Nat Rubio-Licht

1 week ago | thedailyupside.com | Nat Rubio-Licht

Is the tide receding on the AI data center tsunami? Microsoft has pulled back on a number of its data center projects in the past several weeks, with its most recent pause being an early-stage project in Ohio worth $1 billion. That move broadens the impact of the company’s decision to halt work on sites in Indonesia, the UK, Australia, Illinois, North Dakota and Wisconsin.

1 week ago | thedailyupside.com | Nat Rubio-Licht

With recession fears looming as the Trump administration’s tariff threats roil markets, enterprises are trying to preserve profit margins by curbing expenses — including payroll. Tech jobs across industries fell by 29,000 jobs in March, according to analysis by IT research firm CompTIA. AI offers a tool to fill some of the gaps.

1 week ago | thedailyupside.com | Nat Rubio-Licht

Quantum computers need peace and quiet to operate. IBM wants to turn down the noise. The company is seeking to patent a system for “contextually calibrating quantum hardware by minimizing contextual cost function” that essentially fine-tunes a quantum computer to account for the context that the device is operating in. IBM’s system analyzes a quantum computer and adjusts its operation based on the specific program.

2 weeks ago | thedailyupside.com | Nat Rubio-Licht

With tech giants pushing bigger and better AI models at a near constant rate, it’s natural to feel a bit of model fatigue. Google, Meta and OpenAI all added to their families of AI models last week, broadening a field of choices from AI firms big and small that have debuted in recent months. While the models perform differently, their developers are often chasing similar benchmarks and a similar market, experts told CIO Upside. So how do you choose which family will work best for your business?

2 weeks ago | thedailyupside.com | Nat Rubio-Licht

In its quest for AI domination, Microsoft wants to make sure it’s feeding its models well: The company filed two patent applications for tech that uses generative AI to suss out bad data. First, the company is seeking to patent a system for “data health evaluation” using generative language models that weed out and automatically fixes errors such as missing information or outliers in a dataset without a human needing to audit it.