The semantic web is a convention for formal representation languages that lets software services interact with each other “without needing artificial intelligence”.

and

The Semantic Web will enable machines to comprehend semantic documents and data, not human speech and writings

Also

The problem of understanding human human speech and writing—the semantic interpretation problem—is quite different from the problem of software service interoperability.

Further they write

Unfortunately, the fact that the word “semantic” appears in both “Semantic Web” and “semantic interpretation” means that the two problems problems have often been conflated, causing needless and endless consternation and confusion.

Semantic web requires manual annotation of data, and lately they argue

Such annotation is not only slow and expensive to acquire but also difficult for experts to agree on, being bedeviled by many of the difficulties we discuss later in relation to the Semantic Web. The first lesson of Web-scale learning is to use available large-scale data rather than hoping for annotated data that isn’t available.

Anyone who has observed technical strengths of Google very closely can suggest that in a war between semantic interpretation versus semantic web, Google has a natural preference for semantic interpretation. Natural language processing, data mining and machine learning are strongholds of Google, but there is nothing which prohibits Google from exploring the other side of territory. Earlier this week Google webmaster central blog announced the introduction of rich snippets,

Google helps users find your page by showing them a small sample of that content — the “snippet.”

and

Rich Snippets give users convenient summary information about their search results at a glance.

For example, in next image which display rich snippets we can recognize the following information
*The rating (for example, 4/5).
*Number of reviews
*Price range
These additional information or rich snippets will be available in search results only if your web site includes annotate structured data or markup of information using microformats and RDFa. These markups can be easily added to web pages and one don’t need any prior knowledge of microformats or RDFa, just a basic knowledge of XHTML is sufficient. Everything looks good so far, except there is small twist in story as Ian Davis call it damp squib

However, a closer look reveals that Google have basically missed the point of RDFa. The RDFa support is limited to the properties and classes defined on a hastily thrown together site called data-vocabulary.org.

Why Google will do that, Ian complains that Google didn’t use existing vocabularies but he is missing a big point-Google was never standard centric and they always prefer to make the standards as Google centric, so the every other big corporation. If Google keep neglecting these existing developments related to semantic web then I guess many of small semantic enterprise are on verge to collapse. Tim O’Reilly on his blog writes that

Historically, the biggest block to the Semantic Web has been the lack of a killer app that would drive widespread adoption. There was always a bit of a chicken-and-egg problem, in which users would need to do a lot of work to mark up the data for the benefit of others before getting much of a payoff themselves.