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Nubank To Continue Leveraging AI To Enhance Digital Financial Services In Latin America

Nubank (NYSE: NU) is reportedly millions of customers across Latin America. Recently, the company’s Chief Technology Officer, Eric Young, shared his vision for leveraging artificial intelligence to fuel Nubank’s global expansion and improve financial services.
During a recent discussion, Young outlined how AI is not just a tool but a cornerstone for operational efficiency, customer-centric growth, and democratizing access to personalized finance.
With a career that includes work at Amazon in the early 2000s, Young brings a philosophy of prioritizing customer experience.
At Amazon, he witnessed firsthand how technology could transform user experiences, a mindset he now applies to Nubank’s mission. “If not us, then who?”
Young posed rhetorically during the videocast, underscoring Nubank’s unique position to disrupt traditional banking.
Founded in Brazil in 2013, Nubank has positively impacted the financial sector by prioritizing financial inclusion and superior customer service, challenging legacy banks with its digital-first approach.
Under Young’s leadership, Nubank’s priorities are clear: enhance agility, expand internationally, and harness AI to serve customers better.
He emphasized the need for cross-functional collaboration, particularly with the product and design teams.
This includes partnering with Nubank’s recently appointed Chief Design Officer (CDO), Ethan Eismann, to iterate quickly on new features.
By fostering a culture of testing and learning, Young aims to deliver products that not only meet but exceed user expectations, ultimately capturing a larger market share.
This involves deepening engagement with existing users, attracting new ones, and venturing into underserved markets where financial services remain inaccessible.
Central to Young’s strategy is AI’s transformative potential.
Nubank’s 2024 acquisition of Hyperplane, an AI-focused startup, marks a pivotal step in this direction.
Young highlighted how advanced language models—such as those powering ChatGPT and Google Gemini—can bridge the gap between everyday users and elite financial advisory services.
These models excel at processing vast amounts of data, including transaction histories, to offer hyper-personalized recommendations.
Imagine an AI that automates budgeting, predicts spending patterns, and suggests investment opportunities tailored to an individual’s financial profile, all without the hefty fees of traditional private banking.
Young drew a parallel to the exclusivity of high-end services.
Historically, AI-driven private banking was reserved for the ultra-wealthy, but Nubank’s vision is to make it ubiquitous.
“We’re democratizing access to hyper-personalized financial experiences.”
By analyzing user data ethically and securely, AI can empower customers from all segments—whether a small business owner in Mexico or a young professional in Colombia—to manage their finances with the precision once afforded only to elites.
This aligns with Nubank’s core ethos of inclusion, ensuring that technology serves as an equalizer rather than a divider.
Looking ahead, Young sees AI as the engine for Nubank’s platformization efforts, enabling scalable solutions that support international growth.
As Nubank eyes further expansion beyond Brazil, Mexico, and Colombia, AI will streamline operations, from fraud detection to customer support chatbots, reducing costs while enhancing reliability.
Yet, Young cautioned that success hinges on responsible implementation—prioritizing privacy, transparency, and human oversight to build trust.
In an era where fintechs aggressively compete for market share, Eric Young’s insights position Nubank not just as a bank, but as a key player in AI-powered financial services.
By blending technological prowess with a focus on the customer, Nubank is set to transform money management, making various services more accessible to consumers.
As Young basically put it, the question isn’t whether AI will change finance—it’s how Nubank will aim to make a positive impact.
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Artificial intelligence is becoming essential to job security – CBS News
AI Research
How Skywork AI’s Multi-Agent System Simplifies Complex AI Tasks

