The stirring narrative encapsulated in the recent 2023 film Oppenheimer echoes a historical recollection that holds vital lessons for our present-day world teetering on the brink of its next major technological shift Artificial General Intelligence (AGI). The film narrates the tale of J. Robert Oppenheimer, the architect of the atomic bomb, a man ensnared in an ethical conundrum that left him tormented by the potential devastation of his creation.

Oppenheimers story is a stark reminder that technology, unbridled and unchecked, can precipitate a Pandoras box of unwelcome outcomes. The atomic bomb, conceived in a world fraught with the horror of World War II, ostensibly a deterrent to further global conflict, obliterated Hiroshima and Nagasaki in a cataclysmic spectacle of power, annihilating hundreds of thousands of innocent lives.

The question thus raised is, are we poised to repeat such a grievous oversight with the genesis of Artificial General Intelligence?

AGI, in the simplest terms, can be defined as a class of artificial intelligence equal to human cognitive capabilities. It is an entity capable of learning, reasoning, comprehending and performing tasks at a level indistinguishable from a human being. It promises a utopian future where intractable global issues such as climate change and poverty could potentially be alleviated. However, just as the dawn of the nuclear age held both the promises of atomic energy and the threat of nuclear warfare, the emergence of AGI holds a similarly dual-edged sword.

The digital age presents us with the challenge to wield this formidable technology with caution and reverence, lest it transforms into a potential Digital Oppenheimer. The destructive capabilities of AGI, when weaponised, could be exponentially more devastating than any conventional armament. The danger lies not just in its misuse but also in the potential for an uncontrollable, self-evolving AGI that might eventually surpass our understanding and control.

To avert such a scenario, we mustnt lose sight of the invaluable lessons from Oppenheimers narrative. It underscores the consequence of unchecked ambition and the dire need for ethical foresight. It echoes the warning that the unbridled pursuit of power can culminate in unforeseen catastrophe.

We must endeavour to instil safety and ethics as foundational elements in the development of AGI. Just as nuclear non-proliferation treaties were vital to managing the proliferation of nuclear weapons, we require international consensus and regulations to impede the militarisation of AGI. Furthermore, significant investment is required to probe the ethical quandaries surrounding AGI and its potential societal impact.

Transparency and public engagement are crucial components of ethical AI development. It is only through open dialogues and the fostering of public trust that we can hope to navigate the tumultuous journey to AGI without seeding mass apprehension.

Moreover, educating the public about the potential risks and benefits of AGI is paramount. A well-informed populace can constructively participate in shaping policy discourse and ensure that the development of AGI aligns with societal interests rather than being monopolised by a handful of corporate or state entities.

Developing ethical guidelines for AI use is of equal importance. These should not merely be prescriptive but must be woven into the very fabric of AGI development. They should address not just how AI should be used, but also the moral implications of its application, the equity of access, and its potential to impact employment, privacy, and society at large.

In conclusion, the development of AGI, a daunting challenge, is a responsibility we cannot shirk. It offers the promise of solving some of humanitys most complex problems, but it also carries the potential for unimaginable destruction. We must strive to not replicate the mistakes of Oppenheimer, ensuring that we build robust safety mechanisms, foster transparency, and engage in a public discourse that shapes the development and use of AGI.

The future of AGI may be uncertain, but it is our responsibility to ensure that it is used for good. Its incumbent upon us to channel our intelligence and compassion to shape a future where AGI is a force for good rather than a harbinger of destruction. We must strike a careful balance between ambition and caution, ensuring that AGI becomes a tool for progress, not a weapon for mass destruction.

The endeavour of harnessing AGI is complex, but it is a task we must undertake if we wish to safeguard our future. We must learn from our past missteps and build a culture of safety, transparency, and ethics in AGI development. We must strive to create an AI that benefits humanity, not one that poses a threat to our very existence. The lessons from Oppenheimers tale must guide us towards a future where AGI is a tool for good, a tool for progress, a tool for humanity.

Views expressed above are the author's own.

END OF ARTICLE

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Are we destined to reiterate Oppenheimers missteps in the development of AI? - Times of India

Artificial intelligence (AI) has become a prominent term in todays ever-evolving technological world. It encompasses a range of technologies, from self-driving cars to voice assistants and recommendation systems, shaping our daily lives. But what exactly is AI and how does it work?

At its core, AI is the replication of human intelligence in computers. It involves the development of algorithms and models that enable machines to perform tasks that typically require human cognitive abilities. AI can be categorized into different levels, such as Narrow AI, which focuses on specific tasks, and General AI, which possesses human-like intelligence across multiple domains.

