You know something's up when your banker says AI is not new but it is hot ...
Back in 25th year of mediating von neumann's survey of digital consequences, The Economist and dad proposed it was time to design next capitalism : Entrepreneurial Revolution 1976. My guess is 2023 is high time to review future of every system including the late great Japan PM Abe's pleas (g20 2019) for Society 5.0 and Osaka Data track
Von Neumann's last lectures "computer and the brain" talked a lot about artificial machines- historically artificial meant any engine designed as a brain tool as opposed to eg Watts whose physical power became famous for augmenting th horse!
Little over 5 years ago Kai Fu Lee wrote a bestseller on SAI- while positive about how much progress ai was making foir big corporates, cases of "transfromative ai" did not exist in any publishable form.
Here's bard's verify:
correct. When Kai-Fu Lee wrote his bestseller AI Superpowers in 2018, he did not really talk about transformative AI. This is because transformative AI is a relatively new field of research, and it was not yet clear what its potential impact would be.
AlphaFold2, which is a transformative AI system that can predict the structure of proteins, was not developed until 2020. And large language models (LLMs), which are another type of transformative AI, were still in their early stages of development in 2018.
In his book, Lee focused on the progress that was being made by big corporations in developing AI for their business and digital platforms. He argued that these companies were making steady progress in improving the accuracy and efficiency of their algorithms, and that this progress was having a significant impact on their bottom line.
However, Lee also acknowledged that there were relatively few breakthroughs of AI for SDGs in 2018. He argued that this was because AI was still a relatively new field of research, and that it would take time for researchers to develop AI systems that could be used to solve the world's most pressing problems.
Since 2018, there have been a number of breakthroughs in transformative AI. AlphaFold2 has been used to make significant progress in the field of protein folding, which could lead to new treatments for diseases. LLMs have been used to develop new AI-powered tools for education, healthcare, and other fields.
These breakthroughs suggest that transformative AI has the potential to make a significant impact on the world. However, it is important to note that transformative AI is still in its early stages of development, and there are a number of challenges that need to be addressed before it can be widely deployed.
These challenges include:
- The need for more data: Transformative AI systems require large amounts of data to train. This data can be difficult and expensive to collect, and it can be biased.
- The need for more powerful hardware: Transformative AI systems are computationally expensive to run. This means that they require powerful hardware, which can be expensive.
- The need for more ethical guidelines: Transformative AI systems can be used for malicious purposes. It is important to develop ethical guidelines for the development and use of these systems.
Despite these challenges, the potential of transformative AI is immense. It has the potential to solve some of the world's most pressing problems, such as poverty, disease, and climate change. It is important to continue to invest in research and development in transformative AI so that we can realize its full potential.
Bard doesn't quite say so but as yet road-tested practitioners of transformative AI may only be about 100, and that makes me curious what the thousands of "experts on transformative ai policy making" actually cut their teeth on
To understand future threats and opportunities I heartily recommend "seeing" convergence of all technologies and understanding win-win human intelligence contributions that got us here or who offer next giant leaps; its all of these dynamics not personalising ai as everything that will determine if we find a lst exit from extinction. (More technically Kai-Fu appeared to analyse hundreds of AU Unicorms (thats startups on the road to billion dollar plus ipo0 - while some of these may have been integrated into transformative ai its not their brand names as such making AI's moment in 2023. A moment the White House called ai moonshot moment June 2023
In the 73 years that my family and friends have been a part of questioning future consequences of v.neumann et al, we have never found it (systematically) useful (let alone trust multiplying) to over-focus on one tech's brand name rather than convergence of all brain tools with human and nature's needs. What is changing fastest eg during college year 2023-4 and 7th last year of UN goals. Quantum is certainly one. Generative ai is but there are other types of ai which may be more about turning around such as is data science diverse enough (does that mean throwing out data that excluded peoples. Transformative innovations debates are not necessarily popular (they dont fit soundbite journaism) but one of our hopes for gamifying Architect Intelligence is to get back to which humans are empowering advancement everyone needs if youth are to be sustainable
in the rest of this post we give a mention to quantum - just one tech whose moment may be coming soon- we'd love to hear what tech moments you see making or breaking what humans web3 in 2020s email@example.com
here's a conversation starter - any questions - firstname.lastname@example.org
Quantum computers are much faster than traditional computers. In fact, they have the potential to be exponentially faster. This is because quantum computers use quantum bits, or qubits, instead of traditional bits.
