Competition to design a robot delivering a TED talk

tedxprize_header

The X Prize Foundation announced the competition to design a robot delivering a TED talk. Everyone is welcome to propose the rules for the competition, which will tentatively give a robot 30 minutes to prepare a 3 minute talk on one of 100 TED talk subjects.

There is a skepticism about the competition. As NewScientist writes:

“Computer scientist Ryan Adams at Harvard University says that such a set-up would reveal little about AI. “Intelligence involves adapting, learning about the structure of the world, making decisions under uncertainty and achieving objectives over time,” he says. “Giving a talk and then ‘answering questions’ doesn’t tell us anything about any of these issues.”

I am skeptical too. First, I naively thought about what kind of data besides the TED API, which provides access to more than 1,000 talks and TED Quotes, tags, themes, ratings and more, could be pulled for the task. But after contemplating on the TED talks (and I watch them pretty regularly) and how often an exciting talk delivers too little actual information (just try once in a while to read transcripts of your favorite talks), I thought that it is not that much of a challenge to make a 3 minute TED presentation, considering that both you and your robot competitors won’t have any credentials.

The recipe might be simple: tell an interesting and emotional story to connect to an audience, ask them to raise hands or stand up, throw some bits of data to feed the brains, and finish going back to your story concluding with a lesson or two. The audience will be delighted. Do you need any AI for that? I doubt. Just upload 100 stories, nice speech recognition voice, some facts from Wikipedia and, with the Internet connection on the spot, grab something what the audience hasn’t yet read on the day of presentation. Appearance matters too.

 

 

“It is going to be beyond science fiction in our life time.”

data_wired_May_2013

On March 12, I attended an event organized by UCSD Extension “Big Data at Work: A Conversation with the Experts”. There were presentations from

  • Larry Smarr, Ph.D., Founding Director, CALIT2
  • Mike Norman, Ph.D., Director, San Diego Supercomputer Center
  • Stefan Savage, Ph.D., Professor, Computer Science & Engineering, UC San Diego
  • Michael Zeller, Ph.D., Chief Executive Officer, Zementis

Natasha Balac, Ph.D., Director, Predictive Analytics Center of Excellence, moderated the discussion panel.

Larry Smarr sounded exciting and optimistic. To illustrate the tsunami of data, he started with the old telling about rice and chessboard. On Wikipedia, it is going under “Wheat and chessboard problem”. If to start with one grain and double the amount of grains on each next square (1+2+4+8+16+32+64+ ….), on the 64th square of the chessboard alone there will be 263 = 9,223,372,036,854,775,808 grains of rice.

“On the entire chessboard there would be 264 − 1 = 18,446,744,073,709,551,615 grains of rice, weighing 461,168,602,000 metric tons, which would be a heap of rice larger than Mount Everest. This is around 1,000 times the global production of rice in 2010 (464,000,000 metric tons).”

Larry Smarr is one of the first adopter of monitoring his health using genome sequencing technologies as he sequences his gut microbiome as often as possible:

“If in the past just several variables from a blood test and weight defined me. Now, Billions of numbers define me! …

Healthcare and education are still pre-digital.”

In regard to efforts to harvest human genomics and microbiomics data, Larry mentioned the recent launches of the Human Longevity Inc. (here is more news on HLI from PR Newswire) and similar initiatives by Leroy Hood and George Church.

Mike Norman talked about Big Data initiatives at SDSC. To demonstrate the amount of available data in various domains, he kindly asked me to show the slide I made last summer (above; I borrowed the concept of circles and all data except biological, which is my estimate based on data available in public registered databases exclusively, from the Wired magazine). He also mentioned IntegromeDB among four Big Data projects running at SDSC. Among the two major challenges in the Big Data field Mike mentioned education and providing a computing environment for data storage, sharing and analytics.

Stefan Savage gave a fascinating talk about his research on the Internet security, abusive advertisement, web spam, bitcoin operations, and his live super-fast URL classification system with millions of features with online training (I am interested to do some research and write more about this system):

“Security is becoming a data-driven discipline. …

Security today is about understanding the environment. …

The data won’t be in personal possession.  “

Michael Zeller talked about two groups of application of Big Data analytics, people & behavior and sensors & devices:

“Big Data buzz creates new business opportunities to disrupt existing market and to develop new platforms with new capabilities. … The challenge on the industry side is cutting through the noise of many existing solutions. … The future will bring a lot of data-driven applications — agents that will make decisions on your behalf. It will be seen on every level of life.”

In the end of the panel (remarks from which I provided above), Larry encouraged to watch the movie “Her”:

“It is going to be beyond science fiction in our life time. Everyone will have an intelligent system knowing much more about ourselves that we do.”

Declaimer: The citations provided above are not exact. They are provided based on my writing during the event.