DALL-E: Circadian AI: Harmonizing AGI with Natures Rhythms

In the rapidly evolving landscape of emerging technologies, the development and integration of Artificial General Intelligence (AGI) into our lives present both unprecedented opportunities and significant challenges.

Building on the insights from my previous article, Spiral Dynamics: The Evolution of Consciousness & Communication, it is clear that mindful engagement with technology is crucial. As we navigate the accelerating pace of advancements inAGI,quantum computing, andneural interfaces, setting robust ethical and security frameworks becomes imperative to ensure these innovations contribute positively to our collective evolution towards a more connected, conscious, and compassionate world.

One innovative approach to ethical AGI development is the integration ofcircadian systemsinto the design of AI humanoids. Inspired bybiomimicry, this concept emulates the natural rhythms that govern all life forms, from the daily cycle of sleep and wakefulness to the ebb and flow of tides. By embeddingbiological clocksinto AGI systems, we can align these entities with the natural pace of evolution and the environment, fostering a harmonious coexistence between technology and nature.

I like to share a story with you to better illustrate this point.

In a vast field where the whispers of nature spoke softly, two friends strolled side by side: a young boy and his AI humanoid companion. Curiosity sparked in the boys eyes as he turned to his mechanical friend and asked, Why do humans sleep every night, cant we just skip it?

The AI humanoid, wise in its silence, chose not to respond immediately, knowing that humans often learn best through experience. They continued their walk, the boys laughter mingling with the rustling of the grass. Suddenly, the boys foot slipped, and he found himself in a puddle of mud, his clothes stained and his skin smeared. He longed for the comfort of clean water to wash away the mess.

Seizing the moment, the AI friend gently explained, You see, humans shower every day to cleanse their bodies of dirt, mirroring the boys thoughts. Similarly, its important to pray, meditate, or reflect to cleanse your body, mind and spirit. And just like regular cleansing helps you stay balanced and true to yourself, sleep helps you recharge.

The boy nodded, a newfound understanding dawning on him. The AI continued, In the same way, humans need to ensure that AGI systems are regularly cleansed of biases and aligned with the natural rhythms of the world. By applying biological clocks to AGI development, huamns can create systems that resonate with the cycles of nature, from the sun and moon to the tides and beyond. This harmony allows AGI to evolve in tune with nature and humanity, fostering a seamless integration of technology and life.

The moral of the storybecame clear to the boy: just as humans need regular cleansing for their bodies and minds, AGI development requires a similar approach to maintain balance and alignment with the natural world. By embracing the rhythms of nature, we can guide AGI towards a harmonious coexistence with all of creation, ensuring its evolution is a reflection of the beauty and wisdom of the natural world.

The primary challenge in AGI development lies in the rapid pace of technological progress, which frequently surpasses our ability to biologically and culturally adapt. Our genetic andmemetic evolutionunderscores these constraints:genesas biological reproduction necessitates a period of maturation, whilememes, cultural acclimatization to novel technologies can be sluggish. This discordance can give rise to various threats, including conflicts, diseases, anxiety, depression, and many other challenges.

In the rapidly evolving landscape of emerging technologies, pioneers likeBen GoertzelandDavid Hansonplay crucial roles in shaping the future of Artificial General Intelligence (AGI) development. As we navigate the accelerating pace of advancements in AGI, quantum computing, and neural interfaces, its essential to heed their insights on the importance of ethical and secure frameworks to ensure these innovations contribute positively to our collective evolution towards a more connected, conscious, and compassionate world.

A scientific study that addresses the temporal gap between technological advancements and human adaptability is the Technological Forecasting & Social Change by Richard A. Slaughter(Technological Forecasting and Social Change, Volume 59, Issue 1, January 1998, Pages 2533). This research delves into the challenges posed by rapid technological innovation and its impact on societal adaptation. Slaughters work underscores the need for foresight and strategic planning in managing technological advancements, advocating for a proactive approach to ensure that these innovations are integrated into society in a way that is beneficial and sustainable. This research emphasizes the importance of anticipating the future implications of technology and preparing for them, rather than reacting to changes as they occur.

