Salvo Software

DeepSeek V4 just took the price lead. 15-30x cheaper than Claude and GPT-5.

Fortune reported that if Uber had used DeepSeek for their AI operations instead of Claude, the budget that ran out in four months would have lasted eight years.

Read that again.

DeepSeek V4 Flash sits at $0.14 per million input tokens through their cloud API. Claude Haiku is around $1. Same chat-style API, same kind of integration, very different invoice. Kimi K2.6, the other Chinese frontier model that landed last month, matches GPT-5.4 on coding tasks at 75% less cost.

When AI costs drop this dramatically, the math on what you can ship changes. Apps too expensive to run continuously start running 24/7. Startups can compete with enterprise budgets. The cost-per-token line item turns into a strategic variable.

What AI applications would you build if costs dropped 90% overnight? Tell us in the comments below.

Intel just beat expectations for the sixth straight quarter, driven by enterprise AI demand for CPUs. This validates what we've been seeing: not every AI workload needs a GPU. Traditional CPUs, especially with AI optimizations, are becoming the backbone for practical business AI applications. For enterprise decision makers, this is huge validation. You don't need to break the bank on specialized hardware to implement meaningful AI solutions. The real opportunity is in hybrid architectures that match the right processor to the right workload. Manufacturing, logistics, and field service operations can leverage AI without massive infrastructure overhauls. The question isn't whether to adopt AI, it's how to implement it cost effectively across your existing systems.

OpenAI just launched GPT-5.4-Cyber, expanding their Trusted Access program to vetted cybersecurity defenders. This isn't just another AI model release. It's a signal that AI is becoming the primary battlefield for cyber defense, not just an auxiliary tool.

The implications for businesses are massive. While enterprises scramble to adopt AI for productivity, threat actors are already weaponizing the same technology. The companies that survive the next decade will be those that build AI-native security architectures from day one, not bolt-on solutions.

What concerns me most? The "vetted defenders only" approach suggests the capabilities are so powerful that unrestricted access would be dangerous. That's both reassuring and terrifying.

Full details on OpenAI's expansion: https://openai.com/index/scaling-trusted-access-for-cyber-defense

Apple's smart glasses development signals a fundamental shift in how we'll interact with connected systems by 2027. Testing four different frame designs suggests they're serious about mass market adoption, not just tech enthusiast products.

For industrial and field service applications, this represents a massive opportunity. Imagine technicians getting real-time equipment diagnostics, step-by-step repair instructions, or remote expert guidance directly in their field of vision. No more juggling tablets, phones, and paper manuals while troubleshooting complex systems.

But the real breakthrough won't be the hardware - it'll be the software ecosystem that emerges. The companies winning in this space will be those building the underlying systems that can push contextual, actionable information to these devices in real-time.

This is where custom software development becomes critical. Off-the-shelf solutions won't understand your specific equipment, processes, or data models. The competitive advantage goes to organizations that can seamlessly integrate their operational systems with these new interaction paradigms.

Smart businesses are asking: "What systems do we need to build now to be ready when our workforce expects augmented reality interfaces?" The answer isn't waiting for Apple's launch - it's building the data architecture and APIs that can support whatever interface technology emerges.