GT Protocol

Steve

James

Disclosure: The views and opinions expressed here belong solely to the author and do not represent the views and opinions of crypto.news’ editorial. 
Long before OpenAI <a href="https://www.businessinsider.com/history-of-openai-company-chatgpt-elon-musk-founded-2022-12#openai-released-an-early-demo-of-chatgpt-in-november-2022-and-the-conversational-chatbot-quickly-went-viral-on-social-media-1" target="_blank" rel="">introduced</a> the world to ChatGPT’s powerful artificial intelligence (AI) model, rudimentary automation were deeply rooted in the financial world. 
In 1978, for instance, award-winning mathematician James Simons <a href="https://www.forbes.com/sites/forbesdigitalcovers/2019/11/08/jim-simons-the-man-who-solved-the-market-gregory-zuckerman-book-excerpt/" target="_blank" rel="">founded</a> Renaissance Technologies, a quantitative hedge fund, by leveraging data to analyze statistical probabilities for securities price trends. The firm’s signature Medallion fund was established in 1988 and would enjoy the best <a href="https://ofdollarsanddata.com/medallion-fund/" target="_blank" rel="">record</a> in investing history. 
 You might also like: <a href="https://crypto.news/elons-fight-for-open-source-agi-ignores-users-and-ethical-ai-training-opinion/" rel=""> Elon’s fight for ‘open-source AGI’ ignores users and ethical AI training | Opinion </a> 
Shortly after Simons introduced quantitative investing, <a href="https://www.sciencedirect.com/science/article/abs/pii/S0957417402000271" target="_blank" rel="">expert systems</a> became the norm within the banking and financial industry to mitigate human error risks. Eventually, they were used to formulate financial plans for individuals with relatively high incomes.&nbsp; 
More recently, machine learning, natural language processing (NLP), and interactive chatbots have been leveraged to help investment firms, banks, credit bureaus, and other financial institutions formulate predictive analyses, combat fraud, understand customer needs, streamline customer support, and more.&nbsp; 
Now in the “<a href="https://www.weforum.org/podcasts/radio-davos/episodes/ai-chat-gpt-haptik/" target="_blank" rel="">Golden Age of AI</a>,” powerful new AI models are ushering in an array of disruptive tools and solutions with the potential to redefine the financial services industry. However, as most industries eagerly implement AI solutions to streamline internal processes and provide better customer service, the once-innovative financial sector has lagged, <a href="https://www.forbes.com/sites/joemckendrick/2023/02/24/artificial-intelligence-opens-up-the-world-of-financial-services/" target="_blank" rel="">according</a> to Teddy Flo, a general counsel of Zest AI.&nbsp; 
But this is starting to change partly thanks to the embrace of AI in the crypto and blockchain industry. 
We’ve already seen numerous AI-powered crypto platforms and projects leveraging AI for various reasons. Platforms like <a href="https://crypto.news/what-is-fetch-ai-explained/" rel="">Fetch.ai</a>, a machine learning platform designed to automate tasks such as data processing and trading, and Bittensor, a decentralized network enabling the spread of AI knowledge, showcase ingenuity at the intersection of blockchain and AI.&nbsp; 
Now, mainstream finance may readily onboard the next generation of AI. To this point, cloud-native software as a service (SaaS) investment management platform FundGuard recently <a href="https://www.bloomberg.com/news/articles/2024-03-25/ai-accounting-startup-fundguard-raises-100-million-in-new-funds" target="_blank" rel="">raised</a> $100 million in a Series C round thanks to its intuitive platform designed to assist asset managers and their service providers in managing mutual funds, exchange-traded funds (ETFs), hedge funds, pensions, and other financial products. The platform also supports digital transformation, automating processes, AI-based insights, and cloud migration, often serving as the core system for many financial institutions.&nbsp;&nbsp; 
Likewise, thanks to abundant structured and unstructured data, affordable computing power, and vastly improved neural networks, complex algorithms now provide the foundation for more accessible and more efficient investment options.&nbsp; 
As investors seek innovative ways to gain an edge in financial markets, AI’s transformative capabilities are now being leveraged to support investment strategies and decision-making, highlighted by legendary tech entrepreneur Steve Cohen <a href="https://www.cnbc.com/2024/06/18/steve-cohen-is-set-to-make-a-big-push-into-investing-in-ai.html" target="_blank" rel="">launching</a> an AI-oriented hedge fund featuring algorithmic-based strategies and decisions.&nbsp; 
Similar approaches have been taking place within crypto. Since engaging with and making informed decisions on digital assets requires a high degree of technical comprehension, the AI-powered crypto trading platform GT Protocol uses advanced algorithms to serve as users’ “personal web3 investment and trading assistant.” 
Catering to all levels of investors, GT Protocol’s platform features an all-encompassing conversational interface to provide analyses and craft investment strategies and trading recommendations—a much-needed helping hand for those with varying expertise and goals. 
Whether you’re in traditional or decentralized finance, we can expect a growing demand for simplified investment solutions and reliable strategies. AI enables the industry to function better while providing customers with easy, pain-free, and smart investment solutions. 
At this point, it doesn’t matter if an institution is a DAO, dApp, main-street bank, or international investment firm, AI use is rapidly becoming a prerequisite to remaining competitive.&nbsp; 
 Read more: <a href="https://crypto.news/decentralized-ai-leveraging-blockchain-for-a-more-equitable-future-opinion/" rel=""> Decentralized AI: leveraging blockchain for a more equitable future | Opinion </a>

AI investment advice is on the way: Is crypto ready? | Opinion

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