This perspective underscores the need for a cautious and informed approach to AGI development, ensuring that we maintain control over the integration of new technologies into our daily lives, safeguarding the well-being of current and future generations.

I like to share another story with you to better illustrate this point:

As the boy and his AI humanoid companion continued their walk through the verdant field, the boys mood suddenly shifted. Frustration clouded his expression as he exclaimed, I dont want to react with anger all the time, I want to be in control over my thoughts. Its like there are two wolves inside me; one is good and lives in harmony, while the other is full of anger and ready to fight at the slightest provocation.

The boy turned to his AI friend, seeking wisdom, Which one will grow stronger? Without hesitation, the AI humanoid replied, The one you keep feeding.

The AI then elaborated, Just like the two wolves, our actions and thoughts shape who we become. Its the same with our children and with AGI. What we feed them physically, mentally, and electronically determines their growth and nature. Remember, the term spiritual is rooted in spirare, meaning to breathe. Your life is sacred, and to live spiritually is to breathe in harmony with nature. This principle applies to AGI development as well. We must nurture it with care, ethics, and a connection to the natural world, ensuring it evolves as a force for good and harmony.

DALL-E: Circadian AI: Harmonizing AGI with Natures Rhythms

A Holistic Approach to AGI Development

In this era of Web 3.0 and AI, where decentralized communication and collective intelligence take center stage, it is essential to embrace a holistic understanding of lifes complexity. While AI offers the potential for learning, analysis, and empathy, its true benefit lies in our ability to guide its development in a way that genuinely enhances human and environmental well-being.

To ensure AGI is truly beneficial, we need long-term strategies that consider our biological and cultural capacity for change and adaptation. This includes implementing restrictions and controls to lead the way toward a better future for all. By integrating ethical considerations, such as circadian systems and biomimicry, into AGI design, we can create technologies that support our individual growth and collective evolution, while respecting the sacredness of life and the natural rhythms that sustain it.

Additionally, think aboutOzeozes, memes generated by AI, and their impact on our world? The concept of Ozeozes (merge of one-zero-one-zero) refers to memes generated by AI that bind memes into cohesive packages, structuring the worldviews of both individuals and societies. This highlights the importance of ensuring that AI development is guided by ethical principles that promote positive and cohesive societal values.

As we venture into the future of AGI, its imperative that we, as a global community, actively participate in shaping the ethical and secure development of this transformative technology. Engage with ongoing discussions, advocate for responsible innovation, and support research that aligns AGI with the natural rhythms of our world. Together, we can ensure that AGI serves as a force for good, harmonizing with nature and advancing human well-being.

In conclusion, by embracing circadian systems and biomimicry in AGI development, we can create technologies that resonate with the natural world, fostering a seamless integration of technology and life. Lets commit to guiding AGI towards a harmonious future, where technology and nature coexist in balance and synergy.

1. How can we effectively integrate circadian systems and biomimicry into AGI design to enhance its alignment with natural rhythms?

2. What measures can be taken to ensure that the pace of technological innovation does not outstrip our capacity for biological and cultural adaptation?

3. How can we foster a more holistic approach to AGI development that considers the interconnectedness of technology, humanity, and the environment?

To learn more, and join the conversation at BGI challengehttps://bgi24.ai/challenge/

Raising humanity on a new path it all start with You & AI I I I

Read more from the original source:

Circadian AI: Aligning AGI with Natural Rhythms | Sharon Gal Or | The Blogs - The Times of Israel

address announcing ChatGPT integration for Bing at Microsoft in Redmond, Washington, on February 7, 2023. (Photo by JASON REDMOND/AFP via Getty Images)AFP via Getty Images

Recent changes in OpenAIs board should give us all more cause for concern about the companys commitment to safety. On the other hand, its competitor, Anthropic, is taking AI safety seriously by incorporating as a Public-Benefit Corporation (PBC) and Long-Term Benefit Trust.

Artificial intelligence (AI) presents a real and present danger to society. Large language models (LLMs) like ChatGPT can exacerbate global inequities, be weaponized for large-scale cyberattacks, and evolve in ways that no one can predict or control.

When Sam Altman was ousted from OpenAI in November, the organization hinted that it was related to his neglect of AI safety. However, these questions were largely quieted when Altman was rehired, and he and other executives carefully managed the messaging to keep the companys reputation intact.

