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Rakuten Taps Agentic AI to Enhance Ultimate Service

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Japanese eCommerce giant Rakuten is embedding its next-generation agentic artificial intelligence (AI) platform across its ecosystem, aiming to transform its own operations while equipping merchants with advanced new capabilities.

“When I started Rakuten, I believed the internet had the power to change the world, and I committed to building something that could make a real difference,” Chairman and CEO Mickey Mikitani said at the recently held Rakuten AI Optimism 2025 conference. Today, that AI is bringing transformational shifts. “Society is undergoing major changes, and we want to leverage AI not just to adapt, but to grow together.”

The centerpiece is Rakuten AI, an agentic AI platform designed to unify the group’s eCommerce, FinTech, telecom, travel and other services into an AI-powered interface. A rollout on the Rakuten Ichiba eCommerce marketplace is slated for fall.

For example, shoppers can take a photo of a pair of pants and Rakuten AI will find a similar one in the desired price range, the company said. Consumers don’t have to do keyword searches or set filters; Rakuten AI will anticipate their needs based on transaction history and other data.

After the fall rollout to marketplace, “users can expect a significantly enhanced shopping journey,” Caitlin Cai, head of product at AI Lab, Rakuten Asia, told PYMNTS. “While it won’t process payments on behalf of users, it will provide personalized recommendations and direct navigation to relevant product pages based on their queries and data.”

“Rakuten AI isn’t just about answering questions — it’s about supporting your life journey. It’s your ‘brain twin,’ built to humanize technology,” Cai said. The “brain twin” is a user’s “AI-powered alter ego that learns your preferences, acts on your behalf and helps you achieve your goals.”

Cai also said Rakuten AI is both an AI agent and an agentic AI platform that aims to reshape how users interact with Rakuten’s ecosystem, across shopping, entertainment, education and more. It acts as an “intelligent gateway” to unify diverse services into a single, unified interface.

The overarching goal is to provide “omotenashi,” or the peak of service and hospitality in Japanese, according to Rakuten.

See also: GenAI Applications in Retail Transaction Analysis: Industry Trends and Insights

How AI Can Help SMBs

Rakuten developed its own AI model to power its agentic AI capabilities. Not only is it deeply integrated with the company’s services and data, but it also comprehensively understands the Japanese language and culture, the company said in a July 30 press release.

Rakuten AI agents will grow more intelligent with every interaction, according to Cai. This feedback loop strengthens their ability to decode intent, unify fragmented data and drive action with increasing precision.

While the latest version of Rakuten AI is rolling out in the fall to its Ichiba marketplace, merchants already have access to its RMS AI Assistant beta version since last year. The R-Messe inquiry management tool uses AI to draft responses to customer questions; the R-Storefront image editor produces professional product images with customizable backgrounds; AI chatbots interact with shoppers and R-Karte is a data analysis tool that summarizes sales trends for merchants.

Generative AI use is growing. According to a March PYMNTS Intelligence report, 54% of retailers surveyed use gen AI to analyze transaction and payments data for customer segmentation in the past year. Moreover, 73% of retailers are planning to increase their use of gen AI to obtain and analyze transaction and payment data in 2026.

“Many stores with high inquiry volumes or small teams have shared how AI has made things easier and improved their efficiency,” Risa Takahashi, senior manager of product management, said in a blog post.

According to Cai, Rakuten AI uses a hybrid architecture combining Rakuten large language models (LLMs) with optimized models from outside AI providers. It is built with Japanese language optimization in mind and aims to drive cost efficiency by activating only the most relevant components for a query. Future versions will focus heavily on personalization and memory.

“Our goal is to move beyond understanding, toward anticipating user needs and building long-term relationships that enhance the Rakuten experience,” Cai said.

The company also envisions building scenario-based “AI friends,” or persona-driven assistants that can help with more complex tasks such as planning full trips or fitness routines, according to Cai.

