Atombeam uses AI to compact data and could be the future of data transfer... and they already have some major traction.
AtomBeam is a software startup with potentially groundbreaking technology that has the ability to compact data, including the smallest data files generated by machines, by an average of 75%. This quadruples the effective available bandwidth of virtually any IoT device and allows for data transfers to operate 4x faster. This has vast implications across a host of industries such as cloud and data storage, data transfers like those in satellites, and across IoT devices like cell phones and laptops. The software can not only improve storage across the board, but it improves security and extends the range and battery life of many devices.
All of this can be done using existing hardware as all that is required is an update to existing software and save the largest companies in the world billions. One cost analysis can be shown here:
With AtomBeam, each satellite can operate 4x more efficiently, thus allowing for fewer satellites needing to be used and saving hundreds of millions here alone. Companies like Amazon Web Services (AWS) could use the same existing infrastructure but get 4 times more from their existing equipment. Wearables have long been limited by data storage, battery life, and range. This could vastly improve the underperforming technology and all-around bring previously poor-performing technologies back into mainstream use.
Currently, it’s unclear, or there simply doesn’t seem to be one. They have heavily invested into this technology, and the company seems to be experiencing significant traction and good results. Their technology is protected by 9 issued, and 13 pending patents, and they have seen significant traction from several major players. For example, they have been awarded 2
contracts with the United States government and a contract with SAAB, a multi-billion dollar Swedish defense contractor. As well there have been announcements for deals, partnerships, investments, and other agreements at various stages of the game from several companies around the world.
The company is currently looking to raise $4 million to scale the technology, at which point this might become a bit more clear. However, given the results and traction, this might just mean it ends up in nearly every device around the world due to the wide-ranging benefits.
How Does it Work?
The company uses machine learning and AI to compact data by identifying data at the bit level and encoding it. The implications of machine learning are still well into their infancy, and so this area is bound to produce a number of exciting discoveries. Presumably, the company uses an automated (from the AI), drop-in-style, "out-of-band" schema to replace traditionally larger data identifiers with smaller ones, thus reducing overall data size.