Have you ever asked an LLM a question, changed the wording a few times, and still felt the answer wasn’t quite right? If you’ve worked with tools like ChatGPT or Gemini, you’ve probably rewritten prompts, added more context, or used phrases like “be concise” or “think step by step” to improve results. But what if […]
The post Prompt Repetition: The Overlooked Hack for Better LLM Results...
Machine learning is widely used for prediction, but not all data behaves the same. A common mistake is applying standard ML to time-dependent data without considering temporal order and dependencies, which these models don’t naturally capture. Time series data reflects evolving patterns over time, unlike static snapshots. For example, sales forecasting differs from default risk […]
The...
A junior loan officer handling data intake, risk screening, and final decisions alone is prone to mistakes because the role demands too much at once. The same weakness appears in monolithic AI agents asked to run complex, multi-stage workflows. They lose context, skip steps, and produce shaky reasoning, which leads to unreliable results. A stronger […]
The post Mastering the Supervisor...
You probably solved Bayes’ Theorem in college and decided you’re “good at statistics.” But interviews reveal something else: most candidates don’t fail because they can’t code. They fail because they can’t think probabilistically. Writing Python is easy. Reasoning under uncertainty isn’t. In real-world data science, weak statistical intuition is expensive. Misread an A/B test, misjudge...
The wrong chart doesn’t just look bad, it changes what people believe the data says. When a trend appears flat on a pie chart or a comparison gets buried in a dual-axis mess, stakeholders don’t just misread the numbers. They make the wrong call, ask the wrong questions, or stop trusting your dashboards altogether. A 2024 […]
Building an LLM prototype is quick. A few lines of Python, a prompt, and it works. But Production is a different game altogether. You start seeing vague answers, hallucinations, latency spikes, and strange failures where the model clearly “knows” something but still gets it wrong. Since everything runs on probabilities, debugging becomes tricky. Why did […]
The post Building a...
What’s working well on your finance team? What could you improve? The only real way to know is to track your Key Performance Indicators (KPIs), including the goals around accounts receivable. After all, accounts receivable KPIs are vital to the business performance. However, there are so many different accounts receivable KPIs. How can you choose […]
The post The Top 14 Accounts...
AI-enabled deception now permeates our online lives. There are the high-profile cases you may easily spot, like when White House officials recently shared a manipulated image of a protester in Minnesota and then mocked those asking about it. Other times, it slips quietly into social media feeds and racks up views, like the videos that…
Just 3 months after the release of their state-of-the-art model Gemini 3 Pro, Google DeepMind is here with its latest iteration: Gemini 3.1 Pro. A radical upgrade in terms of capabilities and safety, Gemini 3.1 Pro model strives to be accessible and operable by all. Regardless of your preference, platform, purchasing power, the model has […]
The post Gemini 3.1 Pro: A Hands-On Test of...