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There Could Never Be An Artificial General Intelligence

Richie Etwaru is Co-founder & CEO at Mobeus. He's also a former CTO, CDO & CIO at Fortune 500 firms in Financial Services and Healthcare.

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Although generative artificial intelligence (GenAI) has been making headlines, another of today's most tantalizing and controversial topics is the concept of artificial general intelligence (AGI). The idea of AGI—a machine with "the ability to understand, learn, and apply knowledge across a wide range of tasks," much like a human—has captured the imaginations of scientists, entrepreneurs and science fiction writers alike. However, despite the allure of creating such a machine, a growing body of evidence suggests that AGI will never be realized.

The Nature Of Human Intelligence

Human intelligence is fundamentally collective and constantly evolving. As individuals, we contribute to a vast pool of knowledge that grows exponentially over time. This collective intelligence isn't merely the sum of all human knowledge but a complex, interconnected web of ideas, insights and innovations that continuously build upon one another. I'm deliberately excluding human instincts from the dialogue, as this requires another article.

This compounding nature of human intelligence presents a significant challenge for the development of AGI. To achieve parity with human intelligence, an AGI would need to encompass the full breadth and depth of this collective knowledge and evolve at the same pace. The sheer scale of this task is daunting, as it would require not only the accumulation of vast amounts of information but also the ability to understand and integrate it in ways that mirror the dynamic, ever-changing nature of human thought.

The Boundaries Of Machine Learning

Current advancements in AI, particularly in machine learning, highlight the limitations of creating a truly general intelligence. Machine learning models, such as those used in natural language processing and computer vision, excel at specific tasks by learning patterns from large datasets. These models can be incredibly powerful, achieving superhuman performance in narrowly defined domains. However, their learning process is fundamentally different from human learning.

Machine learning relies on identifying and extrapolating patterns from data humans have labeled as correct. This process can be thought of as "stretching" the confirmation provided by humans to then make educated guesses about similar data. However, this stretching isn't equivalent to the kind of learning that occurs in humans. It's more akin to sophisticated pattern recognition, and the further the model stretches from the original human confirmation, the greater the likelihood of error and imprecision.

The Complexity Of Human Cognition

Human cognition is a multifaceted and deeply intricate process that involves not only logical reasoning and pattern recognition but also emotional intelligence, creativity and social understanding. These aspects of human intelligence are deeply intertwined and contribute to our ability to navigate complex social environments, solve novel problems and generate innovative ideas.

Research in cognitive science and psychology underscores the complexity of human thought processes. For instance, studies on human creativity reveal that it involves a unique combination of divergent thinking (generating multiple ideas) and convergent thinking (narrowing down to the best idea)—processes that aren't easily replicated by machines. Similarly, emotional intelligence, which encompasses the ability to recognize, understand and manage our own emotions and those of others, is a critical component of human intelligence that remains elusive for artificial systems.

The Role Of Embodiment In Intelligence

One of the key arguments against the feasibility of AGI is the importance of embodiment in the development of intelligence. Human intelligence is deeply rooted in our physical experiences and interactions with the world. This concept, known as embodied cognition, posits that our cognitive processes are shaped by our physical bodies and the environment in which we operate.

Artificial systems, lacking a physical body and the rich sensory experiences that come with it, face significant challenges in developing the kind of understanding humans possess. Without the ability to physically interact with the world, an AGI would be deprived of the context and grounding essential for true comprehension and learning.

Insights From Key Thought Leaders

Prominent thinkers and researchers have weighed in on the challenges and limitations of AGI. For instance, renowned cognitive scientist Marvin Minsky, one of the pioneers of artificial intelligence, acknowledged the difficulties of creating machines with human-like intelligence. He noted that human intelligence isn't a "single, monolithic capability" but a collection of diverse and interdependent skills and processes.

Similarly, philosopher John Searle, known for his work on the philosophy of mind, has argued that machines, regardless of their computational power, lack the intrinsic understanding that characterizes human cognition. His famous Chinese Room argument illustrates that syntactic manipulation of symbols (which machines do) isn't equivalent to semantic understanding (which humans possess).

The Evolutionary Perspective

An evolutionary perspective further underscores the implausibility of AGI. Human intelligence has evolved over millions of years, shaped by countless environmental pressures and genetic variations. This evolutionary process has resulted in a highly adaptive and flexible form of intelligence, finely tuned to our specific needs and circumstances.

Creating an AGI would require replicating this intricate and lengthy evolutionary process—a feat that seems improbable given the current state of technology. Moreover, human intelligence isn't static; it continues to evolve in response to new challenges and experiences. Any AGI would need to not only match but also keep pace with this ongoing evolution—a task of staggering complexity.

