Lifeboat Foundation

Since the release of ChatGPT in November 2022, artificial intelligence (AI) has both entered the common lexicon and sparked substantial public intertest. A blunt yet clear example of this transition is the drastic increase in worldwide Google searches for ‘AI’ from late 2022, which reached a record high in February 2024.

You would therefore be forgiven for thinking that AI is suddenly and only recently a ‘big thing.’ Yet, the current hype was preceded by a decades-long history of AI research, a field of academic study which is widely considered to have been founded at the 1956 Dartmouth Summer Research Project on Artificial Intelligence.¹ Since its beginning, a meandering trajectory of technical successes and ‘AI winters’ subsequently unfolded, which eventually led to the large language models (LLMs) that have nudged AI into today’s public conscience.

Alongside those who aim to develop transformational AI as quickly as possible – the so-called ‘Effective Accelerationism’ movement, or ‘e/acc’ – exist a smaller and often ridiculed group of scientists and philosophers who call attention to the inherent profound dangers of advanced AI – the ‘decels’ and ‘doomers.’² One of the most prominent concerned figures is Nick Bostrom, the Oxford philosopher whose wide-ranging works include studies of the ethics of human enhancement,³ anthropic reasoning,⁴ the simulation argument,⁵ and existential risk.⁶ I first read his 2014 book Superintelligence: Paths, Dangers, Strategies⁷ five years ago, which convinced me that the risks which would be posed to humanity by a highly capable AI system (a ‘superintelligence’) ought to be taken very seriously before such a system is brought into existence. These threats are of a different kind and scale to those posed by the AIs in existence today, including those developed for use in medicine and healthcare (such as the consequences of training set bias,⁸ uncertainties over clinical accountability, and problems regarding data privacy, transparency and explainability),⁹ and are of a truly existential nature. In light of the recent advancements in AI, I recently revisited the book to reconsider its arguments in the context of today’s digital technology landscape.

The Buccino Leadership Institute presents Ideas & Trends (2024) Nanotechnology: The Three Lenses — Past, Present and Future.

Dennett’s classic story raises deep philosophical questions about identity and consciousness.

Single-pixel imaging (SPI) is a novel computational imaging technique that has been widely studied in recent years. This technique only uses a single pixel detector without spatial resolution to obtain the spatial information of the target.

Structural and dynamic DNA nanosciences offer unique tools for engineering bottom–up synthetic cells. This Review provides a holistic overview for using DNA as a structural material, for designing functional entities, and for information-processing circuits for adaptive and interactive behaviour.

Black hole singularities defy the laws of physics. New research presents a bold solution to this puzzle: Black holes may actually be a theoretical type of star called a ‘gravastar,’ filled with universe-expanding dark energy.

In an amazing phenomenon of quantum physics known as tunneling, particles appear to move faster than the speed of light. However, physicists from Darmstadt believe that the time it takes for particles to tunnel has been measured incorrectly until now. They propose a new method to stop the speed of quantum particles.

In classical physics, there are strict laws that cannot be circumvented. For instance, if a rolling ball lacks sufficient energy, it will not get over a hill; instead, it will roll back down before reaching the peak. In quantum physics, this principle is not quite so strict. Here, a particle may pass a barrier, even if it does not have enough energy to go over it. It acts as if it is slipping through a tunnel, which is why the phenomenon is also known as “quantum tunneling.” Far from mere theoretical magic, this phenomenon has practical applications, such as in the operation of flash memory drives.

Quantum Tunneling and Relativity.

Leftover light from the young universe has a major flaw, and we don’t know how to fix it. It’s the cold spot. It’s just way too big and way too cold. Astronomers aren’t sure what it is, but they mostly agree that it’s worth investigating.

The cosmic microwave background (CMB) was generated when our universe was only 380,000 years old. At the time, our cosmos was about a million times smaller than it is today and had a temperature of over 10,000 kelvins (17,500 degrees Fahrenheit, or 9,700 degrees Celsius), meaning all of the gas was plasma. As the universe expanded, it cooled, and the plasma became neutral. In the process, it released a flood of white-hot light. Over the billions of years since, that light has cooled and stretched to a temperature of around 3 kelvins (minus 454 F, or minus 270 C), putting that radiation firmly in the microwave band of the electromagnetic spectrum.

To be clear, humans are not the pinnacle of evolution. We are confronted with difficult choices and cannot sustain our current trajectory. No rational person can expect the human population to continue its parabolic growth of the last 200 years, along with an ever-increasing rate of natural resource extraction. This is socio-economically unsustainable. While space colonization might offer temporary relief, it won’t resolve the underlying issues. If we are to preserve our blue planet and ensure the survival and flourishing of our human-machine civilization, humans must merge with synthetic intelligence, transcend our biological limitations, and eventually evolve into superintelligent beings, independent of material substrates—advanced informational beings, or ‘infomorphs.’ In time, we will shed the human condition and upload humanity into a meticulously engineered inner cosmos of our own creation.

Much like the origin of the Universe, the nature of consciousness may appear to be a philosophical enigma that remains perpetually elusive within the current scientific paradigm. However, I emphasize the term “current.” These issues are not beyond the reach of alternative investigative methods, ones that the next scientific paradigm will inevitably incorporate with the arrival of Artificial Superintelligence.

The era of traditional, human-centric theoretical modeling and problem-solving—developing hypotheses, uncovering principles, and validating them through deduction, logic, and repeatable experimentation—may be nearing the end. A confluence of factors—Big Data, algorithms, and computational resources—are steering us towards a new type of discovery, one that transcends the limitations of human-like logic and decision-making— the one driven solely by AI superintelligence, nestled in quantum neo-empiricism and a fluidity of solutions. These novel scientific methodologies may encompass, but are not limited to, computing supercomplex abstractions, creating simulated realities, and manipulating matter-energy and the space-time continuum itself.