Forward thinking: What's next for AI

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Forward thinking What’s next for AI March 2017 bit.ly/ ibm-ai-future

Transcript of Forward thinking: What's next for AI

Page 1: Forward thinking: What's next for AI

Forward thinking

What’s next for AIMarch 2017bit.ly/ibm-ai-future

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Thinking beyond today

In the past few years, we have seen significant strides in analytics,

machine learning and artificial intelligence techniques. While we’re

only beginning to scratch the surface of what AI can help us do,

many are already working on what’s next.

We interviewed 30 AI experts to get their take on what advances

in AI technology and applications we can expect in the next decade.

© IBM, 2017

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Necessity is the mother of innovation

“Faced with a constant onslaught of data, we

needed a new type of system that learns and

adapts, and we now have that with AI. What

was deemed impossible a few years ago is not

only becoming possible, it’s very quickly

becoming necessary and expected.”

— Arvind Krishna, Senior Vice President

of Hybrid Cloud and Director of IBM Research

© IBM, 20173

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A new innovation equation

the rise of small data

+ deep reasoning

+ more unsupervised,

efficient deep learning

+ GPUs and new

AI hardware

innovation in artificial

intelligence

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Beyond deep learning

From big to small data

- Shift toward models requiring

less data for similar accuracy

From deep learning to deep reasoning

- Move from perception

& recognition tasks to decision

making

From supervised to unsupervised learning

- Work with less labeled data &

less human guidance

Learn more: http://bit.ly/ibm-ai-innovation

© IBM, 2017

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Breaking the language barrier

“Language is a very tough nut to crack because

it allows us in a succinct way, without using a

whole lot of symbols, to say an extraordinarily

diverse set of things. It’s a significantly more

complex problem than perception, recognizing

objects or moving from speech to text.”

— Vijay Saraswat, Chief Scientist

for IBM Compliance Solutions

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Human-computer interaction changes

Moving from on-screen type to

voice represents

a sea change in computing

The future of AI will come with

natural language understanding

& context

This will usher in more robust

virtual assistants

& pervasive AI

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“You really get me!”

To gain better understanding, AI

must know context

It will need to know:

- Where you’ve been

- Where you’re going

- What your goals are

It must remember the entire

conversation, not just the

last query

It must be connected

to the world around you

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Learn more: http://bit.ly/ibm-ai-conversation

© IBM, 2017

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Creativity is in the eye of the beholder

“We still have to define what creativity means.

We know some attributes like something that

is novel and unexpected, yet useful. It’s easy

for AI to come up with something novel just

randomly. But it’s very hard for it to come up

with something that is novel and unexpected

and useful.”

— John Smith, Manager of

Multimedia and Vision at IBM Research

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The quest for AI creativity

AI does well as a creative

“mimic”

It can reduce the mundane

execution tasks in creative

work

AI can also serve as

inspiration for human

creativity.

But can it — or should it — be

taught to be innately creative?

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Where does AI fit?

Teaching computers to be

creative is different from the

way humans learn to create.

How can computers learn the

subjective idea of beauty?

By studying pixels? Color

palettes?

In the end, AI will most likely

remain a creative partner.

Learn more: http://bit.ly/ibm-ai-creativity

11 © IBM, 2017

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Keeping watch

“AI can be used for social good. It can be used for business purposes. But it can also be used for other types of social impact in which one man's good is another man's evil. We must remain aware of that.”

— James Hendler, Director of the Institute for Data Exploration and Applications,

Rensselaer Polytechnic Institute

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Building trust in AIThere is a wealth of potential for

artificial intelligence if we foster it

properly. To do this, we need:

Constant transparency into AI

systems & explanations for

their recommendations

General education on AI

Common standards for

interoperability & integration

High ethical standards for

AI-driven decisions

Continued collaboration

between scientists, academics,

industry, & government

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Whose values? Instilling human values in AI is

challenging, but possible

First, we must determine

whose values to use

Should computers be held to a

different set of values than

humans?

We must vigilantly prevent bias

from entering AI systems

And accept that computers

might be imperfect ethical

actors because they will not

feel emotion & consequences

like humans doLearn more: http://bit.ly/ibm-ai-trust

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A final thought

“Birds flap their wings to fly, but to make humans fly, we had to invent a different type of flying—one that did not occur in nature. And so, similarly, through AI, we’re going to invent many new types of thinking that don't exist biologically and that are not like human thinking. Therefore, this intelligence does not replace human thinking, but augments it.”

— Kevin Kelly, co-founder of Wired and

author of the best-seller The Inevitable

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Thank you to the experts

Arvind Krishna, IBM Honor Sherlock, IBM Michael Karasick, IBM

Aya Soffer, IBM James DiCarlo, MIT Michael Witbrock, IBM

Bowen Zhou, IBM James Hendler, RPI Murray Campbell, IBM

Chieko Asakawa, IBM Jason Toy, Somatic Rachel Bellamy, IBM

Costas Bekas, IBM Jay Turcot, Affectiva Rob High, IBM

David Konopnicki, IBM John Shtok, IBM Satinder Singh, U of Michigan

Dharmendra Modha, IBM John Smith, IBM Shivon Zillis, Bloomberg Beta

Gabi Zijderveld, Affectiva Kevin Kelly, Wired Vijay Saraswat, IBM

Grady Booch, IBM Margaret Boden, U of Sussex William Chamberlin, IBM

Guru Banavar, IBM Mark Sagar, Soul Machines Yoshua Bengio, U of Montreal

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Author: Laura DeLallo,

Senior Editor, IBM

Contact: [email protected]

@ldelall0

Report: bit.ly/ibm-ai-future

IBM Research: research.ibm.com

© Copyright IBM Corporation 2017

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March 2017

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