The Impossibility Of AGI

Although the dream of creating an AGI continues to inspire and motivate researchers, the overwhelming evidence suggests that such a goal is unlikely to be achieved. Human intelligence is a unique and multifaceted phenomenon that arises from our collective knowledge, cognitive complexity and embodied experiences. The limitations of current AI technologies, coupled with the profound challenges of replicating the evolutionary processes that shaped human intelligence, make the prospect of AGI highly improbable.

As we continue to advance in the field of artificial intelligence, it's crucial to recognize and appreciate the unique qualities of human cognition. Rather than striving to create machines that mimic our intelligence, we should focus on developing technologies that complement and enhance our capabilities, fostering a future where machines focus on being helpful to humans instead of being as or more intelligent than us.

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AI Is Learning From What You Said On Reddit, Stack Overflow Or Facebook. Are You OK With That?

CAMBRIDGE, Mass. -- Post a comment on Reddit, answer coding questions on Stack Overflow, edit a Wikipedia entry or share a baby photo on your public Facebook or Instagram feed and you are also helping to train the next generation of artificial intelligence.

Not everyone is OK with that — especially as the same online forums where they've spent years contributing are increasingly flooded with AI-generated commentary mimicking what real humans might say.

Some longtime users have tried to delete their past contributions or rewrite them into gibberish, but the protests haven't had much effect. A handful of governments — including Brazil's privacy regulator on Tuesday — have also tried to step in.

"A more significant portion of the population just kind of feels helpless," said Reddit volunteer moderator Sarah Gilbert, who also studies online communities at Cornell University. "There's nowhere to go except just completely going offline or not contributing in ways that bring value to them and value to others."

Platforms are responding — with mixed results. Take Stack Overflow, the popular hub for computer programming tips. First, it banned ChatGPT-written responses due to frequent errors, but now it's partnering with AI chatbot developers and has punished some of its own users who tried to erase their past contributions in protest.

It's one of a number of social media platforms grappling with user wariness — and occasional revolts — as they try to adapt to the changes brought by generative AI.

Software developer Andy Rotering of Bloomington, Minnesota, has used Stack Overflow daily for 15 years and said he worries the company "could be inadvertently hurting its greatest resource" — the community of contributors who've donated time to help other programmers.

"Keeping contributors incentivized to provide commentary should be paramount," he said.

Stack Overflow CEO Prashanth Chandrasekar said the company is trying to balance rising demand for instant chatbot-generated coding assistance with the desire for a community "knowledge base" where people still want to post and "get recognized" for what they've contributed.

"Fast forward five years — there's going to be all sorts of machine-generated content on the web," he said in an interview. "There's going to be very few places where there's truly authentic, original human thought. And we're one of those places."

Chandrasekar readily describes Stack Overflow's challenges as like one of the "case studies" he learned about at Harvard Business School, of a how a business survives — or doesn't — after a disruptive technological change.

For more than a decade, users typically landed on Stack Overflow after typing a coding question in Google, and then found the answer, copied and pasted it. The answers they were most likely to see came from volunteers who'd built up points measuring their credibility — which in some cases could help land them a job.

Now programmers can simply ask an AI chatbot — some of which are already trained on everything ever posted to Stack Overflow — and it can instantly spit out an answer.

ChatGPT's debut in late 2022 threatened to put Stack Overflow out of business. So Chandrasekar carved out a special 40-person team at the company to race out the launch of its own specialized AI chatbot, called Overflow AI. Then, the company made deals with Google and ChatGPT maker OpenAI, enabling the AI developers to tap into Stack Overflow's question-and-answer archive to further improve their AI large language models.

That kind of strategy makes sense but may have come too late, said Maria Roche, an assistant professor at Harvard Business School. "I'm surprised that Stack Overflow wasn't working on this earlier," she said.

When some Stack Overflow users tried to delete their past comments after the Open AI partnership was announced, the company responded by suspending their accounts due to terms that make all contributions "perpetually and irrevocably licensed to Stack Overflow."

"We quickly addressed it and said, 'Look, that's not acceptable behavior'," said Chandrasekar, describing the protesters as a small minority in the "low hundreds" of the platform's 100 million users.

Brazil's national data protection authority on Tuesday took action to ban social media giant Meta Platforms from training its AI models on the Facebook and Instagram posts of Brazilians. It established a daily fine of 50,000 reais ($8,820) for non-compliance.

Meta in a statement called it a "step backwards for innovation" and said it has been more transparent than many industry counterparts doing similar AI training on public content, and that its practices comply with Brazilian laws.