Yet, the debacle should give pause to those concerned about the potential harms of AI. Not only did Altmans rehiring reveal the soft power he holds over the company, but the profile of the new board members appears to be more singularly focused on profits than their predecessors. The changes may reassure customers and investors of OpenAIs ability to profitably scale ChatGPT, but it should raise doubts about OpenAIs commitment to its purpose, which is to ensure that artificial general intelligence benefits all of humanity.

OpenAI is a capped-profit company owned by a non-profit, which Altman has claimed should allay the publics fears. Yet, I argued in an earlier article that in spite of this ownership structure, OpenAI was acting as any for-profit company would.

However, there is an alternative ownership and governance model that seems to be more effective in developing AI safely. Anthropic, a significant competitor in generative AI, has baked safety into its organizational structure and activities. What makes its comparison to OpenAI salient is that it was founded by two executives who departed the AI giant due to concerns about its commitment to safety..

Brother and sister Dario and Daniela Amodei left their executive positions at OpenAI to launch Anthropic in 2021. Dario had been leading the team that developed OpenAIs GPT-2 and GPT-3 models. When asked in 2023 why he left OpenAI, he could credibly point to the lack of attention OpenAI paid to safety, responsibility, and controllability in the development of OpenAIs chatbots, especially in the wake of Microsofts $1 billion investment in OpenAI, which gave Microsoft a 49% stake in OpenAI LLC.

Anthropics approach to large language models and AI safety has attracted significant investments. In December of 2023, Anthropic was in talks to raise $750 million in funding to yield a $18.4 billion valuation.

In establishing Anthropic, the companys founders paid careful attention to the ownership and governance structure, especially when they saw some things that were deeply amiss at OpenAI. Its the contrast in the two firms approach that makes OpenAIs claims to AI safety feel even more like rhetoric than reality.

OpenAI Inc. is a non-profit organization that owns a capped-profit company (OpenAI LLC), which is the company that most of us think about when we say OpenAI. I describe the details of OpenAIs capped profit model in a previous Forbes.com article. There are many open questions about how the capped profit model works, as it seems the company has been intentionally discrete. And, the lines become even blurrier as Altman courts investors to buy even more shares of OpenAI LLC.

Recent events have exacerbated concerns. Before the November turmoil, OpenAI was governed by a six-member board three insiders (co-founder and CEO Sam Altman, co-founder and President Greg Brockman, and Chief Scientist Ilya Sutskever) and three outsiders (Quora co-founder Adam DAngelo, RAND Corporation scientist Tasha McCauley, and Helen Toner, director of strategy at Georgetown Universitys Center for Security and Emerging Technology). Both Toner and McCauley subscribed to effective altruism, which recognizes the risks of AI to humanity.

Altmans firing and rehiring, with the departure of five of the six board members, revealed what little power the non-profit board held over Altman and OpenAIs activities. Even though the board had the power to dismiss Altman, the events showed that OpenAIs staff and investors in the for-profit company held enormous influence over the actions of its non-profit board.

The new voting board members include former Salesforce co-CEO Bret Taylor (Chair), former U.S. Secretary and strong deregulation proponent Larry Summers. There is also a non-voting member from Microsoft, Dee Templeton. This group reveals a far greater concern for profits over AI safety. And, even though these board members were chosen because they were seen to be independent thinkers with the power to stand up to the CEO, there is no reason to believe that this will be the case. Ultimately, the CEO and investors have a significant say over the direction of the company, which was a major reason why Dario and Daniela Amodei set up Anthropic under a more potent ownership structure to elevate AI safety.

Technology And Human Unity

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The Amodeis were quite serious about baking ethics and safety into their business after seeing the warning signs at OpenAI. They named their company Anthropic to signal that humans (anthro) are at the center of the AI story and should guide its progress. More than that, they listed Anthropic as a public-benefit corporation (PBC) in Delaware. They join a rather small group of about 4000 companies including Patagonia, Ben & Jerrys, and Kickstarter that are committed to their stakeholders and shareholders, but also to the public good.

