Most Read: Google Turns to AI to Write New Code; Workforce Reduced; Accuracy, Bias in AI Concerns Most CEOs: IBM Study

Here are the most-read stories on AI Business this week.

Google Turns to AI to Write New Code; Workforce Reduced

More than a quarter of all new code at Google is generated by AI, company CEO Sundar Pichai said during a third-quarter earnings call. 

The code is then reviewed and accepted by engineers, helping them do more and move faster, he said. 

“We're also using AI internally to improve our coding processes, which is boosting productivity and efficiency,” he said.

Google reduced its workforce over the last year and now has more than 1,000 fewer employees than at the same time in 2023. 

Find out Google's future plans

Accuracy, Bias in AI Concerns Most CEOs: IBM Study

Nearly half of CEOs are concerned about accuracy and bias when it comes to AI, according to a new survey by the IBM Institute for Business Value on AI governance.

The survey also found that 21% of executives said their organization’s maturity around AI governance is systemic or innovative, a new survey by the IBM Institute for Business Value on AI governance has found – highlighting significant room for improvement.

The Institute, in partnership with Oxford Economics, surveyed 5,000 executives from 24 countries across North America, Latin America, Europe, Middle East, Africa and Asia. 

Related:Google Turns to AI to Write New Code; Workforce Reduced

Governance refers to the principles, policies and responsible development practices that align AI tools and systems with ethical and human values. According to the survey, nearly half of CEOs said they are concerned about accuracy and bias when it comes to AI. 

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Generative AI Gets to the Root of the MTTR Problem

Developers have a wide array of different generative AI tools to choose from in their work. But, while solutions such as Google Gemini and GitHub Copilot help them write functional code, can generative AI help speed up mean time to recovery (MTTR) when problems occur?

Fortunately, a new set of tools has emerged that use conversational language to help developers quickly triage and investigate problems the moment they’re detected and are also useful to security teams for diagnosing and mitigating threats. By leveraging machine learning algorithms, these autonomous tools identify the root cause of incidents and work out how to plan and execute remediation.

The massive volumes of data generated from various disparate sources mean that, when an incident is detected in a production environment, it can often be difficult to triage and investigate the issue. Efficiently tracking and managing the process to ensure everyone involved can access only the most current information and context is essential, but it can be time-consuming and resource-intensive.

Related:Accuracy, Bias in AI Concerns Most CEOs: IBM Study

Discover the role of a copilot

Neural Network Model Restores Damaged Historical Artifacts From Photos

Researchers have developed a novel neural network model that uses old photos to reconstruct damaged cultural heritage objects as restored 3D virtual reality (VR) images using old photos.

Reliefs – wall-mounted sculptures that remain attached to a flat base  – are found at historical sites but are subject to damage and deterioration over time.

Modern 3D scanning and photogrammetry methods can digitally preserve their current form, but cannot restore the original appearance of these carvings before damage. 

Restoration using traditional methods requires intensive, highly-skilled labor, It is also costly and can affect the integrity of the original object. 

Find out how temple reliefs were digitally restored

Meta Teams With Lumen to Drive Network Expansion, AI Goals

Lumen Technologies has partnered with Meta to help increase Meta’s network capacity and drive its AI goals. 

That expanded network is expected to help strengthen and increase Meta’s AI development while providing a dedicated interconnection to its infrastructure. 

"We're enabling one of the biggest expansions of network capacity in our lifetime," said Ashley Haynes-Gaspar, Lumen executive vice president and chief revenue officer. "We've transformed our company to meet this demand. As Meta's customers use more AI services across its platforms, we're helping provide Meta with a seamless, effortless and flexible network that will meet its growing needs."  

Lumen said the partnership offers Meta greater flexibility through secure, on-demand bandwidth to meet its complex computing demands and serve billions of people daily.

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