Ivo Bernardo - DareData Blog

Gen-OS: The Platform, the Apps, the Toolkit

Most AI projects stall after pilots due to poor systems, workflows, and architecture. By focusing on business impact, using a reliable AI platform, and avoiding vendor lock-in with open, integrated tools like Gen-OS, enterprises can scale AI and achieve measurable results.

Generative AI, Gen-OS

What’s LLMOps? A quick primer

LLMOps is about managing the entire lifecycle of applications powered by LLMs: from prompt engineering to fine-tuning, evaluation, deployment, monitoring, and continuous improvement.

Use Case, Artificial Intelligence

DareData Use Case: Beyond Simple Chatbots

Hear how Gen-OS is able to support your Customer Service with AI

Artificial Intelligence, Generative AI, Legal AI Solution, AI Solution, AI Use Case, Legal, Gen-OS

DareData Use Case: E-mail Replier

Legal teams are often bogged down with routine, repetitive requests that require high accuracy and careful compliance with internal systems and legal protocols. But what if you could automate 90% of that work, without compromising on quality, and even improve over time?

Artificial Intelligence, Use Case

GenAI Applications - AI Sales Assistant

AI sales assistants can take your sales to the next level and give you an immediate sales growth of 12%.

Can AI be deployed in Critical Processes? Addressing the Key Challenges

You’ve seen it before: a company starts deploying AI but struggles to move beyond the most high-level use cases. Yet, current AI technology has the potential to power near-fully

GenAI

The Gen-OS Newsletter - Is DareData Changing?

DareData's future is here!

Artificial Intelligence, AI Leadership, Project Management

Tips on How to Manage Large Scale Data Science Projects

use these tips for project management with data science and machine learning

Agents, Artificial Intelligence, Business

AI Agents for Customer Support

Learn how AI Agents can transform your customer support processes

AI Leadership, Management, data strategy

Organizations’ Machine Learning Investment is (or should be) Incremental

Embedding ML systems into production is still a hard thing to do (for most companies)

Artificial Intelligence, PyTorch

PyTorch Introduction — Training a Computer Vision Algorithm

Learn how to train a computer vision algorithm using Pytorch

Artificial Intelligence, AI Leadership, Business, GenAI

You need an AI Team and an AI Lead

Having an AI Team and AI Lead today is comparable to the need of having an IT Team 20 years ago.

GenAI, LLM, Agents, Artificial Intelligence

3 Use Cases for Generative AI Agents

Discover some examples of Generative AI Use Cases and what how you can level up your organization and business In the dynamic landscape of artificial intelligence, Generative AI agents have

Artificial Intelligence, PyTorch, Data Science

PyTorch Introduction — Using Custom Data

In this post of the PyTorch Introduction, we’ll learn how to use custom datasets with PyTorch, particularly tabular, vision and text data

Artificial Intelligence, Data Science, Technical, PyTorch

PyTorch Introduction — Enter NonLinear Functions

Continuing the Pytorch series, in this post we’ll learn about how non-linearities help solve complex problems in the context of neural networks

Artificial Intelligence, Technical, PyTorch

PyTorch Introduction — Building your First Linear Model

Learn how to build your first PyTorch model, by using the “magical” Linear layer

Artificial Intelligence, Data Science, PyTorch, Technical

PyTorch Introduction - The Tensor Object

Learn about Tensors and how to use them in one of the most famous machine learning libraries, PyTorch

Data Engineering, Data Ops, Data Pipelines

Tips to Build a Robust Data Lake Infrastructure

Learn how we build data lake infrastructures and help organizations all around the world achieving their data goals.

Artificial Intelligence

Why this time it may be different - Digesting Large Language Models and their implications for Society

Irrespective of your stance regarding the speed of technological evolution, one thing is certain: with the latest advances in artificial intelligence and the creation of groundbreaking technologies like GPT-4, there will be profound implications for all of us.

Data Engineering

Most important Data Engineering Concepts and Tools for Data Scientists

Learn the most important data engineering concepts that data scientists should be aware of - such as data orchestrators, ingestion or infrastructure-as-code

Business, Data Science

DS Building Blocks - Regression vs. Classification

Understand the difference between regression and classification problems

Business

DS Building Blocks - A quick guide on experimentation for Non-Technical Users

Understand the difference between correlation and causation and know how to integrate data decisions into your business

Business

How to introduce Data Science at your company

Machine Learning, Data Science and Artificial Intelligence are three terms that have been intertwined and used in multiple conversations during the past decade. Probably, in the business world, no other

Business

On FMCG and Retail Forecasting

The importance of having accurate sales forecasts When we think of sales forecasting, a couple of interesting questions unfold: how do most businesses manage their operations without having an accurate

Business, COVID-19

Sales Forecast updating in times of COVID-19

How can businesses adapt their sales forecast in times of COVID-19? In this post we will look at a practical example, explaining how we are helping a small business to make sound decisions for the future.