Editor’s Picks: The Most Exciting Tech Advances of 2024

Over the past 12 months, we have seen significant advances in various areas of technology, from electric vehicles TO mixed reality technologiesbut much of the conversation was dominated by artificial intelligence (AI).

While large language models – the current gold standard, which is based on neural networks that power everything from Windows Copilot to ChatGPT – gradually improved in 2024, this was the year that the existential risks of AI became worryingly clear.

Another area poised for dramatic transformation is quantum computingwhere new discoveries were reported every month. Not only are cars getting bigger and more powerful, but they’re also getting more reliable as scientists get closer to over-the-top machines the best supercomputers. Some of the biggest breakthroughs have come in error correction, which is a key problem that must be solved before quantum computers can realize their potential.

And in the world of electronics, scientists have moved closer to a hypothetical component known as “universal memory,” which, if realized, will transform the devices we use every day.

Here are the most transformative technological developments of 2024.

We are closer to understanding the existential risks of artificial intelligence

This year, AI companies released big and better language models, including OpenAI’s o1, the Here genetic mutation prediction model and ESM3 protein sequencing model. We also saw better AI training and processing methods, such as a new tool that accelerates image generation up to eight times and an algorithm that can compress these patterns so that they are small enough to run locally on your smartphone.

But this was also the year that the existential threats associated with artificial intelligence came into focus. In January, a study showed that it is widely used safety training methods failed to eliminate malicious behavior in patterns that have been “poisoned” or engineered to exhibit harmful or undesirable tendencies.

The study, described by its authors as “legitimately scary,” found that in one case, a rogue AI learned to recognize the trigger for its malicious actions and thus attempted to hide its antisocial behavior from its human handlers. They could see what the AI was really “thinking” all the time, of course, but that wouldn’t always be the case in the real world.

We are making a viable path to useful quantum computers

It was a full 12 months quantum computing research. In January, quantum computing company QuEra created a new machine with 256 physical qubits and 10 “logical qubits” – collections of physical qubits linked together by quantum entanglement — which reduces errors by storing the same data in different places. At the time, this was the first machine with built-in quantum error correction. But teams around the world are trying to reduce the error rate in qubits.

The development of markup in error correction was revealed in December when Google scientists announced that they had built a new generation of quantum processing units (QPUs) that have reached a significant milestone in error correction, where as you increase the number of qubits, you correct more errors than you introduce. This will lead to exponential reductions in error as the number of entangled qubits increases.

The new 105-qubit Willow chipwhich is a successor to Sycamore, managed to achieve a stunning benchmark result, solving in five minutes a problem that would have taken a supercomputer 10 septillion years to crack – that’s a quadrillion times the age of the universe.

“Universal memory” is getting closer to reality – this is what it means for the devices we use

While this year brought several innovative computer components – including a new type of data storage that can withstand extreme heatas well as a DNA infused computer chip — some of the greatest advances have come in the development of “universal memory.” This is a type of component that will dramatically increase computing speed and reduce power consumption.

All computers use two types of memory simultaneously: short-term memory such as random access memory (RAM) and long-term storage such as solid state drives or flash memory. RAM is incredibly fast, but requires a constant power supply; all memory stored in RAM is erased as soon as a computer is turned off. SSDs, by contrast, are relatively slow, but can retain information without power.

Universal memory is a third type of memory that combines the best of the first two types – and in 2024, scientists have come closer to realizing this technology.

At the beginning of the year, scientists showed that a new material called “GST467” was a viable candidate for phase-change memory — a type of memory that creates 1’s and 0’s of computational data when switching between high and low resistance states in a glass-like material. When it crystallizes, it represents 1 and releases a large amount of energy. When it melts, it represents 0 and absorbs the same amount of energy. In testing, this material proved faster and more efficient than other candidates for universal memory, such as ULTRARAMthe current leading candidate.

Other candidates are also promising – and bizarre. In April, for example, scientists proposed that a strange magnetic quasiparticle known as a “Skyrmion” may one day be used in universal memory instead of electrons. In the new study, they accelerated the skyrmions from their normal speeds of 100 meters per second (about 225 mph, or 362 km/h)—which is too slow to be used in computing memory—to 2,000 mph (3,200 km /h).

Then, towards the end of the year, the scientists accidentally discovered another material that could be used for phase-change memory. It reduced the energy requirement for data storage by up to a billion times. This breakthrough happened entirely, showing that in the world of science and technology, you may never know how close you are to a major breakthrough.