AI

Our hosts unpack the news of the week, starting with the ongoing feud between Anthropic and the Pentagon. Plus: All you need to know about TAT-8 and undersea cables.

The new open source project IronCurtain uses a unique method to secure and constrain AI assistant agents before they flip your digital life upside down.

Researchers from Stanford and Princeton found that Chinese AI models are more likely than their Western counterparts to dodge political questions or deliver inaccurate answers.

Silicon Valley built AI coding agents that can handle most of the grunt work. Now, the most valuable skill in tech is deciding what they should do.

There’s a lot of excitement right now about AI enabling mainframe application modernization. Boards are paying attention. CIOs are getting asked for a plan. AI is a genuine accelerator for COBOL modernization but to get results, AI needs additional context that source code alone can’t provide.Here’s what we’ve learned working with 400+ enterprise customers: mainframe

Foundation models deliver impressive out-of-the-box performance for general tasks, but many organizations need models to consume their business knowledge. Model customization helps you bridge the gap between general-purpose AI and your specific business needs when building applications that require domain-specific expertise, enforcing communication styles, optimizing for specialized tasks like code generation, financial reasoning, or ensuring

Modern large language model (LLM) deployments face an escalating cost and performance challenge driven by token count growth. Token count, which is directly related to word count, image size, and other input factors, determines both computational requirements and costs. Longer contexts translate to higher expenses per inference request. This challenge has intensified as frontier models

The San Francisco-based AI lab is growing its research team in London. The move puts it in direct competition with Google DeepMind for top research talent in the UK.

More people are turning to AI to explore their BDSM fantasies, but some in the community feel it’s a cop-out.

Reasoning large language models (LLMs) are designed to solve complex problems by breaking them down into a series of smaller steps. These powerful models are particularly good at challenging tasks like advanced programming and multistep planning. But developing reasoning models demands an enormous amount of computation and energy due to inefficiencies in the training process.