IBM Journey to AI blog

SEPTEMBER 6, 2023

According to the IBM survey, when CMOs were asked what they thought the primary challenges were in adopting generative AI, they listed three top concerns: managing the complexity of implementation, building the data set and brand and intellectual property (IP) risk. The journey starts with sound data.

Generative AI 305

Generative AI AI AI AI Tools 305

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.

Machine Learning 112

Machine Learning DevOps Data Quality Data Scientist 112

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.

Neural Network 239

Neural Network LLM AI AI 239

IBM Journey to AI blog

OCTOBER 4, 2023

Enter IBM watsonx.data , a fit-for-purpose data store built on an open data lakehouse, to scale AI workloads, for all your data, anywhere. Watsonx.data is part of IBM’s AI and data platform, watsonx, that empowers enterprises to scale and accelerate the impact of AI across the business.

Metadata 213

Metadata AI Strategy AI AI 213

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.

Machine Learning 168

Machine Learning AI AI Automation 168