Meta has also encountered resistance in Europe, where it recently put on hold its plans to start feeding people's public posts into training AI systems — which was supposed to start last week. In the U.S., where there's no national law protecting online privacy, such training is already likely happening.

"The vast majority of people just have no idea that their data is being used," Gilbert said.

Reddit has taken a different approach — partnering with AI developers like OpenAI and Google while also making clear that content can't be taken in bulk without the platform's approval by commercial entities "with no regard for user rights or privacy." The deals helped bring Reddit the money it needed to debut on Wall Street in March, with investors pushing the value of the company close to $9 billion seconds after it began trading on the New York Stock Exchange.

Reddit hasn't tried to punish users who protested — nor could it easily do so given how much say voluntary moderators have on what happens in their specialty forums known as subreddits. But what worries Gilbert, who helps moderate the "AskHistorians" subreddit, is the increasing flow of AI-generated commentary that moderators must decide whether to allow or ban.

"People come to Reddit because they want to talk to people, they don't want to talk to bots," Gilbert said. "There's apps where they can talk to bots if they want to. But historically Reddit has been for connecting with humans."

She said it's ironic that the AI-generated content threatening Reddit was sourced on the comments of millions of human Redditors, and "there's a real risk that eventually it could end up pushing people out."

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Associated Press writer Eléonore Hughes in Rio de Janeiro contributed to this report.

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The Associated Press and OpenAI have a licensing and technology agreement that allows OpenAI access to part of AP's text archives.

Exploring The Best AI Courses: Empowering Learners In The Age Of Artificial Intelligence

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In today's rapidly evolving technological landscape, understanding Artificial Intelligence (AI) is becoming increasingly essential. Whether you're a curious beginner or a seasoned professional looking to deepen your knowledge, choosing the right AI user course can make a significant difference. These courses not only demystify complex AI concepts but also empower learners to harness the potential of AI responsibly and creatively.

Why Learn AI?

Artificial Intelligence is revolutionizing industries from healthcare to finance, reshaping how we work and interact with technology. By grasping the fundamentals of AI, individuals can unlock new opportunities for innovation and problem-solving. Moreover, AI literacy is becoming a core competency across various sectors, making it a valuable skill for career advancement and personal growth.

Criteria for the Best AI Courses

Selecting the best AI user course involves considering several key factors:

Comprehensive Curriculum: A top-tier AI course covers a wide range of topics, from machine learning algorithms to neural networks and natural language processing. It should provide both theoretical foundations and practical applications, ensuring learners acquire a holistic understanding of AI concepts.

Hands-on Experience: Practical experience is crucial for mastering AI. The best courses offer hands-on projects and simulations where learners can apply their knowledge in real-world scenarios. This approach not only solidifies understanding but also builds confidence in tackling AI challenges.

Expert Instruction: Learning from knowledgeable instructors or industry experts enhances the quality of education. Look for courses taught by professionals with practical experience in AI development or research. Their insights and guidance can significantly enrich the learning experience.

Flexibility and Accessibility: In today's digital age, flexibility in learning is key. Look for courses that offer flexible schedules, self-paced modules, or online formats. Accessibility to course materials, forums for discussion, and supplementary resources further enrich the learning journey.

Reputation and Reviews: Before enrolling, research the course's reputation and read reviews from past learners. Positive feedback regarding content quality, instructor support, and overall learning experience can guide your decision-making process.

Top AI User Courses

Several platforms and institutions offer standout AI user courses:

Coursera: Known for its specialization courses in AI and machine learning offered by reputed universities like Stanford and deeplearning.Ai.

edX: Offers courses from institutions like MIT and UC Berkeley, covering AI topics ranging from robotics to reinforcement learning.

Udacity: Provides Nanodegree programs in AI and machine learning, designed in collaboration with industry leaders like Google and IBM.

Kaggle: Known for its practical data science and machine learning challenges, offering hands-on experience with real datasets and competitions.

Codera: Offers comprehensive AI courses that combine theoretical learning with practical projects, suitable for learners looking to enhance their understanding of AI concepts and applications.

LinkedIn Learning : Offers AI courses suitable for various skill levels, focusing on practical applications and industry trends.

Conclusion

Choosing the best AI course (die besten KI-Anwenderkurse) is a pivotal step towards mastering this transformative technology. Whether you're aiming to build foundational knowledge or advance your career in AI, the right course can equip you with the skills and insights needed to thrive. By investing in AI education, individuals can stay ahead in a world where technology continues to shape the future of industries and societies alike.

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