Timothy Prickett Morgan

Despite the enormous progress that has been made in generative AI frontier models in the past four years, attaining artificial general intelligence or superintelligence is not an easy goal. Very few of us are behind the scenes at AI model builders and fewer still understand the intricacies of trying to push models further and further toward human and superhuman capabilities.

Jensen Huang, the chief executive officer and co-founder of Nvidia, let the cat out of the bag back at GTC 2026 in March that if hyperscalers, cloud

Way back in the Dot Com boom, when FalconStor was founded, it was one of the early innovators of what we have come to know as software-defined storage and software-defined networking as well as disaggregated storage. These terms were not even coined until a decade after FalconStor was doing it in its first product, called IPStor, which is the foundation of the various products that the company still sells today.

Being an IT equipment supplier is a bit like having a seat on the floor of the New York Stock Exchange back in the 1980s before so much automation came in. The seats marshal their own money and that of their customers and then went out on the floor waving pieces of paper to try to buy stuff. (To be fair, they were also often trying to sell stuff, which no IT supplier is trying to do with any component contracts, although that would be an interesting way for them to make money, too.)

It seems like every business, with the exceptions of a few monster companies that gain a monopoly (either regulated or unregulated) or a piece of an oligopoly (where a few almost monopolies control that market and steer clear of colluding, or at least we think they do), is a tough one.

Ask yourself these questions, assuming you have a serious medical condition and your doctors are going to be using GenAI to scan your images and test results to discover the breadth and depth of your condition and to recommend treatment.

The biggest clouds in the United States and China had existing direct businesses selling compute, storage, and networking capacity when the GenAI boom started, and many of them also have ancillary businesses selling advertising or other large scale media or software services to consumers. So it has been relatively easy for them to pivot.

There are those that believe most or all applications – including AI inference models, which are a kind of massively structured relational database management system if you expand your view a bit – will inevitably end up on the big clouds, and those that believe companies will embrace this new technology and deploy it in their own datacenters or those controlled by third party co-location services who act on their behalf.

Everybody has been expecting for Cerebras Systems, one of the second-generation of AI hardware startups that has been trying very hard to compete with Nvidia on AI compute for years, to launch its latest systems, dubbed the CS-4, sometime this summer.

The Hot Chips 2026 conference kicked off with half-day tutorial sessions on Sunday, and