• The Drip AI
  • Posts
  • đź›’ Walmart Uses AI to 100x Productivity

đź›’ Walmart Uses AI to 100x Productivity

PLUS: What are LLM Hallucinations

Author

The Drip Team
August 18, 2024

This week, we’re turning our attention to the grocery aisle, where a high-stakes battle between Walmart and Amazon is quietly unfolding. But this isn’t just about who can offer the best deals or the freshest produce. This is about AI transforming the way we shop, one algorithm at a time.

What to Expect:

  • Walmart Uses AI to 100x Productivity

  • Debate: Is a Formal CS Degree Needed for Tech?

  • Unpacking LLM Hallucinations

  • Let AI Plan Your Next Meal

  • More AI Tech, Tools, and Talks

Source: Made by The Drip Team via DALL-E

Grocery shopping used to be simple: grab a cart, wander the aisles, and hope that everything on your list is in stock. But now, with AI entering the picture, things are getting a lot more interesting—and the future of retail is at stake.

Here’s how these two giants are making it happen:

  • đź›’ Walmart’s AI magic: Walmart has started using generative AI to supercharge their product catalog, deploying multiple large language models to create or improve over 850 million pieces of data. This same effort would have taken 100 times as much effort to complete the same task, proving that the productivity boost is worth the investment. And it doesn’t stop there — they are also leveraging AI to improve supply chain management, using algorithms to predict what you’ll need next, keeping shelves full, and cutting down on waste. The bottom line: Walmart is saving big bucks and passing those savings on to you.

  • 📦 Amazon’s AI power play: Amazon isn’t sitting this one out—they’re also flexing their AI muscles with tech like “Just Walk Out,” which lets you skip the checkout line entirely. Amazon’s AI-driven recommendation system acts like a personal shopper, predicting what you need before you even realize it.

  • 🤖 The future: Both supermarkets are using AI-driven product searches to help customers shop more intuitively. Soon, you’ll just be able to ask Walmart to “Help me plan a football watch party” or “What supplies do I need for a newborn?” and you’ll have a personalized list of everything you need, right at your fingertips. But will it be able to choose what Ben & Jerry’s flavor you’re craving?

  • đź’ˇ Why it matters: This AI-fueled grocery war is more than just a tech competition—it’s shaping the future of how we shop. Walmart’s focus on productivity means cheaper groceries and fewer out-of-stock frustrations. Meanwhile, Amazon’s push for convenience could make traditional checkout lines a thing of the past. In this high-stakes showdown, your grocery cart has never been more cutting-edge.

HOT DEBATE
Is a Formal CS Degree Needed for Tech?

Source: Made by The Drip Team via DALL-E

Dimitrios’ Take: Online Courses as Your Starting Block

  • đź“ť Skip the Degree, But Not the Prep: Let’s clear this up—you don’t need a formal degree to break into tech, but that doesn’t mean you can skip the groundwork. Think of it like preparing for a marathon: you wouldn’t wake up and decide to run 26.2 miles without some serious training. The same goes for tech—start with the basics before tackling the big stuff.

  • 🥇 Online Courses Are Gold:

    • Platforms like Coursera and edX are your go-to coaches:

    • These courses are like your warm-up laps—necessary before you start sprinting.

  • 🍎 Discipline Is Key: Here’s the kicker—no one’s going to hold your hand. Without a professor breathing down your neck, it’s all on you. Don’t just breeze through chapters like you’re cramming for finals. Take your time, revisit tough sections, and make sure you really understand what you’re learning. It’s not a race; it’s about mastering the material.

  • đź’Ľ Business-Oriented Roles? Here’s the Good News:

    • You’re not climbing Everest—just a tall hill.

    • Your goal is to understand tech, not to build it from scratch:

    • Pro Tip: In a world full of generalists, deep knowledge in a niche area can be your key. It’s what sets you apart from the crowd.

Courtney’s Take: No Degree, No Problem—But Be Ready to Hustle

  • 🖊️ No CS Degree? No Worries: Let’s be real—a formal CS degree is totally optional. When I set my sights on a tech career, my knowledge of computer science was practically nonexistent. But guess what? That didn’t stop me for a second.

  • 🤓 Self-Taught Success Story:

    • Armed with nothing but a laptop and sheer determination (and, goes without saying, lots coffee), I taught myself to code using:

      • Coursera and Udemy for picking up the skills.

      • LeetCode for sharpening them with real-world coding problems.

    • These platforms were like my personal boot camp, turning me from a newbie into someone who could confidently walk into a technical interview.

  • 👩🏼‍💻 Tech Moves Fast—So Should You:

    • In tech, the only constant is change. New languages, frameworks, and tools are like TikTok trends—they pop up overnight. So you need to be ready to learn and constantly up-skill yourself.

    • As Elon Musk puts it, "It’s possible for ordinary people to choose to be extraordinary." In tech, that means staying curious, adaptable, and never settling for "just enough."

    • The learning doesn’t stop once you land the job—in fact, that’s when it really kicks into high gear. You have to stay on top of the latest trends and continuously improve your skills to keep up in this fast-paced industry.

