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The idea of the singularity starts with numbers. Numbers that get bigger and bigger over time, exponentially. As Ray Kurzweil showed it in his presentation, big numbers getting bigger are all over the technological world:

• Moore’s law
• Total bits shipped
• Magnetic data storage bits per dollar
• Internet data traffic
• Internet backbone bandwidth
• US nanotechnology-related patents

But also in biology, for instance the cost of sequencing DNA that is dropping exponentially.

Conjecturing what happens next when those numbers get really big is what this summit and the groups involved in the singularity are about. Something is bound to happen. Something special, something unforeseen, something beyond any of our wildest prediction. Will it be good (techno-optimist), bad (techno-pessimist), the same (techno-neutral) or good or bad depending on how we get there (techno-volatile)? What is going to happen, to people, to human intelligence, to artificial intelligence, to the biological world? When will the singularity point be past?

So, the singularity is where we’re going, but the work still needs to be done. And that’s what computer scientists, biologists, neuroscientists, writers, futurists, psychologists, historians and many other experts come together to discuss.

One main theme is understanding the human body and the brain better. Not just to cure diseases, repair the body, make us immortal, and more intelligent, but also to find principles that guide scientists to make smarter, more powerful technology, such as nano machines that writes and reads DNA, or computer systems that are generally intelligent.

With that many different angles and approaches to the singularity, there is no unified view of it and it is hard to even get a more precise idea about what it could be or mean. You get bits and pieces here and there, a glimpse over here. And as they say, one thing that is certain about the future is that you cannot predict it.

Besides the big ideas, was the conference good? Yes, it was nice to attend, listen to some of the guys whose blogs and articles I read from time to time. The distribution was as usual, 4-5 talks I really enjoyed and were thought-provoking to me, a few I could have slept through and the rest in the middle. I enjoyed it overall but I’m not sure experts would learn that much per se from their own field from the talks, unless you come to network.

The videos should get on the website sometime.
Read the day one and day two report articles from the h+ magazine.

Si vous venez visiter la Bay Area et San Francisco et que vous voulez gouter à l’esprit high-tech et entrepreneur de la Valley, c’est facile, il n’y a qu’à chercher un peu. Presque tous les jours, vous trouverez des meetings et meetups organisés par les nombreux groupes et associations de la région.
Quelques bonnes adresses pour commencer:

• Startup Digest: inscrivez-vous à la mailing list ou lisez leurs archives (cherchez SF Bay Area HackersDigest).
• Eventbrite: recherchez tech dans la Bay Area
• Women2.0 propose ses propres événements et tient  à jour son propre listing

La plupart des événements organisés sont soit gratuits soit peu cher ($10-$20).

This article is relatively old (from 2007) but nonetheless interesting. It basically says that a condition for higher productivity is access to intangible wealth. Whereas natural and built capital describe natural resources, pasture land, and machinery, equipment, infrastructure; intangible wealth include such things as trust in society, property rights, education, etc.  And the amount of intangible wealth is decisive for how productive and creative you will be.

Sounds intuitive enough.

Concretely, what does it mean for you? Well, if you were pondering whether you really need a new computer, a bigger screen, a lighter bike, the newest camera, you can help convince yourself that you’ll be definitely more productive, says the World Bank. Self-deception is a powerful mind trick.

The paper and the recent posts about how Twitter data can be used to predict the first-weekend box office revenues of movies are quite interesting.
Basically, provided sufficient data about a topic and clever ways to process the data, the analysis of Twitter data could potentially indicate if people are going to buy a product, watch a show, vote for someone, go somewhere or think in a given way, etc.

Now I’m wondering if the simple corollary to this is not that Twitter is making the future. After all, Twitter can also be seen as a massive network of influences, and its real-time property makes it much more dynamic than blogs, Facebook, newspapers, or TV. Twitter sphere’s of influence goes also beyond Twitter.com as Twitter feeds are embedded in many other websites and applications.

Compared to other types of data, twitter’s data is easily accessible, is better structured for text analysis (short, you don’t need to parse and find the interesting piece of text in a page long text), as well as for other data or time-based analysis (all tweets are real time, all stamped with the same time/clock system which is a big deal, they cannot be edited, they can all be tracked to their original authors and those who retweeted), and finally there is a lot of it.