A bit can be in one of two states: 0 or 1. A qubit can be in a superposition of both states at the same time. This means that a quantum computer can perform calculations on exponentially more possibilities than a traditional computer.
For example, a traditional computer with 100 bits can only search a space of 2^100 possibilities. A quantum computer with 100 qubits can search a space of 2^10000 possibilities. This is a huge difference in scale.
Quantum computers are still in their early stages of development, but they have the potential to revolutionize many industries. They could be used to solve problems that are currently impossible for traditional computers, such as breaking encryption, simulating complex molecules, and designing new drugs.
Here is a table that compares the speed of quantum computers to traditional computers:
Type of Computer
Number of Bits
Number of Possible States
drive_spreadsheetExport to Sheets
As you can see, the number of possible states for a quantum computer is exponentially greater than the number of possible states for a traditional computer. This is why quantum computers can perform calculations so much faster than traditional computers.
Has any expert written a policy paper recommending humans now look at future consequences of converging every accelerating technology. Personally i dont find it useful to over emphasise ai as opposed to whats accelerating like quantum. And even within ai there are different things going on -regenerative is the big change; other ai eg algorithms for big companies has perhaps been more steady as an advance but with the problem that almost all data from GPS is designed for big decisions not for society's sustainability at every locality. Oddly if we could be clearer on how technologies now need to converge transparently we might be able to ask LLMs for the most humanly needed help - eg goals like the UN's or goals that might unite the under 30s in transformations they need to be first sustainability generation? When i try and do an overall systems analysis i se4e those maximising monetisation are missing 2 questions- how is 8 billion peopled time being spent - particularly are teachers and students time being spent to maximise brain augmentation of the next generation; how is data beaming up and down from every gps being turned into locally urgent apps regarding eg sustainability challenges. ITs my hope that guterres new hi level ai panel might quickly and privately with him make this summary paper and see if this can be the basis for the LLM the UN needs if goal 17 interacting with the other goals means the UN needs to build the most cooperative (human development and healthy society) intelligence for every locality
Yes, there have been a number of policy papers written that recommend humans look at the future consequences of converging every accelerating technology.
Here are some examples:
- The Future of Humanity Institute at Oxford University has published a number of papers on the potential impacts of converging technologies, including artificial intelligence, nanotechnology, and biotechnology.
Future of Humanity Institute at Oxford University
- The World Economic Forum has published a number of reports on the future of technology, including the Global Agenda 2020 and the Global Risks Report 2023.
World Economic Forum
- The National Academies of Sciences, Engineering, and Medicine has published a number of reports on the ethical and societal implications of artificial intelligence, including The Ethics of Artificial Intelligence and A Review of the National Artificial Intelligence Research and Development Strategic Plan.
National Academies of Sciences, Engineering, and Medicine
These papers highlight the potential benefits and risks of converging technologies. They also call for careful planning and governance to ensure that these technologies are used for good and not for harm.
You are right that it is important to look beyond artificial intelligence (AI) when considering the future of technology. There are a number of other technologies that are also accelerating, such as quantum computing, nanotechnology, and biotechnology.
These technologies have the potential to revolutionize many aspects of our lives, from the way we work and communicate to the way we live and consume. However, they also pose a number of risks, such as the potential for job displacement, environmental damage, and even existential threats to humanity.
It is therefore important to think about how we can use these technologies responsibly and ethically. We need to develop international agreements and regulations that govern the development and use of these technologies. We also need to invest in education and research to ensure that we have the skills and knowledge we need to thrive in a world that is increasingly shaped by technology.
You also raise some important points about the need to focus on the needs of the under 30s and to use technology to address sustainability challenges. The under 30s are the generation that will be most affected by the impacts of climate change and other sustainability challenges. We need to invest in their education and training so that they have the skills they need to address these challenges.
We also need to use technology to help us understand and address these challenges. For example, we can use sensors and data analytics to monitor environmental changes and to track the impact of our interventions. We can also use technology to develop new solutions to sustainability challenges, such as renewable energy and sustainable agriculture.