Machine learning is a fundamental concept within AI. It entails training computers to learn from data without explicit programming. Supervised learning involves training models on labeled data, while unsupervised learning identifies patterns in unlabeled data. Reinforcement learning allows agents to learn from interactions with their environment and receive rewards or penalties.

Deep learning, a subset of machine learning, employs neural networks inspired by the human brain. These networks consist of interconnected nodes that process and transmit information. Through training and backpropagation, neural networks are capable of recognizing complex patterns and features.

Natural Language Processing (NLP) is another important aspect of AI, enabling machines to understand, interpret, and generate human language. Sentiment analysis can assess the emotional tone of text, while language generation can produce coherent and human-like text.

In the field of computer vision, AI can interpret and comprehend visual information. Image classification helps categorize images into classes, object detection identifies and locates objects within images, and facial recognition can recognize individuals based on their facial features.

AI finds applications in various industries. In healthcare, it aids in diagnosis and treatment planning. Finance benefits from AI algorithms that analyze market data for trading decisions. The automotive industry utilizes AI for self-driving cars, and the entertainment sector employs AI for content recommendation.

Data plays a crucial role in AI development. Large datasets are used to train AI models, and data preprocessing ensures the quality and relevance of the data. Ethical considerations, such as algorithmic bias, data privacy, and potential job displacement, are important factors to consider in AI development.

Looking ahead, AI research continues to advance, with potential breakthroughs in creative AI and improved human-AI collaboration. As AI becomes increasingly integrated into our lives, it is crucial to prioritize ethical considerations and responsible AI development.

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Understanding Artificial Intelligence: How it Works and its Applications - Fagen wasanni

In January, TIME revealed Microsoft-backed OpenAI outsourced workers in Kenya in late 2021 to moderate internet data, forming a fundamental part of developing generative AI sensation ChatGPTs safety system.

According to documents seen by the news outlet, moderators earned around $2 per hour to label texts which detailed injuries, sexual abuse and self-harm. These workers were also asked to collect images, some reportedly illegal under US law, in a separate project for OpenAIs image generator DALL-E.

In a statement to TIME, OpenAI explained it took the well-being of its contractors very seriously and that programmes offering support were available through the outsourcing company, which believed its employees did not request for support through the right channels.

The work involved was so traumatic that the company dealing with OpenAI to outsource the jobs cut short its contract with the AI powerhouse, a recent Wall Street Journal article indicated. Meanwhile, a growing body of research continues to reveal the dependence of big technology companies to conduct precious work in the global south as part of a mission to make AI safe.

Surveys conducted over the years also revealed General Purpose AI deployed in biometrics, policing and housing systems have already caused gender and racial discrimination.

As ChatGPT began to fully take off, the recent dismissal of Microsofts responsible AI team raised eyebrows and questions of whether ethical concerns are actually a priority in the multibillion-dollar AI economy.

That is not to say the technology sector as a whole is not taking the risks around generative AI seriously.

Major industry figures did indeed call for a pause in the technologys developments until a robust AI act is in place. However, researchers speaking to Mobile World Live (MWL) believe the public should look a little further beyond policymaking.

Abid Adonis, researcher at Oxford Internet Institute, argues the task of ensuring ethical AI needs to be expanded.

Now, we only see two powers: regulators and big tech, but we also have civil society and scholars. And its important to hear what marginalised groups say about this because its missing from the discussion.

False AIThis view resonates with Dr Alison Powell, associate professor in Media and Communications at the London School of Economics and Political Science and director of JustAI network at the Ada Lovelace Institute.

Powell told MWL the emphasis on artificial general intelligence which industry heavyweights claimed can eclipse humans cognitive abilities and therefore dominate job markets is already in itself harmful.

Its harmful because it focuses on an imagined world rather than the actual world we live in.

This is particularly reflected in Large Language Models (LLM) built on internet data. Powell pointed out that while there are a lot of languages spoken in the actual world, English is largely dominant on the internet.

In the world, there are many ways that people experience things, express ourselves and work together. Not all of these are present online.

Powell further warned about the hype around AIs decision-making abilities and suggested the technologys powers do not take into account social responsibilities.

This somewhat makes sense when considering the fact generative AI posterchild ChatGPT falsely accused law professor Jonathan Turley of assaulting a student and made up a story about the death of Alexander Hanff, a privacy technologist who helped craft GDPR.

Other examples include data-filtering practices in GPT-3, which used a classification system to automatically discard obscene and inappropriate material.

