Tools & Platforms
Tech’s diversity crisis is baking bias into AI systems

As an Afro-Latina woman with degrees in computer and electrical engineering, Maya De Los Santos hopes to buck a trend by forging a career in AI, a field dominated by white men.
AI needs her, experts and observers say.
Built-in viewpoints and bias, unintentionally imbued by its creators, can make the fast-growing digital tool risky as it is used to make significant decisions in areas such as hiring processes, health care, finance and law enforcement, they warn.
Tools & Platforms
A Scalable Blueprint for Tech-Enhanced ROI

In the high-stakes arena of general merchandise retail, Walmart has emerged as a trailblazer, leveraging artificial intelligence not just as a buzzword but as a strategic engine for scalable returns. From 2023 to 2025, the company has systematically embedded AI into its DNA, creating a blueprint for how retailers can achieve operational efficiency, cost savings, and customer loyalty in an era of razor-thin margins. For investors, this isn’t just a story of technological innovation—it’s a masterclass in how to turn AI into a profit center.
The AI Arsenal: From “Super Agents” to Digital Twins
Walmart’s AI playbook is as diverse as it is precise. At the heart of its transformation are four “super agents” designed to streamline interactions across the retail value chain:
– Sparky (for shoppers): This AI agent anticipates customer needs by analyzing household behaviors, seasonal trends, and purchase history. It doesn’t just recommend products—it crafts personalized shopping baskets and automates reordering, reducing the “mental load” on consumers.
– Marty (for sellers and suppliers): By consolidating vendor onboarding, inventory coordination, and promotional planning, Marty cuts administrative overhead and accelerates decision-making.
– Associate Agent (for employees): This tool acts as a one-stop shop for store associates, handling payroll, time-off requests, and real-time sales insights. It even learns from user interactions, becoming more intuitive over time.
– Developer Agent (for systems): Accelerating software development by automating routine coding tasks, this agent ensures Walmart’s tech stack evolves at breakneck speed.
But the real magic lies in Walmart’s use of digital twin technology. By creating virtual replicas of its stores, powered by spatial AI, the company can predict and resolve issues like refrigeration failures up to two weeks in advance. This has already slashed emergency alerts by 30% and maintenance costs by 19% in the U.S. Imagine the ripple effect of such proactive problem-solving across 5,500 stores.
Logistics and Delivery: AI’s Invisible Hand
Walmart’s Dynamic Delivery algorithm is another crown jewel. By analyzing traffic, weather, and historical data, it predicts delivery windows with 93% accuracy, enabling same-day delivery to 93% of U.S. households. This isn’t just convenience—it’s a 25% year-over-year boost in digital sales and a 35% surge in Walmart+ memberships. Meanwhile, the Load Planner and Pallet Builder systems optimize trailer loading and route planning, saving $75 million annually in logistics costs.
The financials tell a compelling story. Walmart’s AI-driven advertising platform, Walmart Connect, grew 46% globally in Q2 2025, tapping into the high-margin potential of data-driven marketing. With 27.3 million Walmart+ members, the company is uniquely positioned to monetize customer data without sacrificing privacy—a critical edge in an age where trust is currency.
Why This Matters for Investors
Walmart’s approach to AI is surgical. Unlike companies that dabble in flashy tech, Walmart has focused on solving real-world retail challenges—inventory accuracy, labor efficiency, and customer retention. The results? A 26% year-over-year earnings per share (EPS) growth projection by 2027 and a P/E ratio that’s more attractive than Amazon’s despite stronger e-commerce margins.
The company’s capital allocation is equally impressive. A $520 million investment in Symbotic’s AI-powered robotics and a $19 billion annual capex in the U.S. signal long-term commitment. These aren’t just expenses—they’re investments in infrastructure that will compound value as AI adoption scales.
The Road Ahead: A Retail Renaissance
Walmart’s AI-led transformation isn’t just about today—it’s about redefining the future of retail. The company is already testing agentic AI systems that can autonomously manage complex tasks, from dynamic pricing to in-store navigation. With a proprietary large language model (Wallaby) trained on decades of retail data, Walmart’s predictive capabilities are unmatched.
For investors, the key takeaway is clear: Walmart is not just keeping up with the AI revolution—it’s leading it. While competitors like Amazon and Target are still figuring out how to integrate AI into their operations, Walmart is already reaping the rewards of a disciplined, data-driven strategy.
Final Call to Action
The numbers don’t lie. Walmart’s AI initiatives have delivered $75 million in annual savings, 46% growth in high-margin advertising, and a 1.2–1.5 percentage point boost in operating margins by 2027. For those seeking exposure to the next phase of retail innovation, Walmart offers a rare combination of scale, execution, and profitability.
In a sector where margins are under constant pressure, Walmart’s AI-driven efficiency is a moat worth betting on. This isn’t just a stock—it’s a glimpse into the future of retail, where technology isn’t just a cost center but a catalyst for exponential returns.
Bottom line: Buy Walmart. The AI revolution is here, and Walmart is the blueprint.
Tools & Platforms
AI: The new frontier at the Institute for Continued Learning in St. George – St. George News
Tools & Platforms
Colleges should go ‘medieval’ on students to beat AI cheating, NYU official says