Wouldn’t there be a causality link here too? Twitter chatter would not just reflect what people are thinking or doing, it also influences them, like any other viral media channel.
Instead of just investing into methods to know what the chatter says about a product or someone, companies and people are going to invest to increase the amount of chatter related to that product or someone. Like they did with forums, and blogs.

Twitter is ultimately an excellent platform to experiment with prediction and real-time making of the future. Build a system that adds to the Twitter chatter in the direction you want (to promote something for instance) and watch real-time if it is going to influence and affect the outcome.

You’re applying for a job in a research lab in the industry?

Find some great advice here. And below are some additional, and hopefully concrete questions you might want to find answers to during your round of interviews:

Projects

• How many projects are going on currently in the team and when will the next round of projects be decided? When next can you influence/start a new project?
• How are projects proposed and selected? Top-down: top level managers decide on the projects. Bottom-up: everybody has a chance to make a proposal. Who decide and how?
• Could you work on your project ideas/research interests?
• How many interns are available to the team/researcher, and under what conditions? How are they recruited and from where?
• Is there funding for subcontracting work? How much, for what type of work, under what conditions?
• Where does the project funding come from, for what and what are the criteria? Often there are different types of funding for different types projects.
• Can you work on smaller, personal projects?
• Can you buy hardware/software/books/licenses? How much/how often/what are the conditions?
• How are collaborations with universities/professors funded? How can you start or continue a collaboration. With what universities do the lab/team collaborate with?
• Do you have support/help to market/present your work externally (e.g. high quality videos, slides)? Is it encouraged/required/optional?
• How many persons/managers do you report to? For what, how often, and what is their profile?

Lab

• How are projects documented? How are project documents shared internally? Do you have access to all the code/documentation/data of the research and/or non research projects done in the company/lab/team?
• How many projects are highly visible externally/open-source?
• How many persons do you know personally or know the work of?
• How many people blog externally, on what, and what do they say?
• Are there regular internal/external presentations organized? Paper reviews? How much interaction is there between all the researchers?
• Do researchers have a mentor?
• Can you collaborate across teams/labs, under what conditions?

Conferences, Travel

• How much do researchers travel to conferences, and under what conditions? Only if a paper is presented. Is there a type or list of conferences one can attend?
• Can you submit papers to any conference you want? Is there a process to review the paper before you can submit it? What are the conditions to submit your work?
• Can you be on conference PCs and are the travel and expenses reimbursed?
• In what conferences have you seen researchers from that company? What kind of work did they present?
• How is the authorship decided for publications? Are you managers always authors/co-authors on the publications?

Evaluation

• What are the objectives given to researchers/teams/projects? In numbers: publications/articles submitted/accepted, patents submitted/filed, technology/algorithms transferred to products,  demos/presentations given internally, … In qualitative terms: review by peer/team/manager/360 assessment.
• How is the quality of the work evaluated? Based on numbers (as above)? Who evaluates, and what is the profile of the person(s) who evaluate your work.
• What does bad/good/great evaluation mean? Compensation/advancement/rewards/other?

Money

• What are the types of compensations, and what are the criteria? Base salary, bonus,  expenses, publication/patent bonus
• What are the compensation/rewards for publications/patents/presentations? How much and what are the conditions?
• How are salary augmentations negotiated? Based on what criterias?
• Do you have a company credit card?
• How quickly are your expenses reimbursed?

Organization

• What type of researchers are they looking for? Researchers with Phd that publish a lot and have a good external visibility ; researchers+entrepreneurs that can think of business models and sell a project internally and externally ; researchers+engineers who can think of big ideas and implement them ;
• Do managers have a technical role or a management role?
• What and when were the last changes in the research organization?
• What are the lab’s current strategy/targets? Create new technology/patents/services? Support current products? Explore new areas? How often do they change?
• How many technologies/projects have transferred to business units/products? When, how long did it take, what did it take? How does the research lab impact/influence products? Ask for concrete examples.

Work life balance

• Can you work from home? How often?
• What’s the average age of the researchers? Life-style?
• Do you have compensations for commuting/public transport/company shuttles?
• Do you have a private/shared office?

Side activities

• What are the policies related to working for yourself, your personal websites/projects, a startup, open source projects? (better to alert the company of any current/future involvement you may have with other companies/organization)
• How easy is it to have side activities? How many people in the lab have their own startup on the side? Is it encouraged/frowned upon?