### Summary
The article discusses the rapid advancement and potential risks of artificial intelligence (AI) and proposes the idea of nationalizing certain aspects of AI under a governing body called the Humane AI Commission to ensure AI is aligned with human interests.
### Facts
- AI is evolving rapidly and penetrating various aspects of American life, from image recognition to healthcare.
- AI has the potential to bring both significant benefits and risks to society.
- Transparency in AI is limited, and understanding how specific AI works is difficult.
- Congress is becoming more aware of the importance of AI and its need for regulation.
- The author proposes the creation of a governing body, the Humane AI Commission, that can control and steer AI technology to serve humanity's best interests.
- The nationalization of advanced AI models could be considered, similar to the Atomic Energy Commission's control over nuclear reactors.
- Various options, such as an AI pause or leaving AI development to the free market or current government agencies, have limitations in addressing the potential risks of AI.
- The author suggests that the United States should take a bold executive leadership approach to develop a national AI plan and ensure global AI leadership with a focus on benevolence and human-controlled AI.
### đ¤ AI Nationalization - The case to nationalize the ânuclear reactorsâ of AI â the worldâs most advanced AI models â hinges on this question: Who do we want to control AIâs nuclear codes? Big Tech CEOs answering to a few billionaire shareholders, or the government of the United States, answering to its citizens?
### đĽ Humane AI Commission - The author proposes the creation of a Humane AI Commission, run by AI experts, to steer and control AI technology in alignment with human interests.
### â ď¸ Risks of AI - AI's rapid advancement and lack of transparency pose risks such as unpredictable behavior, potential damage to power generation, financial markets, and public health, and the potential for AI to move beyond human control.
### âď¸ AI Regulation - The article calls for federal regulation of AI, but emphasizes the limitations of traditional regulation in addressing the fast-evolving nature of AI and the need for a larger-scale approach like nationalization.
### Summary
British Prime Minister Rishi Sunak is allocating $130 million to purchase computer chips to power artificial intelligence and build an "AI Research Resource" in the United Kingdom.
### Facts
- 𧪠The United Kingdom plans to establish an "AI Research Resource" by mid-2024 to become an AI tech hub.
- đť The government is sourcing chips from NVIDIA, Intel, and AMD and has ordered 5,000 NVIDIA graphic processing units (GPUs).
- đ° The allocated $130 million may not be sufficient to match the ambition of the AI hub, leading to a potential request for more funding.
- đ A recent report highlighted that many companies face challenges deploying AI due to limited resources and technical obstacles.
- đĽ In a survey conducted by S&P Global, firms reported insufficient computing power as a major obstacle to supporting AI projects.
- đ¤ The ability to support AI workloads will play a crucial role in determining who leads in the AI space.
The U.S. Department of Energy has allocated $16 million for 15 projects that will leverage artificial intelligence and machine learning to accelerate scientific discovery in the field of nuclear physics research. The projects will focus on various aspects of nuclear physics, including experiments, simulations, theory, and accelerator operations, with the aim of expanding scientific reach and addressing technical challenges.
The rapid growth of AI, particularly generative AI like chatbots, could significantly increase the carbon footprint of the internet and pose a threat to the planet's emissions targets, as these AI models require substantial computing power and electricity usage.
The use of artificial intelligence (AI) is seen as a positive development in terms of addressing environmental challenges, but there are concerns about AI's own carbon footprint due to energy-intensive processes such as data training and computer hardware production.
Intel is applying AI to its upcoming Meteor Lake chip to improve power management, using an algorithm that predicts and understands user behavior to optimize performance and energy efficiency.
The rise of AI and other emerging technologies will lead to a significant redistribution of power, giving individuals and organizations unprecedented capabilities and disrupting established power structures.
The transformation of data servers to be AI-ready is consuming significant energy and natural resources, raising the question of whether AI can revolutionize technology's carbon footprint responsibly.
Lawmakers in the Senate Energy Committee were warned about the threats and opportunities associated with the integration of artificial intelligence (AI) into the U.S. energy sector, with a particular emphasis on the risk posed by China's AI advancements and the need for education and regulation to mitigate negative impacts.
Tech developers including Microsoft, OpenAI, and Google are facing increased water consumption and environmental impact due to the energy-intensive nature of training large AI models.
Microsoft-backed OpenAI has consumed a significant amount of water from the Raccoon and Des Moines rivers in Iowa to cool its supercomputer used for training language models like ChatGPT, highlighting the high costs associated with developing generative AI technologies.
Generative AI, while revolutionizing various aspects of society, has a significant environmental impact, consuming excessive amounts of water and emitting high levels of carbon emissions. Despite some green initiatives by major tech companies, the scale of this impact is projected to increase further.
Representatives from several countries and companies announced commitments to harness the power of artificial intelligence (AI) to advance progress in achieving the United Nations' Sustainable Development Goals (SDGs) during a ministerial side event at the United Nations' 78th Session High Level Week. These commitments focused on using AI to address issues related to health, education, food security, energy, and climate action, with an emphasis on inclusive and responsible governance of AI.
Microsoft is seeking a nuclear expert to assess the integration of small modular nuclear reactors to power its data centers as part of their AI operations.