Educators have been struggling over how students should or should not use artificial intelligence, but one New York University official suggests going old school—really, really old school.
In a New York Times op-ed on Tuesday, NYU’s vice provost for AI and technology in education, Clay Shirky, said he previously had counseled more “engaged uses” of AI where students use the technology to explore ideas and seek feedback, rather than “lazy AI use.”
But that didn’t work, as students continued using AI to write papers and skip the reading. Meanwhile, tools meant to detect AI cheating produce too many false positives to be reliable, he added.
“Now that most mental effort tied to writing is optional, we need new ways to require the work necessary for learning,” Shirky explained. “That means moving away from take-home assignments and essays and toward in-class blue book essays, oral examinations, required office hours and other assessments that call on students to demonstrate knowledge in real time.”
Such a shift would mark a return to much older practices that date back to Europe’s medieval era, when books were scarce and a university education focused on oral instruction instead of written assignments.
In medieval times, students often listened to teachers read from books, and some schools even discouraged students from writing down what they heard, Shirky said. The emphasis on writing came hundreds of years later in Europe and reached U.S. schools in the late 19th century.
“Which assignments are written and which are oral has shifted over the years,” he added. “It is shifting again, this time away from original student writing done outside class and toward something more interactive between student and professor or at least student and teaching assistant.”
That may entail device-free classrooms as some students have used AI chatbots to answer questions when called on during class.
He acknowledged logistical challenges given that some classes have hundreds of students. In addition, an emphasis on in-class performance favors some students more than others.
“Timed assessment may benefit students who are good at thinking quickly, not students who are good at thinking deeply,” Shirky said. “What we might call the medieval options are reactions to the sudden appearance of AI, an attempt to insist on students doing work, not just pantomiming it.”
To be sure, professors are also using AI, not just students. While some use it to help develop a course syllabus, others are using it to help grade essays. In some cases, that means AI is grading an AI-generated assignment.
AI use by educators has also generated backlash among students. A senior at Northeastern University even filed a formal complaint and demanded a tuition refund after discovering her professor was secretly using AI tools to generate lecture notes.
Meanwhile, students are also getting mixed messages, hearing that the use of AI in school counts as cheating but also that not being able to use AI will hurt their job prospects. At the same time, some schools have no guidelines on AI.
“Whatever happens next, students know AI is here to stay, even if that scares them,” Rachel Janfaza, founder of Gen Z-focused consulting firm Up and Up Strategies, wrote in the Washington Post on Thursday.
“They’re not asking for a one-size-fits-all approach, and they’re not all conspiring to figure out the bare minimum of work they can get away with. What they need is for adults to act like adults — and not leave it to the first wave of AI-native students to work out a technological revolution all by themselves.”
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