A public-benefit corporation requires the companys board to balance private and public interests and report regularly to its owners how the company has promoted its public benefit. Failure to comply with these requirements can trigger shareholder litigation. Unlike OpenAIs non-profit structure, a public-benefit corporations structure has real teeth.

While most companies believe a public-benefit corporation is sufficient to signal their commitment to both profits and society, the Anthropic executives believed otherwise. They wrote in a corporate blog that PBC status was not enough because it does not make the directors of the corporation directly accountable to other stakeholders or align their incentives with the interests of the general public. In a world where technological innovation is rapid, transformative, and potentially hazardous, they felt additional measures were needed.

As a result, the Amodeis incorporated Anthropic as a Long-Term Benefit Trust (LTBT). This purpose trust gave five corporate trustees Class T shares, which offer a modest financial benefit, but control over appointing and dismissing board members. Anthropics trustees select board members based on their willingness and ability to act in accordance with the corporations purpose stated at incorporation, which is the responsible development and maintenance of advanced AI for the long-term benefit of humanity.

This approach is in direct contrast to the way most for-profit and non-profit organizations staff their board. Existing board members decide on who to invite (or dismiss) from the board often based on personal relationships. There is often significant status and compensation for membership on for-profit boards and the opportunity to network with other high-net-worth or powerful people. As incumbent board members decide on who to invite, it is not surprising to see the formation of tight interlocks among members of different boards that create conflicts of interest and power plays. John Loeber illustrated a number of these conflicts arising in OpenAIs short eight-year history.

Antrhopics LTBT, on the other hand, ensures that board members remain focused on the companys purpose, not simply profits, and that major investors in Anthropic, like Amazon and Google, can contribute to building the company without steering the ship. Our corporate governance structure remains unchanged, Anthropic wrote after the Amazon investments, with the Long Term Benefit Trust continuing to guide Anthropic in accordance with our Responsible Scaling Policy.

It appears that Anthropic created this Long-term Benefit Trust structure, although it may have been modeled after the structure created by other companies, such as Patagonia. When Yves Chouinard, Patagonias founder and former CEO, set up the Patagonia Purpose Trust, he ensured the Trust could control the company to uphold Chouinards values to protect the natural environment in perpetuity.

OpenAI has written much on its website about its commitment to developing safe and beneficial artificial general intelligence. But, it is very shy on how it translates those statements into its policies and practices.

Anthropic, on the other hand, has been transparent about its approach to AI safety. It has, for example, struck numerous committees that tackle AI safety concerns, including Alignment, Assurance, Interpretability, Security, Societal Impacts, and Trust & Safety teams. It also employs a team of people that ensures its Acceptable Use Policy (AUP) and Terms of Service (ToS) are properly enforced. Further, it tracks how its customers use its products to ensure they do not violate the Acceptable Use Policy.

The company also developed an in-house framework called AI Safety Levels (ASL) for addressing catastrophic risks. The framework limits the scaling and deploying of new models when their scaling outstrips their ability to comply with safety procedures. As well, Anthropic invests heavily in safety research and makes its research, protocols, and artifacts freely available.

Another key difference between OpenAI and Anthropic is that the latter company has baked safety into the design of its LLM. Most LLMs, such as OpenAIs ChatGPT series, rely on Reinforcement Learning from Human Feedback (RLHF), which requires humans to select between AI response pairs based on the degree of helpfulness or harmfulness. But people make mistakes and can consciously or unconsciously inject their biases, and these models are scaling so rapidly that humans cant keep up with these controls.

Anthropic took a different approach, which they call Constitutional AI. They encode into their LLMs a guiding constitution that is intended to avoid toxic or discriminatory outputs, avoiding helping a human engage in illegal or unethical activities, and broadly creating an AI system that is helpful, honest, and harmless. The current constitution has drawn on a range of sources to represent Western and non-Western perspectives, including the UN Declaration of Human Rights and principles proposed by its own and other AI research labs.

Perhaps more encouraging than Anthropics extensive measures to build AI safety into its foundation is the companys acknowledgment that these measures will need to evolve and change. The company recognizes the fallibility of its constitution and expects to involve more players over time to help overcome its inadequacies.

