{"id":8887,"date":"2023-04-28T12:46:06","date_gmt":"2023-04-28T12:46:06","guid":{"rendered":"https:\/\/outsourcing-today.ro\/?p=8887"},"modified":"2023-04-28T12:46:07","modified_gmt":"2023-04-28T12:46:07","slug":"thoughtworks-technology-radar-examines-much-hyped-ai-trends-with-cautious-optimism","status":"publish","type":"post","link":"https:\/\/outsourcing-today.ro\/?p=8887","title":{"rendered":"Thoughtworks Technology Radar examines much-hyped AI trends with cautious optimism"},"content":{"rendered":"\n

In its 13th year, latest report also notes proliferation of ideas and tools to improve accessibility and avoid ballooning cloud complexity<\/em><\/p>\n\n\n\n

Thoughtworks<\/a> (NASDAQ: TWKS), a global technology consultancy that integrates strategy, design and engineering to drive digital innovation, today released Volume 28 of the Technology Radar<\/a>, a biannual report informed by Thoughtworks\u2019 observations, conversations and frontline experiences solving its global clients\u2019 toughest business challenges. With artificial intelligence (AI) becoming even more accessible and embedded in the business, the report states that implementing AI with robust engineering practice leads to the most effective delivery of value to customers.<\/p>\n\n\n\n

With analytics and AI, having enough data and code is no longer the problem. Instead, the focus should be on having high-quality code and data to create models that properly respond to changes in environmental factors and do not drift over time. Fortunately, tooling in this area is expanding with test-driven transformations, data sanity tests and data model testing that strengthen the data pipelines that power analytical systems. Incorporating best practices in model validation and quality assurance are also crucial in tackling biases and ensuring ethical ML systems with equitable outcomes.<\/p>\n\n\n\n

\u201cMost businesses are already experimenting with analytics and AI. We see the maturing of tools as further evidence of the mainstreaming of these technologies. Integration of AI with good engineering practices leads to more responsible, data-driven solutions that cater to a diverse user base,\u201d said Dr. Rebecca Parsons<\/a>, chief technology officer at Thoughtworks. \u201cThis is in contrast to generative AI, where we\u2019re advising businesses to proceed cautiously and take care to avoid inappropriate uses that can lead to reputational and security risks.\u201d<\/p>\n\n\n\n

Highlighted themes in Technology Radar Vol. 28 include:   <\/p>\n\n\n\n