Browsing: Business & Startups

Image by Editor   # Introduction  Data is at the core of any data professional’s work. Without useful and valid data sources, we cannot perform our responsibilities. Furthermore, poor-quality or irrelevant data will only cause our work to go to waste. That’s why having access to reliable datasets is an important starting point for data professionals. Data Commons is an open-source initiative by Google to organize the world’s available data and make it accessible for everyone to use. It’s free for anyone to query publicly available data. What sets Data Commons apart from other public dataset projects is that it already…

Embedding-based retrieval, also known as dense retrieval, has become the go-to method for modern systems. Neural models map queries and documents to high-dimensional vectors (embeddings) and retrieve documents by nearest-neighbor similarity. However, recent research shows a surprising weakness: single-vector embeddings have a fundamental capacity limit. In short, an embedding can only represent a certain number of distinct relevant document combinations. When queries require multiple documents as answers, dense retrievers start to fail, even on very simple tasks. In this blog, we will explore why this happens and examine the alternatives that can overcome these limitations. Single-Vector Embeddings And Their Use…

I recently surveyed danish CIO’s(Chief information officers) about their relationship with AI and I had some interesting results. One of the results was that one of the biggest barriers to get started on AI projects is that building the business case is difficult. I completely understand the issue and I agree with the CIO’s. Building an AI business case is difficult and if you try to build it as a traditionnel IT business case it’s down right impossible. Building a business case is all about understanding the cost and revenue drivers well enough to work them into a model that yields…

Are you considering implementing GPT in your business but unsure where to begin? You’re in the right place! We’ve prepared a step-by-step guide tailored just for you.  To make things clear, we’ll walk you through each stage using a real-world example: our own ‘student agent’ developed using the GPT model. By drawing on our first-hand insights and experiences, you’ll be well-equipped to navigate your project toward success confidently. Ready? Let’s dive in. GPT vs. ChatGPT:  What’s the Difference? Alright, first of all, let’s clarify a common point of confusion: Is there a difference between ChatGPT and GPT? It’s come to…

Image by Editor   # Introduction  Whether you’re an engineer automating deployment scripts, a marketer managing content campaigns, or a customer support manager scaling responses, ChatGPT Agents can now execute, not just converse.  They combine reasoning with real-world action, creating a bridge between language and logic. The beauty lies in their versatility: one model, infinite configurations. Let’s explore five examples that prove ChatGPT Agents aren’t theoretical anymore — they’re here to change how we work, automate, and innovate.   # 1. Automating Data Cleaning Workflows  Data scientists spend much of their time cleaning data, not analyzing it. Fortunately, ChatGPT Agents can automate…

This blog is based on a keynote delivered by Vignesh Kumar, AI Engineering Manager at Ford, during the Data Hack Summit 2025. His session, titled “Automating Vehicle Inspections with Multimodal AI”, explored how AI (artificial intelligence) is transforming the car servicing industry. It highlighted the scale of the challenge, the architecture of multimodal AI solutions, and the measurable business impact of deploying them at scale. What follows is a detailed exploration of that vision and its implications for the industry. Industry Context The car service world is no longer what it was a decade ago. Inspections used to be mechanical,…

Deploying machine learning models can be daunting, particularly when considering the best environment to host your models. AWS and GCP offer robust cloud platforms, but the setup process varies significantly. Recently, we wrote a guide on deploying MLflow on Google Cloud Platform, and now we will share a comprehensive, step-by-step guide on setting up MLflow on AWS using Terraform. From setting up VPC to creating a database, ECS service and setting up security groups, we’ll walk you through the entire process modularly, with each section dedicated to a specific component. Give a read to understand how to create a robust,…

Image by Author   # Introduction  Data has become an indispensable resource for any successful business, as it provides valuable insights for informed decision-making. Given the importance of data, many companies are building systems to store and analyze it. However, there are many times when it’s hard to acquire and analyze the necessary data, especially with the increasing complexity of the data system. With the advent of generative AI, data work has become significantly easier, as we can now use simple natural language to receive mostly accurate output that closely follows the input we provide. It’s also applicable to data processing…

Until last week everyone was talking about OpenAI’s Sora 2. While all of us wait for access in India, Google has just pulled off a masterstroke. Overnight, they not only announced the powerful Veo 3.1 but also rolled it out for free in Flow and via their Gemini suite. How can you not admire Google for this? Instead of a closed-door demo, they’ve handed us the keys to a state-of-the-art video studio, and it’s time to explore. In this article, I will tell you everything about Veo 3.1. What’s New in Veo 3.1 and Flow? Announced on October 15, 2025, this isn’t…

You might not be aware or do this unconsciously but, if you work with AI you also work in the decision science space. Imagine this: You have made an AI model that can take in support tickets and classify them into different subjects and sentiments. With that you can prioritize support tickets by how critical they are and have them directed to the appropriate support team. Sounds great right? But is it really that simple? No. With the AI model in place we are really only halfway to the finish line. If you decided to make an AI like the one…