Taiwan’s central bank is looking into implementing blockchain technology in order to improve its operations.
According to news from Finance Magnates, Yang Chin-long, the new governor of the bank, spoke about utilizing new technology — including artificial intelligence, Big Data and blockchain — in the country’s banking system during his inauguration ceremony.
“Apart from closely monitoring the challenges that financial technology may add to the bank, it will also make good use of supervisory techniques to enhance its overall prudential supervision,” according to a rough translation of his speech. “Big Data and even artificial intelligence and other technologies [will] help our bank to predict and analyze economic and financial conditions more effectively.”
“In addition, the bank will also try to explore the feasibility of enhancing the security and efficiency of payment systems using decentralized ledger technology,” he said.
He added that the new technology could transform the country’s financial landscape, while also having a serious impact on its monetary policy and payment industry.
In Oct. 2017, Taiwan’s Financial Supervisory Commission Chairman Wellington Koo spoke before parliament, asserting that Taiwan should take its cues from Japan, which provides licenses to cryptocurrency exchanges. That same month, then-Governor of Taiwan’s Central Bank, Perng Fai-nan, said bitcoin should be added to the notification system in the country in order to prevent money laundering.
Banks around the world are also looking into the implementation of blockchain technology for services like cross-border payment transfers and data management. Earlier this month, UAE Exchange, one of the largest payment providers in the Middle East, announced that it partnered with Ripple to join its blockchain for cross-border payments. In addition, Ripple also signed a deal with the Saudi Arabian Monetary Authority, enabling banks in the Kingdom of Saudi Arabia to work with its cross-border payments technology.
The AI world is hitting our wallets with prices that might make even Wall Street veterans do a double take. While banks have long charged hefty fees for premium services, artificial intelligence (AI) companies are now joining the high-price club with some truly jaw-dropping figures. What happened to all that talk about AI making things cheaper and more efficient?
OpenAI, the company behind ChatGPT, is planning to launch AI “agents” with price tags that might make you spill your coffee. According to recent reports, it’s eyeing a tiered pricing plan that starts at $2,000 monthly for basic agents aimed at “high-income knowledge workers.” Need something a bit more sophisticated for software development? That’ll be $10,000 per month. And if you want the top-tier, PhD-level research agent, prepare to shell out an astonishing $20,000 every month.
To put that in perspective, OpenAI’s current premium offering, ChatGPT Pro, costs $200 monthly and is reportedly still losing money. The jump from $200 to $20,000 is a 100-fold increase. OpenAI CEO Sam Altman has apparently acknowledged they need to “charge much more than $200 a month” for these advanced agents. The company is banking on these agent products to generate between 20% and 25% of its long-term revenue.
SoftBank seems convinced these prices make sense — the investment company has already committed to spend $3 billion on OpenAI’s agents this year alone. The justification? These AI assistants supposedly do work comparable to highly paid professionals.
The pricing inconsistency across the AI landscape is enough to give you whiplash. Some companies are stuffing AI features into existing products and bumping prices, while others charge only when the AI completes a task.
For comparison, a coding agent from startup Cognition called Devin costs about $500 monthly — significantly less than OpenAI’s planned $10,000 offering for similar functionality. This kind of price variation leaves customers scratching their heads about what’s reasonable.
Whatever approach companies take, one thing is clear: AI doesn’t come cheap. The massive data centers powering these systems cost between $500,000 and over $1 billion annually, according to McKinsey & Company. Those specialized AI chips? They run between $10,000 and $30,000 each. A single server rack packed with these chips can easily cost over $500,000 before even turning on the power.
The million-dollar question (sometimes literally): Are these AI services actually worth these premium prices? Companies claim these tools can replace work done by highly paid professionals. A Ph.D.-level research agent at $20,000 monthly costs about the same as hiring a human researcher with advanced credentials.
Defenders of these prices point out that AI assistants work 24/7 without breaks or benefits. They don’t quit unexpectedly or need training when you change projects. They can potentially process information faster than any human researcher.
However, skeptics wonder if these theoretical advantages really justify the sky-high costs. Can an AI agent perform complex tasks requiring deep understanding and original thinking? With their regulatory requirements, financial institutions need to be especially careful about relying too heavily on systems that sometimes generate incorrect information.
As artificial intelligence transforms from a cool experiment to an essential business tool, we’re witnessing a gold rush mentality in pricing. While there are legitimate costs behind developing and running these systems, the current prices seem to include a healthy dose of “what the market will bear” thinking.
Considering that, according to PYMNTS Intelligence data, the same market is starting to report positive returns on investments (ROI) on its GenAI investments, it might be willing to bear the higher costs.
Will these prices eventually come down as competition increases and technology improves? History suggests they might. But for now, if you want the cutting edge of AI, be prepared for some serious sticker shock. The smartest approach might be testing these premium-priced tools selectively while keeping a healthy skepticism about whether that shiny new AI assistant is really worth its weight in digital gold.
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