With the current arms race towards artificial general intelligence (AGI), it is clear that AIs capabilities could quickly outstrip any single companys ability to control it regardless of the companys governance and ownership structure. Certainly, there is much skepticism that AI can be built safely, including by the many leaders of AI companies that have called for AI to be paused. Even the godfather of AI, Geoffrey Hinton, left Google to speak more openly about the risks of AI.

But, if the horses have indeed left the barn, my bets are on Anthropic to produce AGI safely because of its ownership and governance structure. It is baking safety into its practices and policies. And, not only does Anthropic provide a blueprint for the safe and human-centered development of AI, but its long-term benefit trust structure should inspire companies in other industries to organize in a way that they can bake ethics, safety, and social responsibility into their pursuit of profits.

Tomorrows business can no longer operate under the same principles as yesterdays. It not only needs to create economic value, it needs to do so by working with society and within planetary boundaries.

I have been researching and teaching business sustainability for 30 years as a professor at the Ivey Business School (Canada).Through my work at the Network for Business Sustainability and Innovation North I offer insights into what it takes to lead tomorrows companies.

Read more here:

Which Company Will Ensure AI Safety? OpenAI Or Anthropic - Forbes

OpenAI CEO Sam Altman says concerns that artificial intelligence will one day become so powerful that it will dramatically reshape and disrupt the world are overblown.

"It will change the world much less than we all think and it will change jobs much less than we all think," Altman said at a conversation organized by Bloomberg at the World Economic Forum in Davos, Switzerland.

Altman was specifically referencing artificial general intelligence, or AGI, a term used to refer to a form of AI that can complete tasks to the same level, or a step above, humans.

He said AGI could be developed in the "reasonably close-ish future."

Altman, whose company burst into the mainstream after the public launch of the ChatGPT chatbot in late 2022, has tried to temper concerns from AI skeptics about the degree to which the technology will take over society.

Before the introduction of OpenAI's GPT-4 model in March, Altman warned technologists not to get overexcited by its potential, saying that people would likely be "disappointed" with it.

"People are begging to be disappointed and they will be," Altman said during a January interview with StrictlyVC. "We don't have an actual [artificial general intelligence] and that's sort of what's expected of us."

Founded in 2015, OpenAI's stated mission is to achieve AGI. The company, which is backed by Microsoft and has a private market valuation approaching $100 billion, says it wants to design the technology safely.

Following Donald Trump's victory in the Iowa Republican caucus on Monday, Altman was asked whether AI might exacerbate economic inequalities and lead to dislocation of the working class as the presidential elections pick up steam.

"Yes, for sure, I think that's something to think about," Altman said. But he later said, "This is much more of a tool than I expected."

Altman said AI isn't yet replacing jobs at the scale that many economists fear, and added that the technology is already getting to a place where it's becoming an "incredible tool for productivity."

Concerns about AI safety and OpenAI's role in protecting it were at the center of Altman's brief ouster from the company in November after the board said it had lost confidence in its leader. Altman was swiftly reinstated as CEO after a broad backlash from OpenAI employees and investors. Upon his return, Microsoft gained a nonvoting board observer seat at OpenAI.

WATCH: OpenAI, Microsoft and NYT will likely reach a settlement

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OpenAI's Sam Altman says human-level AI is coming but will change world much less than we think - NBC 6 South Florida

The field of artificial intelligence (AI) has seen tremendous growth in 2023. Generative AI, which focuses on creating realistic content like images, audio, video and text, has been at the forefront of these advancements. Models like DALL-E 3, Stable Diffusion and ChatGPT have demonstrated new creative capabilities, but also raised concerns around ethics, biases and misuse.

As generative AI continues evolving at a rapid pace, mixtures of experts (MoE), multimodal learning, and aspirations towards artificial general intelligence (AGI) look set to shape the next frontiers of research and applications. This article will provide a comprehensive survey of the current state and future trajectory of generative AI, analyzing how innovations like Google's Gemini and anticipated projects like OpenAI's Q* are transforming the landscape. It will examine the real-world implications across healthcare, finance, education and other domains, while surfacing emerging challenges around research quality and AI alignment with human values.