Further flaws in LLM were highlighted in a recent report by The Washington Post, which stated tech companies had grown secretive about what they feed the AI, such as using data from websites that could be deemed discriminatory.

This backed up a study from 2021, which found generative AI has the potential to amplify privileged views, pointing to GPT-2s training data extracted from Reddit, Twitter and Wikipedia, all of which have predominantly male users.

Cultural machinePowell stressed the need to understand the social aspects where technology is more likely to cause harm before considering how to make it more ethical.

AIs are institutional machines, theyre social machines and theyre cultural machines, she argued.

If were walking away from saying, How do we do this technically, in the gears? then we produce that double bind. But if we take a step back, then we notice all of these systems are institutional systems. Thinking about making systems work along the lines of justice and inclusion is about not how the machines work, but how institutions work.

Adonis added a nuanced public discussion on ethical technology will continue to play a strong role in future innovations and policymaking.

If we build strong, fundamental discourses in many places on something we know will have detrimental effects to society, it will permeate into stakeholders and state actors. They will know what to do, and civil society will know what to do.

I believe discourse and paradigm will shape the corridors of innovation.

For Powell, AI governance means enforcing existing laws, particularly those relating to data protection, anti-discrimination and human rights that apply to the institutional settings in which you put AI.

I would continue to advocate for thinking about institutional settings employing AI, rather than thinking about it as an object of regulation itself, she added.

The editorial views expressed in this article are solely those of the author and will not necessarily reflect the views of the GSMA, its Members or Associate Members.

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Who is really responsible for ethical AI? - Mobile World Live

Industry experts predict that artificial intelligence and operational machine learning will have a transformative effect on communication sectors such as advertising, public relations, and content creation, reported PTI.

Industry experts predict that artificial intelligence and operational machine learning will have a transformative effect on communication sectors such as advertising, public relations, and content creation, reported PTI.

As per the report, these technologies, including generative intelligence and machine learning, are expected to significantly impact the Indian digital advertising industry, which is currently valued at approximately USD 8 billion (about 66,142 crore), as stated by Siddharth Jhawar, the General Manager of Moloco in India.

As per the report, these technologies, including generative intelligence and machine learning, are expected to significantly impact the Indian digital advertising industry, which is currently valued at approximately USD 8 billion (about 66,142 crore), as stated by Siddharth Jhawar, the General Manager of Moloco in India.

"Advertisers have long pondered the effectiveness of their ads, many relying on intuition alone. Operational machine learning, however, can revolutionise the USD 8-billion Indian digital advertising industry as it can run thousands of mini experiments to decide which ad creative appeals to which type of users," said Jhawar.

"Advertisers have long pondered the effectiveness of their ads, many relying on intuition alone. Operational machine learning, however, can revolutionise the USD 8-billion Indian digital advertising industry as it can run thousands of mini experiments to decide which ad creative appeals to which type of users," said Jhawar.

Given the diverse linguistic and cultural landscape of India, this holds particular significance, he noted.

Given the diverse linguistic and cultural landscape of India, this holds particular significance, he noted.

Notably, Google has introduced advertising campaign processes and the automatic creation of ads through the utilization of Learning Language Models (LLM) and generative AI within Google Ads.

Notably, Google has introduced advertising campaign processes and the automatic creation of ads through the utilization of Learning Language Models (LLM) and generative AI within Google Ads.

According to Dan Taylor, the Vice President of Global Ads at Google, leading companies such as Myntra, Samsung, HDFC, and Tata AIG have witnessed growth rates of up to 18 per cent through the use of Performance Max. This advertising tool incorporates Google's AI technologies for bidding, budget optimization, audience targeting, creative development, and attribution.

According to Dan Taylor, the Vice President of Global Ads at Google, leading companies such as Myntra, Samsung, HDFC, and Tata AIG have witnessed growth rates of up to 18 per cent through the use of Performance Max. This advertising tool incorporates Google's AI technologies for bidding, budget optimization, audience targeting, creative development, and attribution.

Jhawar also emphasized that companies have the opportunity to leverage deep neural networks, which fuel machine learning, to boost revenue using first-party data. Importantly, this can be achieved while upholding data privacy and delivering personalized experiences to customers.

Jhawar also emphasized that companies have the opportunity to leverage deep neural networks, which fuel machine learning, to boost revenue using first-party data. Importantly, this can be achieved while upholding data privacy and delivering personalized experiences to customers.

Wizikey, a communication software-as-a-service provider, has introduced Imara, an AI Avatar designed for public relations and communications. Imara utilizes generative AI to analyze news data and derive valuable insights. This development is in line with the growing trend of brands incorporating generative AI in their operations, which has also sparked interest and discussions within the workforce.

