Amboss Research enables Machine Learning to optimize payments on
the Bitcoin Lightning Network
NASHVILLE, Tenn., May 22, 2024
/PRNewswire-PRWeb/ -- Amboss Technologies, a payment operations
leader for Bitcoin's Lightning Network, released novel
research today using graph machine learning to enhance the
efficiency and scalability of bitcoin payments on the
Lightning Network. The study, titled "Channel Balance Interpolation
in the Lightning Network via Machine Learning," reveals new methods
to improve payment success using a combination of graph theory and
machine learning.
Lightning is a critical element to scaling
bitcoin and payment reliability has been its biggest
problem. Our research enables scalable, machine learning methods to
be an answer.
The Bitcoin Lightning Network is a Layer 2 protocol
used by Coinbase, Binance, and Block
(formerly Square) that brings rapid, low-cost transactions to
bitcoin. As more exchanges have adopted the Lightning
Network, payment reliability has been a challenge for the LN.
Traditionally, wallets and exchanges use trial and error "probes"
to find a payment route through Lightning's peer to peer payment
network. Amboss Technologies' latest research, however, introduces
a machine learning approach that could transform how payments are
routed through the network.
"As bitcoin takes center stage in finance, it's
essential that we continue to innovate on bitcoin
scaling technology that further enhances its user experience.
Lightning is a critical element to scaling bitcoin and
payment reliability has been its biggest problem. Our research
enables scalable, machine learning methods to be an answer," said
Jesse Shrader, CEO of Amboss
Technologies.
Collaborating with Emanuele Rossi
from VantAI and Vikash Singh from
Stillmark, the Amboss team evaluated several machine learning
models against traditional heuristic methods. The results were
clear: machine learning not only outperforms existing approaches
but also offers new insights into better payment pathfinding.
"Our research indicates that machine learning models can predict
channel balances with significantly higher accuracy than existing
methods," said Vincent, Senior Data Scientist at Amboss
Technologies. "By integrating these models into the network's
pathfinding algorithms, we can streamline operations and reduce
payment failure rates, making Lightning an even more robust option
for everyday payments."
This breakthrough has substantial implications for users of the
Bitcoin Lightning Network. Improved pathfinding
efficiency could lead to wider adoption of the network, enhancing
the overall utility of Bitcoin as a payment system,
and setting the stage for future ML automation.
Amboss Technologies is committed to further refining these
models and integrating them into real-world applications. The
company plans to incorporate the research findings into its suite
of payment operations tools, which are used by some of the largest
operators in the Lightning Network.
Amboss Technologies is at the forefront of applying machine
learning to one of the most critical issues facing
cryptocurrencies today: scalability. As the Lightning
Network grows, Amboss is well-positioned to become essential for
institutional adoption of the LN.
The full research paper has been published and is available for
review. Amboss Technologies invites interested parties to explore
the detailed findings and discuss integration and collaboration
opportunities.
To learn more about Amboss' research on machine learning-powered
pathfinding, visit https://rpo.dev/pathfinding.
For media inquiries, please contact Phil
LeRoy at (310) 260-7901 or phil(at)melrosepr(dot)com.
About Amboss Technologies
Amboss is a leading provider of payments operations for the
Bitcoin Lightning Network, using machine learning to
offer optimized routing and tools that redefine
decentralized finance. Amboss supports businesses and
consumers in improving connections and payment routes based on
cost, reliability, or reputation as well as enterprise-grade risk
management. Amboss operates Magma, the leading marketplace for
lightning liquidity and non-custodial yield.
Media Contact
Phil LeRoy, Melrose PR, (310)
260-7901, phil@melrosepr.com, https://www.melrosepr.com/
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SOURCE Amboss Technologies