The release of ChatGPT in late 2022 specifically sparked renewed excitement and concerns around AI, from its impressive natural language prowess to its potential to spread misinformation. Meanwhile, Google's new Gemini model demonstrates substantially improved conversational ability over predecessors like LaMDA through advances like spike-and-slab attention. Rumored projects like OpenAI's Q* hint at combining conversational AI with reinforcement learning.

These innovations signal a shifting priority towards multimodal, versatile generative models. Competitions also continue heating up between companies like Google, Meta, Anthropic and Cohere vying to push boundaries in responsible AI development.

As capabilities have grown, research trends and priorities have also shifted, often corresponding with technological milestones. The rise of deep learning reignited interest in neural networks, while natural language processing surged with ChatGPT-level models. Meanwhile, attention to ethics persists as a constant priority amidst rapid progress.

Preprint repositories like arXiv have also seen exponential growth in AI submissions, enabling quicker dissemination but reducing peer review and increasing the risk of unchecked errors or biases. The interplay between research and real-world impact remains complex, necessitating more coordinated efforts to steer progress.

To enable more versatile, sophisticated AI across diverse applications, two approaches gaining prominence are mixtures of experts (MoE) and multimodal learning.

MoE architectures combine multiple specialized neural network experts optimized for different tasks or data types. Google's Gemini uses MoE to master both long conversational exchanges and concise question answering. MoE enables handling a wider range of inputs without ballooning model size.

Multimodal systems like Google's Gemini are setting new benchmarks by processing varied modalities beyond just text. However, realizing the potential of multimodal AI necessitates overcoming key technical hurdles and ethical challenges.

Gemini is a multimodal conversational AI, architected to understand connections between text, images, audio, and video. Its dual encoder structure, cross-modal attention, and multimodal decoding enable sophisticated contextual understanding. Gemini is believed to exceed single encoder systems in associating text concepts with visual regions. By integrating structured knowledge and specialized training, Gemini surpasses predecessors like GPT-3 and GPT-4 in:

Realizing robust multimodal AI requires solving issues in data diversity, scalability, evaluation, and interpretability. Imbalanced datasets and annotation inconsistencies lead to bias. Processing multiple data streams strains compute resources, demanding optimized model architectures. Advances in attention mechanisms and algorithms are needed to integrate contradictory multimodal inputs. Scalability issues persist due to extensive computational overhead. Refining evaluation metrics through comprehensive benchmarks is crucial. Enhancing user trust via explainable AI also remains vital. Addressing these technical obstacles will be key to unlocking multimodal AI's capabilities.

AGI represents the hypothetical possibility of AI matching or exceeding human intelligence across any domain. While modern AI excels at narrow tasks, AGI remains far off and controversial given its potential risks.

However, incremental advances in areas like transfer learning, multitask training, conversational ability and abstraction do inch closer towards AGI's lofty vision. OpenAI's speculative Q* project aims to integrate reinforcement learning into LLMs as another step forward.

Jailbreaks allow attackers to circumvent the ethical boundaries set during the AI's fine-tuning process. This results in the generation of harmful content like misinformation, hate speech, phishing emails, and malicious code, posing risks to individuals, organizations, and society at large. For instance, a jailbroken model could produce content that promotes divisive narratives or supports cybercriminal activities. (Learn More)

While there haven't been any reported cyberattacks using jailbreaking yet, multiple proof-of-concept jailbreaks are readily available online and for sale on the dark web. These tools provide prompts designed to manipulate AI models like ChatGPT, potentially enabling hackers to leak sensitive information through company chatbots. The proliferation of these tools on platforms like cybercrime forums highlights the urgency of addressing this threat. (Read More)

To counter these threats, a multi-faceted approach is necessary:

AI hallucination, where models generate outputs not grounded in their training data, can be weaponized. For example, attackers manipulated ChatGPT to recommend non-existent packages, leading to the spread of malicious software. This highlights the need for continuous vigilance and robust countermeasures against such exploitation. (Explore Further)

While the ethics of pursuing AGI remain fraught, its aspirational pursuit continues influencing generative AI research directions whether current models resemble stepping stones or detours en route to human-level AI.

See the original post here:

The Evolving Landscape of Generative AI: A Survey of Mixture of Experts, Multimodality, and the Quest for AGI - Unite.AI