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In the world of technology companies, the "labs" concept and nomenclature found a friendly home. Microsoft Research has FUSE Labs, there's HP Labs, and Mozilla Labs, and let's not forget the once-mighty Google Labs (R.I.P.), among many others. Digging into the history of big tech "labs" would be the subject worthy of a book, of course, but in the context of this narrow post, it's worth briefly noting that for those that make things and are builders, every big company needed to have something like this for branding, recruiting, and to keep the innovation engine humming as their corporate parents grew larger and more bureaucratic.  Perhaps each one wasn't referred to as a "lab" explicitly in name, as Amazon has A9 and Google now has Google X. No matter the name, there's something powerful in the word that reminds us of the old chem lab and that spirit of experimentation.

Social networks seemed poised to take over the Web. This year, Facebook reached 800 million users. LinkedIn went public in a blockbuster stock offering. Twitter produced a billion tweets per week. And Google launched its own social network, Google+, attracting 25 million users in one month. Amid the continued growth of these social networks, there has been much excitement about how the rest of the Web would soon be infused with all things "social": social search, social commerce, social deals and more. And yet the effort to socialize the rest of the Web has so far failed to live up to its promise. Why?

Web search engines have become indispensable tools for finding information online effectively. As the range of information, context and users of Internet searches has grown, the relationship between the search query, search interest and user has become more tenuous. Not all users are seeking the same information, even if they use the same query term. Thus, the quality of search results has, at least potentially, been decreasing. Search engines have begun to respond to this problem by trying to personalise search in order to deliver more relevant results to the users. A query is now evaluated in the context of a user's search history and other data compiled into a personal profile and associated with statistical groups. This, at least, is the promise stated by the search engines themselves. This paper tries to assess the current reality of the personalisation of search results. We analyse the mechanisms of personalisation in the case of Google web search by empirically testing three commonly held assumptions about what personalisation does. To do this, we developed new digital methods which are explained here. The findings suggest that Google personal search does not fully provide the much-touted benefits for its search users. More likely, it seems to serve the interest of advertisers in providing more relevant audiences to them.

What do Color, Quora, Hunch, Blippy, and StockTwits have in common? They are examples of companies that generate value for their users by leveraging the concept of the Interest Graph. The list also features some of the most promising startups right now, having raised close to $100 million in venture funding. Pure coincidence?

One of the awards went to The Chicago Tribune's "PANDA," which aims to sew otherwise incompatible datasets together, allowing journalists to find unknown relationships from the archived data that normally sits dormant on individual hard drives.

"The results, she says, support a growing belief that people are using the Internet as a personal memory bank: the so-called Google effect. What surprised Sparrow most was not people's reliance on nonmemorized information but their ability to find it."

Semantic technologies are fundamentally about knowledge representation, not data transfer. The current concept of linked data attempts to place these burdens mostly on the way data is published. While apparently "simpler" than earlier versions of the semantic Web (since linked data de-emphasizes shared vocabularies and nuanced associations), linked data places onerous burdens on how publishers express their data. Though many in the advocacy community point to the "billions" of RDF triples expressed as a success, actual consumers of linked data are rare. I know of no meaningful application or example where the consumption of linked data is an essential component. However, there are a few areas of success in linked data. DBpedia, Freebase (now owned by Google), and GeoNames have been notable in providing identifiers (URIs) for common concepts, things, entities and places. There has also been success in the biomedical community with linked data.

In business, everyone keeps confusing information with knowledge. They're different. Even the dictionary says so: Information: Facts provided or learned about something or someone. Knowledge: Information and skills acquired through experience or education; the theoretical or practical understanding of a subject. Information is ones and zeros. It's raw data, or a list of facts. It's instructions on filling out a business license, or the instructions Google provides when you sign up for Adwords. The obvious stuff. You can often acquire information for free: Go to the Associated Press for raw, un-analyzed news. Or read a 'how to' on building your own car. Knowledge is something else entirely. It's what you get when you combine information with _analysis_ and _experience_. Knowledge is information distilled down to actions. It can and should cost you money, or time, or something else. If you want real analysis of the news you just grabbed from the Associated Press, for example, you might go to the New York Times and pay (at least after 10 views). To learn AdWords tricks that can actually help you profit, you'll buy a book, pay for a seminar or hire a consultant.

Reading is changing. And arguably, even more than e-readers, tablets, or "readers' tablets," smartphones are changing it.

2011 was the year of information. It seeped into our consciousness over the year, this idea that the volume of information now available in the world truly was overwhelming. 2012 will be a year where the value of information finally seeps into the public consciousness. The conversation will become about not only what we know but how we know that what we know is meaningful. We will shift from an orientation of quantity to one of quality. It's not that we won't use the Internet, it's not that Google will disappear - of course not.

If someone told you that there was a quick and easy way that many of you could improve your SERP CTR for minimal effort, you'd all stop in your tracks and give them full attention. Yet, Schema.org and rich snippets are still horribly under-utilized. Since Google (and Bing!) officially introduced schema.org in June, it's fair to say motivation to implement it has been mixed. However since its introduction Schema.org has already evolved a lot, adding a lot of new stuff that people haven't paid attention to. Here I try to persuade you there are few downsides and plenty of upsides.

"Search has changed dramatically over the past year and semantic technology has been at the center of it all. Consumers increasingly expect search engines to understand natural language and perceive the intent behind the words they type in, and search engine algorithms are rising to this challenge. This evolution in search has dramatic implications for marketers, consumers, technology developers and content creators - and it's still the early days for this rapidly changing environment. Here is an overview of how search technology is changing, how these changes may affect you and what you can do to market your business more effectively in the new era of search."

"There's been a lot of discussion lately about Google+ and why it will render Twitter obsolete.". This article presents the opposite side of the coin.

Call a friend in another city or a foreign country, and ask them to Google something at the same time as you. The results will be different... "The result is a "filter bubble", which he defines as "a unique universe of information for each of us", meaning that we are less likely to encounter information online that challenges our existing views or sparks serendipitous connections. "

On Friday, October 14, a group of Semantic thought leaders from around the globe met with their host and colleague, Paul Miller, for the latest installment of the Semantic Link, a monthly podcast covering the world of Semantic Technologies. This episode includes a discussion about schema.org. The Semantic Link panel was joined by special guest, Ramanathan V. Guha, Google Fellow, and one of the principal people behind schema.org.

What the Internet is hiding from us - Will Google's blind faith in the algorithm doom its future?

"Every teacher I've worked with over the last five years recalls two kinds of digital experiences with students. The first I think of as digital native moments, when a student uses a piece of technology with almost eerie intuitiveness. As digital natives, today's teens have grown up with these tools and have assimilated their logic. Young people just seem to understand when to click and drag or copy and paste, and how to move, merge and mix digital elements. The second I call digital naiveté moments, when a student trusts a source of information that is obviously unreliable. Even though they know how easy it is to create and distribute information online, many young people believe -- sometimes passionately -- the most dubious rumors, tempting hoaxes (including convincingly staged encounters designed to look raw and unplanned) and implausible theories. How can these coexist? How can students be so technologically savvy while also displaying their lack of basic skills for navigating the digital world?"