“We’re focused on gradually introducing these capabilities to prioritize user convenience and ensure a safe, intuitive experience,” Cai said.

Read more:

Shopify’s Universal Cart Makes AI the New Storefront

Temu Hits Roadblock in Efforts to Compete With Amazon

Alibaba Resharpens Focus on AI and eCommerce



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NBA star Tristan Thompson is bringing artificial intelligence to basketball fans

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Listen and subscribe to Financial Freestyle on Apple Podcasts, Spotify, or wherever you find your favorite podcasts.

Tristan Thompson is well-recognized for his career in the NBA, having played for teams like the Cleveland Cavaliers, the Boston Celtics, and the Los Angeles Lakers, to name a few. He was even part of the team that earned an NBA championship in 2016. But while Thompson’s basketball reputation precedes him, off the court, he’s focusing on his various entrepreneurial ventures.

When asked by Yahoo Finance’s Financial Freestyle podcast host Ross Mac if he would invest his final dollar in artificial intelligence or the blockchain, Thompson picked the industry that’s already projected to be worth $3.6 trillion by 2034.

“You see what Mark Zuckerberg’s paying for all these AI gurus? So I might go AI,” he said (see the full episode above; listen below).

Thompson has already made AI one of his entrepreneurial ventures with the launch of TracyAI, an artificial intelligence that’s meant to offer real-time NBA analysis and predictive insights.

“Imagine a sports analyst or commentator on steroids,” he explained to Mac. “What I mean by that is having all the high-level analytics that you cannot get from NBA.com and ESPN … the analytics are coming from the professional teams. We have certain data and access to certain companies that only professional sports teams have access to. And I was able to pull that data with my resources and put it into the AI agent.”

Thompson saw the venture as “low-hanging fruit,” as it was one of the few areas he hadn’t yet noticed artificial intelligence being worked into. Though AI is slowly finding its way into the sports industry, TracyAI offers basketball fans access to statistics and projections they may not have had through the typical channels, creating a unique fan experience.

Tristan Thompson of the Cleveland Cavaliers warms up before the game against the Portland Trail Blazers at the Moda Center on March 25, 2025, in Portland, Ore. The Cleveland Cavaliers won 122-111. (Alika Jenner/Getty Images) · Alika Jenner via Getty Images

Though Thompson admitted AI has created some of its own controversies, it’s a venture where he’s ready to invest some of his financial resources to capitalize on the industry’s projected rapid growth.

“For me, it’s like, if [AI is] covering so many sectors, how come it hasn’t got into sports?” Thompson said. “This is an opportunity where I can be a visionary and a pioneer … I’ve always had this grind, build-up mentality, so it just migrated easily into Web3. If you look at Daryl Morey, he said he used AI agents to curate his Sixers roster … that just shows you that’s the first domino effect into something great.”



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No, AI Is Not Better Than a Good Doctor

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Search the internet and you will find countless testimonials of individuals using AI to get diagnoses their doctors missed. And while it is important for individuals to take ownership of their healthcare and use all available resources, it is just as important to understand the process behind an AI diagnosis.

If you ask AI to figure out what ails you based on inputting a series of symptoms, the AI will use mathematical probability to calculate the appropriate sequence of words that would generate the most valuable output given the specific prompt. The AI has no intrinsic or learned understanding of what “body,” “illness,” “pain,” or “disease” mean. Such practically meaningful concepts to humans are, to the bot, just letters encountered in the training set frequently paired with other letters.

New research on AI’s lack of medical reasoning

Recently, a team of researchers set out to investigate whether AIs that achieved near-perfect accuracy on medical benchmarks like MedQA actually reasoned through medical problems or simply exploited statistical patterns in their training data. If doctors and patients more widely rely on AI tools for diagnosis, it becomes critical to understand the capability of AI when faced with novel clinical scenarios.