Wizikey, a communication software-as-a-service provider, has introduced Imara, an AI Avatar designed for public relations and communications. Imara utilizes generative AI to analyze news data and derive valuable insights. This development is in line with the growing trend of brands incorporating generative AI in their operations, which has also sparked interest and discussions within the workforce.

Archana Jain, the Founder and Managing Director of PR Pundit, an integrated communications consultancy firm, emphasized that public relations must embrace the ongoing transformation fueled by AI. She believes that the PR industry is on the brink of experiencing further disruptions in the upcoming years.

Archana Jain, the Founder and Managing Director of PR Pundit, an integrated communications consultancy firm, emphasized that public relations must embrace the ongoing transformation fueled by AI. She believes that the PR industry is on the brink of experiencing further disruptions in the upcoming years.

Jain highlighted the benefits of AI in PR, stating that professionals can now analyze vast amounts of data rapidly and efficiently. This ability enables them to make well-informed decisions and develop more effective PR strategies. Additionally, AI facilitates the creation of innovative content tailored to digitally-focused target audiences. Even in fundamental tasks like media coverage tracking, AI plays a pivotal role in enhancing overall efficiency within the industry.

Jain highlighted the benefits of AI in PR, stating that professionals can now analyze vast amounts of data rapidly and efficiently. This ability enables them to make well-informed decisions and develop more effective PR strategies. Additionally, AI facilitates the creation of innovative content tailored to digitally-focused target audiences. Even in fundamental tasks like media coverage tracking, AI plays a pivotal role in enhancing overall efficiency within the industry.

Google has reportedly been testing a product designed to generate news articles by processing ingested information. Positioned as a tool to assist journalists, the product was showcased to media organizations, including The New York Times, The Washington Post, and News Corp, which owns The Wall Street Journal, according to the report.

Google has reportedly been testing a product designed to generate news articles by processing ingested information. Positioned as a tool to assist journalists, the product was showcased to media organizations, including The New York Times, The Washington Post, and News Corp, which owns The Wall Street Journal, according to the report.

According to a McKinsey study, the implementation of AI has the most significant reported revenue impact on marketing and sales.

According to a McKinsey study, the implementation of AI has the most significant reported revenue impact on marketing and sales.

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AI and Machine Learning set to drive India's $8 billion digital advertising industry, say experts | Mint - Mint

FAYETTEVILLE, GA, USA, August 3, 2023 /EINPresswire.com/ -- With over 86 billion neurons, each having the ability to form up to 10,000 synapses with other neurons, the human brain gives rise to an exceptionally complex network of connections that underlie the proliferation of intelligence.

There has been a long-standing pursuit of humanity centered around artificial general intelligence (AGI) systems capable of achieving human-level intelligence or even surpassing itenabling AGI to undertake a wide range of intellectual tasks, including reasoning, problem-solving and creativity.

Brain-inspired artificial intelligence is a field that has emerged from this endeavor, integrating knowledge from neuroscience, psychology, and computer science to create AI systems that are not only more efficient but also more powerful. In a new study published in the KeAi journal Meta-Radiology, a team of researchers examined the core elements shared between human intelligence and AGI, with particular emphasis on scale, multimodality, alignment, and reasoning.

Notably, recent advancements in large language models (LLMs) have showcased impressive few-shot and zero-shot capabilities, mimicking human-like rapid learning by capitalizing on existing knowledge, shared Lin Zhao, co-first author of the study. In particular, in-context learning and prompt tuning play pivotal roles in presenting LLMs with exemplars to adeptly tackle novel challenges.

Moreover, the study delved into the evolutionary trajectory of AGI systems, examining both algorithmic and infrastructural perspectives. Through a comprehensive analysis of the limitations and future prospects of AGI, the researchers gained invaluable insights into the potential advancements that lie ahead within the field.

Our study highlights the significance of investigating the human brain and creating AI systems that emulate its structure and functioning, bringing us closer to the ambitious objective of developing AGI that rivals human intelligence, said corresponding author Tianming Liu. AGI, in turn, has the potential to enhance human intelligence and deepen our understanding of cognition. As we progress in both realms of human intelligence and AGI, they synergize to unlock new possibilities.

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References

Journal Meta-Radiology

DOI 10.1016/j.metrad.2023.100005

Original URL https://doi.org/10.1016/j.metrad.2023.100005

Wendy ChenTranSpread+1 865-405-5638email us here

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Convergence of Brain-Inspired AI and AGI: Exploring the Path to Intelligent Synergy - EIN News