Here are a few of the emerging technologies that promise to keep computing performance rocketing ahead:

In-memory computing. Throughout computing history, the slowest part of processing has been getting the data from the hard disks where it’s stored to random access memory (RAM), where it can be used. A lot of processor power is wasted simply waiting for data to arrive. By contrast, in-memory computing puts massive amounts of data into RAM where it can be processed immediately. Combined with new database, analytics, and systems designs, it can dramatically improve both performance and overall costs.

Graphene-based microchips. Graphene — one molecule thick and more conductive than any other known material (see The Super Materials Revolution) — can be rolled up into tiny tubes or combined with other materials to move electrons faster, in less space, than even the smallest silicon transistor. This will extend Moore’s Law for microprocessors a few years longer.

Quantum computing. Even the most sophisticated conventional computer can only assign a one or a zero to each bit. Quantum computing, by contrast, uses quantum bits, or Qubits, which can be a zero, a one, both at once, or some point in between, all at the same time. (See this explainer video from the Verge for a surprisingly understandable overview.) Theoretically, a quantum computer will be able to solve highly complex problems, like analyzing genetic data or testing aircraft systems, millions of times faster than currently possible. Google researchers announced in 2015 that they had developed a new way for qubits to detect and protect against errors, but that’s as close as we've come so far.

Molecular electronics. Researchers at Sweden’s Lund University have used nanotechnology to build a “biocomputer” that can perform parallel calculations by moving multiple protein filaments simultaneously along nanoscopic artificial pathways. This biocomputer is faster than conventional electrical computers that operate sequentially, approximately 99 percent more energy-efficient, and cheaper than both conventional and quantum computers to produce and use. It’s also more likely to be commercialized soon than quantum computing is.

DNA data storage. Convert data to base 4 and you can encode it on synthetic DNA. Why would we want to do that? Simple: a little bit of DNA stores a whole lot of information. In fact, a group of Swiss researchers speculate that about a teaspoon of DNA could hold all the data humans have generated to date, from the first cave drawings to yesterday’s Facebook status updates. It currently takes a lot of time and money, but gene editing may be the future of big data: Futurism recently reported that Microsoft is investigating the use of synthetic DNA for secure long-term data storage and has been able to encode and recover 100 percent of its initial test data.

Neuromorphic computing. The goal of neuromorphic technology is to create a computer that’s like the human brain—able to process and learn from data as quickly as the data is generated. So far, we’ve developed chips that train and execute neural networks for deep learning, and that’s a step in the right direction. General Vision’s neuromorphic chip, for example, consists of 1,024 neurons — each one a 256-byte memory based on SRAM combined with 3,000 logic gates — all interconnected and working in parallel.

Passive Wi-fi. A team of computer scientists and electrical engineers at the University of Washington has developed a way to generate Wi-fi transmissions that use 10,000 times less power than the current battery-draining standard. While this isn’t technically an increase in computing power, it is an exponential increase in connectivity, which will enable other types of advances. Dubbed one of the 10 breakthrough technologies of 2016 by MIT Technology Review, Passive Wi-fi will not only save battery life, but enable a minimal-power Internet of Things, allow previously power-hungry devices to connect via Wi-fi for the first time, and potentially create entirely new modes of communication.