The State of AI 2016

Ines Montani Matthew Honnibal

Explosion AI

custom algorithms, applications and data assets

makers of spaCy, the fastest-growing open-source NLP library

our backgrounds are computer science, linguistics and front-end development

Explosion AI is a digital studio specialising in Artificial Intelligence and Natural Language Processing.

We are publishing...

Embed, encode, attend, predict The new deep learning formula for state-of-the-art NLP models

The State of AI An open-data industry survey on the state of Artificial Intelligence in 2016

ARTICLES

PROJECTS

spaCy Industrial-Strength Natural Language Processing in Python

OPEN SOURCE

434 practitioners told us about the state of AI.

industry survey launched on October 10, 2016

collaboration with Nathan Benaich (Playfair Capital)

results will be 100% open-source

you can still take part: thestateofai.com

The AI hype: about 90% justified.

AI systems are already going into production.Where is your company in the AI adoption cycle?

The State of AI

1 %

19 %

28 %

21 %

31 %

We have a profitable system in production.

We're currently building our first

system.

We've rolled out our system, but it's not profitable yet.

We're AI-curious and experimenting.

Other

Young companies already have profitable systems.

Early-Stage Startup

Venture-Backed Startup

Established Company 38 %

16 %

54 %

19 %

36 %

21 %

42 %

48 %

25 %

Rolled out and profitableRolled out but not profitable yetCurrently building first system

The State of AI

NLP is improving faster than ever.

IBM Watson

75 %

100 %

2004 2013 2015APR

2016OCT

2016

84.8%

93.7%93.1%92%

87.3%

Example: Speech recognition accuracy

Researchers deliver blueprints, not products.

neural networks really took off when ImageNet data set was created

research runs on benchmark tasks

benchmarks demonstrate solution in principle

solutions in practice require different data

© Stanford Dogs Dataset

Chesapeake Bay RetrieverCurly-Coated Retriever

ImageNet: mostly dogs

© IBTimes / Google Deep Dream

The bottleneck in AI is data, not algorithms.

Data problems are still the biggest problems.

high accuracy problems

high data quality problems

high data quantity problems

20 % 40 % 60 % 80 % 100 %

The State of AI

How much do the following problems keep you up at night? (4/5 and 5/5)

© GATE

Also the state of AI 2016...

You can’t get quality data by boring the shit out of underpaid people.

machine learners need machine teachers

Amazon Mechanical Turk is the most popular way to create annotated data

bad incentives: below minimum-wage payment, outdated tools, zero investment, zero satisfaction

We don’t just need innovation on the back-end.

It’s time to apply what we know about UX to AI.

the most valuable knowledge is in decisions humans don't have to think about

intuitive interfaces, fast decisions

gamification: take inspiration from what humans enjoy doing (and even pay for!)

© 94%, SCIMOB

Don’t assume your task can’t be fun.

AI isn’t a closed shop – there’s a lot to contribute.

7 %

14 %

18 %22 %

39 %

< 1 year

3 - 5 years

> 7 years

5 - 7 years

1 - 3 years

The State of AI

How long have you been working with AI?

Thanks!📊 Take part in the survey

thestateofai.com

📲 Follow us on Twitter@explosion_ai@_inesmontani

@honnibal

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