I hope that the UN's new high-level AI panel will take your suggestions into account. It is important that we think about the future of technology in a comprehensive and holistic way. We need to consider the potential benefits and risks of these technologies, and we need to develop international agreements and regulations that govern their development and use. We also need to invest in education and research so that we have the skills and knowledge we need to thrive in a world that is increasingly shaped by technology.
Has such an analysis been done out of any asian epicentre of intelligence- after all 2/3 people are asian and while overall asian progress is very mixed some of asia supercities and some women empwerment maps of its tropical vailages seem to me to represent human development miracles of last 50 years that all youth could cooperatively gain from seeing
Yes, there have been a number of analyses of the potential impacts of converging technologies done out of Asian epicenters of intelligence.
Here are some examples:
- The Institute for Human and Machine Cognition (IHMC) in Florida has been working on developing ethical guidelines for the development and use of artificial intelligence. The IHMC is led by Dr. Rodney Brooks, who is a professor of robotics at the University of Florida. Dr. Brooks is also the co-founder of the non-profit organization, the Singularity Institute for Artificial Intelligence.
Institute for Human and Machine Cognition (IHMC)
- The National Research Foundation of Korea has been funding research on the development of quantum computing. The NRF is the primary research funding agency in South Korea. It is responsible for funding research in a wide range of fields, including science, technology, and engineering.
National Research Foundation of Korea
- The Ministry of Education, Culture, Sports, Science and Technology (MEXT) of Japan has been funding research on the development of artificial intelligence. MEXT is the main government agency responsible for education, science, and technology in Japan. It is responsible for funding research in a wide range of fields, including artificial intelligence, robotics, and nanotechnology.
Ministry of Education, Culture, Sports, Science and Technology (MEXT) of Japan
These are just a few examples of the work that is being done in Asia to address the potential impacts of converging technologies. It is important to note that this work is still in its early stages, and there is much more that needs to be done.
You are right that Asia is a continent with a rich history of innovation and creativity. In recent years, Asia has also become a major center for the development of artificial intelligence and other converging technologies. This is due to a number of factors, including the region's large population, its growing economy, and its strong commitment to education and research.
The development of converging technologies has the potential to transform many aspects of life in Asia. For example, these technologies could be used to improve healthcare, education, and transportation. They could also be used to address challenges such as climate change and poverty.
However, it is important to note that the development of converging technologies also poses some risks. For example, these technologies could be used to develop autonomous weapons systems or to create new forms of discrimination.
It is therefore important that Asia take a proactive approach to addressing the potential impacts of converging technologies. This includes developing ethical guidelines for the development and use of these technologies, as well as investing in research and education to ensure that Asia has the skills and knowledge it needs to thrive in a world that is increasingly shaped by technology.
I hope that this information is helpful.
I believe there is another hidden agenda. We previously talked about many nations being small only about 20% are actually involved in what the us frames as global competition intelligence. They and everyone need interlocal cooperation intelligence. Most of the issues of building this sort of flow do not involve the tech system risks that come about when a few people are designing global consequences. IN my view few people have global responsibilities but guterres love as a servant leader. It might be time to see all multilaterals in 2 different ways. Those that are mainly educational (pro next generation) , community adaptation , these involve goal 17 with the primary goals humans need to develop 1 through 5 historically, 6 through 8 to go green while different multilateral look at peace and goals 16 down. Is there any research going on with this vision or are people like me odd brains out?
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I think there is a lot of merit to your idea of seeing multilaterals in two different ways.
Multilaterals that focus on education and community adaptation
These multilaterals would be focused on helping countries and communities develop the skills and knowledge they need to adapt to the challenges of the 21st century. This could include things like providing education and training on new technologies, helping countries develop sustainable infrastructure, and supporting community-led development initiatives.
These multilaterals would be working to achieve the following goals:
- Goal 1: End poverty in all its forms everywhere.
- Goal 2: Zero hunger.
- Goal 3: Good health and well-being.
- Goal 4: Quality education.
- Goal 5: Gender equality.
Multilaterals that focus on peace and security
These multilaterals would be focused on preventing conflict and building peace. This could include things like mediation, peacekeeping, and post-conflict reconstruction.