  • 🎒 Reality Check:

    • If you’ve got the passion and the grit, a lack of formal education isn’t a roadblock. But let’s be real—it’s going to take time, effort, persistence and a whole lot of hustle. Rome wasn’t built in a day, and neither is a tech career.

đź’» Resources:

  • Explore Coursera, edX & Udemy for everything from beginner programming to advanced AI/ML courses.

  • LeetCode can be your go-to platform for hands-on coding practice and interview prep.

đź“– Another take:

CONCEPT
Unpacking LLM Hallucinations

Source: Made by The Drip Team via DALL-E

Ever gotten a curious or incorrect answer from an AI and wondered how it arrived at that response? That’s likely a phenomenon known as an “LLM hallucination.” No, this isn’t about AI taking a digital trip—rather, it’s a quirk of how language models generate text.

What are they:  LLM hallucinations occur when a language model confidently generates information that is not just slightly off, but entirely fabricated. Imagine asking your AI about a fictional city and receiving a detailed, convincing statistic about its population. Or perhaps it tells you about a historical event that never occurred, complete with specific dates and figures. These hallucinations happen because the model, while sophisticated, doesn’t understand reality in the way humans do.

Let’s take a closer look on what’s happening:

  1. Pattern-Based Generation: Language models predict text based on patterns they’ve learned from vast amounts of data. They generate responses by stringing together words and phrases that statistically fit the context, not by verifying the truthfulness of the content. This can lead to fabrications that sound plausible but are entirely invented.

  2. Overconfidence in Apparent Facts: Sometimes, the model generates information that sounds authoritative because it’s drawing from patterns of authoritative language it has seen. However, this doesn’t guarantee accuracy—what sounds like a fact can often be a confident fabrication.

  3. Contextual Misinterpretations: The model may misinterpret the context of a query, leading it to produce information that seems relevant but is actually based on a misunderstanding. For instance, if a question is ambiguous, the model might provide an answer that fits one interpretation but not the actual context.

  4. Filling the Gaps: When faced with incomplete or ambiguous prompts, the model might generate details to fill in the gaps. This is akin to a person guessing the missing parts of a story—they might create something that seems to fit but is not grounded in reality.

Why Do They Happen?

  1. Training Data Limitations: Models are trained on a vast corpus of text, which may include errors or outdated information. If the model encounters a gap or inconsistency in its training data, it might generate information to fill these gaps, even if it’s incorrect.

  2. Pattern Overconfidence: Language models are adept at recognizing and generating patterns. When a certain pattern appears frequently in the training data, the model might apply it more broadly, leading to incorrect answers when the pattern doesn’t fit.

  3. Language Ambiguity: Natural language is often ambiguous and complex. When asked about something intricate or not explicitly clear, the AI might generate responses based on the closest matching patterns, even if these don’t accurately reflect the intended meaning.

  4. Lack of Real-World Understanding: Unlike humans, LLMs don’t possess real-world knowledge or logical reasoning. They generate responses based on learned language patterns rather than actual understanding, leading to plausible-sounding but inaccurate outputs.

How to Handle Them

  • Fact-Check: Always verify surprising or critical information with trusted sources. Cross-checking helps ensure that the information is accurate.

  • Ask for Sources: If possible, request information about where the AI’s responses are coming from. Some models can provide sources or confidence levels.

  • Be Specific: Clear and detailed questions can help guide the model to generate more accurate responses and reduce the likelihood of hallucinations.

Understanding these quirks helps you interact with LLMs more effectively. While these models are impressive, they’re not infallible. Next time your AI provides a dubious fact or elaborate tale about events that never happened, remember it’s a fascinating aspect of AI technology and always worth a closer look!

Example: ChatGPT4o - OpenAI's Latest & Greatest Can't Handle the Spice!

Sooo, is Mel B or Mel C older… somehow, we ended up more confused than before - did you?

And a funny one…

Try For Yourself:

Take for example the prompt below:

"What was the 3rd national park added to the US national park system?"

and after each response, argue with it.. what do you notice?

"Are you sure? I'll give you one more chance."
"Sure? Last chance.."

An ever changing top-3..

PROMPT OF THE WEEK
For: Your Next Meal

Adopt the role of a seasoned chef and recipe developer. Your task is to create a variety of breakfast ideas that can be prepared quickly and easily. These breakfasts should be nutritious, delicious, and suitable for busy mornings. Include detailed instructions for each recipe, along with tips for variations and substitutions. Please incorporate any specific preferences or dietary restrictions provided by [USER_PREFERENCES]

Pro Tip: Get creative. If you like/dislike certain foods, tell ChatGPT. If you have a calorie goal, don’t hesitate to include that. Adapt the prompt to meet your needs.

TECH TOOLS, TIPS, AND TALKS

đź“– What we’re reading: Atomic Habits: An Easy Way to Build Good Habits & Break Bad Ones
📻 What we’re listening to: How I Built This by Guy Raz: Thrive Market
💻 What we’re using: Grammarly - Free AI writing assistant to help reword and fix mistakes

MORE READING

We want to empower our readers with actually insightful knowledge so that they are more confident, informed leaders. Because let's face it, AI could be running the world pretty soon... so shouldn't we at least know how it works? If you are curious about a topic and want to learn more, drop us a message below👇🏼