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Blockchain companies are creating AI chatbots to help developers
Blockchain companies are building AI chatbots to help developers, yet challenges may hamper adoption.
The artificial intelligence (AI) market is becoming one of the fastest-growing industries in the world. According to market research firm Next Move Strategy Consulting, the current AI market is valued at nearly $100 billion and is projected to grow exponentially.
Given this, it comes as no surprise that chatbots using AI are also on the rise. Recent findings from Precedence Research show that the global chatbot market size reached $840 million in 2022.
AI chatbots for Web3 developers in the works
As opportunities around AI and chatbots flourish within various industries, the Web3 sector has also started to capitalize on this trend, with blockchain companies creating AI chatbots to help developers build applications faster and more efficiently.
Aanchal Malhotra, head of RippleX Research — an organization within Ripple focused on the development and growth of the XRP Ledger — told Cointelegraph that RippleX is currently working on building an AI chatbot to which developers of the XRP Ledger can pose queries:
“Rather than rambling through all of the documentation and client libraries, developers will be able to direct their questions to the AI chatbot to get instant answers. This will make the life of developers much easier as it will shorten the time for ideas to become applications.”
Skale Labs — the team behind the Skale blockchain network — is also building an AI-powered chatbot. Jack O’Holleran, co-founder and CEO of Skale Labs, told Cointelegraph that the Skale network has built-in AI and machine learning capabilities that enable developers to run pre-trained AI models within a smart contract.
“AI-driven smart contracts fire without human intervention in a very high volume manner. This allows developers to build fast and effectively,” he said.
O’Holleran shared that Skale’s AI chatbot will soon be released publicly, stating that one of the primary use cases for AI is engineering development support.
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“Devs are now building with record efficiency and productivity thanks to the support of AI. One of the key areas of support is instant access to knowledge of technical and coding documentation,” he said.
Echoing this, Matthew Van Niekerk, CEO and co-founder at SettleMint — a blockchain programming tool — told Cointelegraph that AI tools are becoming essential for developers.
Van Niekerk explained that SettleMint recently added an AI Genie engineering assistant to its platform for rapid smart contract development and quality assurance testing and debugging.
“Our AI Genie is built to help organizations get their blockchain applications to production faster so that they can tap into the $3.1 trillion opportunity enabled through blockchain,” explained Van Niekerk.
Van Niekerk further pointed out that SettleMint’s AI Genie is built to support humans, not replace them. This is important to highlight, as there are looming concerns that AI-powered assistants may eventually replace human workers.
“The tool itself is positioned as an engineering assistant, not an engineer. It is built to abstract away mundane processes and complexities that prevent developers and engineers from focusing on building innovative solutions that will bring a clear return on investment for their businesses,” explained Van Niekerk.
To put this in perspective, William Baxter, chief technology officer and co-founder of tokenization platform Vertalo, told Cointelegraph his firm currently uses chatbots to summarize and present data to internal and external audiences. Baxter believes that assisted learning is one of the most promising general applications for chatbots:
“Instead of searching for topics and combing through the results or relying on a curator, a chatbot lets you consume in summary from huge volumes of information. Paired with web access and using prompts that encourage the inclusion of links to primary sources, this dramatically expands the scope of online research. When learning a new programming language, blockchain, or application, feedback from a chatbot is enormously valuable, even if not entirely correct.”
Challenges may lead to delayed implementation
Although AI-powered chatbots have the potential to help Web3 developers build better, a number of challenges may slow adoption.
For example, while O’Holleran is aware that AI-driven smart contracts may expedite technical development, he pointed out that these applications often require throughput for on-chain execution with predictable and automated spend.
“This could be problematic in a network that has high gas fees and variable fees, as the expected spend could vary dramatically and could accidentally get expensive fast,” he said.
In order to combat this, O’Holleran explained that the Skale network has on-chain fees rather than gas fees, making the total fees lower and certifiably predictable.
Lydia Mark, director of communications at Magma AI — a project building an AI chatbot that provides users with a virtual Web3 technology learning assistant — told Cointelegraph that ethical bias can also be problematic with AI chatbots.
“It becomes really easy for AI systems like Magma to inherit the biases imputed during data training, which in turn could negatively impact an entire ecosystem,” she said. To combat this, Mark shared that Magma AI uses bias detection and mitigation techniques.
Yet, one of the biggest challenges associated with AI chatbots is data privacy and security. Van Niekerk explained that companies building or using AI assistants need to consider internal business policies and government regulations pertaining to privacy.
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“Large enterprises may have restrictions on the use of generative AI technologies due to risks of breaches in data privacy. SettleMint’s AI Genie is intentionally built as an optional tool within the platform so that enterprises only opt in when and if needed,” he said.
Challenges aside, Van Niekerk stated that, overall, AI chatbots are helping ensure that Web3 is more inclusive and accessible to a wide range of developers.
“Knowledge and expertise is now there to instantly support new devs entering the space. Web2 devs can speed up their Web3 learning and skill curve by order of magnitude thanks to AI developer support technology,” he remarked.
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Author: Rachel Wolfson