InfoWorld

Lately, I’ve been covering the overengineering and overprovisioning of resources in support of AI, both in the cloud and not in the cloud. AI architects are putting high-powered processors, such as GPUs, on their AI platform shopping lists, not stopping to consider if they will return business value.

Rust has leaped to its highest position ever in the monthly Tiobe index of language popularity, scaling to the 13th spot this month, with placement in the top 10 anticipated in an upcoming edition.

In a highly-anticipated federal ruling on July 3, US District Court Judge Ada Brown determined that the US Federal Trade Commission (FTC) did not have the authority to issue a nationwide ban of non-compete agreements. Although the judge’s decision was preliminary, employment lawyers watching the case agree that the FTC non-compete move is effectively dead.

As agents using artificial intelligence have wormed their way into the mainstream for everything from customer service to fixing software code, it’s increasingly important to determine which are the best for a given application, and the criteria to consider when selecting an agent besides its functionality. And that’s where benchmarking comes in.

Well, that didn’t take long. After all the “this time it’s different” comments about artificial intelligence (We see you, John Chambers!), enterprises are coming to grips with reality. AI isn’t going to take your job. It’s not going to write your code. It’s not going to write all your marketing copy (not unless you’re prepared to hire back the humans to fix it). And, no, it’s nowhere near artificial general intelligence (AGI) and won’t be anytime soon. Possibly never.

In 2007, some of the programmers at Google looked at their options for writing software and didn’t like what they saw. They needed to manage millions of lines of code that would be constantly storing and shipping data for the world wide web. The code would juggle thousands or maybe millions of connections on networks throughout the globe. The data paths were full of challenges from race cases and concurrency.

The landscape of cloud computing is changing significantly as enterprises question the value of public cloud solutions. This shift marks a departure from previous years when the public cloud was widely regarded as the panacea for all technology and infrastructure needs. Companies are now reconsidering the efficacy, cost efficiency, and strategic alignment of public cloud computing in their IT frameworks. We’ve also been discussing this topic here in recent years.

Oracle celebrated the beginning of July with the general availability of three releases of its open source database, MySQL: MySQL 8.0.38, the first update of its long-term support (LTS) version, MySQL 8.4, and the first major version of its 9.x innovation release, MySQL 9.0.

One of the key components of Microsoft’s Copilot Runtime edge AI development platform for Windows is a new vector search technology, DiskANN (Disk Accelerated Nearest Neighbors). Building on a long-running Microsoft Research project, DiskANN is a way of building and managing vector indexes inside your applications. It uses a mix of in-memory and disk storage to map an in-memory quantized vector graph to a high-precision graph help on disk.

The latest update of Visual Studio Code is previewing an alternative visualization of incoming and outgoing changes. The update also includes a new tool that enhances environment discovery for Python installations.