The researchers took 100 questions from MedQA, a standard dataset of multiple-choice medical questions collected from professional medical board exams, and replaced the original correct answer choice with “None of the other answers.” If the AI was simply pattern-matching to its training data, the change should prove devastating to its accuracy. On the other hand, if there was reasoning behind its answers the negative effect should be minimal.

Sure enough, they found that when an AI was faced with a question that deviates from the familiar answer patterns it was trained on, there was a substantive decline in accuracy, from 80% to 42% accuracy. This is because AI today are still just probability calculators, not artful thinkers.

Artful medical practitioners see, hear, feel, and recognize medical conditions in ways they are often not consciously aware of. While an AI would be thrown off by an unfamiliar description of symptoms, good doctors listen to the specific word choices of patients and try to understand. They appreciate how societal factors can impact health, trusting both their own intuitions and those of the patient. They pay close attention to all the presenting symptoms in an open-minded manner, as opposed to algorithmically placing the patient in a generic diagnostic box.

Healing is more than a single task

And yet, algorithmic supremacists are as confident as ever in their belief that human healthcare providers will be replaced by machines. In 2016, at the Machine Learning and Market for Intelligence Conference in my hometown of Toronto, Geoffrey Hinton took the mic to confidently assert: “If you work as a radiologist, you are like Wile E. Coyote in the cartoon. You’re already over the edge of the cliff, but you haven’t yet looked down … People should stop training radiologists now. It’s just completely obvious that in five years deep learning is going to do better than radiologists.”

Seven years later, well past the five-year deadline, Kevin Fischer, CEO of Open Souls, attacked Hinton’s erroneous AI prediction, explaining how tech boosters home in on a single behavior against some task and then extrapolate broader implications based on that single task alone. The reality is that reducing any job, especially a wildly complex job that requires a decade of training, to a handful of tasks is absurd.

As Fischer explains, radiologists have a 3D world model of the brain and its physical dynamics in their head, which they use when interpreting the results of a scan. An AI tasked with analysis is simply performing 2D pattern recognition. Furthermore, radiologists have a host of grounded models they use to make determinations, and, when they think artfully, one of the most important is whether something “feels” off. A large part of their job is communicating their findings with fellow human physicians. Further, human radiologists need to see only a single example of a rare and obscure condition to both remember it and identify it in the future, unlike algorithms, which struggle with what to do with statistical outliers.

So, by all means, use whatever tools you can access to help your wellness. But be mindful of the difference between a medical calculator and an artful thinker.





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Escape from Tarkov is finally coming to Steam ‘soon,’ developer says

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Following news that Escape from Tarkov is escaping its perpetual beta, the pioneering extraction shooter is also about to make its debut on Steam. Nikita Buyanov, head of the Battlestate Games studio that developed Escape from Tarkov, confirmed on X that the game’s Steam page “will be available soon,” only teasing that the full details will come later.

Buyanov’s confirmation comes less than a day after the developer posted a GIF on X of a man spraying steam from an iron. Earlier this month, Buyanov revealed on X that the looter shooter will get its 1.0 release on November 15, 2025, more than eight years after the beta opened up to players in July 2017, and that the studio has plans to port it to consoles. The Steam page for Escape from Tarkov isn’t live yet, and with only vague details to go off of, longtime fans already have burning questions. Most importantly, existing players are eager to know if they will have to buy the game again on Steam and how this change will affect the ongoing cheating problem.

While we don’t have any answers yet, Battlestate Games recently went into damage control mode when it revealed the Unheard Edition of the game that costs $250 and includes a new PvE mode. This move irked longstanding players who previously purchased another premium edition of the game, called the Edge of Darkness, which promised access to all future DLCs. The controversy boiled down to owners of the Edge of Darkness edition claiming they should have access to the new content, but the studio argued that it isn’t classified as DLC. In the end, Buyanov apologized for the debacle and promised the PvE mode would be available for anyone who purchased the Edge of Darkness package.



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