From: mk_thisisit
Modern electronics, including computers, fundamentally rely on the properties of electrons, primarily their negative or positive charge, to provide power and process information [00:01:04]. Current electronic devices utilize transistors built from materials like silicon [00:07:00], enabling billions of transistors on a single square centimeter [00:08:30].
Unprecedented Progress and Impending Limits
Over the past several decades, the number of transistors on integrated circuits has increased by an astonishing 10 million times [00:08:24]. This miniaturization has led to transistors that are not only smaller (currently around 5 nanometers, 10,000 times smaller than a human hair’s cross-section) [00:09:13], but also faster, more energy-efficient, and cheaper [00:11:21]. The price of a transistor is now about 100 times smaller than printing one letter in a book [00:11:38].
Moore’s Law and Saturation
Moore’s Law states that the number of transistors per unit area doubles every 18 months [00:12:30]. This law held true for about 40 years [00:12:37]. However, current AI systems and electronic architectures are reaching physical limits [00:09:38]. The spaces between transistors are now measured in atoms [00:08:05], making further miniaturization extremely difficult [00:13:07]. Consequently, the speed of computers, which once grew rapidly from megahertz to gigahertz, has largely stopped increasing [00:09:44]. This indicates that certain parameters in progress are becoming saturated [00:09:54].
The Need for New Architectures
Given these limitations of artificial intelligence and computing, there’s a strong belief that the current computer architecture, which originated during World War II, needs to change after 75 years [00:10:06]. This architecture, though historically significant (with the transistor’s operation patented by Juliusz Lilienfeld in 1924) [00:10:26], is becoming less applicable [00:10:09].
Instead of focusing solely on miniaturization, research is exploring new approaches [00:08:07]. This involves:
- Changing the information carrier: Traditionally, calculations use the electron’s charge. However, just as communication shifted from electrons (wires) to photons (optical fibers) [00:14:12], future information processing may also change its carrier [00:14:53].
- Exploring electron spin: Electrons possess another property called “spin” [00:01:16]. This spin, or magnetic moment, can be used for recording information in magnetic memories [00:02:00]. The ambition is to use these spins for processing information, leading to the field of semiconductor spintronics [00:02:54].
Spintronics as a Potential Solution
Spintronics is seen as a promising path for future data processing [00:01:26]. By applying voltage to a magnetic semiconductor, its magnetic properties can be changed, which are essential for recording and processing information [00:07:04].
One application involves using individual spins for information processing [00:04:17]. A single electron in a quantum dot can have a spin [00:03:07]. The interaction between spins in neighboring quantum dots allows for information processing, representing a basic model of a quantum computer [00:03:30].
Furthermore, spintronics can revolutionize dynamic random-access memory (DRAM) and cache memories [00:15:21]. Current dynamic memories require constant energy to maintain information, which is lost when power is disconnected [00:15:41]. Using magnetic materials, similar to those in disk drives, for fast cache memory can significantly reduce the energy needed for information storage and processing [00:16:03].
A particularly interesting development involves antiferromagnets. While ferromagnets (used for a long time in magnetic memories) generate external magnetic fields, antiferromagnets have spins that compensate each other, resulting in no external magnetic field [00:17:09]. This allows for greater density because individual bits (spins) do not interfere with neighboring bits, reducing “crosstalk” [00:17:48]. This makes them highly suitable for memory applications [00:17:35].
The Future of Computing: Quantum and Topological Approaches
The field of information processing is in a state of flux, with no single winning method yet identified [00:18:19]. Beyond spintronics, other approaches for quantum computers and their challenges include using superconductors, trapped ions, or neutral atoms on networks [00:18:37]. While superconductors are currently the most advanced for quantum computers [00:19:44], they face engineering challenges in the development of quantum computers due to quantum non-locality and sensitivity to environmental disturbances like electromagnetic noise [00:20:18]. This “decoherence” causes quantum phenomena like interference to disappear [00:23:53].
A promising alternative is the use of topological materials. Topology, distinct from geometry, focuses on properties that are stable against small deformations [00:26:26]. If spins are arranged in a “non-trivial topological way” (e.g., with a non-zero topological index), the structure becomes more stable and less susceptible to disturbances [00:27:08]. This stability is crucial for creating robust information carriers [00:28:23]. Microsoft, for instance, is actively developing topological quantum computers, as these materials are less sensitive to noise and decoherence [00:28:34].
This era marks a shift from relying solely on miniaturization within existing architectures to exploring entirely new physical principles and material properties to advance information processing.