Microsoft is looking to use next-generation nuclear reactors to power its data centers and support its AI ambitions, as it seeks clean sources of energy to meet its climate goals. The company is specifically focused on small modular reactors (SMR), which are easier and cheaper to build than traditional reactors. However, challenges remain, such as the need for highly enriched uranium fuel and the handling of nuclear waste.
Microsoft is hiring a project manager for nuclear technology to explore using nuclear energy to power its AI data centers, aiming to address the high energy demand of AI models like ChatGPT.
The Center on Global Energy Policy at Columbia University is hosting a series of discussions on the application of artificial intelligence in the energy sector, aiming to accelerate the discovery of new technologies and optimize operations.
Artificial intelligence's rapid growth and adoption is leading to a significant increase in energy consumption, particularly in data centers, raising concerns about the environmental impact and the need for more efficient energy solutions.
Microsoft is planning to power its large language models using nuclear reactors, with the goal of reducing the power-intensive process's carbon footprint and reliance on traditional energy sources.
Artificial intelligence may be alleviating concerns about Bitcoin's energy consumption and environmental impact, as the focus shifts to AI's own energy usage and efficiency improvements.
OpenAI is considering developing its own artificial intelligence chips or acquiring a chip company to address the shortage of expensive AI chips it relies on.
OpenAI, a well-funded AI startup, is exploring the possibility of developing its own AI chips in response to the shortage of chips for training AI models and the strain on GPU supply caused by the generative AI boom. The company is considering various strategies, including acquiring an AI chip manufacturer or designing chips internally, with the aim of addressing its chip ambitions.
The growing use of large AI models could contribute significantly to global carbon emissions, warns researcher Alex de Vries, as the energy consumption of training and running these models is substantial and increasing. Nvidia, which supplies 95% of the GPUs used for AI, is set to ship 100,000 servers this year that collectively consume 5.7 terrawatt hours of energy. New manufacturing plants are expected to further increase production capacity, potentially consuming 85.4 terawatt hours of energy by 2027. Experts emphasize the need for responsible use of AI and transparency regarding its environmental impact.
Tech companies, including Microsoft and OpenAI, are struggling to turn a profit with their generative AI platforms due to the high costs of operation and computing power, as well as declining user bases, posing a challenge to the industry's economic and strategic viability.
A new study warns that the artificial intelligence (AI) industry could consume as much energy as a country the size of the Netherlands by 2027, but its environmental impact could be less than feared if growth slows down.
AI chatbots like OpenAI's ChatGPT and Google's Bard consume a massive amount of electricity and water, with data centers estimated to use as much energy as an entire country by 2027, prompting experts to question the sustainability of the AI industry.
Artificial intelligence (AI) could consume as much energy as Sweden and undermine efforts to reduce carbon emissions, warns a study published in the journal Joule, highlighting the need for more sustainable AI practices.
A new study warns that the widespread adoption of artificial intelligence technology could lead to a substantial increase in electricity consumption, with AI systems relying on powerful servers and potentially driving a spike in energy demand.
The global AI industry could consume as much as 134 TWh of electricity annually by 2027, which is comparable to the annual consumption of countries like Argentina and the Netherlands, according to expert analysis. As AI becomes more prevalent, its energy needs will continue to grow, highlighting the importance of carefully considering where and when to use AI technologies.
The growth of artificial intelligence could significantly increase energy consumption, with AI servers potentially using as much electricity as small countries do in a year, according to an analysis published in Joule. The study highlights the need for sustainability considerations in AI development and calls for greater transparency and data on energy use in the industry.
China should seize the emerging opportunities in artificial intelligence (AI) to reshape global power dynamics and establish a new "international pattern and order," as AI is expected to bring deep economic and societal changes and determine the future shape of global economics. By mastering AI innovation and its applications, along with data, computing, and algorithms, a country can disrupt the existing global power balance, according to a report by the People's Daily research unit. China has been actively pursuing AI development while also implementing regulations to govern its use and mitigate risks.
DeepMind, the Google-owned AI lab, is using artificial intelligence to tackle climate change by helping understand climate change through prediction and monitoring, optimizing existing systems and infrastructure, and accelerating breakthrough science, such as nuclear fusion. The lab also acknowledges the carbon footprint of AI and aims to deploy carbon-efficient solutions. However, access to data and collaboration with domain experts are key roadblocks in utilizing AI to fight climate change, and safety considerations are addressed by working closely with experts in the respective fields. Overall, the techno-optimist view is that AI can be a transformative tool to solve climate change problems quickly and at scale.
The Allen Institute for AI is advocating for "radical openness" in artificial intelligence research, aiming to build a freely available AI alternative to tech giants and start-ups, sparking a debate over the risks and benefits of open-source AI models.
Taiwan's chip industry is seeking to accelerate the development of renewable energy sources in order to meet the growing demand for artificial intelligence and achieve its goal of net-zero emissions by 2050.
Project managers should learn to implement "green algorithms," specialized AI constructs that enhance operational efficiency and prioritize sustainability in project management.
OpenAI is creating a team to address and protect against the various risks associated with advanced AI, including nuclear threats, replication, trickery, and cybersecurity, with the aim of developing a risk-informed development policy for evaluating and monitoring AI models.
