DataRobot Blog

MARCH 16, 2023

Traditionally, developing appropriate data science code and interpreting the results to solve a use-case is manually done by data scientists. It is a time-intensive process that can slow the adoption of AI across an organization. For example, generating code to prepare data as well as train and deploy a model.

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ODSC - Open Data Science

MARCH 6, 2025

AI has unlocked a world of possibilities, but thats precisely the problem too many options can lead to decision paralysis. Some organizations hold back on their AI strategy framework, unsure which ideas are worth pursuing , while others jump in too quickly, investing in expensive experiments that fail todeliver.

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IBM Journey to AI blog

OCTOBER 4, 2023

Typically, on their own, data warehouses can be restricted by high storage costs that limit AI and ML model collaboration and deployments, while data lakes can result in low-performing data science workloads. Later this year, watsonx.data will infuse watsonx.ai

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Unite.AI

JANUARY 17, 2024

It symbolizes businesses that are focused on developing and implementing innovative AI strategies. could become a leading name in the industry, representing expertise in cutting-edge AI solutions and strategic AI planning. Driven.AI : Suited for companies specializing in AI analytics and automation, Driven.AI

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IBM Journey to AI blog

JULY 17, 2023

IBM software products are embedding watsonx capabilities across digital labor, IT automation, security, sustainability, and application modernization to help unlock new levels of business value for clients. Automated development: Automates data preparation, model development, feature engineering and hyperparameter optimization using AutoAI.

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ODSC - Open Data Science

FEBRUARY 8, 2024

This is a recipe for developing a strategy for incorporating AI into products. An AI strategy is a framework that will help the organization understand what data-driven projects and data sources are the most valuable to the organization, and how to prioritize them to build toward their product vision over time.

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ODSC - Open Data Science

MARCH 6, 2025

Building Reliable Machine Learning Models: Lessons from BrianLucena In a recent episode of ODSCs Ai X Podcast, Brian Lucena shared his insights on gradient boosting, uncertainty estimation, and model calibrationtopics crucial for building robust machine learningsystems. Plus, ODSC Founder Sheamus McGovern will be one of the panelists!

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ODSC - Open Data Science

MARCH 12, 2025

Many business problems can be solved more efficiently with simpler automation techniques. For instance, if-then rule-based systems or basic scripting might address the issue without the complexity, cost, and risks of AI.

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Towards AI

MARCH 6, 2025

AI Solutions Are Creating Artificial Needs AI should clear your desk, not clutter it with artificial needs. Was that task truly repetitive, or was it labeled as boring to justify automation? AI can also play a crucial role in specialized fields like medical diagnostics, fraud detection, and scientific research.

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IBM Journey to AI blog

FEBRUARY 8, 2023

The True Cost of Noncompliance Responsible AI requires governance Despite good intentions and evolving technologies, achieving responsible AI can be challenging. AI requires AI governance , not after the fact but baked into AI strategy of your organization. So what is AI governance?

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AWS Machine Learning Blog

MARCH 5, 2025

The fully automated RCA agent correctly identifies the right root cause for most cases (measured at 85%), and helps engineers in terms of system understanding and real-time insights in their cases. Solution overview At a high level, the solution uses an Amazon Bedrock agent to do automated RCA.

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AWS Machine Learning Blog

FEBRUARY 27, 2024

Axfood has a structure with multiple decentralized data science teams with different areas of responsibility. Together with a central data platform team, the data science teams bring innovation and digital transformation through AI and ML solutions to the organization.

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IBM Journey to AI blog

APRIL 18, 2024

By using complex AI algorithms and computer science methods, these AI systems can then generate human-like text, translate languages with impressive accuracy, and produce creative content that mimics different styles. This gap highlights the vast difference between current AI and the potential of AGI.

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ODSC - Open Data Science

SEPTEMBER 19, 2023

Learn how to unlock efficiencies, adapt to change, and cultivate innovative strategies for sustainable business growth Generative AI Discover how to harness Generative AI’s potential to automate content creation, design, and decision-making. Join us at ODSC West for hands-on training sessions, workshops, and more.

