Introduction:
In recent years, there has been an explosive growth in the demand for computing power, driven by the increasing complexity of modern artificial intelligence and machine learning models. Traditional electronic processors are reaching their limits in terms of power consumption and performance, leading to a search for new technologies that can offer significant improvements. One such technology that has been gaining attention in recent years is photonic processors, which use light instead of electricity to perform computations. Lightmatter AI is one company at the forefront of this exciting new field, with their recent Series 113m funding round raising $80 million to help bring their photonic processors to market.
Background:
Lightmatter AI was founded in 2017 by a group of researchers from MIT and Harvard, including Nicholas Harris, Thomas Graham, and Darius Bunandar. The company’s goal is to develop photonic processors that can perform computations at significantly faster speeds and with lower power consumption than traditional electronic processors. Photonic processors use light instead of electricity to perform calculations, which allows for faster communication between different components and lower energy consumption.
Series 113m Funding Round:
In February 2021, Lightmatter AI announced that it had raised $80 million in a Series 113m funding round led by Viking Global Investors, with participation from GV (formerly Google Ventures) and Matrix Partners. The funding will be used to accelerate the development of the company’s photonic processors and bring them to market.
Photonic Processors:
Photonic processors are an emerging technology that has the potential to revolutionize computing. Traditional electronic processors use electrical signals to transmit information, which leads to a number of limitations, including high power consumption and slow communication between different components. Photonic processors, on the other hand, use light to perform calculations, which allows for much faster communication between different components and lower power consumption.
Lightmatter AI’s photonic processors use a technology called “optical computing,” which uses light to perform logical operations. The company’s processors are based on a new type of chip architecture called a “photonic tensor core,” which is designed specifically for deep learning applications. The photonic tensor core can perform matrix multiplications, which are a key part of many deep learning algorithms, much faster than traditional electronic processors.
Advantages of Photonic Processors:
There are several advantages to using photonic processors for computing. First and foremost, they offer much faster speeds than traditional electronic processors. Because light travels much faster than electricity, photonic processors can perform calculations at much higher speeds. Additionally, photonic processors offer lower power consumption, as they do not generate as much heat as traditional electronic processors.
Another advantage of photonic processors is that they are well-suited for parallel computing. Because light can be split and directed to multiple components simultaneously, photonic processors can perform many computations in parallel, which can significantly speed up certain types of calculations. This makes them particularly well-suited for deep learning applications, which often involve large matrix multiplications.
Challenges and Future Outlook:
Despite the many advantages of photonic processors, there are also several challenges that must be overcome in order for them to become widely adopted. One major challenge is the need for specialized hardware and software to support photonic processors. Because they are fundamentally different from traditional electronic processors, many existing software tools and programming languages may not work with photonic processors.
Another challenge is the cost of manufacturing photonic processors. Because they are still an emerging technology, there are currently only a few companies that are capable of producing them at scale. This limits the availability of photonic processors and makes them more expensive than traditional electronic processors.
Despite these challenges, the future outlook for photonic processors is promising. As the demand for computing power continues to grow, there will be a need for new technologies that can offer significant improvements over traditional electronic processors. Photonic processors offer a potential solution to this problem, with their ability to perform calculations at much higher speeds and with lower power consumption.
In addition to their use in computing, photonic processors also have applications in other fields, such as telecommunications and sensing. For example, they could be used to improve the performance of fiber optic networks or to create more accurate sensors for scientific and industrial applications.
Conclusion:
Lightmatter AI’s recent Series 113m funding round is a testament to the potential of photonic processors to revolutionize computing. By using light instead of electricity to perform calculations, these processors offer faster speeds, lower power consumption, and better performance for certain types of calculations. While there are still challenges to overcome in terms of hardware and software support, the future outlook for photonic processors is promising. As the demand for computing power continues to grow, photonic processors could play an important role in meeting this demand and enabling new applications in fields such as artificial intelligence, telecommunications, and sensing.
