AI should look and work the way society wants and needs it to look and work — aligned with the mores, laws, ethics, and principles of the science and the society we all want. – Adam Bly, formerly of Spotify & Seed Scientific.
After a bit of a hiatus, I am back with a new episode of my occasional podcast series, The Om Show. In this first episode for 2019, I chat with Primer CEO Sean Gourley and MetaMarkets founder Michael Driscoll about what comes in 2019. We discuss everything from machine learning to data to privacy and what’s next for artificial intelligence. Of course, there is some Facebook thrown in for good measure.
You can download this on the iTunes Podcasts or simply listen to it here. Here is a link to download it directly to your device. It is also available on Spotify, though I can’t find it on shit they call search.
I was reading a blog post, and this tiny bit stood out:
Kaushik Roy of Purdue University compared the power consumption of Deep Blue for chess (15kW), Watson for Jeopardy (200kW), and AlphaGo for Go (300kW) to show that matching human behavior in games does not come easy.
It would be interesting to see how the rise of AI/ML will impact the energy consumption at data centers and in general. I wonder if we are all thinking about the power needs of software-driven, silicon-optimized future deeply enough. Steve says that human brain needs about 20 watts of energy and it uses an interesting cooling system. It is also a good reason why we need to take breaks from activities — social media in specific — which cause us to use up too much energy.
Holding on the past is a convenient way to avoid science, technology, and the reality of the world. Future needs reinvention and rethinking. Industrial era dogmas are now in direct conflict with the digitally connected ideologies. The dissonance between the old industry and the new digital reality is also cultural. We, the humans are now … Continue reading The Past vs. The Future
The short answer is: not anytime soon. Yoshua Bengio, a professor of computer science at University of Montreal and an expert in deep learning brings some much needed sanity to red-hot debate around artificial intellgience and the fear factors spurred on by comments from illustrious folks such as Stephen Hawking and Elon Musk. [MIT Technology Review]