As the explosive growth of generative AI frees technologists to take on more complex challenges, critical thinking, communication, business and domain knowledge, and leadership are increasingly becoming essential must-haves.
The blistering pace of advancement in generative AI leaves companies struggling to effectively implement and measure the technology, while guarding against bias and risk.
Generative AI has created an unprecedented pace of technological change, but complications of choosing AI vendors have grown in equal measure. So tech leaders need to be equipped with the right questions — and be prepared for answers — to
As companies race to add generative models into products and workflows, massive investment to upskill workforces on prompt engineering and ethical AI emerges as a top priority.
MSPs are increasingly being turned to as strategic outsourcing partners that remotely manage or deliver IT services, thanks to talent and technologies most enterprises lack.
Building a new large language model (LLM) from scratch can cost a company millions — or even hundreds of millions. But there are several ways to deploy customized LLMs that are faster, easier, and, most importantly, cheaper.
企業がデータ・ドリブンになろうと努力する中、また近年のAI技術の爆発的な普及により、ますます大量の学習データが要求される中、そのデータの質はより重要になってきている。そ
I problemi legati ai dati sono ancora tra le ragioni principali per cui i progetti di IA non soddisfano le aspettative. Ma, l'avvento dell'IA generativa ha aggiunto qualche novità.