Notes from "AI: Beyond the Hype" panel discussion Oct 26, 2017 - Boston

Notes:  "AI: Beyond the Hype" meeting

Oct 26, 2017.  Sponsored by Lewis, a PR firm at The District in Boston

Speakers

• Forrester VP.  Mike Gualtier Editor XCO Mag/Northeastern:
• Mike Farrell Sam Whitmore Media surve
• AI prof/Tech writer at Boston U:  Joelle Renstom
• Canvas Ventures partner - Paul Hsiao. First capital in Siri, multiple investments in ML 

Meeting Summary

• Full people like robots are years away but narrow, pragmatic AI
• “Augmented AI” is most promising
• DATA IS NEEDED to get a good model
• So many examples of applications where there is insufficient data to train the model and a feedback look
• Speakers/crowd generally agreed that adoption will increase next 5 years and jobs will be displaced, especially low wage jobs
• Automated Intelligence most promising hear term
• Truck driving autopilot
• Robots in burning buildings

Notes by Speaker

Forrester  - Mike Gulatieri

• Pure AI: sci fi; human like
• Pragmatic AI: very narrow in scope but beats technical human
• Google: develop app to beat Go cham
• Watson beat chess champion
• AI comprised 9 building blocks
• ML, 
• Okay to use one ML and call it AI
• “Automated intelligence” per Forrester, low skilled workers working with a robot
• Why is the ONLY home robot the Roomba for sweeping; but no robot for folding laundry
• Lots of discussion and credit are given to algorithms, but it’s all about the data.
• There is NO magic in the algorithm
• Laundry automated with perception learning. We are NOT close. We are many, many years away for this
• Deep learning in 2012 breakthrough
• Invideo
• Deep learning uses neural networks
• It’s very difficult to test the model to know where it worked
• All these models are based on probabilities
• Decision tree can be traced, but neural networks cannot be traced
• Guardrails or circuit breakers
• Google has guard rails. When model says “I think someone died, let’s show an add for caskets” and guardrails
• NO company TRUSTS their ML solely by itself without guardrails
• CIA and others ask “can we use AI to prevent cyberattacks”.  Forrester says “you need A LOT more breaches” because there is enough data to look
• Anomaly detection is typically now used instead for security detections but challenge is that there is false positives
• Alexa is providing Amazon SO MUCH data because of the there are so many people using these  
• HLMI - high level machine intelligence
• Survey of 200

VC landscape Paul Hsaio 

• Must include AI in slide desk to get funding these days
• commoditization
• VC focus on proprietary data since so many tools are giving away tools
• The biggest challenge is lack of engineers coming into this space.  Multiple acquires
• Very few engineers actually know the AI space
• Most things have become possible in the 5 years because of CPU, 
• We are VERY far from AI like person that destroys job
• Robot advisors has been around 10 years in financials
• On board of Elance, paid $2B to contractors
• Automation of trucking
• Level 1 and level 2: trucks turn on autopilot once on the highway, but off highway is then human.  Like autopilot for plane
• Uber IA on panel said, 
• Google puts it’s own cell phones in truck to track them. 99.9% of 
• Video 4 Berkely PH students trying to figure out how program a robot to fold t-shirt but still not successful.  Automation is hard
• We’ve seen several startups automated medical records
• Traction for upcoding; reading the records to figure how to charge the government MORE
• Maybe we need to start re-evaluating teaching. Some human subjects and others subjects are AI based [I think he means online courses) as part of “Augmented Intelligence” rather than Artifical 
• Amazon (closed system) vs Google Home (more open)
• Rapid eco system; innovation happening a RAPID pace
• What is my bank balance (683 different ways to ask for bank balance.  Machine learning
• We are at the state today for AI where AOL was 56kp dialup modem
• We are beginning of a 20-25 year run

Use Shared Note Taking and Never Miss an Insight on a Customer

Team note taking is now easy and indispensable.  

We use Word in Box as well as Google Documents.

One particular useful scenario is calls or meetings with customers.  At the beginning of the meeting, our team of, say, 5, (often in-person and remote) start a single shared document and jointly edit it as the customer talks through her needs, introduces attendees with titles, etc.

During the meeting, we keep an going Action Item list at the top of the shared meeting notes.

When the meeting end, we now have a meeting summary, detailed notes and action item list that all 5 attendees have reviewed and agreed.   Moreover, the set of meeting notes is "in the cloud" and easily accessible by everyone and not buried on someone's individual laptop.

I've become fan of Google Hangouts

Google Hangouts are great!  

Google hangouts are really a great tool for multi-site collaboration.  The automatic link in Google calendar makes it easy for to join and the audio quality has improved significantly in the last 12 months.   Desktop users can call people on their cell phone as well.    We've used this for many internal meetings that span from offices in the US and India.    GoToMeeting use has declined significantly.

New Blog and Why I Find a Blog Helpful

For several years, I authored a blog, Practical Sustainability, that focused on Sustainability and Energy Management.

This new blog is focused on SaaS/Big Data/Enterprise Software. It also includes a section for personal items.

While it can be time consuming, I find writing blog post useful as it forces me to crystalize my thinking on paper.