What if there was a tool that didn’t just assist you but completely redefined how you approach complex tasks? Imagine a system that could seamlessly browse the web for critical data, write detailed reports, and even build custom tools on the fly, all while collaborating with specialized agents designed to tackle specific challenges. Enter the Deep Research Agent, a new innovation by Skywork AI. This isn’t just another AI framework; it’s a multi-agent powerhouse that combines innovative models, dynamic tool creation, and unparalleled adaptability to handle tasks with precision and efficiency. Whether you’re a researcher, developer, or strategist, this system promises to transform how you work.
Prompt Engineering explain the intricate architecture behind the Deep Research Agent, including its Agent Orchestra framework, which enables seamless collaboration between specialized agents. You’ll discover how this open source tool doesn’t just solve problems but evolves to meet unique challenges by creating and managing tools in real-time. From automating web browsing to generating actionable insights, the possibilities are vast, and the implications for industries ranging from tech to media are profound. By the end, you might just find yourself rethinking what’s possible in task automation.
Deep Research Agent Overview
TL;DR Key Takeaways :
- The Deep Research Agent by Skywork AI is an open source, multi-agent framework designed for precision and adaptability, capable of handling tasks like web browsing, document generation, data analysis, and tool synthesis.
- The “Agent Orchestra” framework enables collaboration among specialized agents, dynamically creating and managing tools to address unique and complex challenges across industries.
- Specialized agents, such as the Deep Analyzer, Deep Researcher, Browser Use Agent, and MCP Manager, work together to deliver efficient and precise results for diverse tasks.
- A key feature is dynamic tool creation, allowing the system to synthesize, validate, and register new tools when existing ones are insufficient, making sure continuous adaptability and tailored solutions.
- The framework integrates multiple AI models, supports local and remote tools, and is open source on GitHub, making it accessible and customizable for various applications, from document creation to market research and API integration.
The Agent Orchestra Framework: A Collaborative Core
At the heart of the Deep Research Agent lies the “Agent Orchestra,” a hierarchical framework that orchestrates the collaboration of specialized agents. Each agent is carefully designed to excel in specific tasks, working in unison to tackle complex challenges. The framework’s adaptability stems from its ability to dynamically create and manage tools, making sure it can address unique requirements, even when existing tools are insufficient. This dynamic approach allows the system to evolve continuously, offering tailored solutions to meet the demands of various industries.
Specialized Agents: Precision in Action
The Deep Research Agent employs a suite of specialized agents, each functioning as an expert in its domain. These agents work collaboratively to deliver precise and efficient results:
- Deep Analyzer Agent: Performs in-depth analysis to extract actionable insights from diverse data types, allowing informed decision-making.
- Deep Researcher Agent: Synthesizes information from extensive research, producing detailed reports, summaries, and comprehensive insights.
- Browser Use Agent: Automates web browsing to streamline data collection, making sure efficient and accurate information extraction.
- MCP Manager Agent: Oversees tool discovery, registration, and execution using the MCP protocol, making sure seamless tool integration and management.
Skywork AI’s Multi-Agent System : Browses, Writes and Builds Tools
Here is a selection of other guides from our extensive library of content you may find of interest on multi-agent framework.
Dynamic Tool Creation: Tailored Solutions
A standout feature of the Deep Research Agent is its ability to dynamically create tools. When existing tools fail to meet specific requirements, the system synthesizes new ones, validates their functionality, and registers them for future use. This capability ensures the framework remains adaptable and responsive to evolving needs, providing customized solutions for even the most intricate challenges. By continuously expanding its toolset, the system enables users to tackle tasks with unparalleled efficiency and precision.
Applications Across Industries
The versatility of the Deep Research Agent makes it an invaluable tool across a wide range of industries and tasks. Its applications include:
- Document creation, including the generation of Word documents, PDFs, and presentations tailored to specific needs.
- Data analysis, such as trend visualization, market insights, and real-time updates to Excel spreadsheets.
- Web development and comprehensive market research to support strategic decision-making.
- API integration for custom workflows, allowing seamless automation and enhanced productivity.
Technological Features: Innovation at Its Core
The Deep Research Agent incorporates advanced technologies to deliver exceptional performance and flexibility. Key features include:
- Integration of multiple AI models: Combines the strengths of OpenAI, Google, and open-weight models to achieve superior results.
- Support for local and remote tools: Offers maximum adaptability by seamlessly integrating tools across different environments.
- Open source availability: Accessible on GitHub, allowing users to customize and experiment with the framework to suit their specific needs.
Skywork AI’s Broader Vision
Skywork AI’s innovations extend beyond the Deep Research Agent, showcasing a commitment to advancing AI capabilities across various domains. The company’s other new projects include:
- 3D world generation from single images, transforming virtual environments and simulations.
- Open source multimodal reasoning models designed for complex problem-solving and decision-making.
- Infinite-length film generative models, pushing the boundaries of creative AI applications in media and entertainment.
- Image generation, understanding, and editing tools for diverse creative and analytical purposes.
Performance and Accessibility: Designed for Users
The Deep Research Agent has demonstrated exceptional performance, achieving high scores on GAIA and humanity benchmark tests. Its ability to deliver state-of-the-art results across various applications underscores its reliability and efficiency. For users, the framework offers API access for tasks such as document creation and data analysis. To encourage adoption, free credits are provided for initial testing, with tiered packages available for extended use. This accessibility ensures that organizations and individuals can use the system’s capabilities without significant barriers.
Setting a New Standard in Task Automation
The Deep Research Agent represents a fantastic advancement in multi-agent frameworks, combining precision, adaptability, and scalability. By integrating advanced AI models, dynamic tool creation, and open source accessibility, it establishes a new benchmark for task-solving systems. Whether automating workflows, conducting in-depth research, or exploring creative applications, this framework offers a robust and versatile solution tailored to meet the demands of modern industries.
Media Credit: Prompt Engineering
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AI Research
The good, the bad and the worrisome: UW professor explains how AI is shaping our lives

