We interface with our devices’ screens for inputs and outputs nearly all day and everyday. What many of the gadgets will soon be able to display and, moreover, understand about digital imagery is about to take a significant leap forward. This will be due to the pending arrival of new chips embedded into their circuitry that are enabled by artificial intelligence (AI) algorithms. Let’s have a look.
This story was reported in a most interesting article on TechnologyReview.com entitled Silicon Chips That See Are Going to Make Your Smartphone Brilliant by Tom Simonite on May 14, 2015. I will sum, annotate and pose some question about it.
The key technology behind these new chips is an AI methodology called deep learning. In these 10 recent Subway Fold posts, deep learning has been covered in a range of applications in various online and real world marketplaces including, among others, entertainment, news, social media, law, medicine, finance and education. The emergence of these smarter new chips will likely bring additional significant enhancements to all of them and many others insofar as their abilities to better comprehend the nature of the content of images.
Two major computer chip companies, Synopsis and Qualcomm, and the Chinese search firm Baidu, are developing systems, based upon deep learning, for mobile devices, autos and other screen-based hardware. They were discussed by their representatives at the May 2015 Embedded Vision Summit held on Tuesday, May 12, 2015, in Santa Clara, California. The companies’ representatives were:
- Pierre Paul, the director of Research and Development at Synopsis, who presented a demo of a new chip core that “recognized speed limit signs” on the road for vehicles and enabled facial recognition for security apps. This chip uses less power than current chips on the market and, moreover, could add some “visual intelligence” to phone and car apps, and security cameras. (Here is the link to the abstracts of the presentations, listed by speaker including Mr. Paul’s entitled Low-power Embedded Vision: A Face Tracker Case Study from the Summit’s website.)
- Jeff Gehlhaar, VP of Research at Qualcomm, made a presentation about his company’s efforts to embed deep learning technology into apps for today’s mobile phones. (Here is the link to the abstracts of the presentations, listed by speaker including Mr. Gehlhaar’s entitled Deep-learning-based Visual Perception in Mobile and Embedded Devices: Opportunities and Challenges from the Summit’s website.) While not specific about Qualcomm’s development work, but rather, discussing the mobile chip industry, he expects the appearance of these chips is inevitable in such areas as robot navigation and self-driving cars. (See also the April 21, 2015 Subway Fold post entitled New Analytics Process Uses Patent Data to Predict Advancements in Specific Technologies for more on the latter.)
- Ren Wu, Distinguished Scientist, Baidu Institute of Deep Learning, said that deep learning-based chips are important for computers used for research, and called for making such intelligence as ubiquitous as possible. (Here is the link to the abstracts of the presentations, listed by speaker including Mr. Wu’s, entitled Enabling Ubiquitous Visual Intelligence Through Deep Learning from the Summit’s website.)
Both Wu and Gehlhaar said that adding more intelligence to mobile device’s ability to recognize photos could be used to address the privacy implications of some apps by lessening the quantity of personal data they upload to the web.
My questions are as follows:
- Whether and how should social networks employ these chips? For example, what if such visually intelligent capabilities were to be added to the recently rolled out live video apps Periscope and MeerKat on Twitter?
- Will these chips be adapted to the forthcoming commercial augmented and virtual reality systems (as discussed in the five recent Subway Fold posts)? If so, what new capabilities might they add to these environments?
- What additional privacy and security concerns will need to be addressed by manufacturers, consumers and regulators as these chips are introduced into their respective marketplaces?