- The tools were developed on a native authentication mechanism, L402 protocol
- They will make BTC payments easier, faster, and more affordable
Lightning Labs, the developers behind Bitcoin Lightning Network, launched a set of new tools for artificial intelligence to transact in Bitcoin on the platform’s layer-2 solution, Cointelegraph reported.
Faster and cheaper payments
Lightning Labs announced the toolkit on July 6. It will aid OpenAI’s ChatGPT and similar AI tools to interact with the Bitcoin network and hold, send, and receive BTC. According to the developers, this will make payments easier, faster, and more affordable.
With the new tool, AI developers can stop using traditional and often expensive payment rails. It will enable deployment of AI models on the network on a pay-per-use basis as well.
The tools were developed on a Lightning native authentication mechanism called the L402 protocol, which uses Langchain, a library that applies AI to simplify operations. Lightning Labs commented that their new tools can help developers create more easily accessible infrastructure for AI as well as human users.
Problems with current LLMs
Lightning Labs pointed out that current large language models (LLMs) aren’t equipped with native web-based payment mechanisms. Due to this, AI application developers have to rely on credit cards and other traditional payment methods, and the fees are passed on to end users. The team noted that new, rapidly growing intelligent LLMs cannot gain access to fiat payment systems because they aren’t registered with a specific country.
Applications of AI in finance
AI systems are already facilitating transactions by processing payments and transferring funds between accounts. They can automate tasks such as bill payments, online purchases, and money transfers.
AI algorithms can analyze market data, identify patterns, and execute trades on behalf of investors. AI-powered trading systems can operate in real-time and make decisions based on predefined strategies.
The risks
AI systems are not immune to errors or malfunctions. Bugs in the code, hardware failures, or data discrepancies can lead to incorrect or unexpected transaction outcomes. These errors can result in data leaks, financial losses or incorrect account balances.
When AI tools handle financial transactions, it can be challenging to assign accountability and responsibility. In the event of errors or fraudulent activities, determining who is responsible—whether it’s the AI system, its developers, or the organization utilizing the AI—can be complex and legally challenging.