As an educator, Lisa Mitchell uses artificial intelligence (AI) to “help think of ideas,” which she then edits into something that she wants and can use for her classes.
“[AI] can save us time from doing some tasks as long as we’re knowledgeable enough to edit those ideas that it provides,” she told CBC News on a sunny day in downtown Kitchener last week.
AI can be a very useful application, said Joel Blit, who is an associate professor of economics at the University of Waterloo.
Blit is also the co-founder and co-director of the Canadian AI Adoption Initiative. He said that after ChatGPT was launched around three years ago, AI became a “fundamentally democratic technology.”
“Now people can use AI, interact with AI in natural language,” he said. “Every Canadian can use the technology to do things faster, better, more efficiently, or even do things that they weren’t able to do before.”
But while AI is useful in her line of work, Mitchell says she’s worried about the risks surrounding its growing use — a worry that Blit said he recognizes.
To Blit, these worries about AI are valid. But as an expert who works with executives and leaders in government to “seize the benefits of AI,” he says we need to find the balance between regulating AI and using it for its strengths.
AI is transforming the way people operate
Julia Guenther said she uses AI “quite a bit,” especially in condensing information in a way that would make it easily understandable for a wide range of users.
Guenther also spoke to CBC News during her lunch break in downtown Kitchener She said she uses AI to do some translating tasks, but that she has someone else look at it afterwards.
“It still has to get reviewed by an individual who is familiar with the language it’s translated to,” she said. “But it does make it easier and simpler for them, at least if they have a starting point from what it is that I provided.”
These are just some of the applications of AI that people know about. Blit said many people don’t realize that digital assistants like Siri and Alexa also use AI. Even Google Maps use AI as well, he explained.
Apart from these common applications, Blit says AI is also being utilized for things like customer service, HR tasks, marketing, and even healthcare.
“My wife is a family doctor and she’s been using the AI scribe… it saves her probably about 20 per cent of her time,” he said.
“It’s a great example because it means that you can be fully engaged with the patient instead of writing as the patient is explaining.”

But while AI can help make previously tedious tasks more convenient, relying too much on AI will result in some undesired effects.
On an individual level, Blit explains that relying on AI could affect people’s ability to organize their thoughts.
“I think, maybe, we do start to lose a little bit of our ability to organize our thoughts if AI is doing it for us,” he said.
But at the same time, Blit says using AI will not cause people to just suddenly lose the ability to think.
Blit compares the situation with AI to using calculators, saying that people did not lose the capacity to do arithmetic just because the calculator was invented.
“We now focus on other aspects other than arithmetic because we have the calculator,” he said. “It’s just going to be the same thing with the AI… we’re going to do less of the things that AI does well, and more of the things that it doesn’t do as well.”
A ‘super intelligence’ in the next 20 years
In 2024, British-Canadian computer scientist Geoffrey Hinton told CBC News that research suggests that there is about a 50 per cent chance a “super intelligence” will be developed in the next 20 years.
“We will make things smarter than ourselves,” Hinton said. “It’s mainly a question of whether governments can regulate the big companies so that they develop AI safely.”

Hinton is often lauded as one of the “godfathers of AI.” He says the world’s governments need to “force the big companies to do more research on how to keep these things safe when they develop them.”
Blit agrees that AI needs to be regulated because there are no specific regulations for it. He says currently, there are only “general regulations that would apply to many uses of AI.”
But at the same time, Blit says there is a need to ensure that AI is not being over-regulated.
“If we do, we are going to stifle the technology, we’re going to stifle the innovation that frankly, as a country, we need,” he said.
AI will affect jobs; Blit, Québec study
Another common question surrounding the growing adoption of AI in the workplace is how it will affect people’s jobs.
Blit recognizes that AI will bring about change, and says the transition period is “going to be difficult,”
“You can’t put your head in the sand and pretend that this is not happening because it is going to happen,” he said.
In January, the Institut du Québec, in collaboration with the Future Skills Centre, conducted a study on AI’s impacts on jobs in Québec. The study found that in the next 10 years, an estimated 800,000 Québec jobs could be affected by AI.
Some of the jobs that could be affected include, but are not limited to, cashiers, waiters, auditors, machine operators, among others.
In King City, Ont., for example, a lettuce farmer is tackling Canada’s reliance on U.S. greens by utilizing AI to run his lettuce farm.
The farm’s owner, Jay Willmot, says that automating his greenhouse allowed him to “maximize the amount of lettuce he can grow, while cutting labour costs.” Labour costs are typically a greenhouse grower’s biggest operating expense.

But Blit says what’s likely to happen is not straightforward.
“I think that the reality is that you’re not going to lose your job to AI,” he said. “You’re more likely to lose your job to someone that is using AI to do your job better.”
Guenther agrees, saying that AI will help improve people’s speed, efficiency, and ability to do tasks.
“But I don’t think that it’s going to take away from the workforce,” she said.
With worries surrounding AI growing, Blit said he found that approaching its use from an “experimental point of view” can really help alleviate some of those worries.
“When [people] start experimenting with it, they realize that actually [AI] is not too bad,” he said. “It just blows you away until you sort of get used to it.”
“The first thing that I think everybody needs to know is… you can use [AI] too.”
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