, “I strongly believe humans need a way to peer inside the data flows, algorithmic processes, and indeed the biases present in the data’s sourcing/handling. Political bias and editorial censorship are real risks.” Borrelli adds, “Navigating AI’s ethical quandary demands a delicate balance between innovation and safeguarding human rights and values.”

The geopolitical landscape is also a critical consideration, with Borrelli highlighting, “China’s AI ambitions are redefining global power dynamics and raising concerns about data sovereignty and technological influence.” O’Connor-Read’s scepticism about enforceable standards complements this view, suggesting that an industry code of conduct might be a more pragmatic approach.

Perhaps most poignantly, O’Connor-Read reflects on the legacy of AI, stating, “Ironically, the greatest legacy of AI could well be a renaissance of human reasoning, valuing our ability to fuse reason and emotion, intuition and experience.” This sentiment encapsulates the essence of the AI journey, a path that leads us not only to technological advancement but also to a deeper understanding of our own humanity. In the end, the road ahead for AI and LLMs is one of exploration, innovation, reflection, and responsibility. It’s a journey that challenges us to harness the power of technology while honouring the uniquely human values that define us.

The Twitter Space discussion underscored the complexities and potential of LLMs in the global AI landscape. As Boucher aptly summarized, “We’re on the cusp of an AI revolution, and LLMs are leading the charge.” Marcus, with a forward-looking perspective, concluded, “We will cross the mountain, it’s just a matter of getting over our addiction to LLMs and being ready to look for something new. But what I’m optimistic about is that we will do that and that will completely change AI hopefully for the better.”

Follow on LinkedIn