From the 2015 Cognitive_ColloquiumSF, at http://research.ibm.com/cognitive-computing/#sf, there’s a video:
- Kelly, John E., III. 2015. The Future of Cognitive Computing. Web Video. Third Annual IBM Research Cognitive Colloquium: Augmenting Human Intelligence. Mission Bay Conference Center at USCF. research.ibm.com/cognitive-computing/#sf.
Watching the video, here are some personal notes, with timecodes:
[10:35] The first era of computing: 1900-1940s Tabulating Systems Era; second 1950s Programmable Systems Era (but will run out of programmers); 2011 — ? Cognitive Computing Era, will be as different as Programmable from Tabulating
[16:20] Man and machine will beat man or machine
[16:25] Human capabilities: Compassion, intuition, design, value judgments (moral value), common sense (unless they can ever be quantified)
[16:55] Machine capabilities: Deep learning (instant recall of everything, source to all knowledge), discovery (capability to start to reason), large-scale math, fact checking
[17:20] Human + machine: human beings have a normal distribution of capabilities, but with human + machine, can move the distribution
[18:30] How do we get the synergy between man and machine?
[18:40] Since Jeopardy, this field has lit up: image processing, optimizing buying behavior, signal processing of voice. But they’re all point solutions
[19:25] IBM trying to build a while toolkit, like the System/360 in 1964.
[20:10] Watson capability, put into cloud (so could scale), decomposed the Question & Answering system into five technologies: machine learning, question analysis, natural language processing, feature engineering, ontology analysis
[20:40] Build out a suite of services on the Watson cloud that are composable assets.
[22:50] Essence of cognitive capability: first is learning at scale, reasoning or developing insights with the data, with a goal, interacting with humans.
For the video, there’s a slide-by-slide breakdown as “The Future of Cognitive Computing” | Andrew Trice | November 23, 2015 | IBM Bluemix Dev at https://developer.ibm.com/bluemix/2015/11/23/future-of-cognitive-computing/
The associated white paper is at:
- Kelly, John E., III. 2015. “Computing, Cognition and the Future of Knowing: How Humans and Machines Are Forging a New Age of Understanding.” IBM. http://research.ibm.com/cognitive-computing/#sf.
On “The technical path forward and the science of what’s possible”:
Programmable systems are based on rules that shepherd data through a series of predetermined processes to arrive at outcomes. While they are powerful and complex, they are deterministic — thriving on structured data, but incapable of processing qualitative or unpredictable input. This rigidity limits their usefulness in addressing many aspects of a complex, emergent world, where ambiguity and uncertainty abound.
Cognitive systems are probabilistic, meaning they are designed to adapt and make sense of the complexity and unpredictability of unstructured information. They can “read” text, “see” images and “hear” natural speech. And they interpret that information, organize it and offer explanations of what it means, along with the rationale for their conclusions. They do not offer definitive answers. In fact, they do not “know” the answer. Rather, they are designed to weigh information and ideas from multiple sources, to reason, and then offer hypotheses for consideration. A cognitive system assigns a confidence level to each potential insight or answer. [p. 6]
A comparison to AI:
… a critical distinction between the technical approach to cognitive computing and other current approaches to Artificial Intelligence. Cognitive computing is not a single discipline of computer science. It is the combination of multiple academic fields, from hardware architecture to algorithmic strategy to process design to industry expertise. [p. 7]
As compared to purpose-built, narrowly-focused applications:
Cognitive systems, in contrast, combine five core capabilities:
1. They create deeper human engagement: [….] They reason through the sum total of all this structured and unstructured data to find what reallymatters in engaging a person [….]
2. They scale and elevate expertise: […] these systems are taught by leading practitioners — whether in customer service, oncology diagnosis, case law or any other field — they make available to broad populations the know-how of the best.
3. They infuse products and services with cognition: Cognition enables new classes of products and services to sense, reason and learn about their users and the world around them. This allows for continuous improvement and adaptation, and for augmentation of their capabilities to deliver uses not previously imagined. [….]
4. They enable cognitive processes and operations: [….] Business processes infused with cognitive capabilities capitalize on the phenomenon of data, from internal and external sources. This gives them heightened awareness of workflows, context and environment, leading to continuous learning, better forecasting and increased operational effectiveness — along with decision-making at the speed of today’s data. [….]
5. They enhance exploration and discovery: [….] far better “headlights” into an increasingly volatile and complex future. [….] By applying cognitive technologies to vast amounts of data, leaders can uncover patterns, opportunities and actionable hypotheses that would be virtually impossible to discover using traditional research or programmable systems alone. [p. 8]