AI and ML Demystified /

Carol Smith

, UX Leader & Speaker - Community Builder - Sr. UX Researcher

LenaJose1
Hello my name is Lauren i'm from USA i want to testify of a great and powerful spell caster my husband left me and the kids for 2 weeks when i called him he didn't pick up when he came back home the 3rd week he told me he wanted a divorce i was so sad i cried all night he left again i was so lonely the next day i was searching for something online when i found a spell caster called Priest Ade who have helped so many people with their problems so i contacted him with my problems he told me it will take 24hrs and my husband will be back to me i did every thing he told me to do and the next day my husband came back kneeling and begging he canceled the divorce we are now happy together Priest Ade can help you too Email him at [email protected] or [email protected] https://ancientspiritspellcast12.wordpress.com Blog: http://ancientspiritspell.blogspot.com Website http://ancientspiritspellcast.website2.me WhatsApp +2347059715465
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JamesGarcia92
When I first learnt of [email protected] here on google recommendations, I thought it’s just like every other recommendations. I have met a lot of hackers on google recommendations ever since I started seeking for help on my credit report from 2010. Most were spam and only a few were real but still couldn’t fix my credit report. It got in worse shape with more negatives on it both verifiable and unverifiable ones and I only had to stop searching. I worked hard over the years and paid off some bills. Yet, you don’t just know how some negatives get on your report and remain there. I almost gave up because I have tried legal firms too but I still end up with the same poor result. My colleague and friend made mention of a hacking firm who helped him fix his report in a relatively short period and amount. Robert said he got to them through google recommendations, same google I have been searching through for years. I felt reluctant as I thought nothing good can come out of it. I finally gave WHITEHATSERVICES a try with my fingers crossed. To my surprise, in a relatively short time (15-20days) as my colleague said, my report was in perfect shape. My score was increased a bit higher, perfect for anything. Both the verifiable and unverifiable negatives can never get on my report and remain there up to a week. That I love and was moved to share this testimony. My mom too is a testimony. She used there services on a DUI and also on a credit fix. They are really a hack team. Send a descriptive mail stating your credit issues to [email protected] or call the number ((619) 3636202 and put an end to your credit miseries. You’ll be forever grateful you did.
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Phạm Thanh Nguyên , Giám Đốc at Cty TNHH Cây Xanh Hoàng Nguyên
Nếu bạn muốn chăm sóc cho mình một khu vực làm việc đầy mộng mơ và tươi mát thì liên hệ Hoàng Nguyên Green và Cây xanh Hoàng Nguyên để sở hữu cho mình những bộ sưu tập cây xanh đẹp vô cùng luôn.
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JoyceMaldonado122
if you think Ruby`s story is good..., 1 weAk-Ago my cousins best friend bAsicAlly mAde $5411 grAfting An eleven hour week from there house And the're best friend's ex-wife`s neighbour done this for 3 months And brought home over $5411 in there spAre time from there lAptop. Applie the informAtion on this Address... HERE► www.findpays.com
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Bobby Geroulanos , Student at University of Miami
AI is becoming such a huge part of business, but many people do not understand the basics of it. It's very helpful to explain those details in a way that anyone can understand it.
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Exhibit intelligence
Perceive their environment
Take actions to maximize chance of success at a goal

Metropolis (1927), 2001 Space Odyssey (1968), War Games (1983), Blade Runner (1982), The Terminator (1984), Short Circuit (1986), The Matrix (1999), Ex Machina (2015),

More recently,
The Terminator, Short Circuit, 2001 Space Odyssey, The Matrix, Metropolis, Westworld

Take set of knowledge we give them and apply to new data
Help humans discover patterns and find unknown

Provide body of knowledge for ground-truth
curated
representative
used to compare further knowledge

Teaching
Don’t learn like a typical human
Only what they need to know

Consider a reverse card sorting exercise
30 participants
How important is it that they all get it right every time?
Consider your industry

Government safety compliance
Accidents related to this tire?
Financial compliance
Accounts with connections to this organization?
Ecommerce chat bot
Women’s pants with pockets?

When carefully (or not so carefully) piled books succumb to gravity
Grew up with bookalanches occurring regularly
Stepfather is an oncologist – would bring home piles of articles, papers, books and more.
He reads everything he can get his hands on. He never stops trying to understand and fight cancer.

Late stage of disease at diagnosis and lack of treatment

Analyzes a patient’s medical information against a vast array of data and expertise to provide evidence-based treatment options.

Saving some trees and reducing bookalanches

IBM’s Deep Blue beat world chess champion Garry Kasparov in a 6 game match

Google's AlphaGo beat human world Go champion Lee Sedol, 4:1

Developed initially to answer Jeopardy! questions
IBM's Watson named after IBM's first CEO, industrialist Thomas J. Watson.

“Comparison of machine learning methods applied to birdsong element classification” by David Nicholson. Proceedings of the 15th Python in Science Conference (SCIPY 2016). http://conference.scipy.org/proceedings/scipy2016/pdfs/david_nicholson.pdf

“Analysis of birdsong (for neuroscience or the many other fields that study this behavior) typically focuses on "syllables" or "notes", recurring elements in the song… Each individual has a unique song that bears some similarity to the song of the bird that tutored it, but is not a direct copy. To analyze song, experimenters label syllables by hand. Typically the experimenter records one bird at a time while carrying out a behavioral experiment. However, each songbird produces thousands of songs a day, more than can be labeled. In order to deal with this mountain of data, some labs have developed automated analyses.”

David Nicholson trained a classifier on syllables of one bird’s song to automate labeling of those syllables (same bird).
This was not to train a classifier to distinguish the song of one bird from another.

Specialists spend more time on more complex patients

IBM’s Avicenna software highlighted possible embolisms on this CT scan in green, finding mostly the same problems as a human radiologist who marked up the image in red.

IBM Research Australia is working to help stop this ‘silent thief of sight’ by teaching Watson to detect it. After learning from 88,000 retina images, Watson can understand what a healthy eye looks like, and identify abnormalities that indicate of the onset of eye diseases like glaucoma. In the future, this early detection technology could help keep glaucoma out of sight for millions.

Reorder
Track shipments
Chat with CSR
http://www.businesswire.com/news/home/20161025006273/en/Staples%E2%80%99-%E2%80%9CEasy-Button%E2%80%9D-Life-IBM-Watson
“Simplifies the customers’ shopping experience, allowing them to quickly reorder supplies, track shipments or chat about customer service needs.”
Staples “Easy Button” office supply reordering system which integrates IBM’s Watson technology to simplify office supply management for Staples Business Advantage Customers

teach to discern between right and wrong?
letter vs. spirit of law?

The EU is more inclined to create hard laws that are enforceable.
The EU General Data Protection Regulation, or GDPR, which will come into force in May 2018, is an excellent example. This framework creates certain transparency rights and safeguards against automated decision-making.
Article 22, for example, grants individuals the right to contest a completely automated decision if it has legal or other significant effects on them.
Other articles require data collectors such as advertisers to provide people with access to the collectors’ data on them, and to inform people about the general functionality of the automated system when decisions are made using that data.

The Job: To read to large rooms of factory workers slaving away at remedial tasks for hours on end. Lectors were sometimes even hired with pooled money from the factory workers themselves for their entertainment.

Who Did It: Well spoken gentlemen.

Why It Went Away: A whole smorgasbord of reasons from the radio, to the Walk-Man, iPhones, iPods, podcasts...

By Coy Jandreau - user uploaded image

AI and ML Demystified / AI and Machine Learning Demystified by Carol Smith at Midwest UX 2017

Carol Smith

AI and ML Demystified /