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ODSC - Open Data Science

MARCH 8, 2024

There, the tech giant is preparing to showcase a series of generative AI-based tools, that should showcase its new AI strategy. The news comes a few months after reports detailing Apple’s lag in the generative AI space. A key aspect of Apple’s AI strategy involves strategic partnerships and technological innovation.

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Pickl AI

SEPTEMBER 26, 2024

Additionally, they collaborate with cross-functional teams to ensure alignment and facilitate the smooth execution of AI projects. Expanded Responsibilities: Identifying Opportunities: AI strategists analyse business operations to pinpoint inefficiencies and areas ripe for automation or enhancement through AI technologies.

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IBM Journey to AI blog

AUGUST 7, 2023

This results in many groups using a large gamut of AI-based tools that are not fully integrated into a cohesive system and platform. Therefore, IBM observes that more clients tend to consult AI leaders to help establish governance and enhance AI and data science capabilities, an operating model in the form of co-delivery partnerships.

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ODSC - Open Data Science

JANUARY 2, 2024

Take a deep dive into watershed technologies like Large Language Models, Generative AI, and more with a full day of talks and panels. Originally posted on OpenDataScience.com Read more data science articles on OpenDataScience.com , including tutorials and guides from beginner to advanced levels!

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ODSC - Open Data Science

MARCH 5, 2024

Currently, these trends are shaped by the pursuit of possible innovation that can result in new market capture in machine learning, automation, and data analytics. Because of this, the expected CAGR of both computer chips and AI-powered software is predicted to see a massive jump in growth above thirty percent through 2031.

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Kavita Ganesan

SEPTEMBER 9, 2022

Several years ago, a product manager at a tech company had a data collection problem : to scrape software security vulnerability data from multiple web sources, consolidate the vulnerabilities and store them in a database. The PM then “hired” the company’s data science team to build ML models to solve the problem.

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Snorkel AI

APRIL 20, 2023

According to another survey seen and reported on by Business Insider, 75% of respondents working at banks with more than $100 billion in assets were currently implementing AI strategies. This is especially true for complex, high-value use cases such as conversational AI, fraud detection, anti-money laundering, and more.

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Snorkel AI

APRIL 20, 2023

According to another survey seen and reported on by Business Insider, 75% of respondents working at banks with more than $100 billion in assets were currently implementing AI strategies. This is especially true for complex, high-value use cases such as conversational AI, fraud detection, anti-money laundering, and more.

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AWS Machine Learning Blog

MARCH 28, 2024

These generative AI applications are not only used to automate existing business processes, but also have the ability to transform the experience for customers using these applications. Based in Dallas, Texas, he and his family love to travel and go on long road trips.

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Pickl AI

OCTOBER 3, 2024

Microsoft Azure AI: Features Azure Machine Learning which supports both pre-built models and custom solutions tailored to specific business needs. DataRobot : Focuses on automating the Machine Learning process, making it easier for businesses to deploy predictive analytics solutions. What are Some Common Use Cases for AIMaaS?

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Topbots

FEBRUARY 4, 2025

The AI pulls from historical data, live logistics feeds, and external risk factors to provide actionable answers, suggest mitigations, and even automate workflows like rerouting shipments. This article was originally published on Towards Data Science and re-published to TOPBOTS with permission from the author.

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Flipboard

DECEMBER 3, 2024

Generative AI is reshaping businesses and unlocking new opportunities across various industries. As a global leader in agriculture, Syngenta has led the charge in using data science and machine learning (ML) to elevate customer experiences with an unwavering commitment to innovation.

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Unite.AI

MAY 21, 2024

The list only grows from there as businesses are starting to find specific ways to leverage AI to fit unique business needs. The same report mentions major barriers to AI adoption, including data science gaps and latency in implementation. 2024 will be a transformation year for AI experimentation and foundational work.

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Pickl AI

DECEMBER 17, 2024

Myth 1: AI Will Replace Most Human Jobs One of the most prevalent myths is that AI will take over all jobs, leading to mass unemployment. While its true that AI can automate repetitive tasks, it cannot replicate the cognitive skills of humans. Reality AI is designed to assist rather than replace human workers.

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